• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.515-522
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• 2021

In this paper, we present and analyze a method of applying a machine learning to ultrasonic test signals for constant monitoring of the welding faults in a tubular steel tower. For the machine learning, feature selection based on genetic algorithm and fault signal classification using a support vector machine have been used. In the feature selection, the peak value, histogram lower bound, and normal negative log-likelihood from 30 features are selected. Those features clearly indicate the difference of signals according to the depth of faults. In addition, as a result of applying the selected features to the support vector machine, it has been possible to perfectly distinguish between the regions with and without faults. Hence, it is expected that the results of this study will be useful in the development of an early detection system for fault growth based on ultrasonic signals and in the energy transmission related industries in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.58-63
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• 2022

The daily number of confirmed cases of Coronavirus disease 2019(COVID-19) ranges between 1,000 and 2,000. Despite higher vaccination rates, the number of confirmed cases continues to increase. The Mu variant of COVID-19 reported in some countries by WHO has been identified in Korea. In this study, we predicted the number of confirmed COVID-19 cases in Korea using the SARIMA for the Covid-19 prevention strategy. Trends and seasonality were observed in the data, and the ADF Test and KPSS Test was used accordingly. Order determination of the SARIMA(p,d,q)(P, D, Q, S) model helped in extracting the values of p, d, q, P, D, and Q parameters. After deducing the p and q parameters using ACF and PACF, the data were transformed and schematized into stationary forms through difference, log transformation, and seasonality removal. If seasonality appears, first determine S, then SARIMA P, D, Q, and finally determine ARIMA p, d, q using ACF and PACF for the order excluding seasonality.

• 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.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.463-472
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• 2022

In this study, a microbial risk assessment was performed for the bacteria Vibrio parahaemolyticus, which causes a foodborne illness following the consumption of Jeotgal, a fermented seafood in South Korea. The assessment comprised of six stages: product, market, home, consumption, dose-response, and risk. The initial contamination level (IC) was calculated based on the prevalence of V. parahaemolyticus in 90 Jeotgal samples. The kinetic behavior of V. parahaemolyticus was described using predictive models. The data on transportation conditions from manufacturer to market and home were collected through personal communication and from previous studies. Data for the Jeotgal consumption status were obtained, and an appropriate probability distribution was established. The simulation models responding to the scenario were analyzed using the @RISK program. The IC of V. parahaemolyticus was estimated using beta distribution [Beta (1, 91)]. The cell counts during transportation were estimated using Weibull and polynomial models [δ = 1 / (0.0718 - 0.0097 × T + 0.0005 × T²)], while the probability distributions for time and temperature were estimated using Pert, Weibull, Uniform, and LogLogistic distributions. Daily average consumption amounts were assessed using the Pareto distribution [0.60284,1.32,Risk Truncate(0,155)]. The results indicated that the risk of V. parahaemolyticus infection through Jeotgal consumption is low in South Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.641-648
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• 2022

This paper is a study to find out the factors affecting the defects that occur during the use of Electron Beam Melting (EBM), one of the 3D printer output methods, through data analysis. By referring to factors identified as major causes of defects in previous studies, log files occurring between processes were analyzed and related variables were extracted. In addition, focusing on the fact that the data is time series data, the concept of a window was introduced to compose variables including data from all three layers. The dependent variable is a binary classification problem with the presence or absence of defects, and due to the problem that the proportion of defect layers is low (about 4%), balanced training data were created through the SMOTE technique. For the analysis, I use XGBoost using Gridsearch CV, and evaluate the classification performance based on the confusion matrix. I conclude results of the stuy by analyzing the importance of variables through SHAP values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1741-1746
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• 2022

As the use of school buses becomes more common, related laws are being enacted, such as making it mandatory for children to check school bus dropouts due to frequent accidents caused by the negligence of school bus drivers and their guardians. In this paper, we propose a safe school bus system that links efficient radio-frequency identification (RFID) and mobile APP in terms of energy utilization and cost. The school bus system uses RFID cards to check information on children boarding the school bus, and real-time SMS transmission allows parents to safely send their children to and from school. Instructors on the school bus can check their children's disembarkation information once more through APP, preventing various accidents that may occur to children left on the bus. Due to the automation of the school bus operation log, daycare center teachers can not only check the information on getting on and off, but also manage the information on the attendance and discharge of the students.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.95-103
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• 2024

