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1
Schewe, Frederik, Hao Cheng, Alexander Hafner, Monika Sester, and Mark Vollrath. "Occupant Monitoring in Automated Vehicles: Classification of Situation Awareness Based on Head Movements While Cornering." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 2078–82. http://dx.doi.org/10.1177/1071181319631048.
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We tested whether head-movements under automated driving can be used to classify a vehicle occupant as either situation-aware or unaware. While manually cornering, an active driver’s head tilt correlates with the road angle which serves as a visual reference, whereas an inactive passenger’s head follows the g-forces. Transferred to partial/conditional automation, the question arises whether aware occupant’s head-movements are comparable to drivers and if this can be used for classification. In a driving-simulator-study (n=43, within-subject design), four scenarios were used to generate or deteriorate situation awareness (manipulation checked). Recurrent neural networks were trained with the resulting head-movements. Inference statistics were used to extract the discriminating feature, ensuring explainability. A very accurate classification was achieved and the mean side rotation-rate was identified as the most differentiating factor. Aware occupants behave more like drivers. Therefore, head-movements can be used to classify situation awareness in experimental settings but also in real driving.
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Krishnan, Deepu, Scott Kelly, and Yohan Kim. "A Meta-Analysis Review of Occupant Behaviour Models for Assessing Demand-Side Energy Consumption." Energies 15, no. 3 (2022): 1219. http://dx.doi.org/10.3390/en15031219.
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Occupant behaviour plays a significant role in shaping the dynamics of energy consumption in buildings, but the complex nature of occupant behaviour has hindered a deeper understanding of its influence. A meta-analysis was conducted on 65 published studies that used data-driven quantitative assessments to assess energy-related occupant behaviour using the Knowledge Discovery and Data Mining (KDD) framework. Hierarchical clustering was utilised to categorise different modelling techniques based on the intended outcomes of the model and the types of parameters used in various models. This study will assist researchers in selecting the most appropriate parameters and methods under various data constraints and research questions. The research revealed two distinct model categories being used to study occupant behaviour-driven energy consumption, namely (i) occupancy status models and (ii) energy-related behaviour models. Multiple studies have identified limitations on data collection and privacy concerns as constraints of modelling occupant behaviour in residential buildings. The “regression model” and its variants were found to be the preferred model types for research that models “energy-related behaviour”, and “classification models” were found to be preferable for modelling “occupancy” status. There were only limited instances of data-driven studies that modelled occupant behaviour in low-income households, and there is a need to generate region-specific models to accurately model energy-related behaviour.
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Senger, R. S., and M. N. Karim. "Variable Site-Occupancy Classification of N-Linked Glycosylation Using Artificial Neural Networks." Biotechnology Progress 21, no. 6 (2005): 1653–62. http://dx.doi.org/10.1021/bp0502375.
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Burgos, Julian M., and John K. Horne. "Characterization and classification of acoustically detected fish spatial distributions." ICES Journal of Marine Science 65, no. 7 (2008): 1235–47. http://dx.doi.org/10.1093/icesjms/fsn087.
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AbstractBurgos, J. M., and Horne, J. K. 2008. Characterization and classification of acoustically detected fish spatial distributions. – ICES Journal of Marine Science, 65: 1235–1247. High-resolution, two-dimensional measurements of aquatic-organism density are collected routinely during echo integration trawl surveys. School-detection algorithms are commonly used to describe and analyse spatial distributions of pelagic and semi-pelagic organisms observed in echograms. This approach is appropriate for species that form well-defined schools, but is limited when used for species that form demersal layers or diffuse pelagic shoals. As an alternative to metrics obtained from school-detection algorithms, we used landscape indices to quantify and characterize spatial heterogeneity in density distributions of walleye pollock (Theragra chalcogramma). Survey transects were divided into segments of equal length and echo integrated at a resolution of 20 m (horizontal) and 1 m (vertical). A series of 20 landscape metrics was calculated in each segment to measure occupancy, patchiness, size distribution of patches, distances among patches, acoustic density, and vertical location and dispersion. Factor analysis indicated that the metric set could be reduced to four factors: spatial occupancy, aggregation, packing density, and vertical distribution. Cluster analysis was used to develop a 12-category classification typology for distribution patterns. Visual inspection revealed that spatial patterns of segments assigned to each type were consistent, but that there was considerable overlap among types.
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Li, Wei, Libo Cao, Lingbo Yan, Chaohui Li, Xiexing Feng, and Peijie Zhao. "Vacant Parking Slot Detection in the Around View Image Based on Deep Learning." Sensors 20, no. 7 (2020): 2138. http://dx.doi.org/10.3390/s20072138.
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Due to the complex visual environment, such as lighting variations, shadows, and limitations of vision, the accuracy of vacant parking slot detection for the park assist system (PAS) with a standalone around view monitor (AVM) needs to be improved. To address this problem, we propose a vacant parking slot detection method based on deep learning, namely VPS-Net. VPS-Net converts the vacant parking slot detection into a two-step problem, including parking slot detection and occupancy classification. In the parking slot detection stage, we propose a parking slot detection method based on YOLOv3, which combines the classification of the parking slot with the localization of marking points so that various parking slots can be directly inferred using geometric cues. In the occupancy classification stage, we design a customized network whose size of convolution kernel and number of layers are adjusted according to the characteristics of the parking slot. Experiments show that VPS-Net can detect various vacant parking slots with a precision rate of 99.63% and a recall rate of 99.31% in the ps2.0 dataset, and has a satisfying generalizability in the PSV dataset. By introducing a multi-object detection network and a classification network, VPS-Net can detect various vacant parking slots robustly.
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Ostermann, Adrian, Yann Fabel, Kim Ouan, and Hyein Koo. "Forecasting Charging Point Occupancy Using Supervised Learning Algorithms." Energies 15, no. 9 (2022): 3409. http://dx.doi.org/10.3390/en15093409.
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The prediction of charging point occupancy enables electric vehicle users to better plan their charging processes and thus promotes the acceptance of electromobility. The study uses Adaptive Charging Network data to investigate a public and a workplace site for predicting individual charging station occupancy as well as overall site occupancy. Predicting individual charging point occupancy is formulated as a classification problem, while predicting total occupancy is formulated as a regression problem. The effects of different feature sets on the predictions are investigated, as well as whether a model trained on data of all charging points per site performs better than one trained on the data of a specific charging point. Reviewed studies so far, however, have failed to compare these two approaches to benchmarks, to use more than one algorithm, or to consider more than one site. Therefore, the following supervised machine-learning algorithms were applied for both tasks: linear and logistic regression, k-nearest neighbor, random forest, and XGBoost. Further, the model results are compared to three different naïve approaches which provide a robust benchmark, and the two training approaches were applied to two different sites. By adding features, the prediction quality can be increased considerably, which resulted in some models performing better than the naïve approaches. In general, models trained on data of all charging points of a site perform slightly better on median than models trained on individual charging points. In certain cases, however, individually trained models achieve the best results, while charging points with very low relative charging point occupancy can benefit from a model that has been trained on all data.
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López-Medina, Miguel Ángel, Macarena Espinilla, Chris Nugent, and Javier Medina Quero. "Evaluation of convolutional neural networks for the classification of falls from heterogeneous thermal vision sensors." International Journal of Distributed Sensor Networks 16, no. 5 (2020): 155014772092048. http://dx.doi.org/10.1177/1550147720920485.
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The automatic detection of falls within environments where sensors are deployed has attracted considerable research interest due to the prevalence and impact of falling people, especially the elderly. In this work, we analyze the capabilities of non-invasive thermal vision sensors to detect falls using several architectures of convolutional neural networks. First, we integrate two thermal vision sensors with different capabilities: (1) low resolution with a wide viewing angle and (2) high resolution with a central viewing angle. Second, we include fuzzy representation of thermal information. Third, we enable the generation of a large data set from a set of few images using ad hoc data augmentation, which increases the original data set size, generating new synthetic images. Fourth, we define three types of convolutional neural networks which are adapted for each thermal vision sensor in order to evaluate the impact of the architecture on fall detection performance. The results show encouraging performance in single-occupancy contexts. In multiple occupancy, the low-resolution thermal vision sensor with a wide viewing angle obtains better performance and reduction of learning time, in comparison with the high-resolution thermal vision sensors with a central viewing angle.
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Cai, Lei, Jincheng Zhou, and Dan Wang. "Improving temporal smoothness and snapshot quality in dynamic network community discovery using NOME algorithm." PeerJ Computer Science 9 (July 18, 2023): e1477. http://dx.doi.org/10.7717/peerj-cs.1477.
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The goal of dynamic community discovery is to quickly and accurately mine the network structure for individuals with similar attributes for classification. Correct classification can effectively help us screen out more desired results, and it also reveals the laws of dynamic network changes. We propose a dynamic community discovery algorithm, NOME, based on node occupancy assignment and multi-objective evolutionary clustering. NOME adopts the multi-objective evolutionary algorithm MOEA/D framework based on decomposition, which can simultaneously decompose the two objective functions of modularization and normalized mutual information into multiple single-objective problems. In this algorithm, we use a Physarum-based network model to initialize populations, and each population represents a group of community-divided solutions. The evolution of the population uses the crossover and mutation operations of the genome matrix. To make the population in the evolution process closer to a better community division result, we develop a new strategy for node occupancy assignment and cooperate with mutation operators, aiming at the boundary nodes in the connection between the community and the connection between communities, by calculating the comparison node. The occupancy rate of the community with the neighbor node, the node is assigned to the community with the highest occupancy rate, and the authenticity of the community division is improved. In addition, to select high-quality final solutions from candidate solutions, we use a rationalized selection strategy from the external population size to obtain better time costs through smaller snapshot quality loss. Finally, comparative experiments with other representative dynamic community detection algorithms on synthetic and real datasets show that our proposed method has a better balance between snapshot quality and time cost.
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Stetsky, S. V., A. O. Zheltaya, and E. A. Dorozhkina. "Functional zoning in urban planning and architectural design." E3S Web of Conferences 402 (2023): 09005. http://dx.doi.org/10.1051/e3sconf/202340209005.
