Notion Of Distance Research Articles

Trust Assessment Model Based on a Zero Trust Strategy in a Community Cloud Environment

The adoption of Cloud Computing services in everyday business life has grown rapidly in recent years due to the many benefits of this paradigm. The various collaboration tools offered by Cloud Computing have eliminated or reduced the notion of distance between entities of the same company or between different organizations. This has led to an increase in the need to share resources (data and services). Community Cloud environments have thus emerged to facilitate interactions between organizations with identical needs and with specific and high security requirements. However, establishing trust and secure resource sharing relationships is a major challenge in this type of complex and heterogeneous environment. This paper proposes a trust assessment model (SeComTrust) based on the Zero Trust cybersecurity strategy. First, the paper introduces a community cloud architecture subdivided into different security domains. Second, it presents a process for selecting a trusted organization for an exchange based on direct or recommended trust value and reputation. Finally, a system for promoting or relegating organizations in the different security domains is applied. Experimental results show that our model guarantees the scalability of a community cloud with a high success rate of secure and quality resource sharing.

Retrieving the Missing Data From Incomplete Soft Set, Incomplete Fuzzy Soft Set and Incomplete Intuitionistic Fuzzy Soft Set

Dealing with an incomplete information has been a major issue in the theory of soft sets. In this paper, we have presented an approach to deal with incomplete soft set, incomplete fuzzy soft set and incomplete intuitionistic fuzzy soft set. For this purpose, we have introduced the notion of distance between two objects (parameters) which will be used to compute the degree of interdependence between them. This approach will use the full information of known data and the relationships between them. Data filling converts an incomplete soft set into a complete one which makes the soft sets applicable not only to decision making but also to other fields.

Performing closeness: Al-ghurbah and co-presence in Syrian refugee women’s vernacular media

This ethnographic case study focuses on newly resettled refugee women from Syria to the greater Houston, Texas area and how they used smartphone technology and various social media platforms to navigate the resettlement process between 2015 and 2018. They arrived at a critical time in the United States, just having acquired refugee status and resettling in Houston at the end of the Obama era. Trump era immigration policies (known as The Muslim Ban) denied immigration and asylum from majority Muslim nations. This participatory ethnographic study examines how, under the harshest circumstances, newly arriving refugees relied on smartphones, social media platforms and digital networks to create and perform a new collective community while remaining close to displaced family members. Technological engagement and polymediated experiences are examined through the lens of co-presence, gender performativity and visual media studies and how mobile technology helped engender a new vernacular space outside of and in opposition to nativist discourse. Their transnational caregiving and emotional labour and its digital footprints are the very architecture of emerging social networks, space building, and community cohesion. Mobile technology creates new forms of connectedness, constant contact and co-presence, a state wherein people attempt to overcome physical separation anxiety by performing, reproducing and inventing new forms of ambient polymedia environments, or, forms of digital communications that blur conventional notions of presence and distance. The question here is how the rupture of displacement might drive technology usage to continually expand the ways humans connect, and more importantly, how they find new ways to feel more connected.

A New Approach Towards Intuitionistic Fuzzy Multisets

In this paper a new definition of Intuitionistic fuzzy multisets (IFMS) has been introduced. Algebraic operations on these intuitionistic fuzzy multisets are defined and their properties under these algebraic operations are studied. The author has also introduced a new notion of complement for an IFMS in which the complement of the original set is also an IFMS. The notion of distance and similarity between two IFMS’s has been defined and their properties have also been studied here. An application of IFMS in solving a medical diagnosis problem has been provided at the end.

Circuit complexity in U(1) gauge theory

In this paper, we study circuit complexity for a free vector field of a [Formula: see text] gauge theory in Coulomb gauge, and Gaussian states. We introduce a quantum circuit model with Gaussian states, including reference and target states. Using Nielsen’s geometric approach, the complexity then can be found as the shortest geodesic in the space of states. This geodesic is based on the notion of geodesic distance on the Lie group of Bogoliubov transformations equipped with a right-invariant metric. We use the framework of the covariance matrix to compute circuit complexity between Gaussian states. We apply this framework to the free vector field in general dimensions where we compute the circuit complexity of the ground state of the Hamiltonian.

Behavioral Analysis and Individual Tracking Based on Kalman Filter: Application in an Urban Environment.

