• 한국공작기계학회논문집
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• 제10권1호
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• pp.1-9
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• 2001

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system A major topic relevant to metal-cutting operations is monitoring toll wear, which affects process efficiency and product quality, and implementing automatic toll replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. The static com-ponents of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force dis-parities are defined in this paper, and the relationships between normalized disparity and flank were are established. Final-ly, artificial neural network is used to learn these relationships and detect tool wear. According to proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

• 한국IT서비스학회지
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• 제15권1호
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• pp.39-66
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• 2016

There is growing evidence that professional work is changing as a result of the application of information technology (IT). However, the impact of information technology on professional work has produced mixed results. Our paper considers the source of these mixed results through a greater analytical attention paid to the nature of professional work. Defined as work involving expertise expressed through abstract and formalized knowledge as well as extensive working knowledge, the professional work logic assumes the greatest autonomy and discretion for workers in collectively controlling work characteristics-division of labor and its permanence, control over education, and control over new entrants and the monitoring and disciplining of existing members. The impact of IT on professional work will be difficult to control and predict without considering the assumptions and tensions within and across the three major types of work logics (Professional, Market and Bureaucratic). Using healthcare as an example, the paper provides various propositions for researching the initiation and effects of ICT design through these three work logics. These propositions illustrate the active role that IS researchers can take in researching an important economic and work-related topic, professional work, and in understanding how ICT affects work-related expertise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• 대한지역사회영양학회지
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• 제9권5호
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• pp.597-605
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• 2004

The purpose of the study was to investigate relationships among food safety training, knowledge, and practices of school food service employees. A questionnaire that identified employees' food safety training experience, knowledge, and practices was developed based on a review of literature. A total of 341 Korean school food service employees participated in the survey; the final usable responses were 293 (a response rate: 86%). Statistical analyses were conducted using SPSS for Windows (version 10). Most of the respondents (> 86%) took training sessions on 'proper hand washing' and 'proper food storage temperatures', whereas less than 60% had training on 'monitoring procedures and corrective actions at critical control points'. The mean score of their food safety knowledge was 8.02 out of 11. The majority of the employees knew correctly 'potentially hazardous foods (93.2%)' and 'diseases and symptoms with which they are excluded from working (87.0%)'; less than 50% chose a correct answer for 'sanitizing food contact surfaces.' A chi-square analysis revealed that the employees' actual knowledge did not differ significantly by whether they had food safety training (at the level of a =0.01), except one topic 'diseases and symptoms with which they are excluded from working.' Their self-reported practice scores were rated as 2.98 - 3.39 based on a 5-point Likert-type scale (1-not at all, 5-always). Employees' food safety training should be conducted continuously and repetitively to improve the effectiveness of the training.

• Earthquakes and Structures
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• 제8권4호
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• pp.935-956
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• 2015

Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

• 대한물리의학회지
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• 제18권3호
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• pp.73-84
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• 2023

PURPOSE: This study analyzed the impact of AI and biosensors on physical therapy, identifying the stage of customized technology development and future prospects. AI and biosensors improve the efficiency, establish customized treatment plans, and expand patient treatment opportunities. The study employed a literature review by searching databases and collecting research. METHODS: This study searched various databases related to the topic, collected existing research, papers, and reports, evaluated the literature, and summarize the results. RESULTS: Exercise therapy utilizing artificial intelligence can provide personalized and optimal exercise plans while monitoring rehabilitation progress. In addition, biosensors such as EMG sensors and accelerometers can monitor the individual progress in physical therapy, particularly in stroke patients, which can help improve physical therapy strategy and promote patient recovery. CONCLUSION: This study suggested that artificial intelligence can be applied in many areas of physical therapy, such as exercise therapy, customized treatment plans, rehabilitation and management, pain management, neuro rehabilitation, and auxiliary devices. Using AI technology, it is possible to analyze and improve exercise and posture, retrain the central nervous system, establish customized treatment plans for individual patients, predict and compare patient progress before and after treatment, and provide customized pain analysis and treatment methods. In addition, AI can provide neuro rehabilitation programs and customized auxiliary devices.

• 산업경영시스템학회지
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• 제46권2호
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• pp.22-31
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• 2023

Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.

• 산업경영시스템학회지
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• 제46권spc호
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• pp.1-8
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• 2023

To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: 'equipment,' 'smart,' and 'eco-friendly.' Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.

• 산경연구논집
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• 제15권4호
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• pp.1-9
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• 2024

Purpose: The purpose of this paper is to explore literature on performance management in order to get insight into how the concept could be optimised during VUCA times for better performance of organisations. Research design, data and methodology: The study adopted a desktop research methodology. Extensive literature review has been conducted from various sources such as journals, research papers, organizational reports, government reports, media reports and articles available on web and effort has been made to assimilate the knowledge body on the topic in the current paper. Literature that enhances understanding on managing performance during VUCA times was reviewed. Results: Solutions to optimise performance management in organisations during VUCA times were proffered and these include innovative planning, innovative monitoring, innovative training and development, innovative rating and innovative rewarding. Conclusions: The study proves that, performance management process should not be done the ordinary way during VUCA times, but innovatively. In this regard innovative performance management can optimise performance of organisations during VUCA period. The study recommends that a further quantitative study be done to test the suitability of each of the proposed ways of innovatively practicing each element of the performance management process across different industries, countries or sector.

• International Journal of Contents
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• 제12권2호
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• pp.12-23
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• 2016

This paper presents a novel concept of Disaster Prevention Design (DPD) and its derived subjects and topics for the safety of folk villages in both Korea and Japan. Nowadays, design concepts are focused on 'human-oriented nature' as a whole and this tendency fits to be appropriate for disaster prevention against real dangers of a future society, which is expected to have far more complicated features. On the other hand, convergences have performed with other areas in the field of Information Communication Technology (ICT) so that we can easily find examples like 'the strategy of ICT-based convergence' of the Korean Government in 2014. Modern content designs including UI (user interface) and USN (ubiquitous sensor network) have been developed as one of the representative areas of ICT & UD (universal design) convergences. These days this novel concept of convergence is overcoming the existing limitations of the conventional design concept focused on product and/or service. First of all, from that point our deduced topic or subject would naturally be a monitoring system design of constructional structures in folk villages for safety. We offer an integrated model of maintenance and a management-monitoring scheme. Another important point of view in the research is a safety sign or sign system installed in folk villages or traditional towns and their standardization. We would draw up and submit a plan that aims to upgrade signs and sign systems applied to folk villages in Korea and Japan. According to our investigations, floods in Korea and earthquakes in Japan are the most harmful disasters of folk villages. Therefore, focusing on floods in the area of traditional towns in Korea would be natural. We present a water-level expectation model using deep learning simulation. We also apply this method to the area of 'Andong Hahoe' village which has been registered with the World Cultural Heritage of UNESCO. Folk village sites include 'Asan Oeam', 'Andong Hahoe' and 'Chonju Hanok' villages in Korea and 'Beppu Onsen' village in Japan. Traditional Streets and Markets and Safe Schools and Parks are also chosen as nearby test-beds for DPD based on ICT. Our final goal of the research is to propose and realize an integrated disaster prevention and/or safety system based on big data for both Korea and Japan.