Reviewerly/exHarmony huggingface dataset:
The Use of Chain Word Game as Vocabulary Building Activity in Vocational High School

This paper aims to describe the implementation of chain word game in vocational high school in automotive program in order to improve students’ vocabulary knowledge. This research is self-observational study that involves a class that consist of 36 students. The data were obtained from the assignment given to students regarding to basic competence designed by Indonesia’s government which was giving congratulation and compliment and its responses. In this study, fun learning plays important role to maintain students’ engagement and giving reward system to appreciate students’ activeness is applied to keep the students’ motivated. The findings from data showed that misspelled words were found less in the students’ assignment that have been collected.
Sharing Secrets with Agents: Improving Sensitive Disclosures Using Chatbots

There is an increasing shift towards the use of conversational agents, or chatbots, thanks to their inclusion in consumer hardware (e.g. Alexa, Siri and Google Assistant) and the growing number of essential services moving online. A chatbot allows an organisation to deal with a large volume of user queries with minimal overheads, which in turn allows human operators to deal with more complex issues. In this paper we present our work on maximising responsible, sensitive disclosures to chatbots. The paper focuses on two key studies, the first of which surveyed participants to establish the relative sensitivity of a range of disclosures. From this, we found that participants were equally comfortable making financial disclosures to a chatbot as to a human. The second study looked to support the dynamic personalisation of the chatbot in order to improve the disclosures. This was achieved by exploiting behavioural biometrics (keystroke and mouse dynamics) to identify demographic information about anonymous users. The research highlighted that a fusion approach, combining both keyboard and mouse dynamics, was the most reliable predictor of these biographic characteristics.
RATT: Leveraging Unlabeled Data to Guarantee Generalization

To assess generalization, machine learning scientists typically either (i) bound the generalization gap and then (after training) plug in the empirical risk to obtain a bound on the true risk; or (ii) validate empirically on holdout data. However, (i) typically yields vacuous guarantees for overparameterized models. Furthermore, (ii) shrinks the training set and its guarantee erodes with each re-use of the holdout set. In this paper, we introduce a method that leverages unlabeled data to produce generalization bounds. After augmenting our (labeled) training set with randomly labeled fresh examples, we train in the standard fashion. Whenever classifiers achieve low error on clean data and high error on noisy data, our bound provides a tight upper bound on the true risk. We prove that our bound is valid for 0-1 empirical risk minimization and with linear classifiers trained by gradient descent. Our approach is especially useful in conjunction with deep learning due to the early learning phenomenon whereby networks fit true labels before noisy labels but requires one intuitive assumption. Empirically, on canonical computer vision and NLP tasks, our bound provides non-vacuous generalization guarantees that track actual performance closely. This work provides practitioners with an option for certifying the generalization of deep nets even when unseen labeled data is unavailable and provides theoretical insights into the relationship between random label noise and generalization.
Virtual reality training platform for a computer numerically controlled grinding machine tool

In-depth training of machine tool (MT) operators is crucial to avoid machine damage due to faulty operation. However, machine-hours are costly and during the training, the MT is unavailable for regular production purposes. Here, virtual real-size models offer a solution by providing basic operation principles to future operators. In this context, it is yet unknown whether a virtual teaching enhanced by real walking is similar to a real teaching scenario regarding the learning efficiency and long-term memory retention. This paper describes a study comparing the learning efficiency of a virtual training session with traditional instructions on a real MT. The learning success of both training groups is objectively and subjectively assessed on a real MT a week later. In this assessment, the task completion time and the number of errors are recorded. We observed that the virtually taught group slightly outperformed trainees taught in reality regarding both objective measurements.
A Study on the Prospect of Using IoMT for Disease Prevention and Management

Background/objectives: With the development of IT technology and interdisciplinary convergence technology, interest in medical services, healthcare, bioinformatics, and public management is increasing. It is changing from passive disease management to active disease management using IoT devices. Methods/Statistical analysis: Due to the paradigm shift in the medical and health industries due to the Fourth Industrial Revolution, interest in disease prevention including disease management is increasing. Research on the Internet of Medical Things is being actively conducted as a method for such disease prevention and management services. Therefore, in this paper, we will examine medical ICT devices, healthcare devices, and IoMT in the IoT environment, and propose an efficient use method of IoMT for disease prevention and management and a prospect for this. Findings: In order to smoothly operate disease prevention and management based on the IoMT environment, problems such as expansion of ICT infrastructure, development of the system, and training of experts are expected to be solved. Improvements/Applications: In addition, in the use of IoMT, reorganization of policies and legal systems, improvement of security technology and awareness of personal information, and user consent for sensitive information are tasks to be resolved.
Generación de ambientes virtuales para la modalidad de educación a distancia.

