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Journal articles on the topic 'Multi close domain'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Iping, Supriana Ayu Purwarianti Wiwin Suwarningsih*. "ESTIMATION QUESTION TYPE ANALYZER FOR MULTI CLOSE DOMAIN INDONESIAN QAS." INTERNATIONAL JOURNAL OF RESEARCH SCIENCE & MANAGEMENT 4, no. 6 (2017): 59–66. https://doi.org/10.5281/zenodo.583975.

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We propose an automated estimation scheme to analyze question classification in Indonesian multi closed domain question answering systems. The goal is to provide a good questioning classification system even if using only available language sources. Our strategy here is to build a pattern and rule to extract some important words and utilize the results as a feature for classification estimation of automated learning-based questions. Scenarios designed in automated learning estimates: (i) Analyzing questions, to represent the key information needed to answer user questions using target focus an

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Yang, Dan, Tianyu Ma, and Zhipeng Li. "A multi-source domain adaption intelligent fault diagnosis method based on asymmetric adversarial training." Measurement Science and Technology 36, no. 3 (2025): 036123. https://doi.org/10.1088/1361-6501/adb2b1.

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Abstract To enhance the cross-domain diagnostic ability of the model, domain adaptation method is adopted. When using traditional domain adaption methods to extract domain invariant characteristics of axial flow fan faults, the characteristics of the source and target domains will be close to each other, thereby the distribution of trained source domain characteristics will be changed. When the fault characteristics of the source domain gather at the classification boundary, the trained model will incorrectly classify some target samples. In addition, single source domain adaptation can lead t

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Zhao, S., S. Saha, and X. X. Zhu. "GRAPH NEURAL NETWORK BASED OPEN-SET DOMAIN ADAPTATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 31, 2022): 1407–13. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-1407-2022.

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Abstract. Owing to the presence of many sensors and geographic/seasonal variations, domain adaptation is an important topic in remote sensing. However, most domain adaptation methods focus on close-set adaptation, i.e., they assume that the source and target domains share the same label space. This assumption often does not hold in practice, as there can be previously unseen classes in the target domain. To circumnavigate this issue, we propose a method for open set domain adaptation, where the target domain contains additional unknown classes that are not present in the source domain. To impr

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Syed, Muhammad Adnan, Yongsheng Ou, Tao Li, and Guolai Jiang. "Lightweight Multimodal Domain Generic Person Reidentification Metric for Person-Following Robots." Sensors 23, no. 2 (2023): 813. http://dx.doi.org/10.3390/s23020813.

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Recently, person-following robots have been increasingly used in many real-world applications, and they require robust and accurate person identification for tracking. Recent works proposed to use re-identification metrics for identification of the target person; however, these metrics suffer due to poor generalization, and due to impostors in nonlinear multi-modal world. This work learns a domain generic person re-identification to resolve real-world challenges and to identify the target person undergoing appearance changes when moving across different indoor and outdoor environments or domai

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Gysi, Tobias, Christoph Müller, Oleksandr Zinenko, et al. "Domain-Specific Multi-Level IR Rewriting for GPU." ACM Transactions on Architecture and Code Optimization 18, no. 4 (2021): 1–23. http://dx.doi.org/10.1145/3469030.

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Most compilers have a single core intermediate representation (IR) (e.g., LLVM) sometimes complemented with vaguely defined IR-like data structures. This IR is commonly low-level and close to machine instructions. As a result, optimizations relying on domain-specific information are either not possible or require complex analysis to recover the missing information. In contrast, multi-level rewriting instantiates a hierarchy of dialects (IRs), lowers programs level-by-level, and performs code transformations at the most suitable level. We demonstrate the effectiveness of this approach for the w

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Xiao, Haitao, Limeng Dong, Wenjie Wang, and Harutoshi Ogai. "Adversarial Auxiliary Weighted Subdomain Adaptation for Open-Set Deep Transfer Bridge Damage Diagnosis." Sensors 23, no. 4 (2023): 2200. http://dx.doi.org/10.3390/s23042200.

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Deep learning models have been widely used in data-driven bridge structural damage diagnosis methods in recent years. However, these methods require training and test datasets to satisfy the same distribution, which is difficult to satisfy in practice. Domain adaptation transfer learning is an efficient method to solve this problem. Most of the current domain adaptation methods focus on close-set scenarios with the same classes in the source and target domains. However, in practical applications, new damage caused by long-term degradation often makes the target and source domains dissimilar in

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Zhang, Yangyang, Ning Xu, Ning Li, and Zhengwei Guo. "A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets." Remote Sensing 15, no. 19 (2023): 4878. http://dx.doi.org/10.3390/rs15194878.

