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. 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.
[Dec. 29, 2017] We have selected the papers of 2017 JIPS survey paper awards. Please refer to here for details.
[Dec. 12, 2016] Call for papers about Special sections scheduled in 2017 are registered. Please refer to here for details.
[Aug. 1, 2016] Since August 2016, the JIPS has been indexed in "Emerging Sources Citation Index (ESCI)", a new Web of Science index managed by Thomson Reuters, launched in late 2015 for journals that have passed an initial evaluation for inclusion in SCI/SCIE/AHCI/SSCI indexes. Indexing in the ESCI will improve the visibility of the JIPS and provide a mark of quality. This achievement is good for all authors of the JIPS. For more information about ESCI, please see the ESCI fact sheet file.

Latest Publications

Journal of Information Processing Systems, Vol. 14, No.2, 2018

Enhanced Integrated Algorithm & Software Architecture
Jong Hyuk Park
Page: 281~285, Vol. 14, No.2, 2018
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The Journal of Information Processing Systems (JIPS) has such indices as ESCI, SCOPUS, EI COMPENDEX, DOI, DBLP, EBSCO, Google Scholar, and CrossRef, and has are four divisions: Computer systems and theory, Multimedia systems and graphics, Communication systems and security, and Information systems and applications. Published by the Korean Information Processing Society (KIPS), JIPS places special emphasis on hot research topics such as artificial intelligence, network, databases, and security.

Security and Privacy in Ubiquitous Sensor Networks
Alfredo J. Perez, Sherali Zeadally and Nafaa Jabeur
Page: 286~308, Vol. 14, No.2, 2018
Keywords: Human-Centric Sensing, Internet of Things, Opportunistic Sensing, Participatory Sensing, Privacy, Security, Ubiquitous Sensing
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The availability of powerful and sensor-enabled mobile and Internet-connected devices have enabled the advent of the ubiquitous sensor network (USN) paradigm. USN provides various types of solutions to the general public in multiple sectors, including environmental monitoring, entertainment, transportation, security, and healthcare. Here, we explore and compare the features of wireless sensor networks and USN. Based on our extensive study, we classify the security- and privacy-related challenges of USNs. We identify and discuss solutions available to address these challenges. Finally, we briefly discuss open challenges for designing more secure and privacy-preserving approaches in next-generation USNs.

Verifying Code toward Trustworthy Software
Hyong-Soon Kim and Eunyoung Lee
Page: 309~321, Vol. 14, No.2, 2018
Keywords: Certified Compiler, Formal Verification, Language Semantics, Program Verification
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In the conventional computing environment, users use only a small number of software systems intensively. So it had been enough to check and guarantee the functional correctness and safety of a small number of giant systems in order to protect the user systems and their information inside the systems from outside attacks. However, checking the correctness and safety of giant systems is not enough anymore, since users are using various software systems or web services provided by unskilled developers. To prove or guarantee the safety of software system, a lot of research has been conducted in diverse areas of computer science. We will discuss the on-going approaches for guaranteeing or verifying the safety of software systems in this paper. We also discuss the future research challenge which must be solved with better solutions in the near future.

Sustaining Low-Carbon Emission Development: An Energy Efficient Transportation Plan for CPEC
Asma Zubedi, Zeng Jianqiu, Qasim Ali Arain, Imran Memon, Sehrish Khan, Muhammad Saad Khan and Ying Zhang
Page: 322~345, Vol. 14, No.2, 2018
Keywords: Carbon Emission, Climate Change, CPEC, Green ICT, ITS
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Climate change has become a major challenge for sustainable development of human society. This study is an attempt to analyze existing literature to identify economic indicators that hamper the process of global warming. This paper includes case studies based on various countries to examine the nexus for environment and its relationship with Foreign Direct Investment, transportation, economic growth and energy consumption. Furthermore, the observations are analyzed from the perspective of China-Pakistan Economic Corridor (CPEC) and probable impact on carbon emission of Pakistan. A major portion of CPEC investment is allocated for transportation. However, it is evident that transportation sector is substantial emitter of carbon dioxide (CO2) gas. Unfortunately, there is no empirical work on the subject of CPEC and carbon emission for vehicular transportation. This paper infers that empirical results from various other countries are ambiguous and inconclusive. Moreover, the evidence for the pollution haven hypothesis and the halo effect hypothesis is limited in general and inapplicable for CPEC in particular. The major contribution of this study is the proposal of an energy efficient transportation model for reducing CO2 emission. In the end, the paper suggests strategies to climate researchers and policymakers for adaptation and mitigation of greenhouse gases (GHG).

