• 산업경영시스템학회지
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• 제42권3호
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• pp.52-60
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• 2019

This paper presents a numerically robust algorithm to construct a Voronoi diagram of circles in the plane. The circles are allowed to have intersections among them, but one circle cannot fully contain another circle. The Voronoi diagram is a tessellation of the plane into Voronoi regions of given circles. Each circle has its Voronoi region which is defined by a set of points in the plane closer to the circle than any other circles. The distance from a point p to a circle $c_i$ of center $p_i$ and radius $r_i$ is ${\parallel}p-p_i{\parallel}-r_i$, which is the closest Euclidean distance from p to the circle boundary. The proposed algorithm first constructs the point Voronoi diagram of centers of given circles, then it enlarges each point to the circle and expands its Voronoi region accordingly. This region-expansion process is done by local modifications and after completing this process for the whole circles the desired circle Voronoi diagram can be obtained. The proposed algorithm is numerically robust and we provide with a few examples to show its robustness. The algorithm runs in $O(n^2)$ time in the worst case and O(n) time on average where n is the number of the circles. The experiment shows that the region-expansion algorithm is robust and runs fast with strong linear time behavior.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.

• 한국미생물·생명공학회지
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• 제49권2호
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• pp.249-254
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• 2021

The study of the impact of weather on viral respiratory infections enables the assignment of causality to disease outbreaks caused by climatic factors. A better understanding of the seasonal distribution of viruses may facilitate the development of potential treatment approaches and effective preventive strategies for respiratory viral infections. We analyzed the incidence of human mastadenovirus infection using real-time reverse transcription polymerase chain reaction in 9,010 test samples obtained from Cheonan, South Korea, and simultaneously collected the weather data from January 1, 2012, to December 31, 2018. We used the data collected on the infection frequency to detect seasonal patterns of human mastadenovirus prevalence, which were directly compared with local weather data obtained over the same period. Descriptive statistical analysis, frequency analysis, t-test, and binomial logistic regression analysis were performed to examine the relationship between weather, particulate matter, and human mastadenovirus infections. Patients under 10 years of age showed the highest mastadenovirus infection rates (89.78%) at an average monthly temperature of 18.2℃. Moreover, we observed a negative correlation between human mastadenovirus infection and temperature, wind chill, and air pressure. The obtained results indicate that climatic factors affect the rate of human mastadenovirus infection. Therefore, it may be possible to predict the instance when preventive strategies would yield the most effective results.

• 산경연구논집
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• 제12권6호
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• pp.7-21
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• 2021

Purpose: Modern globalization and Western markets saturation has catalyzed the growth of culinary globalization into developing countries. The question was whether fast food consumers in frontier markets of Sub-Saharan Africa (Zimbabwe), either upholds national gastronomic tendencies in terms of consumer ethnocentrism and buy local or they adopt global fast food brands. Demographic consumer profiles were also analyzed as antecedents of consumer ethnocentrism. Research design, data and methodology: A sample size of 400 fast food-adult consumers was surveyed in the City of Harare. Data was captured on SPSS and Analysis of Moment Structure (AMOS). Hypothesis testing was done using sample t test (H₁), logistic regression (H₂) and multiple regression (H₃, ₄, ₅) analysis. Results: Consumer ethnocentrism in Zimbabwe was marginally above average and no statistically significant relationship between the levels of consumer ethnocentrism and adoption of foreign fast food brands was noted. Age had an inverse relationship; income had a positive association whilst gender had no statistical significance with consumer ethnocentrism. Conclusions: Despite the Zimbabwean consumers being marginally ethnocentric, international restaurateurs should invest in the Zimbabwean fast food market since their nature of being foreign has got an exotic appeal to the Zimbabwean consumers thereby enhancing their likelihood of success.

