Reviewerly/exHarmony huggingface dataset:
Source Parameter Sensitivity of Earthquake Simulations assisted by Machine Learning&amp;#160;

&amp;lt;p&amp;gt;After large magnitude earthquakes have been recorded, a crucial task for hazard assessment is to quickly estimate Ground Shaking (GS) intensities at the affected region. Urgent physics-based earthquake simulations using High-Performance Computing (HPC) facilities may allow fast GS intensity analyses but are very sensitive to source parameter values. When using fast estimates of source parameters such as magnitude, location, fault dimensions, and/or Centroid Moment Tensor (CMT), simulations are prone to errors in their computed GS. Although the approaches to estimate earthquake location and magnitude are consolidated, depth location estimates are largely uncertain. Moreover, automatic CMT solutions are not always provided by seismological agencies, or such solutions are available at later times after waveform inversions allow the determination of moment tensor components. The uncertainty on these parameters, especially a few minutes after the earthquake has been registered, strongly affects GS maps resulting from simulations.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this work, we present a workflow prototype to produce an uncertainty quantification method as a function of the source parameters. The core of this workflow is based on Machine Learning (ML) techniques. As a study case, we consider a domain of 110x80 km centered in 63.9&amp;amp;#186;N-20.6&amp;amp;#186;W in Southern Iceland, where the 17 best-mapped faults have hosted the historical events of the largest magnitude. We generate synthetic GS intensity maps using the AWP-ODC finite-difference code for earthquake simulation and a one-dimensional velocity model, with 40 recording surface stations. By varying a few source parameters (e.g. event magnitude, CMT, and hypocenter location), we finally model tens of thousands of hypothetical earthquakes. Our ML analog will then be able to relate GS intensity maps to source parameters, thus simplifying sensitivity studies.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Additionally, the results of this workflow prototype will allow us to obtain ML-based intensity maps a few seconds after an earthquake occurs exploiting the predictive power of ML techniques. We will evaluate the accuracy of these maps as standalone complements to GMPEs and simulations.&amp;lt;/p&amp;gt;
Comparación de funciones kernel para la predicción de la oferta energética fotovoltaica

Recently, at the fields of climate change and energy demand haveturned their attention to the study and discovery of patterns in renewable energies,such as the photovoltaic-type. Such patterns can be obtained by extrapolatingradiation based on the electromagnetic spectrum bands captured by NASA’sLandsat and MODIS satellites, where artificial neural network (ANN) and supportvector machine (SVM) algorithms have produced the best models. Nonetheless, the acquisition of training data from those sources is expensive, as well as it lacksthe exploration of kernel functions for this application. Therefore, in this study,adjustments were made in the above aspects, mainly through: coupling of newkernels to ANN and SVM in the scikit-learn library, contributing to the reuse androbustness of these algorithms; and implementing an experimental framework totune hyper-parameters, thus generating results comparable to those reported in thestate of the art.
DEVELOPMENT OF LEARNING MANAGEMENT SYSTEM IN VOCATIONAL SCHOOL OF YAMACO NEGERI KATON BASED ON ENTERPRISE ARCHITECTURE PLANNING AND COMPUTER SUPPORTED COLLABORATIVE LEARNING

The development of information systems and technology requires planning to complement the direction of high the development of information systems to complement the strategic direction and management of high schools and above to manage effective and efficient teaching and learning process needs to adopt the concept of electronic learning. In managing electronic learning, a Learning Management System is needed that is able to manage learning content that is more updated and makes learning easier. This Learning Management System (LMS) uses a Computer-Supported Collaborative Learning approach. The design of this LMS uses the Enterprise Architecture Planning (EAP) method as a strategic planning approach to defining data architecture, applications, and technology in the use of information to support business processes then architectural design to identify needs and create architectural schemes and make plans to implement them. The use of computer-supported collaborative learning (CSCL) is a learning model that brings the benefits of collaborative and cooperative learning models for learner actors that are localized with a computer network. The concept of CSLS learning does provide a different perspective on the teaching and learning process. The system design uses the RUP methodology. The methodology has four phases, namely Inception, Elaboration, Construction, and Transition. However, not all phases were carried out in this research. Only two phases were carried out in this study, namely Inception and Elaboration
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers

