Reviewerly/exHarmony huggingface dataset:
Signature Based Authentication: A Multi-label Classification Approach to Detect the Language and Forged Sample in Signature

In this work, we have proposed a multi-label classification algorithm for signature images that can be used to solve multiple objectives: i) It can tell the identity of the image. ii) Can interpret the language of the content written in the image. iii) It can also identify whether the given image is the genuine signature of the person or the forged one. This paper has used the pretrained model GoogLeNet, that has been finetuned on the largest signature dataset present (GPDS). GoogLeNet is used to extract the features from the signature images, and these features are fed to the three-layer neural network. The neural network has been used for the classification of the features of the image. The model has been trained or tested against two regional datasets Hindi and Bengali datasets.
The Missing link between High Performance Work System and product Innovation: a Systematic Review

Aim: Identifying the missing link in the literature between High-Performance Work System (HPWS) and product innovation, and identifying if there are any mediating or moderating variables that play roles in the relationship between HPWS and product innovation. Design of Study: a systematic review of all related articles that link between HPWS and product innovation. Method: a systematic literature searching 8 databases produced 50 articles that touch the subject directly or indirectly. Scanning all of them revealed that only 14 articles were directly examined on the subject and have been published during the last 13 years. Therefore, they were included in the current literature review. Results: the result revealed that HPWS is positively related with product innovation. In addition, the relationship between HPWS and product innovation is mediated by several factors among which the most important are the innovative work behavior and organizational climate. Moreover, a new conceptual model was developed and will be tested in the next phase of this research project. Recommendations: Based on the research results, a set of practical and scientific recommendations were provided. Originality: Emerges from developing a new conceptual model that is missing in the literature and customizing it to fit the Gulf Cooperation Countries (GCC). Future studies: Other organizational factors such as culture, leadership styles, and job engagement could be added to the proposed framework..
Using geographic load shifting to reduce carbon emissions

An increasing focus on the electricity use and carbon emissions associated with computing has lead to pledges by major cloud computing companies to lower their carbon footprint. Data centers have the unique ability to shift computing load between different geographical locations, giving rise to flexibility that can be employed to reduce carbon emissions. In this paper, we present a model where data centers shift load independently of the ISOs. We first consider the impact of load shifting guided by locational marginal carbon emissions, λ CO 2 , a sensitivity metric that measures the impact of incremental load shifts. Relative to previous models for data center load shifting, the presented model improves accuracy and includes more realistic assumptions regarding the operation of data centers and electricity markets. Further, we introduce a benchmark model where data centers have access to the full information about the power system and can identify optimal shifts for the current time period. We demonstrate the efficacy of our model on the IEEE RTS-GMLC system using 5 min load and generation data for an entire year. Our results show that the proposed improvements for the shifting model based on λ CO 2 are highly effective, leading to results that outperform the benchmark model. • Develop a load shifting model to reduce carbon emissions for data center loads. • Introduce a regularization term and cumulative load shifts to existing framework. • Benchmark against a bilevel formulation that enforces DC OPF constraints.
Evidence centered design framework and dynamic bayesian network for modeling learning progression in online assessment system

An overarching mission of the educational assessment community today is strengthening the connection between assessment and learning. To support this effort, researchers draw variously on developments across technology, analytic methods, assessment design frameworks, research in learning domains, and cognitive, social, and situated psychology. The study lays out the connection among three such developments, namely learning progressions, evidence-centered assessment design (ECD), and dynamic Bayesian modeling for measuring students' advancement along learning progression in a substantive domain. Their conjunction can be applied in both formative and summative assessment uses. In addition, this study conducted an application study in domain of beginning computer network engineering for illustrating the ideas with data drawn from the Cisco Networking Academy's online assessment system.
A novel Bayesian method for variable selection and estimation in binary quantile regression

Abstract In this paper, we develop a Bayesian hierarchical model and associated computation strategy for simultaneously conducting parameter estimation and variable selection in binary quantile regression. We specify customary asymmetric Laplace distribution on the error term and assign quantile‐dependent priors on the regression coefficients and a binary vector to identify the model configuration. Thanks to the normal‐exponential mixture representation of the asymmetric Laplace distribution, we proceed to develop a novel three‐stage computational scheme starting with an expectation–maximization algorithm and then the Gibbs sampler followed by an importance re‐weighting step to draw nearly independent Markov chain Monte Carlo samples from the full posterior distributions of the unknown parameters. Simulation studies are conducted to compare the performance of the proposed Bayesian method with that of several existing ones in the literature. Finally, two real‐data applications are provided for illustrative purposes.
Digital curation and open-source software in LAM-related publications

