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Two  appropriate post-tax petroleum exploration models were constructed and tested for three hypothetical field profiles (i.e low, medium and high volume fields) from a development economics perspective and the proposed tax regimes tested for both oil price and development cost ($/bbl). 40% government participation through the international oil company was considered in both cases. The resulted government takes for the first proposal are 76.89%, 83.07%, and 86.94% for low, medium and high volume fields respectively. Respective percentages for the second proposal are 76.20%, 80.03% and 85.43%. These values are above the average global take of 64% but within the range of 40% to 87% for most world oil producers. Analysis of the models indicates an increase in government take as the development costs ($/bbl) increases but a decrease when the oil price ($/bb) increases, which shows regressivity. However, the second regime shows more neutrality, efficiency and focused stability, though still maintaining high government take. This contributes to more attraction for investment from both government and investors perspective. Thus, the second fiscal proposal is recommended to the Nigerian government, considering its incentives.

The entomopathogenic fungus Beauveria bassiana is a promising biocontrol agent against coffee berry borer, Hypothenemus hampei in coffee. The fungus conidial survival was influenced by both environment and agrochemicals normally used to protect crop plants. The present study evaluates the fungitoxic effect of commonly used chemical insecticides (endosulfan, chlorpyriphos, dimethoate and quinalphos) and fungicides (bordeaux, hexaconazole and triadimefon) on germination, vegetative growth and sporulation of B. bassiana. The insecticides and fungicides were tested at three concentrations (Field Recommendation (FR), half FR, and twice FR). All the tested concentrations inhibited the germination (9.0-81.19% and 19.3-100%), vegetative growth (0.5-62.9% and 37.1-100%) and sporulation (7.0-99.9% and 99-100%) of B. bassiana by the insecticides and fungicides respectively, but dimethoate exhibited minimum inhibitory effect. Dimethoate showed better compatibility to B. bassiana in all the three concentrations. As dimethoate is safer to biological control agent, could be used as an integrated pest management in coffee.

This paper aims to examine drivers and its moderating variable that influencing consumers’ purchase intention on green personal care products. Total of 137 completed and usable set of questionnaires was obtained from white collars employees that having knowledge about the availability of green personal care products that working in Penang, Malaysia. Data were analyzed by employing multiple regression analysis on testing on the independent variables (drivers) to dependent variables (purchase intention) and hierarchical regression analysis for moderating relationship between the drivers and purchase intention. The results revealed that environmental attitudes and self efficacy were found to be the factors that drive the purchase intention of consumers on purchasing of green personal care products. In addition, it was found that willingness of consumers to pay more on green personal care products was moderating the relationship between environmental attitudes and purchase intention. The findings created an understanding on what are the factors that influencing consumer purchase intention on green personal care product and serve as the information for marketers to plan for the marketing program that able to enlarge the market size of the said products.

Companies have been collecting data for decades, building massive data warehouses in which to store it. Even though this data is available, very few companies have been able to realize the actual value stored in it. The question these companies are asking is how to extract this value. The answer is Data mining. Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. There are many technologies available to data mining practitioners, including Artificial Neural Networks, Regression, and Decision Trees. Many practitioners are wary of Neural Networks due to their black box nature, even though they have proven themselves in many situations. In our current research we are attempting to compare the aforementioned technologies and determine if Neural Networks outperform more traditional statistical techniques. This paper is an overview of neural networks and questions their position as a preferred tool by data mining practitioners.

Digital comic was developed by students of the Bachelor of creative technology with honours in multimedia elective and visual communication elective. Students developed the comic digital through the process learning which use studio based learning approach is. The implementation of Studio Based Learning approach was been enhance by project based learning approach. Students had been asked to establish their company by group. All activities through the learning process was been activated based on companies activities. Hence, corporate culture will be embedded into students. Digital comic is a big project which is role as a final product. An effort to produce comic digital, students will be able to adopted soft skills attribute and entrepreneur attributes. Therefore, produced digital comic with intelligent collaboration among strategic group such as Faculty of Creative Technology and Heritage, MDeC, Icon, Pekartun, Pekomik and a various of related agency will be a effective platform to generate techno-entrepreneurship in education.

