Reviewerly/exHarmony huggingface dataset:
Features of professional activitythe modern teacher of the subject "technology"

In the modern socio-economic conditions, the vector of development of the system of General education aime data ll-round development of abilities and potential of students who can later become competitive specialists. The answer to this social order was the introduction of the Federal basic curriculum subject are a "Technology", which sumup the fundamental knowledge of natural Sciences and Humanities, entrepreneurial ideas to meet the social task of training competent professionals. The author presents the structure of the subject are a "Technology" and the stages of preparation of pupils, conditional release its specificity to improve the training of teachers of technology in pedagogical higher education institution.
Most readers in dark when bylines differ from staff writer; taglines do little to help

An experiment was conducted to determine whether perceptions of the newspaper and story differed by byline type. The findings not only indicate few participants know a story is native advertising, they rarely know the writer except a staff writer. Thus, perceptions mainly differed little. Other bylines were not detailed enough for readers to fully know the writer’s identity, and few read to the tagline. Stronger measures were recommended to fully inform readers about the writer.
Research Guides: NorQuest College Student Survey - Information and FAQ's: Testing and Assessment

Find answers to frequently asked questions by students asked while conducting the NorQuest College student phone survey for Spring term 2020.
Integration of Natural Science Knowledge as an Incompatible Part of STEM-education

It is shown that an important component of STEM-education is content of natural science knowledge integration; use of general laws and laws of nature can be effective means of transdisciplinary integration. It is emphasized that in order to implement the basic tasks of STEM-training, it is desirable to make wider use of general laws as factors of integration. The experience of conducting a tournament for young researchers and inventors at the Dnipro National University is discussed. The main tasks of the tournament were forming STEM-competencies of schoolchildren; finding gifted and talented students; becoming familiar with leading institutions of higher education; establishing cooperation between schools and universities.The competition theme of the tournament was formed around a transitory legend − a space flight to an unknown planet.
LibGuides: Academic Success Center: Test Reviews

Tutoring, Academic Coaching, Test Reviews, & More! Review upcoming test material with NFC staff and faculty.
To make better exploration tools, we first need to better understand ore deposits

In an era of industry-funded research, there is an imperative that research yields outcomes that can be applied directly, at the expense of improving fundamental understanding. Reality often proves more complex than our simplistic experiments anticipated. A summary of common experimental behaviour might be framed thus:observe something of possible usecollect limited orientation samplesbecome enthused by early resultsroll out the tool to genuine unknownsgenerate abundant data with ambiguous resultsanalyse using a machine learning algorithm hoping for a miracle.This paper documents some of our recent trials and errors, mostly through application of SEM-based Tescan Integrated Mineral Analyser (TIMA) quantitative mineralogy and rock mapping, and attempts to apply mineral chemistry and chronology analysis to detrital sediment samples. We've learned that to improve our new tools we must:expand or customise our characterisation of natural backgroundobserve mineral appearance, assemblage and morphology before microanalysisaccept that detailed observation may demand revisions to existing models of hydrothermal mineral stabilities, and hence provoke more fundamental researchaccept that machine learning classifications tend to be successful only when trained against local or specifically relevant orientation data.
Pedagogical Model "Student-Tutor" in the System of Innovation Ways for Perfecting the Professional Competencies in Future Russian Language and Literature Teachers

The objective of the research was development of organizational and pedagogical support of the process of creation and fulfillment of the Student-tutor pedagogical model in the system of perfecting the professional competencies of philology students by training them for such kind of professional activity as holding individual classes for school students (tutoring), with the classes being in demand in the situation of upgrading the modern school. The theoretical (analysis of psychological and pedagogical literature, summarizing and systemizing the pedagogical experience) and empirical methods (questionnaire survey, observation, designing, modeling) were used. The results of the research are materials for providing the organizational and pedagogical support of the process of creation and fulfillment of the Student-tutor pedagogical model.
LibGuides: How to Use Interlibrary Loan: Important Notes

This guide will help you determine whether Interlibrary Loan is the right choice as well as create an Interlibrary Loan request.
From Feature Selection to Continuous Optimization.

