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)

[April 23, 2019] We announced The 2nd JIPS Survey Paper Awards. Please refer to here for details.
[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.

Latest Publications

Journal of Information Processing Systems, Vol. 15, No.3, 2019

Future Trends of Blockchain and Crypto Currency: Challenges, Opportunities, and Solutions
Yunsick Sung and Jong Hyuk Park
Page: 457~463, Vol. 15, No.3, 2019

Keywords: Blockchain and Crypto Currency, Cloud Computing, Sentiment Analysis, Internet of Things
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The blockchain and crypto currency has become one of the most essential components of a communication network in the recent years. Through communication networking, we browse the internet, make VoIP phone calls, have video conferences and check e-mails via computers. A lot of researches are being conducting to address the blockchain and crypto currency challenges in communication networking and provide corresponding solutions. In this paper, a diverse kind of novel research works in terms of mechanisms, techniques, architectures, and frameworks have been proposed to provide possible solutions against the existing challenges in the communication networking. Such novel research works involve thermal load capacity techniques, intelligent sensing mechanism, secure cloud computing system communication algorithm for wearable healthcare systems, sentiment analysis, optimized resources.

Study on Thermal Load Capacity of Transmission Line Based on IEEE Standard
Fan Song, Yanling Wang, Lei Zhao, Kun Qin, Likai Liang, Zhijun Yin and Weihua Tao
Page: 464~477, Vol. 15, No.3, 2019

Keywords: Dynamic Thermal Rating, Key Parameters, Thermal Equivalent Equation, Thermal Load Capacity, Transmission Line
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With the sustained and rapid development of new energy sources, the demand for electric energy is increasing day by day. However, China’s energy distribution is not balanced, and the construction of transmission lines is in a serious lag behind the improvement of generating capacity. So there is an urgent need to increase the utilization of transmission capacity. The transmission capacity is mainly limited by the maximum allowable operating temperature of conductor. At present, the evaluation of transmission capacity mostly adopts the static thermal rating (STR) method under severe environment. Dynamic thermal rating (DTR) technique can improve the utilization of transmission capacity to a certain extent. In this paper, the meteorological parameters affecting the conductor temperature are analyzed with the IEEE standard thermal equivalent equation of overhead transmission lines, and the real load capacity of 220 kV transmission line is calculated with 7-year actual meteorological data in Weihai. Finally, the thermal load capacity of DTR relative to STR under given confidence is analyzed. By identifying the key parameters that affect the thermal rating and analyzing the relevant environmental parameters that affect the conductor temperature, this paper provides a theoretical basis for the wind power grid integration and grid intelligence. The results show that the thermal load potential of transmission lines can be effectively excavated by DTR, which provides a theoretical basis for improving the absorptive capacity of power grid.

Health and Wellness Monitoring Using Intelligent Sensing Technique
Yao Meng, Sang-Hoon Yi and Hee-Cheol Kim
Page: 478~491, Vol. 15, No.3, 2019

Keywords: Accelerometer, Electrocardiogram, Healthcare, Persuasive Technology, Real-Time Monitoring
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This work develops a monitoring system for the population with health concerns. A belt integrated with an onbody circuit and sensors measures a wearer’s selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with realtime feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users’ physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.

A Fast Rough Mode Decision Algorithm for HEVC
Wei-Xin Yao, Dan Yang, Gui-Fu Lu and Jun Wang
Page: 492~499, Vol. 15, No.3, 2019

Keywords: HEVC, Intra Prediction, Rough Mode Decision, Video Coding
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HEVC is the high efficiency video coding standard, which provides better coding efficiency contrasted with the other video coding standard. But at the same time the computational complexity increases drastically. Thirtyfive kinds of intra-prediction modes are defined in HEVC, while 9 kinds of intra prediction modes are defined in H.264/AVC. This paper proposes a fast rough mode decision (RMD) algorithm which adopts the smoothness of the up-reference pixels and the left-reference pixels to decrease the computational complexity. The three step search method is implemented in RMD process. The experimental results compared with HM13.0 indicate that the proposed algorithm can save 39.7% of the encoding time, while Bjontegaard delta bitrate (BDBR) is increased slightly by 1.35% and Bjontegaard delta peak signal-to-noise ratio (BDPSNR) loss is negligible.

