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SSRN 2024年

作者： Goldstein-Tweg, Tom Ginzburg-Ganz, Elinor Belikov, Juri Levron, Yoash The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel Department of Software Science Tallinn University of Technology Akadeemia tee 15a Tallinn12618 Estonia

The current paper belongs to a class of research works that aim to find analytic and semi-analytic solutions to optimal power flow problems that involve storage systems. The main contribution of this work is a rigorous proof for the uniqueness of the ``shortest-path" optimal solution, which is a cornerstone in this class of algorithms, and relies upon a graphical design procedure presented in an earlier work. The proof builds upon five consequential lemmas, each provides a different characteristic of the optimal solution. These characteristics are then merged to prove the uniqueness of the optimal solution, which is given by the shortest path of the generated energy within bounds. The presented proof provides not only a sound theoretical foundation for this class of algorithms, but may also help develop additional analytic solutions for more complex optimal control problems involving storage systems. © 2024, The Authors. All rights reserved.

关键词： Power management

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Application of AI to formal methods — an analysis of current trends

arXiv

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arXiv 2024年

作者： Stock, Sebastian Dunkelau, Jannik Mashkoor, Atif Johannes Kepler University Linz Institute of Software System Engineering Linz4040 Austria Heinrich Heine University Düsseldorf Faculty of Mathematics and Natural Sciences Institute of Computer Science Düsseldorf40225 Germany

With artificial intelligence (AI) being well established within the daily lives of research communities, we turn our gaze toward an application area that appears intuitively unsuited for probabilistic decision-making: the area of formal methods (FM). FM aim to provide sound and understandable reasoning about problems in computer science, which seemingly collides with the black-box nature that inhibits many AI approaches. However, many researchers have crossed this gap and applied AI techniques to enhance FM approaches. As this dichotomy of FM and AI sparked our interest, we conducted a systematic mapping study to map the current landscape of research publications. In this study, we investigate the previous five years of applied AI to FM (2019–2023), as these correspond to periods of high activity. This investigation results in 189 entries, which we explore in more detail to find current trends, highlight research gaps, and give suggestions for future research. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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An n-MOSFET Layout with Multi-Finger Z Gate for Radiation Tolerance 5

An n-MOSFET Layout with Multi-Finger Z Gate for Radiation To...

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5th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2022

作者： Shan, Chan Liu, Ying Chen, Huan Huo, Dong-Yang Xu, Tian-Rong Jimei University College of Ocean Information Engineering Xiamen China Xiamen Institute of Software Technology Department of Software Technology Xiamen China Minjiang University School of Journalism and Communication Fuzhou China Universiti Malaya Faculty of Computer Science and Information Technology Department of Information Systems Kuala Lumpur Malaysia Universiti Malaya Planning Faculty of Built Environment Department of Urban and Regional Kuala Lumpur Malaysia

ISBN: (数字)9781665479295

ISBN: (纸本)9781665479295

In this paper, a new n-MOSFET layout with multi-finger Z gate is proposed to reduce the total ionizing dose (TID) effect. In addition to the proposed layout, multi-finger single gate layout is also simulated using Sentaurus TCAD in 3D. Firstly, drain current - gate voltage curves of both layouts are compared in order to verify the radiation hardening ability of the proposed layout. Secondly, we compare TID responses by extracting threshold voltages and leakage currents from both layouts. Thirdly, the finger number is investigated for both layouts because it is an important factor for multi-finger layout. The results have indicated that the finger number significantly affects the multi-finger single gate layout, whereas the proposed multi-finger Z gate layout is relatively little affected by the finger number in radiation environment. © 2022 IEEE.

关键词： Drain current

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Evaluating Actors' Performance Using Machine Learning for Gesture Classification

Evaluating Actors' Performance Using Machine Learning for Ge...

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Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International

作者： Hossam Ahmed Omar Amr Ayman Atia Software Engineering Department October University for Modern Sciences and Arts (MSA) Cairo Egypt HCI-LAB Faculty of Computers and Artificial Intelligence Helwan University Giza Egypt Faculty of Computer Science October University for Modern Sciences and Arts (MSA) Giza Egypt

ISBN: (数字)9798350367775

ISBN: (纸本)9798350367782

In the context of advancing technologies in the entertainment industry, this study explores the utilization of machine learning (ML) for assessing actors' performances. The integration of technology in that industry is limited. The methodology encompasses acquiring performance ratings from the model to recognize predefined criteria. These ratings are then subjected to comparative analysis to gauge the system's effectiveness. The system showed 83.2% accuracy using MediaPipe to extract the positions of body part points for each gesture. Then, using One Dollar Py library, positive, mediocre, and negative models are developed using the patterns extracted from MediaPipe. We benchmarked the system against an assessment by a professional director. This work suggests a pathway to the use of Machine Learning tools in the industry and could be viewed as an innovative method for automating performance assessment with real-world applications that extend across the film-making process.

