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Propagation Characterization and Analysis for 5G mmWave Through Field Experiments

computers, Materials & Continua 2021年第8期68卷 2249-2264页

作者： Faizan Qamar Mhd Nour Hindia Tharek Abd Rahman Rosilah Hassan Kaharudin Dimyati Quang Ngoc Nguyen Centre for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia(UKM)43600BangiSelangorMalaysia Department of Electrical Engineering Faculty of EngineeringUniversity of Malaya50603Kuala LumpurMalaysia Wireless Communication Centre Faculty of Electrical EngineeringUniversiti Teknologi Malaysia81310SkudaiJohorMalaysia Department of Computer Science and Communications Engineering Faculty of Science and EngineeringWaseda UniversityTokyo169-8050Japan

The 5G network has been intensively investigated to realize the ongoing early deployment stage as an effort to match the exponential growth of the number of connected users and their increasing demands for high throughput,bandwidth with Quality of Service(QoS),and low *** that most of the spectrums below 6 GHz are nearly used up,it is not feasible to employ the traditional spectrum,which is currently in ***,a promising and highly feasible effort to satisfy this insufficient frequency spectrum is to acquire new frequency bands for next-generation mobile *** this end,the primary effort has been focused on utilizing the millimeter-wave(mmWave)as the most promising candidate for the frequency ***,though the mmWave frequency band can fulfill the desired bandwidth requirements,it has been demonstrated to endure several issues like scattering,atmospheric absorption,fading,and especially penetration losses compared to the existing sub-6 GHz frequency ***,it is fundamental to optimize the mmWave band propagation channel to facilitate the practical 5G implementation for the network ***,this study intends to investigate the outdoor channel characteristics of 26,28,36,and 38 GHz frequency bands for the communication infrastructure at the building to the ground floor in both Line of Sight(LOS)and Non-Line of Sight(NLOS)*** experimental campaign has studied the propagation path loss models such as Floating-Intercept(FI)and Close-In(CI)for the building to ground floor environment in LOS and NLOS *** findings obtained from the field experiments clearly show that the CI propagation model delivers much better performance in comparison with the FI model,thanks to its simple setup,accuracy,and precise function.

关键词： 5G mmWave propagation channel path loss channel characterization field experiment

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NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System 2

NFT-Based Hydroponic Automated Control Using Adaptive Networ...

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2nd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2022

作者： Surantha, Nico Vincentdo, Vito Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Tokyo City University Faculty of Scienc and Engineering Department of Electrical Electronics and Communication Engineering Japan

ISBN: (纸本)9781665459440

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined. © 2022 IEEE.

关键词： Hydroponics

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A Gradient Boosting Algorithm to Predict Energy Consumption for Home Applications 2

A Gradient Boosting Algorithm to Predict Energy Consumption ...

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2nd International Conference on computer, communication and Control, IC4 2024

作者： Sivakumar, V.G. Arunfred, N. Anusha, N. Balakrishnan, C. Meenakshi, B. Sujatha, S. Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Srm Institute of Science and Technology Faculty of Management Studies Kattankulathur Chengalpattu Tamil Nadu Chennai India Vellore Institute of Technology School School of Computer Science and Engineering Department of IoT Tamil Nadu Vellore India S.A.Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

Energy-efficient solutions are in high demand in today's fast-developing technological environment, necessitating the use of sophisticated predictive modeling methods. Conventional forecasting systems have problems given the particular aspects related to home demand for energy. As a consequence, new strategies are constantly being created for more accurately foreseeing future occurrences. Weather, user habits, and advancements in technology interfere with precise forecasts even more. This study provides a novel application of the Gradient Boosting approach to solve such obstacles and enhance energy use prediction for residential applications. Through utilising the electrical energy of Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), the suggested method takes into account prior use patterns, appliance-specific data, and external factors like as climate. The model's response to changes in the actual world provides exact estimates, providing homeowners with the information they require to make energy-saving decisions. This method also investigates the comprehending of Gradient Boosting models, showing key characteristics that affect energy usage patterns. Stakeholders focus heavily on interpretability to make informed decisions with regard to ways to save energy and resource allocation. © 2024 IEEE.

