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)

[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. 14, No.5, 2018

[EDITORIAL] Advanced Data Processing, Optimization & Software Engineering
Young-Sik Jeong and Jong Hyuk Park
Page: 1063~1067, Vol. 14, No.5, 2018
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The Three-Dimensional Partial Differential Equation with Constant Coefficients of Time-Delay of Alternating Direction Implicit Format
QianQian Chu and Yuanfeng Jin
Page: 1068~1074, Vol. 14, No.5, 2018
Keywords: Alternating Direction Implicit Format, Stability, Time-Delay, Partial Differential Equation, Three-Dimensional
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In this paper, we consider the delay partial differential equation of three dimensions with constant coefficients. We established the alternating direction difference scheme by the standard finite difference method, gave the order of convergence of the format and the expression of the difference scheme truncation errors.

Cross-Validation Probabilistic Neural Network Based Face Identification
Abdelhadi Lotfi and Abdelkader Benyettou
Page: 1075~1086, Vol. 14, No.5, 2018
Keywords: Biometrics, Classification, Cross-Validation, Face Identification, Optimization, Probabilistic Neural Networks
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In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer’s size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

GOPES: Group Order-Preserving Encryption Scheme Supporting Query Processing over Encrypted Data
Hyunjo Lee, Youngho Song and Jae-Woo Chang
Page: 1087~1101, Vol. 14, No.5, 2018
Keywords: Cloud Computing, Data Encryption, Query Processing over Encrypted Data
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As cloud computing has become a widespread technology, malicious attackers can obtain the private information of users that has leaked from the service provider in the outsourced databases. To resolve the problem, it is necessary to encrypt the database prior to outsourcing it to the service provider. However, the most existing data encryption schemes cannot process a query without decrypting the encrypted databases. Moreover, because the amount of the data is large, it takes too much time to decrypt all the data. For this, Programmable Order-Preserving Secure Index Scheme (POPIS) was proposed to hide the original data while performing query processing without decryption. However, POPIS is weak to both order matching attacks and data count attacks. To overcome the limitations, we propose a group order-preserving data encryption scheme (GOPES) that can support efficient query processing over the encrypted data. Since GOPES can preserve the order of each data group by generating the signatures of the encrypted data, it can provide a high degree of data privacy protection. Finally, it is shown that GOPES is better than the existing POPIS, with respect to both order matching attacks and data count attacks.

Designing a Vibrotactile Reading System for Mobile Phones
Shaowei Chu and Keying Zhu
Page: 1102~1113, Vol. 14, No.5, 2018
Keywords: Blind Use, Mobile Accessibility, Tactile Reading, User Study, Vibrotactile Interface
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Vibrotactile feedback is widely used in designing non-visual interactions on mobile phones, such as message notification, non-visual reading, and blind use. In this work, novel vibrotactile codes are presented to implement a non-visual text reading system for mobile phones. The 26 letters of the English alphabet are formed in an index table with four rows and seven columns, and each letter is mapped using the codes of vibrations. Two kinds of vibrotactile codes are designed with the actuator’s on and off states and with specific lengths (short and long) assigned to each state. To improve the efficiency of tactile perception and user satisfaction, three user experiments are conducted. The first experiment explores the maximum number of continuous vibrations and minimum vibration time of the actuator’s on and off states that the human can perceive. The second experiment determines the minimum interval between continuous vibrations. The vibrotactile reading system is designed and evaluated in the third experiment according to the results of the two preceding experiments. Results show that the character reading accuracy reaches 91.7% and the character reading speed is approximately 617.8 ms. Our method has better reading efficiency and is easier to learn than the traditional Braille coding method.

A Multi-Level Integrator with Programming Based Boosting for Person Authentication Using Different Biometrics
Sumana Kundu and Goutam Sarker
Page: 1114~1135, Vol. 14, No.5, 2018
Keywords: Accuracy, Back Propagation Learning, Biometrics, HBC, F-score, Malsburg Learning, Mega-Super-Classifier, MOCA, Multiple Classification System, OCA, Person Identification, Precision, Recall, RBFN, SOM, Super- Classifier
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A multiple classification system based on a new boosting technique has been approached utilizing different biometric traits, that is, color face, iris and eye along with fingerprints of right and left hands, handwriting, palm-print, gait (silhouettes) and wrist-vein for person authentication. The images of different biometric traits were taken from different standard databases such as FEI, UTIRIS, CASIA, IAM and CIE. This system is comprised of three different super-classifiers to individually perform person identification. The individual classifiers corresponding to each super-classifier in their turn identify different biometric features and their conclusions are integrated together in their respective super-classifiers. The decisions from individual superclassifiers are integrated together through a mega-super-classifier to perform the final conclusion using programming based boosting. The mega-super-classifier system using different super-classifiers in a compact form is more reliable than single classifier or even single super-classifier system. The system has been evaluated with accuracy, precision, recall and F-score metrics through holdout method and confusion matrix for each of the single classifiers, super-classifiers and finally the mega-super-classifier. The different performance evaluations are appreciable. Also the learning and the recognition time is fairly reasonable. Thereby making the system is efficient and effective.