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As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to

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SANG NOUR POUR, N., M. NEMATI, M. GOALIPOUR, M. REZAEI, R. KHERADMAND, and G. YU KRYUCHKYAN. "MULTI-FREQUENCY SECOND HARMONIC GENERATION IN IRREGULAR TWO DIMENSIONAL APERIODIC OPTICAL SUPERLATTICES." International Journal of Modern Physics: Conference Series 15 (January 2012): 197–203. http://dx.doi.org/10.1142/s2010194512007155.

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We investigate two dimensional nonlinear aperiodic structures leading to multi quasi-phase-matching conditions and multi-frequency second-harmonic generation (SHG) in one chip. For arranging devices close to an experimental situation the intensities of SHG in dependence from frequencies and direction of radiation are studied for irregular structures with random fluctuations of the sizes of each poling domain. Comparing the regular and irregular two dimensional nonlinear aperiodic structures we study the role of imperfection effects of random fluctuations in multi-frequency SHG.

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Djuhana, Dede, Dita C. C. Oktri, and D. H. Kim. "Micromagnetic Simulation on Ground State Domain Structures of Barium Hexaferrite (BaFe₁₂O₁₉)." Advanced Materials Research 896 (February 2014): 414–17. http://dx.doi.org/10.4028/www.scientific.net/amr.896.414.

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We have systematically investigated the domain structures of Barium Hexaferrite (BaFe12O19) by means of a micromagnetic simulation under zero external magnetic field. A hexagonal-shaped and cylindrical-shaped models are used in this simulation with respect to the diameter variation from 50 nm to 600 nm. A transition domain structure is found from a single-domain (SD) to multi-domain (MD) at a certain diameter. The hexagonal-shaped occurs in diameter 430 nm and cylindrical-shaped in diameter 410 nm. Interestingly, the domain wall of MD structure exhibits a Bloch-wall type. The domain wall width

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Murshid, Syed, Adam Linoby, and Raja Nurul Jannat Raja Hussain. "Effect of single bout exercise modalities on multi-domain cognitive function in recreationally active older adults." Retos 66 (April 14, 2025): 313–22. https://doi.org/10.47197/retos.v66.110457.

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Introduction: The cognitive benefits of a single session of physical activity in older adults are still being studied. Objective: This study explored the effects of single bout exercise of open-skill and closed-skill on cognitive functions, in physically active older adults. Methodology: Ninety-nine health elderly were recruited and assigned to three groups: badminton (n=33), close skill (n=33), and control (n=33). Cognitive assessments, such as the N-back, Stroop, and Trail Making Tests, were administered before and after the exercise sessions. Results: ANOVA showed a primary effect of group

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Zeng, Zhengzhi, Chunshan Jiang, Yuanming Zhou, and Tianwei Zhou. "A Time–Frequency Domain Analysis Method for Variable Frequency Hopping Signal." Sensors 24, no. 19 (2024): 6449. http://dx.doi.org/10.3390/s24196449.

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A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time–frequency domain features, which adopts multi-level processing to solve the time–frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time

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Xia, Ming Fei, Yong Chuan Wang, and Gui Zhou Lv. "Single-Carrier Frequency Domain Equalization and Wireless Applications." Applied Mechanics and Materials 135-136 (October 2011): 907–12. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.907.

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In recent years, single-carrier system has again become an interesting and complementary alternative to multi-carrier system such as orthogonal frequency division multiplexing (OFDM). This has been largely due to the use of frequency domain equalizer implemented by means of fast Fourier transforms (FFT), bringing the complexity close to that of OFDM. This paper aims at providing an overview of single-carrier frequency domain equalization (SC-FDE) and its Wireless applications. We review the brief history and system model of SC-FDE, and the integration of SC-FDE and other wireless transmission

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Zhang, Junbo, Shifeng Xu, Jun Sun, Dinghua Ou, Xiaobo Wu, and Mantao Wang. "Unsupervised Adversarial Domain Adaptation for Agricultural Land Extraction of Remote Sensing Images." Remote Sensing 14, no. 24 (2022): 6298. http://dx.doi.org/10.3390/rs14246298.

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Agricultural land extraction is an essential technical means to promote sustainable agricultural development and modernization research. Existing supervised algorithms rely on many finely annotated remote-sensing images, which is both time-consuming and expensive. One way to reduce the annotation cost approach is to migrate models trained on existing annotated data (source domain) to unannotated data (target domain). However, model generalization capability is often unsatisfactory due to the limit of the domain gap. In this work, we use an unsupervised adversarial domain adaptation method to t

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Vorwerk, Pascal, Jörg Kelleter, Steffen Müller, and Ulrich Krause. "Classification in Early Fire Detection Using Multi-Sensor Nodes—A Transfer Learning Approach." Sensors 24, no. 5 (2024): 1428. http://dx.doi.org/10.3390/s24051428.

