Reviewerly/exHarmony huggingface dataset:
The Advantages of Human Evaluation of Sociomedical Question Answering Systems

The paper presents a study on question answering systems evaluation. The purpose of the study is to determine if human evaluation is indeed necessary to qualitatively measure the performance of a sociomedical dialogue system. The study is based on the data from several natural language processing experiments conducted with a question answering dataset for inclusion of people with autism spectrum disorder and state-of-the-art models with the Transformer architecture. The study describes model-centric experiments on generative and extractive question answering and data-centric experiments on dataset tuning. The purpose of both model- and data-centric approaches is to reach the highest F1-Score. Although F1-Score and Exact Match are well-known automated evaluation metrics for question answering, their reliability in measuring the performance of sociomedical systems, in which outputs should be not only consistent but also psychologically safe, is questionable. Considering this idea, the author of the paper experimented with human evaluation of a dialogue system for inclusion developed in the previous phase of the work. The result of the study is the analysis of the advantages and disadvantages of automated and human approaches to evaluate conversational artificial intelligence systems, in which the psychological safety of a user is essential.
An Improved Mean Filtering Algorithm for Measuring Data of Robotic Arm Force Sensor

Force sensor plays a very important role in the development and application of intelligent robot. Aiming at the problems of long sampling period, a large amount of calculation and poor real-time performance in the data processing of six axis force sensor of robotic arm, an improved mean filtering algorithm for the measurement data of robotic arm force sensor is proposed. By calculating the average value of the original signal and the original signal translated by n AD sampling intervals, the interference signal whose period is even multiple of the sampling interval can be quickly filtered. The six axis force sensor with cross beam is selected as the research object to carry out the weight loading experiment in F <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z</inf> direction. The experimental results show that the proposed algorithm reduces the operation time by 2/3 compared with the conventional mean filtering algorithm, and can quickly filter out the interference signal in the sensor signal processing circuit and retain the effective component of DC signal, which is suitable for the data processing of six axis force sensor.
Fractional Differentiation-Based Edge Energy Driven Active Contours for Robust Image Segmentation

In this paper, a new fractional differentiation-based active contour model for robust image segmentation is presented. A new edge energy is introduced, in which the contour evolution is driven by the difference between the fractional derivatives directed along the inward and outward normal directions of the evolving contour. We provide the level set formulation of this novel energy and show that this energy is minimized when there is an accurate alignment of the zeroth level set of the evolving contour with the actual object boundary. The proposed model outperforms other state-of-the-art active contour methods in eliciting weak/fuzzy boundaries in real world images and provides robust segmentation even under influence of various types of noise as quantified by segmentation metrics.
Linear Registration and Robot Motion Planning

This paper presents preliminary results of applying the image registration paradigm to robotics. Specifically, we explore a specific version of the image registration problem, called linear, whose registering diffeomorphism is defined by the flow of a linear, time-dependent dynamical system. Optimality conditions for the linear registration have been provided, and the registering diffeomorphism derived explicitly. Results are applied to motion planning of manipulation and mobile robots. Computer simulations serve as a means for evaluation of the results. An extension to multiple point robot motion planning is proposed.
Research on Blended Learning Practice Based on Student Engagement

Blended learning has become a mainstream teaching mode in the "Internet + Education" era.Improving student engagement is an effective way to improve the quality of blended learning.To study blended learning practice based on student engagement, we surveyed behavioral engagement, cognitive engagement and emotional engagement.The study found that the overall level of three engagements in blended learning practice is relatively high.However, there are also problems with low cooperative learning among students, weak interaction between students and teachers, and limited ability to expand knowledge.Three suggestions are given to strengthen the blended instructional design, utilize high-quality resources, develop learning platforms, and establish a good learning attitude.
Exploring the variable efficacy of Google speech-to-text with spontaneous bilingual speech in Cantonese and English

With the growth of Automatic Speech Recognition (ASR) and voice user interface software, it is important to test for efficacy across different language varieties and identify sources of bias. Recent work assessing ASR efficacy and bias implicates factors like race, gender, dialect, and age as leading to different efficacy rates. Multilingualism presents another source of variation that ASR systems must grapple with, ranging from code-switching to phonetic variation both within and across speakers. Thus, variable ASR performance is likely exacerbated for multilingual communities. Using a spontaneous Cantonese-English bilingual speech corpus (Johnson, 2021), this study tests the efficacy of Google Speech-To-Text (STT) language models (Canadian English and Hong Kong Cantonese) with a heterogeneous bilingual speech community. Efficacy is assessed via fuzzy string matching between the STT and the manually corrected transcripts. STT performance is variable but overall better for English. Confidence ratings and matching scores are evaluated alongside listener ratings of perceived accentedness and various demographic groupings. The results of this study will provide practical guidance for using STT in the context of speech production research pipelines while highlighting its drawbacks concerning bias in a relatively understudied, multilingual group.
ERROR ANALYSIS OF SIMPLE PRESENT TENSE SENTENCES IN ENGLISH BY INFORMATION SYSTEMS STUDENTS

