• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.328-342
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• 2020

As the cloud-based ICT(Information & Communication Technology) infrastructure matures, the existing monolithic software development method is evolving into a micro-service structure based on cloud native computing. To develop and operate the services efficiently under the cloud native environment, DevOps-based application development plans through MSA(Micro Service Architecture) design based are essential. A cloud native environment is an approach to developing and running applications that take advantage of cloud computing models such as automation of source distribution, container-based virtualization, application scalability, resource efficiency, and flexible maintenance through object independence. To implement this approach, the utilization of key elements such as DevOps, continuous delivery, micro service, and containers is essential, but there are not enough previous studies on case analyses or application methods of these key elements. Therefore, in this paper, we analyze the cases of application development in cloud native environment and propose the optimized application development process and development method through small and medium-sized SI projects.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Management & Information Systems Review
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• v.27
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• pp.31-52
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• 2008

Intangible Assets are more important determinants of firm value than others in a digital information-based economy(Lev, 2001). Prior research reveals that investments in intangible assets such as R&D and advertising expenditures are associated with firm value. This paper examines the effects of the corporate investments in the information technologies(IT) on stock return and economic goodwill. The sample consists of 152 firms listed on the Korean stock market in 2002. To test hypothesis We employed multiple regression models. Results are as follows; First, IT environment, IT process, and IT human resource are positively associated with firm's IT value. Second, firm's IT value is positively correlated with firm's economic goodwill. Third, firm's IT value is positively correlated with firm's stock return. These results suggest that the investments related with IT are effective in cultivating firm's value and Stock investors can make the best use of firm's announcements related with IT value. Thus the authorities concerned need to expand the public announcements related IT value.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.188-189
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• 2021

The technology of manufacturing freeform molds with S-LOM based 3D printer has advantages in the production period and the curvature range. However, there is no any support tool about productivity analysis of S-LOM technology because S-LOM technology is early-stage technology. There can be problems about increase of construction time and cost without any decision support tool like productivity analysis models etc. Therefore, in this study, the productivity analysis simulation model for freeform formwork based on S-LOM technology was developed using ARENA software. The process and logic of manufacturing freeform molds can be easily visualized in this model. Futhermore, the resource like labor, equipment and material can be easily optimized with this model. As a result, it can contribute to preventing the increase of construction time and cost in formwork with further productivity analysis.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.125-137
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• 2018

Simulations have been used to evaluate the efficiency of logistics or manufacturing systems and predict the outcomes of the systems. New simulation models are needed to evaluate new alternative plants and layouts during the resource design process. Although it is easy to handle minor changes in parameters by modifying a simulation model, it takes considerable time and effort for simulation modelers to alter the layout, which involves changes in many simulation sub-models. Therefore, this study proposes a method to transfer information in AutoCAD layout to the simulation model automatically. This study also defines a standard document as an Excel Form, and suggests a method to transfer information on the basic layouts, processes, resources, and workers to a simulation model automatically. A simulation tool, called Tecnomatix Plant Simulation 9.0, was used for this study. The proposed approach in this study was applied to a semiconductor wafer factory for a case study.

• IE interfaces
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• v.25 no.3
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• pp.347-356
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• 2012

The acquisition cost of defense weapon system has been continuously increasing because of art-of-technology of it. This phenomenon requires efficiency and transparency in the weapon system acquisition process through cost estimation. Therefore cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as a key decision point. The Commercial parametric cost estimating models have been using extensively to obtain appropriate cost estimates in early acquisition phase. These models have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed based on foreign R&D data. Also estimation results are different from Korean defense industry accounting system. So, some studies have been tried to develop a CER (Cost Estimation Relationship) based on the Korean historical data. However, there are some restrictions to improve the predictability and ensure the stability of the developed singular CERs which consider the following data characteristics individually. The the abnormal conditions of data that is multicollinearity, outlier and heteroscedasticity under rack of the number of observations. In this paper, a CER's Linear Combining Model is proposed to overcome those limitations which guarantee more accurate estimation (25.42% higher precision) than other singular CERs. At least, this study is meaningful as a first attempt to improve the predictability of CER with insufficient data. The methodology suggested in this study will be useful to develop a complex Korean version cost estimating model development in future.

• Food Science and Preservation
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• v.22 no.1
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• pp.1-11
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• 2015

Raspberries are a good resource of polyphenols and have a powerful antioxidant activity, but shelf life for raspberries is short which brings a lot of economic losses. In this study, we try to use cool-air ($20{\sim}40^{\circ}C$) or hot-air ($60{\sim}100^{\circ}C$) to produce semi-dried raspberries with extended shelf life, and to determine the best method for improving fruit quality by minimizing nutrient losses during drying processes. The effects of process variables (drying temperature and processing time) on the quality of final dried raspberries were investigated. Response surface methodology was employed to establish statistical models for simulating the drying processes, and the moisture residue content and the loss ratios of total phenolic content (TPC), vitamin C (VC), and ellagic acid (EA) that result from the drying processes of raspberries using either hot or cool-air were predicted. Superimposed contour plots have been successfully used in the determination of the optimum zone within the experimental region. Optimal conditions determined for achieving minimal losses of TPC, VC, and EA, and a final moisture residue of 45% using the hot-air drying process were a drying temperature of $65.75^{\circ}C$ and a processing time of 4.3 hr. While for the cool-air process, the optimal conditions predicted were $21.3^{\circ}C$ and 28.2 hr. Successful application of response surface methodology provided scientific reference for optimal conditions of semi-drying raspberries, minimizing nutrient losses and improving product quality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.21-29
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• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.147-156
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• 2011

Though a dozen of different software life cycle models are suggested, there is no universal model which can satisfy all the characteristics of software. Organizations mix and match different life cycle models to develop a model more tailored for their systems and capabilities. We suggest overlapped-concurrent development life cycle model that is more suitable in various software development environment. Firstly, we divided the development process into abstract and implementation stage. Abstract stage is from software concept phase to detailed design starting time, and implementation stage is from detailed design phase to system testing phase. Next, the abstract stage introduced the overlapped phase concept that begins the next phase when the step is completed 20% by applying pareto's law. In the implementation stage, we introduced the concurrent development which the several phases are performed some time as when one use-case (UC) is completed the next development phase is started immediately. The proposed model has an advantage that it can reduce the inefficiency of development resource greatly. This model can increase the customer satisfaction with a great product at a low cost and on a short schedule. Also, this model can contribute to increase the software development success rate.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.127-138
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• 2021

The aim of this study is to demonstrate interaction as a describable field and tries to understand interaction from the perspective of attributes, thus building a theoretical to help interactive designer understand this field by common rule, rather than waste huge time and labor cost on iteration. Since the concept of interaction language has been brought out in 2000, there are varies of related academical studies, but all with defect such as proposed theoretical models are built on a non-uniform scale, or the analyzing perspective are mainly based on researcher's personal experience and being too unobjective. The value of this study is the clustered resource of research which mainly based on academical review. It collected 21 papers researched on interaction paradigm or interaction attributes published since 2000, extracting 19 interaction attribute models which contains 174 interaction attributes. Furthermore, these 174 attributes were re-clustered based on a more unified standard scale, and the two theoretical models summarized from it are respectively focuses on interaction control and interaction experience, both of which covered 6 independent attributes. The propose of this theoretical models and the analyzation of the cluster static will contribute on further revealing of the importance of interaction attribute, or the attention interaction attribute has been paid on. Also, in this regard, the interactive designer could reasonably allocate their energy during design process, and the future potential on various direction of interaction design could be discussed.