Reviewerly/exHarmony huggingface dataset:
Multi-Regularization-Constrained Blur Kernel Estimation Method for Blind Motion Deblurring

Blur kernel (BK) estimation is the crucial technique to guarantee the success of blind image deblurring. In this paper, we propose a multi-regularization-constrained method to estimate an accurate BK from a single motion-blurred image. First, in order to generate sharp and reliable intermediate latent results, we propose a model which combines the spatial scale, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${L} _{0}$ </tex-math></inline-formula> norm, and the dark channel prior. Second, in order to preserve the continuity and the sparsity, and to remove the flaw in the BK, a dual-constrained regularization model, which combines the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${L} _{0}$ </tex-math></inline-formula> -regularized intensity prior and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${L} _{2}$ </tex-math></inline-formula> -regularized gradient prior, is proposed for accurate BK estimation. The proposed model can not only preserve the continuity and the sparsity of the BK very well but also can remove the flaw thoroughly. Finally, we propose an efficient optimization strategy which can solve the proposed model efficiently. Extensive experiments compared with the state-of-the-art methods demonstrate that our method estimates more accurate BKs and obtains higher quality deblurring images in terms of both subjective vision and quantitative metrics.
An Empirical Study of Speculative Concurrency in Ethereum Smart Contracts

We use historical data to estimate the potential benefit of speculative techniques for executing Ethereum smart contracts in parallel. We replay transaction traces of sampled blocks from the Ethereum blockchain over time, using a simple speculative execution engine. In this engine, miners attempt to execute all transactions in a block in parallel, rolling back those that cause data conflicts. Aborted transactions are then executed sequentially. Validators execute the same schedule as miners. We find that our speculative technique yields estimated speed-ups starting at about 8-fold in 2016, declining to about 2-fold at the end of 2017, where speed-up is measured using either gas costs or instruction counts. We also observe that a small set of contracts are responsible for many data conflicts resulting from speculative concurrent execution.
Shared Representation Generator for Relation Extraction With Piecewise-LSTM Convolutional Neural Networks

Traditional distant supervision for relation extraction is faced with the problem of introducing noises. In this paper, we present a shared representation generator to de-emphasize the noisy expressions by extracting common features in relation. Different from computing weighted sum in widespread attention mechanism, we directly generate bag representation in multi-instance learning by feature transformation, which only remains the semantics related to predict relation. We introduce the generator loss into objective function to improve the performance of shared representation. Also, the structure of our proposed generator is flexible and scalable. To capture more structural information, piecewise convolutional neural network (PCNN) is widely used to divide the output of convolutional layer into three segments, but this approach breaks the consistence and inner relationship of the sentence. We encode the sentence with piecewise-LSTM convolutional neural network (PLSTM-CNN) to alleviate this issue, which adopts BiLSTM after the pooling layer of PCNN. The experimental results show that we achieve significant improvement on relation extraction as compared with the baselines.
Efficient High-Dimensional Quantum Key Distribution with Hybrid Encoding

We propose a schematic setup of quantum key distribution (QKD) with an improved secret key rate based on high-dimensional quantum states. Two degrees-of-freedom of a single photon, orbital angular momentum modes, and multi-path modes, are used to encode secret key information. Its practical implementation consists of optical elements that are within the reach of current technologies such as a multiport interferometer. We show that the proposed feasible protocol has improved the secret key rate with much sophistication compared to the previous 2-dimensional protocol known as the detector-device-independent QKD.
Optimized Clustering Scheme-Based Robust Vanishing Point Detection

Robust vanishing point estimation has been widely applied to various applications in the field of computer vision and pattern recognition for robotics, advanced driver assistance systems, and autonomous driving vehicles. The major challenge for vanishing point detection lies in line segments, spurious vanishing candidate removal, and clustering for refinement. Recent vanishing point detection approaches have attempted to reduce the computational complexity involved with voting processes using optimized voter selection strategies to identify the vanishing point from line segments. This paper proposes a novel vanishing point detection method to select robust candidates, applying optimized minimum spanning tree-based clustering of the vanishing point candidates by analyzing the lines within a unit sphere domain. The proposed scheme was applied to an open database that included illumination, partial occlusion, and viewpoint changes to validate robustness without prior scene information.
Contour extraction of a laser stripe located on a microscope image from a stereo light microscope

