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Full-Text Articles in Social and Behavioral Sciences
A Data-Driven Predictive Model For Residential Mobility In Australia - A Generalised Linear Mixed Model For Repeated Measured Binary Data, Mohammad-Reza Namazi-Rad, Payam Mokhtarian, Nagesh Shukla, Albert Munoz
A Data-Driven Predictive Model For Residential Mobility In Australia - A Generalised Linear Mixed Model For Repeated Measured Binary Data, Mohammad-Reza Namazi-Rad, Payam Mokhtarian, Nagesh Shukla, Albert Munoz
Faculty of Engineering and Information Sciences - Papers: Part A
Household relocation modelling is an integral part of the Government planning process as residential movements influence the demand for community facilities and services. This study will address the problem of modelling residential relocation choice by estimating a logit-link class model. The proposed model estimates the probability of an event which triggers household relocation. The attributes considered in this study are: requirement for bedrooms, employment status, income status, household characteristics, and tenure (i.e. duration living at the current location). Accurate prediction of household relocations for population units should rely on real world observations. In this study, a longitudinal survey data gathered …
A Local Field Correlated And Monte Carlo Based Shallow Neural Network Model For Non-Linear Time Series Prediction, Qingguo Zhou, Huaming Chen, Hong Zhao, Gaofeng Zhang, Jianming Yong, Jun Shen
A Local Field Correlated And Monte Carlo Based Shallow Neural Network Model For Non-Linear Time Series Prediction, Qingguo Zhou, Huaming Chen, Hong Zhao, Gaofeng Zhang, Jianming Yong, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part A
Water resource problems currently are much more important in proper planning especially for arid regions, such as Gansu in China. For agricultural and industrial activities, prediction of groundwater status is critical. As a main branch of neural network, shallow artificial neural network models have been deployed in prediction areas such as groundwater and rainfall since late 1980s. In this paper, artificial neural network (ANN) model within a newly proposed algorithm has been developed for groundwater status forecasting. Having considered previous algorithms for ANN model in time series forecast, this new Monte Carlo based algorithm demonstrated a good result. The experiments …
Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu
Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu
Faculty of Engineering and Information Sciences - Papers: Part A
Nowadays an increasing amount of data stored in the public cloud need to be searched remotely for fast accessing. For the sake of privacy, the remote files are usually encrypted, which makes them difficult to be searched by remote servers. It is also harder to efficiently share encrypted data in the cloud than those in plaintext. In this paper, we develop a searchable encryption framework called Linear Encryption with Keyword Search (LEKS) that can semi-generically convert some existing encryption schemes meeting our Linear Encryption Template (LET) to be searchable without re-encrypting all the data. For allowing easy data sharing, we …
Flexible Analysis Of Digital Pcr Experiments Using Generalized Linear Mixed Models, Matthijs Vynck, J Vandesompele, Nele Nijs, Björn Menten, Ariane De Ganck, Olivier Thas
Flexible Analysis Of Digital Pcr Experiments Using Generalized Linear Mixed Models, Matthijs Vynck, J Vandesompele, Nele Nijs, Björn Menten, Ariane De Ganck, Olivier Thas
Faculty of Engineering and Information Sciences - Papers: Part A
The use of digital PCR for quantification of nucleic acids is rapidly growing. A major drawback remains the lack of flexible data analysis tools. Published analysis approaches are either tailored to specific problem settings or fail to take into account sources of variability. We propose the generalized linear mixed models framework as a flexible tool for analyzing a wide range of experiments. We also introduce a method for estimating reference gene stability to improve accuracy and precision of copy number and relative expression estimates. We demonstrate the usefulness of the methodology on a complex experimental setup.
