• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.425-437
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• 2018

Since the 1990s, clusters defined as a geographic concentration of interconnected companies, research and educational institutions, technology transfer agencies, and other public or semi-public institutions in a particular field have not only been subject to academic research, but have also become goals for various innovation and regional policies. Over the past 20 years Germany at both the Federal and $L{\ddot{a}}nder$ levels has been pursuing various cluster promotion policies and initiatives for upgrading industries' competitiveness and innovations, and some of these measures have been evaluated as successful. This study aims to examine the industrial cluster promotion policy of Germany. For this purpose, the study first outlines the concept of cluster and cluster policy theoretically, and then explores the formation and historical development of cluster polices of the German federal government.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.75-83
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• 2021

This research is to analyze how an introduction of full-time quality control("QC") personnel system in audit firms influences on audit quality and verify how important it is to establish the quality control system for auditing quality. We measure audit quality as the level of discretionary accruals and compare the differences between audit firms with QC and without QC. In addition, we analyze the difference in audit qualities between before and after activating the full-time QC personnel system by comparing audit quality of before 2015 with that of after 2016. The results of this study are summarized as follows. First, the audit quality is higher when audit firms have QC personnel. Second, the audit quality is improved after the introduction of the full-time QC personnel system.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.47-56
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• 2021

The purpose of this research was to develop an augmented reality-based surgical nursing practice education application. The research proceeded in ADDIE order of analysis, design, development, implementation, and evaluation stages. In the analysis phase, we analyzed the surgical nursing learning needs of the expert group and nursing student group. As a result of the analysis, the demand for surgical instruments was generally high. We selected 51 surgical instruments of the 7 categories most frequently used in the operating room based on the needs, and produced them as AR Book. The augmented reality application was created based on the Unity 3D engine, and the application was built with Android OS so that the target person could use it. Expert assessment of application for augmented reality-based surgical nursing practice education application showed 73.4±4.3 out of 80. This study is significant in the part that first developed a new method of learning tools for surgical instruments. We determined that an augmented reality-based application has reality, portability, accessibility and simplicity.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.7-13
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• 2021

This study develops an artificial intelligence prediction system for Fine particulate Matter(PM2.5) based on the deep learning algorithm GAN model. The experimental data are closely related to the changes in temperature, humidity, wind speed, and atmospheric pressure generated by the time series axis and the concentration of air pollutants such as SO2, CO, O3, NO2, and PM10. Due to the characteristics of the data, since the concentration at the current time is affected by the concentration at the previous time, a predictive model for recursive supervised learning was applied. For comparative analysis of the accuracy of the existing models, CNN and LSTM, the difference between observation value and prediction value was analyzed and visualized. As a result of performance analysis, it was confirmed that the proposed GAN improved to 15.8%, 10.9%, and 5.5% in the evaluation items RMSE, MAPE, and IOA compared to LSTM, respectively.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.73-84
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• 2020

As the Internet began to become popular, there have been hacking and attacks on networks including systems, and as the techniques evolved day by day, it put risks and burdens on companies and society. In order to alleviate that risk and burden, it is necessary to detect hacking and attacks early and respond appropriately. Prior to that, it is necessary to increase the reliability in detecting network intrusion. This study was conducted on applying weight initialization and weight optimization to the KDD'99 dataset to improve the accuracy of detecting network intrusion. As for the weight initialization, it was found through experiments that the initialization method related to the weight learning structure, like Xavier and He method, affects the accuracy. In addition, the weight optimization was confirmed through the experiment of the network intrusion detection dataset that the Adam algorithm, which combines the advantages of the Momentum reflecting the previous change and RMSProp, which allows the current weight to be reflected in the learning rate, stands out in terms of accuracy.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.126-132
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• 2022

At present, due to the rapid spread of smartphones and activation of IoT, malicious codes are disseminated using SNS, or intelligent intrusions such as intelligent APT and ransomware are in progress. The damage caused by the intelligent intrusion is also becoming more consequential, threatening, and emergent than the previous intrusion. Therefore, in this paper, we propose an intelligent intrusion situation-aware reasoning system to detect transgression behavior made by such intelligent malicious code. The proposed system was used to detect and respond to various intelligent intrusions at an early stage. The anticipated system is composed of an event monitor, event manager, situation manager, response manager, and database, and through close interaction between each component, it identifies the previously recognized intrusive behavior and learns about the new invasive activities. It was detected through the function to improve the performance of the inference device. In addition, it was found that the proposed system detects and responds to intelligent intrusions through the state of detecting ransomware, which is an intelligent intrusion type.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.213-226
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• 2022

The importance of gamification is garnering increased attention in the corporate world. Gamification refers to using game mechanics and thinking patterns in non-game domains to promote user engagement. By reviewing the definition of gamification and related literary research, we aim to understand how to put theory into practice and determine the organization of gamification's main features. Next, in order to understand the current implementation methods of mobile payment gamification marketing. We analyze popular mobile payment apps as case studies. To examine the effectiveness of game mechanics on mobile payment marketing to determine whether there is a positive impact on brand loyalty and stickiness. The results are used to identify shortcomings in gamified mobile payment systems. Finally, we propose a gamification framework model for mobile payments and offer recommendations for underutilized game mechanics based on previous cases. Future research can reference our model for deeper studies on the effectiveness and impact of gamified mobile payments.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.155-161
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• 2022

The outbreak of the Covid 19 increased the interest on the 'Virtual Tourism. In this research the key word related to "Virtual Tourism" was collected through the search engine and was analyzed through the data mining method such as Log-odds ratio, Frequency, and network analysis. It is clear that the information and communication dependency increased in the field of "Virtual Tourism" after Covid 19 and also the trend have changed from "securement of the contents diversity" to "project related to economic recovery." Since the demands for the "Virtual Reality" such as metaverse is increasing, there should be an economic and circular structure in which the government establishing a related policy and the funding plan based on the research, local government and the private companies planning and producing discriminate contents focusing on AISAS(Attension, Interest, Search, Action, Share) aand the research institutions and universities developing, applying, assessing and commercializing the technology.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.159-165
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• 2023

This study aims to analyze the changes in the management efficiency of public institutions in time series, and to examine the relationship with financial performance based on the results of time series changes. Specifically, we classified into upper and lower groups of financial performance based on the government's management evaluation results, and analyze how the management efficiency of each group changed in the period before the evaluation year. Based on public institutions published in public business information system, DEA(Data Envelopment Analysis) was performed for estimating management efficiency. The results are summarized as follows; First, we find that DEA of the upper group changed in the direction of increasing, but DEA of the lower group changed in the direction of decreasing. Second, we find that there is a significant positive relation between DEA and financial performance. This result means that the higher financial performance, the higher management efficiency. These findings imply that management efficiency can be a factor that improve financial performance in public institutions. The results also suggest that government's innovation strategies to improve financial stability by enhancing management efficiency were effective.