Reviewerly/exHarmony huggingface dataset:
Ambient Healthcare: A New Paradigm in Medical Zone

Ambient intelligence (AmI), a new paradigm in artificial intelligence, seeks to enhance people's abilities by utilizing sensitive digital surroundings that are responsive to human requirements, routines, activities, and emotions. With the use of perceptive communications that are intrusive, covert, and proactive, future society will be able to communicate with humans and machines in novel ways. Such AmI technology is a result of cutting-edge interaction paradigms. An appropriate choice for developing a variety of workable solutions, notably in the field of healthcare. To provide the necessary context for the scientific community, this survey will explore the development of AmI approaches in the healthcare industry. We will discuss the infrastructure and technology required to implement AmI's vision, such as smart environments and wearable medical technologies. The most recent artificial intelligence (AI) development approaches used to produce AmI systems in the healthcare area will be outlined. making use of a variety of learning strategies (to learn from user interaction), reasoning techniques (to reason about the aims and objectives of users), and planning approaches (for organising activities and interactions). We'll also go over the possible advantages of AmI technology for those with various long-term physical, mental, or emotional conditions. In order to determine new avenues for future studies, we will showcase some of the successful case studies in the field and examine current and upcoming difficulties.
Healthcare Management and Prediction of Future Illness Through Autonomous Intelligent Advisory System Using AAT Computational Framework

The various technological evolutions in IT healthcare systems have transformed from Electronic Health Records (EHR) to personalized health support systems with ambient assistive technologies (AAT). This chapter focuses on Healthcare management tools and techniques with a major focus on technological innovations and disruptions; services and tools; Recommendation systems in health care; The proposed Autonomous Intelligent Advisory System termed as H-Pilot using the Social Internet of Things (SIOT) computational framework. SIoT framework in H-Pilot is an integrated application that supports the flow of app information from interconnected apps in various verticals. It provides various AAT services like Alerts and recommendations, activity monitoring with reports, communication among various devices, feedback support, navigation, and emergency health monitoring through various autonomous existing apps. The information must be blended to generate overall actions to increase efficiency and effectiveness to satisfy the tasks and needs of the individuals with personalized recommendations for improving the QOL. To make the study's contributions more evident, a sample user story is depicted to show the usage of the H-Pilot enabling person-centric healthcare using Ambient Assistive Technologies.
Verified Given Clause Procedures

Abstract Resolution and superposition provers rely on the given clause procedure to saturate clause sets. Using Isabelle/HOL, we formally verify four variants of the procedure: the well-known Otter and DISCOUNT loops as well as the newer iProver and Zipperposition loops. For each of the variants, we show that the procedure guarantees saturation, given a fair data structure to store the formulas that wait to be selected. Our formalization of the Zipperposition loop clarifies some fine points previously misunderstood in the literature.
SAT-Based Subsumption Resolution

Abstract Subsumption resolution is an expensive but highly effective simplifying inference for first-order saturation theorem provers. We present a new SAT-based reasoning technique for subsumption resolution, without requiring radical changes to the underlying saturation algorithm. We implemented our work in the theorem prover Vampire , and show that it is noticeably faster than the state of the art.
Verification of NP-Hardness Reduction Functions for Exact Lattice Problems

Abstract This paper describes the formal verification of NP-hardness reduction functions of two key problems relevant in algebraic lattice theory: the closest vector problem and the shortest vector problem, both in the infinity norm. The formalization uncovered a number of problems with the existing proofs in the literature. The paper describes how these problems were corrected in the formalization. The work was carried out in the proof assistant Isabelle.
Iscalc: An Interactive Symbolic Computation Framework (System Description)

Abstract The need to verify symbolic computation arises in diverse application areas. In this paper, based on earlier work on verifying computation of definite integrals in , we present a tool for performing a variety of symbolic computations interactively, taking a middle ground in terms of easy of use and rigor between computer algebra systems and interactive theorem provers. The tool supports user-level definitions and dependency among computations, allowing construction and reuse of custom theories. Side conditions are checked on a best-effort basis. The tool is applied to highly non-trivial computations from the textbook Inside Interesting Integrals.
Buy One Get 14 Free: Evaluating Local Reductions for Modal Logic

