• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• Journal of Oriental Neuropsychiatry
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• v.31 no.2
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• pp.89-99
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• 2020

Objectives: The purpose of this study was to identify the needs of bio-signal devices for the diagnosis, assessment, and analysis of neurocognitive disorder in Korean medicine (KM) hospitals and clinics. Methods: A questionnaire was developed to survey the current status of medical device use, and diagnosis and interventions for patients with cognitive disorders in KM hospitals and clinics. November 11~December 2, 2019, 114 responses (71.9% completed) were collected by internet-based questionnaires from the members of the Korean society of Oriental Neuropsychiatry. Results: The clinical requests were in the descending order of hematology analyzer, ultrasound imaging system, and electroencephalography among the 15 most commonly used devices of which research would support for their clinical usability. The biosignal-based devices showed the highest research demands for patients with mild cognitive impairment rather than more severe stages of cognitive impairment. Prevention rather than diagnosis, or several treatment regimens was the strongest clinical area of the KM for patients with neurodegenerative cognitive impairment. Many responded that five to 10 minutes of test duration and 20,000 won to 30,000 won of cost would be appropriated for a new device to be developed. Conclusions: There were strong demands for the development of bio-signal devices for neurocognitive disorders among the KM doctors. Specifically, it showed high needs for the technology that can be used in the prevention area of cognitive disorders. Additionally, new medical devices to assess cognitive functions and to obtain KM pattern-related information were the high needs.

• Journal of Oriental Neuropsychiatry
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• v.30 no.1
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• pp.31-38
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• 2019

Objectives: To identify the cost effectiveness of early dementia diagnosis using the 2014 Health Insurance Review & Assessment Service-National Patients Sample (HIRA-NPS). Methods: The medical costs of dementia between Western medical care and Korean medical care were compared through the reimbursement and non-reimbursement item code for dementia examination. In addition, the medical expenses of patients with dementia and mild cognitive impairment were compared and analyzed with respect to Western and Korean medical care. Results: There were 87,434 claims, of which 16,101 patients were diagnosed with dementia and 38,680,789,560 won was found to be the medical expenses. 12,881 patients (80.0%) with dementia, 3,144 patients (19.5%) with mild cognitive impairment, and 76 patients (0.5%) progressing from mild cognitive impairment to dementia. The proportion of medical expenses was 97.6% for dementia patients, 2.3% for mild cognitive impairment, and 1% for patients progressing from mild cognitive impairment to dementia. 86,070 claims (98.4%) were from Western medical care, with16,824 patients (98.2%), and the medical expenses was 38,546,895,400 won (99.7%). 1,361 claims (1.6%) were from Korean medical care, with 303 patients (1.8%), and the medical expenses was 133,894,160 won (0.3%). Conclusions: This study compared and analyzed the medical costs of dementia patients and the diagnosis of both Korean and Western medical care. The results of this study are expected to be used as basic research data for investigating cost effectiveness of developing early diagnosis of dementia.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.812-823
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• 2009

The purpose of this study is to search effective assessments methods by using the Fusion model of Cognitive diagnosis theory. Attributes are skills or cognitive processes that are required to perform correctly on a particular item. After test items were developed, item's attributes were decided and Q-matrix about item's attributes was made. After testing, the result was analyzed according to gender and achievement level. The results of the analysis showed that students mastered 'Interpreting data' best, and 'synthesizing' worst among the five attributes. Female students showed higher ability than male students in 'recalling.' Students of high achievement level mastered more scientific attributes than students of low achievement level. Conventional assessments only provided a single summary score but Cognitive diagnosis modeling provided useful information by estimating individual knowledge states by assessing whether an examinee has mastered specific attributes measured by the science test. The skill profiles can offer a skill level of strong, weak, or mixed for each student for each skill. Therefore, the skill profiles will provide useful diagnostic information in addition to single overall scores.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.595-617
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• 2010

This paper proposes a novel of a personalized Computer Assisted Language Learning (CALL) system based on learner's cognitive abilities related to foreign language proficiency. In this CALL system, a strategy of retrieval learning, a method of learning memory cycle, and a method of repeated learning are applied for effective vocabulary memorization. The system is designed to offer personalized learning based on cognitive abilities related to the human language process. For this, the proposed CALL system has a cognitive diagnosis module which can measure five types of cognitive abilities. The results of this diagnosis are used to create dynamic learning scenarios for personalized learning and to evaluate user performance in the learning. This system is also designed in order to have users be able to create learning word lists and to share them simply with various functions based on open APIs. Additionally, through experiments, it has shown that this system helps students to learn English vocabulary effectively and enhances their foreign language skills.

• Journal of Oriental Neuropsychiatry
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• v.32 no.3
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• pp.285-302
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• 2021

Objectives: To examine the effect of long-term Korean medicine treatment on mild cognitive impairment (MCI). Methods: This study was conducted on two patients who were diagnosed with mild cognitive impairment and received long-term Korean medicine treatment. In order to evaluate the degree of cognitive decline, SNSB and K-MMSE were performed 2~3 times at the first visit and during the treatment process. Results: Both cases 1 and 2 were diagnosed with MCI with a high possibility of developing dementia. In case 1, MCI progressed to early dementia at one year after the diagnosis of MCI. However, in case 2, that MCI status was maintained without progressing to dementia for 4 years after the diagnosis of MCI. The cause of such difference in the course of MCI might be attributed to the fact that Case 1 had lower K-IADL level but higher SGDS level than Case 2 at the time of initial diagnosis, with weak family support and irregular herbal medicine intake. Conclusions: Korean medicine treatment could improve and manage symptoms of cognitive decline due to MCI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3266-3285
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• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.

• Educational Technology International
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• v.23 no.2
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• pp.157-181
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• 2022

Scale scores for cognitive domains have been used as an important indicator for both academic achievement and clinical diagnosis. For example, in education, Cognitive Abilities Test (CogAT) has been used to measure student's capability in academic learning. In a clinical setting, Cognitive Impairment Screening Test utilizes items measuring cognitive ability as a dementia screening test. We demonstrated a procedure of generating cognitive ability test items similar as in CogAT but the theory associated with the generation is totally different. When creating cognitive test items, we applied automatic item generation (AIG) that reduces errors in predictions of cognitive ability but attains higher reliability. We selected two cognitive ability test items, categorized as a time estimation item for measuring quantitative reasoning and a paper-folding item for measuring visualization. As CogAT has widely used as a cognitive measurement test, developing an AIG-based cognitive test items will greatly contribute to education field. Since CLASS is the only LMS including AIG technology, we used it for the AIG software to construct item models. The purpose of this study is to demonstrate the item generation process using AIG implemented within CLASS, along with proving quantitative and qualitative strengths of AIG. In result, we confirmed that more than 10,000 items could be made by a single item model in the quantitative aspect and the validity of items could be assured by the procedure based on ECD and AE in the qualitative aspect. This reliable item generation process based on item models would be the key of developing accurate cognitive measurement tests.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.860-863
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• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme. However, the previously proposed scheme has the problem of lower diagnostic resolution. In order to improve the diagnostic resolution, a new diagnostic scheme based on extended FCM which incorporates the concept of fuzzy number into FCM is developed in this paper. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and pattern matching scheme are also proposed.