Journal of Information Processing Systems

The Journal of Information Processing Systems (JIPS) is the official international journal of the Korea Information Processing Society. As information processing systems are progressing at a rapid pace, the Korea Information Processing Society is committed to providing researchers and other professionals with the academic information and resources they need to keep abreast with ongoing developments. The JIPS aims to be a premier source that enables researchers and professionals all over the world to promote, share, and discuss all major research issues and developments in the field of information processing systems and other related fields.

ISSN: 1976-913X (Print), ISSN: 2092-805X (Online)

[Jan. 23, 2018] Call for papers about JIPS Future Topic Track - Special Section scheduled in 2019 are registered. Please refer to here for details.
[Nov. 16, 2018] JIPS committee has made a decision for the article processing charge (APC), thus the new policy applies to all published papers after January 1, 2019. For more information, click here.
[Nov. 06, 2018] Call for papers about JIPS Award scheduled in 2018 are registered. Please refer to here for details.
[Jan. 01, 2018] Since January 01, 2018, the JIPS has started to manage the three manuscript tracks; 1) Regular Track, 2) Fast Track, and 3) Future Topic Track. Please refer to the details on the author information page.

Latest Publications

Journal of Information Processing Systems, Vol. 15, No.1, 2019

Advanced Big Data Analysis, Artificial Intelligence & Communication Systems
Young-Sik Jeong and Jong Hyuk Park
Page: 1~6, Vol. 15, No.1, 2019

Keywords: Artificial Intelligence, Big Data, Communication System
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Recently, big data and artificial intelligence (AI) based on communication systems have become one of the hottest issues in the technology sector, and methods of analyzing big data using AI approaches are now considered essential. This paper presents diverse paradigms to subjects which deal with diverse research areas, such as image segmentation, fingerprint matching, human tracking techniques, malware distribution networks, methods of intrusion detection, digital image watermarking, wireless sensor networks, probabilistic neural networks, query processing of encrypted data, the semantic web, decision-making, software engineering, and so on.

An Improved Level Set Method to Image Segmentation Based on Saliency
Yan Wang and Xianfa Xu
Page: 7~21, Vol. 15, No.1, 2019

Keywords: Canny Operator, Edge Energy, Level Set Method, Local Renyi Entropy, Saliency Map
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In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

An Efficient Fingerprint Matching by Multiple Reference Points
Kittiya Khongkraphan
Page: 22~33, Vol. 15, No.1, 2019

Keywords: Fingerprint Matching, Matching Score, Multiple Reference Points, Non-linear Distortion
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This paper introduces an efficient fingerprint matching method based on multiple reference minutiae points. First, we attempt to effectively align two fingerprints by employing multiple reference minutiae points. However, the corresponding minutiae points between two fingerprints are ambiguous since a minutia of one fingerprint can be a match to any minutia of the other fingerprint. Therefore, we introduce a novel method based on linear classification concept to establish minutiae correspondences between two fingerprints. Each minutiae correspondence represents a possible alignment. For each possible alignment, a matching score is computed using minutiae and ridge orientation features and the maximum score is then selected to represent the similarity of the two fingerprints. The proposed method is evaluated using fingerprint databases, FVC2002 and FVC2004. In addition, we compare our approach with two existing methods and find that our approach outperforms them in term of matching accuracy, especially in the case of non-linear distorted fingerprints. Furthermore, the experiments show that our method provides additional advantages in low quality fingerprint images such as inaccurate position, missing minutiae, and spurious extracted minutiae.

Foreign Detection based on Wavelet Transform Algorithm with Image Analysis Mechanism in The Inner Wall of The Tube
Jinlong Zhu, Fanhua Yu, Mingyu Sun, Dong Zhao and Qingtian Geng
Page: 34~46, Vol. 15, No.1, 2019

Keywords: Foreign Substance Inspection, Monte Carlo, Wavelets Transform
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A method for detecting foreign substances in mould based on scatter grams was presented to protect moulds automatically during moulding production. This paper proposes a wavelet transform foreign detection method based on Monte Carlo analysis mechanism to identify foreign objects in the tube. We use the Monte Carlo method to evaluate the image, and obtain the width of the confidence interval by the deviation statistical gray histogram to divide the image type. In order to stabilize the performance of the algorithm, the high-frequency image and the low-frequency image are respectively drawn. By analyzing the position distribution of the pixel gray in the two images, the suspected foreign object region is obtained. The experiments demonstrate the effectiveness of our approach by evaluating the labeled data.

