• Journal of Communications and Networks
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• 제11권6호
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• pp.544-555
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• 2009

This work continues a trend of developments aimed at exploiting the physical layer of the open systems interconnection (OSI) model to enhance wireless network security. The goal is to augment activity occurring across other OSI layers and provide improved safeguards against unauthorized access. Relative to intrusion detection and anti-spoofing, this paper provides details for a proof-of-concept investigation involving "air monitor" applications where physical equipment constraints are not overly restrictive. In this case, RF fingerprinting is emerging as a viable security measure for providing device-specific identification (manufacturer, model, and/or serial number). RF fingerprint features can be extracted from various regions of collected bursts, the detection of which has been extensively researched. Given reliable burst detection, the near-term challenge is to find robust fingerprint features to improve device distinguishability. This is addressed here using wavelet domain (WD) RF fingerprinting based on dual-tree complex wavelet transform (DT-$\mathbb{C}WT$) features extracted from the non-transient preamble response of OFDM-based 802.11a signals. Intra-manufacturer classification performance is evaluated using four like-model Cisco devices with dissimilar serial numbers. WD fingerprinting effectiveness is demonstrated using Fisher-based multiple discriminant analysis (MDA) with maximum likelihood (ML) classification. The effects of varying channel SNR, burst detection error and dissimilar SNRs for MDA/ML training and classification are considered. Relative to time domain (TD) RF fingerprinting, WD fingerprinting with DT-$\mathbb{C}WT$ features emerged as the superior alternative for all scenarios at SNRs below 20 dB while achieving performance gains of up to 8 dB at 80% classification accuracy.

• Smart Structures and Systems
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• 제4권2호
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• pp.209-220
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• 2008

A methodology for the seismic vulnerability assessment of historical monuments is presented in this paper. The ongoing work has been conducted in Tunisia within the framework of the FP6 European Union project (WIND-CHIME) on the use of appropriate modern seismic protective systems in the conservation of Mediterranean historical buildings in earthquake-prone areas. The case study is the five-century-old Zaouia of Sidi Kassem Djilizi, located downtown Tunis, the capital of Tunisia. Ambient vibration tests were conducted on the case study using a number of force-balance accelerometers placed at selected locations. The Enhanced Frequency Domain Decomposition (EFDD) technique was applied to extract the dynamic characteristics of the monument. A 3-D finite element model was developed and updated to obtain reasonable correlation between experimental and numerical modal properties. The set of parameters selected for the updating consists of the modulus of elasticity in each wall element of the finite element model. Seismic vulnerability assessment of the case study was carried out via three-dimensional time-history dynamic analyses of the structure. Dynamic stresses were computed and damage was evaluated according to a masonry specific plane failure criterion. Statistics on the occurrence, location and type of failure provide a general view for the probable damage level and mode. Results indicate a high vulnerability that confirms the need for intervention and retrofit.

• Asian Pacific Journal of Cancer Prevention
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• 제16권18호
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• pp.8351-8358
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• 2016

Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

• Journal of Power Electronics
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• 제15권1호
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• pp.216-226
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• 2015

Grid synchronization is one of the key techniques for the grid-connected power converters used in distributed power generation systems. In order to achieve fast and accurate grid synchronization, a new phase locked loop (PLL) is proposed on the basis of the complex filter matrixes (CFM) orthogonal signal generator (OSG) crossing-decoupling method. By combining first-order complex filters with relation matrixes of positive and negative sequence voltage components, the OSG is designed to extract specific frequency orthogonal signals. Then, the OSG mathematical model is built in the frequency-domain and time-domain to analyze the spectral characteristics. Moreover, a crossing-decoupling method is suggested to decouple the fundamental voltage. From the eigenvalue analysis point of view, the stability and dynamic performance of the new PLL method is evaluated. Meanwhile, the digital implementation method is also provided. Finally, the effectiveness of the proposed method is verified by experiments under unbalanced and distorted grid voltage conditions.

• 한국IT서비스학회지
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• 제8권1호
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• pp.203-215
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• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Asia-Pacific Journal of Atmospheric Sciences
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• 제54권4호
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• pp.527-544
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• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.

