Archives-J  

In this paper, we employ Multiple Linear Regression Model to fit a model of Gross Domestic Product Per Capita of Nigeria using some World Development Indicators (WDI) as explanatory variables. Data were collected from 1981 to 2013. The five WDI are OER-Official Exchange Rate (LCU Per US$, Period Average), BM-Broad Money (% of GDP), INF-Inflation, GDP deflator (Annual %), TNR-Total Natural Resources Rents (% of GDP) and FDI-Foreign Direct Investment, Net Inflows (% of GDP).At the end of the analysis it was discovered that the OER and BM are statically significant while INF, TNR and FDI are not statistically significant. The average estimated GDP per capita of Nigeria when the effect of OER, BM, INF, TNR and FDI are zero is $-360.81. Also, 1 unit increase in OER-Official Exchange Rate (LCU Per US$, Period Average) will lead to a significant increase in GDP per capita by $4.42 (4.42USD); if BM-Broad Money (% of GDP) increases by 1% then GDP per capita will increase by $25.17; if INF-Inflation, GDP deflator (Annual %) increases by 1% then GDP per capita will decrease by $0.08; if TNR-Total Natural Resources Rents (% of GDP) increases by 1% then GDP per capita will decrease by $0.63 and if FDI-Foreign Direct Investment, Net Inflows (% of GDP) increases by 1% then GDP per capita will increase by $13.52. (Note: All the estimated parameters are significant at 5% without exception). 71.1% of the total variation in GDP per capita of Nigeria can be explained by the variations in OER-Official Exchange Rate (LCU Per US$, Period Average), BM-Broad Money (% of GDP), INF-Inflation, GDP deflator (Annual %), TNR-Total Natural Resources Rents (% of GDP) and FDI-Foreign Direct Investment, Net Inflows (% of GDP) while the remaining 28.9% could be explained by other variables other than the ones used in this model.

Speaker identification followed by speech recognition system is developed. The system makes use of MFCC (mel frequency cepstrum coefficients) to process the input signal and extract the features. VQ (Vector quantization) is used to identify the speaker. LPC (Linear Predictive Coding) and BNN (Back Propagation Neural Network) technique of hyperbolic tangent function under ANN (Artificial Neural Network) is used for speech recognition system. The implementation is done using MATLAB. The results of the developed system proved to be efficient and faster.

In the current paper, firstly literature is reviewed and various R & D assessment models in different industries are studied and finally, an assessment model selected that can evaluate R & D capabilities with the approach to new products development in automotive industry. Meanwhile this model has been tested in that article by structural equations and AMOS software, and also it was divided into 9 main classes with 29 indexes. In this research For the research purpose, firstly face validity, and then content validity was calculated using CVR form and Cronbach's reliability was calculated for research tool. Following approval of these items, questionnaires were distributed among 40 experts in Iran Khodro Co. working in engineering, new products development, quality and other units cooperating with R & D unit. Then, scores were given to 29 indexes by automotive industry experts and final score of 29 indexes and 9 main dimensions were evaluated. Considering obtained scores it was specified this company has highest capability in financial capability (80.83%) and technology capability (80.08%) dimensions compared to other dimensions. Also, it has lowest capability in strategic capability (61.38%) and customer and market capability (62.03%)dimensions compared to others. In addition, intellectual capital (70.17%), organizational structure (71.17%), research and design (73.17%), management (73.42%), and new products development process (77.50%) capabilities are in average level compared to other dimensions. Finally, some recommendations are made regarding dimensions and indexes with lower score in the organization.

Crop-Benefit analysis was used to assess fresh fruit yield responses of two day-neutral okra varieties: NHAe 47-4 and LD 88-1-8 to nitrogen (N) fertilizer application in trials conducted over three years at Ado-Ekiti in the sub-humid agro-ecological zone of south-western Nigeria. Fruit yield increased with N application in all years and reflected in high returns at subsidized and unsubsidized fertilizer (urea) prices. Value-Cost ratio (VCR) was highest at 60 kg N.ha^-1 for the two varieties in 2007 and for NHAe 47-4 in 2008 but at 30 and 120 kg N.ha^-1 for LD 88-1-8 and NHAe 47-4, respectively in 2009. The current economic environment in 2010, characterized by higher producer prices due to nationwide inflationary pressure on food items and regime of high fertilizer prices from a deregulating market necessitated an assessment of the returns from the responses to application of subsidized and unsubsidized urea. Profitability of N application increased as VCR rose to 1.57 and 2.39 for NHAe 47-4 and LD 88-1-8 at 60 kg N.ha^-1. This 60 kg N.ha^-1 is the economic rate to recommend for fresh fruit production in sole okra.

