Reviewerly/exHarmony huggingface dataset:
School libraries in the virtual world

Goal. The paper aims to present the database of links of virtual libraries designed by school librarians, in order to highlight the importance of the school libraries’ role in e-learning and the use of new technologies in education. Approach/methodology. The paper presents an analysis of virtual libraries available in the repository of the school librarianship UDK02, the Croatian network of school librarians. The classification, i.e. the taxonomy of repository content was created with the list of topics, subtopics, and digital tools used by school librarians. Results. The Croatian Library Repository UDK02 contains links to 243 virtual libraries (183 primary and 60 secondary school libraries). Practical implementation. By uniting all virtual libraries in one place, the librarians and all other users have access to a large number of different information. Besides, this website could be the starting page for one joint page for all librarians in the future. Limitations. It is necessary to constantly update virtual pages of all libraries and check the links because some links are no longer available after some time, and also publish our own new materials. Social significance. The pandemic caused by the COVID-19 disease has had a huge impact on society as a whole. The school librarians have aimed to reduce/mitigate all elements of the negative impact with the activities of virtual libraries. The school librarians have continued to support the educational process by referring to available learning and teaching online materials. Originality. The paper presents some high-quality solutions of school librarians in providing services to their users during the pandemic caused by the COVID-19 disease and after the closure of libraries at the national level. Furthermore, the paper empha-sizes the importance of the school library visibility and the library’s importance as a reinforcement to the educational process. In addition, a brief analysis indicates the op-portunities for improvement and further development. © 2021, Hrvatsko Knjiznicarsko Drustvo. All rights reserved.
ESP Learners Pronounce in New Trend (You Tube) Application: Instructor's Perception and Practice

The aim of teaching English for Specific Purposes (ESP) is not to imitate the native speakers or to develop the British or American accents. English communication influences the first language or mother tongue for ESP learners. Meanwhile, According to Evan (1997), ESP has some characteristics, such as: firstly, ESP may be related or designed for specific disciplines, secondly, ESP may be used in specific teaching situations and has different methodology from that of General English (GE); thirdly, ESP is likely to be designed for adult learners, either at a tertiary level education or in a professional work situation; fourthly, most ESP courses take on some basic knowledge of the language systems. This research used descriptive qualitative research as a design to gather or collect the data because of the current phenomenon to explain the error of pronunciation and the causes of error in pronouncing words. This paper will be done by researchers at Management Class who learn the ESP program in Kaltara University. This research also used observation field notes and interview guide as the instruments. Hence, the researchers found that there were fifteen pronunciation errors who were presented by ESP learners’ mother tongue in learning speaking through YouTube Application. Besides, there were four materials in You Tube Application that pronounced by ESP Learners such as: Promotion, Bargaining, Complaining, and Response.&#x0D;
Remotely controlling TrustZone applications? A study on securely and resiliently receiving remote commands

Mobile devices are becoming an indispensable part of work for corporations and governments to store and process sensitive information. Thus, it is important for remote administrators to maintain control of these devices via Mobile Device Management (MDM) solutions. ARM TrustZone has been widely regarded as the de facto solution for protecting the security-sensitive software, such as MDM agents, from attacks of a compromised rich OS. However, little attention has been given to protecting the MDM control channel, a fundamental component for a remote administrator to invoke the TrustZone-based MDM agents and perform specific management operations. In this work, we design an ARM TrustZone-based network mechanism, called TZNIC, towards enabling resilient and secure access to TrustZone-based software, even in the presence of a malicious rich OS. TZNIC deploys two NIC drivers, one secure-world driver and one normal-world driver, multiplexing one physical NIC. We utilize the ARM TrustZone-based high privilege to protect the secure-world driver and further resolve several challenges on sharing one set of hardware peripherals between two isolated software environments. TZNIC does not require any changes or collaboration of the rich OS. We implement a prototype of TZNIC, and the evaluation results show that TZNIC can provide a reliable network channel to invoke the security software in the secure world, with minimal system overhead on the rich OS.
DeCSIDH: Delegating Isogeny Computations in the CSIDH Setting

Delegating heavy computations to auxiliary servers, while keeping the inputs secret, presents a practical solution for computationally limited devices to use resource-intense cryptographic protocols, such as those based on isogenies, and thus allows the deployment of post-quantum security on mobile devices and in the internet of things. We propose two algorithms for the secure and verifiable delegation of isogeny computations in the CSIDH setting. We then apply these algorithms to different instances of CSIDH and to the signing algorithms SeaSign and CSI-FiSh. Our algorithms present a communication-cost trade-off. Asymptotically (for high communication), the cost for the delegator is reduced by a factor 9 for the original CSIDH-512 parameter set and a factor 30 for SQALE'd CSIDH-4096, while the relative cost of SeaSign vanishes. Even for much lower communication cost, we come close to these asymptotic results. Using the knowledge of the class group, the delegation of CSI-FiSh is basically free (up to element generation) already at a very low communication cost.
Quick Black Box Variational Inference Using Gaussian Cubature Integration Rules