Most current classifiers are vulnerable to adversarial examples, small input perturbations that change the classification output. Many existing attack algorithms cover various settings, from white-box to black-box classifiers, but typically assume that the answers are deterministic and often fail when they are not. We therefore propose a new adversarial decision-based attack specifically designed for classifiers with probabilistic outputs. It is based on the HopSkipJump attack by Chen et al. (2019, arXiv:1904.02144v5 ), a strong and query efficient decision-based attack originally designed for deterministic classifiers. Our P(robabilisticH)opSkipJump attack adapts its amount of queries to maintain HopSkipJump's original output quality across various noise levels, while converging to its query efficiency as the noise level decreases. We test our attack on various noise models, including state-of-the-art off-the-shelf randomized defenses, and show that they offer almost no extra robustness to decision-based attacks. Code is available at this https URL .
The Uses of Fan-Aquadrones in Case of Floods or Tsunami Rescue and Relief Operations: MAR21 Prototype and MAR27 Prototype

This research presents two new fan-aquadrones in case of floods or Tsunami rescue and relief operations anywhere and anytime. We have two models of fan-aquadrones such as the MAR21 prototype and MAR27 prototype. Initially, the MAR21prototype has a large structure to facilitate the carrying of food, medicines, and water to areas were affected severally by any flood or Tsunami. At the same time, the MAR21 prototype can handle also to do it a deep cleaning service of any area was affected by a flood or Tsunami subsequently. Additionally, the MAR21 prototype and MAR27 prototype offer to government and humanitarian agencies an alternative emergency maritime transportation system in case of floods or Tsunami disasters. The MAR21 prototype and MAR27 prototype construction is based on a high reception radio control system, a modern GPS system, high reception antenna and radar systems, HD cameras (live), powerful batteries, high resistance ESC systems, and powerful electric motors to support large operation in case of a flood or Tsunami rescue and relief operations anytime. The design of the structure of the MAR21 prototype and MAR27 prototype have special characteristics that can be adapted to any weather condition, temperature levels, and levels of water respectively. In fact, the cost of production of MAR21 prototype and MAR27 prototype is relatively cheap and easy for his construction according to this research. On the other hand, the MAR27 prototype is a smaller fan-aquadrone that can help to monitoring and scanning the pre and post flood or Tsunami disaster by using advanced GPS system, HD cameras with high resolution to observe the levels of damage in real time. Finally, the MAR21 prototype and MAR27 prototype are complementary emergency maritime transportation systems that can help in any case of floods or Tsunami rescue and relief operations rapidly and efficiently.
Genetic Algorithm-Based Image Watermarking Using Multiple Location

The process of image watermarking is used to digitally mark the image before storing or transmitting to other agents. For preservation of the original content, sometimes the log data of the image or document being used is also required. This paper mainly aims at the development of an algorithm which embeds a watermark to an image which can be used for its copyright preservation issues or patent issues. The paper aims at development of an algorithm which remains unaltered in most adverse situations. An image is made of pixels and anything which is being embedded into an image will invariably be made of pixels. Any bulk embedding process which aims at a particular section of an image can be easily targeted or altered by several filtering techniques. But in this paper, the concept that the fundamental entity of any image is pixel is being used. This helps us to embed the required image with much more secured process. Moreover, the process of locating the sections for embedding is also determined by the machine itself which makes it much safer reason being if allocation of the section would have been done by use of any algorithm, there are chances of decoding that algorithm, which would eventually reveal the position of the watermark. But since this entire process is automated by machine itself, the probability of any such decoding becomes nil. Platform used for this is MATLAB. Wavelet transform is used for development of the program because of its higher efficiency in case of digital domain.
Python Loves Numbers

In the previous chapter, we learned how to get started with Python. We looked at downloading the latest version of Python for Windows, Mac, and Linux and then looked at working with IDLE to create our very first Python program.
An Edge Detection Algorithm Based on Fuzzy Adaptive Median Filtering and Bilateral Filtering

As the basic feature of image, edge can be used to identify target, extract feature and provide valuable feature parameters. In the process of image acquisition, transmission and processing, it is inevitable that images will be affected by different degrees of noise. Gaussian noise and salt and pepper noise, as common noises, are often the causes of image blurring and deformation. As the traditional Canny algorithm does not have the disadvantage of removing the salt and pepper noise, this paper adopts the hybrid de-noising method of fuzzy adaptive median filtering and bilateral filtering to remove the salt and pepper noise while achieving the effect of maintaining the edge and smoothing the noise reduction. At the same time, 5 × 5sobel operator and Oust adaptive threshold are selected to better obtain edge information and improve edge connection. The experiment shows that the improved edge detection algorithm is better than the traditional Canny algorithm when adding high-density salt and pepper noise. It can filter out the sundries and identify the subject target.
A corpus-driven analysis of adjective/noun collocations in travel journalism in English, Italian and Polish

