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Describes current research work into the design of a 3‐D vision sensor for use in the field of robot navigation and autonomous vehicles. Outlines the development of a stereo vision system which uses fast data processing to extract feature points in the stereo images and a new fast stereo matching algorithm. Gives results of experiments performed using this system and concludes that the applications require fast, self‐adaptive algorithms which can be processed by parallel processors. This was obtained by means of a special configuration and a highly parallelizable stereo vision process based on the declivity feature matched by dynamic programming.

Social and emotional learning (SEL) is critical for students' social and academic success. Students' SEL is often contingent on their teachers' social and emotional competencies and capacities (SECC; Jennings & Greenberg, 2009; Chapter 5) and teacher preparation to facilitate SEL in classrooms (Schonert-Reichl, Kitil, & Hanson-Peterson, 2017). Concerningly, teacher training to facilitate SEL is frequently predicated on a color-evasive perspective that ignores the ways structural racism impacts the schooling experiences of racially minoritized students and associated academic and SEL outcomes (Jagers, Rivas-Drake, & Borowski, 2018; Jagers, Rivas-Drake, & Williams, 2019). In order to support SEL for students from racially minoritized communities, we assert that teachers' social and emotional competencies and capacities must incorporate a culturally responsive pedagogical approach that explicitly acknowledges and addresses issues of race and justice (Jagers et al., 2019; Ladson-Billings, 2014; Ladson-Billings & Tate, 1995). In this chapter we (1) provide an overview of culturally relevant pedagogy in relation to teacher social and emotional competencies and capacities; (2) outline existing models that support a culturally relevant approach to teacher social and emotional competencies and capacities; and (3) discuss future directions for education research, practice, and policy.

Allan A. S. Rae has been appointed as the new chairman of CIBA‐Geigy (U.K.) Ltd., The Clayton Aniline Company Ltd., CIBA‐Geigy Chemicals Ltd. and Ilford Ltd. Mr Rae succeeds Lord Harvey of Prestbury who retired but continues as a Director of the parent company CIBA‐Geigy AG, Basle, and in the U.K. will act as consultant and adviser to Mr Rae.

The purpose of this paper is to demonstrate the applicability of swarm and evolutionary techniques for regularized machine learning. Generally, by defining a proper penalty function, regularization laws are embedded into the structure of common least square solutions to increase the numerical stability, sparsity, accuracy and robustness of regression weights. Several regularization techniques have been proposed so far which have their own advantages and disadvantages. Several efforts have been made to find fast and accurate deterministic solvers to handle those regularization techniques. However, the proposed numerical and deterministic approaches need certain knowledge of mathematical programming, and also do not guarantee the global optimality of the obtained solution. In this research, the authors propose the use of constraint swarm and evolutionary techniques to cope with demanding requirements of regularized extreme learning machine (ELM).

To implement the required tools for comparative numerical study, three steps are taken. The considered algorithms contain both classical and swarm and evolutionary approaches. For the classical regularization techniques, Lasso regularization, Tikhonov regularization, cascade Lasso-Tikhonov regularization, and elastic net are considered. For swarm and evolutionary-based regularization, an efficient constraint handling technique known as self-adaptive penalty function constraint handling is considered, and its algorithmic structure is modified so that it can efficiently perform the regularized learning. Several well-known metaheuristics are considered to check the generalization capability of the proposed scheme. To test the efficacy of the proposed constraint evolutionary-based regularization technique, a wide range of regression problems are used. Besides, the proposed framework is applied to a real-life identification problem, i.e. identifying the dominant factors affecting the hydrocarbon emissions of an automotive engine, for further assurance on the performance of the proposed scheme.

Through extensive numerical study, it is observed that the proposed scheme can be easily used for regularized machine learning. It is indicated that by defining a proper objective function and considering an appropriate penalty function, near global optimum values of regressors can be easily obtained. The results attest the high potentials of swarm and evolutionary techniques for fast, accurate and robust regularized machine learning.

The originality of the research paper lies behind the use of a novel constraint metaheuristic computing scheme which can be used for effective regularized optimally pruned extreme learning machine (OP-ELM). The self-adaption of the proposed method alleviates the user from the knowledge of the underlying system, and also increases the degree of the automation of OP-ELM. Besides, by using different types of metaheuristics, it is demonstrated that the proposed methodology is a general flexible scheme, and can be combined with different types of swarm and evolutionary-based optimization techniques to form a regularized machine learning approach.

In this paper, the authors extend their understanding of the internal dynamics of routines in contexts characterized by increased levels of virtuality. In particular, the authors focus on the role of routine artifacts in the internal dynamics of routines to answer the question: How does extensive reliance on information and communication technologies (ICTs) due to physical distance influence the internal dynamics of the new product development (NPD) routine (i.e. interactions between performative, ostensive and artifacts of routines) enacted by a virtual team?

This paper is based on an 18-month ethnographic study of the NPD routine performed by a virtual team. The authors relied predominantly on qualitative, ethnographic data collection and analysis methods, using semi-structured interviews, non-participant observation, and the collection of archival data and company documents (formal procedures, guidelines, application designs etc). Qualitative research offers a valuable means to investigate dynamic processes in organizations due to its sensitivity to the organizational context and potential to focus on activities as they unfold.

The findings highlight the central role of routine artifacts (ICTs) in the routine dynamics of the NPD routine performed by virtual team. In particular, the authors show that the use of the particular types of ICTs enabled team members to confidently and meaningfully relate to the overall routine activity and coordinate their actions in a context characterized by physical distance and extensive reliance on communication and collaboration technologies.

The paper sheds light into role of routine artifacts in the routine dynamics in a context characterized by a high degree of virtuality. This work contributes to the literature on routine dynamics by theorizing about the processes through which routine artifacts (ICTs) afforded routine participants the ability to act confidently and meaningfully to the present and dynamically coordinate their actions with their fellow routine participants.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

The chapter focuses on humanizing higher education by infusing ethical leadership in the curriculum to improve the public service. Its design is qualitative in nature and literature reviews and document analysis were employed in compiling the chapter. It followed an interpretive paradigm and used Kolb’s Experiential Learning Theory as a lens in understanding humanizing education in higher education. Nowadays ethical leadership is of paramount importance in higher education and in the public service. Ethical leadership should be based on the moral person and on the moral manager. The moral person component focuses on desirable personal qualities of leaders such as being perceived as honest, fair and trustworthy. The moral manager focuses on the leader and uses transactional efforts such as rewards and punishments to reinforce desired behaviors. Soft skills are very important in higher education and should be transferred through coursework. Students need to be supported in all aspects of education including the academic, emotional and social demands in higher education.