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International Conference of computer and Informatics engineering (IC2IE)

作者： Wandy Wandy Kusworo Adi Media Anugerah Ayu Doctoral Program of Information Systems School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Computer Science Faculty of Engineering and Technology Sampoerna University South Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. Technology also plays an essential role in supporting runners and running races. Technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential.

关键词： Training Roads Artificial intelligence Informatics

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Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

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InfoMat 2020年第6期2卷 1131-1162页

作者： Qiongfeng Shi Bowei Dong Tianyiyi He Zhongda Sun Jianxiong Zhu Zixuan Zhang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore117576Singapore Center for Intelligent Sensors and MEMS National University of SingaporeSingapore117608Singapore Hybrid-Integrated Flexible(Stretchable)Electronic Systems Program National University of SingaporeSingapore117608Singapore NUS Suzhou Research Institute(NUSRI) Suzhou215123China NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingapore117456Singapore

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life,for example,healthcare monitoring and treatment,ambient monitoring,soft robotics,prosthetics,flexible display,communication,human-machine interactions,and so *** to the development in recent years,the next-generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence(AI)and internet of things(IoT),to achieve a higher level of comfort,convenience,connection,and ***,this review provides an opportune overview of the recent progress in wearable electronics,photonics,and systems,in terms of emerging materials,transducing mechanisms,structural configurations,applications,and their further integration with other ***,development of general wearable electronics and photonics is summarized for the applications of physical sensing,chemical sensing,humanmachine interaction,display,communication,and so *** self-sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage ***,technology fusion of wearable systems and AI is reviewed,showing the emergence and rapid development of intelligent/smart *** the last section of this review,perspectives about the future development trends of the next-generation wearable electronics/photonics are provided,that is,toward multifunctional,self-sustainable,and intelligent wearable systems in the AI/IoT era.

关键词： artificial intelligence energy harvesting human-machine interface internet of things wearable electronics wearable photonics

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Implementation of Fuzzy-based Model for Prediction of Thalassemia Diseases 3

Implementation of Fuzzy-based Model for Prediction of Thalas...

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3rd International Conference on Applied sciences Mathematics and Informatics, ICASMI 2020

作者： Susanto, E.R. Syarif, A. Muludi, K. Perdani, R.R.W. Wantoro, A. Doctoral Program of Mathematics and Science Faculty Lampung University Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Jl. ZA. Pagaralam No.9-11 Bandar Lampung Indonesia Department of Computer Science Faculty of Mathematics and Science University of Lampung Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia Faculty of Medical Science Lampung University Jl. Sumantri Brojonegoro No 1 Bandar Lampung Indonesia

Thalassemia is known as one of the blood disorder diseases that is inherited by parents. There are several types of Thalassemia, namely as Thalassemia major, minor, and intermedia. Among them, Thalassemia major is the most dangerous and needs more attention. Generally, it can be detected since the child is one year old. Late detection of this disease can have adverse consequences and various complications. This study aims to develop a new model for the prediction of thalassemia for children. The model adopts a fuzzy-based rule. The novelty in this article is that our model has 4 outputs, namely thalassemia major, intermedia, minor and not thalassemia. In the previous article it only had 3 outputs. In this study, we intend to implement a model that we developed using a fuzzy-based approach to classify thalassemia diseases based on CBC data. This article describes how to build a model and implement it in software. We compare the test results with the opinion of pediatricians regarding thalassemia. The final results of testing 4 CBC data show that our proposed model has successfully identified the type of thalassemia. © Published under licence by IOP Publishing Ltd.

关键词： Blood

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Synthesis and Second-Order Nonlinear Optical Properties of New Coumaromethacrylate-Methylmethacrylate Copolymers

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MRS Online Proceedings Library 2011年第1期173卷 601-606页

作者： R. A. Henry J. M. Hoover A. Knoesen S. T. Kowel G. A. Lindsay M. A. Mortazavi Research Department Chemistry Division China Lake USA Department of Electrical Engineering and Computer Science Organized Research Program on Polymeric Ultrathin Film Systems University of California Davis USA

The synthesis and second-order nonlinear optical (NLO) properties of a new family of optically nonlinear coumarin dye-containing polymers is reported. Polymerizable coumaromethacrylate (CMA) monomers having various alkyl spacers (C2 to C5) between the polymerizable group and the chromophore were prepared and copolymerized with methylmethacrylate (MMA) and other vinyl monomers. The CMA copolymers had high chromophoric content (up to 18 × 1020) and glass transitions as high as 132°C. Spin cast films were prepared on BK7 substrates and oriented by corona-onset poling at elevated temperatures (COPET). The poled CMA copolymer films were characterized for spectroscopic absorption and second harmonic properties. A comparison of the nonlinear optical properties of poled CMA-MMA copolymers to poled guest-host systems is made. Relative to guest/host systems, CMA-MMA copolymer films exhibit larger and much more stable second-order nonlinear optical properties.

