Sensor networks are driven by the activities of their deployed environment and they have the potential to use data that has previously been sensed in order to classify current sensed data. In this paper, we propose the Knowledge-Based Hierarchical Architecture for Sensing (K-HAS), an architecture for Wireless Sensor Networks (WSNs) that uses different tiers within a network to classify sensed data. K-HAS uses three tiers for in-network classification: the lower tier actively senses the data and packages it with relevant metadata, the middle tier processes the data using a knowledge base of previously classified sensed data and the the upper tier provides storage for all data, a global overview of the network and allows users to access, and modify classifications in order to improve future classifications. Initial experiments on the performance of the individual components of K-HAS have proven successful and a prototype network is planned for deployment in the Kinabatangan Wildlife Sanctuary, Malaysia.

The aim of this paper is to explore Greenstone open source digital library software which considered to be one of most essential open-source Content Management Systems (CMSs) that are available for use in creating, organizing, and managing Arabic content on the Internet. It focuses on the appropriateness of the system for Arabic content from different perspectives, such as its ability to support the Arabic language and to sustain and maintain different file formats. It also aims to examine Greenstone software and discuss its weaknesses and strengths in terms of managing Arabic digital content. Greenstone search facilities were tested and evaluated in this study using a quasi-experimental approach. The National Oil Cooperation standalone CDS/ISIS database in Libya (NOC) was converted into web interface using Greenstone software to explore the system’s functionality and to test its search and browse facilities. This database consists of 3400 Arabic bibliographic records. As previously stated, this paper aims to assess Greenstone retrieval facilities in the context of Arabic digital content to provide a full picture of the system’s suitability for the Arabic language and to highlight its limitations and strong points in the overall process of information retrieval.

Teaching computer science courses is a big challenge to majority of teachers in developing countries institutions. Most of these courses consist of abstract concepts where traditional pedagogical methods such as lectures and textbooks cannot be suited to enable students understand them. It becomes even more challenge due to the fact that majority of these institutions are faced with large class sizes while teaching facilities are few. Although several solutions have been proposed to alleviate these problems such as increasing student-computer ratio, improving teaching pedagogy and increasing number of teaching staff, the problem still exists. In this paper, we propose the use of computer animations as instructional tools so as to enable students learn difficult concepts in developing countries institutions. We conducted a pilot study at University of Dar es Salaam (UDSM) to determine if the use of animations can enable students to learn difficult concepts easier and master course contents. The study revealed that 67% of respondents (of 108 students) indicated that animated courses enabled them to grasp difficult concepts more easily. The study also found that the process of developing animations improves the quality of course design. However, it is essential to incorporate pedagogical and instructional design principles in the whole process of development and integration of animations into courses.

In this paper, we consider a two-level problem of resource allocation in a telecommunication network divided into zones. At the upper level the network manager distributes homogeneous resource shares among zones in order to maximize the total network profit, which takes into account the inner zonal payments from users and the implementation costs. This means that each zonal income calculation at a given resource share requires solution of the inner resource allocation problem. As a result, we obtain a two-level convex optimization problem involving non smooth functions whose values are calculated algorithmically. Unlike the usual convex non smooth optimization methods we suggest this problem to be solved by a Lagrangean duality method which enables us to reduce the initial problem to a sequence of hierarchical one-dimensional problems. Besides, we suggest new ways to adjust the basic problem to networks with moving nodes. We present results of computational experiments which confirm the applicability of the new method. n this paper, we consider a two-level problem of resource allocation in a telecommunication network divided into zones. At the upper level the network manager distributes homogeneous resource shares among zones in order to maximize the total network profit, which takes into account the inner zonal payments from users and the implementation costs. This means that each zonal income calculation at a given resource share requires solution of the inner resource allocation problem. As a result, we obtain a twolevel convex optimization problem involving non smooth functions whose values are calculated algorithmically. Unlike the usual convex non smooth optimization methods we suggest this problem to be solved by a Lagrangean duality method which enables us to reduce the initial problem to a sequence of hierarchical onedimensional problems. Besides, we suggest new ways to adjust the basic problem to networks with moving nodes. We present results of computational experiments which confirm the applicability of the new method.

In this paper an object recognition system using template matching is implemented. Since objects are represented by either an external or internal descriptors, a combination of using signature, principal component analysis and color is used. The system efficacy is measured by applying it to recognize an image of a chessboard with a set of objects (pieces). The output of the system includes the pieces names, locations and color. The signature feature is used to distinguish the pieces types based on their external shape but when it falls short, the principal components analysis is used instead. The object color is also obtained. The matching between features is carried out based on Euclidean distance metric .The proposed system is implemented, trained, and tested using Matlab based on a set of collected samples representing chessboard images. The simulation results show the effectiveness of the proposed method in recognizing the pieces locations, types, and color.

One of the crucial matters in software development is to what extent users can satisfy with the interfaces and functions provided. In order to measure whether the users are satisfied to use the software or tools, we need to evaluate the product before handover to the customer. However, the tools or instrument to be chosen to evaluate the product is still unresolved. In this paper, Software Usability Measurement Inventory (SUMI) is used to evaluate a tool for cost estimate called WebCost. WebCost is the stand alone application that developed by using Java programming language. A set of questions that adopted from SUMI instrument was used. The result shows WebCost provides easier interfaces and produces accurate cost estimation results.