• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.6
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• pp.255-260
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• 2023

As demanding the detection of explosive molecules, it is required to develop rapidly and precisely responsive sensors with ultra-high sensitivity. Since two-dimensional semiconductors have an atomically thin body nature where mobile carriers accumulate, the abrupt modulation carrier in the thin body channel can be expected. To investigate the effectiveness of WSe₂ semiconductor materials as a detection material for TNT (Trinitrotoluene) explosives, WSe₂ was synthesized using thermal chemical vapor deposition, and afterward, WSe₂ FETs (Field Effect Transistors) were fabricated using standard photo-lithograph processes. Raman Spectrum and FT-IR (Fourier-transform infrared) spectroscopy reveal that the adsorption of TNT molecules induces the structural transition of WSe₂ crystalline. The electrical properties before and after adsorption of TNT molecules on the WSe₂ surface were compared; as -50 V was applied as the back gate bias, 0.02 μA was recorded in the bare state, and the drain current increased to 0.41 μA with a dropping 0.6% (w/v) TNT while maintaining the p-type behavior. Afterward, the electrical characteristics were additionally evaluated by comparing the carrier mobility, hysteresis, and on/off ratio. Consequently, the present report provides the milestone for developing ultra-sensitive sensors with rapid response and high precision.

• Korean Journal of Cognitive Science
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• v.25 no.4
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• pp.385-416
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• 2014

In this study, memory for emotional words was compared between extraverts and introverts, employing signal detection analysis to distinguish differences in discriminative memory and response bias. Subjects were presented with a study list of emotional words in an encoding session, followed by a recognition session. Effects of task difficulty were examined by varying the nature of the encoding task and the intervals between study and test. For an easy task, with a retention interval of 5 minutes (Study I), introverts exhibited better memory (i.e., higher d') than extraverts, particularly for low-frequency words, and response biases did not differ between these two groups. For a difficult task, with a one-month retention period (Study II), performance was poor overall, and only high-frequency words were remembered; also extraverts adopted a more liberal criterion for 'old' responses (i.e., more hits and more false alarms) for positive emotional-valence words. These results suggest that as task difficulty drives down performance, effects of internal control processes become more apparent, revealing differences in response biases for positive words between extraverts and introverts. These results show that extraversion can distort memory performance for words, depending on their emotional valence.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5889-5897
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• 2015

Background: The performance of combined testing visual inspection with acetic acid (VIA) and cervical cytology tests might differ from one setting to another. The average estimate of the testing accuracy across studies is informative, but no meta-analysis has been carried out to assess this combined method. Objective: The objective of this study was to estimate the average sensitivity and specificity of the combined VIA and cervical cytology tests for the detection of cervical precancerous lesions. Materials and Methods: We conducted a systematic review and a meta-analysis, according to the Cochrane Handbook for Systematic Review of Diagnostic Test Accuracy. We considered two cases. In the either-positive result case, a positive result implies positivity in at least one of the tests. A negative result implies negativity in both tests. In the both-positive case, a positive result implies having both tests positive. Eligible studies were identified using Pubmed, Embase, Website of Science, CINHAL and COCRANE databases. True positive, false positive, false negative and true negative values were extracted. Estimates of sensitivity and specificity, positive and negative likelihood (LR) and diagnostic odds ratios (DOR) were pooled using a hierarchical random effect model. Hierarchical summary receiver operating characteristics (HSROC) were generated and heterogeneity was verified through covariates potentially influencing the diagnostic odds ratio. Findings: Nine studies fulfilled inclusion criteria and were included in the analysis. Pooled estimates of the sensitivities of the combined tests in either-positive and both-positive cases were 0.87 (95% CI: 0.83-0.90) and 0.38 (95% CI: 0.29-0.48), respectively. Corresponding specificities were 0.79 (95% CI: 0.63-0.89) and 0.98 (95% CI: 0.96-0.99) respectively. The DORs of the combined tests in either-positive or both-positive result cases were 27.7 (95% CI: 12.5-61.5) and 52 (95% CI: 22.1-122.2), respectively. When including only articles without partial verification bias and also a high-grade cervical intraepithelial neoplasia as a threshold of the disease, DOR of combined test in both-positive result cases remained the highest. However, DORs decreased to 12.1 (95% CI: 6.05-24.1) and 13.8 (95% CI: 7.92-23.9) in studies without partial verification bias for the combined tests in the either-positive and both-positive result cases, respectively. The screener, the place of study and the size of the population significantly influenced the DOR of combined tests in the both-positive result case in restriction analyses that considered only articles with CIN2+ as disease threshold. Conclusions: The combined test in the either-positive result case has a high sensitivity, but a low specificity. These results suggest that the combined test should be considered in developing countries as a primary screening test if facilities exist to confirm, through colposcopy and biopsy, a positive result.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.17-25
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• 2023

In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.

