Reviewerly/exHarmony huggingface dataset:
It’s Time to Stop Reinventing the Wheel; Let’s Connect Those Dots Instead

A constant question I see come up for anything related to scholarly publishing—or really anything related to life in general—is: “How do I get started?” And now that I have entered the “halftime” of my life, as my husband so lovingly calls it, I see the hardest part of really any project is just figuring out how to get going. (Side note: Jonathan Schultz, our beloved Editor-in-Chief, is nodding his head knowingly as he reads this wee-bit-late column that I promised him would be early this month. We are all guilty of not knowing where to start.) Publishing used to be so much simpler. I copyedited an article and saved it on a floppy disk. I marked up paper page proofs with my purple editing pen using old school copyediting marks. I had a pica ruler and a hardcover dictionary along with paper style guides. I even used to hand code articles with XML for overtime. I will always love those overtime opportunities both for the XML knowledge and the Christmas gifts they bought my kids. Articles were published and then largely forgotten as we moved on to the next ones. Glossy journals piled up in stacks and collected dust as the same cycle repeated itself again and again. Thank you for indulging my walk down memory lane, but I am here to tell you that the way we do things today is so much better. Looking back, I think of all of those amazing articles that readers missed out […]
USING MOODLE FOR ENGINEERING COURSE DELIVERY

Biotechnology concepts will be a key skill set for future chemical engineers.However, when biological concepts are conveyed to chemical engineering students in a traditional manner, the students often end up lacking the ability to translate these ideas to engineering applications.This discrepancy arises in part from the different way in which engineering students think and approach problems relative to their natural science colleagues.Due to this, the chemical engineering department of Texas A&M has introduced a new course in biology which emphasizes student ability to apply biological concepts to solving engineering problems.Results from survey evaluation of student ability to apply learned biotechnology concepts to new problems indicates that the application oriented approach to teaching biotechnology concepts is effective and should be further developed.
AUTOMATIC KEYWORD EXTRACTION USING ARTIFICIAL NEURAL NETWORK AND FEATURE EXTRACTION

Extracting keywords from documents is an essential task in natural language processing. A challenge of this task is to define a reasonable set of keywords from which we can find all relevant documents. This paper proposes a new approach that exploits word-level handcrafted features and machine learning models to select a single document's most important keywords. To evaluate the proposed solution, we compare our results with the latest supervised and unsupervised automatic keyword extraction methods. Experiment results show that our model achieves the best results on the 9/20 data corpus. It points out that our proposed approach is promising.
PMHE:A Wearable Medical Sensor Assisted Framework For Health Care Based On Blockchain And Privacy Computing

Abstract Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy protection framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged; Besides, it use fully homomorphic encryption method to design a disease prediction model, which was implemented using smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping; Smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too, so it avoids privacy and security issues caused by platform data leakage. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.
Advanced fibonacci sequence and its sum by second order variable co-efficient difference operator

We introduce a second order difference operator with specific powers of variable co-efficient and its inverse in this study, which allows us to derive the (α1tr1, α2tr2 )-Fibonacci sequence and its summation. This series is known as the Fibonacci sequence with variable co-efficients (VCFS). On the sum of the terms of the variable co-efficient Fibonacci sequence, some theorems and intriguing findings are generated. To demonstrate our findings, appropriate instances arepresented.
What makes a human? Conscious human beings are hyperobjects that interact via physical and mental representations in an ecosystem based on fundamental story-flow interactions.

What is a human being? Some might answer this question by referring to a biological body, growing from genetic information passed on through generations. Others refer to a mind, developed from infancy to adulthood, expressing itself self-aware and intelligently. Few will argue that a human being could exist without one or the other, but many disagree on their relative contribution. Does the conscious mind emerge solely from a single physical body? Is the developing body shaped purely by biological predetermination? I propose that the formation of individual human beings is subject to an environment that envelops both, the physical and mental realms. This environment is here referred to as story-verse of humanity. It is an ecosystem that emerged from biological activity but grew and evolved into an interactive space that includes temporal interactions, such as created by nervous system activity. The emerging story-verse gives rise to persistent hyperobjects, including individual human beings, whose stories perpetuate themselves via physical and mental representations. The story-verse is a real physics realm that includes the four fundamental interactions described by particle physics, but additionally requires higher-order fundamental forces that facilitate interactions between the physical and mental realm.
REVIEW ON APPLICATION AREAS OF DEEP LEARNING

