• 한국항공운항학회지
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• 제29권2호
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• pp.14-24
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• 2021

This study aims to examine probable human errors when landing an airplane by the use of SHERPA(systematic human error reduction and prediction approach) and propose methods for preventing the predictive human errors. It has been reported that human errors are concerned with a lot of accidents or incidents of an airplane. It is significant to predict presumable human errors, particularly in the operation mode of human-automation interaction, and attempt to reduce the likelihood of predicted human error. By referring to task procedures and interviewing domain experts, we analyzed airplane landing task by using HTA(hierarchical task analysis) method. In total, 6 sub-tasks and 19 operations were identified from the task analysis. SHERPA method was used for predicting probable human error types for each task. As a result, we identified 31 human errors and predicted their occurrence probability and criticality. Based on them, we suggested a set of methods for minimizing the probability of the predicted human errors. From this study, it can be said that SHERPA can be effectively used for predicting probable human error types in the context of human-automation interaction needed for navigating an airplane.

• 한국인공지능학회지
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• 제12권1호
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• pp.25-29
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• 2024

In this study, research was conducted to predict the probability of cervical cancer occurrence associated with the use of hormonal contraceptives. Cervical cancer is influenced by various environmental factors; however, the human papillomavirus (HPV) is detected in 99% of cases, making it the primary attributed cause. Additionally, although cervical cancer ranks 10th in overall female cancer incidence, it is nearly 100% preventable among known cancers. Early-stage cervical cancer typically presents no symptoms but can be detected early through regular screening. Therefore, routine tests, including cytology, should be conducted annually, as early detection significantly improves the chances of successful treatment. Thus, we employed artificial intelligence technology to forecast the likelihood of developing cervical cancer. We utilized the logistic regression algorithm, a predictive model, through Microsoft Azure. The classification model yielded an accuracy of 80.8%, a precision of 80.2%, a recall rate of 99.0%, and an F1 score of 88.6%. These results indicate that the use of hormonal contraceptives is associated with an increased risk of cervical cancer. Further development of the artificial intelligence program, as studied here, holds promise for reducing mortality rates attributable to cervical cancer.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.61-68
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• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• 한국수학교육학회지시리즈A:수학교육
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• 제63권1호
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• pp.19-33
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• 2024

본 연구는 중학생들의 수학 흥미와 성취도의 종단적인 변화 양상을 알아보기 위해 경기교육종단연구 4-6차년도 데이터를 분석하였다. 다변량 성장혼합모형을 이용하여 분석한 결과 학생들의 수학 흥미와 성취도의 변화 양상에 이질적인 특성이 존재함을 확인하였고, 종단적인 변화 양상에 따라 학생들을 4개의 잠재집단으로 구분하였다. 학생들은 흥미와 성취도가 모두 낮은 저수준 유형, 모두 높은 고수준 유형, 학년이 올라감에 따라 증가하는 중수준-증가 유형, 학년이 올라감에 따라 감소하는 중수준-감소 유형으로 구분되었으며, 유형마다 흥미와 성취도의 종단적인 변화 양상이 다르게 나타나는 것을 확인하였다. 또한, 다변량 성장혼합모형의 초기값과 기울기 사이의 상관관계를 분석한 결과, 수학 흥미와 성취도는 초기값뿐 아니라 변화율에 있어서도 서로 긍정적인 영향이 있는 것으로 나타났다. 잠재집단의 결정에 영향을 미치는 요인을 개인, 수업방식, 가정 변인으로 나누어 그 영향력을 살펴보았고, 학생의 교육포부와 사교육 시간은 수학 흥미 및 성취도에 긍정적인 영향을 미치며 선행학습의 경우 그 정도에 따라 영향력이 달라지는 양상을 확인하였다. 학생이 인식한 수업방식의 경우, 교수자 중심 수업은 흥미와 성취도가 높은 집단에 속할 확률을 높이고, 학습자 중심 수업은 흥미와 성취도가 낮은 집단에 속할 확률을 높이는 것으로 나타났다. 본 연구는 다변량 성장혼합모형을 통해 수학교육에서 흥미와 성취도를 비롯한 다양한 특성에 대한 학생들의 변화 양상을 분석하는 새로운 방법을 제시하였다는 점에서 의의가 있다.

• Journal of Gastric Cancer
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• 제10권4호
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• pp.162-167
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• 2010

Purpose: The incidence of lymph node metastasis has been reported to range from 2.6 to 4.8% in early stage gastric cancer with mucosal invasion (T1a cancer). Lymph node metastasis in early stage gastric cancer is known as an important predictive factor. We analyzed the prediction factors of lymph node metastasis in T1a cancer. Materials and Methods: A total of 9,912 patients underwent radical gastrectomy due to gastric cancer from October 1994 to July 2006 in the Department Of Surgery at Samsung Medical Center. We did a retrospective analysis of 2,524 patients of these patients, ones for whom the cancer was confined within the mucosa. Results: Among the 2,524 patients, 57 (2.2%) were diagnosed with lymph node metastasis, and of these, cancer staging was as follows: 41 were N1, 8 were N2, and 8 were N3a. Univariate analysis of clinicopathological factors showed that the following factors were significant predictors of metastasis: tumor size larger than 4 cm, the presence of middle and lower stomach cancer, poorly differentiated adenocarcinoma and signet-ring cell carcinoma, diffuse type cancer (by the Lauren classification), and lymphatic invasion. Multivariate analysis showed that lymphatic invasion and tumor larger than 4 cm were significant factors with P<0.001 and P=0.024, respectively. Conclusions: The frequency of lymph node metastasis is extremely low in early gastric cancer with mucosal invasion. However, when lymphatic invasion is present or the tumor is larger than 4 cm, there is a greater likelihood of lymph node metastasis. In such cases, surgical treatments should be done to prevent disease recurrence.

