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Shrinking population can have significant negative impacts on the social and economic fabric of a city. This paper aims to understand different urban transportation policies to respond to population decline in shrinking cities by examining two case studies of urban interventions in mid-size cities in Japan.

The paper analyzes the implementation of sustainable mobility strategies in the urban transport sector in the Japanese cities of Toyama and Kanazawa, which risk having their populations significantly reduced in the next decades. The analysis is based on case study research that uses the data and information collected through desk and field research. Interviews with local actors, as well as published policy and academic documents on the case studies provided critical data and information to analyze the case studies.

Both cities have tried to make urban mobility more sustainable via different strategies. Toyama used more structural changes, called the “sticks and dumplings” approach, having land use incentives and the Light Rail Transit reinforced by bus routes as the backbone of its strategy. Kanazawa relied on a city center revitalization plan to densify residential use in the city center.

More structural interventions are necessary to change the declining of shrinking cities, mitigating some of the negative effects. City administrations need to have clear policy priorities and should not allocate their limited resources to competing policy agendas.

The study is unique as it is one of the first efforts to analyze urban transportation interventions in shrinking cities in Japan.

The combination method, combined finite element‐boundary element approach, is suitable for unbounded field problems. Although this technique attains a high degree of accuracy, the matrix of the discretized system equation is not banded but sometimes densely or sparsely populated. We reported the development of an infinite boundary element for 2‐D Laplace problems, with which the bandwidth of the discretized system matrix does not increase beyond that of the finite element region. In this paper, we extend this approach and propose another infinite boundary element for 2‐D Helmholtz problems. To illustrate the validity of the proposed technique, some numerical examples are given and their results are compared with those of other methods.

A technique combining finite elements and boundary elements is promising for unbounded field problems. A hypothetical boundary is assumed in the unbounded domain, and the usual finite element method is applied to the inner region, while the boundary element method is applied to the outer infinite region. On the coupling boundary, therefore, both potential and flux must be compatible. In the finite element method, the flux is defined as the derivative of the potential for which a trial function is defined. In the boundary element method, on the other hand, the same polynomial function is chosen for the potential and the flux. Thus, the compatibility cannot be satisfied unless a special device is considered. In the present paper, several compatibility conditions are discussed concerning the total flux or energy flow continuity across the coupling boundary. Some numerical examples of Poisson and Helmholtz problems are demonstrated.

The boundary element method is a useful method for the analysis of field problems involving unbounded regions. Therefore, the method can be used advantageously in combination with the finite element method. This is sometimes called a combination method and it is suitable as a picture‐frame technique. Although this technique attains good accuracy, the matrix of the discretized equation is not banded, since it is a dense matrix. In this paper, we propose an infinite boundary element which divides the unbounded region radially. By the use of this element, the bandwidth of the discretized system matrix does not increase beyond that of the finite element region and its original matrix structure is maintained. The infinite boundary element can also be applied to homogeneous unbounded field problems, for which the Green's function of the mirror image is difficult to use. To illustrate the validity of the proposed technique, some numerical calculations are demonstrated and the results are compared with those of the usual combination method and the method using the hybrid‐type infinite element.

The purpose of this study is to develop a cost-effective autonomous wheelchair robot navigation method that assists the aging population.

Navigation in outdoor environments is still a challenging task for an autonomous mobile robot because of the highly unstructured and different characteristics of outdoor environments. This study examines a complete vision guided real-time approach for robot navigation in urban roads based on drivable road area detection by using deep learning. During navigation, the camera takes a snapshot of the road, and the captured image is then converted into an illuminant invariant image. Subsequently, a deep belief neural network considers this image as an input. It extracts additional discriminative abstract features by using general purpose learning procedure for detection. During obstacle avoidance, the robot measures the distance from the obstacle position by using estimated parameters of the calibrated camera, and it performs navigation by avoiding obstacles.

