2018 International Conference on System Science and Engineering (ICSSE)最新文献_第4页

Cell-on-a-Chip with Reversible Package for Studying the Drug Metabolism Between Cancer and Liver Cells 研究肿瘤与肝细胞间药物代谢的可逆封装细胞芯片

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8519969

J. Weng, Yu-En Lee, Lin-Chi Chen

引用次数: 0

The Application of Innovation and Catapult Research Techniques to Future Smart Cities Assessment Framework 创新和弹射研究技术在未来智慧城市评估框架中的应用

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520043

W. Wey, C. Ching

{"title":"The Application of Innovation and Catapult Research Techniques to Future Smart Cities Assessment Framework","authors":"W. Wey, C. Ching","doi":"10.1109/ICSSE.2018.8520043","DOIUrl":"https://doi.org/10.1109/ICSSE.2018.8520043","url":null,"abstract":"For the past few years, the concept of urban sustainability and smart city has been viewed as a crucial way to solve the problem regarding urbanization, and the global city thus ranks it as a future development goal. With the implementation of the above strategies, the construction of relevant city assessment tools is essential. However, the assessment framework of urban sustainability focuses on the aspect of environment and society, while smart city puts emphasis on economic and social indicators. Therefore, integrating the two concepts as “Smart Sustainable City” and constructing a related evaluation model would be more comprehensive. Moreover, the development of “Big Data” theory allows city planners to interpret and apply large amounts of data collected from various sources. Under this opportunity, the result of analyzing the actual big data to forecast the variance ratio of each indicator can be used as the objective basis to construct the model, which can increase the accuracy of the city assessment. Based on the big data analysis, this paper will construct an assessment framework of smart sustainable city in line with the future situation, and further conduct the model validation through city evaluation. First, this paper reviews the concepts and assessment framework of sustainable development and smart city in order to sum up the appropriate indicators to construct the model, and applies “Fuzzy Delphi Technique (FDT)” to select the indicators which are considered important regarding the smart sustainable city. In addition, “Data Mining” and “Analytic Network Process (ANP)” are used to predict the future variance ratio of smart sustainable city indicators and to apply the variance ratio regarding the future scenario to determine their weights. Finally, this paper will conduct an empirical analysis by assessing the smart sustainable level of cities, hoping to validate the model and propose related suggestions to promote the idea exchange of urban development.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121432542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Design and Construction of an Intelligent Stacking Cone Upper Limb Rehabilitation System 智能叠锥上肢康复系统的设计与构建

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520085

Ya-Hui Chiu, San-Feng Yen, Shien‐Fong Lin

{"title":"Design and Construction of an Intelligent Stacking Cone Upper Limb Rehabilitation System","authors":"Ya-Hui Chiu, San-Feng Yen, Shien‐Fong Lin","doi":"10.1109/ICSSE.2018.8520085","DOIUrl":"https://doi.org/10.1109/ICSSE.2018.8520085","url":null,"abstract":"Stroke patients, due to lack of exercise, usually suffer from muscle atrophy or functional deterioration. Therefore the patients need to do long-term rehabilitation therapy activities. The current clinical practice uses static rehabilitation tools such as stacking cones without immediate functional feedback. During the procedure, an occupational therapist (OT) fills out a Brunnstrom stage form to evaluate the status of upper limb. This approach has not been effective because patients may feel tired and boring with these tools. According to Brunnstrom stage, the palm grip ability level between three to six, and the arm strength level between four to six can use stacking cones for rehabilitation purposes. The research methods in this project are based on the patients' need to do rehabilitation with stacking cones, such as those with stroke, spinal cord injury, brain injury, Parkinson's disease, hand and visual perception problems. This study aims to establish a smart stacking cones device for upper limb rehabilitation with evaluation function. The goal is to raise the efficacy and add fun level during diagnostic and therapeutic procedures, therefore to achieve improved upper limb action, palm grip action, strength, endurance, coordination and other capabilities.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123273235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Biochemical Sensor Based on Surface Plasmon Resonance Technology in Heterodyne Interferometry 外差干涉测量中基于表面等离子体共振技术的生化传感器

