Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.
This paper is written to introduce and review Shinji Matsunaga's The Aesthetics of Video Games which published in Japan in 2018. Shinji Matsunaga has studied video games from a philosophical and aesthetic perspective. In The Aesthetics of Video Games, he took video games as a hybrid form of traditional games. Shinji Matsunaga particularly notes that video games can design human behaviors and experiences. From this point of view, he tries to construct a theoretical framework that will be able to describe the ways of signification in games and fiction respectively. In previous studies, video games have been mainly discussed in the context of cultural studies and entertainment culture in Japan. The Aesthetics of Video Games is distinguished from the previous studies in the following points. First, The Aesthetics of Video Games pioneered the method of studying video games in art theory. Second, it established various types of relationships with video games and traditional aesthetic concepts. Third, this book connects new concepts that emerged in the age of artificial intelligence to video games as an aesthetic action. Through this work, not only video games were discussed academically, but also the fields of aesthetics and art were expanded. The Aesthetics of Video Game is like a collection of philosophical concepts for video games. Through this book, it can be said that the path for artificial intelligence to approach human secrets is closer than before.
Journal of Korea Entertainment Industry Association
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v.14
no.3
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pp.431-442
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2020
This study examined the effect of the theratainment swiss ball exercise on the upper limb function, pain, and daily activities of a patient with axillary nerve injury. The research duration was from November 5th, 2019 to February 25th, 2020. The research subject was a 23-year-old female patient living in the metropolitan city of G in South Korea, and the A-B-A' type of single-subject experimental research design was used. In this study, repeated training was provided to the patient in the form of exercises employing different directions and gradually increased weights. The training increased the structural stability and mobility of the shoulder and was effective for pain relief as it strengthened shoulder function. The training helped the subject improve her posture change adaptability and reaction ability in different environments and ultimately enabled her to increase and maximize her performance of independent daily activities. This study thus demonstrated the positive effect of the Swiss ball exercise on the upper limb function, pain and disability, daily activities of a patient with axillary nerve injury and confirmed the potential of the exercise as an intervention method. Continued investigation to develop and test the effect of the Swiss ball exercise will be required for it to be used professionally as a therapeutic approach by occupational therapists in treating a variety of patients.
As an emerging power generation technology, triboelectric nanogenerators (TENGs) have received increasing attention due to their boundless promise in energy harvesting and self-powered sensing applications. The recent rise of soft robotics has sparked widespread enthusiasm for developing flexible and soft sensors and actuators. TENGs have been regarded as promising power sources for driving actuators and self-powered sensors, providing a unique approach for the development of soft robots with soft sensors and actuators. In this review, TENG-based soft robots with different morphologies and different functions are introduced. Among them, the design of biomimetic soft robots that imitate the structure, surface morphology, material properties, and sensing/generating mechanisms of nature has greatly benefited in improving the performance of TENGs. In addition, various bionic soft robots have been well improved compared to previous driving methods due to the simple structure, self-powering characteristics, and tunable output of TENGs. Furthermore, we provide a comprehensive review of various studies within specific areas of TENG-enabled soft robotics applications. We first explore various recently developed TENG-based soft robots and a comparative analysis of various device structures, surface morphologies, and nature-inspired materials, and the resulting improvements in TENG performance. Various ubiquitous sensing principles and generation mechanisms used in nature and their analogous artificial TENG designs are demonstrated. Finally, biomimetic applications of TENG enabled in tactile displays as well as in wearable devices, artificial electronic skin and other devices are discussed. System designs, challenges and prospects of TENGs-based sensing and actuation devices in the practical application of soft robotics are analyzed.
Purpose - This paper examines South Korea's potential status as a carbon leakage country, and the level of risk posed by the Korean emissions trading scheme (ETS) for Korean industries. The economic effects of border carbon adjustments (BCAs) to protect energy-intensive Korean industries in the process of achieving the carbon reduction target by 2030 through the Korean ETS are also analyzed. Design/methodology - First, using the Korean Input-Output (IO) table, this paper calculates the balance of emissions embodied in trade (BEET) and the pollution terms of trade (PTT) to determine Korean industries' carbon leakage status. Analyses of the risk level posed by carbon reduction policy implementation in international trade are conducted for some sectors by applying the EU criteria. Second, using a computable general equilibrium (CGE) model, three BCA scenarios, exemption regulations (EXE), reimbursement (REB), and tariff reduction (TAR) to protect the energy-intensive industries under the Korean ETS are addressed. Compared to the baseline scenario of achieving carbon reduction targets by 2030, the effects of BCAs on welfare, carbon leakage, outputs, and trading are analyzed. Findings - As Korea's industrial structure has been transitioning from a carbon importing to a carbon leaking country. The results indicate that some industrial sectors could face the risk of losing international competitiveness due to the Korean ETS. South Korea's industries are basically exposed to risk of carbon leakage because most industries have a trade intensity higher than 30%. This could be interpreted as disproving vulnerability to carbon leakage. Although the petroleum and coal sector is not in carbon leakage, according to BEET and PTT, the Korean ETS exposes this sector to a high risk of carbon leakage. Non-metallic minerals and iron and steel sectors are also exposed to a high risk of carbon leakage due to the increased burden of carbon reduction costs embodied in the Korean ETS, despite relatively low levels of trade intensity. BCAs are demonstrated to have an influential role in protecting energy-intensive industries while achieving the carbon reduction target by 2030. The EXE scenario has the greatest impact on mitigation of welfare losses and carbon leakage, and the TAF scenario causes a disturbance in the international trade market because of the pricing adjustment system. In reality, the EXE scenario, which implies completely exempting energy-intensive industries, could be difficult to implement due to various practical constraints, such as equity and reduction targets and other industries; therefore, the REB scenario presents the most realistic approach and appears to have an effect that could compensate for the burden of economic activities and emissions regulations in these industries. Originality/value - This paper confirms the vulnerability of the Korean industrial the risk of carbon leakage, demonstrating that some industrial sectors could be exposed to losing international competitiveness by implementing carbon reduction policies such as the Korean ETS. The contribution of this paper is the identification of proposed approaches to protect Korean industries in the process of achieving the 2030 reduction target by analyzing the effects of BCA scenarios using a CGE model.
