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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Han, Jinjing Ho, Tawen Stine, Justin M. Straker, Michael A. Herberholz, Jens Ghodssi, Reza University Of Maryland Department Of Electrical And Computer Engineering College ParkMD United States University Of Maryland Institute For System Research College ParkMD United States University Of Maryland Robert E. Fischell Institute For Biomedical Devices College ParkMD United States University Of Maryland Department Of Psychology College ParkMD United States University Of Maryland Program In Neuroscience And Cognitive Science College ParkMD United States University Of Maryland Fischell Department Of Bioengineering College ParkMD United States

ISBN: (纸本)9784886864352

This work presents, for the first time, an implantable biosensor for continuous in vivo serotonin (5-HT) monitoring in freely moving crayfish. 5-HT is an important neurotransmitter that regulates animal behaviors. Conventional methods for detecting 5-HT do not provide real-time information. Our approach facilitates continuous electrochemical monitoring of 5-HT levels without impeding animal natural behavior. The sensing system shows a linear range of 0.4 - 1.2 μΜ with a sensitivity of 0.07 μA/μΜ for 5-HT detection. With a 3D-printed package, the sensor can be easily attached to crayfish dorsal carapace allowing electrodes implantation into crayfish heart to monitor neurohormonal dynamics of 5-HT. The implantable biosensor system displayed a significant increase in oxidation currents after 5-HT injections. The device successfully demonstrates the application for in vivo detection of 5-HT in the hemolymph (i.e., blood) of freely behaving crayfish underwater. © 2023 IEEJ.

关键词： Biosensing Electrochemical Device Electrochemistry Implantable Electrode In Vivo Sensing

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The utilization of search engines by students of the Library and Information science program at Universitas Padjadjaran

The utilization of search engines by students of the Library...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information systems, and Information Technology, WMA-Mathcomtech 2018

作者： Kurniasih, Nuning Kurniawati, Nanik Yulianti, Y. Rahim, Robbi Sujito, S. Ikhwan, Afiful Aimang, Hasrat A. Haluti, Farid Putri, Lusi Dwi Napitupulu, Darmawan Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Jakarta Indonesia Sekolah Dasar Negeri 3 Rajapolah Tasikmalaya Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Department of English Language Education IAIN Surakarta Surakarta Indonesia Postgraduate Universitas Muhammadiyah Ponorogo Ponorogo Indonesia Universitas Muhammadiyah Luwuk Luwuk Banggai Indonesia Universitas Lancang Kuning Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia

Search engines have become an integral part of student learning activities. This study aims to see how the use of search engines by students, especially by students of the Library and Information science program, Faculty of Communication sciences, Universitas Padjadjaran. This study uses the mixed method. The research data was obtained through questionnaires, in-depth interviews, observations and literature studies. The results of the study showed that in learning activities, the respondents used search engines to find the references for college assignments and thesis writing material. The students also use search engines to meet daily information needs, solve problems, increase knowledge, reduce doubts, clarify things, entertain, fulfill curiosity about others, etc. The retrieval technique used by students is by using keywords/queries, Boolean logic, query strategies in the form of a brief search and using the advanced search feature. This research is expected to contribute to the university in supporting online-based learning facilities for students. © Published under licence by IOP Publishing Ltd.

关键词： Search engines

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VIRTUAL PROTOTYPING USING KNOWLEDGE - BASED MODELING AND SIMULATION TECHNIQUES

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NAVAL ENGINEERS JOURNAL 1993年第3期105卷 201-212页

作者： SHEA, JG The Author:holds bachelor and master of engineering degrees in mechanical engineering a M.Eng. in engineering management and is currently fulfilling requirements for the M.S. and Ph.D. degrees in computer science at the University of Louisville. He is employed as program manager Phalanx Advanced Engineering Development at the Naval Ordnance Station Crane Div. NavSurfWarCen Louisville Ky. During his tenure with Phalanx Mr. Shea has contributed to system reliability improvement system performance upgrading and the development of the Phalanx HOL (RISC) Computer. Mr. Shea is a member of ASNE the Institute of Electrical and Electronics Engineers American Institute of Aeronautics and Astronautics Society for Computer Simulation International Test & Evaluation Association and the Military Operations Research Society.

Knowledge-based modeling and simulation bridges the gap between ''conventional'' artificial intelligence implementations (such as expert systems) and more traditional computer-aided design techniques. We are currently developing software, whose primary function is to capture a user-input design specification and produce a ''virtual'' rapid prototvpe in the form of executable rule-based code. This code can then be exercised either as an interactive part of a hardware-in-the-loop testbed simulator or as a component of an object-oriented ''behavioral'' simulation environment. While the Phalanx Testbed is the immediate beneficiary of this work, the techniques described have a wide range of application in the modeling of conceptual design and performance characteristics. This paper describes the system architecture and software tools that we are applying to generate virtual rapid prototypes for use in the Phalanx Testbed. Particular attention is paid to defining the intelligent knowledge-capture mechanisms and model generation methodologies that we are using to translate design knowledge and performance requirements into rule-based simulations. The object-oriented programming approach to the merging of ''new'' data with previouslv-captured and stored data is discussed, and the issues of verifying and validating prototypes generated using such partiallv ''reengineered'' models are examined. An application currently in use as an investigative prototype for testbed development, a simple position controller servomechanism used to control the azimuth angle of a target-tracking sensor, is used to illustrate the process.