Abstract A stereo light microscope has a special optical structure that consists of two optical paths. With two cameras fitted on its imaging planes, a microscopic binocular vision system can be constructed, and this system can be applied in three‐dimensional (3D) shape measurements of a microscopic object. A novel‐shape reconstruction system is developed in this article composed of laser fringe scanning and a stereo light microscope. A laser projector emits a thin light sheet and projects it onto the microscopic object's surface. The microscopic object is placed on a micro‐displacement mechanism and moved in a given direction. The entire surface of the object is scanned by the light sheet. This system captures a series of microscopic images of the laser stripe, which are used to restore the 3D shape of the object. In this article, we mainly focus on the study of the laser stripe detection method, which is derived based on the Canny rule. First, the Canny rule outputs pixels at the left and right edges of the laser stripe. Then, a subpixel edge extraction method is proposed based on polynomial fitting that outputs the center curve of the laser stripe. Finally, an edge filter is used to smooth the edge burrs, and the Hermite interpolation method is used to link the broken edges and construct continuous, smoothing edge contours. The results show that this method can effectively find the subpixel position of the laser stripe and output high‐quality edge contours. The method is suitable for extracting the contours of a laser stripe located in a microscope image.
TrABin: Trustworthy analyses of binaries

Verification of microkernels, device drivers, and crypto routines requires analyses at the binary level. In order to automate these analyses, in the last years several binary analysis platforms have been introduced. These platforms share a common design: the adoption of hardware-independent intermediate representations, a mechanism to translate architecture dependent code to this representation, and a set of architecture independent analyses that process the intermediate representation. The usage of these platforms to verify software introduces the need for trusting both the correctness of the translation from binary code to intermediate language (called transpilation) and the correctness of the analyses. Achieving a high degree of trust is challenging since the transpilation must handle (i) all the side effects of the instructions, (ii) multiple instruction encodings (e.g. ARM Thumb), and (iii) variable instruction length (e.g. Intel). Similarly, analyses can use complex transformations (e.g. loop unrolling) and simplifications (e.g. partial evaluation) of the artifacts, whose bugs can jeopardize correctness of the results. We overcome these problems by developing a binary analysis platform on top of the interactive theorem prover HOL4. First, we formally model a binary intermediate language and we prove correctness of several supporting tools (i.e. a type checker). Then, we implement two proof-producing transpilers, which respectively translate ARMv8 and CortexM0 programs to the intermediate language and generate a certificate. This certificate is a HOL4 proofdemonstrating correctness of the translation. As demonstrating analysis, we implement a proof-producing weakest precondition generator, which can be used to verify that a given loop-free program fragment satisfies a contract. Finally, we use an AES encryption implementation to benchmark our platform.
A Trace Lasso Regularized Robust Nonparallel Proximal Support Vector Machine for Noisy Classification

Generalized eigenvalue proximal support vector machine (GEPSVM) and its improvement IGEPSVM are excellent nonparallel classification methods due to their excellent generalization. However, all of them adopt the square L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm metric to implement their empirical risk or penalty, which is sensitive to noise and outliers. Moreover, in many real-world learning tasks, it is a significant challenge for GEPSVMs when the data appears highly correlated. To alleviate the above issues, in this paper, we propose a novel trace lasso regularized robust nonparallel proximal support vector machine (RNPSVM) for noisy classification. Compared with GEPSVMs, our RNPSVM enjoys the following advantages. First, the empirical risk of RNPSVM is implemented by the robust L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm metric with a maximum margin criterion. Namely, it aims to maximize the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm inter-class distance dispersion while minimizing the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm intra-class distance dispersion simultaneously. Second, to capture the sparsity and the underlying correlation of data, a trace lasso (adaptive norm-based training data) is further introduced to regularize RNPSVM. Third, an iterative algorithm is designed to solve the maximization optimization problem of RNPSVM, whose convergence is guaranteed theoretically. The extensive experimental results on both synthetic and real-world noisy datasets demonstrate the effectiveness of RNPSVM.
A Comparative Analysis of Web Search Query: Informational Vs. Navigational Queries

