Reviewerly/exHarmony huggingface dataset:
Λογισμικό οργάνωσης ιατρικών ραντεβού & επισκέψεων σε περιβάλλον υπολογιστικού νέφους

The purpose of current thesis is to make use of Cloud technologies and look into cutting edge technologies (C#, AJAX, NodeJS, Angular). It is a software that is called upon to meet the needs of data management and storage as well as the medical records of patients with hierarchical privilege management, following a role assignment and authorization system. In addition, there will be complete traceability of each user's actions. It will also be able to create and track appointments.
Development Problems of Trusted Software in Critical Information Infrastructure Systems

Due to the increasing complexity of information systems, information security threats associated with the presence of software vulnerabilities used in the information infrastructure systems become relevant. Today in order to protect against this type of threat one usually applies a range of measures implemented in the operation and maintenance of the software. At the same time, to ensure the required level of data protection, it is necessary to implement measures aimed at preventing vulnerabilities during the software life cycle. Secure software development is the basis for trust in information and communication technologies in the context of modern cyber threats. The aim of this paper is to summarize and analyze the problems of creating trusted software used in critical information infrastructure, and to find possible ways to solve them. The organizational and methodological aspects of the creation of trusted software used in critical information infrastructure are discussed, and the main problems, strategies and technologies to ensure the trust for various software components are described. The issue of trust for tools, system-wide and special software is still open both in methodological and organizational terms. To solve these problems, it is necessary to have a long-term state policy, development and clarification of legal documents that define common approaches and specific ways to ensure the reliability and security of the software used in critical information infrastructure, taking into account the actual conditions of their operation.
Quantifying the Influence of Browser, OS and Network Delay on Time Instant Metric Measurements for a Web Mapping Application

Modelling Web Quality of Experience (QoE) using technical quality metrics has received much attention over the past years and has become an important part of network QoE monitoring and management studies. Mapping Web QoE metrics (e.g. MOS) to application metrics (e.g. waiting time) and network QoS metrics (e.g delay) helps to quantify the influence of different factor on the perceived quality. The literature shows that network delays can result in significantly longer loading times for web browsing and consequently impact the user's perceived quality. We investigate the impact of network delay on the measurement of application quality metrics for three browsers and three operating systems using a web mapping application for our experimental tests. We then analyse how the choice of browser and operating system influences application level quality metrics. We demonstrate how time instant quality metrics measurement vary depending on the operating system due to TCP Retransmition TimeOut (RTO). Finally, we publish the collected data for the future studies.
ІННОВАЦІЙНА ПЕДАГОГІЧНА ТЕХНОЛОГІЯ ФОРМУВАННЯ ПРАВОПИСНИХ НАВИЧОК У ПЕРШОКЛАСНИКІВ

The article describes an innovative pedagogical technology, the specificity of which is that the orthography skills are formed without learning spelling and punctuation rules by heart. The acquaintance of children with the “secrets” of the reproduction of oral speech in writing, the disclosure of the linguistic nature of spelling phenomena, taking into account the graphics of the Ukrainian language, necessitated the introduction of a generalized concept of orthograms at the stage of literacy teaching, as well as separate rules for the use of punctuation marks. The concept of orthography is introduced on the example of copying words that mean proper names. While explaining the orthogram, teachers are guided by the definition: an orthogram is a letter, a sign in a word, or a gap between words that have to be explained. At the beginning of the pre-ABC book period, it is expedient to use propaedeutic exercises throughout the whole period of literacy teaching. The second group of exercises consists of the ones designed to perform a support role, but which are directly related to the development of literacy skills. A fundamentally new methodical technique in achieving the positive results of introducing meaningful writing by the pattern is the use of a computer program. It provides an opportunity to implement an individual approach, to guarantee high enough cognitive activity of pupils and optimally use the training time. Requirements of the existing ABC books are taken into account in the process of selecting the didactic material for the computer program. The program includes tasks, designed according to the order of the letters studying. Letters, syllables, words, and sentences are used as didactic material. Consequently, the high efficiency of the developed and tested technology gives grounds to encourage primary school teachers to use this method in the process of first-graders’ literacy skills formation.
Intelligence Information System for Forensic Microscopical Hair Analysis

