• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.95-103
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• 2016

In a dynamic environment autonomous robots often encounter unexpected situations that the robots have to deal with in order to continue proceeding their mission. We propose an adaptive goal-based model that allows cyber-physical systems (CPS) to update their environmental model and helps them analyze for attainment of their goals from current state using the updated environmental model and its capabilities. Information exchange approach utilizes Human-Agent-Robot-Machine-Sensor (HARMS) model to exchange messages between CPS. Model validation method uses NuSMV, which is one of Model Checking tools, to check whether the system can continue its mission toward the goal in the given environment. We explain a practical set up of the model in a situation in which homogeneous robots that has the same capability work in the same environment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.6
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• pp.533-542
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• 2003

This study aims to propose a simplified mathematical model for calculating vertical air temperature distribution in a four-sided atrium. In the first stage of the mathematical modeling, the computer model combined zonal model and solar radiation model using Monte Carlo method and Ray tracing technique went through a computer simulation with architectural variables applied to a four-sided atrium in summer. In the next stage, Curve Expert, a computer program that gets the most suitable solution ac-cording to the least squares method, is used to analyze the results of the computer simulation and to derive the mathematical model. The accuracy of the mathematical model was evaluated through a comparison of calculation results from a mathematical model and computer simulation. In this validation step using the least square method, the R2 value of the Zones 1, 2 and 3 showed higher than 0.945. Zone 4 has an R2 value of 0.911, lower than the previous three zones. However the relative error was below 0.5%, which is considered very small.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.61-68
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• 2022

The present study was based on developing an AI based model to facilitate the academic registration needs of blind students. The model was developed to enable blind students to submit academic service requests and tasks with ease. The findings from previous studies formed the basis of the study where functionality gaps from the literary research identified by blind students were utilized when the system was devised. Primary simulation data were composed based on several thousand cases. As such, the current study develops a model based on archival insight. Given that the model is theoretical, it was partially applied to help determine how efficient the associated AI tools are and determine how effective they are in real-world settings by incorporating them into the portal that institutions currently use. In this paper, we argue that voice-activated personal assistant (VAPA), text mining, bag of words, and case-based reasoning (CBR) perform better together, compared with other classifiers for analyzing and classifying the text in academic request submission through the VAPA.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.91-98
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• 2023

The rapid increase in the use of new technology known as 'blockchain technologies' has addressed many challenges in different areas and provided benefits to users, in this paper we discuss the field of supply chains, improve confidence and transparency between participants and stakeholders significantly also in this paper we Compare between different blockchain frameworks focusing on most popular frameworks. Moreover, we proposed a model in the supply chain using a blockchain framework, the proposed supply chain model included many different resources that help to exchange information over the network. The proposed model also includes smart contracts that maintain all rules for transactions. using blockchain technology information such as transaction details, time and money are recorded and stored within the system from the beginning of the transaction entry.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.49-59
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• 2012

In computer simulation models the output from the computer code is often deterministic, i.e., running the code twice with the same values for the input variables would give the same output. It is discussed why the response surface method with polynomial approximation for the true response function is a good approximation to the computer experiments model. A sequential strategy to find the proper reduced quadratic polynomial model is illustrated with a case study in the military war game computer simulation model.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.53-58
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• 2022

Pneumonia is a form of acute respiratory infection that affects the lungs. According to the World Health Organization, pneumonia is the leading cause of death for children worldwide. As a result, pneumonia was the top killer of children under the age of five years old in 2015, which is 15% of all deaths worldwide. In this paper, we used CNN model architectures to compare between the result of proposed a CNN method with VGG based model architecture. The model's performance in detecting pneumonia shows that the proposed model based on VGG can classify normal and abnormal X-rays effectively and more accurately than the proposed model used in this paper.

• The Journal of Korean Association of Computer Education
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• v.16 no.2
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• pp.29-37
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• 2013

In the environment of emphasizing creativity, computer application instruction model is in demand which is developed for the group discussion, enlarging the range of thinking, and creativity. The purpose of this study is to develop a PBL-based computer application instruction model concerning creativity after researching problems during the use of computer education by group. The theoretical background of class model is PBL, and the efficiency and creativity of class is considered while using web-mind map as the tool for the discussion and data sharing. As a result of applying the suggested model to the students enrolled in the production of presentation instruction, it made probabilistic meaningful outcome where complaint with communication, data sharing, role sharing, difference of contribution, excessive run-time and etc. were reduced.

• Smart Media Journal
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• v.8 no.3
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• pp.31-40
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• 2019

To understand how a Convolutional Neural Network (CNN) model captures the features of a pattern to determine which class it belongs to, in this paper, we use Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize and analyze how well a CNN model behave on the CNU weeds dataset. We apply this technique to Resnet model and figure out which features this model captures to determine a specific class, what makes the model get a correct/wrong classification, and how those wrong label images can cause a negative effect to a CNN model during the training process. In the experiment, Grad-CAM highlights the important regions of weeds, depending on the patterns learned by Resnet, such as the lobe and limb on 미국가막사리, or the entire leaf surface on 단풍잎돼지풀. Besides, Grad-CAM points out a CNN model can localize the object even though it is trained only for the classification problem.

• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.277-299
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• 2002

Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.