In order to improve behavioral analysis systems in urban environments, this paper proposes, using data extracted from video surveillance cameras, a tracking method through two approaches. The first approach consists in comparing the position of people between two images of a video and to perform tracking by proximity. The second method using Kalman filters is based on the anticipation of the position of an individual in the upcoming image. The use of this method proves to be more efficient as it allows continuing a detection even when people cross each other or when they pass behind obstacles. The use of Kalman filters in this domain provides a new approach to obtain reliable tracking and information on speed and trajectory variations. The proposed method is innovative in the way the tracking is performed and the results are exploited. Experiments were conducted in a real situation and showed that the use of some elements of the first method could be reused to integrate a notion of distance in the method based on the Kalman filter and thus improve the latter both in tracking and in detecting of abnormal behavior. This article deals with the functioning of the two methods as well as the results obtained with the same scenarios. The experimentation concludes through concrete results that the Kalman filter method is more efficient than the proximity method alone. A sample result is available online for two of the seven videos used in this article (accessed on 19 July 2021).

Wiener, edge-Wiener, and vertex-edge-Wiener index of Basilica graphs

We determine the exact value of the Wiener index, the edge-Wiener index, and the vertex-edge-Wiener index of the Basilica graphs, i.e., the sequence of finite Schreier graphs associated with the action of the Basilica group on the rooted binary tree. Moreover, we give a formula for the total distance of every vertex in the Basilica graphs, and we are able to make it explicit for some special vertices. We finally introduce the notions of asymptotic Wiener index and asymptotic total distance, which are compatible with that of convergence of the sequence of finite Basilica graphs to an infinite orbital limit graph in the Gromov–Hausdorff topology: the asymptotic values are explicitly computed.

A journey through mapping space: characterising the statistical and metric properties of reduced representations of macromolecules

A mapping of a macromolecule is a prescription to construct a simplified representation of the system in which only a subset of its constituent atoms is retained. As the specific choice of the mapping affects the analysis of all-atom simulations as well as the construction of coarse-grained models, the characterisation of the mapping space has recently attracted increasing attention. We here introduce a notion of scalar product and distance between reduced representations, which allows the study of the metric and topological properties of their space in a quantitative manner. Making use of a Wang–Landau enhanced sampling algorithm, we exhaustively explore such space, and examine the qualitative features of mappings in terms of their squared norm. A one-to-one correspondence with an interacting lattice gas on a finite volume leads to the emergence of discontinuous phase transitions in mapping space, which mark the boundaries between qualitatively different reduced representations of the same molecule.Graphicabstract

Distanciamiento social y COVID-19. Distancias y proximidades desde una perspectiva relacional

As part of the global response to COVID-19, categorized by the WHO as a pandemic, social distancing has emerged as a key concept in the management of the bioemergency. This article discusses social distancing from a sociological perspective, drawing on Simmel, Cantó-Milà and Sabido Ramos’ notions of proximity and distance. We intend to illustrate the implicit and explicit meanings and dimensions given to the concepts of social distance and distancing during the initial months of the pandemic, along with their impact on relationships, interactions, and ties. We reflect on the function of framing all social relations in terms of distance and proximity, analytically differentiating between the concepts of relationship, interaction, and ties.

Neighborhood-Based Information Costs

We derive a new cost of information in rational inattention problems, the neighborhood-based cost functions, starting from the observation that many settings involve exogenous states with a topological structure. These cost functions are uniformly posterior separable and capture notions of perceptual distance. This second property ensures that neighborhood-based costs, unlike mutual information, make accurate predictions about behavior in perceptual experiments. We compare the implications of our neighborhood-based cost functions with those of the mutual information in a series of applications: perceptual judgments, the general environment of binary choice, regime-change games, and linear-quadratic-Gaussian settings. (JEL C70, D11, D82, D83, D91)

A Randomized Greedy Algorithm for Piecewise Linear Motion Planning

We describe and implement a randomized algorithm that inputs a polyhedron, thought of as the space of states of some automated guided vehicle R, and outputs an explicit system of piecewise linear motion planners for R. The algorithm is designed in such a way that the cardinality of the output is probabilistically close (with parameters chosen by the user) to the minimal possible cardinality.This yields the first automated solution for robust-to-noise robot motion planning in terms of simplicial complexity (SC) techniques, a discretization of Farber’s topological complexity TC. Besides its relevance toward technological applications, our work reveals that, unlike other discrete approaches to TC, the SC model can recast Farber’s invariant without having to introduce costly subdivisions. We develop and implement our algorithm by actually discretizing Macías-Virgós and Mosquera-Lois’ notion of homotopic distance, thus encompassing computer estimations of other sectional category invariants as well, such as the Lusternik-Schnirelmann category of polyhedra.

