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2023 IEEE Virtual Conference on communications, VCC 2023

作者： Elshishtawy, Rhana M. Ali, Shimaa S. Tag Eldien, Adly S. Fouda, Mostafa M. Ismail, Mohamed I. Eid, Esraa M. Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Egypt Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Idaho FallsID United States Department of Electronic Engineering & Communication Technology Modern Academy for Engineering Egypt

ISBN: (纸本)9798350318807

This paper presents a comprehensive investigation into the effect of Electromagnetic Interference (EMI) on wireless systems employing single and distributed Intelligent Reflecting Surfaces (IRSs) in three distinct conditions by varying the number of antennas, elements, and users. Through extensive numerical simulations, the performance of the wireless systems is rigorously evaluated under different EMI scenarios. Firstly, the influence of varying the number of antennas on the system performance is thoroughly analyzed. The results demonstrate that an increased number of antennas contributes to improved signal reception and reduced interference levels. Moreover, the enhanced beamforming capabilities offered by additional antennas lead to higher signal quality and increased system Achievable Rate (AR). Secondly, the impact of changing the number of elements within the IRS under EMI conditions is investigated in detail. The simulations reveal that an augmented number of elements facilitates efficient EMI mitigation, enabling advanced signal manipulation and more precise signal focusing. As a result, the system exhibits improved performance in terms of signal strength, coverage, and AR. Lastly, the effect of varying the number of users on system performance in the presence of EMI is thoroughly assessed. The findings unveil that an increased number of users under EMI conditions leads to elevated interference levels, degraded signal quality, and diminished system AR. Thus, it is crucial to develop effective EMI mitigation strategies and resource allocation schemes to ensure reliable and efficient communication in IRS-enabled wireless systems. © 2023 IEEE.

关键词： MIMO systems

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A Novel Determination of Soluble NPK Nutrient Measurement system Using K-means and SOM Methods Compared with UV Visible Spectrophotometer

A Novel Determination of Soluble NPK Nutrient Measurement Sy...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University of Technology Krungthep Department of Electrical and Telecommunication Engineering Bangkok Thailand Thammasat School of Engineering Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department of Robotic Engineering and Automation System Bangkok Thailand

ISBN: (纸本)9798350332360

Technologies are currently being used in smart farms to improve productivity. Agricultural innovation is also widespread. Therefore, the development of Internet of Things (IoTs) technologies and devices to collect data is important. Finding essential nutrients for growth such as Nitrogen (N), Phosphorus (P) and Potassium (K) are important factors. Competitiveness is the important key for growing vertically or indoors. However, soil testing can be expensive, complicated and time consuming. The development of devices that can effectively measure nutrient NPK levels could be used over time. This paper presents a suitable clustering using the K-means method and a forecasting method using the Self-Organizing Map (SOM) method to enhance the device's ability to analyze nutrients in real time. A total of 50,688 samples were tested using the K-Means clustering algorithm, and the sample data were also analyzed. A SOM was prepared to predict the accuracy of the analysis. A total of 11,486 samples were tested and analyzed, then the results of the soluble NPK nutrient monitoring system were taken. It has an efficiency of 84.15% compared to using a UV Visible spectrophotometer, allowing data to be predicted during nutrient solubility changes and to operate according to the proposed system. Therefore, the unsupervised machine learning will improve the measurement system of future cultivation systems. © 2023 IEEE.

关键词： Nutrients

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Cephalopods Classification Using Fine Tuned Lightweight Transfer Learning Models

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Intelligent Automation & Soft Computing 2023年第3期35卷 3065-3079页

作者： P.Anantha Prabha G.Suchitra R.Saravanan Department of Computer Science&Engineering Sri Krishna College of TechnologyCoimbatore641042Tamil NaduIndia Department of Electronics and Communication Engineering Government College of TechnologyCoimbatore641013Tamil NaduIndia Department of Marine Pharmacology Faculty of Allied Health SciencesChettinad Academy of Research and EducationKelambakkamChengalpattu603103Tamil NaduIndia

