Vol. 42, No. 1,
Jan. 2015
Digital Library
A Synchronization Technique for Android Multivision Applications with Multiple Smart Devices
Ganghyeon Kim, Junho Yun, Bupjae Lee, Daeyoung Kim
Smart electronics are now widely used in everyday life, but the size of the screen of such devices is still too small to fully enjoy multimedia content. Therefore, if the display is comprised of multiple views produced by multiple smart devices, then the screen output size can increase. However, a time delay between the devices can generate a discordance in the video and sound. This paper compares two synchronization techniques that can be used to minimize such a time delay, and proposes a synchronization technique in which, the timing of the screen for each device is calculated by synchronizing the playback time, using the timing information transferred from the control device, and periodically adjusting the playback timing forward or backward. When multimedia content is reproduced using multiple views from multiple smart devices, we can minimize the time delay, regardless of the network quality or the differences in the devices used for this technique.
Data Consistency-Control Scheme Using a Rollback-Recovery Mechanism for Storage Class Memory
Hyun Ku Lee, Junghoon Kim, Dong Hyun Kang, Young Ik Eom
Storage Class Memory(SCM) has been considered as a next-generation storage device because it has positive advantages to be used both as a memory and storage. However, there are significant problems of data consistency in recently proposed file systems for SCM such as insufficient data consistency or excessive data consistency-control overhead. This paper proposes a novel data consistency-control scheme, which changes the write mode for log data depending on the modified data ratio in a block, using a rollback-recovery scheme instead of the Write Ahead Logging (WAL) scheme. The proposed scheme reduces the log data size and the synchronization cost for data consistency. In order to evaluate the proposed scheme, we implemented our scheme on a Linux 3.10.2- based system and measured its performance. The experimental results show that our scheme enhances the write throughput by 9 times on average when compared to the legacy data consistency control scheme.
A Case Study of Drug Repositioning Simulation based on Distributed Supercomputing Technology
Jik-Soo Kim, Seungwoo Rho, Minho Lee, Seoyoung Kim, Sangwan Kim, Soonwook Hwang
In this paper, we present a case study for a drug repositioning simulation based on distributed supercomputing technology that requires highly efficient processing of large-scale computations. Drug repositioning is the application of known drugs and compounds to new indications (i.e., new diseases), and this process requires efficient processing of a large number of docking tasks with relatively short per-task execution times. This mechanism shows the main characteristics of a Many-Task Computing (MTC) application, and as a representative case of MTC applications, we have applied a drug repositioning simulation in our HTCaaS system which can leverage distributed supercomputing infrastructure, and show that efficient task dispatching, dynamic resource allocation and load balancing, reliability, and seamless integration of multiple computing resources are crucial to support these challenging scientific applications.
Study on the Improvement about User Authentication of Android Third Party Application Through the Vulnerability in Google Voice
Seyeong Lee, Jaekyun Park, Sungdae Hong, Hyoungki Choi
In the Android market, a large portion of the market share consists of third party applications, but not much research has been performed in this respect. Of these applications, mobile Voice Over IP (VoIP) applications are one of the types of applications that are used the most. In this paper, we focus on user authentication methods for three representative applications of the Google Voice service, which is a famous mobile VoIP application. Then, with respect to the Android file system, we developed a method to store and to send user information for authentication. Finally, we demonstrate a vulnerability in the mechanism and propose an improved mechanism for user authentication by using hash chaining and an elliptic curve Diffie-Hellman key exchange.
Patent Image Retrieval Using SURF Direction histograms
Recently, patent images are growing importance and thus patent image retrieval is a growing area of research. However, most existing patent image retrieval systems use edges extracted in the images, whose performance is affected by the quality of edge detection in the image pre-processing step. To overcome this disadvantage, we propose a SURF-based patent image retrieval method which uses the morphological characteristics of the images. The proposed method detects SURF interest points with directions and computes regional histograms. We apply the proposed method to a patent image database with 2000 binary images and we show the proposed retrieval system achieves excellent results, even when the images have some loss or degradation.
