• Journal of Broadcast Engineering
• /
• v.20 no.4
• /
• pp.580-597
• /
• 2015

Broadcast encryption system is a cryptographic primitive that enables a sender to broadcast a message to a set of receivers in a secure channel. Out of previous proposed broadcast encryption systems, the most effective is the one that uses the Subset Difference(SD) method in a binary tree structure. The SD method has been realized by two underlying approaches: Pseudo-Random Generator(PRG) and Secret Sharing(SS). 2-SD method is the generalized version of the SD method by which two subsets of revoked receivers can be dealt with by one subset (in an SD-based broadcast encryption system). The primary advantage of the 2-SD method is to further reduce the size of transmission overhead, compared to the SD method. Until now, however, there is no known broadcast encryption system that is based on such a 2-SD technique using either PRG or SS basis. In this paper, we suggest a new 2-SD broadcast encryption system using the SS-based technique that was suggested by Jae Hwan Lee et al. in 2014[9]. The new system can reduce the size of ciphertext by 25% of the one in the previous SS-based broadcast encryption system. Also, on a theoretical note, ours is the first 2-SD broadcast encryption system that is provably secure.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.3
• /
• pp.123-129
• /
• 2009

Ubiquitous home is emerging as the future digital home environments that provide various ubiquitous home services like u-Life, u-Health, etc. It is composed of some home appliances and sensors which are connected through wired/wireless network. Ubiquitous home services become aware of user's context with the information gathered from sensors and make home appliances adapt to the current home situation for maximizing user convenience. In these context-aware home environments, it is the one of significant research topics to predict user behaviors in order to proactively control the home environment. In this paper, we propose Multi-Level prediction algorithm for context-aware services in ubiquitous home environment. The algorithm has two phases, prediction and execution. In the first prediction phase, the next location of user is predicted using tree algorithm with information on users, time, location, devices. In the second execution phase, our table matching method decides home appliances to run according to the prediction, device's location, and user requirement. Since usually home appliances operate together rather than separately, our approach introduces the concept of mode service, so that it is possible to control multiple devices as well as a single one. We also devised some scenarios for the conceptual verification and validated our algorithm through simulations.

• The KIPS Transactions:PartD
• /
• v.12D no.5 s.101
• /
• pp.663-672
• /
• 2005

This Paper Proposes an approach that removes the redundancy of Path information and uses an inverted index, as an efficient way to store a large volume of XML documents and to retrieve wanted information from there. An XML document is decomposed into nodes based on its tree structure, and stored in relational tables according to the node type, with path information from the root to each node. The existing methods using path information store data for all element paths, which cause retrieval performance to be decreased with increased data volume. Our approach stores only data for leaf element path excluding internal element paths. As the inverted index is made by the leaf element path only, the number of posting lists by key words become smaller than those of the existing methods. For the storage and retrieval of U data, our approach doesn't require the XML schema information of XML documents and any extension of relational database. We demonstrate the better performance of on approach than the existing approaches within the scope of our experiment.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.5_6
• /
• pp.268-278
• /
• 2004

In this paper, we describe our experience in the design and implementation of the SMART file system to handle multimedia workload. Our work has three design objectives: (ⅰ) efficient support for sequential workload, (ⅱ) avoiding disk fragmentation, (ⅲ) logical unit based file access. To achieve these three objectives, we develop a file system where a file consists of linked list of Data Unit Group. Instead of tree like structure of the legacy Unix file system, we use single level file structure. Our file system can also access the file based upon the logical unit which can be video frame or audio samples. Data Unit Group is a group of logical data units which is allocated continuous disk blocks. At the beginning of each Data Unit Group, there exists an index array. Each index points to the beginning of logical data units, e.g. frames in the Data Unit Group. This index array enables the random access and sequencial access of semantic data units. SMART file system is elaborately tailored to effectively support multimedia workload. We perform physical experiments and compare the performance of SMART file system with EXT2 file system and SGI XFS file system. In this experiment, SMART file system exhibits superior performance under streaming workload.

• The Journal of the Korea Contents Association
• /
• v.21 no.8
• /
• pp.356-366
• /
• 2021

The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1283-1293
• /
• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.04a
• /
• pp.576-579
• /
• 2011

Wireless sensor network are widely all over different fields. Because of its distinguished characteristics, we must take account of the factor of energy consumed when designing routing protocol. Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors sends data from the CH (Cluster Head) and then to the BS (Base Station). BCDCP works well in a smallscale network however is not preferred in a large scale network since it uses much energy for long distance wireless communication. TBRP can be used for large scale network, but it weakness lies on the fact that the nodedry out of energy easily since it uses multi-hops transmission data to the Base Station. Here, we proposed a routing protocol. A Cluster Based Energy Efficient Tree Routing Protocol (CETRP) in Wireless Sensor Networks (WSNs) to prolong network life time through the balanced energy consumption. CETRP selects Cluster Head of cluster tree shape and uses maximum two hops data transmission to the Cluster Head in every level. We show CETRP outperforms BCDCP and TBRP with several experiments.