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Event and Anomaly Detection and Classification in Cyber-Physical Power System 4

Event and Anomaly Detection and Classification in Cyber-Phys...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Kabir, Shaharier Paul, Hridoy Anjum, Md. Samin Rahman Zishan, Md. Saniat American International University-Bangladesh Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331530938

Integrating digital and physical components in modern power grids has created new vulnerabilities, particularly from False Data Injection Attacks (FDIA). this complexity has also opened avenues for sophisticated cyberattacks, particularly False Data Injection Attacks (FDIA), which pose a significant threat to the stability and security of smart power grids. this research presents a novel approach to anomaly detection within the IEEE 39 bus system, with a specific emphasis on identifying FDIA in smart power grids. Leveraging the capabilities of Autoencoder-Long Short-Term Memory (LSTM) models, our study introduces a hybrid methodology that combines feature extraction, dimensionality reduction, and advanced classification techniques to enhance the accuracy and efficiency of anomaly detection. the proposed approach addresses the limitations of existing methods by effectively distinguishing between normal and malicious activities in the power grid, thereby mitigating the risks associated with FDIA. Extensive simulations were conducted to validate the effectiveness of our approach, demonstrating its superior performance in detecting anomalies within the power system. the results indicate a marked improvement in detection accuracy, highlighting the potential of the proposed method as a robust solution for safeguarding smart power grids against cyber threats. © 2025 IEEE.

关键词： Smart power grids

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Deep Learning-Based Brain Tumor Detection and Classification Using VGG16 4

Deep Learning-Based Brain Tumor Detection and Classification...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Shib, Sowrov Komar Dipto, Durjoy Roy Rahman, Md Tanvir Shufian, Abu American International University-Bangladesh Dept. of Electrical & Electronic Engg. Dhaka Bangladesh

ISBN: (纸本)9798331530938

the early perception of brain tumors is a crucial endeavor for neurologists and radiologists. Identifying and segregating brain tumors from Magnetic Resonance Imaging (MRI) scans is a strenuous, time-intensive process susceptible to delusion. To overcome these obstacles, this study introduces a deep learning-based framework that utilizes the VGG16 architecture for improved brain tumor perception and codification. the system categorizes MRI images into four distinct groups: glioma, meningioma, pituitary, and no tumor. To enhance the quality of input data and minimize overfitting, advanced preprocessing techniques, including resizing, normalization, and data augmentation, were employed. the VGG16 model, fine-tuned using hyperparameter optimization and transfer learning, extracts critical features to ensure accurate classification. A thorough evaluation on diverse datasets demonstrated the model's robust performance, achieving an validity of 96% while excelling in precision, recall, and F1-score. By addressing challenges related to limited dataset size and computational complexity, this study presents a scalable and automated approach for accurate tumor detection, significantly improving diagnostic efficiency and enabling timely clinical interventions. © 2025 IEEE.

关键词： Magnetic resonance imaging

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Development and Performance Analysis of Darrieus and Savonius Turbines Using QBlade 4

Development and Performance Analysis of Darrieus and Savoniu...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Apu, Arnendu Roy Mazumder, Gour Chand Dey, Dhiman Ashiquzzaman, Md. Pathik, Bishwajit Banik Ghosh, Himangshu Ranjan Institute of Energy University of Dhaka Dhaka Bangladesh American International University-Bangladesh Dept.of Eee Dhaka Bangladesh

ISBN: (纸本)9798331530938

In this research a vertical-axis wind turbine (VAWT-Darrieus type) is designed and optimized using QBlade software based on three design parameters. three types of airfoils have been chosen to find out the suitable design to make three-bladed Darrieus type VAWT. A Savonius type VAWT was developed practically to characterize the developed generator coupling arrangement. this Darrieus type was simulated and optimized using Qblade. A practical test was done to compare the electrical and mechanical power, thrust of both turbines using a wind tunnel. After simulation, it was found that the Darrieus type VAWT with 1 meter height, 0.75-meter radius and 0.075-meter chord length with 75° circular angle made by 'DU 06-W-200' airfoil has better coefficient of performance. On the other hand, the Savonius type VAWT having 0.37 meter and a radius of 0.11 meter showed 0.0006 Watt electrical power and 5.8844 Watt mechanical power at 4 m/s. Savonius type wind turbine with 0.37 meter height and 0.11 meter radius is applicable for low speed whereas larger 1 meter Darrieus type could be the proper choice. © 2025 IEEE.

