• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.61-72
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• 2005

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The experimental results for an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

• Journal of Gastric Cancer
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• v.18 no.1
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• pp.1-19
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• 2018

Gastric cancer (GC) is the second leading cause of cancer mortality and the fourth most commonly diagnosed malignant diseases. While continued efforts have been focused on GC treatment, the introduction of trastuzumab marked the beginning of a new era of target-specific treatments. Considering the diversity of mutations in GC, satisfactory results obtained from various target-specific therapies were expected, yet most of them were unsuccessful in controlled clinical trials. There are several possible reasons underlying the failures, including the absence of patient selection depending on validated predictive biomarkers, the inappropriate combination of drugs, and tumor heterogeneity. In contrast to targeted agents, immuno-oncologic agents are designed to regulate and boost immunity, are not target-specific, and may overcome tumor heterogeneity. With the successful establishment of predictive biomarkers, including Epstein-Barr virus pattern, microsatellite instability status, and programmed death-ligand 1 (PD-L1) expression, as well as ideal combination regimens, a new frontier in the immuno-oncology of GC treatment is on the horizon. Since the field of immuno-oncology has witnessed innovative, practice-changing successes in other cancer types, several trials on GC are ongoing. Among immuno-oncologic therapies, immune checkpoint inhibitors are the mainstay of clinical trials performed on GC. In this article, we review target-specific agents currently used in clinics or are undergoing clinical trials, and highlight the future clinical application of immuno-oncologic agents in inoperable GC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.62-67
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• 1999

In this paper, we investigates a reliable model of the Predictive Recurrent Neural Network for the speech recognition. Predictive Neural Networks are modeled by syllable units. For the given input syllable, then a model which gives the minimum prediction error is taken as the recognition result. The Predictive Neural Network which has the structure of recurrent network was composed to give the dynamic feature of the speech pattern into the network. We have compared with the recognition ability of the Recurrent Network proposed by Elman and Jordan. ETRI's SAMDORI has been used for the speech DB. In order to find a reliable model of neural networks, the changes of two recognition rates were compared one another in conditions of: (1) changing prediction order and the number of hidden units: and (2) accumulating previous values with self-loop coefficient in its context. The result shows that the optimum prediction order, the number of hidden units, and self-loop coefficient have differently responded according to the structure of neural network used. However, in general, the Jordan's recurrent network shows relatively higher recognition rate than Elman's. The effects of recognition rate on the self-loop coefficient were variable according to the structures of neural network and their values.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.833-839
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• 2019

Bus Information System (BIS) collects information related to the operation of buses and provides information to users through predictive algorithms. Method of predicting through recent information in same section reflects the traffic situation of the section, but cannot reflect the characteristics of the target line. The method of predicting the historical data at the same time zone is limited in forecasting peak time with high volatility of traffic flow. Therefore, we developed a pattern recognition bus arrival time prediction algorithm which could be overcome previous limitation. This method recognize the traffic pattern of target flow and select the most similar past traffic pattern. The results of this study were compared with the BIS arrival forecast information history of Seoul. RMSE of travel time between estimated and observed was approximately 35 seconds (40 seconds in BIS) at the off-peak time and 40 seconds (60 seconds in BIS) at the peak time. This means that there is data that can represent the current traffic situation in other time zones except for the same past time zone.

• Clinical and Experimental Reproductive Medicine
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• v.21 no.1
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• pp.13-20
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• 1994

Status of endometrium is a very important factor which influences the implantation of fertilized embryos. In this study, we evaluated the possibility that the endometrial depth and pattern assessed by vaginal sonography on the day of human chorionic gonadotropin (HCG) injection in in vitro fertilization (IVF) cycles could be used to predict the IVF outcome. A total of 112 cycles using gonadotropin releasing hormone agonist (GnRHa) for ovulation induction were evaluated. We classified all patients into group A(<9mm) or group B(${\geq}$ 9mm) according to endometrial depth, and into group l(hyperechogenic), group 2(isoechogenic) or group 3(hypoechogenic and triple line) according to endometrial pattern. The other classification was made considering both endometrial depth and pattern. There was no significant correlation between serum estradiol level and endometrial sonographic findings(depth and pattern)(p>0.05). The pregnancy rate of group A(31.3%) did not differ significantly from that of group B(43.7%), but no pregnancies were found in any patients with endometrial depth less than 6mm. The pregnancy rate was 40%, 35.7%, and 44.6 % for group 1, gorup 2, and group 3, respectively, but there was no statistically significant difference between these groups(p>0.05). In combined classification, there was a trend of higher pregnancy rate in case of endometrial depth greater than 9mm and hypoechogenic triple line pattern, but there was no statistically significant differences between these groups(p>0.05). The conclusion from the present data is that endometrial ultrasonography on the day of hCG administration had no predictive value for conception in IVF cycles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.55-65
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• 2006

