Reviewerly/exHarmony huggingface dataset:
In Favor of Logarithmic Scoring

Shuford, Albert, and Massengill proved, a half century ago, that the logarithmic scoring rule is the only proper measure of inaccuracy determined by a differentiable function of probability assigned the actual cell of a scored partition. In spite of this, the log rule has gained less traction in applied disciplines and among formal epistemologists that one might expect. In this article we show that the differentiability criterion in the Shuford et al. result is unnecessary and use the resulting simplified characterization of the logarithmic rule to give novel arguments in favor of it.
On simulating one-trial learning using morphological neural networks

“Learning once, remembering forever”, this wonderful cognitive phenomenon sometimes occurs in the learning process of human beings. Psychologists call this psychological phenomenon “one-trial learning”. The traditional artificial neural networks can simulate the psychological phenomenon of “implicit learning”, but can’t simulate the cognitive phenomenon of “one-trial learning”. Therefore, cognitive psychology gives a challenge to the traditional artificial neural networks. From two aspects of theory and practice in this paper, the possibility of simulating this kind of psychological phenomenon was explored by using morphological neural networks. This paper takes advantage of morphological associative memory networks to realize the simulation of “one-trial learning” for the first time, and gives 5 simulating practical examples. Theoretical analysis and simulation experiments show that the morphological associative memory networks are a higher effective machine learning method, and can better simulate the cognitive phenomenon of “one-trial learning”, therefore provide a theoretical basis and technological support for the study of intelligent science and cognitive science.
Multiple-scale analysis of open quantum systems

In this work, we present a multiple-scale perturbation technique suitable for the study of open quantum systems, which is easy to implement and in few iterative steps allows us to find excellent approximate solutions. For any time-local quantum master equation, whether markovian or non-markovian, in Lindblad form or not, we give a general procedure to construct analytical approximations to the corresponding dynamical map and, consequently, to the temporal evolution of the density matrix. As a simple illustrative example of the implementation of the method, we study an atom-cavity system described by a dissipative Jaynes-Cummings model. Performing a multiple-scale analysis we obtain approximate analytical expressions for the strong and weak coupling regimes that allow us to identify characteristic time scales in the state of the physical system.
Partition problems in high dimensional boxes

Alon, Bohman, Holzman and Kleitman proved that any partition of a $d$-dimensional discrete box into proper sub-boxes must consist of at least $2^d$ sub-boxes. Recently, Leader, Mili\'{c}evi\'{c} and Tan considered the question of how many odd-sized proper boxes are needed to partition a $d$-dimensional box of odd size, and they asked whether the trivial construction consisting of $3^d$ boxes is best possible. We show that approximately $2.93^d$ boxes are enough, and consider some natural generalisations.
On consistency of the MLE under finite mixtures of location-scale distributions with a structural parameter

We provide a general and rigorous proof for the strong consistency of maximum likelihood estimators of the cumulative distribution function of the mixing distribution and structural parameter under finite mixtures of location-scale distributions with a structural parameter. The consistency results do not require the parameter space of location and scale to be compact. We illustrate the results by applying them to finite mixtures of location-scale distributions with the component density function being one of the commonly used density functions: normal, logistic, extreme-value, or t. An extension of the strong consistency results to finite mixtures of multivariate elliptical distributions is also discussed.
Sliding-Window Correlation Attacks Against Encryption Devices with an Unstable Clock

Power analysis side channel attacks rely on aligned traces. As a counter-measure, devices can use a jittered clock to misalign the power traces. In this paper we suggest a way to overcome this counter-measure, using an old method of integrating samples over time followed by a correlation attack (Sliding Window CPA). We theoretically re-analyze this general method with characteristics of jittered clocks and show that it is stronger than previously believed. We show that integration of samples over a suitably chosen window size actually amplifies the correlation both with and without jitter—as long as multiple leakage points are present within the window. We then validate our analysis on a new data-set of traces measured on a board implementing a jittered clock. The data-set we collected is public and accessible online. Our experiments show that the SW-CPA attack with a well-chosen window size is very successful against a jittered clock counter-measure and significantly outperforms previous suggestions, requiring a much smaller set of traces to correctly identify the correct key.
Characterization of &lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;$p$ &lt;/tex-math&gt; &lt;/inline-formula&gt;-ary Bent Functions in Terms of Strongly Regular Graphs

