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Using Artificial Intelligence in the Internet of Things

ZTE Communications 2015年第2期13卷 1-2页

作者： Fuji Ren Yu Gu Faculty of Engineering University of Tokushima Japan Federation of Engineering Societies the International Advanced Information Institute School of Computer and Information Hefei University of Technology

The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （and related problems） are becoming more complex and uncertain. Researchers have therefore turned to artificial intelligence （AI） to efficiently deal with the problems ereated by big data.

关键词： AI data Using Artificial Intelligence in the Internet of Things WSN

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Determining Network Performance Through Bandwidth Optimization in Underwater Fiber Optic Communication 3

Determining Network Performance Through Bandwidth Optimizati...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Diwakar, Mandar P. Beemkumar, N. Yadav, Dhananjay Mishra, Varun Khandari, Harsimrat Divya, K. Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Department of Mechanical Engineering Faculty of Engineering and Technology Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India

ISBN: (纸本)9798350319125

information the overall performance of underwater fiber optic (UWFO) communique networks is vital for a hit deployment of this technology in an expansion of applications. That allows you to achieve most efficient community overall performance, bandwidth optimization must be hired. This paper examines distinctive bandwidth optimization techniques and how they're used to improve conversation among UWFO elements. The proposed approach utilizes adaptive modulation and coding techniques, as well as advanced error correction coding schemes, to efficiently utilize the available bandwidth and minimize signal degradation. Through extensive simulations and experiments, we demonstrate the effectiveness of our approach in improving network performance, including increased data transfer rates and reduced error rates, compared to traditional methods. Our findings have significant implications for the design and operation of underwater fiber optic communication systems, potentially enhancing their potential for a wide range of applications in marine environments. In the end, several destiny studies guidelines are diagnosed to in addition enhance the overall performance and reliability of UWFO conversation networks. © 2023 IEEE.

关键词： Communiqué Conversation Investigates Networks Optimization

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Amazon in business to customers and overcoming obstacles 2

Amazon in business to customers and overcoming obstacles

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2nd International Conference on Smart Computing and Electronic Enterprise, ICSCEE 2021

作者： Altrad, Abdullah Pathmanathan, P. Ravindran Al Moaiad, Yazeed Endara, Yousef Mohamed Aseh, Khairi El-Ebiary, Yousef A. Baker Farea, Mazen Mohammed Latiff, Nurul Adilah Abdul Saany, Syarilla Iryani Ahmad Faculty of Computer and Info. Tech. Al Madinah International University Malaysia International Institute of Applied Science Swiss School of Management Netherlands Faculty of Computer and Information Technology Malaysia Misurata University Libya UniSZA Faculty of Informatics and Computing Malaysia Al-Madinah International University Faculty of Finance and Admin. Sciences Malaysia Universiti Malaysia Terengganu Faculty of Ocean Engineering Technology and Informatics Malaysia

ISBN: (纸本)9781665432221

Electronic commerce, or people call it e-commerce, it refers to buying and selling products or services on the Internet and transferring money and data to carry out these transactions. More consumers are shifting from traditional transactions to e-commerce, as e-commerce becomes faster and cheaper. In contrast, electronic commerce provides more ease and variety in the composition of goods and services worldwide. E-commerce is the type of electronic business that has been in business for more than 25 years and is used by many users around the world. This research aims to shed light on the nature of electronic commerce and the difficulties it faces on the technical side. This research used descriptive methodology after gathering data from online and indexed research. The research also mentioned five of these obstacles, and how the Amazon overcomes them, and we will take a look at how the opportunities of the Amazon grow so that they have an effect called the Amazon effect, the research reached an important conclusion that eDesk is the leading help desk for online sellers, specifically designed to meet the exact requirements of e-commerce. The research also found solutions to some of the weaknesses faced by electronic commerce platforms. © 2021 IEEE.

关键词： Electronic commerce

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Power Generation Improvement using Active Water Cooling for Photovoltaic (PV) Panel 4

Power Generation Improvement using Active Water Cooling for ...

