• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.199-211
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• 2015

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.257-262
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• 2001

As computer-related technologies have been developed, legacy design systems have not been appropriate for new computing environment. Therefore, it is necessary that most of them are either modified or newly developed. However, this requires quite much amount of cost and time. This paper presents a method of extending legacy design system without modification using XML and XSLT. In order to apply the developed method, a good example of legacy design systems, AGMA gear rating system has been extended so as to be suitable for the distributed computing environment. An XML document for AGMA gear rating process is defined. It is transformed to the form of the input document of AGMA gear rating system by XSLT processor according to the transformation rules defined in the AGMA gear rating XSLT document. After that, AGMA gear rating system reads this input document and generates an output document in the server. These operations are automatically executed by the external legacy system controller without user interactions. Using these operations, AGMA gear rating web service has been developed based on SOAP and WSDL to provide the functions of legacy AGMA gear rating system through the distributed network. Any system or user can implement AGMA gear rating process independently to the platform type, without making it for oneself, by simply referring the AGMA gear rating web service via Internet.

• Management Science and Financial Engineering
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• 제11권3호
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• pp.137-153
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• 2005

Collaborative filtering-based recommendation systems make personalized recommendations based on users' ratings on products. Recommender systems must collect sufficient rating information from users to provide relevant recommendations because less user rating information results in poorer performance of recommender systems. To learn about new users, recommendation systems must first present users with an initial item list. In this study, we designed and analyzed seven selection strategies including the popularity, favorite, clustering, genre, and entropy methods. We investigated how these strategies performed using MovieLens, a public dataset. While the favorite and popularity methods tended to produce the highest average score and greatest average number of ratings, respectively, a hybrid of both favorite and popularity methods or a hybrid of demographic, favorite, and popularity methods also performed within acceptable ranges for both rating scores and numbers of ratings.

• Smart Structures and Systems
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• 제32권6호
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• pp.371-382
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• 2023

Box girder bridges are now widely used in bridge construction, and it is necessary to perform load rating regularly to evaluate the load capacity of box girder bridges. Load testing is a common measure for load rating. However, the bridge must be loaded by many trucks under different loading conditions, which is time-consuming and laborious. To solve this problem, this paper proposes a load rating method for box girder bridges based on rapid moving loads testing. The method includes three steps. First, the quasi-influence factors of the bridge are obtained by crossing the bridge with rapidly moving loads, and the structural modal parameters are simultaneously obtained from the dynamic data to supplement. Second, an objective function is constructed, consisting of the quasi-influence factors at several measurement points and structural modal parameters. The finite element model for load rating is then updated based on the Rosenbrock method. Third, on this basis, a load rating method is proposed using the updated model. The load rating method proposed in this paper can considerably reduce the time duration of traditional static load testing and effectively utilize the dynamic and static properties of box girder bridges to obtain an accurate finite element model. The load capacity obtained based on the updated model can avoid the inconsistency of the evaluation results for the different structural members using the adjustment factors specified in codes.

• Asia pacific journal of information systems
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• 제25권3호
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• pp.579-596
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• 2015

Many studies have focused on the prediction of corporate credit rating using various data mining techniques. One of the most frequently used algorithms is support vector machines (SVM), and recently, novel techniques such as SVM+ and SVM+MTL have emerged. This paper intends to show the applicability of such new techniques to multi-classification and corporate credit rating and compare them with conventional SVM regarding prediction performance. We solve multi-class SVM+ and SVM+MTL problems by constructing several binary classifiers. Furthermore, to demonstrate the robustness and outstanding performance of SVM+MTL algorithm over other techniques, we utilized four typical multi-class processing methods in our experiments. The results show that SVM+MTL outperforms both conventional SVM and novel SVM+ in predicting corporate credit rating. This study contributes to the literature by showing the applicability of new techniques such as SVM+ and SVM+MTL and the outperformance of SVM+MTL over conventional techniques. Thus, this study enriches solving techniques for addressing multi-class problems such as corporate credit rating prediction.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.437-443
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• 2013

Recently, sustainable building design, a growing field within architectural design, has been emerged in the construction industry as the practice of designing, constructing, and operating facilities in such a manner that their environmental impact, which has become a great concern of construction professionals, can be minimized. A number of different green rating systems have been developed to help assess that a building project is designed and built using strategies intended to minimize or eliminate its impact on the environment. In the United States, the widely accepted national standards for sustainable building design are known as the LEED (Leadership in Energy and Environmental Design) Green Building Rating System. The assessment of sustainability using the LEED green rating system is a challenging and time-consuming work due to its complicated process. In effect, the LEED green rating system awards points for satisfying specified green building criteria into five major categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, and indoor environmental quality; and sustainability of a project is rated by accumulating scores (100 points maximum) from these five major categories. The sustainability rating process could be accelerated and facilitated by using computer technology such as BIM (Building Information Modeling), an innovative new approach to building design, engineering, and construction management that has been widely used in the construction industry. BIM is defined as a model-based technology linked with a database of project information, which can be accessed, manipulated, and retrieved for construction estimating, scheduling, project management, as well as sustainability rating. This paper will present a framework representing the building knowledge contained in the LEED green building criteria. The proposed building knowledge framework will be implemented into a BIM platform (e.g. Autodesk Revit Architecture) in which sustainability rating of a building design can be automatically performed. The development of the automated sustainability rating system and the results of its implementation will be discussed.

