Information Measures Research Articles

Wear diagnosis for rail profile data using a novel multidimensional scaling clustering method

AbstractThe diagnosis of railway system faults is significant for its comfort, efficiency, and safety. The rail surface wear is the key impact factor when considering the health conditions of rails. This paper accomplishes contactless rail wear diagnosis by using multidimensional scaling based on a novel informational dissimilarity measure (IDM) to cluster intact and different worn rail profile data. The IDM uses weighted‐probability distribution of dispersion patterns to extract accurate time domain features from rail profile data, and the loss of information is minimized, which can greatly improve the accuracy for wear diagnosis. All the analyzing data for real experiments are collected by a laser scanner camera on an inspection car, where heavy‐haul railway rails with different types of surface wear are inspected. Experimental results with simulated and reality‐based data show that the proposed methods can identify worn profile data and discriminate different types of worn profiles more effectively when compared with existing methods. Thus, the proposed method offers a new thinking for the diagnosis of rail surface wear for heavy‐haul railways.

Implementation of the electronic health record in the German healthcare system: an assessment of the current status and future development perspectives considering the potentials of health data utilisation by representatives of different stakeholder groups.

The digitalisation of the German healthcare system enables a wide range of opportunities to utilize healthcare data. The implementation of the EHR in January 2021 was a significant step, but compared to other European countries, the implementation of the EHR in the German healthcare system is still at an early stage. The aim of this paper is to characterise the structural factors relating to the adoption of the EHR in more detail from the perspective of representatives of stakeholders working in the German healthcare system and to identify existing barriers to implementation and the need for change. Qualitative expert interviews were conducted with one representative from each of the stakeholder groups health insurance, pharmacies, healthcare research, EHR development and panel doctors. The interviews with the various stakeholders revealed that the implementation process of the EHR is being delayed by a lack of a viable basis for decision-making, existing conflicts of interest and insufficient consideration of the needs of patients and service providers, among other things. The current status of EHR implementation is due to deficiency in legal regulations as well as structural problems and the timing of the introduction. For instance, the access rights of various stakeholders to the EHR data and the procedure in the event of a technical failure of the telematics infrastructure are remain unclear. In addition, insufficient information and communication measures have not led to the desired acceptance of EHR use among patients and service providers.

New information measures for linear Diophantine fuzzy sets and their applications with LDF-ARAS on data storage system selection problem

In addition to membership and non-membership degrees, linear Diophantine fuzzy set (LDFS) incorporates two reference parameters in fuzzy set definition to represent human judgment more comprehensively. It also provides flexibility in updating the decision setting by changing the meaning of the reference parameters when required by the decision-maker. Information measures in fuzzy sets have many application areas in the literature. Especially, distance and entropy measures are utilized in multiple attribute decision-making (MADM) field. Distance measures are needed by distance-based methods like TOPSIS and EDAS because their alternative ranking procedure is based on measuring the distances between alternatives and some artificial ideal or average solutions. Entropy measure is a very important tool being used in objective attribute weighting procedures of MADM applications. Thus, new distance and entropy measure propositions for LDFS are the first contribution of the study. Also, Additive Ratio Assessment (ARAS) method is extended into LDFS (LDF-ARAS) for the first time in the literature as a second contribution. In this extension, we selected ARAS as one of the most cited tools because it is found flexible and easily adaptable by researchers who do not have any background in MADM. The proposed entropy measure is integrated with the objective attribute weighting procedure of the novel LDF-ARAS approach. The third contribution is the newly developed decision model proposed for a real-life data storage system (DSS) selection problem. Three DSS options were evaluated with respect to thirteen attributes by five skilled and well-educated experts and LDF-ARAS was performed to rank alternatives. The entropy-based LDF-ARAS approach was validated by comparing the results of six different applications. In the first three, different entropy formulas are used and in the last three, these entropy measures are integrated with LDF-TOPSIS. All six comparisons gave similar alternative rankings.

