Reviewerly/exHarmony huggingface dataset:
Model of Educational Work on Career Guidance in the System of Secondary Vocational Education

Youth is a dynamically developing social group that actively participates in the reproduction process of the social and professional structure of society. The complication of production processes and rapid scientific and technological progress increase the importance of this social group in Russian society. This scientific article attempts to study the level of implementation of career guidance in the system of educational work of an educational institution of secondary professional level. Using a system-synergetic approach and various methods of scientific research, the authors revealed not only the state of the problem under consideration but also determined the relevance of such research in contemporary conditions. Based on the obtained data, a theoretical universal model of educational work has been developed, which assumes the formation of value orientations among young people in the course of its implementation. The student professional development model concerning the educational activities of the College consists of three interrelated units: target, substantive-operational, and evaluation- performance blocks. The model provides self-development of the individual through the cardinal renewal of all the above-mentioned components, and the formation of general cultural competencies. The main advantage of the created model is the development of complete professionalism through the implementation of career growth mechanisms in students, as well as the orientation of young people to actively search for innovative conditions for professional self-actualization and civic-mindedness.
Hybrid Behavior-based Biometric Authentication Systems (HBAS)

An idea of proposing hybrid security based on behavioural biometrics is displayed in this paper, on the two bases of tapping and swiping. Tapping and swiping are the main focus as they are the easiest actions to perform on a mobile device. Actions and mannerisms performed by either attacker and/or the user are explained alongside the results of said actions and mannerisms. An attacker will haphazardly try to brute force the motion while the owner will perform his action consistently. Then, a training set is done where an attacker and an owner’s training sets are obtained and set, to determine which classifiers work best in determining the confusion matrix from a range of training set values with Hoeffiding Tree and Naive Bayes Multinomial classifiers performing the best over the three sets of training values provided.
RoRePo: Detecting the role information and relative position information for contexts in multi-turn dialogue generation

In multi-turn dialogue generation, dialogue contexts have been shown to have an important influence on the reasoning of the next round of dialogue. A multi-turn dialogue between two people should be able to give a reasonable response according to the relevant context. However, the widely used hierarchical recurrent encoder-decoder model and the latest model that detecting the relevant contexts with self-attention are facing the same problem. Their given response doesn’t match the identity of the current speaker, which we call it role ambiguity. In this paper, we propose a new model, named RoRePo, to tackle this problem by detecting the role information and relative position information. Firstly, as a part of the decoder input, we add a role embedding to identity different speakers. Secondly, we incorporate self-attention mechanism with relative position representation to dialogue context understanding. Besides, the design of our model architecture considers the influence of latent variables in generating more diverse responses. Experimental results of our evaluations on the DailyDialog and DSTC7_AVSD datasets show that our proposed model advances in multi-turn dialogue generation.
Keyphrase Extraction on Covid-19 Tweets Based on Doc2Vec and YAKE

Keyword and keyphrase extraction are one of the initial foundations for performing several text processing operations such as summarization and document clustering. YAKE is one of the techniques used for unsupervised and independent keyphrase extraction, it does not require a corpus for linguistic tools such as NER and POS-tag. However, the use of YAKE in microblogging documents such as Twitter often results in a keyphrase that is less representative because of the lack of words used for ranking. This paper offers a solution to this problem by looking for similar tweets in the keyphrase extraction process using Doc2Vec so that the number of words used in the YAKE ranking process can be greater. Covid-19 tweets related are used as dataset as the topic is currently widely discussed on social media to prove that the proposed approach could improve keyphrase extraction performance
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning

Training agents to autonomously learn how to use anthropomorphic robotic hands has the potential to lead to systems capable of performing a multitude of complex manipulation tasks in unstructured and uncertain environments. In this work, we first introduce a suite of challenging simulated manipulation tasks that current reinforcement learning and trajectory optimisation techniques find difficult. These include environments where two simulated hands have to pass or throw objects between each other, as well as an environment where the agent must learn to spin a long pen between its fingers. We then introduce a simple trajectory optimisation that performs significantly better than existing methods on these environments. Finally, on the challenging PenSpin task we combine sub-optimal demonstrations generated through trajectory optimisation with off-policy reinforcement learning, obtaining performance that far exceeds either of these approaches individually, effectively solving the environment.
Hierarchical Representation Network With Auxiliary Tasks For Video Captioning