The current era is the golden era of Artificial Intelligence. Machine learning is used mostly in all Applications of Artificial intelligence(AI). Machine learning is proven as a great tool to make AI strong. As an advanced form of machine learning, the popularity and success of Deep Learning is proven in different applications is at the top level. As the accuracy in forecasting is high as well as it is very important for the corporate world. The leadership of deep learning cannot be underestimated. It is used to develop systems that mimic the human knowledge gain process using neural networks. In this paper, we are going to discuss innovative developments in application areas of deep learning.
Preface

The International Conference on Advanced Optics &amp; Photonics Research in Engineering (AOPR 2021) (http://www.aopr-conf.com/) held from November 13-14, 2021 in Wuhan, China. Aiming at providing an excellent international academic forum for all the researchers and practitioners, the conference enjoys a wide spread participation among all over the universities and research institutes. It was provide opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration. Papers and topic concentrates on related fields of Optics and photonics are presented. AOPR 2021 proceeding tends to collect the most up-to-date, comprehensive, and worldwide state-of-art knowledge on Advanced Optics &amp; Photonics Research in Engineering and other related topics. All the accepted papers have been submitted to strict peer-review by 2-3 international expert referees, and selected based on originality, significance and clarity for the purpose of the conference. The conference program is extremely rich, profound and featuring high-impact presentations of selected papers and additional late-breaking contributions. I sincerely hope that the conference would not only show the participants a broad overview of the latest research results on related fields, but also provide them with a significant platform for academic connection and exchange. The Technical Program Committee members have been working very hard to meet the deadline of review. The final conference received over 75 submissions, and 28 papers have been accepted. I would like to express our sincere gratitude to all the keynote speakers, editors, TPC members and organizers for their hard work, precious time and endeavor preparing for the conference. Our deepest thanks also go to the volunteers and staffs for their long-hours work and generosity they’ve given to the conference. The last but not least, we would like to thank each and every of the authors, speakers and participants for their great contributions to the success of AOPR 2021. Dr. Changbo Cheng Hubei Zhongke Research Institute of Nature Science, China Nov.2 2021
Review of Carrió-Pastor (2020): Corpus Analysis in Different Genres: Academic Discourse and Learner Corpora

Abstract This article reviews Corpus Analysis in Different Genres: Academic Discourse and Learner Corpora 9780367417161
Sentiment Analysis of Covid-19 Related Contents in Microblogs

With the emergence of Web 2.0, internet users share their feelings, thoughts and ideas with other people using social networks.Understanding people's thought analysis is important for examining marketing and user feedback in social networks.For this reason, sentiment analysis on social networks with machine learning algorithms is a popular field of study.Our study is based on the sentiment analysis of people against the new coronavirus, which affects the world.People can have different moods due to pandemia.The governance of mental issues must be observed to manage the pandemic time period more successfully.In this article, we retrieved 387,953 tweets due to the ten most frequently used COVID-19 related keywords.The most frequently used keywords about COVID-19 which enable to obtain and assess the reaction of Twitter users are investigated.Even if COVID-19 is a health issue and tweets about COVID-19 is expected to contain negative content, we found positive, negative and neutral tweets to analyze texts using sentiment analysis and machine learning approaches.We applied four classifiers like logistic regression, multinomial naive Bayes, support vector machines and decision tree.These classifiers are well studied and utilized in many studies which we mentioned in our study.The performance of the support vector machine, decision tree and logistic regression classifiers are close to each other.The lowest F-score is obtained from multinominal naive Bayes classifier.The classification results for each negative, neutral and positive class were compared separately in our study.
Fast Computation of the EM Algorithm for Mixture Models

