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Nowadays, Wi-Fi fingerprinting-based positioning systems provide enterprises the ability to track their various resources more efficiently and effectively. The main idea behind fingerprinting is to build signal strength database of target area prior to location estimation. This process is called calibration and the positioning accuracy highly depends on calibration intensity. Unfortunately, calibration procedure requires huge amount of time and effort, and makes large scale deployments of Wi-Fi based indoor positioning systems non-trivial. In this research we present a novel location estimation algorithm for Wi-Fi based indoor positioning systems. The proposed algorithm combines signal sampling and hyperbolic location estimation techniques to estimate the location of mobile users. The algorithm achieves cost-efficiency by reducing the number of fingerprint measurements while providing reliable location accuracy. Moreover, it does not require any additional hardware upgrades to the existing network infrastructure. Experimental results show that the proposed algorithm with easy-to-build signal strength database performs more accurate than conventional signal strength-based methods.

This paper introduces a new variant of Petri net controlled grammars, namely a concurrently controlled grammar, where the control over the application of the productions of a grammar is realized by a Petri net with different parallel firing strategies. The generative capacity of these grammars is investigated with respect to transition labeling strategies, definitions of final marking sets and parallel transition firing modes. It is shown that the labeling strategies do not effect the computational power whereas the maximal firing modes increase the power of concurrently controlled grammars with erasing rules up to Turing machines.

An interface is very effective to encourage the users intention and engage them to achieve their destination in e-learning process. This research aims to explore the user needs through learner experience on using e-learning interface. The case study is needed to identify and to collect the learner problem in e-learning, especially in User Interface. It took three months to get the user interface problems, such as login page, choice menus, and table of contents, content presentation, interactive media, and presentation of exercises, example solutions, and self-assessment. The research took three months data collection of forty-seven students in Mulawarman University. Based on this research, it shows that the communicativeness of the interface is the most difficult part, followed by choices menu, and self-assessment. Meanwhile, the example solutions and login page are among the least difficult of the menu.

Data centers had been evolving progressively since the first supercomputer invention. Although the main functions remain the same, the goals and characteristics change parallel with technology and market demands. Characteristics that perfectly suited data centers in the 90’s or even early new millennium are no longer valid nowadays. Computing nodes or servers are gradually transforming into energy hunger machines as a consequence of being powerful. Therefore energy efficient data center came into the picture to resolve the issue in order to reduce world’s carbon footprints and ensuring sufficient energy for the next generation. However the existing energy efficient data centers are portrayed in exclusive approaches which are costly and complicated hence hindering solid data centers stakeholders participation. Thus the aim of this paper is to highlight simple and economical attributes of energy efficient data centers. The attributes focus on aspects that are free of charge (FOC), require minimal capital expenditure (CapEx) and involve minimal operating expenditure (OpEx) with continuous efforts. These attributes were extracted from five existing energy efficient data center frameworks and fused into an adaptive energy efficient data center model. The model is represented in an appealing and implementable approach to promote green awareness implementation among data center stakeholders. Additionally, the model could be the starting point for small and medium sized, existing and new data centers in adopting hassle free green initiatives with hardly any extra investment.

In this research we propose a new approach of constructing Wi-Fi fingerprints database using Chebyshev wavelet functions. Proposed algorithm combines the reference data collection procedure with path-loss prediction. Our algorithm requires only a few samples to be collected in a given region, and thus significantly reduces the calibration time. Next, the collected reference samples are used to construct area specific path-loss prediction function using Chebyshev wavelets. Once we have the path-loss function, we can predict the signal strength values at any point of the target area. One of the advantages of proposed algorithm is that it does not require any detailed information about target area, i.e. location of wireless access points, number of walls (floors, obstructions) between the transmitter and reference points and etc.

Logic modeling and mathematical model can aid system analysts, system developers and programmers to construct a system during a system development process. Logic modeling and mathematical model are the techniques used in the system analysis phase. In the midst of the most common logic modeling, are decision tables and structured English. These techniques help the person in charge to develop a system through illustrations in order to give better understanding and for solving a problem specification. In this article, we briefly describe on decision tables, structured English and mathematical model. The article aims to explain the use of decision tables, structured English and mathematical model for the development of a tree species selection prototype for Malaysian forest plantation. The algorithms related to the analysis of the systems prototype were also presented in this article. Overall, the techniques are capable of supporting the data acquisition and presentation from the context of the given problem specification.

