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International Conference on Information Technology, Information systems and Electrical engineering (ICITISEE)

作者： Adri Gautama Adian Fatchur Rochim Luhur Bayuaji Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Computer Engineering Diponegoro University Semarang Indonesia Computer Science Budi Luhur University Jakarta Indonesia

Every patient has health record, it was written as statement of patient's conditions, treatments, and medications, and nowadays it is become digitalized, it can be copied and shared easily, but the nature of EHR is private, not for public, private between patients and healthcare provider. Privacy preserving can be done by implementing Blockchain network for storing EHR, only authorized users or nodes can access and write data to the network. New block in blockchain created as per consensus among nodes, every node can join a blockchain network if it is public, to meet a consensus required resources intensive cryptographic challenge, in private blockchain, only selected can join and involved in the network or specific transaction. In healthcare, data privacy is the main concerned, need a secure, scalable, and efficient blockchain hence implementing consortium blockchain is perfect match for EHR where multiple healthcare provider can operate in a single platform to conduct transaction or sharing EHR among members. This study analyzes 15 articles derived from IEEE Explore, science Direct and Scopus by implementing screening with keyword Consortium Blockchain and EHR and proposing new blockchain model accommodating solution for challenges on access, storage, sharing, privacy, and performance.

关键词： Electrical engineering Data privacy Privacy Analytical models Monte Carlo methods Medical services Blockchains

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WebComposer: a tool for the composition and execution of Web service-based workflows

WebComposer: a tool for the composition and execution of Web...

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Proceedings of the Latin American Web Congress (LA-Web)

作者： L.A.G. da Costa P.F. Pires M. Mattoso COPPE-Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil DCC-IM/NCE Federal University of Rio de Janeiro Rio de Janeiro Brazil

We present the WebComposer tool for the automatic composition and execution of Web service-based workflows. We use ontologies to describe and browse workflows. We associate messages and operations with workflow domain concepts using WSDL extensibility. The automatic workflow implementation through WebComposer enables the full separation of the workflow logic and the implementation technology. WebComposer provides the execution of ad-hoc programs by users and the automatic maintenance of these programs, as the available Web services are altered.

关键词： Web services Ontologies Software agents Automatic logic units Semantic Web systems engineering and theory computer science Web sites Information resources Application software

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Automatic composition of Web services with contingency plans

Automatic composition of Web services with contingency plans

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IEEE International Conference on Web Services (ICWS)

The semantic Web technology and the Web services description language extensibility may be combined to describe services in an unambiguous and machine interpretable way, automating Web services discovery, selection and invocation. In this paper, we present an algorithm and a prototype for the automatic composition of Web services that implement workflows described in a high level language. Our approach has many advantages comparing to the manual creation of a simple program composition, such as smaller implementation time and cost, reliability with the generation of contingency plans, greater capacity to evolve with the dynamic service discovery, and faster execution time with the use of heuristics. We use the OWLS ontology to semantically describe Web services metadata and indexes to help selecting them. The proposed algorithm considers that equivalent services may have different interfaces and also respects preferences of the users.

关键词： Web services Semantic Web Ontologies programming profession Prototypes Robustness systems engineering and theory computer science High level languages Costs

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WANN-Tagger: A weightless artificial neural network tagger for the portuguese language

WANN-Tagger: A weightless artificial neural network tagger f...

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作者： Carneiro, Hugo C. C. França, Felipe M. G. Lima, Priscila M. V. Systems Engineering and Computer Science Program/COPPE Universidade Federal do Rio de Janeiro Caixa Postal 68511 21941-972 Rio de Janeiro RJ Brazil Department of Mathematics Universidade Federal Rural do Rio de Janeiro Km 47 Campus Universitário BR-465 23890-000 Seropédica RJ Brazil

ISBN: (纸本)9789898425324

Weightless Artificial Neural Networks have proved to be a promising paradigm for classification tasks. This work introduces the WANN-Tagger, which makes use of weightless artificial neural networks for labelling Portuguese sentences, tagging each of its terms with its respective part-of-speech. A first experimental evaluation using the CETENFolha corpus indicates the usefulness of this paradigm and shows that it outperforms traditional feedforward neural networks in both accuracy and training time, and also that it is competitive in accuracy with the Hidden Markov Model in some cases. Additionally, WANN-Tagger shows itself capable of incrementally learning new tagged sentences during runtime.

