• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.357-362
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• 2023

The conflict between upstream and downstream regions is a representative social conflict in Korea. It is important issues in the economic and environmental aspects related to interests of property rights and water quality conservation. however, it is insufficient for studies on the economic damage and benefits between upstream and downstream by policy. We studied validity for drinking water protect zone, one of the major water conflict in Korea, by comparison between social loss by property rights restriction in the upstream and social benefits in the downstream and we proposed integrated water management policy in basin level.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.131-143
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• 2024

Purpose - The purpose of this study was to analyze cases of big data-driven business in the financial industry, focusing on organizational structure and business processes using big data in banking industry. Design/methodology/approach - This study used a case study approach. To this end, cases of two banks implementing big data-driven business were collected and analyzed. Findings - There are two things in common between the two cases. One is that the central tasks for big data-driven business are performed by a centralized organization. The other is that the role distribution and work collaboration between the headquarters and business departments are well established. On the other hand, there are two differences between the two banks. One marketing campaign is led by the headquarters and the other marketing campaign is led by the business departments. The two banks differ in how they carry out marketing campaigns and how they carry out big data-related tasks. Research implications or Originality - When banks plan and implement big data-driven business, the common aspects of the two banks analyzed through this case study can be fully referenced when creating an organization and process. In addition, it will be necessary to create an organizational structure and work process that best fit the special situation considering the company's environment or capabilities.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Journal of radiological science and technology
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• v.47 no.4
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• pp.287-294
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• 2024

Radiation oncology departments are at high risk for potential radiation safety incidents. This study aimed to identify risk factors for these incidents using the P-mSHEL (Patient, Management, Software, Hardware, Environment, and Liveware) model and to evaluate potential accident types through Failure Mode and Effects Analysis (FMEA). FMEA identified seven accident types with high Risk Priority Number (RPN). A total of 56 detailed risk factors were classified using the P-mSHEL model, and measures to prevent radiation safety incidents were implemented. The effect of these preventive measures on workers' safety perception was confirmed through two indicators (FMEA and safety perception). After implementing the preventive measures, the FMEA analysis showed that the highest reduction in RPN was for A-6 (radiation exposure while other patients/guardians are present) with a reduction rate of 33.3%, followed by B-3 (radiation exposure while staff are present) with a reduction rate of 33.3%. Overall safety perception significantly improved after the preventive measures (4.17±0.35) compared to before (2.76±0.33) (p<0.05), with notable increases in both employee safety culture (3.93±0.51) and patient safety culture (3.73±0.62) (p<0.05). This study identified risk factors in radiation oncology departments. Continuous management, maintenance, and fostering a strong safety culture are crucial for preventing incidents. Regular problem identification and collaboration with relevant departments are essential for maintaining safety standards.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.909-916
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• 2024

The emergence of Building Information Modelling (BIM), reality data, Virtual Reality (VR), and Augmented Reality (AR) has significantly enhanced the collaboration between stakeholders in construction management. The utilization of VR/AR devices holds considerable potential for monitoring safety in complex and constrained working environments on the construction site. On the other hand, near-miss incidents remain an important early sign of struck-by accidents. However, research on early warning and prevention methods for this risk is still limited. This paper, therefore, presents a framework for on-site and off-site collaborative safety monitoring framework using augmented and virtual reality for near-miss incidents. In the proposed framework, three phases to develop a VR/AR-based safety monitoring system include (1) construction safety simulation environment, (2) localization-based interaction system, and (3) safety monitoring system. The system can undertake the processing of data and enables communication among disparate VR/AR devices. VR clients are observational tools and offer guidance, while the AR client stays onsite for construction tasks. All clients connect to a processing computer, which also works as a host. The system embedded in the AR device can trigger an alarm or receive signals from the VR client when a near-miss issue happens. Additionally, all device clients possess the capability to share data acquired from onsite monitoring cameras, thereby fostering effective discussions and decision-making. The efficacy of this cross-platform system has been validated through the implementation of an outdoor coordination case study.