A Study on an Automatic Multi-Focus System for Cell Observation
Jaeyoung Park and Sangjoon Lee
Page: 47~54, Vol. 15, No.1, 2019

Keywords: Automatic Multi-Focus, Cell Observation, Cubic Spline Interpolation, Peak Detection
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This study is concerned with the mechanism and structure of an optical microscope and an automatic multifocus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of 0.1 ?m was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

HRSF: Single Disk Failure Recovery for Liberation Code Based Storage Systems
Jun Li and Mengshu Hou
Page: 55~66, Vol. 15, No.1, 2019

Keywords: Erasure Codes, Disk Failure, Recovery Scheme, Reliability, Storage System
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Storage system often applies erasure codes to protect against disk failure and ensure system reliability and availability. Liberation code that is a type of coding scheme has been widely used in many storage systems because its encoding and modifying operations are efficient. However, it cannot effectively achieve fast recovery from single disk failure in storage systems, and has great influence on recovery performance as well as response time of client requests. To solve this problem, in this paper, we present HRSF, a Hybrid Recovery method for solving Single disk Failure. We present the optimal algorithm to accelerate failure recovery process. Theoretical analysis proves that our scheme consumes approximately 25% less amount of data read than the conventional method. In the evaluation, we perform extensive experiments by setting different number of disks and chunk sizes. The results show that HRSF outperforms conventional method in terms of the amount of data read and failure recovery time.

Hierarchical Graph based Segmentation and Consensus based Human Tracking Technique
Sunitha Madasi Ramachandra, Haradagere Siddaramaiah Jayanna and Ramegowda
Page: 67~90, Vol. 15, No.1, 2019

Keywords: Consensus Based Framework, Hierarchical Graph Based Segmentation, SIFT Keypoint Descriptor
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Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a stateof- the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

Feature Extraction based on DBN-SVM for Tone Recognition
Hao Chao, Cheng Song, Bao-yun Lu and Yong-li Liu
Page: 91~99, Vol. 15, No.1, 2019

Keywords: Deep Belief Networks, Deep Learning, Feature Fusion, Support Vector Machine, Tone Feature Extraction
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An innovative tone modeling framework based on deep neural networks in tone recognition was proposed in this paper. In the framework, both the prosodic features and the articulatory features were firstly extracted as the raw input data. Then, a 5-layer-deep deep belief network was presented to obtain high-level tone features. Finally, support vector machine was trained to recognize tones. The 863-data corpus had been applied in experiments, and the results show that the proposed method helped improve the recognition accuracy significantly for all tone patterns. Meanwhile, the average tone recognition rate reached 83.03%, which is 8.61% higher than that of the original method.

Automated Link Tracing for Classification of Malicious Websites in Malware Distribution Networks
Sang-Yong Choi, Chang Gyoon Lim and Yong-Min Kim
Page: 100~115, Vol. 15, No.1, 2019

Keywords: Auto Link Tracer, Drive-by Download, Malicious Website, MDN, Real Browser and Forward Proxy
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Malicious code distribution on the Internet is one of the most critical Internet-based threats and distribution technology has evolved to bypass detection systems. As a new defense against the detection bypass technology of malicious attackers, this study proposes the automated tracing of malicious websites in a malware distribution network (MDN). The proposed technology extracts automated links and classifies websites into malicious and normal websites based on link structure. Even if attackers use a new distribution technology, website classification is possible as long as the connections are established through automated links. The use of a real web-browser and proxy server enables an adequate response to attackers’ perception of analysis environments and evasion technology and prevents analysis environments from being infected by malicious code. The validity and accuracy of the proposed method for classification are verified using 20,000 links, 10,000 each from normal and malicious websites.

