Reviewerly/exHarmony huggingface dataset:
To Enhance the Quality of HCRS using Fuzzy-Genetic Approach

Abstract Social media is recent generation of Recommender Systems (RS). Health Care Recommender System (HCRS) term used to analyse the medical data and then predict the disease of a patient with the help of various techniques used in RS. To ensure the quality and trustworthiness of medical data, machine learning algorithms are applied. Even though, there is a much gap between health care diagnosis and IT solutions. To evade this gap, the hybrid Fuzzy-genetic approach is used in HCRS. In this, Genetic algorithm is used for similarity computations with the help of mutation and crossover operators. Later fuzzy rules are generated for the data set with the additional personalized information of a user. Considering these approaches, the proposed model enhances the quality of recommendation in HCRS.
Application of Artificial Intelligence in News Communication

With the development of artificial intelligence technology, all aspects of society have been changed, and artificial intelligence technology has penetrated into all aspects of news communication activities. The application of artificial intelligence technology in news communication has accelerated the speed and scope of news dissemination. However, due to the immature technology, there are still many deficiencies. Therefore, this paper puts forward the application of artificial intelligence in news communication. This paper makes an in-depth study on the existing AI news writing mode, and analyzes the main problems in the current AI news writing. In view of these shortcomings, based on the characteristics of artificial intelligence technology, combined with the actual needs of news communication, this paper puts forward the optimization and improvement measures of artificial intelligence news communication system. This measure mainly from the short-term and long-term development as the focus of research, and analyzes the optimal solution of the elements and structure problems in the artificial intelligence news production mode. The solution of this paper effectively improves the shortcomings of the current AI news writing mode, and strengthens the supervision of news content while strengthening the writing level. It is suggested that a set of effective supervision and management mechanism should be established to guide the artificial intelligence news format scientifically.
THE USE OF INDIRECTNESS AND TAG QUESTIONS BY POWERFUL AND FOWERLESS MEN AND WOMEN ON TRIALS: EVIDENCE FROM INDONESIA

This study was aimed at investigating the use of indirectness and question tags in some Indonesian trials. The data were chosen randomly from YouTube’s videos. The subjects were twenty people consisting of judges, witnesses, and defendants (the accused). To analyze the data, the conversations of the videos were firstly transcribed verbatim. Then, they were analyzed using the framework of Thomas (1995) and Holmes (1984). The data showed that indirect speech style and question tags were more attached to powerful women.
Effectiveness of website application (Sumiferos) for preventing anemia with pregnant women compliance in consuming Fe tablets

Background: The consumption of Fe tablets needs to be the attention of midwives as one of the spearheads in providing antenatal care services. Due to the low level of compliance of pregnant women to consume Fe tablets, it is necessary to provide appropriate counseling as an effort to increase compliance with Fe tablets. Objective: This study aimed to determine the effectiveness of the application model (Sumiferos) for preventing anemia with pregnant women compliance in consuming Fe tablets at Putri Ayu Health Center in Jambi city. Materials and methods: This study used a quasi-experimental research design with a post-test design by involving an intervention group and a control group (post-test), two group designs. With the total of 70 subjects;the intervention group, 35 respondents were given a website application (sumiferos), and a control group 35 respondents were given a leflet. After a month, the number of Fe tablets that have been consumed was monitored. Compliance of pregnant women in consuming Fe tablets required a monitoring or supervisioncarried out by health workers. Therefore, an intervention was given by using a website-based application (sumiferos) for pregnant women as a communication tool that has been created and designed previously by researchers. Results: Posttest statistical analysis showed that pregnant women who were given a website application (sumiferos) in the intervention group showed better compliance than pregnant women in the control group given lefket. Conclusion: Based on the results,a website application (sumiferos) is more effective than leaflets in improving maternal compliance to consume Fe tablets given by health workers.
Leveraging Big Data Analytics for Predictive Policing in India

India ranks 67th out of 135 countries on the Crime Index. (Numbeo, Crime Index by Country, 2021, https://www.numbeo.com/crime/rankings_by_country.jsp?title = 202) According to the Indian Penal Code, there are almost 32.2 lakh criminal offences in India and 19.4 lakh in Special and Local Laws (SLL). As of 2019, this makes the safety of civilians very daunting. (Tom Reding, Jan 8, 2021 Crime in India, https://en.wikipedia.org/wiki/Crime_in_India ) Police officers cannot handle crime in such a way that allows them to examine each case individually. They must be steered to felony-intensive areas pre-emptively. Big data is an area that deals with methods for analysing, systematically extracting information from and dealing with data sets that are too large or complex for conventional data-processing application software to handle. Over the years, there have been several implementations that have demonstrated the potential ability to leverage big data technologies. The paper focuses on predictive policing as one such implementation. The goal of the paper is to examine how big data can be applied to this segment of Indian government to locate inefficiencies and identify ways of minimizing them.
E-Learning challenge studying the COVID-19 pandemic

