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Optimization of Cooperative RelayingMolecular communications for Nanomedical Applications

computer Modeling in engineering & Sciences 2024年第2期138卷 1259-1275页

作者： Eman S.Attia Ashraf A.M.Khalaf Fathi E.Abd El-Samie Saied M.Abd El-atty Konstantinos A.Lizos Osama Alfarraj Heba M.El-Hoseny Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61111Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer science The Higher Future Institute for Specialized Technological StudiesEl ShoroukEgypt

Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)***,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is *** this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift *** fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)*** the previous work,the probability of bit error is expressed in a closed-form *** is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano *** simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

关键词： Nanomedical system molecular communication cooperative relay optimization

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Efficient Classification of Rice Varieties Using Optimized Convolutional Neural Networks 8

Efficient Classification of Rice Varieties Using Optimized C...

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8th IEEE International Conference on Information and communication Technology, CICT 2024

作者： Pathak, Abhishek Kumar Singh, Ankit Kumar Bhatia, Vimal Singh, Puneet Indian Institute of Technology Department of Electrical Engineering Indore India Motihari College of Engineering Department of Computer Science and Engineering India

ISBN: (纸本)9798331531539

Rice type classification is a crucial task in agri-cultural automation, aimed at improving quality control and ensuring market standards. This study presents a deep learning-based approach using a optimized Convolutional Neural Network (CNN) model implemented with PyTorch to classify five rice varieties: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. Our proposed model diverges from conventional methods that rely heavily on complex machine learning algorithms or pretrained CNN architectures like MobileNetV2, VGG16, EfficientNetB0 etc., which require a large number of parameters and layers, re-sulting in increased computational complexity. Through proposed approach, we achieved a remarkable 99.81% validation accuracy and a minimal validation loss of 0.01 % with a significantly reduced model size 30.76 MB. The simplicity of the proposed CNN architecture not only enhances computational efficiency but also maintains high accuracy, making it a viable solution for rice type classification in practical applications. This study demonstrates that a fine-tuned CNN model can outperform more complex models, providing an efficient and effective alternative for agricultural classification tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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A New MRACS Approach for High-order System Following Low-order Model Using State Variables Taking from the Model

A New MRACS Approach for High-order System Following Low-ord...

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2024 International Conference on Advanced Control Systems and Automation Technologies, ACSAT 2024

作者： Wei, Yongdong Liu, Xiaojing Kong, Jiayi Cheng, Zixuan Fang, Wen Beijing Institute of Graphic Communication Department of Mechanical and Electrical Engineering Beijing102600 China

ISBN: (纸本)9798331541668

This paper proposes a model reference adaptive control system (MRACS) approach for high-order systems that are required to follow a low-order model, utilizing state variables derived from the model itself. Drawing from Popov hyperstability theory, the method addresses several critical challenges in control system design. The MRAC strategy is employed to tackle the issue of unmeasurable plant states, enabling the control system to adaptively adjust despite the lack of direct state measurement. This adaptation is crucial in maintaining system stability and performance in the presence of uncertainties. To enhance the robustness of the control system, an adjustable linear compensator is introduced. This compensator alleviates the need for the assumption of strictly positive real conditions, which is often a limitation in traditional control methods. By incorporating this flexible compensation mechanism, the proposed approach ensures better handling of various system dynamics and uncertainties, thereby increasing the overall reliability of the control system. The effectiveness of the proposed MRACS approach is substantiated through comprehensive digital simulation results. These results demonstrate that the controlled object is capable of closely following the output of the reference model, highlighting the robustness and adaptability of the method. This capability is particularly advantageous in practical engineering applications, where precision and reliability are paramount. © 2024 IEEE.

关键词： Model reference adaptive control

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Automatic emotion recognition using deep neural network

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Multimedia Tools and Applications 2025年 1-30页

作者： Sujatha, R. Chatterjee, Jyotir Moy Pathy, Baibhav Hu, Yu-Chen School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of CSE Graphic Era University Dehradun India School of Electrical Engineering Vellore Institute of Technology Vellore India Department of Computer Science Tunghai University Taichung City Taiwan

