Reviewerly/exHarmony huggingface dataset:
Detecting Compressed Deepfake Images Using Two-Branch Convolutional Networks with Similarity and Classifier

As a popular technique for swapping faces with someone else’s in images or videos through deep neural networks, deepfake causes a serious threat to the security of multimedia content today. However, because counterfeit images are usually compressed when propagating over the Internet, and because the compression factor used is unknown, most of the existing deepfake detection models have poor robustness for the detection of compressed images with unknown compression factors. To solve this problem, we notice that an image has a high similarity with its compressed image based on symmetry, and this similarity is not easily affected by the compression factor, so this similarity feature can be used as an important clue for compressed deepfake detection. A TCNSC (Two-branch Convolutional Networks with Similarity and Classifier) method that combines compression factor independence is proposed in this paper. The TCNSC method learns two feature representations from the deepfake image, i.e., similarity of the image and its compressed counterpart and authenticity of the deepfake image. A joint training strategy is then utilized for feature extraction, in which the similarity characteristics are obtained by similarity learning while obtaining authenticity characteristics, so the proposed TCNSC model is trained for robust feature learning. Experimental results on the FaceForensics++ (FF++) dataset show that the proposed method significantly outperforms all competing methods under three compression settings of high-quality (HQ), medium-quality (MQ), and low-quality (LQ). For the LQ, MQ, and HQ settings, TCNSC achieves 91.8%, 93.4%, and 95.3% in accuracy, and outperforms the state-of-art method (Xception-RAW) by 16.9%, 10.1%, and 4.1%, respectively.
Lessons for science and technology policy? Probing the Linkedin network of an RDI organisation

In this paper, we seek to examine the network of the Greek National Documentation Centre (EKT) as formed by its LinkedIn followers. By applying specific data collection and processing techniques, we explore the network of all the individuals that follow EKT's LinkedIn page. Significant manual and automatic approaches have been implemented with regard to data extraction, data curation and data homogenization. The aim is to identify the network's advancement over time, the institutions involved and the countries. The timeframe of the study spans from when the relevant LinkedIn page was constructed in 2015 to 2020. Findings indicate that there is a steady increase in the number of new followers, peaking in 2020. On an international scale, the evolution of the network of followers is imprinted and distributed in worldwide maps. In total, 68 countries have followed EKT over the examined time period. Also, in terms of followers' institutional sector the Business Sector (BES) stands out (46.5%). Higher Education (HES) and Government Sector (GOV) are associated with 26.4 and 22.2% of the followers, respectively. Lastly, this paper provides a first institutional and country-level mapping of who constitutes the organisation's interlocutors in the national and global RDI ecosystem.
Kesiapan Teknologi dan Penerimaan Pengguna Sistem Informasi Sumber Daya Terintegrasi (SISTER) Menggunakan TRAM

SISTER is an application that is used so that educators, namely lecturers, can manage and manage and integrate all educator data services. This makes it easier because SISTER is integrated with the DIKTI database so that the tridharma activities of higher education carried out by lecturers are well documented. Musi Charitas Catholic University (UKMC) which has urged all its lecturers to use SISTER since 2020. In using this new application (SISTER), it will definitely cause problems for some lecturers. These constraints such as several points in SISTER that are different from the BKD guide, when saving data will appear: something went wrong, if there is a revision by the assessor, the lecturer cannot see it and only the college admin can see it. The constraints above show how users are prepared and behave when facing new technology. This study will use the TRAM method to see Technology Readiness and User Acceptance of SISTER. The result is that all independent variables affect the dependent variable except for the discomfort and insecurity variables. And the respondents agree with all the existing hypotheses based on the evidence in the discussion section because they are in accordance with what they feel while using SISTER. For the level of readiness of information technology, SISTER is included on a scale of 9 because SISTER is no longer a prototype but has also become a complete system
Analysis on Factors for Prior Evaluation of PBL Class Using IPMA

Purpose: This study examines how students value each of the factors represented in a matrix reflecting the following importance-performance matrix analysis (IPMA). This IPMA was used as the primary survey (Kim, 2019), and each evaluation factor, the average value of the latent variable, and the estimated path coefficient were usedMethods: SmartPLS 3.0 was used for the numerical calculations and SPSS 19.0 was used to create the graph. Analysis occurs prior to student participation in the class to form a consensus among students at the beginning of the semester.Results: Attempts are made to derive the analysis results and apply them to actual problem-based learning classes to improve class evaluation through feedback. The results show that prioritizing the evaluation factors such as learning outcomes and self-directed learning is meaningful in terms of lecture efficiency.Conclusions: This approach is particularly meaningful, as it attempts an integrated model (importance-performance matrix-analytical hierarchy process) and is a continuation of a previous study (Kim, 2019)
A Probabilistic Logic Between LPP1 and LPP2

