• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.5
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• pp.54-59
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• 2011

Reliable starting capability of a gas turbine engine calls the engine industry's attention recently. So far the gas turbine engine performance researches have focused on the range between idle to Max rpm, but recent attention on the starting has brought interests in the range of "Sub-dile". As component characteristic maps are essential for the starting research, various kinds of studies have been doing and proposing ways to expand the existing maps toward sub-idle range. In this paper, previous studies were discussed and a new method suggested and validated.

• Bulletin of the Korean Chemical Society
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• v.28 no.3
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• pp.379-385
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• 2007

Receptor-oriented pharmacophore-based in silico screening is a powerful tool for rapidly screening large number of compounds for interactions with a given protein. Inhibition of the enzyme catechol-Omethyltransferase (COMT) offers a novel possibility for treating Parkinson's disease. Bisubstrate inhibitors of COMT containing the adenine of S-adenosylmethionine (SAM) and a catechol moiety are a new class of potent and selective inhibitor. In the present study, we used receptor-oriented pharmacophore-based in silico screening to examine the interactions between the active site of human COMT and bisubstrate inhibitors. We generated 20 pharmacophore maps, of which 4 maps reproduced the docking model of hCOMT and a bisubstrate inhibitor. Only one of these four, pharmacophore map I, effectively described the common features of a series of bisubstrate inhibitors. Pharmacophore map I consisted of one hydrogen bond acceptor (to Mg2+), three hydrogen bond donors (to Glu199, Glu90, and Gln120), and one hydrophobic feature (an active site region surrounded by several aromatic and hydrophobic residues). This map represented the most essential pharmacophore for explaining interactions between hCOMT and a bisubstrate inhibitor. These results revealed a pharmacophore that should help in the development of new drugs for treating Parkinson's disease.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.694-699
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• 2010

Reliable starting capability of a gas turbine engine calls the engine industry's attention recently. So far the gas turbine engine performance researches have focused on the range between idle to Max rpm, but recent attention on the starting has brought interests in the range of "Sub-dile". As component characteristic maps are essential for the starting research, various kinds of studies have been doing and proposing ways to expand the existing maps toward sub-idle range. In this paper, previous studies were discussed and a new method suggested and validated.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.163-171
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• 2014

Under amazing increase in markets and certain demand on qualified service in the delivery system, global logistic optimization is becoming a keen interest to provide an essential infrastructure coping with modern competitive prospects. As a key technology for such deployment, we have been engaged in the practical studies on vehicle routing problem (VRP) in terms of Weber model, and developed a hybrid approach of meta-heuristic methods and the graph algorithm of minimum cost flow problem. This paper extends such idea to multi-depot VRP so that we can give a more general framework available for various real world applications including those in green or low carbon logistics. We show the developed procedure can handle various types of problem, i.e., delivery, direct pickup, and drop by pickup problems in a common framework. Numerical experiments have been carried out to validate the effectiveness of the proposed method. Moreover, to enhance usability of the method, Google Maps API is applied to retrieve real distance data and visualize the numerical result on the map.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.89-100
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• 2006

Recently the dramatical development of domestic spatial information technology and the successful construction of Korea NGIS(Nation Geographic Information System) have been the foundation of the scientific national territory utilization and management. However, there still exists the original problems to construct the thematic maps for supporting the various administrative services because administrative officials tend to depend on paper maps and inventories to generate spatial information, process, upgrade and manage. In this situation, there is a greater need to develop GIS system for the effective construction of various thematic maps. In this study, the satellite image based high accurate e-thematic construction and management system was developed to support the forest administrative service such as generating user based forest thematic maps, modifying them, analyzing and outputting through GIS, GPS and satellite images. For the case study, the previous forest paper map of Jeju Island was converted in format of raster and vector data using satellite images to maintain more exact location information so that this system helps to manage domestic spatial information scientifically and effectively within shorter time then support the standard for domestic spatial information. Moreover, this system plays the role of DSS(Decision Supporting System) for forest administrative affairs by integrating the attribute data, managing the GPS data and linking the multimedia data. For this, the additional main objective of this study was acquired powerful GIS component, which is called as e-mapping component, so that it could be regarded as enabling interoperability and reusability within this application. For the future works, the essential element idea and technology in this study could be applied very usefully to other official works such as constructing thematic maps and supporting the desired affairs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.381-389
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• 2019

