Reviewerly/exHarmony huggingface dataset:
“Instructional design” as a system-forming category: approaches and definitions

Introduction. The article is devoted to the essence of the concept of "instructional design". In the course of the study, scientific sources, experience and speeches of educational content developers were analyzed in order to clarify the interpretation of the term “instructional design”. The authors define the content of the concept and its structure, differences in the professional characteristics of specialists implementing the foundations of instructional design, identify the stages and tools for creating distance courses using pedagogical design approaches. Materials and Methods. In the course of the study, an analysis of the scientific literature devoted to instructional design was carried out. Systematized and summarized the practical experience of applying the basics of instructional design to create educational content. Results. Approaches to the understanding of the term “instructional design”, features of the interaction of specialists involved in the development of educational content in the context of digital learning are defined. The tools for creating distance courses are described, using the basics of instructional design at each stage of development. Discussion and Conclusions. The study made it possible to identify the essential characteristics of the concept of "instructional design" and the stages of the process of constructing educational content, taking into account the basics of instructional design and different formats of interaction in the implementation of curricula.
Optimal multi-kernel SVM classifier with rotation, illumination and scale invariant hybrid DWT-Shearlet based GLCM feature descriptor and its application to face recognition

In computer vision, we must handle with the various structural aspects of image or video data. The texture is one of the most important aspects of this type of data, which is utilised to identify objects or regions of interest in an image. As imaging conditions change, textures inside actual images significantly change in brightness, contrast, size, and skew. To recognise textures in real-world images, a similarity measure that is invariant to these features must be used. Existing recognition techniques did not perform well due to issues such as illumination, scale, and subject rotation. To address this issue, invariant feature representation methods are being developed to generate features that are insensitive to such variations. In this paper, we proposed a robust hybrid feature descriptor and predicted the faces under illumination, scale, and pose variations using an optimum multi-kernel support vector machine. Additionally, the suggested robust hybrid feature descriptor is enhanced by combining a hybrid transform composed of discrete wavelet and discrete shearlet transforms with some image statistical textural data. The proposed face recognition system is implemented in MATLAB, and analysed using various parameters to show proposed methods improved performance as compared to the state of the art methods.
Achieving software development agility: different roles of team, methodological and process factors

Purpose Agile principles have been widely used in software development team practice since the creation of the Agile Manifesto. Studies have examined variables related to agile principles without systematically considering the relationships among key team, agile methodology, and process variables underlying the agile principles and how these variables jointly influence the achievement of software development agility. In this study, the authors tested a team/methodology–process–agility model that links team variables (team autonomy and team competence) and methodological variable (iterative development) to process variables (communication and collaborative decision-making), which are in turn linked to software development agility (ability to sense, respond and learn). Design/methodology/approach Survey data from one hundred and sixty software development professionals were analyzed using structural equation modeling methods. Findings The results support the team/methodology–process–agility model. Process variables (communication and collaborative decision-making) mediated the effects of team (autonomy and competence) and methodological (iterative development) variables on software development agility. In addition, team, methodology and process variables had different effects on the three dimensions of software development agility. Originality/value The results contribute to the literature on organizational IT management by establishing a team/methodology–process–agility model that can serve as a basis for developing a core theoretical foundation underlying agile principles and practices. The results also have practical implications for organizations in understanding and managing holistically the different roles that agile methodological, team and process factors play in achieving software development agility.
Cross‐class pest and disease vegetation detection based on small sample registration

Abstract This paper introduces few‐shot anomaly detection (FSAD), a practical and less anomaly detection (AD) method, which can provide a limited number of normal images for each class during training. So far, studies on FSAD have been carried out according to each model, and there is no discussion of commonalities between different types. Depending on how people detect unusual lies, the problematic images are compared to the normal ones. The image alignment method based on different classifications is used to train the target detection model independent of classification, and performed ablation experiments on the pest and disease datasets in different environments for verification. This is the first time the FSAD method has been used to train a single scalable model without the need to train new classifications or adjust parameters. The experimental results show that the application of AUC based on vegetation disease data set and vegetation pest data set in FSAD algorithm is improved by 19.5% compared with the existing algorithm.
“Mudra” (Text to Speech Conversion with Hand Gestures)

