• Journal of Korean Neurosurgical Society
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• v.50 no.5
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• pp.409-414
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• 2011

Objective : The aim of this study was to evaluate the impact of sodium hyaluronate-sodium carboxymethyl cellulose (HA-CMC), an anti-adhesive material for spinal surgery, on bone fusion by applying it to rat spinal models after lumbar posterolateral fusion. Methods : Lumbar posterolateral fusion was performed at L4-5 using bone graft substitutes in 30 rats. HA-CMC was injected in 15 rats at a dose of 0.2 cc (HA-CMC group) and a saline solution of 0.2 cc in the other 15 rats (control group). Simple radiographs were taken until postoperative 9 weeks with an interval of one week. At postoperative 4 and 9 weeks, three dimensional computed tomography (3D CT) scanning was performed to observe the process of bone fusion. At 9 weeks, bone fusion was confirmed by gross examination and manual palpation. Results : There were no statistically significant differences in bone fusion between the two groups. 3D CT scanning did not reveal significant differences between the groups. The gross examination and manual palpation after autopsy performed at 9 weeks confirmed bone union in 93.3% of both groups. Conclusion : The anti-adhesive material used for spinal surgery did not have adverse effects on spinal fusion in rats.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5392-5418
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• 2017

The primary aim of this paper is to propose a non-linear regression based technique for mapping different network Quality of Service (QoS) factors to an integrated end-user Quality of Experience (QoE) or Mean Opinion Score (MOS) value for an online video streaming service on a mobile phone. We use six network QoS factors for finding out the user QoE. The contribution of this paper is threefold. First, we investigate the impact of the network QoS factors on the perceived video quality. Next, we perform an individual mapping of the significant network QoS parameters obtained in stage 1 to the user QoE based upon a non-linear regression method. The optimal QoS to QoE mapping function is chosen based upon a decision variable. In the final stage, we evaluate the integrated QoE of the system by taking the combined effect of all the QoS factors considered. Extensive subjective tests comprising of over 50 people across a wide variety of video contents encoded with H.265/HEVC and VP9 codec have been conducted in order to gather the actual MOS data for the purpose of QoS to QoE mapping. Our proposed hybrid model has been validated against unseen data and reveals good prediction accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.821-832
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• 2021

Economic deprivation of households remains a significant economic issue in the world. Researchers have shown great concern in identifying crucial factors to enhance poor households' socio-economic performance. Therefore, this paper aims to develop a new conceptual framework to investigate the influence of different microfinance services on households' socioeconomic performance using moderated mediation analysis of various crucial factors. Focus-group interviews with managements of the microfinance institution, i.e. Amanah Ikhtiar Malaysia (AIM), and a systematic literature review were conducted for this purpose, and a new framework for the future study has been developed. The result from focus-group interviews and systematic literature review propose microfinance financial services, training programs, and business coaching as independent factors, whereas household socioeconomic performance as a dependent factor in the proposed model. Specifically, this study provides the direction to scholars to empirically test the direct relationship between financial services and household socioeconomic performance and the indirect relationship between training programs, business coaching, and household socioeconomic performance. Further, microfinance institutions' service efficiency is also included as a moderator that can strengthen microfinance services' effectiveness. The study also provides useful implications for policymakers, financial institutions, households, micro-enterprises, and researchers to better understand microfinance interventions and household economic mechanisms.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1301-1311
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• 2022

Global climate change brings environmental quality sensitivity, especially in developed countries. Developed countries use non-renewable energy sources intensively both in their own countries and in other countries, they make productions that cause an enormous rate of increase in CO₂ emissions and unsustainable environmental costs. This has increased the interest in environmentally friendly alternative energy sources. The aim of this study is to investigate the impact of nuclear energy consumption and technological innovation on environmental quality in G7 countries using annual data over the period 1970-2015. The Panel Threshold Regression Model was used for the analysis. Empirical findings have indicated that the relationship between nuclear energy consumption and carbon emissions differs according to innovation for nuclear power plants. It was also concluded that nuclear energy consumption reduces carbon emissions more after a certain level of innovation. This result shows that the increase in innovative technologies for nuclear power plants not only increases energy efficiency but also contributes positively to environmental quality.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.145-156
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• 2022

