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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Tsugawa, Seizan Toma, Takao Oshiro, Shiho Wada, Tomohisa University of the Ryukyus Computer Science and Intelligent Systems Program Okinawa Japan Magna Design Net Inc Okinawa Japan University of the Ryukyus Information Technology Center Okinawa Japan University of the Ryukyus Area of Computer Science and Intelligent Systems Dept. of Engineering Okinawa Japan

ISBN: (纸本)9798350305142

This paper proposed Scalability in Autoencoder-based Orthogonal Frequency Division Multiplexing(OFDM) communication system. In the previous research, only the comparison between IEEE802.11a and Autoencoder by the conventional OFDM communication system was performed, and it was proved that the communication system created by Autoencoder exceeded the performance of the conventional system. Therefore, in this paper, it uses IEEE802.11n and compare whether it can be improved by expanding the bandwidth and using ***802.11n standard has an FFT length of 128, a subcarrier number of 114 (108 for data), and modulation schemes of Quadrature Phase Shift Keying(QPSK), 16 Quadrature Amplitude Modulation (16QAM). The GI length is 800ns and the symbol length is 4000ns. In the simulation, a computer simulation was performed using a conventional OFDM communication system and a communication system generated by Autoencoder. Assuming that the simulation environment had an Signal-to-Noise Ratio (SNR) of 0 to 30 and an amplitude r of 0.0 to 1.0, the Symbol Error Rate (SER) status for each SNR was output. As a result of computer simulation, QPSK converged at SNR 27 at IEEE 802.11a, but was able to reduce SER overwhelmingly to SNR 12 at IEEE 802.11n. Also, in 16QAM the convergence at r=0.0 is the same as for SNR22 , but in IEEE 802.11a it does not converge after r=0.6, but in IEEE 802.11n it does not converge only at r=0.9 and r=1.0. As a future task, it will use IEEE802.11ac, which enables communication speeds several times faster than IEEE802.11n, examine whether it is possible to further improve accuracy. And it will continue our research to correspond MIMO communication. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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Leveraging Attention to Achieve Generalization for Image Forgery Detection

Leveraging Attention to Achieve Generalization for Image For...

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Intelligent Methods, Systems, and Applications (IMSA)

作者： Mohamed Atta School of Information Technology and Computer Science Artificial Intelligence Program Nile University Giza Egypt

Recently, image forgery has become an alarming trend with the growth of available easy-to-use editing and generation tools. Modern DeepFake methods have achieved extraordinary progress in realistic face manipulation, thus raising concerns among the public about the misuse of such technologies. Unfortunately, with the obnoxiously wide range of possible manipulation and artifact-covering methods, most existing state-of-the-art detection methods lack the generalization capability to handle the output variations. To address this issue, a noticeable shift towards using attention mechanisms has emerged using balanced portions of the latest challenging datasets to detect intra-and inter-spatial relations. Our paper provides a comprehensive analysis of modern deep learning-based methods, showing the benefits of the shift. In addition, we make propositions for future research directions and dataset-building methodology.

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Online Handwritten Recognition for Alphabet Writing Practice 4

Online Handwritten Recognition for Alphabet Writing Practice

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Santiari, Ni Putu Linda Rahayuda, I Gede Surya Institute of Technology and Business STIKOM Bali Information System Study Program Faculty of Informatics and Computer Denpasar Indonesia Informatics Study Program Faculty of Math and Natural Sciences Udayana University Mangupura Indonesia

ISBN: (纸本)9781665453950

Learning to write in children requires the child's habit of using a pencil to write on paper. The manual method has drawbacks such as the use of a lot of paper when children have to study harder to keep repeating the exercises and also cannot be done online remotely. In addition to this, writing exercises on the touchscreen can also train children to be more skilled at using the touchscreen. To overcome these problems, the author will discuss the use of handwriting recognition technology to practice writing capital letters (A-H), where the technology will be built on a web-based basis. The recognition algorithm used is K-NN. Testing the use of the website was carried out at Tunas Mekar Sari Kindergarten, Denpasar. The identification number and result will be stored on the web server. Based on the experiment, it was found that from 80 image data, the K-NN algorithm succeeded in providing accurate recognition results on 60 image data, and obtained an accuracy of 78.75%. © 2022 IEEE.

