Reviewerly/exHarmony huggingface dataset:
Measuring liquid density in a system for ensuring uniformity of measurements

The article presents the results of a study aimed at creating the national standard for liquid density. The standard provides reproduction, storage and transmission of the liquid density unit in the range from 650 to 2000 kg/m3. Based on the method of hydrostatic weighing, the measurement of liquid density was implemented in accordance with the GOST OIML R 111-1-2009 «State system for ensuring the uniformity of measurements. Weights of classes Е1, Е2, F1, F2, M1, M1–2, M2, M2–3 and M3. Part 1. Metrological and technical requirements». It is shown that the use of a high-precision mass comparator can significantly reduce the systematic measurement error and the standard deviation when reproducing and transferring the unit of liquid density to reference measuring instruments of the 1st and 2nd category and working measuring instruments. A method for transferring a unit of liquid density by means of a standard density measure – a silicon sphere and a comparator liquid – has been implemented, which made it possible to exclude the transfer link in the form of a standard liquid density solution. In the range of reproduction, storage and transmission of the liquid density unit, a systematic error of 2.1 ⋅ 10–3 kg/m3 was obtained, the standard deviation in the reproduction of the liquid density unit was 4.0 ⋅ 10–4 kg/m3, the standard deviation of the total error in the transmission of the liquid density unit 3.14 ⋅ 10–3 kg/m3.
CLOUD SECURITY WITH AWS

Cloud computing is a modern method of computing in the field of computer science.A collection of resources and services known as "cloud computing" are provided by a network or the internet.New techniques are emerging as the field of cloud computing expands.The environment for cloud computing is expanding, which presents new security difficulties for cloud developers.Because cloud users save their data there, a lack of security in the cloud may undermine user confidence.The best part about cloud security is that it not only safeguards data, especially PII (personally identifiable information) like SSNs, bank account numbers, passport numbers, and so forth, but also applications that access the data.Even the infrastructure (such as servers) on which apps are running is protected by cloud security.Amazon Web Services (AWS) delivers a scalable cloud computing platform with reliability ..offering the resources necessary for users to operate a variety of apps.The security, integrity, and availability of our customers' systems and data, as well as preserving their trust and confidence, are of the utmost importance to AWS.In This paper we are going to understand and learn about cloud security with aws , how aws providing security to its underlying customers and tools and services provided by aws .at the end we will learn how can we secure S3 Storage Buckets.
Ontology and Knowledge Graphs for Natural Language Processing

Natural language processing (NLP) is an important and challenging field of computer science. With the advent of computers and related technologies, NLP has grown out of the field of linguistics and is getting more attention in the computer field to support a wide variety of intelligent applications. NLP basically refers to automatic processing of natural languages by computers or machines in order to understand human language in written or spoken form. Ontologies are semantic models that provide general description of the types and structures of objects in a particular subject area or domain. Core components of ontology include concepts, relationships, instances, and axioms. Ontology is used to depict the hierarchical organization of concepts and their relationships. Knowledge graphs represent a set of interconnected descriptions of objects or concepts, and are sometimes referred to as semantic networks. In short, an ontology can be treated as a meta-model for data and knowledge graphs as a representation of the actual data or facts. An ontology (a formal description of relationships) plays a vital role in building a knowledge graph. Ontology and knowledge graphs have proven to be powerful tools to manage enterprise or big data. Today, a number of applications rely on ontology and knowledge graphs, such as knowledge management, information discovery, text extraction, semantic search, content-based recommendation, and intelligent chatbots. This chapter focuses on the importance of ontology and knowledge graphs for Developing NLP-based applications is difficult because computers require structured data, and human speech is highly complex, extremely diverse, unstructured in nature, and often ambiguous. In general, manual creation of knowledge graphs is expensive, therefore any automation of the process is highly desirable. Here, ontologies and knowledge graphs play a crucial role by providing a well-structured knowledge base, allowing semi-automatic creation of a lexicon to be used effectively in language translations, spellcheckers, keyword extraction and similar NLP applications.
Intelligent recommendation system based on decision model of archive translation tasks

