Reviewerly/exHarmony huggingface dataset:
Automatic swarm analyzer based on matched filtering algorithms: El Hierro 2011 and Torreperogil 2012-2013

&amp;lt;p&amp;gt;Dense seismic swarms usually show a high number of earthquakes per hour, the events may overlap and in most of the cases seismic records are characterized by a low signal-to-noise ratio. As a result, the manual characterization performed by seismic and volcanic observatories can become very complicated or impossible to perform. In order to solve this problem, we have developed a set of algorithms whose purpose is to detect the events, pick their phases and give a location (in an absolute and relative way) of the earthquakes associated with a known swarm.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;These algorithms have been tested in two different tectonic environments: the volcano-tectonic pre-eruptive swarm of El Hierro, Spain (2011) and the tectonic seismic series of Torreperogil, Spain (2012-2013).&amp;amp;#160; Both crises mainly differ in the distances from the seismic stations to the hypocentres of the swarms: in the case of El Hierro,&amp;amp;#160; data corresponds to local epicentral distances (5-20Km) while the case of Torreperogil seismic series deals with regional distances (10-180km). Otherwise, both series present a similar evolution of the seismic network: as the number of earthquakes increased, more stations were deployed and the network became denser.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To analyze these series, we have used two sets of well relocated earthquakes of both swarms as masters, considering manually analyzed events by National Geographic Institute (IGN) with magnitude mbLg greater than 1.5. After the application of the new algorithms, we have increased the number of earthquakes of&amp;amp;#160; the IGN seismic catalog by a factor of 4.5 for Torreperogil and 2.9 for El Hierro. Similarly, the number of picked phases for these two series has been increased by a factor of 4.5 and 3.5, respectively.&amp;lt;/p&amp;gt;
Lasige-BioTM at ProfNER: BiLSTM-CRF and contextual Spanish embeddings for Named Entity Recognition and Tweet Binary Classification

The paper describes the participation of the Lasige-BioTM team at sub-tracks A and B of ProfNER, which was based on: i) a BiLSTM-CRF model that leverages contextual and classical word embeddings to recognize and classify the mentions, and ii) on a rule-based module to classify tweets.In the Evaluation phase, our model achieved a F1-score of 0.917 (0,031 more than the median) in sub-track A and a F1score of 0.727 (0,034 less than the median) in sub-track B.
Optimized Multirate Wideband Speech Steganography for Improving Embedding Capacity Compared with Neighbor-Index-Division Codebook Division Algorithm

Aim: The main motive of this study is to perform Adaptive Multi Rate Wideband (AMR-WB) Speech Steganography in network security to produce the stego speech with less loss of quality while increasing embedding capacities. Materials and Methods: TIMIT Acoustic-Phonetic Continuous Speech Corpus dataset consists of about 16000 speech samples out of which 1000 samples are taken and 80% pretest power for analyzing the speech steganography. AMR-WB Speech steganography is performed by Diameter Neighbor codebook partition algorithm (Group 1) and Neighbor Index Division codebook division algorithm (Group 2). Results: The AMR-WB speech steganography using DN codebook partition obtained average quality rate of 2.8893 and NID codebook division algorithm obtained average quality rate of 2.4196 in the range of 300bps embedding capacity. Conclusion: The outcomes of this study proves that the decrease in quality in NID is twice more than the DN based steganography while increasing the embedding capacities.
Exploring Android Concepts: Layouts and More

Understanding the various UI widgets available in Android definitely empowers you to make various design choices about how specific functions and behaviors in your application should present themselves, but there is more to activity design than picking a radio button or TextView. Layouts are Android's declarative mechanism that arms you with control over the complete on-screen landscape for your application.
Methods of developing "Creative Thinking" skills in teaching physics

The article discusses the psychological state of adolescents and opportunities for developing "creative thinking" skills in them. For indirect knowledge that is important for the natural sciences, including physics:-The role of idealization, modelling and scientific experimentation is great. These experiments deal with physical quantities. The values of the physical quantities are determined in units. The article presents an intellectual map of the International System of Units.
LAYANAN INFORMASI PEMBAYARAN BIAYA KULIAH BERBASIS SMS GATEWAY