Cephalopods identiﬁcation is a formidable task that involves hand inspection and close observation by a *** observation and iden-tiﬁcation take time and are always contingent on the involvement of experts.A system is proposed to alleviate this challenge that uses transfer learning techni-ques to classify the cephalopods *** the proposed method,only the Lightweight pre-trained networks are chosen to enable IoT in the task of cephalopod ***,the efﬁciency of the chosen models is determined by evaluating their performance and comparing theﬁ***,the models areﬁne-tuned by adding dense layers and tweaking hyperparameters to improve the classiﬁcation of *** models also employ a well-tuned Rectiﬁed Adam optimizer to increase the accuracy ***,Adam with Gradient Cen-tralisation(RAdamGC)is proposed and used inﬁne-tuned models to reduce the training *** framework enables an Internet of Things(IoT)or embedded device to perform the classiﬁcation tasks by embedding a suitable lightweight pre-trained ***ﬁne-tuned models,MobileNetV2,InceptionV3,and NASNet Mobile have achieved a classiﬁcation accuracy of 89.74%,87.12%,and 89.74%,***ﬁndings have indicated that theﬁne-tuned models can classify different kinds of *** results have also demonstrated that there is a signiﬁcant reduction in the training time with RAdamGC.

关键词： Cephalopods transfer learning lightweight models classiﬁcation deep learning ﬁsh IoT

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Enhancing IT Risk Management in XYZ Vocational School: Leveraging COBIT 5 Framework with the APO12 Domain

Enhancing IT Risk Management in XYZ Vocational School: Lever...

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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent systems, ICETSIS 2024

作者： Winanti Fernando, Erick Gate, Jullend Universitas Insan Pembangunan Department of Information Systems Indonesia Universitas Multimedia Nusantara Information System Faculty of Engineering and Informatics Tangerang Indonesia Bina Nusantara University Binus Online Learning Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350372229

This article explores the importance of IT risk management, especially at XYZ Vocational School. The agency is equipped to manage business risks, emphasizing the need to improve decision-making and risk mitigation by identifying potential hazards and evaluating internal and external threats, including hacking risks. The research investigates IT risk management at XYZ Vocational School using a qualitative and quantitative method with a focus on the APO12 COBIT 5 domain: Align, plan, and organize. It assesses subdomains such as data collection, risk analysis, profile maintenance, risk articulation, portfolio management, and response strategies. Conclusively, the research reveals institutional IT capabilities at level 1 (Performed Process) in the APO12 subdomain. Recommendations include developing COBIT-compliant SOPs for processes at this level, highlighting the need for further improvements in IT governance. This study provides valuable insights into IT risk management practices, offering recommendations for improving IT governance in educational settings. © 2024 IEEE.

关键词： APO12 Domain COBIT 5 Information technology Risk Management Vocational School

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Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

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computer Modeling in engineering & Sciences 2022年第3期130卷 1309-1324页

作者： Rizwan Taj Feng Tao Shahzada Khurram Ateeq Ur Rehman Syed Kamran Haider Akber Abid Gardezi Saima Kanwal School of Computer and Communication Lanzhou University of TechnologyLanzhouChina Faculty of Computing The Islamia University of BahawalpurBahawalpurPakistan Department of Electrical Engineering Government College UniversityLahorePakistan College of Internet of Things Engineering Hohai UniversityChangzhouChina Department of Computer Science COMSATS University IslamabadIslamabadPakistan

In telemedicine,the realization of reversible watermarking through information security is an emerging research ***,adding watermarks hinders the distribution of pixels in the cover image because it creates distortions(which lead to an increase in the detection probability).In this article,we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high *** proposed method selects two adjacent gray pixels whose least significant bit(LSB)is different from the relevant message bit and then calculates the distortion *** use the LSB pairing method to embed the secret matrix of patient record into the cover image and exchange pixel *** results show that the designed method is robust to different attacks and has a high PSNR(peak signal-to-noise ratio)*** MRI image quality and imperceptibility are verified by embedding a secret matrix of up to 262,688 bits to achieve an average PSNR of 51.657 *** addition,the proposed algorithm is tested against the latest technology on standard images,and it is found that the average PSNR of our proposed reversible watermarking technology is higher(i.e.,51.71 dB).Numerical results show that the algorithm can be extended to normal images and medical images.