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4th International Conference on Electrical, computer and Communication Technologies, ICECCT 2021

作者： Rahim, Mohamad Shukor Bin Abdul Tajuddin, Mohammad Faridun Naim Bin Saad, Mohd Sazli Nalini, C. Edaris, Zahratul Laili Bt Hasanuzzaman, Md. Faculty of Electrical Engineering Technology Perlis Arau02600 Malaysia Kongu Engineering College Department of Information Technology Erode India Politeknik Tuanku Syed Sirajuddin Department of Mathematics Science and Computer Perlis Arau02600 Malaysia Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781665414807

Photovoltaic (PV) cooling systems are commonly used to improve photovoltaic panels power generation and efficiency. Photovoltaic (PV) panels require irradiance to generate power, although increasing irradiance is often correlated with increasing temperature. These rapid increases of temperature in photovoltaic (PV) panels severely affect the power conversion operation. With a proper cooling process on its surface, a solar photovoltaic (PV) system can operate at a higher efficiency. This research aims to study the power improvement of active water-cooling on photovoltaic (PV) panels. A fixed minimum water flow of 5.80 l/min is sprayed onto the panel's front surface to reduce the temperature. The sprayed water created a thin water film and managed to reduce the temperature. Other than that, there is also reference photovoltaic (PV) panel, which is a panel without any cooling system. The outputs compared are the module temperature, maximum output power, open circuit voltage, and short circuit current. As the irradiance starts increasing, the panel temperature also begins to spike. However, with active water cooling, the temperature was able to be reduced by 37.67% during the day's hottest temperature. This reduction of temperature creates power improvement to the cooled panel up to 253W, compared to the reference panel output of only 223W. During the overheating of a photovoltaic (PV) panel, the open circuit voltage was found to be the most affected. This increase in power with active water cooling can potentially have a massive impact on large-scale photovoltaic (PV) panel installations. © 2021 IEEE.

关键词： Solar panels

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Data-efficient Large Vision Models through Sequential Autoregression 41

Data-efficient Large Vision Models through Sequential Autore...

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41st International Conference on Machine Learning, ICML 2024

作者： Hao, Zhiwei Guo, Jianyuan Wang, Chengcheng Tang, Yehui Wu, Han Hu, Han Han, Kai Xu, Chang School of Information and Electronics Beijing Institute of Technology Beijing China School of Computer Science Faculty of Engineering University of Sydney Sydney Australia Huawei Noah's Ark Lab Beijing China

Training general-purpose vision models on purely sequential visual data, eschewing linguistic inputs, has heralded a new frontier in visual understanding. These models are intended to not only comprehend but also seamlessly transit to out-of-domain tasks. However, current endeavors are hamstrung by an over-reliance on colossal models, exemplified by models with upwards of 3B parameters, and the necessity for an extensive corpus of visual data, often comprising a staggering 400B tokens (Bai et al., 2023). In this paper, we delve into the development of an efficient, autoregression-based vision model, in-novatively architected to operate on a limited dataset. We meticulously demonstrate how this model achieves proficiency in a spectrum of visual tasks spanning both high-level and low-level semantic understanding during the testing phase. Our empirical evaluations underscore the model's agility in adapting to various tasks, heralding a significant reduction in the parameter footprint, and a marked decrease in training data requirements, thereby paving the way for more sustainable and accessible advancements in the field of generalist vision models. The code is available at https://***/ggjy/DeLVM. Copyright 2024 by the author(s)

关键词： Spatio-temporal data

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Exploring Post Quantum Blockchain Technologies: Potential and Challenges in Digital Forensics Applications 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Rajawat, Anand Singh Goyal, S.B. Joshi, Poonam Solanki, Ram Kumar Singh, Kuldeep Deaprtment of CSE Sandip University Nashik422213 India Faculty of Information Technology City University Petaling Jaya46100 Malaysia Department of Computer Engineering Thakur College of Engineering and Technology Mumbai400101 India GL Bajaj Institute of Technology and Management Greater Noida201306 India

ISBN: (数字)9783031508875

ISBN: (纸本)9783031508868

As the world prepares for the arrival of quantum computing, numerous conventional cryptographic methods confront imminent vulnerabilities. The field of post-quantum cryptography endeavors to construct cryptographic algorithms that are impervious to the potential threats presented by quantum computers. The technology underlying cryptocurrencies, known as blockchains, heavily rely on cryptographic security and consequently assume a pivotal role in the quantum era. This scholarly article investigates the potential of post-quantum blockchain technologies and their implications in the realm of digital forensics applications. We initiate with a comprehensive overview of the fundamental concepts of post-quantum cryptography and delve into its applicability within the blockchain domain. The potential advantages of integrating post-quantum techniques into blockchain technologies encompass heightened security against quantum attacks, lengthened cryptographic life cycles, and the establishment of platforms that ensure forensic soundness. Nevertheless, along with these potential benefits, challenges also emerge. The increased complexity of post-quantum algorithms may result in lengthier transaction du-rations, augmented computational requirements, and issues pertaining to scalability. Moreover, from the perspective of digital forensics, the robustness of post-quantum blockchains may introduce intricacies in data retrieval, evidence authentication, and cross-jurisdictional investigations. The study assesses a variety of post-quantum blockchain projects currently under development, evaluating their strengths and limitations within the context of digital forensics. In conclusion, while post-quantum blockchains offer a new frontier of security and forensic reliability, their effective implementation necessitates a harmonious balance between cryptographic robustness, practicality, and the evolving needs of digital forensic practitioners. © The Author(s), under exclusive license to S