A p-ary function f in n variables is an l-form if f(tu) = t <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sup> f (u) for any nonzero t in Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> and u in Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> . Let n be a positive even integer, p an odd prime, and l an element of {1, 2, . . . , p -1} provided that l ≠ p -1 if p > 3. Let f be a p-ary bent function in n variables of l-form with f (0) = 0 and gcd(l - 1, p - 1) = 1, and let H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sub> = {t <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sup> : t ∈ Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> *}. We denote by G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f,l</sub> the Cayley graph Cay(Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> , ∪ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s∈Hl</sub> f <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> (s)). Our main results are as follows: 1) if there is weakly regular p-ary bent f which is not regular, then l is 2; 2) if l = 2, then f is weakly regular p-ary bent if and only if the Cayley graph G f,l is strongly regular; 3) if l ≠ 2, then f is regular p-ary bent if and only if the Cayley graph G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f,l</sub> is strongly regular; 4) G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f,l</sub> can be replaced by Cay(Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> , f <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> (0)\{0}) in 2) and 3); and 5) amorphic association schemes are derived by using 2) and 3). We prove our main results by computing at most four distinct restricted eigenvalues of G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f,l</sub> .
Zip Trees

We introduce the zip tree, (Zip: "To move very fast.") a form of randomized binary search tree that integrates previous ideas into one practical, performant, and pleasant-to-implement package. A zip tree is a binary search tree in which each node has a numeric rank and the tree is (max)-heap-ordered with respect to ranks, with ties broken in favor of smaller keys. Zip trees are essentially treaps [8], except that ranks are drawn from a geometric distribution instead of a uniform distribution, and we allow rank ties. These changes enable us to use fewer random bits per node. We perform insertions and deletions by unmerging and merging paths (unzipping and zipping) rather than by doing rotations, which avoids some pointer changes and improves efficiency. The methods of zipping and unzipping take inspiration from previous top-down approaches to insertion and deletion by Stephenson [10], Martínez and Roura [5], and Sprugnoli [9]. From a theoretical standpoint, this work provides two main results. First, zip trees require only $$O(\log \log n)$$ bits (with high probability) to represent the largest rank in an n-node binary search tree; previous data structures require $$O(\log n)$$ bits for the largest rank. Second, zip trees are naturally isomorphic to skip lists [7], and simplify Dean and Jones' mapping between skip lists and binary search trees [2].
Safety Practices in Requirements Engineering: The Uni-REPM Safety Module

Context: Software is an important part in safety-critical system (SCS) development since it is becoming a major source of hazards. Requirements-related hazards have been associated with many accidents and safety incidents. Requirements issues tend to be mitigated in companies with high processes maturity levels since they do their business in a systematic, consistent and proactive approach. However, requirements engineers need systematic guidance to consider safety concerns early in the development process. Goal: the paper investigates which safety practices are suitable to be used in the Requirements Engineering (RE) process for SCS and how to design a safety maturity model for this area. Method: we followed the design science methodology to propose Uni-REPM SCS, a safety module for Unified Requirements Engineering Process Maturity Model (Uni-REPM). We also conducted a static validation with two practitioners and nine academic experts to evaluate its coverage, correctness, usefulness, and applicability. Results: The module has seven main processes, fourteen sub-processes and 148 practices that form the basis of safety processes maturity. Moreover, we describe its usage through a tool. Conclusions: The validation indicates a good coverage of practices and well receptivity by the experts. Finally, the module can help companies in evaluating their current practices.
Parallelizing pairings on Hessian elliptic curves

This paper considers the computation of the Ate pairing on the Hessian model of elliptic curves. Due to the many important properties making the model attractive in cryptography, we compute for the first time the Ate pairing on this model and show how both the Tate and the Ate pairings can be parallelized on this curve. We wrote codes in the Sage software to ensure the correctness of formulas in this work.
Making AES Great Again: The Forthcoming Vectorized AES Instruction