The objective of this scientific article was to identify the generation of virtual environments for distance education in Private Universities in the city of Santa Marta, Department of Magdalena, Colombia, based on theoretical contributions from different authors in relation to the area of Virtual environments such as: Silvio (2000), Moreno (2001), Barajas (2003), Garcia (2007), Basabe (2007), Galvis (2008). The type of research that was used is framed by the descriptive, field, non-experimental and descriptive transectional type. The study population was made up of seventy-eight (78) subjects, from the Universidad Antonio Narino, Universidad de Magdalena and Universidad Cooperativa de Colombia. The information was collected through the application of one (1) instrument that consisted of twelven (12) items with five (5) response alternatives, aimed at the study subjects. This instrument was validated through the judgment of five (5) experts. Reliability was calculated using the Alpha Cronbach Statistical Coefficient, the result of which was r = 0.91, which indicated that the instrument is of very high reliability. The results of the study allowed the need to carry out a management analysis of virtual environments aimed at optimizing current management processes and strengthening the distance education modality available to the universities under study, for which the creation of guidelines was concluded. theoretical - practical to increase the values ​​in the performance of managers.
Automatic Extraction of Slides from Scientific Papers

Presentations slides have been an important and effective way to deliver the key information of a scientific paper, especially in conferences. Normally the speakers have to spend a major amount of time preparing for making slides because scientific papers are different to read and summarize the content. Automatic extraction of slides from scientific papers will be quite helpful and time-saving during the preparation of presentation slides by providing the keywords and bullet points. [Yue Hu et al., 2015] introduced a system called PPSGen, it can automatically generate presentation slides for academic papers which can be used as drafts to help the writing of the final presentation. The tool applies a Support Vector Regressor (SVR) model for sentence ranking and then Integer Linear Programming(ILP) model is used to select important sentences with a set of sophisticated constraints. In this paper, a system extends the PPSGEN system is proposed to automatically extracting the presentation slides from scientific papers. It firstly applies an unsupervised summarization algorithm to rank the input sentences in the academic paper based on relative importance.Then, it selects the key sentences and phrases to include in each slide using a optimization-based algorithm, which is based on an Integer Linear Programming (ILP) Module. Finally the selected key sentences and phrases can be used to output the well-structured slides. The evaluation rouge results is based on the test of 195 paper-slides pairs which is collected from the website. Our goal is to compare the performance of unsupervised and supervised learning models, to verify whether a unsupervised learning model could get a better rouge score than a supervised one and finally to find a better performance system for automatically extracting presentation slides from scientific papers. Based on our current evaluation rouge results, supervised learning models performs better than unsupervised learning models and RFR can have a higher rouge score (ROUGE-1-F, ROUGE-2-F, ROUGE-SU4-F ) among the other supervised learning models.
Maryland State Library LibGuides: Grants for Public Libraries: MSL Grants Management System Guidance

Information on LSTA grants and other funding opportunities. How to Create a Grant Application on the MSL Grants Management System, how to submit a reimbursement, and how to request a grant revision.
How to Increase the Usability of a Power BI Report through Report Design

Report design is critical for the effective and efficient consumption of information. This presentation outlines established design principles to improve BI report designs and shows how to measure the added value (usability) of report re-designs. The presentation is enriched with a live-demo from a recent Power BI re-design research project at the University of St.Gallen (HPC – House of Performance Cockpit).
Breast Cancer observation using Python

Worldwide cancer growth confirms more than 2 million ladies determined to have breast cancer every year reflecting larger part of new cancer growth cases and related deaths, making it critical general wellbeing concern. However, luckily, it is likewise the treatable disease in its beginning phase. Early determination of breast cancer with opportune and powerful treatment administrations improves the visualization and endurance of patients. During grouping tumors, there are critical odds of mistake and false conclusion which is should have been worked upon. Precise classification can keep patients from pointless medicines. Along these lines, it is imperative to precisely characterize patients into dangerous and kind gatherings with right finding. This investigation depends on machine learning (ML) calculations, planning to survey python strategy and its application in breast cancer finding and forecast by building basic AI model. AI has remarkable favorable position as it distinguishes basic highlights from complex breast cancer datasets. The technique is broadly utilized for arrangement of example and gauge demonstrating. The essential information for this examination is extricated from Wisconsin breast cancer information base (WBCD). It is the benchmark information base which thinks about outcome by means of various calculations. Keywords: Breast Cancer, machine learning, Python, Wisconsin breast cancer information base Cite this Article Vani Tirpathi. Breast Cancer observation using Python. Research & Reviews: A Journal of Bioinformatics . 2020; 7(3): 15–33p.
Quantum process tomography of adiabatic and superadiabatic Raman passage

