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8th international conference on Applied Cognitive Computing, ACC 2024, and 26th international conference on Artificial Intelligence, ICAI 2024, held as part of the World Congress in computer Science, computer Engineering and Applied Computing, CSCE 2024

8th International Conference on Applied Cognitive Computing,...

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8th international conference on Applied Cognitive Computing, ACC 2024, and 26th international conference on Artificial Intelligence, ICAI 2024, held as part of the World Congress in computer Science, computer Engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031856273

The proceedings contain 37 papers. The special focus in this conference is on Applied Cognitive Computing. The topics include: Assessing Information Influence for Node Attribute Prediction;in-Vehicle Sensing Platform for the Inference of Older Drivers’ Mild Cognitive Condition;infusing Human Feedback into Intermediate Prompting Steps of Large Language Models;experimental Analysis of Contemporary Trends, Performance, and Limitations in Graph Embeddings: A Concise Review;a Secure Self-Adaptive System in Applications of Cognitive Computing;revisiting the Nexus Between Handwriting and Personality: Graphology;from Static Graph Attention Generation to Dynamic Graph Attention Coefficient;An Integrated Approach for AI-Assisted Survey Systems Using Deterministic and Nondeterministic Models;a Voxel-Representation-Based Data Generator of Adversarial Objects for Robotic Manipulators;an Analysis of Different Information Granularity Distribution Protocols to Improve Consistency in Intuitionistic Reciprocal Preference Relations;enhancing Differential Evolution for Neural Network Optimization Through Boundary Individual Consideration;predictive modeling of Shading Effects on Photovoltaic Panels Using Regression Analysis;enhancing Cultural Algorithm Guided Policy Gradients with Parameter-Based Exploration Through Topographic Knowledge and Adaptive Weighting;Enhancing Clinical Documentation Through NLP-Driven Disease Categorization and Visualization: A Case Study Utilizing the Llama2 AI Model;automatic Modulation Recognition: A Hybrid Approach Using Deep Learning and K-Means Clustering;An ISR Asset Planning Application;causal Discovery with Interactive Human Inputs;implementation of a Lightweight Gradient Descent Trained Expert System Algorithm;Leveraging JSBSim and Gymnasium: A Reinforcement Learning Approach for Air Combat simulation;orthogonal Activation Functions in Neural Networks: Utilizing Chebyshev, Legendre, and Hermite Polynomials;XAI-Based Assessment of Software Vulnerabil

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Performance Enhancement and Secrecy Analysis of Hybrid RF/FSO Communication Links Under Combined κ-μ Fading and Exponential Turbulence Conditions

Performance Enhancement and Secrecy Analysis of Hybrid RF/FS...

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Computational Intelligence, Communication Technology and Networking (CICTN), international conference on

作者： Deepak Upadhyay Prakhar Prakhar Rashmy Moray Rashmi Sharma Nookala Venu Shipra Shukla Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of CSE Roorkee Institute of Technology Pune India Symbiosis Institute of Management Studies (SIMS) A Constituent of Symbiosis International Deemed University Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India Dept. of CSE (Data Science) G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

In this study, the secrecy performance evaluation of hybrid RF/FSO communication systems over κ-μ fading and exponential turbulence channels are conducted. We analyse the secure information rate and evaluate the throughput and secrecy capacity of the system through simulations. The results indicate that the proposed hybrid system improves reliability and security by combining adaptive modulation, beamforming, and encryption to combat interference and secure data transmission. Geographical heat maps help to visualize the influence of environmental factors on system performance. Federated learning in hybrid RF/FSO systems have been investigated in detail through simulations and numerical results to show the considerable improvements in communication reliability and performance that the increased redundancy and robustness of the hybrid scheme provides. This helps gain valuable insights into a better design of wireless networks in the future by highlighting the benefits of hybrid communication techniques and simulation-driven design to enhance performance and security across diverse complex environments and conditions.

关键词： Fading channels Analytical models Adaptation models Array signal processing Atmospheric modeling Computational modeling Modulation Throughput Encryption Security

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Computational Approaches to Molecular Dynamics simulation for Drug Design and Discovery

Computational Approaches to Molecular Dynamics Simulation fo...

