{"title":"A method for Content-Based Image Retrieval using visual attention model","authors":"Mostafa Mohammadpour, S. Mozaffari","doi":"10.1109/IKT.2015.7288764","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288764","url":null,"abstract":"In this paper we present a new method for Content-Based Image Retrieval, in which regions of interest (ROIs) are being extracted from images using visual attention models. After finding salient map of regions in image, which humans pay attention to those region, we calculate Histogram of Orientation Gradient (HoG) and some useful features for those regions to make a feature vector in order using in retrieval process. Whereas Saliency Detection finds important regions in image, but it is insufficient to compare two objects, Because two objects may have different color, orientation and some of another aspect. For this we use those features to make a similarity measure to take account another aspect similarity between two objects. The experimental results demonstrated that the proposed method which uses those features to seek image in a database more efficiently rather than traditional methods.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127461054","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}
{"title":"Reengineering Purchase Request process of TAM Iran Khodro Company using Best Practices","authors":"S. H. Siadat, Simin Maleki Shamasbi","doi":"10.1109/IKT.2015.7288804","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288804","url":null,"abstract":"This research focuses on using Business Process Reengineering Best Practices in order to improve the purchase request of TAM as an EPC Company, revealing their impact on performance indicators of time, cost, quality and flexibility. This study aims to redesign the Purchase Request process, using Sharp & McDermott methodology. First, the process map is depicted considering APQC-PCF standard and SAP Solution Composer tools. Purchase request process was chosen to be redesigned due to TAM strategies as an EPC Company and the main drivers extracted by monitoring the process regarding the enablers. In order to depict the as-is and to-be models, BPMN standard and Bizagi Process Modeler tools have been used; However, because of the necessity of speed and agility in the process, time has been considered as the most important criteria and the to-be process has been modeled so as to accelerate the process. 12 candidate best practices include order type, task elimination, triage, parallelism, exception, numerical involvement, case manager, extra resources, specialist-generalist, control addition, integral technology and task automation. The selection of these best practices was done regarding literature review, monitoring the process and interviews with TAM experts and managers. The expected impact of BPR and each best practice has been shown on time, cost, quality and flexibility. This case can be studied and referenced so as to clarify the proper use of BPR best practices on one of the core processes of an EPC Company.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"52 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114128438","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}
{"title":"K-means++ for mixtures of von Mises-Fisher Distributions","authors":"Mohamadreza Mash'al, Reshad Hosseini","doi":"10.1109/IKT.2015.7288786","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288786","url":null,"abstract":"Von Mises-Fisher (vMF) Distribution is one of the most commonly used distributions for fitting directional data. Mixtures of vMF (MovMF) distributions have been used successfully in many applications. One of the important problems in mixture models is the problem of local minima of the objective function. Therefore, approaches to avoid local minima problem is essential in improving the performance. Recently, an algorithm called k-means++ was introduced in the literature and used successfully for finding initial parameters for mixtures of Gaussian (MoG) distributions. In this paper, we adopt this algorithm for finding good initializations for MovMF distributions. We show that MovMF distribution will lead to the same cost function as MoGs and therefore similar guarantee as the case of MoG distributions will also hold here. We also demonstrate the performance of the method on some real datasets.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131292224","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}
{"title":"Determining the best proportion of music genre to be played in a radio program","authors":"M. Keshtkar, A. Bastanfard","doi":"10.1109/IKT.2015.7288794","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288794","url":null,"abstract":"In this paper a scheme for a monitoring system is proposed that can determine the best proportion of music genre to be played in a radio program based on music genre variety and audience feedback. An audio fingerprinting algorithm has been used to determine the music genres played through a radio program. This method is noise and distortion resistant and very scalable. Moreover a feedback system has been employed to gather feedback from audience. Finally an evaluation is presented by observing the data from both steps. To find the proper proportion, the proportion of music genres was changed each time and monitored the system thoroughly to see whether the results change or not. In this approach, the audience behavior can be monitored in music listening and the best proportion of music genre will be determined with a quite good accuracy as well.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490655","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}
{"title":"Intrusion detection system based on Multi-Layer Perceptron Neural Networks and Decision Tree","authors":"J. Esmaily, R. Moradinezhad, J. Ghasemi","doi":"10.1109/IKT.2015.7288736","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288736","url":null,"abstract":"The growth of internet attacks is a major problem for today's computer networks. Hence, implementing security methods to prevent such attacks is crucial for any computer network. With the help of Machine Learning and Data Mining techniques, Intrusion Detection Systems (IDS) are able to diagnose attacks and system anomalies more effectively. Though, most of the studied methods in this field, including Rule-based expert systems, are not able to successfully identify the attacks which have different patterns from expected ones. By using Artificial Neural Networks (ANNs), it is possible to identify the attacks and classify the data, even when the dataset is nonlinear, limited, or incomplete. In this paper, a method based on the combination of Decision Tree (DT) algorithm and Multi-Layer Perceptron (MLP) ANN is proposed which is able to identify attacks with high accuracy and reliability.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129221959","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}
