Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis: Classifier and Summarizer

Sentiment Analysis and summarization has a large number of application that are useful for determining the sentiment of the text and summarizing a big text into a small paragraph of few lines. Thus it has become an important topic to work on and for fulling the requirements of the customer. It has also become an important topic for researchers to focus on, as it is highly demanded and beneficial in different fields of product, services and growth of the business. At present when 89.9% of people are using social media platform, they express their reviews, feelings, emotions and share their comments and some exciting activities of their life through social media platform, so it becomes very important to analyses them and classify them as positive or negative, this can be done with the help of sentiment analysis. Also, to find the summary of a big document with large amount of data summarizer is very useful as we can get the summary of a document in the favorable number of line. The basic model of sentimental analysis classify the word as positive as negative with the help of some machine learning approaches, which will help in improving the quality of product and providing the service to the customer for building up a healthy competition in market and keeping the goodwill of the business . It also displays the output in the form of graph whose data is taken from social media platform. Sentimental analysis also helps in getting the summary of the document by picking the lines containing the words having maximum repetitions. It has been found that sentiment analysis able to classify the positive sentence by giving the output as 1 and negative sentences as 0. The model which is being built also graphically represents the classifications of positive and negative words picked from the dataset and it’s also useful in summarizing a document Thus sentiment analysis comes out to be very important for classify the unstructured data on social media platform and so there is always a scope of building a better model which is more accurate and efficient.
Image Denoising and Colorization Based on Plug and Play Framework

A digital image has become an essential carrier of information transmission, but it will inevitably be destroyed during the transmission process. For image denoising or image colorization, there are already many excellent algorithms, and there have been promising developments in the field of deep learning. However, in these classic methods, few algorithms can accomplish image denoising and colorization simultaneously. This paper proposes a plug and play framework to solve this problem, which combines the advantages of generative adversarial networks and plug and play framework. Moreover, we design a lightweight conditional GAN to achieve the purpose of training with fewer computing resources. Experiments on CFP and Landscape datasets show that this method can effectively complete image denoising and image colorization tasks.
Analisis Pembelajaran Matematika Menggunakan Vlog Pada Masa Pandemi (Studi Kasus di SMA Negeri 1 Wuryantoro)

This research is a quantitative descriptive study conducted at SMA N 1 Wuryantoro which conducts the online learning process in teaching and learning activities with the aim to find out online learning in math learning during the covid-19 pandemic. The data collection technique used is an online questionnaire sheet. The subjects in the study were high school student N 1 Wuryantoro. The results of this study showed that learners are actively involved in learning Mathematics using Vlogs, this is indicated by video products that are done according to the set deadline. This includes the preparation of themes, equipment and venues, as well as an understanding of the concepts used in the presentation. Learners' learning interest in learning using Vlogs tends to increase, this is indicated by students' creativity in displaying the results of vlogging videos that they will post on social media.
LINKING OF AUTHOR PROFILES IN BIBLIOGRAPHIC DATABASES ON THE EXAMPLE OF РИНЦ AND ЕГИСУ

For scientometric analysis, several systems are usually used with a different format for presenting information, which may not have common identifiers. This, in turn, makes it difficult to conduct a joint analysis. The article presents an algorithm for linking data on dissertations from the EGISU R AND D system of Russian researchers with their author profiles in the RSCI. As a result of the comparison, for 63,38 of dissertations, the authors profile was found in the RSCI system.
Novelty-based Generalization Evaluation for Traffic Light Detection

The advent of Convolutional Neural Networks (CNNs) has led to their application in several domains. One noteworthy application is the perception system for autonomous driving that relies on the predictions from CNNs. Practitioners evaluate the generalization ability of such CNNs by calculating various metrics on an independent test dataset. A test dataset is often chosen based on only one precondition, i.e., its elements are not a part of the training data. But it may contain objects that are both similar and novel w.r.t. the training dataset. Nevertheless, existing works do not reckon the novelty of the test samples and treat them all equally for evaluating generalization. Such novelty-based evaluations are of significance to validate the fitness of a CNN in autonomous driving applications. Hence, we propose a CNN generalization scoring framework that considers novelty of objects in the test dataset. We begin with the representation learning technique to reduce the image data into a low-dimensional space. It is on this space we estimate the novelty of the test samples. Finally, we calculate the generalization score as a combination of the test data prediction performance and novelty. We perform an experimental study of the same for our traffic light detection application. In addition, we systematically visualize the results for an interpretable notion of novelty.
Pioneering a Next-generation Basic Theory and Purpose-specific Cryptography toward the Future of Symmetric-key Cryptography

