• Journal of Korean Society on Water Environment
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• v.34 no.5
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• pp.487-493
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• 2018

Urban stormwater runoff is the one of the most extensive causes of deterioration of water quality in streams in urban areas. Especially, in the Suyeong River watershed, non-point sources from urban-residential areas are the most common cause of water pollution. Also, it has been ascertained that BOD and COD as indexes of organic matter, have limitation on management of Suyeong River's water quality. In this study, changes of organic matter properties of Suyeong River from inflow of non-point source during rainfall were investigated. Fractions of organic matters were analyzed using water samples collected at two sites (Suyeong River and Oncheon Stream) during a rain event. Variations of dissolved organic carbon (DOC) concentration by rainfall were similar to flow rate change in the river. Distribution of organic matter fraction according to change of rain duration revealed that while hydrophilic component increased at initial rainfall, the hydrophobic component was similar to change in dissolved organic carbon (DOC) concentration. Also, the relative proportion of hydrophilic components in organic matter in river water increased, due to rainfall. Results of biodegradation of organic matters revealed that decomposition rate of organic matters during rainfall was higher than that of during a non-rainfall event.

• Journal of Information Processing Systems
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• v.6 no.4
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• pp.609-620
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• 2010

In order to provide a tailored education for learners within the ubiquitous environment, it is critical to undertake an analysis of the learning activities of learners. For this purpose, SCORM (Sharable Contents Object Reference Model), IMS LD (Instructional Management System Learning Design) and other standards provide learning design support functions, such as, progress checks. However, in order to apply these types of standards, contents packaging is required, and due to the complicated standard dimensions, the facilitation level is lower than the work volume when developing the contents and this requires additional work when revision becomes necessary. In addition, since the learning results are managed by the server there is the problem of the OS being unable to save data when the network is cut off. In this study, a system is realized to manage the actions of learners through the event interception of a web-browser by using event hooking. Through this technique, all HTMLbased contents can be facilitated again without additional work and saving and analysis of learning results are available to improve the problems following the application of standards. Furthermore, the ubiquitous learning environment can be supported by tracking down learning results when the network is cut off.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.146-157
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• 2009

In order to implement ontology data searching system, this paper uses some methods that effectively analyse searching options/key words with event process model and design pattern. I will propose some techniques on object-oriented process model that should improve reusability of system and reusability of ontology data which users can obtain more precise searching results. This paper shows that ontology-based data searching can assure users of the precision of searching results. Therefore, ontology-based data searching system on object-oriented design pattern is expected to show high stability and reliability, enhance reusability and scalability of modules and softwares and provide reliable data searching results to users.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.1-11
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• 2021

This paper proposes a novel mechanism called Event-driven Uncore Frequency Scaler (eUFS) to improve the energy efficiency of the HPC systems. UFS exploits the hardware events such as LAPI (Last-level Cache Accesses Per Instructions) and CPI (Clock Cycles Per Instruction) to dynamically adjusts the uncore frequency. Hardware events are collected at a reference time period, and the target uncore frequency is determined using the collected event and the previous uncore frequency. Experiments with the NPB benchmarks demonstrate that the eUFS reduces the energy consumption by 6% on average for class C and D NPB benchmarks while it only increases the execution time by 2% on average.

• Steel and Composite Structures
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• v.43 no.3
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• pp.375-388
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• 2022

Nibellen structural system is a novel resilient bracing system based on the application of Bellville disks and Nitinol rods. The cyclic behavior of Nibellen assembly was obtained, and the design equations were developed based on the available literature. Seismic performance of the system was then studied analytically. Two groups of buildings with different lateral force resisting systems were designed and studied: one group with the Nibellen system, and the other with the special concentrically braced frame system. Each building group consisted of 5-, 10-, and 15-story buildings. The Design-Base-Event (DBE) and Maximum Considered Event (MCE) were considered as the seismic hazard, and a suite of seven ground motions were scaled accordingly for response history analyses. Finally, the resiliency of the buildings was studied by obtaining the functionality curve of the buildings before and after the seismic event. The construction cost of the 5-story building with Nibellen bracing system increased but the post-earthquake cost decreased significantly. The application of Nibellen system in the 10- and 15-story buildings reduced both the construction and repair costs, considerably. Resiliency of all the buildings was improved when Nibellen system was used as the lateral force resisting system.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.217-223
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• 2023