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Effective early fire detection is crucial for preventing damage to people and buildings, especially in fire-prone historic structures. However, due to the infrequent occurrence of fire events throughout a building’s lifespan, real-world data for training models are often sparse. In this study, we applied feature representation transfer and instance transfer in the context of early fire detection using multi-sensor nodes. The goal was to investigate whether training data from a small-scale setup (source domain) can be used to identify various incipient fire scenarios in their early stages withi

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Bragin, Alexey. "A Problem-oriented Language for Modeling Communities." Artificial societies 19, no. 2 (2024): 0. http://dx.doi.org/10.18254/s207751800030750-4.

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In multi-agent modeling, a key aspect is the implementation of the model as a computer program. The model implementation can be made more convenient by using a domain-specific language (DSL). In this work, a library was developed in the C# programming language, representing a domain-specific language that allows for the formulation of the modeling task at a high level in terms that are close to the subject area. Data structures and a class hierarchy were proposed. An implementation of an agent whose composition of attributes can change during the modeling process was proposed. The library also

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Maisto, Maria Antonia, Mehdi Masoodi, Giovanni Leone, Raffaele Solimene, and Rocco Pierri. "Scattered Far-Field Sampling in Multi-Static Multi-Frequency Configuration." Sensors 21, no. 14 (2021): 4724. http://dx.doi.org/10.3390/s21144724.

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This paper deals with an inverse scattering problem under a linearized scattering model for a multi-static/multi-frequency configuration. The focus is on the determination of a sampling strategy that allows the reduction of the number of measurement points and frequencies and at the same time keeping the same achievable performance in the reconstructions as for full data acquisition. For the sake of simplicity, a 2D scalar geometry is addressed, and the scattered far-field data are collected. The relevant scattering operator exhibits a singular value spectrum that abruptly decays (i.e., a step

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Liu, Chun, Junjun Yin, Jian Yang, and Wei Gao. "Classification of Multi-Frequency Polarimetric SAR Images Based on Multi-Linear Subspace Learning of Tensor Objects." Remote Sensing 7, no. 7 (2015): 9253–68. http://dx.doi.org/10.3390/rs70709253.

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One key problem for the classification of multi-frequency polarimetric SAR images is to extract target features simultaneously in the aspects of frequency, polarization and spatial texture. This paper proposes a new classification method for multi-frequency polarimetric SAR data based on tensor representation and multi-linear subspace learning (MLS). Firstly, each cell of the SAR images is represented by a third-order tensor in the frequency, polarization and spatial domains, with each order of tensor corresponding to one domain. Then, two main MLS methods, i.e., multi-linear principal compone

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Denoyelle, Dirk. "Up Close: The Interuniversity Microelectronics Center (IMEC), Leuven, Belgium." MRS Bulletin 14, no. 6 (1989): 35–38. http://dx.doi.org/10.1557/s0883769400062692.

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The Interuniversity Microelectronics Center, Leuven, Belgium (IMEC) is one of the world's largest independent research centers for microelectronics. It was established in 1984 by the Flemish government as a part of a comprehensive program to promote high technology in Flanders, Belgium. Benefiting from existing experience available mainly at the University of Leuven, IMEC moved into its present facilities in 1986 (Figure 1).The Center covers a wide range of research topics in the microelectronics domain—VLSI systems design methodologies, advanced semiconductor processing, materials, packaging,

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MAO, WENTAO, JIUCHENG XU, SHENGJIE ZHAO, and MEI TIAN. "RESEARCH OF MULTI-TASK LEARNING BASED ON EXTREME LEARNING MACHINE." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, supp02 (2013): 75–85. http://dx.doi.org/10.1142/s0218488513400175.

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Recently, extreme learning machines (ELMs) have been a promising tool in solving a wide range of regression and classification applications. However, when modeling multiple related tasks in which only limited training data per task are available and the dimension is low, ELMs are generally hard to get impressive performance due to little help from the informative domain knowledge across tasks. To solve this problem, this paper extends ELM to the scenario of multi-task learning (MTL). First, based on the assumption that model parameters of related tasks are close to each other, a new regulariza

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Zheng, Zumei, Shasha Zhou, Jun Chen, Naoto Mitsume, and Shunhua Chen. "A Multi-Resolution MPS/FEM Coupling Method for Three-Dimensional Fluid–Structure Interaction Analysis." Journal of Marine Science and Engineering 11, no. 8 (2023): 1483. http://dx.doi.org/10.3390/jmse11081483.