Cryptography is an essential technology for secure information communications.Types of cryptography include public-key cryptography and symmetric-key cryptography.Here, we're talking to Yosuke Todo, a distinguished researcher who is working on building a basic theory for symmetric-key cryptography and researching purpose-specific cryptography.
Straight quotes, square brackets: Page-based poetics inflected with the syntax and grammar of code languages

This article traces the translation of texts between cultural and linguistic contexts, between academic and public-facing audiences, between print, digital, and performed forms. It is primarily concerned with questions of punctuation arising from the translation of poetic texts from digital into print contexts, with a particular attention to brackets and quotation marks. Building on a series of talks, its current iteration as an online publication this article continues an on-going exploration of the movement of language across, beyond, and through in-between spaces. The idea of "between" is considered here as a third time/space/state, a texture, an event, a palpable unfolding fraught with cacophony, liminality, atemporality and asynchronous exchanges. In keeping with its transient subject, this article alternates between lyrical and analytical modes.
Anti-noise Object Tracking Based on Siamese Octave Convolution and Attentional Correlation Fusion

The task of object tracking is to calculate the location of the selected object in the video sequence, but it will face the problem of performance reduction in the noise environment. The goal of this paper is to enhance the noise resistance of the tracking network without increasing the computational burden. The Siamese Octave convolution module is proposed to improve the noise resistance of CNN features and to further enhance the self-similarity of template feature map and search feature map. At the same time, a new cross-correlation fusion method is introduced, which improves the multi-scale of cross-correlation results by aggregating local and global context information, and brings better adaptability at various noise levels. Through the use of our method on the anchor-free tracker Ocean, the experimental results show that the improved method proposed in this paper can effectively improves the noise resistance of the object tracking model.
Musicians of the Titanic: An EFL teacher’s classroom management experiences during Covid-19 pandemic

This single-subject case study dwells on the classroom management (CM) practices during emergency remote teaching (ERT) that resulted from the COVID-19 pandemic. The participant is an English teacher, teaching young learners (aged 6-8) during the time of the study. Under the qualitative research framework, the strategies and views upon CM practices were derived from observation of 20 lessons, 4 weekly reflection reports, and a semi-structured interview. The data were transcribed, analyzed using in-vivo and descriptive coding methods, and interpreted with relating to the existing literature. As a result, it was found out that there were many factors interwoven in this subject matter, giving rise to an intricate network of developing strategies, perceptions, and roles. In this vein, various teacher roles/resources, dynamic learners’ roles, a toolkit for dealing with CM issues, the intervening surrounding factors affecting the course of CM during ERT were presented and discussed within the related literature. Accordingly, practical implications upon ameliorating this process and recommendations for enhancing the understanding of the subject matter were provided.
Prediction of malignancy upgrade rate in high-risk breast lesions by artificial intelligence model

Thank you very much for joining EUSOBI 2021 ONLINE and celebrating the Breast Cancer Awareness Month with us! This year we had a terrific programme and we are indebted to Dr. Ritse Mann and his Programme Committee for all their hard work in putting this together. We had a wonderful selection of international speakers who gave the latest updates in all your favourite topics and ensured that you are kept up to date with the latest developments in breast imaging. A special focus was given to the interactivity of this year’s programme, by adding expert discussions and concluding with the first virtual edition of our famous Breast Interpretation Quiz. Thanks to all of you who submitted abstracts and therefore having been an important part of this scientific event. We are also very grateful for the support of our industry partners who are listed here: https://www.eusobi.org/congress-sponsors-2/ Most of them have contributed to the extension of our scientific programme by offering interesting sessions and workshops. Have a look by scrolling through all sessions. All sessions have been recorded and are available on-demand.
Cognitive Map: Universal Code for Learning and Memory

Ever since the discovery of place cells, the conception of the cognitive map has revived and the intriguing assumption that spatial navigation system also encodes other cognitive functions has aroused interest among neuroscientists.Though the hypothesis has been viewed with some skepticism, evidence gradually accumulated in the last decade, especially with regard to more abstract functions of the human brain.Drawing on the most recent experimental results, this theoretical literature review attempted to further assess the possibility that the human brain processes various kinds of information by constructing cognitive maps and uncover some of its governing principles.Conclusions are that recent evidence generally supports the hypothesis, though the characteristics of spatial map and cognitive map exhibit differences.Moreover, time scale and reference frame are two variables that determine the neural activity during cognitive tasks, more specifically, the brain regions that exhibit signals that are thought to reflect the participation of cognitive maps vary with changes in time scale and reference frame.Therefore, these two variables should be taken into account when designing experiments and interpreting the results.The review will help guide future exploration of the cognitive map, which is a promising candidate for unraveling the universal rule of human cognition.
KLASIFIKASI REGRESI LOGISTIK MULTINOMIAL DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) DALAM PEMILIHAN METODE KONTRASEPSI DI KECAMATAN BULAKAMBA, KABUPATEN BREBES, JAWA TENGAH

