Reviewerly/exHarmony huggingface dataset:
Why do Energy Subsurface Organisations Need Digital Transformation?

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.
Tripolar Fuzzy Ideals of a Near Algebra

We present the idea of tripolar fuzzy ideals of a near algebra based on the theory of tripolar fuzzy sets. It is a generalisation of fuzzy set, bipolar fuzzy set, intuitionistic fuzzy set, fuzzy ideals. We also discuss some of its properties.
Analysis techniques of autonomy framework metrics for autonomous developers

As autonomous systems proliferate, empirical measurement of their fitness is paramount. Several frameworks have been developed that provide guidance on what should be measured. However, these frameworks require users to develop their own metrics. Additionally, these frameworks focus on the autonomous systems rather than the enablers. An enabler could be the process used by developers. This research introduces novel techniques to analyze metrics used to measure fitness of autonomy architectures for developers. Crucially, this will be generalizable across autonomy measurement frameworks. The results are new techniques acquisition professionals can use to help better make tradeoffs development-wise for different architectures.
STRUCTURING THE CONTENT OF EDUCATION AS A CONDITION FOR IMPROVED TRAINING FUTURE TEACHER IN HIGHER SCHOOL

The structuring of the contents of education is oriented on the unity, coordination and presentation of educational information. It helps to organize the process of education on higher-level quality. The technology of structuring of contents of education includes: of definition of the contentional, operational, practical, supplementary, enlarging and control elements of education. The structuring gives the possibility to work out the model programmed of educational course on the basis of which every student can work out individual programmer of educational activity. It enables the student to work according to his intentions ad possibilities, to study on the basic level, to provide self-development and training of the future specialist.
A Use of Variety as a Law of the Universe

This paper explores the idea of a toy model universe as a character string where each character is either X or -. The string makes a transition between states that are of maximal variety. The definition of variety given by Barbour and Smolin is used in this paper. An interpretation of the toy model universe is given in terms of Everett’s many-worlds interpretation. The paper also discusses whether new maximal variety strings can be obtained by addition or subtraction of maximal variety strings. A few comments are included about the use of quantum computers, which may help find the maximal variety strings more quickly.
On-Line Big Data Processing Using Python Libraries for Multiple Linear Regression in Complex Environment

The phenomenon called Big Data today is one of the most significant and least visible consequences of the development of technology and the Internet. Namely, the data generated by today's globally connected world is growing at an exponential rate and they are a real "gold mine" for those users who know how to correctly interpret such data and make successful decisions based on them. Data analysis and processing is one of the most important components of a large data system, and in this branch of data science the most popular is the Python programming language, which provides its users with a large number of constantly maintained program libraries and developing environments. The most important thing for legal entities and individuals is that almost all program libraries and functions provided by this programming language come with free licenses and possess open code, maintained and quality technical documentation, which provides each company with significant money savings and time. This research paper is dedicated to the possibility of determining and creating a multi regression model of large amounts of data by using Python, on the basis of large amounts of data provided by two market retailers in order to display a multi regression model and assess its predictive power. Because the number of variables is large, several models have been made in this research paper and a comparative analysis of the different models has been made, which shows that Python is a good tool that can be used repeatedly to select different variants and evaluate the resulting model for which a graphical interface can be made and would be much more acceptable as an end user, can be placed on a server on the Internet or on a modern Cloud platform and used by users as an on-demand concept and the results can be embedded in end-user interfaces and models made in this way (with dynamic data extraction)can be used in BI and machine learning processes.
The Sensuality of Low Frequency Sound

This chapter will examine musical works that feature electronically produced low frequency sound to create unique, sensuous responses in listeners. How these sounds and related concepts are rendered and received is discussed in the works of three artists working across music performance, installation, and composition: Thembi Soddell (Australia), Marina Rosenfeld (United States of America) and myself (Australia). The distinctive and unique approach to employing low frequency sound by each of us is framed as a way to extend the listening experience toward a more physical and embodied experience for audiences. The engagement of very low frequency (VLF) sound in the works is discussed from compositional, performative, and reception perspectives. A brief overview of the experience of VLF in music is followed by a claim for its sensuous nature, and the range of theoretical approaches to engaging VLF are discussed, informing the subsequent discussion of exemplar works.
USE OF INTERACTIVE METHODS TRAINING IN PREPARING FUTURE TEACHERS FOR PEDAGOGICAL INTERACTION WITH STUDENTS

