Reviewerly/exHarmony huggingface dataset:
Concept Summarization of Uncertain Categorical Data Streams Based on Cluster Ensemble Approach

Summarizing data into unrealistic or unsafe information flows is an essential idea in social information sources. The extraordinary information on assessing the flow of insecure information with the re-bound of information flow situations were analyzed. Typically, the idea of summary approach to learning a class was known to characterize the comparison case and then develop the uncertain class classifier (UOCC) functionally using a class schema. This technique based on the thickness of the system part to produce an imaginable score to obtain each property with the maintenance of practical information. The UOCC also offers a representation of the support vector (SV) to the synopsis depending on the client’s inclinations and the client’s need to save the source of the information. A conceivable score was produced based on reporting occasions. It is overlooked to search for information that depends on information properties (attributes) to use occurrences of information with many social information indexes. Therefore, in this article, a group ensemble approach (CEA) is proposed to characterize the information synthesis, narratives of customer groups, and the investigation of information within questionable information streams. CEA features a grid for building unidentified records into groups (dubious) and reliable information streams with ownership splitting and highlighting options. The exploratory outcomes show a useful data outline with a uniform review of client data with their overview accounts of faulty data streams after some time and different variables.
POETRY OF VELIMIR KHLEBNIKOV IN THE WORKS OF THE BAND “AUKTYON”. ON THE EXAMPLE OF THE ALBUM “ZHILETS VERSHIN”

The article establishes and for the first time describes in detail the dialogue relationship of the Leningrad rock band “Auktyon” and the avantgarde poet Aleksei Khvostenko (1940–2004) with the poetic heritage of Velimir Khlebnikov (1885–1922). The author notes the closeness of the poetry of a major figure of the Russian avant-garde of the turn of the 19th and 20th centuries with the poets and musicians of the underground of the second half of the 20th century. The research is based on the analysis of the reception of Velimir Khlebnikov’s poetry in the album “Zhilets vershin” (The summits dweller) (1995). The author defines the levels of the poetic dialogue of rock musicians with the work of the futurist and describes the structural and informative changes that the original texts have undergone in comparison with their existence in the musical creativity of the band “Auktyon”. The formation of the album in rock culture determines the specifics of the dialogue, mainly it is the correlation of the texts of other poets in the album and their transformation. The group of Khlebnikov’s lyrical works, which were selected and reworked by Khvostenko for the album, are considered from the point of view of their chronological sequence and the deployment of the lyrical plot. The author identifies the changes that the original texts have undergone and analyzed such cycle-forming connections of the album “Zhilets vershin” as the composition, title and chronotope.
Random Numbers and Simulation

A random number or a random variable is a result of a random process where the result is not deterministic. We can only know the exact value of the variable a posteriori, meaning after the fact. For example, the next roll of a dice is random. We only know the face after we roll it. A coin toss is also random. We only know the fact after it happens. Another way of looking at a random variable is looking at what information it reveals. For example, while the test score of a student in a class is already fixed, it is random because it is unknown or uncertain to us before we look at it. We only know the test score after the information becomes available. Many applications and physical phenomena are therefore random either because of their nature, uncertainty, or unavailable information. The study of random numbers is central to statistics.
ACTIVE TEACHING METHODS IN THE DEVELOPMENT OF UNIVERSITY STUDENTS’ CIVIC ENGAGEMENT

The authors consider the issue of civic engagement among students as one of the significant tasks of studying at university. In modern society, thanks to information technologies, the number of possibilities to manipulate public and individual consciousness, to involve young people in protest actions including illegal activities has increased significantly. Studying at university should contribute not only to the development of professional competencies, but also to the development of active civic engagement among students, since it is the youth who is responsible for the future of our country. As an example of solving an education problem, the authors present a training module on philosophy applying active teaching methods when studying the topic “Russia - West - East in the dialogue of cultures”.
Preface

About NCAIEV’21, Department of Science and Technology (DST) sponsored National Virtual Conference on Advanced Informatics, Electronics and Vision (NCAIEV’ 21) was organized on 23 rd April, 2021 in connection with the funded Science Equity and Empowerment Division (SEED) - Science and Technology (S&amp;T) for Women project in the department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering Technology (MCET), Pollachi, Tamilnadu, India. A one day National Virtual Conference on Advanced Informatics, Electronics and Vision (NCAIEV’ 21) has been organized to focus on the recent R&amp;D activities, to provide the knowledge on research cues and to possess a network with eminent academicians and industrialists. NCAIEV’ 21 was carried out in the form of virtual conference due to the impact of COVID-19 through MS-Teams. This conference has been organized from the funded project with the aim to continue disseminating the latest advanced research in the field of Advanced Informatics, Electronics and knowledge sharing among researchers. Also this conference provided an opportunity to the young budding researchers to show up their innovative ideas through the special event – Idea Contest on Smart systems. List of Committee of NCAIEV’21 are available in this pdf.
Adaptive Moment Estimator (Adam) Optimizer in ITK v3

