• The Journal of Asian Finance, Economics and Business
• /
• 제7권2호
• /
• pp.301-308
• /
• 2020

This study focuses on determining the impacts of organizational culture on the accounting information system and the operational performance of small and medium-sized enterprises in Ho Chi Minh City. The paper is organized in five parts: introduction, literature review, research methodology, research results, and conclusion and policy implications. Based on the samples of 353 respondents working in small and mediumsized enterprises in Ho Chi Minh City, the research employs both qualitative and quantitative methods to find the answers for research questions. Group discussion, which yields final observed variables of the factors of organizational culture is used for qualitative method. Statistics, assessment of the reliability of Cronbach's Alpha scale, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) are used for quantitative procedure. The results show that mission, involvement and inconsistency in organizational culture positively affect the accounting information system of small and medium-sized firms in Vietnam. In addition, mission, involvement, adaptability and consistency in organizational culture are found to have positive impacts on the firm operational performance. Another finding of the study is that the accounting information system has a positive effect on operational performance of small and medium-sized firms in Vietnam.

• 한국멀티미디어학회:학술대회논문집
• /
• 한국멀티미디어학회 2000년도 춘계학술발표논문집
• /
• pp.328-331
• /
• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• 한국정보시스템학회지:정보시스템연구
• /
• 제10권1호
• /
• pp.257-278
• /
• 2001

An IR(information retrieval) index for dynamic document databases where insertion, deletion, and update of documents happen frequently should be frequently updated. As the conventional structure of IR index is, however, focused on the information retrieval purpose, its structure is inefficient to handle dynamic update of it. In this paper, we propose a new structure for IR Index, we call it Index Graph, which is organized by connecting multiple indexes into a graph structure. By analysis and experiment, we prove the Index Graph is superior to the conventional structure of IR index in the performance of insertion, deletion, and update of documents as well as the performance of information retrieval.

• 전자공학회논문지C
• /
• 제34C권7호
• /
• pp.70-81
• /
• 1997

In this paper, we propose HMCNN(hybrid multiple component neural networks) that enhance performance of MCNN by adapting new pattern partitioning algorithm which can cluster many input patterns efficiently. Added neural network performs similar learning procedure that of kohonen network. But it dynamically determine it's number of output neurons using algorithms that decide self-organized number of clusters and patterns in a cluster. The proposed network can effectively be applied to problems of large data as well as huge networks size. As a sresutl, proposed pattern partitioning network can enhance performance results and solve weakness of MCNN like generalization capability. In addition, we can get more fast speed by performing parallel learning than that of other supervised learning networks.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.119.4-119
• /
• 2001

It is the advantage of PLC that digitalization and networking of existing facility can be organized at low price because there is no need further construction of communication line considering that home appliance, information device and various kind of control devices are digitalized at low price. Moreover, AMR(Automatic Meter Reading) is very attractive to utility company because not only does it reduce the cost of reading meter, but also it can control and monitor the demand for energy. So, it can solve the consumers problem best and easily. It also can be easily realized that the utilities can expand there areas to values-added service through existing network. The performance of the PLC modem which is being developed now is not moven enough and much more test for outdoor modem is needed especially. Therefore, we, KEPRI, concentrate our efforts on configuring AMR system for test and investigation of the actual performance of various kinds ...

• 수산해양교육연구
• /
• 제28권1호
• /
• pp.289-299
• /
• 2016

The purpose of the study was to develop evaluation methods which would measure student achievement and progress without traditional paper-pencil tests such as mid-term and final examinations. More specifically, the main research focus were to establish general directions of student assessment during free semester, to build evaluation models supporting student's participation and learning, and to report and record various student evaluation results. As research results, we found that student evaluation of free semester should be organized to improve a) experience learning activity, self-regulatory and collaboratory study, b) high-order thinking ability and character-building, and c) teacher-student-parent cooperation. Since traditional paper-pencil tests were restricted in free semester, student achievement should be provided by a way of performance descriptions on transcripts rather than quantitative grade points. Student performance descriptions had to show not only subject knowledge but also students efforts, motivation, and participation. These multiple and educationally meaningful information would be collected by teacher-student-parent communication and collaboration.

• 산업경영시스템학회지
• /
• 제29권1호
• /
• pp.94-100
• /
• 2006

The risk management is an organized method for identifying and measuring risk and for selecting, developing, and implementing options for the handling of risk. The risk management covers all programatic and technical factors which affect the system development performance, cost, and schedule. While technical issues are primary concern for systems engineering, the three elements(performance, cost, and schedule) must be balanced for a successful risk management process. This paper proposes the risk management process for the KSLV-I(Korea Space Launch Vehicle-I) program using computer-aided systems engineering tool, Cradle. The risk management process of KSLV-I program is similar to the general risk management process, but it has its own specific features to manage large-scale complex characteristics of KSLV-I program.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 ITC-CSCC -3
• /
• pp.1859-1862
• /
• 2002

The replication of data is used to increase its availability, improve the performance of a system, and advance the fault-tolerance of a system. In this paper, it is required for the information about the location of a primary site of the replicas of each data item. The replicas of each data item are hierarchically organized to a tree based on the fact that the root is the primary replica in partially replicated databases. It eliminates useless propagation since the propagation can be done to only sites having replicas following the hierarchy of data. And our algorithm schedules transactions so that the execution order of updates at each primary site is identical at all sites by using timestamp. Using our algorithm, the consistent data are supplied and the performance of read-only transactions can be improved by using tree structure of replicas of each data item.

• 반도체디스플레이기술학회지
• /
• 제18권3호
• /
• pp.140-143
• /
• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• 디지털산업정보학회논문지
• /
• 제20권2호
• /
• pp.1-10
• /
• 2024

For the purpose of predicting credit card customer churn accurately through data analysis, a model can be constructed with various machine learning algorithms, including decision tree. And feature importance has been utilized in selecting better input features that can improve performance of data analysis models for several application areas. In this paper, a method of utilizing feature importance calculated from the MDI method and its effects are investigated in the credit card customer churn prediction problem with classification trees. Compared with several random feature selections from case data, a set of input features selected from higher value of feature importance shows higher predictive power. It can be an efficient method for classifying and choosing input features necessary for improving prediction performance. The method organized in this paper can be an alternative to the selection of input features using feature importance in composing and using classification trees, including credit card customer churn prediction.