The characteristics of society in choosing contraceptive methods are also the crucial factors for the government to prepare the family planning services needed at Bulakamba District, Brebes Regency, Central Java. In this case, a classification process needs to be done to assist the process of classifying the characteristics of society in the selection of contraceptive methods. Multinomial Logistic Regression classification is good in exploring data information meanwhile Fuzzy K Nearest Neighbor (FK-NN) classification is good for handling big data and noise. These two methods used in this study because they are relevant to the data applied and will be compared their classification accuracy through APER and Press's Q calculations.The classification accuracy results obtained based on the APER calculation for Multinomial Logistic Regression is 88,25% and Fuzzy K Nearest Neighbor (FK-NN) is 88,92%. Meanwhile, the Press's Q value of both methods are 9600,945 and 9518,014 greater than χ 2𝛼,1 which is 3,841, so that it is statistically accurate. Based on the results obtained, it can be concluded that Multinomial Logistic Regression classification method has a better classification accuracy than Fuzzy K Nearest Neighbor (FK-NN) method.
Atendimento de Enfermagem COVID-19 :Um serviço de Saúde à distância / Nursing Care COVID-19 : A distance health service

The evolution of the COVID-19 pandemic imposed an unusual physical distance in societies, calling on health services to develop new strategies for serving population.Within the scope of the COVID-19 Contingency Plan, the Covid-19 Nursing Care Service was created in early March 2020 with the aim of informing users who use the Emergency Service of the hospital institution by telephone about the result of the SARS laboratory test-CoV-2 and the respective health measures to be adopted.After one year of operation, there were more than 26000 nursing telephone contacts.The user contacted are informed about their health situation, reinforcing measures and care in isolation from the person and/or family.It was a nursing intervention that intended to contribute not only to the access health information, through information the result on the COVID-19 test, but also to the activation of the person in the person of recovery from the disease and the adoption of behaviours of self-care; a person centered care.
Influence Of Digitalization On Expectations And Real Prospects Of Students And Employers

The paper considers the issue of the impact of digitalization processes on mutual expectations and real prospects of future young agricultural specialists and employers in the field of the agro-industrial complex.The authors, characterizing the features of the modern stage, state that today there is another global transformation caused by the processes of digitalization.Digitalization determines trends in the labor market and sets new trends in all spheres of society, including education.Digital economy requires professionals with up-to-date knowledge and a set of universal competencies, capable of continuous development of new knowledge, skills and abilities.The analysis of the current situation leads the authors to the conclusion that digitalization, on the one hand, aggravates the existing contradictions in the labor market and educational services, and, on the other hand, gives new opportunities and prospects for selfrealization, life and professional identity of young people.The study allowed analyzing the level of the compliance of expectations of future young professionals and their potential employers.It is found out that while young people, entering the labor market, rely on high wages, comfortable working and living conditions and the prospect of career growth, employers express distrust in the quality of their professional training and the level of formation of the necessary competencies, which leads to the need for their retraining or advanced training and as a result to the increase in the costs of employers.
Cepsa upgrades alkylbenzene plant

Most of the available recommender systems focus on the accuracy of recommendations. As a result, their recommendations are often popular and very close to user preferences, which make them repetitious and predictable, hence adversely affecting user satisfaction. Recent studies on recommender systems, however, aim for factors beyond accuracy as accuracy alone cannot ensure the satisfaction of all users. One of the most important criteria beyond the accuracy is serendipity, which includes relevant, unexpected, and novel recommendations that cannot be easily discovered by users themselves. In this paper, a Convolutional Neural Network (CNN) is integrated with the Particle Swarm Optimization (PSO) algorithm to generate serendipitous recommendations. The proposed method is based on the focus shift points, consisting of unexpectedness and relevance parameters. In this approach, these points are considered as the factors showing whether recommendations are serendipitous. The CNN is employed to predict the focus shift points for each user. Then, the PSO is utilized to search for recommendations close to the predicted focus shift points and generate the list of candidate recommendations. After that, the Serendipitous Personalized Ranking (SPR) method is employed to re-rank the candidate recommendations and generate the final list. According to the evaluation results, the proposed approach outperforms other state-of-the-art methods in SRDP, Hit Ratio, and NDCG factors.
On Consistent and Weak Transitive Intuitionistic Fuzzy Matrices