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The article discusses a variety of issues, concerning functional zoning. These questions are being considered, starting from the wide-scale urban territories and up to small private plots and dwellings. The urban planning and design are being analyzed in accordance to the main classification features, i.e., in accordance to the number of population, planning schemes and planning structures. It is noted, that in the long run, the principles of zoning are highly dependent in the above-mentioned points of a master planning. The functional zoning of individual houses or flats are being considered with nearly the same method adopted. A dwelling division to functional zones depends upon its size, number of occupants, personal desires, etc.
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Quero, Javier, Matthew Burns, Muhammad Razzaq, Chris Nugent, and Macarena Espinilla. "Detection of Falls from Non-Invasive Thermal Vision Sensors Using Convolutional Neural Networks." Proceedings 2, no. 19 (2018): 1236. http://dx.doi.org/10.3390/proceedings2191236.
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In this work, we detail a methodology based on Convolutional Neural Networks (CNNs) to detect falls from non-invasive thermal vision sensors. First, we include an agile data collection to label images in order to create a dataset that describes several cases of single and multiple occupancy. These cases include standing inhabitants and target situations with a fallen inhabitant. Second, we provide data augmentation techniques to increase the learning capabilities of the classification and reduce the configuration time. Third, we have defined 3 types of CNN to evaluate the impact that the number of layers and kernel size have on the performance of the methodology. The results show an encouraging performance in single-occupancy contexts, with up to 92 % of accuracy, but a 10 % of reduction in accuracy in multiple-occupancy. The learning capabilities of CNNs have been highlighted due to the complex images obtained from the low-cost device. These images have strong noise as well as uncertain and blurred areas. The results highlight that the CNN based on 3-layers maintains a stable performance, as well as quick learning.
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Tao, Minjie, Jianshe Lou, and Li Wang. "MRI Liver Image Assisted Diagnosis Based on Improved Faster R-CNN." Traitement du Signal 39, no. 4 (2022): 1347–55. http://dx.doi.org/10.18280/ts.390428.
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In response to challenges in liver occupancy such a variety of types and manifestations and difficulties in differentiating benign and malignant ones, this paper takes liver images of enhanced MRI scan as the research object, targets on the detection and identification of liver occupancy lesion areas and determining if it is benign or malignant. Accordingly, the paper proposes an auxiliary diagnosis method for liver image combining deep learning and MRI medical imaging. The first step is to establish a reusable standard dataset for MRI liver occupancy detection by pre-processing, image denoising, lesion annotation and data augmentation. Then it improves the classical region-based convolutional neural network (R-CNN) algorithm Faster R-CNN by incorporating CondenseNet feature extraction network, custom-designed anchor size and transfer learning pre-training. This is to further improve the detection accuracy and benign and malignant classification performance of liver occupancy. Experiments show that the improved model algorithm can effectively identify and localise liver occupancies in MRI images, and achieves a mean average precision (mAP) of 0.848 and an Area Under the Curve (AUC) of 0.926 on the MRI standard dataset. This study has important research significance and application value for reducing manual misses and misdiagnosis and improving the early clinical diagnosis rate of liver cancer.
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Gorresen, P. Marcos, Kevin W. Brinck, Megan A. DeLisle, et al. "Multi-state occupancy models of foraging habitat use by the Hawaiian hoary bat (Lasiurus cinereus semotus)." PLOS ONE 13, no. 10 (2018): e0205150. https://doi.org/10.5281/zenodo.13485397.
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(Uploaded by Plazi for the Bat Literature Project) Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.
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Gorresen, P. Marcos, Kevin W. Brinck, Megan A. DeLisle, et al. "Multi-state occupancy models of foraging habitat use by the Hawaiian hoary bat (Lasiurus cinereus semotus)." PLOS ONE 13, no. 10 (2018): e0205150. https://doi.org/10.5281/zenodo.13485397.
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(Uploaded by Plazi for the Bat Literature Project) Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.
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Gorresen, P. Marcos, Kevin W. Brinck, Megan A. DeLisle, et al. "Multi-state occupancy models of foraging habitat use by the Hawaiian hoary bat (Lasiurus cinereus semotus)." PLOS ONE 13, no. 10 (2018): e0205150. https://doi.org/10.5281/zenodo.13485397.
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(Uploaded by Plazi for the Bat Literature Project) Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.
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Gorresen, P. Marcos, Kevin W. Brinck, Megan A. DeLisle, et al. "Multi-state occupancy models of foraging habitat use by the Hawaiian hoary bat (Lasiurus cinereus semotus)." PLOS ONE 13, no. 10 (2018): e0205150. https://doi.org/10.5281/zenodo.13485397.
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(Uploaded by Plazi for the Bat Literature Project) Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.
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Zhu, Lisha, Chao Dai, Shuang Gan, Shidong Jia, and Pan Du. "Abstract 3505: Classification of cancer subtypes by cfDNA fragmentomics analysis." Cancer Research 84, no. 6_Supplement (2024): 3505. http://dx.doi.org/10.1158/1538-7445.am2024-3505.
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Abstract Introduction Fragmentation patterns of cell-free DNA (cfDNA) from whole genome sequencing offer insights into nucleosome occupancy, providing a tool to infer epigenomic and transcriptomic information. The nucleosome complex, the primary protector of cfDNA, is reflected in the size distribution of cfDNA fragments, with a mode fragment size of 167 bp corresponding to the wrapping of DNA around a single nucleosome. Nucleosome occupancy patterns at transcription factor binding sites (TFBS) exhibit differences between circulating tumor DNA in cancer patients and normal plasma controls, as well as among different tumor subtypes. Therefore, cfDNA fragmentomics can be employed for cancer subtyping analysis. Methods We utilized the Griffin framework to classify tumor subtypes based on nucleosome profiling of cancer-specific TFBS and tumor subtype-specific chromatin accessibility regions from low-pass whole genome sequencing data of cfDNA. For prostate cancer subtyping, AR and ASCL1 binding sites were used to distinguish between androgen receptor-dependent prostate cancer (ARPC) and neuroendocrine prostate cancer (NEPC). ER and ERBB2 were employed for breast cancer subtyping to differentiate between ER-positive and ER-negative tumor subtypes. Results Nucleosome profiling patterns at AR binding sites (ARBS) were compared among over 500 prostate cancer plasma samples and 42 normal plasma backgrounds. The ARBS nucleosome profiling abnormality score (ARBS score) was quantified by comparing its GC-corrected fragment central coverage with the normal background using a standard Z-score.Majority of prostate cancer samples with a high ARBS score could be classified as ARPC. For 12 samples with high tumor fraction but low ARBS score and no AR copy number amplification, we found that 8 had a high ASCL1 nucleosome profiling abnormality score. All these samples also exhibited RB1 copy number loss, suggesting that these 8 samples likely belong to NEPC. Nucleosome profiling of 171 breast cancer plasma samples at breast cancer-specific ER binding sites revealed that majority of samples had a high ERBS abnormality score, indicating likely ER-positive breast cancer. Conclusion Our results demonstrate that nucleosome profiling of tumor cfDNA exhibits distinct patterns across different tumor types. Integrating nucleosome profiling at cancer-specific transcription factor binding sites can facilitate cancer subtyping, highlighting its potential clinical utility for patient stratification. Citation Format: Lisha Zhu, Chao Dai, Shuang Gan, Shidong Jia, Pan Du. Classification of cancer subtypes by cfDNA fragmentomics analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3505.
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Biagioni, Cristian, Luke L. George, Nigel J. Cook, et al. "The tetrahedrite group: Nomenclature and classification." American Mineralogist 105, no. 1 (2020): 109–22. http://dx.doi.org/10.2138/am-2020-7128.
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Abstract The classification of the tetrahedrite group minerals in keeping with the current IMA-accepted nomenclature rules is discussed. Tetrahedrite isotypes are cubic, with space group symmetry I43m. The general structural formula of minerals belonging to this group can be written as M(2)A6M(1)(B4C2)X(3) D4S(1)Y12S(2)Z, where A = Cu+, Ag+, ☐ (vacancy), and (Ag6)4+ clusters; B = Cu+, and Ag+; C = Zn2+, Fe2+, Hg2+, Cd2+, Mn2+, Cu2+, Cu+, and Fe3+; D = Sb3+, As3+, Bi3+, and Te4+; Y = S2– and Se2–; and Z = S 2–, Se2–, and ☐. The occurrence of both Me+ and Me2+ cations at the M(1) site, in a 4:2 atomic ratio, is a case of valency-imposed double site-occupancy. Consequently, different combinations of B and C constituents should be regarded as separate mineral species. The tetrahedrite group is divided into five different series on the basis of the A, B, D, and Y constituents, i.e., the tetrahedrite, tennantite, freibergite, hakite, and giraudite series. The nature of the dominant C constituent (the so-called “charge-compensating constituent”) is made explicit using a hyphenated suffix between parentheses. Rozhdestvenskayaite, arsenofreibergite, and goldfieldite could be the names of three other series. Eleven minerals belonging to the tetrahedrite group are considered as valid species: argentotennantite-(Zn), argentotetrahedrite-(Fe), kenoargentotetrahedrite-(Fe), giraudite-(Zn), goldfieldite, hakite-(Hg), rozhdestvenskayaite-(Zn), tennantite-(Fe), tennantite-(Zn), tetrahedrite-(Fe), and tetrahedrite-(Zn). Furthermore, annivite is formally discredited. Minerals corresponding to different end-member compositions should be approved as new mineral species by the IMA-CNMNC following the submission of regular proposals. The nomenclature and classification system of the tetrahedrite group, approved by the IMA-CNMNC, allows the full description of the chemical variability of the tetrahedrite minerals and it is able to convey important chemical information not only to mineralogists but also to ore geologists and industry professionals.
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Gedeon, Csongor I., Mátyás Árvai, Gábor Szatmári, et al. "Identification and Counting of European Souslik Burrows from UAV Images by Pixel-Based Image Analysis and Random Forest Classification: A Simple, Semi-Automated, yet Accurate Method for Estimating Population Size." Remote Sensing 14, no. 9 (2022): 2025. http://dx.doi.org/10.3390/rs14092025.