Optimal Manipulation of Voting Rules

Complexity of voting manipulation is a prominent research topic in computational social choice. The voting manipulation literature usually assumes that the manipulator is only concerned with improving the outcome of the election from her perspective. However, in practice, the manipulator may also be reluctant to lie, i.e., she may have a preference for submitting a vote that does not deviate too much from her true ranking of the candidates. In this paper, we study the complexity of finding a manipulative vote that achieves the manipulator's goal yet is as close as possible to her true preference order. We analyze this problem for three natural notions of closeness, namely, swap distance, footrule distance, and maximum displacement distance, and a variety of voting rules, such as scoring rules, Bucklin, Copeland, and Maximin. For all three distances, we obtain polynomial-time algorithms for all scoring rules and Bucklin and hardness results for Copeland and Maximin.

Children’s documentaries: distance and ethics in European storytelling about the wider world

ABSTRACT The material challenges of funding, commissioning and distribution that are well known to inhibit production of children’s factual content about other countries and cultures operate in parallel with challenges arising from the moral responsibilities inherent in what Roger Silverstone called “the problem of proper distance”. By that he signified a “moral category” requiring filmmakers to provide “context as well as imagination” and be willing to “recognise the other in her sameness and difference”. “Distance” and “difference” have become at once more significant but also more ambiguous at a time of mass forced migration, in which traditions, religions and cultures from distant places are brought together in physical proximity. Based on input from cross-cultural dialogues, screenings and interviews involving European producers of children’s documentaries, this article explores dilemmas and experiences faced in representing the backgrounds and stories of children who arrived in Europe from Syria, Iraq, Afghanistan and elsewhere in the mid-2010s. It shows the resonance of Silverstone’s thinking by revealing that many practitioners themselves apply notions of closeness and distance, both physically and metaphorically, in their choices about combining the familiar and unfamiliar and co-creating content with child participants. IMPACT SUMMARY a. Prior State of Knowledge: Existing power imbalances between filmmaker and subject/participant are accentuated when documentaries are made about vulnerable children. Studies have pinpointed competing pressures to tell a compelling story, respect privacy and provide background, while avoiding exoticism, didacticism and cultural preconceptions. b. Novel Contributions: Practitioners’ spontaneous references to “distance” when discussing their filming of refugee children demonstrate that Silverstone’s concept of “proper distance” as a “moral category” can be operationalised in co-creating content with documentary participants and evaluating the merits of such documentaries. c. Practical Implications: Creatives and commissioning editors responsible for children’s factual content about other cultures can use the findings to calibrate how they convey children’s “sameness” and “difference” with empathy and respect. Such content’s relevance for promoting social cohesion also matters to policymakers.

Blackening Aesthetic Experience

AbstractContemporary philosophy of art generally assumes that aesthetic experience is constituted by a certain ontological-phenomenological structure: the apprehension by a subject of an object. This article explores an underexamined critique of this philosophical model found within the black intellectual and artistic tradition. I will specifically focus on the version of this critique proposed by the similarly underexamined black philosophers Adrian Piper and Fred Moten. This critique, which I dub the subjectivizing concern, takes issue with the notion of ontological distance that I argue defines the subject-object model. I define ontological distance as the removal and alienation of the subject’s fundamental sense of self from that of so-called objects. The subjectivizing concern holds that this distance is not value neutral. Rather, the subject-object model is considered to be directly entwined with projects and practices of aesthetic and extraesthetic racism and antiblackness. After offering Piper’s own model of aesthetic experience—which she dubs catalysis—as an alternative, I propose three possible ways in which the subject-object model can be conceived as tied to antiblack racism.

Uniqueness questions in a scaling-rotation geometry on the space of symmetric positive-definite matrices