The dispersion of bioactive glass, (BG), sample was studied using cetyltrimethylammonium bromide (CTAB). An array of experimental techniques like adsorption, zeta potential and turbidity were used to achieve this goal. Turbidity was used as a parameter to reflect the degree of dispersion where a higher value of turbidity represents higher dispersion efficiency. Dispersion of the BG particles was largely affected by CTAB concentration and the solution pH. Dispersion of the BG particles was increased with increasing of CTAB concentration till the CMC of CTAB is reached. Beyond the CMC , the BG particles become hydrophilic causing a decrease in glass dispersion. On the other hand, dispersion of the BG particles was affected with the solution pH. It was increased with increasing pH till pH 9. At higher pH, dispersion was decreased where the formation of micelles is favored.

Domain Moderator (DM13) was developed by Che Ghani Che Kob in year 2013 as a part of his Education Doctorate (EdD) research instrument to evaluate engineering students learning and lecturers teaching domains. Domain Moderator is an education instrument to measure the domains of Engineering Learning & Teaching Domains (ELTD). The ELTD model comes out to enhance the whole process of Education Measurement & Evaluation Methods. The data’s of pilot survey among 26 lecturers by using DM13 shown that among engineering lecturer are (61.5% ) at active domain,(38.5%) at reflective domain, (73.1%) at sensing domain, (26.9%) at intuitive domain, (92.3%) at visual domain, (7.7%) at verbal domain, (61.5%) at sequential, and (38.5%) at global domain. This data’s collection hopes can be use as a moderator among engineering lecturers to success in Outcome Based Education (OBE) at Polytechnics & College Community, KPM, MALAYSIA.

In recent years,tribal livelihood has encountered various problems due to economic-social changes in the country,droughts,lack of water and loss of pastures. The purpose of this research is survey of economy and tribal livelihood by emphasis on Qlkhany tribe in sarpolezahab city.the method of the research has been documentary,library and field study.in analysis of data used Excel and Spss software.research population was 270 households of Qlkhany tribe that migrate to sarpolezahab city in winter season.from this households 100 family chose as sample.the purpose of this research was survey of economy and Qlkhany tribe livelihood.the result of this research indicates economic situation of Qlkhany tribe is not good and they are a poor tribal community economically.the rate of life satisfaction is average and the number of livestock is declining due to drought and economic hardship.the men have left the jobs and they engage to worker and pastoral in the surrounding villages and towns.

The focus of this study was to examine the effect of the Millennium Village Primary School Meal Project on enrolment rate and attendance of pupils in public primary schools in Yala Division, Siaya County, Kenya. The evaluation used both ex-post facto and case study research designs. The mixed methods was adopted because when both qualitative and quantitative designs are used in the same study, the strengths of both produce a research synergy in which the whole collective benefits are greater than what is obtained from either designs alone. A sample size of 179 respondents was selected using purposive sampling as well as stratified random sampling procedures. The respondents included the Area Education Officer (AEO), head teachers, other teachers, pupils, project staff and the parents through the Parents Teachers Association (PTA) membership. The instruments of data collection used in the study included questionnaires, interview guide, document analysis guide, Focus Group Discussion (FGD) guide as well as observation guide. The findings indicate that the project had significantly contributed to increased pupils enrollment as well as retention rates. In order to increase its visibility as well as sustainability, the study recommends that there is need for financial support from the government as well as capacity-building the parents on the project related activities like the tendering process so that they may participate and in the process ensure project sustainability.

The aim of this study was to examine energy use pattern and predict the output energy for dry wheat production in Silakhor plain from Lorestan province of Iran. The data used in this study were collected from farmers by using a face to face survey. The results revealed that chemical fertilizer with seed and diesel fuel have consumed 57.93% and 36.58% of total energy, respectively. In this study, several direct and indirect factors have been identified to create an artificial neural networks (ANN) model to predict output energy for dry wheat production. The final model can predict output energy based on human power, machinery, diesel fuel, chemical fertilizer with seed and transportation. The results of ANNs analyze showed that the (5-10-10-1)-MLP, namely, a network having ten neurons in the first and second hidden layer was the best-suited model estimating the output energy. For this topology, MSE and R2 were 0.029 and 90%, respectively. The sensitivity analysis of input parameters on output showed that chemical fertilizer with seed and human power had the highest and lowest sensitivity on output energy with 0.21and 0.03, respectively.