Application and Analysis of Retail Inventory Using Data Mining Techniques

Data mining is one of the most essential tools for gathering information from different datasets in almost all recent industries. In this 21st-century, data mining gained attention because of its significance in decision making, and it has become a key component in various industries such as retail. Inventory management requires pre-planned goals and attention to detail, and prioritizing items that require less attention can be a waste of time and resources. Learning indications about customers2019; shopping patterns by showing associations among various provides significant value in managing retail inventory. In the present research paper, popular data mining techniques have been applied and analyzed for multi-item inventory management in retail sales stores to show how data mining techniques can optimize and organize the retail inventory

Evaluation of Ant Colony Optimization Algorithm Compared to Genetic Algorithm, Dynamic Programming and Branch and Bound Algorithm Regarding Travelling Salesman Problem

We use ant colony optimization (ACO) algorithm for solving combinatorial optimization problems such as the traveling salesman problem. Some applications of ACO are: vehicle routing, sequential ordering, graph coloring, routing in communications networks, etc. In this paper, we compare the performance of ACO to that of a few other state-of-the-art algorithms currently in use and thus measure the effectiveness of ACO as one of the major optimization algorithms in regard with a few more algorithms. The performance of the algorithms is measured by observing their capacity to solve a traveling salesman problem (TSP). This paper will help to find the proper algorithm to be used for routing problems in different real-life situations

Diabetes in Malaysia: A situational study on prevalence factors of the disease based on socioanthropological explorations

Diabetes has now become an acute health hazard causing illness to many people around the world and as such, Malaysia is not an exception. Although genetics and certain epidemiological factors often contribute much to the development of this disease, there is no denying the fact that certain socio-cultural factors like food habits and lifestyles often accentuate the cause and growth of this disease contributing to further of its deterioration. Diabetes prevalence rate has been found to be increasing at a very alarming rate in Malaysia, almost doubling the number since two decades bringing it 15.2% in 2011.This paper thus provides some empirical data based on a field study conducted among patients living in and around Kuala Lumpur in Malaysia. Methodology and Data Sources: Based on convenience sampling, the research adopted the snowball technique in identifying a total of 70 diabetic patients at the National Institute of Diabetes and its catchment areas where they were interviewed extensively to generate some basic socio-economic and numerical data. The research also utilized a triangulation of qualitative techniques including in-depth interviews, personal and group discussions and a few focus group discussions (FGDs)through patients’ participation. Major Findings: The paper describes the socio-cultural situations of diabetes in Malaysia and contextually depicts the real situation of the disease in the country. Through identifying the significant socio-economic variables, the research relates the life and living styles of the patients from multi-ethnic and multi-cultural backgrounds. In relation to the questions that cover the major causes of diabetes, an overwhelming majority of the respondents however, sweepingly assessed and identified both genetic component and indiscriminate food habits as important susceptible factors for diabetes. It could not however, fully affirm the genetic cause as the most significantly overwhelming factor for Malaysia, as many of the patients’ parents and grandparents in the past did not have diabetes in their early and middle periods of their life which leads us to believe that diabetes in Malaysia at large is a recent emergence. Conclusions and Final Comments: In the concluding comments, the paper identified multi-causative factors for diabetes in Malaysia and thus suggests that Malaysian Government and policy planners should take note of all these issues for future protection

Farmer's perception, observed trend and adaptation measures to climate change: Evidence from wheat farmers in Bangladesh

Wheat, the first grain crop in the world, can be negatively impacted by varying temperatures and precipitation patterns, which may pose a threat to the food security. Therefore, the objective of this study is to investigate wheat farmers perception of and adaptation to climate change. Cross-section and historical data on climate variables were used. Cross-section data was collected from 600 wheat farmers in various Agroecological Zones (AEZ) through face-to-face interviews. Descriptive statistics, time-trend regression, and the multinomial logistic regression (MNL) model were used to analyze the data. Using actual meteorological data, a climate change analysis corroborated the farmers' perceptions regarding the variability of temperature and precipitation. Changing planting dates (23 %) and cultivation of short duration wheat varieties (17 %) were identified as the major adaptation measures to climate change, while about 19 % of farmers did not undertake any adaptation measures. Access to climate information increased the likelihood of adopting short-duration wheat varieties by 8.57 % and changing planting date by 9.32 %, while credit access increases the likelihood of adopting short duration wheat varieties by 8.86 %. Increasing awareness of climate change, intensifying extension activities, increasing access to climate information, and modifying wheat production techniques can all help farmers become more resilient to climate change, thereby ensuring food security under changing climate