The research is devoted to the study of modern e-learning challenges in the context of social distance, the analysis of learning experience, problems and opportunities associated with online learning. The research was carried out at the ‘Blinded for peer review’ and involved 300 graduate students. A qualitative method based on a two-step process was used in the study. The online learning challenges and opportunities were analyzed with due regard to pedagogical, social, and technological aspects. The results of the study demonstrated that online learning is an efficient tool for the development of Hard Skills while being less effective for the improvement of Soft Skills; they also allowed us to identify important aspects of professional personnel training which should be taken into account while developing a strategy for harmonizing on-campus and online education with the diversification of curricula by various pedagogical technologies and digital tools, as well as bringing social interactions into classroom activities.
The experience of using miniatures in the exposition work on the popularization of historical and cultural heritage

The article considers the practice of using sculptural historical miniatures by the staff of the Museum of the Railway District of Novosibirsk and the laboratory «Historical Local Lore» of the Altai State Pedagogical University. It is noted that the sculptural miniature has been tested as the main and auxiliary object of the show, within the framework of the exhibition of one and several objects, thematic dioramas and fashion shows, interactive exhibitions, excursions. The authors come to the conclusion about the prospects of using sculptural historical miniatures to increase the immersive effect of scientific and popularization exhibitions.
A COMPARATIVE STUDY OF THE CONCEPT OF TRADITION BY T. S. ELIOT AND F. R. LEAVIS

Tradition is one of the most significant concepts in critical discourses.It is significant because it defines the chronological sequence, peculiar characteristics and tendencies of different periods.And at the same time it addresses the innovation and shifts taken by literary writers, thinkers and critics.Tradition is a comprehensive term that encompasses not only the temporal aspect of literature but also its tendencies and trends.Therefore the study of the concept of tradition becomes imperative to understand literature.The concept of tradition has undergone several temporal and spatial changes in the course of time.The essay 'Tradition and the Individual Talent' was a building block for much Anglo-American criticism.In his essay, Eliot argues that writers must have 'the historical sense' which can be seen as a sense of tradition.It is not the knowledge of specific events in history, but rather an encompassing feeling of past literature which inspires the writer to write originally and with the spirit of the past in mind.Leavis believed that there were 'great works' of literature, therefore he remains a strong supporter of the existing canon.Leavis's criticism has a sense of the past.It relates historical context to the poem and poet.Historical and social background is not a focus of Leavis's criticism.However, the focus of Leavis's criticism has always been on the text in terms of words and how they relate to one another.In 1948, Leavis has focused his attention on fiction and made his general statements about the English novel in The Great Tradition where he has traced this tradition through Jane Austen, George Eliot, Henry James, and Joseph Conrad.He talks about Seriousness and moral purpose of literature.For him literature is great if it teaches morality.
Model predictive collision avoidance for towing robot considering geometric shape

A towing robot, or a tractor-trailer mobile robot(TTMR) has a high loading capacity and locomotion then has been studied for many years. However, it is known that the control of the TTMR automatically avoiding obstacles is difficult due to its underactuated system and nonholonomic constraints. To drive the TTMR in the narrow path is challenging but it is needed to transport in the factories and warehouses. In this study, the authors tried to make the TTMR control and avoid obstacles even in the narrow path, considering the polyhedron shape of both the TTMR itself and obstacles. For collision detection and avoiding, Farkas’ lemma is applied. The usefulness is shown by the simulation in the environment with obstacles and the narrow path.
Stochastic permutation ordering watershed

The stochastic watershed is a morphological approach to segmentation that repeats the application of a seeded watershed from series of uniform random markers. The obtained watershed boundaries are combined to construct a probability density function. We propose an alternative approach called stochastic permutation ordering watershed. Our approach relies on the construction of several permutation orderings of the pixels of an image, starting from a random pixel and using a dedicated Hamiltonian path construction on a graph. From the permutation orderings, several seeded watersheds are applied and averaged. In contrast to the stochastic watershed, our approach enables to take into account any features associated to pixels, such as patches, of prime important to segment textured images. Experimental results show the benefit of the approach.
Biometrics vendors rush to launch Covid ‘passports’

The drive to develop biometrically-secured systems that prove people are free from Covid-19 has accelerated now that vaccinations have begun to be administered worldwide.
The Use of Online Authentic Reading Materials In Online Reading Class

