Vol. 43, No. 5,
May 2016
Digital Library
A Hashing-Based Algorithm for Order-Preserving Multiple Pattern Matching
Munseong Kang, Sukhyeun Cho, Jeong Seop Sim
Given a text Tand a pattern P, the order-preserving pattern matching problem is to find all substrings in T which have the same relative orders as P. The order-preserving pattern matching problem has been studied in terms of finding some patterns affected by relative orders, not by their absolute values. Given a text T and a pattern set ℙ, the order-preserving multiple pattern matching problem is to find all substrings in T which have the same relative orders as any pattern in ℙ. In this paper, we present a hashing-based algorithm for the order-preserving multiple pattern matching problem.
Fabrication of Face Molds and Silicone Masks using 3D Printing
Yea-Jun Choi, Il-Kyu Shin, Kanghyun Choi, Soo-Mi Choi
For old-age makeups, makeup artists first make a mold cast of an actor’s face using plaster and then sculpt wrinkles in clay on the plaster mold. After finishing the clay sculpture, its negative plaster mold is fabricated and silicone skin patches are finally made for application to the actor’s face. This process takes a few days and is tedious for actors and makeup artists. With recent advances in 3D printing and scanning technology, it is becoming easier to scan and fabricate 3D faces. This paper presents a new pipeline composed of facial scanning, interactive wrinkle modeling, and mold printing stages to easily and efficiently fabricate silicone masks for old-age makeups without the use of plaster and clay. An intuitive sketch interface based on a normal map is proposed for the creation of wrinkles in real time, even with a high-resolution face model. Then the geometry of the final wrinkles is reconstructed using a depth map and the negative mold of the wrinkled face is printed. We also show that the presented pipeline can fabricate a silicone mask more conveniently than the traditional one that consists of pouring silicone into the prepared negative mold and then overlapping the mold with the original positive one.
Mapping Cache for High-Performance Memory Mapped File I/O in Memory File Systems
Jiwon Kim, Jungsik Choi, Hwansoo Han
The desire to access data faster and the growth of next-generation memories such as non-volatile memories, contribute to the development of research on memory file systems. It is recommended that memory mapped file I/O, which has less overhead than read-write I/O, is utilized in a high-performance memory file system. Memory mapped file I/O, however, brings a page table overhead, which becomes one of the big overheads that needs to be resolved in the entire file I/O performance. We find that same overheads occur unnecessarily, because a page table of a file is removed whenever a file is opened after being closed. To remove the duplicated overhead, we propose the mapping cache, a technique that does not delete a page table of a file but saves the page table to be reused when the mapping of the file is released. We demonstrate that mapping cache improves the performance of traditional file I/O by 2.8x and web server performance by 12%.
A Context Recognition System for Various Food Intake using Mobile and Wearable Sensor Data
Development of various sensors attached to mobile and wearable devices has led to increasing recognition of current context-based service to the user. In this study, we proposed a probabilistic model for recognizing user"s food intake context, which can occur in a great variety of contexts. The model uses low-level sensor data from mobile and wrist-wearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level activities like food intake, a context model represents the relevant contexts systematically based on 4 components of activity theory and 5 W’s, and tree-structured Bayesian network recognizes the probabilistic state. To verify the proposed method, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods in accuracy (93.21%). Also, we conducted a scenario-based test and investigated the effect contribution of individual components for recognition.
A Process Algebra Construct Method for Reduction of States in Reachability Graph: Conjunctive and Complement Choices
This paper introduces the new notions of conjunctive and complement choices in process algebra, which reduce both process and system complexities significantly for distributed mobile real-time system during specification and analysis phases. The complement choice implies that two processes make cohesive choices for their synchronous partners at their own choice operations. The conjunctive choice implies choice dependency among consecutive choice operations in a process. The conjunctive choice reduces process complexity exponentially by the degree of the consecutive choice operations. The complement choice also reduces system complexity exponentially by the degree of the synchronous choice operations. Consequently, the reduction method makes the specification and analysis of the systems much easier since the complexity is reduced significantly. This notion is implemented in a process algebra, called δ-calculus. The efficiency and effectiveness are demonstrated with an example in a tool for the algebra, called SAVE, which is developed on ADOxx platform.
