• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.38-45
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• 2012

Finding shortest paths on time dependent networks is an important task for scheduling and routing plan and real-time navigation system in ITS. In this research, one-to-one time dependent shortest path algorithms based on link flow speeds on urban networks are proposed. For this work, first we select three general shortest path algorithms such as Graph growth algorithm with two queues, Dijkstra's algorithm with approximate buckets and Dijkstra's algorithm with double buckets. These algorithms were developed to compute shortest distance paths from one node to all nodes in a network and have proven to be fast and efficient algorithms in real networks. These algorithms are extended to compute a time dependent shortest path from an origin node to a destination node in real urban networks. Three extended algorithms are implemented on a data set from real urban networks to test and evaluate three algorithms. A data set consists of 4 urban street networks for Anaheim, CA, Baltimore, MD, Chicago, IL, and Philadelphia, PA. Based on the computational results, among the three algorithms for TDSP, the extended Dijkstra's algorithm with double buckets is recommended to solve one-to-one time dependent shortest path for urban street networks.

• Journal of Science of Art and Design
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• v.1
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• pp.165-188
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• 1999

When we think about visual art, we can't pass over the matter of images and spaces. An image is fixed in a painting space. If the image were posited in the river of time, it would be changed as time flowed on. Its image might be created, rigged, transfigured or it might vanish or remain as traces. The image is changed through the process of expressing them on the painting surfaces. In paintings the changing of the image is caused not only by working processes but also recognizing the objects. In modernist painting, the idea of space was important, but in postmodernist view, the idea of time becomes essential. In this thesis I will focus on the matter of time and image of painting in the late 20th century. Studying the relationship of image and time is not familiar because we had considered the space as being more related to painting distinction than time. Presently, the concept of space can't be divided from that of time. In Physics, they recently called it as a united concept- time-space. Painting space also becomes one asking and recieve the concept of time actively. Now in painting, time is no more a supporting matter but becomes a major matter. In the late 20th century, we can find many trials to catch the change of images as time flowes on and express them as a trace through using verioty media. One of the way to drawing the change of images as time passes could be seen through various joint images in one painting space and another in the traces of one image. The other could be done by using new media such as computer in the example of fractal art. It shows the images chainging of practically as time changes. New understanding about time of this era has to be affirmatively accepted because it reflects the contemporary cultural situation and in art, the concern about the possiblity of it and finding new medias which has to go on.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.19-26
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• 1987

In analyzing time series, estimating the level or the current mean of the process plays an important role in understanding its structure and in being able to make forecasts. The studies the class of time series models where the level of the process is assumed to follow a random walk and the deviation from the level follow an ARMA process. The estimation and forecasting problem in a Bayesian framework and uses the Kalman filter to obtain forecasts based on estimates of level. In the analysis of time series, we usually make the assumption that the time series is generated by one model. However, in many situations the time series undergoes a structural change at one point in time. For example there may be a change in the distribution of random variables or in parameter values. Another example occurs when the level of the process changes abruptly at one period. In order to study such problems, the assumption that level follows a random walk process is relaxed to include a major level change at a particular point in time. The major level change is detected by examining the likelihood raio under a null hypothesis of no change and an alternative hypothesis of a major level change. The author proposes a method for estimation the size of the level change by adding one state variable to the state space model of the original Kalman filter. Detailed theoretical and numerical results are obtained for th first order autoregressive process wirth level changes.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.601-614
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• 2006

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5359-5364
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• 2014

Background: To determine surgical outcomes, perioperative complications, and patient outcomes in gynecologic cancer patients undergoing robotic surgery. Materials and Methods: Surgical outcomes, including docking time, total operative time, console time, estimated blood loss (EBL), conversion rate and perioperative complications were retrospectively reviewed in 30 gynecologic cancer patients undergoing robotic surgery. Patient outcomes included recovery time and patient satisfaction, as scored by a visual analogue scale (VAS) from 0-10. Results: The operations included 24 hysterectomies with pelvic lymphadenectomy (PLD) and/or para-aortic lymphadenectomy, four radical hysterectomies with PLD, and two radical trachelectomies with PLD. Mean docking time was $12.8{\pm}9.7min$, total operative time was $345.5{\pm}85.0min$, and console time was $281.9{\pm}78.6min$. These times were decreased in the second half of the cases. There was no conversion rate. Three intraoperative complications, including one external iliac artery injury, one bladder injury, and one massive bleeding requiring blood transfusion were reported. Postoperative complications occurred in eight patients, most were minor. Only one patient had port herniation that required reoperation. Mean hospital stay was $3.5{\pm}1.7days$, and recovery time was $14.2{\pm}8.1days$. Two-thirds of patients felt very satisfied and one-third felt satisfied; the mean satisfaction score was 9.4 +0.9. Two patients with stage III endometrial cancer developed isolated port site metastasis at five and 13 months postoperatively. Conclusions: Robotic surgery for gynecologic cancer appears to be feasible, with acceptable perioperative complication rate, fast recovery time and high patient satisfaction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.62-65
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• 2006