Power Cable Ampacity and Influential Factors Analysis under Operation
Qiang Tong, Jianping Qi, Yanling Wang, Likai Liang, Xiangxing Meng and Qiang Zhang
Page: 1136~1149, Vol. 14, No.5, 2018
Keywords: Conductor Temperature, Influential Factors, Power Cable, Static Thermal Rating, Transient Temperature
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With the increasing of urban electricity demand, making the most use of the power cable carrying capacity has become an important task in power grid system. Contrary to the rated ampacity obtained under extremely conservative conditions, this paper presents the various steady value of cable ampacity by using the changing surrounding parameters under operation, which is based on cable ampacity calculation equation under the IEC-60287 standard. To some degree, the cable ampacity analysis of actual surroundings improves the transmission capacity of cables. This paper reveals the factors that influence cable ampacity such as insulating layer thickness, allowable long-term conductor temperature, the ambient temperature, soil thermal resistance coefficient, and so on, then gives the class of the influence of these parameters on the ampacity, which plays a great role in accurately calculating the real-time ampacity and improving the utilization rate of cable in the complex external environment condition. Furthermore, the transient thermal rating of the cable is analyzed in this paper, and temperature variation of the conductor under different overload conditions is discussed, which provides effective information for the operation and control of the system.

A Physical Storage Design Method for Access Structures of Image Information Systems
Jung-A Lee and Jong-Hak Lee
Page: 1150~1166, Vol. 14, No.5, 2018
Keywords: Image Access Structure, Image Retrieval Query, Multidimensional File Organizations, Physical Storage Design
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This paper presents a physical storage design method for image access structures using transformation techniques of multidimensional file organizations in image information systems. Physical storage design is the process of determining the access structures to provide optimal query processing performance for a given set of queries. So far, there has been no such attempt in the image information system. We first show that the number of pages to be accessed decreases as the shape of the given retrieval query region and that of the data page region become similar in the transformed domain space. Using these properties, we propose a method for finding an optimal image access structure by controlling the shapes of the page regions. For the performance evaluation, we have performed many experiments with a multidimensional file organization using transformation techniques. The results indicate that our proposed method is at least one to maximum five times faster than the conventional method according to the query pattern within the scope of the experiments. The result confirms that the proposed physical storage design method is useful in a practical way.

A Clustering Approach for Feature Selection in Microarray Data Classification Using Random Forest
Husna Aydadenta and Adiwijaya
Page: 1167~1175, Vol. 14, No.5, 2018
Keywords: Classification, Clustering, Dimensional Reduction, Microarray, Random Forest
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Microarray data plays an essential role in diagnosing and detecting cancer. Microarray analysis allows the examination of levels of gene expression in specific cell samples, where thousands of genes can be analyzed simultaneously. However, microarray data have very little sample data and high data dimensionality. Therefore, to classify microarray data, a dimensional reduction process is required. Dimensional reduction can eliminate redundancy of data; thus, features used in classification are features that only have a high correlation with their class. There are two types of dimensional reduction, namely feature selection and feature extraction. In this paper, we used k-means algorithm as the clustering approach for feature selection. The proposed approach can be used to categorize features that have the same characteristics in one cluster, so that redundancy in microarray data is removed. The result of clustering is ranked using the Relief algorithm such that the best scoring element for each cluster is obtained. All best elements of each cluster are selected and used as features in the classification process. Next, the Random Forest algorithm is used. Based on the simulation, the accuracy of the proposed approach for each dataset, namely Colon, Lung Cancer, and Prostate Tumor, achieved 85.87%, 98.9%, and 89% accuracy, respectively. The accuracy of the proposed approach is therefore higher than the approach using Random Forest without clustering.