Video captioning is to understand a video in depth and generate high-quality descriptions. However, due to the complexity of videos, it is challenging to extract a video feature that can well represent multiple levels of concepts i.e., events, objects and actions. Meanwhile, content completeness and syntactic consistency play an important role in high-quality video captioning. Motivated by these, we propose a novel framework, named Hierarchical Representation Network with Auxiliary Tasks (HRNAT), for learning multi-level representations, and generating syntax-aware video captioning. Specifically, the Cross-modality Matching Task enables the learning of hierarchical representation of videos, guided by the three-level representation of languages. The Syntax-guiding Task and Vision-assist Task contribute to generating descriptions to be not only globally similar to the video, but also syntax-consistent to the ground-truth description. Finally, performances on several benchmark datasets validate the effectiveness and superiority of our method compared with state-of-the-art methods.
Automatic Recognition of Fake Indian Currency Note

The Currency Recognition System was developed for the purpose of fraud detection in paper currency, so this system is u sed worldwide.The uses of this framework can be recognized in banking frameworks, cash observing gadgets, cash trade frameworks.This paper proposes an automatic paper currency recognition system through an application developed using Machine learning Algorithms.The algorithm implemented is simple, robust and efficient.
Introduction of an Improved Attorney System to Spread the Problem Solving Process in Manufacturing Field

Numerous companies have begun to adopt a variety of methodologies for fast andaccurate problem solving.Among them, six sigma, which is a statistical approach, was introduced, but thestatistical method, which requires obtaining results from many experiments, was difficult to apply to sites where production is the top priority.As an alternative, the theory of inventive problem solving (TRIZ), which has beenintroduced to the research institute and has a good effect, is being introduced for field problem solving.However, it was not easily distributed to engineers unfamiliar with the new methodology as they had difficulty in applying them to the field.In this paper, we studied a problem solving process that transformed TRIZ that can be applied to various problem situations.This problemsolving process was developed to provide a guide to quickly and easily analyze the cause and to present creative ideas using TRIZ.In addition, in order to spread this problem-solving process, it was developed as a creative problem-solving methodology that can be effectively utilized in industrial sites by combining the patent attorney system.
Probabilistic Generating Circuits

Generating functions, which are widely used in combinatorics and probability theory, encode function values into the coefficients of a polynomial. In this paper, we explore their use as a tractable probabilistic model, and propose probabilistic generating circuits (PGCs) for their efficient representation. PGCs strictly subsume many existing tractable probabilistic models, including determinantal point processes (DPPs), probabilistic circuits (PCs) such as sum-product networks, and tractable graphical models. We contend that PGCs are not just a theoretical framework that unifies vastly different existing models, but also show huge potential in modeling realistic data. We exhibit a simple class of PGCs that are not trivially subsumed by simple combinations of PCs and DPPs, and obtain competitive performance on a suite of density estimation benchmarks. We also highlight PGCs' connection to the theory of strongly Rayleigh distributions.
Computer science, Mathematics and Logic in the aspect of interdisciplinary and metasubject educational communication

The article discusses the problem of teaching computer science, mathematics and logic in modern education, in particular, in a secondary general education school as inherited from the problems of the existing relationships between the sciences of computer science and mathematics, as well as generated by the prevailing forms and practice of teaching in the system of general education. The methodological aspects of teaching computer science, mathematics and logic are considered inherent in them and applied to them in a differentiated form: - a meaningful approach inherent in computer science and applied in mathematics and logic; - a formal approach inherent in mathematics and used in computer science and logic; - a socio-cultural approach characteristic of the triad ”computer science-mathematics-logic”. Against the background of the existing correspondence of the selected approaches (or the measure of this correspondence) to each local and independent element of the triad, it is assumed that there is an identification of the regular relations between the subject and the subject of education, the principles of organizing the processes of implementing methodological knowledge based on these regularities. For our study, it is important that the methodology and methodology of each differentiated system of the triad should contain everything that is ”necessary and sufficient” for the functioning of the educational system of the corresponding level. In this aspect, the article notes that mathematics studies form, computer science - form and content. The study of objects only in form leads to formalism in the information sphere (which is unacceptable), therefore, possible integration must be combined with the necessary differentiation. Since the processes of the development of knowledge of science, its methodology and teachingmethods are interrelated and interdependent, it is unconditionally interesting to reveal the potential (possibilities) of intersubject and metasubject connections and relations of the triad under consideration as close, but not homogeneous educational systems that have their own subject. specificity of the content, methods and forms of training. In this perspective, possible ways of solving the problems that have arisen are proposed in the context of changes in the school curricula of the content of information and mathematics education under the influence of the requirements of the new federal state educational standards and the structure of subject teaching in computer science and mathematics, ensuring their efficiency and effectiveness.
Foreign and local analysis of the stages of development of information communication technologies in education

