Reviewerly/exHarmony huggingface dataset:
Learnable Maximum Amplitude Structure for Earthquake Event Classification

Recently, most research has been conducted to minimize damage from earthquakes by establishing an early warning system through the analysis of short seismic waves. In particular, deep learning is widely used as it allows to learn complex patterns for earthquake detection from seismic data without complex physical knowledge. In this letter, we propose an improved ConvNetQuake for earthquake event classification by adding learnable features related to the maximum amplitude of the seismic waveform. Since the maximum amplitude is a major factor representing the characteristics of an earthquake, we presented a deep learning structure that can apply this factor in the process of determining whether an earthquake occurs. In the proposed structure, the maximum amplitude is transformed into a feature learned through multi-layer perceptron (MLP) and then concatenates with features extracted through a convolutional neural network (CNN). On the STanford EArthquake Dataset (STEAD) dataset, the proposed method significantly increases the performance for an earthquake event classification than the previous state-of-the-art (SOTA) method by only adding a few parameters.
Improving open domain content generation by text mining and alignment

A text obtained by a deep learning (DL) content generation system (raw text) usually has major issues in terms of randomness and incorrectness. In this chapter, we build a content improvement system specifically oriented towards repairing these errors by finding correct and consistent sentences from various sources and substituting problematic entities, phrases, and sentences in raw content with the correct ones. We use text mining (TM) to identify correct corresponding sentences and the syntactic and semantic generalization procedure (Galitsky, 2017) adopted to the content improvement task. Our evaluation is conducted in the personalized health content domain, and we assess the contribution of each correction operation and the resultant correction accuracy of 84%, having just 5% accuracy of raw text.
On application of the cluster approach in the implementation of the program of educational work in Higher educational institutions of technical profile

This article describes the decision of problem connected with the realization of the program of educational work because of the federal law “About the introduction of amendments in the federal law “About the education connected with the questions about upbringing students in Russian Federation” in the educational organization of higher education of technical profile on the base of the cluster approach with the help of the introduction complex of elements of electronic information and education environment in the practice activity. This environment is a systematic methodological support of the educational process and the system of monitoring and estimation the results of educational activity of the subjects of the educational process. The methods of analyzing the individual development of students are presented, which include an assessment of the level of formation of universal competencies, as well as a mechanism for implementing an educational work program based on a cluster, according to four main blocks: institute, mentoring and tutoring (classroom teachers of secondary vocational educational institutions, mentors of student academic groups, tutors, curators (from among students)); academic disciplines of the general education cycle, elective classes, student scientific societies; structural divisions of the extracurricular direction, professional unit. The structure of the electronic resource — “Mentor / class teacher’s Personal account” is presented in detail.
LES POLITIQUES DE FINANCEMENT DE LINNOVATION AU MAROC - ETAT DES LIEUX ET PERSPECTIVES -

The Morocco has made considerable efforts in order to develop investments in R&amp;D, from public, private sources or through international cooperation. However, the analysis of the funding policy for Research and Innovation in Morocco teaches us that, in addition to the weak presence of the private sector in this area, public policy is exposed to immense constraints, such as the low budget. allocated, the incompatibility of public proceduresÃ¢Â€Â¦ All the more so, the discontinuity and opacity of almost all the funds and programs have prevented any attempt to develop research and innovation in Morocco. These constraints, both economic, institutional and political, lead to recognize the imminent role that large Moroccan companies could play, in terms of financing research and innovation, However, the use of other alternative modes of financing, such capital investment, Business Angels and Crowdfunding constitute a promising choice, faced with the financing problem faced by startups and innovative project leaders in Morocco.
Population Size Management in a Cuckoo Search Algorithm Solving Combinatorial Problems

As is well known in the scientific community, optimization problems are becoming increasingly common, complex, and difficult to solve. The use of metaheuristics to solve these problems is gaining momentum thanks to their great adaptability. Because of this, there is a need to generate robust metaheuristics with a good balance of exploration and exploitation for different optimization problems. Our proposal seeks to improve the exploration and exploitation balance by incorporating a dynamic variation of the population. For this purpose, we implement the Cuckoo Search metaheuristic in its two versions, with and without dynamic population, to solve 3 classical optimization problems. Preliminary results are very good in terms of performance but indicate that it is not enough to vary the population dynamically, but it is necessary to add additional perturbation operators to force changes in the metaheuristic behavior.
Intelligent Systems