Design Of Geometric Parameters Of A Double-Sided Linear Induction Motor With Ladder Secondary And A Consideration For Reducing Cogging Force, Mochammad Rusli, Christopher David Cook
Design Of Geometric Parameters Of A Double-Sided Linear Induction Motor With Ladder Secondary And A Consideration For Reducing Cogging Force, Mochammad Rusli, Christopher David Cook
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, design of the physical of double-sided linear induction motor with ladder secondary is presented. It has aim to obtain the high-precision of DSLIM for the linear slow speed applications. One of limiting factor for precision linear movement is cogging force. The efforts in reducing the cogging action in rotary induction motor has been conducted very well. However, the cogging force reduction in the DSLIM with ladder secondary has not been done before. The DSLIM provide a great advantages for LIM-driven wheel vehicles for specific applications, for example vehicles that are used in over short distances, e.g. at …
Optimal Distribution Control Of Non‐Linear Tire Force Of Electric Vehicles With In‐Wheel Motors, Boyuan Li, Haiping Du, Weihua Li
Optimal Distribution Control Of Non‐Linear Tire Force Of Electric Vehicles With In‐Wheel Motors, Boyuan Li, Haiping Du, Weihua Li
Faculty of Engineering and Information Sciences - Papers: Part A
An over-actuated control system has the advantage of being able to use redundant actuators to reconfigure the control system and it can realize fault tolerant control. In order to achieve improved vehicle stability and handling performance for electric vehicles with in-wheel steering and driving motors, the control of the vehicle body slip angle and yaw rate is actually an over-actuated control problem. To obtain the optimal solution for this control problem, this study proposes a two-level tire force distribution control method, where the upper level controller calculates the desired lateral and longitudinal forces generated by friction on the tire of …
Development Of A Linear Damper Working With Magnetorheological Shear Thickening Fluids, Jian Yang, Shuaishuai Sun, Weihua Li, Haiping Du, Gursel Alici, Masami Nakano
Development Of A Linear Damper Working With Magnetorheological Shear Thickening Fluids, Jian Yang, Shuaishuai Sun, Weihua Li, Haiping Du, Gursel Alici, Masami Nakano
Faculty of Engineering and Information Sciences - Papers: Part A
Magnetorheological shear thickening fluid is a smart material that exhibits both magnetorheological and shear thickening effects. This study focuses on the design and development of a novel magnetorheological shear thickening fluid-based linear damper. First, micron-sized carbonyl iron particles, at a 20% and 80% weight fraction, were immersed among the shear thickening fluid base and thoroughly mixed under a high shear condition to produce the magnetorheological shear thickening fluid. Then, a monotube damper with a bypass was designed and fabricated. The testing results using an MTS machine show that the influence of incorporating shear thickening fluid allows the 20% magnetorheological shear …
A New Approach To Reduce The Non-Linear Characteristics Of A Stressed Power System By Using The Normal Form Technique In The Control Design Of The Excitation System, Hadi Lomei, Danny Sutanto, Kashem M. Muttaqi, Mohsen Assili
A New Approach To Reduce The Non-Linear Characteristics Of A Stressed Power System By Using The Normal Form Technique In The Control Design Of The Excitation System, Hadi Lomei, Danny Sutanto, Kashem M. Muttaqi, Mohsen Assili
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, a new approach is presented to reduce the nonlinear characteristics of a stressed power system by reducing its second-order modal interaction through retuning some parameters of the generator excitation system. In order to determine the second-order modal interaction of the system, a new index on nonlinearity is developed using normal form theory. Using the proposed index of nonlinearity, a sensitivity function is formed to indicate the most effective excitation system parameters in the nonlinear behavior of the system. These dominant parameters are tuned to reduce the second-order modal interaction of the system and to reduce the index …
Power Generation Analysis Of Powerwindow, A Linear Wind Generator, Using Computational Fluid Dynamic Simulations, Seyed A. Jafari, Farzad Safaei, Buyung Kosasih, K C. Kwok
Power Generation Analysis Of Powerwindow, A Linear Wind Generator, Using Computational Fluid Dynamic Simulations, Seyed A. Jafari, Farzad Safaei, Buyung Kosasih, K C. Kwok
