• Journal of Sensor Science and Technology
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• 제26권6호
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• pp.379-385
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• 2017

In this study, an amperometric non-enzymatic glucose sensor was developed on the surface of a glassy carbon electrode by simply drop-casting the synthesized homogeneous suspension of hexagonal boron nitride (h-BN) nanosheets with a copper metal-organic framework (Cu-MOF) composite. Comprehensive analytical methods, including field-emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), cyclic voltammetry, electrochemical impedance spectroscopy, and amperometry, were used to investigate the surface and electrochemical characteristics of the h-BN-Cu-MOF composite. The FE-SEM, FT-IR, and XRD results showed that the h-BN-Cu-MOF composite was formed successfully and exhibited a good porous structure. The electrochemical results showed a sensor sensitivity of $18.1{\mu}A{\mu}M^{-1}cm^{-2}$ with a dynamic linearity range of $10-900{\mu}M$ glucose and a detection limit of $5.5{\mu}M$ glucose with a rapid turnaround time (less than 2 min). Additionally, the developed sensor exhibited satisfactory anti-interference ability against dopamine, ascorbic acid, uric acid, urea, and nitrate, and thus, can be applied to the design and development of non-enzymatic glucose sensors.

• Parasites, Hosts and Diseases
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• 제51권1호
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• pp.93-98
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• 2013

A field applicable diagnostic technique, the dipstick assay, was evaluated for its sensitivity and specificity in diagnosing human Schistosoma mansoni infection. A monoclonal antibody (mAb) against S. mansoni adult worm tegumental antigen (AWTA) was employed in dipstick and sandwich ELISA for detection of circulating schistosome antigen (CSA) in both serum and urine samples. Based on clinical and parasitological examinations, 60 S. mansoni-infected patients, 30 patients infected with parasites other than schistosomiasis, and 30 uninfected healthy individuals were selected. The sensitivity and specificity of dipstick assay in urine samples were 86.7% and 90.0%, respectively, compared to 90.0% sensitivity and 91.7% specificity of sandwich ELISA. In serum samples, the sensitivity and specificity were 88.3% and 91.7% for dipstick assay vs. 91.7% and 95.0% for sandwich ELISA, respectively. The diagnostic efficacy of dipstick assay in urine and serum samples was 88.3% and 90.0%, while it was 90.8% and 93.3% for sandwich ELISA, respectively. The diagnostic indices of dipstick assay and ELISA either in serum or in urine were statistically comparable (P>0.05). In conclusion, the dipstick assay offers an alternative simple, rapid, non-invasive technique in detecting CSA or complement to stool examinations especially in field studies.

• Asian-Australasian Journal of Animal Sciences
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• 제33권10호
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• pp.1683-1690
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• 2020

Objective: The rapid and reliable detection of the African swine fever virus (ASFV) plays an important role in emergency control and preventive measures of ASF. Some methods have been recommended by FAO/OIE to detect ASFV in clinical samples, including realtime polymerase chain reaction (PCR). However, mismatches in primer and probe binding regions may cause a false-negative result. Here, a slight modification in probe sequence has been conducted to improve the qualification of real-time PCR based on World Organization for Animal Health (OIE) protocol for accurate detection of ASFV in field samples in Vietnam. Methods: Seven positive confirmed samples (four samples have no mismatch, and three samples contained one mutation in probe binding sites) were used to establish novel real-time PCR with slightly modified probe (Y = C or T) in comparison with original probe recommended by OIE. Results: Both real-time PCRs using the OIE-recommended probe and novel modified probe can detect ASFV in clinical samples without mismatch in probe binding site. A high correlation of cycle quantification (Cq) values was observed in which Cq values obtained from both probes arranged from 22 to 25, suggesting that modified probe sequence does not impede the qualification of real-time PCR to detect ASFV in clinical samples. However, the samples with one mutation in probe binding sites were ASFV negative with OIE recommended probe but positive with our modified probe (Cq value ranked between 33.12-35.78). Conclusion: We demonstrated for the first time that a mismatch in probe binding regions caused a false negative result by OIE recommended real-time PCR, and a slightly modified probe is required to enhance the sensitivity and obtain an ASF accurate diagnosis in field samples in Vietnam.

• Geophysics and Geophysical Exploration
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• 제20권2호
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• pp.61-71
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• 2017

Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.