关键词： Machine learning

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Real-Time Face Mask Detector 3

Real-Time Face Mask Detector

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3rd IEEE International Conference on Technology, engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Patel, Vishwajeet Guru Prasad, M.S. Aditya Pai, H. Kumar, A Suresh Praveen Gujjar, J. Naveen Kumar, H.N. Dept. of Computer Science and Engg. Dehradun India JAIN [Deemed-to-be University Faculty of Management Studies Bengaluru India Vidyavardhaka College of Engineering Dept. of Electronics and Communication Engg. Karnataka Mysuru India

ISBN: (纸本)9798350397819

When the COVID-19 pandemic was present we all have faced various challenges in our everyday lives. Pandemic created worldwide emergency which led to the lockdown in most of the countries resulting into disruption in world trade and movement. To reduce the covid cases WHO recommended to wear mask and maintain social distancing and then these steps became mandatory for some places, such as restaurants, hospitals, grocery stores etc., The purpose of limiting interaction with individuals as much as possible in such situations is simply defeated by having a staff personally check each person to make sure their mask is on. To avoid this dilemma, it became necessary to build a project named 'Real-time face mask detector', This reveals whether a mask-wearing individual is there. This project needed the use of some python libraries like TensorFlow, Keras, OpenCV. Using this project, we will be able to Detect mask-on faces in live video clip with accuracy of 97-98 %. © 2023 IEEE.

关键词： COVID-19

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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm

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computers, Materials & Continua 2023年第8期76卷 2261-2279页

作者： Ayman Khallel Al-Ani Shams Ul Arfeen Laghari Hariprasath Manoharan Shitharth Selvarajan Mueen Uddin Cybersecurity Research Group Faculty of Computing and InformaticsUniversity Malaysia SabahJalan UMSKota KinabaluSabah88400Malaysia National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaGelugorPenang11800Malaysia Department of Electronics and Communication Engineering Panimalar Engineering CollegePoonamalleeChennai600123TamilnaduIndia Department of Computer Science&Engineering Kebri Dehar UniversityKebri Dehar250Ethiopia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar

In this paper,the application of transportation systems in realtime traffic conditions is evaluated with data handling *** proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the *** to the existing approach,the design model in the proposed method is made by dividing the computing areas into several cluster regions,thereby reducing the complex monitoring system where control errors are ***,a route management technique is combined with Artificial Intelligence(AI)algorithm to transmit the data to appropriate central ***,the combined objective case studies are examined as minimization and maximization criteria,thus increasing the efficiency of the proposed ***,four scenarios are chosen to investigate the projected design’s *** all simulated metrics,the proposed approach provides better operational outcomes for an average percentage of 97,thereby reducing the amount of traffic in real-time conditions.

关键词： Transportation Artificial Intelligence(AI) data-driven Internet of Things(IoT)

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Leveraging Artificial Intelligence in Online Educational Platforms to Enhance Continuous Professional Development in the Teaching Profession 2

Leveraging Artificial Intelligence in Online Educational Pla...

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Amankulovich, Khujakulov Sherzod Tokhirovich, Mannabov Javlon Bakhridinovich, Kadirov Tulkin Kuvandikovich, Taylakov Umid Ananth, Christo Kumar, T. Ananth Samarkand Regional National Center for Training Teachers in New Methods Uzbekistan Uzbekistan Samarkand Agroinnovations and Research University Uzbekistan Samarkand State University Uzbekistan&Adjunct Faculty Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Avadi Chennai India Ifet College of Engineering Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350364699

To keep up with the dynamic nature of the modern classroom, teachers must have access to online learning platforms for professional development purposes. This investigation looks at how these platforms can be used to improve teachers' skills, make information sharing easier, and open doors to CPD opportunities. This study examines the relationship between online resources and methods to demonstrate how digital tools have an impact on teacher training and professional development by leveraging AI. It also draws attention to the fact that these platforms are helping with information-methodological support for teachers as well as the ongoing reforms in our nation. Incorporating empirical observations and case studies, the analysis demonstrates how effective online platforms are in fostering a collaborative and innovative environment for professional learning. Digital transformation has the potential to radically alter how teachers obtain professional development, and this study emphasizes that fact. This will enable teachers to effectively address the demands of modern classrooms. © 2024 IEEE.

关键词： Contrastive Learning

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An Internet of Things Assisted Autism Spectrum Disorder Prediction Using Deep Learning Principles with Medical Image Processing Assistance

An Internet of Things Assisted Autism Spectrum Disorder Pred...