Journal of The Korean Association For Science Education
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v.42
no.2
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pp.227-238
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2022
One of the main roles of the science teacher is to help students become active agents in their learning of science. This study described how an elementary science teacher used students' emotional resources to conduct emotionally responsive teaching and what were the learning outcomes of this approach. The participants of the study included the teacher himself and his 6th grade students, and emotionally responsive teaching was applied in the science unit of 'Various Living Things and Our Human Lives'. Multiple types of data, including the teacher's teaching logs, video recordings of the lessons in the unit, and interviews with the students, were collected. The data were analyzed qualitatively, and the results were described using a self-study method. The teacher took advantage of three kinds of students' emotional resources (i.e., character drawing, t-shirt design, and raps) to organize his emotionally responsive teaching. The learning outcome included the students' positive emotions and active participation in science lessons, their epistemic practices such as explorations and justifications of knowledge, and the students' reconstruction of knowledge in consideration of their everyday lives. It was suggested that emotionally responsive teaching can promote elementary school students' active participation in science learning, resulting in meaningful learning outcomes in emotional, cognitive, and conceptual aspects. Further studies should thus be conducted to understand the characteristics of emotionally responsive teaching and its detailed teaching strategies.
We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.
Purpose - Based on literature studies of movie reviews and movie ratings, this study raised two research questions on the contents of online word of mouth and the number of movie screens as mediator variables. Research question 1 wanted to figure out which topics of word groups had a positive or negative impact on movie ratings. Research question 2 tried to identify the role of the number of movie screens between movie ratings and box office outcomes. Design/methodology/approach - Through R program, this study collected about 82,000 movie reviews and movie ratings posted on Naver's movie website to examine the role of online word of mouths and movie screen counts in 10 movies that were considered commercially unsuccessful with fewer than 2 million viewers despite securing about 1,000 movie screens. To confirm research question 1, topic modeling, a text mining technique, was conducted on movie reviews. In addition, this study linked the movie ratings posted on Naver with information of KOBIS by date, to identify the research question 2. Findings - Through topic modeling, 5 topics were identified. Topics found in this study were largely organized into two groups, the content of the movie (topic 1, 2, 3) and the evaluation of the movie (topics 4, 5). When analyzing the relationship between movie reviews and movie ratings with 5 mediators identified in topic modeling to probe research question 1, the topic word groups related to topic 2, 3 and 5 appeared having a negative effect on the netizen's movie ratings. In addition, by connecting two secondary data by date, analysis for research question 2 was implemented. The outcomes showed that the causal relationship between movie ratings and audience numbers was mediated by the number of movie screens. Research implications or Originality - The results suggested that the information presented in text format was harder to quantify than the information provided in scores, but if content information could be digitalized through text mining techniques, it could become variable and be analyzed to identify causality with other variables. The outcomes in research question 2 showed that movie ratings had a direct impact on the number of viewers, but also had indirect effects through changes in the number of movie screens. An interesting point is that the direct effect of movie ratings on the number of viewers is found in most American films released in Korea.
Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.
Journal of the Korean Society for information Management
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v.40
no.3
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pp.245-271
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2023
The purpose of this study was to assess the perception of e-book subscription services among the digitally native generation in their twenties, who have a high e-book usage rate. This study employed a mixed-methods approach, combining survey responses and usability testing. It aimed to assess the awareness and usage of e-book subscription services among university students in their twenties, a demographic known for their high utilization of electronic devices and e-books. The survey was conducted among 202 university students, and the responses were categorized and examined based on whether they were users or non-users. As a result of the survey, I found there is different awareness of e-book between users and non-users, on the other hand, convenience and portability are the strong point of e-books for users and non-users commonly also. Usability testing was performed on a group of 10 university students in their twenties who had not previously used the 'Millies Library' application, which is renowned as the most widely-used e-book platform. Following the experiment, participants expressed positive feedback regarding various optional features, convenience, design, and cost-effectiveness. However, they also had negative reactions concerning touch errors, malfunctions, functional practicality, a lack of interest, system issues, and the absence of a library.
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