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This work aims to propose an efficient MPS/FEM coupling method for the simulation of fluid–structure interaction (FSI), where the MPS and FEM are respectively employed to account for fluid flows and structural deformation. The main idea of our method is to develop a multi-scale multi-resolution MPS method for efficient fluid simulations in the context of MPS/FEM coupling. In the developed multi-scale MPS method, the fluid domain is discretized into particles of different resolutions before calculation, where particles close to the interest domain will be discretized into high resolution, while

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Peng, Rongrong, Xingzhong Zhang, and Peiming Shi. "Multi-Representation Domain Adaptation Network with Duplex Adversarial Learning for Hot-Rolling Mill Fault Diagnosis." Entropy 25, no. 1 (2022): 83. http://dx.doi.org/10.3390/e25010083.

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The multi-process manufacturing of steel rolling products requires the cooperation of complicated and variable rolling conditions. Such conditions pose challenges to the fault diagnosis of the key equipment of the rolling mill. The development of transfer learning has alleviated the problem of fault diagnosis under variable working conditions to a certain extent. However, existing diagnosis methods based on transfer learning only consider the distribution alignment from a single representation, which may only transfer part of the state knowledge and generate fuzzy decision boundaries. Therefor

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Schuwerack, Clemens, Lukas Quirin, Gunnar Lelle-Neumann, and Ferdinand Maiwald. "Enhancing the accuracy of the Leica Nova TS60 total station: A multi-purpose camera-based optical measurement system." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W7-2024 (December 13, 2024): 153–60. https://doi.org/10.5194/isprs-archives-xlviii-2-w7-2024-153-2024.

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Abstract. The increasing demand for accurate 3D coordinate measures in industry, medicine and environmental sciences often comes with multiple constraints regarding the object distance, required accuracy and object signalization. While many systems are specialized in one domain, there are only few systems that operate in close-range applications with extremely high accuracy and are also capable of monitoring deformations at a distance of a few hundred meters. Therefore, a measurement system based on the astro-geodetic observation system QDaedalus is introduced using two combined image-assisted

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Dubenion-Smith, Shannon A. "Verbal Complex Phenomena in West Central German: Empirical Domain and Multi-Causal Account." Journal of Germanic Linguistics 22, no. 2 (2010): 99–191. http://dx.doi.org/10.1017/s1470542709990249.

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This paper is a synchronic investigation of verbal complex phenomena in the West Central German dialects. The types of verbal complexes attested in 187 recordings of West Central German from the Zwirner Corpus are first classified and analyzed. AGoldVarbanalysis reveals that in subordinate clause two-verb complexes, the factor groups syntagm and verbal prefix type have statistically significant effects on word order, while in main clause two-verb complexes the factor groups syntagm, verbal prefix type, and a grammatical correlate to focus have statistically significant effects. Taking as a poi

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Kartal, Bilal, Pablo Hernandez-Leal, and Matthew E. Taylor. "Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 15, no. 1 (2019): 38–44. http://dx.doi.org/10.1609/aiide.v15i1.5222.

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Deep reinforcement learning has achieved great successes in recent years, but there are still open challenges, such as convergence to locally optimal policies and sample inefficiency. In this paper, we contribute a novel self-supervised auxiliary task, i.e., Terminal Prediction (TP), estimating temporal closeness to terminal states for episodic tasks. The intuition is to help representation learning by letting the agent predict how close it is to a terminal state, while learning its control policy. Although TP could be integrated with multiple algorithms, this paper focuses on Asynchronous Adv

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Gu, Quanquan, Zhenhui Li, and Jiawei Han. "Learning a Kernel for Multi-Task Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (2011): 368–73. http://dx.doi.org/10.1609/aaai.v25i1.7914.

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Multi-task learning has received increasing attention in the past decade. Many supervised multi-task learning methods have been proposed, while unsupervised multi-task learning is still a rarely studied problem. In this paper, we propose to learn a kernel for multi-task clustering. Our goal is to learn a Reproducing Kernel Hilbert Space, in which the geometric structure of the data in each task is preserved, while the data distributions of any two tasks are as close as possible. This is formulated as a unified kernel learning framework, under which we study two types of kernel learning: nonpar

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Zhao, Wendian, Yu Wang, Liang Liang, Daowei Liu, and Xinyang Ji. "An approach to generate damage strategies for inter-domain routing systems based on multi-objective optimization." Mathematical Biosciences and Engineering 20, no. 6 (2023): 11176–95. http://dx.doi.org/10.3934/mbe.2023495.

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<abstract><p>Inter-domain routing systems are important complex networks on the Internet. It has been paralyzed several times in recent years. The researchers pay close attention to the damage strategy of inter-domain routing systems and think it is related to the attacker's behavior. The key to the damage strategy is knowing how to select the optimal attack node group. In the process of selecting nodes, the existing research seldom considers the attack cost, and there are some problems, such as an unreasonable definition of attack cost and an unclear optimization effect. To solve

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Wang, Jing Hui, and Shu Gang Tang. "Quadratic Independent Component Analysis Based on Sparse Component." Applied Mechanics and Materials 442 (October 2013): 562–67. http://dx.doi.org/10.4028/www.scientific.net/amm.442.562.