Control Flow Reconstruction from Virtualization-Obfuscated Binaries
Control flow information is useful in the analysis and comparison of programs. Virtualization-obfuscation hides control structures of the original program by transforming machine instructions into bytecode. Direct examination of the resulting binary reveals only the structure of the interpreter. Recovery of the original instructions requires knowledge of the virtual machine architecture, which is randomly generated and hidden. In this paper, we propose a method to reconstruct original control flow using only traces generated from the obfuscated binary. We consider traces as strings and find an automaton that represents the strings. State transitions in the automaton correspond to the control transfers in the original program. We have shown the effectiveness of our method with commercial obfuscators.
Real-time and Parallel Semantic Translation Technique for Large-Scale Streaming Sensor Data in an IoT Environment
SoonHyun Kwon, Dongwan Park, Hyochan Bang, Youngtack Park
Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.
Automatic Word Spacing Using Raw Corpus and a Morphological Analyzer
This paper proposes a method for the automatic word spacing of unsegmented Korean sentences. In our method, eojeol monograms are used for word spacing as opposed to the syllable n-grams that have been used in previous studies. The use of a Korean morphological analyzer is limited to the correction of typical word spacing errors. Our method gives a 98.06% syllable accuracy and a 94.15% eojeol recall, when 10-fold cross-validated with the Sejong corpus, after filtering out non-hangul eojeols. The processing rate is 250K eojeols or 1.8 MB per second on a typical personal computer. Syllable accuracy and eojeol recall are related to the size of the eojeol dictionary, better performance is expected with a bigger corpus.
Software Product Line Development and Test Process Based on CVL
Eunyoung Cheon, Yongjin Seo, Ju Seok Lee, Su Ji Kim, Jin-a Kim, Hyeon Soo Kim
Software Product Line Engineering is a collection of techniques that analyze the commonalities and variabilities of the products within a product family and produce products using such information. In Software Product Line Engineering, construction of the correct core assets is very important. To accomplish this, the commonalities and variabilities must first be definitively identified, both to provide traceability between the core assets, and to guarantee the reliability of the products. This paper suggests software product line development and test processes based on CVL for the differentiation of commonalities and variabilities. The proposed approach enables correct building of the core assets through procedures to keep traceability and guarantee the reliability of the products.
Creating Level Set Trees Using One-Class Support Vector Machines
A level set tree provides a useful representation of a multidimensional density function. Visualizing the data structure as a tree offers many advantages for data analysis and clustering. In this paper, we present a level set tree estimation algorithm for use with a set of data points. The proposed algorithm creates a level set tree from a family of level sets estimated over a whole range of levels from zero to infinity. Instead of estimating density function then thresholding, we directly estimate the density level sets using one-class support vector machines (OC-SVMs). The level set estimation is facilitated by the OC-SVM solution path algorithm. We demonstrate the proposed level set tree algorithm on benchmark data sets.
Keypoint Detection Using Normalized Higher-Order Scale Space Derivatives
The SIFT method is well-known for robustness against various image transformations, and is widely used for image retrieval and matching. The SIFT method extracts keypoints using scale space analysis, which is different from conventional keypoint detection methods that depend only on the image space. The SIFT method has also been extended to use higher-order scale space derivatives for increasing the number of keypoints detected. Such detection of additional keypoints detected was shown to provide performance gain in image retrieval experiments. Herein, a sigma based normalization method for keypoint detection is introduced using higher-order scale space derivatives.
A Query Result Integrity Assurance Scheme Using an Order-preserving Encryption Scheme in the Database Outsourcing Environment
Recently, research on database encryption for data protection and query result authentication methods has been performed more actively in the database outsourcing environment. Existing database encryption schemes are vulnerable to order matching and counting attack of intruders who have background knowledge of the original database domain. Existing query result integrity auditing methods suffer from the transmission overhead of verification object. To resolve these problems, we propose a group-order preserving encryption index and a query result authentication method based on the encryption index. Our group-order preserving encryption index groups the original data for data encryption and support query processing without data decryption. We generate group ids by using the Hilbert-curve so that we can protect the group information while processing a query. Finally, our periodic function based data grouping and query result authentication scheme can reduce the data size of the query result verification. Through performance evaluation, we show that our method achieves better performance than an existing bucket-based verification scheme, it is 1.6 times faster in terms of
query processing time and produces verification data that is 20 times smaller.