With the rapid decline of the school-age population, the competition for admissions has increased and marketing through digital channels has become more important, so universities are investing more resources in online promotion and communication to recruit new students. This study uses Google Analytics, a web log analysis tool, to track the visitor behavior of a university admissions website and establish a digital marketing strategy based on it. The analysis period was set from July 1, 2023, when Google Analytics 4(GA4) was integrated, to January 10, 2024, when the college admissions process was completed. The analysis revealed interesting patterns such as geographical information based on visitors' access location, devices(operating systems) and browsers used by visitors, acquisition channels through visitors traffic, conversions on pages and screens that visitors engaged with and visitor flow. Based on this study, we expect universities to find ways to strengthen their admission promotion through digital marketing and effectively communicate with applicants to gain a competitive edge.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.651-660
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• 2018

The purpose of this study was to investigate the effects of task-oriented circuit training(: TOCT) on upper extremity function and quality of life in chronic stroke patients. 20 stroke patients were randomized and divided into 2 groups: a preservation therapy group and TOCT group. The intervention sessions were given five times a week for four weeks. The Stroke Impact Scale(: SIS), EuroQual-5Domains(: EQ-5D), Fugl-Myer Assessment(: FMA), Motor Activity Log(: MAL), Canadian Occupational Performance Measure(: COPM) were used to measure the upper extremity function and the quality of life. In results, Two groups improved in upper extremity function after the intervention(p<.05). The EQ-5D scores of TOCT group were a significantly higher than preservation group(p<.05). The Ironing, Folding towels, Hang out towels on drying rack in COPM scores in both of performance and satisfaction have improved more than preservation group(p<.05). In conclusion, the TOCT has significant helpful effect to chronic stroke patients. These findings can be used to chronic stroke patient as an intervention for upper extremity function and quality of life.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.331-339
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• 2002

This paper presents a garbage collection protocol for checkpoints and message logs which are staved on the stable storage or volatile storage for fault tolerancy. The previous works of garbage collections in coordinated checkpointing protocol delete all the checkpoints except for the last checkpoints on earth processes. But implemented in top of reliable communication protocol like as TCP/IP, rollback recovery protocol based on only last checkpoints makes sympathetic rollback. We show that the old checkpoints or message logs except for the last checkpoints have to be preserved in order to replay the lost message. And we define the conditions for garbage collection of checkpoints and message logs for lost messages and present the garbage collection algorithm for checkpoints and message logs in coordinated checkpointing protocol. Since the proposed algorithm uses process information for lost message piggybacked with messages, the additional messages for garbage collection is not required The proposed garbage collection algorithm makes 'the lazy garbage collectioneffect', because relying on the piggybacked checked checkpoint information in send/receive message. But 'the lazy garbage collection effect'does not break the consistency of the whole systems.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.109-120
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• 2018

The smartphone is the communication device that is the most personal to the user, and it keeps a lot of information related to the user and makes information communication with other devices. With these characteristics, forensics on smartphones are one of the most basic methods of investigation in criminal investigations, and have actually contributed to the settlement of the case by providing many clues. However, recently, it is designed to encrypt data stored as a social issue related to the protection of user's personal information, or to delete deleted data or to delete log data together. So, any solutions? In this paper, I try to find the answer from cloud data stored by smartphone user account. Cloud forensics should approach complementary relationships rather than smartphone forensics. There are a lot of data stored in the cloud that can be meaningfully used in the investigation. Online activity information of users, such as Internet usage, YouTube view, and contents purchase information, cloud service such as e-mail, cloud drive, and location information are the most representative data. These data can be unvaluable, but here are some important clues in various types of criminal investigations. In this paper, I propose a method to extract data from the google cloud so that the data can be used for investigation, and to utilize the extracted data for investigation. And it explains the role of the extracted artifacts in the actual investigation business through virtual cases and proves its value.