• Korean Journal of Community Nutrition
• /
• v.12 no.3
• /
• pp.322-332
• /
• 2007

The purposes of this research were to examine the effect of the catering company's dietetic internship program through a self-evaluating ability test about management performance between pre and post internship programs and consequently to suggest improvement in the internship program. In this study, two types of questionnaires were conducted in July and October 2006, targeting 41 dietetic interns who trained in a 6 months internship program. Except the 4 dropped interns, data from 37 interns were collected and used for statistical analysis, using the SPSS Win 11.0 version. The results of this study were as follows: First of all, the analysis on the effect of the internship program according to classified management segments showed significant improvements in the following order: purchase management (p<0.001), computer program management (p<0.001), facilities management (p<0.001), accounting management (p<0.01), personnel management (p<0.01), retention management (p<0.01), sanitation management (p<0.01), service management (p<0.01) and foodservice management (p<0.01). However, there was no significantly improvement in management of clients. Secondly, the result of the analysis on the details of each management segment that were significant improvement and changing score was the top 5 duties were as follows: In the purchase management, the score of weekly and daily order management was increased 1.0 (p<0.001), the score of weekly inventory management was 0.81 (p<0.001). In the computation office management, expenses handling through a computer program was 0.65 (p<0.01). In the personnel management, the score of work schedule management increased 0.81 (p<0.001). In the accounting management, the score of monthly profit and loss account management was 0.65 (p<0.001). Furthermore, qualified educational programs connected with the internship program will have to be systematically developed and continually carried out in order to improve service and management abilities of branch managers.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.5
• /
• pp.82-96
• /
• 2020

The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.

• KNOM Review
• /
• v.22 no.1
• /
• pp.60-67
• /
• 2019

Graphical Processing Units(GPUs) achieve high performance undertaking from relatively uniformed computation in parallel. The technology related to General Purpose GPU(GPGPU) has been enhanced, which provides concurrent kernel execution of multi and diverse applications at the same time, but it is still limited to support resource sharing or planning. NVIDIA recently introduces Multi-Process Service(MPS), which allows kernels from different applications can be execute concurrently. However, the strength of MPS comes along with the characteristics of applications and the order of their execution. This paper shows the performance analysis of diverse scientific applications in real world. Based on the analysis, we prove that it is important to the identify characteristics of co-run applications, and to schedule multiple applications via profiling to maximize MPS functionality.