Earticle

Recently, there is a substantial interest in implementing Business Process Management System(BPMS) among enterprises with the purpose of business process innovation. BPMS redesigns and coordinates business processes in terms of both automated steps and human involvement in order to maximize the value of both involved people and systems. The reason why BPMS is getting attention from top managers is that it has the possibility to optimize the business processes by cycling the process of modeling, execution, monitoring, evaluation, and redesigning work processes. Thus, it has created high expectations about not only productivity improvement but also business process innovation. However. having an innovative nature, which is used for process innovation, BPMS implementation has great potential to stir up employee resistance. The analysis and the discussion about the prevention of the resistance against IS(Information Systems) is important because IS change the way people work and also alter the power structure within the organization, in general. The purpose of this study is to investigate factors that have an impact on the effective adoption of BPMS at the enterprise level. To find out these factors, this study considers two characteristics of BPMS: First. BPMS shares some characteristics with other enterprise-wide IS such as ERP. Second, it has special BPMS-specific characteristics. Due to the lack of previous research on BPMS adoption, interviews were carried out with IT-consultants and CIOs who conducted BPMS projects previously to find out BPMS-specific features that would make BPMS unique when compared to other enterprise-wide IS. As a result, the monitoring function was chosen as the main BPMS-specific factor. Thus, this paper reviewed studies both on enterprise-wide IS adoptions, which applied Technology Acceptance Model (TAM) and secondly on computer based monitoring to find out factors that would influence the employees' perception on the monitoring function of BPMS. Based on the literature review, the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses, out factors that would impact the employees' perception on the monitoring function of BPMS. Based on the literature review the study suggested three factors that would have an impact on the employee's perception of the monitoring function: fairness of enterprise evaluation system, fairness of the boss, and self-efficacy of their work. Three factors that would impact the enterprise-wide IS adoption were also set: the shared belief in the benefit of BPMS, training, and communication. Then, these factors were integrated with TAM. Structural equation modeling was used to test hypotheses. The data analysis results showed that two among three monitoring function related factors - enterprise evaluation system and fairness of the boss - were significant. This implies that employees would worry less about the BPMS implementation as long as they perceive the monitoring results will be used fairly for their performance evaluation. However, employees' high self-efficacy on their job was not a significant factor in their perception of the usefulness of BPMS. This is related to cases that showed employees resisted against the information systems because they automated their works (Markus, 1983). One specific case was an electronic company, where the accounting department workers were requested to redefine their job because their working processes were automated due to BPMS implementation.

The research was performed to develop a CANDU-6 Core Monitoring System(CCMS) that enables operators to have efficient core management by monitoring core power distribution, burnup distribution, and the other important core variables and managing the past core history for Wolsong nuclear power plant unit 1. The CCMS uses Reactor Fueling Simulation Program(RFSP, developed by AECL) for continuous core calculation by integrating the algorithm and assumptions validated and uses the information taken from Digital Control Computer(DCC) for the purpose of producing basic input data. The CCMS has two modules; CCMS server program and CCMS client program. The CCMS server program performs automatic and continuous core calculation and manages overall output controlled by DataBase Management System. The CCMS client program enables users to monitor current and past core status in the predefined GUI(Graphic-User Interface) environment. For the purpose of verifying the effectiveness of CCMS, we compared field-test data with the data used for Wolsong unit 1 operation. In the verification the mean percent differences of both cases were the same($0.008\%$), which showed that the CCMS could monitor core behaviors well.

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.

Virtual Instrument는 컴퓨터를 Main controller로 두어 사용자가 필요로 하는 요소들을 연결하여 컴퓨터 속의 가상 공간에 사용자가 정의한 instrument를 구현하는 것을 그 기본 개념으로 한다. Virtual Instrument를 통하여 사용자는 여러 기능 및 함수를 소프트웨어적으로 추가할 수 있어 기존 방식에 비하여 보다 효율적으로 시스템 업그레이드 및 최적화를 수행할 수 있다. 또한 컴퓨터의 성능이 향상됨에 따라 Virtual Instrument의 성능도 증가하게 되는 기술적 이점을 얻을 수 있고 사용환경이 누구에게나 익숙하기 때문에 작업의 효율을 극대화시킬 수 있다 이러한 여러 효율성에 근거하여 나온 개념이 컴퓨터 기반의 제어 및 모니터링으로써 향후 네트워크 기술을 수용하여 더욱 발전될 것으로 전망되고 있다.

본 연구에서는 비교적 데이터 처리속도가 빠른 80286계의 CPU를 사용한 16bit 퍼스널 컴퓨터를 이용하는 경우보다, 가격면에서는 훨씬 유리하면서도, 성능은 거의 뒤지지 않는 피로시험 자동화 및 피로거동 고정밀 측정을 위한 시스템을 완성하였다. 본 연구에서 사용한 방법 및 작성한 소프트웨어등은 사용시험기, 피로연구 대상등에 거의 관계없이 이용이 가능하나, 여기서는 편의상, 시험기로서는 폐루우프(closed-loop)유압서어보 피로시험기를 사용하였으며, 피로거동의 측정에 대해서는 주로 피로균열지전을 대상으로 하였다.

