Reviewerly/exHarmony huggingface dataset:
“Open Weakness and Vulnerability Modeler” (OVVL): An Updated Approach to Threat Modeling

The development of secure software systems is of ever-increasing importance. While software companies often invest large amounts of resources into the upkeeping and general security properties of large-scale applications when in production, they appear to neglect utilizing threat modeling in the earlier stages of the software development lifecycle. When applied during the design phase of development, and continuously throughout development iterations, threat modeling can help to establish a “Secure by Design” approach. This approach allows issues relating to IT security to be found early during development, reducing the need for later improvement – and thus saving resources in the long term. In this paper the current state of threat modeling is investigated. This investigation drove the derivation of requirements for the development of a new threat modelling framework and tool, called OVVL. OVVL utilizes concepts of established threat modeling methodologies, as well as functionality not available in existing solutions.
Library and Book in the Digital Age: Project Development Vectors

The purpose of the article is understanding of the place and role of the Russian State Library — the National library of the country — in the development of book industry as an active participant in the modern exhibition process of the event-related nature, including the “Red Square” book festival, held this year for the fifth time. The Russian State Library has the capability not only to present its own publishing products at the festival fair, revealing its rich collections, but also to position itself as an active subject of communication, stimulating the book market and giving the publishing business the meaning and values of socio-cultural activity. The book festival, which took place on June 1—6, 2019 in the centre of Moscow, dictates certain formats for presenting the versatile activities of the Library and reveals its strong project focus. Based on the material of major professional branch events of the Russian State Library (RSL) within the framework of the “Red Square” book festival and a number of publications of periodicals, the article considers the project development trends of the RSL related to the implementation of the “Culture” National Project 2019—2024. The author highlights the new trends in book publishing, distribution of publishing products and development of library projects, as well as considers the essential characteristics and outlines the main stages of work of departmental projects on modernization of municipal regional libraries and National Electronic Library (NEL). The joint strong discussion of at first glance purely library projects in the publishing environment expands the library-information space, creates grounds for the formation of multi-level communications and corrects approaches to resolving the problems.
Will the laser cutting machines save Russian libraries?

The author analyzes the new concept of “truly modern libraries” being developed by Vadim Stepanov who suggests to review the library functions and to re-orient the libraries toward providing socio-cultural and leisure services. The author analyzes these methodological and practical recommendations within the concept while demonstrating the practical “misery” of the concept itself and the recommendations which, to one degree or another, have been being developed in the national library studies. Thus, the open access to library collections is a common place since 1930s; every large library has got special room for public events, etc. The author discusses the experience of Helsinki city library (“Oodi”) that has switched to sociocultural and leisure services. Today, “Oodi” – is a cultural and entertaining center, comprising the library oriented toward leisure activities; in fact, it franchises the title of a library. The author demonstrates that accommodating libraries within cultural, leisure and entertaining complexes has been the common practice since the Soviet period. He emphasizes that changes in the national librarianship are of the multifactor character, while automation and computerization of library processes and online access lead to decreasing the library staff number and the volume of library collections. Thus, these changes may not be regarded as the manifestation of a crisis. The author suggests the projects must be being developed more responsibly.
That which we call private

The guarantees of security and privacy defenses are often strengthened by relaxing the assumptions made about attackers or the context in which defenses are deployed. Such relaxations can be a highly worthwhile topic of exploration---even though they typically entail assuming a weaker, less powerful adversary---because there may indeed be great variability in both attackers' powers and their context. However, no weakening or contextual discounting of attackers' power is assumed for what some have called "relaxed definitions" in the analysis of differential-privacy guarantees. Instead, the definitions so named are the basis of refinements and more advanced analyses of the worst-case implications of attackers---without any change assumed in attackers' powers. Because they more precisely bound the worst-case privacy loss, these improved analyses can greatly strengthen the differential-privacy upper-bound guarantees---sometimes lowering the differential-privacy epsilon by orders-of-magnitude. As such, to the casual eye, these analyses may appear to imply a reduced privacy loss. This is a false perception: the privacy loss of any concrete mechanism cannot change with the choice of a worst-case-loss upper-bound analysis technique. Practitioners must be careful not to equate real-world privacy with differential-privacy epsilon values, at least not without full consideration of the context.
Spearman’s rho modification in digital image processing

