Reviewerly/exHarmony huggingface dataset:
Discovering Classification Dimensions for Managing Scientific Resources

The Resource Space Model is a systematic theory and method for managing the contents of resources by a multi-dimensional classification space. Different dimensions represent different classification methods. Each dimension can be regarded as a classification tree. Design of Resource Space is mainly based on domain knowledge and experience of designer. This paper implements an approach to automatic discovering dimensions from texts (taking scientific papers as experimental data). It consists of four stages: 1) representing each text as a collection of tuples in the form of (word, value); 2) constructing an initial dimension; 3) constructing the hierarchical dimensions based on the initial dimension; and 4) post-processing of outlier texts. The experimental results show that our model achieves a significant improvement of performance on classifying texts.
LibGuides: Expanded Access to Digital Content: Home

As a response to the global COVID-19 pandemic, many of the Library’s content providers have expanded our access to digital content in order to support remote research, learning, and teaching.
No standard test in child literature objectives

In controlling the achievement of learning objectives by Blum taxonomy in children's literature, it is important to determine the extent to which students acquire information and information on a particular topic. The above-mentioned non-standard test tasks play an important role in enhancing the student's knowledge of the subject and developing skills and competencies. It tells the story of the fairy tale and its heroes, fiction and story development. Higher education teachers are responsible for educating both physically and mentally qualified professionals in our society - educating and educating young people who are capable of actively working in public life and in various fields of government and science and culture. This, among other subjects, places a significant challenge on children's literature.
PhyMill is created to aid therapists and paediatric patients to undergo physiotherapy treatment

The sympathy towards children who face difficulties in controlling their bodies’ position and activation due to damage to their developing brain, or better known as cerebral palsy, inspired a group of Universiti Malaysia Pahang (UMP) researchers to develop the Smart Physio-Treadmill (PhyMill) to aid patients in training their walking movements.
LibGuides: MK 315 Marketing Principles: Library Catalog(s)

This guide will show you how to find and cite articles for your MK 315 assignments. You can use the highlighted resources for weekly discussion questions and your semester-long final project.
Diversification of the process of training students of pedagogical universities

The article is devoted to the problem of diversification of the process of training future teachers in a modern University, including the redistribution of efforts of the administration and faculty during training sessions, by moving part of the classes with students to their future workplace and in the specific conditions of virtual reality. The ways of transformation of traditional and development of new methods of presentation of the content of education are described, the possibilities of new forms of organization, methods and means that allow to give a new impetus to the process of professional training of future teachers in a modern University are described.
Simplifying Satellite and Ground Data Validation with Level-2 Subsetting

We demonstrate that scientists can simplify their satellite data validation workflow with the use of NASA Godddard Earth Sciences Data and Information Services Center (GES DISC) subsetting services. We perform a sample validation of Aura ozone products collocated with ground-based ozone measurements using subsetting services to trim satellite data to only the relevant user-defined variables and spatio-temporal region. Because the subsetting service automatically returns only relevant data granules that adhere to a set of user-defined coincidence criteria, user workload is greatly reduced. Moreover, the resultant data files are substantially smaller than full data granules due to the subsetting service further culling the data to the relevant geospatio-temporal coincidence criteria, user-defined variables, and user-defined dimensions of variables. This decreases data download throughput and file storage requirements. The validation presented here quantifies the time and file size savings that can be achieved by utilizing subsetting services within the satellite data validation workflow.
Disyllabic Localizers in Modern Chinese

This study investigates the syntactic behavior of disyllabic localizers in Modern Chinese. Recent studies (Huang et al. 2009; Djamouri et al. 2013; Liu and Oakden 2014) point out the boundness nature of disyllabic localizers, but to date there has been no consensus on what syntactic status they have. We examine a wide range of disyllabic localizers and find that disyllabic localizers do not all behave the same. While some can be used both as independent words and as phrasal bound forms, others are always bound at the phrasal level. Nonetheless, there are two characteristics that are shared by all disyllabic localizers: they are all nominal, and they are all bound when occurring at the end of a phrase. The best way to characterize the entire class of disyllabic localizers is that they are nominal phrasal bound forms with some of them also functioning as nouns in certain environments.
An approach of Crypto-token for Smart Contract based on Ethereum Blockchain

Nowadays smart contracts apply in management, bank system, insurance, estate, IoT, and others, because they perform credible and trackable irreversible transactions without third parties. The proposed paper presents a solution for the creation of a decentralized token for the implementation of a smart contract based on Ethereum block-chain. A web based interface has been created for Initial Coin Offering (ICO). In the experimental environment the research was carried out for various scenarios. The results are presented.
Sociocultural Activity Managers’ Professional Training in the Conditions of Information and Educational Environment

