• Structural Engineering and Mechanics
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• v.85 no.2
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• pp.197-206
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• 2023

The deterioration caused by chloride penetration and carbonation plays a significant role in a concrete structure in a marine environment. The chloride corrosion in some marine concrete structures is invisible but can be dangerous in a sudden collapse. Therefore, as a novelty, this research investigates the ability of a non-destructive damage detection method named the Power Spectral Density (PSD) to diagnose damages caused only by chloride ions in concrete structures. Furthermore, the accuracy of this method in estimating the amount of annual damage caused by chloride in various parts and positions exposed to seawater was investigated. For this purpose, the RC Arosa bridge in Spain, which connects the island to the mainland via seawater, was numerically modeled and analyzed. As the first step, each element's bridge position was calculated, along with the chloride corrosion percentage in the reinforcements. The next step predicted the existence, location, and timing of damage to the entire concrete part of the bridge based on the amount of rebar corrosion each year. The PSD method was used to monitor the annual loss of reinforcement cross-section area, changes in dynamic characteristics such as stiffness and mass, and each year of the bridge structure's life using sensitivity equations and the linear least squares algorithm. This study showed that using different approaches to the PSD method based on rebar chloride corrosion and assuming 10% errors in software analysis can help predict the location and almost exact amount of damage zones over time.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.499-510
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• 2022

This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.1
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• pp.1-11
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• 2023

The Indian golden muga silkworm, Antheraea assamensis Helfer is an economically important wild silkworm endemic to Northeastern part of India. In recent years, climate change has posed a threat to muga silk production due to the requirement that larvae be reared outdoors. Since the muga silkworm larvae are exposed to the vagaries of nature, the changing climate has increased the incidence of microbial diseases in the rearing fields. Accurate diagnosis of the disease causing pathogens and its associated epidemiology are prerequisites to manage the diseases in the rearing field. Although conventional microbial culturing methods are widely used to identify pathogenic bacteria, they would not provide meaningful information on a wide variety of silkworm pathogens. The information on use of molecular diagnostic tools in detection of microbial pathogens of wild silk moths is very limited. A wide range of molecular and immunodiagnostic techniques including denaturing gradient gel electrophoresis (DGGE), random amplified polymorphism (RAPD), 16S rRNA/ITSA gene sequencing, multiplex polymerase chain reaction (M-PCR), fluorescence in situ hybridization (FISH), immunofluorescence, and repetitive-element PCR (Rep-PCR), have been used for detecting and characterizing the pathogens of insects with economic significance. Nevertheless, the application of these molecular tools for detecting and typing entomopathogens in surveillance studies of muga silkworm rearing is very limited. Here, we discuss the possible application of these molecular techniques, their advantages and major limitations. These methods show promise in better management of diseases in muga ecosystem.

• The Plant Pathology Journal
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• v.39 no.1
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• pp.88-107
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• 2023

In the present investigation, bacterial isolates from infected apple trees causing apple canker during winter were studied in the northern Gyeongbuk Province, Korea. The pathogen was identified as Pseudomonas syringae pv. syringae (Pss) through various physiological and biochemical characterization assays such as BIOLOG, gas chromatography of fatty acid methyl esters, and 16S rRNA. Bioassays for the production of phytotoxins were positive for syringopeptin and syringomycin against Bacillus megaterium and Geotrichum candidum, respectively. The polymerase chain reaction (PCR) method enabled the detection of toxin-producing genes, syrB1, and sypB in Pss. The differentiation of strains was performed using LOPAT and GATTa tests. Pss further exhibited ice nucleation activity (INA) at a temperature of -0.7℃, indicating an INA⁺ bacterium. The ice-nucleating temperature was -4.7℃ for a non-treated control (sterilized distilled water), whereas it was -9.6℃ for an INA^- bacterium Escherichia coli TOP10. These methods detected pathogenic strains from apple orchards. Pss might exist in an apple tree during ice injury, and it secretes a toxin that makes leaves yellow and cause canker symptoms. Until now, Korea has not developed antibiotics targeting Pss. Therefore, it is necessary to develop effective disease control to combat Pss in apple orchards. Pathogenicity test on apple leaves and stems showed canker symptoms. The pathogenic bacterium was re-isolated from symptomatic plant tissue and confirmed as original isolates by 16S rRNA. Repetitive element sequence-based PCR and enterobacterial repetitive intergenic consensus PCR primers revealed different genetic profiles within P. syringae pathovars. High antibiotic susceptibility results showed the misreading of mRNA caused by streptomycin and oxytetracycline.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.416-423
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• 2009

The ultrasonic pressure fields for the 3 MHz linear phased array transducer with sixteen piezoelectric elements of which one may not be operated by defect were simulated theoretically and measured experimentally using a visualization system of the Schlieren method. The simulation results for steering angles of $0^{\circ}$ and $30^{\circ}$ show that the side-lobe patterns of the transducer including a defective element is quite different from the transducer with all normal elements, and those patterns are in good agreement with the results of visualization. It is shown that the defective elements in a linear array transducer can be detected by comparison of the simulated and the visualized side-lobe patterns in two dimensional acoustic fields.

