Archives-September 2017

The introduction and appearance of Chinese brands in the international market is an emerging issue for Chinese firms. This paper highlights the challenges encountered by Chinese firms while moving towards original brand manufacturing (OBMs from original equipment manufacturers (OEMs). The study identifies that branding dilemma, the performance of Chinese firms in domestic markets, lack of government support, need of global distribution channel and marketing, technology backwardness and need for strong R&D activities are some important factors that are impeding the successful switching of Chinese OEMs to OBMs. The OEMs can convert these challenges into opportunities by effectively coping with them. The study also presents some recommendations to deal with the problems.

The oxidative decolourization of AMCOT Red 3BLF in aqueous medium has been studied using photo Fenton process. Fenton’s reagent (H2O/Fe3+) was used to generated hydroxyl radical (?OH). A visible light source was used to provide radiation for photo Fenton process. The experimental parameter such as pH, air, light, time and catalyst strongly influenced the dye removal rate in photo Fenton process. The result shows that the AMCOT Red 3BLF bleaches upto 70% within 4 hrs and degrades into CO2 and H2O. The proposed mechanism for the reaction of ?OH with AMCOT Red 3BLF dye molecules is summarized.

WSNs are the widely used for the process of sensing and transmitting the data of any environment based on the application and they are mainly employed for the real-time applications. In the real-time applications, the WSNs are advantageous but the efficiency and the system performance are degraded because of the phenomenon termed as congestion. The occurrence of congestion affects the life-time of the nodes resulting in the poor throughput of the network. Thus, in order to enable effective transmission and to enhance the throughput of the network, an efficient congestion control method is required. Accordingly, the literatures present various approaches for the controlling the congestion that occurs in the network and it is very clear that the accuracy of the control mechanism is the outstanding issue at present. Therefore, the need for an effective congestion management system arises that outperforms the current approaches in terms of accuracy, congestion rate, and the packet drop rate. Thus, this review article presents the detailed review of 17 research papers that present the recommendation approaches based on neural networks, fuzzy-logic model, hybrid method, and learning-based models. Additionally, the detailed discussion of the survey taxonomy in terms of the simulation tools and performance metrics are clearly reviewed and analyzed. The research issues of various conventional methods are presented in the literature section along with the description of the methods that promote the researchers towards a better contribution of the congestion control mechanism.

National curriculum framework(2005) focuses on 21st century learning, ensuring learners are equipped to participate in and contribute to their own society and the wider world. An important aspect of this is encouraging students to consider significant future-focused issues such as sustainability.The future-focus theme of sustainability should be evident throughout the curriculum in school education. Structuring learning around a unifying theme such as sustainability provides opportunities for students to make connections between learning areas, competencies, and values. It requires teaching and learning approaches that draw on all elements of effective pedagogy and focuses on empowering students to take action for a sustainable future.Sustainability connects to the principle environmental health is personal health. The curriculum should endorse a place for the school, the family, the community to focus on the place of the student in their own world. Therefore, the school-based curriculum should supports holistic teaching programmes and learning pathways which enable the learner to engage purposefully with the environment.Education for sustainability is about learning to think and act in ways that will safeguard the future wellbeing of people and our planet. Many contexts, topics, or issues that students could explore have a connection to education for sustainability. There are opportunities in most learning areas for students to examine how the resources we use and what gets left over affects the earth.Teachers can introduce students to attitudes and values towards the environment, and create opportunities to explore their own. Students will also have opportunities to take action on issues that are meaningful to them, explore why an issue is important and develop the skills they need to create change.

Computational chemistry is rapidly emerging as a new branch of chemistry. It is basically the application of chemical, mathematical, and information technology principles to the solution of complex chemical problems. It uses computers to the 3-dimensional structures and key properties of molecules and materials. This information can provide critical insight and better mechanistic understanding of complex chemical systems, leading to discovery and development new materials with superior properties. Computational chemistry is widely used in many multidisciplinary fields with applications in chemistry, biology, and material science. This paper provides a brief introduction to computational chemistry.

