2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)最新文献_第2页

Gene Expression Data For Gene Selection Using Ensemble Based Feature Selection 基于集成特征选择的基因表达数据

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014722

Mohamad Aouf, Amr A. Sharawi, Khaled Samir, Sultan Almotatiri, A. Bajahzar, Ghada Kareem

引用次数: 0

Violence Recognition from Videos using Deep Learning Techniques 使用深度学习技术从视频中识别暴力

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014714

Mohamed Soliman, Mohamed Hussein Kamal, Mina Abd El-Massih Nashed, Y. Mostafa, Bassel S. Chawky, D. Khattab

引用次数: 57

An Improved Integrated Intensity-Hue-Saturation with Stationary Wavelet Transform Multi-sensor Image Fusion Approach 一种改进的基于平稳小波变换的强度-色调-饱和度集成多传感器图像融合方法

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014669

Abdelrahman Yehia, H. Elhifnawy, M. Safy

{"title":"An Improved Integrated Intensity-Hue-Saturation with Stationary Wavelet Transform Multi-sensor Image Fusion Approach","authors":"Abdelrahman Yehia, H. Elhifnawy, M. Safy","doi":"10.1109/ICICIS46948.2019.9014669","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014669","url":null,"abstract":"Image fusion aims to retrieve information data from a set of multiple images into a composite output image. Pan-sharpen is the method of combining a high spatial resolution panchromatic (PAN) image and a high spectral resolution multispectral (MS) data of the same scene. It is not only beneficial for enhancing the spatial contents but also to preserve its spectral quality to be more useful for interpretation. Intensity-Hue-Saturation (IHS) transform is a commonly performed method for image fusion, but it causes some spectral distortion. A proposed hybrid approach applies IHS fusion with a Stationary Wavelet Transform (SWT) because the recent usually preserves the color information via multilevel decomposition. By using different fusion rules, for combining the corresponding approximation and details coefficients obtained from wavelet decompositions, a coefficient combining, and activity level measurement based fusion rules are executed. The main characteristic of the composite platform is utilizing the features of the combined algorithms with different fusion rules into a single image. The fusion results are evaluated and compared with results by conventional fusion techniques. Choosing the optimum fusion rules counts on the imageries set and depending upon the application. Visual inspection and quantitative analysis demonstrate that successful results among the different fusion methods.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132344509","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 Dynamic Simulation Environment for Container-based Cloud Data Centers using ContainerCloudSim 使用ContainerCloudSim的基于容器的云数据中心动态模拟环境

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014697

Noorhan Saleh, M. Mashaly

{"title":"A Dynamic Simulation Environment for Container-based Cloud Data Centers using ContainerCloudSim","authors":"Noorhan Saleh, M. Mashaly","doi":"10.1109/ICICIS46948.2019.9014697","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014697","url":null,"abstract":"With the addition of the new type of cloud service known as Container as a Service (CaaS), the need for allocation and scheduling policies as well as modeling and simulation containerization environment for testing has increased. CloudSim simulation tool, which is a framework for modeling and simulation of cloud computing infrastructures and services, has provided an extension called ContainerCloudSim as a testing environment for containers. However, there are still gaps in the simulation that need to be addressed in order to provide accurate modeling for the virtualized container environment. In this paper, we focus on filling these gaps by adding three main features to the CloudSim tool. The first feature is providing datacenters with the capability of supporting both virtualization techniques: virtual machines and containers. The second feature is having a dynamic simulation and application cloudlets that are scheduled dynamically through the simulation time and the third feature is supporting the simulation of applications with dependent tasks. A test case is provided to show the contribution of our proposal, which provides a more realistic testing environment and increases the number of allocation and scheduling algorithms that could be tested upon CloudSim.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125577100","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: 9

Ninth IEEE International Conference on Intelligent Computing and Information Systems 第九届IEEE智能计算与信息系统国际会议

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/icicis46948.2019.9014832

引用次数: 0

Resource Management using Machine Learning in Mobile Edge Computing: A Survey 在移动边缘计算中使用机器学习的资源管理:调查

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014733

Marwa Zamzam, T. Elshabrawy, M. Ashour

{"title":"Resource Management using Machine Learning in Mobile Edge Computing: A Survey","authors":"Marwa Zamzam, T. Elshabrawy, M. Ashour","doi":"10.1109/ICICIS46948.2019.9014733","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014733","url":null,"abstract":"Mobile Edge Computing (MEC) aims to overcome the limited terminal battery and processing capabilities associated with running applications in the mobile terminal and the high latency introduced by offloading these applications to the cloud. It extends the computing resources of the cloud at the edge of the cellular network closer to the mobile user. Resource management in mobile edge computing is one of the main issues that are studied recently by many researchers. It consists of resource allocation and computation offloading. Allocation of resources involves managing and scheduling the resources to accomplish the requests of the users. It depends on the availability and the capacity of the resources. According to the deadline of each requested task, the service provider will assign each user the sufficient resources. Computation offloading is the transfer of the tasks to be executed at an external platform (edge or cloud server). It depends on the processing capability and the storage capacity of the device. It is difficult to provide an optimal solution for resource management in a dynamic system due to the random variations of tasks required by the users and the mobility of these users, thus machine learning techniques are proposed to solve this optimization problem. In this paper we provide the state-of-the-art for using machine learning to optimize resource management in mobile edge computing. We divide the research into four categories: 1) minimizing the cost, 2) minimizing the energy consumption, 3) minimizing the latency and 4) minimizing both latency and energy consumption. We then classify the system model, the constraints and the types of machine learning techniques that are used in each optimization problem.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126468708","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: 15

