2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第2页

EGlossy: An Energy-Efficient Glossy-Based Synchronization and Flooding Protocol in IoT EGlossy:物联网中基于光泽度的高能效同步和泛洪协议

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566650

Samira Parvin Gilavan, G. Ekbatanifard

引用次数: 1

Violence Detection in Indoor Surveillance Cameras Using Motion Trajectory and Differential Histogram of Optical Flow 基于运动轨迹和光流差分直方图的室内监控摄像机暴力检测

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566460

Tahereh Zarrat Ehsan, M. Nahvi

引用次数: 11

Frequent Itemsets as Meaningful Events in Graphs for Summarizing Biomedical Texts 作为有意义事件的频繁项集在图表中用于总结生物医学文本

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566651

M. Moradi

{"title":"Frequent Itemsets as Meaningful Events in Graphs for Summarizing Biomedical Texts","authors":"M. Moradi","doi":"10.1109/ICCKE.2018.8566651","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566651","url":null,"abstract":"In this paper, we introduce a method using graph modeling for summarizing biomedical texts. We address the challenges of identifying meaningful topics of the input document, modeling the relations between the sentences, and selecting the most relevant sentences. Our summarizer utilizes an itemset mining method to discover the topics from the concepts extracted from the input document. It uses a meaningfulness measure to identify the meaningful events, i.e. the essential topics of the input document. Theses meaningful topics are used to construct a small-world network that models the relations between the sentences within the text. Those sentences identified as highly-informative and relevant are selected to generate the final summary. Conducting a set of evaluations, we assess the efficiency of the graph-based approach for summarization of biomedical documents. The evaluations demonstrate that our method can achieve a better performance in comparison with a number of available methods with respect to some widely-used metrics. The summaries produced by the graph-based summarizer contain more informative content compared to the summaries generated by the other methods. This shows that the combination of itemset mining on the concepts, the meaningfulness measure, and modeling the text as a small-world network can perform well in biomedical text summarization.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114487340","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: 12

The Impact of Demographic Factors on Persuasion Strategies in Personalized Recommender System 个性化推荐系统中人口因素对说服策略的影响

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566550

Fakhroddin Noorbehbahani, Zeinab Zarein

{"title":"The Impact of Demographic Factors on Persuasion Strategies in Personalized Recommender System","authors":"Fakhroddin Noorbehbahani, Zeinab Zarein","doi":"10.1109/ICCKE.2018.8566550","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566550","url":null,"abstract":"A recommender system is an information filtering tool that copes with the growing volume of information and helps the user to make faster decisions by providing products and services matched with their needs and interests. However, a large number of users are not satisfied with the provided recommendations and do not accept them. Based on the Elaboration Likelihood Model (ELM), If supplementary information about recommendations is provided, those users having the low motivation and capability to analyze the usefulness of the recommended item can be persuaded to accept it. This paper focuses on analyzing the impact of demographic factors on increasing the acceptance of recommendations. This study was conducted by a web-based online survey. The movie's recommender system has been developed along with the explanations based on Cialdini's persuasion strategies as the peripheral cues. The collected data are analyzed through statistical techniques using the SPSS software. The results show that the persuasiveness degree of the persuasion strategies differs related to individuals with the different demographic factors.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124854932","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: 3

Moving Target Defense Against Advanced Persistent Threats for Cybersecurity Enhancement 移动目标防御高级持续性威胁，增强网络安全

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566531

Masoud Khosravi-Farmad, Ali Ahmadian Ramaki, A. G. Bafghi

{"title":"Moving Target Defense Against Advanced Persistent Threats for Cybersecurity Enhancement","authors":"Masoud Khosravi-Farmad, Ali Ahmadian Ramaki, A. G. Bafghi","doi":"10.1109/ICCKE.2018.8566531","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566531","url":null,"abstract":"One of the main security concerns of enterprise-level organizations which provide network-based services is combating with complex cybersecurity attacks like advanced persistent threats (APTs). The main features of these attacks are being multilevel, multi-step, long-term and persistent. Also they use an intrusion kill chain (IKC) model to proceed the attack steps and reach their goals on targets. Traditional security solutions like firewalls and intrusion detection and prevention systems (IDPSs) are not able to prevent APT attack strategies and block them. Recently, deception techniques are proposed to defend network assets against malicious activities during IKC progression. One of the most promising approaches against APT attacks is Moving Target Defense (MTD). MTD techniques can be applied to attack steps of any abstraction levels in a networked infrastructure (application, host, and network) dynamically for disruption of successful execution of any on the fly IKCs. In this paper, after presentation and discussion on common introduced IKCs, one of them is selected and is used for further analysis. Also, after proposing a new and comprehensive taxonomy of MTD techniques in different levels, a mapping analysis is conducted between IKC models and existing MTD techniques. Finally, the effect of MTD is evaluated during a case study (specifically IP Randomization). The experimental results show that the MTD techniques provide better means to defend against IKC-based intrusion activities.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128262458","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: 4

