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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Meng Chee, Yeow Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan National University of Singapore Department of Industrial Systems Engineering and Management Singapore Technion - Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Turing Machines Inc. Rotterdam3016 DK Netherlands Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore Delft University of Technology Department of Applied Mathematics Delft2628 CD Netherlands

ISBN: (纸本)9781665475549

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints. © 2023 IEEE.

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Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 363-382页

作者： G.Merlin Linda N.V.S.Sree Rathna Lakshmi N.Senthil Murugan Rajendra Prasad Mahapatra V.Muthukumaran M.Sivaram Department of Computer Science and Engineering SRM Institute of Science and Technology–Vadapalani CampusChennaiIndia Department of Electronics and Communication Engineering Agni College of TechnologyChennaiIndia School of Computer Science and Engineering VIT-AP UniversityAmaravatiIndia Department of Computer Science and Engineering SRM Institute of Science and TechnologyGhaziabadIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam

Purpose-The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and *** proposes a convolutional neural network-based capsule network(CNN-CapsNet)model and outlining the performance of the system in recognition of gait and speech *** proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech ***/methodology/approach-This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNNand used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in *** proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of ***-This research work provides recognition of signal,biometric-based gait recognition and sound/speech *** evaluations are conducted on three aspects of scenarios,namely fixed-view,cross-view and multi-view *** main parameters for recognition of gait are speed,change in clothes,subjects walking with carrying object and intensity of *** limitations/implications-The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware *** implications-This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware ***/value-This proposed research work proves to be performing better for the recognition of gait and speech when

关键词： Intelligent system Gait recognition Convolutional neural network Deep learning Capsule network Viewpoint variations

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Cerebral and muscle tissue oxygenation during exercise in healthy adults: A systematic review

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Journal of Sport and Health Science 2024年第4期13卷 459-471,F0003页

作者： Diego Orcioli-Silva Victor Spiandor Beretta Paulo Cezar Rocha Santos Felipe Marroni Rasteiro Anita Brum Marostegan Rodrigo Vitorio Claudio Alexandre Gobatto Fulvia Barros Manchado-Gobatto Laboratory of Applied Sport Physiology(LAFAE) School of Applied Sciences(FCA)University of Campinas(UNICAMP)Limeira 13484-350Brazil Posture and Gait Studies Laboratory(LEPLO) Institute of BiosciencesSao Paulo State University(UNESP)Rio Claro 13506-900Brazil Physical Education Department School of Technology and SciencesSao Paulo State University(UNESP)Presidente Prudente 19060-900Brazil Department of Computer Science&Applied Mathematics Weizmann Institute of ScienceRehovot 7610001Israel Center of Advanced Technologies in Rehabilitation Sheba Medical CenterRamat Gan 5265601Israel Department of Sport Exercise and RehabilitationNorthumbria UniversityNewcastle upon Tyne NE18STUK

Background:Near-infrared spectroscopy(NIRS)technology has allowed for the measurement of cerebral and skeletal muscle oxygenation simultaneously during *** this technology has been growing and is now successfully used in laboratory and sports settings,this systematic review aimed to synthesize the evidence and enhance an integrative understanding of bloodﬂow adjustments and oxygen(O_(2))changes(i.e.,the balance between O_(2) delivery and O_(2) consumption)within the cerebral and muscle systems during ***:A systematic review was conducted using PubMed,Embase,Scopus,and Web of Science databases to search for relevant studies that simultaneously investigated cerebral and muscle hemodynamic changes using the near-infrared spectroscopy system during *** review considered manuscripts written in English and available before February 9,*** step of screening involved evaluation by 2 inde-pendent authors,with disagreements resolved by a third *** Joanna Briggs institute Critical Appraisal Checklist was used to assess the methodological quality of the ***:Twenty studies were included,of which 80%had good methodological quality,and involved 290 young or middle-aged *** types of exercises were used to assess cerebral and muscle hemodynamic changes,such as cycling(n=11),treadmill(n=1),knee extension(n=5),isometric contraction of biceps brachii(n=3),and duet swim routines(n=1).The cerebral hemodynamics anal-ysis was focused on the frontal cortex(n=20),while in the muscle,the analysis involved vastus lateralis(n=18),gastrocnemius(n=3),biceps brachii(n=5),deltoid(n=1),and intercostal muscle(n=1).Overall,muscle deoxygenation increases during exercise,reaching a plateau in voluntary exhaustion,while in the brain,oxyhemoglobin concentration increases with exercise intensity,reaching a plateau or declining at the exhaustion ***:Muscle and cerebral oxygenation respond differently to exercise,with muscle