How to recruit, test, and train the intelligent recommendation system users, and how to assign the archive translation tasks to all intelligent recommendation system users according to the intelligent matching principles are still a problem that needs to be solved. With the help of proper names and terms in China's Imperial Maritime Customs archives, this manuscript aims to solve the problem. When the corresponding translation, domain or attributes of a proper name or term is known, it will be easier for some archive translation tasks to be completed, and the adaptive archive intelligent recommendation system will also improve the efficiency of intelligent recommendation quality of archive translation tasks. These related domains or attributes are different labels of these archives. To put it simply, multi-label classification means that the same instance can have multiple labels or be labelled into multiple categories, which is called multi-label classification. With the multi-label classification, archives can be classified into different categories, such as the trade archives, preventive archives, personnel archives, etc. The system users are divided into different professional domains by some tests, for instance, system users who are good at economic knowledge and users who have higher language skills. With these labels, the intelligent recommendation system can make the intelligent match between the archives and system users, so as to improve the efficiency and quality of intelligent archive translation tasks. In this manuscript, through multi-label classification, the intelligent recommendation system can realize the intelligent allocation of archive translation tasks to the system users. The intelligent allocation is realized through the construction of intelligent control model, and verifies that the intelligent recommendation system can improve the performance of task allocation over time without the participation of task issuers.
Shutterstock to sell AI-generated art

As floral plants took over the world, they usurped the bloom-free gymnosperms that once dominated the planet. How did they win the battle, asks Penny Sarchet
Facilitation pedagogy in the system of the Ministry of Internal Affairs of Russia: from pedagogical practice to scientific concept

Abstract. The article is based on the results of the study of the phenomenon of pedagogical assistance in the system of the Ministry of Internal Affairs of Russia. Pedagogical assistance is considered as a professional and personal position of a pedagogical subject in relation to another person and as the basis of his project activities for the organization of educational environments. Pedagogical assistance acts in a dual capacity – on the one hand, as a way of organizing humanistically directed pedagogical activity, on the other hand, as a system–forming core of the scientific concept of managing the personal self-development of an employee of the Ministry of Internal Affairs of Russia in the educational process and professional activity. The concept of pedagogical assistance presented in the format of the article complements the methodological foundations of modeling pedagogical activity in line with the situational-environmental approach of N.V. It provides the possibility of fixing the dynamics of personality development as increments of personal experience within the boundaries of the stages of the situational cycle in the appropriate environments: goal-setting, sense-seeking and free creativity. The developed scientific concept of pedagogical assistance expands the possibilities of managing the environment of personal development in the system of continuing education.
Development of a Solar diffuse Irradiance Prediction Model using Existing Solar Decomposition Models and Reinforcement Learning

An accurate irradiance prediction by orientation is important for solar systems installed in buildings. Thus, solar decomposition methods are essential. Existing solar decomposition models are site dependent. Thus, elaboration is required for local applications. In this work, we proposed reinforcement learning to improve Watanabe and Reindl models for a target location. For learning, measured solar diffuse irradiance data only for two weeks were required when existing models were employed. Results showed that the proposed model reduced the prediction error compared to the prediction case with existing models. Such an increase in the accuracy was apparent when the proposed method was applied to a relatively inaccurate decomposition model such as the Watanabe model, showing an error reduction by 40%. This was obtained by simple two weeks reinforcement learning for predicting solar diffuse irradiance over one year.
Redirection Masking Strategies: Understanding Attentional Diversion Methods for Redirection Techniques

Imagine you can explore virtual space just by regular walking, even if you are in the very confined tracking space of your living or bedroom. Redirection techniques aim to overcome physical space limitations and enhance capabilities for natural motion when exploring large-scale virtual environments, improving the sense of presence. Techniques include the covert manipulation of user position or rotation to altering the geometry of a virtual environment. Several methods are used to mask redirection techniques, such as the obstruction of view of a user, to using visual or auditory elements to divert the attention of users away from the redirection technique. One recurring masking strategy is the utilisation of a distractor, which attracts user attention by a visual or auditory object, or interactors, an object which engages the user in a series of focused interactions. We provide a simple framework to categorise various masking strategies, to create a general understanding of the usage and implementation of these masking techniques. To validate and demonstrate the usefulness of this framework, we map it against a collection of papers that use masking strategies in different contexts. We identify the types of masking strategies and provide a generalised implementation outline. This provides further insight and understanding of the inner workings of these attentional diversion methods.
Peer-to-Peer Ridesharing Using Blockchain