The changing conditions in which LAM institutions operate require constant monitoring of the development of solutions dedicated to different forms of their activities. This article aims at an analysis of the literature related to LAM institutions on open-source software used in digital curation. The undertaken research was an attempt to check the interest in this issue in publications registered in the BASE multi-search database. The research material collected during library searches was analysed using simple bibliometric methods. Based on literature analysis, this paper indicates a growing interest in digital curation in LAM institutions in the context of open-source software. The first publications on this subject recorded in the BASE database date back to 2005. Since then, the number of different publication types has been growing steadily, including in particular conference proceedings and journal articles. An increasing number of authors interested in digital curation associated with many institutions from around the world has also been recorded. The analysis of the material also allowed us to identify various applications available under open-source licences. The article provides an opportunity to look at the changes occurring in the analysed body of literature. It presents leading authors publishing works related to digital curation. It also identifies the most popular software described over 16 years. It provides a comprehensive description of topics and the structure of literature on open-source software used in digital curation. The described analysis results can be a contribution to in-depth research and a set of solutions for practitioners.
Functionality Study of an Optical Measurement Concept for Local Force Signal Determination in High Strain Rate Tensile Tests

Many mechanical material properties show a dependence on the strain rate, e.g. yield stress or elongation at fracture. The quantitative description of the material behavior under dynamic loading is of major importance for the evaluation of crash safety. This is carried out using numerical methods and requires characteristic values for the materials used. For the standardized determination of dynamic characteristic values in sheet metal materials, tensile tests performed according to the guideline from [1]. A particular challenge in dynamic tensile tests is the force measurement during the test. For this purpose, strain gauges are attached on each specimen, wired to the measuring equipment and calibrated. This is a common way to determine a force signal that is as low in vibration and as free of bending moments as possible. The preparation effort for the used strain gauges are enormous. For these reasons, an optical method to determine the force by strain measurement using DIC is presented. The experiments are carried out on a high speed tensile testing system. In combioantion with a 3D DIC high speed system for optical strain measurement. The elastic deformation of the specimen in the dynamometric section is measured using strain gauges and the optical method. The measured signals are then compared to validate the presented method. The investigations are conducted using the dual phase steel material HCT590X and the aluminum material EN AW-6014 T4. Strain rates of up to 240 s-1 are investigated.
Faculty Salary Structure for Publicly Funded Higher Education Institutions of the Russian Federation

There are some serious issues with the recruitment and motivation of the faculty in the publicly-funded higher education of the Russian Federation. They are a significant reduction in the number of teaching staff, a substantial part of the old-age staff, an increase in the total workload and extracurricular work. The most important reason of the described problems is the issue of remuneration. In this regard, the purpose of the study is to suggest some directions for the development of the material remuneration systems for the employees in the publicly funded higher education. The methodological basis of the research are such methods as analysis and synthesis, as well as abstraction and a structurally systematic approach. As a result, it was determined that: 1) unreasonably low official salaries established by professional qualification groups do not provide the reproduction function of wages in full; 2) the differentiation of official salaries for the lecturers of the same qualification level and the position held, due to the size of the financing of budgetary institutions and the remuneration policy of the university, leads to a violation of the principle of “an equal pay for an equal work”; 3) the presence of a large number of incentive payments in the salary structure leads to the “opacity” of wages. The following recommendations are formulated: the salary structure considering the specifics of the publicly funded higher education is justified, methodological approaches to the structure of the official salaries, as well as the incentive and compensation payments are developed.
Quantum information processing fundamentals

This chapter is devoted to the basic concepts of quantum information processing (QIP). Elementary QIP features are described, and basic quantum mechanics concepts are introduced, including the state vectors, operators, density operators, measurements, and dynamics of a quantum system. Also discussed are the superposition principle, quantum parallelism concepts, and QIP basics, after which a formulation and proof of the no-cloning theorem are presented. In addition, we formulate and prove an important theorem that claims it is impossible to unambiguously distinguish nonorthogonal quantum states. The subsequent section is devoted to various aspects of entanglement, including the Schmidt decomposition theorem, purification, superdense coding, and entanglement swapping. The chapter also describes how entanglement can detect and correct quantum errors. Various entanglement measures are introduced, including the entanglement of formation, concurrence, and entanglement fidelity. Further, we discuss the operator-sum representation of a quantum operation and apply this concept to describe quantum errors and decoherence. The bit-flip, phase-flip, phase damping, depolarizing, and amplitude damping channels are described as well.
Hydra: A Quantitative Overview of the World's Largest Darknet Market