Sentiment Analysis Main Tasks and Applications: A Survey
Sara Tedmori and Arafat Awajan
Page: 500~519, Vol. 15, No.3, 2019

Keywords: Feature Selection, Opinion Mining, Sentiment Analysis, Sentiment Analysis Applications, Sentiment Classification, Sentiment Visualization, Social Media Monitoring
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The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

A System for Improving Data Leakage Detection based on Association Relationship between Data Leakage Patterns
Min-Ji Seo and Myung-Ho Kim
Page: 520~537, Vol. 15, No.3, 2019

Keywords: Apriori Algorithm, Associated Abnormal Behavior List, Comprehensive Leakage Detection Scenario, Convolutional Neural Network, Data Leakage Detection
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This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

A Secure Cloud Computing System by Using Encryption and Access Control Model
Ghassan Sabeeh Mahmood, Dong Jun Huang and Baidaa Abdulrahman Jaleel
Page: 538~549, Vol. 15, No.3, 2019

Keywords: Access Control, Cloud Storage, Encryption, Security
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Cloud computing is the concept of providing information technology services on the Internet, such as software, hardware, networking, and storage. These services can be accessed anywhere at any time on a pay-per-use basis. However, storing data on servers is a challenging aspect of cloud computing. This paper utilizes cryptography and access control to ensure the confidentiality, integrity, and proper control of access to sensitive data. We propose a model that can protect data in cloud computing. Our model is designed by using an enhanced RSA encryption algorithm and a combination of role-based access control model with extensible access control markup language (XACML) to facilitate security and allow data access. This paper proposes a model that uses cryptography concepts to store data in cloud computing and allows data access through the access control model with minimum time and cost for encryption and decryption.

Approaches for Improving Bloom Filter-Based Set Membership Query
HyunYong Lee and Byung-Tak Lee
Page: 550~569, Vol. 15, No.3, 2019

Keywords: Additional Filters, Bloom Filter, False Positive Probability, Hash Table, Processing Time
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We propose approaches for improving Bloom filter in terms of false positive probability and membership query speed. To reduce the false positive probability, we propose special type of additional Bloom filters that are used to handle false positives caused by the original Bloom filter. Implementing the proposed approach for a routing table lookup, we show that our approach reduces the routing table lookup time by up to 28% compared to the original Bloom filter by handling most false positives within the fast memory. We also introduce an approach for improving the membership query speed. Taking the hash table-like approach while storing only values, the proposed approach shows much faster membership query speed than the original Bloom filter (e.g., 34 times faster with 10 subsets). Even compared to a hash table, our approach reduces the routing table lookup time by up to 58%.

LTS Semantics Model of Event-B Synchronization Control Flow Design Patterns
Han Peng, Chenglie Du, Lei Rao and Zhouzhou Liu
Page: 570~592, Vol. 15, No.3, 2019

Keywords: Behavior Semantic, Design Pattern Instantiation, Event-B Design Patterns, Labeled Transition System
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The Event-B design pattern is an excellent way to quickly develop a formal model of the system. Researchers have proposed a number of Event-B design patterns, but they all lack formal behavior semantics. This makes the analysis, verification, and simulation of the behavior of the Event-B model very difficult, especially for the control-intensive systems. In this paper, we propose a novel method to transform the Event-B synchronous control flow design pattern into the labeled transition system (LTS) behavior model. Then we map the design pattern instantiation process of Event-B to the instantiation process of LTS model and get the LTS behavior semantic model of Event-B model of a multi-level complex control system. Finally, we verify the linear temporal logic behavior properties of the LTS model. The experimental results show that the analysis and simulation of system behavior become easier and the verification of the behavior properties of the system become convenient after the Event-B model is converted to the LTS model.

An Adaptive Transmission Power Control Algorithm for Wearable Healthcare Systems Based on Variations in the Body Conditions
Woosik Lee, Namgi Kim and Byoung-Dai Lee
Page: 593~603, Vol. 15, No.3, 2019

Keywords: Healthcare System, Transmission Power Control, Wireless Body Sensor Network
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In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor’s batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

Adaptive Cooperative Spectrum Sensing Based on SNR Estimation in Cognitive Radio Networks
Shuiping Ni, Huigang Chang and Yuping Xu
Page: 604~615, Vol. 15, No.3, 2019

Keywords: Adaptive Spectrum Sensing, Cognitive Radio, Detection Time, Fusion Center, SNR Estimation, Voting Rule
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Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

Movie Recommendation Algorithm Using Social Network Analysis to Alleviate Cold-Start Problem
Khamphaphone Xinchang, Phonexay Vilakone and Doo-Soon Park
Page: 616~631, Vol. 15, No.3, 2019

Keywords: Cold Start Problem, Collaborative Filtering (CF), Movie Recommendation System, Social Network Analysis
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With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

The Design of Remote Monitoring and Warning System for Dangerous Chemicals Based on CPS
Zhe Kan and Xiaolei Wang
Page: 632~644, Vol. 15, No.3, 2019

Keywords: Cloud Services, Cyber-Physical System (CPS), Dangerous Chemicals, Data Collector, Remote Monitoring and Warning
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The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber- Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

User Modeling Using User Preference and User Life Pattern Based on Personal Bio Data and SNS Data
Hyejin Song, Kihoon Lee and Nammee Moon
Page: 645~654, Vol. 15, No.3, 2019

Keywords: Bio Data, Data Tracking, Life Pattern, Machine Learning, Social Behavior Analysis, User Modeling
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The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

