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

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A hybrid SVD-HSV visual sentiment analysis system 一种混合SVD-HSV视觉情感分析系统
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260063
Asmaa M. El-Gazzar, Taha M. Mohamed, R. Sadek
{"title":"A hybrid SVD-HSV visual sentiment analysis system","authors":"Asmaa M. El-Gazzar, Taha M. Mohamed, R. Sadek","doi":"10.1109/INTELCIS.2017.8260063","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260063","url":null,"abstract":"Image is worth a thousand of words. The use of images to express views, opinions, feelings, emotions and sentiments has increased hugely on social media. A lot of researches have been done for sentiment analysis of textual data. However, there is a limited work regarding visual sentiment analysis. In this paper, we propose a hybrid image sentiment prediction system, which combines low-level features and mid-level features of an image to predict the sentiment in different datasets. The results of the proposed hybrid system are better than using low-level or mid-level features individually. The results show that, the accuracy of the hybrid system exceeds the accuracy of using SVD only by 10% when being applied on photographic based images as in the KDEF dataset. Additionally, the accuracy of the proposed system exceeds the accuracy of using only HSV by 9% when being applied on social media images as in our collected and proposed dataset (SMI dataset). Another contribution of this paper is to avail the benchmarked dataset online for researchers.","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":"116664296","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: 5
Overfitting problem and the over-training in the era of data: Particularly for Artificial Neural Networks 数据时代的过拟合问题与过度训练:特别是人工神经网络
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260032
Imanol Bilbao, J. Bilbao
{"title":"Overfitting problem and the over-training in the era of data: Particularly for Artificial Neural Networks","authors":"Imanol Bilbao, J. Bilbao","doi":"10.1109/INTELCIS.2017.8260032","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260032","url":null,"abstract":"When we try to classify a set of data or to create a model to a cloud of points, different techniques can be used. Among them, Artificial Neural Networks are nowadays reinvented with the peak of the Machine Learning, Big Data, etc. In the process to find the best classification and be sure on it, one of the biggest concerns that we can come up against is the problem of overfitting. In this paper, we analyze it and set out a case study.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"70 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":"126243758","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: 70
Distributed single pass clustering algorithm based on MapReduce 基于MapReduce的分布式单遍聚类算法
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260047
Abdelrahman Elsayed, Osama Ismael, Hoda M. O. Mokhtar
{"title":"Distributed single pass clustering algorithm based on MapReduce","authors":"Abdelrahman Elsayed, Osama Ismael, Hoda M. O. Mokhtar","doi":"10.1109/INTELCIS.2017.8260047","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260047","url":null,"abstract":"Available data increase quickly every moment, this eventually drags to big data flooding. Hence there is an emergent need for exploiting big data in order to extract valuable knowledge from it. Adoption of distributed architecture and data intensive algorithms facilitates handling and processing big data. This paper introduces a distributed single pass clustering algorithm based on MapReduce in order to reduce running time of processing big data. Also, it introduces median based single pass clustering in order to mitigate the order of the input data problem that is associated with single pass clustering. Furthermore, it introduces a new hybrid approach which integrates median based single pass clustering and k-means algorithm. The proposed integration improves the median based clustering to work well with sparse data such as text. The experimental results state that the proposed approaches outperform traditional single pass clustering.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 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":"116480586","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
Evaluation of agile methods for quality assurance and quality control in ERP implementation 对ERP实施中质量保证和质量控制的敏捷方法进行评估
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260055
Jawad Javed Akbar Baig, Atif Shah, Faisal Sajjad