This paper describes the compilation and subsequent analysis of a comparable corpus of travel journalism in three languages (English, Italian, and Polish). By means of a corpus driven methodology, our study focuses on adjective/noun pairings, extracting a list of statistically significant collocations for each language and observing differences and similarities with those of the other two. Social Networks Analysis tolos are used to highlight the most productive collocates. Finally, collocations concerning selected themes are analysed across the three corpora, highlighting how this approach may provide valuable input to the production of reference materials for translators.
Creating a Simple Container Framework

Since we have covered the basics of what constitutes a container, it is time to look at how to write your own simple container. By end of this chapter, you will have created your own simple container using namespace isolation.
Perceptual Model based Surface Tessellation for VR Foveated Rendering

With the rapid development of VR head mounted display, VR scenes need to be presented at higher resolutions and higher frame rates. Foveated rendering is an important technique to balance computing resource demand and user satisfaction. In this paper, we propose a perceptual model based foveated rendering. By culling the imperceptible region and adaptively adjusting the tessellation levels based on visual sensitivity, we improve the rendering performance in real-time rendering frameworks.
An Instruction Method for the Standard Assignment in NOKAIDAI Considering Motivation

This paper proposes an instruction method based on Project-Based Learning for the standard assignment subject in NOKAIDAI1) considering intrinsic motivation. In this subject, students learn embedded systems by designing and constructing their original embedded systems as group works. Our instruction method including the curriculum and teaching materials for this subject is developed based on the prior analysis from the results of questionnaires and examinations in Tokai NOKAIDAI. This paper also gives the effectiveness of our developed instruction method by the class practice in Tokai NOKAIDAI.
Universal Rate-Distortion-Perception Representations for Lossy Compression

In the context of lossy compression, Blau & Michaeli (2019) adopt a mathematical notion of perceptual quality and define the information rate-distortion-perception function, generalizing the classical rate-distortion tradeoff. We consider the notion of universal representations in which one may fix an encoder and vary the decoder to achieve any point within a collection of distortion and perception constraints. We prove that the corresponding information-theoretic universal rate-distortion-perception function is operationally achievable in an approximate sense. Under MSE distortion, we show that the entire distortion-perception tradeoff of a Gaussian source can be achieved by a single encoder of the same rate asymptotically. We then characterize the achievable distortion-perception region for a fixed representation in the case of arbitrary distributions, identify conditions under which the aforementioned results continue to hold approximately, and study the case when the rate is not fixed in advance. This motivates the study of practical constructions that are approximately universal across the RDP tradeoff, thereby alleviating the need to design a new encoder for each objective. We provide experimental results on MNIST and SVHN suggesting that on image compression tasks, the operational tradeoffs achieved by machine learning models with a fixed encoder suffer only a small penalty when compared to their variable encoder counterparts.
МИРОВОЕ АКАДЕМИЧЕСКОЕ МНЕНИЕ: НОВЫЕ ПРОБЛЕМЫ ВЫСШЕГО ОБРАЗОВАНИЯ

Understanding that education and research are key factors in improving the quality of life and stimulating economic and social development coexist with the expectation of new challenges in the development of higher education, the list of which in part varies from country to country, but basically has a common set of problems - financial, recruiting, technological, but primarily related to quality standards, compliance with the requirements of new conditions of modern life. Universities would very much like to preserve their monopoly on educational activities, allowing them to survive and develop in difficult economic, political, and demographic circumstances, but not always and not everyone succeeds. This is evidenced by the competition between various universities, spilling beyond the borders of the state borders into the world academic space. Many experts in the field of education and university leaders believe that in the future students will appreciate personal participation in universities even more than they do now, and that university science will be developed primarily by people and not by artificial intelligence. Another trend in the development of higher education is the growing popularity of professional courses and a decrease in interest in MOOCs.
Documentos produzidos pela pesquisa: uma análise dos instrumentos de gestão arquivística das Universidades Estaduais de São Paulo

