• International conference on construction engineering and project management
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• 2022.06a
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• pp.170-178
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• 2022

A high-performing Earned Value Management System (EVMS) can influence project success and help stakeholders meet project objectives. Although EVMS processes are well-supported by technical guidelines and standards, project managers often face challenges related to the project culture, team, resources, and business practices that make up the project environment within which an EVMS is being used. A comprehensive literature review revealed a lack of a data-driven and consistent assessment frameworks that can gauge the environment surrounding EVMS implementation. This paper will discuss the EVMS environment of construction and environmental projects, and examine its impact on cost performance. The authors used a multi-method approach to identify 27 environment factors that make up the EVMS environment, assessing them on 18 construction and environmental projects worth over $2 billion of total cost. Research methods employed include: (1) a literature review of more than 300 references; (2) a survey of 294 respondents; and (3) remote research charrettes with more than 60 participating expert practitioners. Culture (one of the identified environment categories) was found to be relatively more important in terms of its impact on the EVMS environment, followed by people, practices, and resources. These exploratory results show statistically significant differences in cost performance between completed projects with either a good or poor environment, for the sample projects. Key environment factors are outlined, and guidance is provided to practitioners around how to set up an effective EVMS environment in a construction or environmental project to inform decision-making and support achieving the project cost objectives successfully.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.74-79
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• 2011

Engineering valuation is a specialized discipline requiring expert knowledge and judgment, which scientifically estimates the economic value of industrial properties. By industrial properties, we mean engineering structures such as mines, factories, buildings, machines, and other industrial facilities as well as facilities of public enterprises. Particular industrial properties can have longer economic life if their performance is excellent and they are still suitable for current manufacturing needs. If not, its economic life will be shorter. As speed of technological progress becomes rapid, life-cycle and development period of a product is becoming shorter. In an industry characterized by rapid development of technology, industrial properties can become obsolescent faster. Even if they are in good working order, they could be no longer suitable for manufacturing new products based on radically different technology. In our research, we apply engineering approach to estimating functional economic life by factoring in technological obsolescence in such an industry.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.3
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• pp.69-79
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• 1999

Recently, new concept and paradigm of 'Environmentally-Friendless' is taking a growing interest in environmental planning and design. This study is to develop the new approach of sustainable development, and to establish the indicators for environmentally-friendliness of "Tourism Farms" in rural areas. A questionnaire survey was conducted for deputy manager group and expert group. The environmentally-friendliness of tourism farms is composed of three categories, conservation of global environment(Low Impact), friendliness to surrounding nature(High Contact), and environmental health and amenities (Health '||'&'||' Amenity). Four indicators, such as saving of energy and water resource, reduction and reuse of garbage, natural purification of sewage disposal, and utilization of natural energy, were affecting the first category, i.e., conservation of global environment(Low Impact). And, friendliness to surrounding nature (High Contact) is affected by 3 indicators, such as contact to nature and diverse green areas, water intimate '||'&'||' contact areas, and natural ecology observation by biotope. Finally, the dimension of environmental health and amenity is affected by 3 indicators, such as nature affinity by farming experience, environmental-friendliness of soil '||'&'||' crops by organic farming, campaign and education programs of environmentally-friendliness. From the result of Importance-Performance Analysis(IPA) for 10 indicators, environmentally-friendliness was recommended as 'Concentrate Here'. And, the content validity of 10 indicators for 3 categories was examined by factor analysis. The result showed as the same as hypothetical model, which proved the validity of hypothetical model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.384-394
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• 2020

This paper proposes an outlier detection model based on machine learning that can diagnose the presence or absence of major engine parts through unsupervised learning analysis of main engine big data of a ship. Engine big data of the ship was collected for more than seven months, and expert knowledge and correlation analysis were performed to select features that are closely related to the operation of the main engine. For unsupervised learning analysis, ensemble model wherein many predictive models are strategically combined to increase the model performance, is used for anomaly detection. As a result, the proposed model successfully detected the anomalous engine status from the normal status. To validate our approach, clustering analysis was conducted to find out the different patterns of anomalies the anomalous point. By examining distribution of each cluster, we could successfully find the patterns of anomalies.

