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Journal articles on the topic 'Realistic Accuracy Model (RAM)'

Author: Grafiati

Published: 19 February 2023

Last updated: 31 July 2025

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1

Kalsum, Tehmina, and Zahid Mehmood. "A Novel Lightweight Deep Convolutional Neural Network Model for Human Emotions Recognition in Diverse Environments." Journal of Sensors 2023 (August 5, 2023): 1–20. http://dx.doi.org/10.1155/2023/6987708.

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A picture is worth a thousand words to convey information during daily life communication. Recognizing a person’s emotions from facial expressions (FEs) has become a prevalent research field in the past few decades. Deep learning (DL) models, mainly deep convolutional neural networks (DCNNs), are trending in the last few years to perform recognition/classification tasks. Several prior DCNNs have resulted in good recognition accuracy for facial emotion recognition (FER) systems. Still, there is a need for an effective as well as efficient FER system that can recognize the FEs irrespective of th

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Kalsum, Tehmina, Zahid Mehmood, Farzana Kulsoom, et al. "Localization and classification of human facial emotions using local intensity order pattern and shape-based texture features." Journal of Intelligent & Fuzzy Systems 40, no. 5 (2021): 9311–31. http://dx.doi.org/10.3233/jifs-201799.

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Facial emotion recognition system (FERS) recognize the person’s emotions based on various image processing stages including feature extraction as one of the major processing steps. In this study, we presented a hybrid approach for recognizing facial expressions by performing the feature level fusion of a local and a global feature descriptor that is classified by a support vector machine (SVM) classifier. Histogram of oriented gradients (HoG) is selected for the extraction of global facial features and local intensity order pattern (LIOP) to extract the local features. As HoG is a shape-based

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Delfaure, Colin, Jean-Paul Mazellier, Nicolas Tranchant, Philippe Bergonzo, Pascal Ponard, and Samuel Saada. "Nanofocus diamond X-ray windows: Thermal modeling of nano-sized heat source systems." Diamond And Related Materials 59 (September 28, 2015): 104–15. https://doi.org/10.5281/zenodo.49966.

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An analytical thermal model is proposed to study heat transfers occurring at high power density in X-ray tubes with micron to submicron sized source. The use of a simple analytical approach instead of a complex numerical simulation allows readily modeling of more andmore challenging systems such as multi-source X-ray tubes. By significantly reducing the computing time, it enables a wider parameter range evaluation for engineering phase.We focused our work on tubes integrating a transmission window that is mainly edge-cooled. Our approach can be generally used in cylindrical lateral heat spread

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Middelburg, Cornelis. "Program Algebra for Random Access Machine Programs." Scientific Annals of Computer Science XXXII, no. 2 (2022): 285–319. http://dx.doi.org/10.7561/sacs.2022.2.285.

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This paper presents an algebraic theory of instruction sequences with instructions for a random access machine (RAM) as basic instructions, the behaviours produced by the instruction sequences concerned under execution, and the interaction between such behaviours and RAM memories. This theory provides a setting for the development of theory in areas such as computational complexity and analysis of algorithms that distinguishes itself by offering the possibility of equational reasoning to establish whether an instruction sequence computes a given function and being more general than the setting

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Middelburg, Cornelis. "Program Algebra for Random Access Machine Programs." Scientific Annals of Computer Science XXXII, no. 2 (2022): 285–319. https://doi.org/10.7561/SACS.2022.2.285.

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This paper presents an algebraic theory of instruction sequences with instructions for a random access machine (RAM) as basic instructions, the behaviours produced by the instruction sequences concerned under execution, and the interaction between such behaviours and RAM memories. This theory provides a setting for the development of theory in areas such as computational complexity and analysis of algorithms that distinguishes itself by offering the possibility of equational reasoning to establish whether an instruction sequence computes a given function and being more general than the setting

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HASAN, NADEEM, and SANJEEV SANGHI. "Proper orthogonal decomposition and low-dimensional modelling of thermally driven two-dimensional flow in a horizontal rotating cylinder." Journal of Fluid Mechanics 573 (February 2007): 265–95. http://dx.doi.org/10.1017/s0022112006003806.

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A proper orthogonal decomposition (POD) analysis and low-dimensional modelling of thermally driven two-dimensional flow of air in a horizontal rotating cylinder, subject to the Boussinesq approximation, is considered. The problem is unsteady due to the harmonic nature of the gravitational buoyancy force with respect to the rotating observer and is characterized by four dimensionless numbers: gravitational Rayleigh number (Rag), the rotational Rayleigh number (RaΩ), the Taylor number (Ta) and Prandtl number (Pr). The data for the POD analysis are obtained by numerical integration of the governi

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Bshouty, Nader H. "Lower Bounds for the Complexity of Functions in a Realistic RAM Model." Journal of Algorithms 32, no. 1 (1999): 1–20. http://dx.doi.org/10.1006/jagm.1998.0994.

