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2nd IEEE Global Conference on Life sciences and Technologies, LifeTech 2020

作者： Kishimoto, Yuta Arai, Kenichi Imai, Tetsuo Kobayashi, Toru Nagasaki University Computer and Information Science Program Graduate School of Engineering Nagasaki Japan Nagasaki University Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki Japan

ISBN: (纸本)9781728170633

We have developed the Shopping Refugees Support Robot that enables the elderly to order items through Social Networking Service (SNS) by voice conversation without relying on smartphones. This paper proposes a detection method of dementia signs using this Robot. Concretely, deterioration of cognitive function is detected by the evaluation of short-term memory utilizing order history of the Robot. We expect detection of dementia signs on a daily basis without making the elderly person conscious of having a dementia test, by information that only the person knows. We implemented a prototype and confirmed its functional validity. © 2020 IEEE.

关键词： Internet of things

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An Index-Based Flood Mapping Using Stokes Parameters of Multitemporal SAR Images: 2019 Hagibis Flood Event of Ibaraki, Japan

An Index-Based Flood Mapping Using Stokes Parameters of Mult...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ruma Adhikari Narumasa Tsutsumida Alok Bhardwaj Department of Civil Engineering Indian Institute of Technology Roorkee Uttarakhand India Department of Information and Computer Sciences Graduate School of Science and Engineering Saitama University Saitama Japan

We performed flood inundation mapping using polarimetry decompositions on Sentinel-1 synthetic aperture radar data for the 2019 Hagibis flood event in Ibaraki, Japan. We have proposed an index-based method based on Stokes parameters obtained from dual-polarized Sentinel-1 data. Our method shows that the eigenvalue λ1-based flood inundation (FI) map achieves an F1 score of approximately 0.73 compared to a high-resolution flooded optical image.

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Automatic benign and malignant estimation of bone tumors using deep learning 5

Automatic benign and malignant estimation of bone tumors usi...

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5th IEEE International Conference on Cybernetics, CYBCONF 2021

作者： Furuo, Kaito Morita, Kento Hagi, Tomohito Nakamura, Tomoki Wakabayashi, Tetsushi Mie University Computer and Information Science Faculty of Engineering Japan Mie University Graduate School of Medicine Depautment of Orthopaedic Surgery Japan

ISBN: (纸本)9781665403207

The bone tumor causes the bone pain and swelling, and is firstly diagnosed in a local hospital in many cases. This has become a problem in recent years, and also the benign and malignant nature of bone tumors is difficult and requires a great deal of effort even for medical specialists. Therefore, the development of a system to automatically estimate the benign or malignant nature of bone tumors is required. In this study, we propose a method for automatically estimating the benignity or malignancy of bone tumors using deep learning. We fine-tuned VGG16 and ResNet152 trained on ImageNet using image patches extracted from 38 plain X-ray images of 3 patients. Results on patch-level classification showed that VGG16 achieved higher estimation accuracy (f1-score of 0.790) than ResNet152 (f1-score of 0.784). We also performed the tumor-level classification experiment in which 4 benign and 6 malignant tumors were correctly classified to the appropriate class. © 2021 IEEE.

关键词： computer aided diagnosis

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DiCTI: Diffusion-based Clothing Designer via Text-guided Input

DiCTI: Diffusion-based Clothing Designer via Text-guided Inp...

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International Conference on Automatic Face and Gesture Recognition

作者： Ajda Lampe Julija Stopar Deepak K. Jain Shinichiro Omachi Peter Peer Vitomir Štruc Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Dalian University of Technology China Tohoku University Graduate School of Engineering Sendai Japan

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

Recent developments in deep generative models have opened up a wide range of opportunities for image synthesis, leading to significant changes in various creative fields, including the fashion industry. While numerous methods have been proposed to benefit buyers, particularly in virtual try-on applications, there has been relatively less focus on facilitating fast prototyping for designers and customers seeking to order new designs. To address this gap, we introduce DiCTI (Diffusion-based Clothing Designer via Text-guided Input), a straightforward yet highly effective approach that allows designers to quickly visualize fashion-related ideas using text inputs only. Given an image of a person and a description of the desired garments as input, DiCTI automatically generates multiple high-resolution, photorealistic images that capture the expressed semantics. By leveraging a powerful diffusion-based inpainting model conditioned on text inputs, DiCTI is able to synthesize convincing, high-quality images with varied clothing designs that viably follow the provided text descriptions, while being able to process very diverse and challenging inputs, captured in completely unconstrained settings. We evaluate DiCTI in comprehensive experiments on two different datasets (VITON-HD and Fashionpedia) and in comparison to the state-of-the-art (SoTa). The results of our experiments show that DiCTI convincingly outperforms the SoTA competitor in generating higher quality images with more elaborate garments and superior text prompt adherence, both according to standard quantitative evaluation measures and human ratings, generated as part of a user study. The source code of DiCTI will be made publicly available.