关键词： Feedforward neural networks

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ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

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Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2025年第4期10卷 425-436页

作者： Ganesan, Saampras Barrios, Fernando A. Batta, Ishaan Bauer, Clemens C.C. Braver, Todd S. Brewer, Judson A. Brown, Kirk Warren Cahn, Rael Cain, Joshua A. Calhoun, Vince D. Cao, Lei Chetelat, Gaël Ching, Christopher R.K. Creswell, J. David Dagnino, Paulina Clara Davanger, Svend Davidson, Richard J. Deco, Gustavo Dutcher, Janine M. Escrichs, Anira Eyler, Lisa T. Fani, Negar Farb, Norman A.S. Fialoke, Suruchi Fresco, David M. Garg, Rahul Garland, Eric L. Goldin, Philippe Hafeman, Danella M. Jahanshad, Neda Kang, Yoona Khalsa, Sahib S. Kirlic, Namik Lazar, Sara W. Lutz, Antoine McDermott, Timothy J. Pagnoni, Giuseppe Piguet, Camille Prakash, Ruchika S. Rahrig, Hadley Reggente, Nicco Saccaro, Luigi F. Sacchet, Matthew D. Siegle, Greg J. Tang, Yi-Yuan Thomopoulos, Sophia I. Thompson, Paul M. Torske, Alyssa Treves, Isaac N. Tripathi, Vaibhav Tsuchiyagaito, Aki Turner, Matthew D. Vago, David R. Valk, Sofie Zeidan, Fadel Zalesky, Andrew Turner, Jessica A. King, Anthony P. Department of Biomedical Engineering The University of Melbourne Carlton VIC Australia Contemplative Studies Centre Melbourne School of Psychological Sciences The University of Melbourne Melbourne VIC Australia Systems Lab of Neuroscience Neuropsychiatry and Neuroengineering The University of Melbourne Parkville VIC Australia Universidad Nacional Autónoma de México Instituto de Neurobiolgía México Querétaro Mexico Center for Translational Research in Neuroimaging and Data Science: Georgia State University Georgia Institute of Technology and Emory University Atlanta GA United States Department of Psychology Northeastern University Boston Massachusetts Brain and Cognitive Science McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge Massachusetts Department of Psychological and Brain Sciences Washington University St. Louis Missouri Department of Behavioral and Social Sciences Brown University School of Public Health Providence Rhode Island Department of Psychology Carnegie Mellon University Pittsburgh PA United States University of Southern California Department of Psychiatry & Behavioral Sciences Los Angeles California University of Southern California Center for Mindfulness Science Los Angeles California Institute for Advanced Consciousness Studies Santa Monica California Department of Psychiatry and Behavioral Health The Ohio State University College of Medicine Columbus OH United States Normandie University Université de Caen Normandie INSERM U1237 Neuropresage Team Cyceron Caen France Imaging Genetics Center Mark and Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine of the University of Southern California Los Angeles California Desert-Pacific Mental Illness Research Education and Clinical Center VA San Diego Healthcare System San Diego California Computational Neuroscience Group Center for Brain and Cognition Department of Information and Communication Technologies Universitat Pompeu Fa

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)–Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the f

关键词： Consortium ENIGMA Magnetic resonance imaging (MRI) Meditation Mindfulness Neuroimaging

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Nonlinear internal wave run-up on impermeable steep slopes

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Journal of Offshore Mechanics and Arctic engineering 2009年第4期131卷 1-5页

作者： Tseng, I-Fan Chen, Chen-Yuan Kuo, Hui-Ming Department of Marine Environment and Engineering National Sun Yat-Sen University Kaohsiung 80424 Taiwan Department of Computer Science National Pingtung University of Education No. 4-18 Ming Shen Rd. Pingtung 90003 Taiwan Department of Management Information System Yung-Ta Institute of Technology and Commerce Lin-Luoh Pingtung 90941 Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Department of Logistics Management Shu-Te University Yen Chau Kaohsiung 82445 Taiwan

Laboratory experiments were conducted to investigate the run-up of internal solitary waves (ISWs) on steep uniform slopes in a two-layered fluid system with a free surface. A 12 m long wave flume, which incorporated a movable vertical gate for generating ISWs, was used in the experiments. A steep uniform slope was modeled at one end of the flume. In the present study we looked at internal waves with small and large amplitudes using a steep uniform slope (from one of Θ=30, 50, 60, 90, 120, and 130 deg) much longer than those previously published in the literature. Results collected from a wide range of experimental runs show that the run-up height depends on the planar slope, while the breaking depth is only antecedent to the amplitude of an ISW. The overall quantitative agreement with the linear feature aspects of the incident wave amplitude is encouraging. Copyright © 2009 by ASME.

