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

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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Fabric-substrated capacitive biopotential sensors enhanced by dielectric nanoparticles

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Nano Research 2021年第9期14卷 3248-3252页

作者： Xiangjun Chen Xiaoxiang Gao Akihiro Nomoto Keren Shi Muyang Lin Hongjie Hu Yue Gu Yangzhi Zhu Zhuohong Wu Xue Chen Xinyu Wang Baiyan Qi Sai Zhou Hong Ding Sheng Xu Materials Science and Engineering Program University of California San DiegoLa JollaCA 92093USA Department of NanoEngineering University of California San DiegoLa JollaCA 92093USA Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA Department of Bioengineering University of California San DiegoLa JollaCA 92093USA

Wearable biopotential sensing devices are essential to long-term and real-time monitoring of human ***-contact,capacitive sensing electrodes prevent potential skin iritations,and are thus beneficial for long-term *** capacitive electrodes are either connected to a separate control circuit via external wires or have limited sensing capacitances,which leads to low signal *** study demonstrates a stretchable capacitive sensing device with integrated electrodes and control electronics,with enhanced signal *** electrodes and the control electronics are fabricated on a common fabric substrate for breathability and strain-limiting *** stretchable electrodes are based on an island-bridge design with a stretchability as high as-100%,and an area ratio as high as-80%.By using a dielectric calcium copper titanate(CCTO)composite as the adhesive layer,the electrode capacitance can be increased,yielding an enhanced signal-to-noise ratio(SNR)in the acquired *** device offers a convenient and comfortable approach for long-term non-contact monitoring of biopotential signals.

关键词： capacitive sensing biopotential stretchable calcium copper titanate(CCTO) signal-to-noise ratio(SNR)

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NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improve the Performance of Pretrained Language Model in BioASQ 10b Phase B

NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improv...

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2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Ting, Hao-Hsuan Zhang, Yu Han, Jen-Chieh Tsai, Richard Tzong-Han Interdisciplinary Program of Electrical Engineering and Computer Science National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan IoX Center National Taiwan University Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taiwan

This paper presents our system for the BioASQ10b Phase B task. For ideal answers, we used the fine-tuned BioBERT model on the MNLI dataset to construct sentence embeddings and combined it with BERTScore to select sentences from the provided Snippets as answers. For the exact answers, we also used the BioBERT model and used the snippet scores generated from the ideal answer selection model to predict the exact answers for factoid and list questions. The exact answers of our fifth test batch ranked second place. In addition, the ideal answers we submitted achieved first place in the ROUGE score in all test batches from batch second to fifth. © 2022 Copyright for this paper by its authors.

关键词： Computational linguistics

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Sentiment Analysis of Cooking Oil using Bidirectional Encoder Representations from Transformers 5

Sentiment Analysis of Cooking Oil using Bidirectional Encode...

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5th International Conference on Information and Communications Technology, ICOIACT 2022

作者： Widianto, Mochammad Haldi Heryadi, Yaya Lukas Suparta, Wayan Wibowo, Antoni Bina Nusantara University Computer Science Department Binus Graduate Program - Doctor of Computer Science Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Departement of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (数字)9781665451406

ISBN: (纸本)9781665451406

Recently, cooking oil has been widely discussed on social media. Many people ask how to analyze this phenomenon, one of which is using a sentiment analysis application on Twitter that performs a scientific analysis of the tweets of this media user. This study aims to test the performance of the sentiment analysis algorithm utilizing the Bidirectional Encoder Representations from Transformers (BERT) algorithm from Twitter, which is used to classify the types of tweets processed in 2000 tweets. The study shows the results of the confusion matrix, accuracy, and precision. The study obtained a fairly good accuracy and precision performance of 84%, which occurred at a learning rate of 1e-6 and epoch 5. The author also discusses the factors that affect the performance of BERT, such as;pre-processing, data quantity, and data variation. © 2022 IEEE.