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Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： S. Mohamed Rabeek Ningaraj Belagalla Kanchan Khare Shirish Kumar Kodadi Jonnala Subba Reddy Mohsina Bano Shaik PG and Research Department of Chemistry Jamal Mohamed College (Autonomous) Affiliated to Bharathidasan University Tamil Nadu India Department of Entomology School of Agriculture SR University Ananthasagar Warangal Telangana India Jabalpur Engineering College Madhya Pradesh India Department of Chemistry St. PETER'S ENGINEERING COLLEGE Hyderabad Telangana India Lakireddy Bali Reddy College of Engineering Mylavaram NTR (Dt) Andhra Pradesh India Department of Pharmaceutical Chemistry College of Clinical Pharmacy Imaam Abdulrahman Bin Faisal University Dammam

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Since they offer profound insights into the atomic-level interactions between drug candidates and their biological targets, molecular dynamics (MD) simulations have become extremely effective computational tools for drug design and discovery. MD simulations allow for the estimation of binding affinities, conformational modifications, and the investigation of possible binding sites by simulating the dynamic behaviour of biomolecules over time. These simulations now run much faster and are more accurate thanks to recent improvements in computing power, improved algorithms, and machine learning incorporation. Methods like adaptive sampling and accelerated MD further maximise resource utilisation, making it easier to simulate intricate biological processes in realistic timescales. Furthermore, opportunities for accurate electronic structure analysis have been created by combining MD with quantum mechanical techniques. This presentation highlights how computational methods in MD simulations for drug design can revolutionise the process by supplying crucial information for structure-based drug discovery and promoting the creation of new therapeutic agents with improved efficacy and selectivity.

关键词： Drugs computers Computational chemistry Adaptation models Accuracy Computational modeling Biological system modeling Aerodynamics Drug discovery Bioinformatics

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Osmotic Computing Based Secure Resource Orchestration Scheme for Vehicular Communication

Osmotic Computing Based Secure Resource Orchestration Scheme...

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international Communication Systems and Networks and Workshops, COMSNETS

作者： Deepanshu Garg Mohit Angurala Rasmeet S Bali Neeraj Kumar Computer Science & Engineering Department Chandigarh University India Computer Science Department Guru Nanak Dev University India Computer Science & Engineering Department Thapar University Patiala India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

The advancement in technology leads to provide an efficient communication among vehicles to offload resource-intensive tasks for transportation-based services. However, it may cause issue related to efficient secure resource utilization among vehicular nodes. The key reason behind these considerations are the high mobility of vehicles and their high computational requirements for task execution. To solve these issues, an osmotic computing based vehicular communication scheme has been proposed. The primary objective of the scheme is to provide a communication model which can perform effective secure resource management among static or dynamic vehicular nodes through Osmotic Computing. By utilizing the key components of osmotic computing such as osmotic resource manager and node manager, numerous resources have been shared with the vehicles in an effective way. The performance of the proposed scheme has been evaluated using simulation. Results obtained show that the proposed scheme outperform the existing schemes in terms of various performance evaluation parameters.

关键词： Performance evaluation Communication systems Computational modeling Data dissemination Decision making Dynamic scheduling Data models Resource management Reliability Vehicle dynamics

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Leveraging Python Interpreters for Concurrency in SeQUeNCe 22nd

Leveraging Python Interpreters for Concurrency in SeQUeNCe

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22nd international conference on Scientific Computing and Bioinformatics, CSC 2024, and 25th international conference on Computational Biology, BIOCOMP 2024, held as part of the World Congress in computer Science, computer Engineering and Applied Computing, CSCE 2024

作者： Martin, Brett M. Hodson, Douglas D. Grimaila, Michael R. Department of Electrical and Computer Engineering U.S. Air Force Institute of Technology WPAFB DaytonOH45433 United States Department of Systems Engineering U.S. Air Force Institute of Technology WPAFB DaytonOH45433 United States

