Reviewerly/exHarmony huggingface dataset:
Fortifying the Blockchain: A Systematic Review and Classification of Post-Quantum Consensus Solutions for Enhanced Security and Resilience

The inherent security and computational demands of classical consensus protocols are often presumed impervious to various forms of attack. However, quantum computing advancements present considerable threats to the assumed attack resistance of classical security strategies currently deployed within blockchain systems. Adopting consensus algorithms fortified with post-quantum security measures holds the potential to significantly enhance the privacy and security dimensions of traditional blockchains. Notable advantages of such post-quantum solutions in the context of blockchain consensus include accelerated transaction verification, clarified mining authorship, and resilience against quantum attacks. Yet, a comprehensive analysis of the implications of post-quantum solutions for blockchain consensus is notably absent in the existing scholarly discourse. This paper aims to bridge this gap by delivering a systematic review of Post-Quantum Blockchain Consensus (PQBC). The four primary contributions of this study are (i) a systematic approach to presenting a comprehensive overview of PQBC, (ii) the systematic selection and analysis of 29 key studies from an initial pool of 1192 papers, (iii) a critical review of methods, enhancements to security, scalability, trust, and privacy, as well as the evaluation employed for PQBC, and (iv) a discussion of primary gaps and prospective directions for future PQBC research.
Cryptensor: A Resource-Shared Co-Processor to Accelerate Convolutional Neural Network and Polynomial Convolution

Practical deployment of convolutional neural network (CNN) and cryptography algorithm on constrained devices are challenging due to the huge computation and memory requirement. Developing separate hardware accelerator for AI and cryptography incur large area consumption, which is not desirable in many applications. This article proposes a viable solution to this issue by expressing the CNN and cryptography as generic-matrix-multiplication (GEMM) operations and map them to the same accelerator for reduced hardware consumption. A novel systolic tensor array (STA) design was proposed to reduce the data movement, effectively reducing the operand registers by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> . Two novel techniques, input layer extension and polynomial factorization, are proposed to mitigate the under-utilization issue found in existing STA architecture. Additionally, the tensor processing element (TPE) is fused using DSP unit to reduce the look-up table (LUT) and flip-flops (FFs) consumption for implementing multipliers. On top of that, a novel memory efficient factorization technique is proposed to allow computation of polynomial convolution on the same STA. Experimental results show that Cryptensor achieved 21.6% better throughput for VGG-16 implementation on XC7Z020 FPGA; up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8.40\times $ </tex-math></inline-formula> better-energy efficiency compared to existing ResNet-18 implementation on XC7Z045 FPGA. Cryptensor can also flexibly support multiple security levels in NTRU scheme, with no additional hardware. The proposed hardware unifies the computation of two different domains that are critical for IoT applications, which greatly reduces the hardware consumption on edge nodes.
Impact of Holdings on Resource Sharing

This paper will explore the issues surrounding the impacts of holdings on resource sharing, and identify options for providing users with efficient access to materials. A case can be made for using the term “access” to describe any department or service in a library–access to materials, access to bibliographic records, access to location assistance, access to local collections, access to other collections, access to the information highway, and so on. Then again, the information highway provides access to information, electronic publishers provide access to information, information brokers provide access to information, and commercial document suppliers provide access to information. So, what is the difference? What do libraries have that other information access points lack? That is easy: collections. Well, not exactly easy; in fact, collections are becoming increasingly troublesome, beginning with the basic task of defining them. Let’s stop right there–defining them. That is where holdings and access come together. In order for users to experience a seamless circle of access to information, the definition of collections suddenly incorporates a description of both holdings and access.
Introduction to Digital Libraries

This tutorial is a thorough and deep introduction to the Digital Libraries (DL) field, providing a firm foundation: covering key concepts and terminology, as well as services, systems, technologies, methods, standards, projects, issues, and practices. It introduces and builds upon a firm theoretical foundation (starting with the '5S' set of intuitive aspects: Streams, Structures, Spaces, Scenarios, Societies), giving careful definitions and explanations of all the key parts of a 'minimal digital library', and expanding from that basis to cover key DL issues. Illustrations come from a set of case studies, including from multiple current projects, including with webpages, tweets, and social networks. Attendees will be exposed to four Morgan and Claypool books that elaborate on 5S, published 2012-2014. Complementing the coverage of '5S' will be an overview of key aspects of the DELOS Reference Model and DL.org activities. Further, use of a Hadoop cluster supporting big data DLs will be described.
Sesquióxidos de hierro en bosques templado húmedos del estado de Hidalgo, México