Word Embedding in Small Corpora: A Case Study in Quran 小语料库中的词嵌入:以《古兰经》为例

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566605

Zeinab Aghahadi, A. Talebpour

{"title":"Word Embedding in Small Corpora: A Case Study in Quran","authors":"Zeinab Aghahadi, A. Talebpour","doi":"10.1109/ICCKE.2018.8566605","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566605","url":null,"abstract":"Text is a complex set of words to carry the meaning and representations of words is the first step to perform linguistic processing and text comprehension. So far, many researches have been done on the semantic representations of words using neural networks in various areas of natural language processing using large text corpus from general domain. In the meantime, some efforts have been done to apply deep learning methods to represent the words of small corpus supporting the hypothesis that the bigger corpora doesn't necessarily provide better results in words representation. In this research the capability of word2vec for learning semantic representation of words in small corpus is investigated. Here, we consider Skip-gram and CBOW learning models with different values of hyper parameters. Two new data sets have been created to evaluate the model's performance on the small domain-specific Quranic corpus. First and second datasets are used to test the words categorization and word pairwise similarity respectively. Our results demonstrate that the best performance for skip-gram occurs with 30 numbers of iterations when the dimension is set to 7.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129141089","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

Network Steganography Based on PVD Idea 基于PVD思想的网络隐写

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566629

V. Sabeti, Minoo Shoaei

引用次数: 1

Brain Tumor Classification via Convolutional Neural Network and Extreme Learning Machines 基于卷积神经网络和极限学习机的脑肿瘤分类

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566571

A. Pashaei, H. Sajedi, N. Jazayeri

{"title":"Brain Tumor Classification via Convolutional Neural Network and Extreme Learning Machines","authors":"A. Pashaei, H. Sajedi, N. Jazayeri","doi":"10.1109/ICCKE.2018.8566571","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566571","url":null,"abstract":"Tumor identification is one of the main and most influential factors in the identification of the type of treatment, the treatment process, the success rate of treatment and the follow-up of the disease. Convolution neural networks are one of the most important and practical classes in the field of deep learning and feed-forward neural networks that is highly applicable for analyzing visual imagery. CNNs learn the features extracted by the convolution and maxpooling layers. Extreme Learning Machines (ELM) are a kind of learning algorithm that consists of one or more layers of hidden nodes. These networks are used in various fields such as classification and regression. By using a CNN, this paper tries to extract hidden features from images. Then a kernel ELM (KELM) classifies the images based on these extracted features. In this work, we will use a dataset to evaluate the effectiveness of our proposed method, which consists of three types of brain tumors including meningioma, glioma and pituitary tumor in T1-weighted contrast-enhanced MRI (CE-MRI) images. The results of this ensemble of CNN and KELM (KE-CNN) are compared with different classifiers such as Support Vector Machine, Radial Base Function, and some other classifiers. These comparisons show that the KE-CNN has promising results for brain tumor classification.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124539193","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: 126

Salient Object Detection with Segment Features Using Mean Shift Algorithm 基于Mean Shift算法的分割特征显著目标检测

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566483

Narges Fatemi, H. Sajedi, M. Shiri

引用次数: 3

A Sensitivity Analysis on the Air Quality Index Based on the Pollutants Concentrations in Tehran 基于污染物浓度的德黑兰空气质量指数敏感性分析

2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2018-10-01 DOI: 10.1109/ICCKE.2018.8566657

Saba Fotouhi, M. H. Shirali-Shahreza, A. Mohammadpour

{"title":"A Sensitivity Analysis on the Air Quality Index Based on the Pollutants Concentrations in Tehran","authors":"Saba Fotouhi, M. H. Shirali-Shahreza, A. Mohammadpour","doi":"10.1109/ICCKE.2018.8566657","DOIUrl":"https://doi.org/10.1109/ICCKE.2018.8566657","url":null,"abstract":"As air pollution is one of the most serious global problems nowadays, this project tries to be a part of the studies in this field. Tehran as the capital city of Iran is one of the most polluted cities. This paper includes a sensitivity analysis on the calculation method of the Air Quality Index (AQI) for the whole city. The necessity to be able to analyze the air quality of the city needs a unique AQI for the whole city. Thus, three statistical indicators mean, median and maximum are compared in this paper to find out which of these indicators reports the number of days in each level of the AQI category more precisely in Tehran in the year 1395 (March/20/2016 - March/20/2017). Maximum is expected to be the best indicator but the results show that it is better to consider each pollutant separately for choosing the best indicator. However, maximum reports the air quality worse than what it really is, which leads to more caution. Simulation of the concentration of the pollutants was done by a hybrid model. The observed data of the concentration of the criteria pollutants were denoised by the wavelet transformation, then a neuro-fuzzy system using fuzzy clustering was used for modeling. The value of R2 for the models is almost 0.9 that is a sign of their accuracy.","PeriodicalId":283700,"journal":{"name":"2018 8th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128426081","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: 3