• Food Science of Animal Resources
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• v.37 no.1
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• pp.79-86
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• 2017

Aflatoxin $M_1$ ($AFM_1$) after its bioconversion from aflatoxin $B_1$ in animal liver becomes the part of milk while heavy metals get entry into milk and milk products during handling in the supply chain. Aflatoxin $M_1$ and heavy metals being toxic compounds are needed to be monitored continuously to avoid any ailments among consumers of foods contaminated with such toxicants. Thirteen commercially available infant formula milk (IFM) brands available in Pakistani markets were analyzed for the quantitative determination of $AFM_1$ and heavy metals through ELISA and atomic absorption spectrophotometer, respectively. $AFM_1$ was found positive in 53.84% samples while 30.76% samples were found exceeding the maximum EU limit i.e. $0.025 {\mu}g/kg$ for $AFM_1$ in IFM. Heavy metals lead (Pb) and cadmium (Cd) were found below the detection limits in any of the sample, whereas the concentrations of iron (Fe), zinc (Zn) and nickel (Ni) ranged between 45.40-97.10, 29.72-113.50 and <$0.001-50.90 {\mu}g/kg$, respectively. The concentration of Fe in all the tested brands was found in normal ranges while the concentrations of Zn and Ni were found exceeding the standard norms. Elevated levels of $AFM_1$, Zn and Ni in some of the tested IFM brands indicated that a diet completely based on these IFM brands might pose sever health implications in the most vulnerable community i.e., infants.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• Journal of Environmental Health Sciences
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• v.40 no.3
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• pp.178-186
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• 2014

Background: This study was conducted to assess health risks in regard to exposure by children to volatile organic compounds (VOCs) in children's products. Methods: Ten VOCs were measured by head-space gas chromatography in children's products, including toys, oil pastels, sign pens, furniture, ball pools, and playmats. We estimated the average daily dose (ADD) via inhalation during the use of these children's products and calculated hazard quotient (HQ) by dividing ADD by reference dose of VOCs. Results: Among the measured VOCs, five compounds were identified in children's products: benzene, ethylbenzene, styrene, toluene, and xylene. The detection rates of VOCs in toys, ball pools, furniture, playmats, sign pens, and oil pastels were 85%, 100%, 100%, 30%, 100%, and 60%, respectively. The maximum levels of VOCs were 0.18 mg benzene/kg in toys, 5.92 mg toluene/kg in playmats, 10.37 mg ethylbenzene/kg in ball pools, 24.85 mg xylene/kg in toys, and 118.29 mg styrene/kg in ball pools. From exposure levels of VOCs in the children's products HQs were calculated within a range of $5.71{\times}10^{-10}$ to $4.77{\times}10^{-4}$. The HQ of xylene was the highest for children aged 0-6 playing on the playmats. However, the HQ via inhalation exposure to VOCs in individual products did not exceed 1.00. Conclusion: Based on the results, it was concluded that the use of these children's products do not pose health risks to children.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.597-606
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• 2010

This paper describes a real-time camera tracking framework specifically designed to track a monocular camera in an AR workspace. Typically, the Kalman filter is often employed for the camera tracking. In general, however, tracking performances of conventional methods are seriously affected by unpredictable situations such as ambiguity in feature detection, occlusion of features and rapid camera shake. In this paper, a recursive Bayesian sampling framework which is also known as the particle filter is adopted for the camera pose estimation. In our system, the camera state is estimated on the basis of the Gaussian distribution without employing additional uncertainty model and sample weight computation. In addition, the camera state is directly computed based on new sample particles which are distributed according to the true posterior of system state. In order to verify the proposed system, we conduct several experiments for unstable situations in the desktop AR environments.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.52 no.1
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• pp.19-26
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• 2019

The objective of this study was to analyze bacteriological and chemical hazards in minimally processed commercial fish products, including Hwangtae (freeze-dried pollock), dried anchovy, fermented anchovy sauce, and salted and dried yellow croaker. Escherichia coli counts from all samples were below the regulation limits of the Korean Ministry of Food and Drug Safety Standards on Quality of Seafood and Seafood Products (Food Code). However, the food poisoning bacterium Staphylococcus aureus was detected at levels above $1.0{\times}10^2$ colony forming units (CFU)/g in Hwangtae, dried anchovy, and salted and dried yellow croaker, which are commonly ingested without heating and pose bacteriological hazards. The detection of S. aureus, an organism indicative of poor personal hygiene, which can be introduced by employees and multiply during distribution, indicates the necessity of improving the sanitary control of minimally processed commercial fish products. Histamine was not detected from dried anchovy or salted and dried yellow croaker, but was detected at some of the highest levels in fermented anchovy sauces. This result suggests that efforts to reduce the amount of histamine in fermented anchovy sauces are required.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.257-261
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• 2022

Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.