SMS (Short Message Service) Gateway is an SMS-based system that can be developed in various fields and utilizes a web-based programming language. At STMIK XYZ, the delivery of information about the schedule for tuition payments is still by placing announcements / banners in the campus environment and sending letters to parents / guardians. These methods are not optimal because of the limitations of delivery to students and sometimes students do not pay attention to them. This is evident from the many students who are late in making tuition payments. Therefore, a system / application is needed that can provide services that can be accessed by students and parents / guardians to find out the status of their son / daughter's college payment.&#x0D; The design and manufacture of the SMS gateway-based tuition payment service system uses the Waterfall methodology, which is a software development method that begins with analyzing company needs, designing, building applications, to conducting trials.&#x0D; This tuition payment service system sends SMS to students and parents about the schedule of tuition payments and the status of payments that have been made. Information and payment status is sent to the cellphone number of each student and parent / guardian and provides warning information 7 (seven) days before the payment deadline. This application can also generate various types of reports regarding the status of student tuition payments to management. With this application / system, it is hoped that it can assist the management in accelerating the delivery of information about the schedule and status of student tuition payments.
Abnormal Human Action Detection Based on GAN

One of the important roles of a camera surveillance system is to detect abnormal human actions or events.In this study, we propose a method of abnormal human actions/events detection method using Generative Adversarial Nets (GAN).In anomaly action detection, the main problem is that the image data of abnormal human actions is more difficult to obtain than normal human actions.To solve this difficulty, we use only normal human action data in the employed training network and those actions not recognized as normal are judged as abnormal.Experimental results show effectiveness of the proposed method.
Quantifying the potential for mineral carbonation of processed kimberlite with the Rietveld-PONKCS method

Quantitative phase analysis (QPA) using the Rietveld method and X-ray diffraction (XRD) patterns is useful for predicting the reactivity of a rock to CO 2 and for quantifying mineral carbonation [1].Kimberlites can be reactive to CO 2 , but they are rich in structurally disordered clay minerals.In this study, the method of Partial Or No Known Crystal Structure (PONKCS) [2] was used to model the peak profiles of smectite(s) and lizardite to account for turbostratic stacking disorder in synthetic and natural samples of processed kimberlite.Here we used weighed mixtures to develop an accurate approach to QPA for kimberlite.Lizardite and montmorillonite PONKCS models were made using XRD patterns collected with a Rigaku Ultima IV, a Bruker D8 Advance and a Bruker D8 Advance Eco.PONKCS models were prepared from 50:50 wt% mixtures of lizardite and Ca-exchanged montmorillonite (SWy-2) with NIST or Baikalox α-Al 2 O 3 .Five synthetic samples of processed kimberlite of typical and known composition were then used to test the results of these PONKCS models for all three XRDs.We also tested the sensitivity of the PONKCS method to changes in instrument geometry.PONKCS models calibrated for one instrument were used in refinements using XRD data collected on a different instrument, or on the same instrument with modified geometry.Our results show that even small changes in instrument parameters can lead to inconsistent and inaccurate QPA results using for our weighed mixtures).However, the results can be highly accurate (4.2-14.1% total bias) using correctly calibrated, instrument specific PONKCS models.Finally, we use this approach to quantify the mineralogy of kimberlites from laboratory-based acid leaching experiments and from a threetonne field trial as part of De Beers' Project CarbonVault.[1]
Effect of Hidden Vector on the Speech of PRVA

This study aimed to propose a novel method for designing a product recommendation virtual agent (PRVA) that can keep users motivated to interact with the agent. In prior papers, many methods of keeping users motivated postulated real-time and multi-modal interactions. The proposed novel method can be used in one-direction interaction. We defined the notion of the “hidden vector,” that is, information that is not mentioned by a PRVA and that the user can suppose spontaneously. We conducted an experiment to verify the hypothesis that PRVAs having a hidden vector are more effective than other PRVAs. As a result, it was shown that PRVAs having a hidden vector were perceived as being more persuasive than other PRVAs and strongly motivated the users to use the PRVAs. From these results, the proposed method was shown to be effective.
Real-Time Masked Face Revealing for Video Conference

Video conferencing is an essential way for contactless conversation, which conveys abundant multimedia signals. Especially under COVID-19, the video conference has been becoming a common way for daily communications. However, for the sake of plague prevention, it usually happens that the people attending the video conference are wearing a mouth mask, leading to inconvenient communication due to incomplete facial information. To tackle this problem, we develop a novel system that reveals the masked faces in real-time, making each participant feel like the others are mask-free. Moreover, we map the audio to 3DMM expression to guide the generation of various mouth shapes utilizing multi-modal information. Extensive experiments validate the revealing effectiveness and better user experience of the system. Furthermore, by applying lightweight networks design, the proposed system can run in real-time.
Analysis of Image Registration Algorithm RANSAC and Its Improved Algorithm

