• Parasites, Hosts and Diseases
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• 제47권3호
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• pp.293-297
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• 2009

Improved methods for detection of Cryptosporidium oocysts in environmental and clinical samples are urgently needed to improve detection of cryptosporidiosis. We compared the sensitivity of 7 PCR primer sets for detection of Cryptosporidium parvum. Each target gene was amplified by PCR or nested PCR with serially diluted DNA extracted from purified C. parvum oocysts. The target genes included Cryptosporidium oocyst wall protein (COWP), small subunit ribosomal RNA (SSU rRNA), and random amplified polymorphic DNA. The detection limit of the PCR method ranged from $10^3$ to $10^4$ oocysts, and the nested PCR method was able to detect $10^0$ to $10^2$ oocysts. A second-round amplification of target genes showed that the nested primer set specific for the COWP gene proved to be the most sensitive one compared to the other primer sets tested in this study and would therefore be useful for the detection of C. parvum.

• 대한치과의사협회지
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• 제49권8호
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• pp.461-471
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• 2011

The detection of carious lesions is a key point to apply appropriate preventive measures or operative treatment of dental caries. A laser fluorescence device DIAGNOdent$^{(R)}$ (KaVo, Biberach, Germany) has also been shown to be of additional clinical value in the detection of initial caries. This report focus on the DIAGNOdent$^{(R)}$ for caries detection. DIAGNOdent$^{(R)}$ irradiate visible red light at a wavelength of 655 nm to elicit near-infrared fluorescence from caries lesion. This device is known as a reproducible method for caries detection, with good sensitivity and specificity especially for caries detection on occlusal and accessible smooth surfaces. DIAGNOdent$^{(R)}$ tended to be more sensitive method of detecting occlusal dentinal caries, however, showed more false-positive diagnoses than the visual inspection. So Clinician should not use the device as a clinician's primary diagnostic method and it is recommended that the device should be used in the decision-making process in relation to the diagnosis of caries as a second opinion in cases of doubt after visual inspection. The trend of modern dentistry would be a preventive approach rather than invasive treatment of the disease. This is possible only with early detection and respective preventive measures, DIAGNOdent$^{(R)}$ can help the changes.

• Structural Monitoring and Maintenance
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• 제5권2호
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• Journal of Microbiology and Biotechnology
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• 제9권2호
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• pp.184-190
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• 1999

The use of the polymerase chain reaction (PCR) method was described using two sets of primers based on the ceuN gene (JEJ 1 and JEJ 2) which encodes a protein involved in siderophore transport and 16S rRNA gene (pA and pB) for the sensitive and specific detection of enteropathogen Campylobacter jejuni. Six oligonucleotides were utilized in an amplification experiment and PCR products of predicted sizes were generated from whole cells and boiled cell lysates at the same intensity. Two sets of the primer pairs, JEJ and pAB, were specific enough for all C. jejuni strains tested for the direct use of whole cells without DNA extraction or lysis steps. In the PCR using the pAB primer pair, the detection limit, as determined by the ethidium bromide staining of the amplification products on agarose gels, was at the level of $10^1$ bacteria cells or less in both the pure culture and artificially inoculated milk and chicken enrichment samples, whereas the detection limit with the JEJ primer pair was relatively low, i.e. $10^3$ cells or more in the same PCR samples. The PCR method using either a primer JEJ or pAB was both repeatable and specific for the detection of C. jejuni in food. This method is simply completed within 4 h.

• 한국음향학회지
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• 제15권5호
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• pp.118-124
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• 1996

수동 소나 시스템에서 표적을 탐지, 식별하는데 가장 중요한 인자는 표적소음에서 나타나는 신호 주파수선 성분이다. 수중의 주변잡음과 표적소음이 복합된 환경에서 표적의 신호 주파수선 성분을 정확히 추출하는데는 신호 탐지 문턱값 설정이나 주변잡음의 변화 때문에 어려움이 따른다. 이 연구에서는 자동 연상 기억장치 신경망을 이용하여 신호 탐지 문턱값 설정이나 주변잡음의 변화에 강인한 음향 표적의 신호 주파수선 탐지 방식을 제안한다. 모의 실험 및 실제 표적 신호에 적용하여 제안한 방식이 우수한 신호 주파수선 탐지성능을 나타냄을 보인다.

