• 산업경영시스템학회지
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• 제27권4호
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• pp.170-178
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• 2004

As quality becomes a primary leading factor of organizational success, various management strategies have been introduced to improve quality competitiveness. Quality competitiveness, however, is difficult to measure and numerous organizations are struggling to set realistic improvement objectives. The primary purpose of this research is to propose a systematic approach to help the practitioners develop an improvement plan for their organizational quality competitiveness. This approach employs DEA(Data Envelopment Analysis) to evaluate relative efficiency among companies which make efforts to improve their quality competitiveness. It presents an integer programming model to elicit an optimal improvement plan for meeting a target level. A decision support system is also developed for the managers to plan a sequential improvement plan based on both DEA model and the integer programming model.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.171-178
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• 2019

Computational Thinking is one of the biggest issues in the era of the Fourth Industrial Revolution. It is a core literacy required not only for SW major but also for all students including them. It is not a simple computer software education, but a coding education based on Computational Thinking, and it should be able to solve the problems in everyday life and to express the process and solutions. However, in the case of students who lack background knowledge on SW and programming languages for development, it is hard to know how to algorithmize problems and express them using computer devices. In this study, we proposed a education course model to improve the students' thinking skills and to express them effectively. In addition, we confirmed whether the non-major students who learned through this education course model can express various problems related to the major field by integrating them with computing accidents and improve the problem solving ability.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.489-492
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• 2016

Transportation in the logistics, many business organizations are engaged in monitoring and tracking the vehicles in order to improve logistics services, reduce expenses and secure security in cargo transportation. It is saving time and money by tracking and monitoring vehicles which transport cargo in supply chain of logistics. Therefore the main issue of delivery flow is to improve services, and ensure the safety in transportation system. This article suggests the tracking and monitoring model to keep safety transports on ICT network. It focuses on precise delivery control by monitoring and tracking vehicles to save time and costs. The status of product movement is analyzed for proper decision making. The vehicle embedded with RFID is automatically tracked in the movement process by tracking and monitoring model. The main role keeps safety tracking to reduce costs and to deliver products at proper time and location.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.701-708
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• 2021

As one of the most widely used technology in the world right now, Face recognition has already received widespread attention by all the researcher and institutes. It has been used in many fields such as safety protection, surveillance system, crime control and even in our ordinary life such as home security and so on. This technology with today's technology has advantages such as high connectivity and real time transformation. But we still need to improve its recognition rate, reaction time and also reduce impact of different environmental status to the whole system. So in this paper we proposed a face recognition system model with improved CNN which combining the characteristics of flat network and residual network, integrated learning, simplify network structure and enhance portability and also improve the recognition accuracy. We also used AR and ORL database to do the experiment and result shows higher recognition rate, efficiency and robustness for different image conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4463-4482
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• 2020

Mesh model generated from 3D reconstruction usually comes with lots of noise, which challenges the performance and robustness of mesh simplification approaches. To overcome this problem, we present a novel method for mesh simplification which could preserve structure and improve the accuracy. Our algorithm considers both the planar structures and linear features. In the preprocessing step, it automatically detects a set of planar structures through an iterative diffusion approach based on Region Seed Growing algorithm; then robust linear features of the mesh model are extracted by exploiting image information and planar structures jointly; finally we simplify the mesh model with plane constraint QEM and linear feature preserving strategies. The proposed method can overcome the known problem that current simplification methods usually degrade the structural characteristics, especially when the decimation is extreme. Our experimental results demonstrate that the proposed method, compared to other simplification algorithms, can effectively improve the quality of mesh and yield an increased robustness on noisy input mesh.

• East Asian Economic Review
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• 제25권4호
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• 대한안전경영과학회지
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• 제24권1호
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• pp.1-9
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• 2022

The growth of the online market is accelerating due to the development of technology and the pandemic era. The delivery service through the courier must be used to deliver the ordered goods to the customer through the online market. With the growth of the online market, the logistics market for delivery is also growing. The traffic and environmental problems are emerging as social issues. Urban logistics technology using underground space based on the urban railway developed to improve logistics efficiency in a metropolitan area and a new alternative to environmental problems. This study proposed a plan to secure system safety through safety analysis based on operational concept definition and scenario analysis by applying model-based perspective analysis to the system under development.

• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.221-227
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• 2021

An early warning system was developed to help identify stock status as early as possible. For performance to improve, there needs to be a feature to predict the amount of stock that must be provided and a feature to estimate when to buy goods. This research was conducted to improve the inventory early warning system and optimize the Reminder Block's performance in minimum stock settings. The models used in this study are the single exponential smoothing (SES) method for prediction and the economic order quantity (EOQ) model for determining the quantity. The research was conducted by analyzing the Reminder Block in the early warning system, identifying data needs, and implementing the SES and EOQ mathematical models into the Reminder Block. This research proposes a new Reminder Block that has been added to the SES and EOQ models. It is hoped that this study will help in obtaining accurate information about the time and quantity of repurchases for efficient inventory management.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.117-121
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• 2015

Construction managers use scheduling methods to improve the outcome of their project. Despite the many obvious advantages of the critical path method (CPM), its use in construction has been limited. Understanding the reasons why CPM is not used as extensively as expected could improve its level of acceptance in the construction industry. The link between construction scheduling methods and the tasks expected to be performed by schedulers has been an on-going concern in the construction industry. This study proposes a task-technology fit model to understand why CPM is not used as extensively as expected in construction scheduling. A task-technology fit model that aims to measure the extent to which a construction scheduling method functionally matches the tasks expected to be performed by the scheduling staff. The model that is proposed is an answer to the lack of proper instruments for evaluating the extent to which scheduling methods are used in the industry.