Abstract We are interested in widening the reasoning support for propositional modal logics in the so-called modal cube. The modal cube consists of extensions of the basic modal logic $$\textsf{K}_{}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>K</mml:mi> <mml:mrow /> </mml:msub> </mml:math> with an arbitrary combination of the modal axioms $$\textsf{B}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>B</mml:mi> </mml:math> , $$\textsf{D}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>D</mml:mi> </mml:math> , $$\textsf{T}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> , $$\textsf{4}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mn>4</mml:mn> </mml:math> and $$\textsf{5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mn>5</mml:mn> </mml:math> . We revisit recently developed local reductions from all logics in the modal cube to a normal form comprising sets of clausal formulae with associated modal levels. We extend these reductions further to the basic modal logic $$\textsf{K}_{}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>K</mml:mi> <mml:mrow /> </mml:msub> </mml:math> , called definitional reductions . This enables any prover for $$\textsf{K}_{}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>K</mml:mi> <mml:mrow /> </mml:msub> </mml:math> to be used to solve the satisfiability problem for all logics in the modal cube. We also present alternative, axiomatic , reductions based on ideas originally proposed by Kracht, providing new theoretical results and improved bounds on the size of the reductions. We compare both sets of reductions combined with state-of-the-art provers for $$\textsf{K}_{}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>K</mml:mi> <mml:mrow /> </mml:msub> </mml:math> on a large set of parametric benchmarks for all logics in the modal cube. The results show that the provers perform better with reductions based on the clausal normal form than the axiomatic reductions.
Uniform Substitution for Dynamic Logic with Communicating Hybrid Programs

Abstract This paper introduces a uniform substitution calculus for $${\textsf {d{}L}} {}_{\text {CHP}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi>d</mml:mi> <mml:mrow /> <mml:mi>L</mml:mi> </mml:mrow> <mml:msub> <mml:mrow /> <mml:mtext>CHP</mml:mtext> </mml:msub> </mml:mrow> </mml:math> , the dynamic logic of communicating hybrid programs. Uniform substitution enables parsimonious prover kernels by using axioms instead of axiom schemata. Instantiations can be recovered from a single proof rule responsible for soundness-critical instantiation checks rather than being spread across axiom schemata in side conditions. Even though communication and parallelism reasoning are notorious for necessitating subtle soundness-critical side conditions, uniform substitution when generalized to $${\textsf {d{}L}} {}_{\text {CHP}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi>d</mml:mi> <mml:mrow /> <mml:mi>L</mml:mi> </mml:mrow> <mml:msub> <mml:mrow /> <mml:mtext>CHP</mml:mtext> </mml:msub> </mml:mrow> </mml:math> manages to limit and isolate their conceptual overhead. Since uniform substitution has proven to simplify the implementation of hybrid systems provers substantially, uniform substitution for $${\textsf {d{}L}} {}_{\text {CHP}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi>d</mml:mi> <mml:mrow /> <mml:mi>L</mml:mi> </mml:mrow> <mml:msub> <mml:mrow /> <mml:mtext>CHP</mml:mtext> </mml:msub> </mml:mrow> </mml:math> paves the way for a parsimonious implementation of theorem provers for hybrid systems with communication and parallelism.
Program Synthesis in Saturation

Abstract We present an automated reasoning framework for synthesizing recursion-free programs using saturation-based theorem proving. Given a functional specification encoded as a first-order logical formula, we use a first-order theorem prover to both establish validity of this formula and discover program fragments satisfying the specification. As a result, when deriving a proof of program correctness, we also synthesize a program that is correct with respect to the given specification. We describe properties of the calculus that a saturation-based prover capable of synthesis should employ, and extend the superposition calculus in a corresponding way. We implemented our work in the first-order prover Vampire , extending the successful applicability of first-order proving to program synthesis.
An Isabelle/HOL Formalization of the SCL(FOL) Calculus

Abstract We present an Isabelle/HOL formalization of Simple Clause Learning for first-order logic without equality: SCL(FOL). The main results are formal proofs of soundness, non-redundancy of learned clauses, termination, and refutational completeness. Compared to the unformalized version, the formalized calculus is simpler and more general, some results such as non-redundancy are stronger and some results such as non-subsumption are new. We found one bug in a previously published version of the SCL Backtrack rule. Compared to related formalizations, we introduce a new technique for showing termination based on non-redundant clause learning.
Left-Linear Completion with AC Axioms

Abstract We revisit AC completion for left-linear term rewrite systems where AC unification is avoided and the normal rewrite relation can be used in order to decide validity questions. To that end, we give a new correctness proof for finite runs and establish a simulation result between the two inference systems known from the literature. Furthermore, we show how left-linear AC completion can be simulated by general AC completion. In particular, this result allows us to switch from the former to the latter at any point during a completion process. Finally, we present experimental results for our implementation of left-linear AC completion in the tool .
Sequential adding clustering algorithm