The search engines are mainly used to retrieve relevant information. Information retrieval researchers show that queries are the basis for providing better search engine performance. The search query is becoming a means for users to search for their needed information. Web search query is one of the common search queries that is widely used in domain areas. However, the main challenge is the absence of a clear understanding of how web search query influences the users’ behavior on different web search engines. With the emergence of different types of a web search query, the understanding of user behavior on a web search query guides in improving the performance of many web search engines. Current research focused on using informational queries to search relevance information from a database while ignoring the importance of navigational queries. In this paper, we compared the informational and navigational type of a web search query that is mostly used in academic settings. Specifically, we examine the problems, solutions and techniques used in each of these types. We used a query log to conduct an experiment using BM25 mathematical model. The results indicated that the informational search query performed best because several keywords have been included to properly explain the queries. Also, language vocabularies used in informational queries contributed to better search performance. We believed that the outcomes of our comparisons will guide web search engine developers on the right search query for their web search engines.
Facing cyberthreats: Answering the new security challenges of the digital age

With the second wave of the COVID-19 pandemic, more and more countries are implementing large-scale technology-based tracking measures to monitor and prevent the propagation of the virus across the population. Yet, despite important efforts made by governments in terms of development and media campaigns, these technology-based tracking applications are globally failing to get the adhesion of the population. Indeed, the social acceptability of these technologies is problematic, since these applications are perceived as presenting a risk on individual liberties, resulting in very low levels of trust from the population. The aim of this paper is thus to analyze how technology-based tracking in the context of a pandemic can answer the needs and requirements of social accountability. We will first describe what kind of technological means can be used in a pandemic management context, from Internet control to implanted devices. We will then present some of the key factors that can impact the social acceptability of technological tracking, as well as some of the long-term challenges associated with massive technological tracking of the population. Finally, we will propose an operational framework to conceptualize social acceptability enforcement and to optimize population adhesion to these measures via specific practical actions that can be undertaken by governments, policymakers, decision leaders, and application developers to ensure that technological tracking is not only socially accepted, but also socially acceptable.
Local unambiguous discrimination of symmetric ternary states

We investigate unambiguous discrimination between given quantum states with a sequential measurement, which is restricted to local measurements and one-way classical communication. If the given states are binary or those each of whose individual systems is two-dimensional, then it is in some cases known whether a sequential measurement achieves a globally optimal unambiguous measurement. In contrast, for more than two states each of whose individual systems is more than two-dimensional, the problem becomes extremely complicated. This paper focuses on symmetric ternary pure states each of whose individual systems is three-dimensional, which include phase shift keyed (PSK) optical coherent states and a lifted version of "double trine" states. We provide a necessary and sufficient condition for an optimal sequential measurement to be globally optimal for the bipartite case. A sufficient condition of global optimality for multipartite states is also presented. One can easily judge whether these conditions hold for given states. Some examples are given, which demonstrate that, despite the restriction to local measurements and one-way classical communication, a sequential measurement can be globally optimal in quite a few cases.
Wavelength-tuning point diffraction interferometer resisting inconsistent light intensity and environmental vibration: application to high-precision measurement of a large-aperture spherical surface

Phase-shifting point diffraction interferometers are used to measure large-aperture spherical optical elements because of their high level of measurement accuracy. As the most commonly used phase-shifting method, piezoelectric ceramic transducers are faced with nonlinear problems. Wavelength tuning is typically used to solve the phase-shifting problem; however, it is sensitive to environmental vibrations and light intensity changes during tuning. Therefore, a global optimization iterative algorithm based on interferogram normalization is proposed here. The method is insensitive to noise, defects, and light intensity changes and has a strong ability to resist environmental disturbance. Simulations and experiments are performed to verify the effectiveness of the proposed method.
Diagonal quantum discord

Quantum discord measures quantum correlation by comparing the quantum mutual information with the maximal amount of mutual information accessible to a quantum measurement. This paper analyzes the properties of diagonal discord, a simplified version of discord that compares quantum mutual information with the mutual information revealed by a measurement that correspond to the eigenstates of the local density matrices. In contrast to the optimized discord, diagonal discord is easily computable; it also finds connections to thermodynamics and resource theory. Here we further show that, for the generic case of non-degenerate local density matrices, diagonal discord exhibits desirable properties as a preferable discord measure. We employ the theory of resource destroying maps (Liu Z-W et al 2017 Phys. Rev. Lett. 118 060502) to prove that diagonal discord is monotonically nonincreasing under the operation of local discord nongenerating qudit channels, d > 2, and provide numerical evidence that such monotonicity holds for qubit channels as well. We also show that it is continuous, and derive a Fannes-like continuity bound. Our results hold for a variety of simple discord measures generalized from diagonal discord.
Beyond Turing: Intelligent Agents Centered on the User