关键词： Industries Visualization Shape Image synthesis Source coding Clothing Semantics

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A Finite Difference Method for a Normalized Time-Fractional Black–Scholes Equation

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International Journal of Applied and Computational Mathematics 2025年第3期11卷 1-17页

作者： Nam, Yunjae Wang, Jian Lee, Chaeyoung Choi, Yongho Bang, Minjoon Li, Zhengang Kim, Junseok Program in Actuarial Science and Financial Engineering Korea University Seoul 02841 South Korea School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Department of Mathematics Kyonggi University Suwon 16227 South Korea Computer and Information Engineering Daegu University Gyeongsan 38453 South Korea Department of Mathematics Korea University Seoul 02841 South Korea

In this article, we propose a normalized time-fractional Black–Scholes (TFBS) equation. The proposed model uses a normalized time-fractional derivative which has a distinctive feature wherein a weight function possesses the property that its integral with respect to time is always equal to one. This feature ensures a well-balanced integration over time and provides a fair comparison between different fractional orders. An implicit finite difference method is used for the numerical solution of the TFBS equation. We perform several standard numerical tests to examine the effect of the fractional parameter on the option pricing. These experiments are designed to investigate how variations in the fractional parameter influence pricing outcomes and provide valuable insights into the model’s behavior under different conditions. The computational results demonstrate the model’s potential for capturing more intricate market dynamics, which makes the proposed model a promising tool for financial analysis. In the appendix, we provide a computer program that implements the numerical methods discussed in the paper for interested readers. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Implicit finite difference method Memory effect Normalized time-fractional Black–Scholes equation

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Contribution of Virtual Reality Technology to Increase Student Interest in Vocational High schools

Contribution of Virtual Reality Technology to Increase Stude...

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2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021

作者： Maulana, Fairuz Iqbal Pangestu, Gusti Sano, Albert Verasius Dian Purnomo, Agung Rahmadika, Sandi Widartha, Vandha Pradwiyasma Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Graduate School Pknu Pukyong National University Interdisciplinary Program of Information Security Busan Korea Republic of Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia

ISBN: (纸本)9781665428477

This research investigates the feasibility of school-based learning using Virtual Reality technology in Electric Power Generation learning during the COVID-19 pandemic. This research employs a qualitative approach. Vocational High school Nurul Jadid Paiton Probolinggo is the site of this study. Data was gathered through observation, literature review, and interviews. In the Electrical engineering section, interviews were conducted with a teaching instructor. Triangulation was used to investigate the data's authenticity, in addition to further interviews with the curriculum staff and instructors at the school. The teacher's assessment of learning media using Virtual Reality application technology shows valid criteria with an average value of 3.6. In comparison, after using the Virtual Reality application learning media, the assessment of students obtained an average value of 3.77 compared to conventional assessments with an interval of 2.71. The use of Virtual Reality technology has proven that it can help and facilitate student learning. The use of technologies of Virtual Reality as a means of learning in classrooms will also be an alternate option for virtual laboratories during the COVID-19 pandemic. © 2021 IEEE.

关键词： Virtual reality

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DiCTI: Diffusion-based Clothing Designer via Text-guided Input

arXiv

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arXiv 2024年

作者： Lampe, Ajda Stopar, Julija Jain, Deepak K. Omachi, Shinichiro Peer, Peter Štruc, Vitomir University of Ljubljana Faculty of Electrical Engineering Ljubljana Slovenia University of Ljubljana Faculty of Computer and Information Science Ljubljana Slovenia Dalian University of Technology China Tohoku University Graduate School of Engineering Sendai Japan

关键词： Semantics

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The Evaluation Result Based on the SURE Model: Case of Samarkand Branch of TUIT

The Evaluation Result Based on the SURE Model: Case of Samar...