{"title":"Evaluation of agile methods for quality assurance and quality control in ERP implementation","authors":"Jawad Javed Akbar Baig, Atif Shah, Faisal Sajjad","doi":"10.1109/INTELCIS.2017.8260055","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260055","url":null,"abstract":"Most organizations are now adopting Enterprise Resource Planning (ERP) solutions to standardize, formalized and automate their processes. The organization usually hire IT Consulting Firms (ITCF) for ERP implementation due to its complexity, large scale, and domain knowledge. ERP brings radical changes in the environment, daily processes, and interactions of the organization. To make these changes gradual and incremental, ITCF are moving towards agile methodology. Quality assurance and quality control play a pivotal role in the success of an ERP implementation, with the use of agile methods the implementation becomes more complex. In this paper, grounded theory is used to study the rapid parallel processes of testing, validation, and verification for different phases of ERP implementation through using agile methods. In our study, 23 industry professionals participated from six different organizations. Each participant had experience of various ERP implementations in diverse geographical locations in various domains with different roles. This paper discuss and analyze different agile methods, which can reduce challenges in quality control and assurance during ERP implementation. The results show that agile methods (daily scrum meeting, pair programming and frequent reviews) reduce complexity and increase the quality of ERP implementation.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 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":"131061026","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: 14
A dual sparse and low rank representation for single image super-resolution: A self-learning approach 单幅图像超分辨率的双稀疏低秩表示:一种自学习方法
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260027
Doaa A. Altantawy, A. Saleh, S. Kishk
{"title":"A dual sparse and low rank representation for single image super-resolution: A self-learning approach","authors":"Doaa A. Altantawy, A. Saleh, S. Kishk","doi":"10.1109/INTELCIS.2017.8260027","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260027","url":null,"abstract":"Recently, the sparse representations are one of the most active research areas. Here, the problem of single image super-resolution is revisited with sparse and low rank priors. The introduced algorithm employs a self-learning approach. This self-learning approach is applied on cluster domain rather than the common used patch domain. For supporting the self-learning approach, the learning model adopts an incoherence property with the classical sparse priors. In addition, to compensate the weakness of the high frequency details of the underlying low-resolution image, an edge preserving low lark model is proposed. Hence, the low rank representation guarantees the global structure constraints in the recovered high-resolution images. Experimental results, on different datasets, show that the proposed algorithm can recover high-resolution images compared with the state-of-the art.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"57 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":"132748887","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
Countermeasures for layered security attacks on cognitive radio networks based on modified digital signature scheme 基于改进数字签名方案的认知无线网络分层安全攻击对策
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260019
John N. Soliman, T. A. Mageed, H. El-Hennawy
{"title":"Countermeasures for layered security attacks on cognitive radio networks based on modified digital signature scheme","authors":"John N. Soliman, T. A. Mageed, H. El-Hennawy","doi":"10.1109/INTELCIS.2017.8260019","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260019","url":null,"abstract":"Wireless technologies and services have been witnessed a rapid growth in the past few years, due to this development, spectrum scarcity and shortage has become a major concern, several spectrum portions of the static allocated licensed bands are under-utilized, Cognitive radio networks (CRNs) the most encouraging solution in enhancing the spectrum utilization by providing licensed spectrum portions to unlicensed users, however due to nature of these networks, CRNs are exposed to different types of security threats and attacks from different malicious users, which can affect the network availability and performance, in this paper a proposed countermeasures based on authentication mechanisms and digital signature scheme introduced to provide a defend strategy from the well-known attacks that could be launched by malicious and selfish users in CRNs.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"29 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":"124438910","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
Brain tumor segmentation using wavelet Multi-resolution expectation maximization algorithm 基于小波多分辨率期望最大化算法的脑肿瘤分割
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260030
D. M. S. El-Torky, M. Al-Berry, M. A. Salem, Mohamed Roushdy
{"title":"Brain tumor segmentation using wavelet Multi-resolution expectation maximization algorithm","authors":"D. M. S. El-Torky, M. Al-Berry, M. A. Salem, Mohamed Roushdy","doi":"10.1109/INTELCIS.2017.8260030","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260030","url":null,"abstract":"Magnetic Resonance Imaging is one of the most important tools for diagnosing brain cancer. The variation in shape, size, location and structure of brain tumors makes it challenging for segmentation. Accurate brain tumor segmentation helps in taking accurate treatment decisions. In this paper, the Wavelet Multiresolution Expectation Maximization (WMEM) algorithm is explained and applied on brain MRI for tumor segmentation. The performance of the algorithm is evaluated using real Magnetic Resonance Imaging (MRI) images with segmented ground truth.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 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":"125266552","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
