Theories about the evolution of information in time have begun to be used systematically and repeatedly by communities of scholars to fruitfully generate new knowledge about the past only in 1780, first in German faculties of Protestant theology, among classical linguists and then around the turn of the 19th century in comparative linguistics. Ranke used such theories in the second quarter of the 19th century to generate knowledge of history, and then similar methods spread to biology, geology and archaeology.

We present some university rankings, the differences between them and the role they can play in shaping the higher education landscape. We analyse the position of Polish universities in various rankings and suggest why the Polish economy makes little use of the output of Polish researchers.

Speech enhancement in strong noise condition is a challenging problem. Low-rank and sparse matrix decomposition (LSMD) theory has been applied to speech enhancement recently and good performance was obtained. Existing LSMD algorithms consider each frame as an individual observation. However, real-world speeches usually have a temporal structure, and their acoustic characteristics vary slowly as a function of time. In this paper, we propose a temporal continuity constrained low-rank sparse matrix decomposition (TCCLSMD) based speech enhancement method. In this method, speech separation is formulated as a TCCLSMD problem and temporal continuity constraints are imposed in the LSMD process. We develop an alternative optimisation algorithm for noisy spectrogram decomposition. By means of TCCLSMD, the recovery speech spectrogram is more consistent with the structure of the clean speech spectrogram, and it can lead to more stable and reasonable results than the existing LSMD algorithm. Experiments with various types of noises show the proposed algorithm can achieve a better performance than traditional speech enhancement algorithms, in terms of yielding less residual noise and lower speech distortion.

New equivalent conditions of the asymptotical stability and stabilization of positive linear dynamical systems are investigated in this paper. The asymptotical stability of the positive linear systems means that there is a solution for linear inequalities systems. New necessary and sufficient conditions for the existence of solutions of the linear inequalities systems as well as the asymptotical stability of the linear dynamical systems are obtained. New conditions for the stabilization of the resultant closed-loop systems to be asymptotically stable and positive are also presented. Both the stability and the stabilization conditions can be easily checked by the so-called I-rank of a matrix and by solving linear programming (LP). The proposed LP has compact form and is ready to be implemented, which can be considered as an improvement of existing LP methods. Numerical examples are provided in the end to show the effectiveness of the proposed method.

Supply chain management emerged as the ultimate management strategy to ensure the competitive advantages of companies in their markets. Suppliers are considered as inevitable sources of external risks in modern supply chains. In this respect, resonance is essential for the ability to adapt in resonance to disturbances and to restore in choosing suppliers. As suppliers of critical resources are vulnerable, choosing better suppliers to create resilience, and thereby reducing the risks in the supply chain as a whole. In recent years, emphasis has been placed on supply chain resilience and resilient suppliers, but few studies have been conducted on the evaluation and selection of resilient suppliers with multi-criteria decision making models. The main purposes of this study are a broad review of the literature on the resilient factor, factorization, efficiency of key factors in the reliance of suppliers and the ranking of resilient suppliers using the combined approach of SWARA and WASPAS. For this purpose, after a comprehensive review of Literature interview with the experts of petrochemical upstream industry, six key factors and overall resilience of suppliers were identified in eighteen factors. Then the weight of the dimensions was determined by using the SWARA method. The output of the method showed that supplier accountability and key performance factors were the most important factors in assessing the resilience of suppliers. Using the supporting method, five resilient suppliers were evaluated based on six dimensions and the final ranking of suppliers was determined. With this ranking, the industry will be a major step towards improving supply chain and increasing suppliers’ resilience to address disruptions and risks, improve supply and achieve competitive advantage and satisfy the consumers’ needs.

The direct motivation for this article is the publication of two updates of the Polish Journal Rankings on 9 and 18 February 2021, which were prepared by the Minister of Education and Science and bypassed the Research Evaluation Commission. This article aims to characterize the changes made by the minister in relation to the draft ranking prepared by the commission. For providing a complete picture of the changes, I describe the main principles for building the ranking according to the new model implemented in 2018. Then, I characterize the minister's changes in terms of added journals and changing the points assigned to the journals. The analysis is provided through the lens of the universities publishing these journals and the disciplines assigned to the journals. The article concludes by identifying four main recommendations that should be implemented to restore the usefulness of the ranking as an instrument of science policy.

