• The KIPS Transactions:PartD
• /
• v.15D no.5
• /
• pp.691-698
• /
• 2008

Web designers generally use a story board, a site map, a flow chart or the combination of these for representing web sites. But these methods are difficult to represent the entire architecture of a web site, and may be not adaptive for describing the detail flow of web pages. To solve these problems to some degree, there were works using EMFG(Extended Mark Flow Graph) recently. However the conventional EMFG representation method is not adaptive to represent the dynamic interface of web sites because that cover only the static parts of a web site. Internet utilization is rapidly growing in our life and we cannot imagine the worlds of work, study and business without internet. And web sites recently have not only more complex and various architecture but also web pages containing the dynamic interface. Therefore we propose the representation method of these web sites - for example, a web site containing varying pages with time and varying page status or contents with mouse operations - using EMFG. We expect our work to be help the design and maintenance of web sites.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.11
• /
• pp.2724-2730
• /
• 2015

Internet of Things (IoT) is possibly the most widely discussed technological concept in today's technology circles. This technology is expected to dramatically change not only how we work but also how we live. The concept of IoT basically means a web of connected devices which can be controlled over a data network. With cost of technology required to control these devices going down and increasing internet connectivity through smartphones, IoT is expected to be an all pervasive technology in the next 10 years. In this paper, we study the technological landscape of this fast growing technology domain from an Intellectual Property (Patents) perspective. We find that the patent distribution in this domain is very fragmented with the top patent applicants in the field holding around 5% of the total patents. Especially, the US geography has seen the maximum patent filings and is closely followed by the big Asian markets of Japan and Korea.

• Journal of Internet Computing and Services
• /
• v.15 no.2
• /
• pp.33-39
• /
• 2014

How to transfer spatial data from server to client in wireless broadcasting environment is shown as following: A server arranges data information that client wants and transfers data by one-dimensional array for broadcasting cycle. Client listens data transferred by the server and returns resulted value only to server. Recently number of users using location-based services is increasing alongside number of objects, and data volume is changing into large amount. Large volume of data in wireless broadcasting environment may increase query time of client. Therefore, we propose Client based Data Scheduling (CDS) for efficient data scheduling in wireless broadcasting environment. CDS divides map and then calculates total sum of objects for each grid by considering number of objects and data size within divided grids. It carries out data scheduling by applying hot-cold method considering total data size of objects for each grid and number of client. It's proved that CDS reduces average query processing time for client compared to existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5129-5152
• /
• 2016

Multi-view super-resolution (MVSR) aims to estimate a high-resolution (HR) image from a set of low-resolution (LR) images that are captured from different viewpoints (typically by different cameras). MVSR is usually applied in camera array imaging. Given that MVSR is an ill-posed problem and is typically computationally costly, we super-resolve multi-view LR images of the original scene via image fusion (IF) and blind deblurring (BD). First, we reformulate the MVSR problem into two easier problems: an IF problem and a BD problem. We further solve the IF problem on the premise of calculating the depth map of the desired image ahead, and then solve the BD problem, in which the optimization problems with respect to the desired image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM). Our approach bridges the gap between MVSR and BD, taking advantages of existing BD methods to address MVSR. Thus, this approach is appropriate for camera array imaging because the blur kernel is typically unknown in practice. Corresponding experimental results using real and synthetic images demonstrate the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.5
• /
• pp.2366-2395
• /
• 2018

Multi-view super-resolution (MVSR) refers to the process of reconstructing a high-resolution (HR) image from a set of low-resolution (LR) images captured from different viewpoints typically by different cameras. These multi-view images are usually obtained by a camera array. In our previous work [1], we super-resolved multi-view LR images via image fusion (IF) and blind deblurring (BD). In this paper, we present a new MVSR method that jointly realizes IF and BD based on an integrated energy function optimization. First, we reformulate the MVSR problem into a multi-channel blind deblurring (MCBD) problem which is easier to be solved than the former. Then the depth map of the desired HR image is calculated. Finally, we solve the MCBD problem, in which the optimization problems with respect to the desired HR image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM). Experiments on the Multi-view Image Database of the University of Tsukuba and images captured by our own camera array system demonstrate the effectiveness of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.9-17
• /
• 2019

In this paper, we propose an attribute-based broadcast encryption algorithm that can be applied to satellite broadcasting network. The encryption algorithm is a cryptographic method by which a carrier(sender) can transmit contents efficiently and securely to a plurality of legitimate users through satellites. An attribute-based encryption algorithm encrypts contents according to property of contents or a user, In this paper, we combine effectively two algorithms to improve the safety and operability of satellite broadcasting network. That is, it can efficiently transmit ciphertexts to a large number of users, and has an advantage in that decoding can be controlled by combining various attributes. The proposed algorithm reduces the network load by greatly reducing the size of the public key, the private key and the cipher text in terms of efficiency, and the decryption operation amount is reduced by half to enable fast decryption, thereby enhancing the operability of the user.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.9
• /
• pp.83-95
• /
• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.1
• /
• pp.145-152
• /
• 2019

In this paper, we proposed a shaking image stabilization algorithm using deep learning. The proposed algorithm utilizes deep learning, unlike some 2D, 2.5D and 3D based stabilization techniques. The proposed algorithm is an algorithm that extracts and compares features of shaky images through CNN network structure and LSTM network structure, and transforms images in reverse order of movement size and direction of feature points through the difference of feature point between previous frame and current frame. The algorithm for stabilizing the shake is implemented by using CNN network and LSTM structure using Tensorflow for feature extraction and comparison of each frame. Image stabilization is implemented by using OpenCV open source. Experimental results show that the proposed algorithm can be used to stabilize the camera shake stability in the up, down, left, and right shaking images.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.1-6
• /
• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.1
• /
• pp.1-19
• /
• 2021

The graph-based tag recommendation algorithm FolkRank can effectively utilize the relationships between three entities, namely users, items and tags, and achieve better tag recommendation performance. However, FolkRank does not consider the internal relationships of user-user, item-item and tag-tag. This leads to the failure of FolkRank to effectively map the tagging behavior which contains user neighbors and item neighbors to a tripartite graph. For item-item relationships, we can dig out items that are very similar to the target item, even though the target item may not have a strong connection to these similar items in the user-item-tag graph of FolkRank. Hence this paper proposes an improved FolkRank algorithm named FolkRank++, which fully considers the user-user and item-item internal relationships in tag recommendation by adding the correlation information between users or items. Based on the traditional FolkRank algorithm, an initial weight is also given to target user and target item's neighbors to supply the user-user and item-item relationships. The above work is mainly completed from two aspects: (1) Finding items similar to target item according to the attribute information, and obtaining similar users of the target user according to the history behavior of the user tagging items. (2) Calculating the weighted degree of items and users to evaluate their importance, then assigning initial weights to similar items and users. Experimental results show that this method has better recommendation performance.