• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.125-134
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• 2009

Ubiquitous are not courted in time and place of users and must offer service in network freely. There is telematics by representative application service during it. telematics service must provide service that is personalized according to time and place. Also, user who use telematics service must offer service that can use automatically even if do not request service. Therefore, in the paper wish to embody service discovery way design in telematics environment because treatise that see uses UPnP through PDA that is user Mobile terminal. PDA connected by local server of telematics service point and Bluetooth communication, and use finding UPnP device and service that is linked with local server using UPnP. Design UPnP device that provide service to user in telematics environment. Construct telematics service test bed to test service discovery. Because constructed system applies UPnP on Bluetooth communication base, service discovery system implementation and test.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.86-93
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• 2012

The emergence of cable TV, satellite broadcasting and IPTV provides viewers with a variety of TV programs. However, viewers' desire for watching their favorite TV program at convenient time has increased because of insufficient spare time. As an increase in smart phone market has accelerated an entry into "the age of smart network media" since 2009, mobile media suggests services connected to other digital devices. Recently, there has been growing interest in TV controling system of smart phone. Therefore, the present study aims to provide an concept of the smart phone application which recommends contents of TV program by analyzing personal watching pattern. To suggest detailed direction of the interaction and UI design, we analyzed previous research and examples of TV controlling applications and products. In addition, public opinion survey was carried out to rationalize this study and suggest suitable UI structure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.43-50
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• 2020

The purpose of this study is to examine the case of constructing information and communication facilities in daycare centers and to propose an educational environment that can foster young talents who can lead the era of the fourth industrial revolution. In particular, after COVID19, a method was proposed to create an information and communication environment suitable for children to receive personalized education, and to create an environment for experiential education if possible, and at the same time to enable averaging of customized learning. Since there has been no research on information and communication facilities in daycare centers, we intend to place significance on starting, and in the future, to foster creative and contextual children, we will reduce the movement of teachers through smart speakers and mobile devices, and tailor the educational environment through AI data. I think that the design of the daycare center should be changed in the direction of making the product. To this end, the CM role of information and communication supervision is needed, and it is hoped that it will become a design standard for daycare centers after COVID19 by developing research on daycare centers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.9-13
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• 2020

Sasang Constitutional Medicine is a traditional Korean medicine optimized for personalized medicine, and despite its effective clinical efficacy, the inaccuracy of constitutional diagnosis has been pointed out as a limitation. To improve the accuracy, a constitutional analysis algorithm based on quantitative data was developed. In this study, a constitutional analysis experience system applied with the algorithm was developed and repeatability was evaluated. The system analyzes the constitution of the experiencer by collecting front and side facial images, audio, and questionnaire and calculating the integrated constitution probability value. To evaluate the repeatability of the probability values of the system was performed five times each for three people, and the coefficient of variation was 4.778%, indicating that the repeatability was sufficient. The system could contribute to the promotion of the awareness of Sasang medicine.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.231-243
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• 2021

In Recent years the way we analyze the breast cancer has changed dramatically. Breast cancer is the most common and complex disease diagnosed among women. There are several subtypes of breast cancer and many options are there for the treatment. The most important is to educate the patients. As the research continues to expand, the understanding of the disease and its current treatments types, the researchers are constantly being updated with new researching techniques. Breast cancer survival rates have been increased with the use of new advanced treatments, largely due to the factors such as earlier detection, a new personalized approach to treatment and a better understanding of the disease. Many machine learning classification models have been adopted and modified to diagnose the breast cancer disease. In order to enhance the performance of classification model, our research proposes a model using A Hybrid Modified K-Means Clustering with Modified SVM (Support Vector Machine) Machine learning algorithm to create a new method which can highly improve the performance and prediction. The proposed Machine Learning model is to improve the performance of machine learning classifier. The Proposed Model rectifies the irregularity in the dataset and they can create a new high quality dataset with high accuracy performance and prediction. The recognized datasets Wisconsin Diagnostic Breast Cancer (WDBC) Dataset have been used to perform our research. Using the Wisconsin Diagnostic Breast Cancer (WDBC) Dataset, We have created our Model that can help to diagnose the patients and predict the probability of the breast cancer. A few machine learning classifiers will be explored in this research and compared with our Proposed Model "A Hybrid Modified K-Means with Modified SVM Machine Learning Algorithm to Enhance the Cancer Prediction" to implement and evaluated. Our research results show that our Proposed Model has a significant performance compared to other previous research and with high accuracy level of 99% which will enhance the Cancer Prediction.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.21-31
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• 2018

In Hyper-Connected Society, IoT-based Lifelog data is used throughout the Internet and is an important component of customized services that reflect user requirements. Also, Users are using social network services to easily express their interests and feelings, and various life log data are being accumulated. In this paper, Intelligent characters using IoT based lifelog data have been developed and qualitative/quantitative data are collected and analyzed in order to systematically grasp emotions of users. For this, qualitative data through the social network service used by the user and quantitative data through the wearable device are collected. The collected data is verified for reliability by comparison with the persona through esnography. In the future, more intelligent characters will be developed to collect more user life log data to ensure data reliability and reduce errors in the analysis process to provide personalized services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.149-162
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• 2021

This paper established a new smart factory based on manufacturing data for an introductory company focusing on the personalized cosmetics manufacturing industry. We build on an example of a system that collects, manages, and analyzes documents and data that were previously managed by CGMP-based analog for data-driven use. To this end, we have established a system that can collect all data in real time at the production site by introducing artificial intelligence smart factory platform LINK5 MOS and POP system, collecting PLC data, and introducing monitoring system and pin board. It also aims to create a new business cluster space based on this project.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.223-228
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• 2023

According to the Korea Information Society Development Institute, OTT services grew at a rate of 33.4% in four yearsfrom 2017, when they were first launched.TheKorea Export-Import Bank announced in 2020 that the domestic OTT market was worth 780.1 billionKRW. This growth of the OTT market is expected to stimulate competition among OTT service platforms, and user satisfactionwithconvenience features, such as video recommendations, seems to be acting as an important factor in the competition.Currently, the OTT market uses a variety ofdata for customized recommendations, but the limitationis that it only uses datacollected within the app. Thereby we have proposed the use ofpersonal data collected outside the app for personalized recommendations, and the survey results showed that user satisfaction was 23.72% higher for recommended content based on the proposedmethod thanNetflix recommended content.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.141-147
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• 2024

Recently, there has been growing interest in personalized services tailored to an individual's preferences. This has led to ongoing research aimed at recognizing and leveraging an individual's personality traits. Among various methods for personality assessment, the OCEAN model stands out as a prominent approach. In utilizing OCEAN for personality recognition, a multi modal artificial intelligence model that incorporates linguistic, paralinguistic, and non-linguistic information is often employed. This paper examines the impact of the margin value set for extracting facial areas from video data on the accuracy of a personality recognition model that uses facial expressions to determine OCEAN traits. The study employed personality recognition models based on 2D Patch Partition, R2plus1D, 3D Patch Partition, and Video Swin Transformer technologies. It was observed that setting the facial area extraction margin to 60 resulted in the highest 1-MAE performance, scoring at 0.9118. These findings indicate the importance of selecting an optimal margin value to maximize the efficiency of personality recognition models.