A novel variant of black box variational inference, which employs Gaussian cubature integration rules, is proposed. The method is applicable to small and medium scale problems and is particularly well fitted for real-time applications such as radar. The application of the cubature rule results in noise-free estimates of the evidence lower bound and its gradient. This feature allows one to employ quasi-Newton optimization methods, which converge considerably faster than stochastic gradient methods used in classical black box variational inference. The improvement in convergence speed is demonstrated using the direction of arrival estimation as an example.
First-Order Meta-Learning in Node Classification with Graph Convolutional Network

In recent years, research on graph representation learning within graph neural networks has made great progress. Among them, graph convolutional neural networks (GCN), which is based on spectral domain, have drawn great attention and become one of the mainstream graph embedding approaches. However, few-shot learning on graphs has little related work, as we know. Toward this problem, we propose a meta-learning method on graphs, FOML-GCN (First order meta-learning on GCN), aimed to be applied in various kinds of models of graph convolutional networks. As many common approaches in meta-learning, FOML-GCN involves two phases, meta-training and meta-testing. By learning the potential Knowledge from a small number of samples in existing classes during meta-training, our method enhances the ability in node classification of the base model by training within new few data that only appear in the meta-testing step. The experiment on two benchmark datasets shows that our FOML-GCN performs better than base GCN and other models of graph network in few-shot node classification tasks.
Feature Selection Using Clustering Ensemble with Internal Weighting Strategy

Due to its performance, unsupervised feature selection methods guided by clustering attracted the researchers. Recently, some modified measures taking clustering accuracy and stability into consideration, they adopt the clustering ensemble method to guide feature selection. However, reducing the influnce of low-quality base clusterings on clustering ensemble result is a remarkable challenge for clustering ensemble. In addition, weighting clustering ensemble could appears the condition that the value of weights are close to each other, which cannot effecitively distinguish high-quality base clustering from all clusterings. In light of these, Internal Weighting Clustering Ensemble of Feature Selection (IWCEFS) method is proposed, which combines the Clustering Ensemble with Adaptive Weight Learning (CEAWL) and sparse learning to select features. And CEAWL puts forward maximum validity vector to differentiate the quality of base clustering. Beyond that CEAWL takes a mathematic model and the resoultion to reslove the similarly weights. Finally, the extensive experiments is conducted to demonstrate the superiority of the proposed approach.
Technological and Methodological Advances in the Protection of Soft Targets: The Experience of the STEPWISE Project

The chapter presents the STEPWISE project, funded under the Internal Security Fund Police (ISFP) programme, and related to the provision of a toolkit for the preparation and evaluation of the protection of public spaces through the virtual mock-up of such areas and the use of dedicated tools and methodology. In particular, in this chapter we will argue how methodological and technological advances in the development of Decision Support Systems (DSS) may improve the assessment and the evaluation of security plans and response of critical/relevant buildings and public spaces or even areas, which could constitute elective targets for potential attacks. After briefly discussing the methodological and technological gaps in the development of DSS, we will show the added value in bridging these gaps that will be achieved with the implementation of the STEPWISE project, and we will discuss about its current limitations as well as potential future developments.
How We Can Secure Blockchain-Based Systems

So far, we have considered the basic components of, and some significant unsolved problems in, specific technical aspects of blockchain technology, including trust, consensus, scalability, and key management.
Facial expression video synthesis from the StyleGAN latent space

Generative neural network models have been used to create impressive synthetic images. However, artificial video synthesis is still hard, even for these models. The best videos that generative models can currently create are a few seconds long, distorted, and low resolution. We propose and implement a model to synthesize videos at 1024 &times; 1024 &times; 32 resolution that include human facial expressions by using static images generated from a Generative Adversarial Network trained on human facial images. To the best of our knowledge, this is the first work that generates realistic videos that are larger than 256 &times; 256 resolution from single starting images. Our model improves video synthesis in both quantitative and qualitative ways as compared to two state-of-the-art models: TGAN and MocoGAN. In a quantitative comparison, we achieve a best Average Content Distance (ACD) score of 0.167, as compared to 0.305 and 0.201 for TGAN and MocoGAN, respectively
Multi-label Learning with Missing Labels Based on Instance-Wise and Label-Wise Correlations for Image Classification