关键词： Wind tunnels

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Optimal Sizing of Autonomous Microgrid Using Osprey Optimization Algorithm 4

Optimal Sizing of Autonomous Microgrid Using Osprey Optimiza...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Sagor, Abidur Rahman Ahmad, Shameem Ahmed, Abir Hazari, Rifat Jahan, Effat Hossain, Chowdhury Akram Ogliari, Emanuele Mannan, Mohammad Abdul American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh American International University-Bangladesh Faculty of Engineering Department of Computer Engineering Dhaka1229 Bangladesh Politecnico di Milano Department of Energy Milano20156 Italy

ISBN: (纸本)9798331530938

this paper proposes an optimal size for an autonomous microgrid to satisfy the electrical load demand. the microgrid will comprise many different configurations, such as photovoltaic module, diesel generators, and energy storage technologies. By considering operational constraints to optimize the cost of energy (COE) and life cycle cost (LCC), the Osprey optimization algorithm (OOA) is applied. Furthermore, identify the most economically feasible technology that will ensure a continuous power supply, an economic study of three different energy storage technologies-namely, batteries, hydrogen storage systems, and supercapacitors-is also conducted. Additionally, provide a case study of Manpura island microgrid that validates the proposed approach. the results show that the OOA method in terms of optimal system performance and convergence speed, the loss of power supply probability is set at 0%, the LCC is 196915, the COE is 0.2959 /kWh, and the amount of GHG is 430 kgs/year. © 2025 IEEE.

关键词： Microgrids

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4th international conference on Smart Multimedia, ICSM 2024

4th International Conference on Smart Multimedia, ICSM 2024

引用

4th international conference on Smart Multimedia, ICSM 2024

ISBN: (纸本)9783031824746

the proceedings contain 27 papers. the special focus in this conference is on Smart Multimedia. the topics include: Electrical Impedance Spectroscopy Sensorised Needle for Prostate Cancer Localisation During MRI-Ultrasound-Fused Targeted Biopsy;semantic Browsing & Advertising in YouTube;creating and Analyzing a Multimedia Dataset for Building Energy Efficiency Estimation;affine-Transformation-Invariant image Classification by Differentiable Arithmetic Distribution Module;Performance of Machine Learning Models for OSA Detection Based on ECG signal;the Role of Personality Traits for Tailoring Immersive Experiences in Virtual Reality Environments;a Novel Framework for Assessing Products Case Study: Electric Drives for Terrestrial Vehicles;Innovating Medication Adherence for Smart Cities: Leveraging PERACTIV and Automated Annotation Pipeline for Innovative Solutions;how to Design Intuitive Flight Controls for Novice Onboard Operators?;sliding Adaptive Dynamic Time Warping for Segment Matching in Surgical Simulation Data;concept Factorization with Manifold and Orthogonal Constraint for Data Representation;image Based Cattle Monitoring System;comparative Assessment of Recent Pedestrian Detectors and Trackers;AF Mask R-CNN: Attention Fused Mask R-CNN Mechanism for Instance Segmentation;automatic Data Labeling Using Large Language Models;Overview of Future Video Compression Technology Beyond VVC in Standard;neural Fields for Multimedia Applications (Part-1): Trends in Audio, images and Videos;neural Fields for Multimedia Applications (Part-2): Trends in Volumetric Videos and 3D Objects;characterizing Multimedia Information Environment through Multi-modal Clustering of YouTube Videos;surveying Sidewalk Materials For and By Individuals Who Are Blind or Have Low Vision: Audio Data Collection and Classification;two-Stage Synthetic Supervising and Multi-view Consistency Self-supervising Based Animal 3D Reconstruction by Single image;local Force Isotropy: A New Metric for Measuri

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Enhanced Economic Load Dispatch in Smart Grid through Pelican Optimization Algorithm 4

Enhanced Economic Load Dispatch in Smart Grid Through Pelica...

引用

4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Rofique, Ruham Ahmed, Kazi Firoz Ahmad, Shameem Himu, Suprio Saha Shatil, Abu Hena Hazari, Md. Rifat Jahan, Effat American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331530938

the efficient management of Economic Load Dispatch (ELD) in microgrids is crucial for optimizing energy costs, maintaining grid stability, and integrating renewable energy sources. this paper proposes a method of enhancing the ELD in a multi-microgrid system using the Pelican Optimization Algorithm (POA), tested on IEEE-14 bus system. Here, the objective function includes reduction of line losses, optimization of cost efficiency and reserve generation, enhancement of grid stability, and maximization of power generation for achieving optimal ELD. Further performance of the proposed POA method for ELD enhancement is compared with Moth-Flame Optimization (MFO) and Particle Swarm Optimization (PSO). Additionally, POA provides enhanced operational stability with lower variability in power output and maintenance costs, making it a superior choice for optimizing microgrid operations. the results highlight that POA outperforms MFO, achieving a 45.4% reduction in power generation costs and a 56.3% increase in power output for certain units. Moreover, the comparative analysis underscores the superiority of POA in managing microgrid operations, offering a promising solution for future energy management challenges. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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Machine vision and image processing for intelligent online monitoring and control of pharmaceutical fluidized bed granulation processes 4

Machine vision and image processing for intelligent online m...

引用

4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Liu, Yan Wu, Tao Wang, Xue Zhong Beijing Key Laboratory of Enze Biomass Fine Chemicals College of New Materials and Chemical Engineering Beijing Institute of Petrochemical Technology Beijing102617 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Fluidized bed granulation is a unit operation widely used in the pharmaceutical, chemical and food processing industries. It is a manufacturing technology that by suspending lose powders using hot air and transforms the powders into granules of uniform sizes to improve compaction and flow characteristics. the granule size distribution and moisture content are important quality indicators that are currently characterized by sampling and offline analysis in the laboratory, leading to time delay in measurement. this work reports an investigation of machine vision combined with deep learning image segmentation for on-line real-time monitoring. A non-invasive microscopic imaging probe with an integrated light source is designed and mounted on the granulator’s sight glass to monitoring the granule dynamic changes in particle morphology and size. In addition, a near-infrared spectrometer combined with chemometric modeling is used for real-time monitoring of moisture content. © 2025 SPIE.