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Burrowing mammals such as European sousliks are widespread and contribute significantly to soil ecosystem services. However, they have declined across their range and the non-invasive estimation of their actual population size has remained a challenge. Results support that the number of burrow entrances is positively correlated with population abundance, and burrow locations indicate the occupied area. We present an imagery-based method to identify and count animals’ burrows semi-automatically by combining remotely recorded red, green, and blue (RGB) images, pixel-based imagery, and random forest (RF) classification. Field images were collected for four colonies, then combined and processed by histogram matching and spectral band normalization to improve the spectral distinctions among the categories BURROW, SOIL, TREE, and GRASS. The accuracy indexes of classification for BURROW kappa (κ) were 95% (precision) and 90% (sensitivity). A 10-iteration bootstrapping of the final model resulted in coefficients of variation (CV%) of BURROW κ for sensitivity and precision lower than 5%; moreover, CV% values were not significantly different between those scores. The consistency of classification and balanced precision and sensitivity confirmed the applicability of this approach. Our approach provides an accurate, user-friendly, and relatively simple approach to count the number of burrow openings, estimate population abundance, and delineate the areas of occupancy non-invasively.
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POLITI, NATALIA, SEBASTIÁN MARTINUZZI, PATRICIA SARDINA ARAGÓN, et al. "Conservation status of the threatened and endemic Rufous-throated Dipper Cinclus schulzi in Argentina." Bird Conservation International 30, no. 3 (2019): 396–405. http://dx.doi.org/10.1017/s0959270919000467.
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SummaryThe Rufous-throated Dipper Cinclus schulzi is endemic to the Southern Yungas of north-western Argentina and southern Bolivia. The species is categorised as ‘Vulnerable’ on the IUCN Red List on the basis of small population size and restricted range. The purpose of our study was to determine the distribution of potentially suitable habitat for the Rufous-throated Dipper, estimate its population size, and assess potential distribution within strict protected areas, in north-western Argentina. We surveyed 44 rivers in the Southern Yungas of Argentina from 2010 to 2013 to determine dipper density (i.e. the number of individuals detected per km surveyed). The dipper’s potential distribution was assessed using a maximum entropy modeling approach based on 31 occurrence points and eight bioclimatic and two topographic variables as predictors. The species is dependent on mountain forest rivers, so the potential distribution was restricted to rivers. We estimated dipper population size by multiplying density by the potential distribution along rivers. Finally, we calculated the extent of suitable habitat contained within the boundaries of Argentina´s National Parks. Dipper density was 0.94 ± 1.55 individuals/km. We estimate that within north-west Argentina there are ~2,815 km of river that are potential habitat, with an area of occupancy of 141 km2 and a population size of 2,657 ± 4,355 dippers. However, of this river extent, less than 5% is within National Parks. Our results highlight the need to create new and to enlarge existing National Parks that protect the potentially suitable habitat of the species. Although more information is needed for Bolivia, the country-level area of occupancy and population size of the dipper found in Argentina provides strong evidence that the IUCN Red List classification of this species as ‘Vulnerable’ is warranted.
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Cheung, Sing Yiu, Sinem Coleri, Baris Dundar, Sumitra Ganesh, Chin-Woo Tan, and Pravin Varaiya. "Traffic Measurement and Vehicle Classification with Single Magnetic Sensor." Transportation Research Record: Journal of the Transportation Research Board 1917, no. 1 (2005): 173–81. http://dx.doi.org/10.1177/0361198105191700119.
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Wireless magnetic sensor networks offer an attractive, low-cost alternative to inductive loops for traffic measurement in freeways and at intersections. In addition to providing vehicle count, occupancy, and speed, these sensors yield information (such as non-axle-based vehicle classification) that cannot be obtained from standard loop data. Because such networks can be deployed quickly, they can be used (and reused) for temporary traffic measurement. This paper reports the detection capabilities of magnetic sensors on the basis of two field experiments. The first experiment collected a 2-h trace of measurements on Hearst Avenue in Berkeley, California. The vehicle detection rate was better than 99% (100% for vehicles other than motorcycles), and estimates of average vehicle length and speed appear to have been better than 90%. The measurements also yield intervehicle spacing or headways, revealing interesting phenomena such as platoon formation downstream of a traffic signal. Results of the second experiment are preliminary. Sensor data from 37 passing vehicles at the same site are processed and classified into six types. Sixty percent of the vehicles are classified correctly when length is not used as a feature. The classification algorithm can be implemented in real time by the sensor node itself, in contrast to other methods based on high-scan-rate inductive loop signals, which require extensive off-line computation. It is believed that if length were used as a feature, 80% to 90% of vehicles would be correctly classified.
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Wojna, Zbigniew, Krzysztof Maziarz, Łukasz Jocz, Robert Pałuba, Robert Kozikowski, and Iason Kokkinos. "Holistic Multi-View Building Analysis in the Wild with Projection Pooling." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 2870–78. http://dx.doi.org/10.1609/aaai.v35i4.16393.
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We address six different classification tasks related to fine-grained building attributes: construction type, number of floors, pitch and geometry of the roof, facade material, and occupancy class. Tackling such a remote building analysis problem became possible only recently due to growing large-scale datasets of urban scenes. To this end, we introduce a new benchmarking dataset, consisting of 49426 images (top-view and street-view) of 9674 buildings. These photos are further assembled, together with the geometric metadata. The dataset showcases various real-world challenges, such as occlusions, blur, partially visible objects, and a broad spectrum of buildings. We propose a new \emph{projection pooling layer}, creating a unified, top-view representation of the top-view and the side views in a high-dimensional space. It allows us to utilize the building and imagery metadata seamlessly. Introducing this layer improves classification accuracy -- compared to highly tuned baseline models -- indicating its suitability for building analysis.
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Okokpujie, Imhade P., Victor Essien, Omolayo M. Ikumapayi, Emeka S. Nnochiri, Kennedy Okokpujie, and Esther T. Akinlabi. "An Overview of Thermal Insulation Material for Sustainable Engineering Building Application." International Journal of Design & Nature and Ecodynamics 17, no. 6 (2022): 831–41. http://dx.doi.org/10.18280/ijdne.170603.
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Residential buildings help to facilitate the occupants against solar radiation and adverse weather conditions. However, the growing increase in climate change in our environment has resulted in different side effects on human’s health mostly in the northern region of Nigeria and other parts of the world where high radiation from the sun are experience. This has resulted to the key interests of this research on possible thermal insulation materials that can help resist or absorb the solar radiation effects that can cause damage to lives in our community. This literature review of thermal insulation materials aims to proffer a sustainable solution by evaluating the thermal performance of building materials to provide an eco-friendly environment for building occupants. This research also discusses the Application of Thermal Insulation Materials for Developing Roofing sheets. The classification of thermal insulation materials, heat transfer in insulation materials, factors that influence the choice of building materials and thermal conductivity, resistivity, resistance, and conductance. Advantages of building insulation materials on economic, comfort, and environmental were also studied, and the reviewing of previous and incorporating thermal insulation materials with roofs. From the critical review, the application of insulating materials for developing building materials is highly recommended due to the provision of an eco-friending environment with reduced energy consumption during applications of home appliances.
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Bradshaw, Corey J. A., Barry W. Brook, Steven Delean, et al. "Predictors of contraction and expansion of area of occupancy for British birds." Proceedings of the Royal Society B: Biological Sciences 281, no. 1786 (2014): 20140744. http://dx.doi.org/10.1098/rspb.2014.0744.
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Geographical range dynamics are driven by the joint effects of abiotic factors, human ecosystem modifications, biotic interactions and the intrinsic organismal responses to these. However, the relative contribution of each component remains largely unknown. Here, we compare the contribution of life-history attributes, broad-scale gradients in climate and geographical context of species’ historical ranges, as predictors of recent changes in area of occupancy for 116 terrestrial British breeding birds (74 contractors, 42 expanders) between the early 1970s and late 1990s. Regional threat classifications demonstrated that the species of highest conservation concern showed both the largest contractions and the smallest expansions. Species responded differently to climate depending on geographical distribution—northern species changed their area of occupancy (expansion or contraction) more in warmer and drier regions, whereas southern species changed more in colder and wetter environments. Species with slow life history (larger body size) tended to have a lower probability of changing their area of occupancy than species with faster life history, whereas species with greater natal dispersal capacity resisted contraction and, counterintuitively, expansion. Higher geographical fragmentation of species' range also increased expansion probability, possibly indicating a release from a previously limiting condition, for example through agricultural abandonment since the 1970s. After accounting statistically for the complexity and nonlinearity of the data, our results demonstrate two key aspects of changing area of occupancy for British birds: (i) climate is the dominant driver of change, but direction of effect depends on geographical context, and (ii) all of our predictors generally had a similar effect regardless of the direction of the change (contraction versus expansion). Although we caution applying results from Britain's highly modified and well-studied bird community to other biogeographic regions, our results do indicate that a species' propensity to change area of occupancy over decadal scales can be explained partially by a combination of simple allometric predictors of life-history pace, average climate conditions and geographical context.
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Montereale Gavazzi, Giacomo, Danae Athena Kapasakali, Francis Kerchof, Samuel Deleu, Steven Degraer, and Vera Van Lancker. "Subtidal Natural Hard Substrate Quantitative Habitat Mapping: Interlinking Underwater Acoustics and Optical Imagery with Machine Learning." Remote Sensing 13, no. 22 (2021): 4608. http://dx.doi.org/10.3390/rs13224608.
