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Performance Evaluation of Coverage Prediction in 4G Networks Using Machine Learning Classification Algorithm 10

Performance Evaluation of Coverage Prediction in 4G Networks...

引用

10th International Conference on Wireless and Telematics, ICWT 2024

作者： Yuliana, Hajiar Iskandar Hendrawan Ridwan, Azwar Mudzakkir Charisma, Atik Somantri, Nivika Tiffany Universitas Jenderal Achmad Yani Faculty of Engineering Department of Electrical Engineering Indonesia Institut Teknologi Bandung Doctoral Program of School of Elecrtical Engineering and Informatics Indonesia Bandung Indonesia UIN Sunan Gunung Djati Bandung Department of Electrical Engineering Indonesia

ISBN: (纸本)9798350377057

Network coverage prediction is an important aspect of 4G network planning and optimization. In this study, we conducted a comprehensive analysis of the performance of various machine learning algorithms in predicting 4G network coverage. The data collected includes information on location, signal intensity, topography, and other important variables. Data pre-processing is performed to clean, normalize, and select relevant features. Next, we compared the performance of several machine learning algorithms, including Logistic Regression, KNN, Naïve Bayes, Decision Tree, SVM, XGBoost, AdaBoost, and Bayesian Network Classifier. The model training process is performed using subsets of training, validation, and testing data, with evaluation performed using various evaluation metrics such as accuracy, precision, recall, F1-score, RMSE, MAE, and R-squared. The experimental results show that Random Forest stands out with excellent performance, while Naïve Bayes tends to produce lower performance. The conclusion of this study provides valuable insights into the potential applications of machine learning algorithms in predicting 4G network coverage with accuracy and reliability. © 2024 IEEE.

关键词： Adversarial machine learning

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VidyaMedic: Smart Alert System For Continous Vital Sign Monitoring

VidyaMedic: Smart Alert System For Continous Vital Sign Moni...

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2023 International Conference on Electrical engineering and informatics, ICEEI 2023

作者： Ikawati, Vidya Prihatmanto, Ary Setijadi School of Electrical Engineering and Informatics Bandung Institute of Technology Doctoral Program of Electrical Engineering and Informatics Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350381290

The proposed smart system namely VidyaMedic utilizes continuous heart rate monitoring through sensors, with data transmission to the cloud via an IoT platform. Testing was conducted on a 40-year-old male participant who wore the Polar H10 heart rate monitor for 24 days. The heart rate profile captures the circadian rhythm, the natural internal biological clock governing cardiovascular and behavioral processes over a 24-hour cycle, influencing morning, daytime, and nighttime activities. Health conditions can be assessed using an algorithm which calculates the running sum of standard deviation for heart rate data over this period. Initially, standard deviation is computed for each data point, quantifying data dispersion from the mean. Subsequently, the running sum of standard deviation enables the detection of significant changes over time, abrupt fluctuations indicate outliers or extreme values, potentially impacting overall standard deviation and signaling significant data changes. Deviations from the expected or previous standard deviation values, marked by a regression coefficient less than or greater than 1, may suggest cardiac abnormalities or heart rhythm disturbances. © 2023 IEEE.

关键词： Heart

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Analysis on Performance of Semi-Real-Time Transcription on Health App 18

Analysis on Performance of Semi-Real-Time Transcription on H...

引用

18th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2024

作者： Indrasary, Yoenie Nugraha, Daniel Prihatmanto, Ary Setijadi Sarief, Ivany Gunawan, Rudy Yunautama, Dhema School of Electrical Engineering and Informatics Institut Teknologi Bandung Doctoral Program of Electrical Engineering and Informatics Bandung Indonesia State Polytechnic of Banjarmasin Banjarmasin Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Universitas Sangga Buana Faculty of Engineering Dept. of Electrical Engineering Bandung Indonesia Universitas Sangga Buana Directorate of Vocational Dept. of Informatics Engineering Bandung Indonesia

ISBN: (纸本)9798331527686

The fragmentation of health information systems has hindered seamless data exchange in healthcare services, posing challenges in achieving efficient, real-time access to patient health data. This study addresses these issues by evaluating the implementation of a semi-real-time transcription system using a distributed architecture with a message broker to enhance the documentation of clinical examination processes in primary health services. The research focuses on assessing the feasibility of this approach by measuring key performance indicators such as latency and word error rate (WER) during clinical conversation transcription. Audio recordings were segmented into shorter fragments to simulate real-time transcription, and data transmission was conducted through the Advanced Message Queuing Protocol (AMQP). The findings demonstrate that the average latencys achieved by semi-real-time transcription system is 7.7s, indicating its potential suitability for clinical documentation applications that do not require strict real-time processing. However, glitches observed in the message broker's forwarding mechanism suggest the need for further optimization to ensure consistent performance. Future work aims to develop strategies to minimize transcription errors, enhance reliability, and improve the overall integration of this system in healthcare settings. This study contributes to the advancement of health information systems by offering architecture into scalable and effective methods for semi-real-time data transcription and interoperability. © 2024 IEEE.

