Chun Hei Michael Shiu, Hei Victor Cheng, Lele Wang
The graph alignment problem aims to identify the vertex correspondence between two correlated graphs. Most existing studies focus on the scenario in which the two graphs share the same vertex set. However, in many real-world applications, such as computer vision, social network analysis, and bioinformatics, the task often involves locating a small graph pattern within a larger graph. Existing graph alignment algorithms and analysis cannot directly address these scenarios because they are not designed to identify the specific subset of vertices where the small graph pattern resides within the larger graph. Motivated by this limitation, we introduce the subgraph alignment problem, which seeks to recover both the vertex set and/or the vertex correspondence of a small graph pattern embedded in a larger graph. In the special case where the small graph pattern is an induced subgraph of the larger graph and both the vertex set and correspondence are to be recovered, the problem reduces to the subgraph isomorphism problem, which is NP-complete in the worst case. In this paper, we formally formulate the subgraph alignment problem by proposing the Erdos-Renyi subgraph pair model together with some appropriate recovery criterion. We then establish almost-tight information-theoretic results for the subgraph alignment problem and present some novel approaches for the analysis.
We theoretically and numerically investigate helical Ince-Gaussian modes, hIGp,q(x, y, ε). Explicit analytical expressions are derived that describe dependence of the orbital angular momentum of the helical Ince-Gaussian modes at p=2, 3, 4, 5 on the ellipticity parameter ε. For this purpose, the earlier obtained expansions of Ince-Gaussian modes in terms of Hermite-Gaussian modes are used. We demonstrate that in general the orbital angular momentum is an even function of ε, which changes non-monotonically when ε varies from zero to infinity. At zero ε, the orbital angular momentum is equal to the index q of the Ince-Gaussian mode, whereas at ε=∞, the orbital angular momentum is [q(p–q+1)]1/2. Topological charge of the helical Ince-Gaussian mode depends on ε and is equal to the index q at ε=0 and to the index p at ε=∞.
This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in neuroscience have been treated separately, in contrast to physics approaches, where the relationship of entropy production with heat is a central idea. It is argued here that also in neural systems, information and energy can be considered within the same theoretical framework. Starting from basic ideas of thermodynamics and information theory on a classic Brownian particle, it is shown how noisy neural networks can infer its probabilistic motion. The decoding of the particle motion by neurons is performed with some accuracy, and it has some energy cost, and both can be determined using information thermodynamics. In a similar fashion, we also discuss how neural networks in the brain can learn the particle velocity and maintain that information in the weights of plastic synapses from a physical point of view. Generally, it is shown how the framework of stochastic and information thermodynamics can be used practically to study neural inference, learning, and information storing.
We study the problem of weakly private information retrieval (PIR) when there is heterogeneity in servers' trustworthiness under the maximal leakage (Max-L) metric and mutual information (MI) metric. A user wishes to retrieve a desired message from N non-colluding servers efficiently, such that the identity of the desired message is not leaked in a significant manner; however, some servers can be more trustworthy than others. We propose a code construction for this setting and optimize the probability distribution for this construction. For the Max-L metric, it is shown that the optimal probability allocation for the proposed scheme essentially separates the delivery patterns into two parts: a completely private part that has the same download overhead as the capacity-achieving PIR code, and a non-private part that allows complete privacy leakage but has no download overhead by downloading only from the most trustful server. The optimal solution is established through a sophisticated analysis of the underlying convex optimization problem and a reduction between the homogeneous setting and the heterogeneous setting. For the MI metric, the homogeneous case is studied first for which the code can be optimized with an explicit probability assignment, while a closed-form solution becomes intractable for the heterogeneous case. Numerical results are provided for both cases to corroborate the theoretical analysis.