Quantum control methods for three-level systems have become recently an important direction of research in quantum information science and technology. Here we present numerical simulations using realistic experimental parameters for quantum process tomography in STIRAP (stimulated Raman adiabatic passage) and saSTIRAP (superadiabatic STIRAP). Specifically, we identify a suitable basis in the operator space as the identity operator together with the 8 Gell-Mann operators, and we calculate the corresponding process matrices, which have $9\times 9=81$ elements. We discuss these results for the ideal decoherence-free case, as well as for the experimentally-relevant case with decoherence included.
MUB-like structures and tomographic reconstruction for N-ququart systems

We construct an informationally complete set of mutually unbiased—like bases for any number of ququarts. These bases are used in an explicit tomographic protocol which performance is analysed by estimating quadratic errors and compared to other reconstruction schemes.
Motivational Aspects of Research Activities of University Students in Modern Conditions

This paper discusses modern approaches to motivating students to participate in research activities of Universities and their effectiveness in the conditions of Informatization of society. The authors draw conclusions about the applicability of various types of incentives for research activities of University students in modern realities. Within the framework of this topic, a study was conducted to identify the level of motivation of students on the example of Samara state University of Economics and presented methods to increase the motivation of University students to research activities, based on the results of the current level and the analysis of the applicability of these approaches in practice.
Application of Blockchain Technology in Short Video Ecosystem

Driven by mobile technology, the short video industry has shown an explosive growth trend in recent years. This paper discusses the current situation of the short video industry and the problems existing in the short video business circle. Combined with the current application scenarios of blockchain technology, this paper discusses the necessity of building a new ecosystem based on blockchain, presents a method to solve the problems related to short video ecosystem by using blockchain smart contract and other technologies, and introduces the application process of blockchain in data sharing, smart contract, asymmetric encryption and other key technologies in the new ecosystem. Finally, according to the analysis of the application process, the possible problems are put forward and suggestions are given.
Image confusion and diffusion based on multi-chaotic system and mix-column

In this paper, a new image encryption algorithm based on chaotic cryptography was proposed. The proposed scheme was based on multiple stages of confusion and diffusion. The diffusion process was implemented twice, first, by permuting the pixels of the plain image by using an Arnold cat map and, the second time by permuting the plain image pixels via the proposed permutation algorithm. The confusion process was performed many times, by performing the XOR operation between the two resulted from permuted images, subtracted a random value from all pixels of the image, as well as by implementing the mix column on the resulted image, and by used the Lorenz key to obtain the encrypted image. The security analysis tests that used to exam the results of this encryption method were information entropy, key space analysis, correlation, histogram analysis UACI, and NPCR have shown that the suggested algorithm has been resistant against different types of attacks.
Psychological aspects of learning english

The article discusses issues of effective learning and mastering a foreign language and factors affecting the learning process. The author focuses on the methodological and psychological aspects of this process. The effectiveness of learning and mastering a foreign language, its further professional use, in addition to the teacher’s talent to use the correct method of presenting and activating teaching material, the ability to build trust with students and create a comfortable environment for them in the classroom, depends largely on psychological factors, on the students’ ability to change established ideas about their ability to assimilate and freely use foreign language speech both in class and in real life.
Možnosti identifikace silně poškozených mohylových náspů nedestruktivními metodami: případová studie Sedlec-Hůrka

This work addresses the possibility of identification of heavily damaged tumuli by non-destructive methods. We targeted the known location of tumulus cemetery Sedlec-Hůrka, which had been excavated by the West Bohemian amateur archaeologist Frantisek Xaver Franc in 1883. Our article is divided into three main parts. In the introduction, we describe the natural environment of the studied site and our goals and methods. The next section describes the site itself: the number of mounds identified in a 19th century plan and archaeologically excavated. Particularly, reasons of their destruction (archaeological excavation and agriculture), the composition of the cemetery and typical features of burial mounds (construction, ground plan, skeletal remains and burial goods), as well as their cultural affiliation (Middle Bronze Age Tumulus Culture, Late Bronze Age Milavce Cul - ture and Hallstatt Period). The last part concerns our non-destructive research. We conclude that surface visual survey was ineffective, aerial photography could identify the destroyed tumuli only in optimal conditions, and lidar survey detected small terrain anomalies in places of most burial mounds. Soil geochemistry indicated significant differences in concentrations of K, Ti, Mn, and Pb in the locations of former tumuli, compared to background values in the surrounding topsoil.
Pengaruh Model Pembelajaran Problem Based Learning Terhadap Hasil Belajar Matematika Siswa Kelas Vii SMPN 4 Siak Hulu