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Subtidal natural hard substrates (SNHS) promote occupancy by rich benthic communities that provide irreplaceable and fundamental ecosystem functions, representing a global priority target for nature conservation and recognised in most European environmental legislation. However, scientifically validated methodologies for their quantitative spatial demarcation, including information on species occupancy and fine-scale environmental drivers (e.g., the effect of stone size on colonisation) are rare. This is, however, crucial information for sound ecological management. In this investigation, high-resolution (1 m) multibeam echosounder (MBES) depth and backscatter data and derivates, underwater imagery (UI) by video drop-frame, and grab sediment samples, all acquired within 32 km2 of seafloor in offshore Belgian waters, were integrated to produce a random forest (RF) spatial model, predicting the continuous distribution of the seafloor areal cover/m2 of the stones’ grain sizes promoting colonisation by sessile epilithic organisms. A semi-automated UI acquisition, processing, and analytical workflow was set up to quantitatively study the colonisation proportion of different grain sizes, identifying the colonisation potential to begin at stones with grain sizes Ø ≥ 2 cm. This parameter (i.e., % areal cover of stones Ø ≥ 2 cm/m2) was selected as the response variable for spatial predictive modelling. The model output is presented along with a protocol of error and uncertainty estimation. RF is confirmed as an accurate, versatile, and transferable mapping methodology, applicable to area-wide mapping of SNHS. UI is confirmed as an essential aid to acoustic seafloor classification, providing spatially representative numerical observations needed to carry out quantitative seafloor modelling of ecologically relevant parameters. This contribution sheds innovative insights into the ecologically relevant delineation of subtidal natural reef habitat, exploiting state-of-the-art underwater remote sensing and acoustic seafloor classification approaches.
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Kaya, Sezgin, and Keith Alexander. "Classifying client side FM organisations in the United Kingdom." Journal of Facilities Management 4, no. 2 (2006): 86–98. http://dx.doi.org/10.1108/14725960610651188.
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PurposeTo demonstrate the negative results of market sector based classification of client side FM organisations (FMOs) in benchmarking studies, and propose collection of both external and internal organisational patterns as the key characteristics of FMOs.Design/methodology/approachInterviews with leading consultants, clients and academics on the negative side effects of the current benchmarking studies in FM, followed by a critique of published FM and Organisational management studies to explore the characteristics of FMOs. As a result, it is proposed that characteristics of FMOs depend on its relations to the external and internal patterns.FindingsIt has been found that in literature and practice on FMOs, characteristics related to the internal environment of FMOs are neglected. These characteristics are: hierarchy, specialisation, centralisation, span of control, size, and reporting line. On the other hand, those related to the external environment of FM are widely covered in FM literature. These characteristics are occupancy profile, change, visibility to customers, and procurement options. This paper concludes with the proposition that the external and internal patterns collectively define the characteristics of FMOs and should equally be taken into account.Research limitations/implicationsPrepares the background for an exploration of what makes FM organizations similar and dissimilar to each other. The extent of interviews and literature survey is explorative and hence inclusive.Practical implicationsA systematic exploration for comparative FM studies in the UK, and also source of information for FM scholars striving for understanding the context and relationships in client FM organizations.Originality/valueThis paper extends the depth and scrutiny of studies related to FM organizations by investigating both practice and theory and proposes a system that can explain the differences between FM organizations.
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Jiang, Qiwen, Jialu Liu, and Xian Yang. "Optimization of indoor quality and thermal comfort for university classrooms using data-based machine learning." E3S Web of Conferences 546 (2024): 02011. http://dx.doi.org/10.1051/e3sconf/202454602011.
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Improving indoor environment quality on university classrooms is a hot research topic. The on-site experiment was conducted on indoor environmental quality regarding temperature, humidity, air pollutants, light and acoustics during different seasonal conditions. The result shows that nearly 25% of indoor particulate matters exceeded the GB18883 standard when the outdoor environmental pollution was severe under natural ventilation conditions in autumn. More than 20% of students experienced symptoms of drowsiness, dizziness, chest tightness, poor breathing, as well as depression and irritability. From the analysis of occupant demand, indoor air pollution and thermal comfort are the most anticipated areas for students to improve their learning environment. This paper proposes an optimal IEQ prediction model integrated with students’ satisfaction and indoor environmental features using machine-learning classification algorithms. The back-propagation neural network shows the high prediction accuracy among different algorithms. The traditional PMV-PPD model shows an accuracy rate of only 28% for thermal sensation prediction, while the highest prediction accuracy obtained through machine learning algorithms is about 75%. Moreover, the influence of individual’s thermal adaptation ability, including gender, long-term thermal experience, and psychological factors, and environmental factors was analyzed in this study.
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Qi, Xuan, Zegang Sun, Xue Mei, and Ryad Chellali. "A Lightweight Binarized Convolutional Neural Network Model for Small Memory and Low-Cost Mobile Devices." Mobile Information Systems 2023 (April 12, 2023): 1–11. http://dx.doi.org/10.1155/2023/5870630.
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In recent years, the high cost of implementing deep neural networks due to their large model size and parameter complexity has made it a challenging problem to design lightweight models that reduce application costs. The existing binarized neural networks suffer from both the large memory occupancy and the big number of trainable params they use. We propose a lightweight binarized convolutional neural network (CBCNN) model to address the multiclass classification/identification problem. We use both binary weights and activation. We show experimentally that a model using only 0.59 M trainable params is sufficient to reach about 92.94% accuracy on the GTSRB dataset, and it has similar performances compared to other methods on MNIST and Fashion-MNIST datasets. Accordingly, most arithmetic operations with bitwise operations are simplified, thus both used memory size and memory accesses are reduced by 32 times. Moreover, the color information was removed, which also reduced drastically the training time. All these together allow our architecture to run effectively and in real time on simple CPUs (rather than GPUs). Through the results we obtained, we show that despite simplifications and color information removal, our network achieves similar performances compared to classical CNNs with lower costs in both in training and embedded deployment.
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Porter, Keith. "Cracking an Open Safe: Uncertainty in HAZUS-Based Seismic Vulnerability Functions." Earthquake Spectra 26, no. 3 (2010): 893–900. http://dx.doi.org/10.1193/1.3459153.
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The “cracking an open safe” methodology has been used to tabulate HAZUS-based seismic vulnerability as functions of structure-independent intensity, while avoiding iteration in the structural analysis. The vulnerability functions give mean damage factor (MDF, defined here as mean repair cost as a fraction of replacement cost) versus 5%-damped elastic spectral acceleration response at 0.3-second and 1.0-second periods, for every combination of occupancy type, model building type, design level, magnitude, distance, site soil classification, etc. Like HAZUS-MH, these prior seismic vulnerability functions give no estimate of uncertainty in damage factor. The coefficient of variation (COV) of damage factor is readily calculated by taking advantage of the fact that that at any level of excitation there is a probability mass function of damage state and an implicit distribution of repair cost conditioned on damage state. COV is calculated here for each combination of occupancy type, model building type, etc., tabulated alongside MDF, and the tables presented for public use at www.risk-agora.org . It is found that a HAZUS-based COV generally decreases with increasing MDF (as has been observed using other analytical vulnerability methods), and the standard deviation of damage factor generally increases with increasing MDF.
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Wang, Ping, Thomas P. Gray, Zhe Li, et al. "Mineralogical classification and crystal water characterisation of beryl from the W–Sn–Be occurrence of Xuebaoding, Sichuan province, western China." Mineralogical Magazine 85, no. 2 (2021): 172–88. http://dx.doi.org/10.1180/mgm.2021.13.
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AbstractBeryl from Xuebaoding, Sichuan Province, western China is known for its unusual tabular habit and W–Sn–Be paragenesis in a greisen-type deposit. The crystals are typically colourless transparent to pale blue, often with screw dislocations of hexagonal symmetry on the (0001) crystal faces. Combining electron microprobe analyses and laser ablation inductively coupled plasma mass spectrometry with single-crystal X-ray diffraction (XRD), correlated with Raman and micro-infrared (IR) spectroscopy and imaging, the crystal chemical characteristics are determined. The contents of Na+ (0.24–0.38 atoms per formula unit (apfu)) and Li+ up to 0.38 apfu are at the high end compared to beryl from other localities worldwide. Li+ substitution for Be2+ on the tetrahedral (T2) site is predominantly charge balanced by Na+ on the smaller channel (C2) site, with Na+ ranging from 91.5% to 99.7% (apfu) of the sum of all other alkali elements. Cs+ and minor Rb+ and K+ primarily charge balance the minor M2+ substitution for Al3+ at the A site; all iron at the A site is suggested to be trivalent. The a axis ranges from 9.2161(2) to 9.2171(4) Å, with unit-cell volume from 678.03(3) to 678.48(7) Å3. The c/a ratio of 1.0002–1.0005 is characteristic for T2-type beryl with unit-cell parameters controlled primarily by Be2+ substitution. Transmission micro-IR vibrational spectroscopy and imaging identifies coordination of one or two water molecules to Na+ (type IIs and type IId, respectively) as well as alkali free water (type I). Based on IR absorption cross section and XRD a C1 site water content of 0.4–0.5 apfu is derived, i.e. close to 50% site occupancy. Secondary crystal phases with a decrease in Fe and Mg, yet increase in Na, suggest early crystallisation of aquamarine, with goshenite being late. With similar crystal chemistry to beryl of columnar habit from other localities worldwide, the tabular habit of Xuebaoding beryl seems to be unrelated to chemical composition and alkali content.
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Sulistiyo, Restu Budi, and Fakhri. "Malacofauna from Cappa Lombo Site: Environmental Reconstruction and Subsistence Strategies of The Bontocani Highland Karst Region, South Sulawesi." KALPATARU 32, no. 1 (2023): 47–62. http://dx.doi.org/10.55981/kpt.2023.1045.
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The remains of mollusk shell fragments are ecofacts that can explain the environmental conditions occupied by humans, especially in the context of the Holocene period in Sulawesi. This research answers questions related to the types of mollusks found in the cultural layer and aims to identify malacofauna remains at the Cappa Lombo site, Bontocani, South Sulawesi. The data collection method was carried out through excavation, and the analytical method involved taxonomic identification, external morphological identification, taxonomic classification, and documentation. This study successfully identified 10 families consisting of 15 genera and species. Terrestrial gastropod mollusks consist of the families Alycaeidae, Cyclophoridae, Ariophantidae, Dyakiidae, Clausiliidae, Achatinidae, and Camaenidae. Freshwater gastropods consist of 2 families, namely Pachychilidae and Viviparidae, while the bivalve class is only represented by the Cyrenidae family, which inhabits estuaries. Based on this identification, this research shows that the reconstruction of the environmental conditions around this site indicates a wet rainforest environment, which tends to be covered with vegetation and primary tropical forest. Additionally, during the occupancy period, there was a change in land use around this site. Data on the presence of mollusks also indicate consumption. Although mollusks were not a primary dietary source, humans during the Holocene at this site were able to utilize the aquatic environmental resources around the site they inhabited.