Even though there had been recent advances in the field of machine learning, the fast and ever-growing security concerns of the world need to be fulfilled by a more specific technology. We know that machine learning is a subfield of artificial intelligence, and it aims to achieve knowledge from data. The specific technology that we need is fulfilled by deep learning — one of the fastest emerging subfields of machine learning. Deep learning is the finest method of machine learning to achieve more efficient and accurate models. Deep learning focuses on representational learning called feature learning. Feature learning includes feature selection and feature extraction. In this chapter, we will be learning how deep learning technology — its algorithms and techniques — is used in areas like face detection, face recognition, handwritten digit recognition, and a lot more. Many libraries have executed deep learning tasks and achieved better efficiency. A system called FaceNet has been introduced in this chapter to understand why computer vision algorithms tend to use deep learning. One-shot learning is one of the favorite object categorization problems in the field of computer vision. FaceNet was introduced by Google researchers in 2015. It transforms images into 128D Euclidean space. Effective clustering of faces can be done by the embedding by the FaceNet model. Triple loss plays a significant role by adjusting the distances between an anchor and a negative &amp; the anchor and a positive based on a different and same identity, respectively. The use of feature vectors is explained as well. In this chapter, we will see how models built using the latest technologies can make machines intelligent enough to provide security.
Online Learning Platform for Application-Inspired Cloud and DevOps Curriculum

Cloud-hosted services are being increasingly used in hosting business applications due to cost effectiveness, scalability, and ease of deployment. To facilitate rapid development, change and release process of cloud-hosted applications, the area of Development and Operations (DevOps) is fast evolving. It is necessary to train the future generation of application development professionals such that they are knowledgeable in the continuous integration and continuous delivery automation. In this paper, we present the design and development of our “Mizzou Cloud DevOps platform”, an online platform to learn cutting-edge Cloud and DevOps tools/technologies using open/public cloud infrastructures for wide adoption amongst instructors/students. Our learning platform features scalability, flexibility, and extend ability in providing Cloud and DevOps concepts knowledge and hands-on skills. We detail our “application-inspired learning” methodology that is based on integration of real-world application use cases in four learning modules that include laboratory exercises and self-study activities using realistic cloud/HPC-based application testbeds. We describe the learning modules that allow students to gain skills in using latest technologies (e.g., containerization, cluster and edge computing, data pipeline automation) to implement relevant security, monitoring, and adaptation mechanisms. Lastly, we evaluate our platform via a knowledge growth study survey with instructors and students.
A formalization of one of the main claims of “The FAIR Guiding Principles for scientific data management and stewardship” by Wilkinson et al. 20161

Wilkinson et al. claimed in previous work that Adherence of a dataset to the FAIR Guiding Principles enables its automated discovery. We present here a formalization of that claim, stating that all things of class “adherence to the FAIR Guiding principles” that are in the context of a thing of class “data set” can generally have a relation of type “enables” to a thing of class “automated discovery” in the same context.
Dynamic Context in Graph Neural Networks for Item Recommendation

Graph neural networks allow to build recommendation systems which can straightforwardly take into account relational knowledge concerning multiple types of interactions, such as user-item relationships, but also interactions between users and within items. Graph-based approaches in the literature consider such interactions to be static, independent of the surroundings. In this paper, we put forward a novel approach to graph-based item recommendation built on the foundational idea that relational knowledge is characterized by a dynamic nature of the user and its surroundings. We claim that being able to capture such dynamic knowledge allows to build richer contexts upon which more precise recommendations can be built, e.g., taking into account current location, weather conditions, and user mood. The paper provides recipes to build and integrate dynamic user and item contexts in existing item recommendation tasks. We also introduce a novel Dynamic Context-aware Graph Neural Network (DCGNN) that can effectively leverage the knowledge of surroundings to learn the context-aware recommendation behaviour of users. The empirical analysis shows how our model outperforms static state-of-the-art approaches on four movie and travel recommendation benchmarks.
An Anonymous Communication System Based on Software Defined Architecture