Total iron dissolved and iron forms extracted with acid ammonium oxalate, sodium pyrophosphate and dithionate- citrate- bicarbonate were studie...
Measurement-Induced Nonlocality in an n-Partite Quantum State

We generalize the concept of measurement-induced non-locality (MIN) to an n-partite quantum state. We get exact analytical expressions for MIN in an n-partite pure and n-qubit mixed state. We obtain the conditions under which MiN equals geometric quantum discord in an n-partite pure state and an n-qubit mixed state.&#x0D;
THE MASKS OF AN ORGANISATION. METACOMMUNICATION ELEMENTS IN THE DIGITAL MEDIA

Gaining a modus vivendi status in the contemporary society, the new communication means bring new values to the construction of meaning. The complex interaction between the technical instrument and the message points out the way in which, by articulating the enunciation, the technical devices turn into metacommunication elements and thus contribute to the meaning production. Our observations focus on the online organisational communication and pursue the creation and perception of the identity image. The comparative study on which our research is based on Samsung’s digital communication in Romania and France. Taking into account Thierry Libaert’s theory according to which the brand strategy is determined by four factors: the desired image, the possible image, the projected image and the perceived image, our study reveals the various masks used by the issuing organisation in relation to its receiver.
A COMPREHENSIVE PERFORMANCE EVALUATION OF DATA STORES IN CONTEXT WITH APPLICATION MANAGEMENT TOOLS

As of 2012, limits on the size of data sets that are feasible to process in a reasonable amount of time were on the order of exabytes of data.business informatics. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s, as of 2012, every day 2.5 quintillion (2.5×1018) bytes of data were created and it is required to analyze a vast amount of data. A number of companies have developed sophisticated monitoring tools for data analysis. For specialized APIs, can monitor single invocations. To maximize the benefit of data monitoring, the data has to be stored for an extended period of time for ulterior analysis. This new wave of big data analytics imposes new challenges especially for the application performance monitoring systems. The monitoring data has to be stored in a system that can sustain the high data rates and at the same time enable an up-to-date view of the underlying infrastructure. With the advent of modern key-value stores, a variety of data storage systems have emerged that are built with a focus on scalability and high data rates as predominant in this monitoring use case. In this work, we present our experience and a comprehensive performance evaluation of six modern (open-source) data stores in the context of application performance monitoring. We evaluated these systems with data and workloads that can be found in application performance monitoring, as well as, on-line advertisement, power monitoring, and many other use cases. We present our insights not only as performance results but also as lessons learned and our experience relating to the setup and configuration complexity of these data stores in an industry setting.
Does school spending matter?

Journal of Policy Analysis and ManagementVolume 42, Issue 4 p. 1117-1117 POINT/COUNTERPOINT Does school spending matter? First published: 22 August 2023 https://doi.org/10.1002/pam.22512 Handling Co-Editors: Paul Decker and Kevin Kelly Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume42, Issue4Autumn (Fall) 2023Pages 1117-1117 RelatedInformation
Delphi Study on Curriculum Development for Unification Social Welfare

Owing to the increase of the aged, a positive analysis was earned out for developing the aged volunteering program. This study aiming at planning for the aged volunteering activation, desirable leasure activity in the dimension of social welfare, by assaying the real states of the aged making the use of the leasure and especially aiming at surveying the aged need in relation with the aged volunteering activity on which to present the revolving method and qualitative advance. The method of study was interview the aged over 60 with the questionnaire of the general features of the participants, the motive, the career, the participation method, the satisfaction degree, the cost necessity, the participation degree, the pre-education, and the desirable program of the volunteering and what is got from the volunteering, etc. The collected data were statistical-processed through Spss Win(Ver 8.0) and chi-square verified. As the result of this study, there are the needs for developing various program, the motivation for the participation and maintenance, and the suitable places for volunteering. The poly-dimensional social welfare approaches are presented for the above needs.
Integrating Certifications Into Information Systems Curricula