Expert systems are widely used in healthcare for predicting and diagnosing diseases. Several efforts have been made to help diagnose diseases, and to identify their codes, signs and symptoms. However, abnormal findings, social circumstances and external causes of diseases in the psychological arena are a huge burden of illness in the community and still a complicated task. Several intelligent techniques based on different rules are used in developing CDSS. Therefore, further investigation on the current state of the field is required in order to identify the related issues and the future directions. This study intends to analyze the current state of the expert systems’ development for psychodiagnostics. That provides a comprehensive background of the available methods, techniques and issues related to CDSS.

In this research we compare Wi-Fi received signal strength indication and magnetic field based real-time location systems (RTLS) from various perspectives such as system complexity, accuracy and stability. To evaluate the performance of these systems we built several test fields with different types of environments. We will compare both approaches side-by-side and answer such issues as optimal calibration step (measurement interval), location accuracy, effect of minor and major environment changes to fingerprint DB and overall system accuracy.

Data centers are the heart of computing and emergence of internet services demands has increased its vitality. The intense workload of data centers in order to fulfill customers need indirectly contributed to world pollution through massive usage of energy. Thus an energy efficient framework for steering the data centers design and management is needed. Besides the green factor, the framework should take into consideration total cost of ownership (TCO) as one of the key components to make it budget friendly and feasible to all kind of budget. To achieve this, comparison on five existing energy efficient data center framework was performed. The comparison deduced that the frameworks have the opportunities for improvement in term of components, attributes, energy efficient metrics and implementation methodology. Propositions and novel ideas from industry leaders are also gathered to provide diverse views on energy efficiency approaches and opportunities in data center. Categorization of attributes based on return on investment (ROI) and energy efficiency level in one of the frameworks that allows it to be implemented in phases is a sensible and practical approach. Works focusing on developing higher ROI attributes will definitely contribute in building more energy efficient and greener data center in the future.

Nowadays, fingerprinting based Wi-Fi positioning systems successfully provide location information to mobile users. Main idea behind fingerprinting is to build signal strength database of target area prior to location estimation. This process is called calibration. Indoor positioning system accuracy highly depends on calibration (sampling) intensity. This procedure requires huge amount of time and effort, and makes large-scale deployments of indoor positioning systems non-trivial. Newly constructed database may no longer be valid if there are any major changes in the target site. In this research we present a new approach of constructing fingerprint database. We propose a hybrid calibration procedure that combines signal sampling process with path-loss prediction algorithm. Instead of manual signal sampling, proposed method requires several Wi-Fi RFID tags to be installed in a target site. Advantage of such tag is that it can be read directly by commercial Wi-Fi access points from long distance. Several RFID tags mounted in target area will monitor the signal strength levels continuously and send scan data to the server. Whenever there are significant changes in signal levels detected, server will initiate database reconstruction procedure. Compared to existing calibration procedure our method requires only few signal samples from RFID tags to be collected and rest of the database is recovered using path-loss prediction algorithm.

E-learning does not function properly if the system is not in accordance with user needs. This study aims to establish an evaluation model for e-learning user interface according to user acceptance. The model is designed based on three categories: user learning style, usability and user benefits. Results of measurements of the three categories will determine the level of user acceptance of the e-learning interface. The data were taken using a questionnaire which was distributed to 125 ELS students from various countries. Then processed using SEM and Lisrel v8.80. This paper presents experimental set up for the general research and some results for technology acceptance theories.

In this paper we study some properties of context-free concurrent grammars which are controlled by Petri nets under parallel firing strategies, i.e., the transitions of a Petri net fire simultaneously in different modes. These variants of control increase the computational power of generative devices. Moreover, they can be used as theoretical models for parallel computing devices.

The present invention relates to an application framework (100) for managing knowledge in open source software development characterized by: domain open source knowledge (101) comprising an open source software development process; knowledge management process (102) for acquiring, collecting, organizing, disseminating or sharing the domain open source knowledge (101); repository (103) for storing the domain open source knowledge (101); community of practice (104) in the open source software development; networking system (105) for supporting communication among the community of practice (104); and connection platform (106) for connecting the community of practice (104) to the repository (103) and networking system (105).

In any customer driven supply chain, the acquisition of customer knowledge can help companies to attain a competitive advantage in product innovation. Since the existing approaches have not considered this knowledge as a weighted factor in the case based supplier selection processes, this paper aims to present an agent-based framework for supplier selection based on the case-based reasoning approach. This framework uses customer knowledge to evaluate the price, volume, quality grade, and delivery date of supply materials and provide them with alternative products which are closest to their first order if it was out of stock. Based on the proposed framework, a numerical example of the known case study is illustrated for highlighting the effectiveness of the approach.