关键词： Sentiment analysis

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Grating Coupled Attachment of Optical Fiber Arrays for in Situ Photonics Experimentation

Grating Coupled Attachment of Optical Fiber Arrays for in Si...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Kellen P. Arnold Joel B. Slaby Hannah M. Dattilo C. Alex Kaylor Ronald D. Schrimpf Daniel M. Fleetwood Stephen E. Ralph Robert Reed Sharon M. Weiss Interdisciplinary Materials Science Program Vanderbilt University Nashville TN USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Vanderbilt University Nashville TN USA

We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ra... 详细信息

ISBN: (纸本)9798350369311

关键词： Optical fibers Radiation effects X-ray lasers Waveguide lasers Fiber gratings Robustness Optical fiber devices Arrayed waveguide gratings Photonics Optical arrays

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Comparison of Coherent and Incoherent Donut Beams for Deep Tissue STED Microscopy

Comparison of Coherent and Incoherent Donut Beams for Deep T...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Shanavas, Thariq McLeod, Robert R. Siemens, Mark E. Gopinath, Juliet T. Department of Physics University of Colorado BoulderCO80309 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Department of Physics University of Denver DenverCO80204 United States Materials Science Engineering Program University of Colorado BoulderCO80309 United States

We numerically compare the null quality for STED microscopy generated by Laguerre-Gaussian beams with orbital angular momentum and donut beams generated by incoherent addition of orthogonal Hermite Gaussian beams when... 详细信息

ISBN: (纸本)9781957171258

关键词： Tissue

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Broadband Untuned Active Cancellation and Phase Correction of Direct Feedthrough Interference Enables 100-fold Improved Magnetic Particle Imaging Detection

TechRxiv

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TechRxiv 2023年

作者： Huynh, Quincy Doyle, Owen Guo, Kelvin Swamynathan, Arvind Huang, Leo Garlepp, Justin Dambal, Nessia Bryan, Jacob Ramdani, Syahrul Saayujya, Chinmoy Fung, Barry K.L. Lu, Yao Fellows, Benjamin Sehl, Olivia Conolly, Steven The Department of Electrical Engineering and Computer Science University of California BerkeleyCA94720 United States The Department of Bioengineering Department of Electrical Engineering and Computer Science University of California BerkeleyCA94720 United States Department of Bioengineering University of California BerkeleyCA94720 United States Magnetic Insight Inc. AlamedaCA94501 United States Department of Electrical Engineering Universitas Indonesia Depok Indonesia

Magnetic particle imaging (MPI) is a tracer imaging modality that detects superparamagnetic iron oxide nanoparticles (SPIOs), enabling sensitive, radiation-free imaging of cells and disease pathologies. The arbitrary waveform relaxometer (AWR) is an indispensable platform for developing magnetic nanoparticle tracers and evaluating tracer performance for magnetic particle imaging applications. One of the biggest challenges in arbitrary waveform excitation is direct feedthrough interference, which is usually six orders of magnitude larger than the signal from magnetic nanoparticles. This work will showcase hardware that suppresses this interference by an order of magnitude, increasing the dynamic range of the instrument and enabling mass-limited detection at full scale range. © 2023, CC BY.

关键词： Iron oxides

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Convergent effects of peptides on the initiation of feeding motor programs in the mollusk Aplysia

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Journal of Neurophysiology 2025年第5期133卷 1368-1379页

作者： Evans, Colin G. Barry, Michael A. Reaver, Carrie N. Patel, Paras R. Chestek, Cynthia A. Perkins, Matthew H. Jing, Jian Cropper, Elizabeth C. Department of Neuroscience Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY United States Department of Biomedical Engineering Biointerfaces Institute University of Michigan Ann Arbor MI United States Department of Electrical Engineering and Computer Science Neurosciences Program Robotics Program University of Michigan Ann Arbor MI United States State Key Laboratory of Pharmaceutical Biotechnology Institute for Brain Sciences Chemistry and Biomedicine Innovation Center Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology Advanced Institute for Life Sciences School of Life Sciences Nanjing University Nanjing China

Neuropeptides configure the feeding network of Aplysia. For example, egestive activity is promoted by small cardioactive peptide (SCP), and ingestive activity is promoted by a combination of feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP-2). In addition, SCP and FCAP/CP-2 have a common network effect that does not contribute to motor program specification. They increase the excitability of an interneuron, B63. In this report, we further characterized the effects of peptides on B63. We performed voltage-clamp experiments and used a step protocol to look at steady-state currents. We found that SCP and FCAP/CP-2 both induced an inward current that was virtually absent in low-sodium saline. Previous work has established that B63 is unusual in the feeding circuit in that subthreshold depolarizations are autonomously generated that can trigger motor programs. Here, we show that this autonomous activity is more frequent in the presence of peptides. Previous studies have also shown that activity of the feeding central pattern generator (CPG) can be initiated by neurons that excite B63, e.g., by cerebral buccal interneuron 2 (CBI-2), a projection neuron that triggers biting-like motor programs. Here, we show that the latency of CBI-2-induced activity is decreased by stimulation of the esophageal nerve (EN) (which releases endogenous SCP). These results, taken together with previous results, indicate that peptides that act divergently to configure network activity additionally act convergently to promote motor program induction. We present data that suggest that this arrangement facilitates brief switches between ingestive and egestive motor activity. © 2025 The Authors.

