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This study aims to examine the evolution of spatial–temporal patterns in China’s hotel industry from 1978 to 2018.

A database comprising over 140,000 hotels with more than 30 rooms was created. The exploratory spatial–temporal data analysis (ESTDA) method, based on space–time cube model, was used to explore and visualize the spatial–temporal pattern of hotels.

The Chinese hotel industry can be divided into two development stages, namely, a large hotel-dominant stage before 2000 and a small–medium-sized hotel-dominant stage after 2000. China’s prefecture-level cities were clustered into four tiers. The higher the tier, the earlier the city will initiate hotel development. The Chinese hotel industry has four continuous hotspots (the Yangtze River Delta, Pearl River Delta, Bohai Rim and Sichuan and Chongqing) and some temporary hotspots.

This study lacks quantitative investigation, which could show the underlying mechanism of the evolution of the Chinese hotel industry.

This study is the first to investigate China’s hotel evolution over 40 years by applying big data and the ESTDA method. The systematic and evolutionary exploration will enable hotel researchers to understand the spatial–temporal nature of hotel distribution better. Introducing the ESTDA method into tourism and hotel research also provides an additional tool to researchers. Hotel investors and operators, city and tourism planners and market regulators can learn from the evolution of location patterns to make better where and when decisions.

The spatial feature is important for scene saliency detection. Scene-based visual saliency detection methods fail to incorporate 3D scene spatial aspects. This paper aims to propose a cube-based method to improve saliency detection through integrating visual and spatial features in 3D scenes.

In the presented approach, a multiscale cube pyramid is used to organize the 3D image scene and mesh model. Each 3D cube in this pyramid represents a space unit similar to a pixel in the image saliency model multiscale image pyramid. In each 3D cube color, intensity and orientation features are extracted from the image and a quantitative concave–convex descriptor is extracted from the 3D space. A Gaussian filter is then used on this pyramid of cubes with an extended center-surround difference introduced to compute the cube-based 3D scene saliency.

The precision-recall rate and receiver operating characteristic curve is used to evaluate the method and other state-of-art methods. The results show that the method used is better than traditional image-based methods, especially for 3D scenes.

This paper presents a method that improves the image-based visual saliency model.

This paper aims to semantically linking scientific research events implied by scientific and technical literature to support information analysis and information service applications. Literature research is an important method to acquire scientific and technical information which is important for research, development and innovation of science and technology. It is difficult but urgently required to acquire accurate, timely, rapid, short and comprehensive information from the large-scale and fast-growing literature, especially in the big data era. Existing literature-based information retrieval systems focus on basic data organization, and they are far from meeting the needs of information analytics. It becomes urgent to organize and analyze scientific research events related to scientific and technical literature for forecasting development trend of science and technology.

Scientific literature such as a paper or a patent is represented as a scientific research event, which contains elements including when, where, who, what, how and why. Metadata of literature is used to formulate scientific research events that are implied in introduction and related work sections of literature. Named entities and research objects such as methods, materials and algorithms can be extracted from texts of literature by using text analysis. The authors semantically link scientific research events, entities and objects, and then, they construct the event space for supporting scientific and technical information analysis.

This paper represents scientific literature as events, which are coarse-grained units comparing with entities and relations in current information organizations. Events and semantic relations among them together formulate a semantic link network, which could support event-centric information browsing, search and recommendation.

The proposed model is a theoretical model, and it needs to verify the efficiency in further experimental application research. The evaluation and applications of semantic link network of scientific research events are further research issues.

This paper regards scientific literature as scientific research events and proposes an approach to semantically link events into a network with multiple-typed entities and relations. According to the needs of scientific and technical information analysis, scientific research events are organized into event cubes which are distributed in a three-dimensioned space for easy-to-understand and information visualization.

Although extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for transportation cost optimization. Traditional irregular component loading methods are based on past performance, which frequently wastes vehicle space. Additionally, real-time road conditions, precast component assembly times, and delivery vehicle waiting times due to equipment constraints at the construction site affect transportation time and overall transportation costs. Therefore, this paper aims to provide an optimization model for Just-In-Time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time.

In order to propose a JIT (just-in-time) delivery optimization model, the effects of the sizes of irregular precast components, the assembly time, and the loading methods are considered in the 3D loading constraint model. In addition, for JIT delivery, incorporating real-time road conditions in the transportation process is essential to mitigate delays in the delivery of precast components. The 3D precast component loading problem is solved by using a hybrid genetic algorithm which mixes the genetic algorithm and the simulated annealing algorithm.

A real case study was used to validate the JIT delivery optimization model. The results indicated this study contributes to the optimization of strategies for loading irregular precast components and the reduction of transportation costs by 5.38%.

