• Journal of Korea Multimedia Society
• /
• v.21 no.5
• /
• pp.599-608
• /
• 2018

As natural disasters are increasing due to the unusual weather and the modern society is getting complicated, the rapid change of the urban environment has increased human disasters. Thus, citizens are becoming more anxious about social safety. The importance of preparation for safety has been suggested by providing the disaster safety services such as regional safety index, life safety map, and disaster safety portal application. In this paper, we propose an application framework to predict the urban safety index based on user's location with realtime weather/atmosphere data after creating a predication model based on the machine learning using number of occurrence cases and weather/atmosphere history data. Also, we implement an application to provide traffic safety index with executing preprocessing occurrence cases of traffic and weather/atmosphere data. The existing regional safety index, which is displayed on the Si-gun-gu area, has been mainly utilized to establish safety plans for districts vulnerable to national policies on safety. The proposed system has an advantage to service useful information to citizens by providing urban safety index based on location of interests and current position with realtime related data.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.5
• /
• pp.2778-2791
• /
• 2017

In the age of big data, distributed data providers need to ensure the privacy, while data analysts need to mine the value of data. Therefore, how to find the privacy-utility tradeoff has become a research hotspot. Besides, the adversary may have the background knowledge of the data source. Therefore, it is significant to solve the privacy-utility tradeoff problem in the distributed environment with side information. This paper proposes a distributed privacy-utility tradeoff method using distributed lossy source coding with side information, and quantitatively gives the privacy-utility tradeoff region and Rate-Distortion-Leakage region. Four results are shown in the simulation analysis. The first result is that both the source rate and the privacy leakage decrease with the increase of source distortion. The second result is that the finer relevance between the public data and private data of source, the finer perturbation of source needed to get the same privacy protection. The third result is that the greater the variance of the data source, the slighter distortion is chosen to ensure more data utility. The fourth result is that under the same privacy restriction, the slighter the variance of the side information, the less distortion of data source is chosen to ensure more data utility. Finally, the provided method is compared with current ones from five aspects to show the advantage of our method.

• Journal of Multimedia Information System
• /
• v.6 no.1
• /
• pp.23-30
• /
• 2019

A communications profile is a system that acquires information from communication links to an ambulance or other vehicle moving on a road and compiles a database based on this information. The equipment (six sets of HDTVs, fish-eye camera, satellite antenna with tracking system, and receiving power from the satellite beacon of the N-star) mounted on the roof of the vehicle, image data were obtained at Yokohama Japan. From these data, the polygon of the building was actually produced and has arranged on the map of the Geographical Survey Institute of a 50 m-mesh. The optical study (relationship between visibility rate and elevation angle) were performed on actual data taken by fish-eye lens, and simulated data by 3D-Map with polygons. There was no big difference. This 3D map system then predicts the communication links that will be available at a given location. For line-of-sight communication, optical analysis allows approximation if the frequency is sufficiently high. For non-line-of-sight communication, previously obtained electric power data can be used as reference information for approximation in certain cases when combined with predicted values calculated based on a 3D map. 3D maps are more effective than 2D maps for landing emergency medical helicopters on public roadways in the event of a disaster. Using advanced imaging technologies, we have produced a semi-automatic creation of a high-precision 3D map at Yokohama Yamashita Park and vicinity and assessed its effectiveness on telecommunications and ambulatory merits.

• Journal of Korea Multimedia Society
• /
• v.25 no.5
• /
• pp.748-756
• /
• 2022

Thanks to the competition of AlphaGo and Sedol Lee, machine learning has received world-wide attention and huge investments. The performance improvement of computing devices greatly contributed to big data processing and the development of neural networks. Artificial intelligence not only imitates human beings in many fields, but also seems to be better than human capabilities. Although humans' creation is still considered to be better and higher, several artificial intelligences continue to challenge human creativity. The quality of some creative outcomes by AI is as good as the real ones produced by human beings. Sometimes they are not distinguishable, because the neural network has the competence to learn the common features contained in big data and copy them. In order to confirm whether artificial intelligence can express the inherent characteristics of different arts, this paper proposes a new neural network model called Humming. It is an experimental model that combines vgg16, which extracts image features, and DeepJ's architecture, which excels in creating various genres of music. A dataset produced by our experiment shows meaningful and valid results. Different results, however, are produced when the amount of data is increased. The neural network produced a similar pattern of music even though it was a different classification of images, which was not what we were aiming for. However, these new attempts may have explicit significance as a starting point for feature transfer that will be further studied.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.11
• /
• pp.1330-1336
• /
• 2019

As the Fourth Industrial Revolution era began, a variety of devices are running on the cloud. These various devices continue to generate various types of data or large amounts of multimedia data. To handle this situation, a large amount of storage is required, and big data technology is required to process stored data and obtain accurate information. NAS (Network Attached Storage) or SAN (Storage Area Network) technology is typically used to build high-speed, high-capacity storage in a network-based environment. In this paper, we propose a method to construct a mass storage device using Network-DAS which is an extension technology of DAS (Direct Attached Storage). Benchmark experiments were performed to verify the scalability of the storage system with 76 HDD. Experimental results show that the proposed high performance mass storage system is scalable and reliable.

