• Smart Structures and Systems
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• v.30 no.1
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• pp.49-62
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• 2022

Experimental and discrete element methods were used to investigate the effects of triple joints lengths and triple joint angle on the failure behavior of rock mass under uniaxial compressive test. Concrete samples with dimension of 20 cm × 20 cm × 5 cm were prepared. Within the specimen, three imbedded joint were provided. The joint lengths were 2 cm, 4cm and 6 cm. In constant joint lengths, the angle between middle joint and other joints were 30°, 60°, 90°, 120° and 150°. Totally 15 different models were tested under compression test. The axial load rate on the model was 0.05 mm/min. Concurrent with experimental tests, the models containing triple joints, length and joint angle are similar to the experiments, were numerical by Particle flow code in two dimensions (PFC2D). Loading rate in numerical modelling was 0.05 mm/min. Tensile strength of material was 1 MPa. The results show that the failure behaviors of rock samples containing triple joints were governed by both of the angle and the length of the triple joints. The uniaxial compressive strengths (UCS) of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. Furthermore, it was shown that the compressive behavior of discontinuities is related to the number of the induced tensile cracks which are increased by decreasing the joint length. Along with the damage failure of the samples, the acoustic emission (AE) activities are excited. There were only a few AE hits in the initial stage of loading, then AE hits rapidly grow before the applied stress reached its peak. In addition, every stress drop was accompanied by a large number of AE hits. Finally, the failure pattern and failure strength are similar in both methods i.e., the experimental testing and the numerical simulation methods.

• Health Policy and Management
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• v.3 no.2
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• pp.159-176
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• 1993

The utilization of outpatient care services involves two steps of sequential decisions. The first step decision is about whether to initiate the utilization and the second one is about how many more visits to make after the initiation. Presumably, the initiation decision is largely made by the patient and his or her family, while the number of additional visits is decided under a strong influence of the physician. Implication is that the analysis of the outpatient care utilization requires to specify each of the two decisions underlying the utilization as a distinct stochastic process. This paper is concerned with the number of physician visits, which is, by definition, a discrete variable that can take only non-negative integer values. Since the initial visit is considered in the analysis of whether or not having made any physician visit, the focus on the number of visits made in addition to the initial one must be enough. The number of additional visits, being a kind of count data, could be assumed to exhibit a Poisson distribution. However, it is likely that the distribution is over dispersed since the number of physician visits tends to cluster around a few values but still vary widely. A recently reported study of outpatient care utilization employed an analysis based upon the assumption of a negative binomial distribution which is a type of overdispersed Poisson distribution. But there is an indication that the use of Poisson distribution making adjustments for over-dispersion results in less loss of efficiency in parameter estimation compared to the use of a certain type of distribution like a negative binomial distribution. An analysis of the data for outpatient care utilization was performed focusing on an assessment of appropriateness of available techniques. The data used in the analysis were collected by a community survey in Hwachon Gun, Kangwon Do in 1990. It was observed that a Poisson regression with adjustments for over-dispersion is superior to either an ordinary regression or a Poisson regression without adjustments oor over-dispersion. In conclusion, it seems the most approprite to assume that the number of physician visits made in addition to the initial visist exhibits an overdispersed Poisson distribution when outpatient care utilization is studied based upon a model which embodies the two-part character of the decision process uderlying the utilization.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.147-154
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• 2009

In this study we investigate the problem of reducing color change cost at painting operations in an automobile assembly plant. Changing control logic at conveyor junction points prior to the top coat line has been proposed and analyzed using the discrete event simulation model we developed using AutoMod. We also discussed the project which initiated this research as well as the details of painting operations. Simulation analysis showed that the grouping ratio increases from 1.8 to 2.5 if the proposed control logic change is applied to the plant. Contrary to other approaches such as using dedicated equipment for resequencing, our approach has the merit of less investment cost, no need for additional space consumption. We finally note that the grouping ratio can be further increased if our algorithms is implemented as well as CRS (Color Rescheduling Storage) is installed.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.127-135
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• 2010

Modern marine navigation requires officers on the bridge to monitor a torrent of data on both the insides and outsides of the ship from numerous useful devices. But despite these tools, navigators can still find it difficult to make a safe decision for two reasons: one is that too much data if provided too quickly tends to cause fatigue and overwhelm the officer, and the other is that any inconsistency across data from several different types of devices can lead to confusion. Indeed, the fact remains that the many marine accidents can be attributed to human error, and hence there is a strong need for decision-support tools for marine navigation. One technique of providing decision support is through the use of simulation to evaluate or predict system dynamics over time using an accurate model. This paper, as a simulation method for risk prediction for a navigation safety information system of ship, suggests a navigation prediction simulation system using various knowledge bases and discrete event simulation methodology, and supports the validity of the system through the examples of components in a restricted navigation situation scenario.

