IJACSA Volume 1 Issue 2

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Paper 1: The effect of Knowledge Characteristics in students performances

Abstract: Knowledge characteristics are the essential step in leveraging knowledge value in the university. Share Document, and contributes knowledge may not be useful without the context provided by experience. This paper focuses on the characteristics of knowledge in applied science private university and its effect on student’s performance, which aim to focus in the nature knowledge and the quality of material. Questioner was designed and sent to MIS students in the applied sciences university in order to improve the context of the knowledge and facilitated the knowledge usage in order to improve the student knowledge level. The result lead recommends that the university should understand the knowledge characteristics and the potential techniques that support sharing knowledge. In addition the university should now which type of knowledge can by articulated or which knowledge can be taught to individuals, through training, practices or apprenticeship, in order to improve the student performance.

Author 1: Asmahan M. Altaher

Keywords: codify ability, Explicitness, Availability, Teach ability, student performance.

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Paper 2: A New Personalized Recommendation Technique Based on the Modified TOPSIS Method

Abstract: Personalized recommendation service helping users to target the interesting information from the excessive information set has been widely concerned. In this paper, we firstly propose a new method named Modified TOPSIS Method utilizing the Improved Gray Correlation Analysis Method. Then, we present a new personalized recommendation technique based on the Modified TOPSIS Method. Finally, the verification method utilizing Spearman’s Rank Correlation Coefficient demonstrates that our new personalized recommendation technique is efficient.

Author 1: Guan-Dao Yang
Author 2: Lu Sun

Keywords: Personalized Recommendation Technique; Improved Gray Correlation Analysis; Modified TOPSIS Method.

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Paper 3: Detection and Measurement of magnetic data for short length wireless communication using FT-IR

Abstract: Infrared (IR) radiation is a type of electromagnetic radiation. Infrared “light” has a longer wavelength than visible light. Red light has a longer wavelength than other colors of light, and infrared has even longer waves than red does; so infrared is sort of “redder-than-red” light or “beyond red” light. Infrared radiation lies between visible light and radio waves on the electromagnetic spectrum. In this paper, the infrared radiation is used for detecting the magnetic data for high speedy short range wireless communication. But infrared radiation may use in various way. This paper contains the performance of the FT-IR technique that is for multiplexing the transmissions of different users are viewed at the same time.

Author 1: Abu Saleh

Keywords: FT; FT-IR; Spectrum; prism.

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Paper 4: A Novel and Efficient countermeasure against Power Analysis Attacks using Elliptic Curve Cryptography

Abstract: Recently, there is a leakage in the communication channel information by the cryptographic processors. It is the major chore to overcome the pouring out or spreading out of the secure data. In this paper, a new level of security analysis model is constructed in power analysis using Elliptic Curve Cryptography. And so many side channel attacks and their countermeasures are explained undeniably. An algorithm design based on power analysis is also described and it makes our countermeasure more secure against simple power analysis, differential power analysis and other attacks. The theoretical analysis based on these result has been shown and it represents how the algorithm design should fluctuate from the facade side channel attacks.

Author 1: M Prabu
Author 2: R.Shanmugalakshmi

Keywords: component Simple Power Analysis, Differential Power Analysis, Security Analysis Model, Algorithm design, Side Channel Attacks

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Paper 5: Dynamic path restoration for new call blocking versus handoff call blocking in heterogeneous network using buffers for QoS

Abstract: An Ad hoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any existing heterogeneous network infrastructure or centralized administration. Routing protocols used inside ad hoc networks must be prepared to automatically adjust to an environment that can vary between the extremes of high mobility with low band width, and low mobility with high bandwidth The tremendous growth of wireless networks demands the need to meet different multimedia (such as voice audio, video, data, etc) applications available over the network. This application demand and allocation could lead to congestion if the network has to maintain such high resources for the quality of service (QoS) requirements of the applications. In this paper, a new Protocol is proposed for wireless mobile heterogeneous networks are based on the use of. path information, traffic and bandwidth resource information at each node, for allocation of route path and Handoff problem. The proposed protocol uses two buffers one for new call and another buffer is use for handoff calls if there is no channel available instead of dropping (rejecting) them it store in the buffer and when ever the channel is free it allocate for communication The protocol improved the performance of the network especially by the effect of the dynamic threshold of buffer size of new call buffer and handoff call buffer In the link failure situation we provide another path for the communication by applying a Restoration Mechanism for the survivability of link and improved the QoS of mobile network .

