• 천문학회보
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• 제43권2호
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• pp.40.4-41
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• 2018

The current 'standard model' of cosmology provides a minimal theoretical framework that can explain the gaussian, nearly scale-invariant density perturbations observed in the CMB to the late time clustering of galaxies. However accepting this framework, requires that we include within our cosmic inventory a vacuum energy that is ~122 orders of magnitude lower than Quantum Mechanical predictions, or alternatively a new scalar field (dark energy) that has negative pressure. An alternative approach to adding extra components to the Universe would be to modify the equations of Gravity. Although GR is supported by many current observations there are still alternative models that can be considered. Recently there have been many works attempting to test for modified gravity using the large scale clustering of galaxies, ISW, cluster abundance, RSD, 21cm observations, and weak lensing. In this work, we compare various modified gravity models using cosmic shear data from the Deep Lens Survey as well as data from CMB, SNe Ia, and BAO. We use the Bayesian Evidence to quantify the comparison robustly, which naturally penalizes complex models with weak data support. In this talk we present our methodology and preliminary results that show f(R) gravity is mildly disfavoured by the data.

• 대한금속재료학회지
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• 제46권9호
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• pp.604-608
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• 2008

The layered compounds vanadium disulfide($VS_2$) and vanadium dioxide($VO_2$) intercalated with Li are investigated for using the Discrete Variational $(DV)-X{\alpha}$ molecular orbital method. The chemical bonding properties of the atoms were examined by bond overlap population of electronic states. The plot of density of states supports the covalent bonding properties by showing the overlap between the atoms. There is a strong tendency of covalent bonding between V-S and V-O. The intensity of covalent bonding of $VS_2$ is stronger than $VO_2$. The net charge of $LiVO_2$ is higher than that of $LiVS_2$. This results of the calculation of $VO_2$ and $VS_2$ indicate that $(DV)-X{\alpha}$ method can be widely applied in the new practical materials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1708-1727
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• 2021

In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.29-36
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• 2022

In deep learning classification tasks, most models frequently assume that all labels are available for the training datasets. As such strategies to learn new concepts from unlabeled datasets are scarce. In fingerprint classification tasks, most of the fingerprint datasets are labelled using the subject/individual and fingerprint datasets labelled with finger type classes are scarce. In this paper, authors have developed approaches of classifying fingerprint images using the majorly known fingerprint classes. Our study provides a flexible method to learn new classes of fingerprints. Our classifier model combines both the clustering technique and use of deep learning to cluster and hence label the fingerprint images into appropriate classes. The K means clustering strategy explores the label uncertainty and high-density regions from unlabeled data to be clustered. Using similarity index, five clusters are created. Deep learning is then used to train a model using a publicly known fingerprint dataset with known finger class types. A prediction technique is then employed to predict the classes of the clusters from the trained model. Our proposed model is better and has less computational costs in learning new classes and hence significantly saving on labelling costs of fingerprint images.

• 농촌계획
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• 제28권3호
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• pp.25-33
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• 2022

Due to the standardized urban development since the industrial era, many urban spaces have experienced non-placeness. Recently, although interest in urban landscape, history, and cultural elements has been increasing, landscape management and control measures are being implemented mainly in large cities due to the low status of rural areas in the country. From this point of view, this study tried to lay the foundation for basic research in related fields by classifying the characteristics and types of streetscapes located near large cities, and to suggest directions that should be considered when managing streetscapes in the future. As a result of the analysis of landscape adjectives, the village felt secluded due to the low density compared to the city street overall, but it did not have a unique image of the region. Three factors were derived through factor analysis, and preference was affected in the order of aesthetic, regularity, and uniqueness. In addition, the research site was classified into three types through cluster analysis, and it was confirmed that the differences by type were due to aesthetics and naturalness. On the other hand, the uniqueness is generally low in all regions, so it seems that fundamental countermeasures are needed.

• 천문학회보
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• 제45권1호
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• pp.41.1-41.1
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• 2020

Different molecular lines trace different physical environments (with various densities and temperatures) within molecular clouds (MCs). Therefore, multimolecular line observations are crucial to study the physical and chemical structures of MCs. We observed the Orion A and Ophiuchus clouds in six different molecular lines as a Taeduk Radio Astronomy Observatory Key Science Program (TRAO-KSP), "mapping Turbulent properties In star-forming MolEcular clouds down to the Sonic scale" (TIMES; PI: Jeong-Eun Lee). Here, we investigate the characteristic relations between the observed lines by performing the Principal Component Analysis (PCA). We also investigate the correlation between the line intensity distributions and the physical parameters, such as the gas column density and dust temperature. Finally, we will discuss how the correlations among different chemical tracers vary with the star formation environments.

