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Cognitive small cell networks, consisting of macro-cells and small cells, are foreseen as a promising candidate solution to address 5G spectrum scarcity. Recently, many technological issues (such as spectrum sensing, spectrum sharing) related to cognitive small cell networks have been studied, but the common control channel (CCC) establishment problem has been ignored. CCC is an indispensable medium for control message exchange that could have a huge significant on transmitter-receiver handshake, channel access negotiation, topology change, and routing information updates, etc. Therefore, establishing CCC in cognitive small cell networks is a challenging problem. In this paper, we propose a potential game theory-based approach for CCC establishment in cognitive radio networks. We design a utility function and demonstrate that it is an exact potential game with a pure Nash equilibrium. To maintain the common control channel list (CCL), we develop a CCC update algorithm. The simulation results demonstrate that the proposed approach has good convergence. On the other hand, it exhibits good delay and overhead of all networks.

Software applications have a huge and inseparable impact on our lives. The complexity of the applications increases rapidly to support high performance and multifunction. Accordingly, the cost model for applications is increasingly important. Line of Code (LOC) and Man-Month (M/M) as the cost model measure the quantitative sides of the applications. Unlike them, Function Point (FP) measures the functionalities of the application. FP is efficient for estimating qualitative characteristics, but it is restricted to measuring the cost of an application using the wireless data broadcast which can support any number of clients. In this paper, we propose, a Function Point model for Information services using wireles data Broadcast (FPIB) to measure the development cost of an application that serves using the wireless data broadcast environment. FPIB adopts critical parameters of the wireless broadcast environment and the complexity of them to measure effectively the cost developing the application. Through the evaluation comparing the proposed FPIB with FP, we reveal the effectiveness of the proposed FPIB.

Interest in virtual humans continues to increase due to the development of generative AI, extended reality, computer graphics technology, and the spread of a converged metaverse that goes beyond the boundaries between reality and virtuality. Despite the negative public opinion that virtual humans were just temporary form of entertainment event in the early days of their emergence, the reason they are showing continuous growth is due to the unique characteristics of virtual humans and the expansion of diverse usage from technological advancements. The production of video content using virtual humans is becoming vigorously active, but currently there is limitation and no exact process for the technology to apply virtual humans to video content for it to be produced accordingly to the characteristics or situations of virtual humans. In this study, we investigated the characteristics of virtual human production technology methods & processes, and identifying the impact of each production technology on the production environment through examples of virtual human content applied to domestic and international video contents. In conclusion, by proposing an appropriate production method for each content, we hope to develop and assist production practitioners so they can effectively use virtual humans in video content production.

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

The application of artificial intelligence (AI) is becoming increasingly important to coping with air pollution. AI is effective in coping with it in various ways including air pollution forecasting, monitoring, and control, which is attracting a lot of attention. This attention has created high need for analyzing studies on AI and air pollution. To contribute for satisfying it, this study performed bibliometric analyses on the studies on AI and air pollution from 2012 to 2022 using the Web of Science database. This study analyzed them in various aspects such as the trend in the number of articles, the trend in the number of citations, the top 10 countries of origin, the top 10 research organizations, the top 10 research funding agencies, the top 10 journals, the top 10 articles in terms of total citations, and the distribution by languages. This study not only reports the bibliometric analysis results but also reveals the eight distinct features in the research steam in studies on AI and air pollution, identified from the bibliometric analysis results. They are expected to make a useful contribution for understanding the research stream in AI and air pollution.

In this paper, we are interested in how creator economy startups allowing creators to make money from doing that they love. So, we look at European creator economy startups among Web3.0 business model landscape surveyed in 2022, because the US is home of Web2.0 giant platforms like YouTube. Totally seventeen European startups are investigated, and the theoretical logic is the disruptive innovation. We firstly review the survey published in 2022 and utilize the theory of the disruptive innovation to design the research framework including questions with each type of the disruptive innovation. In this paper, we firstly show, Kalao and Gem as NFT ecosystem platforms aim at service convenience. Secondly, Talkbase, Passionfroot, Bildr, Customuse, and Earnr aim at providing creator tools for under-skilled customers. Lastly, when it comes direct monetization with a decentralized business model, CrowdPad, Admix, GOALS, Realm, Dropstar, Pianity, Sonomo, Stage11, Miiji, and ReadyPlayerMe are representative. Despite the relatively small data size, the results are meaningful as they contribute to a more profound comprehension of the Web3.0 business models and offer guidance for future research directions.

