This paper examines the possibility of adopting cleaner production (CP) practices as a sustainable approach along the tea supply chain in the tea industry under small and medium-sized enterprises (SMEs). Data were collected through questionnaires, in-depth interviews, and observation from 100 farmers, 60 transport drivers, and 5 SME factories. The observation showed that the average monthly raw tea leaf yield per acre was 499.03 kg. Further, to produce 1 kg of black tea, 4.53 kg of fresh tea leaves, 0.30 hours of human energy, and 0.89 kWh of electricity were required. Additionally, there was a significant inorganic fertiliser usage in the sector's planting and plucking stages. The study recommends reducing water consumption, practising wastewater treatment, promoting good manufacturing practices and teamwork, shifting to organic fertiliser, growing ground tea plants instead of basket tea plants and improving the motivation and attitudes of workers as CP options.
To eradicate malnutrition problem in rural areas of developing countries like Bangladesh, the Government of Bangladesh started school feeding programme as a pilot project. But the current operational structure of the programme does not provide varying nutritious foods and has no reliable monitoring system. To eradicate the problems, this paper proposes a complete solution residing in a mobile application for school feeding programme. This paper provides a meal generation system based on remaining budget, attendance on each day, nutrition, and students' preference. After serving the selected meal, the meal serving process is monitored by first recognising students who were present before serving the meal through face recognition and then recognising if the selected meal was served through food recognition. The evaluation result verifies that our food recognition model achieves up to 98% precision and almost 80% of users are satisfied with our android application features for the school feeding programme.
Homelessness is a state in which a person does not have access to an appropriate housing facility for living. The number of homeless people in developing countries like Bangladesh is on the rise. But due to a lack of proper prediction and assistance systems, they could not get the basic needs they deserve. This paper focuses on gaining useful insights into why people are becoming homeless in our country and which criteria can be selected for identifying homeless people effectively. Based on the data from the survey, this paper created a dataset for homeless people and applied five machine learning classifier algorithms to find out the best one for creating the prediction model for identifying homeless people. This paper also developed an Android Homeless People Aid application to provide immediate help to homeless people. The prediction model was also integrated into the application. The results highlight the usefulness of this work.
In this paper, how to collect the data related to personal information of students by smart education system (SES), and how to open these data to faculty members for improving online education at Kanazawa University are discussed from the perspective of SES design and user usage. In the new era of big data, administration and education management in universities adopt online SES. Even though Kanazawa University started to encourage faculty members to start dynamic teaching course using SES, few faculty members use the SES to improve the education style because they must teach in the ordinal classroom way. However, SES improves the convenience of personal information management of registered students in universities, including basic information, course registration, course grade, consultation record, etc. In this paper, we investigated the problems with ordinal classroom currently in the case that SES has been installed.
In this paper, we address the multi-vehicle covering tour problem where only the restriction on the number of vertices in each route (m-CTP-p). The objective of the m-CTP is to minimise the total routing cost and fulfill the demand of all customers such that each customer which is not included in any route must be covered. Each covered vertex must be within a given distance of at least a visited vertex and the number of vertices on a route does not exceed a pre-defined number p. We propose two approaches to solve this variant. First, we develop a genetic algorithm (GA) using an iterative improvement mechanism. Then, an effective hybrid genetic algorithm (HGA) is developed in addition to a local search heuristic based on variable neighborhood descent method to improve the solution. Extensive computational results based on benchmark instances on the m-CTP-p problem show the performance of our methods.
Green initiatives in businesses have received attention in recent years and human resource management (HRM) departments have important role to play. The study sought to explore the awareness and promotion of green HRM in the University of Cape Coast, Ghana. The study was qualitative and adopted a case study design. Nine non-academic senior members whose work involved green HRM practices were purposively sampled, and in-depth interviews were conducted to collect qualitative data, which were analysed using inter-textual analytical tool. It emerged that participants had none to moderate knowledge of green HRM; UCC had not made any special effort to spread the awareness; and there was no documented policy on green HRM. However, there were some green HRM interventions though employees were not aware of being green HRM practices. It is recommended that the university should design a green HRM policy and to make employees aware of the importance of practicing green HRM to contribute towards the achievement of environmental sustainability.
Hand sanitisers have emerged as basic necessities with the outbreak of the COVID-19 pandemic. The study aims to understand consumer behaviour towards hand sanitisers and to highlight the attributes of hand sanitisers which consumers consider important while selecting a hand sanitiser to purchase. Primary and secondary data are collected and are statistically analysed. Exploratory factor analysis (EFA) is performed to develop a factor structure. The six factors which emerge from the analysis include ingredients of the sanitiser, properties of the sanitiser, branding of the sanitiser, efficacy of the sanitiser, cost-effectiveness of the sanitiser, and alcohol content in the sanitiser. This research would be useful for academicians and researchers who could develop hand sanitisers which are more hygienic and consumer friendly. Marketing managers of firms selling hand sanitisers would greatly benefit as this study could help them shape their marketing campaigns and in turn improve their product sales.