Faculty of Engineering and Information Sciences - Papers: Part A
A new linear wind generator (LWG), named PowerWindow, is introduced. The modular and scalable LWG is capable of generating power in low wind velocity condition, and hence can be an effective and safe power generator in built environments. The aerodynamic mechanism of the LWG power generation is elucidated using computational fluid dynamic (CFD) simulations, and the results are validated against the experimental data obtained from the prototype wind tunnel tests. The simulations provide important insights into the flow field in and around LWG particularly over the front and rear blades and how each one contributes to the power generation. This …
Linear Regression With Nested Errors Using Probability-Linked Data, Klairung Samart, Raymond Chambers
Linear Regression With Nested Errors Using Probability-Linked Data, Klairung Samart, Raymond Chambers
Faculty of Engineering and Information Sciences - Papers: Part A
Probabilistic matching of records is widely used to create linked data sets for use in health science, epidemiological, economic, demographic and sociological research. Clearly, this type of matching can lead to linkage errors, which in turn can lead to bias and increased variability when standard statistical estimation techniques are used with the linked data. In this paper we develop unbiased regression parameter estimates to be used when fitting a linear model with nested errors to probabilistically linked data. Since estimation of variance components is typically an important objective when fitting such a model, we also develop appropriate modifications to standard …
Hep-2 Cell Image Classification With Multiple Linear Descriptors, Lingqiao Liu, Lei Wang
Hep-2 Cell Image Classification With Multiple Linear Descriptors, Lingqiao Liu, Lei Wang
Faculty of Engineering and Information Sciences - Papers: Part A
The automatic classification of the HEp-2 cell stain patterns from indirect immunofluorescence images has attracted much attention recently. As an image classification problem, it can be well solved by the state-of-the-art bag-of-features (BoF) model as long as a suitable local descriptor is known. Unfortunately, for this special task, we have very limited knowledge of such a descriptor. In this paper, we explore the possibility of automatically learning the descriptor from the image data itself. Specifically, we assume that a local patch can be well described by a set of linear projections performed on its pixel values. Based on this assumption, …
Design And Evaluation Of A Linear Damper Working With Mr Shear Thickening Fluids, Tongfei Tian, Weihua Li, Masami Nakano
Design And Evaluation Of A Linear Damper Working With Mr Shear Thickening Fluids, Tongfei Tian, Weihua Li, Masami Nakano
Faculty of Engineering and Information Sciences - Papers: Part A
Magnetorheological (MR) materials and shear thickening fluids are both smart material and their combination could offer both MR and ST effects. This study looks at the properties and behaviour of magnetorheological shear thickening fluid (MRSTF) in particular whilst applied as a semi-active energy absorber. A device with two forms of varying vibration control has been created and measured. The result shows that this MRSTF filled damper showed both MR and properties.
Anonymous Signcryption Against Linear Related-Key Attacks, Hui Cui, Yi Mu, Man Ho Au
Anonymous Signcryption Against Linear Related-Key Attacks, Hui Cui, Yi Mu, Man Ho Au
Faculty of Engineering and Information Sciences - Papers: Part A
A related-key attack (RKA) occurs when an adversary tampers the private key stored in a cryptographic hardware device and observes the result of the cryptographic primitive under this modified private key. In this paper, we concentrate on the security of anonymous signcryption schemes under related-key attacks, in the sense that a signcryption system should contain no information that identifies the sender of the signcryption and the receiver of the message, and yet be decipherable by the targeted receiver. To achieve this, we consider our anonymous signcryption scheme being semantically secure against chosen ciphertext and related-key attacks (CC-RKA), existentially unforgeable against …
W^{M,P}-Solution (P ≥ 2) Of Linear Degenerate Backward Stochastic Partial Differential Equations In The Whole Space, Kai Du, Shanjian Tang, Qi Zhang
W^{M,P}-Solution (P ≥ 2) Of Linear Degenerate Backward Stochastic Partial Differential Equations In The Whole Space, Kai Du, Shanjian Tang, Qi Zhang
Faculty of Engineering and Information Sciences - Papers: Part A
No abstract provided.