Extensive cracking on the runway slabs at the Srinagar (Jammu & Kashmir) International Airport has taken place due to overloading of aircraft operations and poor sub grade stability. A visual crack survey was carried out. The survey detected cracks of width of less than 6.4 mm to more than 50 mm which were classified into four types according to their width of opening. Repair methodologies were developed for each category of crack. The repair works and the construction of the overlay were carried out at night as the runway has to be kept operational. The runway has been in service and no sign of distress has been observed since the completion of repair works and overlay construction in September 2010.

The purpose of research was to study the most important factors that are causing growth of industry and then suggest a plan of action that could be followed in response to the existing decline Of textile growth in Pakistan. The Pakistan textile industry contributes more than 60 percent (US $ 9.6 billion) to the country’s total exports. However, currently this industry is facing great decline in its growth rate. The major reasons for this decline can be the global recession, internal security concerns, the high cost of production due to increase in the energy costs etc. Depreciation of Pakistani rupee that significantly raised the cost of imported inputs, rise in inflation rate, and high cost of financing has also effected seriously the growth in the textile industry. As a result neither the buyers are able to visit frequently Pakistan nor are the exporters able to travel abroad for effectively marketing their products. With an in-depth investigation it was found that the Pakistan’s textile industry can once again be brought back on winning track if government takes serious actions in removing or normalizing the above mentioned hurdles. Additionally, the government should provide subsidy to the textile industry, minimize the internal dispute among the exporters, withdraw the withholding and sales taxes etc. Purchasing new machinery or enhancing the quality of the existing machinery and introducing new technology can also be very useful in increasing the research & development (R & D) related activities that in the modern era are very important for increasing the industrial growth of a country.

This paper mainly deals with the solution of Optimal Power Flow (OPF) problem which can be formulated as a Quadratic Programming (QP) model and then decomposed by Lagrangian Relaxation (LR) method.The objective of this model is to minimize the total cost of real power generation. Many researchers have discussed the solution for OPF by using different methodologies like Newton Raphson (NR) method, Particle Swarm Optimization (PSO) method, Genetic Algorithm (GA), Artificial Intelligence (AI) method, Interior Point (IP) method, Differential Evolution (DE) algorithm. In this paper the proposed methodology is compared with the other methods like Particle Swarm Optimization method, Genetic Algorithm and Differential Evolution algorithm. These methods have been tested through the results of IEEE 30 bus system. The optimum generation cost is minimized for OPF using Lagrangian Relaxation method.

We are very happy to announce that from 7th July 2017, Dr. Mohammad Arif Kamal has joined the team of Elixir Editorial Advisory Board. He/She will carry a special responsibility for dealing with manuscripts based on Architecture. Dr. Mohammad Arif Kamal working as Associate Professor, Architecture Section, Aligarh Muslim University, Aligarh - 202002 (INDIA). The appointment of Dr. Mohammad Arif Kamal as member Editorial Advisory Board strengthens the links and will make it easier for prospective authors to establish contact with the journal.

We are very happy to announce that from 11th October 2016, Dr.D.Muruganandam has joined the team of Elixir Editorial Advisory Board. He/She will carry a special responsibility for dealing with manuscripts based on Production Engineering. Dr.D.Muruganandam working as Professor in Production Engineering, Sri Sairam Engineering College, Chennai. The appointment of Dr.D.Muruganandam as member Editorial Advisory Board strengthens the links and will make it easier for prospective authors to establish contact with the journal.

Stock control is an important functional branch of any manufacturing/service organization. Stock control has been discussed using the dynamic programming model approach. The distribution of goods to warehouses is a multistage process which the dynamic programming is adapted to providing solution to and also guarantees optimal feasible solution. The stock in warehouses is used as a partition of the firms main store. An equation ensues from the stock record which is shown to be piecewise continuous. The Laplace transform is used to test the existence of the function. The step function that derives from the supply to the warehouses is transformed to a piecewise linear function which can be approximated as continuous function. The step function is then applied on the function to obtain the returns from the respective allocations if the function exists. The allocation with the highest return is the optimum. Some relevant theorem have been stated and proved and illustrative examples included.