关键词： LSB reversible watermarking medical images security data distortion

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Analysis of integration of IoMT with blockchain: issues, challenges and solutions

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Discover Internet of Things 2024年第1期4卷 21页

作者： Mazhar, Tehseen Shah, Syed Faisal Abbas Inam, Syed Azeem Awotunde, Joseph Bamidele Saeed, Mamoon M. Hamam, Habib Department of Computer Science Virtual University of Pakistan Lahore55150 Pakistan Department of Artificial Intelligence and Mathematical Sciences Sindh Madressatul Islam University Karachi74000 Pakistan Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Sana’a Yemen Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Electrical and Electronic Engineering Science University of Johannesburg Auckland Park Johannesburg2006 South Africa Av. Grandes Ecoles LibrevilleBP 1989 Gabon Bridges for Academic Excellence Spectrum Tunis Tunisia

The incorporation of Artificial Intelligence (AI) into the fields of Neurosurgery and Neurology has transformed the landscape of the healthcare industry. The present study describes seven dimensions of AI that have transformed the way of providing care, diagnosing, and treating patients. It has exhibited unparalleled accuracy in analyzing complex medical imaging data and expediting precise diagnoses of neurological conditions. It has also enabled personalized treatment plans by harnessing patient-specific data and genetic information, promising more effective therapies. For instance, AI-powered surgical robots have brought precision and remote capabilities to neurosurgical procedures, reducing human error. In AI, machine learning models predict disease progression, optimizing resource allocation and patient care, whereas wearable devices with AI provide continuous neurological monitoring, and enable early intervention for chronic conditions. It has also accelerated drug discovery by analyzing vast datasets, potentially leading to breakthrough therapies. Chatbots and virtual assistants powered by AI, enhance patient engagement and adherence to treatment plans. It holds promise in further personalization of care, augmented decision-making, earlier intervention, and the development of groundbreaking treatments. The present study mainly focuses on the incorporation of blockchain technology and provides a reasonable understanding of the associated issues and challenges along with its solutions. It will allow AI and healthcare professionals to advance the field and contribute towards the improvement of an individual's well-being when facing neurological challenges. © The Author(s) 2024.

关键词： Neurosurgery

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Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform

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Light(Science & Applications) 2025年第3期14卷 746-756页

作者： Na Qian Defu Zhou Haowen Shu Ming Zhang Xingjun Wang Daoxin Dai Xiao Deng Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBejingChina State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityHangzhouChina

Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial ***,broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic ***,we report an analog parallel processor(APP)based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog *** APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel *** photonic analog parallelism,data rate and data volume in each sequence are simultaneously compressed,which mitigates the requirement on each parallel computing ***,the fusion of the outputs from each computing core is equivalent to directly processing broadband *** the proof-of-concept experiment,two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated *** bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is *** wireless communication rate of 8 Gbit/s is also *** the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture,we anticipate that the proposed APP will accelerate the development of powerful optoelectronic processors as critical support for applications such as satellite networks and intelligent driving.

关键词： analog parallel processor sharing hardware platform multifunctional integrated systems establish full cooperation different functionalities analog parallel processor app based silicon photonic platform electronic circuitryherewe broadband signal

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Intelligent Caching Strategies for 5G Edge Networks using Machine Learning 4

Intelligent Caching Strategies for 5G Edge Networks using Ma...