Abstract The RANSAC (random sampling consensus) algorithm is an estimation method that can obtain the optimal model in samples containing a lot of abnormal data. This algorithm uses a small number of points in the data to estimate the model, and then uses the remaining points to check the model. It is now widely used in computer vision image stitching. This algorithm has disadvantages such as slow operation speed and poor sample adaptability. In order to improve the efficiency of image registration, many researchers have made improvements on the basis of the RANSAC principle. This article introduces the principles and shortcomings of RANSAC, and introduces four ways to improve it in view of its shortcomings. The advantages and problems of the improved algorithm are analyzed to provide a basis for the field of image registration.
On the Concatenated Code Constructions for Slotted Multiuser Communication Channel

We consider a vector-disjunctive channel where users transmit some vector of bits of length L. Previously the capacity of this channel was estimated and it was shown that there are some cases when it achieves on non-uniform input distribution. It motivates us to study a question of applying some classes of codes that allows in one hand to reach target input distribution and in another one to add some redundancy to transmitted messages to detect or correct some error patterns that appears during transmission either in the case of user interference or due to channel noise.
Ranking Icelandic volcanoes by threat and prioritizing their monitoring requirements&amp;#160;

&amp;lt;p&amp;gt;How well are our volcanoes monitored? When and why should we review and enhance the monitoring setup for volcano surveillance? These questions are often raised at Volcano Observatories or at those Institutions in charge of monitoring volcanoes and their associated hazards. The Icelandic Meteorological Office (IMO) is responsible for monitoring natural hazards in Iceland, including volcanoes and volcanic eruptions. IMO operates an extended multidisciplinary monitoring network which comprises seismometers, cGPS, gas sensors, MultiGAS and DOASes, hydrological stations, strainmeters and tiltmeters, infrasound networks and webcams, with the aim of detecting in a timely manner potential unrest at any of the 32 active volcanoes in the country. Limited resources and funding opportunities often pose limitations on how extensive (in terms of number of sensors and their variety) a volcano monitoring network can be. Therefore, the Volcano Observatories are often required to decide how to prioritize the monitoring needs and find a balance in sensitivity, reliability, and efficacy of the network. &amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this contribution, we will present the results of the analysis performed at the IMO to rank the Icelandic active volcanoes by their threat and, consequently, to prioritize their monitoring needs. Some criteria (based on eruption frequency, potential hazards, infrastructure exposure and current status) are defined as guidelines and they are used to drive decisions regarding when and how to alter the monitoring setup. The specific case of Hekla volcano is used here to evaluate the validity of such criteria and to perform an analysis of the current capability of issuing a timely warning for one of the most dangerous volcanoes in Iceland.&amp;amp;#160;&amp;lt;/p&amp;gt;
Research on the Development of Artificial Intelligence into VR Practice Teaching

This paper focuses on the increasingly clear integration of artificial intelligence and virtual reality, to study the possible development and changes brought by the integration of AI into VR practice teaching from the aspects of VR practice teaching activities interactivity, scene authenticity, feedback intelligence, etc. This will provide a basis for VR practice teaching to break through environmental constraints and achieve in-depth development in a wider range of fields.
REQUIREMENTS FOR PROFESSIONAL AND PERSONAL QUALITIES OF PRIMARY SCHOOL TEACHERS

The article discusses the requirements for professional and personal qualities of primary school teachers. The rapidly changing modern world simultaneously changes the socio-pedagogical functions of the teacher and the requirements imposed on him. Today, the goal of the school is not only to transfer new knowledge, goals, values and personal meanings, but also to reveal the abilities of a growing person. Traditional views are replaced by a new pedagogical system, in connection with which the requirements of society to the teacher's personality change, which reflects the updated content and structure of his professional activity. An important factor affecting the effectiveness of the teacher's activity is his personal qualities. When considering the qualities of a teacher as a subject of activity, researchers distinguish professional and pedagogical qualities that are very close in abilities and can be individual.
Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization

Bandit and reinforcement learning (RL) problems can often be framed as optimization problems where the goal is to maximize average performance while having access only to stochastic estimates of the true gradient. Traditionally, stochastic optimization theory predicts that learning dynamics are governed by the curvature of the loss function and the noise of the gradient estimates. In this paper we demonstrate that this is not the case for bandit and RL problems. To allow our analysis to be interpreted in light of multi-step MDPs, we focus on techniques derived from stochastic optimization principles (e.g., natural policy gradient and EXP3) and we show that some standard assumptions from optimization theory are violated in these problems. We present theoretical results showing that, at least for bandit problems, curvature and noise are not sufficient to explain the learning dynamics and that seemingly innocuous choices like the baseline can determine whether an algorithm converges. These theoretical findings match our empirical evaluation, which we extend to multi-state MDPs.
Predicting climate model response to changing emissions

