• Imaging Science in Dentistry
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• v.50 no.2
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• pp.81-92
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• 2020

Intelligent systems(i.e., artificial intelligence), particularly deep learning, are machines able to mimic the cognitive functions of humans to perform tasks of problem-solving and learning. This field deals with computational models that can think and act intelligently, like the human brain, and construct algorithms that can learn from data to make predictions. Artificial intelligence is becoming important in radiology due to its ability to detect abnormalities in radiographic images that are unnoticed by the naked human eye. These systems have reduced radiologists' workload by rapidly recording and presenting data, and thereby monitoring the treatment response with a reduced risk of cognitive bias. Intelligent systems have an important role to play and could be used by dentists as an adjunct to other imaging modalities in making appropriate diagnoses and treatment plans. In the field of maxillofacial radiology, these systems have shown promise for the interpretation of complex images, accurate localization of landmarks, characterization of bone architecture, estimation of oral cancer risk, and the assessment of metastatic lymph nodes, periapical pathologies, and maxillary sinus pathologies. This review discusses the clinical applications and scope of intelligent systems such as machine learning, artificial intelligence, and deep learning programs in maxillofacial imaging.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.41-48
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• 2011

In order to detect driver's state in a driver safety system, both overt and covert measures such as driving performance, visual attention, physiological arousal and traffic situation should be collected and interpreted in the driving context. In this paper, we suggest a vehicle monitoring system that provides multimodal information on a broad set of measures simultaneously collected from multiple domains including driver, vehicle and road environment using an elaborate timer equipped as a soft synchronization mechanism. Using a master timer that records key values from various modules with the same master time of short and precise interval, the monitoring system provides more accurate context awareness through synchronized data at any given time. This paper also discusses the data collected from nine young drivers performing a cognitive secondary task through this system while driving.

• Child Health Nursing Research
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• v.1 no.1
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• pp.26-36
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• 1995

Children with metabolic disorders suffer from retardation and cognitive dysfunction. The task of caring for a mother may mean that she has less time and mony and more workload which may result in increased fatigue and depression and low well-being. The burden carried by mother due to the responsiblity take care of child. The descriptive study was done identify the burden in mother of children with metabolic disorders. The data was collected from November 1 to November 16, 1993. nineteen mothers were interviewed with metabolic disorders with questionnaire by mail. Burden was measured using existing tools by Zarit (1980), Montgomery(1985) . et al. Burden data was analyzed by the SPSS /pc+ program were tested using means, frequencies, Mann-Whitney, U-Wilcoxon Rank Sum Test and Kruskal-Wallis one way ANOVA The result of this study as follows : The meas score for burden was 2.8. (range from 34 to 4.95) The result of reiationship of demographic character and burden was no significant. In conclusion it was found that burden is correlated negatively to quality of life. In this study, burden was scored relatively low. Further qualitative research is needed to validats the nature of burden.

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.127-133
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• 2007

The purpose of this study is to apply WDA (Work Domain Analysis) for the development of EID (Ecological Interface Design) of vehicle control display. At first, a work domain model on the automobile operation was developed using the AH (Abstraction Hierarchy) which is one of WDA tools. Secondly, information requirements that should be included in vehicle control displays were extracted on the basis of the completed model. The vehicle control information that typical automobiles interface displays currently provide occurred on the low level of the work domain model. This implies that current control displays impose too heavy cognitive workload on automobile drivers. Information requirements that can be included new vehicle control display are also discovered in the high level of the work domain model. The detailed information for EID was not proposed in this study. In the further study, the development of vehicle control display will be deeply conducted, using the results of this study.

• The Journal of Pediatrics of Korean Medicine
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• v.21 no.3
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• pp.85-95
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• 2007

Objectives Attention Deficit Hyperactivity Disorder(ADHD) is a type of psychiatric disorder characterized with the primary symptoms of inattention and/or impulsivity and hyperactivity. The purpose of this study is to examine ADHD children who were treated with neurofeedback therapy. Methods We analyzed clinical report of 3 ADHD children who treated with neurofeedback therapy from January 2006 to June 2006. Results 1. All 3 children were diagnosed with predominantly inattention type of ADHD. 2. After treatment, cognitive strength, response, concentration, workload, left / right brain activity score were all different from each children. 3. After treatment, left and right brain activities were balanced. 4. After treatment, learning ability level was increased. 5. After treatment, the childrenwere in a better state referred to conner's scale and H.S.Q. score. Conclusions Further studies will be needed to get more clinical cases about the benefits of neurofeedback therapy with herbal medicine and acupuncture treatment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.281-293
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• 2023

This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS's rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.47-53
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• 2010

An analysis of biosignal and performance data collected during driving has increasingly employed in research to explore a human-vehicle interface design for better safety and comfort. The present study developed a protocol and a system to effectively analyze biosignal and driving performance measurements in various driving conditions. Electrocardiogram (ECG), respiration rate (RR), and skin conductance level (SCL) were selected for biosignal analysis in the study. A data processing and analysis protocol was established based on a comprehensive review of related literature. Then, the established analysis protocol was implemented to a computerized system so that immense data of biosignal and driving performance can be analyzed with ease, efficiency, and effectiveness for an individual and/or a group of individuals of interest. The developed analysis system would be of use to examine the effects of driving conditions to cognitive workload and driving performance.