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In this paper, a novel signal blind separation using adaptive multi-resolution independent component analysis based on sparse component is presented. This method separates mixed signal based on quadratic function and sparse representation. The quadratic function can be interpreted as the time-frequency function or time-scale function, or other. The sparse expression is the original signal through the dictionary to get their coefficients. Most of the coefficients is very small, close to zero, can greatly save separate computing time. At the same time this method can filter out the noise. The ar

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Dawadi, Babu R., Danda B. Rawat, Shashidhar R. Joshi, and Pietro Manzoni. "Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment." Electronics 9, no. 9 (2020): 1454. http://dx.doi.org/10.3390/electronics9091454.

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The logical separation of the data plane and the control plane of the network device conceptually defined by software-defined networking (SDN) creates many opportunities to create smart networking with better efficiency for network management and operation. SDN implementation over telecommunications (Telcos) and Internet service provider (ISP) networks is a challenging issue due to the lack of a high maturity level of SDN-based standards and several other critical factors that are considered during the real-time migration of existing legacy IPv4 networks. Different migration approaches have be

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Chen, Nai-Ching, Chiung-Chih Chang, Ker-Neng Lin, et al. "Patterns of executive dysfunction in amnestic mild cognitive impairment." International Psychogeriatrics 25, no. 7 (2013): 1181–89. http://dx.doi.org/10.1017/s1041610213000392.

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ABSTRACTBackground: Executive dysfunction is not uncommon in patients with amnestic mild cognitive impairment (aMCI). This study aimed to investigate the applicability of executive function tests (EFTs) in aMCI as an aid in establishing the diagnosis of multi-domain MCI.Methods: One hundred and twenty (120) aMCI patients, 126 Alzheimer's disease (AD) patients, and 100 normal controls were enrolled. The EFTs evaluated included the trail making test, digit backward span, Stroop color–word test, and design fluency and category fluency tests.Results: Of the aMCI participants, 66% exhibited impairm

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Petrov, George M., and Jack Davis. "Parallelization of an Implicit Algorithm for Multi-Dimensional Particle-in-Cell Simulations." Communications in Computational Physics 16, no. 3 (2014): 599–611. http://dx.doi.org/10.4208/cicp.070813.280214a.

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AbstractThe implicit 2D3V particle-in-cell (PIC) code developed to study the interaction of ultrashort pulse lasers with matter [G. M. Petrov and J. Davis, Computer Phys. Comm. 179, 868 (2008); Phys. Plasmas 18, 073102 (2011)] has been parallelized using MPI (Message Passing Interface). The parallelization strategy is optimized for a small number of computer cores, up to about 64. Details on the algorithm implementation are given with emphasis on code optimization by overlapping computations with communications. Performance evaluation for 1D domain decomposition has been made on a small Linux

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Erban, Radek. "From molecular dynamics to Brownian dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470, no. 2167 (2014): 20140036. http://dx.doi.org/10.1098/rspa.2014.0036.

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Three coarse-grained molecular dynamics (MD) models are investigated with the aim of developing and analysing multi-scale methods which use MD simulations in parts of the computational domain and (less detailed) Brownian dynamics (BD) simulations in the remainder of the domain. The first MD model is formulated in one spatial dimension. It is based on elastic collisions of heavy molecules (e.g. proteins) with light point particles (e.g. water molecules). Two three-dimensional MD models are then investigated. The obtained results are applied to a simplified model of protein binding to receptors

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Keeney, Lynette, Louise Colfer, Debismita Dutta, Michael Schmidt, and Guannan Wei. "What lies beneath? Investigations of atomic force microscopy-based nano-machining to reveal sub-surface ferroelectric domain configurations in ultrathin films." Microstructures 3, no. 4 (2023): 2023041. http://dx.doi.org/10.20517/microstructures.2023.41.

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Multiferroic materials, encompassing simultaneous ferroelectric and ferromagnetic polarization states, are enticing multi-state materials for memory scaling beyond existing technologies. Aurivillius phase B6TFMO (Bi6TixFeyMnzO18) is a unique room temperature multiferroic material that could ideally be suited to future production of revolutionary memory devices. As miniaturization of electronic devices continues, it is crucial to characterize ferroelectric domain configurations at very small (sub-10 nm) thickness. Direct liquid injection chemical vapor deposition allows for frontier development

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Khanykov, Igor, Vadim Nenashev, and Mikhail Kharinov. "Algebraic Multi-Layer Network: Key Concepts." Journal of Imaging 9, no. 7 (2023): 146. http://dx.doi.org/10.3390/jimaging9070146.

