Reviewerly/exHarmony huggingface dataset:
Human–Robot Collaboration: Understanding the Effects of Different Levels of Automation Assistance on Enhancing Eye-Gaze-Based Mobile Robot Tele-operation

The introduction of autonomous technologies in cities—such as driverless cars, ground robots, and drones—promises to transform urban services and interactions. As a newly emergent, intuitive, and promising technology, eye-gaze-based mobile robot teleoperation (referred to as Tele-gaze in this context) has recently been applied to human–mobile robot interaction for various activities in cities, such as in the use of assistive technologies to improve the autonomy and well-being of people with limited mobility. More recently, we have begun to witness a shift that takes advantage of automation assistance to improve human performance using Tele-gaze. However, there is a knowledge gap with regard to how various levels of automation assistance, when combined with interaction modalities, can affect human operators and their collaboration with non-human agents. More specifically, we need to identify the factors that can influence the Tele-gaze-based systems and their effects on the human–robot collaboration. In this paper, a novel Tele-gaze system supported by four interactive modalities is proposed. The eye-gaze control is supported by increasing levels of automation assistance from the mobile robot side, with two basic mechanisms (eye-imitation camera and user-will trigger mechanisms) present in all four modalities—Modality 1: without any automation assistance; Modality 2: with a collision-avoidance mechanism; Modality 3: with a collision-avoidance mechanism and pathway middle mechanism; and Modality 4: with a collision-avoidance mechanism and a guideline-following mechanism. Four sets of experiments with an indoor navigation task were conducted with the four interactive modalities. Each set was tested by our 12 participants using one of the four modalities. We analyzed and discussed the experiments’ outcomes from both (1) the mobile robot side and (2) the human operator side. Early findings indicated that automation assistance and human capacity can not only reinforce one another but also constrain one another. We suggest that adopting the right balance, with the appropriate level of automation assistance, is key to enhancing the Tele-gaze-based interactions without compromising human dominance, user experience, and the flexibility of the system capacity.
Inspection of Differences of Self-esteem, Depression, and Life-satisfaction after a Food-therapy Program: Mainly on the Senior-over-65

The purpose of this research is verifying the effect of food-therapy program for emotionally supporting senior-over-65. To conduct the research, we inspected the differences of senior self-esteem, depression, and life-satisfaction through Paired-samples t-test. As results of the food-therapy program, self-esteem and life-satisfaction increased, and depression decreased. In this point of view, we could verify that the food-therapy program suitable for programs emotionally supporting the seniors. In consequence, we directed the direction of the programs emotionally supporting the seniors based on the food-therapy program.
Digitalization And Education In The Covid-19 Pandemic: Practices And Innovations In Higher Education System In Kazakhstan

The article analyzes new methods and innovative approaches to the implementation of education in digital format, which are actively being introduced in higher educational institutions. The scientific work is based on the method of theoretical analysis of research of the universities of the Republic of Kazakhstan. New methods and innovative approaches to the implementation of education in digital format have been identified and are being actively implemented by higher educational institutions. In general, this study shows that Kazakh universities are adapting to distance education with certain difficulties. Despite sais difficulties that the pandemic has presented in the field of education, it is important to emphasize the possibilities of distance learning.
Analysis of Data Security and Privacy Protection in Cloud Computing Services

Abstract: Cloud computing will become a successful paradigm for statistics computing and storage. Increasing worries about information security and privateness in the cloud, however, have emerged. Ensuring protection and privacy for facts management and question processing in the cloud is imperative for better and broader uses of the cloud. Usually cloud computing services are delivered with the aid of a third celebration issuer who owns the infrastructure. It blessings to point out but a few encompass scalability, resilience, flexibility, effectivity and outsourcing non- core activities. Cloud computing provides an progressive commercial enterprise model for corporations to undertake IT services without upfront investment. Despite the possible positive aspects achieved from the cloud computing, the businesses are sluggish in accepting it due to safety issues and challenges related with it. Security is one of the primary problems which bog down the growth of cloud. The notion of handing over essential facts to any other organization is worrisome; such that the buyers want to be vigilant in understanding the risks of records breaches in this new environment. This paper introduces a specific evaluation of the cloud computing safety problems and challenges focusing on the cloud computing. Keywords: Cloud Computing, Privacy, data security, Monotoring
Multi Cloud Data Hosting with SIC Architecture

Abstract: Data hosting on cloud decreases cost of IT maintenance and data reliability get enhance. Nowadays, customers can store their data on single cloud, which has some drawbacks. First is vendor lock in problem and second is security on cloud. The solution to this problem is to store the data on different cloud server without redundancy using encryption algorithm. Customers do not want to lose their sensitive data on cloud. Another issue of cloud computing is data thievery should be overcome to supply higher service. Multi-cloud environment has ability to scale back security risks. To avoid security risk we offer framework. Keywords: Cloud computing, cloud storage, data hosting, data intrusion, multi-cloud, single cloud.
STATE-PUBLIC MANAGEMENT OF EDUCATIONAL ORGANIZATION

