Reviewerly/exHarmony huggingface dataset:
CHALLENGES FACED BY TEACHERS IN EDUCATING MODERN PRESCHOOL CHILDREN

Preschool education is a priority area of education in the European Union and Lithuania. Today, a new look is taken at the organization of the process of preschool education not only in terms of quality, but also in terms of pedagogical relationships, i.e., the whole educational process is organized from the perspective of the child, recognizing him/her as an equal partner in the educational process. Researchers explain that there are still educators who still find it quite difficult to give up the elements of previous pedagogy, because for too long the aspiration to supervise and control children prevailed in their conception often prioritizing formal educational outcomes over the quality of the process of children’s education or the culture of pedagogical relationships. As the attitude towards the organization of the educational process and the role of educational participants in it changes, so does the role of the teacher. The teacher in the reality of education faces many challenges, for the solution of which new tasks are posed and new competences are required. The concept of the role of the teacher is also changing when it comes to modern preschool children and their education.The aim is to analyse the challenges faced by teachers in educating modern preschool children.The research sample is non-probability, targeted, convenience sample. Eighty-three preschool teachers from various preschool institutions of Lithuania, who work with children aged five to six, participated in the research on a voluntary basis.Methodology: Prior to the empirical research, scientific and methodological literature, information sources and the documents on education of the Republic of Lithuania were analysed. A quantitative research strategy was chosen to implement the research aim. Data were collected through a questionnaire survey. The survey was conducted remotely in September-October 2020. Results: The analysis of the scientific literature and the results of the research allow to state that the teacher in the reality of education faces many challenges in educating modern preschool children.The research found that teachers must be able to work in constant change, be able to manage the educational process, which requires modern didactic knowledge, to solve complex educational situations arising from children’s differences and the diversity of their educational needs, to perfectly manage information technology without which a modern educational process is not possible and have other important competences that are necessary in the diversity of the activities of the teacher of the 21st century.
Dynamic Volatility Modelling of Bitcoin Using Time-Varying Transition Probability Markov-Switching GARCH Model

Bitcoin (BTC), as the dominant cryptocurrency, has attracted tremendous attention lately due to its excessive volatility. This paper proposes the time-varying transition probability Markov-switching GARCH (TV-MSGARCH) models incorporated BTC logarithmic daily trading volume or Google daily searches as exogenous factors to model the volatility dynamics of BTC return series. Extensive comparisons were carried out to evaluate the modelling and forecasting performances of TV-MSGARCH models with the benchmark models such as GARCH, GJRGARCH, threshold GARCH and constant transition probability MSGARCH. Results reveal that the TV-MSGARCH models predominate other models for the in-sample model fitting based on log-likelihood function and other benchmark criteria. Furthermore, the TV-MSGARCH model with Google daily searches offers the best out-of-sample forecast evaluated based on quasi-likelihood loss function and also using Hansen’s model confidence set. In addition, the Filardo’s weighted transition probabilities is computed and the results show the existence of time-varying effect on transition probabilities. Lastly, new approach for computing different levels of long and short positions of value-at-risk forecasts based on TV-MSGARCH models are also provided and tested.
Metrological study of measuring the interfacial tension of liquids by the method of a rotating drop

An improved procedure for measuring the interfacial tension of liquids by the rotating drop method is considered. In the improved method it is proposed to determine the coordinates of the points of the contour of the rotating drop from the digital image using iterative calculation of the coordinates of the points of the corresponding contour of the rotating drop. The coordinates of the points of the drop shape are calculated by the numerical method of Runge-Kutta integration of the 4th order with step correction.The sources of uncertainty of measuring the interfacial tension of liquids are determined by the improved method of a rotating drop and the device that realizes it. Uncertainties of input values are the following: uncertainty of measuring the difference of densities of investigated liquids, uncertainty of measuring the frequency of rotation of the tube with liquids, uncertainty of coordinates of points and radius of the rotating drop contour in the image, uncertainty of calculated coordinates of points and radius of rotating drop contour. A mathematical model for estimating measurement uncertainty has been developed. It is shown that the procedure has a higher sensitivity to the uncertainties of the optical magnification of the glass tube and the conversion factor of the optical system of the device. It is also shown that the uncertainty of the calculation of the coordinates of the points and the radius of the contour of the rotating drop by the Runge-Kutta method can be neglected.The value of the measurement uncertainty estimate was calculated on the example of measuring the interfacial tension of 0.02% aqueous solution of “Stinol” at the boundary with kerosene. The obtained value of the expanded uncertainty confirms the effectiveness of the method of calculating the interfacial tension of liquids using the set of coordinates of the points of the drop shape.
A Succinct Analysis for Deep Learning in Deep Vision and its Applications

