The effort invested in a software project is one of the most challenging task and most analyzed variables in recent years in the process of project management. Software cost estimation predicts the amount of effort and development time required to build a software system. It is one of the most critical tasks and it helps the software industries to effectively manage their software development process. There are a number of cost estimation models. Each of these models have their own pros and cons in estimating the development cost and effort. This paper investigates the use of Back-Propagation neural networks for software cost estimation. The model is designed in such a manner that accommodates the widely used COCOMO model and improves its performance. It deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates. The model is tested using three publicly available software development datasets.The test results from the trained neural network are compared with that of the COCOMO model. From the experimental results, it was concluded that using the proposed neural network model the accuracy of cost estimation can be improved and the estimated cost can be very close to the actual cost.

Cloud computing is a new paradigm in the field of distributed computing. The objective of cloud computing is to provide various computing resources over the internet in the form of service to number of cloud consumers. Cloud provides the computing environment to organization in a cost effective manner and give flexibility to increase the number of resources as required during peak load time. In this paper we have tried to highlight some of the major challenges like security, availability of cloud services, reliability and auto-provisioning of cloud resources etc. which need to be addressed by researchers. Certainly there are some performance implications which also need to be resolved in order to get maximum output from the cloud so we need to manage the cloud resources in optimized way to increase the performance of cloud and its adaptability among different organization.

The use of renewable energy sources is a fundamental factor for a possible energy policy in the future. Taking into account the sustainable character of the majority of renewable energy technologies, they are able to preserve resources and to provide security, diversity of energy supply and services, virtually without environmental impact. This paper outlines possible energy savings and better performance achieved by different solar passive strategies (skylights, roof monitors and clerestory roof windows) and element arrangements across the roof in zones of cold to temperate climates. The aim of this work is to find possible design strategies, and to find solutions to provide thermal and luminous comfort in spaces of intermittent use and a poor aspect or orientation. In regions where heating is important during winter months, the use of top-light solar passive strategies for spaces without an equator-facing façade can efficiently reduce energy consumption for heating, lighting and ventilation. Passive solar systems for space heating and cooling, as well as passive cooling techniques when used in combination with conventional systems for heating, cooling, ventilation and lighting, can significantly contribute to the energy saving in the buildings sector, and the thermal behaviour of the dependent on the alternatives and interventions made on the building’s shell. Exploitation of renewable energy in buildings and agricultural greenhouses can significantly contribute to energy saving. Promoting innovative renewable applications and reinforcing renewable energy market will contribute to preservation of the ecosystem by reducing emissions at local and global levels and will contribute to the amelioration of environmental conditions by replacing conventional resources with renewable sources that produce no air pollution or greenhouse gases and coexist comfortably with existing urban, agricultural and tourist land uses. Sustainable low-carbon energy scenarios for the ne

The Pareto distribution is to model the income data set of a society. The distribution is appropriate to the situations in which an equilibrium exists in distribution of small to large. There exists many generalization approaches to the distribution. In this paper an effort has been made to compare the applicability of generalized Pareto distribution with Picklands (1975) by using a real life income data set. The model has provided considerable a good fit to the data set. Some well known distributions has been derived as a special case of this model for suitable choice of parameters.

In this paper, we extend the concept of strict practical stability to impulsive functional differential equations by using Lyapunov functions and Razumikhin technique. As practical stability does not give us much information about the rate of decay of solution so we develop the idea for strict practical stability of functional differential equations with impulsive effect and obtained some conditions for strict practical uniform stability for functional differential equations with impulse by using piecewise continuous Lyapunov functions and Razumikhin technique.