Digital Forensics: Review of Issues in Scientific Validation of Digital Evidence
Humaira Arshad, Aman Bin Jantan and Oludare Isaac Abiodun
Page: 346~376, Vol. 14, No.2, 2018
Keywords: Criminal Investigation, Data, Digital Forensics, Electronic Evidence, Reliability, Validation, Verification
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Digital forensics is a vital part of almost every criminal investigation given the amount of information available and the opportunities offered by electronic data to investigate and evidence a crime. However, in criminal justice proceedings, these electronic pieces of evidence are often considered with the utmost suspicion and uncertainty, although, on occasions are justifiable. Presently, the use of scientifically unproven forensic techniques are highly criticized in legal proceedings. Nevertheless, the exceedingly distinct and dynamic characteristics of electronic data, in addition to the current legislation and privacy laws remain as challenging aspects for systematically attesting evidence in a court of law. This article presents a comprehensive study to examine the issues that are considered essential to discuss and resolve, for the proper acceptance of evidence based on scientific grounds. Moreover, the article explains the state of forensics in emerging sub-fields of digital technology such as, cloud computing, social media, and the Internet of Things (IoT), and reviewing the challenges which may complicate the process of systematic validation of electronic evidence. The study further explores various solutions previously proposed, by researchers and academics, regarding their appropriateness based on their experimental evaluation. Additionally, this article suggests open research areas, highlighting many of the issues and problems associated with the empirical evaluation of these solutions for immediate attention by researchers and practitioners. Notably, academics must react to these challenges with appropriate emphasis on methodical verification. Therefore, for this purpose, the issues in the experiential validation of practices currently available are reviewed in this study. The review also discusses the struggle involved in demonstrating the reliability and validity of these approaches with contemporary evaluation methods. Furthermore, the development of best practices, reliable tools and the formulation of formal testing methods for digital forensic techniques are highlighted which could be extremely useful and of immense value to improve the trustworthiness of electronic evidence in legal proceedings.

Dynamic Cloud Resource Reservation Model Based on Trust
Jiao-Hong Qiang, Ding-Wan Ning, Tian-Jun Feng and Li-Wei Ping
Page: 377~398, Vol. 14, No.2, 2018
Keywords: Cloud-Domain-Based Management Architecture, Decision of Candidate Resources, Dynamic Resource Reservation, Two-Way Trust Evaluation Mechanism
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Aiming at the problem of service reliability in resource reservation in cloud computing environments, a model of dynamic cloud resource reservation based on trust is proposed. A domain-specific cloud management architecture is designed in which resources are divided into different management domains according to the types of service for easier management. A dynamic resource reservation mechanism (DRRM) is used to test users’ reservation requests and reserve resources for users. According to user preference, several resources are chosen to be candidate resources by fuzzy cluster analysis. The fuzzy evaluation method and a two-way trust evaluation mechanism are adopted to improve the availability and credibility of the model. An analysis and simulation experiments show that this model can increase the flexibility of resource reservation and improve user satisfaction.

Routing Techniques for Data Aggregation in Sensor Networks
Jeong-Joon Kim
Page: 396~417, Vol. 14, No.2, 2018
Keywords: Itinerary, R-tree, Routing, Sensor Networks, Spatio-temporal Data
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GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.

Impact of Instance Selection on kNN-Based Text Categorization
Fatiha Barigou
Page: 418~434, Vol. 14, No.2, 2018
Keywords: Classification Accuracy, Classification Efficiency, Data Reduction, Instance Selection, k-Nearest Neighbors, Text Categorization
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With the increasing use of the Internet and electronic documents, automatic text categorization becomes imperative. Several machine learning algorithms have been proposed for text categorization. The k-nearest neighbor algorithm (kNN) is known to be one of the best state of the art classifiers when used for text categorization. However, kNN suffers from limitations such as high computation when classifying new instances. Instance selection techniques have emerged as highly competitive methods to improve kNN through data reduction. However previous works have evaluated those approaches only on structured datasets. In addition, their performance has not been examined over the text categorization domain where the dimensionality and size of the dataset is very high. Motivated by these observations, this paper investigates and analyzes the impact of instance selection on kNN-based text categorization in terms of various aspects such as classification accuracy, classification efficiency, and data reduction.

