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Exploring Sequential Algorithms for Anomaly Detection in Multivariate time Series

Exploring Sequential Algorithms for Anomaly Detection in Mul...

引用

2024 international conference on Industrial Engineering, applications and Manufacturing, ICIEAM 2024

作者： Musayev, A. Grigoriev, D. Makshanov, A. Itmo University Saint-Petersburg Russia Saint-Petersburg Russia Admiral Makarov State University Of Maritime And Inland Shipping Department Of Computing Systems And Computer Science Saint-Petersburg Russia

ISBN: (纸本)9798350395013

This study delves into the development and application of sequential algorithms for detecting spontaneous changes, or anomalies, in the probabilistic characteristics of multivariate time series. The research is primarily motivated by the challenges associated with providing mathematical support for decision-making processes that depend on data from multi-channel monitoring of large systems. The focus is on the spatial-temporal dynamics of multidimensional time series measurements. Unlike conventional approaches, this study proposes innovative techniques for examining inter-channel connections. These techniques involve reducing the dimensionality of the data by representing data matrices in terms of their first singular basis and employing multiple regression in the projection space. The paper also demonstrates the practical application of the developed approach in analyzing the characteristics of turbulent flow, based on measurements of pressure deviation at different spatial locations. This research contributes significantly to the field by offering a novel approach to anomaly detection in multivariate time series data. © 2024 ieee.

关键词： Singular value decomposition

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Zero-Order Optimization in Security Constrained Power System Scheduling 4

Zero-Order Optimization in Security Constrained Power System...

引用

4th ieee international conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： An, Qi Wang, Jianxiao Wu, Shengyu Ren, Weikai Huang, Ruanming Li, Gengyin North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China Peking University National Engineering Laboratory for Big Data Analysis and Applications Beijing China State Grid Energy Research Institute CO. LTD. Beijing China Institute of Energy Peking University Beijing China Planning Center State Grid Shanghai Electric Power Company Shanghai China

ISBN: (纸本)9798350395914

The security and resilience of power systems are gradually challenged. As a typical index measuring the security and resilience of power systems, the frequency stability issue is becoming prominent. Due to the increase in the complexity of power systems, the frequency stability boundary is gradually becoming fuzzy, leading to traditional analytical-modeling algorithms hardly applicable for frequency stability constrained dispatch. Existing data-driven methods for characterizing frequency stability boundary typically requires massive simulation calculations, leading to unnecessary computing power consumption. To this end, zeroth-order (ZO) optimization, which aims to solve optimization problems embedding non-analytic functions, is adopted for solving the frequency stability constrained dispatch in this paper. In contrast to traditional data-driven methods, we directly embed frequency stability simulation check into power system dispatch. The gradient of frequency stability simulation check is estimated through ZO optimization, thereby realizing the interaction optimization between power system dispatch and real-time simulation. In this way, the solution for the frequency stability constrained dispatch is modified towards the optimal point along the gradient descent direction. Cases studies based on ieee-9 bus system verifies that, compared with traditional data-driven methods, the solution approach we propose could reduce the system cost while significantly improving the calculation efficiency. © 2024 ieee.

关键词： Frequency stability

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Highly Accurate Approximate Ternary Multipliers for Error Resilient applications 11

Highly Accurate Approximate Ternary Multipliers for Error Re...

引用

11th international conference on Intelligent systems and embedded Design, ISED 2023

作者： Burri, Shalini Kudulla, Gowtham Sri Harsha Jogi, Pavan Kumar Vysyaraju, Anantha Sai Satwik Kumar, Uppugunduru Anil Ahmed, Syed Ershad Veeramachaneni, Sreehari Gokaraju Rangaraju Institute of Engineering & Technology Electronics and Communication Engineering Hyderabad India Bits Pilani Electrical and Electronics Engineering Hyderabad India Hyderabad India

ISBN: (纸本)9798350318159

Approximate computing is a technique to obtain notable improvement in power and power-delay product parameters where accurate computation is not necessary. This paper presents a simple and energy-efficient approximate 1-blt ternary multiplier and approximate ternary half adder, which are used to implement 6×6 approximate ternary multipliers. The 6×6 ternary multipliers are implemented by introducing errors in generation or reduction stages. The proposed approximate ternary 6×6 multipliers show good accuracy-power trade-off compared to existing designs;it exhibits an improvement up to 99.6% in terms of NMED∗Power parameter compared to existing approximate multiplier designs. Further proposed ternary multipliers are evaluated using image processing applications. © 2023 ieee.