This research is a qualitative descriptive research. The purpose of this study was to determine students' understanding in making simple sentences with simple present tense patterns, the types of grammatical errors made by students in making simple sentences with simple present tense patterns, grammatical errors that generally occur in making simple sentences with simple present tense patterns. The subjects of this research are students of semester 1, class A, Information Systems study program. The data collection technique was done by written test. In the written test, the researcher used a written test instrument in the form of English questions about the simple present tense. The written test questions are in the form of multiple choice and essay. The test questions are divided into 3 parts in the tryout test, namely completing sentences, making sentences, and translating sentences. In the third meeting, students complete sentences, answer questions and make a simple present tense paragraph. Based on the research, it was found that: after students were given another explanation about simple present tense sentences, 20 students out of 27 students (74%) answered using simple present tense sentences correctly. It can be said that there has been a 26% increase in understanding of simple present tense sentence patterns.&#x0D;
Techno-pedagogical competency of higher secondary school teachers in relation to students’ academic achievement in science

More than three decades ago computers and related information technologies were introduced to education for direct teaching and learning purposes. It started with the presentation of the software to CAL/CBT/CAI and then moving multimedia course and finally to learning management system using open and flexible learning. Every day new scientific and technological innovations are taking place. These innovations are to be implemented in the field of educational theory and practice. Technology interferes; each aspect of human life, including the field of education. Being a teacher one should know the importance of technology as it had made the student to understand easily the content deliver by the teacher. When it came to teaching theories, the Teachers should give up the mechanical approach and make it interesting by simulating problems and finding solutions to such imaginary issues. The purpose of this study is to determining the technological and pedagogical competency of higher secondary school teachers with the relation to students’ academic achievement in science. This is a descriptive study. It was conducted using the survey model. This research aims to investigate whether the academic achievements in science of higher secondary school students and the techno-pedagogical competency of their teachers show statistically significant relationship in terms of some variables like gender and locale. The study was administered upon 100 teachers and 100 students of Cuttack district. And the findings of the study were revealed that majority of teachers were having moderate level techno-pedagogical competency and teachers belong to urban area were having high techno-pedagogical competency than that of rural area because of the variability in facilities available in urban and rural school. The techno-pedagogical competency of teachers and academic achievement of students are related each other.
EDUCATION OF TALENTED HIGH SCHOOL STUDENTS BY DESIGNING RESEARCH IN ELEMENTARY PARTICLE PHYSICS

N. Dzelalija1, M. Dzelalija2 1III. Gimnazija, Prirodoslovno-matematička gimnazija, Split (CROATIA) 2University of Split, Faculty of Science (CROATIA)
EFEKTIVITAS PENGGUNAAN MEDIA VIDEO PEMBELAJARAN DI RANAH SEKOLAH DASAR DALAM METODE PEMBELAJARAN ELEKTRONIK

This study aims to determine the difference in the effectiveness of other learning methods with learning methods using SD thematic learning videos in the Pembelajaran elektronik method. This study uses a meta-analysis research type, namely using several studies that have been conducted. This research method is quantitative. This study aims to determine the effectiveness of using SD Thematic Learning Video Media in the Pembelajaran elektronik Method. Research data collection was carried out by searching Google Scholar using the keywords effectiveness, instructional video media, thematic, elementary students, and Pembelajaran elektronik. The results of the analysis show that the use of SD thematic learning videos in the Pembelajaran elektronik method has increased interest in learning from the lowest 14.08% to the highest 76.18% with an average of 40.86%. Keywords : effectiveness, instructional video media, thematic, elementary students, and E-Learning
The Importance of Intrinsic Factors in Keeping Employees Motivated: The Difference between Public and Private Sectors