Abstract The article presents an alternative Spearman’s rank correlation pattern as an innovative method in detecting the edges of an image by defining characteristic points of the image. Edge detection methods can be counted as the image processing stage following the implementation of the “initial” image processing, which includes: use of filters such as low-pass or high-pass, wavelet transform, etc. In this article hitherto known edge detection algorithms will be replaced with image ranking method. The first chapter of this work contains an analysis of the current knowledge on the ranking of the image. The operation of the Spearman rho algorithm together with its various configurations and the comparison of the two methods studied are presented in turn. Next, the modification of the Spearman rho pattern is presented along with the justification for the use of such a transformation. The same chapter also presents the effects of the algorithm, comparing it with known image ranking methods. The next stage of works consisted in developing a method for the interpretation of the results obtained. In the last chapter of the work, the obtained test results were summarized and analysed.
An Approach for Sentiment Analysis of GST Tweets Using Words Popularity Versus Polarity Generation

This paper represents an experimental approach for sentiment analysis of GST tweets, along with generating the most popular GST buzzwords with their respective popularity to polarity scores within a given range of tweets. In India, one of the most trending issues of 2017 was the implementation of Goods and Services Tax (GST) during June–July 2017. GST is a single tax-settled nation wise upon the supply chain of goods and services, primitively from the manufacturer to the consumer. GST was launched in India on the midnight of June 30, 2017, marked by a midnight (June 30–July 1, 2017) session of both the houses of parliament coalesced at the Central Hall of the Parliament. This new taxation system is governed by an GST Council formed by the Govt. of India and the chairman of this council is the Finance Minister of India, himself. As an immediate effect of the cumulation of these ongoing events, a lot of opinion contrast emerged on popular social networks such as Twitter, Facebook regarding this new taxation system. Inspired from this entire event, we propose a new Twitter-based polarity–popularity framework and words cluster for identifying most popular GST-exclusive word counts and sentiment analysis within a given range of tweets, which can be the good indicators of words occurrence probability specific to such an event regarding this topic. This work gives us a much more detailed aspect of the lexical-level analysis of tweets from several directions, along with the future improvement prospects.
Collaborative Authentication Using Threshold Cryptography

We propose a collaborative authentication protocol where multiple user devices (e.g., a smartphone, a smartwatch and a wristband) collaborate to authenticate the user to a third party service provider. Our protocol uses a threshold signature scheme as the main building block. The use of threshold signatures minimises the security threats in that the user devices only store shares of the signing key (i.e., the private key) and the private key is never reconstructed. For user devices that do not have secure storage capability (e.g., some wearables), we propose to use fuzzy extractors to generate their secret shares using behaviometric information when needed, so that there is no need for them to store any secret material. We discuss how to reshare the private key without reconstructing it in case a new device is added and how to repair shares that are lost due to device loss or damage. Our implementation results demonstrate the feasibility of the protocol.
A Robust Anaglyph 3D Video Watermarking based on Multi-sprite Generation

Collusion presents a malicious attack for video watermarking techniques. In the case of anaglyph 3D video, this attack is not yet considered. In fact, only several watermarking techniques were proposed for this type of media and they are not robust against dangerous attacks such as MPEG compression and collusion. In this paper, a robust anaglyph 3D video watermarking technique is proposed. It is based on multi-sprites as a target of insertion. This allows obtaining a robustness against collusion attacks. First, several sprites are generated from original video. Then, a hybrid embedding scheme based on the least significant bit and the discrete wavelet transformation based method is applied on every sprite to insert signature. This improves invisibility and robustness against usual attacks. Experimental results show a high level of invisibility and a good robustness against collusion, compression and against additional attacks such as geometric and temporal attacks.
A collective challenge: Open Science from the perspective of Science Europe

Open Science aims to enhance the quality of research by making research and its outputs openly available, reproducible and accessible. Science Europe, the association of major Research Funding Organisations and Research Performing Organisations, advocates data sharing as one of the core aspects of Open Science and promotes a more harmonised approach to data sharing policies. Good research data management is a prerequisite for Open Science and data management policies should be aligned as much as possible, while taking into account discipline-specific differences. Research data management is a broad and complex field with many actors involved. It needs collective efforts by all actors to work towards aligned policies that foster Open Science.
Determination of the Shortest Hamiltonian Paths in an Arbitrary Graph of Distributed Databases

