The employment rate of a college has long been one of the most important elements in college survival strategies. Employment rates may not be key to colleges' survival in other countries, but they are fundamental to colleges in Korea as seen in the Korean government-led National Competency Standard (NCS), which has been underway since its introduction to colleges in Korea. Against this backdrop, if the engineering accreditation system can contribute to improving employment rate in this context, it can take root more quickly. The process conducive to improving employment rates can be classified as both direct and indirect methods. With dwindling school-age population having impacts on colleges and universities, the environment and the education directions of colleges have rapidly been shifting since the introduction of the NCS. Therefore, various survival strategies for colleges need to be developed. An indicator of employment rate of college graduates is among the most important things during this transition process. The Department of Mechanical Engineering at Koje College has consistently shown good records during the past 5 years by matching the accreditation schemes and employment strategies. The department will help put in place the engineering technology education accreditation system at the college through its various innovative and effective programs. To formulate a better employment strategy, it is needed to reflect and consolidate the engineering accreditation scheme into the existing employment policy of college. In short, this paper examines both the engineering accreditation scheme and the employment policy in ways that helps produce a coupling matrix structure. This study looks into the measures for improving employment rates by better adjusting the engineering education methods under the accreditation scheme.
Journal of Information Technology Applications and Management
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v.24
no.2
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pp.39-54
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2017
At present, various technologies are rapidly advancing, centering on the concept of virtuality. From the technology of virtual reality, which allows us to experience the senses as if they existed, to the technology of augmented reality, which provides new information or services based on reality, they are no longer strange things for ourselves because we experience them every day and night. Even though the concept of virtual is very familiar in terms of technology, it is not known how individuals accept the concept of virtuality, how they change our way of thinking, and how their behavior changes. This study aims to approach virtuality perceived by the individual from the viewpoint of individual's information processing. Virtuality is defined as the degree to which the situation facing an individual is far from actual reality. An individual can judge the degree of virtuality easily, which is considered to be a psychological distance which is an important factor in personal information processing. In this study, we have confirmed whether the argument is applied to the real world in the context of advertisement. According to the construal level theory, when an individual feels virtuality at a high level, the individual thinks that the situation they are facing is psychologically distant and accordingly has a high level construal. Therefore, it is more influenced by 'advertisement emphasizing symbolic appeal' which is matching with higher level. On the other hand, when an individual feels a low level of virtuality, the individual thinks that the situation they are facing is psychologically near and thus has a low level construal. Therefore, respondents are more sensitive to functional appeal, which is related to lower level. This study has the theoretical contribution in terms that the degree of virtuality affects the psychological distance of the individual. In addition, the results of this study have practical contribution in terms of being able to be actively used in the information delivery strategy centered on the advertisement.
Recently, various universities in Korea have started to work on strengthening their liberal arts and character education through the residential college (RC) system, carrying out various community programs for this purpose. However, because most programs are based on student-to-student relationships, problems can often arise within the community living environments. This paper proposes the roommate assignment algorithm in the context of a residential college, as to effectively achieve character education goals. The clustering algorithm we propose is based on the similarity hypothesis. As a result of the assignment, the degree of similarity (euclidean distance) between roommates was significantly higher than that assigned randomly. The algorithm developed in this study was applied to the data of the students living in the international campus of H University.
Journal of Korean Society of Industrial and Systems Engineering
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v.38
no.4
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pp.168-176
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2015
Trends of integrating products and services lead to the emergence of Product-Service System (PSS). To implement and embody a PSS solution in new product development, a comprehensive design framework is allowed designers to facilitate the design factors of the PSS in complex business environments. A physical product, containing functionalities for services, is the role of medium between customers and a manufactures. Customers can access those metaphysical interfaces to utilize the product fully or expand its performances. The PSS is aiming to prolong its lifecycle while maintaining its expected quality. Since the quality can be represented as a measure which belongs to user's perspective, guaranteeing certain level of quality can be interpreted to sustaining customer satisfaction. The objective of this paper is to propose a PSS design framework to identify design factors for developing products and services by integrating object-oriented concepts and blueprinting in context of a business ecosystem. The proposed model is developed based on relationship products and services matching with their design factors. The products and the services are then brought together to form a PSS. Functions and processes can be categorized to identify the design factors in different levels using the object-oriented concepts. Objected-oriented concepts provide PSS analysis tools for describing a business process or a workflow process in the PSS. The blueprint is used to identify the relationships between the products functions and the service processes that are offered as part of a job. To demonstrate of the effectiveness of the proposed model, we use a case study involving a smart phone.