• Journal of Preventive Medicine and Public Health
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• v.29 no.2 s.53
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• pp.239-254
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• 1996

Health services on industrial noisy environment have been provided only for noise-induced hearing loss management until now. But gradually, modem diseases and death have come to be related to stress and mental health deeply, therefore noise-induced mental disorder, like a stress became very important. In this point, the purpose of this study was to analyze the relationship between noise exposure level in worksite and workers' stress symptoms. This study included a survey of 786 manual workers selected from 89 worksites in 21 factories in Puchon. The results were as follows: 1. For demographic characteristics, most of the workers were males(80.8%), the $20\sim29years$ old were 34.5% and those who graduated from high school were 65.3%. The workers whose monthly income ranged from 100,000 to 800,000 won were 37.5% and who have a religion were 47.9%. 2. For occupational characteristics, workers who had worked $1\sim5$ years in the factories were 33.0%. Those who were much for them workload were 43.9% and who worked more than 8 hours a day were 73.9%. Those who were disatisfied with their job and pay were 31.9% and 50.6%. The workers who responsed ventilation condition of their worksites were bad were 51.9% and the dissatisfed with working environment of their worksites were 45.9%. 3. Workers who were suffering from tinnitus were 53.3% and those who perceived hearing loss were 50.1%. Persons who reported they always wore earplugs at work were 35.4%. Those who felt earplugs bigger than their ears were 30.6% and those who experienced eardiseases caused by earplugs were 25.6%. 4. For the noise exposure level in worksite, workers who were exposed to $80\sim90dB$ were 30.3%, $90\sim100dB$ were 26.4% and $50\sim70dB$ were 19.2%. 5. Workers' stress symptoms were significantly related to marital status and their monthly income(p<0.05). Workers who were single and had lower monthly income showed higher PSI (Psychiatric Symptom Index) scores than those who were married and had higher monthly income. Higher PSI scores were also significantly related to $1\sim2$ days hight-work per week, much for them workload, dissatisfaction with their job, and bad relationship with their bosses and coworkers. 6. Higher PSI scores were significantly related to severe tinnitus and perceived hearing losso(p<0.001). Workers who felt the earplugs they use did not fit their ears showed significantly higher PSI scores(p<0.01). Workers who reported that they did not feel they need earplugs showed. significantly higher PSI scores (p<0.05). Increased experience of eardisease caused by earplugs that did not fit were also significantly related to higher PSI scores(p<0.01). 7. The higher noise exposure level in worksite from 80dB was, the more severe stress symptoms including PSI subparts were reported; Anxiety, Anger, Depression, and Cognitive disorder(p<0.001). 5. According to the results of stepwise multiple regression analysis, factors affecting workers' PSI scores were perceived hearing loss$(R^2=0.160)$, noise exposure level in worksite$(R^2=0.110)$, realtionship with coworkers, amount of workload, monthly income and relationship with bosses orderly and the total $R^2$ of this 6 factors was 0.371. 9. The most significant factors that have impact on manual workers' stress symptoms were perceived hearing loss and noise exposure level in worksite, especially noise exposure level in the worksite was the most affective factor on the depression symptom.

• Communications of Mathematical Education
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• v.34 no.3
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• pp.215-234
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• 2020

With the advent of the AI, the need to use AI in the field of education is widely recognized. The purpose of this study is to shed light on how prospective mathematics teachers perceive the need for AI and the role of teachers in future mathematics education. As a result, with regard to teaching, prospective teachers recognized that the use of AI in school mathematics is a demand of a new era, that various types of lesson can be implemented, and that accurate knowledge and information can be delivered. On the other hand, they recognized that AI has limitations in having cognitive and emotional interactions with students. As for mathematics learning, the prospective teachers recognized that AI can provide individualized learning, be used for supplementary learning outside of school, and stimulate students' interest in learning. However, they also said that learning through AI could undermine students' ability to think on their own. With regard to assessment, the prospective teachers recognized that AI is objective, fair and can reduce teachers' workload, but they also said that AI has limitations in evaluating students' abilities in constructed-response items and in process-focused assessment. The roles of teachers that the prospective teachers think were to conduct a lesson, emotional interaction, unstructured assessment, and counseling, and those of AI were individualized learning, rote learning, structured assessment, and administrative works.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.9-23
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• 2015

A lane change maneuver which has a high driver cognitive workload and skills sometimes leads to severe traffic accidents. In this study, the Advanced Lane Change Assist System (ALCAS) was developed to assist with the automatic lane changes in merging sections which is mainly based on an automatic control algorithm for detecting an available gap, determining the Optimal Lane Change Start Point (OLCSP) in various traffic conditions, and positioning the merging vehicle at the OLCSP safely by longitudinal automatic controlling. The analysis of lane change behavior and modeling of fundamental lane change feature were performed for determining the default parameters and the boundary conditions of the algorithm. The algorithm was composed of six steps with closed-loop. In order to confirm the algorithm performance, numerical scenario tests were performed in various surrounding vehicles conditions. Moreover, feasibility of the developed system was verified in microscopic traffic simulation(VISSIM 5.3 version). The results showed that merging vehicles using the system had a tendency to find the OLCSP readily and precisely, so improved merging performance was observed when the system was applied. The system is also effective even during increases in vehicle volume of the mainline.