• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.3
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• pp.125-137
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• 1987

The purpose of this paper is to examine some difficulties in water management of agricultural reservoirs in Korea, for there are approximately more than 15,000 reservoirs which are now being utilized for the purpose of irrigation, along with the much amount of expenses and labors to be invested against droughts and floods periodically occurred. Recently, the effective use of water resources in the agricultural reservoirs with a single purpose, is becomming multiple according to the alterable environment of water use. Therefore, the task to allocate agricultural water rationally and economically must be solved for the multiple use of agricultural reservoirs. On the basis of the above statement, this study aims at suggesting the rational method of water management by introducing an optimal technique to allocate the water in an existing agricultural reservoir rationally, for the sake of maximizing the economic effect. To achieve this objective, a reservoir, called "0-Bongje" as a sample of the case study, is selected for an agricultural water development proiect of medium scale. As a model for the optimum allocation of water in the multi-purpose use of reservoirs a linear programming model is developed and analyzed. As a result, findings of the study are as follows : First, a linear programing model is developed for the optimum allocation of water in the multi-purpose use of agricultural reservoirs. By adopting the model in the case of reservoir called "O-Bongje," the optimum solution for such various objects as irrigation area, the amount of domestic water supply, the size of power generation, and the size of reservoir storage, etc., can be obtained. Second, by comparing the net benefits in each object under the changing condition of inflow into the reservoir, the factors which can most affect the yearly total net benefit can be drawn, and they are in the order of the amount of domestic water supply, irrigation area, and power generation. Third, the sensitivity analysis for the decision variable of irrigation which may have a first priority among the objects indicate that the effective method of water management can be rapidly suggested in accordance with a condition under the decreasing area of irrigation. Fourth, in the case of decision making on the water allocation policy in an existing multi-purpose reservoir, the rapid comparison of numerous alternatives can be possible by adopting the linear programming model. Besides, as the resources can be analyed in connection with various activities, it can be concluded that the linear programing model developed in this study is more quantitative than the traditional methods of analysis. Fifth, all the possible constraint equations, in using a linear programming model for adopting a water allocation problem in the agricultural reservoirs, are presented, and the method of analysis is also suggested in this study. Finally, as the linear programming model in this study is found comprehensive, the model can be adopted in any different kind of conditions of agricultural reservoirs for the purpose of analyzing optimum water allocation, if the economic and technical coefficients are known, and the decision variable is changed in accordance with the changing condition of irrigation area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.1-20
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• 2022

The basic way to charge vehicles for using road and public transport networks is the entry-exit toll system. This system works by reading Hi-Pass and public transportation cards of the vehicles using card readers. However, the problems of navigating a route in consideration of entry-exit toll systems include the non-additive costs of enumerating routes. This problem is known as an NP-complete task that enumerates all paths and derives the optimal path. So far, the solution to the entry-exit toll system charging has been proposed in the form of transforming the road network. However, unlike in the public transport network where the cards are generalized, this solution has not been found in situations where network expansion is required with a transfer, multi-modes and multiple card readers. Hence, this study introduced the Link Label for a public transportation network composed of card readers in which network expansion is bypassed in selecting the optimal path by enumerating the paths through a one-to-one k-path search. Since the method proposed in this study constructs a relatively small set of paths, finding the optimal path is not burdensome in terms of computing power. In addition, the ease of comparison of sensitivity between paths indicates the possibility of using this method as a generalized means of deriving an optimal path.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.78-88
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• 2017

With the growing use of BIM in the AEC industry, various new applications are being developed to meet these specific needs. Such developments have increased the importance of Industry Foundation Classes, which is the international standard for sharing BIM data and thus ensuring interoperability. However, mapping individual BIM objects to IFC entities is still a manual task, and is a main cause for errors or omissions during data transfers. This research focused on addressing this issue by applying novelty detection, which is a technique for detecting anomalies in data. By training the algorithm to learn the geometry of IFC entities, misclassifications (i.e., outliers) can be detected automatically. Two IFC classes (ifcWall, ifcDoor) were trained using objects from three BIM models. The results showed that the algorithm was able to correctly identify 141 of 160 outliers. Novelty detection is thus suggested as a competent solution to resolve the mapping issue, mainly due to its ability to create multiple inlier boundaries and ex ante training of element geometry.

• Korean Security Journal
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• no.20
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• pp.229-248
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• 2009

This research is looking for the private security industry and diagnostic issues and enable our strategy will be presented through SWOT analysis for the management environment of private security industry to ultimately contribute to the private security industry. Along, the purpose of this research is to want to reach key factors which affect the competitiveness of the private security industry. This study was to conduct literature research and surveys. And analyzing literature and data was collected. And determined the status of private security industry by conducted a comprehensive survey with 13 experts is causal. The question investigation hemisphere the question which harmonizes became accomplished in the center. Like this question analyzed the opinion of the identical research participant and 3 times was executed repetitively, and 2 to verify the data through multiple data as a basis for the SWOT analysis of the environment. Accordingly, the following conclusion emerges. First, the private security industry-related legislation will complement the systematic. This is the task of the public security authority and the relationship will be in the direction for improvement. Second, to develop strategies for diversification of products and services through the use of IT. This business what development security services and products based on IT advanced technology can provide a solution to maximize profits to large security companies and to all of the small companies. Third, it should seek ways to make exports that social safety net project based on security technology and capital of Kore for other Asian countries or developing countries in the world.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.41-55
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• 2023

In order to secure sustainable competitiveness of startups, business model innovation is an important task to achieve competitive advantage by transforming the various elements that make up the business model. This study conducted a multi-case analysis study on leading smart farm companies around the world using an analysis framework based on business model theory. Through this, we sought to identify business model types and their constituent elements. For this, 19 companies were selected from the list of top 10 investment startups of the year for the past three years published by Agfunder, a global investment research company specializing in AgTech. Then data collection and analysis of the company cases were conducted according to the case study protocol. As a result of the study, the business model types were analyzed into four types: large-scale centralized production model, medium-to-large local distributed production model, small-scale hyperlocal modular FaaS model, and small-scale hyperlocal turnkey solution supply model. A comparative analysis was conducted on five business model components for each type, and strategic implications were derived through this. This study is expected to contribute to improving the competitiveness of domestic smart farm startups and diversifying their strategies by identifying the business models of overseas leading companies in the smart farm field using an academic analysis framework.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.