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Analysis of Perturb and Observe MPPT under Varying PV Operating Climatic Conditions 21

Analysis of Perturb and Observe MPPT under Varying PV Operat...

引用

21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Addawe, Abdirahim Mahmood, Musaria K. Karim, Sulaiman M. Nezam, Ahmad M. Ankara Yildirim Beyazit University Dept. of Energy Systems Engineering Ankara Turkey Jannat Iraq College Dept. of Medical Instr. Tech. Eng. Ramadi Iraq Al-Hadba'a University College Dept. of Computer Technology Engineering Mosul Iraq Karabuk Üniversitesi Dept. of Computer Engineering Karabuk Turkey

ISBN: (纸本)9798350374131

Improving the efficiency of photovoltaic (PV) sys-tems has emerged as a critical priority. Achieving optimal power production from solar modules requires operating at maximum power point (MPP) under various climatic conditions. This paper describes the operation of the Perturb and Observe (P&O) as an efficient Maximum Power-Point Tracking (MPPT) algorithm. Simulations of various operating scenarios are performed using MATLAB to assess the algorithm efficiency under both Standard Test Conditions (STC) and Partial Shading Conditions (PSC). This study considers factors such as output power efficiency, time response, and steady-state power oscillation. The simulation results show a fast-tracking, lower oscillation in the case of STC but fail to track the MPP in the case of multi-panel under PSC. © 2024 IEEE.

关键词： MATLAB

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A Transpose-SELDNet for Polyphonic Sound Event Localization and Detection 8

A Transpose-SELDNet for Polyphonic Sound Event Localization ...

引用

8th IEEE International Conference for Convergence in technology, I2CT 2023

作者： Spoorthy, V. Koolagudi, Shashidhar G. National Institute of Technology Karnataka Surathkal Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798350334012

Human beings have the ability to identify a particular event occurring in a surrounding based on sound cues even when no visual scenes are presented. Sound events are the auditory cues that are present in a surrounding. Sound event detection (SED) is the process of determining the beginning and end of sound events as well as a textual label for the event. The term sound source localization (SSL) refers to the process of identifying the spatial location of a sound occurrence in addition to the SED. The integrated task of SED and SSL is known as Sound Event Localization and Detection (SELD). In this proposed work, three different deep learning architectures are explored to perform SELD. The three deep learning architectures are SELDNet, D-SELDNet (dept.wise Convolution), and T-SELDNet (Transpose Convolution). Two sets of features are used to perform SED and Direction-of-Arrival (DOA) estimation tasks in this work. D-SELDNet uses a dept.wise convolution layer which helps reduce the model's complexity in terms of computation time. T-SELDNet uses Transpose Convolution, which helps in learning better discriminative features by retaining the input size and not losing necessary information from the input. The proposed method is evaluated on the First-order Ambisonic (FOA) array format of the TAU-NIGENS Spatial Sound Events 2020 dataset. An improvement has been observed as compared to the existing SELD systems with the proposed T-SELDNet. © 2023 IEEE.

关键词： Convolution

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Unified Object Detection Model for Image Style Convertible Modalities

Unified Object Detection Model for Image Style Convertible M...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Li, Mu-Chuan Chen, Xiu-Zhi Chen, Yen-Lin National Taipei University of Technology Dept. of Computer Science & Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324174

Object detection is an important task in computer vision. In earlier studies, object detection mostly works on single-modal. But recently, in order to improve detection efficiency, researchers start adding more modals for improving the robustness of detection result. In this paper, we assume that all input modals which can convert to image style are able to complete object detection task through a unified model. We choose YOLOv7 as our baseline model and use RGB and infrared images from the public dataset Camel to test our hypothesis. Based on our experiment results, training RGB and IR images together obtains better performance than training individually, which shows that all image style modalities are possibly handled by a unified model and even achieve better results. © 2023 IEEE.

关键词： Object detection

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Exploring CNN Architectures for Seizure Detection from MRI during Pregnancy 3

Exploring CNN Architectures for Seizure Detection from MRI d...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Nayak, Geetanjali Padhy, Neela Madhab Mishra, Tusar Kanti Giet Unviersity Dept. of Computer Science and Engineering Odisha Gunupur India Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Computer Science and Engineering Karnataka Manipal India

ISBN: (纸本)9798350375190

Deep Learning (DL) represents a subset that has revolutionized traditional machine learning. Unlike earlier methods relying on handcrafted feature extraction, DL automates both feature extraction and classification. This innovation has significantly advanced applications in various medical domains, including the diagnosis of epileptic seizures. This research provides a comparative overview of studies concentrating on automated epileptic seizure detection using leading convolutional neural networks (CNN) architectures. It explores diverse architectures proposed for the automatic diagnosis of epileptic seizures through MRI, encompassing an analysis of rehabilitation systems utilizing DL. The proposed work investigates the application of four primitive CNN architectures on the identification of onset of seizure. The proposed architectures are validated through benchmark MRI samples. Experimental evaluation is made on samples of pregnant females. Overall rate of accuracy stands at 85%, 80%, 90%, and 95% respectively. © 2024 IEEE.

