Reviewerly/exHarmony huggingface dataset:
Conceptual foundations for establishing an independent evaluation system of educational outcomes of future teachers in the Russian Federation

This article discusses the conceptual foundations of establishing an independent evaluation system (IES) of educational outcomes of future teachers. The following competencies and corresponding educational outcomes groups are identified: educational, psychological and pedagogical, methodological and subject competencies. There is a presentation form description of evaluation tools with organizational-methodical, content, and criterion-evaluation parts that help link the educational outcomes, teacher functionality, and appropriate professionally-oriented tasks and describe indicators of achieving educational outcomes as evaluated actions of the learner. The association of the selected parts with the principles of constructing evaluation of objectivity, validity, and openness of evaluation procedures tools is disclosed. The inclusion of evaluation tools and funds of evaluation tools involves their testing and examination. As a mechanism for implementing IES, it is proposed to use a digital platform including groups of evaluation tools adequate to the selected educational outcomes groups.
Early Stages of Automatic Speech Recognition (ASR) in Non-english Speaking Countries and Factors That Affect the Recognition Process

There has been a considerable stream in ASR over the past few decades, but it may seem strange why this field is still a subject for researchers to work on.There are many reasons, but somewhat because the discipline is created with the promise of human-level performance under pragmatic states and this is an inextricable problem.In addition, the increasing advancement of technology in various fields has caused a more compelling need for this field.Especially the establishment of such a system in the security sector in insecure third world countries such as Afghanistan is an urgent need.This paper began with the reflection of all the necessary knowledge about speech recognition and then suggested an unprecedented method for building an automated speech recognition (ASR) system in the Dari language using the two most powerful open source engines CMUSphinx, from Carnegie Mellon University and DeepSpeech v0.9.3 /.These systems are much more impressive than early speech recognition systems.Using my own collected dataset, a speech-to-text model has been trained for the Dari language.Firstly, the dataset is filtered according to the task, then demonstrated the possible compatibility from the hidden Markov (HMM) models, the phoneme concept to RNN training.The system surpassed previously predicted results, as CMUSphinx stated, "for a typical 10-hour operation, the WER should be around 10%." Finally, 3.3% WER was achieved with 10.3-hours of audio recording using CMUSphinx.1% WER with DeepSpeech.
Blockchain Technology in Agriculture

The World Economic Forum marked Blockchain technology (BCT) as one of the seven revolutionary technologies of the future. It is a distributed ledger system ensuring transparency, security, immutability, interoperability, and provenance. This article tries to understand the technological aspects, working mechanism and explore different areas where BCT can be applied in agriculture. Data in BCT is stored in a series of blocks contains the hash value (previous and the current), timestamp, and difficulty details, secured cryptographically with a symmetric or asymmetric digital signature to avoid data tampering and fraud. Traceability (supply chain), using Smart contracts (in Agricultural insurance, Crop finance, Land records) achieved by the BCT and the companies (Carrefour, Trace harvest), states (Telangana, Andhra Pradesh), and countries (Kenya, European Union) practicing are discussed. The Farmer producer company- Sahyadri farms keen implementation of blockchain fetched benefits to farmers amid Covid times. Finally, addressing the barriers in practicing the BCT in India- Technology maturity, energy cost, and education. The massive potential of BCT is yet untapped, to reach up to the farmer level, which will flourish in the coming years.
Encryption key management as a trusted security as a service for cloud computing

Cloud computing has become very popular and its users and services are in constant increase. Currently, many mobile IT users are accessing business data and services without going through corporate networks. Consequently, the need for putting appropriate and robust security controls between mobile users and cloud-based services is crucial. This is the main reason behind the proliferation of new security as a service (SecaaS) offers. The common security mechanism of most services and communications is based on the encryption/signing keys, which themselves depend highly on the cryptographic key management system (CKMS) itself. This is called trustworthy protocol and its implementation is the most challenging of the whole security and protection policies and mechanisms. To deal with this challenge, we propose an approach that provides a CKMS as a trusted SecaaS based on the trusted platform module (TPM), which is the foundation for the trust, keys generation, and SecaaS authentication. We define an efficient security protocol that creates, certifies, and encrypts any encryption/signing key inside TPM. Key leaves TPM in encapsulated format, and it delivered to its owner in a secure way without decryption.
Descriptive Statistics 1: Univariate Analysis