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Börjesson Axén, Jenny, Henrik Ekström, Erika Widenkvist Zetterström, and Göran Lindbergh. "Building a P2D Model for the NiMH Battery." ECS Meeting Abstracts MA2023-02, no. 1 (2023): 52. http://dx.doi.org/10.1149/ma2023-02152mtgabs.

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For understanding a battery when working under realistic conditions, a dynamic battery model is a useful tool. One of the most known electrochemical model types for batteries is the Newman P2D model.[1] This model has a good balance between complexity and computational efficiency. Due to the level of complexity, using a P2D model allows us to make simulations to optimize battery design by adjusting parameters such as electrode porosity and tortuosity, electrode thickness, and overall cell thickness. But it can also be used to optimize battery management system (BMS) functionality. There are ma

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Cronin, MaryAnne, Nancy Dengler, Eugene S. Krauss, et al. "Completion of the Updated Caprini Risk Assessment Model (2013 Version)." Clinical and Applied Thrombosis/Hemostasis 25 (January 1, 2019): 107602961983805. http://dx.doi.org/10.1177/1076029619838052.

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The Caprini risk assessment model (RAM) has been validated in over 250 000 patients in more than 100 clinical trials worldwide. Ultimately, appropriate treatment options are dependent on precise completion of the Caprini RAM. As the numerical score increases, the clinical venous thromboembolism rate rises exponentially in every patient group where it has been properly tested. The 2013 Caprini RAM was completed by specially trained medical students via review of the presurgical assessment history, medical clearances, and medical consults. The Caprini RAM was completed for every participant both

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Zhang, Hengjian. "Sound-based animal recognition model." Applied and Computational Engineering 4, no. 1 (2023): 760–67. http://dx.doi.org/10.54254/2755-2721/4/2023420.

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Conservation of biological and biological diversity is the goal of joint efforts worldwide, and protecting wild creatures requires various monitoring equipment with identification capabilities. In this case, this article will introduce a model with animal call recognition ability designed using edge impulse. A two-layers convolutional neural network (CNN) is selected and trained with the input features generated by Mel Frequency Cepstral Coefficient, Spectrogram and Mel-Spectrogram. The model hoped not only to focus on the recognition accuracy rate of the model but also on the inferencing time

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REDDY, BOMMU SATISH, Dr VEERAVALLI SITARAM Prasad, VENGALA UPENDER, and M. SATISH. "EXPLORING VIBRATIONAL PROPERTIES OF THE COKE PUSHING RAM DURING THE COKE PUSHING PROCESS." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 11, no. 3 (2020): 2987–98. http://dx.doi.org/10.61841/turcomat.v11i3.14681.

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Throughout the process, there could be severe vibrations in the coke pushing ram, which could have an instant impact on the regular production of the coke oven. To find out more about the coke pushing ram's vibration characteristics and take precautions against vibrations, an analysis of those features is required. A mathematical model of a coke pushing ram in use during the coke pushing process is constructed in order to investigate the vibration mechanism of a coke pushing ram. In this section, the coke pushing current is used to estimate the coke pushing resistance. The results demonstrate

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Inatsu, Masaru, Tsubasa Nakayama, Yoshie Maeda, and Hirotaka Matsuda. "Dynamical Downscaling for Assessment of the Climate in Ghana." Journal of Disaster Research 9, no. 4 (2014): 412–21. http://dx.doi.org/10.20965/jdr.2014.p0412.

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Dynamical downscaling (DDS), in which a regional atmospheric model (RAM) experiment nested into coarser-resolution data provides a spatio-temporal fine dataset for a particular region, was performed to assess the present climate in Ghana. The DDS successfully evaluated realistic seasonal march and inter-annual variability in rainfall, in comparison with gauge and satellite observation. The DDS also indicated that land-lake and land-sea circulation interacted with the West African monsoon likely characterized the local climate in Ghana.

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Korchak, O. "Investigation of oscillatory displacement of the hydraulic presses moving parts during their braking in the upper initial position." Scientific journal of the Ternopil national technical university 99, no. 3 (2020): 66–74. http://dx.doi.org/10.33108/visnyk_tntu2020.03.066.

