• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.5
• /
• pp.235-244
• /
• 2017

As creativity and problem-solving ability become core competencies, the main objectives of programming subjects in the elementary and secondary educational curriculum is 'computational thinking'. This goal can not be achieved at the level of understanding the characteristics of the programming language and the simple utilization abilities of the computer. The abilities to write algorithms and solve problems in real life situations using programming languages are required. In order to cultivate these abilities, the curriculum of the programming area was strengthened in the elementary and middle education curriculum, and the criteria for evaluating the achievement level were also prepared. However, the curriculum that can be used in actual education field is not yet established. In this study, we analyzed the researches on the existing programming curriculum and evaluated how well the curriculum meets the achievement criteria. Also, we can suggest the aspects to be considered in the study of programming curriculum and to verify whether the results of curriculum operation are in line with achievement criteria. In addition, future directions in elementary and middle school programming curriculum are suggested.

• The KIPS Transactions:PartA
• /
• v.13A no.3 s.100
• /
• pp.191-198
• /
• 2006

Today's portable electric consumer devices, which are operated by battery, tend to integrate more multimedia processing capabilities. In the multimedia processing devices, multimedia system-on-chips can handle specific algorithms which need intensive processing capabilities and significant power consumption. As a result, the power-efficiency of multimedia processing devices becomes important increasingly. In this paper, we propose a reconfigurable data caching architecture, in which data allocation is constrained by software support, and evaluate its performance and power efficiency. Comparing with conventional cache architectures, power consumption can be reduced significantly, while miss rate of the proposed architecture is very similar to that of the conventional caches. The reduction of power consumption for the reconfigurable data cache architecture shows 33.2%, 53.3%, and 70.4%, when compared with direct-mapped, 2-way, and 4-way caches respectively.

• Journal of KIISE:Software and Applications
• /
• v.27 no.4
• /
• pp.432-440
• /
• 2000

In this study, a new algorithm for canceling MRI artifact due to translational motion in image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is presented. In previous approaches, the motions in the x(read out) direction and the y(phase encoding) direction are estimated simultaneously. However, the features of x and y directional motions are different from each other. By analyzing their features, each x and y directional motion is canceled by different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non-zero area of the spectrum just corresponds to the projected area of the density function on the x-axis. So the motion is estimated by tracing the edges between non-zero area and zero area of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled by using a new constraint condition, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by using a phantom image with simulated motion.

• Journal of KIISE:Software and Applications
• /
• v.31 no.2
• /
• pp.203-212
• /
• 2004

The watermarking is a method to achieve the copyright protection of multimedia contents. Among several media, the left documents show very peculiar properties: block/line/word patterning, clear separation between foreground and background areas. So algorithms specific to the text documents are required that meet those properties. This paper proposes a novel watermarking algorithm for the grayscale text document images. The algorithm inserts the watermark signals through the edge direction histograms. A concept of sub-image consistency is developed that the sub-images have similar shapes in terms of edge direction histograms. Using Korean, Chinese, and English document images, the concept is evaluated and proven to be valid over a wide range of document images. To insert watermark signals, the edge direction histogram is modified slightly. The experiments were performed on various document images and the algorithm was evaluated in terms of imperceptibility and robustness.

• Journal of KIISE:Software and Applications
• /
• v.32 no.2
• /
• pp.85-98
• /
• 2005

Recently, a lot of researches about mobile vision using Personal Digital Assistant(PDA) has been attempted. Many CPUs for PDA are integer CPUs, which have no floating-computation component. It results in slow computation of the algorithms peformed by vision system or image processing, which have much floating-computation. In this paper, in order to resolve this weakness, we propose the Client(PDA)/server(PC) architecture which is connected to each other with a wireless LAN, and we construct the system with pipelining processing using two CPUs of the Client(PDA) and the Server(PC) in image sequence. The Client(PDA) extracts tentative text regions using Edge Density(ED). The Server(PC) uses both the Multi-1.aver Perceptron(MLP)-based texture classifier and Connected Component(CC)-based filtering for a definite text extraction based on the Client(PDA)'s tentativel99-y extracted results. The proposed method leads to not only efficient text extraction by using both the MLP and the CC, but also fast running time using Client(PDA)/server(PC) architecture with the pipelining processing.