Children are the foundation and future of this society and understanding their impressions and behaviors is very important and the child's behavioral problems are a burden on the family and society as well as have a bad impact on the development of the child, and the early diagnosis of these problems helps to solve or mitigate them, and in this research project we aim to understand and know the behaviors of children, through artificial intelligence algorithms that helped solve many complex problems in an automated system, By using this technique to read and analyze the behaviors and feelings of the child by reading the features of the child's face, the movement of the child's body, the method of the child's session and nervous emotions, and by analyzing these factors we can predict the feelings and behaviors of children from grief, tension, happiness and anger as well as determine whether this child has the autism spectrum or not. The scarcity of studies and the privacy of data and its scarcity on these behaviors and feelings limited researchers in the process of analysis and training to the model presented in a set of images, videos and audio recordings that can be connected, this model results in understanding the feelings of children and their behaviors and helps doctors and specialists to understand and know these behaviors and feelings.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.49-60
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• 2024

This study used the Unified Theory of Acceptance and Use of Technology(UTAUT) model to find factors that influence consumer acceptance intention toward Vertiport, a physical ground support technology required to implement AAM services. The analysis showed that among the four independent variables, Vertiport's social influence and facilitating conditions have a significant impact on future Vertiport usage behavior. At this point, the public has not yet had actual experience with Vertiport, so there is a limitation of considering it as a future concept based on speculation and measuring acceptance by actual behaviors related to its use (inquiries, information gathering, interest, etc.). Research on acceptance and attitudes toward new transportation methods should be further activated and developed along with future service development. Through the results of this study, we aim to understand the initial public acceptance of Vertiport as a ground-based infrastructure in the AAM field (or UAM) and propose strategic implications for the direction of service development.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.1
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• pp.73-84
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• 2020

Recently, there has been a change in consumer culture. The paradigm is changing from a consumption model that used to emphasize rationality to an ethical consumption model that focuses on sustainability. Such a change in consumption patterns has also been seen in the cosmetics industry, but studies to empirically assess this trend are incomplete. Therefore, the purpose of this study is to empirically identify the impact of ethical consumption proprieties on attitudes and purchasing intentions for ethical cosmetics. To achieve the aim of this study, 506 adult women residing in Korea were selected as subjects and surveyed. To identify the demographic characteristics of the study participants, a technical statistical analysis and frequency analysis were conducted. To check the validity and reliability of the measuring tools, an exploratory factor analysis was performed, and the Cronbach's α factor was calculated. The analysis method was analyzed using the SPSS 25.0 and the Amos 25.0 statistical analysis programs. The results of this study are as follows. First, ethical spending tendencies had a positive impact on attitudes toward ethical cosmetics. Specifically, interest in ethical issues, altruism, and business ethics perception have had a positive impact on attitudes toward ethical cosmetics. However, consumer effectiveness had no significant impact on attitudes toward ethical cosmetics. Second, attitudes toward ethical cosmetics had a positive effect on purchasing intentions. This study found that for the spread of ethical cosmetics and ethical consumption trends varied according to the age and that attitudes toward ethical cosmetics and differences in purchasing intentions should be kept in mind. It also showed that attitudes toward ethical cosmetics affect purchasing intentions. The results of this study suggested that the analysis of adult women, the main consumers of cosmetics, by age was meaningful for finding the factors for growth in the macroscopic ethical cosmetics industry and that the industry could raise its ethical awareness. If such tasks are systematically established, ethical cosmetics are thought to be able to actively solve social problems and lead a mature cosmetics industry.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.3
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• pp.408-415
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• 2020

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas. Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit. Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values. Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

• Geomechanics and Engineering
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• v.20 no.3
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• pp.191-205
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• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.