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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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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...

引用

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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Rib Fracture Diagnosis System on Chest X-Rays with Deep Learning 9

Rib Fracture Diagnosis System on Chest X-Rays with Deep Lear...

引用

9th international Conference on Orange technology, ICOT 2021

作者： Tsai, An-Chao Ou, Yang-Yen Lin, Chuan-Han Chen, Che-Wen Wang, Jhing-Fa National Pingtung University International Master Program of Information Technology and Application Pingtung Taiwan National Cheng-Kung University Department of Electronic Engineering Tainan Taiwan

ISBN: (纸本)9781665478427

Chest X-Rays is an important imaging modality for diagnosing thorax diseases. However, it is a challenging task to identify rib fractures. The features of rib fractures including various shapes, various sizes, and might overlapped by other organs. It is then time consuming and hard for clinicians to deal with it. Hence, automatically rib fractures recognition is important to clinicians. In this work, we trained two deep convolutional neural networks in order to classify rib fractures in chest x-ray images. One for frontal view images, and another for oblique view images. We present a two-stage method including lung field cropping with U-Net [1] and rib fracture classification with EfficientNet-B0 [2]. We evaluated models' classification performance using Area Under Receiver Operating Characteristic Curve (AUROC), Area Under Precision Recall Curve (AUPRC), and Accuracy. Class Activation Maps (CAMs) were provided to know the image regions most relevant to the model's prediction. © 2021 IEEE.

关键词： Diagnosis

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

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

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

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

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.

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

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

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international Conference on Applied System Innovation (ICASI)

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

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.

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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 ...

引用

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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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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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

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

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