The topic of motivation has been researched over the years and it will continue in the future due to its significant impact to the individual employee and the organization as a whole. Although there are numerous established models of motivation, a specific study on a specific organization is required due to organizational cultural and attributive differences. This study was undertaken to investigate the intrinsic factors that motivate service employees to do their job. A total of 113 respondents participated in the survey questionnaire that was distributed using online means to various organizations; public and private. Factor analysis confirmed the existence of the studied factors and all other analysis results indicate the usability of the data. The results indicate that out of six intrinsic factors, four factors are significant to motivate service employees to do their job. The significant factors are advancement, recognition, growth, and achievement while the non-significant factors are the work itself and responsibility. Types of organization did not moderate the relationship between the predictor variables and the outcome variable. The implications of the study are discussed.
Spectral content of the attack portion of the tone produced by a soprano recorder

We have used Navier-Stokes-based modeling to calculate tones produced by a full-size soprano recorder. Of all the wind instruments, the player of a recorder has relatively little impact on the tone that is produced. However, one thing that the player does control is the way that the blowing pressure is increased from zero at the start of a tone to a final value that is maintained until the end of the tone. We show how the ramp-up time for the blowing pressure has a profound effect on the spectral content of the attack portion of the tone. Using a correlation analysis, we explore this spectral content and consider how it can, in certain blowing regimes, be an important and audible contributor to the tone color produced by a recorder. [Work supported by NSF grant PHY1513273.]
LibGuides: 4th Grade Social Studies Resources: Culture

This guide will serve as a resource for 4th grade students to discover necessary resources to complete their 4th grade Social Studies projects.
Introduction to Climate Change

Summary A lecture presentation has been developed that introduces physics students to the science of climate change and its impact in society. Student feedback indicates a high level of satisfaction with the presentation. Keywords; climate, model, energy, physics, environment, education
SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks

The security is important issue in wireless networks. This paper discusses audio watermarking as a tool to improve the security of image communication over the IEEE 802.15.4 ZigBee network. The adopted watermarking method implements the Singular-Value Decomposition (SVD) mathematical technique. This method is based on embedding a chaotic encrypted image in the Singular Values (SVs) of the audio signal after transforming it into a 2-D format. The objective of chaotic encryption is to enhance the level of security and resist different attacks. Experimental results show that the SVD audio watermarking method maintains the high quality of the audio signals and that the watermark extraction and decryption are possible even in the presence of attacks over the ZigBee network.
The use of knowledge graphs in the educational environment for personalized learning

The article presents some methods for creating knowledge graphs – hierarchical structures used in the educational environment for course development. It is found that the educational environment requires subject-oriented knowledge graphs, for the creation of which the methods of creating general and open graphs are not suitable. The methods of constructing the system of notions of educational discipline on the basis of: analysis of educational texts; human activity in the studied subject area; analysis of the structure of the main sections of knowledge are considered. The central aspect of the study was the possibility of using the resulting tree of concepts to form the content of the training course and to build an individual educational trajectory. The results of the work demonstrate the possibility of applying the developed hierarchical structures to personalize learning. The practical significance of the obtained results lies in the fact that the proposed solutions are focused on computer implementation and are relevant for the management of the learner’s learning activities in the electronic environment. The proposed methodology involves the participation of professional and scientific communities, teachers and students in the development of the knowledge graph. This makes it possible to develop subsequently, on the basis of these graphs, training programs, taking into account the demands of the labor market, the capabilities of the training organization, as well as the goals of trainees. One important indicator of the quality of knowledge graphs is their relevance to a dynamically changing environment. The ability to build up knowledge graphs allows to maintain the relevance of training courses and individual educational trajectories created on their basis.
A Braided Lambda Calculus

We present an untyped linear lambda calculus with braids, the corresponding combinatory logic, and the semantic models given by crossed G-sets.
Finite-key-size Effect in Asymmetric Twin-Field Quantum Key Distribution

Twin-Field(TF) quantum key distribution(QKD) is attracting attention due to the possibility of implementing long-range QKD. However, due to the finite-size effect, the secret key rate becomes relatively low. The statistical fluctuation analysis of the four-intensity decoy-state asymmetric TF-QKD system is considered in this study, and optimized parameters for the Gaussian approximation method are also presented.
Parallel Ping-Pong: Demonstrating Parallel Interaction through Multiple Bodies by a Single User

