• Journal of Radiation Industry
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• v.7 no.1
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• pp.15-21
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• 2013

The detection characteristics of irradiated spices were investigated depending on radiation sources and doses by photostimulated luminescence (PSL) and Thermoluminescence (TL). 6 kinds of spices (turmeric, onion powder, red pepper, basil, parsley, black pepper) were irradiated at 0 to 10 kGy under ambient conditions by both a $^{60}Co$ gamma irradiator and an electron beam (EB) accelerator, respectively. The PSL analysis showed negative results for non-irradiated spices, while irradiated spices gave intermediate and positive value, which presented the limited potential of PSL technique. In TL measurement, TL glow curves on non-irradiated samples appeared at about $300^{\circ}C$ with low intensity. All irradiated samples were easily distinguishable through radiation-specific strong TL glow curves with maximum peak in range of $150{\sim}200^{\circ}C$. TL ratio ($TL_1/TL_2$) obtained by a re-irradiation step could verify the detection result of $TL_1$ glow curves, showing ratios lower than 0.1 in the non-irradiated sample and higher than 0.1 in irradiated ones. Therefore, in PSL measurement, the identification of irradiated spices showed more clear results in electron beam irradiated samples. TL analysis showed obvious difference between non-irradiated and irradiated samples in gamma ray and electron beam irradiated samples.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.461-470
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• 2019

This study was carried out to quantify the drought stress in grafted watermelon seedlings non-destructively by using chlorophyll fluorescence (CF) imaging technique rather than the visual judgment. Six-day old watermelon seedlings were grown under uniform irrigation for 3 days, and then given drought stress. Afterward, the sensor for the measurement of water content in plug tray cell unit was used to classify the drought-stress level into nine groups from D1 (53.0%, sufficient moisture state) to D9 (15.7%, extremely dry stress), and the 16 CF parameters were measured. In addition, re-irrigation was performed on the drought stressed seedlings(D5 - D9) to determine the growth and photosynthesis recovery level, which was not confirmed by visual judgment. The kinetic curve patterns of CF in three different drought stressed seedling groups were found to be different for the early detection of drought stress. All the 16 CF parameters decreased continuously with exposure to drought stress and drastically decreased from D5 (32.1%) where the visual judgment was possible. The fluorescence decline ratio (Rfd_Lss) started to decrease from the initial drought stress level (D5 - D6), and the Maximum PSII quantum yield (Fv/Fm) was significantly decreased in the later extreme drought stress range (D7 - D9) by re-irrigation recovery test. Thus, Rfd_Lss and Fv/Fm parameters were finally selected as potent indicators of growth and photosynthesis recovery in the initial and later stages of drought stress. Also, to the differences in the numerical values of the individual chlorophyll fluorescence parameters, the drought stress level was intuitively confirmed through the image. These results indicate that Rfd and Fv/Fm can be considered as potential CF parameters for the detection of low and extremely high drought stress, respectively. Furthermore, Fv/Fm can be considered as the best CF parameters for recovery at re-irrigation.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.94-102
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• 1997