To address the fierce competition for corporate innovation in the digital economy, this study introduces knowledge integration capability as a mediating variable in light of social information processing theory, and explores the mechanism of team learning climate on innovation performance. Data were collected from a sample of 184 team members for statistical analysis, and Statistical methods such as descriptive statistical analysis, correlation analysis, and regression analysis were used to verify the study hypotheses through SPSS and Amos software, and the results showed that: (1) Team learning climate has a significant positive effect on knowledge integration capability. (2) Team learning climate has a significant positive effect on innovation performance. (3) Knowledge integration capability has a significant positive effect on innovation performance. (4) Knowledge integration capability partially mediates the role between team learning climate and innovation performance. The results proved the perspective of knowledge integration capability for the mechanism of team learning climate on innovation performance from the perspective of knowledge integration capability, and provided theoretical references for creating a learning climate in companies to promote members’ knowledge learning and enhance innovation performance.
The aim of this research is to study the specifics of the road accident rate formation processes in regions of the Russian Federation (2021) using information-entropic analysis. The typical research approaches (correlation-regression, factorial analyses, simulation modelling, etc.) do not always allow us to identify its specificity. It is impossible to evaluate the quality of the researched process’s structure using these methods. However, this knowledge is required to understand the distinctions between high-quality road safety management and its opposite. In order to achieve the goal of the research methodology based on the use of the classical approaches of C. Shannon, the quantitative value of information entropy <i>H</i> was elaborated. The key components of this method are the modelling of the cause-and-effect chain of road accident rate formation and the consideration of the relative significances of individual blocks of the process in achieving the final result. During the research the required statistical data were collected and the structure of the road accident rate formation process in 82 regions of the Russian Federation in the format “Population <i>P</i>—Fleet of vehicles <i>N<sub>Vh</sub></i>—Road Traffic Accidents <i>N<sub>RA</sub></i>—RTA Victims <i>N<sub>V</sub></i>—Fatality Cases <i>N<sub>D</sub></i>” was analyzed. The fact that the structure of the road accident rate formation process is extremely specific in different Russian regions was shown. Exactly this specificity forms the degree of ambiguity in the state of Russian regional road safety provision systems in terms of the probability of death in road accidents. The main conclusion of this research is that information-entropic analysis can be successfully used to assess the structural quality of road safety systems.
The negation of probability distribution is a new perspective from which to obtain information. Dempster–Shafer (D–S) evidence theory, as an extension of possibility theory, is widely used in decision-making-level fusion. However, how to reasonably construct the negation of basic probability assignment (BPA) in D–S evidence theory is an open issue. This paper proposes a new negation of BPA, logarithmic negation. It solves the shortcoming of Yin’s negation that maximal entropy cannot be obtained when there are only two focal elements in the BPA. At the same time, the logarithmic negation of BPA inherits the good properties of the negation of probability, such as order reversal, involution, convergence, degeneration, and maximal entropy. Logarithmic negation degenerates into Gao’s negation when the values of the elements all approach 0. In addition, the data fusion method based on logarithmic negation has a higher belief value of the correct target in target recognition application.
Consider $L$ users, who each hold private data, and one fusion center who must compute a function of the private data of the $L$ users. To accomplish this task, each user may utilize a public and noiseless broadcast channel in a non-interactive manner. In this setting, and in the absence of any additional resources such as secure links, we study the optimal communication rates and minimum information leakages on the private user data that are achievable. Specifically, we study the information leakage of the user data at the fusion center (beyond the knowledge of the function output), as well as at predefined groups of colluding users who eavesdrop one another. We derive the capacity region when the user data is independent, and inner and outer regions for the capacity region when the user data is correlated.
Nelson Luis Manuel, Nihat İnanç, Mustafa Yasin Erten
Formations or groups of robots become essential in cases where a single robot is insufficient to satisfy a given task. With an increasingly automated world, studies on various topics related to robotics have been carried out in both the industrial and academic arenas. In this paper, the control of the formation of differential mobile robots based on the leader-follower approach is presented. The leader's movement is based on the least cost path obtained by the A-star algorithm, thus ensuring a safe and shortest possible route for the leader. Follower robots track the leader's position in real time. Based on this information and the desired distance and angle values, the leader robot is followed. To ensure that the followers do not collide with each other and with the obstacles in the environment, a controller based on Artificial Potential Fields is designed. Stability analysis using Lyapunov theory is performed on the linearized model of the system. To verify the implemented technique, a simulator was designed using the MATLAB programming language. Seven experiments are conducted under different conditions to show the performance of the approach. The distance and orientation errors are less than 0.1 meters and 0.1 radians, respectively. Overall, mobile robots are able to reach the goal position, maintaining the desired formation, in finite time.
