An Efficient RFID-based Tracking System for Airport Luggage
Authors :- Asmae Berrada and Yassine Salih-Alj
Keywords :- RFID, tracking, luggage, Airline system.
Published Online :- 14 December 2015

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    The emergence of new wireless technologies opened new opportunities to develop more efficient information systems. Radio Frequency Identification (RFID) is among those technologies, which extended the potential of wireless identification and present a potential replacement to old-fashioned identification schemes such as the barcode-based system. The suggested system in this paper considers an enhanced RFID–based approach to identify and track the location of passengers’ luggage. The use of an interactive bracelet that communicates with the RFID system by mean of a database application is investigated. The database application interacts with the bracelet using messages that inform the passenger about his luggage status. The proposed system design and implementation are discussed and the corresponding components are detailed with their interactions. Additionally, a draft cost analysis is presented.
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Developing CPDA schema in Privacy Preserving Data Aggregation for Wireless Sensor Networks
Authors :- Sadegh Gilani and Hadi Asharioun
Keywords :- wireless sensor network, Privacy preserving, Energy efficiency, Communications and Computing Overhead
Published Online :- 16 November 2015

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    Due to high traffic load data in sensor networks, low bandwidth wireless links as well as high energy consumption for packet transfer, data aggregation techniques to acquire needed resources and energy. Data aggregation is a mechanism used in wireless sensor and VANETs networking to reduce energy consumption and extend the life of sensor nodes by sending data with stronger signals and avoid repetitive data transmission to the base station. Privacy preserving data aggregation in the network because of dynamic topologies, power limitations, memory, sensors and wireless communications media that could be eavesdropping is a major challenge in the outgoing data network contains important information and is lightweight so, security Information on these networks is very important. Privacy integration protocols aimed at preventing disclosure of confidential information to adversaries through the influence of the link or node data, so for security inevitably incur the overhead of communications and computing will be more. This Cluster-based Private Data Aggregation (CPDA) scheme could aggregate data without revealing any private information and consume fewer resources than others. Simulation results show that using the proposed algorithms, efficient data aggregation privacy of communications and computing overhead and energy consumption in wireless sensor network is improved and thus extend the life of the sensor nodes.
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Enhancing the Performance of BitApriori Algorithm in Data Mining using an Effective Data Structure
Authors :- Abdolrashid Rezvani and Javad Hosseinkhani
Keywords :- Data Mining, Apriori Algorithm, Frequent Item sets, Association Rule Mining, Big Data
Published Online :- 14 December 2015

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    Exploration frequent item sets within transaction databases, time-series databases, and far different form of databases has been analyzed popularly within information exploration investigation. An exploration frequent merchandise unit is one of the nearly all investigated investigated areas within information exploration. Association rules will be the principal way of information exploration. Apriori algorithm is really an established algorithm associated with connection tip exploration. A lot of algorithms regarding exploration connection guidelines as well as the mutations are usually planned in basis associated with Apriori algorithm; One of these algorithms is the BitApriori algorithm. However, this algorithm reduces the time counting amount of support, but when the Database is big, BitApriori may be faced with a shortage of memory; Recently, an algorithm provided called Enhanced BitApriori that by replacing some effective techniques on binary string, improved BitApriori algorithm has somewhat. But this method can still be improved by eliminating infrequent item sets. Therefore, in this study, a method was developed using factors Set Size and Set Size Frequency minimum number of candidates is presented with greater efficiency. The results showed that the proposed method is more efficient than the Enhanced BitApriori algorithm.
  • View References

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    [7] Jaishree Singh, Hari Ram, Dr.J.S.Sodhi, “Improving efficiency of Apriori algorithm using Transaction Reduction” International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013 ISSN 2250-3153.
    [8] Shuo Yang, “Research and Application of Improved Apriori Algorithm to Electronic Commerce” 2012 11th International Symposium on Distributed Computing and Applications to Business, Engineering & Science, 978-0-7695-4818-0/12 $26.00 © 2012 IEEE DOI 10.1109/DCABES.2012.51
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Developing a Clustering Model based on K-Means Algorithm in order to Creating Different Policies for Policyholders in Insurance Industry
Authors :- Saeedodin Ghoreyshi and Javad Hosseinkhani
Keywords :- Health Insurance, Data Mining, Clustering, K-Means
Published Online :- 15 September 2015

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    Due to high competition in the sale of policies between insurance companies and climb increasing of demand for them, knowing the customers of these products is considered important in the maintenance and survival of insurance organizations. One of the important branches of insurance products is individual insurance policies, which is directly cover insurer’s life. Among individual insurance policies, health insurance policies because of diversity of coverages and contracts and high loss ratio are very important in insurance company. This study is considering the practical application of data mining in an insurance company on health insurance policy customers to investigate whether in this way can help insurance companies to identify different customer groups and their characteristics in order to make suitable patterns for offering suitable services to customers. In this way the maximum value of the relationship with the customer is achieved. In this research, the customers of health insurance policies have been clustered by means of some features. The Clustering was done using proposed algorithm based on k-Means algorithm. The proposed model has clustered data in four clusters which each cluster differ from others in terms of usefulness to the organization.
  • View References

