Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Software Engineering, Artificial Intelligence, Networking and Parallel & Distributed Computing (SNPD), 2012 13th ACIS International Conference on

Date 8-10 Aug. 2012

Filter Results

Displaying Results 1 - 25 of 139
  • [Cover art]

    Publication Year: 2012 , Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (1194 KB)  
    Freely Available from IEEE
  • [Title page i]

    Publication Year: 2012 , Page(s): i
    Save to Project icon | Request Permissions | PDF file iconPDF (64 KB)  
    Freely Available from IEEE
  • [Title page iii]

    Publication Year: 2012 , Page(s): iii
    Save to Project icon | Request Permissions | PDF file iconPDF (104 KB)  
    Freely Available from IEEE
  • [Copyright notice]

    Publication Year: 2012 , Page(s): iv
    Save to Project icon | Request Permissions | PDF file iconPDF (64 KB)  
    Freely Available from IEEE
  • Table of contents

    Publication Year: 2012 , Page(s): v - xvi
    Save to Project icon | Request Permissions | PDF file iconPDF (166 KB)  
    Freely Available from IEEE
  • A Message from the Conference Chair

    Publication Year: 2012 , Page(s): xvii
    Save to Project icon | Request Permissions | PDF file iconPDF (90 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • Message from the Program Co-Chairs

    Publication Year: 2012 , Page(s): xviii
    Save to Project icon | Request Permissions | PDF file iconPDF (78 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • Organizing Committee

    Publication Year: 2012 , Page(s): xix
    Save to Project icon | Request Permissions | PDF file iconPDF (76 KB)  
    Freely Available from IEEE
  • Program Committee

    Publication Year: 2012 , Page(s): xx - xxii
    Save to Project icon | Request Permissions | PDF file iconPDF (82 KB)  
    Freely Available from IEEE
  • Keynote abstracts [two abstracts]

    Publication Year: 2012 , Page(s): xxiii - xxiv
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (79 KB)  

    Summary form only given. Provides the abstracts for the following four invited talks: Pursuit of Low-dimensional Structures in High-dimensional Data; Interest Points Detectors and Descriptors in Image Recognition; Patient and Process Specific Imaging and Visualization for computer assisted interventions; Three Approaches of Scene Text Recognition: An informal comparison on difficult images. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Query Range Sensitive Probability Guided Multi-probe Locality Sensitive Hashing

    Publication Year: 2012 , Page(s): 3 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB) |  | HTML iconHTML  

    Locality Sensitive Hashing (LSH) is proposed to construct indexes for high-dimensional approximate similarity search. Multi-Probe LSH (MPLSH) is a variation of LSH which can reduce the number of hash tables. Based on the idea of MPLSH, this paper proposes a novel probability model and a query-adaptive algorithm to generate the optimal multi-probe sequence for range queries. Our probability model takes the query range into account to generate the probe sequence which is optimal for range queries. Furthermore, our algorithm does not use a fixed number of probe steps but a query-adaptive threshold to control the search quality. We do the experiments on an open dataset to evaluate our method. The experimental results show that our method can probe fewer points than MPLSH for getting the same recall. As a result, our method can get an average acceleration of 10% compared to MPLSH. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Computational Model of Imitation and Autonomous Behavior

    Publication Year: 2012 , Page(s): 13 - 18
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (947 KB) |  | HTML iconHTML  

    Learning is essential for an autonomous agent to adapt to an environment. One method that can be used is learning through trial and error. However, it is impractical because of the long learning time required when the agent learns in a complex environment. Therefore, some guidelines are necessary to expedite the learning process in a complex environment. Imitation of the behavior of other agents who have already adapted to the environment would shorten an agent's learning time. Thus, imitation can be used by agents as a guideline for learning. In this study, we propose a computational model of imitation and autonomous behavior. We expect that an agent can reduce its learning time through imitation. The actions that an agent performs are represented by a set of features such as the type, location, and object of an action. The agent tends to imitate the similar actions of other agents, and the similarity between actions is calculated, which is indicative of the importance of each feature. The proposed model is evaluated using a dining table simulator. The experimental results indicate that the proposed model can adapt to the environment faster than a baseline model that learns only through trial and error, and that the proposed model can shorten the learning time further if the importance of each feature can be adjusted by learning. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Does Talking to a Robot in a High-Pitched Voice Create a Good Impression of the Robot?

    Publication Year: 2012 , Page(s): 19 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (380 KB) |  | HTML iconHTML  

    When talking to infants, we tend to use infant-directed speech (IDS) rather than adult-directed speech (ADS). IDS attracts more attention from infants, conveys the emotions of adults more easily, and makes language acquisition easier. It is not clear, however, whether IDS has a cognitive effect on adults as well. To address this issue, we focus on one of the most distinctive features of IDS, a high-pitched voice. In addition, we conduct two human-robot interaction experiments to examine the following two hypotheses: (i) a robot reacting selectively to a high-pitched voice triggers a high-pitched voice of the user (H1), and (ii) talking to a robot in a high-pitched voice improves the user's impression of the robot (H2). The results did not support H1, but marginally supported H2. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Efficiency of Interactive Differential Evolution in Creation of Sound Contents: In Comparison with Interactive Genetic Algorithm