Author 1: Ajai Kumar Daniel
Author 2: R Singh
Author 3: J P Saini

Keywords: Handoff call, New call buffer, Congestion, Heterogeneous network, Quality of Service (QoS),

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Paper 6: PATTERN BASED SUBSPACE CLUSTERING: A REVIEW

Abstract: The task of biclustering or subspace clustering is a data mining technique that allows simultaneous clustering of rows and columns of a matrix. Though the definition of similarity varies from one biclustering model to another, in most of these models the concept of similarity is often based on such metrics as Manhattan distance, Euclidean distance or other Lp distances. In other words, similar objects must have close values in at least a set of dimensions. Pattern-based clustering is important in many applications, such as DNA micro-array data analysis, automatic recommendation systems and target marketing systems. However, pattern-based clustering in large databases is challenging. On the one hand, there can be a huge number of clusters and many of them can be redundant and thus makes the pattern-based clustering ineffective. On the other hand, the previous proposed methods may not be efficient or scalable in mining large databases. The objective of this paper is to perform a comparative study of all subspace clustering algorithms in terms of efficiency, accuracy and time complexity.

Author 1: Debahuti Mishra
Author 2: Shruti Mishra
Author 3: Sandeep Satapathy
Author 4: Amiya Kumar Rath
Author 5: Milu Acharya

Keywords: Subspace clustering; Biclustering; p-cluster; z-cluster

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Paper 7: Real-time Facial Emotion Detection using Support Vector Machines

Abstract: There have been continuous researches in the field of emotion detection through faces of biological species in the last few decades. This was further fuelled by the rise of artificial intelligence which has added a new paradigm to its ongoing research. This paper discusses the role of one of the artificial intelligence techniques, Support vector machines for efficient emotion detection. This study comprised of experiments conducted on Java platform by using libsvm. The coordinates of vital points of a face have been used for training the SVM network which finally led to proper identification of various emotions appearing on a human face.

Author 1: Anvita Bajpai

Keywords: Emotion-Detection;Facial-expressions; libsvm; Support Vector Machines; Facial action coding system(FACS)

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Paper 8: On-line Rotation Invariant Estimation and Recognition

Abstract: Rotation invariant estimation is an important and computationally difficult process in the real-time human computer interaction. Our new methodologies propose here for on-line image rotation angle estimation, correction and feature extractions based on line integrals. We reveal that a set of projection data of line integrals from single (fan-arc and fan-beam) or multi point sources (Radon transform) are employed for orientation estimation. After estimating orientation, image angle variations are altered to its principal direction. We further combine Boltzmann machine and k-mean clustering to obtain parameter optimized Gabor filters, which are used to extract non-redundant compact set of features for classification. The proposed method of fan-line, fan-arc and Radon transform are compared for real-time image orientation detection. Accuracy of classification is evaluated with the classifiers viz., back propagation, Hamming neural network, Euclidean-norm distance, and k-nearest neighbors. Experiment on a database of 535 images consisting of license plate and iris images. The viability of suggested algorithms has been tested with different classifiers. Thus, this paper proposes an efficient rotation invariant recognition for on-line images recognition.

Author 1: R Bremananth
Author 2: Andy W. H. Khong
Author 3: M. Sankari

Keywords: Feature extraction; Line integrals; Orientation-detection; Optimized Gabor filters; Rotation-invariant recognition; Radon transform.

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Paper 9: RSS-Crawler Enhancement for Blogosphere-Mapping

Abstract: The massive adoption of social media has provided new ways for individuals to express their opinions online. The blogosphere, an inherent part of this trend, contains a vast array of information about a variety of topics. It is a huge think tank that creates an enormous and ever-changing archive of open source intelligence. Mining and modeling this vast pool of data to extract, exploit and describe meaningful knowledge in order to leverage structures and dynamics of emerging networks within the blogosphere is the higher-level aim of the research presented here. Our proprieteary development of a tailor-made feed-crawler-framework meets exactly this need. While the main concept, as well as the basic techniques and implementation details of the crawler have already been dealt with in earlier publications, this paper focuses on several recent optimization efforts made on the crawler framework that proved to be crucial for the performance of the overall framework.

Author 1: Justus Bross
Author 2: Patrick Hennig
Author 3: Philipp Berger
Author 4: Christoph Meinel

Keywords: weblogs, rss-feeds, data mining, knowledge discovery, blogosphere, crawler, information extraction

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