• Journal of KIISE:Software and Applications
• /
• v.29 no.1_2
• /
• pp.1-9
• /
• 2002

Evolutionary artificial neural networks (EANNs) are towards the near optimal ANN using the global search of evolutionary instead of trial-and-error process. However, many real-world problems are too hard to be solved by only one ANN. Recently there has been plenty of interest on combining ANNs in the last generation to improve the performance and reliability. This paper proposes a new approach of constructing multiple ANNs which complement each other by speciation. Also, we develop a multiple ANN to combine the results in abstract, rank, and measurement levels. The experimental results on Australian credit approval data from UCI benchmark data set have shown that combining of the speciated EANNs have better recognition ability than EANNs which are not speciated, and the average error rate of 0.105 proves the superiority of the proposed EANNs.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.2
• /
• pp.119-122
• /
• 2013

Repetitive strings such as periods have been studied vigorously in so diverse fields as data compression, computer-assisted music analysis, bioinformatics, and etc. In bioinformatics, periods are highly related to repetitive patterns in DNA sequences so called tandem repeats. In some cases, quite similar but not the same patterns are repeated and thus we need approximate string matching algorithms to study tandem repeats in DNA sequences. In this paper, we propose a new definition of approximate periods of strings based on distance sum. Given two strings $p({\mid}p{\mid}=m)$ and $x({\mid}x{\mid}=n)$, we propose an algorithm that computes the minimum approximate period distance based on distance sum. Our algorithm runs in $O(mn^2)$ time for the weighted edit distance, and runs in O(mn) time for the edit distance, and runs in O(n) time for the Hamming distance.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.4
• /
• pp.273-280
• /
• 2013

This paper presents novel OCS-LBP (Oriented Center Symmetric Local Binary Patterns) based on orientation of pixel gradient and image retrieval system based on BoF (Bag-of-Feature) and random forest classifier. Feature vectors extracted from training data are clustered into code book and each feature is transformed new BoF feature using code book. BoF features are applied to random forest for training and random forest having N classes is constructed by combining several decision trees. For testing, the same OCS-LBP feature is extracted from a query image and BoF is applied to trained random forest classifier. In contrast to conventional retrieval system, query image selects similar K-nearest neighbor (K-NN) classes after random forest is performed. Then, Top K similar images are retrieved from database images that are only labeled K-NN classes. Compared with other retrieval algorithms, the proposed method shows both fast processing time and improved retrieval performance.

• KIPS Transactions on Computer and Communication Systems
• /
• v.7 no.10
• /
• pp.251-258
• /
• 2018

Ransomware, a malicious software that requires a ransom by encrypting a file, is becoming more threatening with its rapid propagation and intelligence. Rapid detection and risk analysis are required, but real-time analysis and reporting are lacking. In this paper, we propose a ransomware infection detection system using social big data mining technology to enable real-time analysis. The system analyzes the twitter stream in real time and crawls tweets with keywords related to ransomware. It also extracts keywords related to ransomware by crawling the news server through the news feed parser and extracts news or statistical data on the servers of the security company or search engine. The collected data is analyzed by data mining algorithms. By comparing the number of related tweets, google trends (statistical information), and articles related wannacry and locky ransomware infection spreading in 2017, we show that our system has the possibility of ransomware infection detection using tweets. Moreover, the performance of proposed system is shown through entropy and chi-square analysis.

• The KIPS Transactions:PartA
• /
• v.9A no.4
• /
• pp.441-450
• /
• 2002

As the size of embedded system software increase bigger and bigger, and it's complexity is grower and grower, the usage of dynamic memory management scheme such collector also has been increased. Using the garbage collector, however, inherently lead us performance degradation. In order to resolve this kind of performance problem in the Java based embedded system. we introduce an explicit dynamic memory free method to the automated dynamic memory management environment. which can be performed by a programmer. In the worst case, the prosed scheme shows the same performance as the case of that only garbage collector is working, since the unclaimed garbage objects will eventually be collected later by the garbage collector. In the best case. our method is free from any runtime overhead because the applications can be implemented without any intervention of the garbage collector. Although the proposed method can be facilitated with all the existing garbage collection algorithms, it shows an outperform in the case of mark-and-sweep algorithm.