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The investigations revealed that, despite the usage of individual servo drive of the inlet valve of return cylinders, ram overrun upwards after its being shut down which is accompanied by intensive oscillatory phenomena is inevitable. By analyzing the experimental diagrams it is stated that the existing mechanism of ram braking in upper starting position is unacceptable from the point of view of fast and non-impact process realization, as well as the accuracy of stoppage. The mathematical model of ram damped oscillations in the upper position after the inlet valve of return cylinders shut down

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Singh, Ankit, Shreya Davessar, Mamta Gulati, Jasjeet Singh Bagla, and Meenu Prajapati. "Study of dependence of ram pressure stripping on the orbital parameters of the galaxies." Monthly Notices of the Royal Astronomical Society 530, no. 1 (2024): 699–709. http://dx.doi.org/10.1093/mnras/stae730.

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ABSTRACT Comprehensive observations of galaxy clusters suggest that gas deficiency in the galaxies could be due to ram pressure stripping due to the high-pressure intra-cluster medium acting on the galactic discs. The presence of gas in galaxies is essential for star formation. The net force due to ram pressure is dependent on the ambient medium and the orbit followed by the galaxy as it moves past the cluster medium. This work deals with the effect of non-radial orbits of galaxies and the inclination of the disc plane of galaxies with the orbital plane on the mass of gas removed due to ram pr

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Kane, Emily A., and Timothy E. Higham. "Modelled three-dimensional suction accuracy predicts prey capture success in three species of centrarchid fishes." Journal of The Royal Society Interface 11, no. 95 (2014): 20140223. http://dx.doi.org/10.1098/rsif.2014.0223.

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Prey capture is critical for survival, and differences in correctly positioning and timing a strike (accuracy) are likely related to variation in capture success. However, an ability to quantify accuracy under natural conditions, particularly for fishes, is lacking. We developed a predictive model of suction hydrodynamics and applied it to natural behaviours using three-dimensional kinematics of three centrarchid fishes capturing evasive and non-evasive prey. A spheroid ingested volume of water (IVW) with dimensions predicted by peak gape and ram speed was verified with known hydrodynamics for

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Wang, Yumo, Zhifeng Liu, Qiang Cheng, Yongsheng Zhao, Yida Wang, and Ligang Cai. "Analysis and optimization of nonlinear carrying performance of hydrostatic ram based on finite difference method and Runge–Kutta method." Advances in Mechanical Engineering 11, no. 6 (2019): 168781401985612. http://dx.doi.org/10.1177/1687814019856128.

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Analyzing of nonlinear carrying performance of hydrostatic ram is among key research questions to improve heavy machine tools because the machining precision will be directly influenced by it. A dynamic model of nonlinear supporting characters for hydrostatic ram is developed in this work. Modified Reynolds equation is resolved by finite difference method numerically to determine the carrying capability. Dynamic equilibrium equation of hydrostatic ram under cutting force impact is solved by Runge–Kutta method to obtain the variation of tool tip position and evaluate the machining accuracy. An

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Hu, Bo. "An assessment of current maximum impact force models for anti-ram bollard systems subjected to truck impact." International Journal of Protective Structures 8, no. 3 (2017): 368–83. http://dx.doi.org/10.1177/2041419617721551.

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Anti-ram bollard systems, which maintain a sufficient standoff in front of a protected area, can prevent vehicle bombs from approaching the area and thus reduce the damage from blast and debris. This article collects the current maximum impact force models for the collision between a vehicle and a barrier and presents an assessment of the applicability of these models for a truck crashing into an anti-ram bollard system. A database, which contains four available crash test results and 63 numerical simulation results, has been established for the evaluation. The assessment results show most of

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Potvin, J. "Testing a new model of ram-air parachute inflation." Aeronautical Journal 101, no. 1007 (1997): 299–314. http://dx.doi.org/10.1017/s0001924000066161.

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AbstractThis paper reports on the experimental validation of a new model of slider-reefed ram-air parachute opening, using jump data collected by this investigator and others. The model is based on the parachute load equation of motion coupled with a new differential equation which describes the rate of change of the parachute's drag area. The model clearly identifies the important factors which determine the inflation peak load and opening time. It also features many scaling relationships useful for design work. Several predictions are shown to be design-independent. The experimental data use

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Speetjens, MFM, R. Lensvelt, and H. Nijmeijer. "Estimating temperature fields in flows from sensors." Journal of Physics: Conference Series 2766, no. 1 (2024): 012076. http://dx.doi.org/10.1088/1742-6596/2766/1/012076.