One of the non-verbal communication techniques utilized in sign language is the hand gesture. Deaf persons who struggle with speech or hearing most frequently use it to converse with each other and hearing people. Several makers around the world have created various sign language systems, but they are neither adaptable nor cost-effective for end users. The majority of programs only provide text- based results. So, we are going to offer a system prototype in an application that solves the aforementioned issue. Hand gestures can be translated into text and then spoken by the system. Several algorithms will be used by the system, including CNN for classifying hand movements and SVM for detection of hand movement &amp; TTS for conversion of Text To Speech.
A symmetric adaptive visibility graph classification method of orthogonal signals for automatic modulation classification

Abstract Visibility graph methods allow time series to mine non‐Euclidean spatial features of sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule‐based univariate time series visibility graph methods, a symmetric adaptive visibility graph method is proposed using orthogonal signals, a method applicable to in‐phase and quadrature (I/Q) orthogonal signals for adaptive graph mapping for radio modulated signals in automatic modulation classification tasks. The method directly models the intra‐channel and inter‐channel graph relations of I/Q signals using two different types of convolutional kernels. It captures non‐Euclidean spatial feature information of I/Q signals using a graph neural network combining graph sampling aggregation and graph differentiable pooling as a feature extractor. Extensive experimental results on two benchmark datasets and a simulated dataset containing channel fading show that the proposed Quadrature Signal Symmetric Adaptive Visibility Graph (QSSAVG) method in this paper outperforms the benchmark method in terms of classification accuracy and is also more robust against channel fading and noise variations.
SUSPICIOUS ACTIVITY DETECTION

With the increasing in the number of anti-social activates that have been taking place ,security has been given utmost importance lately. Many Organizations have installed CCTVs for constant Monitoring of people and their interactions. For a developed Country with a population of 64 million, every person is captured by a camera 30 times a day. A lot of video data generated and stored for a certain time duration. A 704x576 resolution image recorded at 25fps will generate roughly 20GB per day. Constant Monitoring of data by humans to judge if the events are abnormal is near impossible task as requires a workforce and their constant attention. This creates a need to automate the same. Also , there is need to show in which frame and which part of it contain the unusual activity which aid the faster judgment of the unusual activity being abnormal. This is done by converting video into frames and analyzing the persons and their activates from the processed frame .Machine learning and Deep Learning Algorithms and techniques support us in a wide accept to make Possible.
A Republican Approach to Jerkish Speech on Online Platforms

Abstract Jerkish speech on online platforms is at risk of being overlooked as a result of being comparatively insignificant next to the existence of explicit hate speech or other online harms. In this paper I approach online jerkish speech from a republican perspective. I discuss two ways in which republicans can account for jerkish speech. First, jerkish speech could amount to micro-domination, referring to instances of domination that are relatively inconsequential by themselves but problematic when considered in aggregate. Second, jerkish speech can be considered an instantiation of systemic domination, where groups and members are structurally subordinated. I briefly discuss the role of regulatory bans on jerkish speech, before suggesting that Suzanne Whitten’s proposal for critical civility—as an appropriate answer to jerkish speech in online environments—might be too demanding. This might be alleviated by leveraging the role of online platforms.
Attendance System Using Deep Learning

In the traditional system, it is difficult to handle the attendance of a huge number of students in the classroom. Attendance of the students is very important for every university, college as well as school as it keeps the record of every individual. The conventional methodology of taking attendance by calling out the roll number or name of the student and then recording the attendance is a tedious task. Assume the duration of the lecture is 60 minutes or 1 hour and to record the attendance it would take 5 to 10 minutes. Also for every tutor, this is time-consuming. To overcome this problem, real-time face recognition is a real-world solution, which will help in marking the attendance of students in bulk. In this project, face detection and face recognition are used. Attendance marking through face recognition can be implemented in the classroom by capturing the image of students in the classroom via a surveillance camera. Later Haar Cascade algorithm is used for face detection, which helps in locating the position of the face region, and LBPH (Local binary pattern histogram) algorithm for face recognition. The images of all the students in the class are stored in the database and when the face of the individual student matches with one of the faces stored in the database then the attendance is recorded
OPENING OF THE MUSEUM OF V.I. CHAPAYEV IN CHEBOKSARY AND THE FIRST YEARS OF HIS WORK ACCORDING TO ARCHIVAL DOCUMENTS

