• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.17-24
• /
• 2004

In this paper, the wavelet video coding using Low-Band-Shift(LBS) method and multiresolution motion estimation(MRME) is proposed. To overcome shift- variant property on wavelet coefficients, the LBS was proposed. LBS method previously has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. Therefore to reduce computational complexity of video coding using LBS, we combine MRME with LBS. When mm is applied only, it has 7 times as much as existing method's motion vector because each subband has different motion vector using property of LBS, number of motion vector decreases. Proposed method decreases motion vector, and it decreases motion compensated Prediction error by detailed motion estimation. And then it shows better coding performance. Also this method reduces computational amount by smaller search area in higher resolution. The computational complexity of the proposed method is 12.1% of that of existing method at 3-level wavelet transform. The experimental results with the proposed method show about 0.2∼9.7% improvement of MAD performance in case of lossless coding, and 0.1∼2.0㏈ improvement of PSNR performance at 4he same bit rate in case of lossy coding.

• Spatial Information Research
• /
• v.23 no.1
• /
• pp.41-48
• /
• 2015

BIM Technology contains data from the life cycle of facility through 3D modeling. For these, one building products the huge file because of massive data. One of them is IFC which is the standard format, and there are issues that large scale data processing based on geometry and property information of object. It increases the rendering speed and constitutes the graphic card, so large scale data is inefficient for screen visualization to user. The light weighting of large scale BIM data has to solve for process and quality of program essentially. This paper has been searched and confirmed about light weight techniques from domestic and abroad researches. To control and visualize the large scale BIM data effectively, we proposed and verified the technique which is able to optimize the BIM character. For operating the large scale data of facility on web based GIS platform, the quality of screen switch from user phase and the effective memory operation were secured.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.6
• /
• pp.1465-1475
• /
• 2015

Cheating detection models in the online games can be divided into two parts. The one is on client based model, which is designed to detect malicious programs not to be run while playing the games. The other one is server based model, which distinguishes the difference between benign users and cheaters by the server log analysis. The client based model provides various features to prevent games from cheating, For instance, Anti-reversing, memory manipulation and so on. However, being deployed and operated on the client side is a huge weak point as cheaters can analyze and bypass the detection features. That Is why the server based model is an emerging way to detect cheating users in online games. But the simple log data such as FPS's one can be hard to find validate difference between two of them. In this paper, In order to compensate for the disadvantages of the two detection model above, We use the existing game security solution log as well as the server one to bring high performance as well as detection ratio compared to the existing detection models in the market.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.11
• /
• pp.45-52
• /
• 1994

In recent days low cost, high performance microprocessors have led to construction of medium scale shared memory multiprocessor systems with shared bus. Such multiprocessor systems are heavily influenced by the structures of memory systems and memory systems become more important factor in design space as microprocessors are getting faster. Even though local cache memories are very common for such systems, the latency on access to the shared memory limits throughput and scalability. There have been many researches on the memory structure for multiprocessor systems. In this paper, an asynchronous memory architecture is proposed to utilize the bandwith of system bus effectively as well as to provide flexibility of implementation. The effect of the proposed architecture if shown by simulation. We choose, as our model of the shared bus is HiPi+Bus which is designed by ETRI to meet the requirements of the High-Speed Midrange Computer System. The simulation is done by using Verilog hardware decription language. With this simulation, it is explored that the proposed asynchronous memory architecture keeps the utilization of system bus low enough to provide better throughput and scalibility. The implementation trade-offs are also described in this paper. The asynchronous memory is implemented and tested under the prototype testing environment by using test program. This intensive test has validated the operation of the proposed architecture.