Mastering descriptive statistics is mandatory for a geologist. Chapter 5 shows how to describe a geological data set using Python programming, starting with basic metrics such as the location, dispersion, and degree of symmetry of a univariate data set. It then shows how to perform descriptive statistics in pandas and introduces box plot diagrams.
Research on multi level aggregation of privacy preserving data in Internet of things

The traditional privacy protection data aggregation method is prone to errors in the process of aggregation, which affects the final clustering effect. Therefore, this paper proposes and designs a new multilevel aggregation method for privacy protection data in the Internet of Things. First integration of privacy protection data sharing dynamic elements and design specification, clustering based on this, complete the Internet privacy protection data extraction and processing, so as to realize data clustering for many times, and retain most of the features of the original data space, data privacy protection data obtained by multi-stage polymerization can be well preserved. Simulation results show that, compared with the traditional method, the aggregation error rate of this method is obviously lower, which ensures the security, efficiency and applicability of the privacy-protected data to a greater extent.
Performance Analysis of Virtualisation in a Cloud Computing Platform. An application driven investigation into modelling and analysis of performance vs security trade-offs for virtualisation in OpenStack infrastructure as a service (IaaS) cloud computing platform architectures.

Petroleum technology development fund (PTDF) of the government of NigeriaUsmanu Danfodiyo University, Sokoto
Foundation of Cyber Ranges

This report details the design considerations and execution plan for building high-fidelity, realistic virtual cyber ranges that deliver maximum training and exercise value for participants. A cyber range is a fully interactive virtual instance of the IT infrastructure of a mid-to enterprise-level organization that is dedicated to cyberwarfare training and exercise. The Software Engineering Institute CERT Cyber Workforce Development (SEI/CERT/CWD) team at Carnegie Mellon University has provided a wide array of cyber ranges spanning various levels of complexity to the Department of Defense (DoD) since 2012. This report draws on tens of thousands of hours of experience and expertise in designing, developing, deploying, troubleshooting, maintaining, and improving cyber ranges. The most frequent use case for a cyber range is team exercise. Team exercises can focus on incident response, malware removal, network takeover, process improvement, and many other specialized use cases. This report summarizes the SEI/CERT/CWD current state of the art when it comes to delivering high-fidelity/realistic cyber ranges to DoD and non-DoD customers that support the complex operating environments required for their training and exercise purposes.
Dr. Phish: Phishing Website Detector

Phishing is an attack on gullible people by making them disclose their personal and unique information.It is a cyber-crime where false sites attract exploited people to give delicate data.This paper describes the various techniques for detecting phishing websites by analyzing different attributes of URLs with the help of ML techniques.This experimentation discusses the techniques used for detecting phishing websites by extracting their features like URL length, port, HTTPS token and many more.We have used data mining techniques for the extraction of the features of an URL in order to get a clear image of URL's structure that spread phishing.To protect the end users from entering these types of phished websites, we can try to predict whether an URL is phished or not.A challenge in this field is that attackers are constantly making new strategies to tackle our defensive methods.To continuously update our system in this domain, we need ML algorithms that adapt to new instances and features of phishing URLs.
Effort Estimation in Agile Software Development: A Systematic Mapping Study

Context: Estimating effort has always been considered an important element at the start of each software development project. The challenge of estimating the effort of software development lies in its precision. With the emergence of agile methodologies, methods for effort estimation (EE) had to adapt to this new development path. In this article, we are conducting a systematic mapping study on effort estimation in the context of agile software development. Objective: we want to identify the estimation approaches and techniques used in the context of agile development to better understand the specifics and trends relating to this mode of development. Method: we conducted a systematic mapping study by adopting the guideline explained in[1] [2]. A systematic review of the literature [3] has already been carried out for publications between 2001 and 2013. This work is an extension of this previous study. We queried 5 electronic databases. Conclusion: We retrieved 11350 paper from five electronic databases. A total of 108 papers is selected after applying the inclusion and exclusion criteria. Based on the results, there is a general increase over the years of studies concerning effort estimation in agile software development.
An Event-B-Based Approach to Model and Verify Behaviors for Component-Based Applications