Electrical engineering. Electronics. Nuclear engineering, Mechanical engineering and machinery
Patrick Kierkegaard, Timothy Hicks, A. Joy Allen
et al.
Abstract Background The purpose of this study is to develop a theory-driven understanding of the barriers and facilitators underpinning physicians’ attitudes and capabilities to implementing SARS-CoV-2 point-of-care (POC) testing into primary care practices. Methods We used a secondary qualitative analysis approach to re-analyse data from a qualitative, interview study of 22 primary care physicians from 21 primary care practices across three regions in England. We followed the three-step method based on the Behaviour Change Wheel to identify the barriers to implementing SARS-CoV-2 POC testing and identified strategies to address these challenges. Results Several factors underpinned primary care physicians’ attitudes and capabilities to implement SARS-CoV-2 POC testing into practice. First, limited knowledge of the SARS-CoV-2 POC testing landscape and a demanding workload affected physicians’ willingness to use the tests. Second, there was scepticism about the insufficient evidence pertaining to the clinical efficacy and utility of POC tests, which affected physicians’ confidence in the accuracy of tests. Third, physicians would adopt POC tests if they were prescribed and recommended by authorities. Fourth, physicians required professional education and training to increase their confidence in using POC tests but also suggested that healthcare assistants should administer the tests. Fifth, physicians expressed concerns about their limited workload capacity and that extra resources are needed to accommodate any anticipated changes. Sixth, information sharing across practices shaped perceptions of POC tests and the quality of information influenced physician perceptions. Seventh, financial incentives could motivate physicians and were also needed to cover the associated costs of testing. Eighth, physicians were worried that society will view primary care as an alternative to community testing centres, which would change perceptions around their professional identity. Ninth, physicians’ perception of assurance/risk influenced their willingness to use POC testing if it could help identify infectious individuals, but they were also concerned about the risk of occupational exposure and potentially losing staff members who would need to self-isolate. Conclusions Improving primary care physicians’ knowledgebase of SARS-CoV-2 POC tests, introducing policies to embed testing into practice, and providing resources to meet the anticipated demands of testing are critical to implementing testing into practice.
Kyle Schick-Poland, Abdullah Makkeh, Aaron J. Gutknecht
et al.
Conceptually, partial information decomposition (PID) is concerned with separating the information contributions several sources hold about a certain target by decomposing the corresponding joint mutual information into contributions such as synergistic, redundant, or unique information. Despite PID conceptually being defined for any type of random variables, so far, PID could only be quantified for the joint mutual information of discrete systems. Recently, a quantification for PID in continuous settings for two or three source variables was introduced. Nonetheless, no ansatz has managed to both quantify PID for more than three variables and cover general measure-theoretic random variables, such as mixed discrete-continuous, or continuous random variables yet. In this work we will propose an information quantity, defining the terms of a PID, which is well-defined for any number or type of source or target random variable. This proposed quantity is tightly related to a recently developed local shared information quantity for discrete random variables based on the idea of shared exclusions. Further, we prove that this newly proposed information-measure fulfills various desirable properties, such as satisfying a set of local PID axioms, invariance under invertible transformations, differentiability with respect to the underlying probability density, and admitting a target chain rule.
This paper presents a new foundational approach to information theory based on the concept of the information efficiency of a recursive function, which is defined as the difference between the information in the input and the output. The theory allows us to study planar representations of various infinite domains. Dilation theory studies the information effects of recursive operations in terms of topological deformations of the plane. I show that the well-known class of finite sets of natural numbers behaves erratically under such transformations. It is subject to phase transitions that in some cases have a fractal nature. The class is \emph{semi-countable}: there is no intrinsic information theory for this class and there are no efficient methods for systematic search. There is a relation between the information efficiency of the function and the time needed to compute it: a deterministic computational process can destroy information in linear time, but it can only generate information at logarithmic speed. Checking functions for problems in $NP$ are information discarding. Consequently, when we try to solve a decision problem based on an efficiently computable checking function, we need exponential time to reconstruct the information destroyed by such a function. At the end of the paper I sketch a systematic taxonomy for problems in $NP$.