Since the first emergence of The Silk Road in 2011, a plethora of anonymous online marketplaces have appeared and disappeared. This paper focuses on one such market, Hydra, which was the largest darknet marketplace in Russia until its shutdown in April 2022. This paper describes the features this online platform provided: user feedback, escrow and dispute resolution, and certification of drug quality. Using two datasets containing data scraped from the platform, we analyse the spatial distribution of drug listings as well as the variety of drug types on the platform. We find that 69\% of the Russian population live in a settlement where at least one drug stash was available for purchase from Hydra. Mephedrone, amphetamine, alpha-PVP, and MDMA accounted for 67% of unique drug listings. We show that delivery costs comprised a high share of the final price of drugs on Hydra. In addition, examining product feedback we find that user ratings are skewed towards the highest possible rating value, similar to prior findings in relation to clearnet market places. To the best of our knowledge, this is the first quantitative assessment of this marketplace in academic literature.
Information Leaks and Voluntary Disclosure

We study managers’ decisions to voluntarily disclose information to the capital market when they face a risk of information leakage. Our analysis offers three main insights. First, we find that leaks that are less informative create market discipline and motivate more voluntary disclosure. Second, an increasing likelihood of information leakage has ambiguous effects. It fosters market discipline but increases managers’ rewards from successful nondisclosure. Consequently, a higher likelihood of leakage impedes disclosure if leaks represent rare events and fosters voluntary disclosure if leaks are sufficiently probable. Third, we find that market discipline is more effective for myopic managers who focus on short-term prices and cannot react to information leaks on a timely basis. Such managers are willing to preempt information leakage and to disclose their private information.
Construction of Emergency Procurement System and System Improvement Based on Convolutional Neural Network

At this stage, countries around the world have their own operating management model for the procurement system of emergency equipment. This article analyzes the influencing factors affecting the operation of the emergency procurement system through a convolutional neural network analysis method, and the contract management of the emergency procurement system is realized. Management and monitoring and balance of interests on supply and demand also meet the requirements of the construction and improvement of emergency procurement systems at this stage. During the construction and improvement of the emergency procurement system, through the monitoring and management of the procurement system, standardize the management of emergency procurement contracts, and implement the management of the memorandum of emergency procurement contracts to maximize the benefits of supply and demand of emergency equipment, and meet the requirements of different emergency levels in the future equipment procurement requirements.
Natural language report of the composting process status using linguistic perception

The paper presents an automated system to report the evolution of a process in natural language expressions, analyzing wireless sensor data with process patterns by the linguistic description of complex phenomena approach. An implemented system generates reports of the composting process using the temperature measured in the core of a compost pile regarding the temperature pattern during the composting phases. The linguistic reports include sentences about the current status, trend, and behavior of the composting process. The automated system posts each linguistic report via a messaging app, such as Twitter, allowing instant and continuous communication with authorized users on mobile devices. The resulting expressions show that this real-time linguistic report system is a suitable and practical framework to inform users of the process evolution, in preference and complement to a database or graph tools, supporting the users to make decisions for processes that require proper data-interpretation-based supervision.
Improved Lattice Enumeration Algorithms by Primal and Dual Reordering Methods

The security of lattice-based cryptosystems is generally based on the hardness of the Shortest Vector Problem (SVP). There are two common categories of lattice algorithms to solve SVP: search algorithms and reduction algorithms. The original enumeration algorithm (ENUM) is one of the former algorithms which run in exponential time due to the exhaustive search. Further, ENUM is used as a subroutine for the BKZ algorithm, which is one of the most practical reduction algorithms. It is a critical issue to reduce the computational complexity of ENUM. In this paper, first, we improve the mechanism in the so-called reordering method proposed by Wang in ACISP 2018. We call this improvement Primal Projective Reordering (PPR) method which permutates the projected vectors by decreasing norms; therefore it performs better to reduce the number of search nodes in ENUM. Then, we propose a Dual Projective Reordering (DPR) method permutating the projected vectors in its dual lattice. In addition, we propose a condition to decide whether the reordering method should be adopted or not. Preliminary experimental results show that our proposed reordering methods can successfully reduce the number of ENUM search nodes comparing to the predecessor, e.g., PPR reduces around 9.6% on average in 30-dimensional random lattices, and DPR reduces around 32.8% on average in 45-dimensional random lattices. Moreover, our simulation shows that the higher the lattice dimension, the more the proposed reordering method can reduce ENUM search nodes.
Practical Post-quantum Password-Authenticated Key Exchange Based-on Module-Lattice