• 대한화상학회지
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• 제24권2호
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• pp.30-33
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• 2021

Purpose: Dalgona, a kind of candy made of caramelized sugar, is a popular snack for children. Given the popularity of preparing dalgona, increasingly many patients are treated for burns sustained while preparing dalgona. We report the clinical features and dangers of burns from dalgona. Methods: We retrospectively reviewed the clinical records of 11 inpatients and outpatients who had been treated for burns they received while preparing dalgona from March 2020 to December 2020. The data reviewed were age, sex, the severity of the burn, the size and location of the burn, the type of treatment, and the place where the injury occurred. Results: The age of the patients ranged from 3 to 19 years, and the average age was 10.2 years (2 male, 9 female). Three patients had superficial second-degree burns, while eight had deep second-degree or third-degree burns. Most of the cases were treated with a local skin flap or skin graft. All the burned lesions were on the hands and feet. In all cases, the burns occurred at home due to accidental spillage. Conclusion: Most of the patients were children and teenagers, and they had serious burns. Therefore, we report these findings to emphasize the need for public awareness of the potential for burn injuries to occur during dalgona preparation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• International Journal of Internet, Broadcasting and Communication
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• 제14권1호
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• pp.194-200
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• 2022

As of 2020, the cumulative number of electric vehicles worldwide increased 43% from 2019, exceeding 10 million. We surveyed and analyzed important factors when purchasing electric vehicles for consumers who own electric vehicles. Through this, we tried to find an effective way to supply electric vehicles in the future. The purpose of this study is to present customized marketing proposals for companies by empirically analyzing the factors affecting consumers' electric vehicle purchases and deriving market demands for electric vehicles. We identified the market status of electric vehicles through literature research and reviewed previous studies on the factors affecting the purchase intention of electric vehicles. Through empirical studies, differences in electric vehicle purchase factors according to gender, age, and the degree of importance of performance were analyzed. To this end, the SPSS statistics package was used. Factors influencing the purchase of electric vehicles were set to mileage, charging time, new technology, degree of driving autonomous development, design, price, infrastructure for charging, the phase of maintenance and repair, by the government and local governments. In addition, the most important factors were derived, and the average difference analysis was conducted according to gender, age, and performance importance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4456-4475
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• 2021

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras. Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information. Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors. This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features. A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity. The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%), CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works. The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.

• 유통과학연구
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• 제20권10호
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• pp.19-29
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• 2022

Purpose: This study was conducted to gauge the economic evaluation and sample distribution of conserving the Belum Royal State Park (BRSP) in Perak, Malaysia and to identify factors influencing its use by the community. This study aims to examine community perception on the conservation of the Belum Royal State Park (BRSP) and maximum community's willingness to pay for park entry permits fees. Research design, data and methodology: A questionnaire survey was conducted involving a total of 280 respondents. The study adopted the Dichotomous Choice Contingent Valuation Approach (DC-CVM) and the Logistic Model, to estimate the maximum community's willingness to pay for park entry permits fees. Results: The results established that the factors of respondent's occupation, income, ecotourism influence on the BRSP and maximum entry price, significantly influenced visitors' decision on community's willingness to pay. The average community's willingness to pay was RM9.68 per person. Conclusions: In conclusion, surveillance and patrols in protected areas should be expanded. The extra expense for ensuring safety can be offset through income from ecotourism that should also benefit the local community on economic evaluation and equal distribution on the BRSP.

• Current Optics and Photonics
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• 제6권1호
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• pp.44-50
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• 2022

An off-axis zone plate is able to focus on a single order while neglecting the zeroth order in a visible imaging system. This allows one to enhance the contrast quality in diffractive images, which is the major advantage of this type of zone plate. However, most previous reflection zone plates are used in focusing X-rays with a small grazing incident angle and are intricately designed with the use of a local grating period. In this study, we suggest the design of an off-axis elliptical zone plate (EZP) that is used to focus a monochromatic light beam with separation between the first and unfocused orders under a large grazing incident angle of 45°. An assumption using the total grating period, which depends on the average and constant grating period, is proposed to calculate the desired distance between the first and zeroth order and to simplify the construction of a novel model off-center EZP. Four diffractive optical elements (DOEs) with different parameters were subsequently fabricated by direct laser lithography and then verified using a performance evaluation system to compare the results from the assumption with the experimental results.