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Abstract Active control of scalar transport (e.g. temperature or chemical species) in engineering flows by feedback of intermediate scalar fields to the controller to determine the control action can substantially improve the performance of such processes. Key for practical application of such state-feedback control is the fast and accurate estimation of scalar fields from discrete sensor data (e.g. thermocouples in case of heat transfer), since the full field can usually not be measured. This study develops a state observer that enables such sensor-based state estimation for a representative

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Tosun, Abdurrahman, Gurcan Konak, Tugçe Toprak, Dogan Karakus, and Ahmet Hakan Onur. "Development of the Kuz-Ram Model to Blasting in a Limestone Quarry/Opracowanie Modelu Kuz-Ram Do Wykorzystania Przy Pracach Strzałowych W Kopalni Wapienia." Archives of Mining Sciences 59, no. 2 (2014): 477–88. http://dx.doi.org/10.2478/amsc-2014-0034.

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Abstract It is very important to know the degree of disintegration beforehand in open quarry bench blasting in terms of blasting efficiency. Kuznetsov (1973), Cunningham (1987), and Ouchterlony (2005) have developed the Rosin-Rammler distribution function for estimating the degrees of fragmentation (Rosin & Rammler, 1933). However, models they developed do not give realistic results for blast surfaces where there are a lot of discontinuity characteristics with broken and fissured areas due to the difference in structural characteristics of the rocks. In this study, average fragmentative di

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Tri Fidrian Arya, Reza Fuad Rachmad, and Achmad Affandi. "Cloud Node Auto-Scaling System Automation Based on Computing Workload Prediction." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 8, no. 5 (2024): 597–606. https://doi.org/10.29207/resti.v8i5.5928.

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Auto-scaling systems in cloud computing are important for handling application workload fluctuations. This research uses machine learning to predict resource requirements based on workload work patterns and design an automatic scaling system. The dataset used includes features of node name, time, CPU usage percentage, and RAM usage. The ML model is applied for prediction regression of CPU usage percentage, CPU load, and RAM usage, and then server workload is classified into four categories: Very High, High, Low, and Very Low. The autoscaling system used is horizontal scaling. From the results

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Zhao, Qianyu. "A Future Realistic Model of Bionic Limbs with High Accuracy." Theoretical and Natural Science 4, no. 1 (2023): 692–97. http://dx.doi.org/10.54254/2753-8818/4/20220686.

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Bionic limb achievements in the last 10 years have primarily focused on breakthroughs to improve accuracy with new materials and concepts that are unlikely to be used when producing an entire upper bionic limb. For example, studies on bionic limbs with new materials, such as pneumatic bionic flexible arms, which cannot meet the needs of amputees in terms of using comfortably and accurately interpreting users' intentions. Though the future development of bionic limbs has many possibilities, this paper summarizes and analyzes the functions and drawbacks of three most important structures in bion

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Li, Sihui. "Application of Realistic 3D Model in Building Prefabricated Nanomaterial Structure." International Journal of Analytical Chemistry 2022 (August 4, 2022): 1–8. http://dx.doi.org/10.1155/2022/1726948.

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In order to solve the problem of 3D modeling in building assembly, an application of a 3D model based on the real scene in the building assembly structure is proposed. This method, based on the current BIM technology in nanomaterial design research, analyzes the problems existing in the traditional assembly structure design scheme and analyzes the feasibility of BIM technology in the forward design of assembly buildings from the perspective of theory and practical application. The experimental results show that the urban building model established by the 3D model has high precision and a good

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Thwe, Yamin, Nipat Jongsawat, and Anucha Tungkasthan. "Accurate fashion and accessories detection for mobile application based on deep learning." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 4 (2023): 4347. http://dx.doi.org/10.11591/ijece.v13i4.pp4347-4356.

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Detection and classification have an essential role in the world of e-commerce applications. The recommendation method that is commonly used is based on information text attached to a product. This results in several recommendation errors caused by invalid text information. In this study, we propose the development of a fashion category (FC-YOLOv4) model in providing category recommendations to sellers based on fashion accessory images. The resulting model was then compared to YOLOv3 and YOLOv4 on mobile devices. The dataset we use is a collection of 13,689, which consists of five fashion cate

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Yamin, Thwe, Jongsawat Nipat, and Tungkasthan Anucha. "Accurate fashion and accessories detection for mobile application based on deep learning." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 4 (2023): 4347–56. https://doi.org/10.11591/ijece.v13i4.pp4347-4356.

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Detection and classification have an essential role in the world of e-commerce applications. The recommendation method that is commonly used is based on information text attached to a product. This results in several recommendation errors caused by invalid text information. In this study, we propose the development of a fashion category (FC-YOLOv4) model in providing category recommendations to sellers based on fashion accessory images. The resulting model was then compared to YOLOv3 and YOLOv4 on mobile devices. The dataset we use is a collection of 13,689, which consists of five fashion cate

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KEMP, R. A., and J. W. WILTON. "THE EFFECT OF DIFFERENT NUMERATOR RELATIONSHIP MATRICES ON BREEDING VALUES ESTIMATED FROM MULTIPLE TRAIT BLUP." Canadian Journal of Animal Science 67, no. 1 (1987): 201–4. http://dx.doi.org/10.4141/cjas87-022.