Abstract. Education in Indonesia, as the large-scale power of the has to be compelled the continuity of teaching activities during the COVID-19 pandemic online learning. It inspires teachers to choose a suitable material to fulfill students’ needs and interests in teaching language. The appropriateness and well chosen authentic materials used by teachers in a context of reading have to cover meaningful content in which those are relevant. Thus, this study attempts to investigate those authenticity used as well as teachers’ challenges in implementing online authentic reading materials in online reading class of higher education. The study is a qualitative. The subjects are three EFL teachers of higher education that teach General English and English for Specific Purposes freshmen for two semesters. The data collection techniques are observation and interview. In analyzing the data, this study uses Ary et al. (2010) theory: familiarizing and organizing; coding and reduction; interpreting and representing. The findings revealed that authenticity is considered as the pivotal thing since, in this case, English is taught as foreign language. The authentic materials can be said its prevalence by measuring each authenticity based on three areas including SLA (Second Language Acquisition), language pedagogy and ICT (Information and Communication Technology). It could establish the applied authenticity to the language learning design materials, especially learning English language. Moreover, The challenge was about the materials, students’ interests, classroom activities and classroom interaction occurred among teachers and the students.
Saudi Arabia National Cyber Security System: Specificity and Development Risks

The research featured the national cybersecurity system of the Kingdom of Saudi Arabia. The cybersecurity standards developed by the International Telecommunication Union of the United Nations made it possible to reveal the institutional and legal foundations of the digital security system, as well as the degree of involvement in international cybersecurity cooperation. The analysis demonstrated the key risks of the development of the Saudi cyber model. The assessment by the International Telecommunication Union standards gave quite positive results. However, Saudi Arabia proved to adhere to a catching-up development model and still experiences some problems with national cyberspace security. Some are of global nature, e.g. legislation gaps, while others result from the specifics of the national model of state governance. The most obvious risks include the imbalance between the civil and military sectors, the disagreements between various regions, and the poor integration of the local hacker community into the overall structure of national cybersecurity. Saudi Arabia plans to eliminate these imbalances in the medium term in order to build an integrated cybersecurity system by expanding its international cooperation.
Navigation

In the last chapter, we reviewed the various navigational links available on a web page that can be located using web locators. Some of the functionality and features were also discussed. This chapter explains web locator applications for finding navigational elements.
Detection of Region-of-Interest Based on Noise Filtering in High-Speed Images

Relatively inexpensive cameras have become common that can film even minute movements of moving objects at high speeds. This paper introduces a method of removing noise pixels abnormally generated from the ultra-high-speed images entered, and then detecting the skin color area of a person, the area of interest that represents personal information from the images of noise removed. The proposed algorithm eliminates noises by applying bilateral filters from the high-speed images that are first accepted. Then, using color models created through learning, the human skin area, which is an area of interest, is accurately extracted from the image of noise removed. The experimental results show that the proposed algorithm effectively removes noises from the high-speed images entered and then robustly detects the area of interest, the skin color area. The method introduced in this study is expected to be useful in many applications related to pattern recognition, such as image analysis and understanding, video pre-processing, noise removal, etc.
Realization Model of Personal Data Rights Based on Blockchain Technology

In the era of artificial intelligence, personal data is the nourishment for many artificial intelligence algorithms. Some face recognition, voice recognition and other algorithm models must be fed with personal data to bring commercial value. Therefore, various technology companies currently collect user data while providing services, and apply user data to various commercial purposes, such as precision marketing. These companies use users' personal data for revenue. However, as the owner of their own data ownership, individuals cannot obtain any benefits from it, and even in the process of data circulation, they are subject to various harassment and infringements due to personal data being leaked. Blockchain technology benefits from the application of key pairs of asymmetric encryption technology in cryptography, which can prevent data from being copied at will. It cannot only protect user privacy, but also enable personal data to circulate among various business entities, and it can also enable individuals to obtain benefits in the process of their own data circulation. This article proposes a model for the realization of personal data rights and interests based on blockchain technology. Individuals, companies or institutions with a large amount of user data, personal data account banks, personal data regulators and other parties, under the support of blockchain technology, are in their proper place, develop in benign cooperation, and share the results of data economy together.
Metaheuristics Based Clustering Algorithms on Document Clustering