We explore a “Parallel Interaction”, where a user controls several bodies concurrently. To demonstrate this type of interaction we developed “Parallel Ping-Pong”. The user plays ping-pong by controlling 2 robot arms with a Virtual Reality (VR) controller, and while looking from the viewpoint of one of the 2 robot arms with a Head Mounted Display (HMD). The HMD view switches between the 2 robot arms’ viewpoints according to the ping-pong ball position and direction. To keep the sense of agency over the robot arms (hindered by the system latency), the robot arms calculate the balls’ paths and position themselves to hit the balls back; all while integrating the controller motion. Throughout this demonstration, we investigate a real-life design of Parallel Interaction with multiple bodies by a single user.
ISPOL'ZOVANIYE SOVREMENNYKH METODOV ELEKTRONNOGO OBUCHENIYA V VUZE

The article discusses the forms and methods that are optimal for use in e-learning: heuristic, research, game, diagnostic, information-receptive and reproductive. The e-learning environment today represents a wide range of educational technologies, methods and tools that can be used to organize full-fledged education at a university.
Knowledge Organization Affordances in a Faceted Online Public Access Catalog (OPAC)

Faceted navigation is already a standard feature of contemporary Online Public Access Catalogs (OPACs). The article aims to indicate practices in this area and new affordances that faceted navigation provides. The content of 55 Polish university library websites and their OPACs using faceted navigation was analyzed. After selecting the subject facets, the source of the terms constituting their content was analyzed using the MARC 21 bibliographic record format structure. During the transfer of traditional KOS affordances to those of faceted navigation, the former knowledge organization (KO) structures were deconstructed, which may require the creation of a new kind of KOS.
Design and Implementation of Interactive Virtual Museum based on Hand Tracking OpenCV in Indonesia

Covid-19 Pandemic forces people to physical distancing. It affects the business of Museum, especially National Defense Museum. This research designs the National Defense Interactive Virtual Museum in Jakarta, Indonesia, based on OpenCV mediapipe hand and PyautoGUI. The system used MDLC method. OpenCV mediapipe hand is used to generate the method of Interactive program for Users. The virtual museum https://museumnasional.iheritage.id/ is used in this research. The result is that National Defense Interactive Virtual Museum Application can recognize the movement of users' hands using mediapipe hand to control mouse. Moreover, the resources which are used by program are 81 % CPU, 44% of RAM 8GB, and 90% Disk resources. Based on the results, the program requires high performances PC to run smoothly.
Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets

The adoption of electronic health records (EHRs) has made patient data increasingly accessible, precipitating the development of various clinical decision support systems and data-driven models to help physicians. However, missing data are common in EHR-derived datasets, which can introduce significant uncertainty, if not invalidating the use of a predictive model. Machine learning (ML)-based imputation methods have shown promise in various domains for the task of estimating values and reducing uncertainty to the point that a predictive model can be employed. We introduce Autopopulus, a novel framework that enables the design and evaluation of various autoencoder architectures for efficient imputation on large datasets. Autopopulus implements existing autoencoder methods as well as a new technique that outputs a range of estimated values (rather than point estimates), and demonstrates a workflow that helps users make an informed decision on an appropriate imputation method. To further illustrate Autopopulus’ utility, we use it to identify not only which imputation methods can most accurately impute on a large clinical dataset, but to also identify the imputation methods that enable downstream predictive models to achieve the best performance for prediction of chronic kidney disease (CKD) progression.
Cartoon Sliding: An MR System for Experiencing Sliding Down a Cliff

We present an MR system for experiencing the cartoon-like event of sliding down a cliff and stopping by sticking a knife, with enhancement of tactile and muscle stimuli. A player grabs a knife device and presses it against a wall device that rotates upwards in contrast to the player who virtually slides down. We demonstrate an MR content in which a player experiences sliding down the virtual cliff while handling the knife device on the rotating wall device.
My(o) Armband Leaks Passwords

Wearables that constantly collect various sensor data of their users increase the chances for inferences of unintentional and sensitive information such as passwords typed on a physical keyboard. We take a thorough look at the potential of using electromyographic (EMG) data, a sensor modality which is new to the market but has lately gained attention in the context of wearables for augmented reality (AR), for a keylogging side-channel attack. Our approach is based on neural networks for a between-subject attack in a realistic scenario using the Myo Armband to collect the sensor data. In our approach, the EMG data has proven to be the most prominent source of information compared to the accelerometer and gyroscope, increasing the keystroke detection performance. For our end-to-end approach on raw data, we report a mean balanced accuracy of about 76 % for the keystroke detection and a mean top-3 key accuracy of about 32 % on 52 classes for the key identification on passwords of varying strengths. We have created an extensive dataset including more than 310 000 keystrokes recorded from 37 volunteers, which is available as open access along with the source code used to create the given results.