{"title":"A comprehensive mobile e-healthcare system","authors":"Qasim Majeed, Hayder Hbail, A. Chalechale","doi":"10.1109/IKT.2015.7288802","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288802","url":null,"abstract":"Bio-sensors and communication devices like smart phones witnessed significant progress, to take this advances, we propose a mobile heath-care system that reduce the distance between the patient and the health care center especially for the patient that need long term nursing care. This mobile system provide a good monitoring system for the patient in outdoor and indoor. The system is divided into two part, the first is a mobile phone application installed on a smart phone that connected with Bio-sensors, the second is a data base center that connected with different health-care center and then the ambulance center. The application record the Bio-signals from sensors and decide the patient status, send important information to the center, then add it to the patient's history that can accessed by the physician from any where.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134082937","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}
{"title":"A new method for saliency detection using top-down approach","authors":"Mostafa Mohammadpour, S. Mozaffari","doi":"10.1109/IKT.2015.7288763","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288763","url":null,"abstract":"In this paper, we propose a visual saliency detection algorithm which used a learning method. In this model, we train a dictionary for twenty objects from Pascal VOC dataset and then we estimate saliency objects with project each image patch into the space of a dictionary of image patches (basis functions) learned from Pascal VOC dataset. We evaluate our method performance on two dataset along side state-of-the-art saliency detection methods and experimental results show that the proposed saliency model outperforms state-of-the-art saliency models.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130063019","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}
{"title":"A new immunization algorithm based on spectral properties for complex networks","authors":"R. Zahedi, M. Khansari","doi":"10.1109/IKT.2015.7288754","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288754","url":null,"abstract":"Nowadays, we are facing epidemic spreading in many different areas; examples are infection propagation, rumor spreading and computer viruses in computer networks. Finding a strategy to control and mitigate the spread of these epidemics is gaining much interest in recent researches. Due to limitation of immunization resources, it is important to establish a strategy for selecting nodes which has the most effect in mitigating epidemics. In this paper, we propose a new algorithm that minimizes the worst expected growth of an epidemic by reducing the size of the largest connected component of the underlying contact network. The proposed algorithm is applicable to any level of available resources and, despite the greedy approaches of most immunization strategies, selects nodes simultaneously. In each iteration, the proposed method partitions the largest connected component into two groups. These are the best candidates for communities in that component, and the available resources are sufficient to separate them. Using Laplacian spectral partitioning, the proposed method performs community detection inference with a time complexity that rivals that of the best previous methods. Experiments show that our method outperforms targeted immunization approaches in real networks.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"251 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114544563","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}
{"title":"Detection of black hole attack in wireless sensor network using UAV","authors":"Maryam Motamedi, N. Yazdani","doi":"10.1109/IKT.2015.7288749","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288749","url":null,"abstract":"Recently, unmanned aerial vehicles (UAVs) has been proposed for effective data propagation and collection in wireless sensor networks (WSNs). In this paper, we use UAV for detecting black hole attack in WSN. Black hole attack is accomplished by malicious nodes that advertise their route to the intended destination as the shortest and optimized one, therefore, they gather most of the network traffic and then drop all packets. This attack results in loss of critical information on the network. We propose a method to overcome this problem with a shorter running time in comparison to other methods and detect malicious nodes with higher probability. UAV is used for checking nodes and Sequential Probability Ratio Test method as a dynamic threshold scheme for blocking malicious nodes. Simulations and analyses show that our proposed technique achieves effective and fast detection of black hole attack with acceptable energy consumption.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121937621","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}
{"title":"A sound framework for dynamic prevention of Local File Inclusion","authors":"M. S. Tajbakhsh, J. Bagherzadeh","doi":"10.1109/IKT.2015.7288798","DOIUrl":"https://doi.org/10.1109/IKT.2015.7288798","url":null,"abstract":"Web applications take an important role in remote access over the Internet. These applications have many capabilities such as database access, file read/write, calculations as well as desktop applications but run in web browsers environments. As desktop applications, web applications can be exploited but with different techniques. One of the major known vulnerabilities of the web applications is Local File Inclusion. Inclusion in web applications is similar to library imports in desktop applications where a developer can include former developed codes. If an attacker includes his/her libraries, he/she can run his/her malicious code. Current research makes a brief survey of static and dynamic code analysis and suggests a framework for dynamically preventing malicious file inclusions by attackers. It is discussed that this framework prevents local file inclusions even if the developer has exploitable source code. The language PHP is used for describing the vulnerability and prevention framework.","PeriodicalId":338953,"journal":{"name":"2015 7th Conference on Information and Knowledge Technology (IKT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130958513","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}