The article examines the foreign and domestic analysis of the stages of development of information and communication technologies in education. The situation of the use of information and communication technologies (ICT) in education is also studied. The Internet has changed the way people use information and knowledge, the way they communicate. Technology is one of the fundamental general scientific concepts of the present time. The concept of pedagogical technology appeared in the twentieth century and is passing through various stages of development. Initially, this concept was used as “educational technology” from the 1940s to the mid - 50s, expressing the use of audiovisual techniques in the educational process. The concept of pedagogical technology originally began to be used in the US in the middle of the XX century. The terms” pedagogical technology “and” educational technology” were used in relation to teaching only with the help of technical means. Over time, as a result of the increase in the level of their application, the content also changed accordingly.
The Arabic–English Parallel Corpus of Authentic Hadith

We present a bilingual parallel corpus of Islamic Hadith, which is the set of narratives reporting different aspects of the Prophet Muhammad's life. The Hadith collection is extracted from the six canonical Hadith books which possess unique linguistic features and patterns that are automatically extracted and annotated using a domain-specific tool for Hadith segmentation. In this article, we present the methodology of creating the corpus of 39,038 annotated Hadiths which will be freely available for the research community.
Efficient Training of Deep Learning Models Through Improved Adaptive Sampling

Training of Deep Neural Networks (DNNs) is very computationally demanding and resources are typically spent on training-instances that do not provide the most benefit to a network’s learning; instead, the most relevant instances should be prioritized during training. Herein we present an improved version of the Adaptive Sampling (AS) method (Gopal, 2016) extended for the training of DNNs. As our main contribution we formulate a probability distribution for data instances that minimizes the variance of the gradient-norms w.r.t. the network’s loss function. Said distribution is combined with the optimal distribution for the data classes previously derived by Gopal and the improved AS is used to replace uniform sampling with the objective of accelerating the training of DNNs. Our proposal is comparatively evaluated against uniform sampling and against Online Batch Selection (Loshchilov & Hutter, 2015). Results from training a Convolutional Neural Network on the MNIST dataset with the Adadelta and Adam optimizers over different training batch-sizes show the effectiveness and superiority of our proposal.
Anomaly Detection in Time Series Data Using Support Vector Machines

Analysis of large data sets is increasingly important in business and scientific research.One of the challenges in such analysis stems from uncertainty in data, which can produce anomalous results.In this paper, we propose a method of anomaly detection in time series data using a Support Vector Machine.Three different kernels of the Support Vector Machine are analyzed to predict anomalies in the UCR public data set.Comparison of the three kernels shows that the defined parameter values of the RBF kernel are critical for improving the validity and accuracy in anomaly detection.Our results show that the RBF kernel of the Support Vector Machine can be used to advantage in detecting anomalies.
Implementation of Blockchain in Current Transaction Systems

The blockchain technology is being deployed in many areas and the banking system is not an exception. It is a new technology and should be introduced in the modern banking system. The aim of this project is to give an overview of blockchain technology with its benefits and emphasizing on the application of this technology in the banking sector. We are going to generate our own cryptocurrency along with a banking system with number of nodes between which we can perform transactions using blockchain. And we are using Ethereum (Online Transaction Management System) for our ongoing project. Now, blockchain is better than the conventional banking systems as, combining shared databases and cryptography, blockchain technology allows multiple parties that may not know each other from different geographical locations to have simultaneous access to a constantly updated digital ledger that cannot be altered. So, we will generate our own virtual nodes (Users who want to transfer money) which will transfer our own cryptocurrency to each other. The blockchain is a ground-breaking innovation that empowers Bitcoin, Litecoin, Dogecoin, and other virtual monetary standards to be open, mysterious, and secure. The blockchain basically is a database about each Bitcoin exchange in detail. Typically known as an open record, the log contains metadata about when and how every exchange occurred. The record is freely available through APIs and deluge destinations. To forestall messing with current and furthermore past exchanges, the database is cryptographically made sure about. Because of Cryptography can edit only the parts of the blockchain that they “own” - by possessing the private keys required to write to the file. It also keeps everyone’s copy of the distributed blockchain is kept in sync. Using blockchain rather than conventional banking system would help in fraud reduction and that too by quiet a lot of margin. Financial institutions spend millions of money per year to keep up with Know your Customer (KYC) and customer due diligence regulations according to a Thomson Reuters Survey. These regulations are meant to help reduce money laundering and terrorism activities by having requirements for businesses to verify and identify their clients. Blockchain would allow an organization to access the verification details of a client by another organization, thus avoiding repetition of the KYC process. Blockchain disruption could be highly transformative in the payments process. It would allow banks higher security with minimal lower costs to process payment between organizations and their clients and even between banks themselves. Blockchain would get rid of all the intermediaries in the payment processing system. Keywords: Blockchain, current transaction system, KYC, online transaction management system, processing system Cite this Article: Dhruv Rawat, Gaurav Rana, Jaskaran Singh Bindra, Amit Kumar. Implementation of blockchain in current transaction systems. International Journal of Data Structures. 2020; 6(1): 31–59p.
Teaching Tool for Fun Learning of AI-based Banknote Detection Technology