The objective of this paper is to propose a curriculum that provides graduates with an IS degree as well as the opportunity to acquire IT certificates upon graduation.In this paper, we examine institutions which integrate certificates in their IS curriculum.Moreover, we examine the IS 2002 report and ABET requirements to identify IS tracks that can lead to a particular certification.Popular IT certificates are identified and for each certificate a series of IS courses are developed to include the objectives of that particular certificate.For example, we will show how to integrate the Sun Certification for Java Programmer into programming courses, the Cisco CCNA or Network+ certificate into networking course, the A+ certificate into the IT Hardware and Software course and an operating system course, and the MOUS certificate into the personal productivity with IS technology course.Other certifications such as ORACLE can also be included into the IS elective courses.The goal is for the curriculum to provide an avenue for students to take the certification exam after completing the course series leading to that certificate.This research will help faculty design their courses to integrate certain certificates.It will also help students choose their courses in order to acquire certificates.
Ask Njit Library: A Natural Language Knowledge Base Self Service Solution

As library websites proliferated over the years, librarians have developed ways of enhancing users' experiences as they navigate a vast ocean of valuable library resources.Librarians have also been creative in handling high volume inquiries via online help desk service that include FAQ, chat service and email reference that have some 24/7 elements.These services are necessary but still not sufficient for today's impatient library users looking for instant gratification.This paper addresses a 24/7 website self-service experience that makes it easy for website visitors to type a question in natural language and get one right answer.It will be demonstrated how ready reference questions can now be answered through a natural language knowledgebase powered by IntelliResponse that can be updated every time a user asks a new but important question.There are many benefits of this empowering program such as reduction of email volume, phone calls and chat sessions and reduced navigation linked with website Q&A or FAQ solutions.The quality of end user experience is measured objectively via system generated reports.Potential exists for institutions to collaborate and build such knowledgebases more efficiently and for development of self-learning tools.
Figures and Tables

Figures are an extremely important part of any scientific publication. It is a rarepaper that contains no figures (such papers are mostly of the theoretical variety,though even a pure theory paper often benefits from a good graph). As therenowned guru of graphics Edward Tufte put it, “At their best, graphics areinstruments for reasoning about quantitative information.” Because almost allscientific publications include quantitative information to be reasoned about,figures are almost always necessary. 4.1 The Goals of Using Figures As a form of communication, figures (and in particular, the graphical display ofquantitative data) are uniquely suited to conveying information from complex data sets quickly and effectively. Whereas statistical analysis aims for data reduction (expressing a mass of data by a few simple metrics), graphing retains the full information of the data. Graphs take advantage of the magnificent power of the human brain to recognize visual/spatial patterns and to quickly change focus from the big picture to small details. Graphs are used for data analysis and for data communication, though only the latter application will be discussed here. Graphs are extremely popular in scientific literature3 for the simple reason that they work so well. But like all forms of communication, graphics can be used to explain andclarify but also to confuse or deceive. Thus, the first rule of graphics is a simpleone: they must help to reveal the truth. Just as disorganized writing often indicates disorganized thinking, a chart that fails to tell the story of the data usually means the author does not recognize what story should be told. Thus, sufficient care should be given to the design and execution of graphics, just as in the design and execution of the written paper itself.
HB-YOLO: An Improved YOLOv7 Algorithm for Dim-Object Tracking in Satellite Remote Sensing Videos

The You Only Look Once (YOLO) series has been widely adopted across various domains. With the increasing prevalence of continuous satellite observation, the resulting video streams can be subjected to intelligent analysis for various applications, such as traffic flow statistics, military operations, and other fields. Nevertheless, the signal-to-noise ratio of objects in satellite videos is considerably low, and their size is often smaller, ranging from tens to one percent, when compared to those taken by drones and other equipment. Consequently, the original YOLO algorithm’s performance is inadequate when detecting tiny objects in satellite videos. Hence, we propose an improved framework, named HB-YOLO. To enable the backbone to extract features, we replaced the universal convolution with an improved HorNet that enables higher-order spatial interactions. We replaced all Extended Efficient Layer Aggregation Networks (ELANs) with the BoTNet attention mechanism to make the features fully fused. In addition, anchors were re-adjusted, and image segmentation was integrated to achieve detection results, which are tracked using the BoT-SORT algorithm. The experimental results indicate that the original algorithm failed to learn using the satellite video dataset, whereas our proposed approach yielded improved recall and precision. Specifically, the F1-score and mean average precision increased to 0.58 and 0.53, respectively, and the object-tracking performance was enhanced by incorporating the image segmentation method.
Pixel-wise phase unwrapping of fringe projection profilometry based on deep learning

