• Title/Summary/Keyword: Improved classification system

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Gene Discovery Analysis from Mouse Embryonic Stem Cells Based on Time Course Microarray Data

  • Suh, Young Ju;Cho, Sun A;Shim, Jung Hee;Yook, Yeon Joo;Yoo, Kyung Hyun;Kim, Jung Hee;Park, Eun Young;Noh, Ji Yeun;Lee, Seong Ho;Yang, Moon Hee;Jeong, Hyo Seok;Park, Jong Hoon
    • Molecules and Cells
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    • v.26 no.4
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    • pp.338-343
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    • 2008
  • An embryonic stem cell is a powerful tool for investigation of early development in vitro. The study of embryonic stem cell mediated neuronal differentiation allows for improved understanding of the mechanisms involved in embryonic neuronal development. We investigated expression profile changes using time course cDNA microarray to identify clues for the signaling network of neuronal differentiation. For the short time course microarray data, pattern analysis based on the quadratic regression method is an effective approach for identification and classification of a variety of expressed genes that have biological relevance. We studied the expression patterns, at each of 5 stages, after neuronal induction at the mRNA level of embryonic stem cells using the quadratic regression method for pattern analysis. As a result, a total of 316 genes (3.1%) including 166 (1.7%) informative genes in 8 possible expression patterns were identified by pattern analysis. Among the selected genes associated with neurological system, all three genes showing linearly increasing pattern over time, and one gene showing decreasing pattern over time, were verified by RT-PCR. Therefore, an increase in gene expression over time, in a linear pattern, may be associated with embryonic development. The genes: Tcfap2c, Ttr, Wnt3a, Btg2 and Foxk1 detected by pattern analysis, and verified by RT-PCR simultaneously, may be candidate markers associated with the development of the nervous system. Our study shows that pattern analysis, using the quadratic regression method, is very useful for investigation of time course cDNA microarray data. The pattern analysis used in this study has biological significance for the study of embryonic stem cells.

Analysis on Adequacy of the Satellite Soil Moisture Data (AMSR2, ASCAT, and ESACCI) in Korean Peninsula: With Classification of Freezing and Melting Periods (인공위성 기반 토양 수분 자료들(AMSR2, ASCAT, and ESACCI)의 한반도 적절성 분석: 동결과 융해 기간을 구분하여)

  • Baik, Jongjin;Cho, Seongkeun;Lee, Seulchan;Choi, Minha
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.625-636
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    • 2019
  • Soil moisture is a representative factor that plays a key role in hydrological cycle. It is involved in the interaction between atmosphere and land surface, and is used in fields such as agriculture and water resources. Advanced Microwave Scanning Radiometer 2 (AMSR2), Advanced SCATterometer (ASCAT), and European Space Agency Climate Change Initiative (ESACCI) data were used to analyze the applicability and uncertainty of satellite soil moisture product in the Korean peninsula. Cumulative distribution function (CDF) matching and triple collocation (TC) analysis were carried out to investigate uncertainty and correction of satellite soil moisture data. Comparisons of pre-calibration satellite soil moisture data with the Automated Agriculture Observing System (AAOS) indicated that ESACCI and ASCAT data reflect the trend of AAOS well. On the other hand, AMSR2 satellite data showed overestimated values during the freezing period. Correction of satellite soil moisture data using CDF matching improved the error and correlation compared to those before correction. Finally, uncertainty analysis of soil moisture was carried out using TC method. Clearly, the uncertainty of the satellite soil moisture, corrected by CDF matching, was diminished in both freezing and thawing periods. Overall, it is expected that using ASCAT and ESACCI rather than AMSR2 soil moisture data will give more accurate soil moisture information when correction is performed on the Korean peninsula.

