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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Augusta Steven Benedict Umi Rosyidah Ardiawan Bagus Harisa Hanny Haryanto Study Program in Information Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

One of the critical visual components in video game creation is 3D asset prototypes, which also require significant effort. A procedural model using the L-system method for making low-poly buildings can address this issue. This model produces low-poly buildings based on simple parameters input by the user. The model receives input in the form of axioms, which are then processed according to predetermined L-system rules. After the building is formed, it is saved as a prefab in Unity so that it can be reused and modified by the user. The proposed method is implemented to our turn-based tactic *** and provided as a Unity package (add-on). Experimental results show that the buildings generated by the model have a minimalistic yet functional benefits.

关键词： Seminars Visualization Video games Three-dimensional displays Shape Buildings Prototypes Games Rendering (computer graphics) Generators

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Enhancing Video Action Recognition with Spatial–Temporal Convolutional Attention Networks 15th

Enhancing Video Action Recognition with Spatial–Temporal Co...

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15th International Conference on Intelligent Computing and Networking, IC-ICN 2024

作者： Kumar, Pramod Quraishi, Aadam Rusho, Maher Ali Raparthi, Mohan Degadwala, Sheshang Computer Science and Technology Ganga Institute of Technology and Management Haryana Jhajjar Kablana124104 India Intervention Treatment Institute HoustonTX United States Degree Program University of Colorado Boulder CO United States Software Engineer Alphabet Life Science DallasTX75063 United States Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9789819786305

Effectively harnessing feature correlations is crucial for optimal performance in video action recognition tasks, whether in spatial or temporal dimensions. Convolutional operations excel at capturing local features through correlations among nearby points, while self-attention mechanisms capture global information by enabling interactions among all feature points. However, the limitations of a single convolutional layer in comprehending holistic feature correlations and the tendency of self-attention layers to overlook local positional characteristics necessitate an innovative approach. We introduce the Spatial–Temporal Convolutional Attention Network, comprising the Spatial Convolutional Attention Network and the Temporal Convolutional Attention Network. This approach strategically combines the strengths of self-attention for global context and convolution for local features, mitigating the limitations of individual layers. Key innovations include [explicitly state innovations]. To reinforce the uniqueness of our approach, we provide specific comparisons with existing methods, highlighting its superiority. In rigorous experiments, our proposed network demonstrates enhanced recognition performance, quantified through metrics such as accuracy and F1 score improvements over baseline models. By effectively capturing feature correlations, our approach elevates the neural network's capacity for spatiotemporal modeling, marking a significant advancement in video action recognition. Elevating the neural network's capacity for spatiotemporal modeling. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Super-Resolution Displacement Spectroscopic Sensing over a Surface“Rainbow”

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engineering 2022年第10期17卷 75-81页

作者： Lyu Zhou Nan Zhang Chang Chieh Hsu Matthew Singer Xie Zeng Yizheng Li Haomin Song Josep Jornet Yun Wu Qiaoqiang Gan Department of Electrical Engineering The State University of New York at BuffaloBuffaloNY 14260USA Department of Biomedical Engineering The State University of New York at BuffaloBuffaloNY 14260USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA 02115USA Material Science Engineering Program King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia

Subwavelength manipulation of light waves with high precision can enable new and exciting applications in spectroscopy,sensing,and medical *** these applications,miniaturized spectrometers are desirable to enable the on-chip analysis of spectral *** particular,for imaging-based spectroscopic sensing mechanisms,the key challenge is to determine the spatial-shift information accurately(i.e.,the spatial displacement introduced by wavelength shift or biological or chemical surface binding),which is similar to the challenge presented by super-resolution ***,we report a unique"rainbow"trapping metasurface for on-chip spectrometers and *** with super-resolution image processing,the low-setting 4×optical microscope system resolves a displacement of the resonant position within 35 nm on the plasmonic rainbow trapping metasurface with a tiny area as small as0.002 *** unique feature of the spatial manipulation of efficiently coupled rainbow plasmonic resonances reveals a new platform for miniaturized on-chip spectroscopic analysis with a spectral resolution of 0.032 nm in wavelength *** this low-setting 4×microscope imaging system,we demonstrate a biosensing resolution of 1.92×109exosomes per milliliter for A549-derived exosomes and distinguish between patient samples and healthy controls using exosomal epidermal growth factor receptor(EGFR)expression values,thereby demonstrating a new on-chip sensing system for personalized accurate bio/chemical sensing applications.