关键词： Network architecture

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Dynamic Asset Allocation Using Trading Agent

Dynamic Asset Allocation Using Trading Agent

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： You, Shingchern D. Liu, Chien-Hung Yen, Ching-Cheng National Taipei Universiyt of Technology Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324174

We study the use of PPO (Proximal Policy Optimization) algorithm for trading ETFs belonging to different asset classes. The studied asset classes include common stocks, bonds, REIT (Real Estate Investment Trust), gold, and future contracts on agricultural commodities. When properly training the PPO agent with the proposed ratio allocation strategy, the agent outperforms the static, periodical rebalancing approach. © 2023 IEEE.

关键词： Investments

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Software Defect Predictor and Classifier Tool Using Machine Learning Techniques

Software Defect Predictor and Classifier Tool Using Machine ...

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2023 IEEE International Conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Shankar, Sahana P. Pushp, Divyansh Makadia, Nemi Dubey, Raghav Nayak, Anusha Shashikant Chaudhari, Shilpa Ramaiah University of Applied Sciences Dept. of Computer Science and Engineering Karnataka Bangalore India M S Ramaiah Institute of Technology Dept. of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350300826

The Software testing is critical for ensuring the quality of software, but it can consume more than half of a software project's total expenses. This research can help software development teams identify potential bugs early on, leading to efficient and effective software creation. To improve the efficiency of software testing, this report presents research on software defect prediction using a hybrid machine learning algorithm that combines supervised and unsupervised learning techniques. The study used publicly available datasets to train and evaluate various machine learning models, including an ensemble learning model. A comparative analysis was conducted among KNN, Random Forest, Adaboost, Multilayer Perceptron, CNN, and Gaussian Naïve Bayes on different datasets. Feature selection was performed using various methods, including Recurrent Feature Elimination (RFE), SelectKBest, and Correlation, implemented by a tool created to select any feature selection algorithm and compare the results for various combinations with the above mentioned classifiers. The results achieved by the model are showed in detail for each of the algorithms on the selected datasets. The main objectives of the research are to create a tool to apply various machine learning techniques to the datasets and determine the most effective ones, as well as to explore different feature selection methods for improving the accuracy of defect prediction. © 2023 IEEE.

关键词： Software testing

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Implementing Newly Proposed Dynamic Tree Structure: Development, Integration, and Optimization

Implementing Newly Proposed Dynamic Tree Structure: Developm...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Banerjee, Pallab Kumari, Sweety Kumar, Biresh Thakur, Kanika Gaurav, Kumar Kumar, Purushottam Amity University Jharkhand Dept. of Computer Science Engineering Jharkhand Ranchi India Galgotia University Dept. of Computer Science Engineering Greater Noida campus India Amity University Jharkhand Amity School of Information Technology Jharkhand Ranchi India

ISBN: (纸本)9798350385199

An innovative data structure called a 'dynamic tree' has important uses in algorithmic time complexity optimization. It creates well-organized trees by modifying the properties of several single-node trees, therefore preserving the forest structure. This structure is essential to improving the effectiveness of many algorithms. In this work, I particularly address the 'Maximum Flow method,' a crucial subtopic in the larger field of dynamic trees. One basic method for solving network flow issues is the Maximum Flow Algorithm, but it frequently runs into issues with time complexity. My research attempts to overcome these obstacles by using dynamic trees to enhance the efficiency of the algorithm. This work reduces the time complexity of network flow problems, leading to more effective solutions. The findings have potential implications in a variety of computing and real-world scenarios. © 2024 IEEE.

关键词： Ancestor Cut Evert Find Key Link Root Top tree

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IoT ML Driven Holistic Health Monitoring and Fitness Assessment Empowering Proactive Wellbeing Management

IoT ML Driven Holistic Health Monitoring and Fitness Assessm...

