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Bounded Search Strategies of Concolic Testing for Effective and Efficient Structural Coverage Achievement
http://doi.org/10.5626/JOK.2021.48.2.201
This paper proposes a loop-bounded search strategy for effective and efficient coverage achievement in concolic testing. In selecting a new path to explore, a loop-bounded search strategy limits the number of iterations in a loop to a certain loop-bound, so that the concolic testing is guided to explore various program behaviors within a limited range. In addition, to extend the range of path exploration gradually, this search strategy increments the loop-bound over test executions based on their coverage achievement rates. We implemented three versions of loop-bounded search strategies based on three existing concolic search strategies of CREST. The experiments with 4 real-world target programs (Vim, Grep, Busybox Awk, and Busybox Sed) showed that CREST achieves a higher branch coverage more quickly when the loop-bounded search strategies are applied.
Dual Paraboloid Map-Based Real-Time Indirect Illumination Rendering
http://doi.org/10.5626/JOK.2019.46.11.1099
Indirect light rendering, which expresses the light expression more finely and delicately, has been studied in terms of the indirect illumination effect in real-time rendering environment due to the load of the physical calculation process. Among them, the Light Propagation Volumes technique achieved real-time performance by approximating the indirect lighting effect by propagating the volume containing the light information to the adjacent volume. However, as the size of the geometry increases, performance degradation occurs as the Reflective Shadow Map containing the light information is generated as a cube map in the rendering process. Although it is possible to replace the Reflective Shadow Map with other types of textures other than the cube map to reduce the occurrence of bottlenecks, distortion occurs in the nonlinear projection transformation of other type textures. In this study, the Reflective Shadow Map is generated as a dual paraboloid map types to reduce the bottleneck. Distortions occurring in the process of paraboloid map transformation were corrected by using fixed point iteration-based backward warping.
Solving for Redundant Repetition Problem of Generating Summarization using Decoding History
Jaehyun Ryu, Yunseok Noh, Su Jeong Choi, Seyoung Park, Seong-Bae Park
http://doi.org/10.5626/JOK.2019.46.6.535
Neural attentional sequence-to-sequence models have achieved great success in abstractive summarization. However, the model is limited by several challenges including repetitive generation of words, phrase and sentences in the decoding step. Many studies have attempted to address the problem by modifying the model structure. Although the consideration of actual history of word generation is crucial to reduce word repetition, these methods, however, do not consider the decoding history of generated sequence. In this paper, we propose a new loss function, called ‘Repeat Loss’ to avoid repetitions. The Repeat Loss directly prevents the model from repetitive generation of words by giving a loss penalty to the generation probability of words already generated in the decoding history. Since the propose Repeat Loss does not need a special network structure, the loss function is applicable to any existing sequence-to-sequence models. In experiments, we applied the Repeat Loss to a number of sequence-to-sequence model based summarization systems and trained them on both Korean and CNN/Daily Mail summarization datasets. The results demonstrate that the proposed method reduced repetitions and produced high-quality summarization.
Resolution of Answer-Repetition Problems in a Generative Question-Answering Chat System
http://doi.org/10.5626/JOK.2018.45.9.925
A question-answering (QA) chat system is a chatbot that responds to simple factoid questions by retrieving information from knowledge bases. Recently, many chat systems based on sequence-to-sequence neural networks have been implemented and have shown new possibilities for generative models. However, the generative chat systems have word repetition problems, in that the same words in a response are repeatedly generated. A QA chat system also has similar problems, in that the same answer expressions frequently appear for a given question and are repeatedly generated. To resolve this answer-repetition problem, we propose a new sequence-to-sequence model reflecting a coverage mechanism and an adaptive control of attention (ACA) mechanism in a decoder. In addition, we propose a repetition loss function reflecting the number of unique words in a response. In the experiments, the proposed model performed better than various baseline models on all metrics, such as accuracy, BLEU, ROUGE-1, ROUGE-2, ROUGE-L, and Distinct-1.
Parallel Algorithms for Finding δ-approximate Periods and γ-approximate Periods of Strings over Integer Alphabets
http://doi.org/10.5626/JOK.2017.44.8.760
Repetitive strings have been studied in diverse fields such as data compression, bioinformatics and so on. Recently, two problems of approximate periods of strings over integer alphabets were introduced, finding minimum δ-approximate periods and finding minimum γ-approximate periods. Both problems can be solved in O(n²) time when n is the length of the string. In this paper, we present two parallel algorithms for solving the above two problems in O(n²) time using O(n²) threads, respectively. The experimental results show that our parallel algorithms for finding minimum δ-approximate (resp. γ-approximate) periods run approximately 19.7 (resp. 40.08) times faster than the sequential algorithms when n = 10,000.
Matching for the Elbow Cylinder Shape in the Point Cloud Using the PCA
The point-cloud representation of an object is performed by scanning a space through a laser scanner that is extracting a set of points, and the points are then integrated into the same coordinate system through a registration. The set of the completed registration-integrated point clouds is classified into meaningful regions, shapes, and noises through a mathematical analysis. In this paper, the aim is the matching of a curved area like a cylinder shape in 3D point-cloud data. The matching procedure is the attainment of the center and radius data through the extraction of the cylinder-shape candidates from the sphere that is fitted through the RANdom Sample Consensus (RANSAC) in the point cloud, and completion requires the matching of the curved region with the Catmull-Rom spline from the extracted center-point data using the Principal Component Analysis (PCA). Not only is the proposed method expected to derive a fast estimation result via linear and curved cylinder estimations after a center-axis estimation without constraint and segmentation, but it should also increase the work efficiency of reverse engineering.
Repeated Cropping based on Deep Learning for Photo Re-composition
Eunbin Hong, Junho Jeon, Seungyong Lee
This paper proposes a novel aesthetic photo recomposition method using a deep convolutional neural network (DCNN). Previous recomposition approaches define the aesthetic score of photo composition based on the distribution of salient objects, and enhance the photo composition by maximizing the score. These methods suffer from heavy computational overheads, and often fail to enhance the composition because their optimization depends on the performance of existing salient object detection algorithms. Unlike previous approaches, we address the photo recomposition problem by utilizing DCNN, which shows remarkable performance in object detection and recognition. DCNN is used to iteratively predict cropping directions for a given photo, thus generating an aesthetically enhanced photo in terms of composition. Experimental results and user study show that the proposed framework can automatically crop the photo to follow specific composition guidelines, such as the rule of thirds.
δ-approximate Periods and γ-approximate Periods of Strings over Integer Alphabets
(δ, γ)-matching for strings over integer alphabets can be applied to such fields as musical melody and share prices on stock markets. In this paper, we define δ-approximate periods and γ-approximate periods of strings over integer alphabets. We also present two O(n²) - time algorithms, each of which finds minimum δ-approximate periods and minimum γ-approximate periods, respectively. Then, we provide the experimental results of execution times of both algorithms.
Matching for Cylinder Shape in Point Cloud Using Random Sample Consensus
Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.
A Smoothing Method for Digital Curve by Iterative Averaging with Controllable Error
Smoothing a digital curve by averaging its connected points is widely employed to minimize sharp changes of the curve that are generally introduced by noise. An appropriate degree of smoothing is critical since the area or features of the original shape can be distorted at a higher degree while the noise is insufficiently removed at a lower degree. In this paper, we provide a mathematical relationship between the parameters, such as the number of iterations, average distance between neighboring points, weighting factors for averaging and the moving distance of the point on the curve after smoothing. Based on these findings, we propose to control the smoothed curve such that its deviation is bounded particular error level as well as to significantly expedite smoothing for a pixel-based digital curve.
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