• Journal of Satellite, Information and Communications
• /
• v.1 no.2
• /
• pp.83-88
• /
• 2006

Future communication systems are to be designed to support and serve multimedia and multipledata transmission. Nowadays, requirement of mobile subscribers for the various information such as movie, GPS(Global Positioning System) information, news-is increasing significantly. However, due to practical reasons, the capacity and number of capable channels are limited. To solve this problem, a large number of methods and schemes have been proposed and are under research. In this paper, we demonstrate how satellite DMB (Digital Multimedia Broadcasting) system works with hierarchical modulation scheme. By using hierarchical modulation, we can analyze the capacity. Meanwhile, system performance os evaluated and compared to conventional DMB system without using hierarchical modulation.

• Journal of information and communication convergence engineering
• /
• v.15 no.4
• /
• pp.217-226
• /
• 2017

Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

• International journal of advanced smart convergence
• /
• v.5 no.3
• /
• pp.61-65
• /
• 2016

In the TV broadcasting, movie production and business the transportation of video between creators (programmers, studios) and distributors (broadcast and cable networks, cable and satellites companies) is still a mix of File Transfer Protocol (FTP), physical delivery, and expensive multicast satellite. Cloud-based file sync-and-share providers like Dropbox and box are playing an increasing role, but the industry's unique demands for speed and multicasting have fueled the growth of IP Video transport. This paper gives a solid grasp of the major elements of IP video technology, including content preparation, system architecture alternatives and network performance management.

• The Journal of the Convergence on Culture Technology
• /
• v.1 no.4
• /
• pp.65-69
• /
• 2015

This study can read register reviews and search read information that users want by musical, drama and movie by using DB by developing App providing the newest culture view and information in android smart phone, when users want to enjoy cultural life. Also, the administrator logins as Administrator-mode and controls cultural information and makes smooth controlling by identifying user's information. In addition, the user logins as User-mode and reads cultural information and can make possible in reading and writing reviews. It makes possible to enjoy leisure activity as cultural activity by identifying reliable performance information via recommendation of friend groups.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.4
• /
• pp.99-112
• /
• 2015

Drones are more formally known as unmanned aerial vehicles without a human pilot aboard. Its flight is controlled either autonomously by onboard computers or by the remote control of a pilot on the ground. This research aims to analyze market trends and technological developments of drones, use cases and constraints of drones in the cultural industries take advantage of the possibility of future drones. Drones are looking for broadcasting, movie, theater, games, toys drones and racing games in a variety of cultural industry. The biggest problem of drone shall provide penalties for breaches of privacy and security issues in the debate. Drones performances are required such as battery capacity and compactness because of the technical limitations. The drones are expected to be used in various fields such as journalism drone, performance tools, augmented reality games, kidult culture. The drones can create a new cultural industry market such as the combination of robotics and drone journalism, drone crowded theater, utilizing drones character games, racing games etc. In conclusion, drones help reduce manpower, time and costs dramatically and will contribute to creating added value in the cultural industries.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.2
• /
• pp.99-105
• /
• 2007

In this paper, diskless personal multimedia player(PMP) that can access and decode the remote large multimedia data is implemented via wireless network. To implement this, WLAN based NFS protocol is used to connect PMP to the remote server and text image and movie files are decoded and played using ARM9 cored PXA255 embedded processor and Linux OS. The fuction and performance of the PMP is evaluated and verified using variuos types of contents. Linux kernel elements are configured and built in according to the hardware and software on the target board to install on the target board. The confirming result shows the required functions and performances.

• The KIPS Transactions:PartC
• /
• v.12C no.2 s.98
• /
• pp.217-222
• /
• 2005

The IEEE 802.11 based wireless local area networks are candidates to lead the broadband connectivity in the home and office scenarios. Recently IEEE proposed the 802.11e as a new standard to provide appropriate Quality of Services to a plethora of emerging real-time multimedia and high demanding applications such as high definition movie and audio distribution, video-conference and voice over IP. This paper studies the IEEE 802.11e/IEEE 802.11b interactions focusing on potential unfairness problems that might appear in networks with heterogeneous wireless LAN technologies as well as in the IEEE 802.11e deployment phase.

• International Journal of Computer Science & Network Security
• /
• v.22 no.7
• /
• pp.352-358
• /
• 2022

Text mining is an important process used for analyzing the data collected from different sources like videos, audio, social media, and so on. The tools like Natural Language Processing (NLP) are mostly used in real-time applications. In the earlier research, text mining approaches were implemented using long-short memory (LSTM) networks. In this paper, text mining is performed using average-stochastic gradient descent weight-dropped (AWD)-LSTM techniques to obtain better accuracy and performance. The proposed model is effectively demonstrated by considering the internet movie database (IMDB) reviews. To implement the proposed model Python language was used due to easy adaptability and flexibility while dealing with massive data sets/databases. From the results, it is seen that the proposed LSTM plus weight dropped plus embedding model demonstrated an accuracy of 88.36% as compared to the previous models of AWD LSTM as 85.64. This result proved to be far better when compared with the results obtained by just LSTM model (with 85.16%) accuracy. Finally, the loss function proved to decrease from 0.341 to 0.299 using the proposed model

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.4
• /
• pp.693-700
• /
• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.

• Journal of Information Technology Services
• /
• v.22 no.1
• /
• pp.43-56
• /
• 2023

With the development of the e-commerce market, various types of products continue to be released. However, customers face an information overload problem in purchasing decision-making. Therefore, personalized recommendations have become an essential service in providing personalized products to customers. Recently, many studies on GCN-based recommender systems have been actively conducted. Such a methodology can address the limitation in disabling to effectively reflect the interaction between customer and product in the embedding process. However, previous studies mainly use implicit feedback data to conduct experiments. Although implicit feedback data improves the data scarcity problem, it cannot represent customers' preferences for specific products. Therefore, this study proposed a novel model combining explicit and implicit feedback to address such a limitation. This study treats the average ratings of customers and products as the features of customers and products and converts them into a high-dimensional feature vector. Then, this study combines ID embedding vectors and feature vectors in the embedding layer to learn the customer-product interaction effectively. To evaluate recommendation performance, this study used the MovieLens dataset to conduct various experiments. Experimental results showed the proposed model outperforms the state-of-the-art. Therefore, the proposed model in this study can provide an enhanced recommendation service for customers to address the information overload problem.