• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.85-94
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• 2022

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

• Knowledge Management Research
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• v.19 no.2
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• pp.109-132
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• 2018

Recently, new financial services related to FinTech has gained attention more and more. Online P2P financial services transactions such as FinTech require careful examination of the constituents of information systems as an investment is made based on the information presented on the online platform without direct face-to-face contact. The purpose of this study is to find out the success factors of online P2P Lending service among FinTech. To serve the purpose, we build IS (information system) success model, and then use Kano model and fuzzy analytic hierarchy process (Fuzzy-AHP) to find out factors for the success of online P2P Lending service. In particular, this study uses Kano model to classify information system satisfaction factors and to calculate the satisfaction coefficient. The Kano model, however, has a drawback of evaluating single criterion. Therefore, we use multi-criteria decision-making technique such as Fuzzy-AHP to derive the relative importance of the factors. The analysis results show different results depending on the analysis technique. In the Kano model, most of the information system factors are a one-dimensional quality attribute. The satisfaction coefficient is highest for personalized service, followed by the responsiveness of service, ease of using a system, understanding of information, usefulness of information' reliability. The service reliability is the highest in dissatisfaction coefficient, followed by system security, service responsiveness, system stability, and personalized service. The results of the Fuzzy-AHP analysis shows that the usefulness of information quality, the personalization of service quality, and the security of system quality are the significant factors and the stability of system quality was a secondary factor.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.67-75
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• 2014

Nowadays as video services grow rapidly, it is important for the service providers to provide customized services. Video ranking plays a key role for the service providers to attract the subscribers. In this paper we propose a weekly video ranking mechanism based on the quantified user engagement. The traditional QoE ranking mechanism is relatively subjective and usually is accomplished by grading, while QoS is relatively objective and is accomplished by analyzing the quality metrics. The goal of this paper is to establish a ranking mechanism which combines the both advantages of QoS and QoE according to the third-party data collection platform. We use data mining method to classify and analyze the collected data. In order to apply into the actual situation, we first group the videos and then use the regression tree and the decision tree (CART) to narrow down the number of them to a reasonable scale. After that we introduce the analytic hierarchy process (AHP) model and use Elo rating system to improve the fairness of our system. Questionnaire results verify that the proposed solution not only simplifies the computation but also increases the credibility of the system.

• Informatization Policy
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• v.25 no.1
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• pp.3-29
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• 2018

The Federal Communications Commission voted to repeal net neutrality protections on December 14, 2017. This is the very opposite decision of the net neutrality rule that the Obama administration has consistently maintained. The ensuing storm from the repeal of net neutrality protections has an extensively effect enough on individuals and businesses to cover the entire spectrum, and the impact is hard to assess in the U. S. content industry, which dominates the worldwide Internet content and platform market. On the other hand, Korea's net neutrality protections have been firmly pursued, and there is no sign of change even after the decision happened in the U. S. Net neutrality is not a simple theme that is associated with the Constitution, such as freedom of expression, as well as the issue of network enhancement to prepare for 5G. Accordingly, this study examines how the net neutrality has been carried out in the U. S. and Korea over the years, and provides the issues of Internet enhancement, perspectives of ISP and ICP, and implications for the Constitution, market economy, fair competition and zero rating. This research delivers future direction and implications of domestic net neutrality policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.891-899
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• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.65-83
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• 2004

Keen competence in business environments induces companies to introduce Supply Chain Management (SCM), which is accelerated by emerging information technology. Consequently, supply chain integration requires interacting and information sharing among the companies participating in the supply chain. Web services, platform independent technologies, are recently used for SCM. However, web services themselves do not provide high level supply chain integration. Therefore, the ways to control and manage global processes over supply chain need to be developed. In this paper, we introduce a method of executing and managing supply chain process using Business Process Management (BPM) system. BPM system is a software system to support an efficient execution and management of complex business processes, and it is applied to supply chain processes . The supply chain processes can be regarded network of activities, each of which is served as web service and related to one of the participants. Our approach enables not only efficient managing but also effective monitoring of the process, which can be a good basis for improvement of the processes. For a speedy execution of processes, we provide a method to support decision making in course of executing process by software agents, which are also web services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.423-425
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• 2019

Users may experience a sub-type of motion sickness, called cybersickness, when interacting with virtual reality (VR) applications in the state of wearing head mounted display (HMD) devices. Although the root cause of cybersickness is still unclear, it is believed to result from a sensory mismatch between visual and vestibular systems. However, there is a lack of studies developing data collection and analysis systems to measure cybersickness. In this paper, therefore, a system is designed that collects electroencephalography (EEG) and physiological data from a user wearing a VR HMD device through an internet of things (IoT) platform and decides whether a user experiences a symptom of cybersickness, namely dizziness, or not by using a decision threshold. Experimental results showed that the proposed system achieved about 92% accuracy of a dizziness detection when considering 14 participants.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.321-332
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• 2020

Decentralized approaches are extensively researched by academia and industry in order to cover up the flaws of existing systems in terms of data privacy. Blockchain and decentralized learning are prominent representatives of a deconcentrated approach. Blockchain is secure by design since the data record is irrevocable, tamper-resistant, consensus-based decision making, and inexpensive of overall transactions. On the other hand, decentralized learning empowers a number of devices collectively in improving a deep learning model without exposing the dataset publicly. To motivate participants to use their resources in building models, a decent and proportional incentive system is a necessity. A centralized incentive mechanism is likely inconvenient to be adopted in decentralized learning since it relies on the middleman that still suffers from bottleneck issues. Therefore, we design an incentive model for decentralized learning applications by leveraging the Ethereum smart contract. The simulation results satisfy the design goals. We also outline the concerns in implementing the presented scheme for sensitive data regarding privacy and data leakage.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.265-273
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• 2023

To effectively and safely manage the radiation exposure to nuclear power plant (NPP) workers in accidents, major overseas NPP operators such as the United States, Germany, and France have developed and applied realistic 3D model radiation dose assessment software for workers. Continuous research and development have recently been conducted, such as performing NPP accident management using 3D-VR based on As Low As Reasonably Achievable (ALARA) planning tool. In line with this global trend, it is also required to secure technology to manage radiation exposure of workers in Korea efficiently. Therefore, in this paper, it is described the application method and assessment results of radiation exposure scenarios for workers in response to accidents assessment technology, which is one of the fundamental technologies for constructing a realistic platform to be utilized for radiation exposure prediction, diagnosis, management, and training simulations following accidents. First, the post-accident sampling after the Loss of Coolant Accident(LOCA) was selected as the accident and response scenario, and the assessment area related to this work was established. Subsequently, the structures within the assessment area were modeled using MCNP, and the radiation source of the equipment was inputted. Based on this, the radiation dose distribution in the assessment area was assessed. Afterward, considering the three principles of external radiation protection (time, distance, and shielding) detailed work scenarios were developed by varying the number of workers, the presence or absence of a shield, and the location of the shield. The radiation exposure doses received by workers were compared and analyzed for each scenario, and based on the results, the optimal accident response scenario was derived. The results of this study plan to be utilized as a fundamental technology to ensure the safety of workers through simulations targeting various reactor types and accident response scenarios in the future. Furthermore, it is expected to secure the possibility of developing a data-based ALARA decision support system for predicting radiation exposure dose at NPP sites.