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The paper refers to interdisciplinary research in the areas of hierarchical cluster analysis of big data and ordering of primary data to detect objects in a color or in a grayscale image. To perform this on a limited domain of multidimensional data, an NP-hard problem of calculation of close to optimal piecewise constant data approximations with the smallest possible standard deviations or total squared errors (approximation errors) is solved. The solution is achieved by revisiting, modernizing, and combining classical Ward’s clustering, split/merge, and K-means methods. The concepts of object

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Ahlawat, Ritu. "Use of GIS in optimal spatial network of hydrological data in Betwa river catchment." International Journal of Geomatics and Geosciences 4, no. 4 (2014): 646–60. https://doi.org/10.5281/zenodo.5511732.

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The ultimate design for any kind of hydrological data network must evaluate all possible alternatives before rationalising the task of data collection at an optimal level. Wherever different kinds of data collection centres duplicate the measurement of same parameters in close proximity, efforts should be to integrate the entire process of data processing at one place. The extent to which the spatial aspect of data needs to be compromised is examined in this paper at sub-catchment/watershed level of Betwa river, one of the important southern tributaries of River Yamuna after Chambal. An integr

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Rijal, Sadikshya, Ashmita Mainali, Sandesh Acharya, and Hitesh Kumar Bhattarai. "Evolutionary history of the DNA repair protein, Ku, in eukaryotes and prokaryotes." PLOS ONE 20, no. 3 (2025): e0308593. https://doi.org/10.1371/journal.pone.0308593.

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Ku is essential in non-homologous end-joining (NHEJ) across prokaryotes and eukaryotes, primarily in double-stranded breaks (DSBs) repair. It often presents as a multi-domain protein in eukaryotes, unlike their prokaryotic single-domain homologs. We systematically searched for Ku proteins across different domains of life. To elucidate the evolutionary history of the Ku protein, we constructed a maximum likelihood phylogenetic tree using Ku protein sequences from 100 representative eukaryotic, prokaryotic, and viral species. The resulting tree revealed a common node for eukaryotic Ku proteins,

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Ilić, Nemanja, and Marija Punt. "Distributed Ensemble Clustering in Networked Multi-Agent Systems." Electronics 12, no. 22 (2023): 4558. http://dx.doi.org/10.3390/electronics12224558.

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Ensemble clustering, a paradigm that deals with combining the results of multiple clusterings into a single solution, has been widely studied in recent years. The goal of this study is to propose a novel distributed ensemble clustering method that is applicable for use in networked multi-agent systems. The adopted setting supports both object-distributed and feature-distributed clusterings. It is not limited to specific types of algorithms used for obtaining local data labels. The method assumes local processing of local data by the individual agents and neighbor-wise communication of the proc

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Kovačević, Andjelka B., Yu-Yang Songsheng, Jian-Min Wang, and Luka Č. Popović. "Bayesian Synthesis of Astrometric Wobble and Total Light Curves in Close Binary Supermassive Black Holes." Astrophysical Journal 967, no. 1 (2024): 30. http://dx.doi.org/10.3847/1538-4357/ad3729.

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Abstract We test the potential of Bayesian synthesis of upcoming multi-instrument data to extract orbital parameters and individual light curves of close binary supermassive black holes (CB-SMBH) with subparsec separations. Next-generation interferometers, will make possible the observation of astrometric wobbles in CB-SMBH. Combining them with periodic variable time-domain data from surveys like the Vera C. Rubin Legacy Survey of Space and Time, allows for more information on CB-SMBH candidates compared to standalone observational methods. Our method reliably determines binary parameters and

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Avanthey, Loïca, and Laurent Beaudoin. "How to Boost Close-Range Remote Sensing Courses Using a Serious Game: Uncover in a Fun Way the Complexity and Transversality of Multi-Domain Field Acquisitions." Remote Sensing 14, no. 4 (2022): 817. http://dx.doi.org/10.3390/rs14040817.

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Close-range remote sensing, and more particularly, its acquisition part that is linked to field robotics, is at the crossroads of many scientific and engineering fields. Thus, it takes time for students to acquire the solid foundations needed before practicing on real systems. Therefore, we are interested in a means that allow students without prerequisites to quickly appropriate the fundamentals of this interdisciplinary field. For this, we adapted a haggle game to the close-range remote sensing theme. In this article, we explain the mechanics that serve our educational purposes. We have used

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Liu, Zitian, Zhao Chen, Xiaoli Zhang, and Shihan Cheng. "CDP-MVS: Forest Multi-View Reconstruction with Enhanced Confidence-Guided Dynamic Domain Propagation." Remote Sensing 16, no. 20 (2024): 3845. http://dx.doi.org/10.3390/rs16203845.