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A numerator relationship matrix (Ac) due to sires and dams was compared with a numerator relationship matrix (Ai) due to sires and maternal grandsires in a multiple-trait-reduced animal model (MT-RAM). Best linear unbiased predictors of estimated breeding values (EBV) for 200-d weight (WW) and postweaning gain (PG) (gain from 200 to 365 d of age) were estimated from data simulating a beef cattle population. As expected, mean EBV and bias (EBV-BV) for both traits were not significantly affected by different relationship matrices. The mean variances of EBV with Ac were larger than those with Ai

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Carpenter, Chris. "Machine-Learning Upscales Realistic Discrete Fracture Simulations." Journal of Petroleum Technology 73, no. 11 (2021): 65–66. http://dx.doi.org/10.2118/1121-0065-jpt.

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203962, “Upscaling of Realistic Discrete Fracture Simulations Using Machine Learning,” by Nikolai Andrianov, SPE, Geological Survey of Denmark and Greenland, prepared for the 2021 SPE Reservoir Simulation Conference, Galveston, Texas, 4–6 October. The paper has not been peer reviewed. Upscaling of discrete fracture networks to continuum models such as the dual-porosity/dual-permeability (DP/DP) model is an industry-standard approach in modeling fractured reservoirs. In the complete paper, the autho

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FRANCIOSA, PAOLO GIULIO, CARLO GAIBISSO, GIORGIO GAMBOSI, and MAURIZIO TALAMO. "A CONVEX HULL ALGORITHM FOR POINTS WITH APPROXIMATELY KNOWN POSITIONS." International Journal of Computational Geometry & Applications 04, no. 02 (1994): 153–63. http://dx.doi.org/10.1142/s0218195994000100.

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We consider the problem of deriving good approximations of the convex hull of a set of points in the plane in the realistic case that only arbitrary finite approximations of the real valued coordinates can be known. In particular, the algorithm we introduce derives sequences of improved certified approximations converging to the exact solution, at the same time allowing the insertion of new points to the problem instance. The complexity analysis of the algorithm is performed by referring to a suitable computation model, based on a RAM with logarithmic costs, and the derived space and time boun

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Verbiest, Joeri R., Bruno Bonnechère, Wim Saeys, Patricia Van de Walle, Steven Truijen, and Pieter Meyns. "Gait Stride Length Estimation Using Embedded Machine Learning." Sensors 23, no. 16 (2023): 7166. http://dx.doi.org/10.3390/s23167166.

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Introduction. Spatiotemporal gait parameters, e.g., gait stride length, are measurements that are classically derived from instrumented gait analysis. Today, different solutions are available for gait assessment outside the laboratory, specifically for spatiotemporal gait parameters. Such solutions are wearable devices that comprise an inertial measurement unit (IMU) sensor and a microcontroller (MCU). However, these existing wearable devices are resource-constrained. They contain a processing unit with limited processing and memory capabilities which limit the use of machine learning to estim

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Sadovnykov, Borys, and Oleksandr Zhuchenko. "A METHOD FOR SEARCHING AND RECOGNISING OBJECTS IN A VIDEO STREAM BY CALCULATING INTERFRAME DELTAS." Системи управління, навігації та зв’язку. Збірник наукових праць 2, no. 80 (2025): 249–54. https://doi.org/10.26906/sunz.2025.2.249.

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The article proposes an improved method for searching and recognising objects in a video stream in real time using the calculation of interframe changes (deltas) and a neural classifier. The main goal of the study is to achieve high performance and reduce the computational load on system resources while maintaining acceptable accuracy. An experimental comparison with the basic SSD (Single Shot MultiBox Detector) method was carried out, which measured the following indicators: average frame processing time, RAM and video memory usage, CPU and graphics load, and recognition accuracy. Unlike SSDs

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Jin, Chao, Ya’nan Cui, and Qileng Aori. "Evaluation of Low-Temperature Performance of Recycled Asphalt Mixture with Different Thermal History Reclaimed Asphalt Pavement." Applied Sciences 14, no. 24 (2024): 11624. https://doi.org/10.3390/app142411624.