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    [3] Hosseinkhani, Javad, Suriayati Chuprat, and Hamed Taherdoost. “Discovering criminal networks by Web structure mining.” Computing and Convergence Technology (ICCCT), 2012 7th International Conference on. IEEE, 2012.
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    [6] Thiemo Krink and Sandra Paterlini, “Differential Evolution and Particle Swarm optimization in Partitional Clustering”, Journal of Computational Statistics and Data Analysis, Vol. 50. No. 5, 2006.
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Medical Image De-Noising Schemes Using Different Wavelet Threshold Techniques
Authors :- Nadir Mustafa, Jiang Ping Li, Saeed Ahmed Khan and Mohamed Taj El sir
Keywords :- Bayes Wavelet threshold, Discrete Wavelet, Medical Image De noising, Magnetic Resonance Imaging (MRI).
Published Online :- 19 October 2015

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    In recent years most of researcher’s has done tremendous work in the field of medical image applications such as Magnetic Resonance Imaging (MRI), Ultra Sound, CT scan but still there are many research and experiments in medical imaging field and diagnosing of human health by health care institutes. There is a growing interest for medical imaging de-noising as hot area of research and also imaging equipment as a device, which is used for better image processing and highlighting the important features. These images are affected with random noise during acquisition, analysing and transmission process. This results in blurry image visible in low contrast. Wavelet transforms has effective method to separate the noise from original medical image by using threshold techniques without affecting the important data of image. Wavelet transform enables us to use the forward wavelet transform to represent sub band of original image in decomposition process then reconstructing this sub band coefficients to original image using inverse wavelet transform. In this work, the quality of medical image has been evaluated using filter assessment parameters like Variance, standard deviation, the squired difference error between original medical image & de-noised image (MSE) and the ratio between original image & noisy image that has been observed form the numerical results was an efficient de-noising of noisy medical image while investigating with bayes threshold techniques and achieved the best value of peak signal to noise ratio (PSNR). For best medical image de-noising, the wavelet based de-noising algorithm has been investigated and results of bayes techniques and hard & soft threshold methods have been compared [1][2].
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Internet of Things: Features, Challenges, and Vulnerabilities
Authors :- Ebraheim Alsaadi and Abdallah Tubaishat
Keywords :- Internet of things, denial of service attacks, eavesdropping, node capture, physical attack, vulnerabilities.
Published Online :- 13 February 2015

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    The terminology Internet of Things (IoT) refers to a future where every day physical objects are connected by the Internet in one form or the other, but outside the traditional desktop realm. The successful emergence of the IoT vision, however, will require computing to extend past traditional scenarios involving portables and smart-phones to the connection of everyday physical objects and the integration of intelligence with the environment. Subsequently, this will lead to the development of new computing features and challenges. The main purpose of this paper, therefore, is to investigate the features, challenges, and weaknesses that will come about, as the IoT becomes reality with the connection of more and more physical objects. Specifically, the study seeks to assess emergent challenges due to denial of service attacks, eavesdropping, node capture in the IoT infrastructure, and physical security of the sensors. We conducted a literature review about IoT, their features, challenges, and vulnerabilities. The methodology paradigm used was qualitative in nature with an exploratory research design, while data was collected using the desk research method. We found that, in the distributed form of architecture in IoT, attackers could hijack unsecured network devices converting them into bots to attack third parties. Moreover, attackers could target communication channels and extract data from the information flow. Finally, the perceptual layer in distributed IoT architecture is also found to be vulnerable to node capture attacks, including physical capture, brute force attack, DDoS attacks, and node privacy leaks.
  • View References

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How to Lead to Sustainable and Successful IT Project Management? Propose 5Ps Guideline
Authors :- Hamed Taherdoost and Abolfazl Keshavarzsaleh
Keywords :- IT Project Management, Success/Failure Factors, Risk Mitigation, Sustainable Project, Successful Project
Published Online :- 10 August 2015

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    Projects failure may negatively affect the whole implementing enterprise and there is empirical evidence that failure is a persistent trauma within project-oriented organizations. However, it is necessary to know why majority of IT projects fail and what the perceived success/failure factors are and to what extent the risk management concept is of central importance in every IT projects. This study aims to put spotlight on the importance of IT projects success/failure factors and IT project risk factors comprehensively according to literature review. Accordingly, it is proposed 5Ps (Presiding, People, Pragmatic, Process, and Performance) as preventative and proactive measures that IT project managers may consider in order to gain sustainable IT project management development processes. This research indicates how 5Ps consideration will lead to sustainable and successful IT project management.
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An Effective Web Mining-based Approach to Improve the Detection of Alerts in Intrusion Detection Systems
Authors :- Masoud Najjar Barghi and Javad Hosseinkhani
Keywords :- Intrusion Detection Systems, Web mining, Alarms Detection, Online Algorithm
Published Online :- 15 September 2015

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    The Internet and its applications are growing every day, so is the complexity and the number of cyber-attacks. Thus it is essential to use different security tools in order to protect computer systems and networks. Among these tools, Intrusion Detection Systems (IDSs) are one of the components of Defense-in-depth. One major drawback of IDSs is the generation of a huge number of alerts, most of which are false, redundant, or unimportant. Among different remedy approaches, many researchers proposed the use of data mining. Most of the research done in this area could not address the problems completely. Also, most of them suffer from human dependency and offline functionality. In this research, an online approach is proposed in order to manage alerts issued by IDSs. The proposed approach is able to process alerts produced by heterogeneous IDS systems. The approach is evaluated using DARPA 1999 dataset and Shahid Rajaee Port Complex dataset. Evaluation results show that the proposed approach can reduce the number of alerts by 94.32%, effectively improving alert management process. Because of the use of ensemble approach and optimal algorithms in the proposed approach, it can inform network security specialist the state of the monitored network in an online manner.
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