&amp;lt;p&amp;gt;In order to make predictions on how the climate would respond to changes in global and regional emissions, we typically run simulations on Global Climate Models (GCMs) with perturbed emissions or concentration fields. These simulations are highly expensive and often require the availability of high-performance computers. Machine Learning (ML) can provide an alternative approach to estimating climate response to various emissions quickly and cheaply.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We will present a Gaussian process emulator capable of predicting the global map of temperature response to different types of emissions (both greenhouse gases and aerosol pollutants), trained on a carefully designed set of simulations from a GCM. This particular work involves making short-term predictions on 5 year timescales but can be linked to an emulator from previous work that predicts on decadal timescales. We can also examine uncertainties associated with predictions to find out where where the method could benefit from increased training data. This is a particularly useful asset when constructing emulators for complex models, such as GCMs, where obtaining training runs is costly.&amp;amp;#160;&amp;lt;/p&amp;gt;
An Organized Study on Data Divulge Elimination and Discernment

Exchange of information is done in every organization. Information can be confidential and non-confidential. There are several channels through which exchange of data is done. During this process of exchange, data gets leaked. Enterprises are facing a lot of issues with data leakage and also towards recognizing the leakers. It is a very important need for the organization to exchange confidential information securely and easily. The main goal is to create the data leakage prevention and detection model which detects when the allocator’s sensitive information has been disclosed by operators and also to identify the leaker that leaked the data. Leakage of confidential information leads to a great loss to the organization. In addition to financial loss, an organization’s reputation is ruined and facing its identity stolen. These losses take a lot of time to recover. In this paper, it will focus on research papers on various techniques, which consists of classification strategies to identify sensitive and non-sensitive data, distribution strategy to monitor data, and encryption technique used.
Novel Algorithm of Solar PV Calculation and Estimation using Data Analysis via Machine Learning

The solar irradiance or force is the yield of light energy from the entire hover of the Sun, assessed at the Earth. In the proposed work, the Solar Radiation Data and Related Parameters Data is accumulated using the National Solar Radiation Database and we have created the data using text records and work up into the rule reports which is used for taken up the analysis work. In this we used the thought for anticipating the solar power using the possibility of the relationship analysis, direct relapse analysis and Principal Component Analysis and takes a gander at the outlines and choose the mix-up calculation in solar force and examining the limits like temperature, relative moisture, solar radiation, and wind speed.
Hair mineralogram analysis for health assessment: Statistical bias from gender and aesthetic treatments

The hair mineralogram is a complementary multielement analysis that provides information to aid in the diagnosis of a patient’s health status; however, aesthetic treatments can affect the analysis results. This research aimed to identify standard patterns among mineralogram results and some variables, such as gender and the use of aesthetical treatments that can point out differences and causes of variation in elemental concentrations in hair. For this purpose, 151 hair samples were obtained from volunteers and analyzed by inductively coupled plasma mass spectrometry (ICP-MS). This work is pilot research, part of a project to encourage girls to the STEM area, called “Girls in Science”, with financial support from the Brazilian Government. Mineralogram results were compared through statistical analysis. The results of natural hair indicate significant differences (p&lt;0.05) between genders in the concentrations of Ca, Mg, Sr, and Mo, being higher in women. This behavior was related to the remodeling of minerals in bones, which is different between men and women. The metal concentration in natural hair from women was also compared among different skin colors and no significant differences were observed. Hair treatment, in contrast, has affected significantly the concentrations of many elements. Concentrations increased in hair submitted to dyeing only or with straightening, when compared to natural hair, especially for Ca, Mg, Sr, Ba, and Ni. These results confirm the recommendation of physicians to let the hair grow free of aesthetic treatments for at least 3 months before performing the mineralogram.
Creative Analysis of Effective Models of College English Listening Teaching Based on Computer Multimedia

With the development of science and technology, multimedia teaching has been widely used in education and teaching activities around the world. Multimedia software has a wide range of applications in English listening teaching with its graphics and text, sound and format functions, and provides many possibilities for modern English listening teaching methods. The four basic skills for learning English include "listening, speaking, reading and writing". Among them, "listening" is dominant. "Listening" is the source of information and the basis for learning any language. Improving listening skills is not only beneficial to "speaking", but developing "reading and writing" skills can also lay the foundation for daily communication. Most English teachers only focus on cultivating the listening ability of high school students, but ignore their own listening skills. Media software does not provide many advantages in English listening classes, but only plays a role in saving the time of writing on the blackboard. According to the current situation of teaching, the innovative application of multimedia software in English high school listening teaching is particularly important. Although there are many college English listening teaching models, they all have corresponding shortcomings. In order to improve college students' English listening performance, this article uses a combination of literature survey methods and controlled experiments to conduct research. Using the method in this article, through the experimental results of the control experiment, it can be known that the students' English listening comprehension has improved by 15%.