Metaheuristic algorithms (MAs) have seen unprecedented growth thanks to their successful applications in fields including engineering and health sciences. In this work, we investigate the use of a deep learning (DL) model as an alternative tool to do so. The proposed method, called MaNet, is motivated by the fact that most of the DL models often need to solve massive nasty optimization problems consisting of millions of parameters. Feature selection is the main adopted concepts in MaNet that helps the algorithm to skip irrelevant or partially relevant parameters and use those design variables which contribute most to the overall performance. The introduced model is applied on several unimodal and multimodal continuous problems. The experiments indicate that MaNet is able to yield competitive results compared to one of the best hand-designed algorithms for the aforementioned problems, in terms of the solution accuracy and scalability.
LibGuides: Resources for Non-binary Students: Nonfiction - Books

Finding books, movies, and more featuring non-binary characters can be difficult. This is a list of resources, fiction and non-fiction, written about and often by non-binary people.
Demonstrating Rapid Iron-On User Interfaces: Hands-on Fabrication of Interactive Textile Prototypes

Rapid prototyping of interactive textiles is still challenging, since manual skills, several processing steps, and expert knowledge are involved. We demonstrate Rapid Iron-On User Interfaces, a novel fabrication approach for empowering designers and makers to enhance fabrics with interactive functionalities. It builds on heat-activated adhesive materials consisting of smart textiles and printed electronics, which can be flexibly ironed onto the fabric to create custom interface functionality. To support rapid fabrication in a sketching-like fashion, we developed a handheld dispenser tool for directly applying continuous functional tapes of desired length as well as discrete patches. We demonstrate versatile compositions techniques that allow to create complex circuits, utilize commodity textile accessories and sketch custom-shaped I/O modules. We further provide a comprehensive library of components for input, output, wiring and computing. Three example applications demonstrate the functionality, versatility and potential of this approach.
Application of root cause analysis and actions combined with strengthening exercise of knee joint control in fall management of elderly patients

ObjectiveTo analyze the root causes of fall in elderly patients, explore the corresponding countermeasures and combine the balance function and knee joint strengthening training to reduce the incidence of fall in elderly patients.MethodsFirst, the cause of fall of the patients in the department of rehabilitation from November 2014 to October 2016 were analyzed with the method of root cause analysis and retrospective analysis, and targeted corrective measures were formulated. The elderly patients fell between the time period from November of 2016 to October of 2017 and November of 2017 to October of 2018 were enrolled into the control group and observation group by convenience sampling. Corrective measures were formulated based on root cause analysis and action (RCA2) to prevent falls in the control group, on the basis of that balance function training combined with strengthening training of knee joint control were adopted to prevent fall in the observation group. The two groups were compared in terms of the differences in the incidence of fall, five times of sitting and standing test (FTSST) , 10 meters maximum walking speed (10MWS) , Berg Balance Scale (BBS) and Tinetti Gait Analysis (TGA) . The incidence of fall in the department before the implementation of corrective measures based on RCA2 (November 2014 to October 2016) and the time period of November 2016 to October 2018 which is after the implementation of RCA2 based corrective measures were compared.ResultsAfter implementing the corrective measures, the fall rate of the elderly patients reduced from 2.0% to 0.9% with statistical difference (χ2=4.343, P=0.037) . There was statistical difference (χ2=3.899, P=0.048) in terms of the incidence of fall between the observation group (4.24%) and the control group (0.64%) . Before intervention, the two groups had no statistical difference in the FTSST, 10MWS, BBS and TGA (P>0.05) . In the control group, there was no statistical difference before and after intervention (P>0.05) ; in the observation group, there was statistical difference before and after intervention (P<0.05) . After intervention, the observation group was better than the control group in the FTSST, 10MWS, BBS and TGA with statistical difference (P<0.05) .ConclusionsThe comprehensive use of root cause analysis and intensive training of knee joint control and balance function training to manage elderly patients scientifically can effectively reduce the incidence of falls.Key words: Aged; Fall; Root cause analysis; Intensive training of knee joint control
LibGuides: Collection Development & Analysis: Collection Valuation

This is where you will find analysis information which will help you determine what to purchase for your discipline.
Robust Infrared Air Object Tracking Fusing Convolutional And Hand-Crafted Features

The infrared objects do not have color information, and they have low resolution. Therefore, the hand-crafted features cannot robustly describe observation model of the object, and it is easy to track failure in the presence of heavy occlusion and infrared distractors. Based on the correlation filtering theory, a robust air object tracking algorithm using convolutional and hand-crafted features is proposed in this paper. Firstly, there are differences in the ability of different layer features to describe the objects. We reconstruct the foreground mask with feature map selection approach, and select the features which are sensitive to intra-class appearance variation. Then, convolutional and hand-crafted features are fused and embedded in the correlation filtering theory to estimate the object position, achieving the air object tracking. Finally, to re-capture the object when the tracking fails, the proposed algorithm introduces YOLOv3 for re-detection. We verify our algorithm with actual infrared image sequence and the simulation image sequence. The experimental results show that the proposed algorithm can accurately track air objects with high precision.
Transfer Learning for Less-Resourced Semitic Languages Speech Recognition: the Case of Amharic