Cluster analysis is an important exploratory data analysis technique which divides data into groups based on their similarity. Document clustering is the process of employing clustering algorithms on textual data so that text documents can be retrieved, organized, navigated and summarized in an efficient way. Document clustering can be utilized in the organization, summarization and classification of text documents. Metaheuristic algorithms have been successfully utilized to deal with complex optimization problems, including cluster analysis. In this paper, we analyze the clustering quality of five metaheuristic clustering algorithms (namely, particle swarm optimization, genetic algorithm, cuckoo search, firefly algorithm and yarasa algorithm) on fifteen text collections in term of F-measure. In the empirical analysis, two conventional clustering algorithms (K-means and bi-secting k-means) are also considered. The experimental analysis indicates that swarm-based clustering algorithms outperform conventional clustering algorithms on text document clustering.
FPGA Implementation of Interleaved Modular Multiplier with Improved Area-time Efficiency

Modular multiplication is the fundamental operation in Elliptic Curve Cryptography (ECC) and a multitude of hardware implementations have been developed so far. In this paper, a series of modifications to a high performance radix-2 interleaved modular multiplication architecture are proposed. The design was implemented on a Virtex-7 FPGA for five prime fields recommended for ECC by the National Institute of Standards and Technology (NIST), showing a significant improvement in area-time efficiency in comparison to the original architecture.
Accelerating Innovations in Biomanufacturing Approaches through Collaboration (NSF)

Federal Grants & ContractsVolume 46, Issue 4 p. 2-3 Grants alerts Accelerating Innovations in Biomanufacturing Approaches through Collaboration (NSF) First published: 17 January 2022 https://doi.org/10.1002/fgc.32158Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume46, Issue420 January 2022Pages 2-3 RelatedInformation
Pengaruh Lingkungan Keluarga dan Disiplin Belajar terhadap Hasil Belajar Matematika Siswa Kelas IV SD Negeri Se-Kecamatan Bener Tahun Ajaran 2020/2021

&lt;p&gt;Penelitian ini bertujuan untuk membuktikan ada tidaknya (1) pengaruh positif lingkungan keluarga terhadap hasil belajar matematika kelas IV SD; (2) pengaruh positif disiplin belajar terhadap hasil belajar matematika kelas IV SD; (3) pengaruh positif lingkungan keluarga dan disiplin belajar terhadap hasil belajar matematika kelas IV SD. Penelitian ini merupakan penelitian kuantitatif dengan korelasi menggunakan analisis regresi berganda. Hasil penelitian Pertama, terdapat pengaruh positif antara lingkungan keluarga terhadap hasil belajar matematika kelas IV SD sebesar 8,12%. Kedua, terdapat pengaruh antara disiplin belajar terhadap hasil belajar matematika kelas IV SD sebesar 1,78%. Ketiga, terdapat pengaruh pengaruh lingkungan keluarga dan disiplin belajar terhadap hasil belajar matematika sebesar 9,9%. Dengan demikian, dapat disimpulkan bahwa terdapat pengaruh positif antara lingkungan keluarga dan disiplin belajar terhadap hasil belajar matematika siswa kelas IV SDN se-Kecamatan Bener tahun ajaran 2020/2021.&lt;/p&gt;&lt;p&gt;The study aimed to determine positive effect of: (1) family environment on mathematics learning outcomes, (2) learning discipline on mathematics learning outcomes, and (3) the family environment and learning discipline on the mathematics learning outcomes to fourth grade students of public elementary schools. The research was correlational quantitative method and multiple regression analysis. The results showed that: (1) there was 8.12% positive effect of family environment on the mathematics learning outcomes of fourth grade elementary school students. (2)There was 1.78% effect of learning discipline on students mathematics learning outcomes. (3)There was 9.9% effect of the family environment and learning discipline on mathematics learning outcomes. It concludes that there is positive effect between the family environment and learning discipline on the mathematics learning outcomes to fourth grade students of public elementary schools in Bener Sub-district in academic year of 2020/2021.&lt;/p&gt;
An Advanced Ontology based Deep Learning for Computer-aided Interpretation of Mammography Images

Computer assisted detection (CAD) are able to detect and characterize suspicious mammographic images, micro calcifications, masses or more difficult, architectural distortion. With the exploitation of these different characteristics, the system can specify and predict the severity of the tumor to assess the risk in terms of Malignity/Benignness. Our work involves the development of a new method for screening breast cancer, this is achieved by developing a whole strategy of knowledge extraction through deep learning and medical ontology appropriate for the classification of regions selected from digital mammograms, for each radiological sign considered, namely, masses and micro calcifications. First, we extracted the parameters characterizing the images used as input to a deep convolutional neuron network CNN. The learning is supervised because the images used are images from the MARATHON database of the University of Florida; they are already diagnosed by experts. The second phase aims to add a semantic level to our classification through a specialized ontology developed for this purpose based on the BIRADS characterization system. Based on the evaluation performed, the proposed approach provides better classification results than the usual methods for assisting in the computer aided detection of breast cancer.