The objective of this paper is to investigate digital transformation in logistics within the shipping and logistics industry. This paper examines the case of Hyundai Merchant Marine (HMM) and draws insights from its success in becoming the top company amidst the industry challenges. To achieve a more in-depth analysis, a single-case study approach was employed. Various secondary data have been analyzed to support the examination of HMM's digital transformation. HMM has emerged as a global leader in transportation services. The company's success is attributed to its development of diverse ships, robust logistics systems, and pioneering a digital logistics platform, ultimately overcoming the crisis. Especially, this paper show that the digitalization of logistics has been analyzed as the most significant transformation. The findings of this paper can offer valuable implications for other companies grappling with similar challenges in the current trade landscape.

This study delves into the subtle sounds emanating from beneath the earth's surface to unveil hidden messages and the movements of life. It transforms these acoustic phenomena into digital data and reimagines them as visual elements. By employing Sismophone microphones and utilizing the FFT function in p5.js, it analyzes the intricate frequency components of subterranean sounds and translates them into various visual elements, including 3D geometric shapes, flowing lines, and moving particles. This project is grounded in the sounds recorded in diverse 'spaces of death,' ranging from the tombs of Joseon Dynasty officials to abandoned areas in modern cities. We leverage the power of sound to transcend space and time, conveying the concealed narratives and messages of forgotten places .Through the visualization of these sounds, this research blurs the boundaries between 'death' and 'life,' 'past' and 'present,' aiming to explore new forms of artistic expression and broaden perceptions through the sensory connection between sound and vision.

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural languagebased comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

In AI image generation tools, most general users must use an effective prompt to craft queries or statements to elicit the desired response (image, result) from the AI model. But we are software engineers who focus on software processes. At the process's early stage, we use informal and formal requirement specifications. At this time, we adapt the natural language approach into requirement engineering and toon engineering. Most Generative AI tools do not produce the same image in the same query. The reason is that the same data asset is not used for the same query. To solve this problem, we intend to use informal requirement engineering and linguistics to create a toon. Therefore, we propose a sequence diagram and image generation mechanism by analyzing and applying key objects and attributes as an informal natural language requirement analysis. Identify morpheme and semantic roles by analyzing natural language through linguistic methods. Based on the analysis results, a sequence diagram and an image are generated through the diagram. We expect consistent image generation using the same image element asset through the proposed mechanism.

The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

Deleuze and Guattari introduced the concept of minority groups resisting the majorit. Minority groups consist of individuals who are excluded and marginalized by the majority. They advocate for a society in which these individuals, through mutual solidarity, can escape prejudice and fixed ideologies and lead a dignified human life. In this context, through his novels featuring protagonists with disabilities, Stéphane aimed to create an ideal societal atmosphere. The characters with disabilities in the novels incessantly strive toward life goals, emphasizing the importance of the process of effort and progress, even if the ultimate goals are not achieved. The dedicated pursuit of goals and the journey toward them hold significance beyond the attainment of objectives. Such an attitude and approach toward life by minority individuals is deemed sufficient to challenge the power structures established by the majority. This narrative challenges the societal norm and power structures, which highlights the value and meaning found in the process of striving and progressing, and ultimately contributes to breaking down societal barriers and fostering a more inclusive and equitable society.

This study delves into the unique transformation of South Korea's elderly population, distinctively termed 'Nomad Silver'. Characterized by individuals aged 65 and above who actively seek novel experiences and embrace new activities, this demographic shift signifies a departure from traditional perceptions of the elderly. The Nomad Silver cohort, distinguished by their significant economic influence and evolving needs, necessitates a tailored approach to healthcare services. This paper underscores the importance of comprehending both the fundamental biological needs and the personalized desires of the Nomad Silver, aiming to enhance their satisfaction and overall well-being. Hospitals, in response, should innovate their services to resonate with the emotional, psychological, and social facets of this age group. Consequently, the paper proposes a four-pronged strategy for hospitals to adapt: comprehensive healthcare provision, patientcentric service development, senior health education coupled with community engagement, and establishing a generational bridge hub. Furthermore, the paper posits that catering to the Nomad Silver not only promises substantial financial gains for hospitals but also fosters new business opportunities across various sectors.