Hybrid method based on multi-feature descriptor for static sign language recognition 基于多特征描述符的静态手语识别混合方法
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260039
Rania A. Elsayed, M. Abdalla, M. Sayed
{"title":"Hybrid method based on multi-feature descriptor for static sign language recognition","authors":"Rania A. Elsayed, M. Abdalla, M. Sayed","doi":"10.1109/INTELCIS.2017.8260039","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260039","url":null,"abstract":"Sign Language Recognition is an essential research problem for enabling communication with deaf-dumb people. Sign language recognition system confronts many challenges such as complex background, illumination changes, translation, rotation, and scale problem, besides system requirements such as time of recognition, robustness, performance, and computational efficiency. This paper proposes hybridization between two strong descriptors including Histogram of Oriented Gradients (HOG) and Edge Oriented Histogram (EOH) to achieve better recognition rate with relatively low memory requirements. A new feature descriptor is used as a combined feature descriptor, which joins the advantages of each descriptor to achieve good performance. Multi-class support vector machine classifier is utilized to classify the hand gestures. Experimental results demonstrate that the proposed system gives recognition rate of 96.15 % for 1AASVM classifier and 99.23 % for 1A1SVM classifier under different hand poses and complex background with changes in lightning conditions.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"22 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":"114628087","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
Measuring reusability during requirement engineering of an ERP implementation 在ERP实现的需求工程期间测量可重用性
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260056
Jawad Javed Akbar Baig, Mahmoud Abdulkarim Al Fadel
{"title":"Measuring reusability during requirement engineering of an ERP implementation","authors":"Jawad Javed Akbar Baig, Mahmoud Abdulkarim Al Fadel","doi":"10.1109/INTELCIS.2017.8260056","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260056","url":null,"abstract":"Due to growth in size and business, organizations embrace enterprise software solutions. It helps them to formalize and automate their processes. Enterprise Resource Planning (ERP) solutions are widely used in software solutions. They provide standard and flexible processes for a specific domain. Requirement engineering activities play a fundamental and decisive role in ERP implementations success. During requirement engineering cycle, consultants reuse different artifacts from previous implementations and ERP documentation. Those artifacts include business process diagrams, user cases and mapping sheets for configuration and migration. So there is the need of a metric suite, which can help consultants to measure different aspects of reusability. For this study, interviews were conducted with 17 ERP consultants who had diverse regional and ERP solutions experience. Details of different reusable artifacts and their benefits are discussed. Furthermore, reusability metrics suite is presented to measure cost, benefit, and a return of investment of reusable artifact. We concluded that the use of reusable artifacts during requirement engineering cycle of ERP implementation can increase the chances of success.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 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":"125541474","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: 5
Arabic sign language recognition with 3D convolutional neural networks 三维卷积神经网络的阿拉伯手语识别
2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2017-12-01 DOI: 10.1109/INTELCIS.2017.8260028
M. ElBadawy, A. S. Elons, Howida A. Shedeed, M. Tolba
{"title":"Arabic sign language recognition with 3D convolutional neural networks","authors":"M. ElBadawy, A. S. Elons, Howida A. Shedeed, M. Tolba","doi":"10.1109/INTELCIS.2017.8260028","DOIUrl":"https://doi.org/10.1109/INTELCIS.2017.8260028","url":null,"abstract":"Sign Language recognition is very important for communication purposes between Hearing Impaired (HI) people and hearing ones. Arabic Sign Language Recognition field became widespread because of its difficult nature and numerous details. Most researchers employed different input sensors, features extractors, and classifiers on static and dynamic data. These different ways were customized and employed in our previous work in the Arabic Sign Language Recognition field. In this paper, features extractor with deep behavior was used to deal with the minor details of Arabic Sign Language. 3D Convolutional Neural Network (CNN) was used to recognize 25 gestures from Arabic sign language dictionary. The recognition system was fed with data from depth maps. The system achieved 98% accuracy for observed data and 85% average accuracy for new data. The results could be improved as more data from more different signers are included.","PeriodicalId":321315,"journal":{"name":"2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"5 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":"117218781","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: 49
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