Fingerprint Identification Based on Hierarchical Triangulation
Meryam Elmouhtadi, Sanaa El fkihi and Driss Aboutajdine
Page: 435~447, Vol. 14, No.2, 2018
Keywords: Biometric, Fingerprint Identification, Delaunay Triangulation, Fingerprint Matching, Minutiae Extraction
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Fingerprint-based biometric identification is one of the most interesting automatic systems for identifying individuals. Owing to the poor sensing environment and poor quality of skin, biometrics remains a challenging problem. The main contribution of this paper is to propose a new approach to recognizing a person’s fingerprint using the fingerprint’s local characteristics. The proposed approach introduces the barycenter notion applied to triangles formed by the Delaunay triangulation once the extraction of minutiae is achieved. This ensures the exact location of similar triangles generated by the Delaunay triangulation in the recognition process. The results of an experiment conducted on a challenging public database (i.e., FVC2004) show significant improvement with regard to fingerprint identification compared to simple Delaunay triangulation, and the obtained results are very encouraging.

On Modification and Application of the Artificial Bee Colony Algorithm
Zhanxiang Ye, Min Zhu and Jin Wang
Page: 448~454, Vol. 14, No.2, 2018
Keywords: Artificial Bee Colony, Bees’ Number Reallocation, Search Equation
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Artificial bee colony (ABC) algorithm has attracted significant interests recently for solving the multivariate optimization problem. However, it still faces insufficiency of slow convergence speed and poor local search ability. Therefore, in this paper, a modified ABC algorithm with bees’ number reallocation and new search equation is proposed to tackle this drawback. In particular, to enhance solution accuracy, more bees in the population are assigned to execute local searches around food sources. Moreover, elite vectors are adopted to guide the bees, with which the algorithm could converge to the potential global optimal position rapidly. A series of classical benchmark functions for frequency-modulated sound waves are adopted to validate the performance of the modified ABC algorithm. Experimental results are provided to show the significant performance improvement of our proposed algorithm over the traditional version.

Formulating Analytical Solution of Network ODE Systems Based on Input Excitations
Susmit Bagchi
Page: 455~468, Vol. 14, No.2, 2018
Keywords: Computer Networks, Convergent Functions, Dynamic Networks, Ordinary Differential Equations
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The concepts of graph theory are applied to model and analyze dynamics of computer networks, biochemical networks and, semantics of social networks. The analysis of dynamics of complex networks is important in order to determine the stability and performance of networked systems. The analysis of non-stationary and nonlinear complex networks requires the applications of ordinary differential equations (ODE). However, the process of resolving input excitation to the dynamic non-stationary networks is difficult without involving external functions. This paper proposes an analytical formulation for generating solutions of nonlinear network ODE systems with functional decomposition. Furthermore, the input excitations are analytically resolved in linearized dynamic networks. The stability condition of dynamic networks is determined. The proposed analytical framework is generalized in nature and does not require any domain or range constraints.

GLIBP: Gradual Locality Integration of Binary Patterns for Scene Images Retrieval
Salah Bougueroua and Bachir Boucheham
Page: 469~486, Vol. 14, No.2, 2018
Keywords: CBIR, Elliptic-Region, Global Information, LBP, Local Information, Texture
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We propose an enhanced version of the local binary pattern (LBP) operator for texture extraction in images in the context of image retrieval. The novelty of our proposal is based on the observation that the LBP exploits only the lowest kind of local information through the global histogram. However, such global Histograms reflect only the statistical distribution of the various LBP codes in the image. The block based LBP, which uses local histograms of the LBP, was one of few tentative to catch higher level textural information. We believe that important local and useful information in between the two levels is just ignored by the two schemas. The newly developed method: gradual locality integration of binary patterns (GLIBP) is a novel attempt to catch as much local information as possible, in a gradual fashion. Indeed, GLIBP aggregates the texture features present in grayscale images extracted by LBP through a complex structure. The used framework is comprised of a multitude of ellipse-shaped regions that are arranged in circular-concentric forms of increasing size. The framework of ellipses is in fact derived from a simple parameterized generator. In addition, the elliptic forms allow targeting texture directionality, which is a very useful property in texture characterization. In addition, the general framework of ellipses allows for taking into account the spatial information (specifically rotation). The effectiveness of GLIBP was investigated on the Corel-1K (Wang) dataset. It was also compared to published works including the very effective DLEP. Results show significant higher or comparable performance of GLIBP with regard to the other methods, which qualifies it as a good tool for scene images retrieval.

Optimization of Train Working Plan based on Multiobjective Bi-level Programming Model
Xiaowei HAI and Chanchan ZHAO
Page: 487~498, Vol. 14, No.2, 2018
Keywords: Bi-Level Programming, Genetic Algorithm, Multiobjective, Train Working Plan
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The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.