A Study on Management and Utilization of Non-disclosure Records (비공개 기록의 관리와 활용에 관한 연구)

  • Ahn, Ji-Hyun
    • The Korean Journal of Archival Studies
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    • no.13
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    • pp.135-178
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    • 2006
  • The response of public organizations on information offerings has affirmed that the arrangement of the management of records is an important project to be implemented ahead of the enforcement of the information disclosure system. In particular, the absence or non-disclosure of information of public organizations on records containing significant information and abuse of the secret disposition of information has demonstrated that it is imperative to improve radically the management of secret or non-disclosed records as well as overall changes of awareness. This study reviewed the reality of the current non-disclosure and management of confidential records based on the awareness on such records and proposed improvement measures. The study on non-disclosed and confidential records has been discussed from legal and administrative perspectives so that the main focus has been on the institutional aspect. Yet, there is a limitation on such discussions in that there cannot be fundamental access to issues of non-disclosed and confidential records. That is because the management of information classified as non-disclosed and confidential can be improved fundamentally when all processes from the production of the records to their management are carried out reasonably. Accordingly, since our record management system is divided into three phases of the disposition division, record center, and archives and takes a management record by being applied to the flow of the life cycle of records, we have reviewed overall issues from the production of non-disclosed and confidential records to the utilization of the records pursuant to these steps and offered directions for improvement.

A Development of Road Crack Detection System Using Deep Learning-based Segmentation and Object Detection (딥러닝 기반의 분할과 객체탐지를 활용한 도로균열 탐지시스템 개발)

  • Ha, Jongwoo;Park, Kyongwon;Kim, Minsoo
    • The Journal of Society for e-Business Studies
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    • v.26 no.1
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    • pp.93-106
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    • 2021
  • Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

Development of a Real-time Ship Operational Efficiency Analysis Model (선박운항데이터 기반 실시간 선박운항효율 분석 모델 개발)

  • Taemin Hwang;Hyoseon Hwang;Ik-Hyun Youn
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.1
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    • pp.60-66
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    • 2023
  • Currently, the maritime industry is focusing on developing technologies that promote autonomy and intelligence, such as smart ships, autonomous ships, and eco-friendly technologies, to enhance ship operational efficiency. Many countries are conducting research on different methods to ensure ship safety while increasing operational efficiency. This study aims to develop a real-time ship operational efficiency analysis model using data analysis methods to address the current limitations of the present technologies in the real-time evaluation of operational efficiency. The model selected ship operational efficiency factors and ship operational condition factors to compare the operational efficiency of the ship with present and classified factors to determine whether the present ship operational efficiency is appropriate. The study involved selecting a target ship, collecting data, preprocessing data, and developing classification models. The results of the research were obtained by determining the improved ship operational efficiency based on the ship operational condition factors to support ship operators.

Effects of Aquatic Exercise on Upper Extremity Function and Postural Control During Reaching in Children With Cerebral Palsy

  • Yongjin Jeon;Hye-Seon Jeon;Chunghwi Yi;Ohyun Kwon;Heonseock Cynn;Duckwon Oh
    • Physical Therapy Korea
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    • v.30 no.2
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    • pp.128-135
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    • 2023
  • Background: Despite the fact that aquatic exercise is one of the most popular alternative treatment methods for children with cerebral palsy (CP), there are few research regarding its effectiveness. Objects: The purpose of this study was to examine the effects of aquatic exercise on upper extremity function and postural control during reaching in children with CP. Methods: Ten participants (eight males and two females; 4-10 years; Gross Motor Function Classification System levels II-IV) with spastic diplegia were recruited to this study. The aquatic exercise program consisted of four modified movements that were selected from the Halliwick 10-point program to enhance upper extremity and trunk movements. The participants attended treatment two times a week for 6 weeks, averaging 35 minutes each session. The Box and Block Test (BBT), transferring pennies in the Bruininks-Oseretsky Test (BOT), and pediatric reaching test (PRT) scores were used as clinical measures. Three-dimensional motion analysis system was used to collect and analyze kinematic data. Differences in BBT and BOT values among pre-treatment, post-treatment, and retention (after 3 weeks) were analyzed using a Friedman test. In addition, the PRT scores and variables (movement time, hand velocity, straightness ratio, and number of movement units) from the three-dimensional motion analysis were tested using a Wilcoxon signed-rank test. The significance level was established at p < 0.05. When the results appeared to be statistically significant, a post-hoc test for multiple comparisons was performed with the Wilcoxon signed-rank test. Results: All clinical measures, which included BBT, transferring pennies of BOT, and PRT, were significantly increased between pre-intervention and post-intervention scores and between pre-intervention and retention scores after treatment (p = 0.001). Three-dimensional motion analysis mostly were significantly improved after treatment (p = 0.001). Conclusion: Aquatic exercise may help to improve body function, activity, and participation in children with varying types of physical disabilities.

