Reviewerly/exHarmony huggingface dataset:
WearEC Kits: Designing Toolkits for Exploring Subtle Visual Outputs on Wearables with Electrochromic Displays

For designers, exploring subtle visual output modalities in the early phases of wearable design is a challenging task. In this work, we present the design and implementation of two toolkits, Transparent and Programmable WearEC Kits, that aim to enable designers to quickly explore electrochromic displays (EC) as a subtle output modality for wearables. EC displays are graphical displays that transition between two predefined visual states when a small voltage is applied. They are flexible, transparent and can be fabricated in a free-form shape, which makes them fitting candidates for designing wearables. Our work contributes the description of the novel design and implementation of the WearEC kits and reports a design exploration study conducted with a fashion designer.
Social Media as a Tool for the Development of Future Journalists’ Communicative Competence

The aim of the work was to test the opportunities that social media offers on the Internet as a tool to improve the future journalists’ communicative competence. Sociological methods were involved in the research in order to achieve its aim: a method of testing respondents to identify their initial level of communicativeness on the Communicative Competence Test and the Questionnaire Survey Method to obtain feedback from participants in the experiment. Working on media content on the Internet proved to improve communication skills of future journalists with the help of popular YouTube media and blogs with bright visual content. It was found that media resources can be used during lectures to stimulate interest and to engage students in active learning that promote deeper knowledge. The possibility of involving online mass media in joint learning, problem solving, interactive lecture demonstrations, as well as discussions was noted. A number of difficulties that the course participants encountered were found: a thorough understanding of copyright law, increased workload, lack of skills in working with electronic text, video and audio content, increased visual load. However, these difficulties did not affect the quality of training and allowed the participants to improve not only communication skills but also digital information skills and online media literacy. It was proved that social media is a powerful additional tool that encourages students to actively study, get high results and sustainable professional skills that are in demand in the future workplace. The media cannot, however, replace traditional teaching methods which are based on personal communication. Further research is required on complex long-term courses that use a wider range of media, including Tik-Tok, Facebook, Instagram, extended blogs in the form of a multipage website, a funnel for gathering the target audience and subscribing.
Uma janela para dentro da nossa alma: apoiando o professor inclusivo, padrões para a formação inicial de professores na Irlanda

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Semi‐supervised pedestrian and face detection via multiple teachers

Semi-supervised learning aims to boost the model performance by large amounts of unlabelled data, thereby reducing the overheads of labelling. For joint pedestrian and face detection in real-world scenarios, the existing semi-supervised object detection methods rarely focus on the category relevance between samples, resulting in unsatisfied classification performance. And it is not effective for existing semi-supervised methods to integrate the categories from two datasets to obtain an ensemble network. In this work, a novel approach aiming to fully utilise category-relevant information is proposed. Firstly, the multi-teacher distillation for decoupling pedestrian and face categories are introduced to eliminate category unfairness in distillation process. Second, a coupled attention module embedded in classification head of the student network is proposed to better grasp the relevance of different categories from teachers and guide distillation. Moreover, the constraint loss is designed for stabilising the training process and better converging, so as to tailor a versatile student. The experimental results on the CrowdHuman and WiderFace benchmarks demonstrate the superiority of the approach over the state-of-the-art methods.
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts

The relevance of the Key Information Extraction (KIE) task is increasingly important in natural language processing problems. But there are still only a few well-defined problems that serve as benchmarks for solutions in this area. To bridge this gap, we introduce two new datasets (Kleister NDA and Kleister Charity). They involve a mix of scanned and born-digital long formal English-language documents. In these datasets, an NLP system is expected to find or infer various types of entities by employing both textual and structural layout features. The Kleister Charity dataset consists of 2,788 annual financial reports of charity organizations, with 61,643 unique pages and 21,612 entities to extract. The Kleister NDA dataset has 540 Non-disclosure Agreements, with 3,229 unique pages and 2,160 entities to extract. We provide several state-of-the-art baseline systems from the KIE domain (Flair, BERT, RoBERTa, LayoutLM, LAMBERT), which show that our datasets pose a strong challenge to existing models. The best model achieved an 81.77% and an 83.57% F1-score on respectively the Kleister NDA and the Kleister Charity datasets. We share the datasets to encourage progress on more in-depth and complex information extraction tasks.
Model for the formation of students’ interest in STEM through geometry learning based on visual spatial abilities using augmented reality technology