An Improved PSO Algorithm for the Classification of Multiple Power Quality Disturbances
Liquan Zhao and Yan Long
Page: 116~126, Vol. 15, No.1, 2019

Keywords: Classification Accuracy, Classification of Power Quality Disturbance, Particle Swarm Optimization, Support Vector Machine
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In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

A Simple and Effective Combination of User-Based and Item-Based Recommendation Methods
Se-Chang Oh and Min Choi
Page: 127~136, Vol. 15, No.1, 2019

Keywords: Collaborative Filtering, Electronic Commerce, Recommender System, Sparsity
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User-based and item-based approaches have been developed as the solutions of the movie recommendation problem. However, the user-based approach is faced with the problem of sparsity, and the item-based approach is faced with the problem of not reflecting users’ preferences. In order to solve these problems, there is a research on the combination of the two methods using the concept of similarity. In reality, it is not free from the problem of sparsity, since it has a lot of parameters to be calculated. In this study, we propose a combining method that simplifies the combination equation of prior study. This method is relatively free from the problem of sparsity, since it has less parameters to be calculated. Thus, it can get more accurate results by reflecting the users rating to calculate the parameters. It is very fast to predict new movie ratings as well. In experiments for the proposed method, the initial error is large, but the performance gets quickly stabilized after. In addition, it showed about 6% lower average error rate than the existing method using similarity.

An Intrusion Detection Method Based on Changes of Antibody Concentration in Immune Response
Ruirui Zhang and Xin Xiao
Page: 137~150, Vol. 15, No.1, 2019

Keywords: Antibody Concentration, Artificial Immune, Cloud Model, Evolutionary Algorithms, Intrusion Detection
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Although the research of immune-based anomaly detection technology has made some progress, there are still some defects which have not been solved, such as the loophole problem which leads to low detection rate and high false alarm rate, the exponential relationship between training cost of mature detectors and size of selfantigens. This paper proposed an intrusion detection method based on changes of antibody concentration in immune response to improve and solve existing problems of immune based anomaly detection technology. The method introduces blood relative and blood family to classify antibodies and antigens and simulate correlations between antibodies and antigens. Then, the method establishes dynamic evolution models of antigens and antibodies in intrusion detection. In addition, the method determines concentration changes of antibodies in the immune system drawing the experience of cloud model, and divides the risk levels to guide immune responses. Experimental results show that the method has better detection performance and adaptability than traditional methods.

MBS-LVM: A High-Performance Logical Volume Manager for Memory Bus-connected Storages over NUMA Servers
Yongseob Lee and Sungyong Park
Page: 151~158, Vol. 15, No.1, 2019

Keywords: Logical Volume Manager, Memory Bus Connected Storage, Non-volatile Memory, NUMA, NVDIMM
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With the recent advances of memory technologies, high-performance non-volatile memories such as nonvolatile dual in-line memory module (NVDIMM) have begun to be used as an addition or an alternative to server-side storages. When these memory bus-connected storages (MBSs) are installed over non-uniform memory access (NUMA) servers, the distance between NUMA nodes and MBSs is one of the crucial factors that influence file processing performance, because the access latency of a NUMA system varies depending on its distance from the NUMA nodes. This paper presents the design and implementation of a high-performance logical volume manager for MBSs, called MBS-LVM, when multiple MBSs are scattered over a NUMA server. The MBS-LVM consolidates the address space of each MBS into a single global address space and dynamically utilizes storage spaces such that each thread can access an MBS with the lowest latency possible. We implemented the MBS-LVM in the Linux kernel and evaluated its performance by porting it over the tmpfs, a memory-based file system widely used in Linux. The results of the benchmarking show that the write performance of the tmpfs using MBS-LVM has been improved by up to twenty times against the original tmpfs over a NUMA server with four nodes.

Forest fire detection and identification using image processing and SVM
Mubarak Adam Ishag Mahmoud and Honge Ren
Page: 159~168, Vol. 15, No.1, 2019

Keywords: Background Subtraction, CIE L?a?b? Color Space, Forest Fire, SVM, Wavelet
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Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE L?a?b? color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.

Wavelet-based Digital Image Watermarking by using Lorenz Chaotic Signal Localization
Jantana Panyavaraporn and Paramate Horkaew
Page: 169~180, Vol. 15, No.1, 2019

Keywords: Binary Image, Chaotic Signal, QR Code, Watermarking, Wavelet Analysis
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Transmitting visual information over a broadcasting network is not only prone to a copyright violation but also is a forgery. Authenticating such information and protecting its authorship rights call for more advanced data encoding. To this end, electronic watermarking is often adopted to embed inscriptive signature in imaging data. Most existing watermarking methods while focusing on robustness against degradation remain lacking of measurement against security loophole in which the encrypting scheme once discovered may be recreated by an unauthorized party. This could reveal the underlying signature which may potentially be replaced or forged. This paper therefore proposes a novel digital watermarking scheme in temporal-frequency domain. Unlike other typical wavelet based watermarking, the proposed scheme employed the Lorenz chaotic map to specify embedding positions. Effectively making this is not only a formidable method to decrypt but also a stronger will against deterministic attacks. Simulation report herein highlights its strength to withstand spatial and frequent adulterations, e.g., lossy compression, filtering, zooming and noise.