Preoperative Assessment of Renal Sinus Invasion by Renal Cell Carcinoma according to Tumor Complexity and Imaging Features in Patients Undergoing Radical Nephrectomy

  • Ji Hoon Kim;Kye Jin Park;Mi-Hyun Kim;Jeong Kon Kim
    • Korean Journal of Radiology
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    • v.22 no.8
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    • pp.1323-1331
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    • 2021
  • Objective: To identify the association between renal tumor complexity and pathologic renal sinus invasion (RSI) and evaluate the usefulness of computed tomography tumor features for predicting RSI in patients with renal cell carcinoma (RCC). Materials and Methods: This retrospective study included 276 consecutive patients who underwent radical nephrectomy for RCC with a size of ≤ 7 cm between January 2014 and October 2017. Tumor complexity and anatomical renal sinus involvement were evaluated using two standardized scoring systems: the radius (R), exophytic or endophytic (E), nearness to collecting system or sinus (N), anterior or posterior (A), and location relative to polar lines (RENAL) nephrometry and preoperative aspects and dimensions used for anatomical classification (PADUA) system. CT-based tumor features, including shape, enhancement pattern, margin at the interface of the renal sinus (smooth vs. non-smooth), and finger-like projection of the mass, were also assessed by two independent radiologists. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of RSI. The positive predictive value, negative predictive value (NPV), accuracy of anatomical renal sinus involvement, and tumor features were evaluated. Results: Eighty-one of 276 patients (29.3%) demonstrated RSI. Among highly complex tumors (RENAL or PADUA score ≥ 10), the frequencies of RSI were 42.4% (39/92) and 38.0% (71/187) using RENAL and PADUA scores, respectively. Multivariable analysis showed that a non-smooth margin and the presence of a finger-like projection were significant predictors of RSI. Anatomical renal sinus involvement showed high NPVs (91.7% and 95.2%) but low accuracy (40.2% and 43.1%) for RSI, whereas the presence of a non-smooth margin or finger-like projection demonstrated comparably high NPVs (90.0% and 91.3% for both readers) and improved accuracy (67.0% and 73.9%, respectively). Conclusion: A non-smooth margin or the presence of a finger-like projection can be used as a preoperative CT-based tumor feature for predicting RSI in patients with RCC.

Development of the Information Delivery System for the Home Nursing Service (가정간호사업 운용을 위한 정보전달체계 개발 I (가정간호 데이터베이스 구축과 뇌졸중 환자의 가정간호 전산개발))