An extension of the propositional probability logic LPP2 given in Ognjanović et al. (Probability Logics. Probability-Based Formalization of Uncertain Reasoning, Theoretical Springer, Cham, Switzerland, 2016) that allows mixing of propositional formulas and probabilistic formulas is introduced. We describe the corresponding class of models, and we show that the problem of deciding satisfiability is in NP. We provide infinitary axiomatization for the logic and we prove that the axiomatization is sound and strongly complete.
The Phenomenological Turn in Romanian Spectralism

Abstract This chapter approaches the music of Romanian composers Ana Maria Avram and Iancu Dumitrescu from a phenomenological perspective that moves away from a reliance on science and technology characteristic much of French spectralism. These composers have expressed their interest in a shift away from the scientific analysis of timbre and sound toward certain post-Husserlian ideas, and this change in focus coincides with recent work in transformational analysis, studies of embodiment and expression, and the ontology of music. Employing a number of concepts from these fields, including the work of Gilbert Simondon, this article focuses especially on Avram’s concept of transformation, and proposes that her music initiates a phenomenology of musical stability that corrects the simplified reification of musical objects: not simply by opposing stable and unstable, but by also employing multistability and metastability in music.
Spectralism and Research in Psychoacoustics and Music Perception

Abstract Although work in the sciences of musical perception did not wait until the 1970s to reach composers, those in the spectral movement were particularly attentive and used some aspects to fertilize their theoretical thought and their compositional practice. This chapter examines the different ways in which these composers appropriated the knowledge of sound and auditory perception. The chapter will first examine the paradigm shift that has led from note to sound culture and to an awareness of the role of perception in composition. It will then discuss the question of the appropriation of concepts from acoustics and psychoacoustics by spectral composers. Finally, it will focus on some scientific-inspired techniques of composition.
Bitsliced Implementation of Non-Algebraic 8×8 Cryptographic S-Boxes Using ×86-64 Processor SIMD Instructions

The article is devoted to software bitsliced implementation of randomly generated <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> S-Box block ciphers, focused on the use of logical SIMD instructions from the SSE, AVX and AVX-512 extensions in ×86-64 processors. A heuristic algorithm for minimizing non-algebraic S-Boxes in three logical bases is proposed: universal—based on logical instructions AND, OR, XOR, NOT, which allows implementation on any 8/16/32/ 64-bit processors; extended—based on the instructions AND, OR, XOR, NOT, AND-NOT, which allows implementation on ×86-64 processors; ternary—based on ternary logic instructions, for implementation on ×86-64 processors with AVX-512 support. On average, bitsliced representations of non-algebraic S-Boxes in these logical bases require 400/380/200 logical instructions, respectively. The performance of bitsliced implementations of the S-Box cipher “Kalyna” using logical instructions SSE/AVX/ AVX-512 for the Intel Xeon Skylake-SP processor was measured. A fast alternative—non-bitsliced approach to the bytesliced SubBytes operation based on the AVX-512VBMI extension, resistant to timing and cache attacks—is proposed.
Refining History for Future-Aware Neural Machine Translation

Neural machine translation uses a decoder to generate target words auto-regressively by predicting the next target word conditioned on a given source sentence and its previously predicted target words, i.e, its translation history, which suffers from two limitations: 1) the prediction of next word depends heavily on the quality of its history information. Moreover, the discrepancy between training and inference exacerbates this limitation; 2) this left-to-right decoding way cannot make full use of the target-side future information, which leads to the issue of unbalanced outputs. On the one hand, we alleviate the first limitation with a history-refining module, which learns to examine the quality of each history word by assigning it a confidence score. The confidence score is further used as a gate to control the amount of its word embedding flowing to the decoder. On the other hand, we attack the second limitation with a future-foreseeing module, which learns the distribution of future translation at each decoding time step. More importantly, we further propose refining history for future-aware NMT since the two modules can be closely incorporated as they focus on different kinds of context. Experimental results on various translation tasks with different scaled datasets, including WMT English <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\leftrightarrow$</tex-math></inline-formula> {German, French, Romanian}, show that our proposed approach achieves significant improvements over strong Transformer-based NMT baselines.
On removal of one undetected paradox in foundations of probability theory

