Computer Science & Information Technology (CS & IT )最新文献

APPLICATION OF DOMAIN SPECIFIC LANGUAGE FOR DESCRIBING AN ONLINE FILE STORAGE SYSTEM 应用领域特定语言描述在线文件存储系统

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90610

Salla Nelson Stanley

引用次数: 0

RESEARCH ON GAIT PREDICTION BASED ON LSTM 基于LSTM的步态预测研究

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90603

Bofan Liang, Qili Chen

引用次数: 0

PROBABILITY-DIRECTED PROBLEM OPTIMIZATION TECHNIQUE FOR SOLVING SYSTEMS OF LINEAR AND NON-LINEAR EQUATIONS 求解线性和非线性方程组的概率导向问题优化技术

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90605

M. Al-Muhammed

{"title":"PROBABILITY-DIRECTED PROBLEM OPTIMIZATION TECHNIQUE FOR SOLVING SYSTEMS OF LINEAR AND NON-LINEAR EQUATIONS","authors":"M. Al-Muhammed","doi":"10.5121/CSIT.2019.90605","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90605","url":null,"abstract":"Although many methods have been proposed for solving linear or nonlinear systems of equations, there is always a pressing need for more effective and efficient methods. Good methods should produce solutions with high precision and speed. This paper proposed an innovative method for solving systems of linear and nonlinear equations. This method transforms the problem into an optimization problem and uses a probability guided search technique for solving this optimization problem, which is the solution for the system of equations. The transformation results in an aggregate violation function and a criterion function. The aggregation violation function is composed of the constraints that represent the equations and whose satisfaction is a solution for the system of equations. The criterion function intelligently guides the search for the solution to the aggregate violation function by determining when the constraints must be checked; thereby avoiding unnecessary, timeintensive checks for the constraints. Experiments conducted with our prototype implementation showed that our method is effective in finding solutions with high precision and efficient in terms of CPU time.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115559288","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

COPING WITH CLASS IMBALANCE IN CLASSIFICATION OF TRAFFIC CRASH SEVERITY BASED ON SENSOR AND ROAD DATA: A FEATURE SELECTION AND DATA AUGMENTATION APPROACH 基于传感器和道路数据处理交通碰撞严重程度分类中的类不平衡:一种特征选择和数据增强方法

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90611

Deepti Lamba, Majed Alsadhan, W. Hsu, Eric J. Fitzsimmons

{"title":"COPING WITH CLASS IMBALANCE IN CLASSIFICATION OF TRAFFIC CRASH SEVERITY BASED ON SENSOR AND ROAD DATA: A FEATURE SELECTION AND DATA AUGMENTATION APPROACH","authors":"Deepti Lamba, Majed Alsadhan, W. Hsu, Eric J. Fitzsimmons","doi":"10.5121/CSIT.2019.90611","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90611","url":null,"abstract":"This paper presents machine learning-based approaches to classification of historical traffic crashes in Kansas by severity, applied to a data set consisting of highway geometry, weather, and road sensor data. The goal of this work is to identify relevant features using a variety of loss measures and algorithms for feature selection. This is shown to facilitate the discovery of the most relevant sensors for the task of learning to predict severe crashes (those involving bodily injury). The key technical challenges are to cope with class imbalance (as a 75% majority of crashes are non-severe) and a highly correlated and redundant set of features from multiple coalesced sources. The major novel contributions of this work are the development of a random oversampling strategy for data augmentation, combined with the systematic application of multiple feature selection measures over a range of supervised inductive learning models and algorithms. Positive results from this approach, on a data set of 277 initial ground features and 20,000 vehicle crashes collected over 9 years (2007 – 2015) by the Kansas Department of Transportation (KDOT), included models trained using 30 features (out of 277) that achieve cross-validation precision and recall comparable to those obtained using the full set of features. These and other results point towards potential use of feature selection findings and the resultant models in planning future road construction.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128242748","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: 7

NUCLEAR: AN EFFICIENT METHOD FOR MINING FREQUENT ITEMSETS BASED ON KERNELS AND EXTENDABLE SETS 核:一种基于核和可扩展集的挖掘频繁项集的有效方法

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90607

H. Pham, Duc-Hoc Tran, Ninh Bao Duong, Philippe Fournier-Viger, A. Ngom

引用次数: 0

AN ADVISING SYSTEM FOR PARKING USING CANNY AND K-NN TECHNIQUES 使用canny和k-nn技术的停车提示系统

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90604

C. Dow, Wei-kang Wang, Huu-Huy Ngo, Shiow-Fen Hwang

引用次数: 2

BRAIN COMPUTER INTERFACE FOR BIOMETRIC AUTHENTICATION BY RECORDING SIGNAL 脑机接口，通过记录信号进行生物识别认证

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90613

Abd Abrahim Mosslah, R. Mahdi, S. M. Al-Barzinji

引用次数: 1

MACHINE LEARNING AND WEARABLE DEVICES FOR PHONOCARDIOGRAM-BASED DIAGNOSIS 基于心音图诊断的机器学习和可穿戴设备

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90606

S. Abdelmageed, M. Elmusrati

引用次数: 0

DEVELOPMENT OF A KNOWLEDGE- BASED SYSTEM FOR UNDERTAKING THE RISK ANALYSIS OF PROPOSED BUILDING PROJECTS FOR A SELECTED CLIENT 开发一个以知识为基础的系统，为选定的客户进行拟议建筑项目的风险分析

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90608

I. Yakubu

引用次数: 0

EVIDENCE FOR THE CORRELATION BETWEEN CONFLICT RISK INDICATORS GCRI AND FSI USING DEEP LEARNING 使用深度学习的冲突风险指标gcri和fsi之间相关性的证据

Computer Science & Information Technology (CS & IT ) Pub Date : 2019-05-25 DOI: 10.5121/CSIT.2019.90602

V. Kamp, Jp Knust, R. Moratz, Kevin Stehn, Soren Stohrmann

{"title":"EVIDENCE FOR THE CORRELATION BETWEEN CONFLICT RISK INDICATORS GCRI AND FSI USING DEEP LEARNING","authors":"V. Kamp, Jp Knust, R. Moratz, Kevin Stehn, Soren Stohrmann","doi":"10.5121/CSIT.2019.90602","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90602","url":null,"abstract":"Data mining enables an innovative, largely automatic meta-analysis of the relationship between political and economic geography analyses of crisis regions. As an example, the two approaches Global Conflict Risk Index (GCRI) and Fragile States Index (FSI) can be related to each other. The GCRI is a quantitative conflict risk assessment based on open source data and a statistical regression method developed by the Joint Research Centre of the European Commission. The FSI is based on a conflict assessment framework developed by The Fund for Peace in Washington, DC. In contrast to the quantitative GCRI, the FSI is essentially focused on qualitative data. Both approaches therefore have closely related objectives, but very different methodologies and data sources. It is therefore hoped that the two complementary approaches can be combined to form an even more meaningful meta-analysis, or that contradictions can be discovered, or that a validation of the approaches can be obtained if there are similarities. We propose an approach to automatic meta-analysis that makes use of machine learning (data mining). Such a procedure represents a novel approach in the meta-analysis of conflict risk analysis.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123381199","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