Password-authenticated key exchange (PAKE) is a neat technology that can establish secure remote communications between the client and the server, especially with the preponderance of amplifying a memorable password into a strong session key. However, the arrival of the quantum computing era has brought new challenges to traditional PAKE protocols. Thus, designing an efficient post-quantum PAKE scheme becomes an open research question. In this paper, we construct a quantum-safe PAKE protocol which is a horizontal extension of the PAK protocol [22] in the field of module lattice. Subsequently, we accompany our proposed protocol with a rigorous security proof in the Bellare-Pointcheval-Rogaway (BPR) model with two adaptions: applying the CDF-Zipf model to characterize the ability of the adversary and using the pairing with errors (PWE) assumption to simplify the proof. Taking the flexibility of the module learning with errors (MLWE) problem, we elaborately select 3 parameter sets to meet different application scenarios (e.g., classical/quantum-safe Transport Layer Security (TLS), resource-constrained Internet of Things (IoT) devices). Specifically, our Recommended implementation achieves 177-bit post-quantum security with a generous margin to cope with later improvement in cryptanalysis. The performance results indicate that our MLWE-PAKE is quite practical: compared with the latest Yang-PAK, our Recommended-PAK reduces the communication cost and the running time by 36.8% and 13.8%, respectively.
$$T{-}depth$$ Reduction Method for Efficient $$SHA{-}256$$ Quantum Circuit Construction

In order to perform a quantum brute force attack on a crypto-system based on Grover's algorithm, it is necessary to implement a quantum circuit of the cryptographic algorithm. Therefore an efficient quantum circuit design of a given cryptographic algorithm is essential, especially in terms of quantum security analysis, and it is well known that T-depth should be reduced for time complexity efficiency. In this paper, we propose a novel technique to reduce $$T{-}depth$$ (and $$T{-}count$$ ) when some quantum circuits located in between two Toffoli-gates are interchangeable with a controlled phase gate (Controlled-P gate), and apply this technique to four types of quantum adders, resulting in a T-depth reduction of about 33 $$\%$$ . We also present new SHA-256 quantum circuits which have a critical path with only 3 quantum adders while the critical paths of quantum circuits in the previous works consist of 7 or 9 quantum adders, and also apply our technique to the proposed $$SHA{-}256$$ quantum circuits and the included quantum adders. Among the previous results, the T-depth of the circuit with the smallest Width 801 was approximately 109,104. On the other hand, that of the proposed SHA-256 quantum circuit with the width 799 is 16,121, which is remarkably reduced by about 85%. Furthermore, the other proposed quantum circuit only requires 768 qubits which is the smallest Width compared to the previous results to the best of our knowledge.
Compiler-based Attack Origin Tracking with Dynamic Taint Analysis

Over the last decade, many exploit mitigations based on Control Flow Integrity (CFI) have been developed to secure programs from being hijacked by attackers. However, most of them only abort the protected application after attack detection, producing no further information for attack analysis. Solely restarting the application leaves it open for repeated attack attempts. We propose Resilient CFI, a compiler-based CFI approach that utilizes dynamic taint analysis to detect code pointer overwrites and trace attacks back to their origin. Gained insights can be used to identify attackers and exclude them from further communication with the application. We implemented our approach as extension to LLVM’s Dataflow Sanitizer, an actively maintained data-flow tracking engine. Our results show that control-flow hijacking attempts can be reliably detected. Compared to previous approaches based on Dynamic Binary Instrumentation, our compiler-based static instrumentation introduces less run-time overhead: on average 3.52x for SPEC CPU2017 benchmarks and 1.56x for the real-world web server NginX.
Improved See-In-The-Middle Attacks on AES

The See-In-The-Middle attack is designed to work effectively even with a low signal to noise ratio; hence, it can be performed even with poor side-channel analysis tools. Because it exploits the side-channel leakage of the middle round of the block cipher implementations, it is effective for implementations with reduced masking. In this study, we propose attacks to improve the See-In-The-Middle attack against the 4-round masked implemented AES introduced in the previous work. In addition, we present an attack against AES-256 implemented with 12-round reduced masking to recover 2-byte of the master key using the related-key differential trail, showing that the See-In-The-Middle attack is only thwarted by masking the whole rounds of AES-256 in the related-key model.