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Photovoltaic Microinverter with Hybrid Energy Storage System (HESS) and Virtual Impedance Control for Injection into a Microgrid

Photovoltaic Microinverter with Hybrid Energy Storage System...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Patricio Gaisse Javier Muñoz Marco Rivera Carlos Restrepo Galina Mirzaeva Engineering Systems Doctoral Program Faculty of Engineering University of Talca Curicó Chile Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó Chile Doctorate in Engineering Systems Faculty of Engineering Universidad de Talca Curicó Chile School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW Australia

In this work, a photovoltaic (PV) microinverter is developed, which includes an hybrid energy storage system based on a battery and an ultracapacitor that are connected in parallel to the dc-link through two buck-boost bidirectional converters. The PV panel is connected in parallel to dc-link through an unidirectional boost converter. For the dc-ac stage, a two-stage Flyback / H-bridge inverter will be considered, which will be used to inject the available power into a microgrid. The study proposes the necessary control strategies to manage the power flow according to generation and injection conditions, where a virtual impedance loop is incorporated in the control of the energy storage elements. The presented results confirm the suitability of the proposed strategy.

关键词： Photovoltaic systems Microgrids Hybrid power systems Batteries Circuit stability Topology Impedance

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Biological image understanding

Biological image understanding

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Medical Imaging III: Image Processing 1989

作者： Dunn, Stanley M. Department of Biomedical Engineering Rutgers University P.O. Box 909 PiscatawayNJ08855-0909 United States Laboratory for Computer Science Research Rutgers University Diagnostics Systems Program New Jersey Dental School NewarkNJ United States

The primary goal of any computer vision system is to construct scene descriptions similar to those formed by the human visual system. Biological image understanding is the automatic processing and interpretation of imagery of natural structures. The key constraint is the absence of explicit models of the objects anticipated to be in the scene. A clinician interprets imagery using principles of physiology and the image acquisition process. He learns to construct explicit models to recognize patterns from these principles, but is also able to infer an interpretation of an unknown structure from examples and physiology. Our overall goal is to develop a computer vision system to be used to interpret imagery of biological data using these principles. In this paper we present a paradigm for constructing image understanding systems designed to process natural images and present some applications of the system to hematology and radiography. The first step of our general approach is data acquisition. The second step is to find intrinsic properties at each pixel. The third step is to group pixels together to for homogeneous regions using the intrinsic properties. The final step is object recognition, where object type and location are determined from the quantitative features of the homogeneous regions. We shall outline the algorithms and data structures used at each step in the process, and their implementation. We shall describe in detail a key feature of this paradigm - forming homogeneous regions by geometry guided segmentation. The fact that classical algorithms do not always yield correct results led us to an algorithm that uses structural information and intensity values to group homogeneous regions. We shall illustrate this problem and the solution, as well as preliminary results of the application of the image understanding system. © 1989 SPIE. All rights reserved.

关键词： Physiology

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3D-Printed electrochemical sensor-integrated transwell systems

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Microsystems & Nanoengineering 2020年第1期6卷 357-368页

作者： Pradeep Ramiah Rajasekaran Ashley Augustiny Chapin David N.Quan Jens Herberholz William E.Bentley Reza Ghodssi Institute for Systems Research University of MarylandCollege ParkMDUSA Fischell Department of Bioengineering University of MarylandCollege ParkMDUSA Department of Psychology and Neuroscience and Cognitive Science Program University of MarylandCollege ParkMDUSA Institute for Bioscience and Biotechnology Research University of MarylandCollege ParkMDUSA Robert E.Fischell Institute for Biomedical Devices University of MarylandCollege ParkMDUSA Department of Electrical and Computer Engineering University of MarylandCollege ParkMDUSA