关键词： Near infrared spectroscopy

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A Correlative Abstraction Between the Scenario of No-Retransmission and Retransmission Process by Utilizing Evolutionary Game theory for Self-Organized Data Aggregation Mechanism 4

A Correlative Abstraction Between the Scenario of No-Retrans...

引用

4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Kader, Md. Salehin Ferdous Shovon, S M Tanvir Hassan Nahar, Aminun Kar, Tonny Shekha Dhaka Bangladesh American International University-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798331530938

Successive data connectivity is very important for delivering data from one point to another. But sometimes there is no successive data connectivity between the two points. A delay tolerant network (DTN) is one of the best ways to provide data connectivity with no end-to-end connection using self-organized data aggregation techniques. Here, a better strategy (to become sender or aggregator) is selected by the Evolutionary Game theory approach. Special Data Custody Nodules (called Aggregators) are responsible for keeping and holding data until the message ferry visits and collects data from aggregators to deliver it to sink nodules. this message ferry approach is only applicable where there are multiple clusters involved. the choice of strategy-deciding between becoming an aggregator or a sender-is examined using the principles of Evolutionary Game theory. In this context, each nodule assesses its outcomes following interactions with others. To facilitate strategy selection, we can utilize different ordinances from Evolutionary Game theory, such as the Imitation Reform Ordinance, along with the Birth-Death and Death-Birth Reform Ordinances with two different processes named by no retransmission and retransmission. In this recent paperwork, we will compare these two processes for plan of action with the Imitation Reform Ordinance, Birth-Death, and Death-Birth Reform Ordinances. © 2025 IEEE.

关键词： Game theory

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Evaluating the Effectiveness of ML Algorithms in Water Potability Prediction Aligned with SDGs 4

Evaluating the Effectiveness of ML Algorithms in Water Potab...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Ullah Miah, Saef Bhowmik, Abhijit Alam, Tahmid Ahona, Sifat Rahman American International University-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798331530938

this research addresses the critical need for accurate water quality prediction, aligning with Clean Water and Sanitation (SDG 6) and Good Health and Well-being (SDG 3). Utilizing a diverse dataset of water quality attributes, we developed and evaluated multiple machine learning models to predict water potability, contributing to SDG 9 (Industry, Innovation, and Infrastructure) through technological advancement. Our primary contribution is a Hyperparameter-Tuned Histogram Gradient Boosting Classifier, which outperformed several other algorithms, achieving an accuracy of 67%, a ROC-AUC score of 70%, and an F1-score of 66%. the study highlights challenges of class imbalance and feature distribution in water quality prediction, addressing aspects of SDG 11 (Sustainable Cities and Communities) by improving urban water management. Our findings have significant implications for water resource management, supporting SDG 12 (Responsible Consumption and Production) through efficient resource utilization. While acknowledging limitations such as single dataset reliance, this research combines modern machine learning with comprehensive analysis to enhance water quality assessment. It contributes to SDG 17 (Partnerships for the Goals) by providing a framework for collaboration between technology and environmental sectors. Future directions emphasize improving model performance and real-world applicability, potentially supporting SDG 13 (Climate Action) by enhancing resilience to water-related climate impacts. © 2025 IEEE.

关键词： Resource allocation

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A Comprehensive Evaluation of Machine Learning Techniques for Predicting Software Bugs 4

A Comprehensive Evaluation of Machine Learning Techniques fo...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Sakib, Fahim Faysal Islam Juel, Md. Sajjadul Tafannum, Zinniya Joy, Jihad Shahriar Karim, Razuan American International University-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798331530938

Software Bug Prediction (SBP) is essential to control overall software quality. As systems become complex, faults increase, and early prediction is needed to enhance quality and reduce expenses. this paper provides a technical study of thirteen Machine Learning (ML) techniques for predicting software bugs by utilizing NASA's Promise Repository datasets. the study examines the effectiveness of these classification techniques focusing on evaluation metrics such as Precision, Recall, F-measure, Accuracy, Error Rate, FPR, FNR, ROC, and MCC. the results indicate that Random Forest (RF) achieved the highest accuracy on PC1 (94.96%) and CM1 (96.60%), while Multilayer Perceptron (MLP) scored 85.6% on KC1, and Logistic Regression (LR) got 86.25% on KC2. Regarding error rates, RF had the lowest on PC1 (0.050), LR on KC2 (0.137). For FPR, SVM, MLP, LR, RBF, ANN, and AdaBoost excelled on PC1 (0.00). For FNR, Decision Tree (DT) performed best on PC1 (0.611), KC2 (0.518), and LDA on CM1 (0.500). © 2025 IEEE.

关键词： Adversarial machine learning

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