8,229 research outputs found

    Requirements for Explainability and Acceptance of Artificial Intelligence in Collaborative Work

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    The increasing prevalence of Artificial Intelligence (AI) in safety-critical contexts such as air-traffic control leads to systems that are practical and efficient, and to some extent explainable to humans to be trusted and accepted. The present structured literature analysis examines n = 236 articles on the requirements for the explainability and acceptance of AI. Results include a comprehensive review of n = 48 articles on information people need to perceive an AI as explainable, the information needed to accept an AI, and representation and interaction methods promoting trust in an AI. Results indicate that the two main groups of users are developers who require information about the internal operations of the model and end users who require information about AI results or behavior. Users' information needs vary in specificity, complexity, and urgency and must consider context, domain knowledge, and the user's cognitive resources. The acceptance of AI systems depends on information about the system's functions and performance, privacy and ethical considerations, as well as goal-supporting information tailored to individual preferences and information to establish trust in the system. Information about the system's limitations and potential failures can increase acceptance and trust. Trusted interaction methods are human-like, including natural language, speech, text, and visual representations such as graphs, charts, and animations. Our results have significant implications for future human-centric AI systems being developed. Thus, they are suitable as input for further application-specific investigations of user needs

    Adaptive finite-time control of multi-agent systems with partial state constraints and input saturation via event-triggered strategy

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    This paper focuses on the finite-time control problem of multi-agent systems with input saturation, unknown nonlinear dynamics, external disturbances and partial state constraints via output feedback. Fuzzy logic system and fuzzy state observer are introduced to approximate the uncertain nonlinearities and estimate the unmeasurable states, respectively. The partial state constraints are dealt with by using the barrier Lyapunov function, so that all states of the system do not exceed the preset boundary values. In order to reduce the computational complexity of the virtual controller and save communication resources, a first-order filter and an event-triggered mechanism are introduced, respectively. It is proved that the Zeno behavior does not occur via the proposed event-triggered controller. By stability analysis, the finite-time convergence of tracking error to a small neighborhood of the origin is proven. The effectiveness of the theoretical results is verified by examples.http://wileyonlinelibrary.com/iet-cthhj2023Electrical, Electronic and Computer Engineerin

    Multi-dimensional omics approaches to dissect natural immune control mechanisms associated with RNA virus infections

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    In recent decades, global health has been challenged by emerging and re-emerging viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), human immunodeficiency viruses (HIV-1), and Crimean–Congo hemorrhagic fever virus (CCHFV). Studies have shown dysregulations in the host metabolic processes against SARS-CoV2 and HIV-1 infections, and the research on CCHFV infection is still in the infant stage. Hence, understanding the host metabolic re-programming on the reaction level in infectious disease has therapeutic importance. The thesis uses systems biology methods to investigate the host metabolic alterations in response to SARS-CoV2, HIV-1, and CCHFV infections. The three distinct viruses induce distinct effects on human metabolism that, nevertheless, show some commonalities. We have identified alterations in various immune cell types in patients during the infections of the three viruses. Further, differential expression analysis identified that COVID-19 causes disruptions in pathways related to antiviral response and metabolism (fructose mannose metabolism, oxidative phosphorylation (OXPHOS), and pentose phosphate pathway). Up-regulation of OXPHOS and ROS pathways with most changes in OXPHOS complexes I, III, and IV were identified in people living with HIV on treatment (PLWHART). The acute phase of CCHFV infection is found to be linked with OXPHOS, glycolysis, N-glycan biosynthesis, and NOD-like receptor signaling pathways. The dynamic nature of the metabolic process and adaptive immune response in CCHFV-pathogenesis are also observed. Further, we have identified different metabolic flux in reactions transporting TCA cycle intermediates from the cytosol to mitochondria in COVID-19 patients. Genes such as monocarboxylate transporter (SLC16A6) and nucleoside transporter (SLC29A1) and metabolites such as α-ketoglutarate, succinate, and malate were found to be linked with COVID-19 disease response. Metabolic reactions associated with amino acid, carbohydrate, and energy metabolism pathways and various transporter reactions were observed to be uniquely disrupted in PLWHART along with increased production of αketoglutarate (αKG) and ATP molecules. Changes in essential (leucine and threonine) and non-essential (arginine, alanine, and glutamine) amino acid transport were found to be caused by acute CCHFV infection. The altered flux of reactions involving TCA cycle compounds such as pyruvate, isocitrate, and alpha-ketoglutarate was also observed in CCHFV infection. The research described in the thesis displayed dysregulations in similar metabolic processes against the three viral Infections. But further downstream analysis unveiled unique alterations in several metabolic reactions specific to each virus in the same metabolic pathways showing the importance of increasing the resolution of knowledge about host metabolism in infectious diseases

    Artificial Intelligence, Robots, and Philosophy

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    This book is a collection of all the papers published in the special issue “Artificial Intelligence, Robots, and Philosophy,” Journal of Philosophy of Life, Vol.13, No.1, 2023, pp.1-146. The authors discuss a variety of topics such as science fiction and space ethics, the philosophy of artificial intelligence, the ethics of autonomous agents, and virtuous robots. Through their discussions, readers are able to think deeply about the essence of modern technology and the future of humanity. All papers were invited and completed in spring 2020, though because of the Covid-19 pandemic and other problems, the publication was delayed until this year. I apologize to the authors and potential readers for the delay. I hope that readers will enjoy these arguments on digital technology and its relationship with philosophy. *** Contents*** Introduction : Descartes and Artificial Intelligence; Masahiro Morioka*** Isaac Asimov and the Current State of Space Science Fiction : In the Light of Space Ethics; Shin-ichiro Inaba*** Artificial Intelligence and Contemporary Philosophy : Heidegger, Jonas, and Slime Mold; Masahiro Morioka*** Implications of Automating Science : The Possibility of Artificial Creativity and the Future of Science; Makoto Kureha*** Why Autonomous Agents Should Not Be Built for War; István Zoltán Zárdai*** Wheat and Pepper : Interactions Between Technology and Humans; Minao Kukita*** Clockwork Courage : A Defense of Virtuous Robots; Shimpei Okamoto*** Reconstructing Agency from Choice; Yuko Murakami*** Gushing Prose : Will Machines Ever be Able to Translate as Badly as Humans?; Rossa Ó Muireartaigh**

