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2nd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Bishnoi, Amit Kumar Vivek, V. Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

The Structured Random Matrix (SRM) model is an increasingly popular approach to industrial automation. This model is based on the idea that the control systems of industrial machines are "structured"in a certain way, with certain properties that can be predicted and used to model the behavior of the system. SRM incorporates the principles of random matrix theory in order to provide an efficient, reliable, and realistic model for industrial automation. The SRM model works by taking a large set of variables, such as the type of machine, the speed of the machine, the number of required parts, and the number of different components to be used in the system. These variables are then used to generate a random matrix, which can then be analyzed to identify patterns and correlations between the different variables. This allows engineers to develop more accurate models of the system, as well as to identify potential problems and solutions. In addition to providing a more accurate model, the SRM model also allows engineers to simplify the design process by reducing the number of variables used in the system. This simplification means that fewer parts are needed in the system, which reduces the cost and complexity of the system. Furthermore, by reducing the complexity of the system, engineers can reduce the amount of time spent on maintenance and repairs, which saves money and increases efficiency. © 2023 IEEE.

关键词： Automation

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An Innovation Development of Reliable Routing System Based on Industrial Conveyor Weighting and Management System 2

An Innovation Development of Reliable Routing System Based o...

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2nd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Kanniga, Devi Kumari, Neeraj Department of Computer Science and Engineering Bangalore India Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India

ISBN: (纸本)9798350347456

Reliable routing systems for industrial conveyor weighing are essential for ensuring accurate weight readings and efficient operation. Conveyor weighing systems are used in a variety of industrial contexts, including food production and packaging, chemical processing, and the manufacturing of heavy equipment. The reliability of these systems is critical for the successful operation of these industries. The primary components of a reliable routing system for industrial conveyor weighing are the conveyor belt, the load sensors, and the control system software. The conveyor belt is the most essential part of the system, as it carries the material being weighed. The load sensors measure the weight of the material as it moves along the conveyor belt and sends this information to the control system. The software then processes the weight data and sends commands to the conveyor belt, adjusting its speed and direction to ensure accurate weight readings. A reliable routing system should also include safety features to protect operators and equipment. Sensors should be placed near the conveyor belt to detect any potential hazards and notify the operator accordingly. The system should also feature emergency stop buttons to quickly shut down the conveyor belt in the event of an emergency. Additionally, the system should be equipped with alarms and other warning systems to alert operators of any potential issues. © 2023 IEEE.

关键词： Chemical industry

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Enhancing Healthcare AI Sensitivity through Affective computing: Analyzing Human Emotions 1

Enhancing Healthcare AI Sensitivity through Affective Comput...

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1st IEEE International Conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Singh, Rahul Kumar, Avadhesh Sagar, Shraddha Sharma, Vishnu Galgotias University School of Computing Science and Engineering Greater Noida India ITS Engineering College Department of Computer Science Engineering Greater Noida India

ISBN: (纸本)9798350356816

Affective computing (AC), also known as emotion AI, is a concept that applies modern technology to help systems to recognize and process human emotions and their feelings. Several uses of affective computing have been demonstrated, including marketing, healthcare, driving assistance, and education. Linear Support vector machines (SVM), k-nearest neighbor (k-NN), Hidden Markov models (HMMs), Gaussian mixture models (GMM), discriminate classifiers (LDC), decision tree algorithms and artificial neural networks (ANN), are the classifiers that are most frequently used in research on identifying and categorizing human emotions. Selecting the right classifier can significantly increase the system's overall efficiency, as numerous studies have conclusively demonstrated. Through use of cameras, microphones, skin sensors, or other devices, affective computing gathers signals from human users, gathering data on their facial expressions, voice tones, gestures, and other characteristics that can hint at their emotional states. The system deduces the user's emotional state from those data points. This study emphasizes on the fundamentals of computing emotions. © 2024 IEEE.

关键词： Support vector machines

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Cardiac Arrhythmia Disease Classifier Model Based on a Fuzzy Fusion Approach

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computers, Materials & Continua 2023年第5期75卷 4485-4499页

作者： Fatma Taher Hamoud Alshammari Lobna Osman Mohamed Elhoseny Abdulaziz Shehab Eman Elayat College of Technological Innovation Zayed UniversityDubaiUAE Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Electronics and Communications Engineering Delta Higher Institute for Engineering&TechnologyMansouraEgypt College of Computing and Informatics University of SharjahSharjahUnited Arab Emirates Department of Information Systems Mansoura UniversityMansoura35516Egypt Department of Teacher Preparation Faculty of Specific EducationMansoura UniversityMansouraEgypt

Cardiac diseases are one of the greatest global health *** to the high annual mortality rates,cardiac diseases have attracted the attention of numerous researchers in recent *** article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia *** fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection *** ensemble of classifiers is then applied to the fusion’s *** proposed model classifies the arrhythmia dataset from the University of California,Irvine into normal/abnormal classes as well as 16 classes of ***,at the preprocessing steps,for the miss-valued attributes,we used the average value in the linear attributes group by the same class and the most frequent value for nominal ***,in order to ensure the model optimality,we eliminated all attributes which have zero or constant values that might bias the results of utilized *** preprocessing step led to 161 out of 279 attributes(features).Thereafter,a fuzzy-based feature-selection fusion method is applied to fuse high-ranked features obtained from different heuristic feature-selection *** short,our study comprises three main blocks:(1)sensing data and preprocessing;(2)feature queuing,selection,and extraction;and(3)the predictive *** proposed method improves classification performance in terms of accuracy,F1measure,recall,and precision when compared to state-of-the-art *** achieves 98.5%accuracy for binary class mode and 98.9%accuracy for categorized class mode.