Measurement of information content of Perovskite solar cell’s synthesis descriptors related to performance parameters

AbstractPerovskite solar cells (PSC) are formed by different layers composed of thin films of various materials, in which the properties of every thin layer affect the performance of the cell. The identification of those most relevant properties (or descriptors) has a significant impact on the optimization and cost reduction of the Perovskite solar cell. This relevance is typically evaluated by adjusting a model using subsets of features, but in the present work, we propose to use the mutual information measure to quantify the statistical association between input descriptors and Perovskite solar cell performance parameters (Voc, Jsc, FF, PCE). As a result, it is found that ion X is the factor that most impacts the performance of the solar cell. On the other hand, variables such as band gap, Perovskite layer thickness, and A and B ions are also important. In this work, we identify some of the most important factors affecting Perovskite solar cells’ performance, and it could help to improve the efficiency of Perovskite solar cells. In addition, this proposed method could also be applied to other types of functional coatings, thin films, and surfaces.

Strong Asymptotic Composition Theorems for Mutual Information Measures

We characterize the growth of the Sibson and Arimoto mutual informations and α-maximal leakage, of any order that is at least unity, between a random variable and a growing set of noisy, conditionally independent and identically-distributed observations of the random variable. Each of these measures increases exponentially fast to a limit that is order- and measure-dependent, with an exponent that is order- and measure-independent.

Mfind: a tool for DNA barcode analysis in angiosperms and its relationship with microsatellites using a sliding window algorithm.

Mfind is a tool to analyze the impact of microsatellite presence on DNA barcode specificity. We found a significant correlation between barcode entropy and microsatellite count in angiosperm. Genetic barcodes and microsatellites are some of the identification methods in taxonomy and biodiversity research. It is important to establish a relationship between microsatellite quantification and genetic information in barcodes. In order to clarify the association between the genetic information in barcodes (expressed as Shannon's Measure of Information, SMI) and microsatellites count, a total of 330,809 DNA barcodes from the BOLD database (Barcode of Life Data System) were analyzed. A parallel sliding-window algorithm was developed to compute the Shannon entropy of the barcodes, and this was compared with the quantification of microsatellites like (AT)n, (AC)n, and (AG)n. The microsatellite search method utilized an algorithm developed in the Java programming language, which systematically examined the genetic barcodes from an angiosperm database. For this purpose, a computational tool named Mfind was developed, and its search methodology is detailed. This comprehensive study revealed a broad overview of microsatellites within barcodes, unveiling an inverse correlation between the sumz of microsatellites count and barcodes information. The utilization of the Mfind tool demonstrated that the presence of microsatellites impacts the barcode information when considering entropy as a metric. This effect might be attributed to the concise length of DNA barcodes and the repetitive nature of microsatellites, resulting in a direct influence on the entropy of the barcodes.

Changes in high-order interaction measures of synergy and redundancy during non-ordinary states of consciousness induced by meditation, hypnosis, and auto-induced cognitive trance

High-order interactions are required across brain regions to accomplish specific cognitive functions. These functional interdependencies are reflected by synergistic information that can be obtained by combining the information from all the sources considered and redundant information (i.e., common information provided by all the sources). However, electroencephalogram (EEG) functional connectivity is limited to pairwise interactions thereby precluding the estimation of high-order interactions. In this multicentric study, we used measures of synergistic and redundant information to study in parallel the high-order interactions between five EEG electrodes during three non-ordinary states of consciousness (NSCs): Rajyoga meditation (RM), hypnosis, and auto-induced cognitive trance (AICT). We analyzed EEG data from 22 long-term Rajyoga meditators, nine volunteers undergoing hypnosis, and 21 practitioners of AICT. We here report the within-group changes in synergy and redundancy for each NSC in comparison with their respective baseline. During RM, synergy increased at the whole brain level in the delta and theta bands. Redundancy decreased in frontal, right central, and posterior electrodes in delta, and frontal, central, and posterior electrodes in beta1 and beta2 bands. During hypnosis, synergy decreased in mid-frontal, temporal, and mid-centro-parietal electrodes in the delta band. The decrease was also observed in the beta2 band in the left frontal and right parietal electrodes. During AICT, synergy decreased in delta and theta bands in left-frontal, right-frontocentral, and posterior electrodes. The decrease was also observed at the whole brain level in the alpha band. However, redundancy changes during hypnosis and AICT were not significant. The subjective reports of absorption and dissociation during hypnosis and AICT, as well as the mystical experience questionnaires during AICT, showed no correlation with the high-order measures. The proposed study is the first exploratory attempt to utilize the concepts of synergy and redundancy in NSCs. The differences in synergy and redundancy during different NSCs warrant further studies to relate the extracted measures with the phenomenology of the NSCs.

