Reviewerly/exHarmony huggingface dataset:
Development of an Approach for Creating and Storing the Information with the Help of Unity and AR Core SDK

Storing the information in the compact manner which is also easy to access is very difficult during these days. But with the help of AR (Augmented Reality) it is possible to place the notes and information in place without creating mess about it. A note keeping system inputs the note and the place on which it should be placed. This feature can be developed using unity and ARCore Sdk. AR Notekeeper is an AR based application in which user can create Notes and To Do Lists and not only just create them but store them in real word virtually using Augmented Reality with a passcode security feature. This functionality not only allows to keep their notes in a place which is known to only them but also ensures it stays there.
Application Algorithm of Equipment Alarm Data in Power Network Direct Acquisition Data Analysis System

This paper has presented an idea of using equipment alarm data to support relevant departments find easy-to-fault point. According to the information, make next year's equipment update and maintenance plan. The easy-to-fault point could also help with training and equipment design use. The system assisted people to make decision on which part of power grid system to make further investment. In this way, the power system would grow stronger with limited investment. Firstly, coded information according to the characteristics of power system regulation to prepare for data extraction from the Bayesian model. Secondly, in order to solve the problem of accuracy and reliability, the Bayesian model was adopted to calculate the accuracy rate.
Current Drift in Energy Efficiency Cloud Computing

Energy Efficiency can be defined as reduction of energy used by a given service or level of activity. In spite of scale and complexity of data centre equipment it can be highly difficult to define the proper activity that could be examined for the efficiency of energy. So there can be four scenarios which may define within the system where the energy is not utilised in an efficient manner. The main goal of Cloud service providers is creation of usage of Cloud computing resources proficiently for efficient cloud computing. Cloud computing has many serious issues such as load manager, security and fault tolerance. This chapter discusses the energy efficient approaches in cloud computing environment. The energy efficiency has become the major concern for the service providers. In this chapter, the major concern is the high lightly of resource allocation challenges and there are some which will be given in the data center energy consumption. The focus is done on the power management task and even the virtualization of saving the energy.
DSM

The number of cores and the capacities of main memory in modern systems have been growing significantly. Specifically, memory scaling, although at a slower pace than computation scaling, provided opportunities for very large DRAMs with Terabytes (TBs) capacity. Consequently, addressing the performance and energy consumption bottlenecks of DRAMs is more important than ever. DRAM memory refresh operation is one of the main contributing factors to the memory overheads, especially for large capacity DRAMs used in modern servers and emerging large-scale data centers. This paper addresses the memory refresh problem by leveraging the fact that most cloud servers host virtualized systems that use similar kernels, libraries, etc. We propose and experimentally evaluate a novel approach that exploits this observation to address the DRAM refresh overhead in such systems. More specifically, in this work, we present DSM, a light-weight hardware extension in memory controller to detect the pages with same content in memory and refresh only one of them and redirect the requests to the others to this page. Our detailed experimental analysis shows that the proposed DSM design can reduce 99th percentile memory access latency by up to 2.01x, and it also reduces the overall memory energy consumption by up to 8.5%.
A Saddle Point Finding Method for Lorenz Attractor through Business Machine Learning Algorithm

Cancer has a long time history in our human health experience. Practically, one-fifth of the disease was caused by virus infection. Thus, it is important for us to understand the virus-cancer infection mechanism. Statistically, we may perform the necessary causality regression analysis in such a situation to build up the corresponding model just like my previous case in influenza-weather infection. In the present research, I will interaction the systems of differential equations (Lorenz System) with my HKLam theory and figure out the recursive result that we may get. Then we may go ahead with the corresponding policy generated from the dynamic programming that can solve the Markov Decision Process. In addition, we may apply the HKLam theory to the chaotic time series and compare the model with machine learning one for a better selection with failure explanation. Finally, I will also discuss a novel mathematical method in determining the saddle point in the Lorenz attractor together with the gradient descent. The aim is to find the equilibrium for the Lorenz attractor with given initial conditions. It is hoped that the mathematics-statistics interaction together with the causal regression (Artificial Intelligence) model may finally help us fight against those diseases like virus-infected cancer or others.
An multi-task head pose estimation algorithm