关键词： Image processing

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Explainable AI in Large Language Models: A Review 2

Explainable AI in Large Language Models: A Review

引用

2nd ieee international conference on Emerging Research in Computational Science, ICERCS 2024

作者： Sauhandikaa, S. Bhagavath Narenthranath, R. Sathya Bama Krishna, R. Sathyabama Institute of Science and Technology School of Computing Chennai India

ISBN: (纸本)9798331534950

Explainable AI in Large Language Models (LLMs) represents an exciting frontier in Artificial Intelligence. In recent times, LLMs provides various AI applications ranging from chatbots to content generation. While these applications are exciting, their decision-making process behind the intelligent systems plays a major role. These processes are also a mystery and they operate as "Black boxes", where the processes are often challenging to interpret. This paper helps to give a sense of the processes that occurs behind these decisions. It helps to understand why the AI has chosen one sentence rather than the other. It explores key breakthroughs of XAI techniques that helps in solving these complexities. Methods such as Attention Visualization, Feature Importance Analysis and Counterfactual Explanations provide insights on why certain decisions are made. These techniques provide a voice to the intricate processes and address real-world challenges, which makes it more reliable. This enables better transparency and makes it trust-worthy. XAI has the potential to address ethical concerns, enhance user trust and improve Human-AI collaboration. This research highlights how better transparency in AI is not merely a technical challenge but a foundational step towards building a future where humans and AI work together seamlessly and responsibly. © 2024 ieee.

关键词： Intelligent systems

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Tweeting from Left to Right: Tracing the Dynamics of Emotional Messaging and Public Engagement During the 2018 vs. 2022 US Campaigns 21

Tweeting from Left to Right: Tracing the Dynamics of Emotion...

引用

21st ieee international Symposium on Parallel and Distributed Processing with applications, 13th ieee international conference on Big Data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Wang, Meng-Jie University of Canterbury School of Psychology Speech and Hearing Christchurch New Zealand

ISBN: (纸本)9798350329223

Despite numerous studies delving into social media politicking, there is, thus far, little understanding of how distinct emotions spread online. Much of the prior work has focused on positive vs. negative diffusion or measured emotional rhetoric without considering public engagement on such sites. Since elected officials increasingly turn to social media, even less is known about the impact of distinct emotional messaging on mobilizing users, attracting supporters, or disseminating political speeches. Moving beyond merely a valence-based approach, the study here seeks to address this gap by analyzing over 23,000 tweets posted by Senate candidates during the 2018 and 2022 US midterm elections through natural language processing. Specifically, leveraging the IBM Tone Analyzer, the present work implements a cross-sectional examination to explore: a) whether certain emotions - joy, confidence, anger, fear, and sadness - conveyed in candidates' tweets might be more likely to garner public attention;and b) if so, does this pattern vary across the political spectrum, illuminating the ways in which Democratic vs. Republican candidates adopt to expand their online reach over time? © 2023 ieee.

关键词： Natural language processing systems

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Towards Broad Learning Networks on Unmanned Mobile Robot for Semantic Segmentation 39

Towards Broad Learning Networks on Unmanned Mobile Robot for...

引用

ieee international conference on Robotics and Automation (ICRA)

作者： Li, Jiehao Dai, Yingpeng Wang, Junzheng Su, Xiaohang Ma, Ruijun Beijing Inst Technol Sch Automat State Key Lab Intelligent Control & Decis Beijing 100081 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510641 Peoples R China

ISBN: (纸本)9781728196817

This article investigates the real-time semantic segmentation in robot engineering applications based on the Broad Learning System (BLS), and a novel Multi-level Enhancement Layers Network (MELNet) based on BLS framework is proposed for real-time vision tasks in a complex street scene on the unmanned mobile robot. This network mainly solves two problems: (1) mitigating the contradiction between accuracy and speed while maintaining low model complexity, and (2) accurately describing objects based on their shape despite their different sizes. Firstly, the BLS architecture is expanded to the deep network with trainable parameters. This trainable network could adjust its weights in a complex environment, and mitigate the adverse impact of the environment on the complex tasks. Secondly, enhancement layers with the extended enhancement layers could extract both detailed information and semantic information. Moreover, an Upsampling Atrous Spatial Pyramid Pooling (UPASPP) is designed to fuse detail and semantic information to describe object features properly. Finally, in the case of the MNIST dataset and Cityscapes dataset, we get high accuracy with 8.01M parameters and quicker inference speed on a single GTX 1070 Ti card. At the same time, the unmanned mobile robot (BIT-NAZA) is employed to evaluate semantic performance in real-world situations. This reveals that MELNet could be run adequately on the embedded device and effectively operate in the real-robot system.

关键词： Performance evaluation Learning systems Shape Fuses Semantics Feature extraction real-time systems

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IoT Monitoring for Grid Voltage Regulation Using Model Predictive Control in Wind systems 2

IoT Monitoring for Grid Voltage Regulation Using Model Predi...