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Using multi-view images of forest plots to reconstruct dense point clouds and extract individual tree parameters enables rapid, high-precision, and cost-effective forest plot surveys. However, images captured at close range face challenges in forest reconstruction, such as unclear canopy reconstruction, prolonged reconstruction times, insufficient accuracy, and issues with tree duplication. To address these challenges, this paper introduces a new image dataset creation process that enhances both the efficiency and quality of image acquisition. Additionally, a block-matching-based multi-view re

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Scheuvens, Lucas, Tom Hößler, Philipp Schulz, Norman Franchi, André Barreto, and Gerhard Fettweis. "State-Aware Resource Allocation for Wireless Closed-Loop Control Systems." IEEE Transactions on Communications 69, no. 10 (2021): 6604–19. https://doi.org/10.1109/TCOMM.2021.3095953.

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Wireless closed-loop control is of major significance for future industrial manufacturing. However, control applications pose stringent quality of service requirements for reliable operation. Contrary to traditional ultra-reliable low-latency communications design goals such as low packet loss rates and low latency, research results in the domain of networked control systems (NCS) state that depending on the sampling period, control applications inherently tolerate a few consecutive packet losses. This translates into a better-suited metric to capture control application requirements and there

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Mustafa, Hafiz Muhammad Tahir, Jung-In Baik, Young-Hwan You, Hyoung-Kyu Song, and Zunira Abbasi. "Hybrid Beamforming and Relay Selection for End-to-End SNR Maximization in Single-User Multi-Relay MIMO Systems." Sensors 23, no. 4 (2023): 2079. http://dx.doi.org/10.3390/s23042079.

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This paper proposes a novel hybrid beamforming and relay selection scheme for spectral efficiency maximization in a non-regenerative multi-relay multi-input multi-output (MIMO) system. The analog beamforming component in the radio-frequency (RF) domain must follow an element-wise constant modulus constraint, which makes the underlying design problem mathematically intractable and therefore, it is quite challenging to obtain the global optimal solution. To address this problem, phase-only precoding/combining matrices are derived by maximizing the end-to-end received signal-to-noise ratio (SNR)

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Wang, Dong, Houquan Chen, Yunhui Huang, Xiangtian Deng, and Guorong Zhu. "Modeling and Stability Analysis of Weak-Grid Tied Multi-DFIGs in DC-Link Voltage Control Timescale." Energies 13, no. 14 (2020): 3689. http://dx.doi.org/10.3390/en13143689.

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The DC-link voltage control (DVC) timescale (i.e., the frequency dynamics covering converter outer controls) instabilities in wind generation have gained increased attention recently. This paper presents DVC timescale modeling and stability analysis for multi doubly-fed induction generators (DFIGs) connected to weak AC grids. A reduced-order, small-signal model of a grid-tied multi-DFIG system, designed for DVC dynamics analysis, is firstly proposed. The model allows for the dynamic interactions among the DC-link voltage control, active power control (APC), terminal voltage control (TVC) and p

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Wu, Yang, Junli Zhang, Shuang Ding, and Yan-Cheng Liu. "Localized Boundary Knot Method for Solving Two-Dimensional Inverse Cauchy Problems." Mathematics 10, no. 8 (2022): 1324. http://dx.doi.org/10.3390/math10081324.

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In this paper, a localized boundary knot method is adopted to solve two-dimensional inverse Cauchy problems, which are controlled by a second-order linear differential equation. The localized boundary knot method is a numerical method based on the local concept of the localization method of the fundamental solution. The approach is formed by combining the classical boundary knot method with the localization method. It has the potential to solve many complex engineering problems. Generally, in an inverse Cauchy problem, there are no boundary conditions in specific boundaries. Additionally, in o

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Price, Brian R. "Colonel John Boyd’s Thoughts on Disruption: A Useful Effects Spiral from Uncertainty to Chaos." Journal of Advanced Military Studies 14, no. 1 (2023): 98–117. http://dx.doi.org/10.21140/mcuj.20231401004.

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A close examination of John R. Boyd’s concept of disruption as recorded in his 1987 presentation, “An Organic Design for Command and Control.” This article draws attention to a series of disruptive actions Boyd lists, including uncertainty, doubt, mistrust, confusion, disorder, fear, panic, and chaos, noting that the list begins with the mildest effect but that it progresses regularly toward collapse and chaos. The author argues that Boyd was specific in listing these effects in order and notes that this cycle could be developed into a useful effects spiral, which, once understood, can be cata

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Higashi, Takaaki, Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, and Miki Haseyama. "Estimation of Degradation Degree in Road Infrastructure Based on Multi-Modal ABN Using Contrastive Learning." Sensors 23, no. 3 (2023): 1657. http://dx.doi.org/10.3390/s23031657.