The problem of identification by human hair has been considered in the paper. The main aim of this paper is to present a new intelligence information system for forensic microscopical hair analysis. In our research we used micromorphological characteristics of the human hair: cuticle scale pattern, cortical layer background colour, pigment colour, pigment granule size, pigment aggregate size and pigment distribution. The micromorphological characteristics of the hair specimens have been investigated with the special microscope, such as Leica DM 1000 microscope. The result of the work is very important for the development of a mathematical model for the evaluating of the probability of a set of the matching features in the investigated hair object and comparative hair samples. Pattern recognition and decision making is special intelligent technology for forensic examination of human hair. Our results are useful for forensic experts and students from a broad range of disciplines related to intelligent technologies, for forensic microscopical hair analysis and other fields. Gathered information will be used for creating effective intelligence information system for forensic microscopical hair analysis.
An Audio Compression Method Based on Wavelet Packet Decomposition, Ordering, and Polynomial Approximation of Expressive Coefficients

This paper presents a method for audio compression that makes use of wavelet packet decomposition (WPD), ordering, and polynomial approximation of expressive coefficients. The proposed encoder orders the WPD coefficients for a suitable polynomial approximation found by multiple linear regression. In addition, the method makes use of an adaptive system of rate versus distortion control (ASRDC) to maintain a nearly constant bit-rate in the audio output. A discussion on the flexibility of the encoder to different settings is presented. Lastly, experimental results of the proposed system and those of well-known codecs are compared. The results indicate that the proposed system achieves competitive performance concerning SNR, particularly for some instrumental audios. In objective measures of perceived audio quality, the current implementation of the proposed codec has negative results compared to other codecs. This method provides an efficient way to exploit the key strengths of polynomial approximation to audio compression and can be easily adapted to other data types.
OOP Case Study: Considering Performance

The Address Book Application (ABA) case study is continued. Two new ABA requirements are described and implemented in three versions of an object-oriented programming (OOP) solution. Each OOP solution is described using source code, a class diagram, a Nassi–Shneiderman diagram, and a statechart. The program design criteria described in Chaps. 2 and 5 are used to evaluate each solution.
Hybrid 3D/2D-Based Deep Convolutional Neural Network for Spatio-Temporal Denoising of Angiography

Image denoising is one of the important issues for X-ray angiography of C-arm systems. Most existing methods in this field focus only on 2D image denoising from frame-by-frame independently, losing the temporal information of image sequence to some extents. In order to handle both spatial and temporal noises simultaneously to angiography imaging, we propose a novel deep architecture of hybrid 3D/2D CNN (convolutional neural network) for spatio-temporal noise reduction. The developed model takes multiple frames to input channels, and the final result is obtained through combining information of all channels. We evaluate the model applied to angiography images with normal and low doses of X-ray exposures. Results of both cases outperform those of state-of-the-art methods.
Student self-governance as a mean development of youth creative abilities

The article deals with the concept of student self-government from a socio-psychological point of view. The essence of activity, purpose and tasks of student self-government bodies on development of students' creative abilities in the conditions of higher education institution are revealed. It is emphasized that the feature of professional education now stands to increase the requirements for the need to disclose the creative component of the future specialist, increase his personal responsibility for the social realization of his own purpose and recognition, for solving specific production problems. The aim of modern society is to nurture a new personality capable of self-realization and creative ability in all spheres of human activity. In the education of the future, special importance should be given to the formation of educated, high-moral, capable of thinking creatively, making independent decisions and improving their professional skills of specialists. Such development is not possible beyond the various forms of collective self-organization in the student environment, where at the same time considerable potential of creative intellectual energy, social activity and creativity in different types of activity are manifested. It is shown that student self-government has become an integral part of higher education. It aims to form such a community (student-teaching staff) where a harmonious interaction of its members, an atmosphere of creative search, inspiration, a thirst for knowledge and use of them in practical activity will be felt, where a high level of organization and self-discipline will be observed. Designing a situation of personal development as an environmental phenomenon differs from the creation of learning situations on the basis of setting objectives, because it is based on the inclusion of students in various environmental situations, expanding their space of life, imitate a greater degree of completeness in the future life. environment, circles of communication, patterns of attitude to the profession, which will focus the future specialist. It is emphasized that each person has creativity, it is only necessary to overcome psychological obstacles that limit its development, to master the methods of stimulation of creative activity. Democratization of education is one of the decisive conditions for the democratization of society and its further development. This is conditioned by the objective need of society for a new person who will be capable of independent, responsible, creative action, in a free, self-developing person with a critical, dogma-free thinking.
Cluster-Based News Representative Generation with Automatic Incremental Clustering