Confidence Value based Large Scale OWL Horst Ontology Reasoning
Wan-Gon Lee, Hyun-Kyu Park, Batselem Jagvaral, Young-Tack Park
Several machine learning techniques are able to automatically populate ontology data from web sources. Also the interest for large scale ontology reasoning is increasing. However, there is a problem leading to the speculative result to imply uncertainties. Hence, there is a need to consider the reliability problems of various data obtained from the web. Currently, large scale ontology reasoning methods based on the trust value is required because the inference-based reliability of quantitative ontology is insufficient. In this study, we proposed a large scale OWL Horst reasoning method based on a confidence value using spark, a distributed in-memory framework. It describes a method for integrating the confidence value of duplicated data. In addition, it explains a distributed parallel heuristic algorithm to solve the problem of degrading the performance of the inference. In order to evaluate the performance of reasoning methods based on the confidence value, the experiment was conducted using LUBM3000. The experiment results showed that our approach could perform reasoning twice faster than existing reasoning systems like WebPIE.
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.
FBDtoVHDL: An Automatic Translation from FBD into VHDL for FPGA Development
Jaeyeob Kim, Eui-Sub Kim, Junbeom Yoo, Young Jun Lee, Jong-Gyun Choi
The PLC (Programmable Logic Controller) has been widely used for the development of digital control system of nuclear power plant. The PLC has high maintenance costs and increasing complexity, hence, FPGA (Field Programmable Gate Array) based digital control system has been considered as an alternative. However, the development of FPGA based digital control system is a challenge for PLC engineers because they are required to learn about new language to develop FPGA and knowledge and know-how acquired in the development of PLC is not transferable. In this study, we proposed and implemented an automatic translation tool for translation of FBD (Function Block Diagram), a programming language of PLC software, into VHDL (VHSIC Hardware Description Language). Automatically translating the FBD to VHDL using this tool allows PLC engineers to develop FPGA without any knowledge of the hardware description language.
Design of Fourth Generation Knowledge Management System based on Social Network Service
Gilseung Ahn, Minsung Kwon, Changwook Kang, Sun Hur
Currently, corporations have introduced the knowledge management system that utilizes knowledge effectively for practical purpose and development of core ability. However, existing knowledge systems have failed to share the knowledge content due to lack of elements that encourage the members to participate in the system. In this study, we designed a novel knowledge management system that employs the structure of social network service (SNS). More precisely, screen layout according to function and several algorithms to improve user friendliness and produce integrated knowledge content are recommended. The proposed SNS-based knowledge management system encourages the enterprise members to participate in the system to produce and share valuable knowledge contents.
An Efficient Algorithm for Monitoring Continuous Top-k Queries
JaeHee Jang, HaRim Jung, YougHee Kim, Ung-Mo Kim
In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.
Policy Based DDoS Attack Mitigation Methodology
Hyuk Joon Kim, Dong Hwan Lee, Dong Hwa Kim, Myung Kil Ahn, Yong Hyun Kim
Since the Denial of Service Attack against multiple targets in the Korean network in private and public sectors in 2009, Korea has spent a great amount of its budget to build strong Internet infrastructure against DDoS attacks. As a result of the investments, many major governments and corporations installed dedicated DDoS defense systems. However, even organizations equipped with the product based defense system often showed incompetency in dealing with DDoS attacks with little variations from known attack types. In contrast, by following a capacity centric DDoS detection method, defense personnel can identify various types of DDoS attacks and abnormality of the system through checking availability of service resources, regardless of the types of specific attack techniques. Thus, the defense personnel can easily derive proper response methods according to the attacks. Deviating from the existing DDoS defense framework, this research study introduces a capacity centric DDoS detection methodology and provides methods to mitigate DDoS attacks by applying the methodology.
A Video Streaming Scheme for Minimizing Viewpoint Switching Delay in DASH-based Multi-view Video Services
Sangwook Kim, Dooyeol Yun, Kwangsue Chung
The multi-view video service based on the DASH(Dynamic Adaptive Streaming over HTTP) switches the viewpoint or object which is selected by the user among the multiple video streams captured by multiple cameras. However, the problem is that the conventional DASH-based multi-view video service takes a long time to switch the viewpoint. The reason is that the conventional scheme switches to the new video stream after consuming all buffered segments of the previous video stream. In this paper, we propose a video streaming scheme for minimizing the viewpoint switching delay in the DASH-based multi-view video service. In order to minimize the viewpoint switching delay, the proposed scheme configures the video streams by controlling the GoP (Group of Pictures) size and controls the client buffer based on bandwidth estimation and playback buffer occupancy. Through the experimental results, we prove that the proposed scheme reduces the viewpoint switching delay.
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