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25th international Conference on Computers in Education: technology and Innovation: Computer-Based Educational Systems for the 21st Century, ICCE 2017

作者： Chen, Ru-Shan Meng, Shian-Chi Ho, Wei-Kuang Tsui, Chih-Hsuan Chen, Wei-Fan Chen, Sheng-Chih College of International Business and Foreign Language Department of Applied English Chihlee University of Technology Taiwan Institute for Information Industry Taipei Taiwan Master's Program in Digital Content and Technologies College of Communication National Chengchi University Taipei Taiwan

ISBN: (纸本)9789869401227

This study aims to develop a user-center design;UCD English learning toy for children to learn English. The research mainly used qualitative interviews to make a recording and conversation with the children. From observing the users' interaction with the toy, the researchers can record a unique learning process and emotional fluctuation from the children. By doing a comprehensive evaluation, the analytical items include participants' emotion, facial expression, speaking, and motion factors. In addition, the research sought whether the children can use the toy's voice functioning to recognize the English word or a sentence from the word cards. The study results have shown that the English learning toy increased the children's curiosity, motivation and imagination during the interactive process with the toy. © 2017 Asia-Pacific Society for Computers in Education. All rights reserved.

关键词： Toys

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Research on Traffic Sign Detection and Recognition System Using Deep Ensemble Learning

Research on Traffic Sign Detection and Recognition System Us...

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IEEE international Conference on Computer Communication and the Internet (ICCCI)

作者： Lung-Jen Wang Taweelap Suwattanapunkul Jarinya Thalauy Parinya Jansengrat Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan International Master Program in Information Technology and Applications International College National Pingtung University Pingtung Taiwan Department of Big Data Management and Analytics Rajamangala University of Technology Thanyaburi Pathum Thani Thailand

ISBN: (数字)9798350351767

ISBN: (纸本)9798350351774

There is a rise in car accidents due to human errors on the road. A critical task of self-driving cars that can reduce accidents on the road is traffic sign detection and recognition (TSDR), which is vital in alerting drivers to the presence of traffic signs in advance. This research will separate the proposed deep ensemble learning algorithm into two methods. First, after the traffic scene process, the algorithm will detect the traffic sign as two categories with the YOLOv5s network. Then, process the traffic sign to recognize the traffic sign into seven classes with the MobileNet network. The detection model was trained with the Taiwan Traffic Sign Detection (TTSD) dataset collected from Taiwan roads. The recognition model was trained with the Taiwan Traffic Sign Recognition (TTSR) dataset. The result of the proposed algorithm showed high performance when experimenting with 95.83% accuracy, 87.34% true prediction, and 191.3 milliseconds (ms) of inference time.

关键词： YOLO Roads Prediction algorithms Inference algorithms Internet Autonomous automobiles Ensemble learning

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Design and Performance Evaluation of a P4 based Load Balancer

Design and Performance Evaluation of a P4 based Load Balance...

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international Conference on information, Communication and Engineering (ICICE)

作者： Shih-Jung Hsu Chih-Heng Ke Yeong-Sheng Chen Cheng-Feng Hung Yu-Wen Lo Master Degree Program of Computational Intelligence and Applications National Quemoy University National Quemoy University National Taipei University of Education Master of Information Technology and Application National Quemoy University

ISBN: (数字)9781728158396

ISBN: (纸本)9781728158402

Being increasingly dense and mature in layout, Internet has become an infrastructure for a state. The traditional single server can no longer bear the network traffic in rapid growth. For example, once the booking service for concert tickets is made available to the public, we are always prompted when clicking into the booking system that the server is busy. And when the system is finally restored normal, the tickets have been sold out. The load issue puzzling the ticket system also occurs in the transportation section every time when a long holiday is coming. Even though the system is updated on a yearly basis, network congestion still happens frequently. Therefore, there is still great space for the development of the ways and mechanisms of load balance in traditional multi-servers. Evaluation of the mechanism and efficacy of load balance through P4Switch is proposed in this paper in the hope to achieve more efficient server load balance.

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Impact of Social Media Marketing Towards Purchase Intention of Green Cosmetics in Indonesia 10

Impact of Social Media Marketing Towards Purchase Intention ...