Ridesharing has been a popular concept since the advent of vehicular transport and could save a lot of gas, reduce environmental impact, increase social bonding between passengers, reduce traffic jams, etc. The major players in today’s market are central authorities controlling all aspects of the experience from, what cab should be sent to you and how much to charge. This poses a risk for the end users who rely on the central authority. Blockchain is an effective measure against the pitfalls of the traditional central authority. Our application makes use of the advantages of a peer-to-peer system which is enhanced by the security of blockchain. We have created a system where the data lies as immutable ledgers within each node of the p2p network. Each node in the network plays a part in approving the latest ledger, validating it and adding the ledger to the main chain. We have also taken a note of the gas prices that are associated with each transaction and its variations.
Security and Privacy Guidelines for IT Operations Under Pandemics and Epidemics

Deteriorating health conditions under a pandemic force governments and authorities to consider enforcing lockdown protocols to limit the spread of a disease. Once a lockdown protocol is enforced, many verticals are instantly impacted by the lack of available workforce and other issues. Critical infrastructures, information systems, integrated IT systems cannot be administered using existing guidelines/standards under a pandemic. Thus organizations, governments, enterprises, and economies are ill equipped to deal with IT and economic issues emerging as a result of a pandemic. This chapter explores the impact of the COVID-19 pandemic on IT systems, IT operations, and security. This chapter calls attention to the lack of preparedness, absence of standards and protocols that deal with epidemics and pandemics. Thus, considering the changing organizational posture, this chapter brings to light opportunities for redressal, and recommendations have been made to ensure better preparation in the future.
Importance of Offline Access Skills for Students in the Digital Era

Accessing information in the library can be done through the library space and institutional repository. Therefore, both online and offline access skills are indispensable for students. This study aims to determine the correlation between students’ access skills and their intention to access information in the quantitative research method, using the SmartPLS application version 3. The studied samples are 93 students of UIN Saizu who currently sit in semesters 8 and 10 with a repository account. Results show that offline access skills affect students’ intentions to access information both in the physical space and in the repository. On the other hand, online access skills affect the intensity of accessing the repository but do not significantly affect the intention of visiting the library space. Therefore, skills to explore physical materials and gain information through it are negatively correlated with their intention to access the library. This suggested that offine access skills are indispensable for UIN Saizu’s students.
Use of Web Based Resources Among the Social Sciences Faculty and Researchers in the Universities of Punjab and Chandigarh

This study is focused to assess the awareness and use of web-based resources among the social sciences faculty and researchers of select three universities from Panjab and Chandigarh namely Punjabi University, Patiala, Panjab University, Chandigarh and Guru Nanak Dev University, Amritsar. A survey method was used to collect the primary data from the sample of 532 respondents including faculty and researchers from the total population of 1061 including 08 departments of Social Sciences in three universities. The proportionate random sampling method was used to select the sample. The data were collected through structured questionnaire and further analysed using SPSS. Chi-square test and mean based ranking was used to analyse the data. The study reveals that most of the social sciences faculty and researchers were aware and use web resources to some extent but, significant difference was found between them. The study concludes that the majority of the social sciences faculty and researchers are satisfied with web resources for their academic and research work.
Digital Souls: A Philosophy of Online Death

"Digital Souls: A Philosophy of Online Death." Australasian Journal of Philosophy, ahead-of-print(ahead-of-print), p. 1
Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach

This paper proposes a hybrid approach to design and implement query spelling error detection and correction (SEDC) for Tigrigna information retrieval (IR). Our approach, which is the main contribution to this work, is fast and robust to achieve better performance and also helps the users to easily insert their corrected queries to retrieve relevant information from the IR. This is achieved by combining the normalized measure of bigram overlap using the Jaccard coefficient (J.C) technique, a dynamic programming algorithm for edit distance, and probability of occurrence, which were used to make suggestions for the misspelt words. Our approach was evaluated on the SEDC subtasks separately. It achieved an F-measure of 98.85% on the spelling error detection subtask and an accuracy of 95.36% on the spelling error correction subtask. Thus, a comparison was conducted between our approach and the existing Tigrigna spell checker. It is found that our approach outperformed the existing spell checker and shows a 5.36% improvement in accuracy. This is by far the most promising result with regard to correcting the misspelt users’ queries and improving the overall performance of the IR.
Systematic Literature Survey on Sign Language Recognition Systems

