2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)最新文献_第3页

WFEC: Wind farms economic classifier using big data analytics WFEC:使用大数据分析的风电场经济分类

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260046

D. Fawzy, Sherin M. Moussa, N. Badr

{"title":"WFEC: Wind farms economic classifier using big data analytics","authors":"D. Fawzy, Sherin M. Moussa, N. Badr","doi":"10.1109/INTELCIS.2017.8260046","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260046","url":null,"abstract":"Wind energy projects have recently been associated with huge investments. This led researchers to dig more into managing the costs of wind farms. The operation and maintenance (O&M) costs have a big effect on the success of wind farm projects. Thus, monitoring wind turbines and predicting the O&M costs become of a crucial demand. O&M costs are related to some main parts in wind turbines, like the spare parts and rotor blades that are exposed to damage because of the surrounding environmental factors. Hence, they can be monitored via deployed sensors that generate massive quantities of incomplete, and heterogeneous data. Therefore, a big data analytical system is required to analyze these data. In this paper, we propose the Wind Farms Economic Classifier (WFEC) System that uses big data analytics to manage the data volume, variety and veracity to predict the O&M costs. WFEC proposes an enhanced Flexible Naïve Bayes Classifier (FNBC) to classify wind farms profitability according to the predicted O&M costs. Experiments show that WFEC achieves high classification accuracy with less processing time.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126605848","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 comparative analysis of Cross Site Scripting (XSS) detecting and defensive techniques 跨站脚本(XSS)检测和防御技术的比较分析

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260024

Shaimaa Mahmoud, Marco Alfonse, Mohamed Roushdy, Abdel-badeeh M. Salem

引用次数: 11

Design and implementation of multicore support for a highly reliable self-repairing μ-kernel OS 多核支持的高可靠自修复μ内核操作系统的设计与实现

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260021

Hatem A. El-Azab, M. Girgis, Essam-Eldean F. Elfakharany, M. E. Shehab

引用次数: 0

Adaptive group sparse representation for image compressive sensing 图像压缩感知的自适应群稀疏表示

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260026

Tianyu Geng, Guiling Sun, Yi Xu, Bowen Zheng

引用次数: 0

Temporal sentiment analysis and time tags for opinions 时间情感分析和时间标签的意见

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260065

G. Hafez, R. Ismail, O. Karam

{"title":"Temporal sentiment analysis and time tags for opinions","authors":"G. Hafez, R. Ismail, O. Karam","doi":"10.1109/INTELCIS.2017.8260065","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260065","url":null,"abstract":"Nowadays, opinion mining becomes one of the most important fields and it attracts the interest of many researchers. The ‘electronic Word of Mouth’ (eWOM) statements that are expressed on the web, are important for business and service industry to enable customers share their point of view. In the last one and half decades, research communities, academia, public and service industries are working rigorously on opinion mining — which is also called, sentiment analysis to identify and categorize opinions from a piece of text. One key use of sentiment analysis is to extract and analyze public moods and views. Researches used sentiment analysis in different ways. For example, to determine market strategy, to improve customer service. One of the key challenges of sentiment analysis is how to extract temporal synsets from text. Temporal synsets may be events, dates, times, or even Explicit lyrics. Tempowordnet is one of the attempts to building a lexicon that may help in finding temporal synsets. In this paper, we propose a framework for discovering temporal verb references (future, past and present) from opinions and using them to build accurate prediction models. The proposed method improved the percentage of discovering the(past, present and future verbs)over the tempowordnet.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124264124","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: 1

Swarming behaviour of salps algorithm for predicting chemical compound activities 一种预测海鞘化合物活性的群集行为算法

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260072

A. Hussien, A. Hassanien, E. H. Houssein

{"title":"Swarming behaviour of salps algorithm for predicting chemical compound activities","authors":"A. Hussien, A. Hassanien, E. H. Houssein","doi":"10.1109/INTELCIS.2017.8260072","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260072","url":null,"abstract":"The increasing size of chemical search space of chemical compound databases and importance of similarity measurements to drug discovery are main factors in chem.-informatics research. This paper introduces a swarming behavior of salps algorithm for predicting chemical compound activities. The salp optimization algorithm is proposed for chemical descriptor selection with three initialization (small, mixed and large). The K-nearest neighbor (KNN) was utilized for the fitness function of salps swarm optimization algorithm (SSOA) to choose a small number of features and achieve high classification accuracy. Experimental results reveal the capability of SSA to find an optimal feature subset which maximizes the classification performance and minimizes the number of selected features. A set of assessment indicators are used to evaluate and compared with different algorithms inclduing particle swarm optimization (PSO), Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimizer(GWO), Sine Cosine Algorithm (SCA), Whale Optimization algorithm (WOA) using three initialization method and a superior accuracy was obtained with our proposed approach. Also, in comparison with other algorithms that used the same data, our approach has a higher performance using less number of features. The previous algorithms (GOA, GWO, PSO, SSA, SCA, WOA) are compared and three different methods are used to initialize the different optimization algorithms to ensure capability of the different optimizers to converge from different initial positions namely mixed initialization, small initialization, and large initialization.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122819440","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: 93

An evaluation of software requirements tools 对软件需求工具的评估

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260075

Atif Shah, M. A. Alasow, Faisal Sajjad, Jawad Javed Akbar Baig

引用次数: 8

EEG based epilepsy detection using approximation entropy and different classification strategies 基于近似熵和不同分类策略的脑电图癫痫检测

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260038

Aya Naser, M. Tantawi, Howida A. Shedeed, M. Tolba

引用次数: 3

Schema engineering for enterprise knowledge graphs: A reflecting survey and case study 企业知识图谱的模式工程:反映调查和案例研究

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260074

Jonas Jetschni, Vera G. Meister

{"title":"Schema engineering for enterprise knowledge graphs: A reflecting survey and case study","authors":"Jonas Jetschni, Vera G. Meister","doi":"10.1109/INTELCIS.2017.8260074","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260074","url":null,"abstract":"Knowledge graphs for the support of knowledge-intensive tasks and processes, or as a backbone of an organizational digitalization strategy are intensively discussed in recent scientific literature. What is largely missing, are aspects of the organizational management and even the major change of intermediary roles between business domain experts and IT specialists. Based on a literature review this paper introduces a comprehensive definition together with an abstract model of a knowledge graph in companies, a so-called Enterprise Knowledge Graph (EKG). Considering one of its core elements, the development of an EKG schema, i.e. the formal knowledge structure of the business domains to model, was analyzed in detail and reflected in the course of a case study. The new role of a knowledge engineer and its responsibilities as well as necessary competencies were outlined and discussed from real world perspective. The findings of the paper constitute an initial building block of a comprehensive framework for the implementation and the assessment of the maturity of knowledge graphs in organizations.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116948207","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: 10

Development of rheumatoid ontology 类风湿本体的发展

2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260082

M. Gawich, Marco Alfonse, M. Aref, Abdel-badeeh M. Salem

引用次数: 4