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Triqui, Manar, and Fatima Mazouz. "Urban expansion and heritage threats: Preservation of Mansourah archaelogical site in Tlemcen, Algeria." Architecture Papers of the Faculty of Architecture and Design STU 29, no. 4 (2024): 30–41. https://doi.org/10.2478/alfa-2024-0021.
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Abstract As a rule, heritage plays a crucial role in shaping the identity of communities, with archaeological sites, in particular, being irreplaceable material witnesses of bygone eras. However, due to their fragility and non-renewable nature, they require strict protection. In Algeria, the archaeological site of Mansourah, located southwest of Tlemcen, is noticeable for its exceptional historical and architectural significance. A legacy of the Marinids of Fez, the site notably houses the Mansourah Mosque, considered the last great mosque with a military purpose in the Muslim West. This research project addresses the issue of preserving the archaeological site of Mansourah in the face of chaotic urban expansion in Tlemcen. The research is based on a mixed methodology, combining historical, architectural, and urban analyses. Between 2021 and 2023, field surveys were conducted alongside an inventory of relevant documents and multi-temporal satellite images. These data enable a comparative study of the development of the urban fabric on the archaeological site and its surroundings. Semi-structured interviews were also conducted with residents of informal housing units, revealing their perceptions of the importance of the site and its preservation. The aim of this article is to analyse the major challenges in preserving the archaeological site of Mansourah in Tlemcen amid urban expansion, by examining the perception of this heritage by the occupants of dwellings encroaching on the site and its surroundings. The study highlights that, despite its classification, the site is often seen as a constraint rather than a resource. Finally, the article calls for a specific operational management plan to enhance the history of Mansourah while taking contemporary urban realities into account.
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Balachandran, Prasanna V., and Krishna Rajan. "Structure maps for A I 4 A II 6(BO4)6X2 apatite compounds via data mining." Acta Crystallographica Section B Structural Science 68, no. 1 (2012): 24–33. http://dx.doi.org/10.1107/s0108768111054061.
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This paper describes a method to identify key crystallographic parameters that can serve as strong classifiers of crystal chemistries and hence define new structure maps. The selection of this pair of key parameters from a large set of potential classifiers is accomplished through a linear data-dimensionality reduction method. A multivariate data set of known A I 4 A II 6(BO4)6 X 2 apatites is used as the basis for the study where each A I 4 A II 6(BO4)6 X 2 compound is represented as a 29-dimensional vector, where the vector components are discrete scalar descriptors of electronic and crystal structure attributes. A new structure map, defined using the two distortion angles αAII (rotation angle of A II—A II—A II triangular units) and ψAIz = 0 AI—O1 (angle the A I—O1 bond makes with the c axis when z = 0 for the A I site), is shown to classify apatite crystal chemistries based on site occupancy on the A, B and X sites. The classification is accomplished using a K-means clustering analysis.
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Atencio, Daniel, Andrezza A. Azzi, Kai Qu, Ritsuro Miyawaki, Ferdinando Bosi, and Koichi Momma. "Changes to the cerite group nomenclature." European Journal of Mineralogy 35, no. 6 (2023): 1027–30. http://dx.doi.org/10.5194/ejm-35-1027-2023.
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Abstract. The cerite and merrillite groups belong to the cerite supergroup. Some nomenclature and classification changes have been made to the cerite group, whereas the merrillite group remains unchanged. Minerals of the cerite group have the general formula A9XM[T7O24Ø4]Z3, where T is Si. The cerite group, from now on, is subdivided into two subgroups, cerite and taipingite. The root name will be cerite and taipingite if the Z anions are dominated by (OH) and F, respectively. The prefix ferri- or alumino- will be added if the M cations are dominated by Fe3+ or Al, respectively. If the M cation is Mg, there will be no prefix. Taking into account the valency-imposed double site occupancy and the site total charge approach, a double suffix will be used to represent the essential A constituents in the general chemical formula. Cerite-(Ce), aluminocerite-(Ce), ferricerite-(La), and taipingite-(Ce) have been renamed cerite-(CeCa), aluminocerite-(CeCa), ferricerite-(LaCa), and taipingite-(CeCa), respectively. The newly approved mineral aluminotaipingite-(CeCa) also belongs to the taipingite subgroup.
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Shah, Sayyed Sadaqat Hussain, Iqra Mujataba, Muhammad Asif Khan, Hossam Haddad, and Nidal Mahmoud Al-Ramahi. "Unlocking the puzzle: Corporate hedging’s ripple effect on investor sentiments amid asymmetries." Journal of Infrastructure, Policy and Development 8, no. 8 (2024): 3524. http://dx.doi.org/10.24294/jipd.v8i8.3524.
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Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.
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Gomes, Saturnino. "Disasters and Mitigation in Civil Engineering Perspective (Case Study: Flooding Overflow Occurred and Hit Dili, Capital of Timor-Leste on 4th April, 2021)." Transactions on Engineering and Computing Sciences 13, no. 02 (2025): 144–57. https://doi.org/10.14738/tecs.1302.18573.
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Civil engineering disasters refer to failures in infrastructure and construction that result in catastrophic consequences, often leading to loss of life, property damage, and economic setbacks. These disaster can be caused by natural hazards, design flaws, material failures, or human errors. Mitigation strategies in civil engineering focus on designing resilient structures, implementing strict building codes, and using advanced technologies to prevent or minimize disaster impact. This paper presents the concept of civil engineering disasters, their characteristics, classification, causes, and mitigationtechnologies. Civilengineering disasters are caused primarily by civil engineering defects, which are usuallyattributed toimproper selection of construction site, hazard assessment, design and construction, occupancy, and maintenance. Fromthis viewpoint, manynatural disasters such as earthquakes, strong winds, floods, landslides, and debris flowsare substantially due to civil engineering defects rather than the actual natural hazards. Civil engineering disasters occurfrequently and globally and are the most closely related to human beings among all disasters.
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Gomes, Saturnino. "Disasters and Mitigation in Civil Engineering Perspective (Case Study: Flooding Overflow Occurred and Hit Dili, Capital of Timor-Leste on 4th April, 2021)." Transactions on Machine Learning and Artificial Intelligence 13, no. 02 (2025): 144–57. https://doi.org/10.14738/tmlai.1302.18573.
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Civil engineering disasters refer to failures in infrastructure and construction that result in catastrophic consequences, often leading to loss of life, property damage, and economic setbacks. These disaster can be caused by natural hazards, design flaws, material failures, or human errors. Mitigation strategies in civil engineering focus on designing resilient structures, implementing strict building codes, and using advanced technologies to prevent or minimize disaster impact. This paper presents the concept of civil engineering disasters, their characteristics, classification, causes, and mitigationtechnologies. Civilengineering disasters are caused primarily by civil engineering defects, which are usuallyattributed toimproper selection of construction site, hazard assessment, design and construction, occupancy, and maintenance. Fromthis viewpoint, manynatural disasters such as earthquakes, strong winds, floods, landslides, and debris flowsare substantially due to civil engineering defects rather than the actual natural hazards. Civil engineering disasters occurfrequently and globally and are the most closely related to human beings among all disasters.
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Cabral, Matheus R., and Pierre Blanchet. "Prioritizing Indicators for Material Selection in Prefabricated Wooden Construction." Buildings 14, no. 1 (2023): 63. http://dx.doi.org/10.3390/buildings14010063.
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Material selection in buildings profoundly affects project success, encompassing durability, maintenance, customer satisfaction, production systems, lifecycle, usage, environment, and costs. Yet, there is a need for further research on indicators for choosing materials in prefabricated buildings. Therefore, this study’s main objective was to identify the indicators (criteria and sub-criteria) for selecting materials for prefabricated wooden construction and, subsequently, categorize these criteria and sub-criteria based on the perspective of industry professionals. To achieve this goal, three phases were carried out. First, a literature review was conducted to identify potential criteria for choosing structural and envelope materials in wooden prefabricated buildings. Second, a pilot survey was conducted in Canada and the United States to classify the priority order of the criteria obtained from the literature based on professionals’ opinions. Finally, Monte Carlo simulations were conducted with different iterations (1000, 10,000, and 100,000) using the data obtained from the previous phase to improve decision-making and classification processes. For the indicators to select materials, the literature review identified seven main criteria: performance properties, green materials, energy efficiency, circular economy, site conditions and material logistics, standards, and social impact. These criteria contained a total of 25 sub-criteria. The pilot survey data analysis demonstrated that the performance properties, site conditions and material logistics, and social impact criteria were consistently prioritized. The critical sub-criteria identified were fire resistance, watertightness, local availability, occupant health, and safety and protection. For the Monte Calo simulations, the predictions aligned with the pilot study, enhancing the robustness of the results.
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Albatayneh, Aiman, Tarek Tayara, Mustafa Jaradat, et al. "Optimum Building Design Variables in a Warm Saharan Mediterranean Climate Zone." International Journal of Photoenergy 2021 (May 25, 2021): 1–13. http://dx.doi.org/10.1155/2021/6672260.
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This research contributes to making residential buildings more efficient in the city of Azraq, Jordan, which is located in a warm climate zone in the Saharan Mediterranean region (classified as a hot desert climate according to the Köppen climate classification). It involved the optimisation of several envelope parameters with the aim of reducing the usage of energy within a normal structure occupying an area of 186 m2 without the occupants’ involvement in saving energy in the building to solely measure the building envelope’s thermal performance. The DesignBuilder software was used for the sensitivity analysis using 12 design variables, which enabled their significance for both cooling and heating loads. The selected variables were separated into two categories based on their level of significance: a group with higher importance (window to wall %, local type of shading, ground floor building, natural rate of ventilation, rate of infiltration, kind of glazing, and flat roof structure) as well as a group with lower importance (partition construction, site position, construction of outside walls, kind of window blinds, and window shade control timetable); these variables will save a significant amount of heating and cooling energy.
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Choe, Yeong Sim, Regina E. Y. Kim, Hye Weon Kim, et al. "Automated Scoring of Alzheimer’s Disease Atrophy Scale with Subtype Classification Using Deep Learning-Based T1-Weighted Magnetic Resonance Image Segmentation." Journal of Alzheimer's Disease Reports 8, no. 1 (2024): 863–76. http://dx.doi.org/10.3233/adr-230105.
