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From submission to final decision: less than 6 months !
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JIPS OVERVIEW
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The Journal of Information Processing Systems (ISSN: 1976-913X(Print), ISSN: 2092-805X(Online))
is the official international journal of the Korea Information Processing Society (KIPS). It is committed to publishing high-quality papers
on the state-of-the-art of information processing systems. Theoretical research contributions presenting new techniques, concepts, or analyses,
reports on experiences and experiments of implementation and application of theories, and tutorials on new technologies and trends are all welcome.
The subjects covered by the journal include all topics related to a) computer system and theory; b) multimedia system and graphics; c) communication
system and security; d) software system and application. All submitted manuscripts are treated consistently, fairly, and with a minimum of delay from
submission to final decision (less than 6 months!)
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FEATURED PAPERS
LATEST PUBLICATIONS
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Journal of Information Processing Systems, Vol. 10, No.1, 2014
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
Page: 1~22
 10.3745/JIPS.2014.10.1.001
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Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.
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Trivariate B-spline Approximation of Spherical Solid Objects
Junho Kim*,
Seung-Hyun Yoon**
and Yunjin Lee***
Page: 23~35
10.3745/JIPS.2014.10.1.023
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Recently, novel application areas in digital geometry processing, such as simulation, dynamics, and medical surgery simulations, have necessitated the representation of not only the surface data but also the interior volume data of a given 3D object. In this paper, we present an efficient framework for the hape approximations of spherical solid objects based on trivariate B-splines. To do this, we first constructed a smooth correspondence between a given object and a unit solid cube by computing their harmonic mapping. We set the unit solid cube as a rectilinear parametric domain for trivariate B-splines and utilized the mapping to approximate the given object with B-splines in a coarse-to-fine manner. Specifically, our framework provides usercontrollability of shape approximations, based on the control of the boundary condition of the harmonic parameterization and the level of B-spline fitting. Experimental results showed that our method is efficient enough to compute trivariate B-splines for several
models, each of whose topology is identical to a solid sphere.
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A Token Based Protocol for Mutual Exclusion in Mobile Ad Hoc Networks
Bharti Sharma*,
Ravinder Singh Bhatia**
and Awadhesh Kumar Singh**
Page: 36~54
10.3745/JIPS.2014.10.1.036
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Resource sharing is a major advantage of distributed computing. However, a distributed computing system may have some physical or virtual resource that may be accessible by a single process at a time. The mutual exclusion issue is to ensure that no more than one process at a time is allowed to access some shared resource. The article proposes a token-based mutual exclusion algorithm for the clustered mobile ad hoc networks (MANETs). The mechanism that is adapted to handle token passing at the inter-cluster level is different from that at the intra-cluster level. It makes our algorithm message efficient and thus suitable for MANETs. In the interest of efficiency, we implemented a centralized token passing scheme at the intra-cluster level. The centralized schemes are inherently failure prone. Thus, we have presented an intracluster token passing scheme that is able to tolerate a failure. In order to enhance reliability, we applied a distributed token circulation scheme at the inter-cluster level. More importantly, the message complexity of the proposed algorithm is independent of N, which is the total number of nodes in the system. Also, under a heavy load, it turns out to be inversely proportional to n, which is the (average) number of nodes per each cluster. We substantiated our claim with the correctness proof, complexity analysis, and simulation results. In the end, we present a simple approach to make our protocol fault tolerant.
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Stroke Width-Based Contrast Feature for Document Image Binarization
Le Thi Khue Van*
and Gueesang Lee*
Page: 55~68
10.3745/JIPS.2014.10.1.055
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Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.
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The Construction and Viterbi Decoding of New (2k, k, l) Convolutional Codes
Wanquan Peng*
and Chengchang Zhang**
Page: 69~80
10.3745/JIPS.2014.10.1.069
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The free distance of (n, k, l) convolutional codes has some connection with the memory length, which depends on not only l but also on k. To efficiently obtain a large memory length, we have constructed a new class of (2k, k, l) convolutional codes by (2k, k) block codes and (2, 1, l) convolutional codes, and its encoder and generation function are also given in this paper. With the help of some matrix modules, we designed a single structure Viterbi decoder with a parallel capability, obtained a unified and efficient decoding model for (2k, k, l) convolutional codes, and then give a description of the decoding process in detail. By observing the survivor path memory in a matrix viewer, and testing the role of the max module, we implemented a simulation with (2k, k, l) convolutional codes. The results show that many of them are better than conventional (2, 1, l) convolutional codes.
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Push-N-Scheme with Timeout for Content Delivery of Social Networking Services
Kyungkoo Jun*
Page: 81~92
10.3745/JIPS.2014.10.1.081
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Widely spreading smart devices have become an important information sharing channel in everyday life. In particular, social networking services (SNS) are the hub for content creation and sharing. Users post their contents on SNS servers and receive contents of interest. Contents are delivered in either pull or push. Regarding delivery, cost and wait time are two important factors to be minimized, but they are in a trade-off relationship. The Push-N-scheme (PNS) and timeout-based push scheme (TPS) have been proposed for content delivery. PNS has an advantage in cost over TPS, whereas TPS has an edge in terms of the wait time over PNS. We propose a hybrid push scheme of PNS and TPS, called push-N-scheme with timeout (PNT), to balance the cost and the wait time. We evaluate PNT through simulations, with the results showing that PNT is effective in balancing PNS and TPS.
