• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.367-376
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• 2009

This paper proposes an application methodology of AHP(Analytic Hierarchy Process) based decision making theory for improvement priority by assessment of various risk factors affecting on deterioration of water supply systems, as major social infrastructure. AHP method is organized with three level of hierarchy which is introduced for multi-criteria decision making in this study. In the first level, assessment outputs are calculated by AHP for each affecting factor. In the second level, criteria are estimated by using assessment results with respect to structural and environmental factors. Consequently, ranking decision is performed in the third level. In order to present the effectiveness, a proposed method is compared with FCP(Fuzzy Composite Programming) for decision making. Since the results of the proposed method show better performance with consistent results, it can be applied as an efficient information for the determination for improvement priority of the study infrastructure.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.134-137
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• 2007

In this paper the heat health alert system, which is operated this year by way of showing an example, is a simulator linked to the Geographic Information System (GIS), and it uses meteorological data that are observed at Automatic Weather Systems (AWSs) in Seoul, Korea. Simulation results show that it is possible to use meteorological data observed by AWSs when the Korea Meteorological Administration (KMA) has issued alerting the public to the threat of heat waves, and to connect meteorological data to spatial data when the KMA offers local forecasts and weather-related information. However, most AWSs that were installed to manage urban disasters do not measure humidity, so general humidity is used in all districts. Therefore, to issue heat wave warnings about different localities on a small scale, we will study how to complement this problem and to examine the accuracy of data observed at AWS in the future.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.123-128
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• 2019

In modern society, there are WEB sites that provides information in various fields by many advances in IT technology. As the number of users accessing the Web increases, one server becomes unavailable, and multiple servers are deployed to provide the service. In addition, systems that control servers are required to manage multiple servers. However, server control systems in the existing market are mostly those that notify managers through SMS and apps when a server's down or a controlled port is closed. However, in case of servers that generate a lot of traffic, the Web server and the WAS are operated and managed each independently. The WEB and WAS provide service by connecting to each other. However, the connection between WEB and WAS may be disconnected due to various environmental factors. In this case, the existing control system can not determine whether the service is working properly. Even in the case of WEB and WAS of a server that is operated independently, there is a phenomenon that the existing control system does not know the problem even when the normal service is not provided due to environmental factors such as disconnection to DB. In this paper, we implemented a system to check the normal state of Web service using Web crawling to solve this problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.379-381
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• 2021

As information and communication technologies develop, many studies are being conducted to maintain an efficient production environment by applying network and computing technologies to existing production systems. Unlike classical control systems, these smart production systems need to collect data about the production environment in real time, and operate fluidly as it changes. In this paper, we present a measurement system that can collect data in real time through network-based sensors and respond effectively to environmental changes. We also proved this smart system can cope with external environmental changes and maintain an effective production environment.

• Journal of Soil and Groundwater Environment
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• v.22 no.2
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• pp.1-9
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• 2017

Passive treatment systems are commonly used for remediation of mine drainage waters because they do not require continuous chemical inputs and operation. In this study, the selection and design criteria for such systems were evaluated, particularly the two most commonly used ones, i.e., permeable reactive barriers (PRBs) and vertical flow biological reactors (VFBRs). PRBs and VFBRs are operated on the same principles in terms of biochemical reaction mechanisms, whereas differences relate to configuration, engineering, and water management. In this study, each of these systems were described with respect to key design variables, such as metal removal mechanisms and removal rates, effectiveness and longevity, general design and construction, flow capacity, and cost. The information provided from this study could be used as a design guideline when a passive treatment option is considered for potential remediation of a mine site.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• Knowledge Management Research
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• v.9 no.3
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• pp.77-105
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• 2008

This study primarily aims at identifying what factors significantly affect the diffusion of knowledge management systems(KMS) and finding out how these identified factors can be effectively managed, especially for Korean companies. The research model is derived based on previous researches on innovation diffusion, information systems implementation, and KMS. The model is used to examine the role of determinants in influencing the extent to which KMS is diffused within organizations. Independent variables of this research are composed of technical characteristics, organizational characteristics and environmental characteristics. 'Breadth of diffusion' and 'depth of diffusion' concept are used to measure the extent of KMS diffusion which is the dependent variable of this model. The 101 companies of total 1,000 samples responded to the survey. To analyze tile results of this empirical study, we performed the multiple regression analysis. As a result, it was shown that the relative advantage, complexity, information system maturity, size, top management support, champion, competitive pressure have influences on both the breadth and the depth diffusions. On the other hand, the organizational culture, valuation and compensation, and uncertainty of environmental factors were not verified to be significant. This empirical study will provide Korean companies with insights into effective ways to diffuse the KMS and succeed in business competition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.95-105
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• 2019

The importance of environmental industry was recognized as a major issue for the environmental problems (climate change, exhaustion of fossil fuels) of the 21st century. Many country and korea as well are exerting an effort to make plans to develop the environmental industry, expand the domestic market, and make it a global industry. According to this trend, the gyeongbuk province has also designated the environmental industry as a strategic industry with high potential for development when recognizing new growth industries. Gyeongbuk province is faced with a number of unsolved tasks and has not quite grasped current situations of the environmental industry. Based on the policy tasks, the detailed plans for the environmental industry in the gyeongbuk province include: establishing a new organization which will be in charge of various works or strengthening the current organization to expend the supporting developing organization for the environmental industry and the efficiency guidelines.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.181-187
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• 2003

For the moving objects with environmental sensors such as object tracking moving robot with audio and video sensors, environmental information acquired from sensors keep changing according to movements of objects. In such case, due to lack of adaptability and system complexity, conventional control schemes show limitations on control performance, and therefore, sensory-motor systems, which can intuitively respond to various types of environmental information, are desirable. And also, to improve the system robustness, it is desirable to fuse more than two types of sensory information simultaneously. In this paper, based on Braitenberg's model, we propose a sensory-motor based fusion system, which can trace the moving objects adaptively to environmental changes. With the nature of direct connecting structure, sensory-motor based fusion system can control each motor simultaneously, and the neural networks are used to fuse information from various types of sensors. And also, even if the system receives noisy information from one sensor, the system still robustly works with information from other sensors which compensates the noisy information through sensor fusion. In order to examine the performance, sensory-motor based fusion model is applied to object-tracking four-foot robot equipped with audio and video sensors. The experimental results show that the sensory-motor based fusion system can tract moving objects robustly with simpler control mechanism than model-based control approaches.