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The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics.

In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration.

The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments.

The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.

In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of feature extraction is used in two cases: application-based feature expression and mathematical approaches for dimensionality reduction. Feature expression is a technique of describing the image color, texture and shape information with feature descriptors; thus, obtaining effective image features expression is the key to extracting high-level semantic information. However, most of the previous studies regarding image feature extraction and expression methods in the CBIR have not performed systematic research. This paper aims to introduce the basic image low-level feature expression techniques for color, texture and shape features that have been developed in recent years.

First, this review outlines the development process and expounds the principle of various image feature extraction methods, such as color, texture and shape feature expression. Second, some of the most commonly used image low-level expression algorithms are implemented, and the benefits and drawbacks are summarized. Third, the effectiveness of the global and local features in image retrieval, including some classical models and their illustrations provided by part of our experiment, are analyzed. Fourth, the sparse representation and similarity measurement methods are introduced, and the retrieval performance of statistical methods is evaluated and compared.

The core of this survey is to review the state of the image low-level expression methods and study the pros and cons of each method, their applicable occasions and certain implementation measures. This review notes that image peculiarities of single-feature descriptions may lead to unsatisfactory image retrieval capabilities, which have significant singularity and considerable limitations and challenges in the CBIR.

A comprehensive review of the latest developments in image retrieval using low-level feature expression techniques is provided in this paper. This review not only introduces the major approaches for image low-level feature expression but also supplies a pertinent reference for those engaging in research regarding image feature extraction.

This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images.

A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features.

According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision.

This paper presents a novel remote sensing image retrieval method based on VSP features.

This paper aims to present the spherical entropy image (SEI), a novel global descriptor for the scan registration of three-dimensional (3D) point clouds. This paper also introduces a global feature-less scan registration strategy based on SEI. It is advantageous for 3D data processing in the scenarios such as mobile robotics and reverse engineering.

The descriptor works through representing the scan by a spherical function named SEI, whose properties allow to decompose the six-dimensional transformation into 3D rotation and 3D translation. The 3D rotation is estimated by the generalized convolution theorem based on the spherical Fourier transform of SEI. Then, the translation recovery is determined by phase only matched filtering.

No explicit features and planar segments should be contained in the input data of the method. The experimental results illustrate the parameter independence, high reliability and efficiency of the novel algorithm in registration of feature-less scans.

A novel global descriptor (SEI) for the scan registration of 3D point clouds is presented. It inherits both descriptive power of signature-based methods and robustness of histogram-based methods. A high reliability and efficiency registration method of scans based on SEI is also demonstrated.

Large amount of data are stored in image format. Image retrieval from bulk databases has become a hot research topic. An alternative method for efficient image retrieval is proposed based on a combination of texture and colour information. The main purpose of this paper is to propose a new content based image retrieval approach using combination of color and texture information in spatial and transform domains jointly.

Various methods are provided for image retrieval, which try to extract the image contents based on texture, colour and shape. The proposed image retrieval method extracts global and local texture and colour information in two spatial and frequency domains. In this way, image is filtered by Gaussian filter, then co-occurrence matrices are made in different directions and the statistical features are extracted. The purpose of this phase is to extract noise-resistant local textures. Then the quantised histogram is produced to extract global colour information in the spatial domain. Also, Gabor filter banks are used to extract local texture features in the frequency domain. After concatenating the extracted features and using the normalised Euclidean criterion, retrieval is performed.

The performance of the proposed method is evaluated based on the precision, recall and run time measures on the Simplicity database. It is compared with many efficient methods of this field. The comparison results showed that the proposed method provides higher precision than many existing methods.

The comparison results showed that the proposed method provides higher precision than many existing methods. Rotation invariant, scale invariant and low sensitivity to noise are some advantages of the proposed method. The run time of the proposed method is within the usual time frame of algorithms in this domain, which indicates that the proposed method can be used online.

The aim of this study was to first establish foundational algebraic expressions that parametrically describe any advanced dual-energy storage–propulsion–power system (DESPPS) and then proceed to declare the array of fundamental independent variables necessary for the sizing and optimisation of such systems. Upon procurement of a pre-design-level integrated aircraft performance model and the subsequent verification against previously published high-end low-fidelity generated results, opportunity was taken in formulating a set of battery-based DESPPS related design axioms and sizing heuristics.

Derivation of algebraic expressions related to describing DESPPS architectures are based on first principles. Integrated performance modelling by way of full analytical fractional change transformations anchored according to a previously published Energy Specific Air Range (ESAR) figure-of-merit originally derived using the Breguet–Coffin differential equation for vehicular efficiency. Weights prediction of sub-systems that constitute the entire aircraft including DESPPS constituents emphasises an analytical foundation with minimal implementation of linear correlation factors or coefficients of proportionality. An iterative maximum take-off weight build-up algorithm emphasising expedient and stable convergence was fashioned. All prediction methods pertaining to integrated performance were verified according to previously published battery-based DESPPS results utilising high-end low-fidelity methods.