Abstract The paper points out a logical contradiction that arises in the modern approach to teaching the foundations of the probability theory. This contradiction is of the following form: 𝝎 = {𝝎}, where 𝝎 is an arbitrary elementary outcome. In modern mathematics the formation of expressions of the form 𝒙 = {𝒙} is unacceptable. Here {𝒙} is a unit set, i.e., a set whose sole element is some element 𝒙 of an arbitrary nature. This paradox 𝝎 = {𝝎} is a consequence of the fact that random events and between them also elementary outcomes 𝝎 are considered as some subsets in the set of all elementary outcomes. It is shown how this contradiction can be easily eliminated by applying the axiomatic method. It is based on the introduction of two simple axioms that impose restrictions on elementary outcomes and on the class of random events under consideration. In addition from these two axioms on the basis of strictly logical reasoning the authors derived the representation of an arbitrary random event in the form of a sum of elementary outcomes favorable to it. Moreover, another non-axiomatic approach to the elimination of this paradox is proposed. In the final part of the paper other variants of the second of the introduced axioms are considered as well.
Visualization technologies for hybrid training of future engineers

Abstract The paper is devoted to the problems of visualization technology application to train future engineers with a combination of distance learning and full-time training formats (hybrid training). The authors present directions of visualization technologies application such as prototyping of production objects, Flickr-illustration of presentations, animation and video laboratory work. The visualization technologies demonstrate a positive impact on the professional and personal success of future engineers.
Solar radiation spectral composition determination program

Abstract The article describes the work of a software product designed to process the results of analytical studies on the effect of solar radiation intensity on its spectrum by bigarmonic interpolation. As a result of the program, the processed analytical data is converted into three-dimensional surfaces showing the dependencies of studies on the effect of solar radiation intensity on its spectrum, the height of the sun and geographical coordinates. The program allows you to determine areas with a certain percentage of the spectrum from the height of the sun and is used in research organizations, educational institutions and design organizations of the electric power industry.
Comparison of the probabilistic model of a fuzzy Bayesian classifier and the Gaussian mixture problem

Abstract The article shows that the problem of fuzzy classification and the problem of separation of Gaussian mixtures have different theoretical solution models based on the results of the classical probability theory. A probabilistic model of the clustering and classification process based on the Bayesian approach is the joint distribution of multidimensional data points across clusters and cluster prototypes. The model is built for datasets with a normal distribution. Unknown membership values for each data point are assumed to be a random variable with some empirical distribution. The cluster prototype is also assumed to be a normally distributed random variable. The model is compared with the Gaussian mixture separation model and the main difference between them is highlighted: in the Bayesian fuzzy classification model, the product of all component probabilities is used, which means taking into account the possibility of the x n value falling into different clusters. The computational algorithm of this model may have a wider application compared to the traditional fuzzy c-means approach, due to the lack of restrictions on clustering parameters. Some numerical results are presented that confirm the model’s operability for an artificial data set both with parameters within the traditional limitations of the c-means method and for an extended range of parameter values.
Method of preparation of heterogeneous height standards for measurements by means of interferometry

Abstract The results of the practical implementation of a method for preparing calibration standards based on magnetron sputtering of a chromium film on the surface of the standard are presented. This film is an electrically conductive layer that preserves the topography of relief elements and allows scanning without charge accumulation in the sample. The results obtained showed that the sputtering of thin chromium films on the surface of height standards, the relief elements of which have different reflection coefficients, makes it possible to measure the heights of such standards with a fairly low error.
Advanced tendencies and practically oriented approach to training specialists in applied physics

Abstract The existing system of training specialists in the field of applied physics in domestic universities doesn’t allow to fully meet the needs of employers. One of the main drawbacks of the educational process in higher education institution in training future engineers is insufficient use of practice-oriented educational technologies, well-organized internships and independent work of students, real design. It does not give students an opportunity to demonstrate the competences they have acquired while studying individual disciplines of the educational program. According to experts, one of the ways to improve the quality of specialists’ training, capable of eliminating this contradiction to a certain extent, is the introduction and wider spread of practice-oriented educational technologies in engineering universities. The objective of the applied physics course is to develop skills in applying the provisions of fundamental physics to competent scientific analysis of situations which an engineer has to deal with when creating new equipment and new technologies, as well as to develop students’ natural-science worldview and familiarize them with the history of physics development and its main discoveries. As a result of mastering the course of applied physics the student should learn the basic physical phenomena and basic laws of physics; limits of their applicability, application of laws in the most important practical applications; become familiar with the basic physical quantities, know their definition, meaning, methods and units of their measurement; imagine fundamental physical experiments and their role in the development of science; know the purpose and operating principles of the most important physical instruments.
A shape space for generalized beta exponential distributions of the second type