Farmers’ satisfaction and cooperation in conflicts about river restoration in Germany. What influence have economy and participation?

Interest conflicts between agriculture and river restoration are core biodiversity protection problems, as farmers' non-cooperation can be an obstacle to implementing river restoration processes within the context of the EU's Water Framework Directive (WFD). A central issue is ensuring farmers' satisfaction that affects their willingness to cooperate (WTC) in situations of economic losses.During the last years, participation measures were implemented to address this problem and to complement existing information and compensation measures. Focusing on the situation in Germany, we examine the effect of economic factors and procedural measures on farmers' satisfaction and WTC. For this reason, we conducted a structured telephone survey with 300 farmers impacted by river restorations. We investigated the effect of their economic situation, economic impairment, and participation processes on farmers' satisfaction with the project outcome, satisfaction with the participation process, and WTC. We conducted correlation and regression analysis to find relations and effects within the data. The analysis reveals four results: 1) Income situation, soil number of the affected land, and perception of land pressure are economic factors with (negative) effect on farmers' satisfaction. 2) Compensation and participation measures partly positively affect farmers' outcome and procedure satisfaction. 3) Direct talks to planners are mostly the salient significant participation procedure. 4) Satisfaction with the project's outcome and satisfaction with the participatory procedure have considerable explanatory power considering WTC. Our results provide essential information for policymakers and administration in biodiversity protection in general and river restoration in particular. They indicate that involving farmers in planning river restoration measures, assuring high transparency and inclusiveness, and convincing farmers of the reasonableness of the measure is of the same importance to achieve satisfaction and WTC as only focusing on compensation measures.

Evaluating Pauli Errors on Cluster States by Weighted Distances

Evaluating Pauli Errors on Cluster States by Weighted Distances

Information and communication component of the network countermeasure to national security in the military sphere

The article conceptualizes ways of forming strategic guidelines for ensuring national security in the field of countering informational and psychological threats. The elements of the national security strategy, which are potentially significant in view of the development of active forms of information operations on the part of the enemy in the modern conflict, including military ones, are considered. Emphasis is placed on the use of special operations forces units in the field of network countermeasures against threats to national security in the military sphere. Taking this into account requires the development and implementation of the public administration specific mechanisms in the field of the national security ensuring, which are aimed at countering informational and psychological threats. In particular, it is about the need to adequately represent this issue in the national security strategy by defining the specifics of network countermeasures against threats to national security in the military sphere. In particular, it is about the development of the use of new methods of remote influence on the enemy, i.e., the expansion of the space for conducting combat operations and the environments of war, the development of new forms of defense and defensive measures, the growing importance of reconnaissance and sabotage actions in the rear of the enemy, the intellectualization of wars focused on the predominant use of high-precision and robotic weapons. This causes additional tasks to creative use of open source information as well as document analysis from documents like the National Security Strategy, National Military Strategy, taking into account that the main task in the field of military security is the development of deterrence potential, combat-ready armed forces and other components of the defense forces, capable of performing complex tasks in a multidimensional space, development of the components of the defense forces and solving the problems of ensuring the defense of the state. Information measures are an integral part of the state response to threats to national security and one of the main components of the information war aimed at achieving victory in the information space.

Eye movements as predictor of cognitive improvement after cognitive remediation therapy in patients with schizophrenia.