Nowadays, a large volume of news circulates around the Internet in one day, amounting to more than two thousand news. However, some of these news have the same topic and content, trapping readers among different sources of news that say similar things. This research proposes a new approach to provide a representative news automatically through the Automatic Incremental Clustering method. This method began with the Data Acquisition process, Keyword Extraction, and Metadata Aggregation to produce a news metadata matrix. The news metadata matrix consisted of types of word in the column and news section of each line. Furthermore, the news on the matrix were grouped by the Automatic Incremental Clustering method based on the number of word similarities that arised, calculated using the Euclidean Distance approach, and was done automatically and real-time. Each cluster (topic) determined one representing news as a Representative News based on the location of the news closest to the midpoint/centroid on the cluster. This study used 101 news as experimental data and produced 87 news clusters with 85.14% precision ratio.
Automated System for Requirements Assessment

In order for the requirements to be properly used in the design and testing of the system, they must have a number of characteristics. The process of providing these characteristics can be partially automated. The paper discusses the features of assessing the characteristics of requirements, provides information on existing systems for assessing requirements, describes the scenarios and context of their application, as well as the basic functionalities that they should have.
Software Design and Security

Thirteen security design principles are introduced. These are economy of mechanism, fail-safe defaults, complete mediation, open design, separation of privilege, least privilege, least common mechanism, psychological acceptability, secure the weakest link, defend in depth, be reluctant to trust, promote privacy, and use your resources. The data-flow diagram, IDEF0 function model, and statechart design models are described in terms how well they can represent these principles.
Knowledge Graph Modeling based on Generalized Property Graphs

As a popular emerging technology, knowledge graphs (KGs) have become a platform of knowledge applications and services. Two dominant graph-based knowledge models, RDF and LPG, are widely used to construct large-scale KGs. It is argued that these models have some limitations to cope with complicated knowledge structures. This paper proposes a noble generalized property graph model that can seamlessly realize the various types of knowledge structures with compact expressiveness and robust formalism. The paper also describes several structures of knowledge graphs to demonstrate the expressive capability of the proposed property graph model. Since the generalized graph model is compatible with RDF and LPG, it can be practically applied to the usual KGs with effective performance.
Identification of Voice Quality Variation Using I-Vectors

Voice disorders affect a large portion of the population, in particular impacting heavy voice users such as teachers or call-center workers. Voice therapy-the recommended behavioral treatment for a variety of voice disorders-requires regular voice technique practice under the guidance of a voice therapist. Patients commonly have difficulty reproducing this technique without clinician feedback once they get home. Therefore, we developed a system for use in voice therapy to provide feedback to the patient about the quality of their voice practice. Based on i-vector analysis, the system effectively examines a speaker's different vocal modes as if these represent different speakers (i.e. your good-voice-self vs your bad-voice-self). Six adults were recorded producing 5 different voice quality modes: normal, breathy, fry, twang and hyponasal. An i-vector-based algorithm was trained on 6 participants to classify these vocal modes with 97.7% accuracy. The system can be used to detect different voice quality modes in unscripted, connected speech, which has potential to automate analysis of home practice in voice therapy and to serve as a feedback tool to extend therapist judgment beyond the clinic walls.
Distributed Unscented-Information Kalman Filter (UIKF) for Cooperative Localization in Spacecraft Formation Flying

In this work, we proposed two algorithms for cooperative localization for spacecraft formation applications, namely an Unscented Information Filter (UIKF) added Consensus Averaging (CA) and an Unscented Information Filter added Covariance Intersection (CI). The UIKF was used because it operates on the information, and it is suited for nonlinear mapping. The CA is an information fusion algorithm that allows the distributed estimate across a sensors network. We proposed convergence criteria that would enable the distributed estimation generated by the CA algorithm to be equivalent to that of a central fusion node. The CI algorithm allows for producing a consistent estimate when the cross-correlation between the different nodes is unknown. The proposed algorithms are used to estimate the motion of a spacecraft flying in formation around a circular chief.
Minimal abductive solutions with explicit justification