Chapaev is one of the most famous natives of Cheboksary. His name is known not only on the territory of our country, but also abroad. One of the ways to perpetuate the memory of the legendary commander in his homeland was the opening of a museum. The purpose of the study is to analyze the prerequisites for the opening of the Museum of V.I. Chapaev in Cheboksary, to identify the main stages of its creation and the main directions of its activity in the late 1960s – 1970s. Materials and methods. The main research methods were the method of analysis of archival documents and the historical-genetic method. Archival documents have survived that allow you to recreate the history of the emergence of the museum and the organization of its work. Research results. The article provides information about the work done by the staff of the Chuvash Republican Museum of Local Lore in preparing the exposition of the new museum in the 1970s. The attention is focused on the sections of the exposition, which consecrated the periods of life of V.I. Chapaev; described the history of military units associated with the name of the legendary commander; and also talked about the works of literature and the film dedicated to him. On the basis of archival documents, the main directions of the museum’s activity in the first years of its work are revealed: exposition and exhibition, which consisted in the preparation of thematic exhibitions; research, expressed in the study of new publications on the biography of V.I. Chapaev and the history of military units, in the creation of which he was directly involved; collecting, aimed at finding new materials on the topics of the sections of the exposition; cultural and educational, consisting mainly of excursions and lectures. The authors paid special attention to the main events of the first years of the new museum’s activity. Among them are memorable dates dedicated to 60th anniversary of the death of V.I. Chapaev and the 90th anniversary of his birth. Entire complexes of events were timed to coincide with these dates, in preparation for which extensive work was carried out. This work was reflected in the organization of thematic exhibitions, meetings with honored guests, lectures, etc. The article notes the role of A.A. Rozhkova, A.E. Shurkina, V.I. Brovchenkova in organizing the work of the museum. Conclusions. Already from the first years of work, the Museum of V.I. Chapaev has become one of the most visited cultural sites in Cheboksary. It is this museum that is the central “place of memory”, which helps to perpetuate the memory of the legendary commander of the Civil War.
LIBRARY CENSORSHIP IN THE USSR AT THE TURN OF 1950–1960s (adapted from Penza Region)

The purpose of the study is to study the mechanism for implementing the censorship and library policy of the Soviet state on the example of mass libraries of the Penza region in the late 1950s – early 1960s. Materials and methods. The tasks of the Internet were implemented by analyzing and summarizing the documents of the State Archive of the Penza Region (Fund R-2357 – Department of Culture of the Penza Oblast Executive Committee). The work uses methods: historical-genetic, historical-comparative. Results of the study. The article describes the regulatory framework that re-regulates the process of purging library book collections from outdated and politically harmful literature (Instructions of the USSR Ministry of Culture of September 16, 1955 and February 2, 1960, Bibliographic decrees-smolders of outdated publications, Summary lists, etc.), explaining the criteria for classifying publications as «outdated and politically harmful letter-tours». The determination of the work of cultural institutions, including libraries, in general, the configuration of library funds, in particular, political, economic, socio-cultural conditions in the state, a specific international and domestic political situation (for example, the Twentieth Congress of the CPSU, the speech of the «anti-party group», etc.). Attention is paid to the activities of the Penza Regional Department for the Protection of Military and State Secrets in the press for the withdrawal of outdated and politically harmful literature from book funds, a round of quarterly and annual reports of Obllit is disclosed. On the basis of unreleased archive documents, the practice of the Department of Culture of the Penza Regional Committee for the Implementation of Soviet Censorship and Library Policy was studied. According to the work of the regional (in the Department of Culture of the Penza Regional Executive Committee), paradise and city (in the departments of culture) commissions to write off an outdated theater, visits of commission members and local inspections. The state of book funds of urban, district and rural mass libraries of the Penza region was studied for the presence of literature subject to withdrawal from mass circulation; statistics are provided on the «blockage» of book collections of mass libraries of the region. Examples of administrative and disciplinary penalties are given, which were imposed on library workers, mainly managers, for non-compliance with directives on clearing book funds of outdated literature and issuing publications to readers that were subject to seizure. Conclusions. Consideration of the content and methods of library and censorship practice made it possible to identify the features of the exercise of censorship functions in relation to mass libraries at the regional level; determine the vector of subsequent research on the scientific problem.
Simulating quantum key distribution in fiber-based quantum networks

