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- 저자 : Tzu-Ping (검색결과 11 건)
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Tzu-Chi Chan,Yu Ping Hong,Jia-Hong Yu 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.9
The coordinate measuring machine (CMM) is one of the most widely used precision measurement machines in the machinery industry. In this study, the analysis and compensation of structural deformation in spatial coordinates effectively depicts the improvement of the spatial accuracy of the motion of a three-dimensional measuring machine in a measurement area. In addition to accuracy, it is also projected that the measurement can be carried out more efficiently. Therefore, the measurement speed of the CMM and dynamic characteristics of the structure are becoming increasingly important. Consequently, the measuring machine has better dynamic characteristics and meets high precision requirements. During measurement, the geometric errors generated by the machine are mainly because of its moving structure in the spatial position. In this study, the CMM is driven by aerostatic bearings; the boundary conditions and parameter settings of each component are established to obtain analysis results that are highly consistent with the actual machine characteristics. The finite element method is used as an analysis tool, including static deformation, modal, spectrum, and transient analyses. Because of the structural deformation and spatial geometric errors caused by the moving structure of the measuring machine, the relative deformation errors can be evaluated through the analysis of the spatial position error compensation to improve the measurement accuracy of the machine.
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An Efficient Parallel Machine Learning-based Blockchain Framework
Chun-Wei Tsai,Yi-Ping Chen,Tzu-Chieh Tang,Yu-Chen Luo 한국통신학회 2021 ICT Express Vol.7 No.3
The unlimited possibilities of machine learning have been shown in several successful reports and applications. However, how to make sure that the searched results of a machine learning system are not tampered by anyone and how to prevent the other users in the same network environment from easily getting our private data are two critical research issues when we immerse into powerful machine learning-based systems or applications. This situation is just like other modern information systems that confront security and privacy issues. The development of blockchain provides us an alternative way to address these two issues. That is why some recent studies have attempted to develop machine learning systems with blockchain technologies or to apply machine learning methods to blockchain systems. To show what the combination of blockchain and machine learning is capable of doing, in this paper, we proposed a parallel framework to find out suitable hyperparameters of deep learning in a blockchain environment by using a metaheuristic algorithm. The proposed framework also takes into account the issue of communication cost, by limiting the number of information exchanges between miners and blockchain.
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An Efficient Design Support System based on Automatic Rule Checking and Case-based Reasoning
Pin-Chan Lee,Tzu-Ping Lo,Ming-Yang Tian,Danbing Long 대한토목학회 2019 KSCE Journal of Civil Engineering Vol.23 No.5
A well building design support system can not only meet the rules but also automatically recommend the appropriate alternatives for designers, but most modifications now are conducted in the manual way. Although the method of automatic rule checking can effectively identify the compliance of rules in Building Information Modeling (BIM) models, recommendation supports are still lacked in applications. This paper aims to propose a design support system, using automatic rule checking to identify the compliance of rules and adopting case-based reasoning to provide recommendations via ontology and semantics. The AHP-TOPSIS (Analytic hierarchy process-Technique for Order Preference by Similarity to an Ideal Solution) method is used to give reliable recommendations rank. A real case is adopted as an illustrative example. Results show that the proposed system can increase the design efficiency in both design checking and modifying. Similar applications can be extended to other fields and rules.
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Pin-Chan Lee,Wei Xie,Tzu-Ping Lo,Danbing Long,Xiaofei Tang 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.8
The maintenance of historic buildings requires a systematic approach to construct and reuse maintenance knowledge. Maintenance knowledge of historic buildings has extensive and specific knowledge, but a small number of experts provide most of experience. With the rapid development of building information modelling (BIM), it can facilitate maintenance management of historic buildings. Recently, research on connecting ontology and BIM was discussed to promote building knowledge management (BKM). However, BKM is less applied in historic buildings and connection strength is also less discussed. Connection strength of knowledge mapping can increase the performance of knowledge retrieval. Therefore, this study aims to build connection between maintenance ontology of historic buildings and BIM, and also proposes a cloud model-based knowledge mapping method to evaluate the connection strength. This study uses FMEA (failure mode and effects analysis) to connect ontology and BIM, and the grey relational analysis to evaluate the connection strength. Meanwhile, cloud model is integrated into FMEA to better deal with uncertain information to increase the reliability. This study adopts a real case to valid the practicability. The results show the proposed method can evaluate the connection strengths with uncertain information and obtain the maintenance knowledge more efficiently.
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Pin-Chan Lee,Li-Long Zheng,Tzu-Ping Lo,Danbing Long 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.3
Risk management of deep excavation is always an important issue. One of the core problems is to accurately simulate and predict the time series of displacement collected from the site sensors to monitor the risk variation. Meanwhile, the applications of building information modelling (BIM) and geographic information system (GIS) can integrate the construction structures into the surrounding environment, visualizing various information and supporting decision making for risk treatment. Therefore, this paper proposes a risk management system to monitor the risk variation for deep excavation based on optimized grey Verhulst model (GVMm), BIM-3DGIS framework and risk monitoring. The grey Verhulst model (GVM) has demonstrated well performance on saturation curve, such as displacement of deep excavation. This paper establishes the GVMm by improving GVM to predict the displacement more precisely. BIM-3DGIS framework is also built by integrating BIM and 3DGIS in the application level for the efficiency of system operation and the interaction with the risk management platform. BIM-3DGIS framework, working with the risk management platform, can monitor the risk variation of deep excavation effectively and provide visual decision-making supports. A real case of deep excavation is used as an illustrative example to verify the practicability. The results show that the prediction precision of GVMm is better than that of GVM. The application scenarios also demonstrate the effectiveness of the risk management system.