With the rapid advancement of technologies, need for different research fields where this technology can be used is also increasing. One of the most researched topic in computer vision is object detection, which has widely been implemented in various fields which include healthcare, video surveillance and education. The main goal of object detection is to identify and categorize all the objects in a target environment. Specifically, methods of object detection consist of a variety of significant techniq ues, such as image processing and patterns recognition. Anomaly detection is a part of object detection, anomalies can be found various scenarios for example crowded places such as subway stations. An abnormal event can be assumed as a variation from the conventional scene. Since the abnormal event does not occur frequently, the distribution of normal and abnormal events is thoroughly imbalanced. In terms of public safety, abnormal events should be avoided and therefore immediate action need to be taken. When abnormal events occur in certain places, real time detection is required to prevent and protect the safety of the people. To solve the above problems, we propose a modified YOLOv5 object detection algorithm by implementing dilated convolutional layers which achieved 97% mAP50 compared to other five different models of YOLOv5. In addition to this, we also created a simple mobile application to avail the abnormal event detection on mobile phones.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.892-908
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• 2010

Services in SOA are typically perceived as black-box to service consumers, and can be dynamically evolved at runtime, and run on a number of unknown and heterogeneous environments. Because of these characteristics of the services, effective and efficient monitoring of various aspects on services is an essential functionality for autonomous management of service. But the problem with or limitation in conventional or existing approaches is, that they focus on services themselves, ignoring the effects by business processes. Consequently, there is a room for service monitoring which provides more useful information of business level by acquisition of only external monitoring data that depend on specific BPEL engine and middleware. Moreover, there is a strong demand to present effective methods to reduce monitoring overhead which can degrade quality of services. EDA can cope with such limitations in SOA by collecting and analyzing events efficiently. In this paper, we first describe EDA benefits in service monitoring, and classify monitorring target, and present an appropriate monitoring method for each monitoring target. Also to provide the applicability of our approach, an event meta-model is defined, and event processing model and architecture based on the meta-model are proposed. And, with the proposed architecture and method, we implement a prototype of an event-driven dynamic monitoring framework which can collect and process internal and external data at runtime. Finally, we present the result of a case study to demonstrate the effectiveness and applicability of the proposed approach.

• Water Engineering Research
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• v.5 no.4
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• pp.157-176
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• 2004

This research presents a prototype development and implementation of Decision Support System (DSS) for integrated river basin water management for the flood control. The DSS consists of Relational Database Management System, Hydrologic Data Monitoring System, Spatial Analysis Module, Spatial and Temporal Analysis for Rainfall Event Tool, Flood Forecasting Module, Real-Time Operation of Multi Reservoir System, and Dialog Module with Graphical User Interface and Graphic Display Systems. The developed DSS provides an automated process of alternative evaluation and selection within a flexible, fully integrated, interactive, centered relational database management system in a user-friendly computer environment. The river basin decision-maker for the flood control should expect that she or he could manage the flood events more effectively by fully grasping the hydrologic situation throughout the basin.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.449-453
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• 2014

Chronic diseases including hypertension and its complications are major sources causing the national medical expenditures to increase. We aim to predict the risk of hypertension complications for hypertension patients, using the sample national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques, such as logistic regression, linear discriminant analysis, and classification and regression tree to predict the hypertension complication onset event for each patient. The performance of these three methods is compared in terms of accuracy, sensitivity and specificity. The result shows that these methods seem to perform similarly although the logistic regression performs marginally better than the others.

• Management & Information Systems Review
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• v.27
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• pp.149-172
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• 2008

Since the 9/11 terror attack, the event which caused supply chain disruption, supply chain security has becomes more important than ever before. Furthermore, such company's logistics strategies conflicting supply chain security as increased global sourcing, JIT manufacturing are increasing supply chain vulnerability. It could burden for global companies to strengthen supply chain security because not only it requires additional investment cost but also changes of companiy's global logistics strategy. However, on the other hand, supply chain visibility and resilience can be improved through supply chain security. In addition, it allows companies to stabilize supply chain structure as well as rapid and flexible response to market demand. The key issue is balancing between efficiency and supply chain security. To do this, identifying risk elements under the supply chain and assessing vulnerability of each supply chain components should be performed before developing efficient supply chain security management system without obstructing supply chain efficiency.