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Background: Application of visual scoring scales for regional atrophy in Alzheimer’s disease (AD) in clinical settings is limited by their high time cost and low intra/inter-rater agreement. Objective: To provide automated atrophy scoring using objective volume driven from deep-learning segmentation methods for AD subtype classification using magnetic resonance imaging (MRI). Methods: We enrolled 3,959 participants (1,732 cognitively normal [CN], 1594 with mild cognitive impairment [MCI], and 633 with AD). The occupancy indices for each regional volume were calculated by dividing each volume by the size of the lateral and inferior ventricular volumes. MR images from 355 participants (119 CN, 119 MCI, and 117 AD) from three different centers were used for validation. Two neuroradiologists performed visual assessments of the medial temporal, posterior, and global cortical atrophy scores in the frontal lobe using T1-weighted MR images. Images were also analyzed using the deep learning-based segmentation software, Neurophet AQUA. Cutoff values for the three scores were determined using the data distribution according to age. The scoring results were compared for consistency and reliability. Results: Four volumetric-driven scoring results showed a high correlation with the visual scoring results for AD, MCI, and CN. The overall agreement with human raters was weak-to-moderate for atrophy scoring in CN participants, and good-to-almost perfect in AD and MCI participants. AD subtyping by automated scores also showed usefulness as a research tool. Conclusions: Determining AD subtypes using automated atrophy scoring for late-MCI and AD could be useful in clinical settings or multicenter studies with large datasets.
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Missen, O. P., S. J. Mills, M. D. Welch, et al. "The crystal structure of cesbronite, Cu3TeO4(OH)4: a novel sheet tellurate topology." Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials 74, no. 1 (2018): 24–31. http://dx.doi.org/10.1107/s205252061701647x.
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The crystal structure of cesbronite has been determined using single-crystal X-ray diffraction and supported by electron-microprobe analysis, powder diffraction and Raman spectroscopy. Cesbronite is orthorhombic, space group Cmcm, with a = 2.93172 (16), b = 11.8414 (6), c = 8.6047 (4) Å and V = 298.72 (3) Å3. The chemical formula of cesbronite has been revised to CuII 3TeVIO4(OH)4 from CuII 5(TeIVO3)2(OH)6·2H2O. This change has been accepted by the Commission on New Minerals, Nomenclature and Classification of the International Mineralogical Association, Proposal 17-C. The previously reported oxidation state of tellurium has been shown to be incorrect; the crystal structure, bond valence studies and charge balance clearly show tellurium to be hexavalent. The crystal structure of cesbronite is formed from corrugated sheets of edge-sharing CuO6 and (Cu0.5Te0.5)O6 octahedra. The structure determined here is an average structure that has underlying ordering of Cu and Te at one of the two metal sites, designated as M, which has an occupancy Cu0.5Te0.5. This averaging probably arises from an absence of correlation between adjacent polyhedral sheets, as there are two different hydrogen-bonding configurations linking sheets that are related by a ½a offset. Randomised stacking of these two configurations results in the superposition of Cu and Te and leads to the Cu0.5Te0.5 occupancy of the M site in the average structure. Bond-valence analysis is used to choose the most probable Cu/Te ordering scheme and also to identify protonation sites (OH). The chosen ordering scheme and its associated OH sites are shown to be consistent with the revised chemical formula.
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Vega, Julio. "Control System for Indoor Safety Measures Using a Faster R-CNN Architecture." Electronics 12, no. 11 (2023): 2378. http://dx.doi.org/10.3390/electronics12112378.
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This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system’s robustness and scalability to larger indoor environments with more complex safety hazards.
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Jauharatna, Katrynada, and Anggraeni . "PEMANFAATAN ALAT SERPIH DI CERUK LAYAH KECAMATAN SAMPUNG, KABUPATEN PONOROGO, JAWA TIMUR (BERDASARKAN KAJIAN MIKROSKOPIS JEJAK PAKAI DENGAN PERBESARAN RENDAH)." PANALUNGTIK 2, no. 1 (2019): 59–75. http://dx.doi.org/10.24164/pnk.v2i1.21.
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Ceruk Layah is a site that located in Sampung Karst Region, Ponorogo, East Java. Based on the result of excavation conducted by Balai Arkeologi Yogyakarta in the ear of 2000-2002, the finds were dominated by stone artefacts and pottery fragments. Techno-economy study and stone artefacts classification had been done macroscopically. Further analysis is needed to ascertain whether stone tools in Ceruk Layah had been utilized by its occupants. There are three questions, concerning the variation of microware of the flake tools, the utilization of the flake tools, and the resistance of the worked materials on flake tools. This study applies macroscopic and microscopic analysis. Macroscopic analysis aims to determine the dimension, material, distribution, and location of microware of the flake tools. While microscopic analysis aims to identify the microware of flake tools by using low magnification (50 X), and to measure the depth and length of the fracture of the flake tools. The objective of the measurements of the fracture is to distinguish the fracture caused by flaking and utilization of the flake tools. The results of analysis shows that the sixteen pieces of flake tools in the Ceruk Layah carries three microwares which were dominated by fracture, while striation and polish were rarely found. In addition, each flake tool carries fracture that varies on the length and depth. The flake tools of Ceruk Layah might have been used for cutting, whittling, sawing, scraping, and boring. The resistance of the worked material consists of soft resistance, moderate resistance, and hard resistance.
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Khorasani Zadeh, Z., M. Ouf, B. Gunay, B. Delcroix, G. Larochelle Martin, and A. Daoud. "Exploring thermostat override behavior during direct load control events." Journal of Physics: Conference Series 2600, no. 5 (2023): 052003. http://dx.doi.org/10.1088/1742-6596/2600/5/052003.
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Abstract Direct load control (DLC) is considered a viable solution to promote demand-side energy management, in which the utility provider adjusts consumers’ temperature setpoints via smart thermostats. Users commonly have the option to interrupt DLC and override them by adjusting their thermostat setpoints. However, the occurrence of overrides can have a detrimental impact on the overall efficacy of DLC. The user discomfort and the fact that an override may increase the load unexpectedly on the grid highlight the importance of understanding override mechanisms during DLC and the uncertainty related to occupants’ responses. This study examined user interactions with smart thermostats during DLC events using real-world data from the Ecobee Donate Your Data (DYD) program. According to the results, 35% of DLC was overridden by users, resulting in higher energy consumption during peak periods. A comprehensive analysis of four types of variables was conducted. A decision tree algorithm was used to classify smart thermostat users into two categories: “compliant users,” who rarely override DLC, and “non-compliant users,” who frequently override DLC, based on general information about their behavior and preferences and without any prior DLC experience. Moreover, three distinct types of DLC participants, characterized by their preferences and behaviors, were identified using a clustering algorithm. Classification results provide utilities with insight into where resources and efforts should be allocated to users who are more likely to comply with DLC. Clustering users into different typologies will enable utilities to design targeted and less disruptive DLC better aligned with the needs of DLC participants.
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Yu, Shanshan, and Hao Wang. "Prediction of Urban Street Public Space Art Design Indicators Based on Deep Convolutional Neural Network." Computational Intelligence and Neuroscience 2022 (May 11, 2022): 1–12. http://dx.doi.org/10.1155/2022/5508623.
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This paper analyzes and studies the structure and parameters of the VGGNet network model and selects the most commonly used and efficient VGG-16 as the prototype of the improved model. A multiscale sampling layer is added at the end of the VGG-16 convolution part so that the model can input images of any size for training and testing while reducing the number of neurons in the fully connected layer. This improves the training speed of the model under the premise of ensuring the accuracy. This paper uses multisource street spatial data combined with geographic information spatial analysis technology to measure and evaluate the spatial quality of streets in the main urban area. From the three dimensions of vitality, safety, and greenness of urban street space quality, a systematic structure for evaluation and analysis of street space quality is constructed. Street vitality includes eight index factors: entrance and exit density, street furniture density, street sketch density, street characteristic landscape density, POI density, POI diversity, commercial POI ratio, and street population density. There are five index factors: degree, roadside parking occupancy ratio, traffic signal system density, sidewalk width proportion, and street facility density. We use ArcGIS to build an index factor information database for statistical analysis and visualization. According to the natural discontinuous point classification method, the safety level of urban street public space is divided into five grades. The sample size of the first four grades has a small fluctuation range. The sample sizes are 153, 172, 153, and 158, respectively, accounting for 21%, 23%, 21%, and 21% of the total street samples, of which the first two grades occupy a total of 44%, so 44% of the streets in the main urban area have a low-quality level of street space. Level 5 has a sample of 102 streets, accounting for 14%, with an average street space quality value of 0.43.
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Tam, Constantine S., Stephen Opat, Gavin Cull, et al. "Twice Daily Dosing with the Highly Specific BTK Inhibitor, Bgb-3111, Achieves Complete and Continuous BTK Occupancy in Lymph Nodes, and Is Associated with Durable Responses in Patients (pts) with Chronic Lymphocytic Leukemia (CLL)/Small Lymphocytic Lymphoma (SLL)." Blood 128, no. 22 (2016): 642. http://dx.doi.org/10.1182/blood.v128.22.642.642.