Purpose: There have been some efforts to diagnose intracranial aneurysm through a non-invasive method using MRA, although the process may be difficult when the lesion is less than 3mm. The present study prospectively compares the results of high resolution, fast speed slice interpolation MRA and DSA thereby examing the potentiality of primary non-invasive screening test. Materials and Methods: A total of 26 cerebral aneurysm lesions from 14 patients with subarachnoid hemorrhage from ruptured aneurysm (RA) and 5 patients with unruptured aneurysm(UA). In all subjects, MRA was taken to confirm the vessel of origin, definition of aneurysm neck and the relationship of the aneurysm to nearby small vessels, and the results were compared with the results of DSA. The images were obtained with 1.5T superconductive machine (Vision, Siemens, Erlangen, Germany) on 4 slabs of MRA using slice interpolation. The settings include TR/TE/FA=30/6.4/25, matrix $160{\times}512$, FOV $150{\times}200$, 7minutes 42 seconds of scan time, effective thickness of 0.7 mm and an entire thickness of 102. 2mm. The images included structures from foramen magnum to A3 portion of anterior cerebral artery. MIP was used for the image analysis, and multiplanar reconstruction (MPR) technique was used in cases of intracranial aneurysm. Results: A total of 26 intracranial aneurysm lesions from 19 patients with 2 patients having 3 lesion, 3 patients having 2 lesions and the rest of 14 patients having 1 lesion each were examined. Among those, 14 were RA and 12 were UA. Eight lesions were less than 2mm in size, 9 lesions were 3-5mm, 7 were 6-9mm and 2 were larger than IOmm. On initial exams, 25 out of 26 aneurysm lesions were detected in either MRA or DSA showing 96% sensitivity. Specificity cannot be estimated since there was no true negative of false positive findings. When MRA and MPR were used concurrently for the confirmation of size and shape, the results were equivalent to those of DSA, while in the confirmation of aneurysm neck and parent vessels, the concurrent use of MRA and MPR was far superior to the sole use of either MRA or DSA. Conclusion: High resolution MRA using slice interpolation technique showed equal results as those of DSA for the detection of intracranial aneurysm, and may be used as a primary non-invasive screening test in the future.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Parasites, Hosts and Diseases
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• v.29 no.3
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• pp.235-244
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• 1991

An epidemiological study and mass treatments of Enterobius vermicularis infection among children near Wonju area of Kangwon province were carried out. The children were divided into 4 groups according to their residing localities; children in the mountainous area, rural area, urban area and in orphanage. They were examined by adhesive cellotape anal swab technique, and egg positive rates were obtained. The rates of egg reduction and re-infection rates after repeated mass treatments were also observed. The results obtained were as follows: 1. The overall egg Positive rate of E. vermicularis in the first screening was 19.9% (251 out of 1, 262 examinees; 19.7% in males and 20.1% in females). The positive rates were 13.0% in the mountainous area, 11 9% in the rural area, 15.1% in the urban (medium-sized) area and 61.9% in orphanages. 2. The highest positive rates were observed in the kindergarten children, and 1st and 2nd grade children of primary schools (26.2~32.2%), and the lowest rate (13.6%) in 6-year grade children of primary schools. 3. Cumulative detection rates from 3 repeated anal swabs at 4~5 days interval were higher (70.8%) than those from single anal swabs (50.0~59.2%). 4. Out of the examinees who showed the highest cumulative positive rate (70.8%), about 39.2% were consecutively positive in 3 anal swabs. Among different groups of children, the higher the total egg detection rates (87.5%), the higher the consecutive positive rates (71.9%) . 5. A total of 2, 609 (male : female=1 : 12.4) worms were collected from 17 egg-positive cases treated with anthelinintics. The mean number of worms per child was 153 (range: 4-824) . 6. The egg-positive cases in several studied groups (180 children) were treated with anthelmintics 6 times at 3-week intervals. In this case, the overall positive rate was decreased from 54.8% to 2.2% at 15 weeks after the treatments, but no complete negative conversion was experienced. However, in a group of children (154 children) including egg Positive and negative cases who were both treated with anthelmintics at 3-week interval, a complete egg-negative conversion was observed in the 9th week after treatments. 7. The egg-detection rate in the brothers or sisters of egg Positive children was 70.0% (28 out of 40 examined), and the egg-positive rate according to the family unit was 69.7%. In summarizing the above results, it is concluded that Enterobius vermicularis infection is still highly prevalent among children in Korea, and that repeated mass treatments of more than 3 times will be effective for control of this infection.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.6
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• pp.655-662
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• 2012

