• Journal of Information Processing Systems
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• v.17 no.2
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• pp.242-252
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• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.49-53
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• 2017

Breast cancer is the sccond most female cancer patient in the entire female cancer patient, and has emerged as the highest contributor to female cancer deaths. If breast cancer id detected early, the cure rate is 92 percent. However, if early detection fails, breast cancer has a very high rate of metastasis. The transition from cancer to cancer has become more successful as cancer progresses. Early diagnosis of cancer is an important factor in improving quality of life. Examples of breast cancer include Mammograph, ultrasound, and Momotome. Mommography is not only painful for the examiner, but also for easy access to breast cancer exam inations. In this paper, breast cancer diagnosis data mammograph data was used. In addition, the Neural Network were classified for early diagnosis of breast cancer early using NEWFM. After learning of data using NEWFM, the accuracy of the breast cancer data classification was 84.4391%.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.23-35
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• 2017

Objectives : This study analyzed the trends of patient costs in 7diagnosis-related groups(DRG) since July 2013 when the government made it mandatory for all hospitals and clinics. Methods : Data were collected from the 7DRG score chart published by the Ministry of Health and Welfare(MoHW) from July 2013 to January 2017. The average value of the weekday relative value scale was multiplied by unit price, referred to as'- "patient costs by disease group"-' and they were analyzed by time series. Results : Patient costs had increased among all patients with a comprehensive disease. Small and medium-sized hospitals (hospitals and clinics) showed a slight increase in patient costs. Conclusions : Enforcement of the Korean diagnosis-related groups has led to management crisis in small and medium-sized hospitals and deterioration medical service quality. To solve this problem, The weekday relative value scale of small and medium-sized hospitals should be increased significantly.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.89-95
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• 2001

On-site diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for the purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2609-2614
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• 2015

National research and development projects institutions have implemented various measures in order to prevent R&D expenses abuse and negate enforcement. but it reveals a limit to prevent abuse of R&D expenses[1,2]. In this paper, to prevent abuses resulting from the R & D for the unusual trading post caught collecting information from the R & D phase implementation plan to detect unusual transactions. The results are subjective and research institutions, and specialized agencies to take advantage of shared, real-time cross-linkage between the credit card companies. Studies of data quality diagnostic techniques developed for this purpose related regulations and manuals, Q & A, FAQ, Outside-in business rules that derive from a variety of information, such as personnel interviews (Outside-In) was used for analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3123-3129
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• 2016

Background: Cancer is the fourth leading cause of death in Sabah Malaysia with a reported age-standardized incidence rate was 104.9 per 100,000 in 2007. The incidence rate depends on non-mandatory notification in the registry. Under-reporting will provide the false picture of cancer control program effectiveness. The present study was to evaluate the performance of the cancer registry system in terms of representativeness, data quality, simplicity, acceptability and timeliness and provision of recommendations for improvement. Materials and Methods: The evaluation was conducted among key informants in the National Cancer Registry (NCR) and reporting facilities from Feb-May 2012 and was based on US CDC guidelines. Representativeness was assessed by matching cancer case in the Health Information System (HIS) and state pathology records with those in NCR. Data quality was measured through case finding and re-abstracting of medical records by independent auditors. The re-abstracting portion comprised 15 data items. Self-administered questionnaires were used to assess simplicity and acceptability. Timeliness was measured from date of diagnosis to date of notification received and data dissemination. Results: Of 4613 cancer cases reported in HIS, 83.3% were matched with cancer registry. In the state pathology centre, 99.8% was notified to registry. Duplication of notification was 3%. Data completeness calculated for 104 samples was 63.4%. Registrars perceived simplicity in coding diagnosis as moderate. Notification process was moderately acceptable. Median duration of interval 1 was 5.7 months. Conclusions: The performances of registry's attributes are fairly positive in terms of simplicity, case reporting sensitivity, and predictive value positive. It is moderately acceptable, data completeness and inflexible. The usefulness of registry is the area of concern to achieve registry objectives. Timeliness of reporting is within international standard, whereas timeliness to data dissemination was longer up to 4 years. Integration between existing HIS and national registration department will improve data quality.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.276-280
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• 2016

Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $T^2$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.

• Journal of the Korean Dietetic Association
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• v.29 no.4
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• pp.199-210
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• 2023

This study was undertaken to analyze the growth, nutritional, and dietary risk factors of elementary school students belonging to the Busan Metropolitan City Office of Education and provide the basic data needed to develop an underweight and obesity prevention program. In 2021, BMI and Dietary Screening Test (DST) data of 4,046 children surveyed by the Nutrition Education Experience Center's "Diagnosis System" of the Busan Regional Office of Education were analyzed. The DST consists of 36 questions about lifestyle habits, meal quality, meal regularity, snack quality, and eating behavior. Of the children included, 6.8% were underweight, 65.4% were normal weight, 13.4% were overweight, and 14.4% were obese. Children in the obesity group had shorter sleep and meal times (P<0.001), lower vegetable and fruit consumption frequencies (P<0.001), higher fast food consumption frequencies (P<0.001), higher rates of skipping meals (P<0.01) and breakfast (P<0.001), and more frequently used smartphones and watched TV during meals (P<0.001). The underweight group had the highest scores for all eating development factors but more frequently had chewing and swallowing difficulties (P<0.001). The study confirms underweightedness and obesity are present different problems and indicates that nutrition teachers should conduct accurate studies on the eating habits and behaviors of obese and underweight students and provide individually tailored nutritional counseling.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.435-440
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• 2013

Background: Breast cancer is the leading cause of cancer-related death among women in Malaysia. A diagnosis is very stressful for women, affecting all aspects of their being and quality of life. As such, there is little information on quality of life of women with breast cancer across the different ethnic groups in Malaysia. The purpose of this study was to examine the quality of life in Malay and Chinese women newly diagnosed with breast cancer in Kelantan. Materials and Methods: A descriptive study involved 58 Malays and 15 Chinese women newly diagnosed with breast cancer prior to treatment. Quality of life was measured using the Malay version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and its breast-specific module (QLQ-BR23). Socio-demographic and clinical data were also collected. All the data were analyzed using SPSS version 20.0. Results: Most of the women were married with at least a secondary education and were in late stages of breast cancer. The Malay women had lower incomes (p=0.046) and more children (p=0.001) when compared to the Chinese women. Generally, both the Malay and Chinese women had good functioning quality-of-life scores [mean score range: 60.3-84.8 (Malays); 65.0-91.1 (Chinese)] and global quality of life [mean score 60.3, SD 22.2 (Malays); mean score 65.0, SD 26.6 (Chinese)]. The Malay women experienced more symptoms such as nausea and vomiting (p=0.002), dyspnoea (p=0.004), constipation (p<0.001) and breast-specific symptoms (p=0.041) when compared to the Chinese. Conclusions: Quality of life was satisfactory in both Malays and Chinese women newly diagnosed with breast cancer in Kelantan. However, Malay women had a lower quality of life due to high general as well as breast-specific symptoms. This study finding underlined the importance of measuring quality of life in the newly diagnosed breast cancer patient, as it will provide a broader picture on how a cancer diagnosis impacts multi-ethnic patients. Once health care professionals understand this, they might then be able to determine how to best support and improve the quality of life of these women during the difficult times of their disease and on-going cancer treatments.