Introduction: Deep learning methodologies can achieve forefront results on testing deep vision issues, for instance, picture portrayal, an object area, face affirmation, Natural Language Processing, Visual Data Processing and online life examination.ConvNet, Stochastic Hopfield network with hidden units, generative graphical model and sort of artificial neural network castoff to absorb competent information coding in an unproven way are deep learning plans used in deep vision issues.Objection: This paper gives a succinct survey of without a doubt the most critical Deep learning structures.Deep vision assignments, for instance, object revelation, face affirmation, Natural Language Processing, Visual Data Processing, web-based life examination and their utilization of this task are discussed with a short record of the historic structure, central focuses and impairments.Future headings in arranging Deep learning structures for Deep vision issues and the troubles included are analysed.Method: This paper consists of surveys.In Section two, Deep Learning Approaches and Changes are audited.In section three, we tend to portray the uses of Applications of deep learning in deep vision.In Section four, Deep learning challenges and directions are mentioned.At long last, Section five completes the paper with an outline of the results. Results and Conclusion:Though deep learning can recall a huge proportion of data and info, it's feeble cognitive and perception of the data makes it a disclosure answer for certain applications.Deep learning despite everything encounters issues in showing various erratic facts modalities at the equal period.Multimodal profound learning is an extra notable heading in progressing deep learning research.
Ethical intelligence and its relation to the mutual social trust of students

The concept of ethical intelligence is one of the most important and modern concepts. Moral intelligence consists of seven fundamental virtues: compassion, conscience, self-control, respect, compassion, tolerance and justice. These virtues are the basic characteristics of moral intelligence. a place . This is what children and adults need to face the challenges and ethical pressures they face during their lives. So building moral intelligence in children is the best way to put them on track so that they can work and think correctly. It is also the best hope to develop strong personality traits. The acquisition of moral intelligence, as Michelle Bourba asserts, affects all aspects of individual life as well as the quality, careers, productivity, skills, citizenship, and even contributions to art, commerce, literature, the community, and society as a whole.
Proactive Management in Academic Libraries: Promoting Improved Communication and Inclusion of Academic Librarians and Archivists in Cybersecurity Policy Creation

Although increasing cybersecurity threats continue in libraries, not many studies are available which examine surrounding cybersecurity policies. Even less has been done on specific types of libraries such as academic and archives. When it comes to academic libraries, cybersecurity policies take a top-down approach to managing and creating policies. The problem is that both academic libraries and archives are unique areas within a university setting. Some of the general policies do not always handle specific issues dealt with in an academic library or archives. This paper investigates if an actual gap or void in policy exists which could create issues in academic libraries and archives, as well as if the university cybersecurity policy is being communicated, reviewed, reported, and created with inclusion of librarians and archivists. An 18-question survey was administered to librarians, archivists, and university information technology cybersecurity professionals within the 24 academic institutions of University Systems of Georgia (USG). Twenty-seven respondents completed the survey. The survey was, then, analyzed according to subcategories. A general theme emerged: communication of cybersecurity policy and the inclusion of librarians and archivists in policy creation and reporting could improve cybersecurity defense. The lack of participation and report feedback also lead to a very low perception or barometer score (5.1 average on a 10-point scale) as to how well the cybersecurity plan was being communicated. The solution to the communication gap could be in form of a plan. A conceptual model entitled Communication Enlightenment Engagement Plan (CEEP) would increase involvement by community engagement (inclusion, policy review, and policy creation.) Adding a feedback loop to CEEP will aid in the engagement process as well as keeping top tiers of management aware of policy changes and issues.
HUMAN ROBOT INTERACTIVE INTENTION PREDICTION USING DEEP LEARNING TECHNIQUES

In this research, we propose a method of human robot interactive intention prediction. The proposed algorithm makes use of a OpenPose library and a Long-short term memory deep learning neural network. The neural network observes the human posture in a time series, then predicts the human interactive intention. We train the deep neural network using dataset generated by us. The experimental results show that, our proposed method is able to predict the human robot interactive intention, providing 92% the accuracy on the testing set.
WF_DiMP: weight-aware dual-modal feature aggregation mechanism for RGB-T tracking

