Improving OSI Layers Of Nano Network by Introducing Dynamic Routing
Mohsin Nazir, Laraib Sana, Sidra Zafar and Aneeqa Sabah, Lahore College for Women University, Pakistan.
With the passage of time, nano technology has become a mature discipline, which attracts attention of researchers toward nano communication. Nano nodes are tiny functional units that can perform simple task at nano scale. Nano network is the interconnection of nano nodes or machines that has expanded the capabilities and processing of single nano node. Wireless interconnection of these nano nodes can play a critical role in many applications. Wireless interconnection between these nano nodes is not possible with the help of traditional networking techniques. So it is required to develop new networking techniques for nano network, which are appropriate for nano nodes. Many techniques have been developed for interconnection between nano nodes like static routing, but these techniques do not address the issues related to dynamic network environment. This research work will address this issue by introducing dynamic routing technique.
- Unsupervised Detection Of Voilent Content In Arabic Social Media
Kareem E Abdelfatah1,3 ,Ayman A Alhelbawy2,3, Gabriel Terejanu1, 1University of South Carolina, USA, 2University of Essex, United Kingdom, 3Fayoum University, Fayoum, Egypt
A monitoring system is proposed to detect violent content in Arabic social media. This is a new and challenging task due to the presence of various Arabic dialects in the social media and the non-violent context where violent words might be used. We proposed to use a probabilistic non-linear dimensionality reduction technique called sparse Gaussian process latent variable model (SGPLVM) followed by k-means to separate violent from non-violent content. This framework does not require any labelled corpora for training. We show that violent and non-violent Arabic tweets are not separable using k-means in the original high dimensional space, however better results are achieved by clustering in low dimensional latent space of SGPLVM.
- Investigating Binary String Encoding for Compact Representation of XML Documents
Ramez Alkhatib, Hama University, Syria
Since Extensible Markup Language abbreviated as XML, became an official World Wide Web Consortium recommendation in 1998, XML has emerged as the predominant mechanism for data storage and exchange, in particular over the World Web. Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of application areas and new information is increasingly being encoded as XML documents. Because of the widespread use of XML and the large amounts of data that are represented in XML, it is therefore important to provide a repository for XML documents, which supports efficient management and storage of XML data. Since the logical structure of an XML document is an ordered tree consisting of tree nodes, establishing a relationship between nodes is essential for processing the structural part of the queries. Therefore, tree navigation is essential to answer XML queries. For this purpose, many proposals have been made, the most common ones are node labeling schemes. On the other hand, XML repeatedly uses tags to describe the data itself. This self-describing nature of XML makes it verbose with the result that the storage requirements of XML are often expanded and can be excessive. In addition, the increased size leads to increased costs for data manipulation. Therefore, it also seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In our previous works, we aimed at combining the advantages of both areas (labeling and compaction technologies), Specially, we took advantage of XML structural peculiarities for attempting to reduce storage space requirements and to improve the efficiency of XML query processing using labeling schemes. In this paper, we continue our investigations on variations of binary string encoding forms to decrease the label size. Also We report the experimental results to examine the impact of binary string encoding on reducing the storage size needed to store the compacted XML documents.
- Fault Tolerant Leader Election In Distributed Systems
Marius Rafailescu, Politehnica University, Romania.
There are many distributed systems which use a leader in their logic. When such systems need to be fault tolerant and the current leader suffers a technical problem, it is necesary to apply a special algorithm in order to choose a new leader. In this paper I present a new fault tolerant algorithm which elects a new leader based on a random roulette wheel selection.
- An Adaptive Bat Algorithm For Vehicle Routing Problem With Time Windows
Berghida Meryem, LSI Laboratory, Algeria
The VRPTW (Vehicle Routing Problem with Time Windows) consists of a fleet of vehicles which must serve a set of geographically dispersed customers, each with a known demand and a time window, during which it can be served. In this paper, we present a new adaptive approach (EDBA) to solve this problem. This approach named Discrete Bat Algorithm is improved by simulated annealing method. The results obtained in experimentation, for small and large instances, show the effectiveness of the proposed approach.
- Use Of Adaptive Coloured Petri Network In Support Of Decision-Making
Haroldo Issao Guibu1 and João José Neto2, 1Instituto Federal de Educação, Brazil, 2Escola Politécnica da Universidade de São Paulo, Brazil
This work presents the use of Adaptive Coloured Petri Net (ACPN) in support of decision making. ACPN is an extension of the Coloured Petri Net (CPN) that allows you to change the network topology. Usually, experts in a particular area can establish a set of rules for the proper functioning of a business or even a manufacturing process. On the other hand, it is possible that the same specialist has difficulty in incorporating this set of rules into a CPN that describes and follows the operation of the enterprise and, at the same time, adheres to the rules of good performance. To incorporate the rules of the expert into a CPN, the set of rules from the IF - THEN format to the extended adaptive decision table format is transformed into a set of rules that are dynamically incorporated to APN.
- Research on Information Security Risk Assessment Based on EM Algorithm and Bayesian Network Model
Yu Fan, China Changfeng Science Technology Industry Group Corp, China
Bayesian network (BN) has a strong advantage in dealing with uncertainty in the process of information security risk assessment. However, the conditional probability table (CPT) in this evaluation method is usually obtained by expert experience, which is lack of scientific and accuracy. Aiming at this problem, this paper proposes an information security risk assessment method based on EM algorithm for Bayesian network parameter learning. First of all, on the basis of studying the process and elements of information security risk assessment. A Bayesian network model for information security risk assessment is built. Secondly, optimized the CPT of the network model using EM algorithm according to the information from experts. Finally, through the simulation experiment, compared the results of risk assessment before and after learning Bayesian. It is shown that the conditional probability table after parameter learning is more accurate. The data is more consistent with the actual situation. To a certain extent, it enriches and improves the theory of information security risk assessment, and provides some reference value for the relevant personnel to take measures to prevent and resolve risks.