It is important to estimate flood overflow because adverse weather phenomena are frequently occurring in recent years. In order to cope with such abnormal floods, it is essential to perform flood inundation simulations for constructing flood inundation maps as nonstructural countermeasures. However, there is no quantitative evaluation method and criterion for flood inundation prediction. In this study, the Receiver Operation Characteristics (ROC) and Lee Sallee Shape Index (LSSI) were employed to quantitatively evaluate the accuracy of flood inundation maps for 10 administrative districts. Comparing predicted inundation maps with actual inundation trace maps, the ROC score was 0.631 and the LSSI was 25.16 %. Using the ROC and the LSSI, we proposed an evaluation criterion for flood inundation map. The average score was set as an intermediate score and distributed into 5 intervals. The validity of the evaluation criterion was investigated by applying to the XP-SWMM model, which has been verified and corrected. The ROC analysis result was 0.8496 and the LSSI was 51.92 %. It is considered that the proposed evaluation criteria can be applied to flood inundation maps.

• Journal of the Korean earth science society
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• v.44 no.3
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• pp.210-221
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• 2023

The purpose of this study is to evaluate the content knowledge and problem solving process used by pre-service earth science teachers while discriminating faults on geological maps. For this, we collected and evaluated data on fixation duration and gaze plot, while pre-service earth science teachers (N=12) solved the problem on faults interpretation using an eye tracker (Tobii Pro Glass 2 model). The results were as follows. First, most of the pre-service earth science teachers know the concepts of the normal and reverse fault but they do not know the procedural knowledge essential for fault interpretation on geological maps. Second, the pre-service earth science teachers did not draw a geological cross-sectional map to interpret the fault on the geological map and interpreted the fault based on two-dimensional information collected from the geological map rather than three-dimensional information. Therefore, it is essential to improve the teaching and learning environment so that pre-service earth science teachers who will become earth science teachers in the future can learn procedural knowledge essential to comprehend natural phenomena including understanding natural phenomena. The results of this study can substantially help organize a new earth science curriculum or develop materials on teachers' education in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.121-138
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• 2024

Artificial intelligence is crucial to manufacturing productivity. Understanding the difficulties in producing disruptions, especially in linear feed robot systems, is essential for efficient operations. These mechanical tools, essential for linear movements within systems, are prone to damage and degradation, especially in the LM guide, due to repetitive motions. We examine how explainable artificial intelligence (XAI) may diagnose wafer linear robot linear rail clearance and ball screw clearance anomalies. XAI helps diagnose problems and explain anomalies, enriching management and operational strategies. By interpreting the reasons for anomaly detection through visualizations such as Class Activation Maps (CAMs) using technologies like Grad-CAM, FG-CAM, and FFT-CAM, and comparing 1D-CNN with 2D-CNN, we illustrates the potential of XAI in enhancing diagnostic accuracy. The use of datasets from accelerometer and torque sensors in our experiments validates the high accuracy of the proposed method in binary and ternary classifications. This study exemplifies how XAI can elucidate deep learning models trained on industrial signals, offering a practical approach to understanding and applying AI in maintaining the integrity of critical components such as LM guides in linear feed robots.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.195-209
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• 2005

Forest road has been an essential infrastructure for various forestry practices as well as for recreational use, disaster management, and local economics promotion. Since 1980s, extensive network of forest roads has been constructed as an national project in Korea. However, due to the minimal-budget of the project, accurate maps of forest road are not usually available. Although forest road map is a main thematic layer for the forest Geographic Information System (FGIS), its locational accuracy has not been sufficient for the practical applications and, therefore, the update of digital forest road maps is urgent. The objectives of this study is to compare ae methodology of generating and updating digital forest road maps from the aspects of the map accuracy and the efficiency of methods. Four mapping methods (GPS surveying, satellite imagery, ortho aerial photograph, and digital photogrammetry) were applied to generate the forest road maps over the study area of Mt. Oseo in Chungchungnam-do, which has a 35km forest roads distributed in national, public and private forests. The forest road Imp produced by digital photogrammetric method is the most accurate and comparable to GPS surveying although it required the greatest amount of labor time.