Abstract Abductive problems and their solutions are presented by means of justification logic. We introduce additional meta-constructions in order to generate and compare different solutions to the same abductive problem. Our approach has three advantages: (i) it makes structurally explicit the solution to an abductive problem (as it has a syntactic nature); (ii) it gives a precise meaning to the notion of evidence; (iii) it provides clear definitions and procedures for the comparison of solutions that can be adapted to different needs.
Compressing Metaclass Files Through String Optimization

Compilers translate abstract code containing high-level language instructions to low-level form. Meta-compilers are specialized compilers used to compile source code containing statements from multiple programming languages. Data structures in different languages can be used in a single language known as metalanguage. In this paper, optimization techniques on string objects for a metalanguage developed using C++ and Java are presented. It offers a flexible programming environment for users. String objects in Java take more memory and access time since it contains information about the globally shared array, length, and offset of currently executing strings. Most of the time the shared character array is not completely used and the garbage collection becomes difficult. Meta-compiler uses array representation for all string operations allowed in Java and C++. A virtual machine backend is designed for the meta-framework and bytecodes are rewritten for string operations in C++ and Java using arrays. It shows considerable improvement in the execution performance of meta-programs using strings compared to C++ and Java.
Software Design Document

A software design document is described that encapsulates all design knowledge for an application or system. Four sections of a design document—architecture, data, interfaces, and components—are described.
Modal analysis of the washing machine heater

The paper deals with the assessment of the modal parameters of the washing machine heater. At first, a numerical modal analysis based on a finite element method of the heater was performed. Consequently, the experimental modal analysis of the heater was realised to verify the finite element model. As the heater’s shape and dimensions do not allow modal parameters estimation using conventional gages of acceleration, two optical approaches were applied. In both cases, the excitation was realised using Brüel&Kjaer 8206 impact hammer. In the first one, the responses of the heater were captured by Polytec PDV-100 vibrometer, which principle is based on laser Doppler vibrometry. Such a type of device allows capturing of responses in a form of velocity only in the direction of observation. To observe the responses in three mutually perpendicular directions the high-speed digital image correlation system Q-450 Dantec Dynamics was used. Mentioned correlation system uses for the full-field measurement of displacements precise digital cameras with high image resolution. As it is not adapted for modal parameters estimation, the additional software DICMAN 3D, developed at the authors’ workplace, was used. DICMAN 3D allows evaluation of a single-reference as well as a multi-reference measurement in space and for automatic estimation of natural frequencies and damping ratios comprises an advanced estimation module with several algorithms. Finally, the influence of the temperature on the modal parameters was investigated using the finite element model of the heater.
A Generic Construction of Puncturable Encryption

Puncturable encryption can achieve forward secrecy by puncturing the secret key after each decryption operation, such that a given ciphertext can only be decrypted once, and it has many practical applications such as asynchronous messaging transport systems, forward-secret zero round-trip time (0-RTT) protocol, and public-key watermarking schemes. In this paper, we present a generic construction that converts any existing chosen-ciphertext secure identity-based encryption scheme into a puncturable encryption scheme. The security proof of our construction can be derived from the underlying identity-based encryption scheme employing the same assumptions. Furthermore, we present an instantiation of the proposed generic construction. In comparison with previous schemes, our construction of puncturable encryption is efficient, in particular, a puncturing operation only involves a small number of very efficient computations, plus the deletion of certain parts of the secret key.
GDozenHash Hash Function Based on Three-Dimensional Stochastic Transformations

Hash functions along with pseudorandom number generators are the basic elements of stochastic methods of information protection, providing unpredictable behavior of protection tools and objects of protection. The protection from an active opponent can be guaranteed only by using of stochastic methods. GDozenHash hash algorithm based on three-dimensional stochastic transformations Dozen+ is suggested. A feature of the algorithm is a high degree of parallelism at the level of elementary operations, in other words, the hash function is suitable for the implementation with usage of hybrid supercomputer technologies. The paper also presents the results of research on statistical security of the proposed hash algorithm.
Real-Time Human Gaze Estimation

This paper describes a system for estimating the course gaze or 1D head pose of multiple people in a video stream from a moving camera in an indoor scene. The system runs at 30 Hz and can detect human heads with a F-Score of 87.2% and predict their gaze with an average error 20.9° including when they are facing directly away from the camera. The system uses two Convolutional Neural Networks (CNNs) for head detection and gaze estimation respectively and uses common tracking and filtering techniques for smoothing predictions over time. This paper is application-focused and so describes the individual components of the system as well as the techniques used for collecting data and training the CNNs.