The article reveals the concept of state-public management of an educational organization. state-public management is not a set of state and public structures, but a system of interaction, which is based on the voluntary acceptance of certain obligations and decisions by the state and citizens in the management of education. The goal of state-public management should be a combination of state and public principles in the management of the educational organization of the state. The article considers the model of state-public administration of a secondary school in the city of Nizhnevartovsk, describes the strengths of this model and discusses the points that require modernization. A modernized model of state-public management of an educational organization is proposed and considered. The purpose of this model is to put the problems of the functioning and development of education in the center of public attention, to expand collegial, democratic forms of management, to put into practice the state-public principles of management. To develop social partnership in the education system as a way to solve urgent problems of development and modernization of education through the introduction of a public management mechanism. The objectives of the proposed model are: to ensure the involvement of students in self-government activities, to form students' social activity, the ability to socialize in modern conditions; increase the interest of parents in the state of education and upbringing at school, involve parents in the daily activities of the school, increase the level of interest and responsibility for raising children in the family; to encourage the creative attitude of teachers to pedagogical activity, to develop a sense of personal responsibility for the results of the school; develop partnerships with public and private organizations, government agencies to assist the school in the education and upbringing of children, to attract extrabudgetary funds, for financial and material assistance to the school.
Larramendiren Hiztegi Hirukoitzaren digitalizazioa. Karaktereen ezagutze optikoa eta Wikitekara igotzea

Artikulu honetan Larramendiren Hiztegi Hirukoitzaren digitalizazioko OCR prozesua deskribatzen da, adimen artifizialaren adarra den ikasketa automatikoa baliatuz. Horretarako, eskaneatutako irudien aurreprozesamendua deskribatzen da, eta ondoren, Kraken erreminta baliatuz, eskuz transkribatutako laginetik abiatuta hiztegiko testua ezagutuko duen ereduaren trebakuntza azaltzen da. Doitasun handiko testuaz gain, letra etzana eta testuaren posizioa gordetzen dituzten fitxategiak sortu dira, hiztegiaren egitura irudikatzeko balioko dutenak. Emaitzak prozesatu eta Wikiteka plataforman eskuragarri jarri direnez, auzolanez transkripzio osoa zuzendu daiteke. Zuzendutako transkripzio hori informazio-erauzketa prozesutik pasako da, hiztegiaren egitura lexikografikoa ikasketa automatikoz erauzteko. Informazio horrekin RDF estandarrarekin bat datorren moldaketa-eredu baten lehen proposamena landuko da, Wikidatan integratzeko.
Polarization-entangled photon pairs in the visible spectral band using intermodal spontaneous four-wave mixing

Abstract The theoretical and experimental investigation results of the generation of the polarization-entangled photon pairs operating at visible wavelengths are reported. The generation of polarization-entangled photon pairs was based on intermodal spontaneous four-wave mixing (IM-SFWM) using standard step-index few-mode fiber. It was shown theoretically that several combinations of IM-SFWM processes could occur depending on spatial modes of a pump beam. A polarization-entangled photon pair source based on Sagnac loop incorporating a segment of few-mode fiber were then experimentally created. A two-photon interference fringe visibility of our implemented photon pair source were 91.7% and 88.8% in H/V bases and D/A bases, respectively. A quantum state tomography was also conducted to reconstruct the density matrix of the generated state with a fidelity to a maximum entangled state of 93.1%.
Soft Metaclustering for Unsupervised Recognition of Concept Drift

Abstract Streaming data analysis presents numerous challenges: the unbounded and sequential nature of the stream requires evolving models in order to capture its intrinsic non-stationarity and related concept drift. Relatively few methods for the detection of the drift are unsupervised and require no labels during training. In this paper, a soft and dynamic metaclustering approach is used for concept drift detection on streaming data. The pro posed method exploits possibilistic memberships for a natural quantifica tion of the drift and is able to effectively recognize both abrupt and recur ring drift. The effectiveness of the proposed method has been assessed on synthetic data from a public benchmark, yielding notable results.
Cultivating Gender Sensitivity &amp; Critical Reading Skills Using Fiction