In this paper, we discuss in detail several properties of two kinds of intuitionistic fuzzy matrices which they are consistent and weak transitive. The nilpotent and transitive intuitionistic fuzzy matrices play an important role in this discussion. We show that our two kinds of matrices are controllable. We give a formula for the canonical form of a weak transitive intuitionistic fuzzy matrix. Our results are completely by counter examples to clarify it.
RUSI: The UK's Response to Cyber Fraud

The Royal United Services Institute (RUSI) is arguably best known for its studies into geopolitical and defence issues. Cyber security is clearly an intrinsic element of these domains. But to see a report from RUSI on the subject of fraud is interesting – not least because it underlines the damage that fraud can wreak on a nation's economy and therefore its stability and security.
ARGUMENT STRUCTURE OF PERSUASIVE LANGUAGE IN PUBLIC SPACE OF INDONESIA – TIMOR LESTE

Persuasive language is different from declarative language in Bahasa Indonesia. This distinctive form impacts the functional pattern and the argument structure. Thus, this study aimed at identifying and describing argument structure of persuasive language in public space of Indonesia – Timor Leste. Since this study was a qualiative study, the data obtained were analyzed qualitatively using lexical-functional grammar theory (LFG). Persuasive language found in the research was in the form of intransitive and monotransitive clauses. Intransitive clauses have the pattern V – OBJ and V – OBJ – ADV. The monotransitive clauses have the pattern SUBJ – V – OBJ, V – OBJ – SUBJ, and OBJ – V – SUBJ. The intransitive verbs found always bind arguments that semantically have a locative role, therefore the model of the argument structure is ‘jauhi’ locative and 'jaga' locative. The argument structure of monotransitive clauses can be modeled as ‘bersatu membangun’ agent, locative, ‘bersatu membangun’ locative, possessive, ‘membangun’ experiencer, theme, and 'wujudkan’ agent, locative.
Image Compression Techniques with LZW method

Abstract: Image compression is a technique which is used to reduce the size of the data. In other words, it means to remove the extra data from the available by applying some techniques and tricks which makes the data easy for storing and transmitting it over the transmission medium. The compression techniques are broadly divided into two categories. First one is Lossy Compression in which some of the data is lost while compressing it and second technique is lossless technique in which data is not lost after compressing it. These compression techniques can be applied on different image formats. This review paper compares the different compression techniques. Keywords: lossy, lossless, image formats, compression techniques.
MAPLE MATHEMATICAL SYSTEM: SOLVING EQUATIONS

Knowledge of methods and techniques for working with mathematical and practical computer programs using information and communication technologies and computer software and technical complex technologies, the issues of solving mathematical problems are studied, they facilitate obtaining accurate results, etc. Since information and communication technologies are also very useful for creating pedagogical and psychological conditions that promote comprehensive education of future generations, business, talented, creative, and free development, the development of this program is of great importance. The future of Kazakhstan is in the hands of young people. Therefore, every citizen of the country should fully master innovative technologies and implement them in everyday life. Knowledge of information and communication technologies is an important factor in the development of education reform. Knowing these systems makes it easier to get accurate results, graphically present them, create reports, and so on. This programming system is most suitable for engineering and technological specialties. Therefore, multifunctional software and information capabilities of computer technologies: virtual laboratories, Computer software packages, Internet networks, multimedia, electronic textbooks, etc. Whatever innovative technologies may be, their effectiveness can only be achieved with the skill of the teacher and the improvement of this skill. Therefore, the system and methods of teaching AIDS to increase the motivation of students require each teacher to develop them in depth, implement them and their corresponding skills.
Measures to Prevent Damage to Digital Sexual Offences Against Children and Adolescents and to Support Victims

Recently, digital sexual offenses have been continuing in our society. They are becoming more diverse and, victims are getting younger. It is miserable that we can be victims ourselves, and our children can also be victims. The state has to prevent crime, so it has to support and protect victims. Digital Sexual offenses cause constant pain to victims for their life. If victims are Children and adolescents, they suffer from damage for their whole life, perhaps eternally. In this article, I reviewed the concept of digital sexual offenses used in the Korean government policies and the current legislation for victim support and suggested preventing and supporting damage, especially when targets are children and adolescents. After that, I made suggestions for damage preventing and supporting measures.