Understanding the Feature Space and Decision Boundaries of Commercial WAFs Using Maximum Entropy in the Mean.

The security of a network requires the correct identification and characterization of the attacks through its ports. This involves the follow-up of all the requests for access to the networks by all kinds of users. We consider the frequency of connections and the type of connections to a network, and determine their joint probability. This leads to the problem of determining a joint probability distribution from the knowledge of its marginals in the presence of errors of measurement. Mathematically, this consists of an ill-posed linear problem with convex constraints, which we solved by the method of maximum entropy in the mean. This procedure is flexible enough to accommodate errors in the data in a natural way. Also, the procedure is model-free and, hence, it does not require fitting unknown parameters.

Marble melancholy: using crossmodal correspondences of shapes, materials, and music to predict music-induced emotions.

Introduction: Music is known to elicit strong emotions in listeners, and, if primed appropriately, can give rise to specific and observable crossmodal correspondences. This study aimed to assess two primary objectives: (1) identifying crossmodal correspondences emerging from music-induced emotions, and (2) examining the predictability of music-induced emotions based on the association of music with visual shapes and materials. Methods: To achieve this, 176 participants were asked to associate visual shapes and materials with the emotion classes of the Geneva Music-Induced Affect Checklist scale (GEMIAC) elicited by a set of musical excerpts in an online experiment. Results: Our findings reveal that music-induced emotions and their underlying core affect (i.e., valence and arousal) can be accurately predicted by the joint information of musical excerpt and features of visual shapes and materials associated with these music-induced emotions. Interestingly, valence and arousal induced by music have higher predictability than discrete GEMIAC emotions. Discussion: These results demonstrate the relevance of crossmodal correspondences in studying music-induced emotions. The potential applications of these findings in the fields of sensory interactions design, multisensory experiences and art, as well as digital and sensory marketing are briefly discussed.

Electrical Power Diversification: An Approach Based on the Method of Maximum Entropy in the Mean.

Electrical energy is generated in different ways, each located at some specific geographical area, and with different impact on the environment. Different sectors require heterogeneous rates of energy delivery, due to economic requirements. An important problem to solve is to determine how much energy must be sent from each supplier to satisfy each demand. Besides, the energy distribution process may have to satisfy ecological, technological, or economic cost constraints.

Associations between majors of graduating seniors and average SATs of incoming students within higher education in the U.S.

While Scholastic Assessment Test (SAT) scores are becoming less widespread than in previous years, they continue to be used as an input by many higher education institutions in the United States to select which students to accept among applicants. This paper explores the association between average SAT scores of incoming undergraduate cohorts and major completions of graduating student cohorts. College Scorecard data from 2019 is collected from all U.S. undergraduate degree-granting, higher education institutions reporting average SAT scores of incoming cohorts (n=1,389). A multivariate beta regression approach, which allows for overdispersion and unit-interval responses, is proposed to explore associations between graduation rates by major (explanatory variables) and SAT percentiles of new student cohorts (response). Forty-nine percent of the variability in average SAT percentiles of incoming cohorts can be explained by the graduation proportions by major within institutions. Results show strong concurrent positive associations between average SAT percentiles of incoming cohorts and proportions of students graduating in: STEM fields; ethnic, cultural, and gender studies; social science; or languages, among others (p<0.01). A negative association is found between average SAT percentiles of incoming cohorts and graduating cohorts in degrees like security law enforcement or parks & recreation and fitness, as well as some traditional major choices, such as theology and psychology (p<0.01). Results are consistent by institution size, as well as public versus private, across most clusters. A statistical framework is introduced for analysis of the expected impact on average SAT percentiles of future student cohorts derived from changes in proportions by major of graduating student cohorts. Higher education institutions can benefit from the proposed methodology by adjusting their degree offerings to their target cohorts. While illustrated using SAT scores due to their historical prevalence and availability across institutions, the proposed approach can utilize any alternative quantitative measure of student preferred characteristics.

A network analysis of research productivity by country, discipline, and wealth.