only look once (YOLO) This paper presents a teaching tool for schoolchildren to learn artificial intelligence (AI) technology through which a variety of banknotes can be recognized.This was done by first using a pretrained YOLOv3 object detection model.Secondly, transfer learning was conducted on the pretrained model using 11 collected banknotes, including US$, Euro, Japanese Yen, and NT$.The banknote detection model was experimentally validated to give an average precision (AP) of up to 99.09% if the threshold Intersection over Union (IoU) is not less than 0.8.Once a banknote was successfully recognized, the face value and the country name thereon were displayed, and schoolchildren can access suggested websites, i.e., Wikipedia, Google Maps, and the Bank of Taiwan, to learn more about the exchange rate between currencies and the history and location of the country that issued the banknote.Consequently, schoolchildren can have fun using this tool and acquire a more a global outlook.Moreover, they may be motivated to become AI professionals in the future.
SAR Images Denoising Using Bidimensional Variational Mode Decomposition and Nonlocal Means Reprojection with Minimizing Variance

Synthetic aperture radar (SAR) is very high and accurate technology for remote sensing. SAR images are very exploited for change detection and monitoring because of their high resolution. Because of the coherent retro diffusion of the backscattered radar waves with the rigorous earth surface, SAR images are characterized by a multiplicative noise called speckle that influences their analysis. For this reason, this paper aims to exploit the two-dimensional variational mode decomposition and combines it with the nonlocal means reprojection method to denoise SAR images. The proposed method concerns to decompose the SAR image into a series of variational mode functions called S-D IMFs and N-D IMFs, however, the speckle noise is high-frequency information, which means that it is concentrated in N-D IMFs components. Then, the denoising of N-D IMFs components is implemented using NLM reprojection using box kernel with minimizing variance. Firstly, we use numerical simulation to study the performance of our method, this study concerns use several synthetic images and add speckle noise for different variance, and then we apply the proposed method. The quantitative appraisal will be realized using three important metrics such as peak signal to noise ratio (PSNR), Edge preservation index (EPI), and image quality index (Q). Also, we compare our proposed method with other famous techniques as the Lee filter, Frost filter, and NLM-SAR method. Secondly, the proposed method will be exploited to denoise a real SAR image.
Review of software quality related ISO standards

The present study aims to provide an overview of the current state of standardization efforts regarding software quality. Starting with the general characteristics of ISO standards, taking into account both their good and less good properties, briefly covering standardization organizations other than ISO.Starting from a brief, historical recall of the relevant basic concepts of quality and software quality, it outlines the key elements of the ISO / IEC 25000 family of standards, emphasizing the beneficial effects on IT security of using the family of standards, with a brief description of related additional standards.It illustrates the effective applicability of this family of standards with real-life examples from different parts of the world, taking into account Hungary's involvement and position on the subject.
Maximums of the Additive Differential Probability of Exclusive-Or

At FSE 2004, Lipmaa et al. studied the additive differential probability adp⊕(α,β → γ) of exclusive-or where differences α,β,γ ∈ Fn2 are expressed using addition modulo 2n. This probability is used in the analysis of symmetric-key primitives that combine XOR and modular addition, such as the increasingly popular Addition-Rotation-XOR (ARX) constructions. The focus of this paper is on maximal differentials, which are helpful when constructing differential trails. We provide the missing proof for Theorem 3 of the FSE 2004 paper, which states that maxα,βadp⊕(α,β → γ) = adp⊕(0,γ → γ) for all γ. Furthermore, we prove that there always exist either two or eight distinct pairs α,β such that adp⊕( α,β → γ) = adp⊕(0,γ → γ), and we obtain recurrence formulas for calculating adp⊕. To gain insight into the range of possible differential probabilities, we also study other properties such as the minimum value of adp⊕(0,γ → γ), and we find all γ that satisfy this minimum value.