The article deals with the relevance of transformational digitalization processes of the economy and education in Ukraine and in the world. It has been found out that the peculiarities of the information and educational environment lead to the requests for training the participants of the educational center on the usage of science-intensive educational information technologies. Designing the educational environment for the future sociocultural activity managers involves the development of technology to prepare them for the educational and scientific space organization and digitization.
LibGuides: Continuity of Services: Research Help

A guide to Remote Services for the Ruby E. Dare Library during periods when campus is closed or on reduced staffing.
The Synergy Mechanism and Path of the Integration of “Double Innovation” Education and Industry-Education Integration

"Double innovation" education is one of the most popular educational research topics in China today. It is of great significance to promote the social development and economic structural transformation of a country. Exploring the effective synergy mechanism between "double innovation" education and industry-education integration, and expanding the synergy path between two sides have become a new topic of "double innovation" education in colleges and universities and an important way to promote industry-education integration. The mechanism of "double innovation" education and industry-education integration, including the feasibility and necessity of value synergy, object synergy and subject synergy. The coordinated development of "double innovation" education and industry-education integration requires relevant parties to establish the "double innovation" education development concept of industry-education integration, combine professional education and industrial chain to carry out "double innovation" education, and building a "double-creation" education ecosystem of "government, universities, enterprise and society".
Animasyon Aktivitelerinde Deneyim Kalitesinin Otel İşletmelerinin İmajı, Konukların Değer Algısı ve Tekrar Satın Alma Niyetine Etkisi1 (The Impact of Experience Quality of Animation Activities on Hotel Corporate Image, Perceived Value and Repurchase Intention)

Purpose -The purpose of this research is to investigate the impact of experience quality of animation activities on repurchase intention.In accordance with this purpose; the effects of experience quality of animation activities on the perceived value and corporate image were tested.Additionally, the mediation effects of perceived value and hotel corporate image on the among experience quality of animation activities, repurchase intention were tested.Design/methodology/approach -A self-administered questionnaire developed after a comprehensive literature review was used as a data collection instrument.The Immersion, surprise, participation, entertainment and education dimensions were used in measuring experience quality of animation activities.Guests staying at five stars hotel located nearby the sea in Antalya comprise the target population of this study.Five stars hotel guests visiting the Antalya was surveyed using stratified sampling methods, a total of 1086 questionnaires from 28 different countries was analyzed.Findings and Discussion -The hypotheses in the research model were tested using Structural Equation Modelling (SEM).The structural model results indicate that experience quality of animation activities have not a positive influence on repurchase intention, but have a positive influence on perceived value and corporate image of hotels.Furthermore, the study revealed that perceived value and hotel corporate image represents a "full mediator" on the relationship between experience quality of animation activities and repurchase intention.
FAULT MANAGEMENT IN COMMUNICATION NETWORKS USING PROBABILISTIC REASONING AND BELIEF MODELS

The challenge to providing an efficient and reliable fault management system in cellular networks demands intelligent fault detection and correction procedures. Recent investigative study in CDMA neiworks in Nigeria shows that the frequent faults include: faulty links, radio frequency (RI') loss and trunk outages, which gradually degrade quality of service of the networks. Most of these faults occur in the El link between Wit and the BSC. Analysis of logged data over a period of one year shows that signal out of step occurs with probability of 0.62, unusable link occurs with 0.13, while other faults occurs with 0.25. This paper presents a system designed to improve the present system of fault detection and isolation in the base station subsystem of a CDMA network based on this abnormalities. It is based on an intelligent agent technology, with probabilistic networks as framework for knowledge representation and evidence inference. It was found to be robust and has 70% reliability.
Applications of Shearography for Non-Destructive Testing and Strain measurement

Non-Destructive Testing (NDT) technologies have gain importance recently due to the demand of high quality and costs optimization in products. Thus, optical non-contact techniques have been developed, which also have been well accepted in the industry. This work present a background of developments and applications of shearing speckle pattern interferometry, known as shearography, for NDT analysis. Also, some important experimental results, from authors, for NDT analysis and strain measurement are reported.
The Rhetorical Legacy of Wangari Maathai, Eddah M. Mutua, Alberto Gonzalez and Anke Wolbert (eds) (2018)

Abstract Lanham: Lexington Books, 221 pp., ISBN 978-1-49857-112-8, h/bk, $83.07
Rancang Bangun Aplikasi Portable Data Terminal dengan Menggunakan Metode Pemindaian Barcode Scanner Infrared Berbasis Android