Baseline cognitive functions of patients predicted the efficacy of cognitive remediation therapy (CRT), but results are mixed. Eye movement is a more objective and advanced assessment of cognitive functions than neuropsychological testing. We aimed to investigate the applicability of eye movements in predicting cognitive improvement after patients with schizophrenia were treated with CRT. We recruited 79 patients with schizophrenia to complete 8 weeks of CRT and assessed their cognitive improvement outcomes. Eye movements were assessed by prosaccades, antisaccades, and free-viewing tasks at baseline, and neuropsychological tests in four cognitive domains were assessed before and after treatment to calculate treatment outcomes. Predictors of demographic information, clinical characteristics, and eye movement measures at baseline on cognitive improvement outcomes were analyzed using logistic regression analysis. We further compared the predictive performance between eye movement measurements and neuropsychological test regarding the effect of CRT on cognitive improvement, and explored factors that could be affect the treatment outcomes in different cognitive domains. As operationally defined, 33 patients showed improved in cognition (improved group) and 46 patients did not (non-improved group) after CRT. Patients with schizophrenia being employed, lower directional error rate in antisaccade task, and lower the gap effect (i.e., the difference in saccadic latency between the gap condition and overlap condition) in prosaccade task at baseline predicted cognitive improvement in CRT. However, performance in the free-viewing task not associated with cognitive improvement in patients in CRT. Our results show that eye-movement prediction model predicted the effect of CRT on cognitive improvement in patients with schizophrenia better than neuropsychological prediction model in CRT. In addition, baseline eye-movements, cognitive reserve, antipsychotic medication dose, anticholinergic cognitive burden change, and number of training sessions were associated with improvements in four cognitive domains. Eye movements as a non-invasiveness, objective, and sensitive method of evaluating cognitive function, and combined saccadic measurements in pro- and anti-saccades tasks could be more beneficial than free-viewing task in predicting the effect of CRT on cognitive improvement in patients with schizophrenia.

Second-order concomitants of order statistics from bivariate Cambanis family: some information measures–estimation

In this paper, the marginal distribution of second-order concomitants of order statistics (SCOSs) from the Cambanis family is determined. An advantageous recurrence relation between single moments of SCOSs and concomitants of order statistics (COSs) is established based on the Cambanis family. We also use this family to derive an elegant beneficial recurrence relation between single moments of the SCOSs. Some information measures, such as Shannon differential entropy, differential extropy, and negative cumulative extropy (NCEX) of SCOSs based on this family, are investigated. Furthermore, we present some numerical examples to back up the theoretical findings. In addition, a set of bivariate data from the real world was examined. Finally, an estimate of a marginal variable’s scale parameter in the copula Cambanis family is obtained.

Beyond fitness: The information imparted in population states by selection throughout lifecycles

We approach the questions, what part of evolutionary change results from selection, and what is the adaptive information flow into a population undergoing selection, as a problem of quantifying the divergence of typical trajectories realized under selection from the expected dynamics of their counterparts under a null stochastic-process model representing the absence of selection. This approach starts with a formulation of adaptation in terms of information and from that identifies selection from the genetic parameters that generate information flow; it is the reverse of a historical approach that defines selection in terms of fitness, and then identifies adaptive characters as those amplified in relative frequency by fitness. Adaptive information is a relative entropy on distributions of histories computed directly from the generators of stochastic evolutionary population processes, which in large population limits can be approximated by its leading exponential dependence as a large-deviation function. We study a particular class of generators that represent the genetic dependence of explicit transitions around reproductive cycles in terms of stoichiometry, familiar from chemical reaction networks. Following Smith (2023), which showed that partitioning evolutionary events among genetically distinct realizations of lifecycles yields a more consistent causal analysis through the Price equation than the construction from units of selection and fitness, here we show that it likewise yields more complete evolutionary information measures.

Belief Inaccuracy Information Measures and Their Extensions

This work introduces belief inaccuracy information (BII) and Jensen–belief inaccuracy information (JBII), grounded in the foundational concept of basic probability assignment. The significance of these novel methodologies lies in their potential to advance the field by providing valuable insights into belief accuracy assessment. The research not only establishes these measures but also highlights their relevance in addressing critical challenges within the realm of probability assignment. Further, some results associated with these proposed information measures were established. In addition, the BII and JBII measures were examined for escort and generalized escort of basic probability assignment functions, where an escort basic probability assignment with order [Formula: see text] is constructed based on the power [Formula: see text] of a baseline basic probability assignment with a normalizing constant. Finally, this paper presents compelling results derived from the application of BII and JBII measures. A detailed simulation of Conway’s game of life cellular automaton is described, showcasing the utility of these measures in analyzing belief inaccuracies within complex dynamic systems. Furthermore, an application to ozone time series is explored, employing belief Kullback–Leibler and belief chi-square divergences. This application specifically focuses on the study of station discrepancies, revealing the versatility of the proposed measures in addressing diverse scenarios.

