Items 1 – 21 of 21 IRE is a collection of peer-reviewed International Journals published by Praise International Review on Computers and Software (IRECOS). Home > Products > Journal and Reviews > S. > Latest issue. International Review on. Computers and Software (IRECOS) December ( Vol. 8 N. 12). IRECOS, the International Review on Computers and Software, was indeed discontinued by Scopus in due to “publication concerns”.

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Select the previous issues. Abstract – Learning objects retrieval is important for a variety of information needs and applications such as collection management, summary and analysis. Especially, retrieval of learning objects from the big collection of textual database has become a very active field. Since the learning information is stored in textual format in most of the time, the retrieval of learning objects from textual database faces two major challenges such as, large data handling, and effectiveness.

If these two challenges are solved, the performance and its applicability will be improved significantly. Accordingly, the first challenges of large data processing will be handled through the semantic annotations method. In the semantic annotation method, the text document was converted to semantic annotation data using concept-based modeling.

With the help of existing work, the large data will be converted to annotation object so that the matching process with the input query will be reduced and the complexity of handling big data will be also reduced.

The second challenge of effectiveness will be solved using new matching score to obtain better retrieval effectiveness. Here, query will be matched with the annotated object using matching score that will be devised newly and it will be applied for learning object retrieval.

The experimentation will be carried out utilizing the learning objects given in IEEE digital library and the performance of the proposed technique is evaluated using precision, recall and F-measure and also, comparative analysis will be performed to prove the better performance of the proposed technique. The analysis from the experimentations showed that the proposed approach has obtained a maximum precision of 0.

Abstract – Frequent itemset mining from the database is a difficult task. Many techniques have been proposed to mine the frequent rules from the database, but it consider only the frequency value to decide whether the extracted rule is frequent are not. Hence we proposed one technique to overcome these problems by utilizing AFCM. Initially the time series database values are clustered using the AFCM technique. After that, the frequent itemsets are mined from the clustered results by exploiting the sliding window technique.

During the frequent itemsets mining process, the itemsets frequency and utility are considered and that itemsets are frequent which are satisfying the utility and its consistency.

The proposed technique is implemented in the MATLAB platform and its performance is evaluated using rainfall database. Abstract – This paper presents a new technique for efficient searching with fuzzy criteria in very large information systems. The suggested technique uses the Pigeonhole Principle approach. This approach can be utilized with different embodiments, but the most effective realization would be to amplify some already given intrinsic approximate matching capabilities, like those in the FuzzyFind method [1][2].

Considering the following problem, a data to be searched is presented as a bit-attribute vector. The searching operation consists of finding a subset of this bit-attribute vector that is within particular Hamming distance. Normally, this search with approximate matching criteria requires sequential lookup for the whole collection of the attribute vector.

This process can be easily parallelized, but in very large information systems this still would be slow and energy consuming. The suggested method, in this paper, of approximate search in very large files using the Pigeonhole Principle, circumvents the sequential search operations and reduces the calculations tremendously. Abstract – Software clone research has proved that there are redundancies in software. This redundancy increased the maintenance effort. For nearly past two decades a number of software clone detection techniques and clone management techniques have been proposed in the software clone research.

In literature some researchers has also proposed clone management techniques such as clone removal, clone modification, analyses the effect of clones during maintainability, investigating their evolution, and assessing the root causes of clones.

There have been a number of researches which also focused on the evaluation of clone detection approaches. This paper is the analysis of different clone detection and management techniques. First, we analyze and evaluate all the currently available clone detection techniques and tools.


Second, we study and discuss the different clone management techniques and tools which are currently available. Abstract – The goal of software development in today’s industry is to provide products meeting customer requirements at the lowest cost, the best quality and the shortest time.

In addition, software development is becoming increasingly knowledge intensive and collaborative. In this situation, the need for an integrated know-how, know-why and know-what to support the representation, capture, share, and reuse of knowledge among distributed professional actors becomes more critical.

Our approach consists in studying each stage of the process of software development and defining knowledge necessary to capitalize in order to organize the project memory based on domain ontology. Afterwards, the development of such knowledge base will be used to help professional actors to accomplish their task in bringing knowledge of past projects.

It was an efficient approach to evaluate the quality of the Requirements Engineering process execution for improvement of the organization Requirements Engineering process maturity. We present Requirements Engineering process assessment results for four software companies, describe milestone compliance score distribution and compliance score distribution for Requirements Engineering assessment items.

All these companies reported satisfaction with their participation. Our conclusion is that quantitative Requirements Engineering Process Assessment model is useful in assessment of Requirements Engineering process in small organization and in identifying the strength and weakness of the Requirements Engineering processes. The lack of QoS can cause break in network during handoff or loss of network at remote condition.

Initially, when the mobile terminal MT on movement finds a new network, it collects the QoS information of the respective network that includes signal strength, network coverage area, data rate, available bandwidth, velocity of MT and network latency. Then MT compares estimated measurements with its old network and network which provides better QoS is selected as current network.

The old network then performs the data transmission to the new network. By simulation results, we show that the proposed approach enhances the network throughput and minimizes the latency. Unless there is a link failure, the route will not be updated even if another route with lesser hop count becomes available.

