Information Technology

Automated extraction of popular news from the freely accessible news corpora is becoming important in today’s internet world. Because of the availability of large volumes of news wire sources, it is hectic for the human beings to search and decide whether it is popular or not. This necessitates a tool which should extract hot news in a period of time. Term weighting is a useful technique which extracts salient features from the text documents. Though, there exist different tools based on different term weighting algorithms, these are inaccurate in the extraction of hot news. In this paper, a new feature extraction algorithm for long running events based on frequency, position, scattering and topicality is proposed. Experimentation has been done on different retrospective news wire sources. Experimental results demonstrate that the proposed algorithm is suitable for extracting hot news.

Software effort estimation is an important area in the field of software engineering. If the software effort is over estimated it may lead to tight time schedules and thus quality and testing of software may be compromised. In contrast, if the software development effort is underestimated it may lead to over allocation of man power and resource. There are many models for estimating software effort. The aim of the work is to estimate software effort using various machine learning techniques like Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Inference System (ANFIS), and Decision Tree (DT). China dataset of software projects has been used in order to compare the performance results obtained from these models. The indices are Sum-Square-Error (SSE), Mean-Square-Error (MSE), Root-Mean-Square-Error (RMSE), Mean-Magnitude-Relative-Error (MMRE), Relative-Absolute-Error (RAE), Relative-Root-Square-Error (RRSE), Mean-Absolute-Error (MAE), Correlation Coefficient (CC), and PRED (25).

The security of cloud users, a few proposals have been presented recently. Core objective of using cloud is to provide Security, Scalability, Availability, Performance, and Cost effective. A Safe Cloud Storage to provide con?dentiality and fine-grained access control for data stored in the cloud. This system enables the users to enjoy a secure outsourced data services at a minimized security management overhead. Here outsources not only the data but also the security management to the cloud in a trust way. Our system is fully integrates with Encryption , storing and retrival operations. Propose a threshold proxy re-encryption scheme and it integrates with decentralized erasure code such that a secure distributed system is formulated. Analyze and suggest appropriate limitations for the number of copies of a message transmitted to storage servers and the number of storage servers queried by a key server. These restrictions allow more flexible regulation between the number of storage servers and robustness.

Face recognition is major challenge and provides significant attention of research in the computer vision. In recent years, reliable automated face recognition has become a realistic target of biometrics research. This biometrics will provide identity and verification of the person. The objective of face recognition involves the extraction of different features of the human face from the face image which makes it different from the other persons. In this, we give a review on face recognition system and the various classifications of recognition methods. This paper will also contain the various techniques, like PCA, LDA etc, which are used in the recognition of the face.

In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis) methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis) has less error and system worked more accurate and appropriative than prior methods.

Reliable accelerator operation requires control system with higher level of automation, flexibility, robustness, and optimisation. In this paper a multi-agent system based control scheme is presented for optimal control of accelerator system that improves the plant performance in wide-range of operations. The multi-agent based control schemes for accelerators have been reported in literature. But the scheme proposed in this paper differs significantly form the existing schemes. In this work the agent architecture is formulated based on the control requirements of pre-injector accelerator subsystem (Microtron in particular) and transport line of synchrotron radiation sources. The scheme consists of two software agents at supervisory level that work in an autonomous manner for the optimized control of dynamic system. The Microtron agent architecture augments model assisted adaptive controller for realizing feedback control action at lower layer and goal based logic controller with pre-structure model identifier along with the pattern recognizer at supervisory layer. The TL-1 agent has a model-based, goal-based modular architecture and optimizes the TL-1 control using differential evolution based algorithm. The simulation results of applying this scheme to model of Microtron and Transport Line-1 of INDUS complex shows that this approach is very effective in optimizing the Microtron and TL-1 tuning.

This study aimed to assess and rank the quality of central library websites of government universities in Iran based on the fuzzy deduction system. Statistical society includes independent central library websites of government universities in Iran (n=55) that were managed by Ministry of Science, Research and Technology. A survey method research was used for the aim of the study. Moreover, a check list and MATLAB Software were used. Among content criteria, website title was the most important one and among structural criteria, searching in continuous catalogue of the library was the most significant. Classic assessment of findings showed that central library websites of University of Shahed and Sahand University of Technology had the highest quality; on the contrary, central library websites of (Shahid Abbaspour) Power & Water University of Technology and Gorgan University of Agricultural Science and Natural Resources had the lowest quality. Findings of fuzzy deduction system showed that central library website of University of Shahed had the highest quality; however, central library website of (Shahid Abbaspour) Power & Water University of Technology had the lowest quality among other websites. Comparison of classic assessment and fuzzy assessment of central library websites of Iran showed that in an assessment based on the fuzzy deduction system, more precise results are obtained and websites are correctly ranked. In addition, websites can be ranked based on low, medium and high quality. Therefore, it seems that fuzzy deduction system is a better method for assessing and ranking the quality of university library websites. Keywords: Fuzzy Logic; Central Library Website; Applied System, Government Universities, Library Website

IT organizations can now outsource computer hardware by leasing CPU time through cloud computing services. The problem here is the effectiveness is becoming less due to burden on single cloud while working with MTC applications .This paper deals with defining the feasible solutions with MTC applications using the programming models for computing over a Multi clouds instead of single cloud for effectiveness.

Security systems are basically based on authentication process. It is being more secure using different approaches. Verity of security systems is available in market but, they uses conventional scheme for identification of a person for an authentication process. Authentication is based on identification process. Recently signals like EEG and ECG called physiological signal of a human is a famous subject for the researcher. Many systems are being developed using this unique human characteristic. It is very hard to copy and universal for every human kind. In experiment for person identification method uses EEG signal, Wavelet Packet Decomposition (WPD) for feature extraction and Self-organizing map (SOM) as a classifier.

There are many researches that have been proposed for embedding data into digital video. However, most of those schemes extending data hiding technique for still images to videos by treating each single frame as a still image and embed data in intra-frame. In this paper, we propose an effective data-hiding scheme that embeds data in digital videos using the phase angle of the motion vector of the macro blocks in the inter-frame. The scheme can be applied to either compressed or uncompressed videos. Furthermore, the embedded data can be extracted directly without using the original video sequences. Our experimental results prove the feasibility of the proposed method. The method is implemented and tested for hiding data in natural sequences of multiple groups of pictures and the results are evaluated. The evaluation is based on two criteria: minimum distortion to the reconstructed video and minimum overhead on the compressed video size. Based on the aforementioned criteria, the proposed method is found to perform well and is compared to a motion vector attribute-based method from the literature.