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Financial Viability of PV Grid for an Intelligent System of Residential Buildings in sub-urban Areas of Punjab, Pakistan 16

Financial Viability of PV Grid for an Intelligent System of ...

引用

16th Seminar on Power Electronics and Control, SEPOC 2024

作者： Shehzad, Moazzam Jamal, Nasir Muqeet, Hafiz Abdul Qureshi, Noman Sohaib Lincoln University College Dept. of Electrical Engineering Petaling Jaya Malaysia Punjab Tianjin University of Technology Dept. of Electrical Engineering Lahore Pakistan University of Engineering and Technology RCET Campus Dept. of Computer Science Lahore Pakistan

ISBN: (纸本)9798350379419

With fuel prices rising and environmental concerns intensifying, the financial burden on consumers and businesses has shown an upward trajectory, prompting a search for sustainable alternatives sources. This study investigates the financial feasibility of installing a grid-tied solar photovoltaic (PV) system in residential buildings in suburban areas of Punjab, Pakistan. The research uses a complete intelligent financial model to assess the feasibility of a grid-connected solar PV system, incorporating parameters such as solar irradiance levels, system size, capital costs, operating expenses, energy rates, its incentives, and payback periods in a systematic computational optimization methodology. The shift to solar photovoltaic systems provides an affordable way to lower energy bills that can also lessen the dependency on fossil fuels. Additionally, solar PV systems help significantly to reduce greenhouse gas emissions and environmental damages by utilizing the clean energy of the sun. This is in line with worldwide efforts to battle climate change and protect the planet from environmental concerns. This research uses RET Screen software to evaluate the financial feasibility with GHG reduction analysis as well. The study's findings are useful for homeowners, policymakers, and stakeholders interested in encouraging renewable energy adoption and sustainable development in Punjab, Pakistan's suburban region. © 2024 IEEE.

关键词： Computational Optimization Feed-In-Tariff Net Energy Metering Net Present Value Net-Metering

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Towards an Uncertainty-aware Decision Engine for Proactive Self-Protecting Software 4

Towards an Uncertainty-aware Decision Engine for Proactive S...

引用

4th IEEE International Conference on Automatic Computing and Self-Organizing Systems Companion, ACSOS-C 2023

作者： Liu, Ryan University of Waterloo Dept. of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350337464

Proactive protection of software systems can be achieved through Moving Target Defense (MTD) techniques, which are designed based on addressing the questions of what to move, how to move, and when to move. However, the deployment of MTD techniques is subject to overhead and run-time uncertainties that can impact their effectiveness in defending against cyberattacks. The goal in this research is to improve the uncertainty-awareness and self-adaptation in a MTD decision engine in order to enhance the effectiveness of MTD techniques. The proposed approach is based on using the Partially Observable Markov Decision Process framework to quantify uncertainties. A systematic approach is proposed to achieve this objective, which includes modelling, designing, and engineering phases. The outcome of this research will make contributions related to (i) modelling solutions for run-time uncertainty, (ii) designing scalable methods for uncertainty-aware MTD planning, and (iii) realizing an uncertainty-aware MTD decision engine. © 2023 IEEE.

关键词： Decision making

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Psychological Wellbeingness Prediction Using Machine Learning with Hybrid Hyparameter Tuning Techniques

Psychological Wellbeingness Prediction Using Machine Learnin...

引用

2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Rajah, Puvanenthira Habib, Masruk Ravikumar, R.N. Nadarajan, Sivakumar Chougule, Bhagyashree Amit Kirubhakaran, M. Marwadi University Dept. of Computer Engineering Rajkot India Alliance University Dept. of Computer Science and Engineering Bangalore India Tatyasaheb Kore Institute of Engineering and Technology Dept. of Computer Engineering Maharashtra India Suriya Engineering College Dept. of Ai & Ds Erode India

ISBN: (纸本)9798350379716

This study investigates the application of machine learning (ML) techniques in predicting Psychological Well-being outcomes, emphasizing the use of ensemble methods like AdaBoost and Random Forest for enhanced accuracy. With Psychological well-being issues affecting a significant portion of the global population, traditional assessment methods are challenged by issues of accessibility, stigma, and subjectivity. Leveraging data from various surveys, this research compares different ML algorithms, including Logistic Regression and Support Vector Machines, in predicting psychological well-being conditions. The results highlight the superior performance of AdaBoost and Random Forest, particularly when hyperparameters are finely tuned, achieving accuracies up to 0.996. The study underscores the potential of ML in improving psychological well-being interventions by offering precise, unbiased, and accessible diagnostic tools. Future research directions include the integration of multimodal data and the development of models that can suggest personalized treatment plans while ensuring data privacy. This paper advocates for the integration of advanced computational techniques with clinical insights to revolutionize psychological well-being diagnostics and care. © 2024 IEEE.

