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2nd International Conference on Data science, E-Learning and information Systems, DATA 2019

作者： Mohammed, Tareq Abed Ghareeb, Ahmed Al-Bayaty, Hussein Aljawarneh, Shadi Collage of Computer Science and Information Technology University of Kirkuk Kirkuk Iraq Program University of North Carolina at Charlotte Charlotte United States College of Engineering University of Kirkuk Kirkuk Iraq Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9781450372848

In this paper, the Big Data challenges and the processing is analyzed, recently great attention has been paid to the challenges for great data, largely due to the wide spread of applications and systems used in real life, such as presentation, modeling, processing and large (often unlimited) data storage. Mass Data Survey, OLAP Mass Data, Mass Data Dissemination and Mass Data Protection. Consequently, we focus on further research trends and, as a default, we will explore a future research challenge research project in this area of research. © 2019 Association for Computing Machinery. ACM

关键词： Data mining

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The next cryptocurrency price movement prediction application uses patterned datasets

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AIP Conference Proceedings 2024年第1期3116卷

作者： Rizky Parlika Mustafid Basuki Rahmat Diponegoro University Information Systems Doctoral Study Program Graduate School 50241 Jl. Imam Bardjo SH Pleburan Semarang Indonesia University of Pembangunan Nasional “Veteran” Jawa Timur Department of Informaton Technology Faculty of Computer Science 60294 Rungkut Madya Gunung Anyar Surabaya Indonesia

Researchers and experts have developed various techniques, models, and methods to predict the price movements of cryptocurrencies, especially Bitcoin. However, among the many techniques studied in the literature, there is still a lack of focus on mining, creating, and developing datasets with specific patterns for predicting the next cryptocurrency price movement. This is an exciting reason to conduct further research. A web-based Patterned Dataset Application and a Telegram bot were constructed to address this issue. These tools read the price position of each cryptocurrency and predict the next price direction based on the last position indicated by the Patterned Dataset Application. The experiment’s results show that when the Patterned Dataset Application shows a diamond crash position, it is time to make a purchase; conversely, when it shows a diamond moon position, it is time to make a sale. It is hoped that by utilizing the Patterned Dataset Application, potential losses can be minimized, and there is more potential for profit in cryptocurrency trading. Even though the initial data source comes from Indonesia’s most prominent digital cryptocurrency trading market, according to coinmarketcap, namely Indodax, the results of this patterned dataset application can often describe the same cryptocurrency conditions globally. The novelty of this research is to produce a new way of predicting the next cryptocurrency price movement using patterned datasets. At the end of this paper, it will be proven that hypothesis 1 and hypothesis 2 on the results of the patterned dataset are true.

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Mobile Patient Application for Outpatient 4

Mobile Patient Application for Outpatient

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Kristiadi, Dedy Prasetya Hasanudin, Muhaimin Sutrisno Salim, Jennifer Gunawan, Michael Glenn Laurence, Angeline Chandra, Antoni Hendric Spits Warnars, Harco Leslie Mantoro, Teddy Computer Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Faculty of Science and Technology Sampoerna University Jakarta12780 Indonesia

ISBN: (纸本)9781728122076

We as a human can not avoid the disease, and when we are sick, we need to see a practical doctor. However, in term of location and patient's right for changing the practical doctor, then the patient when moving from one practical doctor to others will have similar and repeated questions such as medicine allergy, history of diseases and so on. Moreover, become a problem for a vulnerable patient such as unconscious patient, disabled or elderly when seeing a new practical doctor and at the end of the day, it will become malpractice. Few of the causes of the problem above are the lack of health education, delay in diagnosing/misdiagnosis, and inaccessible healthcare facilities and with the increasing popularity of telemedicine and IoT across the world, then we need to apply IoT in order to help the patient. In this paper, a framework is created and designed for an IoT-integrated mobile application for the patient where this mobile application is expected to be implemented. © 2019 IEEE.