Visual object tracking has attracted a lot of interests due to its applications in numerous fields such as industry and security. Because the change of illumination could lead to RGB tracking failure, more and more researchers focus on RGB-T tracking methods based on fusion of visible and thermal infrared spectrums and hasten their development in recent years. In order to utilize dual-modal complementary information adaptively, we design a weight-aware dual-modal feature aggregation mechanism, and the WF DiMP algorithm for RGB-T tracking is therefore proposed in this paper. In WF DiMP, deep features of visible and thermal infrared images are extracted by ResNet50 and are leveraged to produce heterogenous response maps, from which dual-modal weights are learned adaptively. Weighted deep features are then concatenated as input of classifier and bounding box estimation module respectively in DiMP (Discriminative Model Prediction) network to obtain the final confidence map and an object bounding box. Experiments on VOT-RGBT2019 dataset are carried out. The results show that WF DiMP algorithm has higher tracking accuracy and robustness. The evaluation indexes PR, SR reach 82.1% and 56.3% respectively, which prove the effectiveness of our mechanism given in the paper.
Strategies for Effective Reading Onscreen

Chapter 6 draws upon what we learned in Chapters 4 and 5 to identify effective strategies for onscreen reading, with both single and multiple texts. The chapter begins by emphasizing the importance of determining reading goals, along with thinking about who the reader is, how cost factors in, the importance of active learning, and ways of applying print strategies when reading onscreen. The first set of recommendations is for young children, while the rest of the chapter looks at strategies for school-age readers. In discussing use of single texts, we consider such issues as genre, complexity, scrolling, priming a reading mindset, annotation, and concept maps. The section on reading multiple texts includes the challenge of recognizing online fake news and the potential to use skills developed when scrutinizing online documents to advance the larger civic good.
Why Object-Oriented Programming Is a Must for Code Quality

Did you know that object-oriented (hereafter OO) programming was introduced to SAP as far back as the year 2000 in the form of ABAP Objects? Ergo, there are some people at work who are younger than the ABAP Objects language.
Teaching Descriptive Texts to Tenth Grade Students in Deli Serdang

The objectives of this study were to describe the teachers’ ways of teaching reading of descriptive texts to tenth grade students in Deli Serdang, Indonesia and to reveal the underlying reasons for these approaches. This study was conducted by using a descriptive qualitative design. The subjects were two English teachers who taught the tenth grade students at SMA Swasta Melati Hamparan Perak in the 2018/2019 academic year. The data were collected by observing, video recording and interviewing, and were analyzed by using Miles and Huberman techniques. The findings show that the approaches that the teachers used were not focused on enabling the students to be independent or skilful readers. Most of the ways directed the students to become good at reading texts or translating the texts into Bahasa rather than teaching how to comprehend descriptive texts. Most of the approaches were focused on translation, vocabulary enrichment, stating ideas, pronunciation and managing the class. The approaches did not facilitate reading comprehension. This was due to the misperception of the concept of teaching reading comprehension.&#x0D; Keywords: teaching, reading comprehension, descriptive tex
LibGuides: Archives & Special Collections: Plan Your Visit

This is the home page for Archives & Special Collections, Dean B. Ellis Library, 7th Floor, Arkansas State University
Shot Composition Basics

Chapter 3 describes the fundamentals of shot composition for film. It includes rules of thumb to make shot design work at an abstract level, as well as for clarity, mood, and meaning in storytelling. These ideas can make a composition have more impact, be more interesting, and be more pleasing to the eye. Topics discussed include symmetry, balance, contrast, and using leading lines, as well as how to avoid distracting elements and unintended visual artifacts. The important question of when a shot should be framed off-center and when for film storytelling purposes the subject should be centered is addressed. The essentials of framing people are examined, including cropping, look-space, and walk-space. Several useful compositional techniques are described and illustrated, including creating a frame within a frame, using overlapping shapes, adding foreground and background, soft focus, silhouetting, backlighting, and finding camera angles that create dramatic perspective.
Video Class Agnostic Segmentation Benchmark for Autonomous Driving

Semantic segmentation approaches are typically trained on large-scale data with a closed finite set of known classes without considering unknown objects. In certain safety-critical robotics applications, especially autonomous driving, it is important to segment all objects, including those unknown at training time. We formalize the task of video class agnostic segmentation from monocular video sequences in autonomous driving to account for unknown objects. Video class agnostic segmentation can be formulated as an open-set or a motion segmentation problem. We discuss both formulations and provide datasets and benchmark different baseline approaches for both tracks. In the motion-segmentation track we benchmark real-time joint panoptic and motion instance segmentation, and evaluate the effect of ego-flow suppression. In the open-set segmentation track we evaluate baseline methods that combine appearance, and geometry to learn prototypes per semantic class. We then compare it to a model that uses an auxiliary contrastive loss to improve the discrimination between known and unknown objects. Datasets and models are publicly released at this https URL.
How Portland State University is reimagining unarmed campus security patrols

