• Journal of Communications and Networks
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• v.14 no.5
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• pp.518-523
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• 2012

This paper presents new coherent and non-coherent detection methods for the IEEE 802.15.4a low-rate ultra-wideband physical layer with forward error correction (FEC) coding techniques. The coherent detection method involving channel estimation is based on the correlation characteristics of the preamble signal. A coherent receiver uses novel iterated selective-rake (IT-SRAKE) to detect 2-bit data in a non-line-of-sight channel. The non-coherent detection method that does not involve channel estimation employs a 2-bit data detection scheme using modified transmitted reference pulse cluster (M-TRPC) methods. To compare the two schemes, we have designed an IT-SRAKE receiver and a MTRPC receiver using an IEEE 802.15.4a physical layer. Simulation results show the performance of IT-SRAKE is better than that of the M-TRPC by 3-9 dB.

• Nuclear Engineering and Technology
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• v.29 no.6
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• pp.500-507
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• 1997

The development of detection techniques is needed, in order for regulating authorities to determine whether or not a particular food sample has been irradiated, and label it accordingly so that a consumer's free choice can be exercised. The chemical and physical changes brought about in foods by practical doses of irradiation are very small, and therefore very sensitive methods are required. A number of promising approaches have been developed and evaluated. These include chemical, physical and biological methods ranging from the very simple to highly sophisticated techniques.

• The Journal of Korean Physical Therapy
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• v.22 no.4
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• pp.65-71
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• 2010

Purpose: The aim of this study was to describe the effects of conservative treatment intervention for individual with scoliosis. Methods: Studies were selected through a search of computerized databases of the literature (KERIS, 2000-2010) using "early detection", "conservative treatment", "exercise", "physical therapy", "manipulation", "chiropractic", "therapy", "taping" and "orthosis" as keywords. Selected articles were classified by research design and statistical methods. Results: Application of the search strategy to the KERIS databases resulted in 132 articles. Based on titles and abstracts, 17 studies were selected, excluding articles of overlapping study, surgery, pharmacologic therapy and no correcting aim under conservative treatment. Among the 17 selected studies, the majorityof study design consisted of one group pretest-posttest design and additionally most of these studies were paired (or independent) t-test. The most frequently used intervention was exercise therapy. Conclusion: All articles showed that interventions were effective. Thus, early detection of scoliosis may be connected participation of early conservative treatment. It is important to reduce prevalence of scoliosis in adolescents using regular evaluation as an effective measure.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.281.1-281.1
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• 2003

Purpose. The purpose of this study was to develop and validate sensitive and specific analytical method for determinination of simvastatin in human plasma by the column-switching high-performance liquid chromatography (HPLC) system with UV detection. Methods. Simvastatin and internal standard were extracted into diethyl ether from plasma. (omitted)

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7193-7196
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• 2013

Ovarian cancer patients need a surveillance program for the detection of tumor progression after completion of treatment. The methods generally consist of history taking, physical examination, tumor marker monitoring and imaging. However, the details of recurrence detection with each method are not well defined. To clarify this issue, ovarian cancer patients who achieved complete or partial responses and developed tumor progression at the follow up time between January 2004 and December 2010 in University Hospital Chiang Mai, Thailand, were reviewed. Clinical data, CA 125 level and imaging results at the tumor progression time were recorded and analyzed. There were 144 ovarian cancer patients meeting the inclusion criteria with the mean age of 51 years and 62.5% of them were in an advanced stage. Complete response was achieved in 89 patients (61.8%) after primary treatment. The median progression free survival and overall survival were 15.5 months and 37.5 months, respectively. Abnormal symptoms presented in 49.3% of the studied patients and 59.7% developed physical examination abnormalities. In addition, CA 125 was elevated in 89.6% while in 74.3% of tumor progression was identified by CT-scan. Short treatment time period and a high level of CA 125 were significant independent prognostic factors in these patients. In conclusion, careful history taking, physical examination and monitoring of CA 125 levels are important methods for tumor progression detection in a surveillance program for epithelial ovarian cancer patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3712-3729
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• 2020

Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

• Journal of Sensor Science and Technology
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• v.23 no.4
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• pp.217-223
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• 2014

Nerve agents are major chemical warfare agents with the "G series" and "V series" being the most widely known because of their lethal effect. Although not conspicuously used in major wars, the potential detrimental impact on modern society had been revealed from the sarin terror attack on Tokyo subway, which affected thousands of people. In this mini-review, major nerve agents of the "G series" and "V series" have been described along with various types of their detection methods. The physical properties and hydrolysis mechanisms of the major nerve agents are discussed since these are important factors to be considered in choosing detection methods, and specifying the procedures for sample preparations in order to enhance detection precision. Various types of extraction methods, including liquid-phase, solid-phase, gas-phase and solid-phase microextraction (SPME), are described. Recent development in the use of gas sensors for detecting nerve agents is also summarized.

• Current Research on Agriculture and Life Sciences
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• v.31 no.1
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• pp.1-10
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• 2013

The exposure of food to ionizing radiation has been recognized as a safe and effective mode of food preservation in more than 55 countries. The benefits include eradication of insect pests, inactivation of food pathogens, extension of shelf-life, and improvement in food hygiene. Regulatory authorities around the world have emphasized the implementation of various national and international regulations to facilitate trade and development of consumers' confidence in purchasing irradiated foods. Therefore, the need for reliable irradiation detection methods has increased to enforce these regulations. At present, a number of promising analytical approaches have been developed and evaluated. Moreover, about 10 European Standards have been adopted as General CODEX Alimentarius methods for the detection of irradiated foodstuffs. However, most of these methods demand relatively expensive equipment and prolonged sample preparation. Therefore, simple and cost-effective approaches would be advantageous for rapid screening of foodstuffs. The suspected samples need to be analyzed further with more validated techniques to confirm the screening results. In this review, existing screening methods (i.e. physical, chemical, and biological) for the identification of irradiated foods have been outlined along with their principles, scopes and limitations.

• Preventive Nutrition and Food Science
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• v.3 no.2
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• pp.203-209
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• 1998

The development of methods for the identification of irradiated foods helps enforce national and international regulations on labelling to ensure the consumer's free choice to buy irradiated or unirradiated foods. and the availabilityof such methods may assist the promotion of international trade in irradiated food products and help prevent abuse of the technology. A number of approaches to determine the physical , chemical, microbiological and biological changes that occur in foods treated with ionizing radiation have been studied. However no single method is universally applicable. Among physical measurements, the leading methods of indentification are electron spin resonance (ESR) spectroscopy and thermoluminescence(TL). ESR is an established non-destructive method for the analysis of free radicals from their traps and TL is the emission of light from irradiated mineral extracts by heating. Viscosity of carbohydrate polymers by causing chain breaks by irradiation, measuring the impedance of potatoes and detection of gases produced radiolytically are promising techniques for identification purposes. Irradiated water-containing foods show significant supercooling when monitored with a differential scanning calorimeter (DSC), which can be applied to identifying irradiated ones.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.77-80
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• 2023

Since fires in uncontrolled environments pose serious risks to society and individuals, many researchers have been investigating technologies for early detection of fires that occur in everyday life. Recently, with the development of deep learning vision technology, research on fire detection models using neural network backbones such as Transformer and Convolution Natural Network has been actively conducted. Vision-based fire detection systems can solve many problems with physical sensor-based fire detection systems. This paper proposes a fire detection method using the latest YOLOv8, which improves the existing fire detection method. The proposed method develops a system that detects sparks and smoke from input images by training the Yolov8 model using a universal fire detection dataset. We also demonstrate the superiority of the proposed method through experiments by comparing it with existing methods.