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The utilization of reclaimed asphalt pavement (RAP) in asphalt mixtures not only reduces production costs and resource consumption but also provides significant environmental benefits. Consequently, technology and methodologies used for asphalt pavement recycling, aimed at enhancing the utilization rate of RAPs, have emerged as prominent topics in both academic research and engineering practice. Given the complex thermal history and poor low-temperature performance (LTP) of RAP, investigating the effects of varying thermal histories of RAPs on the LTP of a mixture holds substantial practical s

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Pitayachaval, Paphakorn, and Thanakhan Baothong. "A Review of Process Parameters That Effect to Extrusion on Demand." MATEC Web of Conferences 213 (2018): 01013. http://dx.doi.org/10.1051/matecconf/201821301013.

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An additive Manufacturing (AM) process has been introduced to fabricate three-dimension objects from liquid polymers and powder particles e.g. polymers and metals, this process has been also applied to fabricate three-dimension ceramic objects called paste materials which compose of liquid and solid components. To build additive model, the paste material is extruded via pressure force through the nozzle by using ram extrusion, then the model is constructed layer-by-layer on the table to form designed shape. To improve a capability of extrusion process, the Extrusion On Demand (EOD), that refer

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Neelamadhab Khaya. "Energy Efficient Predictive Maintenance in Resource Constraint Industrial IoT devices using Smoothed Mish Activation Function." Journal of Electrical Systems 20, no. 3 (2024): 3281–87. http://dx.doi.org/10.52783/jes.4931.

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Traditionally, Industrial IoT devices collect sensor data to a cloud platform where ML/DL processing is to be done. Edge computing has the advantage of reducing latency, improved battery performance, safe transmission and reducing vulnerability. These benefits are particularly significant considering the limited resources on IoT devices, such as only a few kilobytes of RAM, and the critical importance of energy savings in industrial applications. Arduino Uno uses 2kB of RAM and 32 kB of read only flash memory. Optimal performance is required for ML inference on EDGE devices to get good accurac

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Tania, Panayiotou, Savva Giannis, Tomkos Ioannis, and Ellinas Georgios. "Decentralizing machine-learning-based QoT estimation for sliceable optical networks." IEEE/OSA Journal of Optical Communications and Networking 12, no. 7 (2020): 146–62. https://doi.org/10.1364/JOCN.387853.

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Dynamic network slicing has emerged as a promising and fundamental framework for meeting 5G’s diverse use cases. As machine learning (ML) is expected to play a pivotal role in the efficient control and management of these networks, in this work, we examine the ML-based quality-of-transmission (QoT) estimation problem under the dynamic network slicing context, where each slice has to meet a different QoT requirement. Specifically, we examine ML-based QoT frameworks with the aim of finding QoT model/s that are fine-tuned according to the diverse QoT requirements. Centralized and distribute

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Schmitt, Manfred, Andreas Hübner, and Jürgen Maes. "Validierung des Vereinfachten Beck-Depressions-Inventars (BDI-V) an Fremdeinschätzungen." Diagnostica 56, no. 3 (2010): 125–32. http://dx.doi.org/10.1026/0012-1924/a000019.

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Zusammenfassung. An N = 177 Dyaden wurden Selbst- und Fremdeinschätzungen der Depressivität anhand des vereinfachten Beck-Depressions-Inventars (BDI-V) und Moderatoren des Realistic Accuracy Model erhoben. Moderatoren der Urteilsperson waren Offenheit, Empathie, Perspektivenübernahme und Alter, Moderatoren der Zielperson Privatheit, Selbstkonsistenz, Selbsttäuschung und Fremdtäuschung. Weitere Moderatoren waren Bekanntschaftsdauer und -qualität sowie Einschätzungen der Beobachtbarkeit von Depressionssymptomen einer unabhängigen Stichprobe (N = 219). Moderatorhypothesen wurden interdyadisch, in

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Velichko, Andrei. "A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare." Sensors 21, no. 18 (2021): 6209. http://dx.doi.org/10.3390/s21186209.

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Edge computing is a fast-growing and much needed technology in healthcare. The problem of implementing artificial intelligence on edge devices is the complexity and high resource intensity of the most known neural network data analysis methods and algorithms. The difficulty of implementing these methods on low-power microcontrollers with small memory size calls for the development of new effective algorithms for neural networks. This study presents a new method for analyzing medical data based on the LogNNet neural network, which uses chaotic mappings to transform input information. The method

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Chen, Roei, Eshkol Rafaeli, Eran Bar-Kalifa, Eva Gilboa-Schechtman, Wolfgang Lutz, and Dana Atzil-Slonim. "Moderators of congruent alliance between therapists and clients: A realistic accuracy model." Journal of Counseling Psychology 65, no. 6 (2018): 703–14. http://dx.doi.org/10.1037/cou0000285.