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2024 International Symposium on computer science and Educational Technology (ISCSET)

作者： Ilkhom Boynazarov Uranchimeg Tudevdagva Gulnoza Safarova Robiya Raxmonova Samarkand Branch of Tashkent University of Information Technologies Samarkand Uzbekistan Computer Science Faculty Graduate School of Engineering Mongolian University of Sceicnce and Technology Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798350390803

ISBN: (纸本)9798350390810

This paper describes self-evaluation of several distance and e-Iearning courses of Samarkand branch of Tashkent University of information Technologies (TUIT) in Uzbekistan. Teaching from distance and use of e-Iearning is one of key issue of the TUIT. Teaching learning from distance is the complex process which requires different kind of actors with own interests. The success of the distance and e-Iearning process depends on cooperation and collaboration of those actors. Therefore, e-Iearning needs to scientific evaluation method to measure success of teaching and learning. The evaluation process which describes in this paper is the first self-evaluation for distance and e-Iearning courses in the Samarkand branch of the TUIT. The structure-oriented evaluation (SURE) model is selected for basic evaluation model for this self-evaluation. The SURE model is originally developed for measure a success of e-Iearning. The data for evaluation is collected by volunteer- based contribution from students in cases of three selected courses. The collected data is processed by online tool of the SURE model. Final evaluation SURE score of the three courses were bigger than 0.80. However, this result has no comparison with other similar evaluation due to the lack of self-evaluation at the university. This confirms that self-evaluation of selected courses and further courses should continue in next studies.

关键词： computer science computer aided instruction Evaluation models Collaboration Size measurement Data models information technology

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Mechanism of Threshold Voltage Instability in Double Gate α-IGZO Nanosheet TFT under Bias and Temperature Stress

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IEEE Journal of the Electron Devices Society 2024年 12卷 464-471页

作者： Aslam, Muhammad Chang, Shu-Wei Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Lee, Wen-Hsi Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan City701401 Taiwan Institute of Pioneer Semiconductor Innovation Industry Academic Innovation School National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for CMOS-compatible, ultra-scaled, reliable, and high-performing devices, we fabricate and analyze scaled-channel a-IGZO-TFTs with an optimal double-gate structure, a thin nanosheet-based channel, and an effective high- κ dielectric namely HfO2. The reliably reported double gate IGZO nanosheet TFTs (DG-IGZO-NS-TFTs) are tested under positive and negative bias stress at variant temperatures, and the resulting modulations are analyzed critically. The reported DG-IGZO-NSTFTs exhibit a negative side threshold voltage shift (Δ Vth) accompanied by an increase in Ion/Ion(0) under negative bias temperature stress (NBTS) at elevated temperatures, which indicates the presence of additional charges. An anomalous negative side shifting of the Vth is observed under positive bias temperature stress (PBTS), where diffused hydrogen atoms are identified as introducing excess n-type carriers into the channel and causing the observed Δ Vth. The spectroscopic analysis is performed to establish evidence for the assumed mechanisms, and the role of individual gates is investigated in the context of performance variance under temperature-bias stress. Moreover, the partial reversibility of the stress-induced degradation is experimentally established and methodically discussed. Overall, the reported results offer a comprehensive understanding of scaled-channel DG-NS-IGZO-TFTs, which help shape performance-enhancement strategies, control degradation mechanisms, and define appropriate application scenarios. © 2013 IEEE.

关键词： Thin film transistors

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DNN and LS Based Channel Estimation in OTFS System

DNN and LS Based Channel Estimation in OTFS System

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International Conference on Communication Technology (ICCT)

作者： Jiacheng Hu Zhiquan Bai Jikai Yang Yueying Cai Di Zhou Yingxun Wang KyungSup Kwak Shandong Provincial Key Lab. of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao Shandong China School of Computer and Information Engineering Qilu Institute of Technology Graduate School of Information Technology and Telecommunications INHA University Incheon Korea

Orthogonal time frequency space (OTFS) system transmits information in the delay-Doppler domain, and it adapts well to high-speed mobile environments and can realize channel estimation with less overhead. Channel estimation in the OTFS system is necessary for subsequent channel equalization and information recovery process, aiming to eliminate the effects, such as inter-symbol interference (ISI) and noise influence. The paper proposes an effective channel estimation for the OTFS system using deep neural network (DNN) and the least square (LS) algorithm, considering the accurate and low latency channel estimation requirement in the Internet of Vehicles, where LS algorithm is first used to perform a rough time-frequency domain channel estimation, and then the DNN model is taken to optimize the rough channel estimation. Simulation results show that the proposed method achieves more accurate channel estimation performance with low complexity and better flexibility, compared with the typical LS and linear minimum mean square error (LMMSE) scheme.

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