Programming companies in last decades have started to depend more and more on software components in developing their systems in order to save development time and increase the productivity of the company. However, this led to dramatically increase in the number of components, and selecting the appropriate component becomes a tough task. In this paper the authors propose an expert system to help developers choosing the best component fit their requirements. A survey is done to evaluate the efficiency of this proposed solution.

Cuckoo Search (CS) is one of the most recent population-based metaheuristics. CS algorithm is based on the cuckoo’s behavior and the mechanism of Lévy flights. The Binary Cuckoo Search algorithm (BCS) is new discrete version used to solve binary optimization problem based on sigmoid function. In this paper, we propose a new cuckoo search for binary multiobjective optimization. Pareto dominance is used to find optimal pareto solutions. Computational results on some bi-criteria knapsack instances show the effectiveness of the proposed algorithm and its ability to achieve good quality solutions.

Interoperability of health related information is one of the agendas of many counties in the world, with no exception to Nigeria and other developing countries. This is because healthcare costs are rising exponentially. However, interoperability of health related information seem largely unattainable in Nigeria due to reluctance to change from the traditional paper based healthcare system to the use of e-health systems, inadequate ICT infrastructure, poor utilization of the available ICT resources, erratic power supply, increased burden of underdevelopment, poverty, political instability, shortage of educational capacity in Nigeria rural and urban healthcare centers, low level of ICT awareness, poor maintenance culture as well as corruption. Consequently, the healthcare system in Nigeria is saddled with high cost, high rate of disease outbreak driven by HIV/AIDs, malaria and other infectious diseases which results in a high rate of mortality. Nevertheless, the urgent need to meaningfully exchange safe and reliable health information is a key priority to the healthcare system in Nigeria as the qualities of patients’ care depend majorly on the timely acquisition, processing and retrieval of data related to the patient. Thus, this paper attempts to unravel the factors hindering interoperability in the Nigeria healthcare system and suggests ways of making total interoperability a reality in Nigeria healthcare system as well as other developing countries.

Film industry is the most important component of entertainment industry. A large amount of money is invested in this high risk industry. Both profit and loss are very high for this business. Thus if the production houses have an option to know the probable profit/loss of a completed movie to be released then it will be very helpful for them to reduce the said risk. We know that artificial neural networks have been successfully used to solve various problems in numerous fields of application. For instance backpropagation neural networks have successfully been applied for Stock Market Prediction, Weather Prediction etc. In this work we have used a backpropagation network that is being trained using a subset of data points. These subsets are nothing but the “natural grouping” of data points, being extracted by an MST based clustering methods. The proposed method presented in this paper is experimentally found to produce good result for the real life data sets considered for experimentation.

Currently due to high awareness and quality audits, the higher education institutions have made to keep a track on various performances of the institutions. One such most important activity that has to be analyzed and evaluated is Instructor’s classroom performance. As the students are the main stakeholders of the educational process, their concerns over the instructor, teaching pedagogies and methodologies, assessment techniques need to be collected and analyzed for achieving the institution’s goals and objectives. The students shall give their opinions related to the various performance indicators of instructor.In general, the higher education institutions use various techniques to evaluate instructor’s performance in the classroom from the students. The latest technological developments help in data collection using web technologies. Online system with required questionnaire and attributes will help the higher education institutions in easy data collection. Apart from that the students shall give their opinions without any fear from any place and at any time. In this paper, we have identified the major factors and users of an instructor online evaluation system. Also, we have proposed a model for such system with subsystem interface, entity relationship diagram and context diagram.

Manual processing of recorded EEG data for characteristics like epileptic spikes is very time consuming since the recording of EEG for a longer duration producing enormous amount of data. Therefore, automated systems are required to speed up the processing. In the current work, a classification method has been proposed for detecting the epileptic spikes in the recorded EEG data by using Linear Discriminant Analysis (LDA) and has been named LDASpike. The prerecorded EEG data files were used as input to LDASpike and the output produced was the total number of spikes present in each EEG file. The proposed method results on an average sensitivity 100% and selectivity 95.38%, when the training and testing data were same. However, with four fold cross-validation applied in this work, the sensitivity and selectivity were achieved as 98.45% and 96.06%, respectively, on an average. Though a little time initially is spent to train the system but the result produced by the system is very promising and can be compared with the existing standard methods. This system can also works with the real time recording and processing for a clinical setup.

The paper concentrates on the theory of domination in graphs. The split domination in graphs was introduced by Kulli and Janakirm. In this paper; we have investigated some properties of the split domination number of some product graphs and obtained several interesting results.

Software development always faces unexpected events such as technology changes, environmental changes, changing user needs. These changes will increase the risk in software projects. We need to risk management to deal with software risks. Risk assessment is one of the most important factors in risk and project management of software projects. In this paper, we use Wallace’s work and five factors to present an efficient method to measure software risk using fuzzy logic. Team, Planning, Complexity, Requirements and User are factors that we use in this paper. Results of experiments shows that our framework is more efficient than other frameworks and approaches for risk assessment in software projects.