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The simple and easy way to manufacture counter electrode for dye-sensitized solar cells
Jo-Lin Lan,Yung-Yun Wang,Chi-Chao Wan,Tzu-Chien Wei,Hsien-Ping Feng,Chao Peng,Hai-Peng Cheng,Ya-Huei Chang,Wen-Chi Hsu 한국물리학회 2010 Current Applied Physics Vol.10 No.2
We previously developed poly-N-vinyl-2-pyrrolidone (PVP)-capped Pt nanoclusters on ITO glass via a simple ‘‘2-step dip coating process” as counter electrode for DSSC. This new counter electrode was examined by transmission electron microscopy (TEM), inductively coupled plasma-atomic emission spectroscopy (ICP-AES), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and current–voltage curve (I–V curve). The TEM results revealed that PVP-capped Pt nanoclusters’ size is about 3 nm, and the amount of Pt deposited on ITO glass is about 5 ㎍/㎠. Comparing with sputtered Pt and Solaronix thermal cluster Pt-catalyst T/SP, the PVP-capped Pt counter electrode has lower amount of Pt deposited on TCO glass,more positive potential of tri-iodide reduction, and better performance for the charge-transfer resistance (RCT) and the cell efficiency (g).
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Pin-Chan Lee,Junhao Wei,Hsin-I Ting,Tzu-Ping Lo,Danbing Long,Luh-Maan Chang 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.10
Construction has long been seen as a high-risk industry. Many studies conduct risk management by controlling construction risk indicators, but few studies associate risk indicators with time and space to propose long-term risk management methods. Therefore, this study proposes a dynamic analysis and visual tracking method based on behavior-based safety (BBS). This study establishes a BBS observation checklist and records workers’ unsafe behavior. The risk level of unsafe behavior is then determined by grey clustering model. When a high risk occurs, an improved grey correlation model is used to track key indicators that affect risk. In order to achieve visual risk management, this study develops semantic logic to predefine the relationship between components and space. In schedule simulation of BIM, the key indicators of BBS are transformed into an executable visual inspection between work items, components, and space through ARC. This method makes it easier for construction managers to combine time and space to manage safety risk and to adopt appropriate strategies in a timely manner to improve the efficiency of safety management.
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Wen-Hsuan Tseng,Wei-Chung Hsu,Tsung-Lin Yang,Tzu-Yu Hsiao,Jia-Feng Wu,Hui-Chuan Lee,Hsiu-Po Wang,Ming-Shiang Wu,Ming-Shiang Wu,Ping-Huei Tseng 대한소화기 기능성질환∙운동학회 2023 Journal of Neurogastroenterology and Motility (JNM Vol.29 No.3
Background/AimsLaryngeal symptoms are largely treated with empiric proton pump inhibitor (PPI) therapy if no apparent pathology shown on ear, nose, and throat evaluation and reflux-related etiologies are suspected. However, treatment response remains unsatisfactory. This study aimed to investigate the clinical and physiological characteristics of patients with PPI-refractory laryngeal symptoms. MethodsPatients with persistent laryngeal symptoms despite PPI treatment for ≥ 8 weeks were recruited. A multidisciplinary evaluation comprising validated questionnaires for laryngeal symptoms (reflux symptom index [RSI]), gastroesophageal reflux disease symptoms, psychological comorbidity (5-item brief symptom rating scale [BSRS-5]) and sleep disturbance (Pittsburgh sleep quality index [PSQI]), esophagogastroduodenoscopy, ambulatory impedance-pH monitoring, and high-resolution impedance manometry were performed. Healthy asymptomatic individuals were also recruited for comparison of psychological morbidity and sleep disturbances. ResultsNinety-seven adult patients and 48 healthy volunteers were analyzed. The patients had markedly higher prevalence of psychological distress (52.6% vs 2.1%, P < 0.001) and sleep disturbance (82.5% vs 37.5%, P < 0.001) than the healthy volunteers. There were significant correlations between RSI and BSRS-5 scores, and between RSI and PSQI scores (r = 0.26, P = 0.010, and r = 0.29, P = 0.004, respectively). Fifty-eight patients had concurrent gastroesophageal reflux disease symptoms. They had more prominent sleep disturbances (89.7% vs 71.8%, P < 0.001) than those with laryngeal symptoms alone but similar reflux profiles and esophageal motility. ConclusionsPPI-refractory laryngeal symptoms are mostly associated with psychological comorbidities and sleep disturbances. Recognition of these psychosocial comorbidities may help optimize management in these patients.
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