• Applied Microscopy
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• v.30 no.4
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• pp.347-355
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• 2000

Zinc is one of the most abundant oligoelements in the living cell. It appears tightly bound to some metalloproteins and nucleic acids, loosely bound to some metallothioneins or even as free ion. Small amounts of zinc ions (in the nanomolar range) regulate a plentitude of enzymatic proteins, receptors and transcription factors, thus rolls need accurate homeostasis of zinc ions. Zinc is an essential catalytic or structural element of many proteins, and a signaling messenger that is released by neural activity at many central excitatory synapses. Growing evidences suggest that zinc may also be a key mediator and modulator of the neuronal death associated with transient global ischemia and sustained seizures, as well as perhaps other neurological disease stoles. Some neurons have developed mechanisms to accumulate zinc in specific membrane compartment ('vesicular zinc') which can be evidenced using histochemical techniques. Substances giving a bright colour or emitting fluorescence when in contact with divalent metal ions are currently used to detect them inside cells; their use leads to the so called 'direct' methods. The fixation and precipitation of metal ions as insoluble salt precipitates, their maintenance along the histological process and, finally, their demonstration after autometallographic development are essential steps for other methods, the so called 'indirect methods'. This study is a short report on the autometallograhical approaches for zinc detection in the central nervous system (CNS) by means of a modified selenium method.

• Korean Security Journal
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• no.22
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• pp.145-168
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• 2010

Since Alarm Monitoring Service was introduced in Korea in 1981, the market has been increasing and is expected to increase continually. Some factors such as the increase of social security need and the change of safety consciousness, increase of persons who live alone could be affected positively on Alarm Monitoring Service industry. As Alarm Monitoring Service come into wide use, the understanding of electronic security service is spread and consumer's demand is difficult, so consideration about new developmental plan is need to respond to the change actively. Electronic security system is consist of various kinds of element, so every element could do their role equally. Alarm Monitoring Service should satisfy consumer's various needs because it is not necessary commodity, also electronic security device could be easily operated and it's appearance has to have a good design. To solve the false alarm problem, detection sensor's improvement should be considered preferentially and development of new type of sensor that operate dissimilarly to replace former sensor is needed. On the other hand, to settle the matter that occurred by response time, security company could explain the limit on Alarm Monitoring System to consumer honestly and ask for an understanding. If consumer could be joined into security activity by security agent's explanation, better security service would be provided with mutual confidence. To save response time the consideration on the introduction of GIS(Global Information System) is needed rather than GPS(Global Positioning System). Although training program for security agents is important, several benefits for security agents should be considered together. The development of new business model is required for preparation against market stagnation and the development of new commodity to secure consumer for housing service rather than commercial facility service. for the purpose of those, new commodity related to home-network system and video surveillance system could be considered, also new added service with network between security company and consumer for a basis is to be considered.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Tuberculosis and Respiratory Diseases
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• v.56 no.5
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• pp.465-484
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• 2004

Background : Insulin-like growth factor (IGF)-binding protein-3 (IGFBP-3) inhibits the proliferation of non-small cell lung cancer (NSCLC) cells by inducing apoptosis. Methods : In this study, we investigated whether hypermethylation of IGFBP-3 promoter play an important role in the loss of IGFBP-3 expression in NSCLC. We also studied the mechanisms that mediate the silencing of IGFBP-3 expression in the cell lines which have hypermethylated IGFBP-3 promoter. Results : The IGFBP-3 promoter has hypermethylation in 7 of 15 (46.7%) NSCLC cell lines and 16 (69.7%) of 23, 7 (77.8%) of 9, 4 (80%) of 5, 4 (66.7 %) of 6, and 6 (100%) of 6 tumor specimens from patients with stage I, II, IIIA, IIIB, and IV NSCLC, respectively. The methylation status correlated with the level of protein and mRNA in NSCLC cell lines. Expression of IGFBP-3 was restored by the demethylating agent 5'-aza-2'-deoxycytidine (5'-aza-dC) in a subset of NSCLC cell lines. The Sp-1/ Sp-3 binding element in the IGFBP-3 promoter, important for promoter activity, was methylated in the NSCLC cell lines which have reduced IGFBP-3 expression and the methylation of this element suppressed the binding of the Sp-1 transcription factor. A ChIP assay showed that the methylation status of the IGFBP-3 promoter influenced the binding of Sp-1, methyl-CpG binding protein-2 (MeCP2), and histone deacetylase (HDAC) to Sp-1/Sp-3 binding element, which were reversed by by 5'-aza-dC. In vitro methylation of the IGFBP-3 promoter containing the Sp-1/Sp-3 binding element significantly reduced promoter activity, which was further suppressed by the overexpression of MeCP2. This reduction in activity was rescued by 5'-aza-dC. Conclusion : These findings indicate that hypermethylation of the IGFBP-3 promoter is one mechanism by which IGFBP-3 expression is silenced and MeCP2, with recruitment of HDAC, may play a role in silencing of IGFBP-3 expression. The frequency of this abnormality is also associated with advanced stages among the patients with NSCLC, suggesting that IGFBP-3 plays an important role in lung carcinogenesis/progression and that the promoter methylation status of IGFBP-3 may be a marker for early molecular detection and/or for monitoring chemoprevention efforts.