• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10c
• /
• pp.443-447
• /
• 2006

경영환경의 변화에 대한 기업의 대처능력이 곧 생존에 직결되고 있는 시점에서 이에 대한 해결책으로 통합업무 프로세스를 지향하는 ERP(Enterprise Resource Planning)을 통하여 경쟁력을 강화하려는 노력이 진행되고 있다. 그러나 ERP는 적용상의 어려움과 실제 업무와의 차이점으로 인하여 막대한 노력을 들이고도 성공적으로 업무에 활용되지 못하는 사례가 많은 실정이다. 특히 건설업의 경우는 주문생산 방식의 프로젝트 특성 및 영세한 외주업체와 협업해야 하는 환경요인으로 인해 전산환경과 정보화에 많은 제약사항들을 가지고 있다. 본 연구에서는 건설업체 D사의 예를 들어 건설업 ERP 패키지를 도입하여 업무 개선에 적용한 사례를 소개하였다. 건설사 고유 업무인 공사관리 업무 및 일반관리 업무를 대상으로 현행 프로세스를 진단하고 문제점을 도출하였으며 ERP의 Best Practice를 바탕으로 프로세스 개선방안을 제시하였다. 회사는 ERP와 유기적으로 연결된 개선안의 추진을 통해 지속적인 경영혁신 활동의 토대를 구축하였으며 이에 따른 정성적, 정량적인 성공요인을 분석하였다.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
• /
• v.25
• /
• pp.189-210
• /
• 2005

The application of 4PL could allow for the efficiency of many logistics operations to be greatly increased, for costs to be reduced, and for operations to become more responsive to consumer demand. It is also possible that higher services level and lower cost products could become available as a consequence. However, in order to implementing 4PL actually it is very important to be met to fundamental determinants of 4PL such as formation of logistics experts group, providing of total logistics service, capacity of IT, implementation of e-Business model, capacity of logistics consulting, higher logistics service level, logistics cost reduction, re-engineering of logistics process, focus of core competence etc.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1998.10a
• /
• pp.255-261
• /
• 1998

본 연구는 물류산업에 있어 중심의 위치를 차지하고 있는 항만산업에서 컨테이너 터미널 운영 기업(Container Terminal Operating Company, TOC)들이 현재 처해 있는 경제 상황하에서 생존을 하기 위해 어떠한 모습으로 변화되어야 할 것인지, 그리고 21세기를 선도하기 위하여 TOC들이 반드시 갖추어야 할 역량이 무엇인가에 관한 체크리스트와 미래를 어떻게 대비해 나가야 하는가에 대한 로드맵(roadmap)을 제시하고자 한다. 먼저 국내의 컨테이너 터미널 운영 기업들이 현재 처해있는 환경에 대한 새로운 인식을 통해 컨테이너 TOC들의 목표를 재 설정하고, 차세대 컨테이너 TOC의 모델을 제시한다. 그리고 이에 대한 추진과제를 설정하고 이렇게 설정된 과제들 중에서 정보시스템 부분에 대한 실행 계획 및 요소 기술, 추진 전략 등을 제시한다.

• Journal of KIISE:Computing Practices and Letters
• /
• v.6 no.5
• /
• pp.528-535
• /
• 2000

This paper aims at providing guidelines enabling productive software construction by offering reusable modules which is used not only for effective maintenance for each step, but also for a re-engineering process after analyzing developed source code. There are four processing steps. The first is to analyze source code. The second is module slicing and clustering using McCabe and BP/Win Tools, The third is to transform the outputs extracted from the business model to reusable modules. The final step is to design repository and to construct a system. In this paper, we applied the fourth step to our case study, which was specified from the first step to the fourth. The specified fourth step contains various things for constructing repository. And the fourth step reanalyzes informal and unstructured information by using reverse engineering tools, in order to provide effective guidelines for productive software maintenance and re-engineering.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.1
• /
• pp.32-41
• /
• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.89-106
• /
• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.539-545
• /
• 2013

