• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• Journal of radiological science and technology
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• v.28 no.1
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• pp.33-44
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• 2005

The objective of this study is to supply the good quality of experts the radiation industries in Korea and develop the major subject matter needed in the radiation industries and the curriculum in order to execute it for the variation of fields of employment at the department of radiation in the junior college and the development of the percentage of employment. In addition, this study is to improve the level of radiation experts engaged in the industries in quality, and it is to improve the social recognition of radiation rather negative now because of the development of radiation industry. As for the core results of this research, it was to suggest the detailed choice method curriculum proper to the service fields of radiation industries, but it may be subject to change due to each college's property and the educational objectives. From the result of this research above, it may be summed up as follows. First, as for the detailed curriculum by the service field, this study was to organize two subject matters: 1. the subject matter proper to the field of using the radiation, and 2. the subject matters proper to the safety control field of radiation. Second, as for the detailed curriculum by the pattern of industries, this study was to organize the four subject matters: 1. the subject matter needed in the manufactures, 2. the subject matter needed in the nondestructive testing industries, 3. the subject matter needed in the sales agencies, and 4. the subject matter needed in the laboratories. This study was to suggest the operational model about the curriculum in order to execute these subject matters. It could be executed as two methods below. First, one method is to execute the major systems by the medical field and industrial field in the third course at the department of radiation in the junior college now. Second, the other method is to make them specialize the industrial radiation in the Advanced Course(one year course) after the graduation of junior college. To operate these curricula successively it needs to assume the deeper research and the development of materials about the subject matters related to the nuclear radiation industries hereafter. In addition, it needs to solve the security of finance like the manpower of professor, space for practice, and the educational appliances, etc. needed in the operation of subject matters. Finally, the effect and result from the development or revision of college curriculum did not come out in a short time. It will require considerable time until the undergraduates at the department in the junior college finish a set of curriculum newly developed, and graduate the university, and can get the results while they engage in their works in the industrial sites. Accordingly, all the interested parties have to anticipate the results of this research with the patience in long-standing point of view. Also, this researcher considers it as it is willing to give them the continuous interest and support.

• The Korean Journal of Archival Studies
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• no.25
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• pp.3-46
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• 2010

Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.197-209
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• 2018

Recently, many start-up failures occur as the number of attempts to start a business increases in a social atmosphere that encourages start-up. In particular, young entrepreneurs have a lower survival rate than general entrepreneurs because young entrepreneurs are challenging just with a simple idea to overcome the difficulties of employment while lacking prior knowledge and experience of business. Therefore, the reason for the failure of start-up is lack of preparation for start-up and lack of entrepreneurship. The purpose of this study is to develop a measurement tool to build a basic framework for entrepreneurship development and start - up preparation activities for young people. To develop an entrepreneurship measurement tool, researchers developed a preliminary question through qualitative research methods such as literature research, focus group interview, and expert verification. After that, researchers surveyed 102 entrepreneurs using quantitative research method and to verify the construct validity of the measurement tool, the final entrepreneurship measurement tool was completed through exploratory factor analysis and confirmatory factor analysis. The entrepreneurship measurement tool developed through this research process consists of 7 components and 15 measurement items. First, in the step of 'confirming entrepreneurial intention', two items of 'self-analytic competence', three items of 'ability of establishing start-up philosophy'are contained. Second, in the step of 'drawing up a start-up model', two items are contained in each category such as, 'ability of eliciting entrepreneurial idea,' 'ability of analyzing idea validity,' 'competence of planning a venture start-up model'. Third, in the step of 'planning the venture start-up,' two items are contained in each category such as, 'business-plan presentation competency,' 'ability of implementing organizational system.'. The measurement tool of entrepreneurship is meaningful as it could help young entrepreneur find out their lacking competence in preparing their start-ups and strengthen necessary competences by measuring their own entrepreneurship. Rather in the entrepreneurship education, basic data that can diagnose the entrepreneurship of young entrepreneurs is provided.

• Journal of Life Science
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• v.29 no.6
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• pp.747-753
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• 2019

Cognitive decline is characterized by reduced long-/short-term memory and attention span, and increased depression and anxiety. Such decline is associated with various degenerative brain disorders, especially Alzheimer's disease (AD) and Parkinson's disease (PD). The increases in elderly populations suffering from cognitive decline create social problems and impose economic burdens, and also pose safety threats; all of these problems have been extensively researched over the past several decades. Possible causes of cognitive decline include metabolic and hormone imbalance, infection, medication abuse, and neuronal changes associated with aging. However, no treatment for cognitive decline is available. In neurodegenerative diseases, changes in the gut microbiota and gut metabolites can alter molecular expression and neurobehavioral symptoms. Changes in the gut microbiota affect memory loss in AD via the downregulation of NMDA receptor expression and increased glutamate levels. Furthermore, the use of probiotics resulted in neurological improvement in an AD model. PD and gut microbiota dysbiosis are linked directly. This interrelationship affected the development of constipation, a secondary symptom in PD. In a PD model, the administration of probiotics prevented neuron death by increasing butyrate levels. Dysfunction of the blood-brain barrier (BBB) has been identified in AD and PD. Increased BBB permeability is also associated with gut microbiota dysbiosis, which led to the destruction of microtubules via systemic inflammation. Notably, metabolites of the gut microbiota may trigger either the development or attenuation of neurodegenerative disease. Here, we discuss the correlation between cognitive decline and the gut microbiota.

• 한국사회정책
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• v.24 no.1
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• pp.33-66
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• 2017

Based on the premise that the systematic career process of workers in the general labor market was one of core elements of successful achievements and their establishment both at the individual and organizational level, this study set out to conduct empirical analysis of factors influencing the subjective career success of disabled workers in competitive employment at the multi-dimensional levels of individuals and organizations(corporations) and thus provide practical implications for the career management directionality of their successful vocational life with data based on practical and statistical accuracy. For those purposes, the investigator administered a structured questionnaire to 126 disabled workers at 48 companies in Seoul, Gyeonggi, Chungcheong, and Gangwon and collected data about the individual and organizational characteristics. Then the influential factors were analyzed with the multilevel analysis technique by taking into consideration the organizational effects. The analysis results show that organizational characteristics explained 32.1% of total variance of subjective career success, which confirms practical implications for the importance of organizational variables and the legitimacy of applying the multilevel model. The significant influential factors include the degree of disability, desire for growth, self-initiating career attitude and value-oriented career attitude at the individual level and the provision of disability-related convenience, career support, personnel support, and interpersonal support at the organizational level. The latter turned out to have significant moderating effects on the influences of subjective career success on the characteristic variables at the individual level. Those findings call for plans to increase subjective career success through the activation of individual factors based on organizational effects. The study thus proposed and discussed integrated individual-corporate practice strategies including setting up a convenience support system by reflecting the disability characteristics, applying a worker support program, establishing a frontier career development support system, and providing assistance for a human network.