• 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.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.561-568
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• 2021

In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movement speed in real time. CNN-based deep learning algorithms and conventional dense optical flows have a large consumption time, making it difficult to detect objects and estimate its movement speed in real time. In this paper, using a single camera image, fast object detection was performed using the YOLOv5 algorithm, a deep learning algorithm, and fast estimation of the speed of the object was performed by using a local dense optical flow modified from the existing dense optical flow based on the detected object. Based on this algorithm, we present a system that can predict the collision time and probability, and through this system, we intend to contribute to prevent tram accidents.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.479-488
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• 2022

In recent years, with the rapid development of machine learning technology, research utilizing machine learning has been actively conducted in fields such as cognition, reasoning and judgment, and action among various technologies constituting intelligent systems. In order to utilize this machine learning, it is indispensable to collect data for learning. However, the types of data generated vary according to the environment in which the data is generated, and the types and forms of data required are different depending on the learning model to be used for machine learning. Due to this, there is a problem that the existing data collection method cannot be reused in a new environment, and a specialized data collection module must be developed each time. In this paper, we propose a specification-based methology for data collection in artificial intelligence system to solve the above problems, ensure the reusability of the data collection method according to the data collection environment, and automate the implementation of the data collection function.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.83-90
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• 2023

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.8-16
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• 2023

In Japan, high-speed ground transportation service using linear motors at speeds of 500 km/h is scheduled to begin in 2027. To accommodate 5G services in trains, a subcarrier spacing frequency of 30 kHz will be used instead of the typical 15 kHz subcarrier spacing to mitigate Doppler effects in such high-speed transport. Furthermore, to increase the cell size of the 5G mobile system, multiple base station antennas will transmit identical downlink (DL) signals to form an expanded cell size along the train rails. In this situation, the forward and backward antenna signals are Doppler-shifted in opposite directions, respectively, so the receiver in the train may suffer from estimating the exact Channel Transfer Function (CTF) for demodulation. In a previously published paper, we proposed a channel estimator based on Delay and Doppler Profiler (DDP) in a 5G SISO (Single Input Single Output) environment and successfully implemented it in a signal processing simulation system. In this paper, we extend it to 2×2 MIMO (Multiple Input Multiple Output) with spatial multiplexing environment and confirm that the delay and DDP based channel estimator is also effective in 2×2 MIMO environment. Its simulation performance is compared with that of a conventional time-domain linear interpolation estimator. The simulation results show that in a 2×2 MIMO environment, the conventional channel estimator can barely achieve QPSK modulation at speeds below 100 km/h and has poor CNR performance versus SISO. The performance degradation of CNR against DDP SISO is only 6dB to 7dB. And even under severe channel conditions such as 500km/h and 8-path inverse Doppler shift environment, the error rate can be reduced by combining the error with LDPC to reduce the error rate and improve the performance in 2×2 MIMO. QPSK modulation scheme in 2×2 MIMO can be used under severe channel conditions such as 500 km/h and 8-path inverse Doppler shift environment.