The introduction of the processor instructions AES-NI and VPCLMULQDQ, that are designed for speeding up encryption, and their continual performance improvements through processor generations, has significantly reduced the costs of encryption overheads. More and more applications and platforms encrypt all of their data and traffic. As an example, we note the world wide proliferation of the use of AES-GCM, with performance dropping down to 0.64 cycles per byte (from ∼23 before the instructions), on the latest Intel processors. This is close to the theoretically achievable performance with the existing hardware support. Anticipating future applications and increasing demand for high performance encryption, Intel has recently announced that its future architecture (codename "Ice Lake") will introduce new encryption instructions. These will be able to vectorize the AES-NI and VPCLMULQDQ instructions, on wide registers that are available on the AVX512 architectures. In this paper, we explain how these new instructions can be used effectively, and how properly using them can lead to the anticipated theoretical encryption throughput of around 0.16 cycles per byte. The included examples demonstrate AES encryption in various modes of operation, AEAD such as AES-GCM, and the emerging nonce misuse resistant variant AES-GCM-SIV.
Subgraph learning for graph matching

Graph matching is a powerful tool for computer vision, distance measure and machine learning. However, many factors influences the accuracy of matching. The outliers is a key problem in the process of matching. In this paper, a novel approach is proposed to handle graph matching problem based on Markov Chain Monte Carlo framework. By constructing a target distribution, the proposed can perform a process of sampling to maximize the graph matching objective. In this process, our method can effectively save matching pairwise under one-to-one matching constraints and also avoid the effect of outliers and deformation. The corresponding experiments on synthetic graphs, real images and view-based 3D model retrieval demonstrate the superiority of the proposed method.
Hierarchical recurrent highway networks

A contemporary approach for acquiring the computational gains of depth in recurrent neural networks (RNNs) is to hierarchically stack multiple recurrent layers. However, such performance gains come with the cost of challenging optimization of hierarchal RNNs (HRNNs) which are deep both hierarchically and temporally. Though the researchers have exclusively highlighted the significance of using highways (or direct shortcuts) for learning deep hierarchical representations and deep temporal dependencies. However, no significant efforts are made to unify these finding into a single framework for learning deep HRNNs. We propose hierarchical recurrent highway network (HRHN) that contains highway within the hierarchical and temporal structure of the network for unimpeded information propagation across both dimensions, thus alleviating gradient vanishing problem. The proposed HRHN contain significantly reduced data-dependent parameters as compared to related methods. The experiments on language modeling (LM) tasks have demonstrated that the proposed architecture leads to design effective models. On character-level LM using Hutter prize dataset, the model achieved entropy of 2.4 bits per character. The attained perplexity on world-level LM using Penn TreeBank is 68.1. The HRHN outperformed other baseline and related models that we tested.
On GPU Connected Components and Properties: A Systematic Evaluation of Connected Component Labeling Algorithms and Their Extension for Property Extraction

Connected component labeling (CCL) is a fundamental image processing problem that has been studied in many platforms, including GPUs. A common approach to CCL performance analysis is studying the total processing time as a function of abstract image features, like the number of connected components or the fraction of foreground pixels, and input data usually includes synthetic images and segmented video datasets. In this paper, we develop on these ideas and propose an evaluation methodology for GPU CCL algorithms based on synthetic image patterns, addressing the nonexistence of a standard and reliable benchmark in the literature. Our methodology, applied on two important algorithms from existing literature, uncovers their data dependency with great detail, and allows us to model their processing time in three real-world video data sets as functions of abstract, high-level image concepts. We also apply our methodology for studying the memory and performance requirements of two strategies for computing connected component properties: an existing memory-hungry approach, and a new memory-preserving strategy.
Evaluation of information retrieval systems using structural equation modeling

The interpretation of the experimental data collected by testing systems across input datasets and model parameters is of strategic importance for system design and implementation. In particular, finding relationships between variables and detecting the latent variables affecting retrieval performance can provide designers, engineers and experimenters with useful if not necessary information about how a system is performing. This paper discusses the use of Structural Equation Modeling (SEM) in providing an in-depth explanation of evaluation results and an explanation of failures and successes of a system; in particular, we focus on the case of evaluation of Information Retrieval systems.
How to implement EU data protection regulation for R&amp;D in biometrics