For all types of DESPPS, two new fundamental independent non-dimensional variables were declared: the Supplied Power Ratio (related to converted power afforded by each energy carrier); and, the Activation Ratio (describing the relative nature of utilisation with respect to time afforded by the motive power device associated with each energy source). For a given set of standalone sub-system energy conversion efficiencies, the parametric descriptor of degree-of-hybridisation (DoH) for Power was found to be solely a function of the Supplied Power Ratio, whereas in contrast, the DoH for Energy was found to be a more complex synthetic function described by comingling of Supplied Power Ratio and the Activation Ratio. Upon examination of the integrated aircraft performance model derived in this treatise, for purposes of investigating CO₂-emissions reduction potential for battery-based DESPPS using kerosene as one of the energy sources, one salient observation was maximising the ESAR figure-of-merit is not an appropriate objective or intermediary function for future optimisation work. It was found maximising block fuel reduction through the use of maximum ESAR would lead to ever diminishing design ranges and curtailment of the payload-range working capacity of the aircraft.

Opportunity is now given to design and optimise aircraft utilising any type of DESPPS architecture. It was established that designing for battery-based DESPPS aircraft can be achieved effectively in a two-stage process that may not require aircraft morphologies more exotic than the so-called “wing-and-tube”. Firstly, a suitably projected state-of-the-art aircraft with solely advanced gas-turbine technology for the propulsion and power system needs to be produced. Thereafter, a revised version of this baseline projected aircraft now using DESPPS architecture should be conceived. A recommendation related to CO₂-emissions reduction potential for battery-based DESPPS using kerosene as one of the energy sources is that during optimisation work the multi-objective formulation should comprise at least two functions: block fuel and operating economics. In all instances, it was advised that the objective function of block fuel should be tempered by an equality constraint of ESAR parity with the baseline projected aircraft using gas-turbine only technology.

A complete, unified analytical description of DESPPS that is universally applicable to any type of energy carrier has been derived and verified for battery-based dual-energy systems. Correspondingly, a set of aircraft design axioms and sizing heuristics relevant to battery-based DESPPS have been presented.

Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

The purpose of this paper is to focus on two questions that are especially pertinent to international marketers. Is a strong ethnic identity (EID) generally incompatible with a globally‐oriented disposition (cosmopolitanism: COS), and to what extent is the EID‐COS relationship stable across cultures and countries? What roles do EID and COS play on consumer behavior alongside key demographic variables, and how do these relationships vary across countries and across consumption contexts?

Using a sample of consumers drawn from eight countries, this study identifies and compares bases for international market segmentation. The antecedent roles of EID, COS, and the four demographics variables on the behaviors associated with nine product categories are examined.

The findings imply that consumers are complementing an identity rooted in their traditional culture with one that is globally‐oriented. The roles played by demographic and psychographic variables varied considerably, not only across product categories, but moreover, across country samples.

The study focuses more on consumer goods and less on intangible services. The sample and sampling approach place some limits on generalizability.

The results provide insights for international managers into when (i.e. product categories) and where (i.e. locations) marketing strategies could be standardized across national frontiers, and when and where these strategies should be customized or “glocalized.”

The paper makes a significant contribution to the international market segmentation literature, demonstrating the variable impact of demographics and identity across consumer behaviors. The findings bolster the notion that many cultures have the innate facility to glocalize, that is, to absorb foreign or global ideas with the best practices and bond these with native customs. The results further imply that globalization takes on many forms throughout the world.

Spatial autocorrelation in regression residuals is a major issue for the modeller because it disturbs parameter estimates and invalidates the reliability of conclusions drawn from models. The purpose of this paper is to develop an approach which generates new spatial predictors that can be mapped and qualitatively analysed while controlling for spatial autocorrelation among residuals.

This paper explores an alternate approach using a Fourier polynomial function based on geographical coordinates to construct an additional spatial predictor that allows to capture the latent spatial pattern hidden among residuals. An empirical validation based on hedonic modelling of sale prices variation using a large dataset of house transactions is provided.

Results show that the spatial autocorrelation problem is under control as shown by low Moran's I indexes. Moreover, this geo‐statistical approach provides coefficients on environmental amenities that are still highly significant by capturing only the remaining spatial autocorrelation.

The originality of this paper relies on the development of a new model that allows considering, simultaneously spatial and time dimension while measuring the marginal impact of environmental amenities on house prices avoiding competition with the weight matrix needed in most spatial econometric models.