In this paper, we propose a route optimization technique using adaptive shrinking mechanism. It initially uses the estimated geometrical distance EGD metric for route discovery and link quality prediction technique.

The adaptive shrinking mechanism involves sending a shrink packet along with the data packets, based on the parameters link quality, traffic rate and link change rate.

When the source want to send some data to destination, it verifies the above said parameters and then decides to send the shrink packet. It optimizes the existing routing protocol by reducing the delay and increasing the lifetime of the network. By simulation, it is shown that the proposed mechanism reduces the delay and packet drop while increasing the throughput. Abstract – Wireless sensor networks have become an important area of research in recent years. A sensor network can be a network infrastructure consisting of elements that are nothing but some sensing devices which perform communication and computation along with the sensing of real world phenomenon.

The data collected by these elements are sent to an administrator located at a base station who can react to specific situations by analyzing the data. Thus data collection is an important activity performed by a sensor network. To facilitate the smooth and faster collection of data, various channel access schemes are available in literature. This paper analyzes the performance of these schemes in wireless sensor networks by considering a data collection scenario with a set of performance metrics.

The TDMA scheme has been implemented using an adaptive timeslot assignment mechanism. The performance done in this paper will be helpful in choosing an optimal protocol based on these schemes for deployment of a network as well as for developing a new medium access protocol. Surrogate Object Based Mobile Transaction. Abstract – The advancement in wireless technology and rapid growth in the use of mobile devices in mobile paradigm have the potential to revolutionize computing by the illusion of a virtually infinite computing infrastructure.

This new mobile paradigm enabled mobile devices to support data and transaction management in addition to the static nodes.

International Review on Computers and Software

A mobile device from anywhere in the wireless environment could utilize seamlessly a large computing power or any other resources in order to provide effective data and transaction process. In addition, advancement in wireless network together with ubiquity of devices has resulted in storing and retrieving incredible volumes of knowledge provided by data in the mobile devices.


Knowledge provided by data from mobile system has become very essential in many day-to-day applications. However, transaction management and knowledge discovery in mobile environment faces several challenges such as scarce bandwidth, limited battery resources, asymmetry in wired and wireless connectivity, asymmetry in mobile and fixed hosts, and mobility of host and their limitations.

In addition to the traditional mobile system challenges, it also faces many challenges such as dependency on continuous network connections, data sharing applications and federation with multiple service providers.

Due to these challenges, data loss, frequent disconnection, unpredicted number of wireless and wired access and high transaction aborts has occurred in data and transaction management over distributed mobile paradigm. To realize data management in mobile cloud, Surrogate Object based Mobile Transaction is proposed to deal with the fundamental issues of asymmetry problems, latency problems, low abort rate and disconnection.

The proposed strategy caches the data in the surrogate object which helps in reducing the average transaction time. The required reliability is provided by sending the transaction request to surrogate object and network lifetime is maximized by migrating the surrogate objects in a way to avoid improper load balancing.

The performance of proposed models have been evaluated and compared with existing models by simulation. Rosy Salomi Victoria, S. Abstract – Wireless systems schedule communicates resourcefully by allocating the shared band among associations in the identical geographic region.

The lack of central journaal in wireless networks calls for the journzl of distributed scheduling algorithms. We present a distributed framework that guarantees maximum throughput. The framework is based on random scheduling which reflect best throughput power distribution in multi-hop wireless systems. The revision of this difficulty has been restricted due to the non-convexity of the primary optimization complications that forbids a well-organized answer.

We yield a randomization method to agree with this trouble. We demonstrate the power distribution result through mathematical analysis and perform numerous extensions for the measured difficulty. Also, we examine how fast data can be composed from a Wireless Sensor WS system structured as tree.

We discover and estimate a method by means of accurate jourmal prototype under join cast. We reflect period setting up on a single occurrence channel with the goal of reducing the number of period slits needed to complete a join cast. We associate Irefos Separation Multiple Access TSMA scheduling with broadcast power controller to lessen the properties of interference and demonstrate that while power controller aids in decreasing the plan distance under a single occurrence, arrangement broadcasts by means of numerous occurrences is well-organized.

Praise Worthy Prize – IRE Journals collection

We estimate journwl performance of several channel task techniques and discovery experientially that for ireocs extent systems of many nodes, the use of multiple occurrence scheduling can be sufficient to reject maximum intervention.

Abstract – Developing the P2P botnets detection framework is crucial when we trying to fight against P2P botnets. Poor detection method can lead to a failure of P2P botnets detection. Thus, it needs to be accurately functioned well.

This paper reviews and evaluates various current frameworks of P2P botnets detection and analyzing the existing gaps to make improvement of P2P botnets detection framework. Based on a review that conducted manually, we report our findings and analysis has been done on different frameworks concern on P2P botnets detection.

Consequently, the gap and jorunal found from this reviews are discussed. Then, the P2P botnets detection framework architecture has been irecox with the new improvement been reinforced by hybrid detection technique, hybrid analyzer and in-depth hybrid analysis.

Future directions of this review are to develop the P2P botnets detection system that has capability in high detection accuracy and efficiency. Abstract – Iris recognition is the process of recognizing a person by analyzing the apparent pattern of his or her iris.