A5031768968- Biomedical Text Mining and Ontologies
- Natural Language Processing Techniques
- Genomics and Phylogenetic Studies
- Topic Modeling
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Industrial Vision Systems and Defect Detection
- Smart Agriculture and AI
- Advanced Manufacturing and Logistics Optimization
- Food Supply Chain Traceability
- Gene expression and cancer classification
- Data Management and Algorithms
- Genetics, Bioinformatics, and Biomedical Research
- Scheduling and Optimization Algorithms
- Open Education and E-Learning
- Analytical Chemistry and Sensors
- Advanced Text Analysis Techniques
- Context-Aware Activity Recognition Systems
- Advanced Neural Network Applications
- Advanced Sensor and Energy Harvesting Materials
- Coffee research and impacts
- nanoparticles nucleation surface interactions
- Medical Image Segmentation Techniques
- AI in cancer detection
- Machine Learning in Bioinformatics
National University of Tainan
2021
National Cheng Kung University
2018-2019
Feng Chia University
2017-2018
University of Connecticut
2013
Academia Sinica
2007-2011
Institute of Information Science, Academia Sinica
2008-2011
National Yang Ming University Hospital
2008
National Yang Ming Chiao Tung University
2008
University of Utah
2008
Tamkang University
2006
Abstract Nineteen teams presented results for the Gene Mention Task at BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding gene name mentions. A variety of different methods were used and varied with a highest achieved F 1 score 0.8721. Here we present brief descriptions all statistical analysis results. We also demonstrate that, by combining from submissions, an 0.9066 is feasible, furthermore that best result makes use...
We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers genes detected full-text articles. For training, 32 fully and 500 partially annotated articles prepared. A total 507 selected as test set. Due high annotation cost, it was not feasible obtain gold-standard human annotations for all Instead, we developed an Expectation Maximization (EM) algorithm approach choosing small number manual that most capable...
We introduce the first meta-service for information extraction in molecular biology, BioCreative MetaServer (BCMS; http://bcms.bioinfo.cnio.es/ ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations PubMed/Medline abstracts. Annotation types cover gene names, IDs, species, protein-protein interactions. The are distributed by meta-server both human machine readable formats (HTML/XML). service intended to be used biomedical...
Tagging gene and product mentions in scientific text is an important initial step of literature mining. In this article, we describe detail our mention tagger participated BioCreative 2 challenge analyze what contributes to its good performance. Our based on the conditional random fields model (CRF), most prevailing method for tagging task 2. interesting because it accomplished highest F-scores among CRF-based methods second over all. Moreover, obtained results by mostly applying open source...
Competitions in text mining have been used to measure the performance of automatic processing solutions against a manually annotated gold standard corpus (GSC). The preparation GSC is time-consuming and costly final consists at most few thousand documents with limited set semantic groups. To overcome these shortcomings, CALBC project partners (PPs) produced large-scale biomedical four different groups through harmonisation annotations from solutions, first version Silver Standard Corpus...
Abstract Background To automatically process large quantities of biological literature for knowledge discovery and information curation, text mining tools are becoming essential. Abbreviation recognition is related to NER can be considered as a pair task terminology its corresponding abbreviation from free text. The successful identification definition not only prerequisite index terms databases produce articles interests, but also building block improve existing gene mention tagging...
In the production process from green beans to coffee bean packages, defective removal (or in short, defect removal) is one of most labor-consuming stages, and many companies investigate automation this stage for minimizing human efforts. paper, we propose a deep-learning-based inspection scheme (DL-DBIS), together with GAN (generative-adversarial network)-structured automated labeled data augmentation method (GALDAM) enhancing proposed scheme, so that degree robotic arms can be further...
Computer numerical control (CNC) tool-wear prediction (TWPred) is an important issue in the industry. Recently, researchers have demonstrated that deep-learning models (DLMs) are effective TWPred. However, DLMs ill-suited to small- and medium-scale manufacturers due high computational costs. Methods exist reduce costs of DLMs, but most them depend on overly-complex pruning processes not appropriate for low-end computers used by above manufacturers. Therefore, we developed a lightweight DLM...
Job allocation and job sequencing decisions are combined to develop scheduling heuristics for non-identical parallel processor systems. Several factors affecting the system examined relative performance of evaluated in terms flow time, tardiness proportion tardy jobs. An understanding relationship between variables a leads decision rules that provide feasible effective production schedules.
In this paper, we propose a novel Hough circle-assisting deep-network inspection scheme (HCADIS), aiming at identifying defects in dense coffee beans. The proposed HCADIS plays critical role camera-based defect removal system to collect defective bean positions for picking all off. idea of the is mix intermediate data from deep network and feature engineering method call circle transform utilizing advantages both methods inspecting adopted because it performs quite stable shapes are highly...
Coffee beans are one of most valuable agricultural products in the world, and defective bean removal plays a critical role to produce high-quality coffee products. In this work, we propose novel labor-efficient deep learning-based model generation scheme, aiming at providing an effective with less human labeling effort. The key idea is iteratively generate new training images containing various locations by using generative-adversarial network framework, these incur low successful detection...
Abstract Background Previously, gene normalization (GN) systems are mostly focused on disambiguation using contextual information. An effective mention tagger is deemed unnecessary because the subsequent steps will filter out false positives and high recall sufficient. However, unlike similar tasks in past BioCreative challenges, III GN task particularly challenging it not species-specific. Required to process full-length articles, an ineffective may produce a huge number of ambiguous that...
The RFID-based real-time monitoring system has become one of the most important in factory. As it can provide managers an easy way to monitor product, overall equipment effectiveness or even condition machines. However, many industries just import this into their factories recent years and have no idea how manage system. Hence, paper reports on approach for manufacturing process a factory by using RFID tags. tags may meet problem reusing tags, we also develop work novel algorithm managing...
In today's information era, using ICT to enhance teaching and learning is an active field of research.However, the implementation in very challenging.In order build effective and/or models, which will be used nationally Taiwan, Ministry Education has initiated a project known as Computer Assisted English Learning: Using High Schools Vocational Schools.The IWiLL (Intelligent Web-based interactive Language Learning) system chosen platform accomplish above objectives.Two main vehicles were...
Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – 8, 2013.
In recent years, many major manufacturers have been incorporating Industry 4.0 technologies such as preventive fault detection, automated scheduling algorithms, and component management to increase productivity reduce production costs. Achieving this objective requires a substantial amount of working capital acquire large quantities new machinery, equipment extract data from the high-priced big analysis software. However, most factories in world are small-or medium-sized companies not enough...
Enterohemorrhagic E. coli (EHEC) O157:H7, which is a foodborne pathogen that causesdiarrhea, hemorrhagic colitis (HS), and hemolytic uremic syndrome (HUS), colonize to the intestinal tract of humans. To study detailed mechanism EHEC colonization in vivo, it essential have animal models monitor quantify colonization. We demonstrate here mouse-EHEC model by transforming bioluminescent expressing plasmid living hosts. Animals inoculated with bioluminescence-labeled show intense signals mice...