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

作者： Sanny, Lim Ludony, Jessica Gabriella Chandra, Kezia Aguzman, Glory Nurcahyo, Rianto Ninal, Melvin M. BINUS Business School Master Program Bina Nusantara University Management Department Jakarta Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Management Department Jakarta Indonesia BINUS Business School Undergraduate Program Bina Nusantara University International Business Management Department Jakarta Indonesia St. Paul University Information Technology Surigao Philippines

ISBN: (纸本)9798350339543

This research aims to find out the effect of social media and green brand knowledge on its purchase intention through attitude as intervening variable. The method used in this research is quantitative method, by using nonprobability sampling-purposive sampling technique and multiple regression analysis. Researchers spread questionnaires to 211 respondents and use path analysis to determine the influence between variables. The results of this research are significantly: social media affect attitude, green brand knowledge affect attitude, attitude doesn't affect green cosmetics purchase intention, social media doesn't affect green cosmetics purchase intention, green brand knowledge affects green cosmetics purchase intention, social media doesn't affect green cosmetics purchase intention through attitude, and green brand knowledge doesn't affect green cosmetics purchase intention through attitude. © 2023 IEEE.

关键词： Cosmetics

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Achieving compelling student comprehension of complex information structures for both on-site and on-line courses

Achieving compelling student comprehension of complex inform...

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2008 ASEE Annual Conference and Exposition

作者： Uhlig, Ronald Farahani, Alireza Viswanathan, Shekar Evans, Howard Sotelo, Mark National University Department of Computer Science and Information Systems School of Engineering and Technology National University Wireless Communications for the Master ot Science in Wireless Communications Program International Telecommunications Academy School of Engineering and Technology Department of Applied Engineering Lead Faculty for Engineering Management and Homeland Security and Safety Engineering Academic Computing for National University

Teaching engineering and technology subjects involves conveying understanding of abstract information structures and processes such as complex telecommunications protocols, complex mathematical concepts, and data structures. These are multidimensional and can be difficult to grasp quickly. Supported by a Hewlett-Packard (HP) technology for Teaching grant, the School of Engineering and technology at National University has embarked on a project to enable students to grasp these complex concepts more quickly and easily, using continuous dialog among students and instructors as the structures are first introduced and then examined from multiple perspectives through real-time interaction among students, small groups, and instructors. HP Wireless Tablet PCs are used to discuss and experiment with diagrams and processes in realtime. This allows combining lectures and problem-solving sessions into a single class session. Our hypothesis is that: 1) an in-depth learning of theory is accomplished, and 2) student engagement is enhanced. Presentation of theory by the instructor is integrated with application while the theory is still in the student's short-term memory. Students no longer have to wait for a separate session such as a recitation session to apply the concepts. This approach often takes less time. In addition to accelerating the learning process, expert instructors find this approach more rewarding as students grasp new concepts more quickly. Analysis of data captured from both students and instructors are presented to support our hypotheses, and our results are compared with similar research carried out by other universities. In addition, the level of interaction enabled by the use of HP Tablets in on-line classes is discussed. The best teaching tools available in existing on-line teaching platforms are compared with the additional tools available in on-site courses when every student has a wireless Tablet PC and specific recommendations are made to on-line teachi

关键词： Students

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Improving Accuracy of Object Quantity and Text-Image Alignment Based on the Stable Diffusion Pretrained Model

Improving Accuracy of Object Quantity and Text-Image Alignme...

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IEEE international Conference on Orange Technologies (ICOT)

作者： An-Chao Tsai Yu-Min Hsu Jhing-Fa Wang International Master Program of Information Technology and Application National Pingtung University Taiwan Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan

ISBN: (数字)9798331523602

ISBN: (纸本)9798331523619

In recent years, advancements in training methods using large-scale text-image datasets and the development of diffusion models have significantly improved the quality and efficiency of image generation from text prompts. Despite these strides, text-to-image generation models still face challenges in producing realistic images that accurately reflect the specified details in the prompts. A common issue with diffusion-based models is their difficulty in generating the precise number of objects described in the text. For instance, a prompt like "six tomatoes in a basket" may often result in an image with an incorrect number of tomatoes. To address this problem, this paper proposes an algorithm designed to enhance the accuracy of object quantity in generated images. The algorithm employs an object counting network to assess the number of objects in a given image and calculates the error between this predicted count and the expected count. This error gradient is then used to guide the predictions of the diffusion model, improving its ability to generate the specified number of objects accurately.