关键词： Internet of things

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Analysis of denial of service attack on web security systems

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Journal of Physics: Conference Series 2021年第1期1811卷

作者： S. Iswandi Walad Muhammad Zarlis M.IT Syahril Efendi Department of Information and Technology Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia. Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia.

In this study, an analysis of the Web security system from a Denial-of-Service Attack (DoS) with SYN Attack, Ping of Death, Land Attack, Smurf Attack and UDP Flood types. The server computer that will be tested for DoS attacks is a local web server including *** IP: 54.169.71.56, *** IP: 104.152.168.14, *** IP: 156.67.210.132, *** IP: 202.162. 207,101 and *** with IP Address 213.136.83.52 port 80. The attack on the local web server computer was carried out through attacking cloned computers as many as 5 zombie computers and then observing data traffic on each Web server computer. The test results use ping to the local web server computer, where the target web server sends a replay request time out and the check results in the Google Chrome browser are slow to inaccessible conditions. Ping access time the greater the packet, the greater the average time when accessing a local web server with 5,000 packets is 242.68 seconds, 10,000 packets is 310.28 seconds, 20,000 packets are 337.4 seconds, 30,000 packets are 377.2 seconds, 40,000 packets are 398.4 seconds, 50,000 packets are 545.4 seconds and 100,000 packets are above 600 seconds with the condition that the web server will recover after 600 seconds where the system recovery process depends on each local web server.

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A Study of Enhancing Computational Thinking Skills through STEAM Robotics Activities

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Journal of Physics: Conference Series 2021年第1期1835卷

作者： Muneeroh Phadung Atcharaporn Yokkhun Sulaiman Persoh Computer Education Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand Information Technology Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand Computer Science Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand

STEAM robotics activities are designed to be an enhancement on students' computational thinking skills, which are claimed to be essential for the 21st century. The aims of this study were to examine the learning outcomes of secondary students' computational thinking skills through the use of STEAM robotics activities, and to investigate the students' satisfaction after the implementation of STEAM robotics activities. A quasi-experimental research design was deployed in this study. The research participants were 37 eleventh-grade students of Private Islamic Schools in Yala province, Thailand. A quiz with pre- and post-test and satisfaction questionnaires were employed as data. Descriptive statistics – including mean, standard deviation and a pair sample t-test – was used to analyse the collected data. The findings were that students' learning outcomes indicated a significant improvement in their computational skills after the use of STEAM robotics activities as compared with before, with the statistical level of significance of 0.05. In response to the second research question, the overall satisfaction of the students after the use of such STEAM robotics activities was high (mean=4.01; SD=0.54).

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On Performance Prediction of Big Data Transfer in High-performance Networks

On Performance Prediction of Big Data Transfer in High-perfo...

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IEEE International Conference on Communications (ICC)

作者： Wuji Liu Daqing Yun Chase Q. Wu Nageswara S.V. Rao Aiqin Hou Wei Shen Department of Computer Science New Jersey Institute of Technology Newark NJ USA Computer and Information Sciences Program Harrisburg University Harrisburg PA USA Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak Ridge TN USA School of Information Science and Technology Northwest University Xi’an Shaanxi China School of Informatics Science and Technology Zhejiang Sci-Tech University Hangzhou Zhejiang China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

关键词： Data transfer Big Data Throughput Bandwidth Measurement Predictive models Protocols

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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A polarization-insensitive fishnet/spacer/mirror plasmonic absorber for hot electron photodetection application

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Chinese Optics Letters 2020年第5期18卷 63-67页

作者： Zhiqiang Yang Kang Du Wending Zhang Soojin Chua Ting Mei Key Laboratory of Space Applied Physics and Chemistry Ministry of Educationand Shaanxi Key Labora tory of Optical Information TechnologySchool of ScienceNorth Western Polytechnical UniversityXi'an 710072China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore LEES Program Singapore-MIT Alliance for Research&Technology(SMART)Singapore 138602Singapore

