• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.559-562
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• 2008

IT와 건설 산업간 융합의 대표적 사례로서 유비쿼터스 도시의 개념이 도입된 이후 현재 여러 지자체에서 u-City 구축이 확산되고 있다. 한편, u-City에 구축된 첨단 인프라의 활용성을 극대화하여야 한다는 부담감이 다양한 u-서비스에 대한 고민으로 이어 졌으며, 이로부터 u-디바이스간 협업의 개념이 파생되었다. u-디바이스간협업의 예로는 공공장소에서의 개인 미디어 재생과 같은 응용이 자주 거론되고 있다. 그러나 음향 미디어의 재생에 있어서는 그 재생의 품질이 서비스의 만족도에 중요한 역할을 할 것이다. 이에 본고에서는 하이파이 재생 시스템의 모델로부터 고충실도 음향 재생을 위한 기능요소를 추출하고, 이를 기반으로 하이파이 응용을 위한 u-서비스 제공 구조를 제시하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1154-1159
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• 2013

Now we are facing various threats as side effects against the growth of smartphone markets. Malicious codes such as mobile worms may bring about disclosures of personal information and confusions to upset a national wireless backbone. In this paper, we examine the existed spreading models and try to describe the correct spread of mobile worms on smartphones. We also analyze the spreading effects, and simulate bluetooth, MMS and Wi-Fi worms by various experiments.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.73-77
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• 2023

As the DeFi market continues to expand, fraudulent activities using smart contracts have also increased. HoneyPot and Ponzi schemes are well-known frauds that exploit smart contracts. While several studies have demonstrated the potential to detect smart contracts implementing these scams, there has been a lack of research focusing on simultaneously detecting both types of fraud. This paper addresses this gap by harnessing artificial intelligence to conduct experiments for the detection of both HoneyPot and Ponzi schemes. The study employs the CNN (Convolutional Neural Network) model, commonly used for malware detection. To effectively utilize CNN, the bytecode of smart contracts is transformed into visual representations. The experimental results showcase a recall rate of 0.89 and an F1 score of 0.85, indicating promising detection capabilities.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.159-162
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• 2024

This paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence models generated from video information, worker's biometric information, and the safety rule to estimate the risk index. We practically designed the proposed SAP architecture by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, Hue, ELK (Elasticsearch, Logstash, Kibana), Ansible, etc., and confirmed that it worked well with safety mobility gateways for providing various safety applications.

• Annual Conference of KIPS
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• 2024.05a
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• pp.137-140
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• 2024

가상 및 증강현실(VR/AR), 원격 제어, 산업 자동화를 위한 실시간 애플리케이션이 증가함에 따라 무선 통신 네트워크의 처리량과 지연시간 성능이 중요해졌다. 이에 따라 Wi-Fi 8 에서는 초고신뢰 (Ultra-High Reliable, UHR)을 목표로 표준화가 진행 중이며 다수의 AP가 협력하여 데이터를 전송하는 다중 AP 협력 기법이 핵심 기술로 논의되고 있다. 하지만 기존의 다중 AP 협력 환경에서 협력 전송을 위한 제어 정보로 인한 간섭 증가와 OBSS(Overlapped Basic Service Set) 간섭 문제를 고려하지 못하고 있다. 따라서 본 논문에서는 효율적인 다중 AP 협력 전송을 위한 단순화된 채널 관리 방법(Simplified Channel Management Mechanism, SCMM)을 제안한다. 실험 결과에 따르면, SCMM 이 종래모델 대비 처리량은 평균 21.23% 증가했고, 지연시간은 평균 51.02% 감소했다.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.82-90
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• 2019

The Box-Benhken Design (BBD) model of response surface methodology (RSM) was used to optimize fluoride adsorption conditions in water using a 350℃ thermally treated cow bone. Water temperature, pH, contact time, and initial fluoride concentration were selected as variables to be optimized. A second order reaction equation was obtained from a Box-Behnken Design DoE experimental matrix of 29 runs. R² and p-value of the model were 0.9242 and <0.0001, respectively, indicating that the selected variables had a very substantial effect on the adsorption results. The optimized adsorption capacity of the thermally synthesized bone char was estimated to be 6.46 mgF/g at the water temperature of 39.68℃, pH 6.25, contact time of 88.81 minutes and an initial fluorine concentration of 14.64 mgF/L.

