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Detecting and tracking the position of a mobile user has become one of the important subjects in many mobile applications. Such applications use location based services (LBS) for learning and training user movements in different places (cities, markets, airports, stations) along different modes of transport (bus, car, cycle, walk). To date, GPS is the key solution to all LBS but repeated GPS querying is not economical in terms of the battery life of the mobile phone. The purpose of this paper is to study how cheap and energy‐efficient air pressure sensors measuring the altitude could be used, as a complement to the dominant GPS system. The location detection and route tracking task is then accomplished by matching the collected altitude traces with the altitude curves of stored data to find the best matching routes.

The cornerstone of the authors' approach is that a huge amount of route data, collected with GPS devices, is available in various cloud services. In order to evaluate the mechanism of matching routes with altitude data, the authors build a prototype system of crowd‐sourced database containing only altitude data of different routes along different modes of transport. How accurately this stored altitude data could be matched with the collected altitude traces is the key question of this study.

Results show that, within a certain level of accuracy, older repeated routes can be detected from newly tracked altitude traces. Further, the level of accuracy varies depending on the length of path traversed, route curvature, speed of travel and sensor used for tracking.

The new contribution in this paper is to propose an alternative route detection mechanism which minimizes the use of GPS query. This concept will help in retrieving the GPS coordinates of already traversed routes stored in a large database by matching them with currently tracked altitude curves.

Recently, service robots have been widely used in various fields. The purpose of this paper is to design a restaurant service robot which could be applicable to provide basic service, such as ordering, fetching and sending food, settlement and so on, for the customers in the robot restaurant.

Based on characteristics of wheeled mobile robots, the service robot with two manipulators is designed. Constrained by the DOF, the final positioning accuracy within ±3 cm must be guaranteed to successfully grasp the plate. Segmented positioning method is applied considering the positioning costs and accuracy requirement in the different stages, and the shape‐based matching tracking method is adopted to navigate the robot to the object.

Experiments indicate that the service robot could successfully grasp the plate, from wherever is its initial position; and the proposed algorithms could estimate the robot pose well and accurately evaluate the localization performance.

At present, the service robot could only work in an indoor environment where there is steady illumination.

The service robot is applicable to provide basic service for the customers in the robot restaurant.

The paper gives us a concept of a restaurant service robot and its localization and navigation algorithms. The service robot could provide its real‐time coordinates and arrive at the object with ±2 cm positioning precision, from wherever is its initial position.

Maps can be challenging to reference librarians, especially to those without the specialized skills needed for working with the material. Such is the same with maps found on the Internet. Finding, using, saving, or printing maps requires different strategies than those taken with other online documents. This article discusses the value of electronic maps, will help to form accurate expectations as to what one should expect to find, and cover some useful Internet sites for finding freely available general maps. Last, some strategies in working with large graphic files will assist reference librarians in putting electronic maps into the hands of their patrons.

This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude, with a focus on assessing the role of feeling right as a mediator and service failure as a moderator.

This paper tested the hypotheses through three experiments and a Supplementary Material experiment, which collectively involved 835 participants.

The results indicated that the adoption of AI by cool brands can foster the right feeling and enhance consumers’ positive brand attitudes. In contrast, employing human staff did not lead to improved brand attitudes toward non-cool brands. Furthermore, the study found that service failure moderated the matching effect between service agents and cool brand images on brand attitude. The matching effect was observed under successful service conditions, but it disappeared when service failure occurred.

The findings offer practical guidance for hospitality companies in choosing service agents based on brand image. Cool brands can swiftly transition to AI, reinforcing their modern, cutting-edge image. Traditional brands may delay AI adoption or integrate it strategically with human staff.

To the best of the authors’ knowledge, this paper represents one of the first studies to address the issue of selecting the optimal service agent based on hospitality brand image. More importantly, it introduces the concept of a cool hospitality brand image as a boundary condition in the framework of AI research, providing novel insights into consumers’ ambivalent responses to AI observed in previous studies.