关键词： central pattern generator invertebrate modulation motor program neuropeptide

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Enhancing the Performance of E-Mode AlGaN/GaN HEMTs With Recessed Gates Through Low-Damage Neutral Beam Etching and Post-Metallization Annealing

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 150-155页

作者： Chen, Yi-Ho Ohori, Daisuke Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan Tohoku University Institute of Fluid Science Sendai980-8577 Japan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Pioneer Semiconductor Innovation Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan

This study investigated the electrical properties of AlGaN/GaN high-electron-mobility transistors (HEMTs) with varied recess depths under the gate electrode. We demonstrated a recess depth of approximately 6 nm, which was achieved through neutral beam etching (NBE) technique with a low etch rate of 1.8 nm/min, resulting in device enhancement-mode (E-mode) behavior with threshold voltage (Vth) of 0.49 V. The effects of post-metallization annealing (PMA) on the device performance were also examined. The results revealed that PMA treatment improves the DC characteristics of the devices, including maximum drain current (IDMAX), transconductance (gm), subthreshold swing (SS), on-off ratio, and off-state leakage current, with maximum enhancement percentage of 18.3% for IDMAX, 3758% for on-off ratio, and 54.3% for SS. Moreover, this study compared the recess depths of metal-insulator-semiconductor high-electron-mobility transistors (MIS-HEMTs) with the SiN dielectric layer. The results showed that MIS-HEMTs exhibit more negative Vth values, which can be attributed to the controlled surface states achieved through passivation. © 2020 IEEE.

关键词： Etching

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Prediction of colorectal cancer based on taxonomic levels of microorganisms and discovery of taxonomic biomarkers using the Grouping-Scoring-Modeling (G-S-M) approach

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computers in Biology and Medicine 2025年 187卷 109813-109813页

作者： Bakir-Gungor, Burcu Temiz, Mustafa Canakcimaksutoglu, Beyza Yousef, Malik Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri38080 Turkey Department of Electrical and Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri38080 Turkey Department of Bioengineering Faculty of Life and Natural Science Abdullah Gul University Kayseri38080 Turkey Department of Information Systems Zefat Academic College Zefat13206 Israel Zefat Academic College Israel

Colorectal cancer (CRC) is one of the most prevalent forms of cancer globally. The human gut microbiome plays an important role in the development of CRC and serves as a biomarker for early detection and treatment. This research effort focuses on the identification of potential taxonomic biomarkers of CRC using a grouping-based feature selection method. Additionally, this study investigates the effect of incorporating biological domain knowledge into the feature selection process while identifying CRC-associated microorganisms. Conventional feature selection techniques often fail to leverage existing biological knowledge during metagenomic data analysis. To address this gap, we propose taxonomy-based Grouping Scoring Modeling (G-S-M) method that integrates biological domain knowledge into feature grouping and selection. In this study, using metagenomic data related to CRC, classification is performed at three taxonomic levels (genus, family and order). The MetaPhlAn tool is employed to determine the relative abundance values of species in each sample. Comparative performance analyses involve six feature selection methods and four classification algorithms. When experimented on two CRC associated metagenomics datasets, the highest performance metric, yielding an AUC of 0.90, is observed at the genus taxonomic level. At this level, 7 out of top 10 groups (Parvimonas, Peptostreptococcus, Fusobacterium, Gemella, Streptococcus, Porphyromonas and Solobacterium) were commonly identified for both datasets. Moreover, the identified microorganisms at genus, family, and order levels are thoroughly discussed via refering to CRC-related metagenomic literature. This study not only contributes to our understanding of CRC development, but also highlights the applicability of taxonomy-based G-S-M method in tackling various diseases. © 2025 Elsevier Ltd

关键词： Colorectal cancer Human gut microbiome Machine learning Taxonomic biomarkers MicroBiomeGSM

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