While building automatic speech recognition (ASR) requires a large amount of speech and text data, the problem gets worse for less-resourced languages. In this paper, we investigate a model adaptation method, namely transfer learning for a less-resourced Semitic language i.e., Amharic, to solve resource scarcity problems in speech recognition development and improve the Amharic ASR model. In our experiments, we transfer acoustic models trained on two different source languages (English and Mandarin) to Amharic using very limited resources. The experimental results show that a significant WER (Word Error Rate) reduction has been achieved by transferring the hidden layers of the trained source languages neural networks. In the best case scenario, the Amharic ASR model adapted from English yields the best WER reduction from 38.72% to 24.50% (an improvement of 14.22% absolute). Adapting the Mandarin model improves the baseline Amharic model with a WER reduction of 10.25% (absolute). Our analysis also reveals that, the speech recognition performance of the adapted acoustic model is highly influenced by the relatedness (in a relative sense) between the source and the target languages than other considered factors (e.g. the quality of source models). Furthermore, other Semitic as well as Afro-Asiatic languages could benefit from the methodology presented in this study.
On the Exploration of English to Urdu Machine Translation.

Machine Translation is the inevitable technology to reduce communication barriers in today’s world. It has made substantial progress in recent years and is being widely used in commercial as well as non-profit sectors. Such is only the case for European and other high resource languages. For English-Urdu language pair, the technology is in its infancy stage due to scarcity of resources. Present research is an important milestone in English-Urdu machine translation, as we present results for four major domains including Biomedical, Religious, Technological and General using Statistical and Neural Machine Translation. We performed series of experiments in attempts to optimize the performance of each system and also to study the impact of data sources on the systems. Finally, we established a comparison of the data sources and the effect of language model size on statistical machine translation performance.
Secret Image Sharing Revisited: Forbidden Type, Support Type, and Their Two Approaches

In this paper, we introduce two new image-sharing types to extend the applicability of sharing. Type 1 is our so-called forbidden type. In its sharing system, any t of the n shares can recover the secret image, unless the t shares form a forbidden group listed in a forbidden list. Type 2 is our so-called cross-department support type. If a government has 3 departments {DEPH, DEPM, DEPL}, then 3 thresholds (tH, tM and tL) exist. Any tH number of officers from department DEPH can unveil the secret image, and likewise for any tM and tL number of officers from departments DEPM and DEPL, respectively. Type 2 image sharing allows a secret to be disclosed not only in an intra-department meeting but also in a cross-department meeting. In this study, both types are implemented through two approaches: the polynomial and linear-equations approaches. Hackers can be confused when two approaches are mixed. As for the applications, use Type 1 to protect sensitive information in medical or military images or legal documents; and use type 2 to support cross-department crime investigation, industrial production, etc.
QSGG

Like [1], we present QSGG, an algorithm to compute the simulation of a query pattern in a graph of labeled nodes and unlabeled edges. However, our algorithm, QSGG, works on a compressed graph grammar, instead of on the original graph. The speed-up of QSGG compared to a previous algorithm [1] grows with the size of the graph and with the compression strength of the grammar.
Design and implementation of a trajectory planning algorithm using Dynamic Programming method on a Hybrid Electric Vehicle

ABSTRACT In the recent years the automotive industry is in a revolution towards the electrified and intelligence mobility. The autonomous driving, which is the possible solution for the traffic congestion, accidents, and emission issues, is quickly becoming one of the hottest topics in the automotive field. However, the technology is still not mature enough for commercialization due to several technical challenges. The trajectory planning is one of them. Many researches regarding the trajectory planning have already been developed in the robotic field, however when it comes to the automotive field, it becomes extremely challenging due to the critical requirements on the system’s real-time performance and on the trajectory generation with multi-objective optimization(Collision avoidance, occupant’s comfort, fuel economy, etc). The two targets are usually contradictory since the planning algorithms with better optimization performance will degrade the real-time performance. In this thesis an approach is proposed to solve this problem. First an off-line optimization based on Dynamic Programming method is implemented on a Hybrid Electric Vehicle to obtain the optimum control sequence considering multi-optimization targets. Then a rule-based planner is established based on the results of the off-line optimization to realize the real-time application. Finally, the results obtained from different algorithm are compared (PID, MPC, DP, rule-based) and it proved that this approach could be a feasible solution for the contradictory requirements on real-time and optimality of the trajectory planning algorithm.
Implementation of Supervised Training Approaches for Monolingual Word Sense Alignment: ACDH-CH System Description for the MWSA Shared Task at GlobaLex 2020.