Estimating head pose is a hot topic in facial behavior analysis and understanding. Most of the existing methods called two-stage method take head pose estimation and face detection as two separate tasks. In general, independent face boxes need to be proposed before head pose estimation. Such scheme is inefficient and has poor robustness. The existing estimation methods for head pose is lack of effective anti-noise design. In this paper, we propose a multi-task deep learning method, which integrate face detection and pose estimation together. Three kind of anti-interference strategy are proposed. Compared with the existing two-stage method, the proposed method can be performed with less consumption of resource. Benefited from the complementary characteristics of multi task joint learning, our proposed has higher accuracy. Experiments on several public datasets fully show that the attitude angle estimation error accuracy of our one stage algorithm reaches 1.96° (MAE). It is better than the existing state of the art method. The speed is twice as fast as that of the two-stage method.
Top Picks

The articles in this special section are from a selection of 2018 conference articles that have the most potential to influence the work of computer architects in the near future. IEEE Micro has had this tradition of evaluating papers from the previous year’s architecture conferences and selecting the papers with the most novelty and potential for long-term impact. IEEE Micro has selected such a compendium of papers for the last 15 years, and the magazine is upholding the tradition this year as well. Any article published in top architecture conferences during 2018 was eligible to compete for the Top Picks honor.
Identifiers in Libraries: ISSN Revision Unique

SUMMARY. The world of unique identifiers can sometimes seem like an alphabet soup: SICIs, PII's, ISSNs, DOIs, ISTCs, InfoURIs, and more. These standards will be explored, and questions raised related to unique identifiers as crucial keys to the new library environment, where information sharing requires the increased precision in identification and linking that can only come from development and use of unique identifiers. How do we uniquely identify a library or branches within a system? What about journals, articles within journals, books, chapters, component and other parts? Existing identifiers such as NUC symbols, ISBN, and ISSN are imprecise and may be inadequate in an age of machine parsing and processing. New identifiers are needed, and there are opportunities for library involvement and advocacy. [Article copies available for a fee from The Haworth Document Delivery Service: l-SOO-HAWORTH. E-mail address: &lt;docdelivety@haworthpress.com &gt; Website: &lt; https://www.HaworthPress.com &gt;]
Digital transformation in the focus of transdisciplinarity of philosophical knowledge

From the perspective of interdisciplinary and transdisciplinary synthesis, there was studied the conceptual and methodological certainty of the existing approaches to understanding digital transformation. The author proceeds from the fact that digital transformation is not only the new technology (artificial intelligence, blockchain, data analysis, Internet of things etc.), but also a deep transformation of the basics of life, the structure of organizations and enterprises, society as a whole. In other words, it is a fundamental transformation of traditional models of life organization, construction, and development of a new reality, which is not always tolerant to humans. Thus, digital transformation is considered as essential characteristic of the modern era, the formation of which was influenced by a number of factors of social dynamics. The key factors are informatization and total digitalization. These processes caused formation of new sociality, which was different from the previous types of civilizational development with a sharp increase of the role of temporal and artificial component in the structure of social-biological evolution. In conditions of intensive social dynamics, choice remains an essential characteristic of new sociality. At the same time, the subjective side of social choice is changing: it is not an atomic personality, group, institution, but a high tech social practice taken from the point of view of the system of interaction of agents that realize the social-economic expediency in line with intensive innovation transformation. There is substantiated the increasing importance of modern social-humanitarian knowledge as conceptual-categorical and methodological base of reflection and prediction of the processes of formation of new sociality. In the structure of scientific-methodological reflection, there is actualized the transdisciplinary status of philosophical knowledge and its potential in connection with new instrumental-technical capabilities of cognitive practice.
Organizational and pedagogical conditions of scientific and methodological work efficiency in pedagogical higher educational establishments