A method has been developed for finding the shortest Hamiltonian path in an arbitrary graph based on the rank approach, which provides high efficiency and a significant reduction in the error in solving the problem of organizing the process of managing multiple transactions and queries when they are implemented in network databases. In many cases, existing solutions do not provide the necessary results in terms of access time and accuracy of the found solution. Using the developed method allows minimizing the idle time of computing devices, reducing the volume and time of data transfer from one device to another, increases overall scalability, minimizes data access time, etc. An important advantage of the proposed method is to reduce the number of elementary operations and the number of vectors being processed the queue of the operations of the request, which leads to a significant reduction in time to implement the procedures for the formation of echer di operations in the requests. Methods of graph theory were used in this paper. The effectiveness of the task solution was evaluated using a systems approach, system analysis and the theory of operations research. Processing of experimental data obtained during the work was carried out in accordance with the provisions of mathematical statistics.
Personal Verification System Using ID Card and Face Photo

Generally, the process of verifying a person's identification in a bank is accomplished by an officer comparing a photo in an ID card with the actual face of the person.This process is prone to mistake as officers usually need to serve several people in a short time.This article proposes the personal verification system using an ID card and face photo by applying face detection and face comparison.A system based on several open source libraries for face recognition including Dlib, Facenet, and ArcFace is implemented.The experimental analysis shows that the system based on ArcFace yields the highest accuracy at 99.06% for face detection and 96.09% for face comparison.ArcFace outperforms other methods because it not only uses MTCNN but also adjusts face image to be in a straight direction as well as fixes the positions of eyebrows, eyes nose, and mouth so that all images have similar references.
A Data Utility-Driven Benchmark for De-identification Methods

De-identification is the process of removing the associations between data and identifying elements of individual data subjects. Its main purpose is to allow use of data while preserving the privacy of individual data subjects. It is thus an enabler for compliance with legal regulations such as the EU’s General Data Protection Regulation. While many de-identification methods exist, the required knowledge regarding technical implications of different de-identification methods is largely missing. In this paper, we present a data utility-driven benchmark for different de-identification methods. The proposed solution systematically compares de-identification methods while considering their nature, context and de-identified data set goal in order to provide a combination of methods that satisfies privacy requirements while minimizing losses of data utility. The benchmark is validated in a prototype implementation which is applied to a real life data set.
Freely Explore the Scene with 360° Field of View

By providing 360° field of view, spherical panoramas are widely used in virtual reality (VR) systems and street view services. However, due to bandwidth or storage limitations, existing systems only provide sparsely captured panoramas and have limited interaction modes. Although there are methods that can synthesize novel views based on captured panoramas, the generated novel views all lie on the lines connecting existing views. Therefore these methods do not support free viewpoint navigation. In this paper, we propose a new panoramic image based rendering method. Our method takes pre-captured images as input and can synthesize panoramas at novel views that are far from input camera positions. Thus, it supports to freely explore the scene with 360° field of view.
FRMN - A Face Recognition Model Based on Convolutional Neural Network

Abstract A face recognition model based on Convolutional Neural Network was proposed in this paper. This model mixed local and global image features at the largest extent. By acquiring the good local feature from mouth, nose and mouth, it is great improvement to enhance the accuracy for face recognition. From the experiment results, this model can better abstract the global feature and show a great improvement in face recognition.
A Multi-grained Log Auditing Scheme for Cloud Data Confidentiality

Abstract With increasing number of cloud data leakage accidents exposed, outsourced data control becomes a more and more serious concern of their owner. To relieve the concern of these cloud users, reliable logging schemes are widely used to generate proof for data confidentiality auditing. However, high frequency operation and fine operation granularity on cloud data both result in a considerably large volume of operation logs, which burdens communication and computation in log auditing. This paper proposes a multi-grained log auditing scheme to make logs volume smaller and log auditing more efficient. We design a logging mechanism to support multi-grained data access with Merkle Hash Tree structure. Based on multi-grained log, we present a log auditing approach to achieve data confidentiality auditing and leakage investigation by making an Access List. Experiments results indicate that our scheme obtains about 54 % log volume and 60 % auditing time of fine-grained log auditing scheme in our scenario.
Choreographic Pattern Analysis from Heterogeneous Motion Capture Systems Using Dynamic Time Warping

