• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.703-712
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• 1999

In order to determine the number concentration of asbestos, it is initially necessary to develop a method to identify the type of asbestos. Thus a SEM/EDX was used to obtain both physical and chemical information from known asbestos samples as reference samples. Based on these information, we could make a source profile matrix consisted of a glass fiber and 3 other types of asbestos such as chrysotile, crocidolite, and tremolite. After collinearity test was performed for these sources, we could successfully develop an expert system by C-language to separate and to identify various unknown types of fiber particles. The expert system was perfectly self-verified with original reference data. Then the program was extensively applied to survey indoor and outdoor environment such as a residential area, an elementary school, and underground store, and an auto junkyard. As a result for surveying, a total of 442 individual fibrous particles were well classified into 4 types of particle classes above mentioned; 5.4% of chrysotile, 4.1% of crocidolite, 3.6% of glass fiber, and 86.9% of unknown fibers in terms of number concentration. However, tremolite was not detected in the study sites. All the samples were satisfied with the recommendation level of 0.01 f/cc.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2434-2441
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• 2015

This paper proposes an exercise recommendation system for treating obesity that provides systematic recommendations for exercise and diet. Five body indices are considered as indicators for recommend exercise and diet. The system also informs users of prohibited foods using health data including blood pressure, blood sugar, and total cholesterol. To maximize the utility of the system, it displays recommendations for both indoor and outdoor activities. The system is equipped with multimode sensors, including a three-axis accelerometer, a laser, a pressure sensor, and a wrist-mounted sensor. To demonstrate the effectiveness of the system, field tests are carried out with three participants over 20 days, which show that the proposed system is effective in treating obesity.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.9-15
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• 2017

According to a recent survey, most elementary and secondary school students nationwide are stressed out by their academic records. Furthermore most of high school students in Korea have to study under the great duress. Some of them who can't overcome the academic stress finalize their life by suiciding. A study has found that it is one of the leading causes of stimulating the thought of committing suicide in Korean high school students. So it is necessary to reduce the high school student's suicide rate. Main content of this research is to implement a personalized music recommendation system. Music therapy can help the student deal with the stress, anxiety and depression problems. Proposed system works as a therapist. The music choice and duration of the music is adjusted based on the student's current emotion recognized automatically from EEG. If the happy emotion is not induced by the current music, the system would automatically switch to another one until he or she feel happy. Proposed system is personalized brain music treatment that is making a brain training application running on smart phone or pad. That overcomes the critical problems of time and space constraints of existing brain training program. By using this brain training program, student can manage the stress easily without the help of expert.

• Korean Journal of Adult Nursing
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• v.17 no.4
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• pp.622-634
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• 2005

Purpose: The purpose of this study was to evaluate the applicability of the evidence based guideline for prompted voiding by Lyons & Specht (2001) in National Guideline $Clearinghouse^{TM}$ for use in Korea based on the experts' opinions. Method: The target expert group consisted of 8 registered nurses, 6 physicians, and 5 nursing professors who are experts in urinary incontinence. This study used a questionnaire survey. The appropriateness, applicability, and the present application of each recommendation in the guideline were analyzed with descriptive statistics using the SPSS program, with content analysis based on the experts' opinions. Result: The scores on each recommendation's appropriateness showed the high degree of agreement among nurses, physicians, and nursing professors. However, the recommendation for 'use of oxybutinin' showed the lowest score as 5.89. It was notable that the most recommendations scored lower for applicability compared with appropriateness. The reasons for lower scores for applicability were the lack of clinicians' knowledge of assessment and management, and the lack of resources in clinical settings in Korea. Conclusion: This study will augment the understanding of the actual urinary incontinence management in Korean clinical settings and can be used as the baseline data for further study of tailoring international guidelines into local and national clinical settings.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.17-22
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• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.1
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• pp.31-40
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• 2020

In this study, we developed an algorithm for automatic travel itinerary planning based on expert recommendation. The proposed algorithm generates an itinerary by patterning a number of travel routes based on the automatic itinerary generation method based on the routes recommended by travel experts. To evaluate the proposed algorithm, we generated 30 itinerary for Singapore, Bankok, and Da Nang using both algorithms and analyzed the mean difference of trip distances with t-test and interater reliability of those itineraries. The result shows that the itineraries based on the proposed algorithm is not different from that of VRP(Vehicle routing problem) algorithm and interater reliability is high enough to show that the proposed algorithm is effective enough for real-world usage.

• Journal of Information Management
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• v.41 no.4
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• pp.227-249
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• 2010

Scholarly information has increased tremendously according to the development of IT, especially the Internet. However, simultaneously, people have to spend more time and exert more effort because of information overload. There have been many research efforts in the field of expert systems, data mining, and information retrieval, concerning a system that recommends user-expected information items through presumption. Recently, the hybrid system combining a content-based recommendation system and collaborative filtering or combining recommendation systems in other domains has been developed. In this paper we resolved the problem of the current recommendation system and suggested a new system combining collaborative filtering and Naive Bayes Classification. In this way, we resolved the over-specialization problem through collaborative filtering and lack of assessment information or recommendation of new contents through Naive Bayes Classification. For verification, we applied the new model in NDSL's paper service of KISTI, especially papers from journals about Sitology and Electronics, and witnessed high satisfaction from 4 experimental participants.

• Korean Journal of Radiology
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• v.24 no.1
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• pp.22-30
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• 2023

Ultrasonography (US) is a primary imaging modality for diagnosing nodular thyroid disease and has an essential role in identifying the most appropriate management strategy for patients with nodular thyroid disease. Standardized imaging techniques and reporting formats for thyroid US are necessary. For this purpose, the Korean Society of Thyroid Radiology (KSThR) organized a task force in June 2021 and developed recommendations for standardized imaging technique and reporting format, based on the 2021 KSThR consensus statement and recommendations for US-based diagnosis and management of thyroid nodules. The goal was to achieve an expert consensus applicable to clinical practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.2
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• pp.115-119
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• 2001

The design and manufacture of injection molded polymeric parts with desired properties is a costly process dominated by empiricism, including the repeated modification of actual tooling. This paper presents an knowledge-based synthesis system which can predict the mechanical performance of a molded product and diagnose the design before the actual mold is machined. The knowledge-based system synergistically combines a rule-based system with CAE programs. Hueristic know]edge of injection molding. flow simulation, and mechanical performance prediction is formalized as rules of an expert consultation system. The expert system interprets the analytical results of the process simulation, predicts the performance, evaluates the design and generates recommendation for optimal design alternatives.