• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.359-365
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• 2022

Scholars are paying increasingly close attention to brain research and the creation of biological neural networks, artificial neural networks, artificial intelligence, neurochips, brain-computer interfaces, prostheses, new research instruments and methods, methods of treatment, as well as the prevention of neurodegenerative diseases based on these data. The authors of the study propose their hypothesis on the understanding of the phenomenon of consciousness that answers questions concerning the criteria of consciousness, its localization, and principles of operation. In the study of the hard problem of consciousness, the philosophical and scientific categories of consciousness, and prominent hypotheses and theories of consciousness, the authors distinguish "the area of the conscious mind", which encompasses several states of consciousness united by the phenomenon of integrated consciousness. According to the authors, consciousness is a kind of executor of the phenomenological idea of the "chalice", so the search for it should be conducted deeper than the processes in the power of thought consciousness and transconsciousness, to which integrated consciousness can act as a lever. However, integrated consciousness may have the capacity to transcend into lower states of consciousness, which requires further study.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Journal of Korean Association for Spatial Structures
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• v.23 no.4
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• Smart Structures and Systems
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• v.33 no.6
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• pp.449-463
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• 2024

Automated crack detection is crucial for structural health monitoring and post-earthquake rapid damage detection. However, realizing high precision automatic crack detection in the absence of corresponding manual labeling presents a formidable challenge. This paper presents a novel crack segmentation transfer learning method and a novel crack segmentation model called Swin-CrackFormer. The proposed method facilitates efficient crack image style transfer through a meticulously designed data preprocessing technique, followed by the utilization of a GAN model for image style transfer. Moreover, the proposed Swin-CrackFormer combines the advantages of Transformer and convolution operations to achieve effective local and global feature extraction. To verify the effectiveness of the proposed method, this study validates the proposed method on three unlabeled crack datasets and evaluates the Swin-CrackFormer model on the METU dataset. Experimental results demonstrate that the crack transfer learning method significantly improves the crack segmentation performance on unlabeled crack datasets. Moreover, the Swin-CrackFormer model achieved the best detection result on the METU dataset, surpassing existing crack segmentation models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6A
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• pp.585-593
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• 2010

Geographic routing has been considered as an efficient, simple, and scalable routing protocol for wireless sensor networks since it exploits pure local location information instead of global topology information to route data packets. Geographic routing requires the sources nodes to be aware of the location of sinks. Most existing geographic routing protocols merely assume that source nodes are aware of the locations of sinks. How can source nodes get the locations of sinks was not addressed in detail. In this paper, we propose a sink location service via circle path for geographic routing in wireless sensor networks. In this scheme, a sink sends a Sink Location Announcement (SLA) message along a circle path, and a source node sends a Sink Location Query (SLQ) message along a straight path that certainly passes through the circle path. By this way we can guarantee the SLQ path and SLA path have at least one crossing point. The node located on the crossing point of the two paths informs the source node the sink location. This procedure can correctly work in any irregular profile sensor networks such as network that has holes or irregular shape by some rules. Simulation results show that our protocol is superior to other protocols in terms of energy consumption and control overhead.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.337-344
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• 2006

KVN simulation, which is focused on evaluating the impacts of KVN to geodetic VLBI network, was performed. The KVN is under construction with three radio telescopes VLBI system for radio astronomy and space geodesy. To distinguish the impacts of KVN on global and local scale networks, we designed two different sizes of VLBI networks, namely, KVN-Asia and KVN-Pacific. While the former consisted of Far East Asia region VLBI stations, the latter consisted of pacific region VLBT stations. The primary purpose of our simulation is quantitative evaluation of KVN impacts before and after the participation of KVN in the previous two virtual networks. We selected two different sets of parameters to be estimated in the simulation as indices of evaluating estimation precision: station coordinates and EOPs. The station coordinates are evaluating index for KVN-Asia and the EOPs are another evaluating index for KVN-Pacific. From the simulation results of comparisons between evaluating indexes, 50% and 20% of maximum improvements for KVN-Asia and KVN-Pacific were anticipated respectively. We expect that the space geodetic use of KVN will be focused on the several promising research fields which are proposed through the simulation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.896-905
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• 2010

The sensor networks can be used attractively for various application areas. Time synchronization is important for any Ubiquitous Sensor Networks (USN) systems. USN makes extensive use of synchronized time in many contexts for data fusion. However existing time synchronization protocols are available only for homogeneous sensor nodes of USN. It needs to be extended or redesigned in order to apply to the USN with heterogeneous sensor nodes. Because heterogeneous sensor nodes have different clock sources with the SinkNode of USN, it is impossible to be synchronized global time. In addition, energy efficiency is one of the most significant factors to influence the design of sensor networks, as sensor nodes are limited in power, computational capacity, and memory. In this paper, we propose specific time synchronization based on master-slave topology for the global time synchronization of USN with heterogeneous sensor nodes. The time synchronization master nodes are always able to be synchronized with the SinkNode. Then time synchronization master nodes enable time synchronization slave nodes to be synchronized sleep periods. The proposed master-slave time synchronization for heterogeneous sensor nodes of USN is also helpful for power saving by maintaining maximum sleep time.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.455-462
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• 2016

Wireless sensor networks have been researched to gather data about events on sensor fields from sources at sinks. Multipath routing is one of attractive approaches to reliably send data against the problem of frequent breakages on paths from sources to sinks due to node and link failures. As mobile events such as humans, animals, and vehicles are considered, sources may be continuously generated according to the movement of the mobile event. Thus, mobile events provide new challenging issue in multipath routing. However, the research on multipath routing mainly focus on both efficient multipath construction from sources to static sinks and fast multipath reconstruction against path breakages. Accordingly, the previous multipath routing protocols request each source continuously generated by a mobile event to construct individual multipath from the source to sinks. This induces the increase of multipath construction cost in the previous protocols in proportion to the number of source. Therefore, we propose efficient multipath routing protocol for supporting continuous sources generated by mobile events. In the proposed protocol, new source efficiently reconstructs its multipath by exploiting the existing multipath of previous sources. To do this, the proposed protocol selects one among three reconstruction methods: a local reconstruction, a global partial one, and a global full one. For a selection decision, we provide an analytical energy consumption cost model that calculates the summation of both the multipath reconstruction cost and the data forwarding cost. Simulation results show that the proposed protocol has better performance than the previous protocol to provide multipath routing for mobile events.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.2
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• pp.125-137
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• 2007

This paper proposes a new scheme to provide the location privacy of sources in Wireless Sensor Networks (WSNs). Because the geographical location of a source sensor reveals contextual information on an 'event' in WSN, anonymizing the source location is an important issue. Despite abundant research efforts, however, about data confidentiality and authentication in WSN, privacy issues have not been researched well so far. Moreover, many schemes providing the anonymity of communication parties in Internet and Ad-hoc networks are not appropriate for WSN environments where sensors are very resource limited and messages are forwarded in a hop-by-hop manner through wireless channel. In this paper, we first categorize the type of eavesdroppers for WSN as Global Eavesdropper and Compromising Eavesdropper. Then we propose a novel scheme which provides the anonymity of a source according to the types of eavesdroppers. Furthermore, we analyze the degree of anonymity of WSN using the entropy-based modeling method. As a result, we show that the proposed scheme improves the degree of anonymity compared to a method without any provision of anonymity and also show that the transmission range plays a key role to hide the location of source sensors.