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This study presents a method for distress image classification in road infrastructures introducing self-supervised learning. Self-supervised learning is an unsupervised learning method that does not require class labels. This learning method can reduce annotation efforts and allow the application of machine learning to a large number of unlabeled images. We propose a novel distress image classification method using contrastive learning, which is a type of self-supervised learning. Contrastive learning provides image domain-specific representation, constraining such that similar images are embe

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Patil, Hemangi, Kyoung-in Cho, James Lee, Yi Yang, Andrew Orry, and Paulo A. Ferreira. "Kinesin-1 and mitochondrial motility control by discrimination of structurally equivalent but distinct subdomains in Ran-GTP-binding domains of Ran-binding protein 2." Open Biology 3, no. 3 (2013): 120183. http://dx.doi.org/10.1098/rsob.120183.

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The pleckstrin homology (PH) domain is a versatile fold that mediates a variety of protein–protein and protein–phosphatidylinositol lipid interactions. The Ran-binding protein 2 (RanBP2) contains four interspersed Ran GTPase-binding domains (RBD n = 1–4 ) with close structural homology to the PH domain of Bruton's tyrosine kinase. The RBD 2 , kinesin-binding domain (KBD) and RBD 3 comprise a tripartite domain (R 2 KR 3 ) of RanBP2 that causes the unfolding, microtubule binding and biphasic activation of kinesin-1, a crucial anterograde motor of mitochondrial motility. However, the interplay be

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Al-Shaqsi, Sultan, and Christopher R. Forrest. "Multi-suture craniosynostosis in Sotos Syndrome: A case Report." Craniomaxillofacial Research & Innovation 8 (January 2023): 275284642311668. http://dx.doi.org/10.1177/27528464231166828.

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Study Design Case report. Objective Sotos syndrome is a rare genetic disorder which is characterized by excessive physical growth during the first few years of life. The principal features of this condition include macrocephaly, learning disability and physical overgrowth. The current diagnosis of Sotos Syndrome is based on identification of genetic mutations and deletions in the NSD family (the Nuclear-receptor-binding SET-Domain containing protein). Single suture craniosynostosis has been reported in a few cases of Sotos syndrome. We report an atypical presentation of multi-suture craniosyno

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Li, Chao Feng, Qin Liang Li, Jie Liu, and Bang Chun Wen. "Research on Periodic Motion Stability of Multi-DOF Rotor-Bearing System with Crack Fault." Applied Mechanics and Materials 148-149 (December 2011): 3–6. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.3.

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Multi-DOF model of double-disc rotor-bearing system taking crack and oil film support into account is established, and the continuation shooting method combined with Newmark is also applied to stability analysis of continuous system. This paper mainly studied the variation law of five parameters domain in crack depth and location, then a number of conclusions are found: first, it’s feasible to study the stability of nonlinear rotor-bearing system with crack faults using FEM; secondly, the crack depth and location has a certain impact on instability speed, but the impact is not great and owns i

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Ieracitano, Cosimo, Francesco Carlo Morabito, Amir Hussain, and Nadia Mammone. "A Hybrid-Domain Deep Learning-Based BCI For Discriminating Hand Motion Planning From EEG Sources." International Journal of Neural Systems 31, no. 09 (2021): 2150038. http://dx.doi.org/10.1142/s0129065721500386.

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In this paper, a hybrid-domain deep learning (DL)-based neural system is proposed to decode hand movement preparation phases from electroencephalographic (EEG) recordings. The system exploits information extracted from the temporal-domain and time-frequency-domain, as part of a hybrid strategy, to discriminate the temporal windows (i.e. EEG epochs) preceding hand sub-movements (open/close) and the resting state. To this end, for each EEG epoch, the associated cortical source signals in the motor cortex and the corresponding time-frequency (TF) maps are estimated via beamforming and Continuous

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Varelas, Xaralabos, Christopher Ptak, and Michael J. Ellison. "Cdc34 Self-Association Is Facilitated by Ubiquitin Thiolester Formation and Is Required for Its Catalytic Activity." Molecular and Cellular Biology 23, no. 15 (2003): 5388–400. http://dx.doi.org/10.1128/mcb.23.15.5388-5400.2003.

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ABSTRACT Using a coimmunoprecipitation strategy, we showed that the Cdc34 ubiquitin (Ub)-conjugating enzyme from Saccharomyces cerevisiae self-associates in cell lysates, thereby indicating an in vivo interaction. The ability of Cdc34 to interact with itself is not dependent on its association with the ubiquitin ligase Skp1-Cdc53/Cul1-Hrt1-F-box complex. Rather, this interaction depends upon the integrity of the Cdc34∼Ub thiolester. Furthermore, several principal determinants within the Cdc34 catalytic domain, including the active-site cysteine, amino acid residues S73 and S97, and its catalyt

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