In article the approaches to students' preparing to the pedagogical co-operation with pupils have been considered. Theeffectiveness of using interactive methods and ways of professionally significant features of future teachers forming process.
Profile of Electronic and Digital Media Learning Implementation During 2018-2022

This research aims to describe and analyze the implementation of digital and electronic media as learning media during the COVID-19 pandemic. This research is a qualitative research using a literacy study method based on articles and books relevant to the implementation of digital and electronic learning media in Indonesia in the period 2018-2022. As for analyzing research data, the author uses inductive thinking methods. This method brings together various information from previous research related to the use of digital and electronic media as learning media during the COVID-19 pandemic. to be generalized into a new idea whose validity can be justified. Based on the results of a study of 20 articles from previous research, it can be seen that research on digital and electronic media as learning media in 2018-2022 contains development and application during the Covid-19 pandemic. The types and methods of research carried out varied including research and development, qualitative, quantitative, and literature review research. The development and application of digital and electronic media has proven to be still not fully effective in the learning process during this pandemic, the difficulty of internet access is still an obstacle for several studies. However, there are also many studies that show that the use of digital and electronic media in the learning process is considered effective, interesting and easily accessible to students wherever and whenever.
MACROSCOPIC ONSITE EVALUATION (MOSE) CAN SOLVE THE “ISSUE OF THE TISSUE” FOR ACQUISITION OF EUS-GUIDED FINE-NEEDLE BIOPSY SPECIMENS: A SYSTEMATIC REVIEW &amp; METAANALYSIS

Hemant Goyal: YES financial relationship with a commercial interest;Aimloxy LLC.:Consulting | Sonali Sachdeva: NO financial relationship with a commercial interest | Abhilash Perisetti: NO financial relationship with a commercial interest | Saurabh Chandan: NO financial relationship with a commercial interest | Muhammad Aziz: NO financial relationship with a commercial interest | Dushyant Dahiya: NO financial relationship with a commercial interest | Jay Bapaye: NO financial relationship with a commercial interest | Neil Sharma: YES financial relationship with a commercial interest;Boston Scoentific :Consulting;medtronic Consulting;mauna kea:Consulting;steris :Consulting | Nirav Thosani: YES financial relationship with a commercial interest;Boston Scientific :Consulting;Pentax America:Consulting;ROSEAId:Other Activities Not in List (use freeform entry below);UpTpDate:Other Activities Not in List (use freeform entry below);Abbvie:Speaking and Teaching
Development of Innovative Entrepreneurial Talent Training Model in Regional Economy Based on Big Data Analysis

<p style="text-align: justify;"><span style="font-size:16px;font-family: 'Times New Roman','serif'">With the rapid development and replacement of various high and new technologies, it has become a consensus to use big data (BD) technology in the exploration of talent training mode. Analyzing the characteristics of regional economy, establishing the talent training direction with innovative thinking, upgrading the education mode, and forming a multi-mode combination of BD processing practice teaching mode. Mastering Internet means and information technology has become an essential skill of current talent cultivation. As high-end talents, innovation and entrepreneurship (IAE) ability is an important skill that can greatly improve productivity. This paper explores the necessity of BD analysis of IAE Talent Training Mode in regional economy, and studies the specific training strategy in detail. This paper uses BD to collect the relevant data of the impact of IAE talents on regional economy, and uses the commonly used data visualization software Excel to generate charts, so as to explore the development of IAE talents training mode in regional economy. And in-depth explore the development countermeasures of innovative talents training mode in the regional economy.</span>
COVID-19

The SARS-CoV-19 coronavirus pandemic has had a huge economic impact around the world. As a result, the behaviour of all financial instruments, including cryptocurrencies, was significantly affected. Following the COVID-19 market crash, cryptocurrency derivative markets have seen a massive increase in popularity as speculators try to profit from the price and trading volume instability. The fluctuations in the virtual currency market during this time span seem to be a reflection of shifts in other capital and commodity markets. During this challenging era, the demand has remained relatively stable. It's yet another example of how cryptocurrencies can be viewed as a fully developed financial tool. Despite mediocre trade volume, the number of markets available increased significantly in the run-up to this case.
Contact Tracing during COVID-19 - A Systemic Public Health Failure

Coronavirus-19 (COVID-19) created many challenges for public health agencies and healthcare services. As a virus that created immense fear of the unknown, researchers and scientists scrambled to come up with solutions to prevent the spread and rate of infection. As previously used in combating infectious diseases, contact tracing was introduced to help decrease the rapidly increasing cases. Although contact tracing is a relatively old idea, it is still a critical part of the non-pharmaceutical interventions needed to fight such an infectious virus. However, it had to be tailored to fit this new rapidly increasing virus. This paper examines the disparities, insufficient infrastructure, and lack of proper testing and reporting during the pandemic, all of which are systemic failures of public health. These systemic failures have an impact on the effectiveness of contact tracing. All barriers will be presented with potential solutions for not only this pandemic, but for any future situations as well.
Improving cybersecurity through deep learning on keystroke and mouse dynamics