The article deals with the problem of ensuring scientific and methodological work efficiency in higher educational establishments, in particular pedagogical ones. Based on the analysis and generalization of scientific literature and practical experience, the essence of key concepts is determined: condition; organizational and pedagogical condition, efficiency. Certain aspects of the place and the role of scientific and methodological work in the holistic pedagogical process of higher educational establishment are identified, which provides professional training of students in the context of cooperation pedagogy. The main problems are highlighted and their consideration in the scientific and methodological work planning process is outlined. It is noted that an important condition for the improvement of scientific and methodological work is the concretization of its areas, which are named and meaningfully characterized. Approaches to the development of scientific bases for effective quality management of the educational process in a higher education establishment, a component of which is scientific and methodological work, are proposed. The essence and the significance of the system diagnostics are clarified, the results of which are decisive for the formation of the content and the development of forms of scientific and methodological work in pedagogical higher educational establishment. According to the results of the research, the pedagogical conditions (external and internal) are singled out, the creation of which is conditioned by the efficiency of the formation of scientific and methodical work system in higher educational establishments, their generalized characteristics are presented. The organic interrelation of the professional educational environment, in particular in pedagogical higher educational establishments, with scientific and methodical work, which is its structural element, is illustrated. The influence of high-quality professional educational environment on increasing the level of the methodological competence of both teachers and future ones is stated.
CONSULTING CENTER "MANAGE-PRO". ACADEMY OF TREND MANAGEMENT

The project of creation a consulting center on the basis of "Secondary General Education School No82" for school administrators "Manage-PRO" is an innovative product of the school's management team in the concept of the National Technology Initiative. The project received a high peer review from HSE experts and is the winner in the Breakthrough nomination of the international competition for innovators in education “KIVO-2020”. The project is based on trends in the development of education in the NTI ideology, on the resources provided by National Projects, on international standards and best practices for the design of engineering and technological education, on the multi-level education infrastructure of the NTI ecosystem and on in-depth analysis of stakeholders. "Manage-PRО" is a consulting support for pivots of leadership management teams of schools: from the choice of small adjustments to a radical change in the concept due to the gradual formation of a competence portrait of members of management teams of schools and the creation of a marketplace of best practices.
The Library Big Data Research: Status and Directions

Libraries are widely used by government, universities, research institutes, and the public since they are storing and managing intellectual assets. The library information directly stored in libraries and about the people interaction with libraries can be transformed into accessible data which then will be used by researchers to help library better serve users. Librarians need to understand how to transform, analyze, and present data in order to facilitate such knowledge creation. For example, the challenges they face include how to make big datasets more useful, visible and accessible. Fortunately, with new and powerful analytics of big data, such as information visualization tools, researchers/users can look at data in new ways and mine it for information they intend to have. Moreover, interaction of users and stored information has been taken into librarian's consideration to improve library service quality. In this work, the authors discuss the characteristics of datasets in library and argue against a popular confusion that data involved in library research is not big enough, conduct a review for the research work on library big data and then summarize the applications and research directions in this field. The status of big data research in library in China is discussed. The challenges associated with it are also discussed and explored.
Decision Making Under Deep Uncertainty With Fuzzy Algorithm in Framework of Multi-Model Approach

Task of soft computing for decision support in field of risk management is analyzed in this chapter. Multi-model approach is described. Interrelations between models, remote sensing data and forecasting are described. Method of water quality assessment using satellite observation is described. Method is based on analysis of spectral reflectance of aquifers. Correlations between reflectance and pollutions are quantified. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality is making based on fuzzy algorithm using limited set of uncertain parameters. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated. Conclusions concerned soft computing in risk management are proposed and discussed. It was demonstrated, that basing on spatially distributed measurement data, proposed approach allows to calculate risk parameters with resolution close to observations.
EXAMINATION MALPRACTICE TENDENCY AND SECONDARY SCHOOL STUDENTS’ ACADEMIC ACHIEVEMENT IN SOCIAL STUDIES IN CALABARE SOUTH LOCAL GOVERNMENT AREA, CROSS RIVER STATE - NIGERIA

ABSTRACTThis study investigated “Examination malpractice tendency and Secondary Schools students’ academic achievement in Social Studies in Calabar South Local Government Area of Cross River State - Nigeria.” Review of relevant literature was carried out in line with the four sub-variables as follows: sorting tendency; students’ purchase of examination paper tendency; copying tendency and impersonation tendency and students’ academic achievement. The population of the study comprised of 1,004. The sample for the study was 150 students of JSS 2 drawn from six (6) secondary schools in the study area. Four research hypotheses were formulated to guide the study. Questionnaire titled: Teachers’ Examination Malpractice Tendency Questionnaire (EMTQ) and Social Studies Achievement Test were used for data collection. Pearson’s Product Moment Correlation Coefficient (r) Statistical tool was used to analyze the data collected from the respondents and tested at 0.05 level of significance and 148 degree freedom. The result showed that the four null hypotheses were rejected and the alternate retained. Recommendation was made as follows: Government should increase the salaries and ensure prompt payment too. As this may reduce the interest of teachers in search of additional pay through sorting from students as well as invoke the necessary laws to convict both teachers and students who engage in this act and the school authorities, teachers/invigilators should be sincere in the checking of photo album where it exists for examinations, to avoid impersonation. There should no compromise for children of the influential families.
Simulation