The developed method is implemented on a wheelchair robot, and it is verified by navigating the wheelchair robot on different types of urban curve roads. Navigation in real environments indicates that the wheelchair robot can move safely from one place to another. The navigation performance of the developed method and a comparison with laser range finder (LRF)-based methods were demonstrated through experiments.

This study develops a cost-effective navigation method by using a single camera. Additionally, it utilizes the advantages of deep learning techniques for robust classification of the drivable road area. It performs better in terms of navigation when compared to LRF-based methods in LRF-denied environments.

Materials with anisotropic conductivity are frequently used as sensors in electrical industries. In this paper, an anisotropic conductivity tensor to express Hall effect in n‐type semiconductors is derived and its steady‐current field is solved using the finite element method. Some numerical examples are given and comparison with measured data is discussed.

Development of autonomous robot manipulator for human-robot assembly tasks is a key component to reach high effectiveness. In such tasks, the robot real-time object recognition is crucial. In addition, the need for simple and safe teaching techniques need to be considered, because: small size robot manipulators’ presence in everyday life environments is increasing requiring non-expert operators to teach the robot; and in small size applications, the operator has to teach several different motions in a short time.

For object recognition, the authors propose a deep belief neural network (DBNN)-based approach. The captured camera image is used as the input of the DBNN. The DBNN extracts the object features in the intermediate layers. In addition, the authors developed three teaching systems which utilize iPhone; haptic; and Kinect devices.

The object recognition by DBNN is robust for real-time applications. The robot picks up the object required by the user and places it in the target location. Three developed teaching systems are easy to use by non-experienced subjects, and they show different performance in terms of time to complete the task and accuracy.

The proposed method can ease the use of robot manipulators helping non-experienced users completing different assembly tasks.

This work applies DBNN for object recognition and three intuitive systems for teaching robot manipulators.

The purpose of this paper is to compare the performance of the robot arm motion generated by neural controllers in simulated and real robot experiments.

The arm motion generation is formulated as an optimization problem. The neural controllers generate the robot arm motion in dynamic environments optimizing three different objective functions; minimum execution time, minimum distance and minimum acceleration. In addition, the robot motion generation in the presence of obstacles is also considered.

The robot is able to adapt its arm motion generation based on the specific task, reaching the goal position in simulated and experimental tests. The same neural controller can be employed to generate the robot motion for a wide range of initial and goal positions.

The motion generated yield good results in both simulation and experimental environments.

The robot motion is generated based on three different objective functions that are simultaneously optimized. Therefore, the humanoid robot can perform a wide range of tasks in real-life environments, by selecting the appropriate motion.

A new method for adaptive arm motion generation of a mobile humanoid robot operating in dynamic human and industrial environments.

The purpose of this study was to explore school principals’ job crafting profiles during the prolonged COVID-19 crisis in 2021, and investigate profile differences regarding principals’ own perceived servant leadership, stress and work meaningfulness.

Using latent profile analysis (LPA), two job crafting profiles were identified: (1) active crafters (55%) and (2) average crafters (45%). By auxiliary measurement-error-weighted-method (BCH), we examined whether and how job crafting profiles differed in terms of servant leadership, stress and work meaningfulness.

Active crafters reported higher than the overall mean level of approach-oriented job crafting (increasing job resources and demands), whereas average crafters reported an overall mean level of approach-oriented job crafting. Avoidance-oriented job crafting by decreasing hindering job demands did not differentiate the two profiles. Active crafters reported significantly higher servant leadership behavior, stress and work meaningfulness than average crafters.

Study findings provide new knowledge and reflect the implications that the unprecedented pandemic had for education. This study contributes to the existing literature within the scholarship of job crafting through empirical research during the prolonged COVID-19 pandemic. For practitioners, these study findings reflect contextual constraints, organizational processes and culture, and leadership in workplaces.

Ion‐acoustic wave propagation in plasma is discussed. Analytical and numerical solutions are given for one‐dimensional plane waves. The similarity of the ion‐acoustic waves to the waves associated with an electrical transmission line is pointed out and the solved examples are compared with experimental observations.