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Gesture Input as an Out-of-band Channel
Oyuntungalag Chagnaadorj*
and Jiro Tanaka*
Page: 92~102
10.3745/JIPS.2014.10.1.092
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In recent years, there has been growing interest in secure pairing, which refers to the establishment of a secure communication channel between two mobile devices. There are a number of descriptions of the various types of out-of-band (OOB) channels, through which authentication data can be transferred under a user’s control and involvement. However, none have become widely used due to their lack of adaptability to the variety of mobile devices. In this paper, we introduce a new OOB channel, which uses accelerometer-based gesture input. The gesture-based OOB channel is suitable for all kinds of mobile devices, including input/output constraint devices, as the accelerometer is small and incurs only a small computational overhead. We implemented and evaluated the channel using an Apple iPhone handset. The results demonstrate that the channel is viable with completion times and error rates that are comparable with other OOB channels.
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Cooperation-Aware VANET Clouds: Providing Secure Cloud Services to Vehicular Ad Hoc Networks
Rasheed Hussain*
and Heekuck Oh*
Page: 103~118
10.3745/JIPS.2014.10.1.103
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Over the last couple of years, traditional VANET (Vehicular Ad Hoc NETwork) evolved into VANET-based clouds. From the VANET standpoint, applications became richer by virtue of the boom in automotive telematics and infotainment technologies. Nevertheless, the research community and industries are concerned about the under-utilization of rich computation, communication, and storage resources in middle and high-end vehicles. This phenomenon became the driving force for the birth of VANET-based clouds. In this paper, we envision a novel application layer of VANET-based clouds based on the cooperation of the moving cars on the road, called CaaS (Cooperation as a Service). CaaS is divided into TIaaS (Traffic Information as a Service), WaaS (Warning as a Service), and IfaaS (Infotainment as a Service). Note, however, that this work focuses only on TIaaS and WaaS. TIaaS provides vehicular nodes, more precisely subscribers, with the fine-grained traffic information constructed by CDM (Cloud Decision Module) as a result of the cooperation of the vehicles on the roads in the form of mobility vectors. On the other hand, WaaS provides subscribers with potential warning messages in case of hazard situations on the road. Communication between the cloud infrastructure and the vehicles is done through GTs (Gateway Terminals), whereas GTs are physically realized through RSUs (Road-Side Units) and vehicles with 4G Internet access. These GTs forward the coarse-grained cooperation from vehicles to cloud and fine-grained traffic information and warnings from cloud to vehicles (subscribers) in a secure, privacy-aware fashion. In our proposed scheme, privacy is conditionally preserved wherein the location and the identity of the cooperators are preserved by leveraging the modified location-based encryption and, in case of any dispute, the node is subject to revocation. To the best of our knowledge, our proposed scheme is the first effort to offshore the extended traffic view construction function and warning messages dissemination function to the cloud.
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Performance Evaluation of the VoIP Services of the Cognitive Radio System, Based on DTMC
Ummy Habiba*,
Md. Imdadul Islam**
and M. R. Amin*
Page: 119~131
10.3745/JIPS.2014.10.1.119
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In recent literature on traffic scheduling, the combination of the twodimensional discrete-time Markov chain (DTMC) and the Markov modulated Poisson process (MMPP) is used to analyze the capacity of VoIP traffic in the cognitive radio system. The performance of the cognitive radio system solely depends on the accuracy of spectrum sensing techniques, the minimization of false alarms, and the scheduling of traffic channels. In this paper, we only emphasize the scheduling of traffic channels (i.e., traffic handling techniques for the primary user [PU] and the secondary user [SU]). We consider the following three different traffic models: the cross-layer analytical model, M/G/1(m) traffic, and the IEEE 802.16e/m scheduling approach to evaluate the performance of the VoIP services of the cognitive radio system from the context of blocking probability and throughput.
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How to Manage Cloud Risks Based on the BMIS Model
Youjin Song*
and Yasheng Pang*
Page: 132~144
10.3745/JIPS.2014.10.1.132
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Information always comes with security and risk problems. There is the saying that, “The tall tree catches much wind,” and the risks from cloud services will absolutely be more varied and more severe. Nowadays, handling these risks is no longer just a technology problem. So far, a good deal of literature that focuses on risk or security management and frameworks in information systems has already been submitted. This paper analyzes the causal risk factors in cloud environments through critical success factors, from a business perspective. We then integrated these critical success factors into a business model for information security by mapping out 10 principles related to cloud risks. Thus, we were able to figure out which aspects should be given more consideration in the actual transactions of cloud services, and were able to make a business-level and general-risk control model for cloud computing.
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Probabilistic Models for Local Patterns Analysis
Khiat Salim*,
Belbachir Hafida*
and Rahal Sid Ahmed*
Page: 145~161
10.3745/JIPS.2014.10.1.145
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Recently, many large organizations have multiple data sources (MDS’) distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.
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CONTACT INFORMATION
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JIPS Secretary: Joo-yeon Lee (joo@kips.or.kr)
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