ISBN: (纸本)9783031859014

With the advent of the Navy Research Laboratory’s announcement of the establishment of the Washington D.C. Metropolitan Quantum Research Consortium (DC-QNet), there has been much interest in the modeling and simulation of the quantum communication network testbed. To that end, we explore in this research the basic functionality of the Simulator of QUantum Network Communication (SeQUeNCe), the developmental Python/C API Interpreters module, and their viability as technologies to be used for high-performance simulation of quantum networks. In this paper, we outline the integration of sub-interpreters with a parallel SeQUeNCe experiment to demonstrate true multi-threading concurrency in quantum network simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quantum communication

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Multi-Scale Electrothermal Co-simulation of GaN HEMTs at the Device and Packaging Levels

Multi-Scale Electrothermal Co-Simulation of GaN HEMTs at the...

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Thermal, Mechanical and Multiphysics simulation and Experiments in Micro-Electronics and Micro-Systems EuroSimE

作者： Yi Zhang Ziyue Zhang Yuchao Wu Zhiying Chen Dong Lu Ke Xue Renjie Wang Smart Manufacturing Thrust HKUST(GZ) Guangzhou China Microelectronics Thrust HKUST(GZ) Guangzhou China College of Future Technology HKUST(GZ) Guangzhou China

ISBN: (数字)9798350393002

ISBN: (纸本)9798350393019

Gallium Nitride High Electron Mobility Transistors (GaN HEMTs) are critical for high-power and high-frequency applications but face challenges from self-heating and inadequate thermal management, which degrade performance and reliability. Existing tools like Technology computer Aided Design (TCAD) and finite element analysis (FEA) lack integrated electrothermal coupling capabilities. This study proposes a multi-scale electrothermal co-simulation framework to bridge device-level electrical behavior and packaging-level thermal dynamics. The methodology integrates 2D TCAD simulations for localized Joule heating in the two-dimensional electron gas (2DEG) region with 3D FEA modeling to evaluate heat dissipation across packaging structures. An iterative loop couples the electrical power density from TCAD into FEA as averaged heat sources, updating boundary conditions until thermal convergence is achieved. Key innovations include a deep neural network (DNN) to resolve highly localized heat distributions from TCAD data and an equivalent thermal conductivity model for computational efficiency. The multi-scale approach successfully captured electrothermal interactions, enabling optimized packaging designs and material adjustments to balance heat generation and power efficiency. This work demonstrates the necessity of a coupled simulation for accurate performance prediction and thermal management in GaN HEMTs, offering a pathway to enhance reliability in high-power applications.

关键词： Heating systems Performance evaluation Temperature distribution Solid modeling HEMTs Packaging Electronic packaging thermal management Thermal management MODFETs Gallium nitride

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Protecting Privacy and Securing Smart Home Network based on Zero Trust Network Approach

Protecting Privacy and Securing Smart Home Network based on ...

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Advanced Innovations in Smart Cities (ICAISC), international conference on

作者： Maryam A. Alghamdi Rahmat Budiarto Dept. of Computer Science College of Computing and Information Albaha University Alaqiq Saudi Arabia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

The main goal of utilizing IoT technology in smart homes is to enhance convenience and flexibility. However, despite the numerous benefits, there are certain vulnerabilities and flaws that can jeopardize security and privacy. This research explores how Zero Trust Network (ZTN) technology can be implemented in smart homes to address crucial objectives such as privacy and security. The study focuses on developing and continuously verifying a ZTN-based system. A key challenge addressed in the research is optimizing security by categorizing home resources and devices based on their importance. To improve the efficiency of verification, authorization, and authentication processes, the research proposes algorithms that utilize Attribute-based Access Control (ABAC) and Elliptic Curve Cryptography (ECC). The simulation results demonstrate that in a Device-to- Device scenario, the attack detection success rates using ABAC and ECC are 87.28% and 94.30%, respectively. These findings suggest that implementing a Zero Trust Network in smart homes can significantly enhance security and privacy for homeowners, protecting them from potential attacks.

关键词： Authorization Adaptation models Privacy Analytical models Authentication Smart homes Elliptic curve cryptography Zero Trust Security Context modeling

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IMC Based PID Controller for Spherical Tank Liquid Level Control

IMC Based PID Controller for Spherical Tank Liquid Level Con...