关键词： Cardiac arrhythmia preprocessing missing values classification model fusion

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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The Smart Application Development in Real Time Parallel Applications with Industrial Automation 2

The Smart Application Development in Real Time Parallel Appl...

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2nd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Khan, Gulista Zabeeulla, Zabeeulla Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

Real-time parallel applications with industrial automation are applications that are designed to run in parallel, in order to accomplish a task in a shorter amount of time. These applications are used in industrial environments to control machines and other processes in order to maximize efficiency and minimize waste. Real-time parallel applications allow machines and processes to be managed simultaneously. This means that instead of needing to wait for one process to finish before starting the next, multiple processes can be run at the same time. This increases the speed at which tasks can be completed, allowing for greater efficiency and productivity. Real-time parallel applications can be used to automate processes and machines. This means that instead of needing to manually manage and monitor a machine, the software can handle all of the work. This can help to reduce errors and improve the overall quality of the product being produced. © 2023 IEEE.

关键词： Efficiency

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An Smart Analysis of Energy Efficiency Issues in Industrial Automation 2

An Smart Analysis of Energy Efficiency Issues in Industrial ...

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2nd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Singhal, Priyank Mahesh, T.R. Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

Industrial automation has become increasingly important in recent years. It has allowed for increased efficiency, productivity and safety in the workplace, as well as improved quality control of products. However, with the increased use of automation, comes the need to be mindful of energy efficiency issues. Energy use in industrial automation is primarily driven by the use of electric motors, pumps and other devices. These devices consume a large amount of electricity, especially when they are running continuously or at high speeds. This can result in significant energy losses and increased costs. Additionally, when the motors are operating at different speeds, they can draw more power than they need and this can also cause energy losses. To reduce energy losses, it is important to ensure that the motors and pumps are properly sized for the application and that they are running at the correct speed. Additionally, it is important to take into account the efficiency of the motors and pumps. For example, variable speed drives can introduce energy savings in certain applications. Additionally, energy-efficient motors and pumps can reduce energy losses significantly. © 2023 IEEE.

关键词： Automation

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A Novel Attention-Based Method for Integrating Facial and Speech Features in Emotion Recognition 2

A Novel Attention-Based Method for Integrating Facial and Sp...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Singh, Rahul Sagar, Shraddha Kumar, Avadhesh Sharma, Vishnu Galgotias University School of Computing Science & Engineering Greater Noida India Its Engineering College Department of Computer Science Engineering Greater Noida India

ISBN: (纸本)9798350388916

Our research introduces a novel approach for recognizing multiple emotions by leveraging perspective-based methods. This technique integrates facial features and speech characteristics obtained from different encoders to pinpoint the most significant attributes. The distinct characteristics of speech and facial expressions, along with effective size management, prove to be highly beneficial. By concentrating on specific components, the system enhances overall accuracy. Images of facial features are captured from both low and high angles to ensure a comprehensive representation. These techniques are merged through a fusion mesh, producing several feature vectors that are subsequently utilized in the classification stage for sensitivity analysis. When tested with both data sets, this algorithm surpassed existing models, achieving a weighted accuracy (WA) of 90.3%. © 2024 IEEE.

关键词： Attention-Based Method Emotion Classification Facial and Speech Features Fusion Network Multimodal Emotion Recognition Weighted Accuracy

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XDGesture: An xLSTM-based Diffusion Model for Co-speech Gesture Generation

XDGesture: An xLSTM-based Diffusion Model for Co-speech Gest...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Zixing Li, Jiajun Wang, Bin Liu, Yiming Zhao, Huan Schuller, Björn W. College of Computer Science and Electronic Engineering Hunan University China GLAM Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9798350368741

In multimodal human-computer interaction, generating co-speech gestures is crucial for enhancing interaction naturalness and user experience. However, achieving synchronized and natural gesture sequences remains a significant challenge due to the complexity of modeling temporal dependencies across different modalities. Existing methods often rely on simple concatenation techniques, which are limited in effectively handling multimodal information. To address this issue, we propose XDGesture, a diffusion-based framework that integrates a Cross-Modal Fusion module and xLSTM. The Cross-Modal Fusion module efficiently merges information from different modalities, providing the model with rich contextual conditions. Meanwhile, xLSTM, with its enhanced memory structure and exponential gating mechanism, processes the fused multimodal data, capturing long-range dependencies between speech and gestures. This enables the generation of high-quality gesture sequences that are naturally synchronized with speech. Experimental results demonstrate that XDGesture remarkably outperforms existing baselines on multiple datasets, particularly in terms of gesture quality, naturalness, and synchronization with speech. © 2025 IEEE.

关键词： Co-speech gesture generation Diffusion model Multimodal feature fusion xLSTM

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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