• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.11-20
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• 2024

Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.303-309
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• 2004

In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

• Parasites, Hosts and Diseases
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• v.57 no.6
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• pp.681-690
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• 2019

The infection status of digenetic trematode metacercariae (DTM) was investigated in fishes from coastal lakes in Gangwon-do, the Republic of Korea (Korea). All fishes collected in 5 lakes were examined with the artificial digestion method. More than 10 species, i.e., Metagonimus spp., Pygidiopsis summa, Centrocestus armatus, Metorchis orientalis, M. taiwanensis, Clinostomum complanatum, Echinostoma spp., Stictodora spp., Diplostomum sp. and Diplostomid No. 1. by Morita (1960), of DTM were detected in fishes from 5 coastal lakes in Gangwon-do. Metagonimus spp. metacercariae were found in 52 (41.3%) out of 126 sea rundace, Tribolodon hakonensis, from 5 lakes, and their density was 14.6 per fish infected. P. summa metacercariae were detected in 48 (84.2%) out of 57 mullets from 5 lakes, and their density was 316 per fish infected. C. armatus metacercariae were detected in 7 (14.6%) T. hakonensis and 3 (15.0%) Tridentiger brevispinis from Hyang-ho, and 5 (19.2%) Acanthogobius flavimanus from Gyeongpo-ho. Stictodora spp. metacercariae were found in 4 fish species, i.e., Tridentiger obscurus, Tridentiger trigonocephalus, Chelon haematocheilus, and Acanthogobius lactipes, from Gyeongpo-ho. Total 15 C. complanatum metacercariae were detected in 2 (9.1%) crucian carp, Carassius auratus, from Songji-ho. M. taiwanensis metacercariae were found in T. hakonensis from Hyang-ho and Gyeongpo-ho and in Pseudorasbora parva from Gyeongpo-ho. Total 11 M. orientalis metacercariae were detected in 3 (6.3%) T. hakonensis from Hyang-ho. From the above results, it was confirmed that various species of DTM are infected in fishes from coastal lakes in Gangwon-do, Korea.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.25-34
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• 2013

In this paper, we propose an activity-performer bipartite matrix generation algorithm for analyzing workflow-supported human-resource affiliations in a workflow model. The workflow-supported human-resource means that all performers of the organization managed by a workflow management system have to be affiliated with a certain set of activities in enacting the corresponding workflow model. We define an activity-performer affiliation network model that is a special type of social networks representing affiliation relationships between a group of performers and a group of activities in workflow models. The algorithm proposed in this paper generates a bipartite matrix from the activity-performer affiliation network model(APANM). Eventually, the generated activity-performer bipartite matrix can be used to analyze social network properties such as, centrality, density, and correlation, and to enable the organization to obtain the workflow-supported human-resource affiliations knowledge.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.15-21
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• 2018

In this study, we try to detect anomalies on the network intrusion detection system by learning only one class. We use KDD CUP 1999 dataset, an intrusion detection dataset, which is used to evaluate classification performance. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve relatively high classification efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data. In this study, we use one class classifiers based on support vector machines and density estimation to detect new unknown attacks. The test using the classifier based on density estimation has shown relatively better performance and has a detection rate of about 96% while maintaining a low FPR for the new attacks.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.905-912
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• 2022

Virtual reality, one of the core technologies of the 4th industrial revolution, is entering a new phase with the spread of low-cost wearable devices represented by Oculus. In the case of disaster evacuation drills, where practical training is almost impossible due to the risk of accidents, virtual reality is becoming a new alternative that enables effective training. In this paper, we propose a smoke modeling method that can be applied to fire evacuation drills implemented with virtual reality technology. In the event of a fire, smoke spreads along the aisle, and the density of the smoke changes over time. The proposed method models the smoke by applying a procedural function that can reflect the density of smoke calculated through simulation to the model in real-time. Implementation results in the background of the factory show that the proposed method produces models that can express the smoke according to the user's movement.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.493-499
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• 2022

This paper reports the results of the eruption of a volcano on Jeju Island at a certain rate, and the tumulus formed after the eruption and the basalt that erupted from the middle of Mt. Halla washed up to the sea. We analyzed the speed when basalt underground magma breaks through the neutral zone on the ground with an absolute temperature of about 1000K and explodes at an absolute temperature of 1200K at an altitude of 1950m. The density of combustion gas becomes smaller than the surrounding air due to the plume volcanic eruption, which is the heat flow of the flame column due to buoyancy, and buoyancy is generated and an updraft is formed. Flame pillars are classified as continuous, intermittent, and buoyant flame zones. As the speed of the flame pillar of Mt. Halla (1950m) falls from the highest point it has risen, potential energy is converted into kinetic energy and is caused by the flow of fluid, solving these two equations equal, the volcanic eruption velocity is 87.5 m/s. At this time, the density of magma is inversely proportional to the temperature. Geomunoreum (456m) had an explosion speed of 42.6m/s.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.253-255
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• 2022

Thanks to the 4th industrial revolution and the development of various communication media, technologies such as artificial intelligence and automation are being grafted into industrial sites in various fields, and accordingly, the importance of data processing is increasing. Image noise removal is a pre-processing process for image processing, and is mainly used in fields requiring high-level image processing technology. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and noise removal in a special area. In this paper, we propose a switching mask filter based on the noise intensity to preserve the detailed image information during the impulse noise removal process. The proposed filter algorithm obtains the final output by switching to the extended mask when it is determined that the density is higher than the reference value when noise is determined in the area designated as the filtering mask. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1109-1114
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• 2003

In this paper, task control architecture is proposed for a mobile robot with behaviors based on cognition theory to endow the robot intelligence. In the task control architecture, task manager is introduced especially for the management of computational resource. The management is based on classical RMS (Rate Monotonic Strategy), but with online rate modulation strategy. The rate modulation is performed using the value variances of behavior execution for the task. Because the values are based on natively uncertain sensor information, they are modeled using PDF (probability Density Function). As a rate modulation process, the range of the rate modulation is defined firstly by real-time constraints of RMS and discrete control stability of behaviors. With the allowable range, rate modulations are performed considering harmonic bases to maintain utilization bound without decrease. To evaluate the efficiency of the proposed rate modulation strategy, a simulation test is performed to compare the efficiency between the control architecture with the proposed strategy and previous one. A performance index with the formalization of propensity of resource allocation is proposed and utilized for the simulation test. To evaluate the appropriateness of the performance index, the performance index is compared with practical one through a practical simulation test.