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4th International Conference on Smart Electronics and communication, ICOSEC 2023

作者： Guduri, Naga Venkata Ramakrishna Sethu, S. Shalinirajan, R. Reena, R. Karthikeyan, M. Uthayakumar, G.S. University of Technology and Applied Sciences-Al Musannah Electrical and Electronics Section Engineering Department Oman Department of Computer Science and Engineering Tamilnadu Chennai India Panimalar Engineering College Department of Computer Science and Business System Tamilnadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India Tamilnadu Chennai India St. Joseph's Institute of Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350300888

To reduce latency and improve the user experience, content caching solutions at the network periphery will become increasingly important as 5G networks and data-intensive applications. In this proposed work, the deployment of a caching architecture for 5G periphery networks using machine learning is done. Utilizing information on user behavior, network conditions, and content prominence enables more accurate forecasts and cache management decisions. This trains the prediction models using a wide range of machine-learning techniques to accommodate the ever-changing needs of both networks and content. To evaluate the efficiency of the proposed architecture by measuring its ability to increase cache hit rates and decrease latency. These techniques significantly outperform the standard caching methods. With the intelligent caching architecture of 5G periphery networks, throughput is increased, latency is reduced, and congestion is alleviated. The findings of this study contribute to the growing corpus of literature on AI-driven optimization in 5G networks and shed light on how such solutions could be enhanced for future networks. Neural Networks achieved 96% accuracy than SVM which is 93%. © 2023 IEEE.

关键词： 5G mobile communication systems

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Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

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computers, Materials & Continua 2023年第3期74卷 6461-6484页

作者： Abeer Bashab Ashraf Osman Ibrahim Ibrahim Abakar Tarigo Hashem Karan Aggarwal Fadhil Mukhlif Fuad A.Ghaleb Abdelzahir Abdelmaboud Faculty of Computer Science&Information Technology Alzaiem Alazhari University13311KhartoumSudan Faculty Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400SabahMalaysia Department of Computer Science University of SharjahSharjah27272United Arab Emirates Electronic and Communication Engineering Department Maharishi Markandeshwar Deemed to be UniversityMullanaAmbala133207HaryanaIndia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi Malaysia81310JohorMalaysia Department of Information Systems King Khaled UniversityMuhayel61913AseerSaudi Arabia

University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.

关键词： University timetabling timetabling approaches meta-heuristics combinatorial optimization

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A Robust Development of Calorie Prediction Methodology based on Artificial Intelligence Assisted Machine Learning Model 4

A Robust Development of Calorie Prediction Methodology based...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Naga Venkata Ramakrishna, G. Sreelakshmi, S. Diwakar, Meenakshi Ramkumar, S. Vinithra Banu, T. Thilagam, T. University of Technology and Applied Sciences Al Musannah Faculty of Engineering Oman Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Tamil Nadu Chennai India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Tamil Nadu Chennai India S.A Engineering College Department of Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350349900

Modern people's hectic schedules are a direct result of the ways they live and the responsibilities they have at work. On the other hand, maintaining a healthy lifestyle demands consistent physical exertion. Obesity is a result of people not paying attention to what they eat. As a result of modern living, obesity is on the rise. As a result, in order to maintain a healthy weight, people pick their food and exercise habits accordingly. People should know how many calories they consume and how many calories they burn. Calorie counts are easy to get online or on product labels, so it's not hard to keep track of one's calorie intake. There aren't many tools available to help you keep track of the calories you burn. To keep up with the hectic pace of modern life and the constant search for shortcuts, we built a system that uses machine learning to track post-workout calorie burn and development. By taking a few attributes as input, this system can approximate the calories burned, which will show daily growth and motivate people to exercise more. This paper presents an innovative ML model for accurate calorie prediction;it's called the Improved Learning Model for Calorie Prediction (ILMCP). To test how well it works, the authors cross-validate it with the traditional Extreme Gradient Boosting (XGBoost) algorithm. As a result, it is the quickest approach and may be utilized for object identification in real-time. Next, we'll apply the ILMCP algorithm to the picture for segmentation. Foreground extraction with little to no user input requires it. Following picture segmentation, we use the probing object's known volume to determine the food item's volume. Once the volume has been determined, the food item's mass may be determined using formulae. Then, the connection between weight and calories can be used to compute the food item's calories. © 2024 IEEE.

关键词： Image segmentation

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