The main focus of this tutorial/review is on presenting Prospect Theory in the context of the still ongoing debate between the behavioral (mainly descriptive) and the classical (mainly normative) approach in decision theory under risk and uncertainty. The goal is to discuss Prospect Theory vs. Expected Utility in a comparative way. We discuss: a) which assumptions (implicit and explicit) of the classical theory are being questioned in Prospect Theory; b) how does the theory incorporate robust experimental evidence, striving, at the same time, to find the right balance between the basic rationality postulates of Expected Utility (e.g. monotonicity wrt. First-Order Stochastic Dominance), psychological plausibility and mathematical elegance; c) how are risk attitudes modeled in the theory. In particular we discuss prospect stochastic dominance and the three-pillar structure of modeling risk attitudes in Prospect Theory involving: the non-additive decision weights with lower and upper subadditivity and their relationship to the notions of pessimism and optimism, as well as preferences towards consequences separated into preferences within and across the domains of gains and losses (corresponding to basic utility and loss aversion), d) example applications of Prospect Theory.

Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.

Simple necessary and sufficient conditions for robust stability of the positive linear discrete-time systems with delays with linear uncertainty structure in two cases: 1) unity rank uncertainty structure, 2) non-negative perturbation matrices, are established. The proposed conditions are compared with the suitable conditions for the standard systems. The considerations are illustrated by numerical examples.

This paper proposes a new fault location method in radial medium voltage distribution networks. The proposed method only uses the measurement data at the feeder beginning to approximate the characteristic equation showing the dependence between the positive-sequence voltage and phase angle at the monitoring point with the distance to the fault location for each fault type on each line segment. To determine these characteristic equation coefficients, the entire distribution network will be modeled and simulated by four types of faults at different locations along the lines to build the initial database. Based on this database, the mathematical functions in MATLAB software are applied to approximate these coefficients corresponding to each type of fault for each line segment in the network. Then, from the current and voltage measurement data at the feeder beginning, the algorithms of global search, comparison, and fault ranking are used to find out where the fault occurs on the distribution network. Two types of distribution network with and without branches are studied and simulated in this paper to verify and evaluate the effectiveness of the proposed method.

Face Sketch Recognition (FSR) presents a severe challenge to conventional recognition paradigms developed basically to match face photos. This challenge is mainly due to the large texture discrepancy between face sketches, characterized by shape exaggeration, and face photos. In this paper, we propose a training-free synthesized face sketch recognition method based on the rank-level fusion of multiple Image Quality Assessment (IQA) metrics. The advantages of IQA metrics as a recognition engine are combined with the rank-level fusion to boost the final recognition accuracy. By integrating multiple IQA metrics into the face sketch recognition framework, the proposed method simultaneously performs face-sketch matching application and evaluates the performance of face sketch synthesis methods. To test the performance of the recognition framework, five synthesized face sketch methods are used to generate sketches from face photos. We use the Borda count approach to fuse four IQA metrics, namely, structured similarity index metric, feature similarity index metric, visual information fidelity and gradient magnitude similarity deviation at the rank-level. Experimental results and comparison with the state-of-the-art methods illustrate the competitiveness of the proposed synthesized face sketch recognition framework.

This article presents the results of a study on the process of creating evaluative homogeneity within the Polish performance-based research funding system. To achieve this, the creation process of the national journal ranking from 2019 was analysed in two scientific disciplines: biology and history. The selection of this case is motivated by its particular nature – the creation of the list using bibliometric indicators and expert input. Therefore, the following question was posed: What guided the actors participating in the process of creating the list using bibliometric indicators when introducing changes to its original form? To answer this question, mixed methods were applied. Firstly, a quantitative analysis was conducted on the changes introduced to the ranking during its various stages of creation. Secondly, a qualitative analysis was carried out on partially structured interviews regarding the motivations of the actors. Through qualitative and quantitative analysis, the study revealed the extent to which actors influence the form that evaluative homogeneity takes within the Polish system. Through qualitative analysis and quantitative results, the study revealed the extent to which actors influence the form that evaluative homogeneity takes in the Polish system. Furthermore, the article argues that the form that evaluative homogeneity takes is dictated by how actors position themselves in relation to two opposing forces: heterogeneity and homogeneity, and the practice and form of research quality evaluation as seen through their prism. The text concludes with a short epilogue, updating the findings of the study beyond its time frame.