关键词： Training Adaptation models Accuracy Image synthesis Text to image Diffusion models Prediction algorithms Social implications of technology Faces

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Enhanced-SETL: A multi-variable deep reinforcement learning approach for contention window optimization in dense Wi-Fi networks

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Computer Networks 2024年 253卷

作者： Tu, Yi-Hao Lin, En-Cheng Ke, Chih-Heng Ma, Yi-Wei Department of Electrical Engineering National Taiwan University of Science and Technology Taipei106335 Taiwan Master Program of Information Technology and Applications National Quemoy University Kinmen892009 Taiwan Department of Computer Science of Information Engineering National Quemoy University Kinmen892009 Taiwan

In this paper, we introduce the Enhanced Smart Exponential-Threshold-Linear (Enhanced-SETL) algorithm, a new approach that uses the multi-variable Deep Reinforcement Learning (DRL) framework to simultaneously optimize multiple settings of the Contention Window (CW) in IEEE 802.11 wireless networks. Unlike traditional DRL methods that adjust only a single CW parameter, our innovative approach simultaneously optimizes both the CW minimum (CWmin) and CW Threshold (CWThreshold), significantly improving network traffic control. We utilize a Double Deep Q-learning Network (DDQN) for dynamic updates of these CW settings, broadcasted across the dense Wi-Fi networks. This dual adjustment method, coupled with dynamic, data-driven updates, not only enhances throughput, but also reduces collision rates, and ensures fairness access across both static and dynamic wireless environments. Enhanced-SETL achieves a throughput improvement ranging from 3.55% up to 43.73% and from 3.98% up to 30.15% in static and dynamic scenarios over standard protocols and state-of-the-art DRL models, while maintaining a fairness index near 99% across diverse stations, showcasing its effectiveness and adaptability in various network conditions. © 2024

关键词： Wireless local area networks (WLAN)

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Application of Named Entity Recognition by Self-Attention BiLSTM-CRF to Chinese Prescription Document

Application of Named Entity Recognition by Self-Attention Bi...

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IEEE international Conference on Orange Technologies (ICOT)

作者： An-Chao Tsai Tsung-Yen Lee Yang-Yen Ou Jhing-Fa Wang International Master Program of Information Technology and Application National Pingtung University Pingtung Taiwan Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan

ISBN: (纸本)9781665454209

Reporting the contents of the prescription is a time-consuming and labor-intensive task for pharmacists, and it is easy to make mistakes in this kind of work that requires repeated confirmation under the time pressure of customers. Because medicines usually have an impact on the human body, if the wrong medicine is accidentally provided to the customer, it may even lead to death. Therefore, in our work, we train a bidirectional LSTM-CRF network combined with an attention mechanism to perform the NER task on prescription notes and extract key prescription declaration information. The semi-automatic labeling module was implemented using a rule-based approach, and a total of 636 different prescription notes were trained and tested, including hospitals, clinics, and medical centers. The identification accuracy rate is more than 90 % in each field of declaration information. Provides a UI interface for subsequent identification to facilitate pharmacists to modify the identification content and declare key information.

关键词： Hospitals Social implications of technology Labeling Data mining Task analysis

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Support issues in distance learning: Supporting teachers and learners 43

Support issues in distance learning: Supporting teachers and...

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43rd Annual Association for Computing Machinery Southeast Conference, ACMSE '05

作者： Baker, Nelson C. Goff, Don Hoganson, Ken Nelson, Michael L. Negash, Solomon Distance Learning and Professional Education Georgia Institute of Technology United States UMUC's Security Studies Laboratory University of Maryland University College United States Master of Science in Applied Computer Science Kennesaw State University United States School of Technology Graduate Program International College United States Information Systems Kennesaw State University United States

Distance Learning physically separates the learner from the teacher often forfeiting the traditional support available in a face-to-face model. What are the issues and lessons learned in supporting teachers and learne... 详细信息

ISBN: (纸本)1595930590

关键词： Distance education

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3D object detection combined with inverse kinematics to achieve robotic arm grasping

3D object detection combined with inverse kinematics to achi...

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IEEE international Conference on Orange Technologies (ICOT)

作者： Che-Wen Chen An-Chao Tsai Yu-Hong Zhang Jhing-Fa Wang Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan International Master Program of Information Technology and Application National Pingtung University Pingtung Taiwan

ISBN: (纸本)9781665454209

In recent years, the research of autonomous robotic arms has received high attention from academia and industry, so this thesis aims to develop a visual detection system for robotic arms to grasp and place objects. Object detection technology The purpose of which is to locate objects of interest (target) in a given image, providing object location bounding boxes and categories. ROS is a set of open-source software libraries designed to simplify the creation of complex and robust on various robotic platforms. the task of the robot behavior. The proposed scheme uses a camera with depth information and combines target localization and edge detection algorithms to accurately measure the relative distance between the object and the robot arm. The process includes deep neural network construction and use, robotic arm positioning, object bounding box position information, and robotic arm movement control. Considering the visual scale, the relative distance between the target and the robotic arm is calculated so that the robotic arm can grasp the target and place the object in a specific position. This paper introduces how to combine the deep learning object detection model and ROS moveit! to complete the object identification and grasp and place the robotic arm.

关键词： Deep learning Visualization Service robots Image edge detection Process control Object detection Grasping

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