Mixture models become increasingly popular due to their modeling flexibility and are applied to the clustering and classification of heterogeneous data. The EM algorithm is largely used for the maximum likelihood estimation of mixture models because the algorithm is stable in convergence and simple in implementation. Despite such advantages, it is pointed out that the EM algorithm is local and has slow convergence as the main drawback. To avoid the local convergence of the EM algorithm, multiple runs from several different initial values are usually used. Then the algorithm may take a large number of iterations and long computation time to find the maximum likelihood estimates. The speedup of computation of the EM algorithm is available for these problems. We give the algorithms to accelerate the convergence of the EM algorithm and apply them to mixture model estimation. Numerical experiments examine the performance of the acceleration algorithms in terms of the number of iterations and computation time.
Towards Generating Financial Reports From Table Data Using Transformers

Financial reports are commonplace in the business world, but are long and tedious to produce. These reports mostly consist of tables with written sections describing these tables. Automating the process of creating these reports, even partially has the potential to save a company time and resources that could be spent on more creative tasks. We implement a transformer network to solve the task of generating this text. By generating matching pairs between tables and sentences found in financial documents, we created a dataset for our transformer. We were able to achieve promising results, with the final model reaching a BLEU score of 63.3. Generated sentences are natural, grammatically correct and mostly faithful to the information found in the tables.
Prerequisites and Barriers to the Use of Digital Tools for Organising Mentoring in a Teaching Team

There is currently an increased research vector related to exploring the application of digital tools in personnel management and a growing research interest in mentoring in educational organisations. The purpose of the article is to identify and justify the factors that facilitate or limit the use of digital tools in the organization of mentoring in a teaching team. Methodology. The methodology of the study is based on the provisions of the systematic approach and on the ideas of interdisciplinary approach to the study of pedagogical phenomena. Theoretical analysis of normative legal acts, results of interdisciplinary research and SWOT-analysis methods are used to solve the problems set. Results. The study showed that the prerequisites for the application of digital tools of mentoring organisation in the pedagogical team to a greater extent are the digital tools used by the educational organisation to solve managerial and learning tasks, as well as the RF policy aimed at developing digitalisation and innovative activities of educational organisations. The barriers to the use of digital tools for mentoring in the teaching staff lie in the properties of the educational organisation’s teaching staff. The economic aspects of the external environment, associated with the imperfect mechanism for calculating teachers’ salaries, also have an unfavourable impact. Conclusion. The results obtained are the basis for the development of strategic alternatives that define, for a particular case, options for the optimization of digital support for the organization of mentoring in the pedagogical team.
The Future Human and Behavioural Challenges of Cybersecurity

Abstract This chapter explores the future human and behavioural challenges that are likely to have an impact on cybersecurity. It identifies some general challenges that will need to be overcome. The first challenge will be to accept that cybersecurity practitioners are not average end users. It is important to understand cybersecurity as a social practice that is carried out in specific and variable contexts if we are to design successful behavioural and social interventions. The second challenge is to improve the levels of creativity and innovation demonstrated by cybersecurity practitioners. Finally, the third challenge is to look at how we address cybersecurity risk. Meeting these challenges will depend on developing a skill set among cybersecurity practitioners that puts soft skills on a par with technical skills, and establishes trust relationships through genuine dialogue realized through participative approaches to cybersecurity.
A Scalable Framework for Customer Sentiment Analysis in the Telecommunication Industry

Big Data explosion is a phenomenon of the 21st century. Nowadays, more and more people are using the internet and creating new data regarding ideas, opinions, feelings or their views on a variety of topics and products. The micro-blogging platform Twitter is very popular and produces massive amount of data every fraction of a second and useful information may be generated from them. Sentiment analysis or opinion mining plays a major role in discovering all this information by analyzing these data and gain better insight of the public opinion on any subject in specific. In this paper a framework is proposed, built on top of the Hadoop ecosystem, for analyzing data from Twitter using a domain-specific Lexicon (in Greek).
Dichotomy model based on the finite element differential equation in the educational informatisation teaching reform model

Abstract The dichotomy model of education informatisation is essential, which means the measurement of education informatisation construction and development. Finite element differential equations play an essential role in signal and information teaching. To improve teaching information, the paper applies the dichotomy model of finite element differential equations to the reform of physics education information teaching. This article fully introduces the basic principles of the dichotomy model in finite element differential equations and introduces several analysis methods of the inverse Laplace transform of differential equations. At last, the method is applied to the informatisation of physics education to improve the quality of teaching.
API Operations