• 연구논문집
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• s.32
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• pp.85-94
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• 2002

Even in the world wide automobile companies where a few simple modules are put into practical use, the front subframe modules of which performances of durability, NVH and crash are significantly important are under planing. In this study, design technology for the automobile front subframe module, which consists of an engine, a transmission and steering parts, structural components (frame, upper arm, lower arm and brake etc.) and rubber components(engine mount, axle mount and rubber disc etc.), was developed. A FEM-based analytical approach was used to evaluate the multiaxial high cycle fatigue damage of the front subframe module. Strain-life fatigue database system and expert system for fatigue properties of welded materials were developed. Stiffness values of the various rubber bushes mounted on the front subframe were evaluated by experimental method and FEM. TWB(Tailor Welded Blank) technology was applied to forming the cross member of the front subframe. Performance evaluations in relation to NVH and crash were conducted by using CAE technologies.

• Korea Journal of Hospital Management
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• v.25 no.3
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• pp.1-13
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• 2020

Purpose: This study was conducted to identify the conceptual definition and attributes of 'Taeoom' (or workplace bullying) inflicted to newly employed nurses in Korea. Method: Walker & Avant(2011)'s eight-stage process was used to perform a conceptual analysis of 'Taeoom'. Literature review of 40 studies published between Jan. 2009 and March 2018 published in Korea was followed by the in-depth interview with nine newly employed hospital nurses and the ex-post review of results by nursing experts. Findings: 'Taeoom' was associated with five attributes: (1) bullying for no reason, (2) peer rejection for no reason, (3) decreased physical function and psychological withdrawal, and (4) verbal abuse, defamation and nagging, (5) impotent feeling due to power imbalance. Four antecedents found in this study include offensive action, distrust, power imbalance, and undue workload exceeding capacity. As consequences of Taeoom, negative physical and psychological symptoms and turnover intention were increased while nursing performance was decreased. Conclusion: This study suggests the need for more qualitative researches with more comprehensive approach on Taeoom and the development of effective program to improve the organizational culture in nursing field. This study is significant in that it provides a qualitative but comparative review on the attributes, antecedents and consequences of Taeoom through literature review accompanied by focus group interview and expert review.

• Plant Journal
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• v.9 no.3
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• pp.43-47
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• 2013

Even if an expert who has majored energy engineering, it is a difficult concept to understand power output optimization and power efficiency optimization. In this study a diagram applying thermodynamic state value as specific exergy and exergy ratio was developed. Although general peoples who did not major energy engineering can be easily understand the concept of power output optimization and power efficiency through the developed diagram. A represented property that can identify the performance of power plant is the main steam temperature and pressure. At the developed diagram the maximum power output line and maximum power efficiency line are shown according to the temperature and pressure of main steam. Therefore we can identify how much a power plant approach to maximum power output and maximum power efficiency.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.2
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• pp.15-23
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• 2012

Today, rapid changes in technologies and everyday lives due to the Internet make it is difficult to make predictions about the future. Generally, the best way to predict the future has been proposed by experts. Although expert opinions are very important, they are liable to produce incorrect results due to human error, insufficient information regarding future outcomes and a state of connectedness between people, among other reasons. One of the ways to reduce these mistakes is to provide objective information to the experts. There are many studies that focus on the collection of objective material from papers, patents, reports and the Internet, among other sources. This research paper seeks to develop a forecasting method using World Wide Web search results according to the Google search engine and a network analysis, which is generally used to analyze a social network analysis(SNA). In particular, this paper provides a method to analyze a complexity network and to discover important technologies in the construction field. This approach may make it possible to enhance the overall performance of forecasting method and help us understand the complex system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1079-1082
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Excavation experiments are carried out to check the performance of the FLC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4204-4222
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• 2015

Cloud is the latest buzz word in the internet community among developers, consumers and security researchers. There have been many attacks on the cloud in the recent past where the services got interrupted and consumer privacy has been compromised. Denial of Service (DoS) attacks effect the service availability to the genuine user. Customers are paying to use the cloud, so enhancing the availability of services is a paramount task for the service provider. In the presence of DoS attacks, the availability is reduced drastically. Such attacks must be detected and prevented as early as possible and the power of computational approaches can be used to do so. In the literature, machine learning techniques have been used to detect the presence of attacks. In this paper, a novel approach is proposed, where intelligent rule based feature selection and classification are performed for DoS attack detection in the cloud. The performance of the proposed system has been evaluated on an experimental cloud set up with real time DoS tools. It was observed that the proposed system achieved an accuracy of 98.46% on the experimental data for 10,000 instances with 10 fold cross-validation. By using this methodology, the service providers will be able to provide a more secure cloud environment to the customers.