• KDI Journal of Economic Policy
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• v.45 no.3
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• pp.49-73
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• 2023

This study examines the usage status of legal services provided by lawyers targeting domestic consumers and investigates empirically how much online platforms that facilitate lawyer search and consultation can increase consumers' utility, and how much the lawyer legal service market will expand through this. To this end, this study applies a discrete choice demand model to the data collected through a conjoint survey to estimate the value of the lawyer search and consultation platform perceived by consumers, and estimates the effectiveness of the platform in expanding the market for lawyer legal services through a simulation method. As a result of the analysis, the relative value that consumers place on finding and consulting a lawyer using the online platform instead of being introduced to a lawyer by an acquaintance or searching for a lawyer offline is estimated to be about 70,414 won. It was found that the existence of lawyer search and consultation platforms could increase the market size of legal services by as little as 18.9% to as much as 70.2%. In particular, the platforms are expected to increase the accessibility of legal services to vulnerable groups.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.333-342
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• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• The Journal of Bigdata
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• v.7 no.1
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• pp.75-87
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• 2022

This study investigates a dynamic flexible flow shop scheduling problem under uncertain rework operations for an automobile pipe production line. We propose a weighted dispatching rule (WDR) based on the multiple dispatching rules to minimize the weighted sum of average flowtime and tardiness. The set of weights in WDR should be carefully determined because it significantly affects the performance measures. We build a discrete-event simulation model and propose a genetic algorithm to optimize the set of weights considering complex and variant operations. The simulation experiments demonstrate that WDR outperforms the baseline dispatching rules in average flowtime and tardiness.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.187-194
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• 2011

Optimizing truck dispatching-intervals is imperative in ready mixed concrete (RMC) delivery process. Intervals shorter than optimal may induce queuing of idle trucks at a construction site, resulting in a long delivery cycle time. On the other hand, intervals longer than optimal can trigger work discontinuity due to a lack of available trucks where required. Therefore, the RMC delivery process should be systematically scheduled in order to minimize the occurrence of waiting trucks as well as guarantee work continuity. However, it is challenging to find optimal intervals, particularly in urban areas, due to variations in both traffic conditions and concrete placement rates at the site. Truck dispatching intervals are usually determined based on the concrete plant managers' intuitive judgments, without sufficient and reliable information regarding traffic and site conditions. Accordingly, the RMC delivery process often experiences inefficiency and/or work discontinuity. Automatic data collection (ADC) techniques (e.g., RFID or GPS) can be effective tools to assist plant managers in finding optimal dispatching intervals, thereby enhancing delivery performance. However, quantitative evidence of the extent of performance improvement has rarely been reported to data, and this is a central reason for a general reluctance within the industry to embrace these techniques, despite their potential benefits. To address this issue, this research reports on the development of a discrete event simulation model and its application to a large-scale building project in Abu Dhabi. The simulation results indicate that ADC techniques can reduce the truck idle time at site by 57% and also enhance the pouring continuity in the RMC delivery process.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.158-168
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• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.

• Transactions of the Korean hydrogen and new energy society
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• v.35 no.3
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• pp.345-351
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• 2024

The unitized regenerative fuel cell (URFC) is a method that can reduce costs and increase system simplification by unitizing a fuel cell system and a water electrolysis system. The spray method is suitable as the membrane electrode assembly (MEA) manufacturing method for URFC because it is easy to control the amount of catalyst, the size of the system is small, and economical manufacturing is possible. In this study, a numerical analysis of the effect of solution concentration on the spray method was performed to use it as basic data for the spray method to be used in MEA manufacturing. As result, as the Nafion solution concentration decreases it was found that the spray speed and the mass flow rate and the discrete phase model concentration increases and the spray range widens.