A Hybrid Proposed Framework for Object Detection and Classification
Muhammad Aamir, Yi-Fei Pu, Ziaur Rahman, Waheed Ahmed Abro, Hamad Naeem, Farhan Ullah and Aymen Mudheher Badr
Page: 1176~1194, Vol. 14, No.5, 2018
Keywords: Image Proposals, Feature Extraction, Object Classification, Object Detection, Segmentation
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The object classification using the images’ contents is a big challenge in computer vision. The superpixels’ information can be used to detect and classify objects in an image based on locations. In this paper, we proposed a methodology to detect and classify the image's pixels' locations using enhanced bag of words (BOW). It calculates the initial positions of each segment of an image using superpixels and then ranks it according to the region score. Further, this information is used to extract local and global features using a hybrid approach of Scale Invariant Feature Transform (SIFT) and GIST, respectively. To enhance the classification accuracy, the feature fusion technique is applied to combine local and global features vectors through weight parameter. The support vector machine classifier is a supervised algorithm is used for classification in order to analyze the proposed methodology. The Pascal Visual Object Classes Challenge 2007 (VOC2007) dataset is used in the experiment to test the results. The proposed approach gave the results in high-quality class for independent objects’ locations with a mean average best overlap (MABO) of 0.833 at 1,500 locations resulting in a better detection rate. The results are compared with previous approaches and it is proved that it gave the better classification results for the non-rigid classes.

Semantic Image Search: Case Study for Western Region Tourism in Thailand
Chantana Chantrapornchai, Netnapa Bunlaw and Chidchanok Choksuchat
Page: 1195~1214, Vol. 14, No.5, 2018
Keywords: Image Search, Ontology, Semantic Web, Tourism, Western Thailand
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Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

Multi-Attribute Decision-Making Method Applying A Novel Correlation Coefficient of Interval-Valued Neutrosophic Hesitant Fuzzy Sets
Chunfang Liu
Page: 1215~1224, Vol. 14, No.5, 2018
Keywords: Correlation Coefficient, Decision-Making, Interval-Valued Neutrosophic Hesitant Fuzzy Set
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Interval-valued neutrosophic hesitant fuzzy set (IVNHFS) is an extension of neutrosophic set (NS) and hesitant fuzzy set (HFS), each element of which has truth membership hesitant function, indeterminacy membership hesitant function and falsity membership hesitant function and the values of these functions lie in several possible closed intervals in the real unit interval [0,1]. In contrast with NS and HFS, IVNHFS can be more flexibly used to deal with uncertain, incomplete, indeterminate, inconsistent and hesitant information. In this study, I propose the novel correlation coefficient of IVNHFSs and my paper discusses its properties. Then, based on the novel correlation coefficient, I develop an approach to deal with multi-attribute decisionmaking problems within the framework of IVNHFS. In the end, a practical example is used to show that the approach is reasonable and effective in dealing with decision-making problems.

A Study on the Design of Humane Animal Care System and Java Implementation
Hui-Su Gong, Sunghyun Weon and Jun-Ho Huh
Page: 1225~1236, Vol. 14, No.5, 2018
Keywords: Animal Care, Artificial Intelligence, BPM, Design, Humane Animal Care, Intelligent Agent, Software Engineering
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Nowadays, the number of pets in the Republic of Korea (ROK) is continuously growing, and people’s perception of animals is changing. Accordingly, new systems and services for them are emerging. Despite such changes, there are still many serious problems such as animal cruelty, abandonment, and factory-type breeding places. In this study, we have conducted a research on the design of a humane animal care system and its implementation with Java. The methodology involved in the design will enable managing animals' safety and health by systematically categorizing and studying each health-related issue for protection. Moreover, with this methodology, animals can avert risks through periodic examinations, and the analyzed data will be useful in managing animals efficiently. Thus, this paper proposes a system that monitors whether the owners actually carry out such obligation. Authors expect this convenient, easily accessible system to lead to a more humane approach to the animals they own. The authors plan to establish an animal care network together with local animal associations for the active promotion of the system implemented in this study, in the hope that the network will be extended nationwide.

An Improved Harmony Search Algorithm and Its Application in Function Optimization
Zhongda Tian and Chao Zhang
Page: 1237~1253, Vol. 14, No.5, 2018
Keywords: Complex Functions, Harmony Search, Intelligent Algorithm, Optimization
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Harmony search algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and can solve different optimization problems. In order to further improve the performance of the algorithm, this paper proposes an improved harmony search algorithm. Key parameters including harmonic memory consideration (HMCR), pitch adjustment rate (PAR), and bandwidth (BW) are optimized as the number of iterations increases. Meanwhile, referring to the genetic algorithm, an improved method to generate a new crossover solutions rather than the traditional mechanism of improvisation. Four complex function optimization and pressure vessel optimization problems were simulated using the optimization algorithm of standard harmony search algorithm, improved harmony search algorithm and exploratory harmony search algorithm. The simulation results show that the algorithm improves the ability to find global search and evolutionary speed. Optimization effect simulation results are satisfactory.