关键词： Rainbow trapping Metasurface Surface plasmon polaritons Super-resolution displacement On-chip biosensing

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Bubble-pen lithography:Fundamentals and applications

Aggregate

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Aggregate 2022年第4期3卷 85-100页

作者： Pavana Siddhartha Kollipara Ritvik Mahendra Jingang Li Yuebing Zheng Walker Department of Mechanical Engineering The University of Texas at AustinAustinTexasUSA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTexasUSA Material Science and Engineering Program Texas Materials InstituteThe University of Texas at AustinAustinTexasUSA

Developing on-chip functional devices requires reliable fabrication methods with high resolution for miniaturization,desired components for enhanced performance,and high throughput for fast prototyping and mass ***,laser-based bubble-pen lithography(BPL)has been developed to enable sub-micron linewidths,in situ synthesis of custom materials,and on-demand patterning for various functional components and *** exploits Marangoni convection induced by a laser-controlled microbubble to attract,accumulate,and immobilize particles,ions,and molecules onto different *** years have witnessed tremendous progress in theory,engineering,and application of BPL,which motivated us to write this ***,an overview of experimental demonstrations and theoretical understandings of BPL is ***,we discuss the advantages of BPL and its diverse applications in quantum dot displays,biological and chemical sensing,clinical diagnosis,nanoalloy synthesis,and *** conclude this review with our perspective on the challenges and future directions of BPL.

关键词： additive manufacturing capillary flow lithography marangoni convection microbubbles sensing

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Metaverse with Mobile Twin Edge Computing: Empowering Optimal Efficiency and Accuracy

Metaverse with Mobile Twin Edge Computing: Empowering Optima...

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2024 International Conference on engineering and Computing, ICECT 2024

作者： Bibi, Asma Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Software Engineering Islamabad Pakistan Kohsar University Department of Computer Science Murree Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul08826 Korea Republic of

ISBN: (纸本)9798350349719

The concept of Digital Twin has been widely used by researchers to represent physical entities in computer-generated reality in the metaverse. In this research, a novel concept of 'Mobile Twin' is coined. Mobile Twin serves as a replica of a mobile device in the virtual environment enabling communication. The purpose of introducing Mobile Twin in the metaverse is to bring mobility and benefits similar to tangible mobile devices while eliminating the need for individual energy sources, storage limitations, resource usage, and efficiency. The true benefits of a mobile twin can be achieved with an architecture where computing nodes are decentralized, data processing is near the network's edge with faster response times and reduced latency. For this purpose, the mobile twin-based applications of metaverse are built over edge computing-based network architecture. This idea introduced the aspect of 'Revolutionary Ultra-low latency (RULL)' in the metaverse. © 2024 IEEE.

关键词： Electric power utilization

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Charging Scheme for Wireless Sensor Network Based on Area Scanning and Energy Detection

Charging Scheme for Wireless Sensor Network Based on Area Sc...