Journal of Korean Society of Industrial and Systems Engineering
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v.43
no.4
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pp.116-122
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2020
Human and material resource planning is one representative example of Operations Research. Resource planning is important not only in civilian settings but also in military ones. In the Air Force, flight scheduling is one of the primary issues that must be addressed by the personnel who are connected to flight missions. However, although the topic is of great importance, relatively few studies have attempted to resolve the problem on a scientific basis. Each flight squadron has its own scheduling officers who manually draw up the flight schedules each day. While mistakes may not occur while drafting schedules, officers may experience difficulties in systematically adjusting to them. To increase efficiency in this context, this study proposes a mathematical model based on a binary variable. This model automatically drafts flight schedules considering pilot's mission efficiency. Furthermore, it also recommends that schedules be drawn up monthly and updated weekly, rather than being drafted from scratch each day. This will enable easier control when taking the various relevant factors into account. The model incorporates several parameters, such as matching of the main pilots and co-pilots, turn around time, availability of pilots and aircraft, monthly requirements of each flight mission, and maximum/minimum number of sorties that would be flown per week. The optimal solution to this model demonstrated an average improvement of nearly 47% compared with other feasible solutions.
Journal of Korean Society of Archives and Records Management
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v.21
no.1
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pp.211-230
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2021
This study aims to design folk song metadata based on the OAIS reference model for the folk songs' preservation and permanent use. Thus, the folk songs' general characteristics were investigated by researching literature and related technical standards. The type of records, the methods and standards for long-term storage of records, OAIS reference models, and each package's metadata elements were identified through opinions from the popular songs' creators and researchers. The results awere that first, folk songs were created for social transformation, serving as a cultural heritage different from popular songs given their noncommercial quality. Second, the types of folk song records were identified, and the long-term preservation system suitable for the types of records was based on the OAIS reference model. Third, the metadata were edited, and the OIS reference model was applied such that respect was given to the folk songs' characteristics, context, and original order. Fourth and last, information package metadata elements matching the folk songs' records were derived and applied to the representative Korean folk song, "The March for Being."
Zhou, Han;Guo, Xuchao;Liu, Chengqi;Tang, Zhan;Lu, Shuhan;Li, Lin
KSII Transactions on Internet and Information Systems (TIIS)
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v.15
no.11
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pp.3991-4010
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2021
The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.
Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
Journal of Intelligence and Information Systems
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v.18
no.1
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pp.1-21
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2012
In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.
Purpose This study examines the roles of individual- and country-level social capital in entrepreneurial activities from the context of crowdfunding. Design/methodology/approach Two primary sources were used for data collection. From Kickstarter, the largest U.S.-based crowdfunding platform, this study obtained 15,716 crowdfunding projects and individual-level social capital. For country-level social capital, the social capital index from the 2016 Legatum Prosperity Index was utilized. By matching individual- and country-level social capital for each crowdfunding project, this research estimates the role of social capital in entrepreneurial activities at the individual and country level using the Poisson regression and the negative binomial regression. Findings Individual-level social capital measured by the number of Facebook friends, the number of other crowdfunding projects that a crowdfunding project founder invested in, and the word count of the description of a crowdfunding project are positively associated with the number of crowdfunding projects created by founders. The country-level social capital measured by aggregated social capital index is also positively associated with the number of crowdfunding projects created by founders. Both individual- and country-level social capital have a positive impact on entrepreneurial activities in terms of the creation of new crowdfunding projects.
Entity Linking find the meaning of an entity mention, which indicate the entity using different expressions, in a user's query by linking the entity mention and the entity in the knowledge base. This task has four challenges, including the difficult knowledge base construction problem, multiple presentation of the entity mention, ambiguity of entity linking, and NIL entity recognition. In this paper, we first construct the entity name dictionary based on Wikipedia to build a knowledge base and solve the multiple presentation problem. We then propose various methods for NIL entity recognition and solve the ambiguity of entity linking by training the support vector machine based on several features, including the similarity of the context, semantic relevance, clue word score, named entity type similarity of the mansion, entity name matching score, and object popularity score. We sequentially use the proposed two methods based on the constructed knowledge base, to obtain the good performance in the entity linking. In the result of the experiment, our system achieved 83.66% and 90.81% F1 score, which is the performance of the NIL entity recognition to solve the ambiguity of the entity linking.
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