Abstract Many disciplines have adopted component-based principles to avail themselves of the many advantages they bring, especially component reusability. In a short time, the component-based architecture became a renown branch in the IT world and the center of interest of many researchers. Much work has been conducted in this context for the verification of component-based applications (CBAs). However, the main focus has been on the structural aspect of such compositions, while the behavioral aspect has seldom been dealt with. In this paper, our goal is to close this gap and propose a formal approach to verify the behavioral correctness of CBAs. We first define a set of requirements to be satisfied by the structure and the behavior of a CBA, represented by a set of interactions that may occur between their components. Then, we build a formal Event-B model to represent these requirements in a rigorous and non-ambiguous way. The use of the Event-B refinement technique allows us to master the complexity of CBAs by introducing their elements in an incremental manner. The correctness of the development is ensured by establishing a set of proof obligations, under the Rodin platform, and also by animating it with the ProB animator/model checker. The approach is illustrated by a running example.
Current Trends in Cloud Computing for Data Science Experiments

Recent trends in data-intensive experiments require extensive computing and storage resources that are now handled using cloud resources. Industry experts and researchers use cloud-based services and resources to get analytics of their data to avoid inter-organizational issues including power overhead on local machines, cost associated with maintaining and running infrastructure, etc. This article provides detailed review of selected metrics for cloud computing according to the requirements of data science and big data that includes (1) load balancing, (2) resource scheduling, (3) resource allocation, (4) resource sharing, and (5) job scheduling. The major contribution of this review is the inclusion of these metrics collectively which is the first attempt towards evaluating the latest systems in the context of data science. The detailed analysis shows that cloud computing needs research in its association with data-intensive experiments with emphasis on the resource scheduling area.
A SWOT Analysis of Instagram English Teaching Pages

In recent years social networking sites have affected almost all aspects of our lives. The Instagram social network has become popular among people, and there are lots of pages on this social media, which are explicitly presenting English materials to their followers. This non-experimental descriptive study aimed to determine the strength, weaknesses, opportunities, and threats of English teaching pages on Instagram. Twelve English teaching pages were observed due to their high number of followers to discover the strengths, weaknesses, opportunities, and threats. To provide more fruitful points for the SWOT analysis, ten active Instagram users were interviewed. They were asked to fill out a SWOT analysis written interview about Instagram English teaching pages. The interpretative approach and frequency and percentage were used to analyze the data, owing to the nature of the gathered data in this research. Employing the results of this study, admins of English teaching pages can take a forward step to make their pages more beneficial and more effective in the process of English teaching. The findings can also help those scholars or teachers who want to use Instagram to present their services. Being aware of the effectiveness of English teaching pages helps language learners be more cautious about selecting them as a source of learning English.
Hierarchical Bit-Plane Slicing for High Dynamic Range Image Stereo Matching

Due to the recent advances of sensing technologies, high dynamic range (HDR) imaging devices have been developed for the image acquisition of real-world scenes with a wide range of luminance changes. In this paper, the hierarchical matching techniques for high dynamic range image pairs are investigated. A bit slicing method is combined with the state-of-the-art stereo matching algorithms for HDR images generated from multiple exposures. Our approach demonstrates that it is possible to use only the most significant 16 bits of the HDR image encoding per pixel to achieve a comparable bad pixel rate on stereo matching. Thus, the computational power and memory constraints can be reduced while benefiting from the HDR images. This makes HDR stereo matching feasible under general resource limited setups. In the experiments, the evaluation and comparison carried out using Middlebury stereo datasets have illustrated the effectiveness of the proposed framework. The source codes are available at: https://github.com/chillwater/HDR Stereo Match.
The impact of hybrid learning in teaching English for Business Communication in Vocational Higher Education of Indonesia

Some studies have been undertaken to decide the impact of hybrid learning on outcomes in higher education settings, with findings indicating that hybrid learning increases student performance more than distant learning or normal face-to-face instruction. This paper focuses on the students’ perspective on the impact of hybrid learning-based instruction in teaching English for Business Communication in Vocational Higher Education of Indonesia. This study is ex post facto research that aims to find the causes that allow changes in behavior, symptoms, or phenomena caused by an event, behavior, or things that cause changes in the independent variables which have occurred. This study employed a case study using students’ reflection journals and online questionnaires to seventy-five students of Business English for Communication class of the Vocational Higher Education in Makassar, South Sulawesi, Indonesia. Data were analyzed descriptively. In analyzing the data, the researcher used thematic analysis and content analysis. Data analysis steps are data familiarization, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the report. This study showed that students perceived the hybrid learning improved students’ technology competence, collaboration participation, and engagement, motivation, self-confidence. The impact of hybrid learning in teaching English for Business Communication can be categorized into three highly impacted, moderately impacted, and lowly impacted on students, attitude, skills and competence, and motivation. This study claims that the more positive students are toward hybrid learning education in the classroom, the higher their English for Business Communication performance. This research improves scholarly understanding of hybrid learning instruction in Indonesian Vocational Higher Education when teaching English for Business Communication.
Early earthquake warning system for city gas network