• Archives of Plastic Surgery
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• 제49권1호
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• pp.91-98
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• 2022

Background Predicting the need for post-traumatic reconstruction of lower extremity injuries remains a challenge. Due to the larger volume of cases in adults than in children, the majority of the medical literature has focused on adult lower extremity reconstruction. This study evaluates predictive risk factors associated with the need for free flap reconstruction in pediatric patients following lower extremity trauma. Methods An IRB-approved retrospective chart analysis over a 5-year period (January 1, 2012 to December 31, 2017) was performed, including all pediatric patients (<18 years old) diagnosed with one or more lower extremity wounds. Patient demographics, trauma information, and operative information were reviewed. The statistical analysis consisted of univariate and multivariate regression models to identify predictor variables associated with free flap reconstruction. Results In total, 1,821 patients were identified who fit our search criteria, of whom 41 patients (2.25%) required free flap reconstruction, 65 patients (3.57%) required local flap reconstruction, and 19 patients (1.04%) required skin graft reconstruction. We determined that older age (odds ratio [OR], 1.134; P =0.002), all-terrain vehicle accidents (OR, 6.698; P<0.001), and trauma team activation (OR, 2.443; P=0.034) were associated with the need for free flap reconstruction following lower extremity trauma in our pediatric population. Conclusions Our study demonstrates a higher likelihood of free flap reconstruction in older pediatric patients, those involved in all-terrain vehicle accidents, and cases involving activation of the trauma team. This information can be implemented to help develop an early risk calculator that defines the need for complex lower extremity reconstruction in the pediatric population.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.690-693
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• 2002

According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

• Safety and Health at Work
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• 제8권3호
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• pp.267-275
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• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

• Asian Pacific Journal of Cancer Prevention
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• 제15권22호
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• pp.10039-10043
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• 2014

Background: In Pakistan thyroid cancer is responsible for 1.2% cases of all malignant tumors. Ultrasonography (US) is helpful in detecting cancerous thyroid nodules on basis of different features like echogenicity, margins, microcalcifications, size, shape and abnormal neck lymph nodes. We therefore aimed to calculate diagnostic accuracy of ultrasound in detection of carcinoma in thyroid nodules taking fine needle aspiration cytology as the reference standard. Materials and Methods: A cross-sectional analytical study was designed to prospectively collect data from December 2010 till December 2012 from the Department of Radiology in Aga Khan University Hospital, Karachi, Pakistan. A total of 100 patients of both genders were enrolled after informed consent via applying non-probability consecutive sampling technique. Patients referred to Radiology department of Aga Khan University to perform thyroid ultrasound followed by fine-needle aspiration cytology of thyroid nodules were included. They were excluded if proven for thyroid malignancy or if their US or FNAC was conducted outside our institution. Results: The subjects comprised 76 (76%) females and 24 males. Mean age was $41.8{\pm}SD$ 12.3 years. Sensitivity and specificity with 95%CI of ultrasound in differentiating malignant thyroid nodule from benign thyroid nodule calculated to be 91.7% (95%CI, 0.72-0.98) and 78.94% (0.68-0.87) respectively. Reported positive predictive value and negative PV were 57.9% (0.41-0.73) and 96.8% (0.88-0.99) and overall accuracy was 82%. Likelihood ratio (LR) positive was computed to be 4.3 and LR negative was 0.1. Conclusions: Ultrasonography has a high diagnostic accuracy in detecting malignancy in thyroid nodules on the basis of features like echogenicity, margins, micro calcifications and shape.

• 한국보건간호학회지
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• 제31권2호
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• pp.376-388
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• 2017

Purpose: The triglyceride-to-high-density lipoprotein-cholesterol (TG/HDL-C) ratio is one of the main predictive indices for cardiovascular disease. This study was examined the relationship between TG/HDL-C ratio and metabolic syndrome (MetS) in male office workers. Methods: Secondary analysis was conducted to determine the risk between the TG/HDL-C ratio and MetS in male office workers. A total of 765 people underwent the 'regular workplace health checkups in 2014'. Among the subjects who were male and responded to the questionnaire and health lifestyle survey, 470 (61.4%) excluding those with missing and/or abnormal values were analyzed. The association between MetS, MetS components, and the TG/HDL-C ratio was examined by a Chi-square test, One-way ANOVA, Turkey post-hoc test and Logistic regression analysis. Results: The number of males with MetS was 70 (14.9%) and the number of MetS components increased with increasing TG/HDL-C ratio (p<.001). Logistic regression analysis with an adjustment for potential confounders revealed a 31.8 times higher odds ratio of the Quartile4 group for MetS than that of the Quartile1 group (p<.001). Conclusion: These results show that the likelihood of MetS, particularly the risk of MetS in the Quartile4, increases with increasing TG/HDL-C ratio.