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    It is too hot in here! A performance, energy and heat aware scheduler for Asymmetric multiprocessing processors in embedded systems.

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    Modern architecture present in self-power devices such as mobiles or tablet computers proposes the use of asymmetric processors that allow either energy-efficient or performant computation on the same SoC. For energy efficiency and performance consideration, the asymmetry resides in differences in CPU micro-architecture design and results in diverging raw computing capability. Other components such as the processor memory subsystem also show differences resulting in different memory transaction timing. Moreover, based on a bus-snoop protocol, cache coherency between processors comes with a peculiarity in memory latency depending on the processors operating frequencies. All these differences come with challenging decisions on both application schedulability and processor operating frequencies. In addition, because of the small form factor of such embedded systems, these devices generally cannot afford active cooling systems. Therefore thermal mitigation relies on dynamic software solutions. Current operating systems for embedded systems such as Linux or Android do not consider all these particularities. As such, they often fail to satisfy user expectations of a powerful device with long battery life. To remedy this situation, this thesis proposes a unified approach to deliver high-performance and energy-efficiency computation in each of its flavours, considering the memory subsystem and all computation units available in the system. Performance is maximized even when the device is under heavy thermal constraints. The proposed unified solution is based on accurate models targeting both performance and thermal behaviour and resides at the operating systems kernel level to manage all running applications in a global manner. Particularly, the performance model considers both the computation part and also the memory subsystem of symmetric or asymmetric processors present in embedded devices. The thermal model relies on the accurate physical thermal properties of the device. Using these models, application schedulability and processor frequency scaling decisions to either maximize performance or energy efficiency within a thermal budget are extensively studied. To cover a large range of application behaviour, both models are built and designed using a generative workload that considers fine-grain details of the underlying microarchitecture of the SoC. Therefore, this approach can be derived and applied to multiple devices with little effort. Extended evaluation on real-world benchmarks for high performance and general computing, as well as common applications targeting the mobile and tablet market, show the accuracy and completeness of models used in this unified approach to deliver high performance and energy efficiency under high thermal constraints for embedded devices

    Stability Verification of Neural Network Controllers using Mixed-Integer Programming

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    We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, which admits an efficient parameterization and can be evaluated at a low computational cost, against a fixed baseline policy, which is known to be stable but expensive to evaluate. We provide sufficient conditions for the closed-loop stability of the candidate policy in terms of the worst-case approximation error with respect to the baseline policy, and we show that these conditions can be checked by solving a Mixed-Integer Quadratic Program (MIQP). Additionally, we demonstrate that an outer and inner approximation of the stability region of the candidate policy can be computed by solving an MILP. The proposed framework is sufficiently general to accommodate a broad range of candidate policies including ReLU Neural Networks (NNs), optimal solution maps of parametric quadratic programs, and Model Predictive Control (MPC) policies. We also present an open-source toolbox in Python based on the proposed framework, which allows for the easy verification of custom NN architectures and MPC formulations. We showcase the flexibility and reliability of our framework in the context of a DC-DC power converter case study and investigate its computational complexity

    Type Synthesis and Performance Optimization of Parallel Manipulators

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    Parallel robots have been widely employed in industrial applications. There are still some challenging topics in the fundamental research, e.g., the primary problem mobility analysis has not been solved for about 150 years. A universal mobility equation for all kinds of parallel architectures has not been found. Another issue lies on the performance measurements for parallel manipulators. There are plenty of kinematic and dynamic performance indices. However, the various ranges and scales of these indicators make the optimal design considering multiple indices complicated. It is essential to search for a unified approach to normalize performance indicators. More dynamic performance measurement indicators should be raised to explore the dynamic features and complete the theory for parallel mechanisms. In this research, an improved mobility equation is designed to reveal the degrees of freedom for a special class of parallel robots. A novel methodology called the kinematic joint matrix is proposed. It possesses the mapping relations with parallel manipulators. A series of 2-6 degrees of freedom parallel architectures is denoted by the kinematic joint matrix. The theory of screw is employed to check the feasibility from several kinds of parallel structures. A special block diagram is introduced to distinguish various kinematic joint matrices. Since this family of parallel robots contains various motion characteristics, four parallel robots with distinct features are selected. Based on the kinematic models, three categories of singularities are explored. The operational and reachable workspaces of the pure-translational parallel robots are searched and the parametric analyses are reported. The linkage’s impacts for the reachable workspace of the mixed-motion parallel architectures are investigated. The novel performance level index is designed to unify the positive performance index and demonstrated the performance rank for any pose (position and orientation). The dexterity index is utilized as an example to verify the characteristics of the level index. The distributions and parametric analyses of two novel mass-related performances are studied. The dimension synthesis of a selected planar parallel robot is presented based on the non-dominated genetic algorithm II. The experiment results testify the correctness of the mobility and kinematic mathematical models of this mechanism
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