In this chapter we look at the geostatistical simulation of compositional data. The workflow typically consists of first applying a log-ratio transformation, then testing the transformed data for multivariate normality, applying an affine equivariant multivariate normal score transformation, if necessary, modelling the spatial continuity of the normal scores, followed by simulation and back-transformation. Several algorithms are available for simulating Gaussian random functions. These include LU decomposition simulation, sequential Gaussian simulation and turning bands simulation, which will be introduced briefly.
BOLD Ideas for Creative Social Networking

To further open the conversation about women's empowerment and global collaborations using new networking technologies, this chapter problematizes some prevalent ideas about creativity and social networking, notes suggested change that carry anti-feminist sentiments throughout the world, and suggests a number of ways that women and men can all benefit from an opening of queries about innovative ways of working together online. With the suggested expansions, the authors welcome more inclusive and invitational discussion about future digital media research and development.
CAPTCHA Basics

This chapter describes the basic concepts underlying the CAPTCHA test. Specifically, the aim of the test is described, together with the main tasks of the CAPTCHA and the requirements that the test has to meet in order to guarantee a high security level. The CAPTCHA test is framed inside the human–computer interaction model and strongly connected with the concept of human interactive proofs, which are used to make a differentiation between the human users and computer bot programs.
Key factors for the success of e-learning in high school students in times of Covid-19

The purpose of the study was to determine the level of influence exerted by the key factors for the success of e-learning, such as computer anxiety, the Collaboration quality, the Information quality, the service quality, the system quality and the use of computer systems, using the level of expert on the Web as a mediating variable and, as a dependent variable, the satisfaction perceived by the user in times of pandemic as a consequence of Covid-19. The applied methodology comprises two phases, firstly, an exploratory factor analysis using the IBM-SPSS, to determine the correct adaptation of the factors with their corresponding items in the instrument for data collection, secondly, it was performed In the confirmatory analysis, for the validation of the proposed structural model and to establish the relationships of the factors proposed in the model, the PLS-SEM methodology, Modeling of Structural Equations with Partial Least Squares, was used. The model was validated with a sample of 271 students from the 3rd to the 5th year of high-school education from a public educational institution in the Moquegua region of Peru. The study came to determine that there are different levels of influence exerted by the key factors for the success of e-learning, in the satisfaction perceived by the user, said influence is explained by 64.6%, considering the R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> statistic, being the most influential factors the Information quality and the quality of the collaboration.
Design and Implementation of Multi-Agent Online Auction Systems in Cloud Computing

Due to the high maintenance cost of traditional online auction system, poor load balance ability and down problems occurring in the peak value of system access, this paper aims to propose a solution to transit from traditional online auction system to cloud computing to get higher work efficiency, lower expenditure and less energy cost. The GAE platform is used to deploy application of the overall framework of online auction system in cloud computing, including development environment as well as online auction system components, and software architecture. The online auction negotiation algorithms in cloud computing are also proposed. Based on these key technologies, the business processes of the online auction system in cloud computing is designed, including users' login system, starting an auction, bidding processes, online auction data storage, and logout system. The online auction system constructed on GAE platform with cloud computing resources and storage ability can reduce the pressure of terminal equipment, which is more robust than traditional online auction system facing users' changeable needs in the process of online auction.
Ontology-Driven Situation Assessment System Design and Development in IoT Domains

An ontology-driven approach to software design and development of situation assessment systems (SAS) for IoT applications is considered. As SAS is used to build the situational model for the external environment, it highly depends on the operational domain. To simplify the transition from the domain description to SAS dataflow process the ontology-driven approach is proposed. The main idea of the approach is to explicitly formalize SAS dataflow process in an ontological form. For this purpose, a domain-independent SAS ontology is proposed that allows automation of the dataflow process design. The dataflow process ontology is used to automate development and runtime stages of SAS lifecycle. The proposed ontology is included into the proposed instrument set. The set can be used to build SAS systems for different domains described with OWL ontology. The set is evaluated on a traffic control scenario.