• Imaging Science in Dentistry
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• 제51권3호
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• pp.237-242
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• 2021

Purpose: The aim of this study was to analyse and review deep learning convolutional neural networks for detecting and diagnosing early-stage dental caries on periapical radiographs. Materials and Methods: In order to conduct this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA) guidelines were followed. Studies published from 2015 to 2021 under the keywords(deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed. Results: When dental caries is improperly diagnosed, the lesion may eventually invade the enamel, dentin, and pulp tissue, leading to loss of tooth function. Rapid and precise detection and diagnosis are vital for implementing appropriate prevention and treatment of dental caries. Radiography and intraoral images are considered to play a vital role in detecting dental caries; nevertheless, studies have shown that 20% of suspicious areas are mistakenly diagnosed as dental caries using this technique; hence, diagnosis via radiography alone without an objective assessment is inaccurate. Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. Conclusion: Clinical applications of deep learning convolutional neural networks in the dental field have shown significant accuracy in detecting and diagnosing dental caries, and these models hold promise in supporting dental practitioners to improve patient outcomes.

• Journal of the Korea Institute of Military Science and Technology
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• 제15권6호
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• pp.812-819
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• 2012

Interference and jamming are becoming increasing concern to a radar system nowdays. AESA(Active Electronically Steered Array) antennas and adaptive beamforming(ABF), in which antenna beam patterns can be modified to reject the interference, offer a potential solution to overcome the problems encountered. In this paper, we've developed a planar active phased array radar system, in which ABF, target detection and tracking algorithm operate in real-time. For the high output power and the low noise figure of the antenna, we've designed the S-band TRMs based on GaN HEMT. For real-time processing, we've used wavelenth division multiplexing technique on fiber optic communication which enables rapid data communication between the antenna and the signal processor. Also, we've implemented the HW and SW architecture of Real-time Signal Processor(RSP) for adaptive beamforming that uses SMI(Sample Matrix Inversion) technique based on MVDR(Minimum Variance Distortionless Response). The performance of this radar system has been verified by near-field and far-field tests.

• Mycobiology
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• 제38권1호
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• pp.33-38
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• 2010

We have successfully applied the nested PCR to detect Cylindrocarpon destructans, a major pathogen causing root rot disease from ginseng seedlings in our former study. The PCR assay, in this study, was used to detect the pathogen from soils. The nested PCR using internal transcribed spacer (ITS) 1, 4 primer set and Dest 1, 4 primer set maintained the specificity in soils containing various microorganisms. For a soil DNA extraction method targeting chlamydospores, when several cell wall disrupting methods were tested, the combination of lyophilization and grinding with glass beads, which broke almost all the chlamydospores, was the strongest. The DNA extraction method which was completed based on the above was simple and time-saving because of exclusion of unnecessary stages, and efficient to apply in soils. As three ginseng fields whose histories were known were analyzed, the PCR assay resulted as our expectation derived from the field information. The direct PCR method will be utilized as a reliable and rapid tool for detecting and monitoring C. destructans in ginseng fields.

• Journal of Advanced Navigation Technology
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• 제18권6호
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• pp.633-639
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• 2014

Recently the study about a smart health care which is combined IT with BT to provide a variety of health care services are being actively investigated. In order to provide the best possible emergency medical services in a short period of time, it is necessary that the rapid emergency measures in the event of an emergency essential. In this paper, we propose an emergency medical service platform to take effective first aid to person who has a NFC tag or NFC-enabled mobile smart phones in an accident. Using NFC, it is possible to help without physical contact to the patient unconscious to emergency incidents such as falling down in everyday life. In this paper, we design and implement an mobile emergency medical system that can deliver first aid information ask for help in case of emergency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• Korean Journal of Food Science and Technology
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• 제39권1호
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• pp.71-76
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• 2007

Foodborne illness caused by Noroviruses (NVs) is increasing rapidly in Korea. This study developed an effective detection protocol for NVs found in contaminated oysters and lettuce through an investigation using the major steps of virus particle separation, concentration and RT-PCR. As a surrogate model for NVs, the cultivable feline calicivirus (FCV) that belongs to the same Caliciviridae family was used. Instead of using a time-consuming ultracentrifugation method, efficient methods based on solvent extraction and PEG precipitation procedure were applied. Direct homogenization of a 25g sample of whole oyster and lettuce in 175mL PBS provided the simplicity that would be needed in the actual field of food product examination. The overnight PEG precipitation step at $4^{\circ}C$ was reduced to 3 h by placing the reaction tube in ice and by adjusting the PEG concentrations. The application of the use of chloroform and 0.2 ${\mu}m$ syringe filtration together showed a better detection efficiency than the use of chloroform alone in removing PCR inhibitors for both oyster and lettuce samples. Also, dilution of the extracted RNA solution before PCR provided increased sensitivity. The improved detection protocol developed in this study could be efficiently applied to detect FCV and most likely NVs from oysters and lettuce.