Portable Data Terminal is a tools for scanning barcode which can record scanned data by itself  to be processed to new information. The high cost of these devices makes the company reluctant to buy such equipment in large quantities. Lack of Portable Data terminal causing data collection was obstructed. the obstructed data collection giving an impact to merchandise which given on next allocation.  By using waterfall method to overcome those problems, in the development of this system using object-oriented analysis method UML (Unified Modelling Language) as Use Case Diagam, Sequence diagram, Activity Diagram and Class Diagram. The programming language used in this application is Java Android by Android Studio and system testing method using black box testing, white box testing and questionnaire.
LibGuides: Online Library Resources and Services for Faculty: Coronavirus info & updates

Resources created by the Canada Librarians for faculty to provide library instruction online.
Medical Image Registration Based on Moving Manifold Regularization

We propose a new registration framework, namely moving manifold regularization, for solving medical image registration problems. The proposed method first uses the Snake model to obtain the region of interest on the images, and then extracts the two landmark point sets from the segmented images. After that, a transformation model based on the two landmark point sets is used to register the medical images. This framework considers the error functional with moving manifold regularization as we formulate this transformation model as a vector-field interpolation problem. The regularized error function moves by pixels, and the manifold regularization is used as the prior of the transformation to capture the underlying geometry information of the input data. The transformation function for each pixel is specified in a special space namely Reproducing Kernel Hilbert Space. Extensive experiments on medical images showed that the proposed method, which overcomes the defects of manual selection error and improves the registration accuracy, is an effective and stable registration method.
LibGuides: Business: Find Web Resources

A research guide designed to introduce you to the field of business. You'll find the materials, search tools, and other resources you need to start your research. If you need any assistance, please contact your librarian
Spatial and vertical metals distribution in sediment cores from Kongkong Laut estuary, Masai, Johor

Sediment has been widely used as a means for assessing the impact of anthropogenic activities on aquatic environment, with metal pollution being the most well-known threat to aquatic environments. Therefore the aim of this study is to identify and determine metal concentrations, specifically that of copper (Cu), chromium (Cr), cadmium (Cd), iron (Fe), and zinc (Zn) on four sediment cores samples of KongKong Laut Masai Johor. The aqua regia method had been used to analyze Cu, Cr, Cd, Fe and Zn concentrations in sediment samples. Metal concentrations had then been determined through the use of flame atomic absorption spectrometry. The degree of metal contamination in sediment core samples had been determined through using Enrichment Factors (EF) and Geoaccumulation Indices (Igeo). From this study, the mean and standard deviation of metal concentrations in each sediment core sample were shown to be lower than the average shale concentration and lower than both the effects-range low (ERL) and effects-range median (ERM) parameters for aquatic toxicity. This information could be useful, serving as a baseline for evaluating the potential impacts of future development in the area.
When it comes to forecasting solar irradiance a complex model is not necessarily the best

A comparison of three clear-sky models reveals that a more intricate program isn’t necessarily better for solar forecasting.
Live Programming Environment for Deep Learning with Instant and Editable Neural Network Visualization.

Artificial intelligence (AI) such as deep learning has achieved significant success in a variety of application domains. Several visualization techniques have been proposed for understanding the overall behavior of the neural network defined by deep learning code. However, they show visualization only after the code or network definition is written and it remains complicated and unfriendly for newbies to build deep neural network models on a code editor. In this paper, to help user better understand the behavior of networks, we augment a code editor with instant and editable visualization of network model, inspired by live programming which provides continuous feedback to the programmer.
Engineering students involved with printing business on campus

Recognizing the interest of university students in sports apparel, this kind of idea gave the idea of Civil Engineering Technology student, Pan Chuan Sin, 24, a venture into the field of sports apparel printing business.
Library Guides: eBooks and audiobooks: Overview

Stuck at home in lockdown? Here are Kerferd Library eBooks and audio books you can use from home
Automation of Analysis Preparation by Using Humanoid Robot