In this paper, nonlinear nonplanar vibration of a flexible rectangular cantilever beam is analyzed when one-to-one resonance occurs to the beam. The planar and nonplanar motions of the beam are analyzed in time and frequency domains. In frequency domain, FFT analyzer is used to perform autospectrum and cepstrum analyses for nonlinear response of the beam. In time domain, an oscilloscope is used to investigate the phase difference between the planar and nonplanar motions and to perform Torus analysis in the phase space. Through those analyzing process, the main frequencies of superharmonic, subharmonic, and super-subharmonic motions are investigated in the nonplanar motion due to one-to-one resonance. Analyzing the phase difference between the planar and nonplanar motions, it is observed that the phase difference varies in time.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4307-4309
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• 2014

Purpose: To calculate the probability of one person's life-time death caused by a malignant tumor and provide theoretical basis for cancer prevention. Materials and Methods: The probability of one person's death caused by a tumor was calculated by a probability additive formula and based on an abridged life table. All data for age-specific mortality were from the third retrospective investigation of death cause in China. Results: The probability of one person's death caused by malignant tumor was 18.7% calculated by the probability additive formula. On the same way, the life-time death probability caused by lung cancer, gastric cancer, liver cancer, esophageal cancer, colorectal and anal cancer were 4.47%, 3.62%, 3.25%, 2.25%, 1.11%, respectively. Conclusions: Malignant tumor is still the main cause of death in one's life time and the most common causes of cancer death were lung, gastric, liver, esophageal, colorectal and anal cancers. Targeted forms of cancer prevention and treatment strategies should be worked out to improve people's health and prolong life in China. The probability additive formula is a more scientific and objective method to calculate the probability of one person's life-time death than cumulative death probability.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.100-102
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• 1991

In this paper, we use LFSR(Linear Feedback Shift Register) as a kind of pseudo-random one-time pad. Key generator is constructed using r separate LFSR's with IP(Irreducible Polynominal) which are relatively prime. Key generated in this method has high linear complexity. And also, file cryptosystem for file encryption and decryption is constructed.

• Animal Bioscience
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• v.34 no.11
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• pp.1776-1783
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• 2021

Objective: This project aimed to evaluate the effects of both different additives and filling methods on nutritive quality, fermentation profile, and in situ digestibility of whole plant corn silage. Methods: Whole plant corn forage harvested at 26.72% dry matter (DM) was chopped and treated with two filling methods, i) fill silos at one time (F1), ii) fill silos at three times (F3), packing samples into one/three silo capacity at the first day, another one/three capacity at the second day, then one/three at the third day, three replicates. For each replicate, samples were treated with three additives, i) control (CTRL, no additive), ii) Sila-Max (MAX, Ralco Nutrition Inc., Marshall, MN, USA), and iii) Sila-Mix (MIX, Ralco Nutrition Inc., USA). With three replicates of each secondary treatment, there were nine silos, 54 silos in total. Each silo had a packing density of 137.61 kg of DM/m3. All silos were weighed and stored in lab at ambient temperature. Results: After 60 d of ensiling, all items showed good silage fermentation under MAX filled one time or three times (p<0.01). Higher silage quality for all additives was obtained at filling one time than that filled three times (p<0.01). The highest DM and lowest DM loss rate (DMLR) occurred to MAX treatment at two filling methods (p<0.01); Digestibility of acid detergent fiber, neutral detergent fiber (NDF), and curde protein had the same results as silage quality (p<0.01). Yield of digestible DM and digestible NDF also showed higher value under MAX especially for filling one time (p<0.05). Conclusion: All corn silages showed good fermentation attributes (pH<4.0). The forage filled one time had higher silage quality than that filled three times (p<0.01). MAX with homofermentative lactic acid bacteria enhanced the lactic acid fermentation, silage quality and nutrient digestibility, and so improved the digestible nutrient yield.