The sequential adding clustering algorithm herein presented adds cluster centers, assigns points to clusters, merges and removes clusters (deleting their centers) iteratively in order to find the optimal cluster partition.Additionally, the algorithm optimizes the cluster center positions by minimizing the 'sum of within-cluster distances'.The preliminary clustering results show that the algorithm is effective and efficient.
Multi-Sensory Wayfinding: Lessons from the Margins Towards the Design of Equitable and Healthy Spaces

Accessibility for marginalized and vulnerable populations has emerged as an urgent public health challenge. MIXdesign investigates how the built environment may enable spatial orientation, agency, and a sense of security in public spaces through the study of individuals with three different ways of being—those requiring assisted mobility, who are deaf, and who are autistic. Each one has developed novel coping mechanisms and ways of negotiating space that content experts and advocates have codified into formal design recommendations. Importantly and previously unrecognized, many commonalities exist among the strategies from each of these populations that we believe can be applied to the design of public domains for enhanced acclimation and safety for the majority of users within today’s spatial paradigm placing health and equity at its center. As pioneers in inclusive architecture, our investigative process and methodology may also serve as a template for the development of design strategies allowing communities to be increasingly open for educational, employment, recreational, and cultural exploration and participation.
How Do Architects Experience Collaborating with User/Experts? Learning from the Accessibility Advisory Council Leuven

Rights to accessibility are encoded in policies that govern architecture and other design domains. Studies show, however, that even well-considered legislative measures are insufficient to ensure inclusively designed environments. In this context the potential of user/expertise remains understudied. We therefore investigate how architects experience collaborating with user/experts, and how they understand and use their advice. We focus on collaboration with the Accessibility Advisory Council in Leuven, Belgium, which is largely composed of people with a mobility or sensory impairment and/or autism. Besides observing how architects discuss design projects with the Council, we interviewed architects and analyzed relevant (design) documents. Our analysis shows that architects experience the collaboration with user/experts as instructive, and their advice as complementary to accessibility legislation. User/experts are good at explaining what their needs are and why or how they matter; architects become convinced to apply their recommendations. They become convinced to take into account certain groups they have knowledge about (e.g. people in wheelchairs); for other groups they become convinced to do something, but have insufficient knowledge (e.g. blind people); yet other groups are largely unknown to them (e.g. people with autism or a hearing impairment). Collaborating with user/experts also affects how the architects understand inclusive design; they realize that its meaning is much broader than (wheelchair) accessibility. Moreover, beyond the projects discussed with the Council, they integrate user/expert advice also into other projects. Our study offers architects without experience with collaborating with user/experts a nuanced insight into its added value and its challenges.
I.N.S.E.C.T—Summercamp: Developing Multispecies Design Perspectives, Practices, and Discourse Through Co-creating (in) Community

We present the two-part I.N.S.E.C.T Summercamp 2022, which aimed to connect designers and researchers who are invested in multispecies perspectives for design. Co-creation was used as a strategy for organizational purposes and co-creation methods played a major role to promote innovative outcomes and strengthen the ownership of solutions and trust among participants. The two parts of the summercamp followed different strategies for co-creating the facilitation and organization of the camp experiences and led, to different degrees, to co-creation that continues beyond the duration of the camp. We apply Bentzen’s conceptual framework, “a continuity perspective on co-creation” as a means to map, describe, and reflect upon the levels, phases, and the roles of involvement of organizers, and human and non-human participants (2022). Part 1 (Case 1) was organized with the focus on designing-for, whereas Part 2 (Case 2) centered around ways of being-with other living beings, i.e., insects. Through this case study, we present and discuss a program and two formats that are based on human co-creation and that allow us to engage with our own and other species more deeply. Thereby we strengthen the field of multispecies design and respond to one of the biggest challenges designers face today: integrating post-anthropocentric perspectives into their work.
Proving Non-Termination by Acceleration Driven Clause Learning (Short Paper)

Abstract We recently proposed Acceleration Driven Clause Learning (ADCL), a novel calculus to analyze satisfiability of Constrained Horn Clauses (CHCs). Here, we adapt ADCL to transition systems and introduce ADCL-NT, a variant for disproving termination. We implemented ADCL-NT in our tool and evaluate it against the state of the art.
Measurement and Applications: Technology Enabling Aging in Place - The Supportive Smart Home

Most people as they age, wish to do so with as much independence as possible, to remain in their homes and communities with the health and social services required [1]. This is known as aging-in-place, and it has many benefits for the aging adult as they remain connected to the places and people they know. With aging-in-place, older adults are more likely to be socially, cognitively and physically active. For many healthcare systems, this can also be a benefit by delaying or avoiding institutional residential care with a subsequent reduction in system demand. Aging-in-place does not come without a cost or challenges as many aging adults need the support of formal and informal caregivers. For the latter, this tends to be family members [2].
Learning-based black box checking for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si525.svg" display="inline" id="d1e498"><mml:mi>k</mml:mi></mml:math>-safety hyperproperties