In digital marketing, the strategic use of emojis in social media advertising, particularly on the Xiaohongshu app, significantly influences consumer acceptance and purchase behavior. This study examines the impact of emoji-laden advertisements and the role of brand metaphorical warmth on consumer perceptions. Employing a tailored questionnaire, the research explores how emojis affect brand advertisement reception, filling a gap in empirical research on emoji advertising effectiveness. Findings indicate that emojis, when used judiciously, enhance consumer acceptance and contribute to a positive brand perception. However, excessive use may undermine trust. Brand metaphorical warmth emerges as a crucial factor, suggesting that emojis can effectively convey warmth, fostering a deeper emotional connection with consumers. These insights offer practical implications for refining social media marketing strategies, advocating for a balanced approach to emoji usage in advertisements to optimize engagement and influence consumer behavior.

This study explores an innovative advertising technique on Bilibili, where product links are embedded as bullet comments visible only to mobile app users. The research involved 140 participants, divided equally between followers and non-followers of a popular influencer, ‘Gourmet WanggangR.’ These groups were further split, with half viewing a video containing the product link on the app and the other half via PC. The study revealed that influencer attachment significantly increased viewer immersion (transportation) and positively influenced attitudes towards the content, which in turn elevated purchase intentions. Importantly, the influencer’s followers showed a stronger attachment and more favorable attitudes towards the content, alongside a heightened likelihood to purchase the advertised product. The presence of the product link further accentuated these effects among the influencer’s followers. Conversely, in the absence of the link, the correlation between influencer attachment and content attitude was less pronounced. These findings highlight the effectiveness of embedding product links in video content as a marketing strategy, particularly when targeting an influencer’s followers through mobile platforms.

The purpose of this study sought to determine the impact of shared leadership perceived by organizational members on team effectiveness and team learning behavior. For this purpose, the results of the empirical analysis of 206 organizational members are as follows. First, shared leadership was analyzed to improve team effectiveness. Second, shared leadership had a positive effect on team learning behavior. Third, team learning behavior was statistically significantly analyzed for team effectiveness. This study confirmed the importance of shared leadership, which has a positive impact on team effectiveness and team learning behavior. This may require building a new culture that can demonstrate the inherent leadership of organizational members in the influence relationship between shared leadership, team effectiveness, and team learning behavior. In other words, in order to systematically demonstrate and implement shared leadership, the execution ability of executives, managers, and working-level managers is important. To this end, it is necessary to build an organizational culture that matches the characteristics of the organization and develop and continuously implement human resource development systems and programs that can implement this.

With the acceleration of China’s urbanization process, the economic development and market potential of small and medium-sized cities have been constantly enhanced, with the urbanization competition having been caught in the vortex of homogenization. However, small and medium-sized cities are exposed to limited resources and funds, and therefore need to be more flexible and innovative in the strategy implementation, while urban brand communication is one of the key factors to promote the competitiveness of cities. Taking the small and medium-sized cities in China as the research objects, this study, based on the domestic and foreign theories about the brand communication of small and medium-sized cities, as well as other city-related theories, analyzes textual materials about the current situation and new changes in brand communication of small and medium-sized cities with grounded theory, reflecting on the problems in brand communication in China’s small and medium-sized cities. Combining the basic elements of urban brand communication, a model for constructing brand communication strategies for small and medium-sized cities is further proposed, so as to provide the differentiated and distinctive strategies for the construction and communication of urban brands in small and medium-sized cities in China, as well as provide a new perspective and strategy on how to enhance the competitiveness and contribute to the sustainable economic development of small and medium-sized.

Since COVID-19, many foreign tourists have visited Korea for medical tourism. When statistical data were checked from 2022, after COVID-19, the number of foreign patients visiting Korea for two years was 24.8 million, an increase of 70.1% from 2020. It was confirmed that it has achieved a 50% level compared to 2019 (Statistics Office, 2023). Therefore, to create a development plan by linking medical tourism and wellness tourism, the purpose of this study is to find the link between medical tourism and wellness tourism as big data and present a development plan. In this research method, medical tourism, and wellness tourism for two years from 2022 to 2023 from the post-COVID period as big data are set as central keywords to compare text data to find common points. When analyzing wellness tourism and medical tourism, it was confirmed that most wellness tourism had a greater frequency than medical tourism. This confirmed that wellness tourism occupies a larger pie than medical tourism. As a result, when checking the word frequency, it was confirmed that wellness tourism and medical tourism share a lot as complex tourism products, and when checking 2-gram, to attract many medical tourists, it is necessary to combine medical tourism clusters and wellness tourism according to each other's characteristics among local governments.