STEM education is one of the primary priorities in the Malaysian Education Blueprint (PPPM) 2013-2025, in line with the relevance of STEM at the global level. In keeping with the educational needs of 21st-century learning, the use of technology in education is also highly encouraged. Unfortunately, the Malaysian government's goal of producing one million experts in Science, Technology, Engineering, and Mathematics (STEM) by 2020 was not met because the 60:40 STEM: non-STEM policy failed to meet the goal. Students' interest in different STEM disciplines has been linked to their interest in integrated STEM in previous studies. Students' lack of interest in STEM fields appears to have an impact on their low mathematics achievement at the international assessment level, including in the field of geometry. Geometry is one of the most important branches of mathematics, and spatial thinking goes hand in hand with it. This paper presents the results of a critical review as well as a brief overview of ongoing research targeted at developing a model for the formation of interest among secondary school students in STEM through geometry learning based on augmented reality (AR) technology and visual-spatial abilities. The first part of the paper provides an in-depth review of these matters based on rather limited resources. The review revealed various difficulties and limitations in piquing students’ interest in STEM and mathematics. The second part describes research being conducted by the researchers to examine the implementation of using AR in geometry learning based on visual-spatial abilities. For the pilot and main stages of the study, pre-and post-test, observations, and semi-structured interviews will be conducted. The data will be analysed quantitatively and qualitatively, and the theory of change approach will be applied. The findings will be used to develop a model for the formation of interests among students as a result of geometry learning. The model aims to provide some relevant information for technology-assisted mathematics instruction, and it aligns with national STEM policy goals of increasing the number of students selecting STEM disciplines in secondary and higher education.
Modeling the number of early detection of cervical cancer in Lampung province using the generalized linear model

In Indonesia, the highest death from cancer in women is cervical cancer and breast cancer. The Indonesian government makes efforts to prevent cervical cancer by conducting early detection targeting women aged 30-50 years which is carried out at every health center in Indonesia. Lampung is one of the provinces with the highest prevalence on the island of Sumatra. The purpose of this study is to model the number of early detection of cervical cancer detections in Lampung Province using the Generalized Linear Model (GLM). This research was conducted using a descriptive quantitative approach. The result of this research is that the negative binomial regression model is used to overcome the case of overdispersion, and two predictor variables that affect the number of cervical cancers are obtained, namely cervical examination (X2) and suspected cancer (X3).
Does Typological Blinding Impede Cross-Lingual Sharing?

Bridging the performance gap between high- and low-resource languages has been the focus of much previous work. Typological features from databases such as the World Atlas of Language Structures (WALS) are a prime candidate for this, as such data exists even for very low-resource languages. However, previous work has only found minor benefits from using typological information. Our hypothesis is that a model trained in a cross-lingual setting will pick up on typological cues from the input data, thus overshadowing the utility of explicitly using such features. We verify this hypothesis by blinding a model to typological information, and investigate how cross-lingual sharing and performance is impacted. Our model is based on a cross-lingual architecture in which the latent weights governing the sharing between languages is learnt during training. We show that (i) preventing this model from exploiting typology severely reduces performance, while a control experiment reaffirms that (ii) encouraging sharing according to typology somewhat improves performance.
ASSESSMENT OF A PROJECT MANAGEMENT CAPSTONE COURSE FOR IS/IT STUDENTS IN A SMALL UNIVERSITY SETTING

Capstone courses, which are often the final course in a student's undergraduate education, provide an opportunity for students to apply and hone the essential skills and knowledge they need to succeed in their chosen field.The focus of this paper is on a project management (PM) capstone course that is offered to Information systems/Information Technology (IS/IT) students at a small Caribbean university.Five years ago, the university's PM capstone program was restructured to use real-world IT projects that would deliver needed solutions to local enterprises serving as program sponsors.Relying on quantitative and qualitative data collected from key stakeholders over the past five years, this paper assesses whether the restructured capstone program has met its objective of enabling IS/IT students to develop both the technical/hard skills and the soft skills needed to succeed as well-rounded IS/IT professionals.
Comparison and Evaluation of Data Composition and Deep Learning Models in Archival Handwritten Digit Classification

Archival maritime logs are well-preserved treasure throve of climate-related data.The analysis of these documents is instrumental to understanding historical climate trends and future predictions.Transcribing such handwritten logs depends on handwritten letter/digit recognition, which is our aim.The shortcomings of OCR (Optical Character Recognition) are manifesting in frequent confusion of digits and letters when it comes to archival handwritten documents.In this extension of conference and thesis work, two such methods are put to the test -convolutional (CNN) and long-short term memory (LSTM) neural networks (NN).A compound model of convolutional NN followed by LSTM is also considered.While all models register high accuracy, it is observed that the compound model performs faster with accuracy above the lone CNN.We also analyse dataset composition and test for size and balance.
METHOD FOR DETECTING FOREIGN OBJECTS ON THE RUNWAY BY VIDEO STREAM