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2024 IEEE Students Conference on engineering and Systems, SCES 2024

作者： Mishra, Sachin Singh, Anurag Dept. of Computer Science and Engineering Government Engineering College Raipur Chhattisgarh Raipur India International Institute of Information Technology Dept. of Electronics & Communication Engineering Chhattisgarh Naya Raipur India

ISBN: (纸本)9798350374711

In recent years, significant advancements in the area of non-invasive and wearable technology have paved the way for widespread applications of personalized and remote health monitoring. Health monitoring enables proactive management of one's well-being, and enhances overall health outcomes. With the advent of such technologies there are lots of platforms developed. But such platforms are not successful in providing the followings: 1) the ability to monitor all major health vitals in one unified application, & 2) the provision of a holistic health score derived from these non-invasive vitals for fitness measurement. In response, this paper presents a novel solution featuring: 1) An IoT-ML enabled platform for self-monitoring of important health vitals, and 2) A fitness assessment score derived through ML algorithm using the health vitals of a person. By integrating data on various health parameters including heart rate, blood oxygen levels, and sleep patterns, advanced machine learning models are developed to analyze this data and predict the fitness score that accurately reflects an individual's overall health and fitness level. The performance of the proposed estimation model is evaluated using R2 and mean square error (MSE) and the best value is achieved using the XGBoost regressor of values 0.967 and 0.0033. This solution empowers individuals to take control of their well-being and improve their overall quality of life. Overall, the integration of non-invasive methods and IoT sensors for health vitals monitoring and fitness assessment presents a novel approach with significant potential to revolutionize health care. By empowering individuals with real-time insights and a comprehensive fitness score, this solution facilitates informed decision-making and enables individuals to proactively manage their health and well-being, ultimately enhancing their overall quality of life. © 2024 IEEE.

关键词： Electronic health record

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Campus Network Configuration, Monitoring and Data Flow Simulation using Cisco Packet Tracer 6

Campus Network Configuration, Monitoring and Data Flow Simul...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Moz, Shahadat Hoshen Hosen, Md Apu Tanny, Nice Fatema Islam Dept. of Computer Science and Engineering Northern University of Business and Technology Khulna Khulna Bangladesh

ISBN: (纸本)9798350398496

The key to communication is being digitalized every day, in order to keep up with technology everyone needs to update their skillset with it. A campus network is connected to us more because all are often a part of it. Everyone uses it most of the time for their daily activities on campus and also for educational purposes, depending on their needs. To ensure that data cannot be corrupted, it is crucial to make specific alterations to it. Integrity and reliability are key issues in all information switch difficulties in order to ensure safe and simple transfers among customers. As a result, this research has developed a secure campus network and a stable campus community for sending and getting data among end users with high levels of security. Using a Cisco packet tracer, this study proposed a topology for a campus of multiple networks and virtual local area networks (VLANs), as well as the most crucial security configurations for the networking used in this design. There used a massive variety of protocols to defend and accommodate the customers of the secure campus network scheme and also added switches, routers, firewalls, Wi-Fi routers, IProuters and printers to this network in order to make communication smoother and more efficient. Digital campus is the place where the next generation goes to gain education and knowledge about the world makes the campus network more secure and tech-focused. The students and other personnel can learn and even get familiar with them all and also helpeveryone. © 2023 IEEE.

关键词： Network security

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Resource Allocation for OTFS-Based ISAC Systems 3

Resource Allocation for OTFS-Based ISAC Systems

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3rd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2023

作者： Zhang, Meiying He, Hengtao Song, Shenghui Zhang, Jun Letaief, Khaled B. The Hong Kong University of Science and Technology Dept. of Electronic and Computer Engineering Hong Kong

ISBN: (纸本)9798350333732

Integrated sensing and communications (ISAC) has been considered as a key technology for future wireless networks. Orthogonal time frequency space (OTFS) modulation is considered as an effective technology to achieve ISAC in high-mobility scenarios due to its ability to combat high delay and Doppler shifts. However, although the performance analysis of OTFS-based ISAC system has been investigated, resource allocation and joint optimization for communication and sensing are still in its fancy. In this paper, we consider resource allocation in OTFS-based ISAC systems. We first introduce the system model and formulate the resource allocation problems. Then, several related works are discussed in detail. Next, an OTFS-based multiple-user multiple-input multiple-output (MIMO) ISAC system model is investigated, where the base station is considered as an ISAC transmitter and sends the message to different vehicles while simultaneously estimating their relative range and velocity via output feedback, respectively. We then formulate the sensing and communication trade-off optimization problem considering the delay Doppler resource block (DDRB) allocation and provide some sample results. Finally, we show several future directions for resource allocation in OTFS-based ISAC systems. © 2023 IEEE.

关键词： Resource allocation

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