Biometrics R&D has to deal with personal data. From the Universal Declaration of Human Rights, privacy of a human being shall be protected, and this is addressed in different ways in each region of the world. In the case of the European Union, Data Protection Directives, Laws and Regulations have been established, and interpreted in different ways by each European Member State. Such a diversity has pushed the European Union to generate an improved regulation that will be mandatory from May 2018. Biometric R&D shall not only comply with the current Directive, but also has to adapt its work to the new Regulation. This work is intended to describe the situation and provide a recommended procedure when having to acquire personal data. The recommended procedure is illustrated by the implementation of a Biometric Data Acquisition Platform, used to acquire fingerprints from nearly 600 citizens using different sensors.
Thermal operations involving a single-mode bosonic bath

We study the limitations on coherence evolutions under the constraints of thermodynamic laws, and focus on the optimal thermal operations (TO) reaching the bounds. For the qubit case, we prove that the TO that preserves maximal coherence can be reproduced by thermal operations involving only a single-mode reservoir, which we call single-mode thermal operations (STO). For higher dimensional systems, we derive tight limitations on coherence merging which are allowed by TO, and find that these bounds can also be reached by STO. By applying the coherence merging bounds to a two-qubit system, we observe that for some states, it is impossible to erase correlations while preserving the marginal states by TO. Our results reveal the strong ability of STO in coherence processing. Because interactions between quantum systems and single-mode reservoirs are realizable under recent techniques, our theoretical results are helpful to experimentally demonstrate the limitations of thermodynamic laws.
Inverse Free Kalman Filter Using Approximate Inverse of Diagonally Dominant Matrices

Conventional Kalman filter (KF) requires matrix inversion. But the pervasive applications of KF cannot at times afford inversion. Especially, embedded implementations do not have the capabilities to compute inverse using methods such as Cholesky decomposition. For large matrices, inversion could be computationally prohibitive even for non-embedded implementations. To address this problem, an inverse free Kalman filter (IFKF) is proposed in this letter. The inverse of innovation covariance matrix required in the update step of the KF is approximated using Taylor series expansion. The approximate inverse has a closed form expression in the elements of the original matrix. Bounds on the error covariance of proposed IFKF are also established. The proposed IFKF does not require any iterations to converge.
Normalized Non-Negative Sparse Encoder for Fast Image Representation

Image representation based on sparse coding generalizes the bag of words model. Although it reduces the reconstruction error for local features to achieve the state-of-the-art image classification performance, the large computational cost hinders the application of sparse coding-based image features. In this paper, we propose approximating a sparse code using the output of a simple neural network. The resulting parameter learning model for the neural network automatically incorporates non-negative and shift-invariant constraints, leading to an efficient normalized non-negative sparse coding (N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> SC) sparse encoder. Without the use of the traditional iterative process to solve the sparse coding objective, the sparse encoder directly “converts” each local feature into a sparse code. We also introduce a method for training the encoder based on the auto-encoder method. In addition, we formally propose the corresponding sparse coding scheme called N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> SC, which enforces both the non-negative constraint and the shift-invariant constraint in addition to the traditional sparse coding criteria. As demonstrated by several experiments, the obtained N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> SC encoder requires only 3%-10% of the processing time for image feature extraction compared with the standard sparse coding scheme. At the same time, the features extracted using the exact solutions of the N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> SC coding scheme and the N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> SC encoder offer superior image classification accuracy compared to the accuracy of many existing sparse coding-based representations.
Drivers of Urban Development in Terms of Education Based on Digital Technologies

To speed up urban economic development there is a need in radical transformation in the technological fields as well as in the field of mechanisms that encourage the creation and implementation of new technologies. The proposed chapter approach can become a methodological foundation of development and self-development of educational institutions on the principles of continuing education using digital technologies. The chapter deals with the methodology of creating a unified information educational environment, providing the implementation of lifelong learning, the development and implementation of educational models, programs, and media performed with the use of digital technologies. The chapter aims to develop conceptual approach to strategic control of continuing education, innovative development of regulation of educational institutions and to propose practical recommendations based on digital technology.