The article considers a problem of detecting foreign objects on the runway. Existing automated systems that solve that issue are based on cameras and radar sensors. However, in those systems, cameras are used only for visual confirmation and are rarely used directly to perform detection. The use of video information for object detection will increase the degree of automation of such systems. The article proposes a method for detecting foreign objects in a video stream based on threshold segmentation. The method works with data from static cameras and can be used both in systems with only cameras and in complex systems as an optical component. The developed method processes a set of consecutive frames of the video stream to perform detection. Object detection is performed in two stages. At the first stage, background subtraction based on Gaussian mixture model is used. At the second stage, adaptive threshold segmentation is applied. The applicability of the developed method was investigated on the basis of experimental data. The dependences of the quality indicators of object detection on the method parameters were obtained. The advantages of the proposed approach are high speed of object detection, high accuracy of object positioning in the frame, adaptivity of segmentation threshold, as well as flexible adjustment of detection sensitivity.
Correction to: Creativity Under COVID-19: How Technology Has Enhanced and Promoted Student Engagement Online

Correction to: Chapter 6 in: C. Hong and W. W. K. Ma (eds.), Applied Degree Education and the Future of Learning, Lecture Notes in Educational Technology, https://doi.org/10.1007/978-981-16-9812-5_6
Structured References from PDF Articles: Assessing the Tools for Bibliographic Reference Extraction and Parsing

Many solutions have been provided to extract bibliographic references from PDF papers. Machine learning, rule-based and regular expressions approaches were among the most used methods adopted in tools for addressing this task. This work aims to identify and evaluate all and only the tools which, given a full-text paper in PDF format, can recognise, extract and parse bibliographic references. We identified seven tools: Anystyle, Cermine, ExCite, Grobid, Pdfssa4met, Scholarcy and Science Parse. We compared and evaluated them against a corpus of 56 PDF articles published in 27 subject areas. Indeed, Anystyle obtained the best overall score, followed by Cermine. However, in some subject areas, other tools had better results for specific tasks.
QR Code Generator: Studi Kasus Orisinalitas Produk Kasepuhan Sinar Resmi

Kasepuhan Sinar Resmi in Cisolok District is an inseparable part of the Ciletuh Geopark Area. The village has several original products made directly by the local community, and marketed online. However, it is often used as a crime by some people who fake products made by the Kasepuhan Sinar Resmi community for personal gain. This crime is certainly very detrimental to the people of Kasepuhan Sinar Official, they do not get the slightest profit from the goods sold and the safety of the product is doubted. The purpose of this study is to create a system that guarantees the authenticity of the sold's products by the Kasepuhan Sinar Resmi community, so that sellers and buyers can get the benefit. In this study, the system development method used is an Object Oriented Programming (OOP) approach with tools such as Use Case Diagrams, Activity Diagram. From the existing problems, this research focuses on the design and construction of a QR Code Generator to detect the originality of the Kasepuhan Sinar Resmi’s product, this is conducted so that people get the original Kasepuhan Sinar Resmi’s product.
Research on Influencing Factors and Training Strategies of Teachers' Leadership Development in Suzhou University

This research is based on the current situation of teacher leadership in Suzhou University.Through the investigation of teacher leadership in Suzhou University and various influencing factors, it comprehensively understands the level of each dimension of teacher leadership in Suzhou University and the level of various influencing factors, finds the correlation and puts forward corresponding training strategies.
Analysis of the piano accompaniment characteristics of the national opera "Yimeng Mountain" and the synergy with the singers

Yimeng Mountain, a Chinese national opera, is a dazzling star in the history of opera.It is well known by the majority of music teachers and students because of its beautiful melody and exciting plot.The national tenor Aria "aiyongzai", as the aria of one of the excellent hero "Lin Sheng", is difficult to sing, long in length, requires high singing skills and has great artistic value.As a student in the art direction of piano accompaniment, the coordination and tacit understanding between piano accompaniment and vocal singers, It is particularly important to complete a work with high quality.The author will start with the creation of Yimeng Mountain, and then the creation background of Aiyong, to specifically analyze the characteristics and performance analysis of piano accompaniment texture.Finally, combined with the author's own professional direction,
Evaluasi Sikap Belajar Daring Mahasiswa Prodi Pendidikan Biologi

