• Journal of Information Processing Systems
• /
• v.17 no.2
• /
• pp.213-226
• /
• 2021

Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

• Journal of Biomedical Engineering Research
• /
• v.42 no.4
• /
• pp.175-185
• /
• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.9
• /
• pp.437-444
• /
• 2017

Although many studies tried to predict movie revenues in the last decade, the main focus is still to learn an efficient forecast model to fit the box-office revenues. However, the previous works lack the analysis about why the prediction errors occur, and no method is proposed to reduce the errors. In this paper, we consider the prediction error comes from the competition between the movies that are released in the same period. Our purpose is to analyze the competition value for a movie and to predict how much it will be affected by other competitors so as to improve the performance of movie box-office prediction. In order to predict the competition value, firstly, we classify its sign (positive/negative) and compute the probability of positive sign and the probability of negative sign. Secondly, we forecast the competition value by regression under the condition that its sign is positive and negative respectively. And finally, we calculate the expectation of competition value based on the probabilities and values. With the predicted competition, we can adjust the primal predicted box-office. Our experimental results show that predictive competition can help improve the performance of the forecast.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.57-60
• /
• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.25 no.1
• /
• pp.138-143
• /
• 2011

In spite of abundant clinical resources of stroke patients, the objective and logical data analyses or diagnostic systems were not established in oriental medicine. As a part of researches for standardization and objectification of differentiation of syndromes for stroke, in this present study, we tried to develop the statistical diagnostic tool discriminating the 4 subtypes of syndrome differentiation using the essential indices considering the sex. Discriminant analysis was carried out using clinical data collected from 1,448 stroke patients who was identically diagnosed for the syndrome differentiation subtypes diagnosed by two clinical experts with more than 3 year experiences. Empirical discriminant model(V) for different sex was constructed using 61 significant symptoms and sign indices selected by stepwise selection. We comparison. We make comparison a between discriminant model(V) and discriminant model(IV) using 33 significant symptoms and sign indices selected by stepwise selection. Development of statistical diagnostic tool discriminating 4 subtypes by sex : The discriminant model with the 24 significant indices in women and the 19 significant indices in men was developed for discriminating the 4 subtypes of syndrome differentiation including phlegm-dampness, qi-deficiency, yin-deficiency and fire-heat. Diagnostic accuracy and prediction rate of syndrome differentiation by sex : The overall diagnostic accuracy and prediction rate of 4 syndrome differentiation subtypes using 24 symptom and sign indices was 74.63%(403/540) and 68.46%(89/130) in women, 19 symptom and sign indices was 72.05%(446/619) and 70.44%(112/159) in men. These results are almost same as those of that the overall diagnostic accuracy(73.68%) and prediction rate(70.59%) are analyzed by the discriminant model(IV) using 33 symptom and sign indices selected by stepwise selection. Considering sex, the statistical discriminant model(V) with significant 24 symptom and sign indices in women and 19 symptom and sign indices in men, instead of 33 indices would be used in the field of oriental medicine contributing to the objectification of syndrome differentiation with parsimony rule.

• Journal of Computing Science and Engineering
• /
• v.10 no.3
• /
• pp.95-101
• /
• 2016

In this study, we propose a new system for constructing parallel corpora for sign languages, which are generally under-resourced in comparison to spoken languages. In order to achieve scalability and accessibility regarding data collection and corpus construction, our system utilizes deep learning-based techniques and predicts depth information to perform pose estimation on hand information obtainable from video recordings by a single RGB camera. These estimated poses are then transcribed into expressions in SignWriting. We evaluate the accuracy of hand tracking and hand pose estimation modules of our system quantitatively, using the American Sign Language Image Dataset and the American Sign Language Lexicon Video Dataset. The evaluation results show that our transcription system has a high potential to be successfully employed in constructing a sizable sign language corpus using various types of video resources.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.6017-6037
• /
• 2017

In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.11 no.1
• /
• pp.6-14
• /
• 2011

This paper presents a high-speed QR decomposition architecture for the multi-input-multi-output (MIMO) receiver based on Givens rotation. Under fast-varying channel, since the inverse matrix calculation has to be performed frequently in MIMO receiver, a high performance and low latency QR decomposition module is highly required. The proposed QR decomposition architecture is composed of Sign-Select Lookahead (SSL) coordinate rotation digital computer (CORDIC). In the SSL-CORDIC, the sign bits, which are computed ahead to select which direction to rotate, are used to select one of the last iteration results, therefore, the data dependencies on the previous iterations are efficiently removed. Our proposed QR decomposition module is implemented using TSMC 0.25 ${\mu}M$ CMOS process. Experimental results show that the proposed QR architecture achieves 34.83% speed-up over the Compact CORDIC based architecture for the 4 ${\times}$ 4 matrix decomposition.

• The Journal of Pediatrics of Korean Medicine
• /
• v.31 no.4
• /
• pp.31-38
• /
• 2017

Objectives The purpose of this study was to find out the clinically reliable relationships between the Risser sign and chronological age, bone age, menarche, and adult height prediction (AHP) and to evidence the reliability of the Risser sign. Methods This study had been carried out with 50 children who had their growth checked in an oriental medical hospital from January 2015 to February 2017. We investigated Risser sign in AP X-rays with iliac crest, bone age, AHP for all 50 children and the timing of menarche from the 22 girls in the study subjects. We also investigated a correlation between the Risser stage and the other indicators to analyze statistical data. Results The mean chronological ages of Risser 1, 2, 3 and 4 were 11.2, 12.6, 14.4, and 15.5 years respectively for the boys and 10.8, 12.2, 13.8 and 14.8 years respectively for the girls. The mean bone ages of Risser 1, 2, 3 and 4 were 12.3, 13.6, 15.7 and 16.5 years respectively for the boys and 11.7, 13.8, 14.3 and 14.9 years respectively for the girls. We analyzed 22 girls' Risser stages in accordance with the duration from menarche. The result showed that in the first six months after menarche, all girls were in Risser 1 and 2; in the next six months, the girls were in Risser 2 on average; in the next 12 months, all girls were in Risser 3 and 4; after more than two years from menarche, all girls were in Risser 4. The mean remaining growth height of Risser 1, 2, 3 and 4 were 27.8, 17.3, 4.4 and 1.0 cm respectively for the boys and 14.5, 5.1, 3.1 and 1.1 cm respectively for the girls. The Risser stage was correlated strongly with chronological age (Spearman's rho=0.707 (boy), 0.841 (girl)), bone age (Spearman's rho=0.869 (boy), 0.875 (girl)), duration from menarche (Spearman's rho=0.909) and remaining growth height (Spearman's rho=-0.784 (boy), -0.878 (girl)). Conclusions This study showed that the Risser sign can be useful in assessing skeletal maturity and predicting remaining growth height based on the Risser stage and the other growth indicators.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.301-303
• /
• 2007

This paper presents user adaptation methods to overcome limitations of a user-independent model and a user-dependent model in a Korean sign language recognition system. To adapt model parameters for unobserved states in hidden Markov models, we introduce new methods based on motion similarity and prediction from adaptation history so that we can achieve faster adaption and higher recognition rates comparing with previous methods.