Securing the Space Data Link Communication Protocol of Earth Observation Satellites 保护对地观测卫星空间数据链通信协议

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014846

A. Abdelaziz, Essam Abdelwanees, A. Elbayoumy

{"title":"Securing the Space Data Link Communication Protocol of Earth Observation Satellites","authors":"A. Abdelaziz, Essam Abdelwanees, A. Elbayoumy","doi":"10.1109/ICICIS46948.2019.9014846","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014846","url":null,"abstract":"Earth Observation Satellites (EOS) as any remote unmanned vehicle need to communicate with its control ground station (CGS) either to send its housekeeping and payload telemetry data or to receive control commands and this is done through simple lightweight communication protocols which are designed taking into account the special conditions of the space environment. For civilian missions, this communication protocol is not protected and has several security issues that result in critical risks and safety concerns. In this paper, we studied the security vulnerabilities of space data link communication protocols and investigate the applicability of software-based solution to secure these communication protocols that adopt a software-friendly cryptographic algorithm to ensure the protection of exchanged data between the EOS and its CGS to reduce the penalties of added hardware device which affects negatively the spacecraft resources power consumption volume and mass. For validation, a software spacecraft simulator developed to evaluate the impact of different cryptographic algorithms on the space link security protocol. The results showed that ChaCha-poly1305 is a good candidate as authenticated-encryption algorithms used to secure space data link protocol (SDLP) to guarantee its messages confidentiality and authentication, without affecting the resources of the spacecraft","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126474527","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

An Intelligent Hybrid Technique of Decision Tree and Genetic Algorithm for E-Mail Spam Detection 基于决策树和遗传算法的垃圾邮件检测智能混合技术

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014756

A. Taloba, Safaa S. I. Ismail

{"title":"An Intelligent Hybrid Technique of Decision Tree and Genetic Algorithm for E-Mail Spam Detection","authors":"A. Taloba, Safaa S. I. Ismail","doi":"10.1109/ICICIS46948.2019.9014756","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014756","url":null,"abstract":"One of the most serious and irritating problem for decades is E-mail spam. These unwanted and unrequested commercial emails are also known as junk emails. Several machine learning approaches are used for detecting emails as spam or ham. These techniques detect spam emails from inbox and pass it to junk email folder. Even though among these approaches, it has been found that simple text classification techniques are not sufficient to detect spam e-mails. It is more preferable to use hybrid techniques to make detecting spam e-mails more efficiently. In this paper, a novel of hybrid machine learning technique of decision tree and genetic algorithm known as GADT is proposed for e-mail spam detection. It is believable that using genetic algorithm to improve the decision tree performance for text classification is effective and precise. Genetic algorithm is used to optimize and find the optimal value of a parameter named confidence factor that control the pruning of the decision tree. A major problem of any application of text classification, as spam detection, is its huge number of features that decrease in the accuracy of the classifiers. In our application, most of the extracted features that are extracted from the content of the email messages are irrelevant noise that can misled the classifier. So, it is found that dimension reduction stage is essential to reduce this huge number of features. In this paper, principle component analysis (PCA) technique is found to be a good choice to eliminate unsuitable features with less processing. The experimental results show the enhancement of accuracy of the hybrid approach GADT for detecting spam e-mail compared to the traditional decision tree. Also, these results show the high performance of GADT after using PCA compared to other traditional text classifiers.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131202847","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: 16

Multi-Emotion Classification Evaluation via Twitter 通过Twitter进行多情绪分类评估

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/ICICIS46948.2019.9014847

S. S. Ibrahiem, S. Ismail, K. Bahnasy, M. Aref

{"title":"Multi-Emotion Classification Evaluation via Twitter","authors":"S. S. Ibrahiem, S. Ismail, K. Bahnasy, M. Aref","doi":"10.1109/ICICIS46948.2019.9014847","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014847","url":null,"abstract":"Recently, twitter has become an indispensable social communication platform. It contains many contrasting views and cultures on miscellaneous topics. This gigantic information bulk has endeared the attention of researchers for its interpretation and serve it in various life applications (e.g. product customer feedback, tourism, voting, product branding, etc.). However, natural languages ambiguity is one of the researchers' limitations, where implicit and diverse emotions are implied in the same context. Emotion analysis is a recent research field that digs to predict the implied emotions in different media types especially written text. Traditional approaches focused on detecting single attitude from social media texts, which isn't considered accurate. This research proposes two Multi-Emotion classification (MEC) approaches, that mine users' attitudes in tweets. These approaches have diverse classifiers' architectures, representative features, and a number of emotions sets. These diversities contribute in each classifier's performance in emotion classification. Eight experiments are applied using two feature representation vectors and two supervised machine learning algorithms on two emotion sets. The proposed systems outperform the contemporary traditional approaches. The first Binary relevance approach achieves hamming score ranging from 0.36 to 0.53, and the second Convolutional neural network approach achieves hamming score ranging from 0.39 to 0.54.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121322390","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

Exascale and the Convergence of High-Performance Computing, Big Data, AI and IoT 百亿亿次与高性能计算、大数据、人工智能和物联网的融合

2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS) Pub Date : 2019-12-01 DOI: 10.1109/icicis46948.2019.9014700

T. Ghazawi

引用次数: 0