• Journal of Korea Spatial Information System Society
• /
• v.6 no.2 s.12
• /
• pp.63-75
• /
• 2004

This paper proposes a Web Service framework on both wired and wireless network environment that can be interoperable and extensible among geo-spatial servers. Mostly, OGC has studied and announced international standards which are related to web services on various kinds of geo-spatial data. Therefore, the proposed framework satisfies interoperability and extensibility for geo-spatial servers by adapting WMS, WFS, WCS, and WRS standards of OGC and web services standards of W3C. This framework, also, satisfies requirements of huge volumed data service, GML service, geo-spatial function service, and wireless network service. This framework consists of geo-spatial servers group, geo-spatial broker, and web-based client. The geo-spatial servers group includes GIS, SIIS, ITS, GNSS, and Telematics server for the purpose of providing various kinds of geo-spatial services. Especially, this paper proposes main memory based GIS server(MMG server) that can efficiently serve huge volumed GML data on wireless network environment. Finally, experimental results about the MMG server and prototype implementations of the framework show the effectiveness of this study.

• The KIPS Transactions:PartB
• /
• v.12B no.6 s.102
• /
• pp.671-678
• /
• 2005

In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.

• Journal of KIISE:Databases
• /
• v.37 no.1
• /
• pp.1-11
• /
• 2010

Recently, there has been a growing interest in the processing of continuous queries over multiple data streams. When the arrival rates of tuples exceed the memory capacity of the system, a load shedding technique is used to avoid the system becoming overloaded by dropping some subset of input tuples. In this paper, we propose an effective load shedding algorithm for multi-way windowed joins over multiple data streams. Most previous load shedding algorithms estimate the productivity of each tuple, i.e., the number of join output tuples produced by the tuple, based on its "join attribute value" and drop tuples with the lowest productivity. However, the productivity of a tuple cannot be accurately estimated from its join attribute value when the join attribute values are unique and do not repeat, or the distribution of the join attribute values changes over time. For these cases, we estimate the productivity of a tuple based on its "arrival order" on data streams, rather than its join attribute value. The proposed method can effectively estimate the productivity of a tuple even when the productivity of a tuple cannot be accurately estimated from its join attribute value. Through extensive experiments and analysis, we show that our proposed method outperforms the previous methods in terms of effectiveness and efficiency.

• Journal of KIISE:Information Networking
• /
• v.35 no.6
• /
• pp.497-509
• /
• 2008

Various algorithms and architectures for efficient packet classification have been widely studied. Packet classification algorithms based on a decision tree structure such as HiCuts and HyperCuts are known to be the best by exploiting the geometrical representation of rules in a classifier. However, the algorithms are not practical since they involve complicated heuristics in selecting a dimension of cuts and determining the number of cuts at each node of the decision tree. Moreover, the cutting is not efficient enough since the cutting is based on regular interval which is not related to the actual range that each rule covers. In this paper, we proposed a new efficient packet classification algorithm using a range cutting. The proposed algorithm primarily finds out the ranges that each rule covers in 2-dimensional prefix plane and performs cutting according to the ranges. Hence, the proposed algorithm constructs a very efficient decision tree. The cutting applied to each node of the decision tree is optimal and deterministic not involving the complicated heuristics. Simulation results for rule sets generated using class-bench databases show that the proposed algorithm has better performance in average search speed and consumes up to 3-300 times less memory space compared with previous cutting algorithms.

• The KIPS Transactions:PartC
• /
• v.17C no.6
• /
• pp.441-450
• /
• 2010

Recently, a lot of interest is increased in sensor network which gathers various data through many sensor nodes deployed in wired and wireless network environment. However, because of the limitation in memory, computation, and energy of the sensor nodes, security problem is very important issue. In sensor network, not only the security problem, but also computing power should be seriously considered. In this paper, considering these characteristics, we make the sensor network consist of normal sensor nodes and clusterheaders with enough space and computing power, and propose a group key rekeying scheme adopting PCGR(Predistribution and local Collaborationbased Group Rekeying) for secure group communication. In our proposal, we enhance the security by minimizing the risk to safety of the entire network through verifying the new key value from clusterheader by sensor nodes. That is, to update the group keys, clusterheaders confirm sensor nodes through verifying the information from sensor nodes and send the new group keys back to authentic member nodes. The group keys sent back by the clusterheaders are verified again by sensor nodes. Through this mutual authentication, we can check if clusterheaders are compromised or not. Qualnet simulation result shows that our scheme not only guarantees secure group key rekeying but also decreasesstorage and communication overhead.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.1
• /
• pp.726-734
• /
• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.