Recently, communication via signing acknowledgment has received a lot of attention in personal computer vision. Sign language is a method of conveying messages by using the hand, arm, body, and face to convey considerations and implications. Communication through gestures, like communication in languages, arises and develops naturally within hearing-impaired networks. All the same, gesture-based communication is uncommon. There is no universally perceived and accepted gesture-based communication for all deaf and hard-of-hearing people. Each nation has its own communication via gestures with a significant level of syntactic variety, just as it does when communicating in language. The gesture-based communication utilized is usually known as sign language.
Promoting gender – Equitable agricultural value chains: the role of corporate social responsibility in Nigeria's Niger Delta

Purpose The purpose of this paper is to critically examine the multinational oil companies' (MOC) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to investigate the impact of the global memorandum of understanding (GMoU) on promoting gender-equitable agricultural value chains in the Niger Delta region. Design/methodology/approach This paper adopts a quasi-experimental design that used survey research technique, aimed at gathering information from a representative sample of the population, as it is essentially cross-sectional, describing and interpreting the current situation. A total of 760 rural women (380 from the treatment group and another 380 from the control group) were sampled across the Niger Delta region. Findings The results from the use of a combination of a logit model and propensity score matching indicate a significant relationship between GMoU model and gender-equitable agricultural value chains in the Niger Delta, Nigeria. Research limitations/implications This study implies that CSR of MOCs is a critical factor in the need to integrating gender into agricultural value chains, achieving the goal of increasing agricultural growth and expanding the stable food supply. Originality/value This research contributes to gender debate in agricultural value chains from a CSR perspective in developing countries and rationale for demands for social projects by host communities. It concludes that business has an obligation to help in solving problems of public concern.
Label Metric for Multi-Class Multi-Target Tracking under Hierarchical Multilevel Classification

Aiming at multiple quantities and types of targets, multi-class multi-target tracking usually faces not only cardinality errors, but also mis-classification problems. Considering its performance evaluation, the traditional optimal subpattern assignment (OSPA) method tends to calculate a separate metric for each class of targets, or introduce other indexes such as the classification error rate, which decreases the value of OSPA as a comprehensive single metric. This paper proposed a hierarchical multi-level class label for multi-class multi-target tracking under hierarchical multilevel classification, which can synthetically measure the state errors, cardinality error, and mis-classification. The hierarchical multi-level class label is introduced as an attached label to finite sets based on the hierarchical tree-structured categorization. A Wasserstein distance type metric then can be defined among the distribution represented by any two labels. The proposed label metric is a mathematic metric, and its advantages are illustrated by examples in several cases.
Session Recommendation Based on Edge Information Clustering

Traditional session recommendation mainly uses the time sequence of users clicking items to construct a user session graph, which often ignores the similarity and differences between user groups. To improve the effect of recommendation, an E-SGNN (E-SGNN, Edge-Session Graph Neural Network) method combining edge information clustering and session recommendation is proposed. Firstly, similar users are clustered by edge information and divided into different session user groups. After extracting the data features of the user site relationship graph in the session, it is reset and updated through the gated graph neural network (GGNN); Secondly, a self-attention mechanism is introduced to adjust the proportion of users’ current preference and historical preference; Finally, the ranking score is obtained through linear transformation and softmax classifier. The higher the score, the more obvious the user’s preference for the item. Experiments show that compared with session-based graph neural network and cross-session information recommendation, the E-SGNN algorithm proposed in this paper has a significant improvement in recall rate and average reciprocal ranking. When the three edge parameters are combined, the recall rate reaches 98.97% and the average reciprocal ranking reaches 45.77%.
RETRACTED: Psychological and pedagogical preparation of the future teacher for the development of dialogical speech of primary school children

The relevance of the research is due to the fact that in modern education there is a growing need for training qualified teachers who are capable of organising dialogical training of younger schoolchildren. In this regard, this article is aimed at identifying and diagnosing aspects and features of the psychological and pedagogical training of future teachers who will teach children dialogic communication and develop in them the need for intercommunication. The leading methods of studying this problem are induction, deduction, comparison, and analysis, which will facilitate determining the features and traits of psychological and pedagogical preparation of future teachers for professional activity, presenting the results of their readiness to develop components of speech competence in younger schoolchildren. The article covers and substantiates the ways of development of communicative skills in younger schoolchildren during the learning process, which should be used by the teacher effectively. The materials of the article are of practical value for students, teachers who should be ready to teach dialogical speech to future generations, develop communication and conversational skills to meet the requirements of the education system and shape a personality that can freely fulfil its potential in all spheres of life.