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West, M., J. D. Turton, and I. D. Todd. "On the accuracy of ray tube model predictions for realistic meteorological conditions." Applied Acoustics 42, no. 3 (1994): 277–89. http://dx.doi.org/10.1016/0003-682x(94)90115-5.

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Bharathi, M., T. Aditya Sai Srinivas, and P. Ravinder. "YOLOv8 on the Road: Next-Level Perception for Autonomous Vehicles." Journal of Image Processing and Image Restoration 1, no. 2 (2024): 17–23. http://dx.doi.org/10.48001/joipir.2024.1217-23.

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The system’s products and features drive the product search process. By enhancing low-quality images to high resolution, its performance can be optimized. As machine learning evolves, advanced tools tackle complex features, improving upon legacy systems. This project introduces a new method for detecting vehicles, pedestrians, and traffic signs using publicly available data. We modify the YOLOv8 model to boost accuracy, leveraging its efficiency on mobile devices and minimal RAM usage, with Unity facilitating conversion.

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Liu, Liu, Kaile Liu, Zhenghai Cong, Jiali Zhao, Yefei Ji, and Jun He. "Long Length Document Classification by Local Convolutional Feature Aggregation." Algorithms 11, no. 8 (2018): 109. http://dx.doi.org/10.3390/a11080109.

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The exponential increase in online reviews and recommendations makes document classification and sentiment analysis a hot topic in academic and industrial research. Traditional deep learning based document classification methods require the use of full textual information to extract features. In this paper, in order to tackle long document, we proposed three methods that use local convolutional feature aggregation to implement document classification. The first proposed method randomly draws blocks of continuous words in the full document. Each block is then fed into the convolution neural net

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Semakin, A. N. "GEM5: DEVELOPMENT OF COMPUTER SYSTEM MODELS WITH PURPOSE TO EVALUATE THE EFFICIENCY OF PARALLEL CODE." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 227 (May 2023): 49–56. http://dx.doi.org/10.14489/vkit.2023.05.pp.049-056.

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In this paper we consider the possibility of using the gem5 computer system simulator to determine such metrics of parallel program code as its acceleration and the average workload of cpu cores on computer systems with shared memory. The working process in gem5 consists of three stages: building a model of a computer system, loading a software environment into the built model and executing a user program within this environment. The considered approach is used to evaluate the efficiency of a parallel program for modeling the transport of pollutants in the atmosphere. The program assumes both

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Punter, Wieger R., Odysseas Papapetrou, and Minos Garofalakis. "OmniSketch: Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates." Proceedings of the VLDB Endowment 17, no. 3 (2023): 319–31. http://dx.doi.org/10.14778/3632093.3632098.

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A key need in different disciplines is to perform analytics over fast-paced data streams, similar in nature to the traditional OLAP analytics in relational databases - i.e., with filters and aggregates. Storing unbounded streams, however, is not a realistic, or desired approach due to the high storage requirements, and the delays introduced when storing massive data. Accordingly, many synopses/sketches have been proposed that can summarize the stream in small memory (usually sufficiently small to be stored in RAM), such that aggregate queries can be efficiently approximated, without storing th

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Punter, Wieger R., Odysseas Papapetrou, and Minos Garofalakis. "OmniSketch: Streaming Data Analytics with Arbitrary Predicates." ACM SIGMOD Record 54, no. 1 (2025): 28–35. https://doi.org/10.1145/3733620.3733627.

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A key need in different disciplines is to perform analytics over fast-paced data streams, similar in nature to the traditional OLAP analytics in relational databases, i.e., with filters and aggregates. Storing unbounded streams, however, is not a realistic approach due to the high storage requirements, and the delays introduced when storing massive data. Accordingly, many synopses/sketches have been proposed that can summarize the stream in small memory (usually sufficiently small to be stored in RAM), such that aggregate queries can be efficiently approximated, without storing the full stream

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Vatta, Federica, Fabio Meneghini, Fabrizio Esposito, Stefano Mininel, and Francesco Di Salle. "Realistic and Spherical Head Modeling for EEG Forward Problem Solution: A Comparative Cortex-Based Analysis." Computational Intelligence and Neuroscience 2010 (2010): 1–11. http://dx.doi.org/10.1155/2010/972060.