Supplier Evaluation in Green Supply Chain: An Adaptive Weight D-S Theory Model Based on Fuzzy-Rough-Sets-AHP Method
Lianhui Li, Guanying Xu and Hongguang Wang
Page: 655~669, Vol. 15, No.3, 2019

Keywords: Adaptive Weight, D-S Theory, Fuzzy-Rough-Sets-AHP, Green Supply Chain, Supplier Evaluation
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Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

Implementation of Low Complexity FFT, ADC and DAC Blocks of an OFDM Transmitter Receiver Using Verilog
Alok Joshi, Dewansh Aditya Gupta and Pravriti Jaipuriyar
Page: 670~681, Vol. 15, No.3, 2019

Keywords: ADC, DAC, DFT, FFT, OFDM, Verilog
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Orthogonal frequency division multiplexing (OFDM) is a system which is used to encode data using multiple carriers instead of the traditional single carrier system. This method improves the spectral efficiency (optimum use of bandwidth). It also lessens the effect of fading and intersymbol interference (ISI). In 1995, digital audio broadcast (DAB) adopted OFDM as the first standard using OFDM. Later in 1997, it was adopted for digital video broadcast (DVB). Currently, it has been adopted for WiMAX and LTE standards. In this project, a Verilog design is employed to implement an OFDM transmitter (DAC block) and receiver (FFT and ADC block). Generally, OFDM uses FFT and IFFT for modulation and demodulation. In this paper, 16-point FFT decimation-in-frequency (DIF) with the radix-2 algorithm and direct summation method have been analyzed. ADC and DAC in OFDM are used for conversion of the signal from analog to digital or vice-versa has also been analyzed. All the designs are simulated using Verilog on ModelSim simulator. The result generated from the FFT block after Verilog simulation has also been verified with MATLAB.

Classification of Imbalanced Data Based on MTS-CBPSO Method: A Case Study of Financial Distress Prediction
Yuping Gu, Longsheng Cheng and Zhipeng Chang
Page: 682~693, Vol. 15, No.3, 2019

Keywords: Chaotic Binary Particle Swarm Optimization (CBPSO), Financial Distress Prediction, Mahalanobis-Taguchi System (MTS), Variable Selection
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The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

Time Series Classification of Cryptocurrency Price Trend Based on a Recurrent LSTM Neural Network
Do-Hyung Kwon, Ju-Bong Kim, Ju-Sung Heo, Chan-Myung Kim and Youn-Hee Han
Page: 694~706, Vol. 15, No.3, 2019

Keywords: Classification, Gradient Boosting, Long Short-Term Memory, Time Series Analysis
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In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

Design of Recruitment Management Platform Using Digital Certificate on Blockchain
Won-Yong Jeong and Min Choi
Page: 707~716, Vol. 15, No.3, 2019

Keywords: Applicants Capability Verification, Blockchain, Digital Certificate, Recruitment Platform
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In this paper, we present a certificate management platform for performance assessment during recruitment using blockchain. Applicants are awarded certificates according to a predetermined level of progress based on their performances. All certificates are stored on a recruitment management platform that serves as an environment for storing and presenting all awarded certificates. The hashed information of all the certificates are stored in the blockchain, and once stored, the contents cannot be tampered with. Therefore, anyone can check the validity of the certificates using this blockchain. Our proposed platform will be useful for recruitment and application management, career management, and personal history maintenance.

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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With regard to ethical standards, the JIPS takes plagiarism very seriously and thoroughly checks all articles. The JIPS defines research ethics as securing objectivity and accuracy in the execution of research and the conclusion of results without any unintentional errors resulting from negligence or incorrect knowledge, etc. and without any intentional misconduct such as falsification, plagiarism, etc. When an author submits a paper to the JIPS online submission and peer-review system, he/she should also upload the separate file "author check list" which contains a statement that all his/her research has been performed in accordance with ethical standards.

Among the JIPS editorial board members, there are four associate manuscript editors who support the JIPS by dealing with any ethical problems associated with the publication process and give advice on how to handle cases of suspected research and publication misconduct. When the JIPS managing editor looks over submitted papers and checks that they are suitable for further processing, the managing editor also routes them to the CrossCheck service provided by iTenticate. Based on the results provided by the CrossCheck service, the JIPS associate manuscript editors inform the JIPS editor-in-chief of any plagiarism that is detected in a paper. Then, the JIPS editor-in-chief communicates such detection to the author(s) while rejecting the paper.


Since 2005, all papers published in the JIPS are subjected to a peer review and upon acceptance are immediately made permanently available free of charge for everyone worldwide to read and download from the journal’s homepage ( without any subscription fee or personal registration. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The KIPS waives paper processing charges for submissions from international authors as well as society members. This waiver policy supports and encourages the publication of quality papers, making the journal an international forum for the exchange of different ideas and experiences.

Contact Information

JIPS Secretary: Ms. Joo-yeon Lee
Phone: +82-2-2077-1414, Fax: +82-2-2077-1472