• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.382-388
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• 2022

Satellite communication for high altitude platform stations (HAPS) and low earth orbit (LEO) systems suffer from dust and sand (DU&SA) storms in the desert regions such as Saudi Arabia. These attenuations have a distorting effect on signal fidelity at high frequency of operations. This results signal to noise ratio (SNR) to dramatically decreasing and leads to wireless transmission error. The main focus in this paper is to propose common relations between HAPS and LEO for the atmospheric impairments affecting the satellite communication networks operating above Ku-band crossing the propagation path. A double phase three dimensional relationship for HAPS and LEO systems is then presented. The comparison model present the analysis of atmospheric attenuation with specific focus on sand and dust based on particular size, visibility, adding gaseous effects for different frequency, and propagation angle to provide system operations with a predicted vision of satellite parameters' values. Skillful decision and control system (SD&CS) is proposed to control applied parameters that lead to improve satellite network performance and to get the ultimate receiving wireless signal under bad weather condition.

• 한국인공지능학회지
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• 제12권3호
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• pp.17-24
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• 2024

This study aims to derive a technology development roadmap in related fields by utilizing patent documents of financial technology. To this end, patent documents are extracted by dragging technical keywords from prior research and related reports on financial technology. By applying the TF-IDF (Term Frequency-Inverse Document Frequency) technique in the extracted patent document, which is a text mining technique, to the extracted patent documents, the Latent Dirichlet Allocation (LDA) algorithm was applied to identify the keywords and identify the topics of the core technologies of financial technology. Based on the proportion of topics by year, which is the result of LDA, promising technology fields and convergence fields were identified through trend analysis and similarity analysis between topics. A first-stage technology development roadmap for technology field development and a second-stage technology development roadmap for convergence were derived through network analysis about the technology data-based integrated management system of the high-dimensional payment system using RF and intelligent cards, as well as the security processing methodology for data information and network payment, which are identified financial technology fields. The proposed method can serve as a sufficient reason basis for developing financial technology R&D strategies and technology roadmaps.

• 한국지리정보학회지
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• 제4권4호
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• pp.61-71
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• 2001

오늘날 측량장비개발의 급속한 발전과 더불어 정밀도가 많이 향상되고 있고, 컴퓨터를 이용한 지형공간정보체계기술의 발달로 보다 정밀한 3차원 지형의 재현이 가능하게 되었다. 그런데 실제 현장에서 이루어지고 있는 면적 및 체적산출방법에 있어서는, 재래적인 측량방법인 평판측량을 통해서 지형을 만들어낸 후 구적기나 기타 다른 방법을 통해서 2차원 물량을 산출해 내고 거기에 일정량의 경사보정계수를 곱하여 3차원 물량을 산출하는 방법을 사용하고 있다. 본 연구에서는 재래적인 측량방법 및 물량산출방법에 대한 비효율성 및 비정밀성을 제시하고, 현대측량장비인 광파거리측량기와 GPS장비를 이용해서 불규칙삼각형방식과 격자형방식으로 측량을 실시하고, 두 측량데이터를 가지고 각각 방법에 따라 3차원 지형모델을 구축한 후 2차원 및 지표면적을 산출하였다. 그 후 재래적인 측량방법을 이용한 면적산출량을 기준으로 불규칙삼각형방식과 격자형방식으로 산출한 면적산출량을 비교 분석함으로써 보다 정밀하고 효율성이 높은 지표면적 산출방법을 제시하였다.

• 한국전자통신학회논문지
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• 제17권6호
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• pp.1129-1136
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• 2022

본 연구는 RSSI의 거리측정 방법이 외부 환경에 의해 쉽게 영향을 받아 위치 오차가 크다는 결점을 도출하였고 이 3차원 배치 환경에서 RSSI의 거리측정 노드에서 측정한 거리값을 최적화하는 문제에 대해 향상된 CA-PSO 알고리즘을 개선한 CA-PSO-BP 알고리즘을 제안하였다. 제안된 알고리즘은 3차원 무선센서네트워크(WSN) 공간에서 인식할 수 없는 노드를 설정할 수 있도록 하였다. 또한, CA-PSO를 BP 신경망에 응용하므로, 학습을 통해 BP 네트워크의 학습시간 단축과 알고리즘의 수렴 속도를 제고 할 수 있었다. 본 연구에서 제안한 알고리즘을 통해 네트워크의 위치의 정밀도를 현저(15%)하게 높일 수 있다는 것을 증명하였고 유의미한 결과를 얻을 수 있었다.

