The main objective of this research paper is to explore and investigate the customer satisfaction level of Berger paints Bangladesh limited. Berger, the market leader in the Bangladesh paint market, is one of the oldest names in the global paint industry. This Research paper will help the company to measure the present level of customer satisfaction and loyalty in Berger paints. This research investigates the factors that affect the level of customer satisfaction among the users, and what are the different influencing them. It has been used simple random sampling under the probability sampling method and used structured questionnaire for collecting information. This research used Microsoft Excel to analyze data. Major findings shows that customer of Berger paints are mostly satisfied about perceived product quality, product reliability, product durability, product availability & size, product innovativeness, product relationship and delivery performance. In case of service quality and customer care service one – third respondents are dissatisfied.

Cell-mediated immunity is critical for the prevention and control of Foot and Mouth Disease (FMD). Despite significant advancements in modern vaccinology, inactivated whole virus vaccines for FMD remain the mainstay for prophylactic and emergency uses. Emergency vaccination as part of the control strategies against foot-and-mouth disease virus (FMDV) has the potential to limit virus spread and reduce large-scale culling. Many efforts are currently devoted to improve the immune responses and protective efficacy of these vaccines. Adjuvants, which are often used to potentiate immune responses, provide an excellent mean to improve the efficacy of FMD vaccines. Aim: To evaluate three oil adjuvants namely: Montanide ISA- 206, ISA-201 and ISA- 61 for adjuvant potential in inactivated FMD vaccine by determination of the produced amounts of interferon-gamma (IFN-gamma) in cattle vaccinated with FMD trivalent vaccine adjuvanted with different Montanide oils using interferon-gamma Assay for evaluation of FMD virus-specific cell-mediated immunity.

Archaeotourism can take place in two main forms: i) on site or locations of discoveries; and ii) assembling the discoveries into museums or exhibitions. Given that the first option in Kosovo has not proven viable, a marketing strategy went on to be explored for the latter in broad terms by taking into account Bronze Age artifacts with engravings from the sacred geometry discovered by the Author of this paper during 2013-14, which were the work of ancient Illyrians. Yet, the results suggesta third alternative of archaeotourism development, and that is the interest by respective foreign scholars, institutions, and foundations by using Long Tail marketing approach. The paper interprets some astrological metaphors of sacred geometry in literature review, but draws conclusions from archeological discoveries.

The Traffic Light approach as a technical procedure was first developed for monitoring the status and level of risk faced by a fish population from fishery-related, environmental, and economic variables (Caddy 1999a). It has also facilitated stock management and stock recovery, in both cases where supporting data series and stock assessment skills were limited. Nonetheless, since the early 2000’s, the range of applications for this methodology have proliferated dramatically into most social and economic sectors, and after a description of the application of the traffic light procedure to fisheries, a second objective of this paper is to show some examples of the recent diffusion of this methodology to a much wider range of applications.

Clustering is a technique in data mining which divides given data set into small clusters based on their similarity. K-means clustering algorithm is a popular, unsupervised and iterative clustering algorithm which divides given dataset into k clusters. But there are some drawbacks of traditional k-means clustering algorithm such as it takes more time to run as it has to calculate distance between each data object and all centroids in each iteration. Accuracy of final clustering result is mainly depends on correctness of the initial centroids, which are selected randomly. This paper proposes a methodology which finds better initial centroids further this method is combined with existing improved method for assigning data objects to clusters which requires two simple data structures to store information about each iteration, which is to be used in the next iteration. Proposed algorithm is compared in terms of time and accuracy with traditional k-means clustering algorithm as well as with a popular improved k-means clustering algorithm.

The Internet has revolutionized, and continues to profoundly affect, the way one does business. Since the Internet has become a main source of communication both within and outside organizations, they are caught between providing Internet access to employees to perform job related activities and monitoring employees’ use of Internet without infringing on their rights and privacy. This study therefore examined the extent of Internet access and use, pervasiveness of Internet monitoring, availability of Internet use policy and compliance to Internet use policy in the selected organisations. The study adopted ex post facto survey design. Stratified random sampling was used to select 246 organisations comprising those in public, private, not for profit and non-governmental sectors. An adapted questionnaire from Alampay and Hechanova’s 2008 study was used to collect data from the organisations. One hundred and eighty three (74.4%) copies of returned questionnaires were used for data analyses. Descriptive statistics specifically frequency, percentage distribution and cross tabulation were used for data analyses. Findings revealed that two-third of the organisations provide Internet access to employees depending on their job category. However, some organisations monitor employee Internet use and also have Internet use policy. Majority of the organisations are concerned about the content accessed by their employees and therefore blocked some online content and applications particularly those related to pornography, gaming and social networking. Most organisations reported difficulties with employees’ excessive chatting that is non-work related and accessing pornography at work. In addition, private organisations monitor employees’ Internet use most. The results suggest the need for more organizations to articulate their policies on Internet use, educate workers on Internet security and formulate mechanisms to ensure the integrity of employee monitoring. Thus, organis

