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Mobile communication Network Site Planning Based on Improved Genetic Algorithm 6

Mobile Communication Network Site Planning Based on Improved...

引用

6th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2024

作者： Zhang, Rui Qin, Haosen Wu, Ziyang School of Traffic and Transportation Engineering Dalian Jiaotong University Dalian China School of Electrical and Automation Engineering Dalian Jiaotong University Dalian China

ISBN: (纸本)9798350374315

This study proposes a model that combines 0-1 dynamic planning, coverage and construction cost for station site planning in mobile communication networks, and is optimised by a genetic algorithm. On the basis of determining the type of base station and its constraints, the weak signal region is clustered and analysed by the K-Means algorithm, followed by a single-objective planning model to minimise the construction cost of the new base station, which solves the non-linear planning problem and achieves 91.3% coverage of the service volume. Further, based on the actual coverage of the base station, a multi-objective planning model is introduced and the sector coverage parameter equations and coverage definitions are updated. Three new decision variables are added to adjust the main direction angle of the base station sector and the objective function is modified to incorporate maximised coverage. A modified genetic algorithm is used for fast non-inferiority ranking and density estimation to obtain the Pareto frontier solution set, which optimally determines the locations and angles of 886 micro-base stations and 1093 macro-base stations with a total coverage of 90.6%. The planning method in this paper provides an efficient and feasible solution for mobile communication network construction. © 2024 IEEE.

关键词： Base stations

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Cloud Detection and Nowcasting for Ship Navigation 15

Cloud Detection and Nowcasting for Ship Navigation

引用

15th international conference on Advances in computing, control, and Telecommunication Technologies, ACT 2024

作者： Sreenivasan, Mahalakshmi Sai Kumar, Kanuri S.V.S. Selvaraj, P. Department of Computing Technologies Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India

ISBN: (纸本)9798331300579

Navigating through oceans is challenging. Sailors are disadvantaged in determining the most appropriate and safe path, free from hurdles and extreme weather conditions, especially on pitch-dark nights. Ships rely on their communication with satellites for navigation. When this connection breaks, the ship loses its ability to navigate and follow the required path. In such scenarios, the Geographical Information System (GIS) and Satellite Imagery-based algorithms are best suited to assist. It is necessary to focus on cloud behavior to ensure the success of ocean endeavors. Cloud Detection is performed by the methods of K-Means clustering and MRCNN. The approach of Mean Path Adjustment (MPA) is used to trace the center of mass to predict Cloud Motion;thereby, building a convolutional LSTM model for Cloud Nowcasting. Collectively, these methods help in detecting clouds, predicting their motion, and helping sailors decide the route to follow, based on the weather conditions. This system works well when the communication between the ship and satellite breaks. A high similarity index of 0.8363 is achieved with the test images. © Grenze Scientific Society, 2024.

关键词： Satellite imagery

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Bandwidth and Power Cost Optimized Over Visible Light communication 1

Bandwidth and Power Cost Optimized Over Visible Light Commun...

引用

1st IEEE international conference on automation, computing and Renewable Systems, ICACRS 2022

作者： Karpagam, M. Sowmya, K. Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (纸本)9781665460842

LEDs were used for data transmission and photodiodes were used as receivers in Visible Light communication, a new branch of Indoor OWC. LEDs can be easily changed, allowing them to operate as both data transmitters and light sources. Our indoor visible light communication simulation model was created using MATLAB. The user profiled the transmitter location as well as the reflections at every block. In a VLC setting, the illumination LED acts as both lighting and a communication device. © 2022 IEEE

关键词： Visible light communication

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communication between two controllers with the different electric grounds for Fail-Operational 22

Communication between two controllers with the different ele...

引用

22nd international conference on control, automation and Systems (ICCAS)

作者： Su, Sung Han Infineon Technol Korea Co Ltd Tech Engn Ctr Seoul South Korea

ISBN: (纸本)9788993215243

As many automotive companies adopt autonomous driving systems, safety is more important than ever. In particular, in autonomous driving levels 4 and 5, design considering Fail-Operational has become an essential element. For Fail-Operational design, it is essential to design two controllers with different electric grounds in one system, and in this case, both controllers must transmit and receive as much data as possible along with periodic continuous communication. A suitable means of communication to implement this would be SPI (Serial Peripheral Interface) with an isolator. During communication between two controllers with SPI, not only data exchange but also system control must be performed, so it is necessary to find and set an optimal transmission speed and a method to reduce CPU load by optimally processing communication data. Therefore, in this paper, try to find the optimal communication data processing method and transmission speed for Fail-Operational of motor control, and to discover unexpected cases that may occur during communication.