This document describes an ITK class implementing an Adaptive Moment Estimator (Adam) optimizer algorithm within the Insight Toolkit ITK www.itk.org. Adam is an adaptive gradient descent optimizer, which independently adaptively estimates the gradient descent step for each parameter, at each iteration, based on stored past gradients. The optimizer stores exponentially decaying averages of past gradients to estimate first moment (the mean) and the second moment (the variance) of the gradients to formulate update rule for present iteration. The Adam optimizer compares favorably to other adaptive learning-method algorithms, converges faster, and is robust to saddle point. This paper is accompanied with the source code, input data, parameters and output data that the authors used for validating the algorithm described in this paper.
Isochronous Gaussian Sampling and its applying to the Falcon Signature Scheme

This paper describes a block framework for generating discrete Gaussian components with arbitrary center and standard deviation. Simplicity makes it easy to implement secure, portable, effective, and time-resistant. This sampler is a good candidate for any sample analysis. Most importantly, it was recently introduced into the Falcon Signature Scheme. Gaussian sampling over integers is a central element of algebraic lattice cryptography, which is difficult to perform efficiently and safely. Given the vast number of uses of sampling processes, it is important to select Gaussian samplers that are effective provably secure, resistant to transient attacks, and generally easy to implement. Sampling with other distributions, other than Gaussian, is yet an open question.
Qualitative and Quantitative Investigation of Bio Tissues using Microscopy and Data Mining

&lt;div&gt;The effects of glucose and salt on white blood cells, red blood cells, and&lt;/div&gt;&lt;div&gt;platelets (PLTs) in the blood of a leukemic patient by using a white light microscope&lt;/div&gt;&lt;div&gt;have been investigated for different concentrations (0 mM to 500 mM) of glucose and&lt;/div&gt;&lt;div&gt;salt. It has been revealed that the shape of erythrocytes, leukocytes, and platelets&lt;/div&gt;&lt;div&gt;changes and forms aggregates. Increasing the concentration of sodium chloride causes&lt;/div&gt;&lt;div&gt;an increase in the rouleaux formation and aggregation of platelets. The comparison of&lt;/div&gt;&lt;div&gt;CBC reports of these samples with and without analytes shows that total leukocyte&lt;/div&gt;&lt;div&gt;count (TLC) decreases gradually towards normal ranges of leukocytes, which is&lt;/div&gt;&lt;div&gt;favorable in the treatment of leukemia; at the same time, decreased level of hemoglobin&lt;/div&gt;&lt;div&gt;HGB, mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin&lt;/div&gt;&lt;div&gt;concentration (MCHC) and increased level of red blood cell (RBCs) causes a reduction&lt;/div&gt;&lt;div&gt;in the oxygen supply, which is in favor of cancer growth and anemia.&lt;br&gt;&lt;br&gt;&lt;/div&gt;&lt;div&gt;In the second set of work, a computer-aided system was planned for automatic&lt;/div&gt;&lt;div&gt;classification of ultrasound kidney diseases and ultrasound liver (i.e., cirrhosis). Two&lt;/div&gt;&lt;div&gt;types of images were considered normal and chronic. By using the data mining&lt;/div&gt;&lt;div&gt;technique, the statistical features were extracted to differentiate between normal and&lt;/div&gt;&lt;div&gt;abnormal ultrasonic kidney images. By using feature extraction software (FES), a set of&lt;/div&gt;&lt;div&gt;statistical features were extracted from the region of interest of each image at different&lt;/div&gt;&lt;div&gt;frame rates. The data sets which were obtained using FES at different frame rates were&lt;/div&gt;&lt;div&gt;then classified by using Weka. These extracted feature results were classified by using&lt;/div&gt;&lt;div&gt;Weka and a 96.5% correct classification rate was obtained. The difference between the&lt;/div&gt;&lt;div&gt;values of these features was useful to identify between normal and abnormal images.&lt;/div&gt;
Intelligent Code Completion