关键词： Near-infrared spectroscopy Hemodynamic Blood flow Brain Muscle metabolism

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Novel characterization and tuning methods for integrating processes

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International Journal of Information technology (Singapore) 2024年第3期16卷 1387-1395页

作者： Jorge, Cárdenas-Cabrera Jorge, Henríquez-Novoa Wendell, Martínez-Rodríguez Edalatpanah, S.A. Shariq, Aziz Butt Naz, Sumera Javier, Jimènez-Cabas Gabriel, Piñeres-Espitia Department of Computer Science and Electronics Universidad de La Costa Calle 58 55-66 Atlántico Barranquilla 080002 Colombia Department of Applied Mathematics Ayandegan Institute of Higher Education Ferdowsi St RVF6+JJ9 Mazandaran Tonekabon *** Iran Deparment of Computer Science University of South Asia 47-Tufail Road Punjab Lahore 110021 Pakistan Department of Mathematics Division of Science and Technology University of Education Lahore Pakistan

The manuscript presents new methodologies for process characterization and control tuning for integrated systems. Integrative systems are widespread in the industrial environment. Some control systems for level, pressure, concentration, and temperature are examples. Although many papers have been published on the subject, no standard has been established, so this remains an open problem. The proposed characterization method consists of deriving the response of the integrating system and applying characterization techniques for self-regulated processes. The proposed tuning method is based on deducing tuning equations for a PD control from the λ tuning rules. The performance of the proposed methods is validated through simulation and experimental tests. © 2024, The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management.

关键词： Integrating process Process characterization/identification λ tuning

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AGV indoor localization: a high fidelity positioning and map building solution based on drawstring displacement sensors

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2277-2293页

作者： Wang, Shih-Yuan Li, Che-Ming Liong, Sze-Teng Sheng, Yu-Ting Huang, Yen-Chang Liong, Gen-Bing Gan, Yee-Siang Graduate Institute of Architecture National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan School of Architecture Feng Chia University Taichung40724 Taiwan Department of Applied Mathematics National University of Tainan Tainan Taiwan Faculty of Computer Science & amp Information Technology University of Malaya Kuala Lumpur50603 Malaysia

The rapid evolution of artificial intelligence (AI) and robotics technologies are bringing drastic changes to society and industry in these recent years. The impressive progress in facilitating smart manufacturing in this era of Industry 4.0 has made our lives much more convenient than ever before. Despite the greater reliability and stability of the robotic system, there are several challenges to overcome such as the restrictions of scenes, obstacles, and hardware specifications. Since a high precision positioning algorithm is of paramount importance in devising a mobile robot, the research in developing simultaneous localization and mapping has been garnered immerse attention especially from domains of the computer vision and autonomous robots. In this paper, a novel method is presented to significantly enhance the positioning precision of indoor unmanned guided vehicles. The approach involves several steps, including setting up hardware configurations and collecting relevant data by installing necessary devices and system packages within the robot operating system (ROS). Trilateration is employed to determine the relative position of the mobile robot using distance measurements. Coordinate transformation is then conducted to convert the collected input data of relative distances and orientations. Trajectory paths are obtained, and occupancy maps are constructed to estimate the resulting trajectory and generate a 2D grid map. Indoor localization and mapping are achieved using three drawstring displacement sensors along with orientation information from an Inertial Measurement Unit (IMU). The proposed method is extensively evaluated through experimentation on predefined navigation paths, and its performance is compared to state-of-the-art methods such as RealSense T265, Hector SLAM, and wheel odometry. The results show that the proposed method exhibits compelling performance in both mean error and occupancy map construction. Ultimately, the findings reported herein

关键词： Mobile robots

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Optimal Prediction of Heart Disease by Identifying the Type of Chest Pain Using Machine Learning Techniques 4th

Optimal Prediction of Heart Disease by Identifying the Type ...