Username, password, and biometrics are three-factor authentication for cybersecurity enhancement. Adding keystroke and mouse biometrics to authentication will definitely improves the cybersecurity. Keystroke dynamics refers to the process of measuring and assessing human’s typing rhythm on digital devices. Keystroke timing information such as digraph, dwell time and flight time are used in our experimental datasets. Mouse dynamics records mouse motion (speed), left-, right-, or double-clicking timing information. Our own dataset includes both types of dynamics from same group of subjects. We develop recurrent neural network (RNN) models and support vector machine (SVM) models to represent user’s biometrics. Keystroke and mouse dynamics can be used as features fed to the models separately for user verification or identification. Feature fusion is applied to improve the accuracy. Our results show the RNN method is better than traditional methods like SVM, and fusion can further improve the performance.
Network Traffic Classification Model using Voting Method

The network is analyzed manually or some fixed abnormal patterns are given in the system in case of traditional model such that an attack present in the system can be identified. Lately, the traffic on network is improved by the use of internet and the threats of attacking are identified since the policy can be accessed easily. Thus, the network analyst can improve the data through these activities and detecting the intrusions becomes difficult. The network traffic classification has various phases in which dataset can be proposed for the elimination of missing and redundant values from the dataset. The Support Vector Machine classier is applied in the existing methodology for the network traffic classification. The voting classification is implemented in this research work for the network traffic classification. The performance is analyzed with regard to accuracy, precision and recall. It is analyzed that voting classification gives high performance as compared to SVM classifier.
THE PROBLEM OF STRUCTURING PEDAGOGICAL KNOWLEDGE IN THE SYSTEM PROFESSIONAL TRAINING OF THE FUTURE FOREIGN LANGUAGE TEACHERS

This article observes a problem of formation person's individuality by means of course - Pedagogical Creative work
Cloud Load Balancing using Meta-Heuristics

When provided as a service, Cloud Computing (CC) makes it possible to access dynamically scalable and regularly virtualized resources through the Internet. It is hoped that this research will contribute to the disciplines of load balancing and task scheduling by understanding the concept of load balancing in cloud computing through the use of a simulator known as "CloudSim." In this research, it was found that, one of the most significant challenges in cloud computing is load balancing. This prevents scenarios in which some nodes are heavily loaded while others are idle or performing limited work. Load balancing (LB) spreads the dynamic local workload evenly among all the nodes in the cloud. The most important decision to make is the sort of program to run on the available system in order to maximise resource utilisation. Scheduling is the process of allocating a job to the resources that can complete it in the Cloud Computing environment.A heuristic is a strategy that may be used to solve issues rapidly. It is vital to have efficient and effective scheduling procedures in place in order to make full use of the large array of cloud computing possibilities. As a consequence of this investigation, a novel scheduling algorithm is introduced that is derived from two old approaches, Min-min and Max-min, and is designed to capitalise on their advantages while eliminating their disadvantages. The parameters are then evaluated by the CloudSim simulator. There are high-level techniques that function as the driving force behind a problem-specific heuristic known as Meta-Heuristics. A New Meta-Heuristic methodology has been developed by investigating and analysing previously developed processes. The primary purpose is to avoid the drawbacks of iterative improvement, particularly descents, by allowing the local search to escape local optima while doing local searches. One technique to accomplish this is to provide more "intelligent" possibilities to the local search engine rather than random initial responses as a way to assist it. The proposed meta-heuristic model is evaluated using CloudSim and the advantages of two existing techniques, Particle Swarm Optimisation and Genetic Algorithm with the results of several simulations.
USE OF AUGMENTED REALITY IN AUTOMOTIVE PROTOTYPING

