• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.23 no.2
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• pp.121-131
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• 2020

Purpose: To determine the long-term efficacy of the anti-tumor necrosis factor (TNF) agents, infliximab (IFX) and adalimumab (ADA), in pediatric luminal Crohn's disease (CD) by performing a systematic literature review. Methods: An electronic search was performed in Medline, Embase, and the Cochrane Library from inception to September 26, 2019. Eligible studies were cohort studies with observation periods that exceeded 1 year. Studies that reported time-to-event analyses were included. Events were defined as discontinuation of anti-TNF therapy for secondary loss of response. We extracted the probabilities of continuing anti-TNF therapy 1, 2, and 3 years after initiation. Results: In total, 2,464 papers were screened, 94 were selected for full text review, and 13 studies (11 on IFX, 2 on ADA) met our eligibility criteria for inclusion. After 1 year, 83-97% of patients were still receiving IFX therapy. After 2 and 3 years the probability of continuing IFX therapy decreased to 67-91% and 61-85%, respectively. In total, 5 of the 11 studies subgrouped by concomitant medication consistently showed that the probabilities of continuing IFX therapy in patients with prolonged immunomodulator use were higher than those in patients on IFX monotherapy. Conclusion: This review of real-world evidence studies confirms the long-term therapeutic benefit of IFX therapy in diverse cohorts of children with luminal CD. Moreover, it supports the view that combination therapy with an immunomodulator prolongs the durability of IFX therapy in patients who previously failed to recover following first-line therapy. The limited number of time-to-event studies in patients on ADA prevented us from drawing definite conclusions about its long-term efficacy.

• Journal of Korean Society of Rural Planning
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• v.9 no.1 s.18
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• pp.65-75
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• 2003

As a pre-step research to make land-use planning in the region level, this study aims to analyze some probability pattern representing transition probabilities from farmland to others using the sequential detailed digital land-use maps. Kinki and Chubu regions of Japan, which have Osaka and Nagoya cities as their center places respectively, were selected as test regions in this study. The 10m grid land-use maps for four time series at every 5 year from 1977 to 1992 were used. In this study, the regions were divided into three sub-areas 10km, 20km, and 30km according to distance from center cities, respectively. The correlation coefficient (CC) between sub-areas with same distance in the two regions was calculated to analyze whether or not the two regions have common points in the pattern of land-use conversion probability from farmland to other types. The probability distribution of the converted areas which were moved to the urbanized area (residential, commercial, industrial, road, park and public facility areas) was about $40{\sim}70%$ for both all periods and sub-areas. According to distance from city centers, the probability moved to the urbanized area was about 60% at 10km area, and 40% at the 30km area, which means that the values we decreased gradually, while in the case moved to the forest and the etc areas, the values were increased slightly. The CC analysis from the paddy field and the dry field to the others separately showed that there is high correlation in the probability pattern between the two regions.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1949-1955
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• 2000

This paper proposes a multistage interconnection ATM switching network without internal blocking. The first is recirculating shuffle-exchange network improved on hardware complexity. The next is connected to Rank network with tree structure. In this network, after the packets transferred to the same output ports are given each priority, only a packet with highest priority is sent to the next, an the others are recirculated to the first. Rearrangeability through decomposition and composition algorithm is applied for the transferred packets in hanyan network and all they arrive at a final destinations. To analyze throughput, waiting time and packet loss ratio according tothe size of buffer, the probabilities are modeled by a binomial distribution of packet arrival.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.297-319
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• 2016

Football match predictions are of great interest to fans and sports press. In the last few years it has been the focus of several studies. In this paper, we propose the Poisson regression model in order to football match outcomes. We applied the proposed methodology to two national competitions: the 2012-2013 English Premier League and the 2015 Brazilian Football League. The number of goals scored by each team in a match is assumed to follow Poisson distribution, whose average reflects the strength of the attack, defense and the home team advantage. Inferences about all unknown quantities involved are made using a Bayesian approach. We calculate the probabilities of win, draw and loss for each match using a simulation procedure. Besides, also using simulation, the probability of a team qualifying for continental tournaments, being crowned champion or relegated to the second division is obtained.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.153-156
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• 2003

In this paper, we propose a new scheme for automatic segmentation of the liver in CT images. The proposed scheme is carried out on region of interest(ROI) blocks that include regions of the liver with high probabilities. The ROI approach saves unnecessary computational loss in finding the accurate boundary of the liver. The proposed method utilizes the composition of multi-size morphological filters with a prior knowledge, such as the general location or the approximate intensity of the liver to detect the initial boundary of the liver. Then, we make the gradient image with the weight of the initial liver boundary and segment the liver legion by using an immersion-based waters hed algorithm in the gradient image. finally, the refining process is carried out to acquire a more accurate liver region.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.109-115
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• 2009

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. In this paper, we investigate several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. At first, word distance method based on phone and syllable distances are considered. These methods use just Levenstein distance on phones or double Levenstein distance algorithm on syllables of candidates. Next, word similarity approaches are presented that they use characters' position information of word candidates. Each character's position is labeled to inserted, deleted, and correct position after alignment between source and target string. The word similarities are obtained from characters' positional probabilities which mean the frequency ratio of the same characters' observations on the position. From experimental results, we can find that the proposed methods are effective for removing non-similar words without loss of system performance from the N-best recognition candidates of the systems.

• Journal of the Korea Society for Simulation
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• v.13 no.3
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• pp.1-10
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• 2004

The cell loss probability required in the ATM network is in the range of 10$^{-9}$ ∼10$^{-12}$ . If Monte Carlo simulation is used to analyze the performance of the ATM node, an enormous amount of computer time is required. To obtain large speed-up factors, importance sampling may be used. Since the Markov-modulated processes have been used to model various high-speed network traffic sources, we consider discrete time single server queueing systems with Markov-modulated arrival processes which can be used to model an ATM node. We apply importance sampling based on the Large Deviation Theory for the performance evaluation of, MMBP/D/1/K, ∑MMBP/D/1/K, and two stage tandem queueing networks with Markov-modulated arrival processes and deterministic service times. The simulation results show that the buffer overflow probabilities obtained by the importance sampling are very close to those obtained by the Monte Carlo simulation and the computer time can be reduced drastically.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1085-1087
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• 1998

A distribution systems loss minimum reconfiguration method by simulated annealing is proposed. The problem is a complex mixed integer programming problem and is very difficult to solve by a mathematical programming approach. Simulated annealing generates feasible solutions randomly and moves among these solutions using a strategy leading to a global minimum with high probabilities. The solution algorithm has been implemented in developed software package and tested on 32-bus system.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.97-106
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• 2010

Various time series representation methods have been suggested in order to process time series data efficiently and effectively. SAX is the representative time series representation method combining segmentation and discretization techniques, which has been successfully applied to the time series classification task. But SAX requires a large number of segments in order to represent the meaningful dynamic patterns of time series accurately, since it loss the dynamic property of time series in the course of smoothing the movement of time series. Therefore, this paper suggests a new time series representation method that combines PIPs detection and Persist discretization techniques. The suggested method represents the dynamic movement of high-diemensional time series in a lower dimensional space by detecting PIPs indicating the important inflection points of time series. And it determines the optimal discretizaton ranges by applying self-transition and marginal probabilities distributions to KL divergence measure. It minimizes the information loss in process of the dimensionality reduction. The suggested method enhances the performance of time series classification task by minimizing the information loss in the course of dimensionality reduction.