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4th International Conference on Communication and Intelligent Systems, ICCIS 2022

作者： Ahmad, Ghulab Nabi Fatima, Hira Shafiullah Noor, Arshil Institute of Applied Sciences Mangalayatan University Uttar Pradesh Aligarh India Department of Mathematics K.C.T.C College BRA Bihar University Muzaffarpur Raxual India Department of Computer Science Institute of Technology and Management Uttar Pradesh Aligarh India

ISBN: (纸本)9789819920990

Any serious heart ailment is referred to as coronary heart disease. Researchers are concentrating on developing smart systems to identify heart disease precisely based on electronic health data, with the use of machine learning algorithms (MLAs), because they can be fatal. This study introduces ten machine learning techniques (MLTs) for predicting heart diseases using patient data on key healthcare outcomes as: logistic regression classifier (LRC), decision tree classifier (DTC), random forest classifier (RFC), extra tree classifier (EXTC), K-nearest neighbours classifier (KNNC), support vector machine classifier (SVMC), bagging classifier (BC), gradient boosting classifier (GBC), light GBM classifier (LGBMC), Gaussian Naive Bayes classifier (GNBC) on standard datasets from Cleveland, Hungarian, Switzerland, Long Beach VA database, and Statlog Heart Disease of University of California Irvine (UCI) repository to build the prediction models. Data preprocessing and feature selection steps are done before building the models. The models are evaluated based on the accuracy, precision, recall, and F1-score, specificity, MCC, ROC–AUC, and balanced accuracy. The extra tree classifier performed best with 89.10% accuracy, 93.50% precision, 87.80% recall, 90.06% F1-score, 91.10% specificity, 78.00% MCC, 89.44% ROC–AUC, and 89.10% balanced accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nearest neighbor search

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Comparative sensitivity analysis of single and multiple modifications in multi-criteria decision analysis 28th

Comparative sensitivity analysis of single and multiple modi...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Wieckowski, Jakub Bialon, Pawel Salabun, Wojciech Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland

In the area of decision-making, where complexities often exceed experts' analytical capabilities, this study addresses a critical gap by introducing a novel methodology for sensitivity analysis within the Multi-Criteria Decision Analysis (MCDA) problems. Current analytical frameworks struggle to comprehensively consider potential modifications to values within decision matrices, making it challenging to understand their impact in detail. To address this challenge, decision-makers need enhanced tools, and MCDA methods combined with systematic changes in selected elements of the decision matrix stand out as a promising approach. However, existing studies primarily focus on different criteria-weight scenarios, leaving an unexplored gap in the simultaneous modification of multiple values within the decision matrix. This paper integrates sensitivity analysis within the MCDA methods, extending its role in the comprehensive assessment of decision problems. Sensitivity analysis becomes crucial in offering decision-makers a broader perspective, aiding them in navigating the complexities of decision-making in dynamic environments. Recognizing the unexplored potential in sensitivity analysis, the study proposed a novel approach of simultaneous modification of multiple values in a decision matrix, offering an extension of conventional one-at-a-time modifications. As a Proof of Concept (PoC) research work, the study investigated whether the determined approach provides divergent preference scores compared to the traditional single-modification method across ten different MCDA techniques. The results showed that modifying multiple values simultaneously produced different preference scores of alternatives than in the case of a conventional single change, showing that additional insight knowledge could be extracted from this type of sensitivity analysis. © 2024 The Authors.

关键词： Sensitivity analysis

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Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading 33

Mutual Contrastive Low-rank Learning to Disentangle Whole Sl...