This study establishes a JIT delivery optimization model with the aim of reducing transportation costs by considering 3D loading constraints, real-time road conditions and assembly time. The irregular precast component is simplified into 3D bounding box and loaded with three-space division heuristic packing algorithm. In addition, the hybrid algorithm mixing the genetic algorithm and the simulated annealing algorithm is to solve the 3D container loading problem, which provides both global search capability and the ability to perform local searching. The JIT delivery optimization model can provide decision-makers with a more comprehensive and economical strategy for loading and transporting irregular precast components.

This paper seeks to develop universal software (a programming framework) enabling the implementation of service robot controllers. The software should distinguish the hardware‐oriented part of the system from the task‐oriented one. Moreover, force, vision as well as other sensors should be taken into account. Multi‐effector systems have to be considered.

The robot programming framework MRROC++ has been implemented as a hierarchical structure composed of processes, potentially consisting of threads. All of the software is written in an object‐oriented manner using C++ and is supervised by a QNX real‐time operating system. The framework has been verified on several systems executing diverse tasks. Here, a Rubik's cube puzzle‐solving system, consisting of two arms and utilizing force control and visual servos, is presented.

The presented framework is well suited to tasks requiring two‐handed manipulation with force sensing, visual servoing and online construction of plans of actions. The Rubik's cube puzzle is a reasonable initial benchmark for validation of fundamental service robot capabilities. It requires force sensing and sight coupled with two‐handed manipulation and logical reasoning, as do the majority of service tasks. Owing to the use of force sensing during manipulation, jamming of the faces has always been avoided; however, visual servoing could only cope with slow handing over of the cube due to the volume of computations associated with vision processing.

The proposed software structure does not limit the implementation of service robot controllers. However, some of the specific algorithms used for the solution of the benchmark task (i.e. Rubik's cube puzzle) need to be less time‐consuming.

The MRROC++ robot programming framework can be applied to the implementation of diverse robot controllers executing complex service tasks.

A demanding benchmark task for service robots has been formulated. This task, as well as many others, has been used to validate the MRROC++ robot programming framework which significantly facilitates the implementation of diverse robot systems.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

The purpose of this paper is to suggest a formalism given by an equation suitable for simulating discrete systems with space-time variation in addition to other change variables. With such formalism, multidimensional dynamical models of discrete complex systems, such as the social systems and ecosystems, can be built.

This formalism is named as discrete multidimensional dynamic system (DMDS). The DMDS provides a way to consider the variation of the density of a state variable with regard to the variables of the change space as a function of multidimensional rates. Multidimensional rates describe this evolution as a consequence of the relation of each multidimensional-point with a given set of other points of the change space. This relation contains the accessibility domains (sets of space points with which each space point is related).

This equation is compared with both the reaction-diffusion equation written in its finite difference form and the cellular-automata model, demonstrating its compatibility with them and an increase in generality, widening the scope of application. The steps to construct models of systems with multidimensional variation based on the equation that defines the DMDS are specified and tested.

Through the DMDS and a well-stated methodology, an application case is provided in order to describe the multidimensional demographic dynamics of an urban system. In this case, the numerical evolution of the population density by districts and cohorts is determined by the DMDS based on some hypothesis about functions of population diffusion between the different districts of the system.

The scope of application of the space-time dynamic system (STDS), given by the authors in a previous work, has been extended to discrete and multidimensional systems. STDS model produces better results than the reaction-diffusion model in validation.

Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

This study shows various pathways manufacturers can take when embarking on digital servitization (DS) journeys. It builds on the DS and modularity literature to map the strategic trajectories of product–service–software (PSSw) configurations.

The study is exploratory and based on the inductive theory building method. The empirical data were gathered through a workshop with focus groups of 15 servitization manufacturers (with 22 respondents), an on-site workshop (in-depth case study), semi-structured interviews, observations and document study of archival data.

The DS trajectories are idiosyncratic and dependent on design architectures of PSSw modules, balancing choices between standardization and innovation. The adoption of software systems depends on the maturity of the industry-specific digital ecosystem. Decomposition and integration of PSSw modules facilitate DS transition through business model modularity. Seven testable propositions are presented.

With the small sample size from different industries and one in-depth case study, generalizing the findings was not possible.

The mapping exercise is powerful when top management from different functional departments can participate together to share their expertise and achieve consensus. It logs the “states” that the manufacturer undergoes over time.

The Digital Servitization Cube serves as a conceptual framework for manufacturers to systematically map and categorize their current and future PSSw strategies. It bridges the cross-disciplinary theoretical discussion in DS.