2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)最新文献_第4页

Research on the present situation and problems of listed companies in Henan 河南上市公司现状与问题研究

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960086

D. Zheng, Sujian Guo

引用次数: 0

Applying parallel programming and high performance computing to speed up data mining processing 应用并行编程和高性能计算来加速数据挖掘处理

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960006

Ruijian Zhang

{"title":"Applying parallel programming and high performance computing to speed up data mining processing","authors":"Ruijian Zhang","doi":"10.1109/ICIS.2017.7960006","DOIUrl":"https://doi.org/10.1109/ICIS.2017.7960006","url":null,"abstract":"Water quality assessment and prediction of Lake Michigan are becoming major challenges in Northwest Indiana, USA. Traditionally, mechanistic simulation models are employed for water quality modeling and prediction. However, given the complicate nature of Lake Michigan in Northwestern Indiana, the detailed simulation model is extremely simple in comparison and, at some point, additional detail exceeds our ability to simulate and predict with reasonable error levels. In this regard, my project applied data mining technologies, as an innovative alternative, to develop an easy and more accurate approach for water quality assessment and prediction. The drawback of the data mining modeling is that the execution takes quite long time, especially when we employ a better accuracy but more time consuming algorithm in clustering. Therefore, we applied the High Performance Computing System of the Northwest Indiana Computational Grid to deal with this problem. Up to now, the pilot experiments have achieved very promising preliminary results. The visualized water quality assessment and prediction obtained from this project would be published in an interactive website so that the public and the environmental managers could use the information for their decision making.","PeriodicalId":301467,"journal":{"name":"2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121522397","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

Auditory mask estimation by RPCA for monaural speech enhancement 基于RPCA的单音语音增强听觉掩码估计

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7959990

Wenhua Shi, Xiongwei Zhang, Xia Zou, Wei Han, Gang Min

引用次数: 5

Outcome prediction of DOTA2 based on Naïve Bayes classifier 基于Naïve贝叶斯分类器的DOTA2结果预测

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960061

Kaixiang Wang, Wenqian Shang

引用次数: 21

Human experience knowledge induction based intelligent train driving 基于人类经验知识感应的智能列车驾驶

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960015

Jin Huang, Fan Yang, Yangdong Deng, Xibin Zhao, M. Gu

{"title":"Human experience knowledge induction based intelligent train driving","authors":"Jin Huang, Fan Yang, Yangdong Deng, Xibin Zhao, M. Gu","doi":"10.1109/ICIS.2017.7960015","DOIUrl":"https://doi.org/10.1109/ICIS.2017.7960015","url":null,"abstract":"As the most sustainable means of modern transportation, the railway trains are eagerly approaching autonomous driving due to their congenital advantages on operating environments compare to, e.g., road traffics. The intelligent automatic train driving aims at train control with a goal of energy efficiency, punctuality and safety. The derivation of an optimized train driving solution by taking advantage of the undulating terrains along a route, however, proves to be a significant challenge due to the high dimension, nonlinearity, complex constraints, and time-varying characteristic of the problem. To tackle the problem, we propose a two-level human driving experience learning framework and employ the fuzzy rule induction method for online generation of the optimized driving solutions. Based on the records of experienced human drivers, a FURIA model was built to learn the driving rules indicating the correlation between the specified features to the decision of a driving sequence. The fuzzy rules can generally find the best-match driving operation under certain running circumstances. The learned model can be used to determine an optimized driving operation in real-time. Validation experiments show that the energy consumption of the proposed solution is around 8.93% lower than that of average human drivers.","PeriodicalId":301467,"journal":{"name":"2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568128","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: 6

An implementation of access-control protocol for IoT home scenario 物联网家庭场景访问控制协议的实现

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7959965

Xiaoyang Wu, Ron Steinfeld, Joseph K. Liu, C. Rudolph

引用次数: 8

FDR verification of a system involving a robot climbing stairs 一个机器人爬楼梯系统的FDR验证

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960115

Tomoo Sumida, Hiroyuki Suzuki, Sho Sei Shun, K. Ohmaki, T. Goto, K. Tsuchida

引用次数: 1

Safety prediction of rail transit system based on deep learning 基于深度学习的轨道交通系统安全预测

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960111

Yan Zhang, Jiazhen Han, Jing Liu, Tingliang Zhou, Junfeng Sun, Juan Luo

引用次数: 5

Double hand-gesture interaction for walk-through in VR environment 在虚拟现实环境中进行双手势交互

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-24 DOI: 10.1109/ICIS.2017.7960051

Fan Zhang, Shaowei Chu, Ruifang Pan, Naye Ji, Lian Xi

引用次数: 24

Reconfigurable smart water quality monitoring system in IoT environment 物联网环境下可重构智能水质监测系统

2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS) Pub Date : 2017-05-01 DOI: 10.1109/ICIS.2017.7960032

Cho Zin Myint, Lenin Gopal, Y. Aung

{"title":"Reconfigurable smart water quality monitoring system in IoT environment","authors":"Cho Zin Myint, Lenin Gopal, Y. Aung","doi":"10.1109/ICIS.2017.7960032","DOIUrl":"https://doi.org/10.1109/ICIS.2017.7960032","url":null,"abstract":"Since the effective and efficient system of water quality monitoring (WQM) are critical implementation for the issue of polluted water globally, with increasing in the development of Wireless Sensor Network (WSN) technology in the Internet of Things (IoT) environment, real time water quality monitoring is remotely monitored by means of real-time data acquisition, transmission and processing. This paper presents a reconfigurable smart sensor interface device for water quality monitoring system in an IoT environment. The smart WQM system consists of Field Programmable Gate Array (FPGA) design board, sensors, Zigbee based wireless communication module and personal computer (PC). The FPGA board is the core component of the proposed system and it is programmed in very high speed integrated circuit hardware description language (VHDL) and C programming language using Quartus II software and Qsys tool. The proposed WQM system collects the five parameters of water data such as water pH, water level, turbidity, carbon dioxide (CO2) on the surface of water and water temperature in parallel and in real time basis with high speed from multiple different sensor nodes.","PeriodicalId":301467,"journal":{"name":"2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)","volume":"16 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121018312","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: 57