Performance Analysis of Flash Memory SSD with Non-volatile Cache for Log Storage
Dae-Yong Hong, Gi-Hwan Oh, Woon-Hak Kang, Sang-Won Lee
In a database system, updates on pages that are made by a transaction should be stored in a secondary storage before the commit is complete. Generic secondary storages have volatile DRAM caches to hide long latency for non-volatile media. However, as logs that are only written to the volatile DRAM cache don’t ensure durability, logging latency cannot be hidden. Recently, a flash SSD with capacitor-backed DRAM cache was developed to overcome the shortcoming. Storage devices, like those with a non-volatile cache, will increase transaction throughput because transactions can commit as soon as the logs reach the cache. In this paper, we analyzed performance in terms of transaction throughput when the SSD with capacitor-backed DRAM cache was used as log storage. The transaction throughput can be improved over three times, by committing right after storing the logs to the DRAM cache, rather than to a secondary storage device. Also, we showed that it could acquire over 73% of the ideal logging performance with proper tuning.
A Congestion Control Scheme Considering Traffic in Large-Scale Wireless Sensor Networks
Moon-Sang Kwak, Young Sik Hong
Large-scale wireless sensor networks are constructed by using a large number of sensor nodes that are non-uniformly deployed over a wide area. As a result, the data collected by the sensor nodes are similar to that from one another since a high density of the sensor nodes may cause an overlap. As a result of the characteristics of the traffic, data is collected from a plurality of sensor nodes by a sink node, and when the sensor nodes transmit their collected data to the sink node, the sensor nodes around the sink node have a higher amount of traffic than the sensor nodes far away from the sink node. Thus, the former sensor encounter bottlenecks due to traffic congestion and have an energy hole problem more often than the latter ones, increasing energy consumption. This paper proposes a congestion control scheme that considers traffic flows in order to control traffic congestion of the sensor nodes that are non-uniformly deployed over a large-scale wireless sensor network.
A Mechanism to Provide Telepresence Service Information to Heterogeneous Services
Yunjin Lee, Younghan Kim, Sunwan Choi
This paper proposes a method for providing the information about multimedia streams for telepresence services to heterogeneous services such as IMS (IP Multimedia Subsystem) and RTCWeb (Real-Time Communication in WEB-browsers). First of all, we design an interworking gateway for each service and suggest a procedure for providing the information about multimedia streams, which is defined by CLUE, a working group for standardization, to the heterogeneous services. We also apply the method of the actual CLUE information exchange and implement it in our experiment environment. Finally, we show that the proposed method can exchange more information than previous methods even though the media session re-establishment time is similar to legacy systems in terms of performance analysis. With the proposed method, the heterogeneous services can collect a variety of information about the telepresence service and use it according to user preference. In this way it provides rich multimedia streaming services for many areas.
A Network Coding Based Green Cognitive Radio Network
With the rapid increase of energy consumption and environmental problems, the need for green techniques is increasing. Network coding can provide a solution by reducing unnecessary data transmission and by estimating traffic patterns. In addition, it can amplify the synergy with the cognitive radio network (CR) since the CR has recognition and optimal decision functionalities. In this paper, we propose a network coding based green cognitive radio network. With the simulations, we show that the proposed scheme is up to 25% better than the previous work.
Image Based Human Action Recognition System to Support the Blind
ByoungChul Ko, Mincheol Hwang, Jae-Yeal Nam
In this paper we develop a novel human action recognition system based on communication between an ear-mounted Bluetooth camera and an action recognition server to aid scene recognition for the blind. First, if the blind capture an image of a specific location using the ear-mounted camera, the captured image is transmitted to the recognition server using a smartphone that is synchronized with the camera. The recognition server sequentially performs human detection, object detection and action recognition by analyzing human poses . The recognized action information is retransmitted to the smartphone and the user can hear the action information through the text-to-speech (TTS). Experimental results using the proposed system showed a 60.7% action recognition performance on the test data captured in indoor and outdoor environments.
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