• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.113-127
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• 2021

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.329-342
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• 2021

The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.59-66
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• 2022

In this paper, by applying IoT technology to the Ultimate game, which is one of the games using Flyingdisc, the process of the game is traced based on the players and the flyingdisc, and a comprehensive relationship analysis between players is performed on the results of the game. A WiFi module with built-in GPS is attached in the players and flyingdisc. The player's ID, latitude/longitude values received from GPS and time are stored in the database in realtime during the game. Process informations of the game is also stored in the database at the same time using mobile Ultimate game App. Based on this informations after the game is over, we developed a system that can perform comprehensive analysis of the game contents. By using the informations stored in the database, the player-based game process and the flyingdisc-based scoring process are visualized in the virtual playground. Various game result informations for players are graphically analyzed using Python.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.534-544
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• 2022

Medical ultrasound system has been widely used to visualize the lesion for diagnostics in most medical service site including hospitals and clinics thanks to its advantages such as real time operation, ease of use, safety. Among many signal processing blocks of the system, one of the most important part that governs the image quality is the beamformer, and technologies for this part has been continuously developed in long time. The synthetic aperture imaging method, that is one of the major technologies of beamforming, was introduced to maximize utilizing the information delivered from the patient's body through the probe, and contributed to breakthrough of the image quality since it was introduced in around 1990's, and evolved continuously in decades. This paper reviews and surveys the process of development of this technology and expects future evolution.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1189-1198
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• 2021

When performing remote tasks using robots in nuclear power plants, a 3D shape measurement system is advantageous in improving the efficiency of remote operations by easily identifying the current state of the target object for example, size, shape, and distance information. Nuclear power plants have high-radiation and underwater environments therefore the electronic parts that comprise 3D shape measurement systems are prone to degradation and thus cannot be used for a long period of time. Also, given the refraction caused by a medium change in the underwater environment, optical design constraints and calibration methods for them are required. The present study proposed a method for developing an underwater 3D shape measurement system with improved radiation tolerance, which is composed of commercial electric parts and a stereo camera while being capable of easily and readily correcting underwater refraction. In an effort to improve its radiation tolerance, the number of parts that are exposed to a radiation environment was minimized to include only necessary components, such as a line beam laser, a motor to rotate the line beam laser, and a stereo camera. Given that a signal processing circuit and control circuit of the camera is susceptible to radiation, an image sensor and lens of the camera were separated from its main body to improve radiation tolerance. The prototype developed in the present study was made of commercial electric parts, and thus it was possible to improve the overall radiation tolerance at a relatively low cost. Also, it was easy to manufacture because there are few constraints for optical design.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.17-22
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• 2021

It is difficult for the hearing impaired to use the counseling service without sign language interpretation. Due to the shortage of sign language interpreters, it takes a lot of time to connect to sign language interpreters, or there are many cases where the connection is not available. Therefore, in this paper, we propose a system that captures sign language as an image using OpenCV and CNN (Convolutional Neural Network), recognizes sign language motion, and converts the meaning of sign language into textual data and provides it to users. The counselor can conduct counseling by reading the stored sign language translation counseling contents. Consultation is possible without a professional sign language interpreter, reducing the burden of waiting for a sign language interpreter. If the proposed system is applied to counseling services for the hearing impaired, it is expected to improve the effectiveness of counseling and promote academic research on counseling for the hearing impaired in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.47-52
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• 2023

Mobile Edge Computing(MEC) is considered as a promising technology to effectively support the explosively increasing traffic demands. It can provide low-latency services and reduce network traffic by caching contents at the edge of networks such as Base Station(BS). Although users may associate with the nearest BSs, it is more beneficial to associate users to the BS where the requested content is cached to reduce content download latency. Therefore, in this paper, we propose a mobility-aware joint caching and user association algorithm to imporve the cache hit ratio. In particular, the proposed algorithm performs caching and user association based on sojourn time and content preferences. Simulation results show that the proposed scheme improves the performance in terms of cache hit ratio and latency as compared with existing schemes.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.202-211
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• 2022

The purpose of this study is to investigate the relationship between job stress, job autonomy, employee support evaluation, and the turnover intentions of workers in the beauty and cosmetics industry. This study assessed 570 workers with 3 months or more of experience in the beauty and cosmetics industry. Data processing was achieved through analyses of frequency, descriptive statistics, exploratory factors, reliability, correlation, and confirmatory factors, as well as the verification of the structural equation model. The results of the study are as follows: first, employee support evaluation in the beauty and cosmetics industry workers was negatively correlated to job stress. Second, employee support evaluation showed a negative relationship with turnover intentions. Third, job stress was found to have a positive relationship with turnover intention.This study suggests that, in order to reduce the turnover intentions of beauty and cosmetics industry workers, it is necessary for employers to make efforts to manage employees' job autonomy, support evaluation, and stress levels.

• Computers and Concrete
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• v.29 no.6
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• pp.375-391
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• 2022

This paper examined the impact of the cross-sectional structure on the structural results under different loading conditions of reinforced concrete (RC) members' management limited in Carbon Fiber Reinforced Polymers (CFRP). The mechanical properties of CFRC was investigated, then, totally 32 samples were examined. Test parameters included the cross-sectional shape as square, rectangular and circular with two various aspect rates and loading statues. The loading involved concentrated loading, eccentric loading with a ratio of 0.46 to 0.6 and pure bending. The results of the test revealed that the CFRP increased ductility and load during concentrated processing. A cross sectional shape from 23 to 44 percent was increased in load capacity and from 250 to 350 percent increase in axial deformation in rectangular and circular sections respectively, affecting greatly the accomplishment of load capacity and ductility of the concentrated members. Two Artificial Intelligence Models as Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) were used to estimating the tensile and flexural strength of specimen. On the basis of the performance from RMSE and RSQR, C-Shape CFRC was greater tensile and flexural strength than any other FRP composite design. Because of the mechanical anchorage into the matrix, C-shaped CFRCC was noted to have greater fiber-matrix interfacial adhesive strength. However, with the increase of the aspect ratio and fiber volume fraction, the compressive strength of CFRCC was reduced. This possibly was due to the fact that during the blending of each fiber, the volume of air input was increased. In addition, by adding silica fumed to composites, the tensile and flexural strength of CFRCC is greatly improved.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.