In recent years, multi-label learning has been widely concerned, especially in the fields of image annotation and classification. However, the problem of missing labels is still an urgent issue to be addressed in this domain. To alleviate the missing labels issue, we propose a multi-label learning algorithm with missing labels for image classification, which makes effective use of instance-wise correlation and label-wise correlation. First, we adopt the weighted least square loss to impel the consistency between the estimated labels and the provided labels. Then we utilize the linear reconstruction strategy to explore the instance-wise correlation, and we also utilize the low rank representation (LRR) to investigate the label-wise correlation. Finally, the Laplacian manifold regularization is applied to incorporate the loss function and the above two correlations. To validate the effectiveness of the proposed algorithm, we compare the proposed algorithm with other four state-of-art methods on three popular image datasets. The experimental results show that our algorithm can achieve a much better performance.
PoSH in Practice: Implementing Proof of Staked Hardware Consensus with Limited Storage

Proof of Staked Hardware Consensus (PoSH) Consensus was designed to achieve Nakamoto-style probabilistic consensus on the contents of a cryptocurrency ledger in a permissionless decentralized network while serving as the foundation of an openly mintable cryptocurrency without winner-takes-all lottery-style block rewards. This demo paper presents a proof of concept implementation of a PoSH consensus blockchain and the technical solutions the implementation introduces to realize PoSH in practice.
Security Debt: Characteristics, Product Life-Cycle Integration and Items

Industries from very diverse domains are realising that security should not be treated in a reactive way (e.g., once the cyberattack has happened). This way, security-related requirements and risks need to be continuously managed, and the need of integrating technical measures should be continuously assessed. In some cases, some decisions led, intentionally or unintentionally, to debt related to security aspects. This security debt is thus incurred when limited approaches or solutions are applied to reach the expected security levels of the system in operation. Identifying and making explicit security debt items is a challenge for companies. In this work, we analyse the literature on security debt to provide initial insights on the topic. Concretely, we discuss its definition, identify its most salient characteristics, present approaches for integrating its management in the product life-cycle, and to present categories and examples of security debt items.
A Study on the Analysis and Improvement of the College Entrance Examinations in the Department of Beauty by the Change of College Entrance System

and Eulji University, which had high competitiveness in the 2018-2020 academic year.These departments have drastically reduced the number of admissions starting in 2022.and also prepared an easy admission support policy by eliminating the minimum academic standards and lowering the ratio of applicants to reflect the admission guidelines, such as practical, interviews, and aptitude tests.Differentiated entrance exams for universities by expanding individual standards, even opportunities, and specialized admission.However, the admission requirements of beauty departments that have been conducted so far are in contrast to the government's policy in the future.Each university focuses on maintaining 30% of the College Scholastic Ability Test (CSAT) and expanding the student record curriculum.However, the five beauty departments are maintaining the status quo or reducing the number of regular admissions, so it is time to consider the operation plan for regular admissions.It is also expected that the number of specialized applicants through certificates will be reduced.Differentiated entrance exams for beauty departments that can replace specialized applications.I hope that the preparation of the river will be preceded by a plan to realize the educational value of the university.
Enterprise Payments with Central Bank Digital Currency

The paper proposes an architecture for implementing the Bank of England's basic principles for the design of a CBDC with a focus on real-time high value, often cross border, enterprise transactions. The use of digital ledger technology makes innovative use of chaincode - smart contracts specifying how transactions are to be conducted - and tokens - providing a convenient mechanism for executing transactions and providing the CB monetary policy management. The proposed approach minimizes counterparty risk, eliminates settlement risk, and enhances transaction efficiency, thereby improving global productivity.
Tracing mineralogy and alteration intensity using the spectral alteration index and depth ratios at the Northwest Zone of the Lemarchant VMS deposit, Newfoundland, Canada

