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application of Named Entity Recognition by Self-Attention BiLSTM-CRF to Chinese Prescription Document 10

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

引用

10th international Conference on Orange technology, ICOT 2022

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

ISBN: (纸本)9781665454193

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. © 2022 IEEE.

关键词： Hospitals

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Enabling Smart Home Energy Management through Gesture-Based Control and IoT technology

Enabling Smart Home Energy Management through Gesture-Based ...

引用

2023 international Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

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The Efficient Traffic Sign Detection and Recognition for Taiwan Road Using YOLO Model with Hybrid Dataset 9

The Efficient Traffic Sign Detection and Recognition for Tai...

引用

9th international Conference on Applied System Innovation, ICASI 2023

作者： Suwattanapunkul, Taweelap Wang, Lung-Jen National Pingtung University International Master Program in Information Technology and Applications Taiwan National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350398380

According to the trend of worldwide car sales have grown up, this cause may increase accidents on the road due to human error. The self-driverless car has been developed to solve this problem. One task of the self-driverless car is traffic sign detection and recognition (TSDR), which will help drivers notify the traffic sign installed on the road in advance. Taiwan roads have specific traffic signs, and no Taiwan traffic sign public dataset is available. In this paper, our proposed object detection method was experimentally performed using YOLOv5s6 and YOLOv8s models on three different datasets, as Tsinghua-Tencent 100K (TT100k), the self-created Taiwan traffic sign (TWTS), and the hybrid dataset, which combine the traffic scenes between TT100k and TWTS dataset. The output results from each dataset and each model, which is trained on the same parameter, will be compared to validate the proposed method. The experiment results' comparison of the hybrid dataset between YOLOv5s6 and YOLOv8s models display the results of the mAP@.5 is about 65% and 76.2%, respectively, which means the performance of the YOLOv8s is higher than the YOLOv5s6 when using hybrid dataset. © 2023 IEEE.

关键词： Object detection

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Key Factors for Unsubscribing from YouTube Channels: A Study of YouTubers in Taiwan 1

引用

13th international Conference on Frontier Computing, FC 2023

作者： Yang, Hsuan-Che Chang, Wen-Chih Department of Information Management Chihlee University of Technology New Taipei City220 Taiwan International Master Program of Information Technology and Applications National Pingtung University Pingtung City Taiwan

ISBN: (数字)9789819993420

ISBN: (纸本)9789819993413

YouTube has become a major advertisement media for industries. People watch TV shows, movie trailers, news and episodes, on-line shows streaming as well. When people want to purchase something, they can find some unboxing reviews, experiences shares, using instructions and services introductions on YouTube before making orders. Traveling guides and educational tutorials are also can be found on YouTube. Thousands of YouTube channels need channel’s subscribers directly or indirectly affect the revenue of channel owners. In addition to YouTube’s own profit from watching, the subscribers are also an important reference when manufacturers want to choose key opinion leaders (KOL) or internet celebrities to promote their products or services. Since, maintaining a stable growth of channel subscribers and reducing the occurrence of unsubscribing are the key issue that every YouTuber needs to understand urgently. In this study, we used a survey to understand subscribers and YouTubers on unsubscribing, and analyzed some key factors for unsubscribing. The data analyses include descriptive analysis, factor analysis, reliability analysis, t-test, one-way ANOVA, and Pearson’s correlation analysis. Through this study, people can understand key factors for unsubscribing reasons on YouTube platform and the priority of these factors. Whether there is special unsubscribe factors for different channel types and attributes. The key contribution of this study is: a questionnaire on key factors for unsubscribing on the YouTube platform was designed, and it could be utilized for further use in related studies in the future. We also summarize the responses and suggestions of we-media channel owners on the factors for unsubscribing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Reliability analysis

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AI Prescription Recognition System 9

AI Prescription Recognition System

引用

9th international Conference on Orange technology, ICOT 2021

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

ISBN: (纸本)9781665478427

In order to improve the work efficiency of pharmacists, this work proposes a prescription recognition system. The prescription recognition system mainly consists of three parts, namely pre-processing, information extraction and post-processing. The pre-processing includes contrast enhancement of the input image, optical character recognition, and the merging and sorting of the characters after optical character recognition. In the information extraction part, we hybrid two different strategies, the rule-based method, and the deep learning-based method. Finally, post-processing corrects some common optical character recognition errors and performs format conversion on specific fields. On the user interface, we build a web application server with Django, which provides pharmacists to upload, edit, and manage prescriptions. In the deep-learning-based information extraction, the average F1-score reached 93.8%. In the experiment of the overall recognition system, we test 202 different prescriptions, and compare the three different information extraction strategies, which are rules-based method, deep-learning-based method, and hybrid method respectively. The hybrid method is improved in most fields, and the accuracy of all the fields in our system is greater than 93%. Finally, the system gets 4.38 point on the average opinion score. © 2021 IEEE.

