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In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.

The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).

Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.

All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.

The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.

The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.

This article outlines the theoretical foundations of the research contributions of this edited collection about “Diversity and Discrimination in Research Organizations.” First, the sociological understanding of the basic concepts of diversity and discrimination is described and the current state of research is introduced. Second, national and organizational contextual conditions and risk factors that shape discrimination experiences and the management of diversity in research teams and organizations are presented. Third, the questions and research approaches of the individual contributions to this edited collection are presented.

The present study contributes to our understanding of how to curb burnout among hospital staff over time. The authors extend existing research by examining the mediating role of mission valence in the link between transformational leadership and burnout.

Self-administered questionnaire data from employees in a Canadian general hospital (N = 185) were analyzed using a time-lagged research design to examine whether transformational leaders can increase employees' attraction to the organization's mission (i.e. mission valence) and in turn alleviate long-term burnout.

Structural equation modeling analysis demonstrated that transformational leadership (time 1) was negatively related to the burnout components of emotional exhaustion and depersonalization (time 2). Further, the results showed that mission valence mediated these relationships.

The study findings are important for managers and professionals as they identify transformational leadership as a potent strategy to alleviate employee burnout and clarify the process through which this is achieved, namely, by increasing mission valence.

To date, surprisingly little research has explored how transformational leadership influences followers' burnout. To address this issue, the present study examined the role of transformational leadership on staff burnout through the mechanism of increasing mission valence. Understanding how to mitigate burnout is particularly critical in health care organizations given that burnout not only negatively impacts employee wellbeing but also the wellbeing and quality of care provided to patients.

Digital technologies, and the affordances they provide, can shape institutional processes in significant ways. In the last decade, social media and other digital platforms have redefined civic engagement by enabling new ways of connecting, collaborating, and mobilizing. In this article, we examine how technological affordances can both enable and hinder institutional processes through visibilization – which we define as the enactment of technological features to foreground and give voice to particular perspectives and discourses while silencing others. We study such dynamics by examining #SchauHin, an activist campaign initiated in Germany to shine a spotlight on experiences of daily racism. Our findings show how actors and counter-actors differentially leveraged the technological features of two digital platforms to shape the campaign. Our study has implications for understanding the role of digital technologies in institutional processes as well as the interplay between affordances and visibility in efforts to deinstitutionalize discriminatory practices and institutions.

Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

An appropriate equivalent model is the key to the effective analysis of the system and structure in which permanent magnet takes part. At present, there are several equivalent models for calculating the interacting magnetic force between permanent magnets including magnetizing current, magnetic charge and magnetic dipole–dipole model. How to choose the most appropriate and efficient model still needs further discussion.

This paper chooses cuboid, cylindrical and spherical permanent magnets as calculating objects to investigate the detailed calculation procedures based on three equivalent models, magnetizing current, magnetic charge and magnetic dipole–dipole model. By comparing the accuracies of those models with experiment measurement, the applicability of three equivalent models for describing permanent magnets with different shapes is analyzed.

Similar calculation accuracies of the equivalent magnetizing current model and magnetic charge model are verified by comparison between simulation and experiment results. However, the magnetic dipole–dipole model can only accurately calculate for spherical magnet instead of other nonellipsoid magnets, because dipole model cannot describe the specific characteristics of magnet's shape, only sphere can be treated as the topological form of a dipole, namely a filled dot.

This work provides reference basis for choosing a proper model to calculate magnetic force in the design of electromechanical structures with permanent magnets. The applicability of different equivalent models describing permanent magnets with different shapes is discussed and the equivalence between the models is also analyzed.

The purpose of this paper is to make the case for bringing compassion to students in educational settings, preschool through graduate school (PK-20).

First, the author defines what is meant by “compassion” and differentiates it from the related constructs. Next, the author discusses the importance of bringing compassion into education, thinking specifically about preschool, K-12 (elementary and middle school/junior high/high school), college students, and graduate students (e.g. law, medical, nurses, counselors and therapists-in-training). The author then reviews the scant empirical literature on compassion in education and makes recommendations for future research. In the final section, the author makes specific and practical recommendations for the classroom (e.g. how to teach and evaluate compassion in PK-20).

While there is a fair amount of research on compassion with college students, and specifically regarding compassion for oneself, as the author reviews in this paper, the field is wide open in terms of empirical research with other students and examining other forms of compassion.

This is not a formal review or meta-analysis.

This paper will be a useful resource for teachers and those interested in PK-20 education.

This paper highlights the problems and opportunities for bringing compassion into education settings.

To date, no review of compassion in PK-20 exists.

The purpose of this study was to explore how variables such as student demographics, pre-college leadership activities, and perceived pre-college parenting behaviors predict students’ leader self-efficacy (i.e., individuals’ confidence in themselves to lead and belief that others will support their leadership [Hannah et al., 2008]) in college and leader emergence (i.e., college-based leadership involvements [DeRue & Ashford, 2010]) in college. Undergraduate students (n = 420) at a large, public university in the Mid-Atlantic were surveyed to examine these relationships and data were analyzed using hierarchical and logistic regression, with appropriate controls and moderators. Findings included discovery that pre-college engagement with sports team positional leadership, community service, extracurriculars, and positive parenting behaviors, such as family routine and greater quality time with parents, predicted leader self-efficacy. Further, findings noted that pre-college community service, extracurriculars, peer tutoring and perceptions of parental quality time and proactive parenting predicted leader emergence. This study suggests that students’ leadership development is influenced by myriad systems across the lifespan and demonstrates that, as educators committed to student development, we must engage the full arc of our students’ leadership journeys and provide for intentional partnerships between higher education and the K-12 community.

This paper aims to explore how unreflective and reflective value experience emerges in value co-creation and co-destruction practices in a consumer context.

This paper presents a Heideggerian phenomenological heuristic consisting of three interrelated modes of engagement, which is used for interpretive sense-making in a dynamic and lively case context of amateur-level football (soccer) played on artificial grass. Based on a qualitative study using ethnographic techniques, this study examines the whats and the hows of value experience by individuals playing football at different qualities and in varying conditions across 25 Dutch football teams.

The findings reveal three interrelated yet distinct modalities of experience in value co-creation and co-destruction presented in a continuum of triplex spaces of unreflective and reflective value experience. The first is a joyful flow of unreflective value experience in emergent and undisrupted value co-creation practice with no potential for value co-destruction. Second, a semireflective value experience caused by interruptions in value co-creation has a higher potential for value co-destruction. Third, a fully reflective value experience through a completely interrupted value co-creation practice results in high-value co-destruction.

This research contributes to the literature on the microfoundations of value experience and value creation by proposing a conceptual relationship between unreflective/reflective value experience and value co-creation and co-destruction mediated through interruptions in consumer usage situations.

This study’s novel perspective on this relationship offers practitioners a useful vantage point on understanding how enhanced value experience comes about in value co-creation practice and how this is linked to value co-destruction when interruptions occur. These insights help bolster alignment and prevent misalignment in resource integration and foster service strategies, designs and innovations to better influence consumer experience in journeys.

This study deploys an integral view of how consumer value experience manifests in value co-creation and co-destruction that offers conceptual, methodological and practical clarity.