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The accuracy of forward models for electroencephalography (EEG) partly depends on head tissues geometry and strongly affects the reliability of the source reconstruction process, but it is not yet clear which brain regions are more sensitive to the choice of different model geometry. In this paper we compare different spherical and realistic head modeling techniques in estimating EEG forward solutions from current dipole sources distributed on a standard cortical space reconstructed from Montreal Neurological Institute (MNI) MRI data. Computer simulations are presented for three different four

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Athawale, Prof. S. V., Shreyash Vyawahare, Priyanshu Marodkar, Srushti Lanjewar, and Pratiksha Tawar. "Deepfake Detection Model." International Journal of Ingenious Research, Invention and Development (IJIRID) 3, no. 2 (2024): 195–202. https://doi.org/10.5281/zenodo.11180891.

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<em>Deepfakes are a type of synthetic media that can be used to create realistic videos of people saying or doing things they never did. This raises concerns about the potential for deepfakes to be used to spread misinformation or propaganda. In this project, we present a deepfake detection module that can be used to identify deepfakes with high accuracy. The deepfake detection module is based on a pre-trained InceptionResNetV2 model that is fine-tuned on a dataset of real and deepfake videos. The model is able to extract features from the videos that are indicative of whether they are real or

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Zhao, Yinyin, Lv Zhou, Chao Chen, et al. "Urban Forest Above-Ground Biomass Estimation Based on UAV 3D Real Scene." Drones 7, no. 7 (2023): 455. http://dx.doi.org/10.3390/drones7070455.

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(1) Background: A three-dimensional (3D) real scene is a digital representation of the multidimensional dynamic real-world structure that enables the realistic and stereoscopic expression of actual scenarios, and is an important technological tool for urban refinement management. The above-ground biomass (AGB) of urban forests is an important indicator that reflects the urban ecological environment; therefore, the accurate estimation of AGB is of great significance for evaluating urban ecological functions. (2) Methods: In this study, multiangle aerial photographs of urban street trees were ob

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Tan, Liang, Jinfeng Huang, Xinghua Kou, Xingzhong Wang, and Wanli Wang. "Simulation of three cylinders synchronous circuit based on RBF neural network optimized PID controller." Journal of Physics: Conference Series 2365, no. 1 (2022): 012043. http://dx.doi.org/10.1088/1742-6596/2365/1/012043.

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Abstract RamRig hosting system is a common system for offshore and onshore drilling rigs, which uses ram cylinders to lift and lower the top drive on the drilling rig. In order to ensure the accuracy, stability and robustness of synchronous control of RamRig hosting system, RBF neural network is used to adjust PID parameters online, and a three cylinders synchronous loop simulation model based on RBF optimized PID controller is built in AMESim and Simulink. The simulation results show that the three cylinders synchronous hydraulic circuit based on RBF neural network optimized PID controller ha

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Gui, Yiwei. "Edge impulse-based convolutional neural network for Hand Posture Recognition." Applied and Computational Engineering 40, no. 1 (2024): 115–19. http://dx.doi.org/10.54254/2755-2721/40/20230636.

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Hand Posture Recognition (HPR) plays a crucial role in enabling effective human-computer interaction, particularly for individuals with hearing disabilities. The study compares five models, including MobileNetV2 96x96 0.35, MobileNetV1 96x96 0.25, MobileNetV1 96x96 0.1, self-designed Network 1, and self-designed Network 2, based on the Sbastien Marcel Static Hand Posture Database. Evaluation metrics - infserencing time, peak RAM usage, flash usage, and accuracy - are used to analyze the performance. The experiment workflow for each model comprises five major steps. Firstly, a random selection

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Yang, Hai Tao, Peng Wei Li, and Hong Li Zhao. "Research on Behavioral Decision Method of Simulation Entity Based on Cognitive Model." Applied Mechanics and Materials 344 (July 2013): 242–45. http://dx.doi.org/10.4028/www.scientific.net/amm.344.242.

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This paper studies how to use the cognitive model to model the behavioral decision-making for the tactical level simulation. The decision making process includes initial behavior planning and behavior modification. This method has the advantages of accuracy and real-time, this makes the behaviors of the simulation entity more realistic and improves the credibility of simulation.

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Carroll, Alison R., Matthew Hall, Mitch Harris, et al. "Validation of 30-Day Pediatric Hospital Readmission Risk Prediction Models." JAMA Network Open 8, no. 2 (2025): e2459684. https://doi.org/10.1001/jamanetworkopen.2024.59684.

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ImportanceAccurate identification of hospital readmission risk during a current hospitalization may enhance decision-making, facilitate targeted systems-level interventions, and avoid preventable readmissions.ObjectiveTo temporally and externally validate a suite of readmission risk prediction models across 48 children’s hospitals to assess their generalizability and feasibility for future clinical implementation.Design, Setting, and ParticipantsThis prognostic study analyzed data from the Pediatric Health Information System (PHIS) database, which contains billing and resource use data from 48

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