This work presents a 3D-printed,modular,electrochemical sensor-integrated transwell system for monitoring cellular and molecular events in situ without sample extraction or microfluidics-assisted downstream *** additive manufacturing techniques such as 3D printing,shadow masking,and molding are used to fabricate this modular system,which is autoclavable,biocompatible,and designed to operate following standard operating protocols(SOPs)of cellular *** to the platform is a flexible porous membrane,which is used as a cell culture substrate similarly to a commercial transwell *** electrochemical sensors fabricated on the membrane allow direct access to cells and their products.A pair of gold electrodes on the top side of the membrane measures impedance over the course of cell attachment and growth,characterized by an exponential decrease(~160%at 10Hz)due to an increase in the double layer capacitance from secreted extracellular matrix(ECM)*** voltammetry(CV)sensor electrodes,fabricated on the bottom side of the membrane,enable sensing of molecular release at the site of cell culture without the need for downstream ***-time detection of ferrocene dimethanol injection across the membrane showed a three order-of-magnitude higher signal at the membrane than in the bulk media after reaching *** modular sensor-integrated transwell system allows unprecedented direct,real-time,and noninvasive access to physical and biochemical information,which cannot be obtained in a conventional transwell system.

关键词： transwell electrochemical culture

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities 7

Learner Action Patterns in the Problem-Solving Process Relat...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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Learning sparse representation for leaf image recognition

Learning sparse representation for leaf image recognition

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chao-Yung Hsu Chia-Yen Chen Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Institute of Information Science Taipei Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image recognition technique via sparse representation is proposed for automatic plant identification. In order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. For each test leaf image, we calculate the correlation between the image and each learned dictionary of leaf species to achieve the identification of the leaf image. As a result, efficient leaf recognition can be achieved on public leaf dataset based on the proposed framework leading to a more compact and richer representation of leaf images compared to traditional clustering approaches. Moreover, our method is also adapted to newly added leaf species without retraining classifiers and suitable to be highly parallelized as well as integrated with any leaf image descriptors/features.

关键词： Image recognition Dictionaries Training Feature extraction Shape Educational institutions computer vision

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Slice-Fusion: Reducing False Positives in Liver Tumor Detection for Mask R-CNN

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IEEE/ACM Transactions on Computational Biology and Bioinformatics 2023年第5期20卷 3267-3277页

作者： Tu, Deng-Yao Lin, Peng-Chan Chou, Hsin-Hung Shen, Meng-Ru Hsieh, Sun-Yuan National Cheng Kung University Master Degree Program on Artificial Intelligence Tainan City70101 Taiwan National Cheng Kung University Institute of Medical Informatics Department of Oncology Department of Genomic Medicine National Cheng Kung University Hospital College of Medicine Department of Computer Science and Information Engineering Tainan City70101 Taiwan National Chi Nan University Department of Computer Science and Information Engineering Nantou County54561 Taiwan National Cheng Kung University Graduate Institute of Clinical Medicine Department of Obstetrics and Gynecology Department of Pharmacology National Cheng Kung University Hospital College of Medicine Tainan City70101 Taiwan National Cheng Kung University Institute of Medical Information Institute of Manufacturing Information and Systems Center for Innovative FinTech Business Models International Center for the Scientific Development of Shrimp Aquaculture Department of Computer Science and Information Engineering Tainan City70101 Taiwan

Automatic liver tumor detection from computed tomography (CT) makes clinical examinations more accurate. However, deep learning-based detection algorithms are characterized by high sensitivity and low precision, which hinders diagnosis given that false-positive tumors must first be identified and excluded. These false positives arise because detection models incorrectly identify partial volume artifacts as lesions, which in turn stems from the inability to learn the perihepatic structure from a global perspective. To overcome this limitation, we propose a novel slice-fusion method in which mining the global structural relationship between the tissues in the target CT slices and fusing the features of adjacent slices according to the importance of the tissues. Furthermore, we design a new network based on our slice-fusion method and Mask R-CNN detection model, called Pinpoint-Net. We evaluated proposed model on the Liver Tumor Segmentation Challenge (LiTS) dataset and our liver metastases dataset. Experiments demonstrated that our slice-fusion method not only enhance tumor detection ability via reducing the number of false-positive tumors smaller than 10mm, but also improve segmentation performance. Without bells and whistles, a single Pinpoint-Net showed outstanding performance in liver tumor detection and segmentation on LiTS test dataset compared with other state-of-the-art models. © 2004-2012 IEEE.

关键词： Tumors

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