This study aims to describe the online learning attitude of students of the Biology Education Study Program, PGRI Silampari University Class of 2021-2022. The method used is a case study. The research data are in the form of interviews and questionnaires given to students of class 1.A Biology Education Study Program. The data analysis techniques of this research include data reduction, data display and conclusion drawing. The results showed that the highest score in the small group test response data related to student attitudes about online learning was 81.25%. In conclusion, the student's learning attitude in the Biology Education study program at PGRI Silampari University is good.&#x0D; Keywords: Learning, Online, Evaluation, Attitude
Kemampuan Belajar Mandiri dan Kemampuan Literasi Baru Calon Guru Biologi

This study aims to determine the ability of self-regulated learning, new literacy and the relationship between the two in perspective biology teachers. The method used is qualitative. The research sample is Biology students, at PGRI Silampari University, totaling 74 people. The data collection instrument was in the form of a questionnaire consisting of self-regulated learning abilities and new literacy skills. The data obtained were analyzed descriptively and the relationship between the two was analyzed using Rank Spearman analysis. The results showed that the ability of prospective biology teacher students in self-study regulation was categorized as good, new literacy was sufficient and the relationship between the two obtained a significance value of 0.00 (&lt;0.05). In conclusion, there is a relationship between the ability to regulate self-study and the new literacy ability of prospective biology teachers.&#x0D; Keywords: Prospective Biology Teacher, New Literacy, Self-Study Regulation
Analysis of Optimizing Factors for Utilization of Research Results in Health College

Week utilization of research results for economic and social development in society as well as the competitiveness of technological products produced by universities encourage the need for factor analysis in optimizing research results that can bridge the solution to this problem. This research uses quantitative descriptive methods to identify and analyze factors that are considered variables to obtain an effective research process so that it can be utilized by users in the form of downstream research results. The results of the field study show several factors that influence the mechanism, including the importance of having a research road map that links and matches not only from a scientific perspective but also with industry through technology and market readiness. Scientific interdisciplinary collaboration and the role of intermediation and incubation are needed for its optimization supported by appropriate regulations. Potential research must be strengthened into research that produces high-value-added products, both economically and socially, capable of transforming into products that have competitive and comparative advantages and provide solutions for users.
Development of Website-Based Thousand Island Tour Package Booking Application Using Waterfall Method

PT. Khatulistiwa Global Wisata is a company engaged in tourism and offers a Tour and Travel service called Explore Thousand Islands. Currently, the process of booking Pulau Seribu tour packages at Explore Seribu Pulau Tour and Travel is still done manually, causing visitor data, bookings, payments, and visitor reviews to not be recorded properly. This website-based thousand island tour package online booking application is designed using the Waterfall method, CodeIgniter as a framework, PHP for designing the web, and MySQL as a database storage. Research has been conducted to overcome problems by creating features such as tour package list features, tour package bookings, tour package payments, manage payments, approve payments, manage assignment trips, complete trip assignments, and give trip reviews. The features developed make it easier for visitors to find information on tour packages, book, pay, and review tour trips that have been carried out. In addition, the existence of the report feature can improve performance and make it easier for tourism agents to record reports from booking thousand island tour packages through the website.
STUDENTS’ PERCEPTIONS ON LEARNING ENGLISH THROUGH MICROSOFT TEAMS

English is one of the subjects that has an important role in communication, because English is an international language used to communicate in various countries. Since the pandemic all activities have been carried out online, including learning activities. Many learning applications are used during online learning, one of them is Microsoft Teams. Microsoft Teams is a learning application that has very complete features. This research aims to describe students' perceptions of learning English through Microsoft Teams in class XI students at SMA 2 Kudus. This research uses a qualitative research design with an open questionnaire instrument given to 50 students and interviews with 15 student. The results of this research indicate that the students of class XI at SMA 2 Kudus have a neutral perception of learning English through Microsoft Teams. This is evidenced by the fact that most students think that learning English through Microsoft Teams is effective and efficient, but they face several obstacles while using Microsoft Teams which causes them do not understand the material and choose face-to-face learning. From the results of this research, it is suggested that students pay more attention to the importance of learning English and motivate themselves to study harder.
SPEECH ACT IN BARACK OBAMA’S SPEECH

The purpose of this study is to analyze Barack Obama's usage of speech acts in speech "A More Perfect Union”. The method used in this research is qualitative research. The data were collected and analyzed by collecting and classifying the utterances that are relevant to Searle’s theory on speech act’s classification. Based on the findings, the researchers discover three directives, four commisives, fifteen representatives, one declarative, and five expressives in the speech. The representative is the most common and declarative is the least common.