Quantum networks exploit the unique properties of quantum mechanics to enable communication and networking tasks unavailable to existing distributed classical systems. Recently, the research community has focused considerable effort on the simulation of large-scale quantum networks with the ultimate goal of understanding their general properties, developing technical standards, and estimating their expected performance. However, comparatively little effort has been spent considering how quantum networks may impact tactical scenarios of military relevance where both quantum and classical resources may be severely constrained. Here, we develop a custom framework, called QuanTACT, for quantum network simulation explicitly designed for future integration into existing tactical simulation tools. In particular, our framework extends the existing quantum networking tool, SQUANCH, to include channel models required to simulate deployed fiber environments. Furthermore, we implement the additional subroutines needed to simulate entanglement-based quantum key distribution (QKD) and use published results from various field-deployed QKD experiments to benchmark the performance of our framework.
Blockchain Enhanced Stock Trading Application

Stock exchange works and functions in a very inconvenient and hectic way because of post-trade processes which are cost-inefficient, time-consuming and can be prone to numerous risks. This motivates us to experiment with new technologies like blockchain which has immense potential to change the process of post-trading. In this paper, we propose an implementation of a stock trading application built on Hyperledger Fabric, a hybrid blockchain architecture. The network for our application is built using Hyperledger Composer framework. All the transactions done on the client app are recorded and appended to the Fabric with the help of a REST server. Fabric contains various security measures such as Access Control Lists and channels to ensure only authorized users to have access to those transactions. Before the users can perform any transactions, they will be given an identity card containing the certificates and credentials required to access the blockchain network. With our approach, we aim to significantly cut the transaction costs of exchanging shares and bring about a seamlessly efficient platform where participants would confirm trades via a distributed ledger
Facial Pose and Expression Transfer Based on Classification Features

Transferring facial pose and expression features from one face to another is a challenging problem and an interesting topic in pattern recognition, but is one of great importance with many applications. However, existing models usually learn to transfer pose and expression features with classification labels, which cannot hold all the differences in shape and size between conditional faces and source faces. To solve this problem, we propose a generative adversarial network model based on classification features for facial pose and facial expression transfer. We constructed a two-stage classifier to capture the high-dimensional classification features for each face first. Then, the proposed generation model attempts to transfer pose and expression features with classification features. In addition, we successfully combined two cost functions with different convergence speeds to learn pose and expression features. Compared to state-of-the-art models, the proposed model achieved leading scores for facial pose and expression transfer on two datasets.
FPGA based hardware platform for trapped-ion-based multi-level quantum systems

We report a design and implementation of a field-programmable-gate-arrays (FPGA) based hardware platform, which is used to realize control and signal readout of trapped-ion-based multi-level quantum systems. This platform integrates a four-channel 2.8 Gsps@14 bits arbitrary waveform generator, a 16-channel 1 Gsps@14 bits direct-digital-synthesis-based radio-frequency generator, a 16-channel 8 ns resolution pulse generator, a 10-channel 16 bits digital-to-analog-converter module, and a 2-channel proportion integration differentiation controller. The hardware platform can be applied in the trapped-ion-based multi-level quantum systems, enabling quantum control of multi-level quantum system and high-dimensional quantum simulation. The platform is scalable and more channels for control and signal readout can be implemented by utilizing more parallel duplications of the hardware. The hardware platform also has a bright future to be applied in scaled trapped-ion-based quantum systems.
Image Hiding in Stochastic Geometric Moiré Gratings

An image hiding scheme based on stochastic moiré gratings is proposed, discussed, and illustrated in this paper. The proposed scheme is based on a counter-intuitive optical feature of specially designed stochastic moiré gratings when similar images in the static mode become very different in the time-averaged mode. A soft computing PSO algorithm was used for the construction of stochastic gratings. Complex computational algorithms were required to construct the cover image; however, the decryption process was completely visual. The cover image must oscillate in a predefined direction and at a predefined amplitude (the amplitude of the harmonic oscillation is one of the parameters of the proposed image hiding scheme). Computational experiments were used to demonstrate the efficacy of this optical image hiding scheme based on the stochastic moiré gratings.