• Journal of Ecology and Environment
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• v.48 no.3
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• pp.343-373
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• 2024

Background: The present study provides valuable insights into the traditional uses of medicinal plants by the inhabitants of the Northern District of the lesser Himalayas in Azad Jammu and Kashmir, Pakistan. The study likely focuses on documenting and preserving the region's indigenous knowledge and practices related to medicinal plants. Ethnobotanical data were collected by interviewing 72 local informants including practitioners, farmers, teachers, and laborers from different localities of District Jhelum Valley. Different quantitative tools were used for the analysis of ethnobotanical data including relative frequency of citation, use value, informant consensus factor, fidelity level, cultural value, practical value, consensus value for plant part, rank order priority, percentage respondent knowledge, economic value and their total value were calculated. Jaccard's index (JI) was used to compare the present knowledge with the previous studies in the same or surrounding areas. Results: A total of 129 species belonging to 111 genera and 63 families were documented along with their ethnobotanical uses. Dominant families based on the number of species include Rosaceae contributing 12 species followed by Asteraceae and Saxifragaceae with 8 species each. The comparative study of the novelty of species and their uses by the JI revealed 13 novel plant species which were not reported earlier from this region. Conclusions: This information is not only important for scientific and ethnobotanical purposes but also for the sustainable management of medicinal plant resources and the potential discovery of new natural medicine. Such studies can help to bridge the gap between traditional and modern medicines and collaboration between traditional healers and health care practitioners.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.28-36
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• 2009

While existing literature has focused extensively on the strengths and weaknesses of the Chaebol and their ownership and governance, there have been few studies of Korean non-Chaebol firms. However, Lee, Lee and Pennings (2001) did not specifically investigate the competitive strategies that non-Chaebol firms use to survive against the Chaebol in the domestic Korean market. The motivation of this paper is to document, through four exploratory case studies, the successful competitive strategies of non-Chaebol Korean companies against the Chaebol and then offer some propositions that may be useful to other entrepreneurial firms as well as public policy makers. Competition and cooperation as conceptualized by product similarity and cooperative inter.firm relationship respectively, are major dimensions of firm.level marketing strategy. From these two dimensions, we develop the following $2{\times}2$ matrix, with 4 types of competitive strategies for non-Chaebol companies against the Chaebol (Fig. 1.). The non-Chaebol firm in Cell 1 has a "me-too" product for the low-end market while conceding the high-end market to a Chaebol. In Cell 2, the non-Chaebol firm partners with a Chaebol company, either as a supplier or complementor. In Cell 3, the non-Chaebol firm engages in direct competition with a Chaebol. In Cell 4, the non-Chaebol firm targets an unserved part of the market with an innovative product or service. The four selected cases such as E.Rae Electronics Industry Company (Co-exister), Intops (Supplier), Pantech (Competitor) and Humax (Niche Player) are analyzed to provide each strategy with richer insights. Following propositions are generated based upon our conceptual framework: Proposition 1: Non-Chaebol firms that have a cooperative relationship with a Chaebol will perform better than firms that do not. Proposition 1a; Co-existers will perform better than Competitors. Proposition 1b: Partners (suppliers or complementors) will perform better than Niche players. Proposition 2: Firms that have no product similarity with a Chaebol will perform better than firms that have product similarity. Proposition 2a: Partners (suppliers or complementors) will perform better than Co.existers. Proposition 2b: Niche players will perform better than Competitors. Proposition 3: Niche players should perform better than Co-existers. Proposition 4: Performance can be rank.ordered in descending order as Partners, Niche Players, Co.existers, Competitors. A team of experts was constituted to categorize each of these 216 non-Chaebol companies into one of the 4 cells in our typology. Simple Analysis of Variance (ANOVA) in SPSS statistical software was used to test our propositions. Overall findings are that it is better to have a cooperative relationship with a Chaebol and to offer products or services differentiated from a Chaebol. It is clear that the only profitable strategy, on average, to compete against the Chaebol is to be a partner (supplier or complementor). Competing head on with a Chaebol company is a costly strategy not likely to pay off for a non-Chaebol firm. Strategies to avoid head on competition with the Chaebol by serving niche markets with differentiated products or by serving the low-end of the market ignored by the Chaebol are better survival strategies. This paper illustrates that there are ways in which small and medium Korean non-Chaebol firms can thrive in a Chaebol environment, though not without risks. Using different combinations of competition and cooperation firms may choose particular positions along the product similarity and cooperative relationship dimensions to develop their competitive strategies-co-exister, competitor, partner, niche player. Based on our exploratory case-study analysis, partner seems to be the best strategy for non-Chaebol firms while competitor appears to be the most risky one. Niche players and co-existers have intermediate performance, though the former do better than the latter. It is often the case with managers of small and medium size companies that they tend to view market leaders, typically the Chaebol, with rather simplistic assumptions of either competition or collaboration. Consequently, many non-Chaebol firms turn out to be either passive collaborators or overwhelmed competitors of the Chaebol. In fact, competition and collaboration are not mutually exclusive, and can be pursued at the same time. As suggested in this paper, non-Chaebol firms can actively choose to compete and collaborate, depending on their environment, internal resources and capabilities.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.