In contrast with other domains in the API Marketplace, which are hyper-flexible and able to pivot or change direction on a dime, our realm of Operations is far more structured, organized, and focused. The team runs on a strict regimen of process and structure and is the foundation of the platform. Any other approach would result in a rapid descent into chaos, and the implementation would quickly be classified under the banner of a prototype. As the platform is an enabling ingredient for greater third-party applications, any internal or supporting system failure is likely to trigger a ripple effect which would eventually cause a larger impact resulting in poor perception of the third-party consumer’s customer-facing product or service.
Workshop Dan Pendampingan Pembuatan Game Edukasi Berbasis Android Bagi Guru SDN 2 Cakranegara

The Covid-19 pandemic has led to policies that make teachers and students have to adapt the face-to-face learning model to online learning. The teacher of SD N 2 Cakranegara admits that there are limitations to the variety of audio-visual learning media used. The teachers also don't know and have never tried to develop game games with learning content, even though Android-based games are very possible to be developed and accessed portable on smartphones, the majority of which are already owned by teachers and students. The provision of workshops and assistance in making Android-based educational games for SD N 2 Cakranegara teachers aims to improve skills in creating and developing learning media in the form of educational games and maximizing the use of smartphones. The targeted output in this service activity is the existence of educational games that are ready to be used for the online learning process through appsgeyser.com and quickappninja.com.&#x0D;
Keynote Day 2: Find an Expert: Who is best to represent a university on matters of 'open'?

Join us for ETD2021 (Electronic Theses and Dissertations) Conference in November 2021 in the United Arab Emirates. Our theme, ‘Open scholarship in a post-pandemic world’ addresses the enhanced need for discoverability of research findings in a virtual world. Since the global impact of the COVID-19 pandemic has constrained international travel and mobility, we have all come to rely on working in the virtual world. These developments have merely accelerated the existing trends towards more electronic and digital repositories. Since 1991, the Networked Digital Libraries of Theses and Dissertations (NDLTD) have contributed to research collaboration by identifying and aggregating digital repositories of theses and dissertations as a previously fugitive class of research resources.
Performance Analysis of ML Algorithms to Detect Gender Based on Voice

Gender classification is amongst the significant problems in the area of signal processing; previously, the problem was handled using different image classification methods, which mainly involve data extraction from a collection of images. Nevertheless, researchers over the globe have recently shown interest in gender classification using voiced features. The classification of gender goes beyond just the frequency and pitch of a human voice, according to a critical study of some of the human vocal attributes. Feature selection, which is from a technical point of view termed dimensionality reduction, is amongst the difficult problems encountered in machine learning. A similar obstacle is encountered when choosing gender particular features—which presents an analytical purpose in analyzing a human’s gender. This work will examine the effectiveness and importance of classification algorithms to the classification of gender via voice problems. Audial data, for example, pitch, frequency, etc., help in determining gender. Machine learning offers encouraging outcomes for classification problems in all domains. An area’s algorithms can be evaluated using performance metrics. This paper evaluates five different classification Algorithms of machine learning based on the classification of gender from audial data. The plan is to recognize gender using five different algorithms: Gradient Boosting, Decision Trees, Random Forest, Neural network, and Support Vector Machine. The major parameter in assessing any algorithm must be performance. Misclassifying rate ratio should not be more in classifying problems. In business markets, the location and gender of people are essentially related to AdSense. This research aims at comparing various machine learning algorithms in order to find the most suitable fitting for gender identification in audial data.
Introduction to Python

I hope you have glanced through the introduction section. If you have not, then I recommend reading it, as it will help you with the context and the philosophy of this book.
Intrinsically motivated option learning: a comparative study of recent methods

Options represent a framework for reasoning across multiple time scales in reinforcement learning (RL). With the recent active interest in the unsupervised learning paradigm in the RL research community, the option framework was adapted to utilize the concept of empowerment, which corresponds to the amount of influence the agent has on the environment and it’s ability to perceive this influence, and which can be optimized without any supervision provided by the environment’s reward structure. Many recent papers modify this concept in various ways achieving commendable results. Through these various modifications, however, the initial context of empowerment is often lost. In this work we offer a comparative study of such papers through the lens of the original empowerment principle.