• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.965-973
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• 2007

We analyzed that the loss of data in TCP protocol based wireless networks caused by overlapped responses in bi-directional nodes that were resulted in out of the data sequence. This loss can be prevented by using revised TCP rate control algorithm and the performance of throughput can also be improved. The rate control algorithm is applied when the congestion happens between nodes while traffic packets are retransmitting in TCP bandwidth. In addition to applying the rate control algorithm, we determine the number of system clients in bandwidth and the average of pausing time between transmitting serial files to produce a competitive level so that an efficient performance of rapid retransmitting for the loss of multi-packets. This paper discusses the improvement of congestion control in that the decrease of the loss, firstly, as ensuring an efficient connection rate and, secondly, as using sliding window flow control.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.953-964
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• 2020

Ever since media contents took over the world, the importance of typography has increased, and the influence of fonts has be n recognized. Nevertheless, the current Hangul font system is very poor and is provided passively, so it is practically impossible to understand and utilize all the shape characteristics of more than six thousand Hangul fonts. In this paper, the characteristics of Hangul font shapes were selected based on the Hangul structure of similar fonts. The stroke element detection training was performed by fine tuning Faster R-CNN Inception v2, one of the deep learning object detection models. We also propose a system that automatically extracts the stroke element characteristics from characters by introducing an automatic extraction algorithm. In comparison to the previous research which showed poor accuracy while using SVM(Support Vector Machine) and Sliding Window Algorithm, the proposed system in this paper has shown the result of 10 % accuracy to properly detect and extract stroke elements from various fonts. In conclusion, if the stroke element characteristics based on the Hangul structural information extracted through the system are used for similar classification, problems such as copyright will be solved in an era when typography's competitiveness becomes stronger, and an automated process will be provided to users for more convenience.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.221-227
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• 2010

Web access sequence mining can discover the frequently accessed web pages pursued by users. Utility-based web access sequence mining handles non-binary occurrences of web pages and extracts more useful knowledge from web logs. However, the existing utility-based web access sequence mining approach considers web access sequences from the very beginning of web logs and therefore it is not suitable for mining data streams where the volume of data is huge and unbounded. At the same time, it cannot find the recent change of knowledge in data streams adaptively. The existing approach has many other limitations such as considering only forward references of web access sequences, suffers in the level-wise candidate generation-and-test methodology, needs several database scans, etc. In this paper, we propose a new approach for high utility web access sequence mining over data streams with a sliding window method. Our approach can not only handle large-scale data but also efficiently discover the recently generated information from data streams. Moreover, it can solve the other limitations of the existing algorithm over data streams. Extensive performance analyses show that our approach is very efficient and outperforms the existing algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2315-2320
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• 2006

A real-time frame-layer rate control algorithm with a token bucket traffic shaper is proposed for low bit rate video coding. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performances than the existing rate control method.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.9 s.339
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• pp.73-80
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• 2005

The Turbo decoders based on Log-MAP decoding algorithm inherently requires large amount of memory and intensive complexity of hardware due to iterative decoding, despite of excellent decoding efficiency. To decrease the large amount of memory and reduce hardware complexity, the result of previous research. And this paper design the Turbo decoder applicable to the 3G W-CDMA systems. Through the result of previous research, we decided 5-bits for the received data 6-bits for a priori information, and 7-bits for the quantization state metrics. The error correction term for $MAX^{*}$ operation which is the main function of Log-MAP decoding algorithm is implemented with very small hardware overhead. The proposed Turbo decoder is synthesized in $0.35\mu$m Hynix CMOS technology. The synthesized result for the Turbo decoder shows that it supports a maximum 9Mbps data rate, and a BER of $10^{-6}$ is achieved(Eb/No=1.0dB, 5 iterations, and the interleaver size $\geq$ 2000).

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.140-149
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• 2004

Data broadcast has received much attention as a very efficient method for disseminating data items in mobile environment with large number of mobile clients. In this approach, a database server periodically and continuously broadcasts data items through wireless channels and clients perform read-only transactions by accessing necessary data items from the air. While broadcasting, the server must also process update transactions on the database, which raises an obstacle for client's accessing consistent data. In this research, we propose a new algorithm SCDSC(Serialization Checking with DirtySet on Commit) which is an alternative for solving the concurrency control problem efficiently. The SCDSC is a kind of optimistic concurrency control in that a client checks the consistency of data using a DirtySet as a part of data broadcast when it commits its transaction. In each broadcast cycle, the server updates and disseminates the DirtySet with newly changed data items for last few cycles in the sliding window approach. We perform an analysis and a simulation study to evaluate the performance of our SCDSC algorithm in terms of data consistency and data currency.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.43-54
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• 2007

This paper presents design and verification of a face detection hardware for real time application. Face detection algorithm detects rough face position based on already acquired feature parameter data. The hardware is composed of five main modules: Integral Image Calculator, Feature Coordinate Calculator, Feature Difference Calculator, Cascade Calculator, and Window Detection. It also includes on-chip Integral Image memory and Feature Parameter memory. The face detection hardware was verified by using S3C2440A CPU of Samsung Electronics, Virtex4LX100 FPGA of Xilinx, and a CCD Camera module. Our design uses 3,251 LUTs of Xilinx FPGA and takes about 1.96${\sim}$0.13 sec for face detection depending on sliding-window step size, when synthesized for Virtex4LX100 FPGA. When synthesized on Magnachip 0.25um ASIC library, it uses about 410,000 gates (Combinational area about 345,000 gates, Noncombinational area about 65,000 gates) and takes less than 0.5 sec for face realtime detection. This size and performance shows that it is adequate to use for embedded system applications. It has been fabricated as a real chip as a part of XF1201 chip and proven to work.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.263-275
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• 2005

In a large DNA database, indexing techniques are widely used for rapid approximate sequence searching. However, most indexing techniques require a space larger than original databases, and also suffer from difficulties in seamless integration with DBMS. In this paper, we suggest a space-efficient and disk-based indexing and query processing algorithm for approximate DNA sequence searching, specially exact match queries, wildcard match queries, and k-mismatch queries. Our indexing method places a sliding window at every possible location of a DNA sequence and extracts its signature by considering the occurrence frequency of each nucleotide. It then stores a set of signatures using a multi-dimensional index, such as R*-tree. Especially, by assigning a weight to each position of a window, it prevents signatures from being concentrated around a few spots in index space. Our query processing algorithm converts a query sequence into a multi-dimensional rectangle and searches the index for the signatures overlapped with the rectangle. The experiments with real biological data sets revealed that the proposed method is at least three times, twice, and several orders of magnitude faster than the suffix-tree-based method in exact match, wildcard match, and k- mismatch, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.