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520081

Jyh-Shyan Chiu, Shinn-Fwu Wang, Wen-June Wang

{"title":"A Biochemical Sensor Based on Surface Plasmon Resonance Technology in Heterodyne Interferometry","authors":"Jyh-Shyan Chiu, Shinn-Fwu Wang, Wen-June Wang","doi":"10.1109/ICSSE.2018.8520081","DOIUrl":"https://doi.org/10.1109/ICSSE.2018.8520081","url":null,"abstract":"In the paper, a biochemical sensor based on surface plasmon resonance technology in heterodyne interferometry is proposed. The biochemical sensor is designed as an elongated prism that is made of BK7 glass. The two-sides of the elongated prism was coated with 2nm Ti-film and 45.5nm Au-film. On the basis of surface plasma resonance principles, the proposed biochemical sensor capitalizes on the adhesion activity between test fluids and metal films. Attenuated total reflection occurs when light permeates metal films, resulting in the phase variation. Thus, the fluid properties can be determined by measuring the phase of the exit light. Because adding chemicals or agents to the proposed biosensor is unnecessary, the properties of the measured sample are unaffected during measurements. With the biochemical sensor, the refractive index of the tested medium can be obtained only by measuring the phase difference between the p-and s-polarization lights due to the multiple attenuated total-internal reflections (MATRs) effect. The photoelectric biosensor has a sensitivity of up to $2.6times 10^{4}$ degree/refractive index. Besides, the best resolution of the sensor can reach $3.8times 10^{-7}$ refractive index unit (RIU). It also features several advantages such as instantaneous measurement, high sensitivity, simple experimental architecture, and low cost.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"633 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123347997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Layer Efficiency and Layer Reduction on Pre-Trained Deep Learning Models 预训练深度学习模型的层效率与层约简分析

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520080

B. T. Nugraha, S. Su

{"title":"Analysis of Layer Efficiency and Layer Reduction on Pre-Trained Deep Learning Models","authors":"B. T. Nugraha, S. Su","doi":"10.1109/ICSSE.2018.8520080","DOIUrl":"https://doi.org/10.1109/ICSSE.2018.8520080","url":null,"abstract":"Recent technologies in the deep learning area enable many industries and practitioners fastening the development processes of their products. However, deep learning still encounters some potential issues like overfitting and huge size. The huge size greatly constrains performance and portability of the deep learning model in embedded devices with limited environments. Due to the paradigm of it mixed with the meaning of “deep” layers, many researchers tend to derive the pre-trained model into building deeper layers to solve their problems without knowing whether they are actually needed or not. To address these issues, we exploit the activation and gradient output and weight in each layer of the pre-trained models to measure its efficiencies. By exploiting them, we estimate the efficiencies using our measurements and compare it with the manual layer reduction to validate the most relevant method. We also use the method for continuous layer reductions for validation. With this approach, we save up to 12x and 26x of the time of one manual layer reduction and re-training on VGG-16 and custom AlexNet respectively.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117314756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Mixed Reality System to Improve Walking Experience 改善步行体验的混合现实系统

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520135

Tz-Yang Chao, Shien‐Fong Lin

引用次数: 4

A System Dynamic Model for Implementation of Industry 4.0 工业4.0实施的系统动态模型

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520101

M. Khakifirooz, Dimitri Cayard, C. Chien, M. Fathi

引用次数: 10

Low Cost and IoT Based Greenhouse with Climate Monitoring and Controlling System for Tropical Countries 低成本和基于物联网的温室与热带国家气候监测和控制系统

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8519997

Y. Jayasuriya, C. S. Elvitigala, Kolitha Warnakulasooriya, B. Sudantha

引用次数: 9

ANFIS Damping Controller Design for SSSC to Improve Dynamic Stability of a Grid Connected Wind Power Systems 提高并网风电系统动态稳定性的SSSC ANFIS阻尼控制器设计

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520210

D. Truong, Q. C. Tran, P. Tran, M. N. Thi

引用次数: 6

Efficient Energy Management of a Time-of-Use Rate Industrial User for Smart Cities 面向智慧城市分时工业用户的高效能源管理

2018 International Conference on System Science and Engineering (ICSSE) Pub Date : 2018-06-01 DOI: 10.1109/ICSSE.2018.8520016

T. Lu, Chieh-Yu Huang, Yi-Yan Chen, Chun-Lung Chen, Tsung-Ying Lee

引用次数: 0