A Study on the Development and Effect of Smart Manufacturing System in PCB Line
Hyun Sik Sim
Page: 181~188, Vol. 15, No.1, 2019

Keywords: Effectiveness Evaluation, Key Function Extraction, Manufacturing Execution System, Smart Factory, Smart Manufacturing System, 4th Industrial Revolution
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A production system is a management system that supports all activities to perform production operations at the manufacturing site. From the point-of-view of a smart factory, smart manufacturing systems redesigned the concept of onsite production systems to fit the entire system and its necessary functional composition. In this study, we select the key functions needed to build a smart factory for a PCB line and propose a new six-step model for the deployment of a smart manufacturing system by integrating essential functions. The smart manufacturing system newly classified the production and operation tasks of PCB manufacturing and selected necessary functions through requirement analysis and benchmarking of advanced companies. The selected production operation tasks are mapped to the functions of the system and configured into seven modules, and the optimal deployment model is presented to allow flexible responses to the characteristics of the tasks. These methodologies are first presented in this study, and the proposed model was applied to the PCB line to confirm that they had significant changes in the work method, qualitative effects, and quantitative effects. Typically, lead time and WIP have reduced by about 50%.

Simulation study on measuring pulverized coal concentration in power plant boiler
Lijun Chen, Yang Wang and Cheng Su
Page: 189~202, Vol. 15, No.1, 2019

Keywords: Circular Waveguide, Concentration of Pulverized Coal, Firing Frequency, HFSS
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During thermal power coal-fired boiler operation, it is very important to detect the pulverized coal concentration in the air pipeline for the boiler combustion stability and economic security. Because the current measurement methods used by power plants are often involved with large measurement errors and unable to monitor the pulverized coal concentration in real-time, a new method is needed. In this paper, a new method based on microwave circular waveguide is presented. High Frequency Electromagnetic Simulation (HFSS) software was used to construct a simulation model for measuring pulverized coal concentration in power plant pipeline. Theoretical analysis and simulation experiments were done to find the effective microwave emission frequency, installation angle, the type of antenna probe, antenna installation distance and other important parameters. Finally, field experiment in Jilin Thermal Power Plant proved that with selected parameters, the measuring device accurately reflected the changes in the concentration of pulverized coal.

A Novel Technique to Detect Malicious Packet Dropping Attacks in Wireless Sensor Networks
J. Sebastian Terence and Geethanjali Purushothaman
Page: 203~216, Vol. 15, No.1, 2019

Keywords: Blackhole Attack, Grayhole Attack, Packet Dropping Attacks, Sinkhole Attack, Wireless Sensor Network
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The nature of wireless transmission has made wireless sensor networks defenseless against various attacks. This paper presents warning message counter method (WMC) to detect blackhole attack, grayhole attack and sinkhole attack in wireless sensor networks. The objective of these attackers are, to draw the nearby network traffic by false routing information and disrupt the network operation through dropping all the received packets (blackhole attack), selectively dropping the received packets (grayhole and sinkhole attack) and modifying the content of the packet (sinkhole attack). We have also attempted light weighted symmetric key cryptography to find data modification by the sinkhole node. Simulation results shows that, WMC detects sinkhole attack, blackhole attack and grayhole attack with less false positive 8% and less false negative 6%.

Digitalization of Seafarer's Book for Authentication and e-Navigation
Jun-Ho Huh and Kyungryong Seo
Page: 217~232, Vol. 15, No.1, 2019

Keywords: Android Application, Authentication, Digitalization, e-Navigation, Parallel Computing, Seafarer’s Book, Seaman Service Book, System Architecture
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Currently, the crew working on a ship is required to carry a seafarer's book in most countries around the world, including the Republic of Korea (ROK). Yet, many fishermen working in the international waters of the ROK do not abide by this rule as the procedure of obtaining it is rather inconvenient or they do not understand the necessity or the benefits of having it. Also, as the regulation of carrying the certificate has been strengthened, it is important for them to avoid making a criminal record unintentionally. This study discusses the digitalization of the seafarer’s book based on several security measures in addition to BLE Beacon-based positioning technology, which can be useful for the e-Navigation. Normally, seamen’s certificates are recorded by the captain, medical institution, or issuing authority and then kept in an onboard safe or a certificate cabinet. The material of the certificates is a cloth that can withstand salinity as the certificate could be contaminated by mold. In the past, the captains and their crews were uncooperative when the ROK’s maritime police tried to inspect several ships simultaneously because of the time and cost involved. Thus, a system with which the maritime police will be able to conveniently manage the crews is proposed.