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A deep learning system for predicting time to progression of diabetic retinopathy

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NATURE MEDICINE 2024年第2期30卷 358-359页

作者： [Anonymous] Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Huadong Sanatorium Wuxi China Department of Ophthalmology Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong China Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Hong Kong China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Department of Ophthalmology Peking Union Medical College Hospital Peking Union Medical College Chinese Academy of Medical Sciences Beijing China Medical Records and Statistics Office Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Geriatrics Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Tech

We developed and validated a deep learning system (termed DeepDR Plus) in a diverse, multiethnic, multi-country dataset to predict personalized risk and time to progression of diabetic retinopathy. We show that DeepDR Plus can be integrated into the clinical workflow to promote individualized intervention strategies for the management of diabetic retinopathy.

关键词： Diabetes complications Machine learning Predictive markers

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

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

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International Conference on Informatics and Computing (ICIC)

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

ISBN: (纸本)9798350345728

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.

关键词： Visualization Codes Media Data models Recording Data mining Problem-solving

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Preferences for Using Canva Apps as a Presentation Media Creation Tool Among Gen Z Students: SEM Analysis with TAM and UTAUT2 Approaches

Preferences for Using Canva Apps as a Presentation Media Cre...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Fairuz Iqbal Maulana Dian Lestari Agung Purnomo Rahman Arifuddin Vandha Pradwiyasma Widartha Puput Dani Prasetyo Adi Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Medicine Airlangga Surabaya 60132 Indonesia Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Department of Electrical Engineering University of Merdeka Malang Malang Indonesia Information System of Industrial Engineering Faculty Telkom University Bandung Indonesia Research Center for Telecommunication National Research and Innovation Agency (BRIN) Bandung Indonesia

ISBN: (数字)9798350378573

ISBN: (纸本)9798350378580

The purpose of this study is to find out what makes Generation Z students accept and use Canva as a tool for making presentation materials. The conceptual framework of this study is the combination of "Technology Acceptance Model (TAM)" and the "Unified Theory of Acceptance and Use of Technology (UTAUT2)". "Structural Equation Modeling (SEM)" used for data analyzation. This research aims to understand the dynamics of Canva acceptance among students. The findings show that enjoyment, fun, and pleasure in using Canva, combined with its creative tools and design-centric approach, significantly resonate with Gen Z's preference for aesthetics. This research highlights that Canva is favored by students for creating engaging presentations.

关键词： Seminars Analytical models Technology acceptance model Accuracy Numerical analysis Media Mathematical models

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DEA and Fuzzy Simple Additive Weighting for Benchmarking Qualitative Data 1

DEA and Fuzzy Simple Additive Weighting for Benchmarking Qua...

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1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Abdullah, Dahlan Hartono, H. Ongko, Erianto Erliana, Cut Ita Irwansyah, Defi Iskandar, Akbar Sari, Ayu Esteka Abdussakir Yuniningsih Siregar, Nurintan Asyiah Kahar, Muhammad Syahrul Waliulu, Raditya Faisal Amalia, Ainna Kurniasih, Nuning Arifin, Muhammad Muzid, Syafiul Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Akademi Teknologi Industri Immanuel Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Economic and Business Universitas Pembangunan Nasional Veteran Surabaya Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Mathematics Education Department Universitas Muhammadiyah Sorong Sorong Indonesia Informatics Engineering Department Universitas Muhammadiyah Sorong Sorong Indonesia Islamic Institut of Miftahul Ula Kertosono Nganjuk East Java Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Information System Faculty of Engineering Universitas Muria Kudus Indonesia Information System Department Universitas Muria Kudus Indonesia

Data Envelopment Analysis (DEA) is one method that is often used in the benchmarking process. The benchmarking process with DEA is often faced with problems where there is a Decision Making Unit (DMU) both Input and Output which is not in the form of qualitative data but in the form of qualitative data. Qualitative data requires an assessment from the appraiser so that it can become quantitative data. This study will use the Fuzzy Simple Additive Weighting method to convert qualitative data into quantitative. The results of this study will produce a model that integrates DEA with Fuzzy Simple Additive Weighting. © Published under licence by IOP Publishing Ltd.