关键词： Accuracy Entertainment industry Machine learning Benchmark testing Activity recognition Ubiquitous computing Libraries

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Client Segmentation and Customization in E-Commerce: Applications of Machine Learning from a Management Perspective

Client Segmentation and Customization in E-Commerce: Applica...

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Communication, computer sciences and engineering (IC3SE), International Conference on

作者： Sriprasadh K Shamik Palit B Pravallika Manjunatha Reena Lenka Atul Singla Department of Computer Science and Applications Faculty of Science and Humanities SRM Institute of Science and Technology Vadapalani Chennai Department of Computing Science and Software Engineering RAK Campus University of Stirling UAE Institute of Aeronautical Engineering Hyderabad Department of Mechanical Engineering New Horizon College of Engineering Bangalore Symbiosis Institute of Management Studies Symbiosis International (Deemed) University Pune Lovely Professional University Phagwara India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

A machine learning-based e-commerce personalised recommendation system helps address the issue of information overload that inevitably arises when consumers have more and more options in e-commerce, leading to an increasingly complex structure. Customer segmentation is a crucial component of contemporary marketing strategy since it enables companies to effectively adjust their advertising campaigns and customise their communications with customers. Through the analysis of enormous quantities of consumer behaviour data and the discovery of trends that can be utilised for dividing customers into segments, ML algorithms provide a potent tool for automating the procedure of customer segmentation. We report our research and results for identifying a customer's segment. In order to perform machine learning, we integrate the Python Tensorflow library with Pandas for manipulating data frames. To address any discrepancies or gaps in the collected client data, it is refined. Key features are found, and to find hidden patterns and relationships, an exploratory analysis of the data is done. After that, we decide on a suitable machine learning technique to divide the clientele into various groups. We also experiment with several clustering models, including conventional machine learning techniques.

关键词： Consumer behavior Social networking (online) Machine learning Companies Market research Real-time systems Libraries

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Automating the Diagnosis of Cucumber Plant Diseases Using Machine Learning

Automating the Diagnosis of Cucumber Plant Diseases Using Ma...

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Information Technology (ACIT)

作者： Ahmed BaniMustafa Hazem Qattouz Sattam Almatarneh Khalid Mansour Raed Alazaidah Olla Bulkrock Computer Information Science Dept Higher Colleges of Technology Abu Dhabi UAE Software Engineering Dept Princess Sumaya University for Technology Amman Jordan Data Science & Artificial Intelligence Dept Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah KSA Faculty of Computer Studies Arab-Open University Bahrain Bahrain

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Farmers all over the world struggle to fight plant diseases. However, the incorrect use of pesticides can waste time, effort, and money and can also be very harmful to the environment and human health. In this work, we present an empirical study that involves identifying two pathogens related to Cucumbers plant diseases: Powdery Mildew and Alternaria Cucumerina. The study aims to develop a computer-based solution based on deep learning and machine learning algorithms to detect these diseases. To achieve this, a dataset of hundreds of samples was collected from ordinary farms in Beqaa, an agricultural region 15 KM north of Amman, Jordan. Three machine learning models were created in this study using Support Vector Machines (SVM), Logistic Regression (LR), and Multi-layer perceptron algorithms. The constructed models were applied to the dataset after embedding the dataset images using the Convolutional Neural Networks (CNN) InceptionV3 pre-trained model. The model was tested and evaluated using cross-evaluation and F1-Score, CA, AUC, Precision, Recall, and Specificity, which all showed excellent results, particularly using the SVM algorithm. The constructed methods are intended to be deployed to farms in their field condition environments using a CCTV system that can capture images of plants during growth, which can help identify plant diseases at that right stage, which would save time, effort, and money and reduce the impact of wrong and overuse of pesticides on consumers and the environment.

关键词： Support vector machines Plant diseases Pathogens Machine learning algorithms Pesticides Soil Cameras Real-time systems Mobile applications Convolutional neural networks

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Transformative Applications and Key Challenges of Generative AI

Transformative Applications and Key Challenges of Generative...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Attila Kovari Jozsef Katona Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Department of Institute of Engineering University of Dunaújváros Dunaujvaros Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The paper discusses the integration and use of generative artificial intelligence technologies in education. Generative AI, such as OpenAI, in particular the GPT model, has fundamentally changed the way humans interact with machines. Advanced technologies in the field of generative AI in education are mostly used to personalize learning experiences by dynamically customizing learning materials according to the needs of learners, thus enabling the improvement of outcomes. This article explores the use of generative AI tools with the aim of assessing how useful students perceive these tools to be. The findings show mixed receptivity from users, highlighting the critical balance in using innovative AI capabilities through AI.

关键词： Power engineering Accuracy Generative AI Education Chatbots Market research Problem-solving Reliability

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Model-driven Multi-objective Optimization Approach to 6G Network Planning 15

Model-driven Multi-objective Optimization Approach to 6G Net...

