• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.129-139
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• 2012

This paper introduces a recommender system that is to recommend broadcast content. Our recommender system uses user's viewing history for personalized recommendations. Broadcast contents has unique characteristics as compared with books, musics and movies. There are two types of broadcast content, a series program and an episode program. The series program is comprised of several programs that deal with the same topic or story. Meanwhile, the episode program covers a variety of topics. Each program of those has different topic in general. Therefore, our recommender system recommends TV programs to users according to the type of broadcast content. The recommendations in this system are based on user's viewing history that is used to calculate content similarity between contents. Content similarity is calculated by exploiting collaborative filtering algorithm. Our recommender system uses java sparse array structure and performs memory-based processing. And then the results of processing are stored as an index structure. Our recommender system provides recommendation items through OPEN APIs that utilize the HTTP Protocol. Finally, this paper introduces the implementation of our recommender system and our web demo.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• Korean Journal of Construction Engineering and Management
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• v.19 no.4
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• pp.70-81
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• 2018

Claims in the construction industry can have a serious impact on the profitability of the project or can even result in project failure if it fails to take appropriate prevention. In order to properly prevent and respond to the potential claims and legal disputes throughout the project execution, it is necessary to continuously accumulate informations and clearly define the roles and responsibilities of the important activities systematically. Based on these needs, this study develops and verifies the project information management system(PMIS) that can prevent and respond possible claims for construction projects. Developed system includes such management modules as schedule, cost, PM/CM, design, collaboration, and claims. The system was validated by adopting it to the practical projects. The results showed that information systems tailored to the construction claim need to elevate users' familiarity to be more useful. Besides, the system can be more functional when used by both owners and contractors.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.7
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• pp.389-397
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• 2016

Digital Humanities System is a method to effectively share and spread Humanities information and knowledge to users by using information technology. It Also comes into the spotlight as a new research methodology for researches of Humanities researchers. Digital Humanities System distinguishes itself from other existing information systems. Therefore, when the system is developed, it needs to supply with manpower related to development process which is specialized for Digital Humanities System, not for the several established construction methodology. Digital Humanities System studies recently is mostly constructed using the usual methodology of information system construction. Because of its falling efficiency and usability after constructing the system, however, examples of failure of operating system occur. In this paper, accordingly, effective and creative Digital Humanities System development methodology will be studied from the point of view of information technology through collaboration with various field of expertise. In detail, based on information system methodologies in software engineering perspective, we propose a methodology to build a specialized system in the digital humanities.

• Information Systems Review
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• v.19 no.2
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• pp.71-94
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• 2017

Recommender systems reduce information overload and enhance choice quality. This technology is used in many services and industry. Previous studies did not consider recommendation quantity and the repetitive recommendations of an item. This study is the first to examine recommender systems by considering recommendation quantity and repetitive recommendations. Only a limited number of items are displayed in offline stores because of their physical limitations. Determining the type and number of items that will be displayed is an important consideration. In this study, I suggest the use of a user-based recommender system that can recommend the most appropriate items for each store. This model is evaluated by MAE, Precision, Recall, and F1 measure, and shows higher performance than the baseline model. I also suggest a new performance evaluation measure that includes Quantity Precision, Quantity Recall, and Quantity F1 measure. This measure considers the penalty for short or excess recommendation quantity. Novelty is defined as the proportion of items in a recommendation list that consumers may not experience. I evaluate the new revenue creation effect of the suggested model using this novelty measure. Previous research focused on recommendations for customer online, but I expand the recommender system to cover stores offline.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.304-311
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• 2023

The 4th Industrial Revolution and the continuous development of Science and Technology have also required a speedy business promotion method in the defense industry. Advanced countries including the United States are already boldly innovating the existing high-cost and long-term acquisition system with the highest priority in weapons development to cope with the military rise of Russia and China. The Ministry of National Defense and the Defense Acquisition Program Administration have also recently introduced a quick acquisition system and are applying it to business promotion. In addition, some small-scale projects and weapons systems are being reorganized so that they can be managed by the units demanding them. After an organizational diagnosis of the Project Acquisition Group by the Ministry of National Defense in 2020, it has been reassigned as a subordinate unit of the Army Logistics Command from a direct unit managed by the Army HQ. As a result, problems such as work conflict or redundancy have been identified. In addition, a system has been implemented to shorten the acquisition period by applying a rapid acquisition program in the field of weapons systems by benchmarking the rapid acquisition program of advanced countries. The force support system project process will also need to introduce such a quick acquisition system. In addition, the Ministry of National Defense is considering ways to delegate some weapon systems to each military, which will then carry out tasks ranging from requirements determination to project management. Accordingly, it is now time to expand the organization for the management of the Army's weapons system acquisition project. Therefore, in this paper, the Army Project Acquisition Group was analyzed on its organization, acquisition procedures, and cooperation systems, with presentations of development plans for each field.

• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.51-60
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• 2003

The growth of the World Wide Web and the advances in high-speed network access have greatly changed existing CAD/CAE environment. The WWW has enabled us to share various distributed product data and to collaborate in the design process. An international standard for the product model data, STEP, and a standard for the distributed object technology, CORBA, are very important technological components for the interoperability in the advanced design and manufacturing environment. These two technologies provide background for the sharing of product data and the integration of applications on the network. This paper describes a distributed CAD/CAE environment that is integrated on the network by CORBA and product model data standard STEP. Several prototype application modules were implemented to verify the proposed concept and the test result is discussed. Finite element analysis server are further distributed into several frontal servers for the implementation of distributed parallel solution of finite element system equations. Distributed computation of analysis server is also implemented by using CORBA for the generalization of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

• Journal of Aerospace System Engineering
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• v.15 no.3
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• pp.65-70
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• 2021

This study presents a method to efficiently advance the Republic of Korea's Unmanned Systems through the analysis of the development of the U.S. Unmanned System Policy. After the occurrence of the September 11 attacks, the U.S. developed Unmanned Systems as a part of RMA and became the leader in this area. The system went through numerous trials and errors during the development and acquisition. From these experiences, the U.S. had embodied Unmanned Systems acquisition methods by establishing Unmanned Systems Development Guidance and DoD Autonomy Community of Interest in 2012. In addition, as diverse unmanned programs started to proceed, it promoted Core Technology development sharing and simplification of functions of the Unmanned Systems to exclude budget-wasting elements such as duplication of programs. The Republic of Korea must politically build a collaborative system between industry/academia/research institute/military and apply evolutionary development strategies from the first step of the development of the Unmanned Systems the future Game Changer. In operations, concepts of the Manned/Unmanned Systems complex operation should be established and intelligent S/W, Open System, and Cyber Security technologies to materialize them developed.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.