• Journal of Korea Multimedia Society
• /
• v.23 no.2
• /
• pp.241-246
• /
• 2020

Hadoop is a framework to process large data sets in a distributed way across clusters of nodes. It has been a popular platform to process big data, but in recent years, other platforms became competitive ones depending on the characteristics of the application. Spark is one of distributed platforms to enable real-time data processing and improve overall processing performance over Hadoop by introducing in-memory processing instead of disk I/O. Whereas Hadoop is designed to work on Java and data analysis is processed using Java API, Spark provides a variety of APIs with Scala, Python, Java and R. In this paper, the goal is to find out whether the APIs of different programming languages af ect the performances in Spark. We chose two popular APIs: Python and Scala. Python is easy to learn and is used in AI domain in a wide range. Scala is a programming language with advantages of parallelism. Our experiment shows much faster processing with Scala API than Python API. For the performance issues on AI-based analysis, further study is needed.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.237-246
• /
• 2022

Among the technologies of the 4th industrial revolution, drones that have grown rapidly and are being used in various industries can be operated by the pilot directly or can be operated automatically through programming. In order to be controlled by a pilot or to operate automatically, it is essential to predict and analyze the optimal path for the drone to move without obstacles. In this paper, after securing and analyzing the pilot training dataset through the unmanned aerial vehicle piloting training platform designed through prior research, the profile of the dataset that should be preceded to search and derive the optimal route of the unmanned aerial vehicle was designed. The drone pilot training data includes the speed, movement distance, and angle of the drone, and the data set is visualized to unify the properties showing the same pattern into one and preprocess the properties showing the outliers. It is expected that the proposed big data-based profile can be used to predict and analyze the optimal movement path of an unmanned aerial vehicle.

• Journal of Korea Multimedia Society
• /
• v.17 no.8
• /
• pp.1033-1040
• /
• 2014

Recently, the concept of mobile content service has changed from providing unilaterally contents for single-device to providing same contents for multi-device. This service should be able to provide diverse contents for multi-devices without platform and specification of multi-device. In this study, we propose a bridge technique of heterogeneous smart platform supporting social immersive game. It is possible to access social immersive game by using a multi-platform bridge. To achieve this, we explain techniques of device connection and data transmission between heterogeneous devices using server-client structure and UPnP. It provides an immersive game environment for multi-user, which is able to play in a public place using big screen.

• Journal of Multimedia Information System
• /
• v.7 no.2
• /
• pp.115-124
• /
• 2020

This paper is a study of deep learning among artificial intelligence technology which has been developing many technologies recently. Especially, I am talking about emotional computing that has been mentioned a lot recently during deep learning. Emotional computing, in other words, is a passive concept that is dominated by people who scientifically analyze human sensibilities and reflect them in product development or system design, and a more active concept that studies how devices and systems understand humans and communicate with people in different modes. This emotional signal extraction, sensitivity, and psychology recognition technology is defined as a technology to process, analyze, and recognize psycho-sensitivity based on micro-small, hyper-sensor technology, and sensitive signals and information that can be sensed by the active movement of the autonomic nervous system caused by human emotional changes in everyday life. Chapter 1 talks about overview and Chapter 2 shows related research. Chapter 3 shows the problems and models of real emotional computing and Chapter 4 shows this paper as a conclusion.

• Journal of Korea Multimedia Society
• /
• v.18 no.3
• /
• pp.330-338
• /
• 2015

Gradually increasing the value of the technology, the techniques of the various security systems to protect the core technology have been developed. The proposed security scheme, which uses both a Password and the various devices, is always open by malicious user. In order to solve that problem, the biometric authentication systems are introduced but they have a problem which is the secondary damage to the user. So, the authentication methods using EEG(Electroencephalography) signals were developed. However, the size of EEG signals is big and it cause a lot of problems for the real-time authentication. And the encryption method is necessary. In this paper, we proposed an efficient real-time authentication system applied encryption scheme with junk data using chaos map on the EEG signals.