• Journal of Biosystems Engineering
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• 제34권4호
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• pp.254-259
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• 2009

Conventional methods for pathogen detection and identification are labor-intensive and take several days to complete. Recently developed biosensors have shown potential for the rapid detection of foodborne pathogens. In this study, an impedimetric biosensor was developed for rapid detection of Salmonella typhimurium. To develop the biosensor, an interdigitated microelectrode (IME) was fabricated by using semiconductor fabrication process. Anti-Salmonella antibodies were immobilized based on either avidin-biotin binding or self assembled monolayer (SAM) on the surface of the IME to form an active sensing layer. To evaluate effect of antibody immobilization methods on sensitivity of the sensor, detection limit of the biosensor was analyzed with Salmonella samples innoculated in phosphate buffered saline (PBS) or food extract. The impedimetric biosensor based on SAM immobilization method produced better detection limit. The biosensor could detect 107 CFU/mL of Salmonella in pork meat extract. This method may provide a simple, rapid, and sensitive method to detect foodborne pathogens.

• 대한의생명과학회지
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• 제25권4호
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• pp.331-338
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• 2019

Human Aichivirus A1 (HuAiV-A1) is a waterborne human pathogenic virus classified as Picornaviridae and Kobuvirus. In this study, we developed a method that can detect about 35 minutes faster with the same detection sensitivity level than the previously reported HuAiV-A1 diagnostic RT-PCR primer. The RT-PCR primer sets developed in this study are capable of detecting HuAiV-A1 at a level of about 100 ag and formed 563 bp amplification product. In addition, the RT-nested PCR method was able to amplify 410 bp using the RT-PCR product as a template. The detection sensitivity of our method was 10 times higher than the method with the highest detection sensitivity to date. Therefore, the detection method of HuAiV-A1 developed in this study is expected to be used in the water environment in which a small amount of virus exists. Also, this detection method is expected to be used as HuAiV-A1 diagnostic technology in both clinical and non-clinical field.

• Smart Structures and Systems
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• 제24권2호
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• pp.233-242
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• 2019

In this paper, an inverse approach based on uniform load surface (ULS) is presented for structural damage localization and quantification. The ULS is excellent approximation for deformed configuration of a structure under distributed unit force applied on all degrees of freedom. The ULS make use of natural frequencies and mode shapes of structure and in mathematical point of view is a weighted average of mode shapes. An objective function presented to damage detection is discrepancy between the ULS of monitored structure and numerical model of structure. Solving this objective function to find minimum value yields damage's parameters detection. The teaching-learning based optimization algorithm has been employed to solve inverse problem. The efficiency of present damage detection method is demonstrated through three numerical examples. By comparison between proposed objective function and another objective function which make use of natural frequencies and mode shapes, it is revealed present objective function have faster convergence and is more sensitive to damage. The method has good robustness against measurement noise and could detect damage by using the first few mode shapes. The results indicate that the proposed method is reliable technique to damage detection in structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• 센서학회지
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• 제32권2호
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• pp.67-74
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• 2023

A microfluidic paper-based analytical device (µPAD) is proposed for the selective detection of ammonia in water by using the modified Berthelot reagent and a fluidic channel consisting of hollow paper. The modified Berthelot reagents were uniformly dispersed in cyclohexane and then immobilized in a detection zone of the µPAD. The loading position of the reagents and the type of a sample flow channel were optimized to achieve a sensitive ammonia detection within a short analytical time. The NH₃ µPAD exhibits a linear colorimetric response to the concentration of ammonia dissolved in water in the range of 1-100 mg L^-1, and its limit-of-detection is 1.75 mg L^-1. In addition, the colorimetric response was not influenced by the addition of 100 mg L^-1 nitrogen containing compounds (sodium nitrate, sodium nitrite, uric acid, hydroxylamine, butylamine, diethylamine) or inorganic salts (NaCl, Na₂HPO₄), presenting the enough selectivity in the detection of water-dissolved ammonia against possible interferents.