The existing low-latency anonymous communication networks represented by Tor and I2P networks are mainly composed of voluntary nodes all over the world, and these nodes use onion routing or garlic routing to implement data hop-by-hop transmission. Due to the high autonomy and randomness of voluntary nodes, the reliability, credibility and availability of the entire anonymous network cannot meet specific QoS requirements. For this reason, based on the advantages of P2P network, this paper proposes an anonymous communication system based on software-defined architecture. The system uses file exchange instead of message exchange, realizes asynchronous communication, realizes the anonymity of transmission path, and introduces The control center performs unified programming on the message forwarding path, which has higher flexibility and reliability. The experimental results show that the entire process is encrypted and different messages cannot be correlated, which can achieve the effect of anti-tracing.
A functional quantum communication network using time-bin entanglement

The network connects multiple users separated by 60 kilometers and allows for simultaneous communication.
Simulation Results

In this chapter, we present results obtained of the String Theory AlgorithmString Theory Algorithm with the different study cases that we are presented in the problem definition section. In addition, we show the statistical tests of the study cases in order to prove the performance of the String Theory AlgorithmString Theory Algorithm with the hypothesis test.
Peringkas Otomatis Teks Berbahasa Arab Menggunakan Algoritma TextRank

Increasingly, the amount of data in the form of text documents scattered on the internet is getting bigger. It took a very long time to get the information from each of these documents. For this reason, several researchers developed the Automatic Text Summarizer to summarize text automatically, so that the time needed to get important information from the entire document can be faster. Research that focuses on automatic summarization of Arabic texts is very rare. In fact, there are more than 300 million Arabic speakers in the world and Arabic is the official language at the United Nations. Therefore, this study develops a model that can perform text summarization automatically using the TextRank algorithm. The test results using Q&amp;A Evaluation show very good results with details of the suitability of the summary results with the original text by 90%, the suitability of the summary results with Arabic grammar is 91.43%, the suitability of the summary results is 90%, the ease of understanding the summary results is 90%. and the useful aspects of the model developed were 91.43%.
Title: The Impact of Food Self-Sufficiency on National Economy in West Africa: Case of the Republic of Guinea

This study examines in the impact of food selficiency on national economy in West Africa particular case Guinea, the major problems of populations needs is food selficiency in Africa. However ; to achieve the self-sufficiency the authorities encourage its production to provide income for Producer, for domestic consumption and for a net exporting country. Local food production remains highly competitive with imported food. In addition, food insecurity across the country is a major development issue that threatens health, productivity and often the survival of the population. This study helps overcome developmental problems due to food selficiency, therefore, the main objective of this study is to analyze the impact of food production in the country and to examine more closely the relationship between food production and national economy on the domestic market. The study used a linear logarithmic model with the exchange rate output as a dependent variable and the food import, inflation rate, umemployment rate, interest rate and population growth. The current results found that imported food is positive sign, supporting the argument that imports products as viable income-generating activity. The self-sufficiency rate is 94%, with strong imports from imports countries, any exports. However, in order to control an national economic income and till increase agriculture production, the government should be able to purchase the food crops production from populations employment to the farmers and then sell them to projects in place for reduce food importation between international, regional and national domestic production along the markets. The development of the national economy Sectors and reduction of poverty and hunger, in particulary growing selficiency of food Security in Guinea.
Corpora in language testing: developments, challenges and opportunities

This chapter presents an overview of applications of corpus linguistics to language testing and assessment. Considerations of test development and validation are discussed, followed by an historical overview of how corpora have been used in language testing over the past several decades. In particular, the availability of large learner and reference corpora, along with more natural language processing tools, have allowed for important innovations in testing such as automated scoring and feedback engines. Examples of how corpus data can be useful in test development and validation are provided. Finally, several caveats and future directions are provided.
Information Technology: A Study of its Concept and Importance in Educational Institutions

The study of the subject of information technology is very important, especially at the present time, and in all fields, especially educational institutions, because of its great impact on its progress and its economic, scientific and social superiority. The research addressed the topic of the concept of information technology and its objectives, and the most important reasons for its use, investment capabilities and importance. The research indicated the most important advantages and functions of information technology, and its optimal strategic use. As well as discussing the topic of information technology infrastructure and capacity building. The research discussed the components of information technology in most fields, especially in educational institutions, and its most prominent characteristics. The research sheds light on the benefits of using information technology in education, the most important obstacles, and the most prominent advantages of using information technology for a university professor. The research addressed the issue of the most important obstacles to the use of information technology in education and the negative effects resulting from the excessive use of information technology.
Load Balancing Based on Estimated Finish Time of Services

