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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Journal of Information Processing Systems
Journal Basic Information
Journal DOI :
Korea Information Processing Society
Editor in Chief :
Young-Sik Jeong / Mohammad S. Obaidat
Volume & Issues
Volume 10, Issue 4 - Dec 2014
Volume 10, Issue 3 - Sep 2014
Volume 10, Issue 2 - Jun 2014
Volume 10, Issue 1 - Mar 2014
Selecting the target year
Non-iterative Bit Loading Algorithm for OFDM in Independent and Correlated fading
Manry, John W. ; Nagaraj, Santosh ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 163~175
DOI : 10.3745/JIPS.03.0001
This paper will focus on improving the performance of orthogonal frequency division multiplexing (OFDM) in Rayleigh fading environments. The proposed technique will use a previously published method that has been shown to improve OFDM performance in independent fading, based on ordered sub-carrier selection. Then, a simple non-iterative method for finding the optimal bit-loading allocation was proposed. It was also based on ordered sub-carrier selection. We compared both of these algorithms to an optimal bit-loading solution to determine their effectiveness in a correlated fading environment. The correlated fading was simulated using the JTC channel models. Our intent was not to create an optimal solution, but to create a low complexity solution that can be used in a wireless environment in which the channel conditions change rapidly and that require a simple algorithm for fast bit loading.
Prioritized Multipath Video Forwarding in WSN
Asad Zaidi, Syed Muhammad ; Jung, Jieun ; Song, Byunghun ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 176~192
DOI : 10.3745/JIPS.03.0002
The realization of Wireless Multimedia Sensor Networks (WMSNs) has been fostered by the availability of low cost and low power CMOS devices. However, the transmission of bulk video data requires adequate bandwidth, which cannot be promised by single path communication on an intrinsically low resourced sensor network. Moreover, the distortion or artifacts in the video data and the adherence to delay threshold adds to the challenge. In this paper, we propose a two stage Quality of Service (QoS) guaranteeing scheme called Prioritized Multipath WMSN (PMW) for transmitting H.264 encoded video. Multipath selection based on QoS metrics is done in the first stage, while the second stage further prioritizes the paths for sending H.264 encoded video frames on the best available path. PMW uses two composite metrics that are comprised of hop-count, path energy, BER, and end-to-end delay. A color-coded assisted network maintenance and failure recovery scheme has also been proposed using (a) smart greedy mode, (b) walking back mode, and (c) path switchover. Moreover, feedback controlled adaptive video encoding can smartly tune the encoding parameters based on the perceived video quality. Computer simulation using OPNET validates that the proposed scheme significantly outperforms the conventional approaches on human eye perception and delay.
Duplication with Task Assignment in Mesh Distributed System
Sharma, Rashmi ; Nitin, Nitin ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 193~214
DOI : 10.3745/JIPS.01.0001
Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).
Optical Image Encryption and Decryption Considering Wireless Communication Channels
Cho, Myungjin ; Lee, In-Ho ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 215~222
DOI : 10.3745/JIPS.03.0003
In this paper, we discuss optical encryption and decryption considering wireless communication channels. In wireless communication systems, the wireless channel causes noise and fading effects of the transmitted information. Optical encryption technique such as double-random-phase encryption (DRPE) is used for encrypting transmitted data. When the encrypted data is transmitted, the information may be lost or distorted because there are a lot of factors such as channel noise, propagation fading, etc. Thus, using digital modulation and maximum likelihood (ML) detection, the noise and fading effects are mitigated, and the encrypted data is estimated well at the receiver. To the best of our knowledge, this is the first report that considers the wireless channel characteristics of the optical encryption technique.
The Design of the IIR Differintegrator and its Application in Edge Detection
Jain, Madhu ; Gupta, Maneesha ; Jain, N.K. ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 223~239
DOI : 10.3745/JIPS.02.0001
New IIR digital differintegrators (differentiator and integrator) with very minor absolute relative errors are presented in this paper. The digital integrator is designed by interpolating some of the existing integrators. The optimum value of the interpolation ratio is obtained through linear programming optimization. Subsequently, by modifying the transfer function of the proposed integrator appropriately, new digital differentiator is obtained. Simulation results demonstrate that the proposed differintegrator are a more accurate approximation of ideal ones, than the existing differintegrators. Furthermore, the proposed differentiator has been tested in an image processing application. Edges characterize boundaries and are, therefore, a problem of fundamental importance in image processing. For comparison purpose Prewitt, Sobel, Roberts, Canny, Laplacian of Gaussian (LOG), Zerocross operators were used and their results are displayed. The results of edge detection by some of the existing differentiators are also provided. The simulation results have shown the superiority of the proposed approach over existing ones.