Two kinds of 16bit-personal computer-based fatigue testing automation and monitoring system were constructed; one is Single-System utilizing a personal computer, the other si Dual-System consisting of two personal computers. The system developed in this study permits to perform multi-step programmed loading and pseudo-random loading fatigue tests, three parameters such as load, total displacement and subtracted displacement can be measured simultaneously. For improvements in measurements of fatigue behavior, two kinds of signal noise reduction software was developed. In addition, a software was also designed to automatically measure the crack opening point and crack length using the unloading elastic compliance technique.

Electronic fetal monitoring system is an easier ar d usual method in various prenatal and labor period fetal surveilence methods currently in use. But there haven't been enough cases of using the central monitoring system despite the fact that the bedside fetal monitoring system have already been widely in use in Korea as an essential medical equipment item. We have developed more efficient central fetal monitoring system based on the personal computer with the visual maternal monotoring device using infrared camera which processes the signals from existing bedside fetal monitoring systems such as H/P's 8040 series. And we have performed the clinical application on 41 pregnant women and the results were satisfactory. In conclusion, more efficient and familial fetal monitoring is possible with our PC based central fetal monitoring system which provides the medical personnel with the view of a selected pregnant woman on the same screen where the electronic waveforms and data are displayed.

As the development of modern technology, human works shift whose roll from physical conditions to the system monitoring tasks. In this paper, safety-presentation configuration is discussed instead of well-known fault-warning configuration. Safety-presentation configuration is verified as superior to the fault-warning configuration in hazard prevention. The estimation of system states involves the decision making environments which lack of required in formations and most of all the informations are not precise too. And the limitation of human information processing show doubtful results. So the estimation of system states is regardes as fuzzy number, and its operation produces the parameter that explain the discriminability(d), decision criterion ($\beta$) of system operator's behaviors. These two values served as performance indices. Especially the $\beta$ is a good milestone of the operator's altitude degree of caution.

전산 설비가 운영되는 전산 기계실은 적절한 온 습도 유지가 매우 중요하다. 따라서, 전산 기계실에 대한 온 습도 모니터링 시스템이 중요하게 운영 된다. 하지만 소형 전산 기계실에서는 24 시간 자동 모니터링 시스템이 구축 안되어 있는 경우도 많이 있다. 본 논문에서는 모니터링 시스템이 구축 안된 소형 전산 기계실에서 운영중인 x86 서버들의 온도를 기반으로 전산 기계실의 온도를 모니터링 하는 방법에 대해 제안한다.

교량을 비롯한 핵심 사회기반시설의 노후화는 전 세계적으로 심화되고 있으며, 이에 따른 구조 건전성의 장기적 모니터링 및 안전 관리의 필요성이 증대되고 있다. 기존의 접촉식 센서 기반 계측이나 무인항공기(드론)를 활용하는 방식은 높은 정확도를 제공하지만, 설치 및 유지관리 비용, 국소 계측의 한계, 그리고 장기간 운용의 제약으로 인해 광범위한 적용에 어려움이 존재한다. 본 연구에서는 이러한 한계를 극복하기 위한 대안으로, 광범위하게 보급된 CCTV 인프라를 활용하는 새로운 변위 모니터링 방법론을 제안한다. 제안된 기법은 CCTV 영상에서 디지털 이미지 상관법(Digital Image Correlation) 기반의 특징(Feature)을 추출하고, 이를 시계열 데이터로 변환한 후, Long Short-Term Memory(LSTM) 및 Gated Recurrent Unit(GRU)과 같은 딥러닝 모델을 적용하여 교량의 미소 변위를 추정한다. 실제 교량에서 취득한 영상을 대상으로 제안된 방법론의 성능을 검증한 결과, 접촉식 변위계로 측정한 실제 변위 데이터와 RMSE 기준 0.1116mm 의 매우 적은 오차를 보이는것을 확인하였다. 본 연구는 기존 모니터링 방식의 기술적, 경제적 단점을 보완하고, 이미 구축된 사회적 자산인 CCTV 인프라를 교량 안전 관리에 적극적으로 활용할 수 있는 새로운 방향을 제시한다는 점에서 학술적, 실용적 의의를 가진다.

The aging of critical social infrastructure, including bridges, is a growing concern worldwide, necessitating long-term structural health monitoring and safety management. While conventional methods utilizing contact-based sensors or unmanned aerial vehicles (drones) offer high accuracy, their widespread application is hindered by challenges such as high installation and maintenance costs, limitations to localized measurements, and constraints on long-term operation. To overcome these limitations, this study proposes a novel displacement monitoring methodology that leverages widely available CCTV infrastructure. The proposed technique extracts features from CCTV footage based on Digital Image Correlation (DIC) and converts them into time-series data. Subsequently, deep learning models such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) are applied to estimate the micro-displacements of the bridge. The performance of the proposed methodology was validated using video footage acquired from an actual bridge. The results confirmed a very low error, with a Root Mean Square Error (RMSE) of 0.1116mm, when compared to the actual displacement data measured by contact-based displacement sensors. This research holds significant academic and practical value as it complements the technical and economic shortcomings of existing monitoring methods and presents a new direction for proactively utilizing CCTV infrastructure, an already established societal asset, for bridge safety management.