Efficient Hybrid Transactional Memory Scheme using Near-optimal Retry Computation and Sophisticated Memory Management in Multi-core Environment
Yeon-Woo Jang, Moon-Hwan Kang and Jae-Woo Chang
Page: 499~509, Vol. 14, No.2, 2018
Keywords: Bloom Filter, Concurrency Control, Hybrid Transactional Memory, Multi-core in-Memory Databases
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Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multicore environment. In this paper, we propose an efficient hybrid transactional memory scheme using nearoptimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

Review on Self-embedding Fragile Watermarking for Image Authentication and Self-recovery
Chengyou Wang, Heng Zhang and Xiao Zhou
Page: 510~522, Vol. 14, No.2, 2018
Keywords: Image Authentication and Self-recovery, Least Significant Bit (LSB), Peak Signal-to-Noise Ratio (PSNR), Self-embedding Fragile Watermarking
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As the major source of information, digital images play an indispensable role in our lives. However, with the development of image processing techniques, people can optionally retouch or even forge an image by using image processing software. Therefore, the authenticity and integrity of digital images are facing severe challenge. To resolve this issue, the fragile watermarking schemes for image authentication have been proposed. According to different purposes, the fragile watermarking can be divided into two categories: fragile watermarking for tamper localization and fragile watermarking with recovery ability. The fragile watermarking for image tamper localization can only identify and locate the tampered regions, but it cannot further restore the modified regions. In some cases, image recovery for tampered regions is very essential. Generally, the fragile watermarking for image authentication and recovery includes three procedures: watermark generation and embedding, tamper localization, and image self-recovery. In this article, we make a review on self-embedding fragile watermarking methods. The basic model and the evaluation indexes of this watermarking scheme are presented in this paper. Some related works proposed in recent years and their advantages and disadvantages are described in detail to help the future research in this field. Based on the analysis, we give the future research prospects and suggestions in the end.

Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment
Sung-Hoon Lee, Jong-hyuk Roh, SooHyung Kim and Seung-Hun Jin
Page: 523~538, Vol. 14, No.2, 2018
Keywords: Feature Subset, Keystroke Dynamics, Smartphone Sensor
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Keystroke dynamics user authentication is a behavior-based authentication method which analyzes patterns in how a user enters passwords and PINs to authenticate the user. Even if a password or PIN is revealed to another user, it analyzes the input pattern to authenticate the user; hence, it can compensate for the drawbacks of knowledge-based (what you know) authentication. However, users' input patterns are not always fixed, and each user's touch method is different. Therefore, there are limitations to extracting the same features for all users to create a user's pattern and perform authentication. In this study, we perform experiments to examine the changes in user authentication performance when using feature vectors customized for each user versus using all features. User customized features show a mean improvement of over 6% in error equal rate, as compared to when all features are used.

An Effective Denoising Method for Images Contaminated with Mixed Noise Based on Adaptive Median Filtering and Wavelet Threshold Denoising
Lin Lin
Page: 539~551, Vol. 14, No.2, 2018
Keywords: Adaptive Median Filter (AMF), Gaussian Mixture Model (GMM), Image Denoising, Mixed Noise, Wavelet Threshold Denoising
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Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.

A Method of Coupling Expected Patch Log Likelihood and Guided Filtering for Image Denoising
Shunfeng Wang, Jiacen Xie, Yuhui Zheng, Jin Wang and Tao Jiang
Page: 552~562, Vol. 14, No.2, 2018
Keywords: Edge Preserving, Expected Patch Log Likelihood, Image De-noising, Guided Filtering
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With the advent of the information society, image restoration technology has aroused considerable interest. Guided image filtering is more effective in suppressing noise in homogeneous regions, but its edge-preserving property is poor. As such, the critical part of guided filtering lies in the selection of the guided image. The result of the Expected Patch Log Likelihood (EPLL) method maintains a good structure, but it is easy to produce the ladder effect in homogeneous areas. According to the complementarity of EPLL with guided filtering, we propose a method of coupling EPLL and guided filtering for image de-noising. The EPLL model is adopted to construct the guided image for the guided filtering, which can provide better structural information for the guided filtering. Meanwhile, with the secondary smoothing of guided image filtering in image homogenization areas, we can improve the noise suppression effect in those areas while reducing the ladder effect brought about by the EPLL. The experimental results show that it not only retains the excellent performance of EPLL, but also produces better visual effects and a higher peak signal-to-noise ratio by adopting the proposed method.

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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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