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33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Zhang, Lipei Wei, Yiran Fu, Ying Price, Stephen Schönlieb, Carola-Bibiane Li, Chao Department of Applied Mathematics and Theoretical Physics University of Cambridge United Kingdom Department of Clinical Neuroscience University of Cambridge United Kingdom School of Computer Science and Technology Beijing Institute of Technology China

Whole slide images (WSI) provide valuable phenotypic information for histological assessment and malignancy grading of tumors. The WSI-based grading promises to provide rapid diagnostic support and facilitate digital health. Currently, the most commonly used WSIs are derived from formalin-fixed paraffin-embedded (FFPE) and Frozen section. The majority of automatic tumor grading models are developed based on FFPE sections, which could be affected by the artifacts introduced from tissue processing. The frozen section exists problems such as low quality that might influence training within single modality as well. To overcome these problems in the single modal training and achieve better multi-modal and discriminative representation disentanglement in brain tumor, we propose a mutual contrastive low-rank learning (MCL) scheme to integrate FFPE and frozen sections for glioma grading. We first design a mutual learning scheme to jointly optimize the model training based on FFPE and frozen sections. In this proposed scheme, we design a normalized modality contrastive loss (NMC-loss), which could promote to disentangle multi-modality complementary representation of FFPE and frozen sections from the same patient. To reduce intra-class variance, and increase inter-class margin at intra- and inter-patient levels, we conduct a low-rank (LR) loss. Our experiments show that the proposed scheme achieves better performance than the model trained based on each single modality or mixed modalities without reducing the efficiency of inference, and even improves the feature extraction in classical attention-based multiple instances learning methods (MIL). The combination of NMC-loss and low-rank loss outperforms other typical contrastive loss functions. The source code is in https://***/uceclz0/MCL_glioma_grading. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Grading

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PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE SELECTION METHODS 17

PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE...

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17th International Symposium on Operational Research in Slovenia, SOR 2023

作者： Akarçay Pervin, Özlem Yapici Pehlivan, Nimet Weber, Gerhard Wilhelm KTO Karatay University Department of Computer Programming Konya Turkey Selçuk University Department of Statistics Konya Turkey Poznan University of Technology Poznan Poland Middle East Technical University Institute of Applied Mathematics Ankara Turkey

ISBN: (纸本)9789616165617

Heart disease, known as cardiovascular disease has been one of the main causes of death worldwide in recent years. It is affected by various risk factors such as high blood pressure, high cholesterol, diabetes, smoking, obesity, physical inactivity, etc. In this study, Cleveland database of UCI repository of heart disease patients is used. The dataset includes 303 instances and 76 variables which of 14 variables are considered. At first, three different feature selection techniques, namely LASSO, Elastic Net and Adaptive LASSO under specific tuning parameters determined by cross-validation, are applied to reduce the number of independent variables used for the prediction. Then, five different classification techniques, K-nearest neighbor, Support Vector Machine, Decision Tree, Random Forest, and Logistic Regression are performed to predict heart disease. Performances of these methods are measured by different metrics, such as accuracy, sensitivity, specificity, and Matthew correlation coefficient. © Proceedings of the 17th International Symposium on Operational Research in Slovenia, SOR 2023. All rights reserved.

关键词： Decision trees

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A Comparative Study on the Efficiency of the Modified COMET in Decision-Making 28th

A Comparative Study on the Efficiency of the Modified COMET ...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Paradowski, Bartosz Olender, Pawel Salabun, Wojciech Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland

Decision-making is a high-risk area and, simultaneously, a process that cannot be ignored. Risks often arise under challenging situations where ranking the options under consideration is a complex problem. For such purposes, multi-criteria decision-making methods are resorted to, which, despite continuous improvement, still have some weaknesses, often due to their characteristics. One such method that has seen many modifications in the literature is the Characteristic Objects METhod (COMET). It allows a simplified comparison of alternatives considered in a given problem, compared to the Analytic Hierarchy Process (AHP), but has a relatively high computational complexity. In this study, we present a modification of the COMET method that simplifies the procedure for assigning preference values to characteristic objects. Furthermore, a comparison with the classical approach is given regarding the obtained preference values, rankings, and criteria weights, which occur implicitly in this method. The study showed that the proposed modification has grounds for broader use and offers similar results to classical COMET while reducing the number of required operations to obtain preference values. © 2024 The Authors.

关键词： Comets

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