Featured Papers

A Survey on Asynchronous Quorum-Based Power Saving Protocols in Multi-Hop Networks
Mehdi Imani, Majid Joudaki, Hamid R. Arabnia and Niloofar Mazhari
Pages: 1436~1458, Vol. 13, No.6, 2017
Keywords: Ad Hoc Networks, Asynchronous Sleep Scheduling Protocols, Power Saving Protocols, Quorum Based Systems
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Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries
Carlos Porcel, Alberto Ching-López, Juan Bernabé-Moreno, Alvaro Tejeda-Lorente and Enrique Herrera-Viedma
Pages: 653~667, Vol. 13, No.4, 2017
Keywords: Digital Libraries, Dissemination of Information, Fuzzy Linguistic Modeling, Recommender Systems
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Granular Bidirectional and Multidirectional Associative Memories: Towards a Collaborative Buildup of Granular Mappings
Witold Pedrycz
Pages: 435~447, Vol. 13, No.3, 2017
Keywords: Allocation of Information Granularity and Optimization, Bidirectional Associative Memory, Collaborative Clustering, Granular Computing, Multi-directional Associative Memory, Prototypes
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Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches
Ning Yu, Zeng Yu, Feng Gu, Tianrui Li, Xinmin Tian and Yi Pan
Pages: 204~214, Vol. 13, No.2, 2017
Keywords: Bioinformatics, Deep Learning, Deep Neural Networks, DNA Genome Analysis, Image Data Analysis, Machine Learning, lincRNA
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A Survey of Multimodal Systems and Techniques for Motor Learning
Ramin Tadayon, Troy McDaniel and Sethuraman Panchanathan
Pages: 8~25, Vol. 13, No.1, 2017
Keywords: Augmented Motor Learning and Training, Multimodal Systems and Feedback, Rehabilitative Technologies
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Survey on 3D Surface Reconstruction
Alireza Khatamian and Hamid R. Arabnia
Pages: 338~357, Vol. 12, No.3, 2016

Keywords: Explicit Surfaces, Implicit Surfaces, Point Cloud, Surface Reconstruction
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A Comprehensive Review of Emerging Computational Methods for Gene Identification
Ning Yu, Zeng Yu, Bing Li, Feng Gu and Yi Pan
Pages: 1~34, Vol. 12, No.1, 2016