关键词： Quantum cryptography

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Prediction of Electrical Characteristics of a-IGZO TFT Based on Transfer Learning-Based Variational Autoencoder

Prediction of Electrical Characteristics of a-IGZO TFT Based...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bea, Khean-Thye Wei-Hsuan Lin, Shih-Shin Hu Lin, Da-Zheng Hu, Hsin-Hui Chen, Xiu-Zhi Lin, Ting-Ru Chen, Yen-Lin Chen, Kun-Ming Cheng, Wai Khuen National Taipei University of Technology Dep. of Electronic Engineering Taipei106 Taiwan National Taipei University of Technology Dep. of Computer Science and Information Engineering Taipei106 Taiwan Taiwan Semiconductor Research Institute Hsinchu30078 Taiwan Universiti Tunku Abdul Rahman Faculty of Information and Communication Technology Kampar31900 Malaysia

ISBN: (纸本)9798350337020

In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation. © 2023 IEEE.

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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Evaluation of Three Different Operators for Object Highlighting in Medical RGB Images: Canny, Roberts, and LoG in Independent Color Spaces 25

Evaluation of Three Different Operators for Object Highlight...

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25th International Arab Conference on information technology, ACIT 2024

作者： Ababneh, Jafar Abu-Jassar, Amer Abuowaida, Suhaila Liubchenko, Valentyn Lyashenko, Vyacheslav Zarqa University Faculty of Information Technology Cyber Security Department Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Amman Arab University College of of Computer Sciences and Information Amman Jordan Al Al-Bayt University Faculty of Information Technology Department of Computer Science Al-Mafraq Jordan Kharkiv National University of Radio Electronics Department of Informatics Kharkiv Ukraine Kharkiv National University of Radio Electronics Department of Media Systems and Technology Kharkiv Ukraine

ISBN: (纸本)9798331540012

The research presents a comparative analysis of the selection of objects of interest in color medical cytology images. For these purposes, the individual edge detection operators studied are Canny, Roberts, and LoG. The comparison contrasts the standard method of assessing color photographs with a technique that incorporates supplementary information. Data from individual color channels, derived from the breakdown of a color image in RGB format, serve as supplementary information. The following individual cases for potential examination are emphasized: Image processing with a complete level of reuse of edge detection operators;with a partial level of reuse of edge detection operators. The results are displayed through an array of tables, graphs, and images. Metrics of visual perception of images are utilized for comparative analysis. Compared with traditional edge detection methods, the proposed approach yields better results, which can exceed the estimates of the classical approach by 20%. © 2024 IEEE.

关键词： Color photography

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Image Splicing Detection Based on Texture Features with Fractal Entropy

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computers, Materials & Continua 2021年第12期69卷 3903-3915页

作者： Razi J.Al-Azawi Nadia M.G.Al-Saidi Hamid A.Jalab Rabha W.Ibrahim Dumitru Baleanu Department of Laser and Optoelectronics Engineering University of TechnologyBaghdad10066Iraq Department of Applied Sciences University of TechnologyBaghdad10066Iraq Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala Lumpur50603Malaysia IEEE:94086547 Kuala Lumpur59200Malaysia Department of Mathematics Cankaya UniversityBalgat06530AnkaraTurkey Institute of Space Sciences R76900 Magurele-BucharestRomania Department of Medical Research China Medical UniversityTaichung40402Taiwan

Over the past years,image manipulation tools have become widely accessible and easier to use,which made the issue of image tampering far more *** a direct result to the development of sophisticated image-editing applications,it has become near impossible to recognize tampered images with naked ***,to overcome this issue,computer techniques and algorithms have been developed to help with the identification of tampered *** on detection of tampered images still carries great *** the present study,we particularly focus on image splicing forgery,a type of manipulation where a region of an image is transposed onto another *** proposed study consists of four features extraction stages used to extract the important features from suspicious images,namely,Fractal Entropy(FrEp),local binary patterns(LBP),Skewness,and *** main advantage of FrEp is the ability to extract the texture information contained in the input ***,the“support vector machine”(SVM)classification is used to classify images into either spliced or *** analysis shows that the proposed algorithm performs better than recent state-of-the-art of splicing detection ***,the proposed algorithm achieves an ideal balance between performance,accuracy,and efficacy,which makes it suitable for real-world applications.

关键词： Fractal entropy image splicing texture features LBP SVM

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