关键词： Clinical research

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Multi-Layered Security Techniques for Protecting Cooperative Relay Networks from Eavesdropping

Multi-Layered Security Techniques for Protecting Cooperative...

引用

2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Upadhyay, Abhay Gupta, Mridul Dhondiyal, Shiv Ashish Asudani, Deepak Suresh Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India Pune India

ISBN: (纸本)9798331542344

In this paper, we study the multi-layered security approaches for cooperative relay networks against passive eavesdropping adversaries. Specifically, we investigated physical layer approaches (i.e., beamformed and artificial noise injections) to improve the signal defence ability at a much lower eavesdropping capacity. Trade-offs in these cryptographic methods were studied in terms of encryption strength vs. decryption time under different loads on the network. The security of the network layer was assessed by measuring packet delivery ratios and data integrity violations under malicious nodes. Results show that multi-layer security is performed at the cost of performance, but much better network defence mechanisms are proposed overall. While this end-To-end approach strikes a reasonable balance between security and real-world performance considerations, it presents itself as a sensible solution for securing network communications against eavesdropping threats. © 2024 IEEE.

关键词： Network layers

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LegalAI Across Languages: A Comprehensive Survey on Tasks, Methodologies and Challenges 1

LegalAI Across Languages: A Comprehensive Survey on Tasks, M...

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1st International Conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Deshpande, Anjali Deshmukh, Pratiksha COEP Technological University Dept. of Computer Science and Engineering Pune India PICT Dept. of AI & DS Pune India School of Computational Sciences COEP Technological University Dept. of Computer Science and Engineering Pune India

ISBN: (纸本)9798350355611

Natural Language Processing (NLP) is revolutionizing the legal domain, enabling tasks such as predicting legal outcomes, summarizing complex documents, identifying key entities, and assessing bail risks. This survey paper presents a comprehensive review of the existing research on NLP tasks applied to legal documents and judgments across various languages, with a special emphasis on low-resource languages. Despite the extensive work done in widely spoken languages like English, there remains a critical need to extend these advancements to languages with limited resources and data availability. This paper categorizes and analyzes the NLP tasks in the legal domain based on the languages they target. It highlights the methodologies employed, datasets utilized, and the performance of different models across diverse languages. Furthermore, it identifies the gaps in current research and proposes potential directions for future work, particularly in improving the accessibility and applicability of NLP solutions for legal texts in underrepresented languages. By providing a comprehensive overview of advancements and obstacles, this survey seeks to assist future research endeavors that bridge the disparity between high-resource and low-resource languages in legalAI applications. © 2025 IEEE.

关键词： Risk assessment

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Finite State Machine for Testing the GUI Using Genetic Algorithm Based on Weightage Given to Different Classes 1

Finite State Machine for Testing the GUI Using Genetic Algor...

引用

1st International Conference on Recent Developments in Electronics and Communication Systems, RDECS 2022

作者： Kumar, Sumit Nitin Yadav, Mitul Department of Computer Science and Engineering Uttarakhand Technical University Dehradun India Educator of Electrical Engineering and Computer Science University of Cincinnati Cincinnati United States Department of Computer Science Dev Bhoomi Institute of Technology Dehradun India

ISBN: (纸本)9781643683607

In this paper, we have proposed testing the graphical user interface (GUI) applications using the idea of finite state machines and then comparing the results with the model generated using Matlab: which represents the machine that tested the actual GUI. This environment can help write efficient test cases to test the actual graphical interfaces of the application under the test. For the testing of our system, a small GUI for the calculator is developed. Then the finite state diagram for the same design will be used as a machine for the simulation. The results from the Matlab model are compared with the actual application. The defects are also identified and demonstrated. © 2023 The authors and IOS Press.

关键词： Genetic algorithms

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Revolutionizing Diabetes Prediction Models: Leveraging Advanced Feature Reduction and Classification Methods 22

Revolutionizing Diabetes Prediction Models: Leveraging Advan...