Two years studies were conducted rice-wheat sequence of 2007-08 and 2008-09 to assess the effect of rice residue management on growth, yield and protein content in grain and straw of wheat. The various rice residue and nutrient management systems significantly affect the plant height and number of tillers per meter and were maximum with 30% additional NPK + recommended NPK over sowing of wheat without incorporation of rice residue and recommended NPK and rice residue incorporation + recommended NPK at wheat sowing during both the years. Among the yield attributes and yield viz. number of effective tillers, length of ear head, number of spikelets per spike, grain and straw yield were also recorded maximum with the same treatment. Nitrogen uptake by grain and straw influenced significantly by rice residue and nutrient management practices during both the years. Highest nitrogen uptake by grain and straw was recorded under the treatment when rice residue incorporated with 30% additional N+P+K + recommended NPK against sowing of wheat without incorporation of rice residue + recommended NPK and rice residue incorporation + recommended NPK.

Pure water is most essential for human life. But it is not available and rare in most of the place in the world. Pure water is not only important for drinking purpose but also for other issue such as boiler make up or feed water, distilled water for medical uses etc. Hence purifying water is the demand of time. Water purifying is an energy consuming process but our conventional energy resource is limited. In that case alternative renewable energy resources can give us better solution. Solar energy is available resource and gives an optimum solution for this experimental purpose. Designed solar water distillation plant has two parts. Upper part is made by glass and a copper plate for absorbing heat inside it. Proper Insulator is attached behind this arrangement. A small container is linked below it by a small elbow, condensed pure water stored in this container. The lower part is made by cellulite. The cellulite box contain wick. This wick spread from the ground to the backside of copper plate. The wick absorbs the ground water and conveys it up to glass box where this water is evaporated in presence of solar energy. Total system is completely air tight. This plant works quit well but its performance is most depended on wick material. A composite wick material can gives better result.

Linear Programming technique was applied to farm data of a representative sample of farmers involved in arable crop farming in combination with monogastric farm animals and fish farming. Thirty farmers were selected from three villages within three circles in a chosen block by means of multi-stage stratified random sampling technique. Primary data were collected using well structured questionnaire on resource use and availability, input and output prices, types of enterprise combination etc. of the representative farms using the cost-route approach in Ohafia zone of Abia State, during the 2010 farming season. Data were analyzed using linear programming. The study was to solve a maximization problem of gross margin among combination of existing enterprises by this category of farmers. The programme recommended yam (0.29ha), cassava (0.02ha) and cassava/maize/cocoyam (0.13ha), broiler I – August – December (70.00 birds), fish I (220.00 fish) and layers (205.00 birds) enterprises for an average farmer in Ohafia to optimize gross margin given the available resources. Optimum gross margin for Ohafia was 72.90% greater than obtained in the existing plan.

Wireless Sensor Networks (WSN’s) have become an important and challenging issue in last year. Wireless Sensor Networks consist of nodes with limited power are deployed to gather useful information from the field and send the gathered data to the users. In WSNs, it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. In this paper, we introduce a heuristic way to reduce energy consumption in WSNs routing process using Ant Colony Optimization. We introduce three Ant Colony Optimization algorithms, the Ant System, Ant Colony System and improved AS and their application in WSN routing process. The simulation results show that ACO is an effective way to reduce energy consumption and maximize WSN lifetime.

This study investigates the influence of mixing and curing temperature on bond behavior of reinforced concrete. The properties examined were compressive strength, splitting tensile strength and bond stress between reinforcing bar and adjacent concrete at three different mixing and curing temperatures (150C, 300C and 450C). For measuring mechanical strength, cylindrical concrete specimens (100 mm dia. x 200 mm height) were prepared. Locally available materials were used to prepare these samples. Bond stress-slip relationship was observed to determine the mechanical properties of the interface between steel re-bars and concrete. Results of compression strength test shows that lower mixing and curingtemperature exhibits higher early age strength and comparatively low long period strength in compare to high mixing and curing temperature. Interpretation of bond stress- slip relationship demonstrates that D15DC sample gives 27.4% more bond strength than D45DC sample and P15DC sample gives 38.5% more bond stress than P45DC sample. Average bond stress of deform bars displays 36% more than plain re-bars. This study contributes mainly to explore the bond behavior for different mixing and curing temperature and enlighten the matter that hot environmental condition has great impact bond strength of reinforced concrete structure.