• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.379-388
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• 2011

At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.1-8
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• 2019

Dialog system is becoming a new dominant interaction way between human and computer. It allows people to be provided with various services through natural language. The dialog system has a common structure of a pipeline consisting of several modules (e.g., speech recognition, natural language understanding, and dialog management). In this paper, we tackle a task of domain classification for the natural language understanding module by employing machine learning models such as convolutional neural network and random forest. For our dataset of seven service domains, we showed that the random forest model achieved the best performance (F1 score 0.97). As a future work, we will keep finding a better approach for domain classification by investigating other machine learning models.

• Korean Journal of Construction Engineering and Management
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• v.13 no.4
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• pp.69-77
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• 2012

The construction data should be controlled from the life-cycle perspective. The current PMIS (Project Management Information System) usually focuses on the construction operation stage. The PMIS does consider the utilization of the construction in the maintenance of constructed facilities. This paper tries to interface the construction data with the maintenance data for effective use of construction data in the life-cycle perspective. To achieve the research objective, a maintenance breakdown structure is established and connected to the work breakdown structures. The connection of the two breakdown structures provide a structured utilization of construction data for efficient maintenance work activities. A prototype suggests that the interface of maintenance and work breakdown structures can help provide a construction and maintenance data in a more efficient way for maintenance activities.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.130-142
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• 2016

BIM library, as a systematic collection of BIM objects where the building information is stored, is a vital factor to construct the BIM based work environment. However, construction business is faced the problems relating BIM library such as the absence of the standard for establishing BIM library, the discontinuity of BIM library's compatibility and the lack of practice applicable BIM library. These problems cause the decreasing work efficiency and the recreating BIM model, by delivering inefficient information required in each stage and application field. The purpose of this study is to suggest the integrated management system for property information of BIM library in order to minimize the reworking and to manage information of each stage and application field when exchanging and sharing information. To achieve this, the BIM information classification, the criteria of property requirements for information exchange in BIM application field and the BIM library management system are developed. This study could contributes to ensuring the reliability and accuracy of results of BIM based analysis and to enhancing the speed of business process with sharing and exchanging building information utilizing a single BIM model.

• Journal of Power System Engineering
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• v.14 no.2
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• pp.40-47
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• 2010

This paper proposes a fault detection system to detect the strip rupture in six-high stand Cold Rolling Mills based on transient current signal of an electrical motor. For this work, signal smoothing technique is used to highlight precise feature between normal and fault condition. Subtracting the smoothed signal from the original signal gives the residuals that contains the information related to the normal or faulty condition. Using residual signal, discrete wavelet transform is performed and acquire the signal presenting fault feature well. Also, feature extraction and classification are executed by using PCA, KPCA and SVM. The actual data is acquired from POSCO for validating the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.1-8
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• 2018

It is the content and scope of this study to analyze the problems of the current wireless service and the classification system of the radio station, and to examine the case of radio control in Japan and to establish a reasonable and efficient radio wave management plan. The results of this study can be used as basic data for reorganizing the legislation on radio wave enforcement ordinance, radio services and radio station classification standards. It is expected that it will be possible to improve the compliance and efficiency of the radio station licensing and inspection service while enhancing the policy compliance in the practical work by providing detailed explanations on the definition and classification system of the new radio task / radio station in the future.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.395-404
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• 2022

Purpose: Small-scale construction sites have insufficient systematic safety management activities, and due to the characteristics of the construction site, the production structure is complex due to external environmental factors, and the risk of construction equipment is very high. We would like to propose a checklist method among practical risk assessment techniques that can derive risk factors for disaster prevention at small construction sites and reduce disasters. Method: Risk factors were derived by analyzing literature research and disaster cases, and detailed work for a checklist of risk assessment suitable for small-scale construction sites was classified based on risk factor items. Result: Hazard factors were divided into 6 major categories, and 29 detailed types of work were classified based on actual work types, and 80 detailed works were classified accordingly. Conclusion: By arranging risk factors suitable for small-scale construction sites according to the classification system, the lack of expertise in the construction site can be supplemented, and risk factors can be derived more easily and disaster reduction can be expected through establishment of safety measures.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.325-327
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• 2008

In electrical industry, classification methodology has been an important issue for analyzing power consumption patterns. It has many applications including decisions on energy purchasing, load switching as well as helping in infrastructure development. Our aim in this work is to classify the electrical section and find potentially non-safe electrical sections. For this purpose, we use Emerging Patterns based classification. The classification method uses the aggregate score of emerging patterns to build classifier. The proposed methodology was applied to a set of electrical section data of the Korea power. The test data and relational electricity information and knowledge are supported by Korea Electric Power Research Institute (KEPRI).

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.774-779
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• 2008

In this work, we describe comments classification system using topic signature. Topic signature is widely used for selecting feature in document classification and summarization. Comments are short and have so many word spacing errors, special characters. We firstly convert comments into 7-gram. We consider the 7-gram as sentence. We convert the 7-gram into 3-gram. We consider the 3-gram as word. We select key feature using topic signature and classify new inputs by the Naive Bayesian method. From the result of experiments, we can see that the proposed method is outstanding over the previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.