• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.9 s.351
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• pp.59-63
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• 2006

With the increasing complexity of VLSI devices, more complex faults have appeared. Many methods for diagnosing the single stuck-at fault have been studied. Often multiple defects on a foiling chip better reflect the reality. So, we propose an efficient diagnosis algorithm for multiple stuck-at faults. By using vectorwise intersections as an important metric of diagnosis, the proposed algorithm can diagnose multiple defects using single stuck-at fault simulator. In spite of multiple fault diagnosis, the number of candidate faults is also drastically reduced. For fault identification, positive calculations and negative calculations based on variable weights are used for the matching algorithm. Experimental results for ISCAS85 and full-scan version of ISCAS89 benchmark circuits prove the efficiency of the proposed algorithm.

• The Journal of Bigdata
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• v.2 no.2
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• pp.75-86
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• 2017

In this study, I propose a method to automate the method to diagnose the quality of big data. The reason for automating the quality diagnosis of Big Data is that as the Fourth Industrial Revolution becomes a issue, there is a growing demand for more volumes of data to be generated and utilized. Data is growing rapidly. However, if it takes a lot of time to diagnose the quality of the data, it can take a long time to utilize the data or the quality of the data may be lowered. If you make decisions or predictions from these low-quality data, then the results will also give you the wrong direction. To solve this problem, I have developed a model that can automate diagnosis for improving the quality of Big Data using machine learning which can quickly diagnose and improve the data. Machine learning is used to automate domain classification tasks to prevent errors that may occur during domain classification and reduce work time. Based on the results of the research, I can contribute to the improvement of data quality to utilize big data by continuing research on the importance of data conversion, learning methods for unlearned data, and development of classification models for each domain.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.275-281
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• 2013

This space is for the of your study in English. If simple menu item changes or the addition of check items are necessary on GUI menu of existing test equipments for military facilities that are programmed by using RAD tools such as Visual C++, they should go through complex steps, such as numerous conducting steps, coding, flash design modification, recompiling and distribution. It is cumbersome process and waste much time. Also, on implementing them, it was worried about leaking secrets because a number of military security considerations were included. To solve such as the above problem, we proposed commercial RIA technologies and a COTS fault diagnostic knowledge-based system that implemented by the XML data design technique in this research. The proposed approach solves the problem of existing methods, reduced inspection time, and improved performance, usability, and maintainability.

• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.124-137
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• 2024

Malrotation and midgut volvulus are surgical emergencies that commonly occur within the first month of life. The classic symptom is acute bilious vomiting, while nonspecific symptoms such as recurrent abdominal pain may be present in older children. Malrotation can be associated with duodenal obstruction caused by an abnormal peritoneal fibrous band or congenital anomalies, such as an annular pancreas or a preduodenal portal vein. Volvulus can lead to bowel ischemia and a life-threatening condition, thus prompt and accurate diagnosis is crucial. Diagnosis can be made through upper gastrointestinal series, ultrasonography, and CT, with ultrasonography being preferred as a screening tool due to its rapid and accurate diagnosis, without radiation exposure, in children. This pictorial essay discusses the key imaging findings and diagnostic approaches for malrotation and midgut volvulus, as well as diagnostic pitfalls based on actual cases.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.23 no.1
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• pp.17-24
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• 2023

Purpose: In the past, detection of metabolic abnormalities in plasma amino acid (PAA) and urine organic acid (UOA) has been widely used to diagnose clinical mitochondrial diseases, such as mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS). In this study, the diagnostic values of PAA and UOA were reviewed, and their effectiveness in the diagnosis of MELAS was examined retrospectively. Methods: Blood and urine samples at the time of diagnosis were collected from all clinically diagnosed MELAS patients (n=31), and PAA and UOA tests were performed. All samples were collected in a fasting state to minimize artifacts in the results. The difference in the ratio of abnormal metabolites of PAA and UOA at initial diagnosis was statistically compared between the MELAS with genetic confirmation (n=19, m.3243A>G mutation) and MELAS without genetic confirmation (n=12) groups. The MELAS without genetic confirmation group was used as control. Results: Comparison of PAA and UOA between the two groups revealed that no abnormal metabolites showed characteristic differences between gene-confirmed MELAS patients with and those without genetic confirmation. Conclusions: Abnormal values of metabolites in PAA or UOA might be useful as a screening test but are not sufficient to diagnose MELAS patients.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.47-53
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• 2020

There is a need for a system that provides early warning of presence and type of failure of automobile wheel bearings through the application of predictive fault analysis technologies. In this paper, we presented a sensor module mounted on a wheel bearing and a diagnostic system that collects, stores and analyzes vehicle acceleration information and vibration information from the sensor module. The developed sensor module and predictive analysis system was tested and evaluated thorough excitation test equipment and real automotive vehicle to prove the effectiveness.

• The Journal of the Korean bone and joint tumor society
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• v.14 no.1
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• pp.62-67
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• 2008

Malignant degeneration of fibrous dysplasia is rare and involves transformation into osteosarcoma, fibrosarcoma and chondrosarcoma. The most frequent sites involved in malignant transformation were craniofacial bones, proximal femur, humerus, pelvis, tibia and scapula in a decreasing order of frequency. An 41-year-old man with a history of polyostotic fibrous dysplasia presented with increasing left arm pain. Plain radiograph showed expansile destructive lesion along the humeral shaft. As initial biopsy report was low grade chondrosarcoma, he underwent marginal resection. However, he developed local recurrence 7 month later and subsequent pathologic finding was chondroblastic osteosarcoma. We report one case of secondary chondroblastic osteosarcoma from polyostotic fibrous dysplasia initially misdiagnosed as low grade chondrosarcoma that caused fallacy in treatment strategy.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.123-133
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• 2019

This research empirically investigated halo effect in evaluating culture and art performance program. We diagnosed halo effect by using correlation analysis, factor analysis, and regression model on results and scores of fifteen evaluation indicators within three categories for the 107 Local Representative Performance Art Festivals in 2014 and 2015. The results indicates strong possibility of halo effect in culture and art performance evaluation. The correlation coefficients between evaluation indicators is higher than 0.5 and factor structure does not match with evaluation categories in both years. Scores in categories and standard deviations also are also significantly correlated with each other. The results implies that more sophisticated standard, diversification of evaluator, education, and meta-anlysis are need to control halo effect.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.150-157
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• 2020

In this study, an algorithm was developed to validate the seismic acceleration measurement data of the seismic acceleration measurement system using measurement data from public buildings currently in operation. Through the results of the study, an algorithm was developed to detect errors and abnormalities in the measurement data itself and the process of generating real-time data (MMA/sec) and event measurement data (MiniSEED), which are the main data generated by the system, and the basic data for determining the direction of inspection through measurement data analysis. It is expected that this will be used as a guideline to determine whether or not the seismic acceleration measurement system, which was managed as receiving/not receiving, is inspected and abnormal types of conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.598-604
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• 2022

The academic information system of a university is the core system of the university, and since it has to manage all the various activities in the university, such as student academic records, it becomes complicated every year and the data increases indiscriminately. As a result, the reliability of the data of the academic information system is lowered, which causes communication problems with users and may cause a major failure in the system. Therefore, in this paper, column attribute analysis, allowable value list analysis, string pattern analysis, date type analysis, and unique value analysis methods were designed for the academic information system using the data profiling technique of data quality management. In the implementation stage, the script was implemented using the above five analysis methods, and by executing the script, errors by type of the academic information system were found, the cause of the error was found and corrected inside the system, and the probability of internal system failure was lowered.