The Hitachi High-Tech Group provides various analytical products created through its core technologies. When our customers use these products, many processes of analysis preparation are necessary before starting analysis of their samples. Most of the processes have been performed manually until today. However, automation of such processes is recently expected by using robots since they are facing a shortage of workers due to a declining birthrate and an aging population. With this kind of background, we have developed a humanoid robot system to perform analysis preparation by using the same apparatus and environment as used by human workers. As a result of an experimental estimation, we confirmed that our robot could perform the analysis preparation correctly.
Programming Languages for Distributed Systems and Distributed Data Management (Dagstuhl Seminar 19442)

language advances have played an important role in various areas of distributed systems research, including consistency, communication, and fault tolerance, enabling automated reasoningand performance optimization.However, over the last few years, researchers focusing on this area have been scattered across different communities such aslanguage design and implementation, (distributed) databases,Big Data processing and IoT/edge computing -- resulting in limited interaction.The goal of this seminar is to build a community of researchers interested inprogramming language techniques for distributed systems and distributed data management, share current research results and set up a common research agenda. This report documents the program and the outcomes of Dagstuhl Seminar 19442 Programming Languages for Distributed Systems and Distributed Data Management.
Computer Artificial Intelligence Recognition System Relying on Firefly Optimization Algorithm

Human behavior recognition is a hot issue in the field of computer artificial intelligence recognition. However, most of the algorithms currently use only RGB or deep video sequences, and they are rarely combined for behavioral artificial intelligence recognition. Therefore, the algorithm relies on the firefly optimization algorithm. The two algorithms of robust depth map and RGB image are effectively combined. The SVM classifiers with multiple different kernel functions are used to evaluate them on the DHA dataset. The experimental results show that the performance of the proposed behavior description algorithm is better than some The performance of representative algorithms is better. At the same time, the performance of the algorithm is further improved after the fusion of depth data and RGB images, and it has better distinguishability and robustness.
Deep Learning Based Cell Parasites Detection.

Deep learning has dramatically improved the performance in many application areas such as image classification, object detection, speech recognition, drug discovery and etc since 2012. Where deep learning algorithms promise to discover the intricate hidden information inside the data by leveraging the large dataset, advanced model and computing power. Although deep learning techniques show medical expert level performance in a lot of medical applications, but some of the applications are still not explored or under explored due to the variation of the species. In this work, we studied the bright field based cell level Cryptosporidium and Giardia detection in the drink water with deep learning. Our experimental demonstrates that the new developed deep learning-based algorithm surpassed the handcrafted SVM based algorithm with above 97 percentage in accuracy and 700+fps in speed on embedded Jetson TX2 platform. Our research will lead to real-time and high accuracy label-free cell level Cryptosporidium and Giardia detection system in the future.
The effect of explanation styles on user's trust

This paper investigates the effects that different styles of textual explanation have on explainee’s trust in an AI medical support scenario. From the literature, we focused on four different styles of explanation: contrastive, general, truthful, and thorough. We conducted a user study in which we presented explanations of a fictional mammography diagnosis application system to 48 nonexpert users. We carried out a between-subject comparison between four groups of 11-13 people each looking at a different explanation style. Our findings suggest that contrastive and thorough explanations produce higher personal attachment trust scores compared to general explanation style, while truthful explanation shows no difference compared to the rest of explanations. This means that users who received contrastive and thorough explanation types found the explanation given significantly more agreeable and suiting their personal taste. These findings, even though not conclusive, confirm the impact of explanation style on users trust towards AI systems and may inform future explanation design and evaluation studies
Cognitive and Affective Mechanisms of Immersive Virtual Reality Learning Environments

Author(s): Parong, Jocelyn | Advisor(s): Mayer, Richard E | Abstract: Students and educators value the potential use of immersive virtual reality (IVR) in the classroom to teach academic content as it may increase interest and motivation to learn, which in turn may increase learning outcomes. However, one criticism is that features of IVR, such as extraneous sounds, animations, and interactions, that are not relevant to the content of the lesson, as well as the affective arousal associated with the use of IVR, may be distracting to learning processes. To examine this distraction hypothesis, two experiments were conducted in which students viewed a biology (Experiment 1) or history (Experiment 2) lesson either in IVR or in a desktop lesson containing the same content, with or without practice questions. In both experiments, students who viewed the lesson on the desktop in a PowerPoint (Experiment 1) or an interactive video (Experiment 2) outperformed those who viewed the IVR lessons on transfer tests. The desktop lessons led to higher cognitive engagement based on EEG measures in both experiments, and less self-reported extraneous cognitive load in Experiment 1. Participants also reported more high-arousal positive emotions after the IVR lessons in both experiments, and experienced higher physiological arousal based on heart-rate measures after the IVR lessons compared to the desktop lessons in Experiment 2. The same pattern of results was found when adjunct practice questions were or were not included in the lessons. Across both experiments, mediation analyses suggest that the negative relationship between instructional media and learning outcomes can be explained by self-reported cognitive processing or emotional arousal, particularly for retention test performance. Overall, immersive environments may create high emotional arousal and cognitive distraction during learning, which leads to poorer learning outcomes than desktop environments.