Auto complete suggestions for IDEs are widely used and often extremely helpful for inexperienced and expert developers alike. This paper proposes and illustrates an intelligent code completion system using an LSTM based Seq2Seq model that can be used in concert with traditional methods (Such as static analysis, prefix filtering, and tries) to increase the effectiveness of auto complete suggestions and help accelerate coding.
Why do people apply for admission to Moscow universities? An analysis of the reasons and development of recommendations

When there is high competition between universities for applicants, research into the applicants’ motives becomes relevant. This research used a survey questionnaire, the results of which were subjected to correlation analysis. The survey involved students from four Moscow universities, differing in both rating and quality of admission. The main reasons why applicants choose their university were the availability of budget places and the cost of training. The source of information about the university is also important. Modern youth (and also their parents) focus mainly on Internet sites for applicants and on the university’s website social networks. The role of Internet resources will only increase in the future although traditional forms of attracting applicants, such as open days and Olympics should not be discounted. They attract at least a quarter of the admissions. The research revealed that school graduates who are strongly oriented toward higher education prepare for exams very seriously. More than two-thirds of all students surveyed noted several options for preparing for the exam. However, not all applications had a solid life position with regard to their future profession. Many have chosen those courses that are easier to pass. One of the important factors in making a choice and in preparation is the image of the university. The higher the rating of the university, the more motivated applicants it attracts and as a result, the level of training of graduates also increases. It is proposed that distance forms of participation in university events are developed so as to expand coverage.
Foreword to the special section on motion, interaction, and games 2020

• Selection of best papers from ACM SIGGRAPH MIG 2020. • Artist-guided, high-resolution facial texture generation system. • Extreme density crowd simulation using SPH. • Systematic investigation of the relative perceptual importance of blendshapes.
Development of higher education in Russian regions

Study was devoted to the assessment of indicators characterizing the number and structure of research and teaching staff at universities and other institutions of higher education in the regions of Russia. These indicators were the number of teachers working in higher education, per thousand residents and per hundred students, proportion of professors and associate professors in the whole number of teachers. Research used official statistical information for 82 regions of Russia. We used density functions of normal distribution as models. Study showed that on average, there was a little more than one teacher working in higher education organizations per thousand residents. It is proved that on average, every seventh teacher in all regions held the position of professor. Approximately two-thirds of all teachers held associate professor positions, there were five teachers per one hundred students.
Parallel Feature Selection Approaches for High Dimensional Data: A Survey

The feature selection task represents an essential phase in machine learning that is time-consuming and requires significant computational resources, especially when considering current increasing trends in terms of data volume. To overcome these constraints, parallel computing models are adopted to reduce the computational time of these approaches while achieving promising results in classification performance. Although several studies reviewed feature selection methods, none of them provided a detailed classification of feature selection methods and viewed existing parallel and distributed feature selection methods. In this paper, we survey different categories of feature selection approaches. Then we present parallel computing paradigm, its models, its libraries, frameworks, and parallel feature selection methods. We also provide an in-depth analysis of their experimental results according to sequential versions of these algorithms. Finally, future issues and direction research are exposed.
Semantic Parsing with Syntax Graph of Logical Forms

Semantic parsing aims to convert natural language queries to logical forms, which are strictly structured. Recently neural semantic parsers have paid attention to structure information of target logical forms and set constraints on generating rules. In this work, we propose to use syntax graphs of both query and logical form and to utilize graph neural networks (GNN) in encoder combined with BERT pre-training and decoder with copy mechanism. Besides, we present a predicate review loss function to help GNNs in the decoder capture the syntax graph structure more precisely. Results of experiments on three datasets show that our model outperforms the baseline on MSParS, achieves state-of-art accuracy on ATIS, and has competitive performance on Job.
Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) : Open • Conference submission management system: EIConferences@126.com • Number of submissions received: 70 • Number of submissions sent for review: 60 • Number of submissions accepted: 53 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 75.71 • Average number of reviews per paper: 2 • Total number of reviewers involved : 5 groups with a total of 20 reviewers (each group consists of a lead reviewer and 3 reviewers, each reviewer reviews about 6 papers on average) • Any additional info on review process : Authors will submit their papers through the official email address of the conference, and the deadline for submission is September 23, 2021. The person in charge of the mailbox of the conference committee will sort out all the submissions, divide them into groups and distribute them equally to 5 review groups. The review groups will return comments one after another within 2 weeks, and the person in charge of the conference committee wills feedback the comments to the authors. Each paper was reviewed by two reviewers who gave their own comments: Papers with good quality and themes will be accepted directly, and the authors can register for the next stage of the conference; for papers with medium quality, revision suggestions will be given, and then the review groups will decide whether to accept them or not after the authors revise and return; For papers with very poor quality, the review groups will give rejection suggestions. All involved reviewers are recognized specialists in fields covered by the Conference. The final decision regarding acceptance/revision/rejection was based on reviews received from the reviewers. If the two reviewers cannot agree on a recommendation, the final at the sole discretion of the lead reviewer. The authors themselves do not have any decision on whether their papers are accepted or not. The final approved papers will be registered until October 15, 2021. The conference committee will send the invitation to the accepted authors and submit the information of the authors’ papers to the publishers. Contact person for queries : Name: Xiangtao Wang Affiliation:Shaanxi higher education alliance Email: lidueiconferences@126.com
Near-maximal Polarization Entanglement for Quantum Communications at 2.1 µm

