At the 5Groningen field lab, the next generation of wireless technology is being put to the test in an experiment with a prototype involving real-time decision-making using 5G edge computing. One of the applications envisioned is a smart police vest that can fully automatically detect threats like firearms and stabbing weapons.
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The development of information and communication technologies (ICT) has led to many innovative technologies. The integration of technologies such as the internet of things (IoT), cloud computing, and machine learning concepts have given rise to Industry 4.0. Fog and edge computing have stepped in to fill the areas where cloud computing is inadequate to ensure these systems work quickly and efficiently. The number of connected devices has brought about cybersecurity issues. This study reviewed the current literature regarding edge/fog-based cybersecurity in IoT to display the current state.
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Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis.
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In today's world, understanding different viewpoints is key for societal cohesion and progress. Robots have the potential to provide aid in discussing tough topics like ethnicity and gender. However, comparably to humans, the appearance of a robot can trigger inherent prejudices. This study delves into the interplay between robot appearance and decision-making in ethical dilemmas. Employing a Furhat robot that can change faces in an instant, we looked at how robot appearance affects decision-making and the perception of the robot itself. Pairs of participants were invited to discuss a dilemma presented by a robot, covering sensitive topics of ethnicity or gender. The robot either adopted a first-person or third-person perspective and altered its appearance accordingly. Following the explanation, participants were encouraged to discuss their choice of action in the dilemma situation. We did not find significant influences of robot appearance or dilemma topic on perceived anthropomorphism, animacy, likeability, or intelligence of the robot, partly in line with previous research. However, several participants hearing the dilemma from a first-person perspective changed their opinion because of the robot's appearance. Future work can expand with different measures such as engagement, in order to shed light on the intricate dynamics of human-robot interaction, emphasizing the need for thoughtful consideration in designing robot appearances to promote unbiased engagement in discussions of societal significance
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In this chapter, we propose an ethical framework for serious game design, which we term the Ecosystem for Designing Games Ethically (EDGE).EDGE expands on Zagal’s categorization of ethical areas in game design by incorporating the different contexts of design and their use. In addition, we leverage these contexts to suggest four guidelines that support Ethical Stewardship in serious game design. We conclude by discussing a number of specific areas inwhich ethics plays a role in serious game design. These include games in (a) amilitary context, (b) the consideration of privacy issues, and (c) the evaluation ofgame design choices.
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Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings.
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Deze publicatie is uitgebracht ter gelegenheid van de rede uitgesproken op 21 september 2022 bij de installatie van Dr. Rix Groenboom als lector New Business & ICT bij het lectoraat Digitale Transformatie.
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IT-based networking trends such as the rise of social media, crowd sourcing, open innovation, and cloud computing enable a profoundly different way of working and collaborating that challenges significantly traditional approaches of companies towards governance, i.e. the mechanisms a company employs to achieving business results and safeguarding information. Standard practices developed with a hierarchical model of the company in mind, are inadequate for providing sufficient correlation between governance mechanisms deployed and results achieved. Popular literature on the subject states that dealing effectively with such new technologies in a business environment requires relinquishing control and subverting to trust. This paper makes the case that deploying successfully new IT-based networking tools rather involves shifting one’s trust from a well-established and well-known governance system based on hierarchy and control towards another governance system, termed in the literature as network governance. This paper assesses when network governance is the better suited governance system. The presented theoretical model helps to understand how companies should use arising new technologies and which tasks are suited for network-driven IT-applications. Furthermore, the model enables to understand how network governance works to achieve business results and to safeguard information exchanges.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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Exploratory analyses are an important first step in psychological research, particularly in problem-based research where various variables are often included from multiple theoretical perspectives not studied together in combination before. Notably, exploratory analyses aim to give first insights into how items and variables included in a study relate to each other. Typically, exploratory analyses involve computing bivariate correlations between items and variables and presenting them in a table. While this is suitable for relatively small data sets, such tables can easily become overwhelming when datasets contain a broad set of variables from multiple theories. We propose the Gaussian graphical model as a novel exploratory analyses tool and present a systematic roadmap to apply this model to explore relationships between items and variables in environmental psychology research. We demonstrate the use and value of the Gaussian graphical model to study relationships between a broad set of items and variables that are expected to explain the effectiveness of community energy initiatives in promoting sustainable energy behaviors.
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