• 천문학회보
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• 제46권1호
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• pp.52.2-52.2
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• 2021

The Black Eye Galaxy M64 is an intriguing spiral galaxy with a Type III disk break. To trace the origin of its Type III component, we present HST/ACS F606W/F814W photometry of resolved stars in the outer disk of M64 (2.5' < R < 6.5'). First, we discover a bright extended globular cluster (GC) M64-GC1 at R ~ 5.5', and find that it is an old metal-poor halo GC ([Fe/H] = -1.5 +/- 0.2). Second, we find that there are two distinct subpopulations of red giant branch stars (RGBs). One is an old metal-rich ([Fe/H] ~ -0.4) disk population, and the other is an old metal-poor halo population similar to the resolved stars in M64-GC1. The radial number density profile of the metal-rich RGB follows an exponential disk law, while that of the metal-poor RGB follows a de Vaucouleurs's low. From these results, we conclude that the origin of the Type III component in M64 is a halo, not a disk or a bulge. We will further discuss the results in regards to the formation and evolution of M64.

• Corrosion Science and Technology
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• 제23권1호
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• pp.1-10
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• 2024

Oil well casing leak is caused by contact of casing outer surface with formation electrolyte. It is usually associated with an aquifer with a high salt content or absence of a cement ring behind the casing. The only way to reduce external casing corrosion is through cathodic protection. Through cathodic polarization of casing structure, electron content in crystal lattice and electron density will increase, leading to a potential shift towards the cathodic region. At Tatneft enterprises, cathodic protection is carried out according to cluster and individual schemes. The main criterion for cathodic protection is the size of protective current. For a casing, the protective current is considered sufficient if measurements with a two-contact probe show that the electric current directed to the casing has eliminated all anode sites. To determine the value of required protective current, all methods are considered in this work. In addition, an analysis of all methods used to determine the minimum protective current of the casing is provided. Results show that the method of measuring potential drop along casing is one of the most reliable methods for determining the value of protective current.

• 한국해양학회지:바다
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• 제23권2호
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• pp.91-108
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• 2018

완도-도암만 주변 조하대 여름철 저서동물 분포 양상을 파악하기 위하여 2013년 8월에 25개 정점을 선정하여 현장조사를 실시하였다. 조사 결과 186종이 출현하였으며, 평균밀도는 $1,229ind./m^2$, 생체량은 $265.7g/m^2$이었다. 출현종수는 환형동물(43%), 밀도 및 생체량은 연체동물이 우점분류군이었다. 신지도 및 조약도, 고금도 주변에서 많은 출현종수와 높은 밀도를 보였으며, 외해역에서 내만역으로 들어가면서 출현종수 및 밀도가 감소하였는데 저층 수온과는 음의 상관관계, 염분 및 DO와는 양의 상관관계를 보였다. 최우점종은 아기반투명조개(Theora fragilis)로서 수하식 양식장이 산재한 고금도-조약도-신지도 주변 정점에서 높은 밀도를 보였으며, TOC와 양의 상관관계를 보였다. 두 번째 우점종인 옆새우류 Eriopisella sechellensis는 도암만 입구역에 폭넓게 분포하였으며, 환경요인과는 유의한 상관관계가 나타나지 않았지만 유기물 함량이 낮으면서 입도가 세립한 정점들에서 상대적으로 높은 밀도를 보였다. BIO-ENV분석 결과 저층수의 수온, 염분, pH, 표층퇴적물의 함수율, 황 함량 조합이 저서동물군집 분포의 71%를 설명하고 있었다. 집괴분석 결과 6개 정점군으로 구분되었으며, SIMPER 분석결과 각 정점군별로 특징적인 종들이 기여한 것으로 나타났다. 저서오염지수(BPI)의 분포에 의한 군집 오염도 평가결과 완도 서측 및 고금도-조약도-신지도 주변의 양식장 밀집지역은 유기오염의 영향을 받고 있었다. 특히 완도-도암만 해역은 만입구역의 섬 사이 해역의 저서동물군집이 유기오염의 영향을 더 받고 있었으나, 그 밖의 대부분의 정점들은 정상적인 저서생태계를 보였다. 연구 해역은 입구역의 양식장으로부터 공급되는 유기물이 내해역까지 영향을 미쳐 만 전체가 유기오염의 영향을 받을 가능성이 있기 때문에 외해역의 유기오염원에 대한 영향을 저감하는 방향으로 생태계 관리가 이루어져야 할 것으로 보인다.