关键词： Fail-Operational SPI with an isolator Motor control

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Comparative Study of Detection of ADHD using EEG Signals 5

Comparative Study of Detection of ADHD using EEG Signals

引用

5th international conference on control, communication and computing, ICCC 2023

作者： Anchana, V. Biju, K.S. College of Engineering Trivandrum Department of Electronics and Communication Engg. Trivandrum India

ISBN: (纸本)9798350334128

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental irregularity which is complex, universal and heterogeneous. Inattention, hyperactivity and impulsiveness are some of the symptoms of ADHD. The disease is developing at preschool years and can even extend to adulthood when proper diagnosis is not provided. Hence detection of ADHD is very essential. ADHD detection can be done using EEG signal. In this review, we analysed the available research on deep and machine learning studies on diagnosing ADHD and found the various diagnostic setups that have been employed. The paper discusses the existing techniques present using different classifiers. It briefly explains the different methods when using Artificial Neural Network (ANN), Support Vector Machine (SVM) and Convolutional Neural Networks (CNN) as classifier. Comparative study on these methods were done and performance measures was increased over time. © 2023 IEEE.

关键词： Support vector machines

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Enhanced Decision Making Through Deep Learning-Driven Robotic Process automation 3

Enhanced Decision Making Through Deep Learning-Driven Roboti...

引用

3rd Odisha international conference on Electrical Power Engineering, communication and computing Technology, ODICON 2024

作者： Jagannath, Amrit Sarkar, Debbarni Patra, Sarat Kumar Veer Surendra Sai University of Technology Department of Pe Burla India Nit Meghalaya Department of Ece Meghalaya India Nit Agartala Department of Ece Tripura India

ISBN: (纸本)9798350354379

Robotics process automation (RPA) is a key technique in modern technology. The RPA guarantees that tasks are completed accurately and consistently, which is essential for decision-making. Further, the performance of the RPA can be enhanced by combined with deep learning (DL) models. DL models perform prediction more effectively than traditional rule-based methods, where RPA handles repetitive tasks and reduces human effort with less processing time. Nowadays, more digital information is generated due to the development of new technologies. DL-driven RPA can effectively process these pieces of digital information. Therefore, this paper presents the performance of DL-driven RPA for name and gender identification. RPA will further use the result of the prediction for automated email drafting and other digital activities. This paper combines three DL models- convolutional neural network, long short-term memory, and gated recurrent unit models with RPA to predict the gender of a specific name. Finally, the proposed model is extensively analyzed through simulation results. The simulation results showed the DL-driven RPA models' efficacy based on accuracy, loss, precision, recall, F1-score, R2-score, mean-squared error, mean absolute error, and confusion matrix. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing Cloud computing Security Through Blockchain-Based communication for Electronic Health Records 20

Enhancing Cloud Computing Security Through Blockchain-Based ...

引用

20th Annual international conference on Distributed computing in Smart Sensor Systems and the Internet of Things (DCOSS-IoT)

作者： Noyon, Md Shahed Islam Moradpoor, Naghmeh Maglaras, Leandros Ahmad, Jawad Univ Greenwich Sch Comp & Math Sci London England Edinburgh Napier Univ Sch Comp Engn & Built Environm Edinburgh Midlothian Scotland

ISBN: (纸本)9798350369458;9798350369441

The health sector stands as one of the most crucial and vulnerable domains, harbouring extensive personal data. Particularly, Electronic Health Records store information in electronic media where users lack control over their data. Unauthorized access to the server or record portal could lead to data manipulation across the entire database. Addressing this security concern, blockchain emerges as a potential solution, surpassing traditional systems in data storage capabilities. In the event of unauthorized access, an attacker can only manipulate a single block of data, leaving the remaining information protected. In addition, blockchain offers new opportunities and avenues for research, particularly in terms of security and scalability. The proposed system in this paper, MediRec, aims to ensure that users have complete control over their personal data by employing a decentralized database. This database securely stores and restricts access to data, allowing only the owner to share it using a secure key. MediRec facilitates patients in creating blockchain-based accounts, ensuring each individual possesses a dedicated block for storing personal data. This innovative approach enables patients to schedule appointments, and doctors can prescribe medications, with details and e -prescriptions securely stored within the patient's block. To maintain the integrity of the system, doctors can undergo verification by healthcare services, such as the National Health Service in the UK, ensuring their validation before accessing the blockchain system. This stringent validation process ensures the security and authenticity of the data stored within the blockchain. Overall, the proposed solution in this paper offers robust security and scalability in electronic data storage, providing users with control over their information through a blockchain-based system. This system presents a promising solution in preventing data breaches and safeguarding sensitive healthcare information.