The L∗ algorithm proposed by Angluin is a standard approach to automata learning of unknown systems that generate regular languages. Black box checking (BBC) based on the L∗ algorithm is a promising formal verification of unknown systems. On the other hand, a k-safety hyperproperty is a hyperproperty that proscribes “bad things”. For example, it can express safety policies for safety-critical and safety-related systems. However, conventional BBC methods based on the L∗ algorithm focuses only on properties, not on hyperproperties. Therefore, this paper proposes an algorithm that checks whether a black box system satisfies a regular k-safety hyperproperty based on the Angluin’s L∗ algorithm. In the proposed algorithm, k-bad prefix automata that violate the regular k-safety hyperproperty are generated from the regular k-safety hyperproperty described as a HyperLTL formula. Because the generated k-bad prefix automata are finite automata, the verification of the k-safety hyperproperty for black box systems can be conducted by automata-theoretic model checking. It is demonstrated that the proposed algorithm can verify noninterference, described as a 2-safety hyperproperty, with an illustrative example.
An Improved grey wolf optimizer with weighting functions and its application to Unmanned Aerial Vehicles path planning

The grey wolf optimizer (GWO) is an optimization algorithm that draws inspiration from nature. It is an optimization algorithm based on population that iteratively searches for the optimal solution by simulating the social behavior and hunting behavior of grey wolves. It has recently been shown that GWO can be improved by the introduction of initializing, movement, selecting and updating. In this paper, we extend an improved grey wolf optimizer with weighting functions (IGWO-WFs), which include multi-modal adaptive function, sigmoid function and autoregressive function. The IGWO-WFs has 74% improved to the conventional algorithms. It can be resolved the instability and convergence issues of GWO and investigate the effectiveness of the methods through numerical simulations and the path planning of Unmanned Aerial Vehicles (UAVs).
Efficient identity-based traceable cloud data broadcasting with outsider anonymity and simultaneous individual transmission

In recent years, cloud data broadcasting system has attracted intensive attention due to its universal applicability in various Internet-of-Things enabled real-life scenarios. Cloud data broadcasting with simultaneous individual transmission is an exciting data broadcasting variant that empowers any data broadcaster to distribute encrypted broadcast data to a subscribed consumer group and the personalized transmission to each group member simultaneously. Recently [IEEE Transactions on Broadcasting (2020)], a certificate-based data broadcasting with simultaneous individual transmission scheme (Chen et al., 2020) is proposed with the aim to solve both key-escrow problem and certificate management problem, and it is claimed to provide subscriber’s outsider anonymity under the nonstandard q-type security assumption with the existence of random oracles. Unfortunately, we can show that this most recent work of Chen et al. (2020) is not secure against insider attacks, meaning that their protocol cannot trace the system’s traitor consumers who can resell the sensitive information for their own profit without valid authorization. Besides, the design of Chen et al. (2020) has significantly high communication bandwidth that is approvingly inconvenient for the Internet-of-Things facilitated low-powerful multimedia devices to reduce unnecessary burden on the encryption costs. We design a provably secure adaptive identity-based data broadcasting technique having simultaneous individual transmission with unbounded number of consumers that can concatenate two mutually orthogonal functionalities, namely consumer’s outsider anonymity and traitor consumer traceability, in a cost-efficient way. Our framework exploits the most secure and advanced asymmetric Type-3 bilinear maps to defend against fault attacks and realizes security in the standard provable security model without the existence of any random oracle. On a positive note, our construction eliminates the q-type security assumption that is so far a plausible achievement compared to all the existing schemes in this area.
Deep learning in bifurcations of particle trajectories

We show that deep learning algorithms can be deployed to study bifurcations of particle trajectories. We demonstrate this for two physical systems, the unperturbed Duffing equation and charged particles in magnetic reversal by using the AI Poincaré algorithm. We solve the equations of motion by using a fourth-order Runge–Kutta method to generate a dataset for each system. We use a deep neural network to train the data. A noise characterized by a noise scale L is added to data during the training. By using a principal component analysis, we compute the explained variance ratios for these systems which depend on the noise scale. By plotting explained ratios against the noise scale, we show that they change at bifurcations. For different values of the Duffing equation parameters, these changes are of the form of different patterns of growth-decline of the explained ratios. For the magnetic reversal, the changes are of the form of a change in the number of principal components. We comment on the use of this technique for other dynamical systems with bifurcations.