The use of hyperspectral reflectance in mineral exploration has been steadily increasing in recent decades. This study presents a novel approach that integrates geochemical and spectral proxies to delineate ore formation and alteration processes, which provide new spectral-based exploration parameters that can be used in real time. The precious metal-bearing, bimodal-felsic Northwest Zone of the Lemarchant VMS deposits, Newfoundland, Canada is used as a case study. Alteration associated with the Northwest Zone includes intense and localized sulfide (pyrite, chalcopyrite, sphalerite and galena) and barite enrichment, and quartz, white mica and chlorite alteration. Zones of elevated Zn (> 5000 ppm) are associated with high chlorite carbonate pyrite index (CCPI), Ishikawa alteration index (AI), Ba/Sr, and low Na2O values and elevated SiO2 and K2O, Fe2O3, Na2O, and BaO contents, similar to global alteration signatures in VMS deposits. Mineralized areas contain phengitic white micas with 2200 nm absorption features longer than 2215nm and Mg-rich chlorites with 2250 nm absorption features shorter than 2252nm. Together, these data are consistent with the Northwest Zone having experienced intense hydrothermal alteration during the mineralization event. A new lithology normalized spectral alteration index (SAI) for white mica and chlorite was developed in order to map and characterize the alteration intensity surrounding the deposit. In addition, depth ratio parameters (2200D/2340D vs 2250D/2340D) were used to characterize mineralogical changes and zonation. Together, these features document a paleo-fluid pathway with Mg-chlorite alteration extending to at least 300 m away from the mineralization, outside the study area, within the andesitic and dacitic units. This study demonstrates that the use of VSWIR spectral reflectance data coupled with geochemical alteration proxies (i.e., AI, CCPI, Ba/Sr, Na2O) and lithogeochemical mass balance changes can identify and characterize alteration haloes and paleo-fluid pathways in the vicinity of VMS deposits. More specifically, hyperspectral reflectance can identify and quantify areas of intense alteration using spectral alteration indexes (SAI), estimate the relative abundances of white mica and chlorite using depth ratios, and characterize the chemical composition of the mineral phases, and relate them to specific alteration processes, which is not possible using only geochemistry. One of the main advantages of this method is that hyperspectral reflectance can be rapidly achieved on drill core at a high resolution for a relatively low cost, minimal sample preparation and results are available instantly, compared to a longer wait time for geochemical results, greatly enhancing decision making processes during drilling exploration programs, allowing vectoring and rapid decisions making during exploration programs.
Path planning for mobile robotic arms incorporating adaptive gravitational fields

Mobile robotic arms require the cooperation of a mobile platform and a robotic arm to reach the desired position rapidly and efficiently to complete the specified operations. By improving the estimation function of the A* algorithm, the number of turns in the path can be reduced, making the overall movement of the robot smoother and more efficient. For the path planning of the robotic arm, a fast random tree method is introduced, and the gravity component is added to guide the growth direction of the random tree for problems such as poor real-time performance and non-global optimal results. For the issue of oscillations and sudden changes in the planning results, a smoothing process is applied to the paths obtained by the improved algorithm. Simulation results and experiments show that the improved path planning method has better performance in the application of mobile robotic arm.
Theory of 3F4D Universe (Beyond Standard Model of Particle Physics)

In this theory, “mass is equivalent to length of imaginary straight line segment” and “direction to imaginary line segment is intrinsic property of that particle which is Equivalent to its intrinsic spin”. With this concept, all fundamental particles, fermions and bosons are described as quanta imaginary string particles with a definite direction. For e.g. unidirectional imaginary straight line with fixed length are massive spin 1/2 fermions; while unidirectional imaginary quanta curved lines are massless spin 1 bosons. Thus, it gives co-relation between massless (curved imaginary line) and spin = 1 properties of boson as proved in QED theory. All fundamental particles of standard model and beyond standard model are arranged in one simple diagram in 3 folds (bottom fold, middle upper and lower folds and top fold) and are projected in 4th Imaginary Dimension in order of decreased in Mass from TeV to approx. 0 eV. This theory is beyond standard model because it predicts new fundamental particles viz. dark matter (spin = 0 massive boson) along with gravitons (spin = 2, massless bosons); 4th pair of neutrinos, vertical massless boson (VMB) particles and tri-axis massive boson (spin = 0) particle. The discovery of these new particles will act as solid proof to this theory. With this 3F4D representation of the universe at an atomic and sub-atomic level, it solves lots of current problems of SM of particle physics like matter-antimatter asymmetry, origin of mass of hadrons like protons, origin of mass and L.H. nature for neutrinos, wave-particle duality of particles, etc. giving true insight of fundamental particles. With proving that, dark matter is not a quanta particle, rather it is a single entity and spreads/expands throughout the universe in the form of “web of spider”, it shows space-time is not empty, but it is filled with Continuous lines of Dark Matter and we, materialistic massive objects are floating/sailing w.r.t. current of this vast ocean. Correlation of its continuity with time gives new a definition to time: “Time is neither Illusion nor 4th Dimension, but, it represents Continuous Flow of Single Entity, Dark Matter”. Space-time is not Empty and is filled with massive dark matter, hence, we have to add more terms to newtonian gravitational equation to account for gravitational strength of mass of surrounding dark matter which represents curvature of space-time in terms of Increase in its mass-density w.r.t. to mass-density of flat universe. Finally, using an empirical formula (h = k*c*Q; k = boltzmann’s constant = mass in TeV range) and inverse relation of mass-density of DM with age of the universe (H2 = Constant&#8226G&#8226Mass-Density of DM); Unification of Gravity at TeV is achieved without consideration of “Gravitational Constant, G”, hence, Planck’s Scale is not required.