关键词： Audio recordings

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Development of Urban Data Sensing for Smart City Platform 10

Development of Urban Data Sensing for Smart City Platform

引用

10th International Conference on ICT for Smart Society, ICISS 2023

作者： Prabowo, Okyza Maherdy Supangkat, Suhono Harso Mulyana, Eueung Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung STMIK AMIK Bandung Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Smart City and Community Innovation Center Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9798350339543

The idea of a 'smart city' is one in which cities may effectively and efficiently manage their resources to raise the standard of living of its residents. Cities are already capable of performing sensing, understanding, and acting at a certain degree because to the existence of information technology as an enabler. Several studies have created various physical sensors for sensing in order to produce data. However, urban data is not limited to factual information on the environment and infrastructure. In order to collect data from the digital world, including social media, online news, and other digital social sensors, this research aims to create an urban data collecting system. The creation of digital urban sensor data can enhance the accuracy of the information that can help decision-makers. © 2023 IEEE.

关键词： Smart city

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Performance Evaluation of Coverage Prediction in 4G Networks Using Machine Learning Classification Algorithm

Performance Evaluation of Coverage Prediction in 4G Networks...

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International Conference on Wireless and Telematics (ICWT)

作者： Hajiar Yuliana Iskandar Hendrawan Azwar Mudzakkir Ridwan Atik Charisma Nivika Tiffany Somantri Department of Electrical Engineering Faculty of Engineering Universitas Jenderal Achmad Yani Doctoral Program of School of Elecrtical Engineering and Informatics Institut Teknologi Bandung School of Electrical Engineering and Informatics (STEI) Institut Teknologi Bandung Bandung Indonesia Department of Electrical Engineering UIN Sunan Gunung Djati Bandung

ISBN: (数字)9798350377057

ISBN: (纸本)9798350377064

关键词： Training Wireless communication Support vector machines Machine learning algorithms Accuracy Surfaces Telematics

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Individual Health Profiling Using Multimodal Sensors on Smart Health Care 17

Individual Health Profiling Using Multimodal Sensors on Smar...

引用

17th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2023

作者： Ikawati, Vidya Saepudin, Didin Susanto, Bambang Munandar, Ahmad Nurba, Hardy Purnama Prihatmanto, Ary Setijadi Doctoral Program of School of Electrical and Informatics Engineering Institute of Technology Bandung Bandung Indonesia Universitas Sangga Buana Bandung Indonesia Universitas Sangga Buana Faculty of Engineering Department of Electrical Engineering Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9798350309164

Health Service, also referred to as Health Care System, plays a pivotal role in maintaining and enhancing health by preventing illnesses and injuries. In this context, electronic health records are essential for both inpatients and outpatients, serving as a crucial tool for healthcare providers and policymakers. However, the potential of these records extends beyond individual care to support broader health policy and research initiatives. Personal Smart Health Care, an individual-based digital health technology, bridges the gap between personal health management and medical records, enabling comprehensive healthcare improvements. Smart healthcare, driven by technologies like IoT, mobile applications, cloud computing, big data, 5G, artificial intelligence, and biotechnology, offers a holistic approach to healthcare, emphasizing diagnosis, treatment, disease prevention, risk monitoring, and virtual assistance. An intelligent framework for smart healthcare includes four layers: The instrumentation layer, information system layer, business intelligence layer, and gamification layer, each contributing to enhanced patient outcomes, streamlined processes, and improved patient care. The gamification layer incentivizes healthy behaviors and fosters patient engagement, especially in healthcare scenarios. This comprehensive framework underscores the transformative potential of smart healthcare, where technology-driven solutions can revolutionize the healthcare landscape, improving patient care, health management, and the overall well-being of individuals and populations. © 2023 IEEE.