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2024 International Conference on Innovative Computing, Intelligent communication and Smart Electrical Systems, ICSES 2024

作者： Bindhu, A. Mol, A. Sruthi Ravi, T. Bodkhe, R.G. Safori, Amjad Omar Vijayalakshmi, S. Infant Jesus College of Arts and Science for Women Department of Computer Science Mulagumoodu India Sathyabama Institute of Science and Technology Department of Ece Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India R.M.K. Engineering College Department of Electronics and Communication Engineering Chennai India Zaraa University Faculty of Media Department of Journalism and Digital Media Zaraa 13110 Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

Characteristics of the complex neuro-developmental condition Autism Spectrum condition (ASD) include impaired social communication and restricted, repetitive patterns of behavior. This study presents a novel approach for identifying ASD in young infants by integrating deep learning, Internet of Things (IoT) and medical image processing. The goal of this research is to create comprehensive and discriminative features by combining wearable sensor data with brain imaging and smart home environments. For the greatest results, early diagnosis is essential. The proposed method called IoT based Autism Predictive Framework (IoTAPF) has a high detection rate of 97.8% and is cross-validated against the current Learning based Autism Detection Strategy (LADS). The proposed approach aims at improving diagnostic specificity which helps in forecasting behaviors and thus pushing earlier interventions, providing better support for ASD individuals and their families. The paper discusses the design and implementation of the framework, including sensor integration, data management, and predictive modeling. Preliminary results from pilot studies are presented, demonstrating the framework's potential to improve diagnostic accuracy and support individualized care plans. The proposed solution represents a significant advancement in the application of IoT technology for early autism detection and management, paving the way for more proactive and data-driven approaches in the field of neuro-developmental disorders. © 2024 IEEE.

关键词： Diseases

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Coding for Composite DNA to Correct Substitutions, Strand Losses, and Deletions

arXiv

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arXiv 2024年

作者： Walter, Frederik Sabary, Omer Wachter-Zeh, Antonia Yaakobi, Eitan Institute for Communication Engineering Technical University of Munich Germany Faculty of Computer Science Technion-Israel Institute of Technology Haifa Israel

Composite DNA is a recent method to increase the base alphabet size in DNA-based data storage. This paper models synthesizing and sequencing of composite DNA and introduces coding techniques to correct substitutions, losses of entire strands, and symbol deletion errors. Non-asymptotic upper bounds on the size of codes with t occurrences of these error types are derived. Explicit constructions are presented which can achieve the bounds. © 2024, CC0.

关键词： DNA

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Coding for Composite DNA to Correct Substitutions, Strand Losses, and Deletions

Coding for Composite DNA to Correct Substitutions, Strand Lo...

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IEEE International Symposium on Information Theory

作者： Frederik Walter Omer Sabary Antonia Wachter-Zeh Eitan Yaakobi Institute for Communication Engineering Technical University of Munich Germany Faculty of Computer Science Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Composite DNA is a recent method to increase the base alphabet size in DNA-based data storage. This paper models synthesizing and sequencing of composite DNA and introduces coding techniques to correct substitutions, losses of entire strands, and symbol deletion errors. Non-asymptotic upper bounds on the size of codes with $t$ occurrences of these error types are derived. Explicit constructions are presented which can achieve the bounds.

关键词： Measurement Sequential analysis Codes Upper bound DNA Symbols Memory

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Enhanced Physical Layer Security for Full-Duplex Facultative Symbiotic Radio: A Pattern Switching and Multi-Device Scheduling Strategy

Enhanced Physical Layer Security for Full-Duplex Facultative...

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IEEE Conference on Wireless communications and Networking

作者： Chi Jin Zheng Chang Fengye Hu Mingan Luan Timo Hämäläinen Faculty of Information Technology University of Jyväskylä Finland School of Computer Science and Engineering University of Electronic Science and Technology of China China College of Communication Engineering Jilin University China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Physical layer security (PLS) in symbiotic radio (SR) systems is primarily considered for passive eavesdropping scenarios. However, overlooking the impact of proactive eavesdroppers poses significant risks. In this paper, we focus on secure transmission in SR systems under proactive eavesdropping conditions. A PLS strategy is investigated for a full-duplex facultative symbiotic radio (FD-FSR) system. First, we introduce an innovative FSR protocol. It allows backscatter devices (BDs) to dynamically switch between cognitive and symbiotic patterns. Next, we develop a multi-device scheduling method. It adaptively assigns BDs as transmitters, cooperators, or jammers to enhance the secrecy rate. We formulate the pattern switching and BD scheduling as a mixed integer programming problem (MIP). To solve this, we first decompose it into binary decision-making and multi-variable optimization sub-problems. Then, a low-complexity two-stage optimization strategy is employed. Numerical results demonstrate that our proposed strategy significantly outperforms existing schemes.

关键词： Symbiosis Decision making Switches Full-duplex system Physical layer security Security Jamming Optimization Eavesdropping Backscatter

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