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Abstract Introduction : BGB-3111 is a potent, highly specific and irreversible Bruton tyrosine kinase (BTK) inhibitor, with greater selectivity than ibrutinib (IB) for BTK vs. other TEC- and HER-family kinases. We previously reported that BGB-3111 320mg daily (the RP2D, given as a single or split dose) achieved plasma concentrations 6- to10-fold higher than that of IB 560mg QD. Complete BTK occupancy in peripheral blood mononuclear cells (PBMCs) was observed in all pts treated in the dose-escalation (DEsc) component of the Phase 1 trial, and preliminary data suggested that >90% blockade was achievable in lymph nodes (LN). We now report the results of BTK occupancy analyses in LN specimens from a dedicated pharmacodynamics (PD) cohort and update safety and efficacy in patients with CLL/SLL. Aims: (1)To determine BTK occupancy in LN samples from pts receiving either a daily or twice-daily regimen; and (2) to define the safety profile and activity of BGB-3111 in pts with relapsed/refractory (R/R) or previously untreated CLL/SLL. Methods: This Phase 1 trial included a DEsc component in pts with R/R B-cell malignancies, and disease-specific expansion cohorts (ECs), including CLL/SLL, at the RP2D (320mg daily, given either QD or as a split BID dose). Additionally, in a PD cohort, pts with R/R B-cell malignancies were assigned to BGB-3111 160mg BID vs 320mg QD, with paired LN biopsies at baseline and at day 3 (pre-dose), in order to determine BTK occupancy in LN at the time of trough drug exposure. Adverse events (AEs) are reported per CTCAE v4.03, and response according to the 2012 clarification of the International Workshop on CLL criteria (for CLL pts) or the 2014 Lugano Classification (for SLL pts). BTK occupancy was determined by competitive fluorescent probe assay. The data cut-off for this report was 10 June 2016. Results: BTK Occupancy: 30 pts were evaluated for LN BTK occupancy (CLL, n=9; DLBCL, n=3; FL, n=5; MCL, n=6; MZL, n=3; WM, n=4), 23 pts were enrolled in the PD cohort; 7 patients in other ECs (160mg BID) consented to optional paired LN biopsies. BTK occupancy in LN by dose/schedule is shown in Figure 1. Median occupancy was 99.5% (160mg BID, n=18) vs 94.4% (320mg QD, n=12) (p=0.002, Wilcoxon). The proportion of pts with >90% occupancy was 94% (160mg BID) vs 58% (320mg QD) (p=0.027, Fisher exact). Occupancy did not appear to differ amongst histologic subtypes. CLL/SLL Safety and Activity: As of 10 Jun 2016, 45 pts with CLL (n=42) or SLL (n=3) have been enrolled: 8 pts in DEsc (80mg QD [n=1], 160mg QD [n=2], 160mg BID [n=2], and 320mg QD [n=3]), and 37 in either the PD cohort or CLL/SLL EC (160mg BID, n=19; 320mg QD, n=18). 29 CLL/SLL pts are included in this analysis; 11 pts were excluded because of short (<12 weeks) follow-up, and 5 pts accrued at a single study site were excluded because of insufficient study documentation at baseline. Demographic and disease characteristics are shown in Table 1. BGB-3111 was well tolerated with 69% subjects reporting no drug related AE >Gr 1 severity within the first 12 weeks of therapy. The most frequent AEs of any attribution were petechiae/ bruising (38%), upper respiratory tract infection (31%, all Gr 1/2), diarrhea (28%, all Gr 1/2), fatigue (24%, all Gr 1/2), and cough (21%, all Gr 1/2). Three SAEs were assessed as possibly related to BGB-3111 (Gr 2 cardiac failure, Gr 2 pleural effusion and Gr 3 purpura, all n=1). The case of Gr 3 purpura was the only major bleeding event reported. Atrial fibrillation (Gr 2) occurred in one pt. Three pts had temporary dose interruption for AE, and one pt discontinued BGB-3111 for AE. After a median follow-up of 7.5 months (2.9-17.3 months), the response rate is 90% (26/29), with PR in 79% (23/29) and, PR-L in 10% (3/29), SD in 7% (2/29), and non-evaluable response in one pt who discontinued treatment prior to week 12. No instances of disease progression or Richter transformation have occurred. Conclusions: BGB-3111 is well-tolerated and highly active in R/R CLL/SLL. While trough BTK occupancy in lymph nodes was robust with either 320mg QD or 160mg BID dosing, complete and continuous occupancy (median 99.5%) was more frequently achieved with the 160mg PO BID regimen. Late stage clinical trials will determine if the optimized BTK occupancy with this regimen translates into improvements in disease control and reduced drug resistance. Figure. Figure. Disclosures Tam: janssen: Honoraria, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees. Opat:Roche: Consultancy, Honoraria, Other: Provision of subsidised drugs, Research Funding. Gottlieb:Indee: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees. Simpson:Celgene, Roche, Janssen: Honoraria; Amgen Pharmaceuticals: Research Funding. Anderson:Walter and Eliza Hall Institute of Medical Research: Other: Walter and Eliza Hall Institute of Medical Research receives milestone payments for the development of venetoclax. Kirschbaum:Beigene: Employment. Wang:Beigene: Employment. Xue:Beigene: Employment. Yang:BeiGene: Employment. Hedrick:Beigene: Employment. Seymour:Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Roberts:Genentech: Patents & Royalties: Employee of Walter and Eliza Hall Institute of Medical Research which receives milestone payments related to venetoclax; Janssen: Research Funding; Genentech: Research Funding; AbbVie: Research Funding; Servier: Research Funding.
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Pieczka, A., R. J. Evans, E. S. Grew, L. A. Groat, C. Ma, and G. R. Rossman. "The dumortierite supergroup. I. A new nomenclature for the dumortierite and holtite groups." Mineralogical Magazine 77, no. 6 (2013): 2825–39. http://dx.doi.org/10.1180/minmag.2013.077.6.09.
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AbstractAlthough the distinction between magnesiodumortieite and dumortierite, i.e. Mg vs. Al dominance at the partially vacant octahedral Al1 site, had met current criteria of the IMA Commission on New Minerals, Nomenclature and Classification (CNMNC) for distinguishing mineral species, the distinction between holtite and dumortierite had not, since Al and Si are dominant over Ta and (Sb, As) at the Al1 and two Si sites, respectively, in both minerals. Recent studies have revealed extensive solid solution between Al, Ti, Ta and Nb at Al1 and between Si, As and Sb at the two Si sites or nearly coincident (As, Sb) sites in dumortierite and holtite, further blurring the distinction between the two minerals.This situation necessitated revision in the nomenclature of the dumortierite group. The newly constituted dumortierite supergroup, space group Pnma (no. 62), comprises two groups and six minerals, one of which is the first member of a potential third group, all isostructural with dumortierite. The supergroup, which has been approved by the CNMNC, is based on more specific end-member compositions for dumortierite and holtite, in which occupancy of the Al1 site is critical.(1) Dumortierite group, with Al1 = Al3+, Mg2+ and ☐, where ☐ denotes cation vacancy. Charge balance is provided by OH substitution for O at the O2, O7 and O10 sites. In addition to dumortierite, endmember composition AlAl6BSi3O18, and magnesiodumortierite, endmember composition MgAl6BSi3O17(OH), plus three endmembers, “hydroxydumortierite”, ☐Al6BSi3O15(OH)3 and two Mg-Ti analogues of dumortierite, (Mg0.5Ti0.5)Al6BSi3O18 and (Mg0.5Ti0.5)Mg2Al4BSi3O16(OH)2, none of which correspond to mineral species. Three more hypothetical endmembers are derived by homovalent substitutions of Fe3+ for Al and Fe2+ for Mg.(2) Holtite group, with Al1 = Ta5+, Nb5+, Ti4+ and ☐. In contrast to the dumortierite group, vacancies serve not only to balance the extra charge introduced by the incorporation of pentavalent and quadrivalent cations for trivalent cations at Al1, but also to reduce repulsion between the highly charged cations. This group includes holtite, endmember composition (Ta0.6☐0.4)Al6BSi3O18, nioboholite (2012-68), endmember composition (Nb0.6☐0.4)Al6BSi3O18, and titanoholtite (2012-69), endmember composition (Ti0.75☐0.25)Al6BSi3O18.(3) Szklaryite (2012-70) with Al1 = ☐ and an endmember formula ☐Al6BAs3+3O15. Vacancies at Al1 are caused by loss of O at O2 and O7, which coordinate the Al1 with the Si sites, due to replacement of Si4+ by As3+ and Sb3+, and thus this mineral does not belong in either the dumortierite or the holtite group. Although szklaryite is distinguished by the mechanism introducing vacancies at the Al1 site, the primary criterion for identifying it is based on occupancy of the Si/As, Sb sites: (As3+ + Sb3+) > Si4+ consistent with the dominant-valency rule. A Sb3+ analogue to szklaryite is possible.
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Abouaiana, Ahmed, and Alessandra Battisti. "Insights and Evidence on Energy Retrofitting Practices in Rural Areas: Systematic Literature Review (2012–2023)." Buildings 13, no. 7 (2023): 1586. http://dx.doi.org/10.3390/buildings13071586.
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Rural commons face extraordinary challenges like fragility and sensitivity due to climate change. Retrofitting rural built environments affords benefits that could overcome these challenges and support sustainable development. However, notwithstanding the vast energy retrofitting interventions available, the associated aspects require investigation, particularly in distinct rural contexts with all their valuable, cultural, and historical inheritance. Hence, this study aimed to examine energy retrofitting practices in rural settlements worldwide over a decade to diagnose the goals that are being undertaken, stakeholder engagement, and finally, the bi-correlation between rural contexts and interventions, and retrofitting contributions to valorizing the place’s identity. This study is a systematic literature review (SLR) considering the items of the PRISMA checklist (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). An SLR of published peer-reviewed studies between January 2012 and March 2023 in 16 electronic databases in all available languages, using a combination of seven keywords within three domains, was conducted. The initial search resulted in 397; after applying the inclusion/exclusion criteria, there were 60 eligible articles. The academic progress and tendencies in the energy retrofitting domain of rural built environments are discussed and summarized into four major thematic classifications (energy efficiency strategies, energy efficiency planning, policy evaluation, and occupant behavior). Briefly, rural buildings lack energy-saving designs. Simulation tools are essential; however, they should be calibrated with on-site conditions, showing the reasons for selecting the applied retrofitting measures and correlation with the surrounding context. Successful implementation requires cross-disciplinary collaboration, engaging decision makers, and providing energy education for the local community. Regulations should include micro-context-specific environmental performance indicators. These insights could help map out future academic pursuits and help the stakeholders better understand their nature. Simultaneously, this study assists early-stage researchers in conducting systematic literature reviews utilizing different tools. However, the SLR protocol may have limited findings due to the specific search terms used, so the authors believe the more the literature search scope is broadened, the more discoveries could be made.
