An Introduction to MultiAgent Systems.

Recent years has witnessed growing interest in hyperspectral image (HSI) processing. In practice, however, HSIs always suffer from huge data size and mass of redundant information, which hinder their application in many cases. HSI compression is a straightforward way of relieving these problems. However, most of the conventional image encoding algorithms mainly focus on the spatial dimensions, and they need not consider the redundancy in the spectral dimension. In this paper, we propose a novel HSI compression and reconstruction algorithm via patch-based low-rank tensor decomposition (PLTD). Instead of processing the HSI separately by spectral channel or by pixel, we represent each local patch of the HSI as a third-order tensor. Then, the similar tensor patches are grouped by clustering to form a fourth-order tensor per cluster. Since the grouped tensor is assumed to be redundant, each cluster can be approximately decomposed to a coefficient tensor and three dictionary matrices, which leads to a low-rank tensor representation of both the spatial and spectral modes. The reconstructed HSI can then be simply obtained by the product of the coefficient tensor and dictionary matrices per cluster. In this way, the proposed PLTD algorithm simultaneously removes the redundancy in both the spatial and spectral domains in a unified framework. The extensive experimental results on various public HSI datasets demonstrate that the proposed method outperforms the traditional image compression approaches and other tensor-based methods.

PLTD: Patch-Based Low-Rank Tensor Decomposition for Hyperspectral Images

In teleradiology, image contents may be altered due to noisy communication channels and hacker manipulation. Medical image data is very sensitive and can not tolerate any illegal change. Illegally changed image-based analysis could result in wrong medical decision. Digital watermarking technique can be used to authenticate images and detect as well as recover illegal changes made to teleradiology images. Watermarking of medical images with heavy payload watermarks causes image perceptual degradation. The image perceptual degradation directly affects medical diagnosis. To maintain the image perceptual and diagnostic qualities standard during watermarking, the watermark should be lossless compressed. This paper focuses on watermarking of ultrasound medical images with Lempel-Ziv-Welch (LZW) lossless-compressed watermarks. The watermark lossless compression reduces watermark payload without data loss. In this research work, watermark is the combination of defined region of interest (ROI) and image watermarking secret key. The performance of the LZW compression technique was compared with other conventional compression methods based on compression ratio. LZW was found better and used for watermark lossless compression in ultrasound medical images watermarking. Tabulated results show the watermark bits reduction, image watermarking with effective tamper detection and lossless recovery.

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Watermark Compression in Medical Image Watermarking Using Lempel-Ziv-Welch (LZW) Lossless Compression Technique.

Data processing with multiple domains is an important concept in any platform; it deals with multimedia and textual information. Where textual data processing focuses on a structured or unstructure...

Review of video compression techniques based on fractal transform function and swarm intelligence

Image compression is an implementation of the data compression which encodes actual image with some bits. Thepurpose of the image compression is to decrease the redundancy and irrelevance of image data to be capable to record or send data in an effective form. Hence the image compression decreases the time of transmit in the network and raises the transmission speed. In Lossless technique of image compression, no data get lost while doing the compression. To solve these types of issues various techniques for the image compression are used. Now questions like how to do mage compression and second one is which types of technology is used, may be arises. For this reason commonly two types’ of approaches are explained called as lossless and the lossy image compression approaches. These techniques are easy in their applications and consume very little memory. An algorithm has also been introduced and applied to compress images and to decompress them back, by using the Huffman encoding techniques.

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Various Image Compression Techniques: Lossy and Lossless

Software development projects still of high failure rates. Different risk management approaches are recommended by researchers and followed by organizations in order to control this failure rate. Current research is focused towards preventive risk management approach that improves the development process. In this study, we introduce a framework that enhances this approach. This framework describes a systematic method towards enhancing preventive risk management throughout the software development process. In this study, we devised sets of risk management strategies and controls that aim at mitigating each of the identified risks in the adapted list. These strategies besides the identified risk factors are utilized and embedded in the right corresponding Software Development Life Cycle phase to construct our preventive framework.

A Framework for Integrating Risk Management into the Software Development Process

In a multi-organization environment like the GRID, each institute might want to apply some boundaries on how its resources are being utilized by other institutes. A disagreement between the multi-Virtual Organizations (VOs) might happen in the security aspect for the policy framework. Mobile Grid Services has given the ability to move jobs, data and application software from nodes to nodes during jobs’ execution in the grid environment. It has also solved some of the lack in finding suitable resources for the jobs. To facilitate the ability to support mobile resource sharing between multiple heterogeneous VOs, an authorization policy management framework is needed to support authorization for heterogeneous authorization systems. Traditional authorization policy management frameworks act well in authorization policy for a single VO where the contributing hosts grant the permission to follow a global authorization system. However most of policy management tools do not provide a clear support for sharing mobile resources between multiple heterogeneous VOs. To solve this problem, we present a dynamic and heterogeneous policy management framework that can give a clear policy definition about the ability to move jobs, data and application software from nodes to nodes during jobs’ execution in the grid environment. We introduce an architecture for policy based resource management in the case of mobile sharing, and a scenario that explain the advantages of mobility mechanism and the role of policy in the grid systems. To check the performance of this architecture, a set of experiments had conducted. The results, analysis and the overheads estimation are presented in this journal.

Policy-Based Support for Mobile Grid Services

DGA-based botnets detection using DNS traffic mining

Software development process is vulnerable to different risk factors. Several works were done in order to identify these factors and to introduce new ones. On the other hand, little research has been conducted around investigating the relationship between these risk factors. In this paper, a detailed set of software risk factors were examined. It was found that the relationship between these factors is a (cause- effect) relationship. As a result, a causality table and a cause-effect diagram are introduced to illustrate this causality relationship.

Identifying Causality Relation between Software Projects Risk Factors

One of the major challenges of the Service Oriented Computing (SoC) paradigm is the Web service discovery. Yet the mechanisms used to match Web services can be improved. However, considering the semantics of the Web service descriptions is a must for automating the process of discovering Web services. We have proposed a semantic-based Web service discovery algorithm that consists of two stages: The registry filtering stage and the descriptions matching stage. The aim of the first stage is to pick the advertisements that are relevant to the client request and ignore, from an early stage and before checking the details of the descriptions, the advertisements that are not able to satisfy the client request. However, the aim of the second stage is to check whether or not the relevant advertisements resulted from the registry filtering stage are actually able to satisfy the client query. This paper concerns the first stage. More precisely, we propose a semantic-based Web service registry filtering mechanism that takes the responsibility of narrowing down the number of Web service descriptions to be checked in detail to the number of only the relevant advertisements to the client request. We also propose an extension to Web Ontology Language for Services (OWL-S). With this extension, filtering the Web service registry based on the semantics of the available descriptions is possible.

Thair Khdour

Papers

A Framework for Integrating Risk Management into the Software Development Process

Policy-Based Support for Mobile Grid Services

DGA-based botnets detection using DNS traffic mining

Identifying Causality Relation between Software Projects Risk Factors

Towards Semantically Filtering Web Services Repository