A Dependency Graph-Based Keyphrase Extraction Method Using Anti-patterns
Khuyagbaatar Batsuren, Erdenebileg Batbaatar, Tsendsuren Munkhdalai, Meijing Li, Oyun-Erdene Namsrai and Keun Ho Ryu
Page: 1254~1271, Vol. 14, No.5, 2018
Keywords: Dependency Graph, Keyphrase Extraction
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Keyphrase extraction is one of fundamental natural language processing (NLP) tools to improve many textmining applications such as document summarization and clustering. In this paper, we propose to use two novel techniques on the top of the state-of-the-art keyphrase extraction methods. First is the anti-patterns that aim to recognize non-keyphrase candidates. The state-of-the-art methods often used the rich feature set to identify keyphrases while those rich feature set cover only some of all keyphrases because keyphrases share very few similar patterns and stylistic features while non-keyphrase candidates often share many similar patterns and stylistic features. Second one is to use the dependency graph instead of the word co-occurrence graph that could not connect two words that are syntactically related and placed far from each other in a sentence while the dependency graph can do so. In experiments, we have compared the performances with different settings of the graphs (co-occurrence and dependency), and with the existing method results. Finally, we discovered that the combination method of dependency graph and anti-patterns outperform the state-of-the-art performances.

An Embedded Multifunctional Media System for Mobile Devices in Terrestrial DTV Relaying
Jun Huang and Haibing Yin
Page: 1272~1285, Vol. 14, No.5, 2018
Keywords: DTV, Media Relaying, Media Server, Mobile Devices, Terrestrial Broadcasting
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The paper presents a novel embedded multifunctional media sever (EMMS) for mobile devices to receive various media programs. Being different from other contemporary system research, the paper mainly studies how to design a reception solution for terrestrial digital television (DTV) on mobile devices and how to enable mobile devices can receive DTV program, enjoy video-on-demand (VOD), achieve video surveillance and relay Internet video program via local Wi-Fi simultaneously. In the system design, we integrate broadcasting-terrestrial DTV tuner, streaming media re-transmission system, VOD disk, video camera and access interface to the Internet into EMMS, which can either receive terrestrial DTV radio signals and demodulate out digital transport stream (TS), or can read streaming media bit-stream from VOD disk, surveillance camera or access interface to the Internet. The experimental results show the proposed system is stable and quality-efficient. Comparing with the other systems, the proposed system has the least packet loss rate and response time.

An Internet of Things System Architecture for Aiding Firefighters in the Scene of Disaster
Hyesun Lee, Sang Gi Hong and Kang Bok Lee
Page: 1286~1292, Vol. 14, No.5, 2018
Keywords: Disaster and Safety, Internet of Things, Reference Architecture
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To support and protect firefighters in the scene of disaster, this research suggests an Internet of Things (IoT) system architecture that can be configurable and applicable to firefighting and rescue in various disaster situations. The proposed approach provides increased adaptability and reusability of systems compared to existing approaches. To validate the feasibility of the approach, a system of systems based on the architecture was developed and successfully tested for a specific firefighting and rescue scenario in a given test environment.

Research on the Multi-Focus Image Fusion Method Based on the Lifting Stationary Wavelet Transform
Kaiqun Hu and Xin Feng
Page: 1293~1300, Vol. 14, No.5, 2018
Keywords: Image Fusion, Lifting Stationary Wavelet Transform, Normalized Cut, Transform of NSCT
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For the disadvantages of multi-scale geometric analysis methods such as loss of definition and complex selection of rules in image fusion, an improved multi-focus image fusion method is proposed. First, the initial fused image is quickly obtained based on the lifting stationary wavelet transform, and a simple normalized cut is performed on the initial fused image to obtain different segmented regions. Then, the original image is subjected to NSCT transformation and the absolute value of the high frequency component coefficient in each segmented region is calculated. At last, the region with the largest absolute value is selected as the postfusion region, and the fused multi-focus image is obtained by traversing each segment region. Numerical experiments show that the proposed algorithm can not only simplify the selection of fusion rules, but also overcome loss of definition and has validity.

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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