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22nd International Learning and Technology Conference, L and T 2025

作者： Attiah, Ameera Alagha, Mawaddah Bukassim, Lujain El-Kafrawy, Passent College of Engineering Effat University Computer Science Dept. Jeddah Saudi Arabia

ISBN: (纸本)9798331532215

The global challenge of diabetes demands innovative approaches for early diagnosis and effective management. This paper investigates the integration of advanced dimensionality reduction and feature selection techniques to improve diabetes prediction models. Utilizing Principal Component Analysis (PCA) and the Artificial Bee Colony (ABC) algorithm, the study focuses on optimizing feature selection to enhance model accuracy, computational efficiency, and interpretability. Employing two diverse datasets - the Behavioral Risk Factor Surveillance System (BRFSS) and the Pima Indians Diabetes Dataset - the research evaluates the performance of Random Forest and Logistic Regression models. Results reveal significant improvements in predictive accuracy and computational efficiency, particularly with ABC-selected features, reducing feature dimensionality while maintaining high accuracy. This study underscores the potential of combining PCA and ABC to revolutionize predictive healthcare analytics, offering robust tools for diabetes management and prevention. © 2025 IEEE.

关键词： Dimensionality reduction

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Real-Time Traffic Management System Using YOLOv8 and CNN: A Deep Learning Approach with IoT Integration 1

Real-Time Traffic Management System Using YOLOv8 and CNN: A ...

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1st International Conference on Advances in computer science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Saklani, Sumit Manchanda, Mahesh Sharma, Raman Singh, Devendra Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Application Dehradun India

ISBN: (纸本)9798331518578

Traffic management also plays a crucial role in urban planning and development, with pressing challenges related to congestion, safety, and environmental impact. In this study, we proposed a real time traffic control system using YOLOv8 and CNNs combined with Internet of Things (IoT) technologies. As a high-performing object detection model, YOLOv8 is able to accurately and rapidly detect vehicles, pedestrians, and other traffic objects. When combined with CNN based data analytics, the proposed system can successfully monitor traffic flow, discover irregularities, and control the signals dynamically. Creating a cohesive framework for intelligent decision-making IoT integration ensures real-time data acquisition from sensors, cameras and edge devices. IoT framework for a smart urban environment the proposed architecture provides the versatility through scalability, low latency, and adjustment to several urban perspective scenarios. The combination leads to greatly enhanced traffic flow efficiency, accident prevention and environmental impact reduction as experimental results show. With data till October 2023, this study resolves a gap between the developing field of deep learning and the Internet of Things (IoT), that creates to be utilized to connect to advanced town environments. © 2025 IEEE.

关键词： Decision making

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Automated Road Extraction in Urban and Rural Regions from Remote Sensing Imagery with U-Net and ResNet-Based Architectures 1

Automated Road Extraction in Urban and Rural Regions from Re...

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

作者： Sharma, Palvi Kumar, Rakesh Gupta, Meenu Obaid, Ahmed J. Chandigarh University Dept. of Computer Science & Engineering Punjab India Chandigarh University Dept. of Computer Science & Engineering Punjab India University of Kufa Faculty of Computer Science and Mathematics Najaf Iraq National University of Science and Technology College of Technical Engineering Dhi Qar Iraq

ISBN: (纸本)9798350356816

Accurate road extraction from Remote Sensing Imagery (RSI) is crucial for various applications, including urban planning, navigation, and disaster response. This study investigates automated road extraction in rural, semi-urban and urban regions using deep learning architectures, specifically UNet and Deep Residual U-Net (ResNet) models. We leverage High-Resolution Satellite Imagery (HRSI) to train and validate our models, focusing on the distinct characteristics and challenges presented by urban and rural environments. Our methodology involves comprehensive data preprocessing and augmentation techniques to enhance model robustness. We evaluate the performance of both architectures using metrics and achieved an accuracy of 90.29%, recall of 80.95%, precision of 74.89%, and F1- score of 77.80% for the Deep Residual U-Net. Experimental results demonstrates that while both models perform well, the Deep Residual U-Net exhibits superior accuracy and generalization, particularly in complex urban landscapes. © 2024 IEEE.

关键词： Urban planning

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Source Localization Using a Single Array of Sensors in Nearfield Configuration, and Application to Active Noise Cancellation

Source Localization Using a Single Array of Sensors in Nearf...

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2024 Intermountain engineering, Technology and Computing, IETC 2024

作者： Moon, Todd K. Shekaramiz, Mohammad Gunther, Jacob H. Utah State University Information Dynamics Laboratory Electrical and Computer Engineering Dept. LoganUT United States Utah State University Electrical and Computer Engineering Dept. LoganUT United States

ISBN: (纸本)9798350373073

In this paper we demonstrate by computed examples that an array of sensors in nearfield configuration can provide source localization in both x and y, going beyond the usual directional localization provided by a 1-dimensional array. This ability to localize a source opens new application areas. An application presented here is the possibility of doing active noise cancellation of the sound of a snorer. © 2024 IEEE.

关键词： Spurious signal noise

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