关键词： Big data

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Thread programming for Blockchain Creation 7

Thread Programming for Blockchain Creation

引用

7th International Conference on Information Technology Systems and Innovation, ICITSI 2022

作者： Parjuangan, Sabam Suhardi Nugraha, I Gusti Bagus Baskara Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung40132 Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung40132 Indonesia

ISBN: (数字)9781665465557

ISBN: (纸本)9781665465557

The process of finding a block hash is a complex problem. One of the problems is making the hash from a generator algorithm that uses the existing string and the transaction data in the block. So far, the idea that has been used is to make it one step at a time using high-powered machines (supercomputing). Developing blockchain applications is hard because supercomputing is expensive. To solve this problem, developers need to use a different method, called parallel programming. This article talks about a parallel way to make block hashes, which are used to make new blocks. We use the SHA256 algorithm to process the hash. When creating a unique character string to be used as a block hash from a set of characters, thread division is done as part of the algorithmic skeleton process. Our experiments show that using threads to split work in parallel has speeded up the build process by 1.56 seconds compared to when blocks are hashed sequentially. In addition, it was also found that the threads that contributed the most to increasing speedup were 3 threads with an average processing time of 111,638 seconds. On average, the parallel hash generation process takes 707,853 seconds, while the sequential one takes 1756,56 seconds. We conclude the solution to building blockchain using the thread programming method with the number of threads is 3 for the computer specifications used to be the same or smaller than the computer specifications we use. © 2022 IEEE.

关键词： Blockchain

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider 6

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

引用

6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Atmaja, Ardian Budi Kusuma Hidayat, Egi Muhammad Idris Riyanto Trilaksono, Bambang Siregar, Simon Habibullah, Natsir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Telkom University Doctoral Program of Electrical Engineering Department Computer Engineering Faculty of Applied Science Indonesia

ISBN: (纸本)9798350358346

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees. © 2023 IEEE.

关键词： Geometry

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Car Detection over Network using Yolov8 in Forza Horizon 4 17

Car Detection over Network using Yolov8 in Forza Horizon 4

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17th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2023

作者： Pratama, Vitradisa Sukoco, Agus Pebriadi, Pebi Kusumastuti, Dyah Paramarta, Vip Prihatmanto, Ary Setijadi Institut Teknologi Bandung Doctoral Program of School of Electrical Engineering and Infomatics Bandung Indonesia Universitas Bandar Lampung Departement of Informatics Lampung Indonesia Uniersitas Sangga Buana Bandung Indonesia Institut Teknologi Bandung School of Electical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350309164

In the realm of autonomous vehicles, object detection holds a pivotal role in enabling accurate perception and safe navigation within complex environments. This study incorporates these domains by proposing a vehicle detection system employing YOLO v8 within the popular game Forza Horizon 4. YOLO v8's real-time, accurate object detection prowess aligns seamlessly with the game's dynamics, enriching the user experience through improved vehicle tracking. The research encompasses YOLO v8 model training on an expansive vehicle dataset, adaptation for Forza Horizon 4, and rigorous evaluation, comparing accuracy, speed, and efficiency against existing methods. The methodology entails dataset preparation, YOLO v8 configuration, object detection, result evaluation, optional fine-tuning, and iterative testing and optimization. By scrutinizing two data transmission protocols, RTMP and HTTPS, the research accentuates RTMP's superiority in real-time image data transmission for object detection, surpassing HTTPS in processing speed. While RTMP excels in low-latency scenarios, HTTPS augments security through encrypted data transmission. The findings prove RTMP's speed in image data transmission for real-time object detection, whereas HTTPS's secure communication advantages. © 2023 IEEE.

关键词： Object detection

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Bibliometric Analysis of Trends and Directions in Machine Learning Applied to FinTech 4

Bibliometric Analysis of Trends and Directions in Machine Le...

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4th International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2024

作者： Arif, Erman Suherman, Suherman Widodo, Aris Puji Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350378368

Our article presents a comprehensive analysis of trends and directions in the application of machine learning in the FinTech sector. By utilizing data from academic databases such as Scopus, our objective is to showcase the advancements in this interdisciplinary research area. The study identifies key trends, influential authors, leading journals, and significant collaborative networks that shape the field. The methodology employed involves quantitative bibliometric analysis to evaluate publications from the past five years. The results indicate a substantial increase in the number of studies during this period, highlighting the importance of machine learning in addressing critical financial challenges, including fraud detection, algorithmic trading, credit scoring, and risk management. Additionally, we delve into the main themes, countries, and institutions that dominate the current research agenda. This analysis provides valuable insights into the present state and future direction of machine learning in FinTech, serving as a resource for researchers and practitioners seeking to comprehend and contribute to this dynamic and rapidly evolving field. We also discuss implications for future research, emphasizing the necessity for continuous innovation and interdisciplinary collaboration to maximize the potential of machine learning in transforming financial services. © 2024 IEEE.

关键词： Adversarial machine learning

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