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Muthusamy, Prema, and Gomathi Pudupalayam Murugan. "An Optimization of Occlusion robust Spatio Temporal Hybrid Cue Network." International Journal of Engineering Research and Applications 14, no. 9 (2024): 68–80. http://dx.doi.org/10.9790/9622-14096880.
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Sign language (SL) is used by deaf-mute individuals for communication but normal people finds hard to understand the SL which causes a communication gap between them. It is crucial to reduce the gap between physically challenged people and normal people. In recent days, Deep Learning (DL) methods are used for the prediction of SLs. Amongst, Occlusion-resistant Spatio-Temporal Hybrid Cue Network (OSTHCN) method is developed which utilizes Skeleton Occupancy Likelihood Map estimation using B-Spline curve in Dynamic Dense Spatio-Temporal Graph Convolutional Neural Network (DDSTGCNN) to refine the skeleton extraction and VGG11+1D-Convolutinal Neural Network (CNN) for full frame data. It employs BLSTM encoders, Connectionist Temporal Classification (CTC), and Self-Attention based LSTM decoders for sequence learning in ISL recognition and translation. However, the networks utilized in the sequence learning are conceived manually by assigning values to a large number of hyper-parameters which results in high computational complexity and lower accuracy performance. Hence, an automated hyperparameter optimization model is developed in this paper using Dove Swarm Optimization (DSO) to lower the computational complexity and enhance the accuracy results. The DSO is adopted for selecting the optimal hyper-parameters in sequence learning like number of neurons, number of hidden units, learning rate, weight decay, number of epochs, batch size, dropout rate, number of partitions, number of clusters per batch, momentum, optimizer and loss function. The essential principle of DSO are derived from the foraging behaviors of doves adopted in real-time applications. The initial population of dove forages represents the initial hyper-parameters and computation of each dove crumbs subsequent locations represents the search for the best hyper-parameter to find the optimal values for the sequence learning. The BLSTM, CTC and SA-LSTM are completely optimized using DSO and it is termed as Optimized OSTHCN (OOSTHCN). Finally, the test findings revealed that the OOSTHCN model achieves 97.86% of accuracy on ISLCSLTR dataset compared to the existing models.
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Nichols, J. D., and D. I. MacKenzie. "Abundance estimation and Conservation Biology." Animal Biodiversity and Conservation 27, no. 1 (2004): 437–39. http://dx.doi.org/10.32800/abc.2004.27.0437.
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Abundance is the state variable of interest in most population–level ecological research and in most programs involving management and conservation of animal populations. Abundance is the single parameter of interest in capture–recapture models for closed populations (e.g., Darroch, 1958; Otis et al., 1978; Chao, 2001). The initial capture–recapture models developed for partially (Darroch, 1959) and completely (Jolly, 1965; Seber, 1965) open populations represented efforts to relax the restrictive assumption of population closure for the purpose of estimating abundance. Subsequent emphases in capture–recapture work were on survival rate estimation in the 1970’s and 1980’s (e.g., Burnham et al., 1987; Lebreton et al.,1992), and on movement estimation in the 1990’s (Brownie et al., 1993; Schwarz et al., 1993). However, from the mid–1990’s until the present time, capture–recapture investigators have expressed a renewed interest in abundance and related parameters (Pradel, 1996; Schwarz & Arnason, 1996; Schwarz, 2001). The focus of this session was abundance, and presentations covered topics ranging from estimation of abundance and rate of change in abundance, to inferences about the demographic processes underlying changes in abundance, to occupancy as a surrogate of abundance. The plenary paper by Link & Barker (2004) is provocative and very interesting, and it contains a number of important messages and suggestions. Link & Barker (2004) emphasize that the increasing complexity of capture–recapture models has resulted in large numbers of parameters and that a challenge to ecologists is to extract ecological signals from this complexity. They offer hierarchical models as a natural approach to inference in which traditional parameters are viewed as realizations of stochastic processes. These processes are governed by hyperparameters, and the inferential approach focuses on these hyperparameters. Link & Barker (2004) also suggest that our attention should be focused on relationships between demographic processes such as survival and recruitment, the two quantities responsible for changes in abundance, rather than simply on the magnitudes of these quantities. They describe a type of Jolly–Seber capture–recapture model that permits inference about the underlying relationship between per capita recruitment rates and survival rates (Link & Barker, this volume). Implementation used Bayesian Markov Chain Monte Carlo methods and appeared to work well, yielding inferences about the relationship between recruitment and survival that were robust to selection of prior distribution. We believe that readers will find their arguments compelling, and we expect to see increased use of hierarchical modeling approaches in capture–recapture and related fields. Otto (presentation without paper) also recommended use of hierarchical models in analysis of multiple data sources dealing with population dynamics of North American mallards. He integrated survival inferences from ringing data, abundance information from aerial survey data, and recruitment information based on age ratios from a harvest survey. He used a Leslie matrix population projection model as an integrating framework and obtained estimates of breeding population size using all data.Otto’s approach also permitted inference about biases in estimated quantities. As with the work of Link & Barker (2004), we find Otto’s recommendation to use hierarchical models to integrate data from multiple sources to be very compelling. Alisauskas et al. (2004) report results of an analysis of capture–recapture data for a askatchewan population of white–winged scoters. They used the approach of Pradel (1996) to estimate population growth rate (See the PDF) directly. Estimates for 1975–1985 were quite low, but estimates for the recent period, 2000–2003,increased to values > 1. Parameter estimates for seniority, survival and per capita recruitment (Pradel, 1996) led to the inference that increased recruitment was largely responsible for the improvements in population status and growth. However, various data sources also indicated that this increase in recruitment was likely a result of increased immigration rather than improved reproduction on the area. This latter inference is important from a conservation perspective in indicating the importance of birds in other locations to growth and health of the study population. Lukacs and Burnham presented material to be published elsewhere that dealt with the use of genetic markers in capture–recapture studies. The data sources for such studies are samples of hair or feces, which are then analyzed using molecular genetic techniques in order to determine individual genotypes with respect to a usually small number of loci. Two types of classification error can arise in such analyses. First, if only a small number of loci is examined, then there may be nonnegligible probabilities that multiple individual animals will have the same genotypes. The second type of error arises during the polymerase chain reaction (PCR) process and can result from failure of alleles to amplify (allelic dropout) or from PCR inhibitors in hair and feces that produce the appearance of false alleles or misprinting (Creel et al., 2003). Lukacs and Burnham developed models that formally incorporate possible misclassification of samples resulting from these errors. These models permit estimation of parameters such as abundance and survival in a manner that properly incorporates this uncertainty of individual identity. We anticipate that noninvasive sampling based on molecular genetic analyses of hair or feces will become extremely important for some species, and that the models of Lukacs and Burnham will become very popular for such analyses. MacKenzie & Nichols (2004) discuss the use of occupancy (proportion of patches or habitat area that is occupied) as a surrogate for abundance. In cases of territorial species and where birds occur at low densities, the number of occupied patches may provide a reasonable estimate of abundance. In other cases, occupancy can be viewed as providing information about one tail of the abundance distribution, P (N = 0). The motivation for considering occupancy as a surrogate for abundance is that occupancy is based on so–called presence–absence surveys that are frequently less expensive of time and effort than methods that estimate abundance directly. We describe one set of models that can be used to estimate occupancy for a single season and another that can be used to estimate parameters such as local probabilities of extinction and colonization that are associated with occupancy dynamics. We outline a possible hybrid approach that combines occupancy data with data on marked individuals in order to betterexplore the mechanisms underlying occupancy dynamics. These five presentations made for an interesting session containing useful information and recommendations for future work. A number of themes connecting these presentations could be emphasized. For example, two of the presentations considered alternatives to standard capture–recapture sampling that can be used to draw inferences about abundance, or a portion of the abundance distribution, with field methods that should be less expensive than usual capture–recapture approaches of handling animals. We believe that the most important theme of the session was the emphasis on the processes responsible for changes in abundance. In particular, we are excited by the potential for using hierarchical models as a means of investigating relationships among vital rates and as a means of combining multiple sources of data relevant to system dynamics. Indeed, we expect the importance of this session theme to be reflected in the content and presentations of the next EURING meeting.
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Ding, Yuxuan, Qiang Wang, Feijiang Wang, et al. "Abstract 3224: TTFields-prolonged the PFS of epithelioid glioblastoma patient: a case report." Cancer Research 83, no. 7_Supplement (2023): 3224. http://dx.doi.org/10.1158/1538-7445.am2023-3224.
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Abstract Epithelioid glioblastoma (EGBM, classified as glioblastoma, wild type, grade IV according to 2021 WHO CNS5 classification of neurological malignancies) is a highly aggressive malignancy, the median progression-free survival (mPFS) of which is about 4.0 months. Although, the introduction of tumor treating fields (TTFields, possessing anti-cancer capability via anti-mitotic effects) in the maintenance of TMZ chemotherapy was demonstrated beneficial for prolonging the mPFS of GBM patients to 6.9 months in the EF-14 clinical trial, studies centering on the significance of TTFields in EGBM treating are very limited due to the rarity of EGBM. Therefore, a 28-year-old patient (male, recurrent left-sided limb twitching for 1 month and dizziness for 1 week) was chosen as a clinical trial participant. A right frontal lobe occupancy was detected based on magnetic resonance imaging (MRI), and total tumor resection was performed on the patient. Meanwhile, postoperative histopathology test, including immunohistochemical and molecular characterization, was conducted and the results revealed a BRAF V600E mutation, no codeletion of 1p and 19q, and negative MGMT promoter methylation, which confirmed EGBM. In this context, chemoradiotherapy was conducted on the patient at first, and then concurrent TTFields and TMZ was performed. Notably, a long-term PFS of 33 months and KPS score of 90 were achieved over the patient upon TTFields combined TMZ, whose average daily usage of TTFields was higher than 90%. This clinical case corroborated the importance of TTFields in EGBM treating, and the higher compliance of TTFields is more beneficial for EGBM patient without additional side effect. YD, QW contributed equally to this work. Citation Format: Yuxuan Ding, Qiang Wang, Feijiang Wang, Nan Wu, Jianrui Li, Xia He, Hao Pan, Lijun Wang. TTFields-prolonged the PFS of epithelioid glioblastoma patient: a case report [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3224.