• 한국전자파학회논문지
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• 제10권7호
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• pp.1095-1103
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• 1999

현재 helix와 monopole로 구성되는 안테나를 갖는 수납형 전화기(retractble phone)가 셀룰라 이동통신에서 가장 널리 사용되고 있다. 그러나 안테나의 monopole의 길이가 약 $\lambda$/4이므로, 강한 복사 전기장이 전화기를 사용하는 인체 두부의 외이 주변에 주로 분포한다. 이러한 전기장 분포는 두부 내에 매우 높은 국부 SAR(specific abs$\alpha$ption rate)을 야기한다. 본 논문은 이동통신단말기의 안테나 배치가 반대인 전화기 형상에 대한 두부 내 전자파 흡수율을 기존의 단말기 형상의 것과 비교, 고찰한다. 이것은 단말기 옴체의 상부가 아닌 바닥 에 안테나를 배치하는 것이다. 인체와 단말기 모델을 포함하는 계산 공간의 시간-평균 전자기장 분포를 얻기 위해 시간영역 유한차분( FDTD) 기법을 사용하였다. 그리고 SAR 분포와 국부 SAR 값이 시간-명균 전기장 분포로부터 계산되었다. 실제 상황을 고려하기 위해 해부학적 인체 두부 모델과 근사된 사용자 손이 고려되었 다. 분석된 데이터는 안테나의 이 같은 배치가 인체 두부 내에 국부 SAR을 상당히 감소시킴을 보인다.

• 지능정보연구
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• 제17권4호
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• pp.213-226
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• 2011

글로벌 공급사슬 환경에서 글로벌하게 분산 조달, 생산, 유통하게 됨에 따라 전체 공급사슬의 스케줄을 최적화하기 위해서 공급사슬상의 개별 기업 혹은 공장의 스케줄링 최적화뿐만 아니라 각 개별 기업 혹은 공장의 스케줄을 긴밀하게 연계하는 것이 필요하게 되었다. 이는 경쟁과 협력을 동시에 하는 개별 기업 혹은 공장을 개별 에이전트로 보고 각 에이전트간 커뮤니케이션을 통해 개별 에이전트가 관할하는 스케줄러의 스케줄을 조정함으로써 가능해진다. 하지만 전통적인 스케줄링 연구는 개별 스케줄러의 최적화에 집중되어 있고, 에이전트 연구는 스케줄링 도메인에 적용한 예가 제한적이며 이 예도 개별 스케줄러 내의 최적화에 적용하거나 실제 현장 문제가 아닌 실험실 문제 수준에 그치고 있다. 따라서 본 연구에서는 전체 글로벌 공급사슬 스케줄의 최적화를 위해 개별 기업 혹은 공장 스케줄러의 스케줄링을 연계하는 경쟁협력 스케줄링을 위한 에이전트 기반 플랫폼을 구축하였다. 글로벌 공급사슬에서 경쟁협력 스케줄링을 위한 에이전트 기반 플랫폼을 구축하기 위해 첫째, 경쟁협력 스케줄링 분류 체계를 확립하고, 둘째, 경쟁협력 스케줄링을 위한 에이전트를 설계하고, 셋째, 경쟁협력 스케줄링을 위한 지식기반 의사결정 모델을 개발한 후, 넷째 조선산업에 적용 가능한 프로토타입 시스템을 개발했다. 이를 통해 글로벌 공급사슬상의 전체 스케줄의 품질과 에이전트간 커뮤니케이션의 노력에 대한 균형점을 찾을 수 있다. 이를 통해 공급사슬내 개별 기업 혹은 공장의 부분 최적화를 극복할 수 있는 대안을 제시할 것으로 기대한다.

• 한국BIM학회 논문집
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• 제13권3호
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• 대한간호학회지
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• 제41권4호
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• pp.471-480
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• 2011

Purpose: The purpose of this study was to evaluate the effectiveness of the Permission, Limited Information, Specific Suggestions, Intensive Therapy (PLISSIT) model sexual program on female sexual function for women with gynecologic cancer. Methods: The integrative 6-hr (two hours per session) program reflecting physical and psychosocial aspects of women's sexuality was developed based on Annon's PLISSIT model. Participants were 61 women with cervical, ovarian, or endometrial cancer. Of them, 29 were assigned to the experimental group and 32 to the control group. The women completed the Female Sexual Function Index (FSFI) including sexual desire, arousal, lubrication, orgasm, satisfaction, and pain. Independent t-test and repeated measured ANOVA were used to test the effectiveness of the program. Results: Significant group differences were found on FSFI sub-domain scores including sexual desire, arousal, lubrication, orgasm, and satisfaction but not pain. Significant time differences were found on all domains except for pain in the experimental group repeated measured ANOVA. Conclusion: The results indicate that the three-week PLISSIT model sexual program is effective in increasing sexual function for women with gynecologic cancer. Nurses may contribute to improving women's sexual function by utilizing the program. Strategies to relieve sexual pain need to be considered for greater effectiveness of the program.