The importance of Critical Reading Skill (CRS) and gender sensitivity to support every individual’s success in academic, personal, and social life has long been acknowledged. The accelerating advancement of technology makes the need for CRS &amp; gender sensitivity more crucial. However, due to various factors, CRS development through the educational process has not been satisfactory. This research reviews current ideas and studies on the nature of CRS, gender sensitivity, the nature of fiction, and their role in developing CRS. To get ideas about how to implement using fiction to promote CRS &amp; gender sensitivity, this study ends with the practical description of a step by step of using fiction with gender sensitivity to promote CRS through an instructional model. This study employs Classroom Action Research (CAR). Action research designs are systematic procedures used by teachers to gather qualitative data to address improvements in their educational setting, their teaching, and the learning of their students. Action research enables teachers to keep track and take account of the many aspects of their work with students through a systematic routine. This study aims to investigate gender sensitivity &amp; the critical reading strategies employed by Indonesian English as Foreign Language (EFL) students. To achieve the aim of the study, the Stringer’s Action Research Model that is a cyclical and repetitive process of inquiry i.e. Look, Think, and Act was utilized. This study used Bloom’s taxonomy as useful reference tool to describe the ability of thinking simply for undergraduate EFL students. Indonesian EFL students are encouraged to employ critical reading strategies systematically thorough their reading process to engage in critical reading &amp; gender sensitivity. The instruction of the critical reading strategies based on cognitive domain of Bloom’s taxonomy is also explicit and direct so that students are able to ask many organized and higher order questions. Throughout the study, students are also encouraged to believe that their reading difficulties were due to lack of strategies &amp; gender sensitivity rather than a lack of their ability and skills.
An overview of AI and Machine Learning methods: motivations, concepts, and examples

Abstract What is artificial intelligence? Big Data? Machine learning? It may seem very difficult to define these terms and identify their use in real life, aside from the hype surrounding them over the past ten years. All of these terms are interconnected - sometimes they intersect, often they are included in each other. The main focus of this presentation is to present ‘Machine learning' methods, which can be defined as algorithms that learn patterns (a function) about a particular phenomenon (an output variable), based on examples (training data), often without any a priori on the shape of these patterns. Therefore, they are a broad family of methods that include traditional statistical methods such as linear regression models, but which often offer more flexibility in terms of hypothesis and complex data settings. Multiple frameworks exist, based on how many examples are available (size of the training data) and the kind of modeling application one wants to perform (e.g., classification, regression, clustering). Many different families of methods exist for each modeling application, which offers a tremendous amount of different algorithms, each having advantages and drawbacks. In practice, easy-to-use libraries were developed in popular programming languages such as Python and R, offering implementations of the majority of essential algorithms.
Neural Layer Bypassing Network

&lt;p&gt;This research introduces and evaluates the Neural Layer Bypassing Network (NLBN), a new neural network architecture to improve the speed and effectiveness of forward propagation in deep learning. This architecture utilizes 1 additional (fully connected) neural network layer after every layer in the main network. This new layer determines whether finishing the rest of the forward propagation is required to predict the output of the given input. To test the effectiveness of the NLBN, I programmed coding examples for this architecture with 3 different image classification models trained on 3 different datasets: MNIST Handwritten Digits Dataset, Horses or Humans Dataset, and Colorectal Histology Dataset. After training 1 standard convolutional neural network (CNN) and 1 NLBN per dataset (both of equivalent architectures), I performed 5 trials per dataset to analyze the performance of these two architectures. For the NLBN, I also collected data regarding the accuracy, time period, and speed of the network with respect to the percentage of the model the inputs are passed through. It was found that this architecture increases the speed of forward propagation by 6% - 25% while the accuracy tended to decrease by 0% - 4%; the results vary based on the dataset and structure of the model, but the increase in speed was normally at least twice the decrease in accuracy. In addition to the NLBN’s performance during predictions, it takes roughly 40% longer to train and requires more memory due to its complexity. However, the architecture can be made more efficient if integrated into TensorFlow libraries. Overall, by being able to autonomously skip neural network layers, this architecture can potentially be a foundation for neural networks to teach themselves to become more efficient for applications that require fast, accurate, and less computationally intensive predictions.&lt;br&gt;&lt;/p&gt;
A Brief History of the Muon

The theoretical and measured values of the muon magnetic moment anomaly have grown apart. Is this due to experimental error, or computational error, or to physics lying beyond the Standard Model?
Reported Speech in Recurrent Courses of Action

Chapter 8 is concerned with the question of how a sharp increase in the use of reported speech, and the heightened prominence of the interaction between the LO and the PM in the 2003–2013 sample are related to the constitution of recurrent, patterned courses of action. The small sample of reported speech from 1978–1988 did not yield such courses of action where reported speech with SAY is relevant. This contrasts with the 2003–2013 sample, where two recurrent adversarial courses of action with a patterned use of reported speech were identified: enticing sequences and trading-quotes sequences. Here enticing sequences seem to be a more recent development. By contrast, there is early evidence for a precursor of trading-quotes sequences in the 1978–1988 sample
Authorship Attribution of Russian Social Media Texts: Does the Volume of Data Favor Idiolect Identification?