Emotions are a vital semantic part of human correspondence. Emotions are significant for human correspondence as well as basic for human–computer cooperation. Viable correspondence between people is possibly achieved when both the importance and the emotion of the correspondence are perceived by all groups included. Understanding the significance of language has generally been concentrated on in natural language processing (NLP) as a semantic examination. In NLP, the text can be handled appropriately for classification. Emotion detection from facial emotion is the subfield of social signal processing applied in a wide assortment of regions, explicitly for human and PC collaboration. Many researchers have proposed various approaches, generally utilizing machine learning concepts. Automatic emotion recognition (AER) is significant for working with consistent intuitiveness between a person and a smart device toward fully acknowledging an intelligent society. Many researchers examined cross-lingual and multilingual speech emotion as a stage toward language-free emotion acknowledgment in natural speech. In the present work, we are proposing a deep learning-based AER system using four openly accessible datasets, namely Basic Arabic Vocal Emotions Dataset (BAVED), Acted Emotional Speech Dynamic Database (AESDD), Urdu written in Latin/Roman Script (URDU), and Toronto Emotional Speech Set (TESS), by utilizing the Jupyter notebook and a Python library for music and audio synthesis named Librosa. The experimental results exhibited that the proposed approach achieves better than the existing approaches, i.e., the accuracy of the proposed system with the URDU dataset is 96.24%, the TESS dataset is 99.10%, the AESDD dataset is 65.97%, and the BAVED dataset is 73.12%. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantics

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Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

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Digital communications and Networks 2023年第6期9卷 1458-1464页

作者： Hemant Kumar Narsani Ali Ranjha Kapal Dev Fida Hussain Memon Nawab Muhammad Faseeh Qureshi Faculty of Engineering and Technology University of SindhPakistan Department of Electrical Engineering Ecole de Technologie Superieure Montreal QCCanada Department of Institute of Intelligent Systems University of JohannesburgSouth Africa Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Computer Education Sungkyunkwan UniversitySeoulRepublic of Korea

Unmanned Aerial Vehicles(UAVs)will be essential to support mission-critical applications of Ultra Reliable Low Latency communication(URLLC)in futuristic Sixth-Generation(6G)***,several security vulnerabilities and attacks have plagued previous generations of communication systems;thus,physical layer security,especially against eavesdroppers,is vital,especially for upcoming 6G *** this regard,UAVs have appeared as a winning candidate to mitigate security *** this paper,we leverage UAVs to propose two *** first method utilizes a UAV as Decode-and-Forward(DF)relay,whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver ***,we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception,*** secrecy rate,and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF ***,simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height,blocklength,decoding error probability and transmitter-receiver separation ***,we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

关键词： URLLC UAV-Assisted communications 6G systems Secrecy rate

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Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

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computers, Materials & Continua 2024年第9期80卷 4791-4812页

作者： Ahmad Yahiya Ahmad Bani Ahmad Jafar Alzubi Sophers James Vincent Omollo Nyangaresi Chanthirasekaran Kutralakani Anguraju Krishnan Department of Accounting and Finance Faculty of BusinessMiddle East UniversityAmman11831Jordan Faculty of Engineering Al-Balqa Applied UniversitySalt19117Jordan Department of Mathematics Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo210-40601Kenya Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Electronics and Communication Engineering Saveetha Engineering College(Autonomous)Chennai602105India Department of Computer Science and Engineering Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.

关键词： Human action recognition multi-modal sensor data and signals adaptive hybrid deep attentive network enhanced archerfish hunting optimizer 1D convolutional neural network gated recurrent units

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Binary Particle Swarm Optimization for Design of a Reconfigurable Transmissive Unit Cell

Binary Particle Swarm Optimization for Design of a Reconfigu...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Roy, Saurav Vinoy, K.J. Department of Electrical Communication Engineering Indian Institute of Science Bengaluru Karnataka Bengaluru India

ISBN: (纸本)9798350379693

Ensuring connectivity between pixels and the switching element on a pixelated unit cell is challenging using binary particle swarm optimization (BPSO). Here, a design approach is formulated to utilize BPSO for a reconfigurable unit cell design, and then a novel random walk-based initialization is proposed to reduce computation cost. The proposed initialization scheme has shown several-fold improvement in the computation time. This approach may be extended for metasurface unit cell designs for various other applications. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Islanding Detection in PV-Grid System by Random Forest and Spectrogram Based LBP 3

Islanding Detection in PV-Grid System by Random Forest and S...

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3rd Odisha International Conference on electrical Power engineering, communication and Computing Technology, ODICON 2024

作者： Singh, Ritu Shukla, S.P. Panda, Archana Sahoo, Subhendu Sekhar Pati, Subhendu Panigrahi, Basant K Bhilai Institute of Technology Department of Electrical Engineering Durg India Soa Deemed to Be University Department of Electronics and Communication Engineering Bhubaneswar India Gandhi Institute for Technology Department of Electrical Engineering Bhubaneswar India Soa University Department of Electrical Engineering Iter Bhubaneswar India