Kerry Wrighton-Araneda, Cristián Valdebenito, Gabriel Abarca
et al.
This work contains data on the computational, structural, and electronic characterization of supported ionic liquids phases anchored to copper nanoparticles using Density Functional theory calculations. The data supplement the paper “Interaction of supported ionic liquids phases onto copper nanoparticles: A Density Functional Theory study” [1], based on the adsorption of ionic liquid onto a Cu nanoparticle is analyzed from a chemical and physical point of view. The chemical analysis is based on Atoms in Molecule theory (AIM) and allows us to differentiate the chemical binding nature between ionic liquid and copper nanoparticle. On the other hand, the energy decomposition analysis based on absolutely localized molecular orbital (ALMO-EDA) describes the physical contributions that govern the interaction between ionic liquid and the copper nanoparticles. Herein, detailed and extended information in the synthesis and computational characterization are presented.
Computer applications to medicine. Medical informatics, Science (General)
The hypodermic needle theory is a prominent theory in social media that affects the understanding, attitudes, and behavior of individuals. In this viewpoint, media is a powerful and dangerous source because the user or audience is vulnerable against the effect of a certain message. In this study, we assess the relationship between this theory in the field of information technology with two person-centered approaches of constructionist or discourse analytic approach and the critical theory approach. Moreover, the libraries’ role in vaccinating users against this theory by increasing their knowledge is shown
Information resources (General), Transportation and communications
The Dempster-Shafer (D-S) theory is widely applied in various fields involved with multi-sensor information
fusion for radar target tracking, which offers a useful tool for decision-making. However, the application of D-S evidence theory has some limitations when evidences are conflicting. This paper proposed a new method combining the Pignistic probability distance and the Deng entropy to address the problem. First, the Pignistic probability distance is applied to measure the conflict degree of evidences. Then, the uncertain information is measured by introducing the Deng entropy. Finally, the evidence correction factor is calculated for modifying the bodies of evidence, and the Dempster’s combination
rule is adopted for evidence fusion. Simulation experiments illustrate the effectiveness of the proposed method dealing with conflicting evidences.
Technology, Motor vehicles. Aeronautics. Astronautics
Flash memory devices are winning the competition for storage density against magnetic recording devices. This outcome results from advances in physics that allow storage of more than one bit per cell, coupled with advances in signal processing that reduce the effect of physical instabilities. Constrained codes are used in storage to avoid problematic patterns. Recently, we introduced binary symmetric lexicographically-ordered constrained codes (LOCO codes) for data storage and data transmission. This paper introduces simple constrained codes that support non-binary physical substrates; multi, triple, quad, and the currently-in-development penta-level cell (M/T/Q/P-LC) Flash memories. The new codes can be easily modified if problematic patterns change with time. These codes are designed to mitigate inter-cell interference, which is a critical source of error in Flash devices. The occurrence of errors is a consequence of parasitic capacitances in and across floating gate transistors, resulting in charge propagation from cells being programmed to the highest charge level to neighboring cells being programmed to lower levels. The new codes are called $q$-ary asymmetric LOCO codes (QA-LOCO codes), and the construction subsumes codes previously designed for single-level cell (SLC) Flash devices (A-LOCO codes). QA-LOCO codes work for a Flash device with any number, $q$, of levels per cell. For $q \geq 4$, we show that QA-LOCO codes can achieve rates greater than $0.95 \log_2 q$ information bits per coded symbol. The complexity of encoding and decoding is modest, and reconfiguring a code is as easy as reprogramming an adder. Capacity-achieving rates, affordable encoding-decoding complexity, and ease of reconfigurability support the growing development of M/T/Q/P-LC Flash memory devices, as well as lifecycle management as the characteristics of these devices change with time.