• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.89-101
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• 2023

The purpose of this study is to empirically analyze the rational decision-making process and perception differences of housing transactions in the market environment. It was designed through an analysis of the factors influencing housing sales based on the rational behavior theory model. Objective evidence was provided for the impact factors affecting the attitude towards housing sales, with the spouse and children being identified as significant influencers. Additionally, children and friends were found to have an impact on subjective norms related to housing sales, especially for unmarried individuals under 40 years of age and those with low income, who were found to be more influenced by their parents. It was also discovered that the influence of these factors varied based on age and income levels. Younger individuals tended to rely more on their parents or friends, while those with high incomes showed stronger willingness to purchase homes. The presence of beneficial infrastructure for children was found to directly influence the decision to purchase a home. The study also provided objective evidence that the decision to purchase a home is influenced not only by economic factors but also by continuous encouragement and information from those around the buyer. These findings demonstrate the importance of the influence of close acquaintances in the rational decision-making process of home buyers. However, this study only investigated a limited portion of the factors influencing housing sales, as the market is affected by a variety of financial and governmental policies. Therefore, future research should consider various complex factors simultaneously when analyzing the influence of housing sales.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.65-70
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• 2023

In recent years, the digital media environment has begun to diversify, with a greater focus being placed on user-centric design. With the development of digital technology, the digital media environment has formed a vast network of information, which supports interactive communication between people, creating a need for user-centric research. Mobile displays, as a representation of the digital media environment, have the advantage of mobility through the use of thin screen displays and low-performance image sensors, which allow for miniaturization and power saving. However, this results in reduced colour accuracy compared to large displays. This study investigates users' colour perception when using dark and light mode mobile displays. Colour perception was measured using a psycho-physical experiment, which controls each colour attribute based on the 12 colours of KS. The results were analysed to determine whether there is a difference in colour perception between dark mode and light mode, and if the difference was statistically significant. Future research directions based on the results are then discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.21-30
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• 2022

This paper describes the design, manufacture, and testing of servos applicable to small tracking radars. First, Chapter 1 describes the necessity of this study. Chapter 2 describes the development of servos applicable to future tracking radars in small missile systems. Chapter 3 describes the design and test results for current control of brushed DC motors, brushless DC motors, and permanent magnet synchronous motors. And Chapter 4 describes the design and test results for speed control of the test wheel. And in Chapter 5, the results of the previous tests are summarized. In this paper, some pictures were intentionally blurred for security reasons, and the control result of test wheel was described, not the test with the developed gimbals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• Convergence Security Journal
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• v.22 no.2
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• pp.59-66
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• 2022

Recently, smart home technology has been developed with a great response due to the convenience of home automation. Smart home technology provides various services by connecting various Internet of Things (IoT) and sensors to a home network through wired/wireless networks. In addition, the smart home service easily and conveniently controls lighting, energy, environment, and door cameras through a wall pad. However, while it has become a social issue due to the recent hacking accident of wall pads, personal information leakage and privacy infringement are expected. Accordingly, it is necessary to prepare preventive and countermeasures against security vulnerability factors of wall pads. Therefore, this study expects that it can be used as basic data for future smart home application and response technology development by examining the weak causes and countermeasures related to wall pads.

• Industry Promotion Research
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• v.8 no.1
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• pp.23-33
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• 2023

In modern times, damage caused by the spread of the Internet has become very diverse. In particular, due to the craze of K-pop since 2008, the damage caused by copyright infringement in the domestic and international music markets has become the biggest problem in the Internet market. However, the manpower of the police and copyright protection agencies to solve these increasingly intelligent crimes is insufficient. Therefore, we are trying to find out the role of the public interest detective as a supplementary force for the public authority and as a substitute for the copyright protection agency that can provide legitimate help for victims in the prevention of music copyright infringement and disputes. For this study, first, the concept and types of music copyright, the concept of public interest detectives, the current status and system of music copyright were identified, and the role of detectives for music copyright protection was explored through system operation and status analysis of protection agencies and literature review. Through the results of this study, it is hoped that the role of a professional detective in the public interest dimension of music copyright protection can be a good soil for the development of the detective industry in the future.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.145-155
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• 2023

A radial combiner with high efficiency characteristics in the X-band was designed and manufactured using a waveguide and matching structure. In particular, in order to manufacture it in a small size, a dual waveguide to coaxial transition structure was applied that allows two ports to be matched to one waveguide. Applying this structure makes it possible to manufacture smaller than typical coaxial to waveguide radial combiner. As a result of measurement in the X-band band of 9.2~10GHz, the return loss was less than -18.408dB and the output insertion loss was less than 0.206dB, and the output combining efficiency was obtained as high as 95.37% or more. It is expected that it can be used in the combining part for high output transmitters in the millimeter wave band in the future. In particular, the range of use is expected to increase by reducing the size and weight.

• Journal of Internet of Things and Convergence
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• v.9 no.4
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• pp.71-75
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• 2023

Changes in modern society are resulting in the emergence of various service models that apply software and artificial intelligence, and all fields are rapidly changing based on software and artificial intelligence. Education on software and artificial intelligence is emerging as a major influencing factor that determines national competitiveness. Following these social changes, interest in the use of software and artificial intelligence is quite high. Starting in 2025, software and artificial intelligence-related curricula are scheduled to be introduced into public education in elementary, middle, and high schools, so many educational activities are becoming active. In this study, based on the content of operating the software and artificial intelligence experience activity program, we would like to propose the efficiency of future learning programs and operating methods for software and artificial intelligence.