This research was aimed to determine the effect of Problem Based Learning model on the learning outcomes of mathematics in grade VII students of SMP Negeri 4 Siak Hulu. The research was conducted in the even semester of the 2017/2018 school year. This sample was taken using purposive sampling. The form of this research is a quasi experiment. The research sample was class VII5 as the experimental class which received treatment with the Problem Based Learning and VII3 learning models as the control class that received treatment in the form of conventional learning using the 2013 curriculum. The data collection technique in this study was carried out by the test technique. Data obtained from the results of the study in the form of pretest and posttest value data were analyzed using descriptive analysis and inferential analysis. After analyzing the research data of experimental class and control class mathematics learning outcomes, it was shown that the average experimental class mathematics learning outcomes were higher than the control class both in the assessment of knowledge and skills assessment, this means that the Problem Based Learning learning model had a positive effect on knowledge assessment and student math skills. So that from the results of the study it can be concluded that there is the influence of the Problem Based Learning learning model on the mathematics learning outcomes of class VII students of SMP Negeri 4 Siak Hulu.
Augmented cut and paste

Augmented reality (AR) is an intelligent involvement of a real-world environment where the objects that dwell inside the world are upgraded by computer-generated perceptual data, now and then over numerous sensory modalities, including visual, auditory, haptic, somatosensory, and olfactory. AR is regularly characterized as a framework that fulfills three essential highlights: a blend of genuine and virtual universes, real-time interaction, and exact 3D enlistment of virtual and genuine objects. The overlaid sensory information can be constructive (i.e. additive to the natural environment), or destructive (i.e. masking of the natural environment). This involvement is consistently interlaced with the physical world such it’s seen as an immersive angle of the vital environment. In human–computer interaction and interface plan, cut, duplicate and glue are related commands that give an inter-process communication method for exchanging information through a computer’s interface. The cut command evacuates the chosen information from its unique position, whereas the duplicate command makes a copy; in both cases, the chosen information is kept in transitory capacity (the clipboard). The information from the clipboard is afterward embedded wherever a glue command is issued. The information remains accessible to an application supporting the highlight, in this way permitting simple information exchange between applications. With modern developments in machine learning, it's possible to accurately detect people and objects around us, remove the background automatically and transfer the result to a computer. To date, AR had been utilized to venture advanced pictures into the genuine world. However, the “AR Cut & Copy” app reverses the process and brings physical things into the digital world.
A Note on Confluence in Typed Probabilistic Lambda Calculi

On the topic of probabilistic rewriting, there are several works studying both termination and confluence of different systems.While working with a lambda calculus modelling quantum computation, we found a system with probabilistic rewriting rules and strongly normalizing terms.We examine the effect of small modifications in probabilistic rewriting, affine variables, and strategies on the overall confluence in this strongly normalizing probabilistic calculus.
A COMPARATIVE ANALYSIS OF THE SEAFARING CAREER PERSISTENCE OF NAUTICAL POST-BACCALAUREATE AND COLLEGE STUDENTS

To foster more maritime human resources, Taiwan's Ministry of Education began to approve the establishment of nautical post-baccalaureate programs at three maritime universities in 2010. This study conducted a comparative analysis of the seafaring career persistence of nautical post-baccalaureate students and college students. Social cognitive career theory (SCCT) served as the research perspective, and data were collected through a questionnaire survey on persistence in the seafaring profession. The collected data were analyzed using structural equation modeling (SEM). This study revealed that seafaring career persistence, self-efficacy, and positive outcome expectation for seafaring careers were significantly higher among the post-baccalaureate students than they were for the college students. In addition, among the post-baccalaureate students, positive outcome expectation had the most significant direct effect on seafaring career persistence, whereas among the college students, vocational interest had the most significant effect on seafaring career persistence. The research findings are discussed in depth in this paper.
API Pipeline for Visualising Text Analytics Features of Twitter Texts

Twitter text analysis is quite useful in analysing emotions, sentiments and feedbacks of consumers on products and services. This helps the service providers and the manufacturers to improve their products and services, address serious issues before they lead to a crisis and improve business acumen. Twitter texts also form a data source for various research studies. They are used in topic analysis, sentiment analysis, content analysis and thematic analysis. In this paper, we present a pipeline for searching, analysing and visualizing the text analytics features of twitter texts using web APIs. It allows to build a simple yet powerful twitter text analytics tool for researchers and other interested users.