    Publication Year: 2012 , Page(s): 25 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    Interactive Evolutionary Computation (IEC) is well known as an effective method to create media contents suited to user's preference and objectives to use. As one of the methods, we have applied Differential Evolution, which is recent evolutionary algorithm to IEC. Concretely, we have already presented a method that creates sign sounds with Interactive Differential Evolution (IDE). This study aims to investigate fundamentally the efficacy of the IDE method in comparison with Interactive Genetic Algorithm (IGA). Two listening experiments were conducted: experiment 1 as a creation experiment with IDE and IGA, experiment 2 as a re-evaluation experiment. Target of the creation was warning sign sounds. In the experiment 2, representative five sign sounds created in both of IDE and IGA were evaluated. Sixteen males participated as subjects in the experiments. In the result of the experiment 1, IDE overcame IGA in subjective fitness value. Drastic shrink of searching space was observed in IGA, and larger time cost was observed in IDE. In the result of the experiment 2, higher fitness value in average was observed in IDE, however, the difference was not significant. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multimodal Medical Image Fusion in Modified Sharp Frequency Localized Contourlet Domain

    Publication Year: 2012 , Page(s): 33 - 37
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (600 KB) |  | HTML iconHTML  

    As a novel of multi-resolution analysis tool, the modified sharp frequency localized contour let transforms (MSFLCT) provides flexible multiresolution, anisotropy, and directional expansion for medical images. In this paper, we proposed a new fusion rule for multimodal medical images based on MSFLCT. The multimodal medical images are decomposed by MSFLCT. For the high-pass sub band, the weighted sum modified laplacian (WSML) method is used for choose the high frequency coefficients. For the low pass sub band, the maximum local energy (MLE) method is combined with "region" idea for low frequency coefficient selection. The final fusion image is obtained by applying inverse MSFLCT to fused low pass and high pass sub bands. Abundant experiments have been made on groups of multimodality datasets, both human visual and quantitative analysis show that the new strategy for attaining image fusion with satisfactory performance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Comparative Analysis of Access Control Systems on Cloud

    Publication Year: 2012 , Page(s): 41 - 46
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (395 KB) |  | HTML iconHTML  

    Cloud computing, a relatively new concept and has gained an immense attention of research community in the past few years. R&D organizations and industry are investing a lot in cloud based research and applications. Similarly on theconsumers' side organizations are moving their business on cloud to provide flexibility and conceive ever increasing computational power requirements. In spite of significant advantages, and its demand, different stakeholders are still reluctant to migrate to cloud. A major hindrance is the absence of reliable and comprehensive access control mechanism for cloud resources. We have analyzed existing cloud based access control systems and evaluated those using NIST defined access control systems evaluation criteria. Based on our analysis we have proposed future research direction in the domain of access control systems for cloud based environments, which will eventually pave the way towards cloud adoption. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Admission Control Strategy of Serving Peers in P2P VoD Systems

    Publication Year: 2012 , Page(s): 49 - 53
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (169 KB) |  | HTML iconHTML  

    Data request task scheduling is one of the important issues for P2P VoD systems. However the existing data scheduling strategies in P2P VoD system is not fair enough. They make many nodes, which upload data actively, bear very heavy load, while those selfish nodes providing no resource sit idle. This paper presents an admission control strategy on serving nodes combining with the incentive mechanism. The serving peers respond the requesting peers that contribute more data to systems with priority and reject some requests which can not be processed in time. The experiments show that this strategy improves the performance of the system and decreases the users' wait time for watching. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Pricing Model and Real Options in 4G LTE Mobile Network

    Publication Year: 2012 , Page(s): 54 - 59
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB) |  | HTML iconHTML  

    This paper focuses on real option theory and on its applications in 4G LTE mobile network. The objective of this paper are (1) to introduce real option theory and to discuss its applicability as a decision support tools, (2) to exemplify some real options present in 4G LTE communication of MNO markets, and (3) to apply real option approach based on the proposed pricing model to the selected case to demonstrate the power of option pricing models as a decision support tool in 4G LTE mobile network. The application of real option approach is valuation of investment opportunities when the future capacity prices are uncertain but the investment costs are unknown. The optimal pricing of capacity tariffs is identified under stochastic capacity prices. The case demonstrates how real option models can be used to derive decision rules to problems faced by several telecom parties. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Understanding Botnet: From Mathematical Modelling to Integrated Detection and Mitigation Framework

    Publication Year: 2012 , Page(s): 63 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (647 KB) |  | HTML iconHTML  

    No one is absolutely sure about cyber security as long as a communication system is connected to the internet, since internet is a wild that comprises all kind of people around the world from white hat to black hat. In other words, virtually any Internet connected system is vulnerable to major outrages from receiving a spam email to a botnet originated DDOS attack. But every individual, company and government wants to make sure that the security of their system is dependable so that they can use the outmost benefits of the twenty first century information society advantage. Since the problem is inevitable it very critical to understand the properties of this nefarious attacking machines from different perspective. In this paper we have developed a mathematical model to scrutinize the favouring and hindering factors for botnet propagation and growth. In addition we have proposed a detection and mitigation framework based on the model we developed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Novel Online Event Analysis Framework for Micro-blog Based on Incremental Topic Modeling