Gas leakage in an oil refinery causes damage to the environment and unsafe conditions. Therefore, it is necessary to develop a technique that is able to detect the location of the leakage and to filter abnormal gas-leakage signals from normal background noise. In this study, the adaptation filter of the finite impulse response (FIR) least mean squares (LMS) algorithm and a cross-correlation function were used to develop a leakage-predicting program based on LABVIEW. Nitrogen gas at a high pressure of 120 kg/$cm^2$ and the assembled equipment were used to perform experiments in a reverberant chamber. Analysis of the data from the experiments performed with various hole sizes, pressures, distances, and frequencies indicated that the background noise occurred primarily at less than 1 kHz and that the leakage signal appeared in a high-frequency region of around 16 kHz. Measurement of the noise sources in an actual oil refinery revealed that the noise frequencies of pumps and compressors, which are two typical background noise sources in a petrochemical plant, were 2 kHz and 4.5 kHz, respectively. The fact that these two signals were separated clearly made it possible to distinguish leakage signals from background noises and, in addition, to detect the location of the leakage.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.15-26
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• 2012

In this paper, we perform interference cancellation in multiuser MIMO (Multiple Input Multiple Output) relay network with improved Amplify-and-Forward (AF) and Decode-and-Forward (DF) relay protocols. The work of interference cancellation is followed by evolved NodeB (eNB), Relay Node (RN) and User Equipment (UE) to improve the error performance of whole transmission system with the explicit use of relay node. In order to perform interference cancellation, we use Dirty Paper Coding (DPC) and Thomilson Harashima Precoding (THP) allied with detection techniques Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Successive Interference Cancellation (SIC) and Ordered Successive Interference Cancellation (OSIC). These basic techniques are studied and improved in the proposal by using the functions of relay node. The performance is improved by Decode-and-Forward which enhance the cancellation of interference in two layers at the cooperative relay node. The interference cancellation using weighted vectors is performed between eNB and RN. In the final results of the research, we conclude that in contrast with the conventional algorithms, the proposed algorithm shows better performance in lower SNR regime. The simulation results show the considerable improvement in the bit error performance by the proposed scheme in the LTE-Advanced system.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4469-4475
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• 2012

Background: The potential use of hypomethylation of Long INterspersed Element 1 (LINE-1) and Alu elements (Alu) as a biomarker has been comprehensively assessed in several cancers, including head and neck squamous cell carcinoma (HNSCC). Failure to detect occult metastatic head and neck tumors on radical neck lymph node dissection can affect the therapeutic measures taken. Objective: The aim of this study was to investigate the LINE-1 and Alu methylation status and determine whether it can be applied for detection of occult metastatic tumors in HNSCC cases. Methods: We used the Combine Bisulfite Restriction Analysis (COBRA) technique to analyse LINE-1 and Alu methylation status. In addition to the methylation level, LINE-1 and Alu loci were classified based on the methylation statuses of two CpG dinucleotides in each allele as follows: hypermethylation ($^mC^mC$), hypomethylation ($^uC^uC$), and 2 forms of partial methylation ($^mC^uC$ and $^uC^mC$). Sixty-one lymph nodes were divided into 3 groups: 1) non-metastatic head and neck cancer (NM), 2) histologically negative for tumor cells of cases with metastatic head and neck cancer (LN), and 3) histologically positive for tumor cells (LP). Results: Alu methylation change was not significant. However, LINE-1 methylation of both LN and LP was altered, as demonstrated by the lower LINE-1 methylation levels (p<0.001), higher percentage of $^mC^uC$ (p<0.01), lower percentage of $^uC^mC$ (p<0.001) and higher percentage of $^uC^uC$ (p<0.001). Using receiver operating characteristic (ROC) curve analysis, $%^uC^mC$ and $%^mC^uC$ values revealed a high level of AUC at 0.806 and 0.716, respectively, in distinguishing LN from NM. Conclusion: The LINE-1 methylation changes in LN have the same pattern as that in LP. This epigenomic change may be due to the presence of occult metastatic tumor in LN cases.