关键词： Websites

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A Simple Deep Learning Model for Classifying Oranges in Embedded Manufacturing Settings

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SSRN 2023年

作者： Salaiwarakul, Anongporn Mungklachaiya, Sujitranan Program in Computer and Information Technology Faculty of Science and Technology Loei Rajabaht University Loei42000 Thailand Department of Computer Science and Information Technology Faculty of Science Naresuan University Phitsanulok65000 Thailand

Recently, deep learning has emerged as a powerful tool for automating various tasks in manufacturing industry. Deep learning has shown promise particularly in classifying food products, e.g., identifying sweet oranges in a factory setting. Traditionally, classification of oranges based on sweetness is a labor-intensive and time-consuming process, requiring manual inspection and tasting by trained personnel. However, by employing deep learning techniques, this process can be automated, giving rise to accurate and consistent results at a much faster rate. In this study, we propose a deep learning model, combined with computer vision, for classifying the sweetness of oranges in a factory setting. By training a deep neural network on a dataset of labeled images, we developed a simple Convolutional Neural Network (sCNN) model with few layers that can accurately predict the sweetness of new oranges based on their images. We evaluated the performance of the model and compare it with four CNN architecture-transfer learning models of orange classification. Upon comparison with four different CNN architecture-transfer learning models, namely, MobileNet-V2, Inception-V3, VGG-16, and ResNet-50, we found that while each of these models yields a satisfactory result, learning rates of 0.001 or 0.0001 yielded superior results in every model. Without the application of dropout and image augmentation, ResNet-50 yielded the best classification accuracy (81.43%) of the five models, and the model performance improved upon employment of these methods. However, the provided images were not suitable for Inception-V3 models. Nevertheless, Simple CNN shows that the augmentation method enables the model to learn, achieving an accuracy of 81.43% with a dropout of 0.3, which is close to the VGG-16's highest accuracy of 83.57% (dropout = 0.0) and MobileNet-V2’s 74.29% (dropout = 0.3). © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Effects of an automated programming assessment system on the learning performances of experienced and novice learners

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Interactive Learning Environments 2023年第8期31卷 5347-5363页

作者： Cheng, Li-Chen Li, Wei Tseng, Judy C. R. Department of Information and Finance Management National Taipei University of Technology Taipei Taiwan STEM Education Research Center Wenzhou University Zhejiang Province Wenzhou China Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are submitted. It also presents an analytical dashboard as a competition mechanism for students to visualize their learning performance and compare their performance with peers. By incorporating APAMP into programming courses, students can master programming skills through repeated practice, and their enthusiasm for learning programming can also be encouraged by peer competition. To evaluate the effects of APAMP on the learning performance of students with programming language learning and novice students, a quasi-experiment was conducted in a high school. The experimental results showed that the learning achievement of the two groups of students improved significantly. Moreover, the learning attitude of students in the experienced group improved significantly, with the experienced students benefiting more from the system than the novice students. In fact, the novice students showed a significant decline in learning attitude and learning motivation, which was contrary to our intuition. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： automated programming assessment systems learning performance mastery learning peer competition programming instruction

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Gamification of Donation App: What Affect Donators' Decision? 6

Gamification of Donation App: What Affect Donators' Decision...

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6th International Conference on information technology, InCIT 2022

作者： Chaichana, Thidawan Preechachot, Peetikorn Uttama, Surapong School of Information Technology Mae Fah Luang University Computer Science and Innovation Program Chiang Rai Thailand School of Information Technology Mae Fah Luang University Center of Excellence in Artificial Intelligence and Emerging Technologies Chiang Rai Thailand

ISBN: (纸本)9781665489126

This paper proposes a donation mobile app gamified to monitor players' donation decision. Three main scenarios were simulated to observe which factors affect the donation. First, five categories of donation project were available. Second, an expiring donation project was set and was alerted to players. Last, auctions were added to some donation projects to draw more players' attention. Testing with twelve young players revealed that the most influenced donation factor is the project's type. Health-related project was the most attentive. Also, the expiring donation project triggered the players' interest. Unfortunately, auctions rarely increased the amount of donation which may be due to the uninteresting bidding products. © 2022 IEEE.