• 한국멀티미디어학회논문지
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• 제22권7호
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• pp.790-803
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• 2019

The effects of different heat treatments on the sensory characteristics of abalones are studied in this study. In this paper, the sensory evaluation of abalone samples under different heat treatment conditions is carried out, and the evaluation results are analyzed. The three-dimensional (3D) scanning and reverse engineering are used in tooth modeling of the sensory evaluation of abalone samples under different heat treatment conditions. Besides, the chewing movement models are simplified into three modes, including the cutting mode, compressing mode and grinding mode, which are simulated using finite element simulation. The elastic modulus of the abalone samples is obtained through the compression testing using a texture analyzer to distinguish their material properties under different heat treatments and to obtain simulated mechanical parameters. Finally, taking the mechanical parameters of the finite element simulation of abalone chewing as input and sensory evaluation parameters as the output, BP neural network is established in which the sensory texture evaluation model of abalone samples is obtained. Through verification, the neural network prediction model can meet the requirements of food texture evaluation, with an average error of 9.12%.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.354-366
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• 2020

This work mainly focuses on determination of the fully plastic J-integral solutions for welded center cracked plates subjected to remote tension loading. Detailed three-dimensional elasticeplastic Finite Element Analyses (FEA) were implemented to compute the fully plastic J-integral along the crack front for a wide range of crack geometries, material properties and weld strength mismatch ratios for 900 cases. According to the database generated from FEA, Back-propagation Neural Network (BPNN) model was proposed to predict the values and distributions of fully plastic J-integral along crack front based on the variables used in FEA. The determination coefficient R2 is greater than 0.99, indicating the robustness and goodness of fit of the developed BPNN model. The network model can accurately and efficiently predict the elastic-plastic J-integral for weld centerline crack, which can be used to perform fracture analyses and safety assessment for welded center cracked plates with varying strength mismatch conditions under uniaxial loading.

• Radiation Oncology Journal
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• 제36권4호
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• pp.276-284
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• 2018

Purpose: Traditionally, three-dimensional conformal radiation therapy (3D-CRT) is used for neoadjuvant chemoradiation in locally advanced rectal cancer. Intensity-modulated radiation therapy (IMRT) was later developed for more conformal dose distribution, with the potential for reduced toxicity across many disease sites. We sought to use the National Cancer Database (NCDB) to examine trends and predictors for IMRT use in rectal cancer. Materials and Methods: We queried the NCDB from 2004 to 2015 for patients with rectal adenocarcinoma treated with neoadjuvant concurrent chemoradiation to standard doses followed by surgical resection. Odds ratios were used to determine predictors of IMRT use. Univariable and multivariable Cox regressions were used to determine potential predictors of overall survival (OS). Propensity matching was used to account for any indication bias. Results: Among 21,490 eligible patients, 3,131 were treated with IMRT. IMRT use increased from 1% in 2004 to 22% in 2014. Predictors for IMRT use included increased N stage, higher comorbidity score, more recent year, treatment at an academic facility, increased income, and higher educational level. On propensity-adjusted, multivariable analysis, male gender, increased distance to facility, higher comorbidity score, IMRT technique, government insurance, African-American race, and non-metro location were predictive of worse OS. Of note, the complete response rate at time of surgery was 28% with non-IMRT and 21% with IMRT. Conclusion: IMRT use has steadily increased in the treatment of rectal cancer, but still remains only a fraction of overall treatment technique, more often reserved for higher disease burden.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• 한국전자파학회논문지
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• 제27권11호
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• pp.1012-1018
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• 2016

본 논문은 유한 차분 시간 영역(FDTD: Finite-Difference Time-Domain)법을 이용하여 낙뢰에 노출된 항공기와 같이 높은 도전성 물질로 구성된 구조체의 간접적 영향 분석을 위한 전자파 해석기법 연구를 수행하였다. 간접적 영향 분석을 위해 사용되는 낙뢰 파형은 매우 낮은 주파수 특성을 가지며, 알루미늄과 탄소섬유복합물질과 같이 높은 도전성 물질들로 구성된 구조체는 매우 짧은 표피 깊이를 가지고 있기 때문에 일반적인 3차원 FDTD법을 이용하여 해석을 수행할 경우, 매우 많은 메모리와 해석시간이 요구된다. 본 연구팀에서는 낙뢰 특성과 높은 도전율을 갖는 구조에 적합한 전자파 해석기법을 개발하였다. 개발된 해석 기법은 2차원 FDTD와 INBC(Impedance Network Boundary Condition) 알고리즘을 적용하였으며, 개발된 해석기법을 이용하여 낙뢰에 노출된 구조체의 간접적 영향을 분석하였다.

• 한국게임학회 논문지
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• 제16권3호
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• pp.109-116
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• 2016

교수자와 학습자가 원격에서 위치하는 원격교육시스템은 영상과 음성을 전달하는 직접적으로 방식으로 진행되어 왔다. 학습자의 흥미와 교육 효과를 얻기 위해서나 열악한 네트워크 환경을 극복하기 위해서, 컴퓨터 그래픽스를 응용한 다양한 방법이 시도되었다. 본 논문은 Kinect 기반의 3차원 애니메이션 제어 기술과 네트워크 게임 기술을 활용한 원격교육시스템의 설계와 구현에 대해서 기술한다. 이 논문에서 설계하고 구현한 원격교육시스템은 교육과 게임 기술이 결합한 좋은 예가 될 것이며, 향후 다양한 교육용 콘텐츠에 응용되기를 기대한다.