The past couple of years have been challenging ones for campus security and public safety agencies. On the one hand, the COVID‐19 pandemic turned 2020 on its head, requiring administrators to adapt quickly to circumstances few could have predicted.
Interlinkage between Governance and Economic Development: A Review of Existing Literature

Governance is defined as the exercise of economic, political and administrative authority to manage a country’s affairs at all levels. It comprises mechanisms, processes and institutions, through which citizens and groups articulate their interests, exercise their legal rights meet their obligations and mediate their differences. Thus, governance can be summed up as a process through which authority in a country is exercised (UNDP, 1997; UNESCO, 2012). Development linked governance has been an issue much debated about in the contemporary world. Since the second half of the 1980’s, growth and development studies have started to shed light on the importance of improving institutions of governance on economic growth. Good institutions, good governance and good leadership are considered by many authors as necessary conditions to support the development effort of a country or region. Good governance is believed to be the single most important factor in eradicating poverty and promoting development, hence, the countries that have a higher rank in the world governance index are often found to be in a higher rank in the other aspects of development.&#x0D; There are several pathways through which governance and its various dimensions can impact a country’s economic growth, therefore, in this paper all the key issues related to governance has been discussed which are indispensable for the development of a nation.
Bilingual Dictionary-based Language Model Pretraining for Neural Machine Translation

Recent studies have demonstrated a perceivable improvement on the performance of neural machine translation by applying cross-lingual language model pretraining (Lample and Conneau, 2019), especially the Translation Language Modeling (TLM). To alleviate the need for expensive parallel corpora by TLM, in this work, we incorporate the translation information from dictionaries into the pretraining process and propose a novel Bilingual Dictionary-based Language Model (BDLM). We evaluate our BDLM in Chinese, English, and Romanian. For Chinese-English, we obtained a 55.0 BLEU on WMT-News19 (Tiedemann, 2012) and a 24.3 BLEU on WMT20 news-commentary, outperforming the Vanilla Transformer (Vaswani et al., 2017) by more than 8.4 BLEU and 2.3 BLEU, respectively. According to our results, the BDLM also has advantages on convergence speed and predicting rare words. The increase in BLEU for WMT16 Romanian-English also shows its effectiveness in low-resources language translation.
SparseGAN: Sparse Generative Adversarial Network for Text Generation

It is still a challenging task to learn a neural text generation model under the framework of generative adversarial networks (GANs) since the entire training process is not differentiable. The existing training strategies either suffer from unreliable gradient estimations or imprecise sentence representations. Inspired by the principle of sparse coding, we propose a SparseGAN that generates semantic-interpretable, but sparse sentence representations as inputs to the discriminator. The key idea is that we treat an embedding matrix as an over-complete dictionary, and use a linear combination of very few selected word embeddings to approximate the output feature representation of the generator at each time step. With such semantic-rich representations, we not only reduce unnecessary noises for efficient adversarial training, but also make the entire training process fully differentiable. Experiments on multiple text generation datasets yield performance improvements, especially in sequence-level metrics, such as BLEU.
Remote sensing interpretation of Erennaoer Sag and research on metallogenesis of sandstone-type uranium deposit

Erennaoer Sag is an important sandstone-type uranium orefield in Erlian Basin. In order to study the characteristics of the structures and the recharge-runoff-discharge groundwater system in Erennaoer Sag, remote sensing technology was applied to extract remote sensing geological information such as structural, the indices of brightness, greenness and wetness. Combined with geological data, the recharge-runoff-discharge groundwater system of Errennaoer Sag is divided, and two structural discharge zones are identified. According to the analysis of spatial distribution characteristics of interpreted structures and regional uranium deposits, it is found that uranium mineralization in Erennaoer Sag is closely related to the NNE structures of remote sensing interpretation. It is concluded that the remote sensing interpreted tectonic zone is a tectono-geochemical variation zone, which is closely related to uranium mineralization, and the superimposed reconstruction of multiple tectonic activities is an important factor for the formation of the uranium deposits in Erennaoer Sag.