Most of fast block motion estimation algorithms reported so far in literatures aim to reduce the computation in terms of the number of search points, thus do not fit well with multimedia processors due to their irregular data flow. For multimedia processors, proper reuse of data is more important than reducing number of absolute difference operations because the execution cycle performance strongly depends on the number of off-chip memory access. Therefore, in this paper, we propose a Hexagon-shape line search (HEXSLS) algorithm using line search pattern which can increase data reuse from on-chip local buffer, and check sub-sampling points in line search pattern to reduce unnecessary SAD operation. Our experimental results show that the prediction error (MAE) performance of the proposed HEXSLS is similar to that of the full search block matching algorithm (FSBMA), while compared with the hexagon-based search (HEXBS), the HEXSLS outperforms. Also the proposed HEXSLS requires much lesser off-chip memory access than the conventional fast motion estimation algorithm such as the hexagon-based search (HEXBS) and the predictive line search (PLS). As a result, the proposed HEXSLS algorithm requires smaller number of execution cycles on media processor.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.4089-4093
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• 2016

Purpose: This study aimed to explore the association of ${\beta}-catenin$ expression pattern with pathological response after neoadjuvant chemotherapy in breast cancer (BC) patients. Materials and Methods: In this retrospective exploratory study, data for 50 BC patients who received neoadjuvant chemotherapy were recorded. ${\beta}-catenin$ expression in tumours was assessed using immunohistochemistry and classified as either membranous or cytoplasmic according to the pattern of staining. Distributions of different clinico-pathological parameters according to ${\beta}-catenin$ expression were assessed using the Chi-square test. Logistic regression analysis was used to assess any relation of the pattern of ${\beta}-catenin$ expression with the pathological response. Results: Cytoplasmic ${\beta}-catenin$ expression was detected in 34% of BCs. Among our cases, 52% were hormonal receptor (HR)-positive, 24% were HER2-positive, 74% were clinical stage III and 74% received both anthracycline and taxane-based chemotherapy. Patients with cytoplasmic expression were more commonly younger than 40 years at diagnosis (cytoplasmic, 41.2% vs. no cytoplasmic expression, 12.1%, p=0.03). By doing t-test, cytoplasmic ${\beta}-catenin$ expression was linked with a higher body mass index compared to membranous-only expression ($mean{\pm}SD$ $33.0{\pm}4.47$ vs. $29.6{\pm}6.01$, respectively, p=0.046). No significant associations were found between ${\beta}-catenin$ expression and other parameters such as HR and HER2 status, or clinical stage. Complete pathological response (pCR) rate was twice as great in patients with membranous expression but without statistical significance (membranous-only, 33.3% vs. cytoplasmic, 17.6%, OR= 2.3, 95% CI= 0.55-9.87, p=0.24). Conclusions: This study suggests that cytoplasmic ${\beta}-catenin$ expression may be linked with lower probability of achieving pCR after neoadjuvant chemotherapy. These data need to be validated in a larger cohort of patients.

• Korean Journal of Community Nutrition
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• v.7 no.4
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• pp.495-505
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• 2002

A study was performed to develop as a screening tool the Simple Evaluation Questionnaire for Screening the Over-weight-type Dietary Pattern in 30 to 49 Year Old Adults. We used the data from the 30 to 49 year old subjects who participated in the three surveys - the health behavior survey, the dietary habit survey and the food intake survey - as the National Health and Nutrition Survey 1998. The 3,598 adults were classified into to two body fatness groups of normal (including underweight) and overweight (including obese) on the basis of their relative body weight (RBW) When comparing variables between the two groups, significant differences were found in gender, education, job, employment status, perceived health status, sadness / depression state, stress level, age, number of diseases, age when overweightedness started, maximum body weight, sleep length, drinking pattern (yes/no) , amount of alcoholic drinks, frequency of intoxication or drunkeness, amount of alcoholic drinks when drunk, intensity of exercise, frequency of exercise, exercise duration, skipped meals, small meals and drug supplements. In terms of food intake, there were significant differences in the daily food intake in terms of breakfast, dinner, daily kimchi and dairy products. In terms of mealtimes, we found differences in the amount of cooked rice at breakfast, kimchi at lunch, soup / kuk at dinner, fresh vegetables for snacks, fried foods for snacks between breakfast and lunch, and fruits /juices for snacks between lunch and dinner. After developing questions with indicators and analyzing the indicators by logistic regression analysis three times, we chose 10 questions for a simple evaluation of dietary patterns for the overweight-type category in order to give one point each. Among them we selected two questions to add one additional point and one question to add two additional points. The average scores of the overweight and normal groups, as shown by the developed questionnaire, were $5.97 \pm 2.36 \pm 7.36 \pm 2.21$, respectively. A score of seven points was selected as the cut-off point. We examined the sensitivity, specificity and positive predictive value of the questionnaire to the results of 67%, 59% and 62%, respectively.