• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.355-357
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• 2019

Now that we are entering an aging society, the user interface for new devices and IoT technology is very inconvenient for senior generation. To improve this, we propose an AI technology-based intelligent senior assistant voice recognition system. This system implements Cloud platform based API to accumulate data for machine learning processing, provides content for diagnosis and prevention of dementia, and provide chat-bot content for senior generation. We hope that senior generations will increase the accessibility and convenience of IoT devices and new technology devices with our system.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.317-322
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• 2019

This study is based on big big data base for real-time collection/analysis/processing of data, creative analysis of data assets, and intelligent processing system based on IoT, which can measure distribution phase in real time. The mobile terminal uses the SDK of the provided device to measure the data information on the consumption of specific seafood production and distribution. We use the oneM2M protocol to store various kinds of information needed for seafood production, and implement a DB Server and a system that allows the administrator to manage the system using the UI.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.286-293
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• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.3
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• pp.1-12
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• 2022

With the rapid development of artificial intelligence technology that gives existing sensors functions similar to human intelligence is drawing attention. Previously, researches were mainly focused on an improvement of fundamental performance indicators as sensors. However, recently, attempts to combine artificial intelligence such as classification and prediction with sensors have been explored. Based on this, intelligent sensor research has been actively reported in almost all kinds of sensing fields such as disease detection, motion detection, and gas sensor. In this paper, we introduce the basic concepts, types, and driving mechanisms of artificial intelligence and review some examples of its use.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.79-84
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• 2023

Social studies show that the number of separated families have lately increased due to different reasons. Despite the causes for family rift, many problems are resulted which affected the children physically and psychologically. This effect may cause them fail in their life especially at school. This paper focuses on the negative reaction of the parents' separation with other factors from the computer science prospective. Since the artificial intelligent field is the most common widespread in computer science, a predictive model is built to predict if a specific child whose parents separated, may complete the school successfully or fail to continue his education. This will be done using Decision Tree that have proved their effectiveness on the predication applications. As an experiment, a sample of individuals is randomly chosen and applied on our prediction model. As a result, this model shows that the separation may cause the child success at school if other factors are satisfied; the intelligent of the guardian, the relation between the parents after the separation, his age at the separation time, etc.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.17-25
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• 2020

This study focuses on the analysis of the service process and interaction mode of the serving robot used in the restaurant, Through user research, shadowing research and indepth interviews with customers and catering service personnel, this paper analyzes the contact points between catering service machines, people and users, constructs user journey map to understand users' expectations. In addition to the delivery service that can be allocated to the machine and people, the blueprint construction of ordering, reception and table cleaning services can also included in the service process. The final proposal is to improve the existing machine human interface and design a new service scheme.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.59-66
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• 2011

This work treat the modeling and simulation of non-linear dynamic behavior of a web winding process during traction. We designate by a winding process any system applying the cycles of unwinding, transport, treatment, and winding to various flat products. This system knows several constraints, such as the thermal effects caused by the frictions, and the mechanical effects provoked by metal elongation, that generates dysfunctions due to the influence of the process conditions. Several controllers are considered, including Proportional-integral (PI) and Backstepping control. This paper presents the study of Backstepping controls strategy of the winding system. Our winding system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.

• Korean Institute of Interior Design Journal
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• no.7
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• pp.70-78
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• 1996

Artificial Intelligence is generally concerned with tasks whose execution appears to involve some intelligence if done by humans, and knowledge-based system ( in other word, expert system) is the research about the specific domain. This concept also can be applied to interior design field. So the purpose of this study is in reconstructing the accomplishment of artificial Intelligence and knowledge engineering, searching basic theories and cased to knowledge engineering , searching basic theories and cases to formulate knowledge -based design system, and testing the posibilities how the design information can be dealt in computer system. Given that recognition , two major problems must be solved before knowledge-based CAD systems could be come practical : Firstly , identification of the interior of designers use .Secondly , representing this knowledge in a computationally effective manner. I had discussed the basic concepts on which to base a knowledge- based design model, knowledge representation schemes, and problem solving, I could find the possibility which the knowledge-based system can be applied to the interior design according to this study. But there are non-deductive, often irrational and now easily computerized design process in interior design. Those are problems which are relevant to the machine learning and the creativity in design. So there should be a lot of research about the machine learning and the creatively in design in order to construct successfully intelligent knowledge-based design system.