关键词： Commerce

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Behavioral Office Syndrome with IoT Devices 6

Behavioral Office Syndrome with IoT Devices

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6th International Conference on information technology, InCIT 2022

作者： Kongsomboon, Pun Uttama, Surapong Mae Fah Luang University Computer Science and Innovation Program School of Information Technology Chiang Rai Thailand School of Information Technology Mae Fah Luang University Center of Excellence in Artificial Intelligence and Emerging Technologies Chiang Rai Thailand

ISBN: (纸本)9781665489126

This paper presents a collection of computer use behavior prone to office syndrome by using pressure sensors in conjunction with IoT devices. IoT device was attached with a chair, and sensors were installed on the seat and the backrest. Another IoT set was linked with sensors installed under the mouse pad. The collected data of seven testers instructed to use computer and move freely revealed different behaviors. Some were sitting constantly with or without using backrest or touching mouse. Also a unique character like standing while using computer was found. To link with office syndrome estimation, we proposed a set of rules including thresholds for pressure values, time criteria and risk scoring. Using these criteria, the testers were found to have low and moderate risks of office syndrome. © 2022 IEEE.

关键词： Risk perception

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A Multi-UAV Charging Station Enabling Free Landing by Grid Pattern Transmitter

A Multi-UAV Charging Station Enabling Free Landing by Grid P...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Jungho Kim Hyunkyeong Jo Seoktae Seo Bonyoung Lee Hyungki Min Franklin Bien School of Electrical and Computer Engineering Ulsan National Institute of Science and Technology Ulsan Korea Program in Information & Communication Technology Convergence Ulsan National Institute of Science and Technology Ulsan Korea

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

This paper proposed a novel landing platform with wireless power transfer (WPT) to charge multiple unmanned aerial vehicles (UAVs) without restrictions on landing locations or alignment. A transmitter is designed using wires to charge a wide area. To overcome the disadvantages of system made by wires, a grid pattern transmitter and double power line are proposed. These structures provide multiple charging with free positioning of receivers and excite the transmitter lines in wide area properly. The optimized system is composed of 0.15m square cells, providing a 0.9 m by 0.9 m charging area. By experiment, it can efficiently charge four 0.1 m square receivers located anywhere in transmitter. The overall efficiency of four receivers is 37.5%. Also, the experimental results verify that it is unnecessary to align the receiver within the cell, as it has a 2.62% error due to rotation and a 2.94 % error due to position within the cell.

关键词： Coils Magnetic flux leakage Transmitters Wires Windings Receivers Wireless power transfer Autonomous aerial vehicles Current distribution Power electronics

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Optimizing 3D Clothing Models for VR: A Deep Learning Approach to Triangle Count Reduction

Optimizing 3D Clothing Models for VR: A Deep Learning Approa...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Surasachai Doungtap Varinya Phanichraksaphong Jenq-Haur Wang International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between efficiency and detail, it cuts triangle count from over 160,000 to below 4,000, maintaining high DPI. The approach automates optimization, promising scalability and efficiency in VR fashion, setting a foundation for future 3D content development, enhancing virtual garment realism and interactivity.

关键词： Deep learning Solid modeling Three-dimensional displays Scalability Clothing Optimization Consumer electronics

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An algorithm for conditional-fault local diagnosis of multiprocessor systems under the MM⁎ model

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Theoretical computer Science 2024年 987卷

作者： Lv, Yali Lin, Cheng-Kuan Hsu, D. Frank Fan, Jianxi School of Information Technology Henan University of Chinese Medicine Zhengzhou China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology NDU Taoyuan Taiwan Department of Computer and Information Science Fordham University New York United States School of Computer Science and Technology Soochow University Suzhou China

Diagnosis is a crucial subject for maintaining the reliability of multiprocessor systems. Under the MM⁎ diagnosis model, Sengupta and Dahbura proposed a polynomial-time algorithm with time complexity O(N5) to diagnose a system with N processors. In this paper, we propose a (α,β)-trees combination S(u,X,α,β) and give an algorithm to identify the fault or fault-free status of each processor for conditional local diagnosis under the MM⁎ model. According to our results, a connected network with a (α,β)-trees combination S(u,X,α,β) for a node u is conditionally locally (α+2β−3)-diagnosable at node u and the time complexity of our algorithm to diagnose u is O(α2β+αβ2). As an application, we show that our algorithm can identify the status of each node of n-dimensional star graph Sn if the faulty node number does not exceed 3n−8. Compared with existing algorithms, our algorithm allows more faulty nodes in a multiprocessor system. © 2024 Elsevier B.V.

关键词： Computational complexity

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