ISBN: (纸本)9798350354379

Islanding is a significant obstacle along with excessive penetration of DG sources. The islanding could cause harm to the customers and their equipment's. The IEEE 1547 DG interconnection regulations stipulate that the DG must be disconnected and the islanding must be observed within two seconds. Basically, this paper presents a novel method for detecting islanding based upon image pattern recognition using random forest (RF) classification technique is proposed. Images are utilized to derive the local binary pattern (LBP) characteristics so as to identify non-islanding as well as islanding events. Hence, the time series signal is obtained and transformed into spectrogram images at the point of common connection. These images are utilized to extract the features using histogram of oriented gradient, which is then utilized as a feature vector input for the RF classifier for training as well as testing. It uses rate of change of negative sequence voltage parameter to derive spectrogram image. The RF classifier's effectiveness is assessed with 5-fold cross-validations. The results from classification demonstrates that detection of islanding using RF classifier and LBP feature being used for image pattern recognition achieved excellent results with 98.25% accuracy and detection time of 182 milliseconds. © 2024 IEEE.

关键词： Spectrographs

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Multi-objective Cluster-head-based Energy-aware Routing using a Separable Convolution Neural Network in a Wireless Sensor Network

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IEIE Transactions on Smart Processing and Computing 2024年第2期13卷 105-112页

作者： Ather, Danish Mary, J. Prisca Singh, Pooja Garg, Kanika Priyadharshini, T.R. Princy, B. Anni Tiwari, Mohit Department of IT and Engineering Amity University in Tashkent Uzbekistan Department of Computer Science and Engineering NPR College of Engineering and Technology Tamil Nadu Dindigul India Department of Physics Faculty of Science SGT University Haryana Gurugram India Department of Computer Science and Engineering SRM Institute of Science and Technology NCR Campus Ghaziabad Modinagar India Department of Information Technology Hindusthan College of Engineering and Technology Pollachi main road Coimbatore India Department of Computer and Communication Panimalar Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering Delhi India

Wireless sensor network (WSN) applications are added day by day owing to numerous global uses (by the military, for monitoring the atmosphere, in disaster relief, and so on). Here, trust management is a main challenge. Sensor nodes are important in wireless sensor networks, but they are easily depleted because of their short lifespan from continuous sensing activity and low battery capacity. So efficient energy utilization is a challenging task in a WSN. To minimize energy loss, clustering with an optimum path selection process is needed to retain energy in sensor nodes. This manuscript proposes multi-objective Pelican Optimization Algorithm (POA) routing to maintain energy efficiency and minimize transmission distances in wireless sensor networks. A cluster head (CH) is selected by using a Separable Convolution Neural Network (SCNN). Simulation outcomes prove the proposed technique attains 22.3% and 25.04% improvements in energy consumption when compared to the Multi-Objective CH Energy-aware Optimized Routing Approach at WSN (MOCH-EORA-WSN) and Multiple Optimum Cluster Head Multi-Objective Grasshopper Optimization with Harmony-search at WSN (MOCH-MOGOH-WSN), respectively. © 2024 institute of Electronics Engineers of Korea. All rights reserved.

关键词： Energy utilization

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A Comprehensive Investigation of GaSb/GaAs0.5Sb0.5/GaAs based Double Gate Source-Pocket Engineered Heterogeneous Gate Dielectric Vertical TFET for Optimized Low-Power Applications 6

A Comprehensive Investigation of GaSb/GaAs0.5Sb0.5/GaAs base...

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6th International Conference on electrical engineering and Information and communication Technology, ICEEICT 2024

作者： Mahbub, Lamiya Masud Badhon, Mehrab Ibne Sultana, Sunjida Saha, Riya Military Institute of Science and Technology Department of Electrical Electronic and Communication Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385779

Recognizing the simplified fabrication and advanced performance of Vertical Tunnel Field Effect Transistors (VTFET) compared to Lateral TFET, numerous research has been con- ducted. In this study, a comparative analysis was performed on two double gate heterojunction source-pocket engineered VTFETs with and without heterogeneous cascaded gate dielectric using ATLAS SILVACO TCAD software. Highly doped GaSb as source intensifies the tunneling rate. GaAs0.5Sb0.5 as source pocket reduces lattice mismatch and increases Ion. The research indicates that using High-? and & Low-? thick gate dielectrics at source and drain ends reduces average subthreshold swing (SSavg), enhances transconductance(gm), and amplifies Ion/Ioff ratio exponentially. This research examines Analog/RF and DC performances of VTFET to optimize crucial device parameters. The heterogeneous gate dielectric structure incorporating HfO2 showed an improved Ion of 1.1 10-5 A/ m, diminished leakage current Ioff of 1.05 10-17 A/ m, SSavg of 19.6 mV/dec, highest Ion/Ioff ratio of 1.04 1012 and gm of 45 S. The analysis revealed that the study is appropriate for assessing low-power applications with increased performance and also has a great potential for broadening the realm of vertical TFETs. © 2024 IEEE.

关键词： Electric fields

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