Tokyo Gas supplies city gas to 8 million customers around Tokyo metropolitan area and has social responsibility to secure safety even after big earthquake. To prevent gas-caused secondary disaster after earthquake, it is necessary to make prompt and reasonable decision. For this purpose, SIGNAL (Seismic Information Gathering Network Alert System) has been developed to support to make decision and has been in operation since June, 1994. One of SIGNAL’S function is quick monitoring SI readings and seismic acceleration at 331 locations, acceleration waves at 5 locations and rising ground water levels at 20 locations considered most at risk from ground liquefaction, using a reliable radio network. This real-time earthquake data is linked to data bases of gas pipelines and ground conditions to give an accurate damage assessment, based on pipe damage experiences suffered in previous earthquakes. The assessment of damage to the gas network is useful for the rapid implementation of emergency work and in drawing up efficient and accurate restoration plans.
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On these bases, this work aims to improve FA using variable neighborhood search (VNS) as a local search method, providing VNS the benefit of the trade-off between the exploration and exploitation abilities. The proposed FA-VNS allows fireflies to improve the clustering solutions with the ability to enhance the clustering solutions and maintain the diversity of the clustering solutions during the search process using the perturbation operators of VNS. To evaluate the performance of the algorithm, eight benchmark datasets are utilized with four well-known clustering algorithms. The comparison according to the internal and external evaluation metrics indicates that the proposed FA-VNS can produce more compact clustering solutions than the well-known clustering algorithms.
SCIENTIST'S PROFESSIONAL IDENTITY: FACTORS AND PATTERNS OF TRANSFORMATION

The article is devoted to the analysis of factors and patterns of transformation the professional identity of scientists on the example of modern Russian science. The analysis was carried out on the basis of both secondary and primary sociological data. As the primary sociological data were used the materials of quantitative and qualitative research carried out in scientific centers of the SB RAS in the period from the end of the 1990s to the end of the 2010s. It is concluded that the leading factor for the transformation of the professional identity of Russian scientists was, first of all, a sharp change in the attitude towards science on the part of society and the state. We can say about the crisis in these relations is evident, which was reflected in a sharp drop of economic and social status of science. In addition, we are also talking about the weakening of the science’s cognitive role in culture. Three post-Soviet decades have shown that science, as a rule, found ways to successfully adapt to a constantly changing situation, primarily a change in the course of state scientific policy.
Gesture Controlled Robot using Accelerometer

Robots are devices that can perform tasks with or without human intervention, based on inputs from its environment. Gestures can be explained as symbolic actions performed by humans having a meaning. In this project, a robot toy car has been developed where the user uses these very gestures to interact with the robot car rather than the established and current technology of using remote controllers with buttons and joysticks, or mobile applications. These gestures are identified with the use of an accelerometer(ADXL345). The entire project is split into two parts: the transmitter circuit and the receiver circuit, where the former uses ADXL345 for gesture recognition, and the latter uses Motor driver (L293D) to move the toy car.
Controlled Vocabularies and SKOS

Thesauri, taxonomies and other forms of controlled vocabularies represent a conceptual backbone of the research, playing an ever-increasing role in various aspects of the data management process. These resources are indispensable to determine common understanding allowing to systematically categorize and enrich research data in a consistent manner, as well as foster the data interoperability and integration among projects and web applications.
Security Issue in DistributedArchitecture of Cloud Computing in Big Data Aspects

In this research paper, we will inspect cloud computing security issues. The main focus will be on distributed computing that are joined with large number of information. Big information Applications are very beneficial for the organizations and for various small-scale ventures. We will discuss many Solution for the security problem and HADOOP. Allocated computing, various info and operation, crucial points are prone to speak to the many capable innovative limits in art and Information (science).