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15th International Conference on Advanced Technologies, Systems and Services in Telecommunications, TELSIKS 2021

作者： Petrovic, Nenad Al-Azzoni, Issam Blank, Julian University of Nis Faculty of Electronic Engineering Aleksandra Medvedeva 14 Nis18000 Serbia Al Ain University Department of Software Engineering and Computer Science Al Ain United Arab Emirates Michigan State University Department of Computer Science and Engineering East Lansing United States

ISBN: (纸本)9781665444422

Ultra high-speed and reliable next-generation 6G mobile networks are recognized as key enablers for many innovative scenarios in smart cities - from vehicular use cases and surveillance to healthcare. However, deployment of such network requires tremendous amount of time and involves various costs. For that reason, optimal network planning is of utmost importance for development of 6G mobile networks in smart cities. In this paper, we explore the potential of multi-objective linear optimization in synergy with model-driven approach in order to achieve efficient network planning in smart cities. As outcome, a solution relying on pymoo is proposed and compared to previous works relying only on single objective implemented in AMPL. According to the achieved results, this approach speeds up the execution, while giving more flexibility when it comes to cost/performance trade-offs. © 2021 IEEE.

关键词： Multiobjective optimization

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Smarter Movement Control Application 5

Smarter Movement Control Application

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5th IEEE International Symposium in Robotics and Manufacturing Automation, ROMA 2022

作者： Hafeez, Yasir Ali, Syed Saad Azhar Moiana, Isaias Johane Shaheen, Ateeq-Ur-Rehman Adil, Syed Hasan Amin, Hafeez Ullah University of Nottingham Malaysia School of Computer Science Faculty of Science and Engineering Semenyih43500 Malaysia King Fahd University of Petroleum and Minerals Aerospace Engineering Department Dhahran31261 Saudi Arabia Universiti Teknologi Petronas Electrical and Electronics Engineering Department Perak Seri Iskandar32610 Malaysia University of Sargodha College of Engineering and Technology Department of Electrical Engineering Punjab Sargodha40100 Pakistan Iqra University Software Engineering Department Karachi Pakistan

ISBN: (数字)9781665459327

ISBN: (纸本)9781665459327

The coronavirus disease 2019 (Covid-19) has devastated the entire globe in a short period of time and was declared a global pandemic by the World Health Organization (WHO) on March 11th, 2020. It rapidly increased in fatality rate and has become an international public health crisis, culminating in social and economic calamity. However, mobile applications are being introduced globally to minimize the coronavirus's continuous spread by tracing people's circulation or mobility using digital software and smartphones. There is no digitally equipped tool that monitors the movement of the people, particularly in the public places. This work on Smarter Movement Control Application (SMCApp) aims to develop methods that will assist Malaysian people to move around with the aid of mobile tracing application. Therefore, the SMCApp was designed and developed as a mobile application software which stands to improve compliance with the mandated SOP measures across the country, as well as to provide digital support to those who wish to travel to various parts of the country. As a result, it is concluded that the usage of Smarter Movement Control Application (SMCApp) is hoped to bring about safe and effective movement of people throughout these two regions, as it will constantly alert individuals of any suspicious close-contact or the state of the location. Once the application is in effect, with at least 90% of users installing the App on their smartphones, it is projected to increase tranquility and elevate compliance with SOP measures. © 2022 IEEE.

关键词： COVID-19

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Early Fault Detection in Rolling Element Bearings Using Signal Processing Techniques

Early Fault Detection in Rolling Element Bearings Using Sign...

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International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Ali Saeed M. Usman Akram Muazzam A. Khan M. Belal Afsar Department of Computer Science ICESCO Chair Big Data Analytics and Edge Computing Quaid-i-Azam University Islamabad Pakistan Department of Computer and Software Engineering National University of Sciences & Technology Islamabad Pakistan Faculty of Electrical Engineering and Information Technology Otto-von-Guericke University Maddeburg DE

ISBN: (数字)9798350378078

ISBN: (纸本)9798350378085

Many studies show that bearings are the most vulnerable components in low-voltage motors. While advanced bearing diagnostic systems exist, their cost can be a barrier for non-critical machinery due to the potential wait time to see a return on investment. This research explores the feasibility of using basic signal processing techniques on vibration data for bearing condition monitoring. The primary goal is to analyze benchmark data from the Case Western Reserve University (CWRU) dataset and establish a baseline performance for this data-driven approach. The results suggest that, with appropriate signal processing, it's possible to achieve early detection of bearing faults, leading to more efficient time-to-fault identification with higher detection accuracies ranging from 83 % to 100 % for each method.

关键词： Vibrations Fault diagnosis Low voltage Smart cities Rolling bearings Signal processing Motors Robots Monitoring Investment

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