Public-Key Encryption Resilient To Linear Related-Key Attacks, Hui Cui, Yi Mu, Man Ho Au
Public-Key Encryption Resilient To Linear Related-Key Attacks, Hui Cui, Yi Mu, Man Ho Au
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, we consider the security of public-key encryption schemes under linear related-key attacks, where an adversary is allowed to tamper the private key stored in a hardware device, and subsequently observe the outcome of a public-key encryption system under this modified private key. Following the existing work done in recent years, we define the security model for related-key attack (RKA) secure public-key encryption schemes as chosen-ciphertext and related-key attack (CC-RKA) security, in which we allow an adversary to issue queries to the decryption oracle on the linear shifts of the private keys. On the basis of the adaptive …
Estimation Of Breeding Values For Mean And Dispersion, Their Variance And Correlation Using Double Hierarchical Generalized Linear Models, M Felleki, D Lee, Y Lee, A R. Gilmour, L Ronnegard
Estimation Of Breeding Values For Mean And Dispersion, Their Variance And Correlation Using Double Hierarchical Generalized Linear Models, M Felleki, D Lee, Y Lee, A R. Gilmour, L Ronnegard
Faculty of Engineering and Information Sciences - Papers: Part A
The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of …
Reducing Cogging Force In A Cage-Secondary Linear Induction Motor (Lim) By One-Side Shifting, Mochammad Rusli
Reducing Cogging Force In A Cage-Secondary Linear Induction Motor (Lim) By One-Side Shifting, Mochammad Rusli
Faculty of Engineering and Information Sciences - Papers: Part A
High precision linear machining tools is one of interesting research field in related to high qualitative products which is also becoming one of competitive factor. The movement precision can be affected by existence of ripple force, unpredicted external load and frictional force. The existence of cogging force is the one limited factor of the linear precision. The reduction of cogging force of its linear movement precision of machining tools using rotary motor drive can be obtained by the skewed rotor or implement the feedback control system. Many researchers have conducted the reduction of cogging torque of its machining tools drive …
An Analytical Method For Predicting Cogging Forces In Linear Induction Motors, Mochammad Rusli, Jeffrey W. Moscrop, Donald Platt, Christopher David Cook
An Analytical Method For Predicting Cogging Forces In Linear Induction Motors, Mochammad Rusli, Jeffrey W. Moscrop, Donald Platt, Christopher David Cook
Faculty of Engineering and Information Sciences - Papers: Part A
Cogging in a linear machine can be described as a variation in the magnetic forces as the machine travels along its linear uis. This effect can have a severe impact on the overall precision and even stability of the linear uis. In this paper an analytical method to predict the cogging forces in Linear Induction Moton (LIMs) is presented. An aecurate estimation of cogging is useful during the LIM design stage to help millimize this performance limiting factor. One common method used to predict cogging torques in rotary induction moton is the tooth overlap method. Due to the complexity of …
Balanced Truncation Of Linear Second-Order Systems: A Hamiltonian Approach, Carsten Hartmann, Valentina-Mira Vulcanov, Christof Schutte
Balanced Truncation Of Linear Second-Order Systems: A Hamiltonian Approach, Carsten Hartmann, Valentina-Mira Vulcanov, Christof Schutte
Faculty of Engineering and Information Sciences - Papers: Part A
We present a formal procedure for structure-preserving model reduction of linear second-order and Hamiltonian control problems that appear in a variety of physical contexts, e.g., vibromechanical systems or electrical circuit design. Typical balanced truncation methods that project onto the subspace of the largest Hankel singular values fail to preserve the problem's physical structure and may suffer from lack of stability. In this paper, we adopt the framework of generalized Hamiltonian systems that covers the class of relevant problems and that allows for a generalization of balanced truncation to second-order problems. It turns out that the Hamiltonian structure, stability, and passivity …
Superposition Coded Modulation And Iterative Linear Mmse Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Superposition Coded Modulation And Iterative Linear Mmse Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Faculty of Engineering and Information Sciences - Papers: Part A
We study superposition coded modulation (SCM) with iterative linear minimum-mean-square-error (LMMSE) detection. We show that SCM offers an attractive solution for highly complicated transmission environments with severe interference. We analyze the impact of signaling schemes on the performance of iterative LMMSE detection. We prove that among all possible signaling methods, SCM maximizes the output signal-tonoise/interference ratio (SNIR) in the LMMSE estimates during iterative detection. Numerical examples are used to demonstrate that SCM outperforms other signaling methods when iterative LMMSE detection is applied to multi-user/multi-antenna/multipath channels. © 2009 IEEE.
