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The paper deals with a spatial discretization of transient semiconductor device equations. The method can be regarded as a combination of FDM‐ and FEM‐ideas. In the first part of the paper the method is described and—for a weakly acute triangulation—existence, uniqueness, non‐negativity, stability and conservativity of the semidiscrete solution are proved. The second part contains an error estimation under stronger assumptions on the regularity of the analytical solution and on the uniformity of the triangulation respectively. A linear convergence rate is obtained.

The discretisation scheme presented for an unstructured triangular grid, is able to reflect the physical properties of stationary, nonlinear heat conduction even in the numerical case and leads to a stabilisation of iterative solution techniques for nonlinearities.

The purpose of this paper is to propose an approach based on Convolution quadrature (CQ) for the modeling and the numerical treatment of impedance boundary condition.

The model is derived from a general setting. Its discretization is discussed in details by providing pseudo-codes and by performing their complexity analysis. The model is validated through several numerical experiments.

CQ provides an efficient and accurate treatment of impedance boundary conditions.

The paper suggests a new effective treatment of impedance boundary conditions.

Gives a bibliographical review of the error estimates and adaptive finite element methods from the theoretical as well as the application point of view. The bibliography at the end contains 2,177 references to papers, conference proceedings and theses/dissertations dealing with the subjects that were published in 1990‐2000.

The purpose of this study is to provide a systematic literature review on taxonomy alignment methods in information science to explore the common research pipeline and characteristics.

The authors implement a five-step systematic literature review process relating to taxonomy alignment. They take on a knowledge organization system (KOS) perspective, and specifically examining the level of KOS on “taxonomies.”

They synthesize the matching dimensions of 28 taxonomy alignment studies in terms of the taxonomy input, approach and output. In the input dimension, they develop three characteristics: tree shapes, variable names and symmetry; for approach: methodology, unit of matching, comparison type and relation type; for output: the number of merged solutions and whether original taxonomies are preserved in the solutions.

The main research implications of this study are threefold: (1) to enhance the understanding of the characteristics of a taxonomy alignment work; (2) to provide a novel categorization of taxonomy alignment approaches into natural language processing approach, logic-based approach and heuristic-based approach; (3) to provide a methodological guideline on the must-include characteristics for future taxonomy alignment research.

There is no existing comprehensive review on the alignment of “taxonomies”. Further, no other mapping survey research has discussed the comparison from a KOS perspective. Using a KOS lens is critical in understanding the broader picture of what other similar systems of organizations are, and enables us to define taxonomies more precisely.

Due to the complex mechanism during walking, human gait takes plenty of information reflecting human motion. The method of quantitative measurement of gait makes a profound influence in many fields, such as clinical medicine, biped robot control strategy and so on. The purpose of this paper is to present a gait analysis system based on inertial measurement unit (IMU) and combined with body sensor network (BSN).

The authors placed two wireless inertial nodes on the left and right ankles, so that the acceleration and angular velocity could be obtained from both sides at the same time. By using the kinematical model of the human gait, many methods such as time series analysis, pattern recognition and numerical analysis, are introduced to fuse the inertial data and estimate the sagittal gait parameters.

The gait parameters evaluation gains a practical precision, especially in the gait phase detection and the process of how the two feet cooperate with each other has been analyzed to learn about the mechanism of biped walking.

The gait analysis procedure is off line, so that the system ensures sampling at a high rate.

This gait analysis system can be utilized to measure quantitative gait parameters. Further, the coordination of dual gait pattern is presented. Last but not least, the system can also be put into capturing and analyzing the motion of other parts of the body.

The purpose of this study is to develop a synthesized conceptual framework for artificial intelligence (AI) adoption in the field of business-to-business (B2B) marketing.

A conceptual development approach has been adopted, based on a content analysis of 59 papers in peer-reviewed academic journals, to identify drivers, barriers, practices and consequences of AI adoption in B2B marketing. Based on these analyses and findings, a conceptual model is developed.

This paper identifies the following two key drivers of AI adoption: the shortcomings of current marketing activities and the external pressure imposed by informatization. Seven outcomes are identified, namely, efficiency improvements, accuracy improvements, better decision-making, customer relationship improvements, sales increases, cost reductions and risk reductions. Based on information processing theory and organizational learning theory (OLT), an integrated conceptual framework is developed to explain the relationship between each construct of AI adoption in B2B marketing.

This study is the first conceptual paper that synthesizes drivers, barriers and outcomes of AI adoption in B2B marketing. The conceptual model derived from the combination of information processing theory and OLT provides a comprehensive framework for future work and opens avenues of research on this topic. This paper contributes to both AI literature and B2B literature.

The purpose of this study is to both understand the motives for volunteering in local government (a strong/structured context) and determine how such motivation and other demographics interact with organisational contexts to influence volunteering outcomes.

The study adopts a functional approach to volunteerism. The Volunteer Functions Inventory is modified to better assess the motivations of elected local government volunteers. The responses of 152 Maltese local councillors were used to answer four research questions empirically.

Exploratory and confirmatory factor analyses supported the introduction of a seventh VFI dimension, namely the political function. The study provides evidence that local councillors who received greater amounts of functionally relevant benefits reported more satisfaction and a stronger intention to continue volunteering in local government. The aggregated effect of multiple motives as well as other person-based determinants (marital status and education) produced a significant impact on volunteering outcomes in this strong/structured situational context of this public sector environment.

This study contributes to a better understanding and assessment of the motivations of elected local government volunteers. It addresses practical recommendations for sustaining civil society, while acknowledging the potential and contribution of volunteers with various demographic characteristics.

Context awareness is one of the key aspects of pervasive computing systems. In such systems, a plethora of dynamic context information needs to be constantly retrieved, soundly interpreted, rapidly processed, maintained in various repositories, and securely disseminated. Thus, a flexible, scalable and interoperable context representation scheme needs to be established and solid context management mechanisms need to be adopted, which will perform well in large‐scale distributed pervasive systems. This paper elaborates on the COMPACT context middleware that has been designed to cope with the issues above and saturate pervasive computing environments with context awareness functionality.

The ability to attract and retain volunteers is crucial for not-for-profit organizations, and consequently, the need to understand and manage volunteers’ engagement is paramount. The purpose of this paper is to investigate the role of five volunteer engagement dimensions (cognitive, affective, behavioral, social and spiritual engagement) on perceived value-in-context, and its subsequent role for volunteer retention. Thus, providing for the first time an understanding of how unique types of value are determined through different facets of volunteer engagement.

To establish the nature and consequences of volunteer engagement, the authors collaborated with an Australian not-for-profit service organization. Using a survey method, the authors studied the organization’s volunteer workforce resulting in 464 usable responses. To capture volunteers’ degree of spiritual engagement, this paper introduces a rigorously developed unidimensional measure.

The results demonstrate the importance of the five engagement dimensions on volunteers’ perceived value-in-context, while highlighting significant effect differences including some counterintuitive consequences. The authors also establish the role of spiritual engagement and demonstrate the impact of value-in-context for volunteer retention.

This research explores the volunteer engagement-retention chain, by empirically studying the role of value-in-context. The authors provide first evidence for the relationship between volunteer engagement and value-in-context, examining the independent yet relative effects of various facets of volunteer engagement. In doing so, the authors offer new insight into the dimensionality of the volunteer engagement construct, broadening its conceptualization to include spiritual engagement as a core constituent. The authors further demonstrate the impact of value-in-context on volunteer retention, helping organizations to better make sense of meaningful volunteer experiences with long-lasting impacts and mutual benefits.