Jung et al. [7] introduced a geometric structure on Sym+(p), the set of p×p symmetric positive-definite matrices, based on eigen-decomposition. Eigenstructure determines both a stratification of Sym+(p), defined by eigenvalue multiplicities, and fibers of the “eigen-composition” map F:M(p):=SO(p)×Diag+(p)→Sym+(p). When M(p) is equipped with a suitable Riemannian metric, the fiber structure leads to notions of scaling-rotation distance between X,Y∈Sym+(p), the distance in M(p) between fibers F−1(X) and F−1(Y), and minimal smooth scaling-rotation (MSSR) curves, images in Sym+(p) of minimal-length geodesics connecting two fibers. In this paper we study the geometry of the triple (M(p),F,Sym+(p)), focusing on some basic questions: For which X,Y is there a unique MSSR curve from X to Y? More generally, what is the set M(X,Y) of MSSR curves from X to Y? This set is influenced by two potential types of non-uniqueness. We translate the question of whether the second type can occur into a question about the geometry of Grassmannians Gm(Rp), with m even, that we answer for p≤4 and p≥11. Our method of proof also yields an interesting half-angle formula concerning principal angles between subspaces of Rp whose dimensions may or may not be equal. The general-p results concerning MSSR curves and scaling-rotation distance that we establish here underpin the explicit p=3 results in Groisser et al. [5]. Addressing the uniqueness-related questions requires a thorough understanding of the fiber structure of M(p), which we also provide.

A New Evolutionary Approach to Optimal Sensor Placement in Water Distribution Networks

The sensor placement problem is modeled as a multi-objective optimization problem with Boolean decision variables. A new multi objective evolutionary algorithm (MOEA) is proposed for approximating and analyzing the set of Pareto optimal solutions. The evaluation of the objective functions requires the execution of a hydraulic simulation model of the network. To organize the simulation results a data structure is proposed which enables the dynamic representation of a sensor placement and its fitness as a heatmap. This allows the definition of information spaces, in which the fitness of a placement can be represented as a matrix or, in probabilistic terms as a histogram. The key element in the new algorithm is this probabilistic representation which is embedded in a space endowed with a metric based on a specific notion of distance. Among several distances between probability distributions the Wasserstein (WST) distance has been selected: WST has enabled to derive new genetic operators, indicators of the quality of the Pareto set and criteria to choose among the Pareto solutions. The new algorithm has been tested on a benchmark water distribution network with two objective functions showing an improvement over NSGA-II, in particular for low generation counts, making it a good candidate for expensive black-box multi-objective optimization

Replacing the Notion of Spacetime Distance by the Notion of Correlation

Spacetime is conventionally viewed as a stage on which actors, in the form of massive and massless matter, move. In this study, we explore what may lie beyond this picture. The starting point is the observation that quantum field fluctuations are the more strongly correlated the shorter their spacetime distance. The notion of spacetime distance can, therefore, be replaced by the notion of correlation strength. This suggests a new picture in which the abstract 2-point and multi-point correlations are the primary structure, a picture which is essentially information-theoretic. In the low energy regime, the secondary notions of spacetime and of matter would then emerge as approximate representations of the abstract correlators, namely, in the form of Feynman rules on curved spacetime.

On a minimum enclosing ball of a collection of linear subspaces

This paper concerns the minimax center of a collection of linear subspaces. For k-dimensional subspaces of an n-dimensional vector space, this can be cast as finding the center of a minimum enclosing ball on a Grassmann manifold. For subspaces of differing dimension, the setting becomes a disjoint union of Grassmannians rather than a single manifold, and the problem is no longer well-defined. However, natural geometric maps exist between these manifolds with a well-defined notion of distance for the images of the subspaces under the mappings. Solving the problem in this context leads to a candidate minimax center on each of the constituent manifolds, but does not provide intuition about which candidate is the best representation of the data. Additionally, the solutions of different rank are generally not nested so a deflationary approach will not suffice, and the problem must be solved independently on each manifold. We propose an optimization problem parametrized by the rank of the minimax center. The solution is computed with a subgradient algorithm applied to the dual problem. By scaling the objective and penalizing the information lost by the rank-k minimax center, we jointly recover an optimal dimension, k⁎, and a subspace at the center of the minimum enclosing ball, U⁎, that best represents the data.

Probing Quantum Speed Limits with Ultracold Gases.

Quantum speed limits (QSLs) rule the minimum time for a quantum state to evolve into a distinguishable state in an arbitrary physical process. These fundamental results constrain a notion of distance traveled by the quantum state, known as the Bures angle, in terms of the speed of evolution set by nonadiabatic energy fluctuations. I theoretically propose how to measure QSLs in an ultracold quantum gas confined in a time-dependent harmonic trap. In this highly-dimensional system of continuous variables, quantum tomography is prohibited. Yet, QSLs can be probed whenever the dynamics is self-similar by measuring as a function of time the cloud size of the ultracold gas. This makes it possible to determine the Bures angle and energy fluctuations, as I discuss for various ultracold atomic systems.

Recurrence analysis of extreme event-like data

Abstract. The identification of recurrences at various timescales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyze an extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in the USA and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.