Classroom teachers of Kindergarten, 1st Grade, or 2nd Grade often use the Hundreds Chart puzzles to teach children the basic mathematical knowledge and skills like counting. Computer programs have been developed to help them to create puzzle sheets by cutting out the numbers, but students still need to solve the puzzles on the printed paper. This study designs and implements a computer application named Hundred Acorn Forest as an instructional method to teach basic counting skills with the Hundreds Chart puzzles using the Unified Process method. The application not only offers an easy way for classroom teachers to create and edit puzzles based on patterns, but also engages students in a unique interactive game play environment, which helps to maintain their interests of learning. In addition, the video playback that demonstrates the process of students solving the puzzle provides classroom teachers valuable information to set up levels of control and consistency that have not been available before.

Websites hide thousands of links and sub-links. Websites’ links contain a huge amount of information and knowledge. This research concentrates mainly on the difficulty of early prediction of web structure size at the beginning of Website Development Life Cycle (WDLC), especially during planning and gathering requirements. There is a lack of finding an appropriate mechanism to assist developers in these steps. The objective of this research is to measure the logical size of a website in order to predict the development time and cost earlier before the development process based on based on the website contents and its internal structure. This objective includes three sub-objectives. First, analysis of seven classes of websites to collect real data sets. Second, extracting a set of relations from the gathered data and use these relations to establish a proposed model. Third, apply the gathered data in the proposed model to predict the development time and cost of a website. This research provides strong and important results that would help developers before the development process to predict total development time and cost which in turn used directly to specify development tools, draw project plan, formulate contract conditions and determine project duration and final price.

Wireless mesh networks, consisting of mesh routers and mesh clients are very robust, reliable and easily maintained networks. The current work is based on IEEE 802.11 standard amendment IEEE 802.11s specific for mesh topology based networks to improve the connectivity and coverage. It aims to control the shared medium access among the stations using Distributed Coordination Function (DCF) MAC protocol for reducing collisions and delays, thereby increasing throughput of the network.. The actual Binary Exponential Backoff (BEB) algorithm as implemented in IEEE 802.11 resets the contention window to its least value after an acknowledged transmission. From the previous works it has been observed that this sudden reset to minimum value of contention window does not ensure a reduction in collisions. It may lead to more contention in the network thereby increasing delays and affecting its throughput. The proposed work presents a Mean Backoff Algorithm in order to solve this flaw of BEB algorithm. The proposed algorithm aims to bring the contention window to some appropriate value in order to cope up with the unfairness caused due to its minimum value on successful transmission.

Software maintenance mainly refers to the process of correcting software after delivery. Maintenance process is usually a high percentage of Organizational effort to the whole process of software programs. As a result, the effectiveness of the entire production process and customer satisfaction is dependent on the effectiveness of maintenance activities. Because many factors including type of service, type of product and human factors is dependent on the maintenance process, And the imprecise nature of qualitative factors and sub-criteria leading software maintenance, accurate assessment can be maintained in order to measure the effectiveness of programs seem highly desirable. In this paper, using adaptive fuzzy neural network to provide a method for evaluating the capability of software maintenance conducted after the tests, the root mean square error of the proposed method was equal to 0.34331. The results show that the method is based on adaptive fuzzy neural, maintainability software performance evaluation is appropriate.

Text Summarization is a process that converts the original text into summarized form without changing the meaning of its contents. It finds its usefulness in many areas when the time to go through a large content is limited. This paper presents a comparative evaluation of statistical methods in extractive text summarization. Top score method is taken to be the bench mark for evaluation. Modified weighing method and modified sentence symmetric feature method are implemented with additional characteristic features to achieve a better performance than the benchmark method. Thematic weight and emphasize weights are added to conventional weighing method and the process of weight updation in sentence symmetric method is also modified in this paper. After evaluating these three methods using the standard measures, modified weighing method is identified as the best method with 80% efficiency.

Data Mining is an analytical process intended to explore the data in search of consistent patterns. Due to its wide spread applications in biomedical industry and publicly available genomic data, data mining has become upcoming topic in the analysis of gene expression data. Clustering is the first step in understanding the complicated biological systems. The objective of clustering is to organize the samples into intrinsic clusters such that samples with high similarity belong to same cluster. The significance of clustering gene profiles is two-fold. Firstly, it assists in diagnosis of the disease condition and secondly it discloses the effect of certain treatment on genes. In this paper, we propose a new method to cluster gene expression data that is solely based on the concept of hierarchical clustering with a different method to compute the similarity between datasets and merge the pairs. The experimental results on two microarray data show the correctness and competence of proposed technique.

The large amounts of available protein structures emerges the need for computational methods for protein function prediction. Predicting protein function is mainly based on finding similarities between proteins with unknown function with already annotated proteins. This may be achieved using different protein characteristics: sequences, interactions, localization, structure and or psychochemical. A lot of review papers mainly focus on sequence and psychochemical features-based methods. This is because sequence and psychochemical data are easy to deal with and to interpret the results, and much available compared to protein structures. However, structure-based computational methods provide additional accuracy and reliability of protein function prediction. Therefore, unlike many review papers, this paper presents an up-to-date review on the structure-based protein function prediction. The aim was to provide a recent and comprehensive review of protein structure related topics: function aspects, structural classification, databases, tools and methods.

Finite State Machines (FSMs) are mathemati-cal abstractions which have a rich use in computer appli-cations. If we build a FSM for software, then it becomes much easier and simpler to understand, debug and modify. The insights developed in FSMs have had great influence on various domains. FSM is as important as any other computer science tool. This paper minimizes the gap which currently exists between software development and the formal method of theoretical com-puter science. So importance of FSMs has been explored over various such domains in this article. These domains include spoken web technology that enables a user to access a massive network of voice sites through speech. Information transfer protocol for Vehicular Computing is another domain, where users can get on road support services using vehicular sensors and global position system. Adding on to the domain list, we have modeled FSMs for Ankle Monitor and Sensor Dust which are applications of mobile ad-hoc networks. Ankle monitor is primarily used to track movements of an individual through wireless communication and Sensor Dusts are tiny sensors which monitor the environment in which they are deployed. We have also modeled Palm Operating System, which is a mobile OS that runs on Linux kernel. This paper presents the FSM for the booting sequence and the user interface of Palm OS. To conclude with we have taken up the domain of satellite simulation and have presented a FSM for the steps involved in Satellite launching and Image Handling within a satellite. Therefore, by modeling a range of applications using FSM we attempt to add-on to the significance of this concept and at the same time provide a single document comprising numerous FSM models. This concept can be used by software developers for easy modeling of their designs and can further use it to verify and debug the model whenever required.