Development of Personal Information Protection Model using a Mobile Agent

Bae, Seong-Hee,Kim, Jae-Joon Korea Information Processing Society 2010 Journal of information processing systems Vol.6 No.2

This paper proposes a personal information protection model that allows a user to regulate his or her own personal information and privacy protection policies to receive services provided by a service provider without having to reveal personal information in a way that the user is opposed to. When the user needs to receive a service that requires personal information, the user will only reveal personal information that they find acceptable and for uses that they agree with. Users receive desired services from the service provider only when there is agreement between the user's and the service provider's security policies. Moreover, the proposed model utilizes a mobile agent that is transmitted from the user's personal space, providing the user with complete control over their privacy protection. In addition, the mobile agent is itself a self-destructing program that eliminates the possibility of personal information being leaked. The mobile agent described in this paper allows users to truly control access to their personal information.

The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing

Pedrycz, Witold Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.3

Granular Computing has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules. Information granules are formalized within various frameworks such as sets (interval mathematics), fuzzy sets, rough sets, shadowed sets, probabilities (probability density functions), to name several the most visible approaches. In spite of the apparent diversity of the existing formalisms, there are some underlying commonalities articulated in terms of the fundamentals, algorithmic developments and ensuing application domains. In this study, we introduce two pivotal concepts: a principle of justifiable granularity and a method of an optimal information allocation where information granularity is regarded as an important design asset. We show that these two concepts are relevant to various formal setups of information granularity and offer constructs supporting the design of information granules and their processing. A suite of applied studies is focused on knowledge management in which case we identify several key categories of schemes present there.

Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries

Porcel, Carlos,Ching-Lopez, Alberto,Bernabe-Moreno, Juan,Tejeda-Lorente, Alvaro,Herrera-Viedma, Enrique Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.4

The significant advances in information and communication technologies are changing the process of how information is accessed. The internet is a very important source of information and it influences the development of other media. Furthermore, the growth of digital content is a big problem for academic digital libraries, so that similar tools can be applied in this scope to provide users with access to the information. Given the importance of this, we have reviewed and analyzed several proposals that improve the processes of disseminating information in these university digital libraries and that promote access to information of interest. These proposals manage to adapt a user's access to information according to his or her needs and preferences. As seen in the literature one of the techniques with the best results, is the application of recommender systems. These are tools whose objective is to evaluate and filter the vast amount of digital information that is accessible online in order to help users in their processes of accessing information. In particular, we are focused on the analysis of the fuzzy linguistic recommender systems (i.e., recommender systems that use fuzzy linguistic modeling tools to manage the user's preferences and the uncertainty of the system in a qualitative way). Thus, in this work, we analyzed some proposals based on fuzzy linguistic recommender systems to help researchers, students, and teachers access resources of interest and thus, improve and complement the services provided by academic digital libraries.

A Video Traffic Flow Detection System Based on Machine Vision

Wang, Xin-Xin,Zhao, Xiao-Ming,Shen, Yu Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.5

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

A Timing Constraint Search Technique for a TMO based Real-time Process

Jeong, Yoon-Seok,Kim, Tae-Wan,Han, Sun-Young,Chang, Chun-Hyon Korea Information Processing Society 2006 Journal of information processing systems Vol.2 No.1

Finding a valid timing constraint is one of the most important issues in the real-time monitoring area. To get the valid timing constraint, a developer executes a real-time process and changes the constraint on a regular basis. This is an exhaustive and time-consuming process. To improve this approach, we propose a timing constraint search technique. This technique uses two load models and one condition proposed in this paper to support the developer in determining the valid timing constraint range in an easy and systematic manner.

The Design of the IIR Differintegrator and its Application in Edge Detection

Jain, Madhu,Gupta, Maneesha,Jain, N.K. Korea Information Processing Society 2014 Journal of information processing systems Vol.10 No.2

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.

A New Image Clustering Method Based on the Fuzzy Harmony Search Algorithm and Fourier Transform

Bekkouche, Ibtissem,Fizazi, Hadria Korea Information Processing Society 2016 Journal of information processing systems Vol.9 No.3

In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

A Tracking-by-Detection System for Pedestrian Tracking Using Deep Learning Technique and Color Information

Truong, Mai Thanh Nhat,Kim, Sanghoon Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.4

Pedestrian tracking is a particular object tracking problem and an important component in various vision-based applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.

Systematic Review of Bug Report Processing Techniques to Improve Software Management Performance

Lee, Dong-Gun,Seo, Yeong-Seok Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.4

Bug report processing is a key element of bug fixing in modern software maintenance. Bug reports are not processed immediately after submission and involve several processes such as bug report deduplication and bug report triage before bug fixing is initiated; however, this method of bug fixing is very inefficient because all these processes are performed manually. Software engineers have persistently highlighted the need to automate these processes, and as a result, many automation techniques have been proposed for bug report processing; however, the accuracy of the existing methods is not satisfactory. Therefore, this study focuses on surveying to improve the accuracy of existing techniques for bug report processing. Reviews of each method proposed in this study consist of a description, used techniques, experiments, and comparison results. The results of this study indicate that research in the field of bug deduplication still lacks and therefore requires numerous studies that integrate clustering and natural language processing. This study further indicates that although all studies in the field of triage are based on machine learning, results of studies on deep learning are still insufficient.

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Muthuvelu, Nithiapidary,Chai, Ian,Chikkannan, Eswaran,Buyya, Rajkumar Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.2

The overhead of processing fine-grain tasks on a grid induces the need for batch processing or task group deployment in order to minimise overall application turnaround time. When deciding the granularity of a batch, the processing requirements of each task should be considered as well as the utilisation constraints of the interconnecting network and the designated resources. However, the dynamic nature of a grid requires the batch size to be adaptable to the latest grid status. In this paper, we describe the policies and the specific techniques involved in the batch resizing process. We explain the nuts and bolts of these techniques in order to maximise the resulting benefits of batch processing. We conduct experiments to determine the nature of the policies and techniques in response to a real grid environment. The techniques are further investigated to highlight the important parameters for obtaining the appropriate task granularity for a grid resource.