In universities, research laboratories develop activities related and produce document that, of its usefulness for research that beyond, can be a source of information in other researches, as well as constituting an important element of the scientific memory developed in the laboratory and at the university. Archives' concern with the management, organization, preservation and access of the archival document results in the classification code and the retention and disposition schedule, as these instruments provide an overview of the complete documents by an organization and the actions that produced them, being a basis for records management This work aims to investigate how the instruments of records management, contemplating the investigation by scientific activities in research laboratories at the university. The work is of a qualitative nature and the research is bibliographic and documentary. An analysis of the classification code and the retention and disposition schedule of UNESP and USP was carried out. The results show that the archival instruments of the analyzed institutions address these documents to a greater or lesser extent. It is also inferred the need for universities to see these documents as an important element of their documentary heritage and that the chosen ones contemplated in a broader perspective, in a policy of archival documents.
INCLUSIVE EDUCATION OF FUTURE TEACHERS ISSUES OF PSYCHOLOGICAL READINESS

In this article, the authors note that the readiness of teachers to work with children with disabilities is an important condition for the successful implementation of inclusive education. The article analyzes the theoretical concepts of the essence and structural components of teachers 'readiness for professional activity from the positions of various scientific approaches, and also considers the specifics of the problem of teachers' psychological readiness to work in conditions of educational inclusion. The theoretical analysis of scientific papers allow us to identify the main aspects of the problem of readiness for professional activity in psychology, to determine the specifics and structure of the psychological readiness of teachers to work in conditions of inclusion, to identifyАбай атындағы main problems of its formation in the course of professional training at the present stage. As a result, the authors came to the conclusion that the psychological and pedagogical training of future teachers for inclusive education is a necessary prerequisite for the success of an effective professional activity of a person in the modern world.
Automatic Solar Based Irrigation System with pH Sensing Technique

The key purpose of this dissertation is to deliver statistics about programmed irrigation structure to the plants which helps in retaining money and water. The complete system is supervised using ATMEGA 328 microcontroller which gives the disturb signal to the motorize mechanism. Temperature & Humidity detector are linked to inner harbours of micro-controller through comparator each time there is a variation in Temperature & Humidity, these sensors senses the variation in Temperature & Humidity and provides a disturb signal to the micro-controller & thus the motorize mechanism is activated, along with this buzzer is used to indicate thatpump is on.
A Gesture based Remote Control for Home Appliances

The manuscript aims to present a project enabling one to control electronic devices though hand gestures and convert one's hand into a wand. All the remote-controlled devices like your television sets, home theatre systems, air conditioners, cars, fans, lights, and other everyday electrical appliances can be controlled just with a flick of the hand. For this, the project uses a smart combination of Inertial Measurement Units (IMUs) and Machine Learning (ML) to identify the control target and command action by intuitive gestures. The control commands are forwarded through home wi-Fi. The product is completely customizable and hence one can easily configure that how one's hand gesture will control a device. Also, one can train it to understand custom hand gestures. The project enables user to have a consistent interaction experience everywhere. This project can be considered as a boon to elderly population who often have a tough time handling several remotes with several buttons on each remote. Hence, the project leads to a seamless experience for them while adapting to the technological advancements unknowingly.
Comparison of Watershed and Local Center of Mass Techniques in Segmentation of Breast Mammogram

Tumor interpretation on cancer image can lead to early detection of cancer with the prevalence of breast cancer being the second leading cause for death in women. Segmentation of mammographic images is a challenging space because of the complexity in extracting data without causing any source of artefacts on the image. Diagnosis becomes difficult when data extraction is challenging. In order to cater effective diagnosis and effective treatment, segmentation is a vital process. This paper discusses about two segmentation method, Watershed and Local Center of Masses. Comparison between these two algorithms based on the amount of data extraction for six different categories of mammographic images, the apt segmentation method for data extraction is found out. Watershed provides an average dice score of 0.53, and occupies 665 KB memory space and avails 5 seconds running time whereas LCM avails on an average of 0.59 dice score, 250 KB memory space and 1008 seconds computing time. This can pave way for selection of effective diagnosis that can result in early diagnosis in turn leading in faster cure.
Toward a knowledge-based economy: evidence from the MENA region

This study aims to investigate the relationship between education, innovation, and technology, which are the main pillars of a knowledge-based economy, and the economic performance in the MENA region. The study uses a vector autoregressive (VAR) approach to examine the short-run dynamics between the variables spanning the period 2007-2017. The results suggest that an improvement in education, innovation, and technology increases economic development in MENA countries. Thus, policymakers in these developing countries should shift their economies toward the knowledge-based economy by enhancing the quality of education and by increasing their expenditures on research and development (R&D) to improve innovation and competitiveness. Moreover, policymakers should facilitate the transfer and adoption of new technologies within different industries and businesses.