• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.467-480
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• 2022

This paper aimed to explore research trends for the conceptualization of IT humanities. Reflecting domestic and international references which focused on the possibility of the integration of digital technology and humanities, the authors examined the beginning, background, and relevant concepts of IT humanities to figure out the meaning and the research trends. In addition, using the search word "IT humanities," the authors analyzed network topics of the keywords retrieved from 1,566 KCI and 64 SCI journal articles published since 2001. The concept of IT humanities in the previous studies has tended to associate with competencies that allow considering various fields of IT based on the lens of humanities perspectives. The result of the topic modeling revealed four groups as fields to be integrated with IT humanities, methods of implementation, connections of literature or culture, and creations of IT humanities. Instead of instrumentalization or merger by one stance of IT or humanities, it is imperative to collaboratively work for the generation of a new viewpoint through mutual respect of disciplines.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.95-107
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• 2023

Purpose: The statistical analysis of point processes on linear networks is a recent area of research that studies processes of events happening randomly in space (or space-time) but with locations limited to reside on a linear network. For example, traffic accidents happen at random places that are limited to lying on a network of streets. This paper applies techniques developed for point processes on linear networks and the tools available in the R-package spatstat to estimate the intensity of traffic accidents in Leon County, Florida. Methods: The intensity of accidents on the linear network of streets is estimated using log-linear Poisson models which incorporate cubic basis spline (B-spline) terms which are functions of the x and y coordinates. The splines used equally-spaced knots. Ten different models are fit to the data using a variety of covariates. The models are compared with each other using an analysis of deviance for nested models. Results: We found all covariates contributed significantly to the model. AIC and BIC were used to select 9 as the number of knots. Additionally, covariates have different effects such as increasing the speed limit would decrease traffic accident intensity by 0.9794 but increasing the number of lanes would result in an increase in the intensity of traffic accidents by 1.086. Conclusion: Our analysis shows that if other conditions are held fixed, the number of accidents actually decreases on roads with higher speed limits. The software we currently use allows our models to contain only spatial covariates and does not permit the use of temporal or space-time covariates. We would like to extend our models to include such covariates which would allow us to include weather conditions or the presence of special events (football games or concerts) as covariates.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.243-252
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• 2023

Satellite imageries are at a greatest importance for land cover examining. Numerous studies have been conducted with satellite images and uses semantic segmentation techniques to extract information which has higher altitude viewpoint. The device which is taking these images must employee wireless communication links to send them to receiving ground stations. Wireless communications from a satellite are inevitably affected due to transmission errors. Evidently images which are being transmitted are distorted because of the information loss. Current semantic segmentation techniques are not made for segmenting distorted images. Traditional image enhancement methods have their own limitations when they are used for satellite images enhancement. This paper proposes an auto-encoder based image pre-enhancing method for satellite images. As a distorted satellite images dataset, images received from a real radio transmitter were used. Training process of the proposed auto-encoder was done by letting it learn to produce a proper approximation of the source image which was sent by the image transmitter. Unlike traditional image enhancing methods, the proposed method was able to provide more applicable image to a segmentation model. Results showed that by using the proposed pre-enhancing technique, segmentation results have been greatly improved. Enhancements made to the aerial images are contributed the correct assessment of land resources.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.259-271
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• 2010

It is inevitable that personal privacy will be one of the most significant pressure points for most of the 2000s. Information privacy has been called one of the most important ethical issues in information age. It has become apparent that organizational practices, individuals' perceptions of these practices, and societal responses are very closely related in many ways. However, unfortunately, researches attempting to develop and validate an instrument that identifies and measures the primary dimensions of individuals' concerns about organizational information privacy practices were scarce. Based on a number of preliminary studies, this study tried to develop and validate an Korean organization oriented measurement instrument. This instrument is expected to be used as useful guide lines for the managers who are responsible for IT/IS ethical issues.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.127-135
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• 2023