• Journal of Welding and Joining
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• v.13 no.2
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• pp.68-81
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• 1995

This paper presents an analytical solution to predict the transient temperature distribution in fillet arc welding. The analytical solution is obtained by solving a transient three -dimensional heat conduction equation with convection boundary conditions on the surfaces of an infinite plate with finite thicknesses, and mapping an infinite plate onto the fillet weld geometry with energy equation. The electric arc heat input on fillet weld and on infinite plate is assumed to have a traveling bivariate Gaussian distribution. To check the validity of the solution, GTA and FCA welding experiments were performed under various welding conditions. The actual isotherms of the weldment cross - sections at various distances from the arc start point are compared with those of simulation result. As the result shows a satisfactory accuracy, this analytical solution can be used to predict the transient temperature distribution in the fiIIet weld of finite thickness under a moving bivariate Gaussian distributed heat source. The simplicity and short calculation time of the analytical solution provides rationales to use the analytical solution for modeling the welding control systems or for an optimization tool of welding process parameters.

• TTA Journal
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• s.132
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• pp.28-33
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• 2010

지난 10년 동안 인터넷은 우리 생활에 가히 혁명적인 영향을 끼쳐 왔습니다. 그러나 지난 10년이 인터넷 혁명의 시대였다고 한다면 향후 10년간은 모바일 혁명의 시대가 될 것이라고들 이야기합니다. 모바일 혁명 시대의 핵심에는 스마트폰이 자리하고 있습니다. 작년 이맘때쯤 국내에 아이폰이 도입되면서 국내에도 불붙기 시작한 스마트폰 광풍은 모든 비즈니스와 우리 생활에서 혁명을 예고하고 있습니다. 스마트폰 플랫폼 개발업체, 이동통신업체, 단말 기업체, 콘텐츠 개발자 등 다양한 플레이어들이 모바일 생태계 속에서 새로운 비즈니스 모델들을 탄생시키고 있고, 개인들의 생활속에서도 스마트폰은 깊숙이 자리매김하고 있습니다. 이처럼 우리 산업 전반과 삶에 새로운 변화를 일으키고 있는 스마트폰은 과연 안전한 것일까요? 스마트폰은 다양한 앱이 구동될 수 있는 개방형 플랫폼을 가지고 있고, 앱스토어를 통해 누구나 앱 사용자이자 제공자도 될 수 있습니다. 또한, 3G뿐만 아니라 Wi-Fi, Bluetooth, PC Sync 등 다양한 네트워킹 기능을 제공해 줍니다. 이러한 개방성을 바탕으로 스마트폰은 급격하게 성장하고 있지만 개방성은 악성코드 감염, 해킹, 프라이버시 침해 등 역기능이 발생할 수 있는 여건도 마련해 주고 있습니다. 실제로 스마트폰 해킹 사고는 국내외에서 빈번하게 발생되고 있고 그 피해가 증가하고 있는 추세입니다. 올 4월에 국내에서도 첫 스마트폰용 악성코드가 발견되었고, 전 세계적으로 524건의 모바일 악성코드가 발견되었습니다. 이처럼 스마트폰 해킹은 현실화되어 우리를 위협하고 있습니다. 본 특집에서는 스마트폰 보안과 관련한 정부의 정책방향, 보안위협과 사례, 프라이버시 이슈, 보안시장 전망, 국내외 표준화 동향, 전문인력 양성계획 등을 살펴보도록 하겠습니다.

• Journal of Environmental Science International
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• v.21 no.6
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• pp.695-704
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• 2012

The application of disinfection models on the plasma process was investigated. Nine empirical models were used to find an optimum model. The variation of parameters in model according to the operating conditions (first voltage, second voltage, air flow rate, pH) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Ralstonia Solanacearum which cause wilt in tomato plantation. Optimum disinfection models were chosen among the nine models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum model was shown as Weibull+talil model followed by Log-linear+ Shoulder+Tail model. Two models were applied to the experimental data according to the variation of the operating conditions. In Weibull+talil model, Log10($N_o$), Log10($N_{res}$), ${\delta}$ and p values were examined. And in Log-linear+Shoulder+Tail model, the Log10($N_o$), Log10($N_{res}$), $k_{max}$, Sl values were calculated and examined.