引用

2nd international conference on Edge computing and applications, ICECAA 2023

作者： Sharma, P. V. V. Raghava Prasanna, D. Sai Sirisha, Grandhi Engineering College Department of Electrical and Electronics Engineering Telangana Hyderabad India

ISBN: (纸本)9798350347579

This research provides a novel approach for achieving efficient grid voltage regulation in wind power systems using Model Predictive Control (MPC) and Internet of Things (IoT) monitoring. The suggested system makes use of an MPC controller that controls the power generated by wind turbines according to real-time measurements of the grid voltage that are collected via an IoT network of sensors and devices for communication. The structure of the system is created to ensure that the grid voltage maintains within a certain range, improving the stability and dependability of the power grid. Extensive MATLAB simulations are used to prove how effective the suggested system is, showing that it performs better in terms of voltage regulation and system stability than traditional control approaches. The feasibility and cost-effectiveness of the suggested system's installation are also examined. According to the research, compared to conventional control methods, the suggested system is simple to set up and maintain and provides considerable cost savings. The performance, dependability, and effectiveness of the power grid may be improved by using the technique presented in the present article, which is feasible and effective for grid voltage control in wind power systems. © 2023 ieee.

关键词： Model predictive control

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IoT applications in Smart Building Energy Management

IoT Applications in Smart Building Energy Management

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2024 international conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Ravichandra, Thangjam Karumudi, Madhavi Maheswari, M. Uma Leela, S. Thamizhkani, B. Kanniyappan, S.P. Alliance School of Business Alliance University Karnataka Bengaluru562106 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Bowrampet Telangana Hyderabad500043 India Rajalakshmi Engineering College Department of Mechatronics Thandalam Tamil Nadu Chennai602105 India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India New Prince Shri Bhavani College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai600073 India R.M.K. Engineering College Department of Civil Engineering Tamil Nadu Kavaraipettai601206 India

ISBN: (纸本)9798331543617

The technologies that are a part of the Internet of Things enable smart buildings to use energy more efficiently. The main focus of the research is on the use of internet-connected sensors and devices. real-time monitoring, analysis, and management of energy consumption are the goals of this. Data is gathered from various sources, such as appliances, lighting, HVAC (heating, ventilation, and air conditioning), and other systems, employing networked systems. This offers the chance for a more effective distribution of energy. The goal of the project is to foresee energy patterns and automatically adjust settings by focussing on the integration of cloud computing, big data analytics, and machine learning algorithms. Furthermore, it highlights how the Internet of Things can help cut down on energy waste and improve sustainability by giving consumers advice and information on how to use less energy. Providing consumers with insights and recommendations helps achieve this. By promoting the adoption of more ecologically friendly energy practices, the implementation of these technologies not only reduces operating costs but also decreases the environmental impact that buildings have. The study's conclusions indicate that the field of smart buildings has advanced significantly, which may help to promote sustainability and higher energy efficiency. © 2024 ieee.

关键词： Green buildings

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Research on moving target detection in complex weather 23

Research on moving target detection in complex weather

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in Sensor, Cloud and Big Data systems and applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Yan, Zhaoqi Gai, Rongli School of Information Engineering Dalian University Dalian China

ISBN: (纸本)9781665494571

Due to the special weather such as haze and strong light, the air visibility will be reduced, which will affect the target capture by the computer vision system. In order to solve the interference with from fog of moving target detection, this design proposes a moving target detection method based on gray channels in complex weather, which can be applied to the embedded systems. In this design, the original image data captured by the camera is defogged, and the moving target is extracted by using an adaptive threshold gray frame difference method of the gray image. Finally, the defogged video is obtained by combining the morphological method and the bounding box method, and the moving target is labeled more accurately, The results show that the design can effectively output clear fog-free images and detect moving targets in haze weather. © 2021 ieee.

关键词： Computer vision embedded systems Smart cities Transportation Object detection Interference Hardware

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Development of a real-time Object Detection System in the Highway Environment Using the YOLOv5 Algorithm for the Blind 7

Development of a Real-Time Object Detection System in the Hi...

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7th international conference of Computer and Informatics Engineering, IC2IE 2024

作者： Prasasat, Bumi Hamami, Faqih Musnansyah, Ahmad Telkom University Faculty of Industrial Engineering Department of Information Systems Bandung Indonesia

ISBN: (纸本)9798331505530

Individuals with visual impairments face significant challenges in navigating daily life, particularly in identifying objects on the road, such as vehicles, which affects their safety and mobility. Previous research has proposed various solutions using object detection technologies, yet there remains a need for further development, particularly in enhancing real-time performance, accuracy and practical deployment. This study aims to develop a real-time object detection system in the highway environment using the YOLOv5 algorithm for the blind deployed on web, specifically designed to support visually impaired individuals. Testing involved analyzing the latency and frames per second (FPS) of the detection system, crucial for real-time performance. The results indicate an average total latency of 1.711 seconds, a detection latency of 0.303 seconds, and an FPS of 1.65, with a Mean Average Precision (mAP) of 0.933 at an IoU threshold of 0.5, underscoring the system's capability to operate efficiently in real-time scenarios. The system achieves high accuracy and low latency real-time performance, demonstrating the effectiveness of YOLOv5 in practical applications. © 2024 ieee.

关键词： Object recognition

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