Although individual-level factors (e.g., attitudes, personality) have long been associated with day-to-day attendance decisions, increasingly researchers have recognized "the social nature of attendance dynamics and their susceptibility to social control (Johns, 2008)." Implications of this social approach for research would be to focus attention on the causes and effects of absence culture (i.e., absence-related perceptions, beliefs, values), and the effects of absence culture on individual and group attendance within social units. Construction projects typically require workers to work in teams or crews on highly interdependent projects, and, thus, are particularly relevant contexts to study absence culture. In this paper we apply a system dynamics (SD) model to study absence culture by utilizing the advantages of SD in capturing a feedback process and state changes. We were particularly interested in: (a) the awareness of social norms within construction crews that pertained to attendance, (b) the interplay between formal attendance rules (policy) and these social norms, and (c) how these sources of influence affected the decision-making process of construction crew members. We expect that the results of this work will help construction organizations evaluate (or re-consider) the effects of their attendance control policies (e.g., timing, strength, and frequency) within a social context. Moreover, our findings suggest that the key to reducing excessive absences might be to invest time in influencing absence culture directly rather than imposing frequent and strict regulations - which, in turn, may inadvertently fortify a culture that works against the organization's interests.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2006.11a
• /
• pp.145-149
• /
• 2006

Building Information Modeling (BIM) is the process of integrating and re-using information generated and used throughout the lifecycle of a building. BIM may not be very different from other management methods in that it aims to minimize the economic loss and maximize the profit by designing, building, and maintaining a building better, faster, yet cheaper. The major difference between BIM and other methods is that BIM approaches the goal from a system point of view whereas other methods generally approaches the goal from a business management point of view. Since a project cannot succeed without considering both systematic and managerial aspects of a project, the line has been blurred these days. This paper explores a historical background of BIM and discusses the key technologies for successful implementation of BIM.

• International Journal of Quality Innovation
• /
• v.6 no.2
• /
• pp.59-89
• /
• 2005

Manufacturing Resources Planning (MRPII) is one kind of manufacturing information system that can help manufacturing companies gain competitive advantages. It is estimated that more than one hundred MRPII systems are available in the market, many of them are mature enough to solve most operational issues in accordance with users' requirements. More often than not, many of these systems provide more functions than a company expects. Manufacturing companies worldwide have attempted to implement these MRPII systems, however, many companies experienced failure (Turbide, 1996) due to managerial rather than technical issues. The authors propose an approach utilising a roadmap to integrate BPR and the MRPII implementation in order to overcome this difficulty. A detail road map is developed to guide this implementation, which is designed using a hierarchical analysis technique known as Integrated DEFinition Method (IDEF). IDEF is a systematic manufacturing management and integration-modeling tool. The proposed approach is implemented and illustrated using a reference company and the results indicated that 66% reduction in errors for maintaining the bills of materials system; 99% reduction in time to carry out material requirement planning; and 70% reduction in time previously taken for non-productive discussions.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.501-506
• /
• 2021

Under the pressure of business competition and effectiveness, more and more organizations in the world are likely to apply modern software such as enterprise resource planning (ERP) which can help them to create better organizing practice, better managing capabilities of administrators, and better operations of personnel. In Vietnam, many firms are afraid to install it and the number of firms adopting this software is limited mainly due to the insufficient scientific evidence of the successful implementation of ERP. This study aims to identify and measure the factors influencing the successful implementation of ERP of firms in Vietnam. Qualitative research methodology combined with quantitative research methodology is used. The data are surveyed with 343 administrators of 45 organizations that have successfully deployed ERP in Ha Noi and Ho Chi Minh cities. Of these 19 were excluded from analyses due to unsatisfactory responses, and only 324 were used for statistical processing. The collected data were processed by using the SPSS software. The result of the study shows that there are six factors affecting the successful implementation of ERP of firms in Vietnam, (ranked in descending order of importance), they are top management commitment and support, business process re-engineering, user involvement, project management board, vendor support, and suitability of software and hardware.