Background: Cervical cancer remains the most common cancer in women in Eastern Africa. Theestimated Incidenceof Cervical Cancer was about 42.7 and Mortality rate of 27.6 per 100,000. InEthiopia, Current estimates indicate that every year 7095 women are diagnosed with cervical cancer and4732 die from the disease.Due to lack of awareness about the disease, inadequacy or lacking ofscreening programs in less developed countries-Ethiopia, the incidence of the disease is increasingalarmingly. This study Assessed the Knowledge about cervical cancer and its associated factors amongreproductive age women at Robeand Goba towns, Bale zone, south east Ethiopia, 2015.Methodology:A community based cross-sectional survey was conduct from February to May 2015 inRobe & Goba towns, southeast Ethiopia. Three Hundred sixty three households having at least onewomen aged 15-49 were included in the study. Systematic sampling method was used to select thehouseholds.A structured questionnaire was used to collect the data. Ten trained Urban Health Extensionworkers were collected the data. Binary and Multiple Logistic regression methods were use to identifyindependent predictors of the knowledge of women on the cervical cancer.

This paper aims to examine the relationship between gross domestic product and Indian stock market from a sectoral perspective by using quarterly time series data from 2003:Q4 to 2014:Q4. Ng-Perron unit root test is utilized to check the order of integration of the variables. The long run relationship is examined by implementing the ARDL bounds testing approach to co-integration. VECM method is used to test the short and long run causality and variance decomposition is used to predict long run exogenous shocks of the variables. The results of the ARDL bounds test confirm the existence of a cointegrating relationship between sectoral GDP and sectoral stock price in India. The results from long-run and short-run coefficient reveals that sectoral price indices are significantly influenced by changes in the respective sectoral GDP in the long-run, whereas, crude oil price is an important factor influencing the sectoral prices in the short-run. The granger causality test demonstrates a unidirectional short-run causality running from manufacturing sector GDP to aggregate stock price index of manufacturing sector. Further, the short-run causality running from electricity, gas and water supply sector GDP to respective sector stock price index. However, unidirectional short-run causality is absent in the service sector.

Onion (Allium cepa L.) is an important vegetable crop for small and commercial growers in Ethiopia where it is produced for both the local and export markets. But loss can be as high as 66% during storage due to loss in bulb fresh mass and sprouting. A study was therefore, conducted with the objective of optimizing curing and topping time for maximum bulb and storage life of onion quality and maximum days of storage on Onion cv. Bombay Red, at Melkassa Agricultural Research Center, Ethiopia, from January to May 2012. Bulbs were cured under shade for 0, 5, 10 and 15 days, respectively. The tops removed immediately, or removed 5, 10 or 15 days after curing or not at all. The experiment was laid out as a RCBD factorial(4x5x7 curing, topping, storage time respectively) and each treatment combination replicated three times. Data were collected with 15 days interval up to 90 days after curing. Data collected included spouted and rotted bulb percentage, bulb total soluble solids (TSS), bulb dry matter, and bulb fresh mass total loss and bulb color.

The earlier defect prediction and fault removal can play a vital role in ensuring software reliability and quality of service. In this paper Hybrid Evolutionary computing based Neural Network (HENN) based software defect prediction model has been developed. For HENN an adaptive genetic algorithm (A-GA) has been developed that alleviates the key existing limitations like local minima and convergence. Furthermore, the implementation of A-GA enables adaptive crossover and mutation probability selection that strengthens computational efficiency of our proposed system. The proposed HENN algorithm has been used for adaptive weight estimation and learning optimization in ANN for defect prediction. In addition, a novel defect prediction and fault removal cost estimation model has been derived to evaluate the cost effectiveness of the proposed system. The simulation results obtained for PROMISE and NASA MDP datasets exhibit the proposed model outperforms Levenberg Marquardt based ANN system (LM-ANN) and other systems as well. And also cost analysis exhibits that the proposed HENN model is approximate 21.66% cost effective as compared to LM-ANN.