关键词： Optical character recognition

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Design and Performance Evaluation of a P4 based Load Balancer 8

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

引用

8th international Conference on Innovation, Communication and Engineering, ICICE 2019

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

ISBN: (纸本)9781728158396

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, net- work 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 mech- anism and efficacy of load balance through P4Switch is proposed in this paper in the hope to achieve more efficient server load balance. © 2019 IEEE.

关键词： loadbalance openflow p4switch sdn

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Real Time Classification System of Black Soldier Fly Larva

Real Time Classification System of Black Soldier Fly Larva

引用

IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS)

作者： Chayanon Pookunngern An-Chao Tsai International Master Program in Information Technology and Applications National Pingtung University Taiwan

ISBN: (数字)9798350361704

ISBN: (纸本)9798350361711

Food waste presents a significant issue, contributing extensively to greenhouse gas emissions and climate change. When food waste decomposes in landfills, it generates methane, a greenhouse gas that is significantly derogation effective to the atmosphere than carbon dioxide. Additionally, the production, transportation, and disposal of food waste significantly contribute to global greenhouse gas emissions. This study explores an innovative approach to mitigate the environmental impact of food waste by using food scraps to create compost for animal feed, specifically utilizing the Black Soldier Fly Larva (BSFL). Accurate control of food quantity for various larval stages is essential, necessitating precise stage classification. This process is complex due to the larvae's similar and small color variations. In this paper, we introduce a mobile application designed to classify and detect the growth stages of BSFL, ranging from stage 1 to stage 4, which are high in protein and beneficial for animal feed, to stages 5 and 6, which are ideal for preparing pupae that can be used in skincare products. Our approach employs the YOLOv8 model for larval stage classification and detection, achieving an impressive mAP50-95 of 0.812, surpassing the performance of YOLOv7 (mAP50-95 of 0.781) and YOLOv5 (mAP50-95 of 0.789).

关键词： Food waste YOLO Waste management Wireless communication Accuracy Animals Transportation

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Using Machine Learning to Predict the Language Proficiency of Thai Students Studying in Taiwan

Using Machine Learning to Predict the Language Proficiency o...

引用

international Conference on Applied System Innovation (ICASI)

作者： Charoenwat Moocharoen Wen-Chih Chang International Master Program in Information Technology and Applications National Pingtung University Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Currently, there are students from Thailand who wish to study abroad. The researchers have chosen Taiwan as the focus. Among the students who come for further studies, there are those proficient in the English language and those who are not. Factors such as language readiness, financial preparedness, scholarship availability, and the university's reputation are crucial in the decision-making process for choosing an educational institution. Simultaneously, some students had the opportunity to study in Taiwan but, due to language unpreparedness, had to withdraw from their studies and return to their home country. The researchers emphasize the importance of language readiness among students. Data has been collected from 316 data including undergraduate, master's, doctoral, and language students of Thai students throughout Taiwan, and a model has been developed to predict the English language proficiency of Thai students. The goal is to create a model with the highest level of accuracy to produce reliable results. This model can be utilized by educational institutions to tailor their courses to match the language abilities of Thai students, thereby enhancing the overall learning experience.

关键词： Logistic regression Technological innovation Machine learning algorithms Scholarships Neural networks Forestry Medical services

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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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Indoor positioning based on Wi-Fi Fingerprint Technique using Fuzzy K-Nearest Neighbor

Indoor positioning based on Wi-Fi Fingerprint Technique usin...

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international Bhurban Conference on Applied Sciences & technology, IBCAST

作者： Peerapong Torteeka Xiu Chundi Master Program of Space Technology and Application School of Electronic and Information Engineering Beihang University Beijing China

Indoor positioning system based on Receive Signal Strength Indication (RSSI) from Wireless access equipment have become very popular in recent years. This system is very useful in many applications such as tracking service for older people, mobile robot localization and so on. While Outdoor environment using Global Navigation Satellite System (GNSS) and cellular [14] network works well and widespread for navigator. However, there was a problem with signal propagation from satellites. They cannot be used effectively inside the building areas until a urban environment. In this paper we propose the Wi-Fi Fingerprint Technique using Fuzzy set theory to adaptive Basic K-Nearest Neighbor algorithm to classify the labels of a database system. It was able to improve the accuracy and robustness. The performance of our simple algorithm is evaluated by the experimental results which show that our proposed scheme can achieve a certain level of positioning system accuracy.

关键词： IEEE 802.11 Standards Wireless communication Wireless sensor networks Training Accuracy Fingerprint recognition Euclidean distance

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