Abstract The generalized beta exponential distribution of the second type contains subfamilies of logistic distributions, that are often used to control time arrays in complex systems. Currently, the choice of a model from possible implementations of a generalized family remains a rather time-consuming task. For this reason, it is often necessary to use complex mixtures of models. Displaying subfamilies of a generalized exponential distribution of the second type in the space of parametric and information features to choose the simplest form of the model from subfamilies and to evaluate the shape parameters is enabled. In the space of standardized moments of the third and fourth order the trajectories position of possible realizations limits the upper limit of distinguish-ability of the shape parameters of distribution models. A significant expansion of the distinguish-ability of trajectories it is possible to achieved by using the entropy coefficient of non-shifted distributions as an additional independent feature of the distribution shape. Mapping subfamilies of distributions in the space of entropy coefficient, antikurtosis and skewness one also to analyse the most important properties of distributions as well is allows. In article it is shows that for all models of the generalized distribution of the second type, the antikurtosis is in the range between the exponential and normal distributions.
Computational model “herd of herbivores &amp; flock of predators” in scope of global optimization problem

Abstract The article proposes a coevolutionary computational model “a herd of herbivores – a flock of predators”. The selfish behavior of individuals of a herd of herbivores being attacked by a pack of predators is modeled. Attractive operators of patterns of individual and collective behavior of agents, as well as mechanisms of population selection, are considered. The results of a series of experiments with the model “herd of herbivores – a flock of predators” for the problems of finding a global minimum in known test functions are presented, as well as a nonparametric proof of the statistical significance of the results obtained using the Wilcoxon signed-rank test.
Formation of a register of special technology objects based on integrating segmented images

Abstract The article considers aerospace technologies in terms of the details of the space survey of distributed objects. With discrete shooting of areas of interest, a set of images is formed, which are processed by segmentation tools. A set of overlapping or overlapping segments forms objects belonging to the register (areas of interest). The theoretical features of creating mathematical support for the process of forming areas of interest in which objects are present, based on a set of image segments obtained as a result of image processing by segmentation tools, are described. In particular, a mathematical model is presented for creating initial zones from multiple segments of sequential images. The process consists of determining the dynamic neighbourhood, determining the interaction weights and the rules for updating them, updating the spatial vectors of the segments of the processed images. The obtained results provide the creation of mathematical support for the process of forming areas of interest in which objects are present, based on a set of image segments obtained as a result of image processing by segmentation tools.
<i>Mineralogy of Arizona</i>, 4th edition, by Raymond W. Grant, Ronald B. Gibbs, Harvey W. Jong, Jan C. Rasmussen, and Stanley B. Keith. University of Arizona Press. 744 pages; 2022; $49.95 (softbound). Both electronic and hardcover versions also available at $49.95 and $75.00, respectively.

"Mineralogy of Arizona, 4th edition, by Raymond W. Grant, Ronald B. Gibbs, Harvey W. Jong, Jan C. Rasmussen, and Stanley B. Keith. University of Arizona Press. 744 pages; 2022; $49.95 (softbound). Both electronic and hardcover versions also available at $49.95 and $75.00, respectively.." Rocks & Minerals, 98(1), p. 102
Lagrangian scale decomposition via the graph Fourier transform

Leveraging tools from graph signal processing and work on Lagrangian coherent structures, we introduce a graph-based scale transform that is fully Lagrangian and based on the transport properties of the flow. Applying this tool to several different flows, we are able to assess the dynamic consequences of kinematic coherence in a variety of contexts. This approach allows us to extend traditional Eulerian techniques (filtering, compression) to the analysis of Lagrangian quantities.
Distributed query execution under access restrictions

The availability of a multitude of data sources has naturally increased the need for subjects to collaborate for supporting distributed computations that combine different data collections for their elaboration and analysis. Due to the quick pace at which datasets grow, often the authorities collecting and owning such datasets resort to external third parties (e.g., cloud providers) for their storage and management. Data under the control of different authorities are autonomously encrypted (using different encryption schemes and keys) for their external storage. This makes distributed computations combining these sources difficult to support. In this paper, we propose an approach enabling collaborative computations over data encrypted in storage, selectively involving also subjects that might not be authorized for accessing the data in plaintext when their collaboration is considered economically convenient. We also consider the possible adoption of trusted hardware components, to enable the evaluation of operations over plaintext data at non-fully trusted computational providers. The experimental results confirm the economic benefits that can be enabled by our proposal.