• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.84-89
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• 2019

This is a pilot study of machine learning based structural health monitoring system using flight data of composite aircraft. In this study, the most suitable machine learning algorithm for structural health monitoring was selected and dimensionality reduction method for application on the actual flight data was conducted. For these tasks, impact test on the cantilever beam with added mass, which is the simulation of damage in the aircraft wing structure was conducted and classification model for damage states (damage location and level) was trained. Through vibration test of cantilever beam with fiber bragg grating (FBG) sensor, data of normal and 12 damaged states were acquired, and the most suitable algorithm was selected through comparison between algorithms like tree, discriminant, support vector machine (SVM), kNN, ensemble. Besides, through neighborhood component analysis (NCA) feature selection, dimensionality reduction which is necessary to deal with high dimensional flight data was conducted. As a result, quadratic SVMs performed best with 98.7% for without NCA and 95.9% for with NCA. It is also shown that the application of NCA improved prediction speed, training time, and model memory.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.181-191
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• 2013

The design process of ecological and environmental detention system located in the housing district of Sinjeong 3-jigu in Seoul are as follows. At stage one, a new dispersal detention was created in the neighborhood park located near the originally planned detention. From this, the amount of storage of this dispersal detention system was enlarged from $28,337m^3/d$, the initial storage amount, to $33,606m^3/d$ as the post storage amount, responsible to the amount of rainfall which happens every 100 years. In particular, the SSB (Sustainable Structured wetland Biotop) system, which was the New Excellent Technology verified by the Ministry of Environment (No. 258) was applied to enhance ecological functioning and water quality with the detention as a constructed wetland. At stage two, the treatment plans for non-point pollutant source occurred at the initial period of rain, flowing into the detention system were built for purifying the water of the retention pond at the base of the detentions, and the water-circulation system was designed at the dispersal detentions on the period of regular rainfalls. The non-point pollutant source flowing into detention site was calculated as $11,699m^3/d$ flowing down from seven small watersheds, which occurred at the initial period of rain. In particular the SSB systems improved the average efficiency of the water processing performance to BOD 60%, SS 90%, T-N 30%, T-P 60%. At stage three, the ecological network and biological diversity were strongly considered so that it brought the residents with amenity places. In particular, the dispersal detentions were successfully designed to restore the ecological habitat of endangered plant and animal species such as narrow-mouthed.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.1-15
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• 2006

Currently the mobile web service is growing with a tremendous speed and mobile contents are spreading extensively. However, it is hard to search what the user wants because of some limitations of cellular phones. And the music is the most popular content, but many users experience frustrations to search their desired music. To solve these problems, this research proposes a hybrid recommendation system, MOBICORS-music (MOBIle COntents Recommender System for Music). Basically it follows the procedure of Collaborative Filtering (CF) system, but it uses Contents-Based (CB) data representation for neighborhood formation and recommendation of new music. Based on this data representation, MOBICORS-music solves the new item ramp-up problem and results better performance than existing CF systems. The procedure of MOBICORS-music is explained step by step with an illustrative example.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.

• Land and Housing Review
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• v.7 no.2
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• pp.103-111
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• 2016

The paradigm of the housing policy has been transformed from housing supply to housing welfare, from the policy of housing quantity expansion to the policy of customized housing welfare. The Housing Act was newly enacted to realize the new paradigm of the housing policy. The Act establishes the role of the Housing Welfare Centers in the housing welfare delivery system, but they have some difficulties in doing their role because of limited amount of centers and their manpower. The desirable and efficient model of housing welfare delivery system, therefore, is that the demand of housing welfare is discovered on local base, and that demanders can be provided housing welfare service connected to local governments or neighborhood housing welfare centers. To do so local communities should be established and activated, and the needs of housing welfare service also be discovered. This study is a exploratory one on communities' role in housing welfare delivery system in spite of some limitations based on existing theories and studies, and is significant as a new trial.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• KIEAE Journal
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• v.11 no.4
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• pp.29-36
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• 2011

The aim of this study was to study the functions and roles of Green Community Rediscovery Center (GCRC) in terms of community integration, to design GCRC with various types of green roofs, and to investigate the possibility of applying a renewable energy system (e.g., PV) to the building greenery systems. The four major functional modules for GCRC were suggested: implementation of ecopark and community gardens with environmental education programs, implementation of green housing model with education programs, Discover Science Center, and implementation of green business model with education programs. Three major functions of the center are also presented in terms of design: 1) functions of community gardens; 2) establishment of a green business model, community composting system and an urban farming system; and 3) roles of community gardens in social interactions within GCRC. GCRC provides residents with the opportunities of community gardens, urban farming based on a successful recycling system, as well as a green business model and environmental education programs near their homes. The air temperature of the green roof (utilizing Sedum sarmentosum as a cover plant) was approximately $3^{\circ}C$ lower than that of the non-green roof, indicating a potential efficiency increase in PV systems for GCRC. It was concluded that the GCRC suggested would enhance the neighborhood satisfaction, improve the quality of life and contribute to social integration and community regeneration.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.3
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• pp.218-224
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• 2011

A modal method is presented for the investigation of the effects of measurement errors in damage detection for dynamic structural systems. The structural modifications to the baseline system result in the response changes of the perturbed structure, which are measured to determine a unique system in the inverse problem of damage detection. If the numerical modal data are exact, mathematical programming techniques can be applied to obtain the accurate structural changes. In practice, however, the associated measurement errors are unavoidable, to some extent, and cause significant deviations from the correct perturbed system because of the intrinsic instability of eigenvalue problem. Hence, a self-equilibrating inverse system is allowed to drift in the close neighborhood of the measured data. A numerical example shows that iterative procedures can be used to search for the damaged structural elements. A small set of selected degrees of freedom is employed for practical applicability and computational efficiency.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.147-152
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• 2008

Ant System(AS) is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem. In this paper, AS is applied to the Multicast Routing Problem. Multicast Routing is modeled as the NP-complete Steiner tree problem. This is the shortest path from source node to all destination nodes. We proposed new AS to resolve this problem. The proposed method selects the neighborhood node to consider all costs of the edge and the next node in state transition rule. Also, The edges which are selected elite agents are updated to additional pheromone. Simulation results of our proposed method show fast convergence and give lower total cost than original AS and $AS_{elite}$.