This study aimed to investigate the immediate physiological responses, including heart rate, blood pressure, and rate pressure product (RPP), following squat exercises performed at three water depths (ground, knee depth, waist depth) and two speed conditions (60bpm speed, Max speed). The participants consisted of 10 men in their 20s with over 6 months of resistance exercise experience. For the 60bpm speed squats, participants performed 30 repetitions in 1 minute at a rate of 2 seconds per repetition, while for Max speed squats, they performed at Max speed without a set limit on the number of repetitions for 1 minute. All experiments were conducted with a random assignment. The study results showed that immediately after the aquatic squat exercise, the average heart rate, blood pressure, and cardiac load were higher in the order of knee depth, ground level, and waist depth at both 60bpm speed and Max Speed. At 60bpm speed, the heart rate was higher in the order of ground level, knee depth, and waist depth. Overall, exercise in an aquatic environment was considered to impose relatively lower physical burden compared to land-based exercise. Therefore, it is suggested that depending on individual fitness levels and exercise goals, appropriately combining aquatic exercise, which imposes lower immediate physiological burden, and land-based exercise may lead to safer and more effective exercise methods.

In the past, antibiotics and antimicrobial substances have been used for the purpose of promoting the growth of livestock or treating livestock, but various problems such as the presence of livestock products or resistant bacteria have emerged. Recently, regulations on the use of antibiotics have been strengthened worldwide, and probiotics are attracting attention as an alternative. Probiotic microorganisms have already been used for human use, such as intestinal abnormal fermentation, diarrhea, and indigestion. In livestock, beneficial microorganisms are increasing in use for the purpose of improving productivity, such as promoting livestock development and preventing diarrhea. Therefore, it is advisable to understand livestock probiotics in deeper and think about effective uses. The role of probiotics in the livestock sector is made with microorganisms themselves, so it is a substance that promotes livestock growth and improves feed efficiency by settling in the intestines of livestock, suppressing the growth of other harmful microorganisms, helping digestion and absorption of ingested feed, and helping to synthesize other nutrients. There is a need for a probiotic that suppresses intestinal bacteria by supplying probiotics used as a means to minimize the effects of stress in livestock management, thereby suppressing disease outbreaks by maintaining beneficial microorganisms and suppressing pathogenic microorganisms. The purpose of this paper is to develop a brand of feed additive probiotics to improve health conditions due to increased feed intake, improve the efficiency of use of feed nutrients, inhibit the decomposition and production of toxic substances, increase immunity, reduce odor in livestock, and improve the environment. We investigated and analyzed feed additive probiotics already on the market, and developed the naming and logo of suitable feed additive probiotic brands in livestock. We hoped that the newly developed product will be used in the field and help solve problems in the livestock field.

Currently, the most important issue on the earth is global warming, which causes climate change and leads to disasters. For this reason, each country is focusing on renewable energy, carbon neutrality, environmentally friendly energy and transportation. Bicycles used as short-distance vehicles do not emit gases harmful to the human body that pollute the Earth's atmosphere. Also, the use of bicycles has the effect of improving the health of people, and each country is designing a short distance transportation network using bicycles. In this study, we propose a model of a bicycle power-train that can use a belt as a power transmission medium. The basic principles and methods for applying the proposed new type of power-train to bicycles are presented.

This study used a total of 205,565 datasets of 'voltage', 'current', '°C', and 'time(s)' to systematically analyze the properties and performance of solid electrolytes. As a method for characterizing solid electrolytes, a linear regression model, one of the machine learning models, is used to visualize the relationship between 'voltage' and 'current' and calculate the regression coefficient, mean squared error (MSE), and coefficient of determination (R^2). The regression coefficient between 'Voltage' and 'Current' in the results of the linear regression model is about 1.89, indicating that 'Voltage' has a positive effect on 'Current', and it is expected that the current will increase by about 1.89 times as the voltage increases. MSE found that the mean squared error between the model's predicted and actual values was about 0.3, with smaller values closer to the model's predictions to the actual values. The coefficient of determination (R^2) is about 0.25, which can be interpreted as explaining 25% of the data.

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.