INTRODUCTION: Research productivity has been linked to a country's intellectual and economic wealth. Further analysis is needed to assess the association between the distribution of research across disciplines and the economic status of countries. METHODS: By using 55 years of data, spanning 1962 to 2017, of Elsevier publications across a large set of research disciplines and countries globally, this manuscript explores the relationship and evolution of relative research productivity across different disciplines through a network analysis. It also explores the associations of those with economic productivity categories, as measured by the World Bank economic classification. Additional analysis of discipline similarities is possible by exploring the cross-country evolution of those disciplines. RESULTS: Results show similarities in the relative importance of research disciplines among most high-income countries, with larger idiosyncrasies appearing among the remaining countries. This group of high-income countries shows similarities in the dynamics of the relative distribution of research productivity over time, forming a stable research productivity cluster. Lower income countries form smaller, more independent and evolving clusters, and differ significantly from each other and from higher income countries in the relative importance of their research emphases. Country-based similarities in research productivity profiles also appear to be influenced by geographical proximity. CONCLUSIONS: This new form of analyses of research productivity, and its relation to economic status, reveals novel insights to the dynamics of the economic and research structure of countries. This allows for a deeper understanding of the role a country's research structure may play in shaping its economy, and also identification of benchmark resource allocations across disciplines for developing countries.

Online interest regarding violent attacks, gun control, and gun purchase: A causal analysis.

BACKGROUND: Increased interest about gun ownership and gun control are oftentimes driven by informational shocks in a common factor, namely violent attacks, and the perceived need for higher levels of safety. A causal depiction of the societal interest around violent attacks, gun control and gun purchase, both synchronous and over time, should be a stepping stone for designing future strategies regarding the safety concerns of the U.S. population. OBJECTIVE: Examine the causal relationships between unexpected increases in population interest about violent attacks, gun control, and gun purchase. METHODS: Relationships among online searches for information about violent attacks, gun control, and gun purchase occurring between 2004 and 2017 in the U.S. are explained through a novel structural vector autoregressive time series model to account for simultaneous causal relationships. RESULTS: More than 20% of the stationary variability in each of gun control and gun purchase interest can be explained by the remaining factors. Gun control interest appears to be caused, in part, by violent attacks informational shocks, yet violent attacks, although impactful, have a lesser effect than gun control debate on long-term gun ownership interests. CONCLUSIONS: The form in which gun control has been introduced in public debate may have further increased gun ownership interest. Reactive gun purchase interest may be an unintended side effect of gun control debate. U.S. policymakers may need to rethink current approaches to promotion of gun control, and whether societal policy debate without policy outcomes could be having unintended effects.

Topics and methods in economics, finance, and business journals: A content analysis enquiry.

This study analyzes the abstracts and titles of 33,454 business finance, economics, management, and business articles published in ISI (frequently cited) journals during 2013-14. The sample represents 46.4 percent of all papers published in ISI journals in those years, and 52.7 percent of the articles published in the selected categories. The journals were ranked in four Q categories according to their impact factors. The analysis revealed that some topics persisted in all Q groups, but others gained frequency by Q, which suggests that Q1 journals (those with higher impact factors) create trends that are followed by other publications. All Q groups have a methodological approach that is predominantly empirical rather than theoretical. In addition, while the business and management categories privileged case studies, economics studies emphasized panel data analyses. Finally, our study confirms the relevance of the English language in academia.

Risk Neutral Measure Determination from Price Ranges: Single Period Market Models.

Risk neutral measures are defined such that the basic random assets in a portfolio are martingales. Hence, when the market model is complete, valuation of other financial instruments is a relatively straightforward task when those basic random assets constitute their underlying asset. To determine the risk neutral measure, it is assumed that the current prices of the basic assets are known exactly. However, oftentimes all we know about the current price, or that of a derivative having it as underlying, is a bid-ask range. The question then arises as to how to determine the risk neutral measure from that information. We may want to determine risk neutral measures from that information to use it, for example, to price other derivatives on the same asset. In this paper we propose an extended version of the maximum entropy method to carry out that task. This approach provides a novel solution to this problem, which is computationally simple and fast.