A polarization-insensitive plasmonic absorber is designed consisting of Au fishnet structures on a TiO2 spacer/Ag mirror. The fishnet structures excite localized surface plasmon and generate hot electrons from the absorbed photons, while the TiO2 layer induces Fabry–Perot resonance, and the Ag mirror acts as a back *** optimizing the TiO2 layer thickness, numerical simulation shows that 97% of the incident light is absorbed in the Au layer. The maximum responsivity and external quantum efficiency of the device can approach 5 mA/W and ~1%, respectively, at the wavelength of 700 nm.

关键词： plasmonic absorber Fabry–Perot resonance internal photoemission surface plasmon

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QoSTCP: Provide Consistent Rate Guarantees to TCP flows in Software Defined Networks

QoSTCP: Provide Consistent Rate Guarantees to TCP flows in S...

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IEEE International Conference on Communications (ICC)

作者： Chien Chen Hoa-Chuan Fang Muhammad Shahid Iqbal Department of Computer Science and Information Technology Service Center National Chiao Tung University Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan EECS International Graduate Program National Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

The Quality of Service (QoS) for applications is becoming increasingly important with the expansion of the Internet. A software-defined network offers flexibility and scalability in the use of network resources, like a meter table, which enables OpenFlow switches to measure flow rates and can be used to realize the rate limiter QoS. However, this drops packets when the flow-rate is over the limit, making the TCP congestion window reduce and grow periodically. The QoS of the upper layer using TCP will suffer regularly because of packet losses and bandwidth oscillation. Therefore, we propose a QoSTCP protocol using the meter and Rate Limiting Notification (RLN) to improve the QoS of TCP in SDN. The meter in the switch measures the flow rate to mark RLNs in the packets when the flow rate exceeds the threshold. A QoSTCP sender gets marking information to reduce the window size proportional to the marking packet ratio to avoid packet drop. We also provide a theoretical analysis to estimate when to mark packets at specific thresholds under two kinds of bandwidth demands in QoS, maximum and average rate. In order to verify QoSTCP performance, we implement a Two Rate Three Color Marker (trTCM) meter to measure the flow rate and mark RLNs using a programming protocol-independent Packet Processors (P4) switch. To simplify our implementation, the existing Explicit Congestion Notification (ECN) and Data Center TCP (DCTCP) are modified to emulate QoSTCP behavior. Experiment results confirm not only that QoSTCP provides a consistent rate guarantee by avoiding packet drop but also that it matches our theoretical analytical results.

关键词： Quality of service Bandwidth Meters Oscillators Protocols Data centers Control systems

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Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar

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Smart Health 2024年 34卷

作者： Chokphukhiao, Chaturapron Pattaranit, Pattrawan Tun, Wonn Shweyi Thet Masa, Sakaowrat Leemananil, Rattikorn Natteerapong, Nuttaphorn Phetcharaburanin, Jutarop Boonlue, Sophon Sunat, Khamron Patramanon, Rina Information Technology International Program College of Computing Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Digital Innovation Faculty of Education Khon Kaen University Khon Kaen 40002 Thailand Integrative Biomedical Informatics and Computational Imaging Center I-BIC Faculty of Associated Medical Science Khon Kaen University Khon Kaen 40002 Thailand Department of System Biosciences and Computational Medicine Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Khon Kaen University National Phenome Institute Khon Kaen University Khon Kaen 40002 Thailand Department of Biochemistry Faculty of Science. Khon Kaen University Khon Kaen 40002 Thailand Department of Microbiology Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Department of Computer Science College of Computing Khon Kaen University 40002 Thailand

Introduction: The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “Digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure. Methods: Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants. Results: Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey. Conclusions: The ‘Digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles. © 2024 The Authors

关键词： Digital health avatar Health sensors Healthcare Three-dimensional model

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