关键词： Data envelopment analysis

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A multi-protease, multi-dissociation, bottom-up-to-top-down proteomic view of the Loxosceles intermedia venom

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Scientific Data 2017年第1期4卷 170090-170096页

作者： Trevisan-Silva, Dilza Bednaski, Aline V. Fischer, Juliana S.G. Veiga, Silvio S. Bandeira, Nuno Guthals, Adrian Marchini, Fabricio K. Leprevost, Felipe V. Barbosa, Valmir C. Senff-Ribeiro, Andrea Carvalho, Paulo C. Department of Cell Biology Federal University of Paraná Curitiba 81531-980 Brazil Computational Mass Spectrometry and Proteomics Group Carlos Chagas Institute Fiocruz Curitiba 81.350-010 Brazil Center for Computational Mass Spectrometry University of California San Diego 92093-0404 United States Functional Genomics Laboratory Carlos Chagas Institute Fiocruz Curitiba 81.350-010 Brazil Mass Spectrometry Facility RPT02H Carlos Chagas Institute Fiocruz Curitiba 81.350-010 Brazil Systems Engineering and Computer Science Program COPPE Federal University of Rio de Janeiro Rio de Janeiro 21941-914 Brazil Laboratory of Toxinology Fiocruz Rio de Janeiro 21040-900 Brazil

Venoms are a rich source for the discovery of molecules with biotechnological applications, but their analysis is challenging even for state-of-the-art proteomics. Here we report on a large-scale proteomic assessment of the venom of Loxosceles intermedia, the so-called brown spider. Venom was extracted from 200 spiders and fractioned into two aliquots relative to a 10 kDa cutoff mass. Each of these was further fractioned and digested with trypsin (4 h), trypsin (18 h), pepsin (18 h), and chymotrypsin (18 h), then analyzed by MudPIT on an LTQ-Orbitrap XL ETD mass spectrometer fragmenting precursors by CID, HCD, and ETD. Aliquots of undigested samples were also analyzed. Our experimental design allowed us to apply spectral networks, thus enabling us to obtain meta-contig assemblies, and consequently de novo sequencing of practically complete proteins, culminating in a deep proteome assessment of the venom. Data are available via ProteomeXchange, with identifier PXD005523.

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FetalNet: Low-light fetal echocardiography enhancement and dense convolutional network classifier for improving heart defect prediction

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Informatics in Medicine Unlocked 2022年 35卷

作者： Sutarno, Sutarno Nurmaini, Siti Partan, Radiyati Umi Sapitri, Ade Iriani Tutuko, Bambang Naufal Rachmatullah, Muhammad Darmawahyuni, Annisa Firdaus, Firdaus Bernolian, Nuswil Sulistiyo, Deny Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya Indonesia Faculty of Medicine Universitas Sriwijaya Indonesia Division of Fetomaternal Department of Obstetrics and Gynaecology Mohammad Hoesin General Hospital Indonesia

Background: Fetal heart defect (FHD) examination by ultrasound (US) is challenging because it involves low light, contrast, and brightness. Inadequate US images of fetal echocardiography play an important role in the failure to detect FHDs manually. The automatic interpretation of fetal echocardiography was proposed in a previous study. However, the low quality of US images reduces the prediction rate of computer-assisted diagnosis results. Methods: To increase the FHD prediction rate, we propose low-light fetal echocardiography enhancement stacking with a dense convolutional network classifier named “FetalNet.” Our proposed FetalNet model was developed using 460 US images to produce an image enhancement model. The results showed that all raw US images could be improved with satisfactory performance in terms of increasing the peak signal-to-noise ratio of 30.85 dB, a structural similarity index of 0.96, and a mean squared error of 18.16. Furthermore, all reconstructed images were used as inputs in a convolutional neural network to generate the best classifier for predicting FHD. Results: The proposed FetalNet model increased the FHD prediction rate by approximately 25% in terms of accuracy, sensitivity, and specificity and produced 100% predictive negative using unseen data. Conclusions: The proposed deep learning model has the potential to identify FHD accurately and shows potential for practical use in identifying congenital heart diseases in the future. © 2022 The Author(s)

关键词： Congenital heart disease Deep learning Low light image enhancement Ultrasound

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An agent-based architecture for knowledge management in context-aware business processes

An agent-based architecture for knowledge management in cont...

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International Conference on computer Supported Cooperative Work in Design

作者： Leonardo A. de C. Gatti Flávia Maria Santoro Vanessa T. Nunes NP2TEC - Research and Practice Group in Information Technology UNIRIO Rio de Janeiro Brazil NP2TEC-Research and Practice Group in Information Technology Department of Applied Informatics UNIRIO Federal University of Rio de Janeiro Rio de Janeiro Brazil COPPE - Systems Engineering and Computer Science Program UFRJ Rio de Janeiro Brazil

The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware architecture to support knowledge management in working processes. The required features for this architecture are processing, reasoning and sharing contextual knowledge involving information about activities performed. We also present results from evaluation of our proposal — A-CoBrA — for a specific domain.

关键词： Knowledge management computer architecture Context modeling Collaborative work Proposals Information technology Informatics Service oriented architecture Ontologies Knowledge engineering

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