The convention for the safeguarding of Intangible Cultural Heritage (ICH) by UNESCO highlights the equal importance of intangible elements of cultural heritage to tangible ones. One of the most important domains of ICH is folkloric dances. A dance choreography is a time-varying 3D process (4D modelling), which includes dynamic co-interactions among different actors, emotional and style attributes, and supplementary elements, such as music tempo and costumes. Presently, research focuses on the use of depth acquisition sensors, to handle kinesiology issues. The extraction of skeleton data, in real time, contains a significant amount of information (data and metadata), allowing for various choreography-based analytics. In this paper, a trajectory interpretation method for Greek folkloric dances is presented. We focus on matching trajectories’ patterns, existing in a choreographic database, to new ones originating from different sensor types such as VICON and Kinect II. Then, a Dynamic Time Warping (DTW) algorithm is proposed to find out similarities/dissimilarities among the choreographic trajectories. The goal is to evaluate the performance of the low-cost Kinect II sensor for dance choreography compared to the accurate but of high-cost VICON-based choreographies. Experimental results on real-life dances are carried out to show the effectiveness of the proposed DTW methodology and the ability of Kinect II to localize dances in 3D space.
Evolution of Stacked Autoencoders

Choosing the best hyperparameters for neural networks is a big challenge. This paper proposes a method that automatically initializes and adjusts hyperparameters during the training process of stacked autoencoders. A population of autoencoders is trained with gradient-descent-based weight updates, while hyperparameters are mutated and weights are inherited in a Lamarckian kind of way. The training is conducted layer-wise, while each new layer initiates a new neuroevolutionary optimization process. In the fitness function of the evolutionary approach a dimensionality reduction quality measure is employed. Experiments show the contribution of the most significant hyperparameters, while analyzing their lineage during the training process. The results confirm that the proposed method outperforms a baseline approach on MNIST, FashionMNIST, and the Year Prediction Million Song Database.
Joint Transcoding Task Assignment and Association Control for Fog-Assisted Crowdsourced Live Streaming

The rapid development of content delivery networks and cloud computing has facilitated crowdsourced live-streaming platforms (CLSP) that enable people to broadcast live videos which can be watched online by a growing number of viewers. However, in order to ensure reliable viewer experience, it is important that the viewers should be provided with multiple standard video versions. To achieve this, we propose a joint fog-assisted transcoding and viewer association technique which can outsource the transcoding load to a fog device pool and determine the fog device with which each viewer will be associated, to watch desired videos. The resulting non-convex integer programming has been solved using a computationally attractive complementary geometric programming (CGP). The performance of the proposed algorithm closely matches that of the globally optimum solution obtained by an exhaustive search. Furthermore, the trace-driven simulations demonstrate that our proposed algorithm is able to provide adaptive bit rate (ABR) services.
Documenting and Exploiting Software Feature Knowledge through Tags

Knowledge about features and their relations to detailed requirements or code is important and useful for many software engineering activities such as for performing change impact analysis and tracking feature progress.Documenting feature knowledge is challenging, as companies document features and requirements in issue tracking systems (ITS) and work on code in integrated development environments (IDE).Managing feature knowledge over time is challenging, as features, requirements, and code continuously change.Also, managing the relationships through trace links is challenging, as creating links manually is too time-consuming, and recovering links retrospectively is too error-prone.We developed an approach and tool TAFT to document feature knowledge in ITS and IDE continuously.TAFT uses feature tags to indicate relations between feature descriptions, requirements, work items, and source code.Currently, TAFT comprises a dashboard to track the feature progress, a recommendation system to suggest feature tags for specifications, an inheritor to apply feature tags automatically, and capabilities to navigate in feature knowledge.The tool is integrated into the developers' work environments Jira and Eclipse.In this paper, we present details on the tool support for TAFT, and we report on the results of a case study, which indicates its acceptance.
Uniform Substitution at One Fell Swoop

Abstract Uniform substitution of function, predicate, program or game symbols is the core operation in parsimonious provers for hybrid systems and hybrid games. By postponing soundness-critical admissibility checks, this paper introduces a uniform substitution mechanism that proceeds in a linear pass homomorphically along the formula. Soundness is recovered using a simple variable condition at the replacements performed by the substitution. The setting in this paper is that of differential hybrid games, in which discrete, continuous, and adversarial dynamics interact in differential game logic "Image missing"<!-- image only, no MathML or LaTex --> . This paper proves soundness and completeness of one-pass uniform substitutions for "Image missing"<!-- image only, no MathML or LaTex --> .