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AIML-Applications for Engineering & Technology (ICAET), international conference on

作者： C. B. Kadu V. P. Bhosale P. S. Vikhe V. V. Mandhare Department of Instrumentation & Control Engineering Pravara Rural Engineering College Loni India Department of Computer Engineering Pravara Rural Engineering College Loni India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

In the process industries, it's hard to control a non-linear process. Nonlinear behavior is frequently seen in real processes. The challenging problem of controlling a spherical tank is result of its nonlinearity caused by the continuously varying cross section. An IMC-based PID controller is employed to improve efficiency of controlling the level of spherical tanks which exhibit nonlinear dynamics. For processes up to second-order with dead time and first-order numerator dynamics, a single tuning parameter will be offered. The process model is determined employing mathematical modeling and standard step response-based system identification. The laboratory model of an interacting and non-interacting nonlinear system is introduced, which is capable of performing more complex tasks. To verify the effectiveness of the suggested IMC based PID controller, results of real-time experiments and a simulation study on spherical tank level control are incorporated.

关键词： Process control Real-time systems Mathematical models Regulation Nonlinear dynamical systems System identification Reliability Level control Tuning Standards

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SBL Algorithms for the Multiple Measurement Vector Problem: New modeling and Inference Methods

SBL Algorithms for the Multiple Measurement Vector Problem: ...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Vinay Kanakeri Florian Meyer Bhaskar D. Rao Department of Electrical and Computer Engineering University of California San Diego

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper introduces new and practically relevant non-Gaussian priors for the Sparse Bayesian Learning (SBL) framework applied to the Multiple Measurement Vector (MMV) problem. We extend the Gaussian Scale Mixture (GSM) framework to model prior distributions for row vectors, exploring the use of shared and different hyperparameters across different measurements. We propose Expectation Maximization (EM) based algorithms to estimate the parameters of the prior density along with the hyperparameters. To promote sparsity more effectively in a non-Gaussian setting, we show the importance of incorporating learning of the parameters of the mixing density. Such an approach effectively utilizes the common support notion in the MMV problem and promotes sparsity without explicitly imposing a sparsity-promoting prior, indicating the methods’ robustness to model mismatches. Numerical simulations are provided to compare the proposed approaches with the existing SBL algorithm for the MMV problem.

关键词： GSM Signal processing algorithms Signal processing Numerical simulation Vectors Inference algorithms Robustness Numerical models Bayes methods Speech processing

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LUT-Optimized Decoding of QC-LDPC Codes for Flash Memory with EoL Layers Variation Model

LUT-Optimized Decoding of QC-LDPC Codes for Flash Memory wit...

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Digital Signal Processing and its Applications (DSPA), international conference on

作者： Yury A. Zamaraev Vasiliy S. Usatyuk Sergey I. Egorov R&D Department T8 Moscow Russia Department of Computer Science South-West State University Kursk Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

NAND flash memory is a pivotal technology in contemporary data storage, but its reliability diminishes due to retention noise and wear-out effects. This paper proposes a novel decoding optimization for Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes tailored for NAND flash memory. The methodology incorporates Lookup Table (LUT)-based reconstruction and quantization, complemented by adaptive read threshold adjustments at the End-of-Life (EoL) stage. Key contributions include a Reconstruction Computation Quantization (RCQ) decoder, which achieves reduced computational and routing complexity through a two-stage optimization process, and a dynamic read threshold adjustment mechanism addressing layer-to-layer variation to improve error correction under evolving threshold voltage distributions. simulation results demonstrate enhanced reliability and performance, with improvements in Raw Bit Error Rate (RBER) of over 0.004 and a throughput-to-area ratio increase of up to 16%. Additionally, the proposed approach extends the endurance of TLC 3D NAND memory by over 30% at a fixed error probability compared to single-layer model and 12% compared to the Neural Network model. This work offers a step forward in improving SSD reliability at the EoL stage.

关键词： Solid modeling Quantization (signal) Three-dimensional displays Computational modeling Noise Threshold voltage Decoding Reliability Flash memories Optimization

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