Cloud computing and crowdsourcing are growing trends in IT. Combining the strengths of both machine and human clouds within a hybrid design enables us to overcome certain problems and achieve efficiencies. In this pap...
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Object tracking and manipulation is an important process for many applications in robotics and computer vision. A novel 3D pose estimation of objects using reflectionally symmetry formulated in Conformai Geometric Alg...
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Object tracking and manipulation is an important process for many applications in robotics and computer vision. A novel 3D pose estimation of objects using reflectionally symmetry formulated in Conformai Geometric Algebra (CGA) is proposed in this work. The synthesis of the kinematics model for robots and a sliding mode controller using the CGA approach is described. Real time implementation results are presented for the pose estimation of object using a stereo vision system.
Textual passwords were first identified as a weak point in information system's security by Morris and Thompson in 1979. They found that 86% of the passwords were weak: being too short, containing lowercase letter...
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ISBN:
(纸本)9781479956579
Textual passwords were first identified as a weak point in information system's security by Morris and Thompson in 1979. They found that 86% of the passwords were weak: being too short, containing lowercase letters only, digits only or a combination of the two, being easily found in dictionaries. OBJECTIVE: Despite the importance of passwords as the first line of defense in most information systems, little attention has been given to the characteristics of their actual use. Thus, the objective of this paper is to identify any problems that may arise in creating and using textual passwords. METHOD: A systematic literature review of studies in the area of password use and password security. Our research is restricted to articles in journals and conference papers written in English and published between 1979 and 2014. The search is conducted through IEEEXplore, ScienceDirect, Springer Link and ACM Digital Library. RESULTS: The computer community has not made a very much-needed shift in password management for more than 35 years. Users and their passwords are still considered the main weakness in any password system, because users often choose easily guessable passwords: words, names, birthdates, etc., because they are easy to remember. CONCLUSION: Password policies and password checkers can help users create strong and easy-to-remember passwords. This work will serve as a starting point for our further research in this area where we want to determine whether these password policies are useful to the users, and whether the users can easily apply them.
In a variety of documents, ranging from forms to archive documents and books with annotations, machine printed and handwritten text may coexist in the same document image, raising significant issues within the recogni...
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This paper presents a novel mechanism of cryptographic one-to-many reversible mapping between two domains and it's applications. One-to-many reversible mapping is a one-to-many mapping in which the relations can b...
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This paper presents a novel mechanism of cryptographic one-to-many reversible mapping between two domains and it's applications. One-to-many reversible mapping is a one-to-many mapping in which the relations can be reversible. Cryptographic one-to-many reversible mapping is that the development of one-to-many mapping is performed based on pseudorandom assignment of the subsets of the other set, such that it is difficult to find the many-to-one reversed relation, in which the assignment is done using cryptographic approach. The one-to-many mapping which generates pseudo-randomly has a high avalanche effect in order to cover the identity. The randomness test is measured in terms of uniformity based on mono-bit tests and avalanche effect based on Hamming distance test. The expected uniformity and avalanche effect value is about 50% of the bits changed has been achieved by using Cipher Feedback mode of Advanced Encryption Standard.
Gaussian processes (GPs) constitute one of the most important Bayesian machine learning approaches. Several researchers have considered postulating mixtures of Gaussian processes as a means of dealing with non-station...
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Gaussian processes (GPs) constitute one of the most important Bayesian machine learning approaches. Several researchers have considered postulating mixtures of Gaussian processes as a means of dealing with non-stationary covariance functions, discontinuities, multi-modality, and overlapping output signals. In existing works, mixtures of Gaussian processes are based on the introduction of a gating function defined over the space of model input variables. This way, each postulated mixture component Gaussian process is effectively restricted in a limited subset of the input space. Additionally, the applicability of these models is limited to regression tasks. In this paper, for the first time in the literature, we devise a Gaussian process mixture model especially suitable for multiclass classification applications: We consider a GP classification scheme the prior distribution of which is a fully generative nonparametric Bayesian model with power-law behavior, generating Gaussian processes over the whole input space of the learned task. We provide an efficient algorithm for model inference, based on the variational Bayesian framework, and exhibit its efficacy using benchmark and real-world classification datasets. (c) 2013 Elsevier B.V. All rights reserved.
The ambition to achieve higher computing performance, is based on using all the advantages of parallel approach. The devices, software development kits and other technologies are leaping forward. Nowadays, they allow ...
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The ambition to achieve higher computing performance, is based on using all the advantages of parallel approach. The devices, software development kits and other technologies are leaping forward. Nowadays, they allow programmer to use more effective and optimized template libraries. They empower him to acces functions of graphics processing unit through the highlevel language. This paper details the experience of using such optimization on basic and more complex algorithms and the measurement of overall effectiveness increase. Our experimental results demonstrate the overall acceleration on various types of GPU.
The assessment is the most effectively tool for the teachers to realized the learning status of the learners. The test sheet assembling is an important job in the E-learning. In the future learning cloud environment, ...
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We propose a resource allocation scheme based on Proportional Fairness (PF) for minimum bit rate guarantee in a multiuser, frequency-selective frame-based OFDMA system. Instead of considering subcarrier-and-bit alloca...
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Wind energy has become one of the fastest growing renewable sources during last few decades. Sudden changes in wind power output, called wind ramps, recently attracted great research interest in wind power forecasting...
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Wind energy has become one of the fastest growing renewable sources during last few decades. Sudden changes in wind power output, called wind ramps, recently attracted great research interest in wind power forecasting community. Conventional ramp prediction methods derive future ramp estimates from power forecast series. We suggest to analyze real wind power series or other weather parameters, searching for specific patterns and dependencies indicating forthcoming wind ramp *** paper presents a methodology for parametric analysis of time series preceding wind ramp events. The presented methodology is based on probabilistic data analysis. Sensitivity of the developed algorithm can be adjusted through the size of the time window defined before a ramp event. Power production and other weather data are standardized, averaged and then searched for specific patterns in the form of trend lines. The resulting methodology does not require the use of a numerical weather prediction (NWP) model; this is a significant simplification compared to most conventional methods. The proposed methodology is tested using power production and wind speed data collected between August 2011 and July 2012 at a wind farm located in a wind-rich region of southern Alberta, Canada.
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