    Publication Year: 2012 , Page(s): 73 - 76
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (165 KB) |  | HTML iconHTML  

    In this paper, we present a scalable implementation of a topic modeling (Adaptive Link-IPLSA) based method for online event analysis, which summarize the gist of massive amount of changing tweets and enable users to explore the temporal trends in topics. This model also can simultaneously maintain the continuity of the latent semantics to better capture the time line development of events. With the help of this model, users can quickly grasp major topics in these twitters. The preliminary results show that our method leads to more balanced and comprehensive improvement for online event detection compared to benchmark approaches. Additionally our algorithm is computationally feasible in near real-time scenarios making it an attractive alternative for capturing the rapidly changing dynamics of microblogs. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Does it Matter What They Said? A Text Mining Analysis of the State of the Union Addresses of USA Presidents

    Publication Year: 2012 , Page(s): 77 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    Text data are a major type of data in the modern society. Literatures have pointed out that more than 80% of data are in text form. It is important to study the insights from text data in addition to quantitative data. The development of text mining techniques started in the early 80's. The methodology has become much more mature in the recent years. In this article, we conduct a case study using text mining technique to analyze the patterns of the president's State of the Union address in USA. The speeches analyzed include the recent four USA presidents, Bush (1989-1992), Clinton (1993 - 2000), G.W. Bush (2001-2008), and Obama (2009-2011). Using two different text mining techniques, we identify six clusters from the 23 speeches using one technique and obtain seven topics based on the other technique. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • DSCLU: A New Data Stream Clustring Algorithm for Multi Density Environments

    Publication Year: 2012 , Page(s): 83 - 88
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (506 KB) |  | HTML iconHTML  

    Recently, data stream has become popular in many contexts of data mining. Due to the high amount of incoming data, traditional clustering algorithms are not suitable for this family of problems. Many data stream clustering algorithms proposed in recent years considered the scalability of data, but most of them did not attend the following issues: (1) The quality of clustering can be dramatically low over the time. (2) Some of the algorithms cannot handle arbitrary shapes of data stream and consequently the results are limited to specific regions. (3) Most of the algorithms have not been evaluated in multi-density environments. Identifying appropriate clusters for data stream by handling the arbitrary shapes of clusters is the aim of this paper. The gist of the overall approach in this paper can be stated in two phases. In online phase, data manipulate with specific data structure called micro cluster. This phase is activated by incoming of data. The offline phase is manually activated by coming a request from user. The algorithm handles clusters by considering with micro clusters created by the online phase. The experimental evaluation showed that proposed algorithm has suitable quality and also returns appropriate results even in multi-density environments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Enhance the Multi-level Fuzzy Association Rules Based on Cumulative Probability Distribution Approach

    Publication Year: 2012 , Page(s): 89 - 94
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (186 KB) |  | HTML iconHTML  

    This paper introduces a fusion model to reinforce multi-level fuzzy association rules, which integrated cumulative probability distribution approach (CPDA) and multi-level taxonomy concepts to extract fuzzy association rules. The proposed model generate large item sets level by level and mine multi-level fuzzy association rule lead to finding more informative and important knowledge from transaction dataset, which is more objective and reasonable in determining the universe of discourse and membership functions with other multi-level fuzzy association rules. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Factor Analysis for Influence Maximization Problem in Social Networks

    Publication Year: 2012 , Page(s): 95 - 101
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB) |  | HTML iconHTML  

    In recent years, researchers have paid more attention to influence maximization problem. This problem is firstly defined by Domingos and Richardson as follows: finding a small set of individuals in a social network that could maximize the spread of influence under certain influence cascade model. To solve this issue, researchers proposed different algorithms. However, in all of these algorithms, the size of the chosen individuals -k, is assigned in advance. In this paper, we conduct a preliminary exploration on the relationship between the size of the chosen set and the corresponding influence spread. We propose two metrics to analyze the factor k. Then we further consider the performance metric of the chosen set, which can be described by the stability of the chosen set. Experimental results on two real social networks show the efficiency and necessity of our proposed metrics. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • GDCLU: A New Grid-Density Based ClustrIng Algorithm

    Publication Year: 2012 , Page(s): 102 - 107
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (711 KB) |  | HTML iconHTML  

    This paper addresses the density based clustering problem in data mining where clusters are established based on density of regions. The most well-known algorithm proposed in this area is DBSCAN [1] which employs two parameters influencing the shape of resulted clusters. Therefore, one of the major weaknesses of this algorithm is lack of ability to handle clusters in multi-density environments. In this paper, a new density based grid clustering algorithm, GDCLU, is proposed which uses a new definition for dense regions. It determines dense grids based on densities of their neighbors. This new definition enables GDCLU to handle different shaped clusters in multi-density environments. Also this algorithm benefits from scale independency feature. The time complexity of the algorithm is O(n) in which n is number of points in dataset. Several examples are presented showing promising improvement in performance over other basic algorithms like optics in multi-density environments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.