422 research outputs found

    Strategies for Promoting Inclusion and Employee Engagement to Improve Remote Teams’ Performance

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    External factors such as the pandemic have forced organizational leaders to embrace flexible work structures. Differences in remote versus collocated workplaces escalate the importance for company leaders to uncover strategies to maintain employee engagement and performance. Grounded in the organizational support theory, the purpose of this qualitative multiple-case study was to explore strategies leaders of remote, diverse teams with high engagement and inclusion use to achieve high team performance. Data were collected using semistructured interviews from a purposeful sampling of five nationally distributed managers. A thematic analysis uncovered three themes: flexible leadership behavior, fair execution of human resource policy and resource allocation, and collaborative work structures. Key recommendations for organizational leaders include (a) investing in training, (b) improving methods of communication, (c) equitably administering policy and resource allocation, and (c) offering program concepts and support for implementing collaborative work structures. The implication for positive social change includes the potential to build solid intercompany and civic relationships, policy awareness, and translate the elements of organizational justice to extend the company’s impact externally to surrounding communities

    A system dynamics approach to evaluate advanced persistent threat vectors.

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    Cyber-attacks targeting high-profile entities are focused, persistent, and employ common vectors with varying levels of sophistication to exploit social-technical vulnerabilities. Advanced persistent threats (APTs) deploy zero-day malware against such targets to gain entry through multiple security layers, exploiting the dynamic interplay of vulnerabilities in the target network. System dynamics (SD) offers an alternative approach to analyze non-linear, complex, and dynamic social-technical systems. This research applied SD to three high-profile APT attacks - Equifax, Carphone, and Zomato - to identify and simulate socio-technical variables leading to breaches. By modeling APTs using SD, managers can evaluate threats, predict attacks, and reduce damage by mitigating specific socio-technical cues. This study provides valuable insights into the dynamics of cyber threats, making it the first to apply SD to APTs

    The Domestic Sublime

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    An investigation of the art of Tara Donovan, Liza Lou, Dave Cole, and Wolfgang Laib precipitated an articulation of a unique concept, the domestic sublime. The use of non-traditional art materials employed by each artist is one of the unifying characteristics that makes their work illustrations of the domestic sublime. Each artist presents work that is familiar yet uncomfortable, comforting yet disturbing, and lastly, finite yet immeasurable. The combination of repetitive labor, vast quantities of physical materials, and forms that present the unknown reveal characteristics of the domestic sublime. Tracing the concept of the sublime from its origins to today allows for its evolution from a transcendental experience to a tangible, material manifestation in contemporary discourse. Key figures in this argument include Immanuel Kant, Jean-François Lyotard, and Jacques Derrida. Domesticity commonly refers to any labor, activity or material related to, in or around the home and has numerous social, historical, and philosophical contexts. Situated in notion of modernity, the domestic’s foundation is comprised of layers of discourse that include the politics of labor, economic implications, boundaries, technology, and identity. Contributing philosophers to the domestic include Gaston Bachelard, Witold Rybczynski, Simone de Beauvoir, Kathleen M. Kirby, Henri Lefebvre, and Martin Heidegger. Characteristics from both the domestic and the sublime meld to a framework that supports the paradoxes and complexities inherent in both notions, while simultaneously revealing the overlapping notions that inextricably create the domestic sublime. The artwork that illustrates the notion of the domestic sublime combines domestic materials, labor, and space with the uncanny relationships inherent in the sublime such attraction and repulsion, interior and exterior, and comfort and terror.https://digitalmaine.com/academic/1050/thumbnail.jp