Natural language interfaces to ontologies allow users to input their queries in natural language to the system and retrieve their desired information from ontologies. Many natural language interfaces have been developed to date but their capability in handling negation queries is limited. This paper proposes a negation query handling engine which is particularly designed to handle user queries with negation. The proposed engine is designed to understand the complexity of natural language queries with negation which was previously not catered effectively by the existing systems. The proposed engine effectively understands the intent of the user query on the basis of a sophisticated algorithm which is governed by a set of techniques and transformation rules. The proposed engine is evaluated using the Mooney data set and was found to comply and satisfy with most of the negation queries in the data set. The implementation of the proposed negation query handling engine can bring considerable improvements in natural language interfaces in handling negation queries.

Hospitals are known for having separate information systems across various departments, which are usually heterogeneous in nature. Medical experts could benefit greatly from the integration of these islands, but the heterogeneity of the sources/databases often impedes this. Most cardiothoracic units use isolated heterogeneous systems to keep patients records as well as to support the experts when deciding for cardiothoracic surgery. These include patient’s information system, lab results for x-ray, angiography, echocardiogram, blood etc. All these information are stored in heterogeneous systems and as such, a user would have to log-in and log-out from one system to another, to monitor/trace a patient’s medical record. As the solution, we proposed a clinical database system in which the system incorporates the overall patient’s management, from ward admission through Operation Theatre, Coronary Intensive Care Unit (CICU), recovery and discharge in which is divided into several modules. The purpose of this paper is to presents the conceptual database design for the Smart Medical Clinical System which include features that could alert the healthcare personnel regarding any abnormal trend in the data, so that medical experts need not have to repeat the same investigations.

The evaluation of Website is a multi-criteria problem, which involves combining several measures into a single value through an aggregation operator. To the best of our knowledge, none of the evaluation approaches study the existence of relationships between the quality criteria. All of the evaluation approaches just simply assume the quality criteria are independent to each other to make the aggregation procedure easy. The process of aggregation should take into account dependence between criteria as the criteria are sometimes interacting with each other. This paper discusses the issues of multi-criteria evaluation and highlights the interaction problem between the quality criteria. The idea to incorporate the fuzzy measures in the evaluation procedure has addressed the issue of dependence between criteria. The relationships between quality criteria need to be investigated to identify their positive or negative interaction. The proposed multi-criteria evaluation procedure has allowed the incorporation of interaction exist between the quality criteria to be considered in the aggregation process. The results are also consistent with the additive model approach when no interaction exists.

Software maintenance (SM) environment is highly complex, knowledge-driven and collaborative. Therefore, a Knowledge Management System (KMS) is critical to provide an environment for sharing and sustaining knowledge among members of SM community of practice (CoP). Based on earlier works on KMS framework for collaborative SM, an agent-based KMS prototype system called SM Collaborative Agent Team (SCAT) is designed and developed, to assist maintainers to share information and perform their SM activities. The aims of this paper are to discuss the design of SCAT and to evaluate SCAT's success as a KMS tool. Designing SCAT involves three major aspects: Multi Agent System (MAS) design, Combined Ontology of SM and Domain knowledge areas, and System design. For evaluation, SCAT was benchmark against another agent-based KMS prototype. A survey was conducted to gauge the responses of users and maintainers on the success of both KMS tools, based on Wu & Wang KMS Success model. The results of the survey are analyzed using Rasch rating-scale model to determine if SCAT fares better than Rodriguez. Based on t-test comparison on overall Rasch estimated measures, SCAT KMS is slightly better than Rodriguez KMS. Using Common Person Equating (CPE) plot, SCAT are better than Rodriguez KMS in several key areas. In future, SCAT could be enhanced to improve the weak areas.

Previous research proposed notions of CLCA and MCLCA to answer keyword query in XML document. The notions are implemented in its proposed algorithms and the result, namely MCCTree, is ranked with its proposed ranking method. The algorithms transform the XML tree into a compact global tree called CGTree, and select the MCCTree from the CGTree. The resulted MCCTree is in a compact structure; however the calculation in the ranking method requires the original structure as in the XML tree. Thus, this paper presents a new algorithm that implements the same notions with different approach. The MCCTree is returned in a structure as required by the ranking method. This algorithm, called XMCCTree, improve the efficiency of producing a set of MCCTree in answering keyword query in XML document.