We have succeeded in capturing porcine 3D surface anatomy in vivo by developing a high‐resolution stereo imaging system. The system achieved accurate 3D shape recovery by matching stereo pair images containing only natural surface textures at high (image) resolution. The 3D imaging system presented for pig shape capture is based on photogrammetry and comprises: stereo pair image acquisition, stereo camera calibration and stereo matching and surface and texture integration. Practical issues have been addressed, and in particular the integration of multiple range images into a single 3D surface. Robust image segmentation successfully isolated the pigs within the stereo images and was employed in conjunction with depth discontinuity detection to facilitate the integration process. The capture and processing chain is detailed here and the resulting 3D pig anatomy obtained using the system presented.

An automatic garment pattern generation system has been developed for the three‐dimensional apparel CAD system. To substitute the garment fitting process, which requires lots of trial and error in the traditional pattern generation methods, we developed a new direct pattern generation method using body‐garment shape matching process. In this method, we first generated a body model using three‐dimensionally measured anthropometric data and transformed it to have a convex shape similar to that of a commonly used dummy model in garment design process. Then a typical garment model has been defined by measuring the surface information of a dummy model using stereoscopy and adjusting its shape considering the geometrical constraints of the underlying body model to obtain the optimum fit garment patterns. Finally, we developed a pattern flattening algorithm that flattens the three‐dimensionally adjusted garment model into two‐dimensional patterns considering the anisotropic properties of the fabric to be used.

Before a trade mark can be registered at the UK Patent Office, registrars need to ensure it isn't confusingly similar to any of 300,000 existing marks in the Registry's database. Many trade marks take the form of abstract geometric designs that are especially difficult for indexers and searchers to describe. ARTISAN, developed at the University of Northumbria, is a system that allows such marks to be indexed and retrieved automatically, on the basis of their shape. Evaluative studies have demonstrated the feasibility of this approach, and the newly‐established Institute for Image Data Research plans further development.

This paper aims to contribute to knowledge by investigating the return behaviour of seven global real estate investment trusts (REITs) with respect to the appropriate distributional fit that captures tail and shape characteristics. The study adds to the knowledge of distributional properties of seven global REITs by using the generalised lambda distribution (GLD), which captures fairly well the higher moments of the returns.

This is an empirical study with GLD through three rival methods of fitting tail and shape properties of seven REIT return data from January 2008 to November 2017. A post-Global Financial Crisis (GFC) (from July 2009) period fits from the same methods are juxtaposed for comparison.

The maximum likelihood estimates outperform the methods of moment matching and quantile matching in terms of goodness-of-fit in line with extant literature; for the post-GFC period as against the full-sample period. All three methods fit better in full-sample period than post-GFC period for all seven countries for the Region 4 support dynamics. Further, USA and Singapore possess the strongest and stronger infinite supports for both time regimes.

The REITs markets, however, developed, are of wide varied sizes. This makes comparison less than ideal. This is mitigated by a univariate analysis rather than multivariate one.

This paper is a reminder of the inadequacy of the normal distribution, as well as the mean, variance, skewness and kurtosis measures, in describing distributions of asset returns. Investors and policymakers may look at the location and scale of GLD for decision-making about REITs.

The novelty of this work lies with the data used and the detailed analysis and for the post-GFC sample.

Aims to report a novel method of estimating the geometric manipulation to which present day data hiding is subjected.

Computes the feature points matching measure for the geometric manipulation using shape‐specific points. The feature points matching is realized by simulated annealing algorithm.

Finds that the purposed scheme does not require the original image because reference point information on the original image has been contained in the secret key.

Experiments herein have proved the method's robustness in face of geometric attacks and a new way of designing a better blind secret message decodes has been revealed.

To develop an image processing approach for jigsaw puzzle assembly.

First, pixels are extracted from the jigsaw puzzle blocks to calculate their rotation angles and centre coordinates. Second, a template matching method is employed to recognise each block and its orientation.

A robot‐based jigsaw puzzle system is established; and an effective image processing approach for assembly is developed.

Automatic assembly lines that assemble parts with the same shape, but random position and angle, can employ the jigsaw puzzle assembly method.

An effective image processing method for jigsaw puzzle assembly is presented in this paper. The validity of the method is proved by analysis and experiment.