关键词： Arctic engineering

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High-Performance Chip Design With Parallel Architecture for Magnetic Field Imaging system

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IEEE Transactions on Instrumentation and Measurement 2024年 73卷 1-13页

作者： Lin, Ming-Yi Hsieh, Sheng-Hsien Chen, Ching-Han Lin, Chun-Hung Yuan Ze University Department of Computer Science and Engineering Taoyuan320315 Taiwan National Pingtung University of Science and Technology Program of Artificial Intelligence and Mechatronics Pingtung912301 Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan32001 Taiwan International Games System Company Ltd. New Taipei City248 Taiwan

To address the limitations of typical coil detection systems and enhance the performance of traditional magnetic field imaging (MFI) systems, we propose a MFI system that uses a 4×4 array of anisotropic magnetoresistance (AMR) sensors. The core controller of the proposed system was designed using a pipelined parallelization algorithm and implemented on a high-speed field-programmable gate array (FPGA) in a fully hardware-based architecture. The designed MFI system can achieve parallel acquisition of magnetic field components from the 16-channel AMR sensor array, parallel data processing, parallel data transmission, and parallel computations in a single cycle of only 4 ms. Compared with typical detection systems, the proposed solution not only exhibits superior performance but can also provide dynamic visual representations of sensed information. © 1963-2012 IEEE.

关键词： Parallel architectures

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Prediction of Post-COVID-19 Pandemic Learning Mode Preferences Using Machine Learning

Prediction of Post-COVID-19 Pandemic Learning Mode Preferenc...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Agus Pratondo Astri Novianty Budi Laksono Putro Siska Komala Sari Department of Multimedia Engineering School of Applied Sciences Telkom University Bandung Indonesia Department of Computer Engineering School of Electrical Engineering Telkom University Bandung Indonesia Department of Computer Science Education Indonesia University of Education Bandung Indonesia Diploma Program of Information System School of Applied System Telkom University Bandung Indonesia

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice.

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Sasirangan Cloth Recognition and Shopping Experience Simulation Based on Virtual Reality Game with Non-Player Character Integration

Sasirangan Cloth Recognition and Shopping Experience Simulat...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Subandi Subandi Aulia Akhrian Syahidi Siti Zakiah Kiyoshi Kiyokawa Ahmad Riyadi M. Helmy Noor Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia Informatics Engineering Undergraduate Program Faculty of Computer Science Universitas Brawijaya Malang Indonesia Cybernetics and Reality Engineering Laboratory Nara Institute of Science and Technology Ikoma Japan Informatics Engineering Diploma Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia

ISBN: (纸本)9781665476652

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91.

关键词： Human computer interaction COVID-19 Solid modeling Pandemics Games Virtual reality User experience

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Separation of mitochondrial diseased cells based on organelle-level difference using a dep microfluidic system 23

Separation of mitochondrial diseased cells based on organell...

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23rd International Conference on Miniaturized systems for Chemistry and Life sciences, MicroTAS 2019

作者： Chi, Pei-Yin Chuang, Ting-Wei Chu, Tzu-Tsai Kuo, Chia-Tzu Wu, Yu-Ting Farmehini, Vahid Shieh, Dar-Bin Tseng, Fan-Gang Wei, Yau-Huei Swami, Nathan Chou, Chia-Fu Nano Science and Technology Program TIGP Academia Sinica Taipei Taiwan Institute of Physics Academia Sinica Taipei Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu Taiwan Center for Mitochondrial Medicine Free Radical Research Changhua Christian Hospital Changhua Taiwan Department of Electrical and Computer Engineering University of Virginia Charlottesville United States Institute of Oral Medicine School of Medicine National Cheng-Kung University Tainan Taiwan

ISBN: (纸本)9781733419000

It is imperative to develop tools to characterize cells with the diseased and normal mitochondria to monitor the healthiness of cells and take preventive measures for potential mitochondrial disease development. Here, we adopt insulator dielectrophoresis (i-DEP), by utilizing the intrinsic dielectric response of a cell to an external AC electric field to differentiate cells, containing partially diseased and normal mitochondria. Taking advantage of dielectrophoresis, DEP, principle, we developed a quick diagnostic method to detect mitochondrial disease in living cells, which is not readily achievable by conventional cell cytometry. © 2019 CBMS-0001.

关键词： Electrophoresis

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