Research on the Volatility of China's Stock Market Returns Based on GARCH Model-Taking CSI 300 Index as an Example

The volatility of yields reflects the degree of risk in the market, and at the same time the volatility of yields is viewed as a measure of information, and high volatility is generally accompanied by large market information shocks. Therefore, it is particularly important to study the volatility of China's stock market returns so as to find out where the problems lie. In this paper, the CSI 300 index is taken as the research object, and a total of 2,671 daily closing prices from 4 January 2013 to 29 December 2023 are taken as the sample, and the GARCH family model is used to analyse this sample data, so as to derive the volatility characteristics of the CSI 300 index and to make static forecasts.

Birth Care Gaps in the Childbirth Options, Information, and Person-Centered Explanation (CHOICEs) Measure.

The objective of this study was to revise and improve the intrapartum items of the shared decision-making (SDM) measure, CH ildbirth O ptions, I nformation and person- C entered E xplanation (CHOICEs). Methodological sequential triangulation was used to select a purposive sample of 29 people who gave birth in the United States between August 2019 and June 2021. A qualitative descriptive approach was used to analyze and interpret the data. We used an interview guide with questions related to the nine intrapartum items in CHOICEs to address the question: How did decision-making occur during your most recent birth? Four major themes were identified: provider told me what to do ; communication about interventions during labor and birth ; preferences overlooked ; multiple team members . Under the theme of provider told me what to do , there was one sub-theme of induction of labor . Participants noted lack of shared decision-making, poor communication, and obstetric violence. We found the need for perinatal providers to improve communication with birthing people on topics such as fetal monitoring, induction of labor, and multiple team members who may participate in their care. Revisions of CHOICEs will include seven new items to further address birth preferences, feeling heard, and multiple team members.

Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

Parametric circular intuitionistic fuzzy information measures and multi-criteria decision making with extended TOPSIS

A computational linguistic methodology for assessing semiotic structure in prehistoric art and the meaning of southern Scandinavian Mesolithic ornamentation

Non-figurative prehistoric art is comparatively common yet challenging to decode and hence to understand. At the heart of the difficulty of assessing the presence of semiotic structure in prehistoric art is a lack of appropriate, replicable, and case-transferable methodologies. We here propose a novel approach derived from computational linguistics, in which k-skip-n-gram (skipgram) models and associated pointwise mutual information (PMI) measures are customised to the analysis of prehistoric art. In applying this methodology to a large corpus of portable art from the South Scandinavian Mesolithic, we demonstrate how the mutual relationship between individual motifs can be established. In the case of Mesolithic portable art, our analysis strongly suggests that there is no evident semiotic structure – this was likely not a form of proto-writing – but salient changes of motif occurrence over time are detectable. These changes are sensitive to changes in population density, structure, and connectedness, and may relate to increased territoriality in the Late Mesolithic. The method presented here is readily case-transferable and renders possible further linguistic and semiotic analyses of prehistoric art.

Probabilistic hesitant fuzzy multiple criteria decision-making with triangular norm based similarity and entropy measures

Existing probabilistic hesitant fuzzy set (PHFS) measures are constructed using two information measures: hesitancy and unwrapped probabilities. We argue that unifying these semantic terms in PHFS information theory is not logical. We introduce a new class of information measures for PHFSs, which address the logical wrapping of hesitant fuzzy sets (HFS) and probability. We propose several similarity measures for these sets that use the Triangular norm operator. We consider the relationship between measures of entropy and similarity and represent the axiomatic definition of PHFS entropy measures. Finally, we use case studies to demonstrate applications of these information measures. We describe two multiple-criteria decision-making algorithms. The last step is devoted to PHFS ranking procedures: one based on the score function of alternatives and the other based on the relative closeness of alternatives. This contribution describes new information measures and uses case studies to illustrate how they can be applied to decision-making processes.

Corrections to “Equivocations, Exponents, and Second-Order Coding Rates Under Various Rényi Information Measures”

Corrections to “Equivocations, Exponents, and Second-Order Coding Rates Under Various Rényi Information Measures”