Evolution Analysis Of Low-Cost Iterative Equalization In Coded Linear Systems With Cyclic Prefixes, Xiaojun Yuan, Qinghua Guo, Xiaodong Wang, Li Ping
Evolution Analysis Of Low-Cost Iterative Equalization In Coded Linear Systems With Cyclic Prefixes, Xiaojun Yuan, Qinghua Guo, Xiaodong Wang, Li Ping
Faculty of Engineering and Information Sciences - Papers: Part A
This paper is concerned with the low-cost iterative equalization/detection principles for coded linear systems with cyclic prefixes. Turbo frequency-domain-equalization (FDE) is applied to systems that may contain the joint effect of multiple-access interference (MAI), cross-antenna interference (CAI) and inter-symbol interference (ISI). We develop an SNK-variance evolution technique for the performance evaluation of the proposed systems. Numerical results in various channel environments demonstrate excellent agreement between the predicted and simulated system performance. © 2008 IEEE.
Impact Of Signaling Schemes On Iterative Linear Minimum-Mean-Square-Error Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Impact Of Signaling Schemes On Iterative Linear Minimum-Mean-Square-Error Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, we study the iterative detection problem for a coded system with multi-ary modulation. We show that, with iterative linear minimum-mean-square-error (LMMSE) detection, superposition coded modulation (SCM) can provide performance superior to that with other traditional signaling schemes used in trellis coded modulation (TCM) and bit-interleaved coded modulation (BICM). This finding provides a useful guideline for system design considering inter-symbol interference (ISI) and other forms of interference. Simulation results are provided to illustrate the efficiency of the iterative LMMSE detection with different signaling schemes. © 2008 IEEE.
Joint Linear Interleaver Design For Concatenated Zigzag Codes, D S. Lin, S Tong, S Q. Li
Joint Linear Interleaver Design For Concatenated Zigzag Codes, D S. Lin, S Tong, S Q. Li
Faculty of Engineering and Information Sciences - Papers: Part A
The design of a class of well-structured low-density parity-check (LDPC) codes, namely linear interleaver based concatenated zigzag (LICZ) codes, is investigated. With summary distances as the design metric, short LICZ codes with large minimum distances can be constructed. Moreover, an efficient cycle-based method is proposed to compute the minimum distances of LICZ codes. Simulation results show that LICZ codes outperform both CZ codes with random interleavers and LDPC codes by the progressive edge growth algorithm.
Performance Analysis Of Multi-Ary Systems With Iterative Linear Minimum-Mean-Square-Error Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Performance Analysis Of Multi-Ary Systems With Iterative Linear Minimum-Mean-Square-Error Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Faculty of Engineering and Information Sciences - Papers: Part A
This paper is concerned with coded multi-ary systems over linear channels. Based on a semi-analytical evolution technique, the impact of signaling schemes on the performance of low-cost iterative linear minimum-mean-square-error (LMMSE) detection is studied. It is shown that superposition coded modulation (SCM) maximizes the output signal-to-noise ratio (SNR) of LMMSE detectors. Consequently, SCM may potentially outperform other conventional signaling schemes when LMMSE detectors are used. Numerical examples are provided to verify the theoretical analysis. © 2008 IEEE.
