• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.4
• /
• pp.1442-1462
• /
• 2014

Packet classification is a key technology of the Internet for routers to classify the arriving packets into different flows according to the predefined rulesets. Previous packet classification algorithms have mainly focused on search speed and memory usage, while overlooking update performance. In this paper, we propose PreCuts, which can drastically improve the update speed. According to the characteristics of IP field, we implement three heuristics to build a 3-layer decision tree. In the first layer, we group the rules with the same highest byte of source and destination IP addresses. For the second layer, we cluster the rules which share the same IP prefix length. Finally, we use the heuristic of information entropy-based bit partition to choose some specific bits of IP prefix to split the ruleset into subsets. The heuristics of PreCuts will not introduce rule duplication and incremental update will not reduce the time and space performance. Using ClassBench, it is shown that compared with BRPS and EffiCuts, the proposed algorithm not only improves the time and space performance, but also greatly increases the update speed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.4005-4025
• /
• 2019

Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.6
• /
• pp.151-156
• /
• 2018

Because of its large differences in writing style, context-independency and high recognition accuracy requirement, free handwritten digital identification is still a very difficult problem. Analyzing the characteristic of handwritten digits, this paper proposes a new handwritten digital identification method based on combining structural features. Given a handwritten digit, a variety of structural features of the digit including end points, bifurcation points, horizontal lines and so on are identified automatically and robustly by a proposed extended structural features identification algorithm and a decision tree based on those structural features are constructed to support automatic recognition of the handwritten digit. Experimental result demonstrates that the proposed method is superior to other general methods in recognition rate and robustness.

• Journal of Ecology and Environment
• /
• v.35 no.2
• /
• pp.91-98
• /
• 2012

This study was performed in order to suggest the possibility of tree species classification using high-resolution QuickBird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey's multiple comparison test was significant among tree species. However, tree species within the same genus, such as $Pinus$ $densiflora-P.$ $rigida$ and $Quercus$ $mongolica-Q.$ $serrata$, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of $Pterocarya$ $stenoptera$, 89.5%, was found to be the highest. The classification accuracy of broad-leaved trees was lower than expected, ranging from 47.9% to 88.9%. $P.$ $densiflora-P.$ $rigida$ and $Q.$ $mongolica-Q.$ $serrata$ were classified as the same species because they did not show significant differences in terms of spectral patterns.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.4
• /
• pp.11-20
• /
• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

• Nuclear Engineering and Technology
• /
• v.33 no.6
• /
• pp.596-604
• /
• 2001

This paper quantitatively presents the effects of important factors of the probabilistic safety assessment (PSA) of safety-critical digital systems. The result which is quantified using fault tree analysis methodology shows that these factors remarkably affect the system safety. In this paper we list the factors which should be represented by the model for PSA. Based on the PSA experience, we select three important factors which are expected to dominate the system unavailability. They are the avoidance of common cause failure, the coverage of fault tolerant mechanisms and software failure probability. We Quantitatively demonstrate the effect of these three factors. The broader usage of digital equipment in nuclear power plants gives rise to the safety problems. Even though conventional PSA methods are immature for applying to microprocessor-based digital systems, practical needs force us to apply it because the result of PSA plays an important role in proving the safety of a designed system. We expect the analysis result to provide valuable feedback to the designers of digital safety- critical systems.

• Journal of Korean Society of Forest Science
• /
• v.86 no.2
• /
• pp.241-250
• /
• 1997

The study was conducted to make a map for selecting righteous tree species for each site by digital terrain analysis. We set an algorithmic value for each tree species' characteristics with distribution pattern analysis, and the soil types were digitized from data indicated on soil map. Mean altitude, slope, aspect and micro-topography were estimated from the digital map for each block which had been calculated by regression equations with altitude. The results obtained from the study could be summarized as follows 1. We could develope a method to select righteous tree species for a given site with concern of soil, forest condition and topographic factors on Muju-Gun in Chonbuk province(2,500ha) by the terrain analysis and multi-variate digital map with a personal computer. 2. The brown forest soils were major soil types for the study area, and 29 tree species were occurred with Pinus densiflora as a dominant species. The differences in site condition and soil properties resulted in site quality differences for each tree species. 3. We tried to figure out the accuracy of a basic program(DTM.BAS) enterprised for this study with comparing the mean altitude and aspect calculated from the topographic terrain analysis map and those from surveyed data. The differences between the values were less than 5% which could be accepted as a statistically allowable value for altitude, as well as the values for aspect showed no differences between both the mean altitude and aspect. The result may indicate that the program can be used further in efficiency. 4. From the righteous-site selection map, the 2nd group(R, $B_1$) took the largest area with 46% followed by non-forest area (L) with 23%, the 5th group with 7% and the 4th group with 5%, respectively. The other groups occupied less than 6%. 5. We suggested four types of management tools by silvicultural tree species with considering soil type and topographic conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.4
• /
• pp.1223-1247
• /
• 2012

The need for securing Wireless Sensor Networks (WSNs) is essential especially in mission critical fields such as military and medical applications. Security techniques that are used to secure any network depend on the security requirements that should be achieved to protect the network from different types of attacks. Furthermore, the characteristics of wireless networks should be taken into consideration when applying security techniques to these networks. In this paper, energy efficient Security Model for Tree-based Routing protocols (SMTR) is proposed. In SMTR, different attacks that could face any tree-based routing protocol in WSNs are studied to design a security reference model that achieves authentication and data integrity using either Message Authentication Code (MAC) or Digital Signature (DS) techniques. The SMTR communication and processing costs are mathematically analyzed. Moreover, SMTR evaluation is performed by firstly, evaluating several MAC and DS techniques by applying them to tree-based routing protocol and assess their efficiency in terms of their power requirements. Secondly, the results of this assessment are utilized to evaluate SMTR phases in terms of energy saving, packet delivery success ratio and network life time.

• Journal of Digital Convergence
• /
• v.18 no.6
• /
• pp.297-309
• /
• 2020

This study focuses on the application of the data mining technique logistic regression analysis and decision tree analysis to the domestic public database called Korean Children Youth Panel Survey (KCYPS) to derive a series of important factors affecting the enhancement of life satisfaction of domestic youth. As a result, the general impact factors on life satisfaction for each grade were derived from logistic regression. Using decision tree analysis, we came to conclusions that those factors such as depression, overall grade satisfaction, household economic level, and school adaptation play crucial roles in affecting high school adolesscents' life satisfaction.

• Journal of Digital Contents Society
• /
• v.18 no.8
• /
• pp.1635-1640
• /
• 2017

In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.