• Atmosphere
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• v.17 no.2
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• pp.125-133
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• 2007

Cloud amount calculation algorithm was developed using MTSAT-1R satellite data. The cloud amount is retrieved at 5 km ${\times}$ 5 km over the Korean Peninsula and adjacent sea area. The algorithm consists of three steps that are cloud detection, cloud type classification, and cloud amount calculation. At the first step, dynamic thresholds method was applied for detecting cloud pixels. For using objective thresholds in the algorithm, sensitivity test was performed for TBB and Albedo variation with temporal and spatial change. Detected cloud cover was classified into 3 cloud types (low-level cloud, cirrus or uncertain cloud, and cumulonimbus type high-level cloud) in second step. Finally, cloud amount was calculated by the integration method of the steradian angle of each cloud pixel over $3^{\circ}$ elevation. Calculated cloud amount was compared with measured cloud amount with eye at surface observatory for the validation. Bias, RMSE, and correlation coefficient were 0.4, 1.8, and 0.8, respectively. Validation results indicated that calculated cloud amount was a little higher than measured cloud amount but correlation was considerably high. Since calculated cloud amount has 5km ${\times}$ 5km resolution over Korean Peninsula and adjacent sea area, the satellite-driven cloud amount could show the possibility which overcomes the temporal and spatial limitation of measured cloud amount with eye at surface observatory.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7149-7154
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• 2013

Objective: Increasing scientific evidence suggests that common variants in the PALB2 gene may confer susceptibility to breast cancer, but many studies have yielded inconclusive results. This meta-analysis aimed to derive a more precise estimation of the relationship between PALB2 genetic variants and breast cancer risk. Methods: An extensive literary search for relevant studies was conducted in PubMed, Embase, Web of Science, Cochrane Library, CISCOM, CINAHL, Google Scholar, CNKI and CBM databases from their inception through September 1st, 2013. A meta-analysis was performed using the STATA 12.0 software and crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: Six case-control studies were included with a total of 4,499 breast cancer cases and 6,369 healthy controls. Our meta-analysis reveals that PALB2 genetic variants may increase the risk of breast cancer (allele model: OR>1.36, 95%CI: 1.20~1.52, P < 0.001; dominant model: OR>1.64, 95%CI: 1.42~1.91, P < 0.001; respectively). Subgroup analyses by ethnicity indicated PALB2 genetic variants were associated with an increased risk of breast cancer among both Caucasian and Asian populations (all P < 0.05). No publication bias was detected in this meta-analysis (all P > 0.05). Conclusion: The current meta-analysis indicates that PALB2 genetic variants may increase the risk of breast cancer. Thus, detection of PALB2 genetic variants may be a promising biomarker approach.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.377-399
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• 2015

Objective: The aim of this study is to understand and identify the critical issues in vision research area using content analysis and network analysis. Background: Vision, the most influential factor in information processing, has been studied in a wide range of area. As studies on vision are dispersed across a broad area of research and the number of published researches is ever increasing, a bibliometric analysis towards literature would assist researchers in understanding and identifying critical issues in their research. Method: In this study, content and network analysis were applied on the meta-data of literatures collected using three search keywords: 'visual search', 'eye movement', and 'eye tracking'. Results: Content analysis focuses on extracting meaningful information from the text, deducting seven categories of research area; 'stimuli and task', 'condition', 'measures', 'participants', 'eye movement behavior', 'biological system', and 'cognitive process'. Network analysis extracts relational aspect of research areas, presenting characteristics of sub-groups identified by community detection algorithm. Conclusion: Using these methods, studies on vision were quantitatively analyzed and the results helped understand the overall relation between concepts and keywords. Application: The results of this study suggests that the use of content and network analysis helps identifying not only trends of specific research areas but also the relational aspects of each research issue while minimizing researchers' bias. Moreover, the investigated structural relationship would help identify the interrelated subjects from a macroscopic view.

• Korean Journal of Materials Research
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• v.11 no.4
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• pp.247-250
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• 2001

We have fabricated and evaluated a new Si pin photodiode for red light detection with the web patterned $p^{+}$ -shallow diffused region in the light absorbing area. From the measurements of electro-optical characteristics under the bias of -5V, the junction capacitance of 4pF and the dark current of 235pA were obtained. When the 1.6㎼ optical power with peak wavelength of 670nm was incident on the device, the optical signal current of 0.48$\mu\textrm{A}$ and the responsivity of 0.30A/W were obtained. The fabricated device showed the improved sensitivity compared to the conventional circular type device and the maximum spectral response in a spectrum of 670~700nm. The web-patterned Si photodiode can be expected to have the good discrimination characteristics between digital signals in the application of red light optics.