Psdboost: Matrix-Generation Linear Programming For Positive Semidefinite Matrices Learning, Chunhua Shen, Alan Welsh, Lei Wang
Psdboost: Matrix-Generation Linear Programming For Positive Semidefinite Matrices Learning, Chunhua Shen, Alan Welsh, Lei Wang
Faculty of Engineering and Information Sciences - Papers: Part A
In this work, we consider the problem of learning a positive semidefinite matrix. The critical issue is how to preserve positive semidefiniteness during the course of learning. Our algorithm is mainly inspired by LPBoost [1] and the general greedy convex optimization framework of Zhang [2]. We demonstrate the essence of the algorithm, termed PSDBoost (positive semidefinite Boosting), by focusing on a few different applications in machine learning. The proposed PSDBoost algorithm extends traditional Boosting algorithms in that its parameter is a positive semidefinite matrix with trace being one instead of a classifier. PSDBoost is based on the observation that any …
Evolution Analysis Of Iterative Lmmse-App Detection For Coded Linear System With Cyclic Prefixes, Xiaojun Yuan, Qinghua Guo, Li Ping
Evolution Analysis Of Iterative Lmmse-App Detection For Coded Linear System With Cyclic Prefixes, Xiaojun Yuan, Qinghua Guo, Li Ping
Faculty of Engineering and Information Sciences - Papers: Part A
This paper is concerned with the iterative detection principles for coded linear systems with cyclic prefixes. We derive a matrix-form low-cost fast Fourier transform (FFT) based iterative LMMSE-APP detector and propose an evolution technique for the performance evaluation of the proposed detector. Numerical results show a good match between simulation and evolution prediction. ©2007 IEEE.
Gaussian Message Passing On Linear Models: An Update, Hans-Andrea Loeliger, Junli Hu, Sascha Korl, Qinghua Guo, Li Ping
Gaussian Message Passing On Linear Models: An Update, Hans-Andrea Loeliger, Junli Hu, Sascha Korl, Qinghua Guo, Li Ping
Faculty of Engineering and Information Sciences - Papers: Part A
This semi-tutorial paper considers message passing algorithms on factor graphs of linear Gaussian models. Freshly polished tables of message computation rules are given and their use is demonstrated for soft-in soft-out equalization.
Linear Code Implies Publicf-Key Traitor Tracing With Revocation, Joseph Tonien, Rei Safavi-Naini
Linear Code Implies Publicf-Key Traitor Tracing With Revocation, Joseph Tonien, Rei Safavi-Naini
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, we show that the linear-coded Kurosawa–Desmedt scheme can be modified to allow revocation of users, that is to show a revocation scheme can be derived from a linear code.
Convergence Of Eigenvalues In State-Discretization Of Linear Stochastic Systems, Jose A. De Dona, Graham C. Goodwin, Richard H. Middleton, Iain Raeburn
Convergence Of Eigenvalues In State-Discretization Of Linear Stochastic Systems, Jose A. De Dona, Graham C. Goodwin, Richard H. Middleton, Iain Raeburn
Faculty of Engineering and Information Sciences - Papers: Part A
The transition operator that describes the time evolution of the state probability distribution for continuous-state linear systems is given by an integral operator. A state-discretization approach is proposed, which consists of a finite rank approximation of this integral operator. As a result of the state-discretization procedure, a Markov chain is obtained, in which case the transition operator is represented by a transition matrix. Spectral properties of the integral operator for the continuous-state case are presented. The relationships between the integral operator and the finite rank approximation are explored. In particular, the limiting properties of the eigenvalues of the transition matrices …