Cloud computing is ace of the widely used paradigm in the arena of Computer Science. Using Cloud computing, different Infrastructure/Software/platform services are delivered to different groups of people belonging to various organizations through the Internet. Users can access services and applications without installing them on any computer or laptop connected to the Internet. It involves saving and retrieving the data from the Cloud but not from resident storage. Load balancing is the area in Cloud computing that helps to balance the load between different virtual machines (VMs). Balancing is required to equally divide data among all machines, resulting in improved imitation results and optimal usage of different resources available. Imitation will try to improve performance with the help of the proposed methodology. This chapter projected a load balancing procedure that tries to advance the system’s routine and is based on the estimated finish of service time. The imitation results show that our projected technique will improve the system’s routine by improving its waiting time, response time and processing time.
On the Design of Solar Energy Tracker System

Solar energy is a very important means of renewable energy resource. With solar tracking, it will become possible to generate more energy since the solar panel can maintain a perpendicular profile to the rays of the sun. Even though the initial cost of setting up the tracking system is considerably high, there are cheaper options that have been proposed over time. This paper discusses the design and construction of a prototype for solar tracking system that has a single axis of freedom. Light dependent resistors (LDRs) are used for sunlight detection. The control circuit is based on an ATMega328P microcontroller. It was programmed to detect sunlight via the LDRs before actuating the servo to position the solar panel. The solar panel is positioned where it is able to receive maximum light. As compared to other motors, the servo motors are able to maintain their torque at high speed. They are also more efficient with efficiencies in the range of 80–90 %. Servos can supply roughly twice their rated torque for short periods. They are also quiet and do not vibrate or suffer resonance issues. Performance and characteristics of solar panels are analyzed experimentally
State Component of the National Cooperative Geologic Mapping Program (DOI)

Federal Grants & ContractsVolume 45, Issue 23 p. 5-5 Grants alerts State Component of the National Cooperative Geologic Mapping Program (DOI) First published: 01 November 2021 https://doi.org/10.1002/fgc.32035Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume45, Issue234 November 2021Pages 5-5 RelatedInformation
Getting Started

Good day, dear readers! Welcome to Chapter 1 of my book, which is about getting started in Creating Game Environment in Blender 3D.
Issues of Assessing the Sustainability of the Educational Ecosystems Potential

The purpose of this work is to develop tools for studying educational ecosystems in terms of assessing their potential. The authors focused on the fact that, like any complex socio-economic system that has the properties of self-regulation and self-organization, the educational ecosystem strives for sustainable development by forming the stability of its potential, consisting of a set of private potentials associated with the directions of the functioning of the educational ecosystem and combined to achieve development goals. The authors chose the research potential as the object of the study and focused their attention on 6 regions of the Russian Federation, each of which was represented by a list of universities that were monitored for the effectiveness of the activities of educational organizations of higher education for the period from 2014 to 2020. To study the quantitative aspect of stability, the theory of cenoses was used due to the universality and interdisciplinarity of its provisions. The authors see that the outlined opportunities in assessing the sustainability of the potential of educational ecosystems have prospects for discussion and further development on the way to building an instrumental research base for creating a systematic understanding of the state and capabilities of educational ecosystems.
Keynote Speech 1: An Overview of How Disruptive Technologies will Transform our Lives!

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. There is no doubt that disruptive technologies such as, Artificial intelligence, virtual/ augmented reality VR/AR), internet of things, blockchain technology, and e-commerce are significantly influencing our future. These technologies will affect the normal operation of industry and displaces a well-established product or technology, creating a new market or industry globally. For example, artificial intelligence continues to transform the world we live in. AI is becoming responsible for everything from medical breakthroughs in cancer research to cutting-edge climate change research. It has the ability to harness massive amounts of data and use their learned intelligence to make optimal decisions and discoveries in fractions of the time that it would take humans. The transformative impact of these disruptive technologies on our society will have far-reaching economic, legal, political and regulatory implications that we need to be preparing for! The Keynote will discuss opportunities and challenges of the application of disruptive technologies in Healthcare, automation, industry, Banking, transportation, cities, education, media, cybersecurity and customer service.