• Asia pacific journal of information systems
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• 제15권1호
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• pp.63-79
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• 2005

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is known to be the most successful recommendation technology, but its widespread use has exposed some problems such as sparsity and scalability in the e-business environment. In this paper, we propose a recommendation system, WebCF-PT based on Web usage mining and product taxonomy to enhance the recommendation quality and the system performance of traditional CF-based recommender systems. Web usage mining populates the rating database by tracking customers' shopping behaviors on the Web, so leading to better quality recommendations. The product taxonomy is used to improve the performance of searching for nearest neighbors through dimensionality reduction of the rating database. A prototype recommendation system, WebCF-PT is developed and Internet shopping mall, EBIB(e-Business & Intelligence Business) is constructed to test the WebCF-PT system.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.724-736
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• 2019

Dynamic thermal rating technology can effectively improve the thermal load capacity of transmission lines. However, its availability is limited by the quantity and high cost of the hardware facilities. This paper proposes a new dynamic thermal rating technology based on global/regional assimilation and prediction system (GRAPES) and geographic information system (GIS). The paper will also explore the method of obtaining any point meteorological data along the transmission line by using GRAPES and GIS, and provide the strategy of extracting and decoding meteorological data. In this paper, the accuracy of numerical weather prediction was verified from the perspective of time and space. Also, the 750-kV transmission line in Shaanxi Province is considered as an example to analyze. The results of the study indicate that dynamic thermal rating based on GRAPES and GIS can fully excavate the line power potential without additional cost on hardware, which saves a lot of investment.

• 경영정보학연구
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• 제18권3호
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• pp.155-183
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• 2016

방대한 콘텐츠가 생산되고 소비되면서 빅데이터를 활용한 개인 추천 서비스가 최근 주목 받고 있다. 개인 추천 서비스를 위하여 개인 정보나 콘텐츠 평가 정보를 수집하는 것은 서비스 제공자 입장에서 중요해지고 있다. 기존 연구들은 적은 평점 정보로 더 나은 추천을 제공할 수 있는 알고리즘을 제안하거나, 평점의 양을 늘리기 위한 서비스 디자인을 제시하였다. 그러나 추천서비스 사용자가 어떤 동기로 평점을 입력하고, 서비스를 지속적으로 사용하는지에 대한 연구는 거의 없었다. 본 논문에서는 추천 서비스를 사용하고 있는 사용자들을 심층 인터뷰하여 평점 입력의 동기와 평점의 의미에 대하여 탐구하였다. 그 결과, 서비스를 경험 하면서 평점의 의미와 활용 정도가 달라짐을 알 수 있었다. 초기 평점을 입력할 때에는 과거 경험에 대한 데이터베이스를 구축하는 의미로 활용하였고, 초기 평점 단계를 지나면 현재의 느낌과 생각을 반영하는 도구로 활용하였다. 이 과정에서 자신의 평점 체계를 정교하게 다듬으며 자신만의 의미를 부여하는 모습을 보였다. 마지막 단계에서는 자신의 평점 체계뿐만 아니라 다른 사람의 평점 체계나 평점의 의미를 읽어내고 적극적으로 활용하는 모습을 보인다. 서비스에서 제공하는 알고리즘의 한계를 파악하고 있기 때문에 서비스의 추천을 불신하기도 하였다. 연구 결과를 바탕으로 추천 서비스에 대한 실무적 시사점을 도출하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.6097-6120
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• 2019

Online consumer reviews (OCRs) provide product information and recommendations especially pictures in reviews depict the true information about the product. This study investigates the influence of pictured reviews on online seller (for a particular product of a seller) rating with moderating effect of price, brand type (foreign vs local), goods type (experience vs search), and brand familiarity. Multiple robust linear regression analysis with moderation interaction and quadratic effect used to explain the relationship of the explanatory variables with the criterion variable. We collected cross-sectional data from the two most renowned Chinese online shopping platforms (B2C) of total 15,621 product links. Results show that higher number of reviews with a low ratio of picture reviews response negative effect on rating, whereas the lower number of reviews with a high ratio of picture reviews response positive effect on the rating. In overall picture in the reviews improve the online seller product rating. For the moderation effect, results show that price and brand familiarity have a positive interaction effect on the relation of pictured reviews and rating whereas experience goods have less negative effect comparing search goods. Finally, local brand has less negative interaction effect comparing foreign brand to pictured reviews and rating.