Keywords: Cloud Computing, Comparative Methods, Deep Learning, Fourier Transform, Gene Identification, Gene Prediction, Hidden Markov Model, Machine Learning, Protein-Coding Region, Support Vector Machine
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On the Performance of Oracle Grid Engine Queuing System for Computing Intensive Applications
Vladi Kolici, Albert Herrero and Fatos Xhafa
Pages: 491~502, Vol. 10, No.4, 2014
Keywords: Benchmarking, Cloud Computing, Computing Intensive Applications, Genetic Algorithms, Grid Computing, Oracle Grid Engine, Scheduling, Simulation
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Training-Free Fuzzy Logic Based Human Activity Recognition
Eunju Kim and Sumi Helal
Pages: 335~354, Vol. 10, No.3, 2014
Keywords: Activity Semantic Knowledge, Fuzzy Logic, Human Activity Recognition, Multi-Layer Neural Network
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Janus - Multi Source Event Detection and Collection System for Effective Surveillance of Criminal Activity
Cyrus Shahabi, Seon Ho Kim, Luciano Nocera, Giorgos Constantinou, Ying Lu, Yinghao Cai, Gérard Medioni, Ramakant Nevatia and Farnoush Banaei-Kashani
Pages: 1~22, Vol. 10, No.1, 2014
Keywords: Multi-source, Multi-modal Event Detection, Law Enforcement, Criminal Activity, Surveillance, Security, Safety
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The Confinement Problem: 40 Years Later
Alex Crowell, Beng Heng Ng, Earlence Fernandes and Atul Prakash
Pages: 189~204, Vol. 9, No.2, 2013
Keywords: Confinement Problem, Covert Channels, Virtualization, Isolation, Taint Tracking
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An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators
B. John Oommen, Anis Yazidi and Ole-Christoffer Granmo
Pages: 191~212, Vol. 8, No.2, 2012
Keywords: Weak es timators, User's Profiling, Time Varying Preferences
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Indoor Link Quality Comparison of IEEE 802.11a Channels in a Multi-radio Mesh Network Testbed
Asitha U Bandaranayake, Vaibhav Pandit and Dharma P. Agrawal
Pages: 1~20, Vol. 8, No.1, 2012
Keywords: IEEE 802.11a, Indoor Test Bed, Link Quality, Wireless Mesh Networks
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A Survey of RFID Deployment and Security Issues
Amit Grover and Hal Berghel
Pages: 561~580, Vol. 7, No.4, 2011
Keywords: RFID, RFID Standards, RFID Protocols, RFID Security, EPC structure, RFID Applications, RFID Classification
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The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing
Witold Pedrycz
Pages: 397~412, Vol. 7, No.3, 2011
Keywords: Information Granularity, Principle of Justifiable Granularity, Knowledge Management, Optimal Granularity Allocation
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CASPER: Congestion Aware Selection of Path with Efficient Routing in Multimedia Networks
Mohammad S. Obaidat, Sanjay K. Dhurandher and Khushboo Diwakar
Pages: 241~260, Vol. 7, No.2, 2011
Keywords: Routing, Multimedia Networks, Congestion-aware Selection, MANET, CASPER, Performance Evaluation
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An Efficient Broadcast Technique for Vehicular Networks
Ai Hua Ho, Yao H. Ho, Kien A. Hua, Roy Villafane and Han-Chieh Chao
Pages: 221~240, Vol. 7, No.2, 2011
Keywords: V2V Communication Protocols, Vehicular Network, Ad Hoc Network, Broadcast, Broadcasting Storm, Routing
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Security Properties of Domain Extenders for Cryptographic Hash Functions
Elena Andreeva, Bart Mennink and Bart Preneel
Pages: 453~480, Vol. 6, No.4, 2010
Keywords: Hash Functions, Domain Extenders, Security Properties
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Hiding Secret Data in an Image Using Codeword Imitation
Zhi-Hui Wang, Chin-Chen Chang and Pei-Yu Tsai
Pages: 435~452, Vol. 6, No.4, 2010
Keywords: Data Hiding, Steganography, Vector Quantization
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DEESR: Dynamic Energy Efficient and Secure Routing Protocol for Wireless Sensor Networks in Urban Environments
Mohammad S. Obaidat, Sanjay K. Dhurandher, Deepank Gupta, Nidhi Gupta and Anupriya Asthana
Pages: 269~294, Vol. 6, No.3, 2010
Keywords: Sensor Network, Security, Energy Efficiency, Routing, Dynamic Trust Factor
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Challenges to Next Generation Services in IP Multimedia Subsystem
Kai-Di Chang, Chi-Yuan Chen, Jiann-Liang Chen and Han-Chieh Chao
Pages: 129~146, Vol. 6, No.2, 2010
Keywords: IP Multimedia Subsystems, Peer-to-Peer, Web Services, SCIM
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TOSS: Telecom Operations Support Systems for Broadband Services
Yuan-Kai Chen, Chang-Ping Hsu, Chung-Hua Hu, Rong-Syh Lin, Yi-Bing Lin, Jian-Zhi Lyu, Wudy Wu and Heychyi Young
Pages: 1~20, Vol. 6, No.1, 2010
Keywords: Operations Support System (OSS), New Generation Operations Systems and Software (NGOSS), enhanced Telecom Operations Map (eTOM), Internet Protocol Television (IPTV), IP-Virtual Private Network (IP-VPN)
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Providing Efficient Secured Mobile IPv6 by SAG and Robust Header Compression
Tin-Yu Wu, Han-Chieh Chao and Chi-Hsiang Lo
Pages: 117~130, Vol. 5, No.3, 2009
10.3745/JIPS.2009.5.3. 117
Keywords: SAG, RoHC, MIPv6, Handoff Latency, Early Binding Update
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A Survey of Face Recognition Techniques
Rabia Jafri and Hamid R Arabnia
Pages: 41~68, Vol. 5, No.2, 2009
Keywords: Face Recognition, Person Identification, Biometrics
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