    NB-IoT via non terrestrial networks

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    Massive Internet of Things is expected to play a crucial role in Beyond 5G (B5G) wireless communication systems, offering seamless connectivity among heterogeneous devices without human intervention. However, the exponential proliferation of smart devices and IoT networks, relying solely on terrestrial networks, may not fully meet the demanding IoT requirements in terms of bandwidth and connectivity, especially in areas where terrestrial infrastructures are not economically viable. To unleash the full potential of 5G and B5G networks and enable seamless connectivity everywhere, the 3GPP envisions the integration of Non-Terrestrial Networks (NTNs) into the terrestrial ones starting from Release 17. However, this integration process requires modifications to the 5G standard to ensure reliable communications despite typical satellite channel impairments. In this framework, this thesis aims at proposing techniques at the Physical and Medium Access Control layers that require minimal adaptations in the current NB-IoT standard via NTN. Thus, firstly the satellite impairments are evaluated and, then, a detailed link budget analysis is provided. Following, analyses at the link and the system levels are conducted. In the former case, a novel algorithm leveraging time-frequency analysis is proposed to detect orthogonal preambles and estimate the signals’ arrival time. Besides, the effects of collisions on the detection probability and Bit Error Rate are investigated and Non-Orthogonal Multiple Access approaches are proposed in the random access and data phases. The system analysis evaluates the performance of random access in case of congestion. Various access parameters are tested in different satellite scenarios, and the performance is measured in terms of access probability and time required to complete the procedure. Finally, a heuristic algorithm is proposed to jointly design the access and data phases, determining the number of satellite passages, the Random Access Periodicity, and the number of uplink repetitions that maximize the system's spectral efficiency

    Bimanual robotic manipulation based on potential fields

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    openDual manipulation is a natural skill for humans but not so easy to achieve for a robot. The presence of two end effectors implies the need to consider the temporal and spatial constraints they generate while moving together. Consequently, synchronization between the arms is required to perform coordinated actions (e.g., lifting a box) and to avoid self-collision between the manipulators. Moreover, the challenges increase in dynamic environments, where the arms must be able to respond quickly to changes in the position of obstacles or target objects. To meet these demands, approaches like optimization-based motion planners and imitation learning can be employed but they have limitations such as high computational costs, or the need to create a large dataset. Sampling-based motion planners can be a viable solution thanks to their speed and low computational costs but, in their basic implementation, the environment is assumed to be static. An alternative approach relies on improved Artificial Potential Fields (APF). They are intuitive, with low computational, and, most importantly, can be used in dynamic environments. However, they do not have the precision to perform manipulation actions, and dynamic goals are not considered. This thesis proposes a system for bimanual robotic manipulation based on a combination of improved Artificial Potential Fields (APF) and the sampling-based motion planner RRTConnect. The basic idea is to use improved APF to bring the end effectors near their target goal while reacting to changes in the surrounding environment. Only then RRTConnect is triggered to perform the manipulation task. In this way, it is possible to take advantage of the strengths of both methods. To improve this system APF have been extended to consider dynamic goals and a self-collision avoidance system has been developed. The conducted experiments demonstrate that the proposed system adeptly responds to changes in the position of obstacles and target objects. Moreover, the self-collision avoidance system enables faster dual manipulation routines compared to sequential arm movements

    Enhancing Geospatial Data: Collecting and Visualising User-Generated Content Through Custom Toolkits and Cloud Computing Workflows

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    Through this thesis we set the hypothesis that, via the creation of a set of custom toolkits, using cloud computing, online user-generated content, can be extracted from emerging large-scale data sets, allowing the collection, analysis and visualisation of geospatial data by social scientists. By the use of a custom-built suite of software, known as the ‘BigDataToolkit’, we examine the need and use of cloud computing and custom workflows to open up access to existing online data as well as setting up processes to enable the collection of new data. We examine the use of the toolkit to collect large amounts of data from various online sources, such as Social Media Application Programming Interfaces (APIs) and data stores, to visualise the data collected in real-time. Through the execution of these workflows, this thesis presents an implementation of a smart collector framework to automate the collection process to significantly increase the amount of data that can be obtained from the standard API endpoints. By the use of these interconnected methods and distributed collection workflows, the final system is able to collect and visualise a larger amount of data in real time than single system data collection processes used within traditional social media analysis. Aimed at allowing researchers without a core understanding of the intricacies of computer science, this thesis provides a methodology to open up new data sources to not only academics but also wider participants, allowing the collection of user-generated geographic and textual content, en masse. A series of case studies are provided, covering applications from the single researcher collecting data through to collection via the use of televised media. These are examined in terms of the tools created and the opportunities opened, allowing real-time analysis of data, collected via the use of the developed toolkit
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