Most research on intelligent agents centers on the agent and not on the user. We look at the origins of agent-centric research for slot-filling, gaming and chatbot agents. We then argue that it is important to concentrate more on the user. After reviewing relevant literature, some approaches for creating and assessing user-centric systems are proposed.
Optimal measurement strategies for fast entanglement detection

With the advance of quantum information technology, the question of how to most efficiently test quantum circuits is becoming of increasing relevance. Here we introduce the statistics of lengths of measurement sequences that allows one to certify entanglement across a given bipartition of a multiqubit system over the possible sequence of measurements of random unknown states and identify the best measurement strategies in the sense of the (on average) shortest measurement sequence of (multiqubit) Pauli measurements. The approach is based on the algorithm of truncated moment sequences, which allows one to deal naturally with incomplete information, i.e., information that does not fully specify the quantum state. We find that the set of measurements corresponding to diagonal matrix elements of the moment matrix of the state are particularly efficient. For symmetric states their number increases only like the third power of the number $N$ of qubits. Their efficiency increases rapidly with $N$, leaving already for $N=4$ less than a fraction ${10}^{\ensuremath{-}6}$ of randomly chosen entangled states undetected.
Adiabatic speedup via zero-energy-change control in a spin system

Adiabatic evolution is required in performing quantum information processing tasks and adiabatic speedup is often used to avoid decoherence problems for a long evolution time. Here, we add a leakage elimination operator (LEO) Hamiltonian to the evolution and adiabatic speedup can be obtained. LEO Hamiltonians can be realized by a sequence of periodic zero-energy-change pulses. By using the Feshbach partitioning technique, we obtain the exact control parameters to realize adiabatic speedup for different types of pulses. Furthermore, we show that this control scheme is fault-tolerant against pulse strength and pulse frequency for specified thresholds.
Micromotion-enhanced fast entangling gates for trapped-ion quantum computing

Radio-frequency-induced micromotion in trapped ion systems is typically minimized or circumvented to avoid off-resonant couplings for adiabatic processes such as multi-ion gate operations. Nonadiabatic entangling gates (so-called ``fast gates'') do not require resolution of specific motional sidebands and are, therefore, not limited to time scales longer than the trapping period. We find that fast gates designed for micromotion-free environments have a significantly reduced fidelity in the presence of micromotion. We show that when fast gates are designed to account for the radio-frequency-induced micromotion, they can, in fact, outperform fast gates in the absence of micromotion. The state-dependent force due to the laser induces energy shifts that are amplified by the state-independent forces producing the micromotion. This enhancement is present for all trapping parameters and is robust to realistic sources of experimental error. This result paves the way for fast two-qubit entangling gates on scalable two-dimensional architectures, where micromotion is necessarily present on at least one interion axis.
Learning to read online: the effect of instruction on e-textbook use

Purpose The purpose of this paper is to examine the effect of library instruction on the use of e-textbook features in a seventh-grade science class in Budapest, Hungary. Using the theory of value-expectancy, library instruction was designed to show students how the e-textbook features would improve their study habits. Design/methodology/approach Using a time-series, within-subject design, the researchers examined the students’ use of e-textbooks before receiving library instruction, and then again after receiving library instruction. Data were collected from student survey responses, focus group interviews, and digital library usage. A repeated-measures t -test was used to compare data collected prior to and following the instructional sessions. Findings The results indicate that the use of e-textbook features (glossary, audio, quizzes, notes, highlighter, and video) increased after library instruction. While the use of e-textbook features increased, this did not translate to other types of e-books: the use of the digital library did not increase. Research limitations/implications This paper has implications for research on the use of e-textbooks in academic settings. Baseline findings support the existing literature that shows that students do not use all of the features of an e-textbook. The research in this study adds that direct instruction on those features will increase use. Practical implications Librarians and teachers may want to consider direct instruction on e-textbooks. While it may not increase digital library usage, it may benefit the student learning experience. Originality/value This study builds on the work related to the student experience of using e-textbook. It highlights the value of library instruction in improving the student experience and use of e-textbooks.
Security Analysis of SM9 Key Agreement and Encryption

SM9 is a Chinese cryptography standard that defines a set of identity-based cryptographic schemes from pairings. Although the SM9 key agreement protocol and the SM9 encryption scheme have been used for years, there is no public available security analysis of these two schemes. In this paper, we formally analyze the security of these two schemes in the random oracle model.