• Knowledge Management Research
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• v.24 no.3
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• pp.1-15
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• 2023

This paper examines research ethics in using the generative AI ChatGPT for research purposes. After reviewing traditional themes of research ethics and relevant principles, it will be argued to be inappropriate to discuss ChatGPT-related issues only from the perspective of permission, detection, and punishment. We need to consider the fundamental problem that the current rules pose concerning the way ChatGPT works. This leads to the proposal that the usage of ChatGPT should be clearly noted when it is used for research purposes and that some unresolved issues should be recognized. Although the advantages of ChatGPT cannot be denied, consensus on the appropriate scope of use is needed from perspectives of the research community and researcher's social responsibility. As generative artificial intelligence technologies are still in the early stages of development, researchers should pay attention to relevant research ethical issues, while not making hasty conclusions. In the conclusion, it will be also proposed to discuss and make a consensus regarding the definition of research that is premised on existing research ethics, but challenged with the advent of ChatGPT and AI technology.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.69-75
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• 2024

This study focuses on enhancing the understanding of the form and characteristics of traditional towers, or 'pagodas,' by utilizing WebXR technology to enable users to explore 3D models and experience them in virtual reality on the web. Traditional towers in Korea pose challenges for direct on-site verification due to their size, making it difficult to examine the structure and features of each level. To address these issues, this research aims to provide users with a WebXR service that allows them to remotely explore and analyze towers without geographical or temporal constraints. The research methodology involves utilizing WebAR to offer a web-based service where users can directly view the original form of the tower's 3D model using smart devices both online and on-site. However, outdoor conditions may affect performance, and to address this, a tower-outline detection and matching technique was employed. Consequently, we propose a remote support service for traditional towers, allowing users to remotely access information and features of various towers nationwide on the web. Meanwhile, on-site visits can involve experiencing augmented reality representations of towers using smart devices.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.441-448
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• 2010

In the aging society, the walking assist robot is a necessary device for being able to help the older and the lower limb disabled people to walk. In order to produce a convenient robot for the older and the lower limb disabled, it is needed for the research to detect the implicit walking intention and to control robot by a user's intention. This study is a previous study to develop the detection model of the walking intention and analyze the user's walking intention while a person is walking with Lofstrand crutches, by the combination of FSR and tilt signals. The FSR sensors attached user's the palm and the soles of foot are sensing force/pressure signals from these areas and are used for detecting the walking intention and states. The tilt sensor acquires roll and pitch signal from area of vertebrae lumbales and reflects the pose of the upper limb. We can recognize the user's walking intention such as 'start walking', 'start of right or left foot forward', and 'stop walking' by the combination of FSR and tilt signals can recognize.

• Environmental Mutagens and Carcinogens
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• v.24 no.1
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• pp.33-39
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• 2004

To validate and to estimate the chemical hazard playa very important role to environment and human health. The detection of many synthetic chemicals including agrochemicals that may pose a genetic hazard in our environment is of great concern at present. Since these substances are not limited to the original products, and enter the environment, they have become widespread environmental pollutants, thus leading to a variety of chemicals that possibly threaten the public health. Pyrazosulfuron-ethyl [Ethyl-5-(4,6-dimethoxypyrimidin-2-ylcarbamoylsulfamoyl)-1-methylpyrazole-4-carboxylate, $C_{14}H_{18}N{6}O_{7}S,$ M.W. =414.39, CAS No. 93697-74-6], is one of well known rice herbicide belong in the sulfonyl urea group. To clarify the genotoxicity of this agrochemical, Ames bacterial reversion assay, in vitro chromosomal aberration assay with Chinese hamster lung (CHL) fibroblast and bone marrow micronucleus assay in mice were subjected. In Ames assay, although pyrazosulfuron-ethyl revealed cytotoxic at 5,000-140 $\mug/plate$ in Salmonella typhimurium TA100, no dose-dependent mutagenic potential in 4.4～70 $\mug/plate$ of S. typhimurium TA 98, TA 100, TA1535 and TA 1537 both in the absence and presence of S-9 metabolic activation system was observed. Using CHL fibroblasts, the 50% cell growth inhibition concentration $(IC_{50})$ of pyrazosulfuron-ethyl was determined as 1,243 $\mug/mL,$ and no chromosomal aberration was observed both in the absence and presence of S-9 mixture in the concentration range of 311-1,243 $\mug/mL.$ And also, in vivo micronucleus assay using mouse bone marrow, pyrazosulfuron-ethyl revealed no remarkable induction of MNPCE (micronucleated polychromatic erythrocytes/1000 polychromatic erythrocytes) in the dose range of 625-2,500 mg/kg body weight when administered orally. Consequently, Ames bacterial gene mutation with Salmonella typhimurium, in vitro chromosome aberration with mammalian cells and in vivo bone marrow micronucleus assay revealed no clastogenic potential of pyrazosulfuron-ethyl in this study.