Phase unwrapping is a crucial step in high-precision optical metrology, aimed at retrieving absolute phases from wrapped phases. This paper presents a deep learning-based phase unwrapping method that enhances the conventional three-wavelength heterodyne method and achieves pixel-wise phase unwrapping using a wrapped phase map and two fringe patterns. The proposed method formulates the phase unwrapping task as a semantic segmentation problem that infers an absolute fringe order for each wrapped phase pixel. The verification results demonstrate that the method can accurately measure surfaces with complex topologies. Under low noise conditions, the proposed method achieves performance comparable to the three-wavelength heterodyne method, with similarity rates between the fringe order maps obtained by the two methods of up to 0.99; additionally, the method exhibits superb resistance to severe noise. Moreover, the proposed method is more efficient in terms of fringe pattern efficiency by at least 44.44%.
Cyber resilience and cyber security issues of intelligent cloud computing systems

It is necessary to provide the cyber security of cloud computing according to the components that constitute its structure. The first step in advancing the cyber security of this technology is to accurately identify its threats. In this paper, a new cyber security reference model of the cloud system, which consists of components making up separate layers of cloud computing is proposed. Available reference models of cloud computing security do not describe the virtualization and service layers and the important components for providing the cyber security of cloud computing in detail, do not consider the social media IoT sensor layer, which collects the text data typed by attackers to carry out cyber attacks on the cloud infrastructure, and the cyber resilience issues of the cloud computing at all In addition, this paper studies the cyber security issues of cloud computing service models, and constructs an attack model to provide security of cloud systems. It gives an interpretation of standards and legislative acts on the cyber security of cloud computing. According to security aspects, clarification of the cyber security and cyber resilience concepts of cloud systems is provided. The cyber resilience architecture of intelligent cloud systems is developed. The advantage of developed cyber resilience model over available one is that, it determines the information security and cyber security aspects of cloud computing and combines them to form the cyber resilience aspects of cloud systems.
Modeling and survival exploration of breast carcinoma: A statistical, maximum likelihood estimation, and artificial neural network perspective

The core objective of this research is to describe the behavior of the distribution using the MLE method to estimate its parameters, as well as to determine the optimal Artificial Neural Network method by comparing it to the maximum likelihood estimation method and applying it to real data for breast cancer patients to determine survival, risk, and other survival study functions of the log-logistic distribution. The parameters were defined in the input layer of the artificial neural network developed for the purpose of survival analysis and reliability function, hazard rate function, probability density function, reserved hazard rate function, Mills ratio, Odd function and CHR values were obtained in the output layer. The findings show that risk function increases with the increase in the time of infection and then decreases for a group of breast cancer patients under study, which corresponds to the theoretical properties of this according to the practical conclusions. The examination of survival analysis reveals that practical conclusions correspond to the theoretical properties of log-logistic distribution. Artificial neural networks have proven to be one of the ideal tools that can be used to predict various vital parameters, especially survival of cancer patients, with their high predictive capabilities.
NNV 2.0: The Neural Network Verification Tool

Abstract This manuscript presents the updated version of the Neural Network Verification (NNV) tool. NNV is a formal verification software tool for deep learning models and cyber-physical systems with neural network components. NNV was first introduced as a verification framework for feedforward and convolutional neural networks, as well as for neural network control systems. Since then, numerous works have made significant improvements in the verification of new deep learning models, as well as tackling some of the scalability issues that may arise when verifying complex models. In this new version of NNV, we introduce verification support for multiple deep learning models, including neural ordinary differential equations, semantic segmentation networks and recurrent neural networks, as well as a collection of reachability methods that aim to reduce the computation cost of reachability analysis of complex neural networks. We have also added direct support for standard input verification formats in the community such as VNNLIB (verification properties), and ONNX (neural networks) formats. We present a collection of experiments in which NNV verifies safety and robustness properties of feedforward, convolutional, semantic segmentation and recurrent neural networks, as well as neural ordinary differential equations and neural network control systems. Furthermore, we demonstrate the capabilities of NNV against a commercially available product in a collection of benchmarks from control systems, semantic segmentation, image classification, and time-series data.
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts

Leading sequential recommendation (SeqRec) models adopt empirical risk minimization (ERM) as the learning framework, which inherently assumes that the training data (historical interaction sequences) and the testing data (future interactions) are drawn from the same distribution. However, such i.i.d. assumption hardly holds in practice, due to the online serving and dynamic nature of recommender system.For example, with the streaming of new data, the item popularity distribution would change, and the user preference would evolve after consuming some items. Such distribution shifts could undermine the ERM framework, hurting the model's generalization ability for future online serving.