Nowadays, the number of patients committing suicide due to depression and stress is rapidly increasing. In addition, if stress and depression last for a long time, they are dangerous factors that can cause heart disease, brain disease, and high blood pressure. However, no matter how modern medicine has developed, it is a very difficult situation for patients with depression and heart disease without special drugs or treatments. Therefore, in many countries around the world, studies are being actively conducted to determine patients at risk of depression and patients at risk of suicide at an early stage using electrocardiogram, oxygen saturation, and brain wave analysis functions. In this paper, in order to analyze these problems, a computer simulation was performed to determine heart disease risk patients by establishing heart disease hypothesis data. In particular, in order to improve the predictive rate of heart disease by more than 10%, a simulation using fuzzy inference was performed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.609-616
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• 2023

In a wireless network environment, since sensors are not always connected to power, the life of a battery, which is an energy source supplied to sensors, is limited. Therefore, various studies have been conducted to extend the network life, and a layer-based routing protocol, LEACH(: Low-energy Adaptive Clustering Hierarchy), has emerged for efficient energy use. However, the LEACH protocol, which transmits fused data directly to the sink node, has a limitation in that it consumes as much energy as the square of the transmission distance when transmitting data. To improve these limitations, this paper proposes an algorithm that can minimize the transmission distance with multi-hop transmission where cluster heads are chained between cluster heads through relative distance calculation from sink nodes in every round.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.401-411
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• 2023

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.365-376
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• 2023

Pig breeding management directly contributes to the profitability of pig farms, and pregnancy diagnosis is an important factor in breeding management. Therefore, the need to diagnose pregnancy in sows is emphasized, and various studies have been conducted in this area. We propose a computer-aided diagnosis system to assist livestock farmers to diagnose sow pregnancy through ultrasound. Methods for diagnosing pregnancy in sows through ultrasound include the Doppler method, which measures the heart rate and pulse status, and the echo method, which diagnoses by amplitude depth technique. We propose a method that uses deep learning algorithms on ultrasonography, which is part of the echo method. As deep learning-based classification algorithms, Inception-v4, Xception, and EfficientNetV2 were used and compared to find the optimal algorithm for pregnancy diagnosis in sows. Gaussian and speckle noises were added to the ultrasound images according to the characteristics of the ultrasonography, which is easily affected by noise from the surrounding environments. Both the original and noise added ultrasound images of sows were tested together to determine the suitability of the proposed method on farms. The pregnancy diagnosis performance on the original ultrasound images achieved 0.99 in accuracy in the highest case and on the ultrasound images with noises, the performance achieved 0.98 in accuracy. The diagnosis performance achieved 0.96 in accuracy even when the intensity of noise was strong, proving its robustness against noise.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.267-274
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• 2023

There is a problem that the size of the dataset is insufficient due to the limitation of the collection of the medical image public data, so there is a possibility that the existing studies are overfitted to the public dataset. In this paper, we compare the performance of eight (Unet, X-Net, HarDNet, SegNet, PSPNet, SwinUnet, 3D-ResU-Net, UNETR) medical image semantic segmentation models to revalidate the superiority of existing models. Anatomical Tracings of Lesions After Stroke (ATLAS) V1.2, a public dataset for stroke diagnosis, is used to compare the performance of the models and the performance of the models in ATLAS V2.0. Experimental results show that most models have similar performance in V1.2 and V2.0, but X-net and 3D-ResU-Net have higher performance in V1.2 datasets. These results can be interpreted that the models may be overfitted to V1.2.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.21-38
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• 2023

An attempt has been made in this article to discuss the fundamentals of technical analysis of the stock market. A retail investor or trader may not have the wherewithal to source that kind of information. Technical analysis requires a candlestick chart only. Most of the brokers in India provide charting solutions as well. Studying the price action of a security or commodity or Forex generally indicates a price pattern. Prices react at certain levels and widely known as support and resistance levels. Since whatever is happening with the price of the security is considered to be a part of a pattern or cycle which has already played out sometime in the past, these studies help a keen technical analyst to identify with certain probability, the future movement of the price. Study of the candlestick patterns, price action, volumes and indicators offer the opportunities to identify a high probability trade with probable target and a stop loss. A trader or investor can take high probability trade or position and control only her losses.