• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.3
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• pp.27-41
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• 2022

Purpose: In this study, pollutants generated in industrial areas were measured using a Portable Air Quality Measurement System(PAQMS). This study intends to examine in detail improvement measures and operational capabilities to operate a more efficient PAQMS. Research design, data and methodology: This study compares and analyzes the measurement values of the PAQMS and the measurement values of the national air quality measurement network. It is intended to develop a PAQMS corresponding to the data of the national measurement network by minimizing the errors that occur during comparative measurement and analysis and supplementing and improving the problems that occur during the current equipment calibration. Results: A PAQMS is an essential equipment for faster and more accurate measurement and analysis of pollutants in case of untimely measurement and civil complaints due to Micro Climate(local weather and environmental influences). Currently, there are many atmospheric measurement equipment in Korea, but only equipment for each item is produced and sold. Currently, these devices on the market must satisfy various conditions such as stable power, temperature, and humidity to calculate accurate measurement values. Conclusions: Therefore, there is no equipment that satisfies the conditions for performing detailed measurement in the field where accurate measurement is required. In this study, these field work conditions and contents for stable measurement were mentioned in the text.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.321-322
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• 2022

In this study, the marine environment is measured and analyzed in real time through the X-band radar installed on the rooftop of the Sokcho Beach administrative Welfare Center and Ulleungdo. Afterwards, the goal is to transmit the analysis results to the client PC. Using electronic maps and electronic navigational charts, the measurement results are overlaid on GIS (spatial information system), real-time data are shared through a website, and information is displayed through a web server. Currently, CCTV information and marine environment information are displayed on the website, but various application studies such as the use of Open AP I will be conducted in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.215-222
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• 2023

Augmented reality (AR), which integrates virtual media into reality, is increasingly utilized across various industrial sectors, thanks to advancements in 3D graphics and mobile device technologies. The IT industry is thus carrying out active R&D activities about AR platforms. Google plays a significant role in the AR landscape, with a focus on ARCore services. An essential aspect of ARCore is the use of anchors, which serve as reference points that help maintain the position and orientation of virtual objects within the physical environment. However, if the accuracy of anchor positioning is suboptimal when running AR content, it can significantly diminish the user's immersive experience. We are to assess the performance of these anchors in this study. To conduct the performance evaluation, virtual 3D objects, matching the shape and size of real-world objects, we strategically positioned ourselves to overlap with their physical counterparts. Images of both real and virtual objects were captured from five distinct camera trajectories, and ARCore's performance was analyzed by examining the difference between these captured images.

• Journal of Microbiology and Biotechnology
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• v.34 no.2
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• pp.349-357
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• 2024

Foodborne pathogens, like Listeria monocytogenes, continue to inflict substantial financial losses on the food industry. Various methods for detecting Listeria in food have been developed and numerous studies have been conducted to compare the different methods. But, in recent years, new Listeria species have been identified, and currently the genus comprises 26 species. Therefore, it would be a more accurate approach to re-evaluate existing detection methods by considering new species. The present investigation involved the analysis of 42 ready-to-eat (RTE) foods, encompassing a variety of food categories, such as mezes, salads, dairy products, and meat products, with the aim of ascertaining the presence of Listeria. Among the traditional culture-dependent reference methods, the ISO 11290 method was preferred. The process of strain identification was conducted with the API Identification System. Furthermore, to ascertain the existence of L. monocytogenes and Listeria spp., the samples underwent additional analysis employing the VIDAS Immunoassay System, ELISA, and RT-PCR methodologies. Thus, four alternative approaches were employed in this study to compare not only the different methods used to determine Listeria while taking into account the newly identified Listeria species, but also to assess the compliance of retail RTE food items with microbiological criteria pertaining to the genus Listeria. Based on the conducted analyses, L. monocytogenes was conclusively determined to be present in one sample. The presence of Listeria spp. was detected in 30.9% of the samples, specifically in Turkish cig kofte, sliced salami, and salads.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.55-62
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• 2005

In this paper, a CAB/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares, for a complicated model for which parametric modeling provided by CAD software is not possible. CAD modeling process is automated by using UG/OPEN API function and UG/Knowledge Fusion provided by Unigraphics. The generated model is transferred to the analysis code ANSYS in parasolid format. Visual DOC software is used for optimization. The system is developed for PLS(Plasma Lighting System), which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The PLS system consists of more then 20 components, which requires a lot of human efforts in modeling and analysis. The analysis for PLS includes static load, wind load and impact load analysis. As a result of analysis, it is found that the most critical component is a tilt assembly, which links lower & upper body assembly. For more reliable analysis, experiment is conducted using MTS and compared with the Finite element analysis result. The objective in the optimization is to minimize the material volume under allowable stresses. The design variables are three parameters in the tilt assembly that are chosen to be the most sensitive in stress values of twelve parameters. Gradient based method and RSM(Response Surface Method) are used for the algorithm and the results are compared. As a result of optimization, the maximum stress is reduced by 57%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.155-161
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• 2016

In current algorithm trading system, general users need to program their algorithms using programing language and APIs provided from financial companies. Therefore, such environment keeps general personal investors away from using algorithm trading. Therefore, this paper focuses on developing user-friendly algorithm trading system which enables general investors to make their own trading algorithms without knowledge on program language and APIs. In the system, investors input their investment criteria through user interface and this automatically creates their own trading algorithms. The proposed system is composed with two parts: server intercommunicating with financial company server to send and to receive financial informations for trading, and client including user convenience-based user interface representing secondary indexes and strategies, and a part generating algorithm. The proposed system performance is proven through simulated-investment in which user sets up his investment strategy, algorithm is generated, and trading is performed based on the algorithm

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.11-20
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• 2015

In this paper, we propose a context awareness system to transfer accurate information of the app store based on collective intelligence. By using collective intelligence the system minimizes the errors that could occur when an individual process the problems, recommends APIs for developers and builds the app store for not only customers but also developers. In addition, this system applies the ontology technique to aware the context of consumers, recommends the app suitable for the consumer and provides the information for app developers. By utilizing the deduction technique of the Jena, the context awareness system infers the context of a consumer and constructs the app store system which improves the existing app stores. In the point of service transfer and accuracy, the proposed app store system module show better performance than the existing app store.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.115-124
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• 2015

In this paper we analyse the previous (Quality of Services) and QoE(Quality of Experience) methods, and propose a high reliable network system framework and its service forwarding method that is able to provide seamless N-Screen services for proliferating disaster informations. The service satisfaction measurement, i.e., QoE, of contents consumers in N-screens services is going to be important the factor in disaster information proliferation because N-Screen services in the previous methods based on multi devices only focused on information transmission. The proposed system around these services is composed of a disaster information process framework for accepting user's service requirement, push service modules for minimizing the number of packets to be caused when carrying out the push service, and a push service controller for maximizing QoE measures. In order to provide a seamless N-Screen service on diverse screens, such as smartphone, PC, and big screen, we also have Open API(Application Programming Interface) functions. Through these results, we expect to evaluate QoS and QoE quality in the seamless N-Screen service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.