The problem of determining the author of a text, formerly solved on fiction texts, has currently become one of the central ones in cybersecurity, which calls for new techniques and approaches to be employed. One of the issues in the field is a short length of texts whose authorship is typically needed to be determined and a small amount of data per author. While a few papers investigate the problem of the minimal text length for authorship analysis, the effect of the total amount of data per author on the accuracy of attribution is not well studied, especially in regards to informal texts. The paper analyzes the effect of the total volume of texts per author on the idiolect identification accuracy separately for different types of stylometric markers on the datasets compiled of Russian forum texts. For text classification a supervised version of principal component analysis (PLS-DA) is applied which is widely used in bioinformatics, but it has been introduced for the first time for an idiolect identification task. The conclusion is made about the absence of a linear effect of the total amount of data on the attribution accuracy. It is assumed that author recognizability for a classifier depends on a variety of factors which are unique to each particular attribution case.
Challenging the Students‘ Sense of Mathematics Via Decoding Problems in Chernorizec Hrabar Tournament

Under consideration is a thematic branch from the Chernorizec Hrabar (ChH) math tournament, which aims to check and develop the student’s sense of mathematics. The ChH competition papers include several types of test items related to codes. These test items require just basic math knowledge but a high level of nonstandard reasoning and a kind of synthetic mathematical abilities. The authors’ standing point is to present by examples how the idea of (de)coding evolves in competition papers for students in different ages.
Virtual Math Class

The challenge of conducting an electronic environment for remote mathematics education is a condition for finding effective methods, forms, approaches, and platforms for a successful learning process. One of the solutions for the implementation of a „virtual lesson“ in mathematics is the cloud environment of GeoGebra. The article discusses various aspects of the application of the online platform GeoGebra in mathematics education: creating interactive worksheets, virtual classrooms, online boards, tools for classroom management, monitoring, and evaluation of student achievement. The attitudes of mathematics teachers about the use of GeoGebra online applications in math lessons are researched and analyzed.
Information systems Estimated demand for certified seed

The availability of certified seeds is a very important strategy to maintain food security. When farmers plant their farms with certified seeds, it can increase the production yields grown by farmers. To answer the availability of sources according to the needs of farmers or consumers, it is necessary to design an information system for forecasting the demand for certified seeds, with a methodology Rational Unified Process (RUP) so that this method can be useful to identify the system that is running and can describe the system to be built. Meanwhile, to produce an estimate of the demand for certified seeds, a linear regression approach will be used which will be included in the design of the system. The design of this system will produce a function to assist producer farmers in estimating certified seed production, assisting the availability of certified seed information for consumers, and assisting the PSBTPH Installation in the Subang Region in carrying out evaluation and monitoring.
A Combinatorial Question Related to an Easter Tradition Led to a New Entry in OEIS

In some regions of Bulgaria (at least) there is an Easter tradition, according to which in group of people first each one chooses a differently coloured egg, then each pair of people performs a swap (or swaps) by exchanging the eggs they currently have until everyone gets the originally chosen egg. This generates a natural question: if there are n people in the group, find the least number E(n) of swaps which makes this possible. We prove that E(n) is the least even number not less than n(n−1)/2. The sequence thus generated was added to the Online Encyclopedia of Integer Sequences and linked from there to several seemingly distant combinatorial results.
Statistical Significance – is it a Panacea or a Pitfall?

Thoughts and considerations are presented about the term “statistical significance” – a common tool for “proving” the compatibility with practice of theoretical models designed on the ground of assumptions. In accordance with the set goal and based on the theoretical features and logics of the concept, there are revealed problematic issues and possibilities for abusing it when verifying statistical hypotheses. The suggested argumentation enables one to claim that the “prescriptive” verification of statistical hypotheses creates conditions for developing a pseudoscience supported by incorrect conclusions which are made on the ground of “statistically significant” results.
Spark SQL: Advanced

Chapter 3 introduced the foundational elements in the Spark SQL module, including the core abstraction, structured operations for manipulating structured data, and various supported data sources to read data from and write data to. Building on top of that foundation, this chapter covers some of the advanced capabilities in the Spark SQL module and peeks behind the curtain to understand the optimization and execution efficiency that the Catalyst optimizer and Tungsten engine provide. To help you with performing complex analytics, Spark SQL provides a set of powerful and flexible aggregation capabilities, the ability to join with multiple datasets, a large set of built-in and high-performant functions, an easy way to write your own custom function, and a set of advanced analytic functions. This chapter covers each of these topics in detail.