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作者： Ye Xiaojie Zau Kaming Electronic and Computer Engineering department Hong Kong University of Science and Technology computer engineering program Hong Kong University of Science and Technology

With the development of wireless sensor networks,the demand for wireless sensors increased *** the same time,there is a problem that the storage of energy is relatively low due to the small size of wireless sensors,which means that it needs to replace when sensors are out of *** will cost huge finance and pollute the ***,many scholars propose using wireless sensors that can recharge instead of primary wireless *** this case,choosing a suitable route to charge wireless sensors has become a significantly critical problem as there is a relationship between energy loss and the charging *** it is unstable or unsuitable to use solar energy and wind energy to charge,charging wireless sensors using drones,proposed by Kulaea ***1,Han Xu,and Bang Wang [1],has become a feasible ***,this solution still has some drawbacks as it only uses energy to charge the point with the lowest energy level by drones without considering the priority,the rest of the power,and the efficiency of time and *** report will use the data about the utilization rate of energy and make some comparisons to improve this solution.

关键词： Wireless Communication Networks Drones Priority Based On Energy Optimized Path Energy Transfer

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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Towards a Healthy AI Tradition: Lessons from Biology and Biomedical science

arXiv

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arXiv 2024年

作者： Kasif, Simon Department of Biomedical Engineering Bioinformatics Graduate Program Department of Computer Science Boston University United States Department of Computer Science Tel Aviv University

AI is a magnificent field that directly and profoundly touches on numerous disciplines ranging from philosophy, computer science, engineering, mathematics, decision and data science and economics, to cognitive science, neuroscience and more. The number of applications and impact of AI is second to none and the potential of AI to broadly impact future science developments is particularly thrilling. While attempts to understand knowledge, reasoning, cognition and learning go back centuries, AI remains a relatively new field. In part due to the fact it has so many wide-ranging overlaps with other disparate fields it appears to have trouble developing a robust identity and culture. Here we suggest that contrasting the fast-moving AI culture to biological and biomedical sciences is both insightful and useful way to inaugurate a healthy tradition needed to envision and manage our ascent to AGI and beyond (independent of the AI Platforms used). After all, the human brain is a biological organ produced by evolution and human intelligence is a remarkable bi-product of nature and nurture and their complex interaction. In this perspective, we focus on traditions and culture, namely the commonly observed practices of evaluating, recognizing applauding, critiquing, debating and managing all progress including useful advances and discovery of challenging limitations. We are not discussing specific scientific exchanges between AI and Biology that include interdisciplinary cross fertilization of scientific methods, technology, ideas and applications that have been amply demonstrated and will continue to be transformative in the future. In a previous perspective, we suggested that biomedical laboratories or centers can usefully embrace logistic traditions in AI labs that will allow them to be highly collaborative, improve the reproducibility of research, reduce risk aversion and produce faster mentorship pathways for PhDs and fellows. This perspective focuses on the benefits of AI a

关键词： Biological organs

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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Prognostics and System Health Management Conference (PHM)

作者： Congrui Cai Zhonghai Lu Embedded Systems Master Program School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Department of Electrical Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms.

关键词： Performance evaluation Semiconductor device modeling Recurrent neural networks Computational modeling Estimation Power electronics Data models

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Students Learning Performance and Engagement in a Visual programming Environment

Students Learning Performance and Engagement in a Visual Pro...

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Proceedings of the 6th International Conference on Innovative Technologies and Learning, ICITL 2023

作者： Wen, Fu-Hsiang Wu, Tienhua Hsu, Wei-Chih Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Management Air Force Institute of Technology Kaohsiung Taiwan Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9783031401121

This study employed a quasi-experimental method to explore differences in students’ learning performance and engagement between visual and textual language programming environments. Specifically, this study examined how strongly engagement dimensions affect participants’ learning achievement in a Scratch experimental setting. One hundred and thirty-two undergraduate students participated. The results revealed that participants with Scratch intervention outperformed those with text-based language instructions in terms of performance and behavioral, emotional, cognitive, and agentic engagement. The findings indicated that engagement significantly predicted student academic success in a visual learning environment. This study concluded that visual programming tools such as Scratch help novices engaged and effectively learn core aspects of programming concepts. Additionally, student engagement deepens an understanding of predictions of programmers’ behaviors and achievements and mechanisms behind the effectiveness of visualization intervention. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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