This paper describes our system for monolingual sense alignment across dictionaries. The task of monolingual word sense alignment is presented as a task of predicting the relationship between two senses. We will present two solutions, one based on supervised machine learning, and the other based on pre-trained neural network language model, specifically BERT. Our models perform competitively for binary classification, reporting high scores for almost all languages. This paper presents our submission for the shared task on monolingual word sense alignment across dictionaries as part of the GLOBALEX 2020 – Linked Lexicography workshop at the 12th Language Resources and Evaluation Conference (LREC). Monolingual word sense alignment (MWSA) is the task of aligning word senses across re- sources in the same language. Lexical-semantic resources (LSR) such as dictionaries form valuable foundation of numerous natural language process- ing (NLP) tasks. Since they are created manually by ex- perts, dictionaries can be considered among the resources of highest quality and importance. However, the existing LSRs in machine readable form are small in scope or miss- ing altogether. Thus, it would be extremely beneficial if the existing lexical resources could be connected and ex- panded. Lexical resources display considerable variation in the number of word senses that lexicographers assign to a given entry in a dictionary. This is because the identification and differentiation of word senses is one of the harder tasks that lexicographers face. Hence, the task of combining dictio- naries from different sources is difficult, especially for the case of mapping the senses of entries, which often differ significantly in granularity and coverage. (Ahmadi et al., 2020) There are three different angles from which the problem of word sense alignment can be addressed: approaches based on the similarity of textual descriptions of word senses, ap- proaches based on structural properties of lexical-semantic resources, and a combination of both. (Matuschek, 2014) In this paper we focus on the similarity of textual de- scriptions. This is a common approach as the majority of previous work used some notion of similarity between senses, mostly gloss overlap or semantic relatedness based on glosses. This makes sense, as glosses are a prerequisite for humans to recognize the meaning of an encoded sense, and thus also an intuitive way of judging the similarity of senses. (Matuschek, 2014) The paper is structured as follows: we provide a brief overview of related work in Section 2, and a description of the corpus in Section 3. In Section 4 we explain all impor- tant aspects of our model implementation, while the results are presented in Section 5. Finally, we end the paper with the discussion in Section 6 and conclusion in Section 7.
CHI 2030: The Future is Wide Open

What is the future of the CHI conference? What will it look like in 2030? In this panel, we will present some data on the current state of the CHI conference - from paper submissions to attendance - and the initial findings on what our community has said is their 'ideal' CHI conference. We will then make wild predictions about the future of CHI and encourage audience discussion on the form that the conference and academic publishing could take in the future.
Who is this Explanation for? Human Intelligence and Knowledge Graphs for eXplainable AI

eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usually a decision-maker. Such user needs to interpret the AI system in order to decide whether to trust the machine outcome. When addressing this challenge, therefore, proper attention should be given to produce explanations that are interpretable by the target community of users. In this chapter, we claim for the need to better investigate what constitutes a human explanation, i.e. a justification of the machine behaviour that is interpretable and actionable by the human decision makers. In particular, we focus on the contributions that Human Intelligence can bring to eXplainable AI, especially in conjunction with the exploitation of Knowledge Graphs. Indeed, we call for a better interplay between Knowledge Representation and Reasoning, Social Sciences, Human Computation and Human-Machine Cooperation research -- as already explored in other AI branches -- in order to support the goal of eXplainable AI with the adoption of a Human-in-the-Loop approach.
Low Power Scanned Laser Eye Tracking for Retinal Projection AR Glasses

Next generation AR glasses require a highly integrated, high-resolution near-eye display technique such as focus-free retinal projection to enhance usability. Combined with low-power eye-tracking, such glasses enable better user experience and performance. This research work focuses on low power eye tracking sensor technology for integration into retinal projection systems. In our approach, a MEMS micro mirror scans an IR laser beam over the eye region and the scattered light is received by a photodiode. The advantages of our approach over typical VOG systems are its high integration capability and low-power consumption, which qualify our approach for next generation AR glasses.
The data ethics challenges of explainable AI and their knowledge-based solutions

This work has been partly funded by Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 P2, Insight SFI Research Centre for Data Analytics.
Analisis Proses Pada Senayan Library Information Management System (SLIMS) Cendana Berbasis Data Flow Diagram (DFD) Di Perpustakaan Universitas Kristen Duta Wicana Yogyakarta

This research aimed to analyze the process of cendana senayan library information management system (SLIMS) based on data flow diagram (DFD) in Duta Wicana Christian University.. Methodology of this research used field research and the object of this research is cendana senayan library information management  system (SLIMS) . Finding of this research is all of the features in SLIMS Cendana such as borrowing process, return process, library member registration process, importing book data collection process, and imposing sanctions on library users who are late returning the books can be cover with Data Flow Digram (DFD), so it can be easier for librarians to conduct library processing activities and in the information retrieval in library.
LibGuides: Video Production: Casting Talent

A guide with tips and trips on how to produce a video, from the pre-production process to the editing phase.