  • Park, J.H;Kim, M.J;Hong, K.J;Han, K.J;Park, S.A;Yung, S.N;Lee, I.S;Joh, H.;Bang, K.S
    • Journal of Home Health Care Nursing
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    • v.4
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    • pp.5-22
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    • 1997
  • The purpose of the study was to development an information delivery system for the home nursing service, to demonstrate and to evaluate the efficiency of it. The period of research conduct was from September 1996 to August 31, 1997. At the 1st stage to achieve the purpose, Firstly Assessment tool for the patients with cerebral vascular disease who have the first priority of HNS among the patients with various health problems at home was developed through literature review. Secondly, after identification of patient nursing problem by the home care nurse with the assessment tool, the patient's classification system developed by Park (1988) that was 128 nursing activities under 6 categories was used to identify the home care nurse's activities of the patient with CAV at home. The research team had several workshops with 5 clinical nurse experts to refine it. At last 110 nursing activities under 11 categories for the patients with CVA were derived. At the second stage, algorithms were developed to connect 110 nursing activities with the patient nursing problems identified by assessment tool. The computerizing process of the algorithms is as follows: These algorithms are realized with the computer program by use of the software engineering technique. The development is made by the prototyping method, which is the requirement analysis of the software specifications. The basic features of the usability, compatibility, adaptability and maintainability are taken into consideration. Particular emphasis is given to the efficient construction of the database. To enhance the database efficiency and to establish the structural cohesion, the data field is categorized with the weight of relevance to the particular disease. This approach permits the easy adaptability when numerous diseases are applied in the future. In paralleled with this, the expandability and maintainability is stressed through out the program development, which leads to the modular concept. However since the disease to be applied is increased in number as the project progress and since they are interrelated and coupled each other, the expand ability as well as maintainability should be considered with a big priority. Furthermore, since the system is to be synthesized with other medical systems in the future, these properties are very important. The prototype developed in this project is to be evaluated through the stage of system testing. There are various evaluation metrics such as cohesion, coupling and adaptability so on. But unfortunately, direct measurement of these metrics are very difficult, and accordingly, analytical and quantitative evaluations are almost impossible. Therefore, instead of the analytical evaluation, the experimental evaluation is to be applied through the test run by various users. This system testing will provide the viewpoint analysis of the user's level, and the detail and additional requirement specifications arising from user's real situation will be feedback into the system modeling. Also. the degree of freedom of the input and output will be improved, and the hardware limitation will be investigated. Upon the refining, the prototype system will be used as a design template. and will be used to develop the more extensive system. In detail. the relevant modules will be developed for the various diseases, and the module will be integrated by the macroscopic design process focusing on the inter modularity, generality of the database. and compatibility with other systems. The Home care Evaluation System is comprised of three main modules of : (1) General information on a patient, (2) General health status of a patient, and (3) Cerebrovascular disease patient. The general health status module has five sub modules of physical measurement, vitality, nursing, pharmaceutical description and emotional/cognition ability. The CVA patient module is divided into ten sub modules such as subjective sense, consciousness, memory and language pattern so on. The typical sub modules are described in appendix 3.

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A Hybrid SVM Classifier for Imbalanced Data Sets (불균형 데이터 집합의 분류를 위한 하이브리드 SVM 모델)

  • Lee, Jae Sik;Kwon, Jong Gu
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.125-140
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    • 2013
  • We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

Outcome of Arthroscopic Suture Bridge Technique for Rotator Cuff Tear: Short Term Clinical Outcome In Full-thickness Tear With Fatty Degeneration Less Than Moderate Degree (회전근 개 파열에 대한 관절경적 교량형 봉합술의 결과: 지방 변성이 중등도 이하인 전층 파열에 대한 단기 추시 임상적 결과)

  • Cheon, Sang-Jin;Hur, Joon-Oh;Suh, Jeung-Tak;Yoo, Chong-Il
    • Clinics in Shoulder and Elbow
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    • v.12 no.2
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    • pp.180-188
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    • 2009
  • Purpose: We evaluate the short-term clinical outcome of arthroscopic rotator cuff tendon repair with suture-bridge technique in patients with full thickness rotator cuff tear. Materials and Methods: 29 (male:17, female:12) consecutive shoulders treated with this index procedure and early rehabilitation were enrolled. Mean age was 56.4 years (range, 34~73 years) and mean follow-up period was 13 months (range, 12-15 months). Clinical outcomes were evaluated by using the University of California Los Angeles (UCLA) score, the Korean Shoulder Scoring System (KSS) and Visual Analogue Scale (VAS). Postoperative cuff integrity was evaluated through magnetic resonance imaging (MRI) and categorized by Sugaya classification. Results: Postoperative UCLA scores improved from 16.4 to 31.6 (p< 0.05) and KSS scores showed 88 at 6 months and 92 at last follow up. Preoperative VAS score was 8.6, which was decreased to 2.1 at 3 months and 1.4 at 6 months postoperatively. 28 patients (96.5%) had increase in range of motion. The follow up MRI was taken in 15 shoulders and the cuff integrity was type I in 6 cases, type II in 7, type III in 1 and type V in 1 by Sugaya classification. Conclusion: Arthroscopic suture-bridge technique resulted in good or excellent clinical outcome in 96.5% of the cases, so we think this technique is one of the reliable procedure for full-thicknes rotator cuff tear.