We demonstrate for the first time a positive secure-key rate at 2.1 µ m (0.417 bits/pair, with a quantum bit error rate of 5.43%), using near-maximally entangled photons in a proof-of-principle device-independent quantum-key-distribution scenario.
Technology Education for High–Ability Students

Best practices in education technology commonly view software and hardware as a means to improve learning and student engagement. Innovation, on the other hand, has been extensively researched. Innovation in education centers around abandoning traditional pedagogical practices in which students are held back by their dependency on being taught. Educational innovation takes two forms: sustaining and disruptive. The standard application of innovative education technologies, whether sustaining or disruptive, can easily become tool-centric. Creating technology is an inherently entrepreneurial endeavor involving both creative risk and making interpersonal connections. Serial entrepreneurship is an additional behavioral characteristic found in gifted innovators, which is the ease of transitioning from project to project and upon completion, providing a point of exit or identifying project failure. Failure is not a deterrent, but provides an opportunity to learn and move on.
What Makes Health Data Privacy Calculus Unique? Separating Probability from Impact

Patient health data is heavily regulated and sensitive.Patients will sometimes falsify data to avoid embarrassment resulting in misdiagnoses and even death.Existing research to explain this phenomenon is scarce with little more than attitudes and intents modeled.Similarly, health data disclosure research has only applied existing theories with additional constructs for the healthcare context.We argue that health data has a fundamentally different cost/benefit calculus than the non-health contexts of traditional privacy research.By separating the probability of disclosure risks and benefits from the impact of that disclosure, it is easier to understand and interpret health data disclosure.In a study of 1590 patients disclosing health information electronically, we find that the benefits of disclosure are more difficult to conceptualize than the impact of the risk.We validate this using both a stated and objective (mouse tracking) measure of patient lying.
The CIC Electronic Journals Collection Project

The Committee on Inter-institutional Cooperation (CIC) is an academic consortium of thirteen large research institutions in the midwest with its own regional network, CICNet. The CIC libraries and CICNet are building a managed electronic journal collection out of the content and collection experience of the CICNet E_Serials Archive—a collection of over 800 freely distributed electronic serials. The libraries have developed and endorsed a broad collecting policy for the new collection, the CIC Libraries Electronic Journal Collection 192(CIC EJC). CIC Librarians are selecting a complete, authoritative and permanent collection of electronic journals to be shared by the CIC libraries. The collection will be actively managed, cataloged and maintained by CIC libraries and CICNet staff. Some titles from the E-Serials Archive are being selected for the EJC, and many new journals are being included as well. Catalogers from six CIC institutions are creating bibliographic records for each selected title. The records will be entered into OCLC and made available to each CIC library’s online catalog. This paper focuses on the specific problems encountered in creating the managed collection: locating all issues of each title, cataloging the collection, providing access and managing the collection as a long-term cooperative resource for all the CIC-libraries, and making it accessible to the scholarly research community at large. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com ]
Identification of Fake vs. Real Identities on Social Media using Random Forest and Deep Convolutional Neural Network

Identity detection is very essential in social media platforms, various platform has facing fake accounts influence since couple of years in current eras. Many researchers has introduces approach for identify the fake profiles, but still system cant able to solve such issues. As these fake identities are being used by offenders for various malicious purposes, it has become necessity of time to identify them. The fake identities are categorized into two main types’ i.e. fake identities by bots and fake identities by humans. This system removes fake identities by bots during preprocessing and focuses mainly on identification of fake identities by humans as very little research has been made till now on the fake identities by humans. For classification we test for two different algorithms i.e. Random Forest (RF) and Recurrent Neural Network (RNN). The classification is based on various features such as user name, location, friends count, followers count and so on. Here, dataset used is that of Twitter.