Leveraged BMIS Model for Cloud Risk Control
Song, YouJin ; Pang, Yasheng ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 240~255
DOI : 10.3745/JIPS.03.0004
Cloud computing has increasingly been drawing attention these days. Each big company in IT hurries to get a chunk of meat that promises to be a whopping market in the future. At the same time, information is always associated with security and risk problems. Nowadays, the handling of these risks is no longer just a technology problem, with a good deal of literature focusing on risk or security management and framework in the information system. In this paper, we find the specific business meaning of the BMIS model and try to apply and leverage this model to cloud risk. Through a previous study, we select and determine the causal risk factors in cloud service, which are also known as CSFs (Critical Success Factors) in information management. Subsequently, we distribute all selected CSFs into the BMIS model by mapping with ten principles in cloud risk. Finally, by using the leverage points, we try to leverage the model factors and aim to make a resource-optimized, dynamic, general risk control business model for cloud service providers.
A High Quality Steganographic Method Using Morphing
Bagade, Anant M. ; Talbar, Sanjay N. ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 256~270
DOI : 10.3745/JIPS.03.0005
A new morphed steganographic algorithm is proposed in this paper. Image security is a challenging problem these days. Steganography is a method of hiding secret data in cover media. The Least Significant Bit is a standard Steganographic method that has some limitations. The limitations are less capacity to hide data, poor stego image quality, and imperceptibility. The proposed algorithm focuses on these limitations. The morphing concept is being used for image steganography to overcome these limitations. The PSNR and standard deviation are considered as a measure to improve stego image quality and morphed image selection, respectively. The stego keys are generated during the morphed steganographic embedding and extracting process. Stego keys are used to embed and extract the secret image. The experimental results, which are based on hiding capacity and PSNR, are presented in this paper. Our research contributes towards creating an improved steganographic method using image morphing. The experimental result indicates that the proposed algorithm achieves an increase in hiding capacity, stego image quality, and imperceptibility. The experimental results were compared with state of the art steganographic methods.
Content Modeling Based on Social Network Community Activity
Kim, Kyung-Rog ; Moon, Nammee ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 271~282
DOI : 10.3745/JIPS.04.0001
The advancement of knowledge society has enabled the social network community (SNC) to be perceived as another space for learning where individuals produce, share, and apply content in self-directed ways. The content generated within social networks provides information of value for the participants in real time. Thus, this study proposes the social network community activity-based content model (SoACo Model), which takes SNC-based activities and embodies them within learning objects. The SoACo Model consists of content objects, aggregation levels, and information models. Content objects are composed of relationship-building elements, including real-time, changeable activities such as making friends, and participation-activity elements such as "Liking" specific content. Aggregation levels apply one of three granularity levels considering the reusability of elements: activity assets, real-time, changeable learning objects, and content. The SoACo Model is meaningful because it transforms SNC-based activities into learning objects for learning and teaching activities and applies to learning management systems since they organize activities -- such as tweets from Twitter -- depending on the teacher's intention.
Skin Segmentation Using YUV and RGB Color Spaces
Al-Tairi, Zaher Hamid ; Rahmat, Rahmita Wirza ; Saripan, M. Iqbal ; Sulaiman, Puteri Suhaiza ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 283~299
DOI : 10.3745/JIPS.02.0002
Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.
Power Consumption Analysis of Prominent Time Synchronization Protocols for Wireless Sensor Networks
Bae, Shi-Kyu ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 300~313
DOI : 10.3745/JIPS.03.0006
Various Time Synchronization protocols for a Wireless Sensor Network (WSN) have been developed since time synchronization is important in many time-critical WSN applications. Aside from synchronization accuracy, energy constraint should also be considered seriously for time synchronization protocols in WSNs, which typically have limited power environments. This paper performs analysis of prominent WSN time synchronization protocols in terms of power consumption and test by simulation. In the analysis and simulation tests, each protocol shows different performance in terms of power consumption. This result is helpful in choosing or developing an appropriate time synchronization protocol that meets the requirements of synchronization accuracy and power consumption (or network lifetime) for a specific WSN application.
Default Prediction for Real Estate Companies with Imbalanced Dataset
Dong, Yuan-Xiang ; Xiao, Zhi ; Xiao, Xue ;
Journal of Information Processing Systems, volume 10, issue 2, 2014, Pages 314~333
DOI : 10.3745/JIPS.04.0002
When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two-class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction-oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset.