Ad hoc network consists of a set of identical nodes that move freely and independently and communicate among themselves via wireless links. The most interesting feature of this network is that they do not require any existing infrastructure of central administration and hence is very suitable for temporary communication links in an emergency situation. This flexibility, however, is achieved at a price of communication uncertainty induced due to frequent topology changes. In this article, we have tried to identify the system dynamics using the proven concepts of time series modeling. Here, we have analyzed variation of link utilization between any two particular nodes over a fixed area for differentmobility patterns under different routing algorithm. We have considered four different mobility models – (i) Gauss-Markov mobility model, (ii) Manhattan Grid Mobility model and (iii) Random Way Point mobility model and (iv) Reference Point Group mobility model. The routing protocols under which, we carried out our experiments are (i) Ad hoc On demand Distance Vector routing (AODV), (ii) Destination Sequenced Distance Vector routing (DSDV) and (iii) Dynamic Source Routing (DSR). The value of link load between two particular nodes behaves as a random variable for any mobility pattern under a routing algorithm. The pattern of link load for every combination of mobility model and for every routing protocol can be well modeled as an autoregressive model of order p i.e. AR(p). The order of p is estimated and it is found that most of them are of order 1 only.

Management of mobility especially balancing the load of handoff for wireless networks is an essential parameter for wireless network design and traffic study. In this paper, we present analytical mobility management in high speed wireless mobile networks focusing on factors such as the number of channel slots and offered load. We demonstrate the performance of handoffs with mobility consideration using several metrics including the alteration of states prior to reaching a cell boundary, the speed of mobile terminal, and the distance between a mobile terminal and a cell boundary. We mainly focus on the performance evaluation for the factor of mobility with taking into account the high speed status of a user.

Cluster analysis was used to create segments of high school graduates based on their motivations/opinions regarding their future education. Data for this study were collected using a questionnaire distributed to high school graduates following State Matura exam. The students were asked to evaluate the importance of 13 different reasons/causes for choosing the faculty selected as their first choice. The analysis yielded five meaningful clusters of students that differ not only in motivations, but also in achievement on State Matura exams and in their preference regarding the scientific field of their future study.

Many real-time applications enable RESET to account for all kinds of unexpected problems, or to accommodate for a users’ want of restarting. Additionally, some software testing techniques must allow for resetting timed-Implementations Under Test (t-IUT). Dedicated internal logic is probably the most common of solutions for accomplishing such tasks. There are situations, however, where such a privilege doesn’t exist; thus, it cannot be built upon. Testing pre-engineered timed-IUTs is one such case. In this paper we wish to present an algorithm for the direct generation of timed RESET sequences from the timed-IUT specification, such that it should be optimal w.r.t. to execution time.

This paper proposes two scheduling approaches, one-level and two-level scheduling, for synchronous periodic real-time task sets based on the Imprecise Computation Model. The imperative of real-time systems is a reaction on an event within a limited amount of time. Sometimes the available time and resources are not enough for the computations to complete within the deadlines, but still enough to produce approximate results. The Imprecise Computation Model is motivated by this idea, which gives the flexibility to trade off precision for timeliness. In this model a task is logically decomposed into a mandatory and optional subtask. Only the mandatory subtask is required to complete by its deadline, while the optional subtask may be left unfinished. Usually, different scheduling policies are used for the scheduling of mandatory and optional subtasks. For both proposed approaches the earliest deadline first and rate monotonic scheduling algorithms are used for the scheduling of mandatory subtasks, whereas the optional subtasks are scheduled in a way that the total weighted error is minimized. The basic idea of one-level scheduling is to extend the mandatory execution times, while in two-level scheduling the mandatory and optional subtasks are separately scheduled. The single preemptive processor model is assumed.

Improving the performance of the Mobile Ad hoc NETworks (MANETs) is a challenge. MANETs present several constraints such as dynamic topology, wireless link communication and limited resources like bandwidth and energy. Routing without taking into account these constraints degrades performance and aggravates congestion problem. This paper proposes a new solution combining QoS (Quality of Service) routing protocol and flow control mechanism. This QoS routing protocol selects the routes with more resources in an intelligent manner rather than diffusion. It returns the best route offering a higher transmission rate, a less delay and a more stability. This protocol uses a new metric to compute the most stable route. To reinforce the congestion avoidance, we add a flow control mechanism to adjust the sender's transmission rate for each route. The solution is modeled by the ant systems. The results obtained under the Network Simulator (NS2.31) show that our QoS routing protocol improves the network performance compared to QoS-AODV protocol. The addition of flow control mechanism produces significant improvements in network system performance.

This paper presents an approach applying social network analysis on collaborative edit log data. Semantic Web Wiki and FAO ontologies are given as case studies. A number of users that are editing the same ontology or the same pages can be viewed as a social network of people interacting via the ontology. We propose to represent the edit log files as a graph either of users that are connected if they are editing the same ontology concepts or of concepts that are connected if edited by the same users. We apply social network analysis on such graphs in order to provide some insights into activity of the wiki/ontology editors. Finally, a plugin was developed which provides a comfortable GUI to some of the used analysis techniques, so that the people interested in monitoring the editing activity can perform that analysis and visualization on their own.

This paper presents the observations of three case studies, reflecting on the practices undertaken in various teaching evaluations. The case studies provide some insight into how many international institutions of higher education follow very traditional evaluation processes, even though they may differ significantly in cultural diversity and organization. Secondly, the paper emphasises the lack of alignment in evaluation practices when Universities try to seek more effective teaching and learning outcomes using these traditional instruments as the conduit. More effective teaching and learning could be accomplished through more aligned and reflective evaluation practices.

Organizations frequently consider offshore systems development in the belief that projects can be completed for lower cost. While prices quoted by offshore vendors are often very appealing when compared with domestic vendors, additional risks must be considered when looking into offshore systems development. These risks typically take the form of intangible and indirect project costs which add to the total cost of the delivered system. This paper describes and classifies these risks, which fall into three primary categories of security risks, legal risks, and general risks. Suggestions for incorporating these intangible and indirect costs into the decision making process, and their effects on total project costs, are offered for the offshore v. domestic vendor selection process.

In this paper, a novel approach for illumination normalization under varying lighting conditions is presented. Our approach utilizes the fact that discrete cosine transform (DCT) low-frequency coefficients correspond to illumination variations in a digital image. Under varying illuminations, the images captured may have low contrast; initially we apply histogram equalization on these for contrast stretching. Then the low-frequency DCT coefficients are scaled down to compensate the illumination variations. The value of scaling down factor and the number of low-frequency DCT coefficients, which are to be re-scaled, are obtained experimentally. The classification is done using k-nearest neighbor classification and nearest mean classification on the images obtained by inverse DCT on the processed coefficients. The correlation coefficient and Euclidean distance obtained using principal component analysis are used as distance metrics in classification. We have tested our face recognition method using Yale face database B. The results show that our method performs without any error (100% face recognition performance) even on the most extreme illumination variations. There are different schemes in the literature for illumination normalization under varying lighting conditions, but no one is claimed to give 100% recognition rate under all illumination variations for this database. The proposed technique is computationally efficient and can easily be implemented for real time face recognition system.