The main purpose of this study was to examine the influence of human resources on the implementation of strategies in commercial banks in Kenya. The focus groups were senior and middle-level managers of commercial banks in Kenya. A mixed research approach, which combined qualitative and quantitative methods, was adopted for this study. Specifically a correlation cross-sectional field data aimed at testing the research hypotheses was used. The researcher used proportionate stratified random sampling technique to obtain a sample of 200 managers. Questionnaires were used to collect data. The organized data from both the qualitative and quantitative sources were entered into the computer application package SPSS after which descriptive and inferential statistics were obtained. Descriptive statistics employed frequencies, percentages, means and standard deviations while inferential statistics employed Pearson (product moment) correlation coefficient and linear regression analysis. The study found a statistically significant relationship between human resources and strategy implementation at 0.05 confidence level. The study recommended that commercial banks should continue investing in human resources through strategies like recruitment and selection, training and development, reward management in order to increases chances of strategy implementation success.

Accurate rainfall prediction is of great interest for water management and flood control. In reality, physical processes influencing the occurrence of rainfall are highly complex, uncertain and nonlinear. In this paper, we present tool for modeling and predicting the behavioral pattern in rainfall phenomena based on past observations. The aim of this paper is to predict the seasonal rainfall of (Iran) khozestan using artificial neural network (ANN) model. In order to evaluate the prediction efficiency, we made use of 33 years of seasonal rainfall data from year 1983 to 2015 of Khozestan Province (Iran). The model were trained with 28 years of seasonal rainfall data. The ANN approache is applied to the data to derive the weights and the regression coefficients respectively. The performance of the model was evaluated by using remaining 5 years of data. The study reveals that ANN model can be used as an appropriate forecasting tool to predict the rainfall.

This study was designed to investigate the biochemical effects of graded doses of aluminum on some serum lipid profile (SLP) of male wistar albino rats. A total of twenty-four male albino rats of 10-12 weeks of age were used for the study. They were randomly assigned to six groups (Groups A-D) of six rats each. The treatment groups-A to C were administered aluminum as aluminum chloride (AlCl3) : 0.38, 3.8, and 38 mg/kg body weight while group D received 0.2ml normal saline which served as vehicle. Assay of the SLP were carried out using standard biochemical methods after 14 days. The results showed that serum total cholesterol of the treatment group administered 38mg/kg decreased significantly (p<0.05) relative to the control whereas the serum low density lipoprotein (LDL) of the treatment groups administered 3.8mg/kg and 38mg/kg decreased significantly (p<0.05) relative to the control after 14 days of treatment. The treatment group administered 0.38mg/kg showed a decrease in serum total cholesterol and low density lipoprotein but were not statistically significant (p>0.05).

This study is a first neuropsychological evaluation of cognitive Impairment generated by the job strain to the teleoperators in call centers in sub-Saharan Africa; Particularly in the Democratic Republic of Congo, city of kinshasa. This study established a statistically significant relationship between Exposure to psychosocial factors (high psychological demand and low decision latitude) and the appearance of job strain in teleoperators. It also showed a statistically significant relationship between job strain and the appearance of cognitive disorders in teleoperators. Lastly, the exposure duration at the call center of six months or more, was retained as necessary time to see the psychosocial factors negatively impacting the mental health of the call center teleoperators.

This study seeks to achieve a complete elucidation of structures of unknown Eudesmane sesquiterpenes from their 13C values. The 13C values for each of the fifteen (15) positions of the skeletons of the Eudesmane compounds were predicted using Generalized Regression Neural Network (GRNN). From the predicted 13C values, GRNN and Scatter Plot methods were used to predict the substituents attached to each position on the skeleton of the Eudesmane compounds. Recognition of the test compounds ranged between 40 and 100%. GRNN and Scatter plots demonstrated great potential for use in the structural elucidation of unknown compounds from 13C values.