Augmented reality (AR) is a technique to enhance the knowledge about an object. This knowledge is in digital format and available on handy gadgets. On the need basis anyone, anywhere, any object information can be obtained within no time using AR technique. This way one may not require expert physical presence to know about any object. This technique is being very well used in many areas like education, medical, aerospace etc. This technique can be extended in manufacturing process also. One important manufacturing process is the vehicle conversion through automotive proto building, where many parts are to undergo changes. This work require expert presence and his knowledge for assembly and disassembly sequence, appropriate tool usage, correct applications of force and torque, correct parts and their fitment. All these requirements are met with in lieu of time and money in terms of expert presence and manual convey of knowledge. All the above requirements can be addressed through application of digital capability of modern world and one of the application is Augmented Reality (AR) in virtual prototyping. This paper discusses about usage of AR technique in making automotive virtual prototype. The virtual prototype is a handy knowledge bank which help technicians and engineers to perform their job without anyone help &amp; hence save money, reduces turnaround time and avoid errors in the process.
Accelerating Deformable Convolution Networks

We propose an accelerator design for Deformable Convolution Network inference. Our design is hybrid of hardware pipelining and hardware re-use. (1) Hardware pipelining hide the offset sampling overhead and uses abundant HBM channels to support high throughput, while (2) hardware re-use ensures scalability to very deep networks. Based on our design paradigm, we develop a polynomial-time 2-step design space exploration (DSE) engine to optimize the tradeoff between (1) and (2) to realize high hardware utilization. We implement our design using HLS on the Alveo U280 FPGA board targeting deformable ResNet-50. Our DSE leads to ∼90% effective hardware utilization, and our design achieves up to 17 (2.2) times higher throughput compared with CPU (GPU) baselines.
Online Teaching Quality Analysis using Learners Feedback

Abstract: From scientific study it is proved that analyzing anything based on the data,facts,issues,problems helps in finding various problems,issues and things that needs to be changed so that the system or the outcome of the result that we want can be up to the mark.These analysis works as an important tool in maintaining the standards and quality of the outcome. Analysis in any field helps in getting insights of that particular filed. These analysis include the deep and thorough information of any thing that needs to be analyzed. The same method can also be used for the analysis of the online teaching quality that is being followed by most of the institutions, and colleges these days due to the pandemic outbreak ,so that students can attend classes in online mode while they are in their home being healthy and safe. Since there are large number of students and they have various subjects and teachers allotted to them, there can be various issues that a student can face while having their online classes. To tackle this what we can do is to make an online system that can collect the feedback of the students in each and every subject with the respective teacher. Through this online system it will be easier for the students to share their problems without any hesitation and difficulty. All these feedback’s then can be used and analyzed to solve each issues and problems faced by the students. This paper deals with the problem of feedback of students regarding their online teaching and presents an online teaching quality feedback system and its importance in improving the quality of teaching. Thus it is clearly visible that online teaching quality feedback system have the ability to improve the quality teaching and learning. Keywords: Online Teaching, Quality Analysis, Learner's Feedback
Imbibing Auxiliary Information Using Transfer Learning to Improve Collaborative Filtering-Based Recommender System

The available data on the Internet can be utilized to obtain valuable information on any given subject. But the data is massive and intricate, which produces many problems for users in finding information of their interests. Recommender Systems (RSs) are successful software techniques designed to solve this issue. The RSs have a broad range of uses, such as providing consumers with a suggested list of products for online shopping, recommending articles or books for reading online, film or music recommendations, media recommendations, and so on. The traditional Collaborative Filtering (CF) recommender systems use different item ratings as a foundation to recommend new items to various users. The sparsity of this user-item matrix affects the performance of RS. Also, most consumers on today's e-commerce websites would not purchase a product that they do not find appealing, even though it has especially favorable feedback. As a result, we can say that consumers give equal importance to product images and the item's ratings. This paper aims to research to improve the traditional collaborative filtering recommender system by imbibing visual characteristics with explicit feedback (ratings). The visual features are extracted using transfer learning with the convolutional neural network (CNN). The amazon product dataset for clothing, shoes, and jewelry is used to validate the proposed approach. The results are compared using standard evaluation measures like MAE and RMSE.
Implementation of IoT for disease detection and prevention

An irresistible sort of infection influences countless people. A ton of examination being Led all through world. There are numerous intelligent equipment stage bundles like IoT in counting brilliant following, shrewd sensors, and clinical gadget reconciliation accessible on lookout. Arising innovation like IoT has a remarkable capacity towards hold patients secure and restorative and furthermore upgrade how doctors supply care. Medical care IoT additionally can reinforce impacted individual pride by allowing patients towards invest more energy cooperating with their clinical specialists because of reality docs aren't as taken with ordinary and repetition parts of their vocation. most impressive benefit towards IoT in medical care is that it upholds specialists in endeavor extra huge clinical work in a calling that as of now is encountering an overall expert difficult work lack. This paper researches premise investigation of relevance of IoT in medical care System.