关键词： Keywords DApps Ethereal'' Encryption Decentralized Health Records Smarr Contact

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Utilizing AI to Advance Data Science Research 15

Utilizing AI to Advance Data Science Research

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Bhushan, Bharat Singh, Akhilendra Pratap Sharma, Sonal Divya, K. Bhimanpallewar, Ratnmala N. Pareek, Ravi Kant Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Department of Computer Science and Engineering Karnataka Bangalore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Pune India Vivekananda Global University Department of Civil Engineering Jaipur India

ISBN: (纸本)9798350370249

The emerging field of artificial Intelligence (AI) offers tremendous capability for advancing studies and improvement in the location of data science. AI is capable of automating and enhancing the method of obtaining, organizing, and deciphering records that may growth the accuracy of facts evaluation and strengthen records technological know-how research tasks. This automation can keep time by streamlining responsibilities and loose up researchers' time to focus on extra complicated components of research. AI can also provide insights into previously unknown records styles, permitting researchers to pursue deeper statistics exploration and find out surprising outputs. Further, AI-based strategies can reveal significant and actionable information from conventional datasets, taking into consideration extra green and correct decisions. © 2024 IEEE.

关键词： Obtaining Permitting Strengthen Surprising Technological

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A Space Vector PWM Signal Generation for Five Level Five Phase Inverter Drives 5

A Space Vector PWM Signal Generation for Five Level Five Pha...

引用

5th international conference on control, communication and computing, ICCC 2023

作者： Shani, S.J. Shiny, G. APJ Abdul Kalam Technological University College of Engineering Trivandrum Power Electronics Research Laboratory Dept. of Electronics and Communication Engg Kerala India

ISBN: (纸本)9798350334128

A space vector PWM (SVPWM) method for a five phase five level inverter is proposed. Two three level inverters are fed from opposite ends of an open end winding induction motor to create five level inversion. The proposed scheme is based on adding an offset voltage to the sampled reference voltage to achieve multilevel operation. The use of carrier region to identify the reference location will simplify the implementation of the algorithm. The eligible vectors, regions and switching sequence of the five vectors that define the accessible region can be directly determined from the modulation index value. This makes it easier to implement the optimal five vectors, and it is extendable to any multiphase multilevel inverter (odd number of levels) by simply changing the carrier region. The proposed algorithm was simulated in MATLAB/SIMULINK, and the results are presented. © 2023 IEEE.

关键词： Vectors

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Hierarchical Classification of Indian Ridge Gourd Varieties: CNN-SVM Fusion Approach 15

Hierarchical Classification of Indian Ridge Gourd Varieties:...

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15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Sharma, Rishabh Mishra, Abhinav Chitkara University Centre for Research Impact & Outcome Punjab Rajpura140401 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India

ISBN: (纸本)9798350370249

This study looks at three main types of ridge gourd-Pusa Nasdar, Pusa Chikni, and Arka Sumeet-in India by using Deep Learning models like Convolutional Neural Network (CNN) and Support Vector Machine (SVM). A group of around 13,000 clear pictures was carefully gathered and labeled. It was used to teach a machine-learning model how to work correctly. The new CNN design, made for identifying different types of ridge gourds, used its ability to see features in a way that is arranged like steps. The SVM model, with its features taken out, went through tough training and testing. The study used 76% of the data to make a model, 12% for checking if it works and another 12% was reserved for testing. The created models had a high overall correctness of 96.5%. A comparison between these classifications and previous methods proves that the new models are better than before. The talk shows how these models can be used in farming. It stresses the need to improve them more and think about real-world uses before they are put into practice. This study shows that CNN and SVM models work well for sorting ridge gourd varieties. It helps understand how to move farming automation forward, making it more precise when taking care of plants. © 2024 IEEE.

关键词： Agricultural automation Classification CNN Convolutional Neural Network Crop Varieties Ridge gourd Support Vector Machine SVM

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