Reviewerly/exHarmony huggingface dataset:
Extreme value statistics of interval maximum amplitudes due to aftershocks and its application for early forecast

&amp;lt;p&amp;gt;Waveforms from many aftershocks occurring immediately after a large earthquake tend to overlap in a seismogram, which makes it difficult to pick their P- and S-wave phases. Accordingly, to determine hypocenter and magnitude of the aftershocks becomes difficult and thereby causes deterioration of earthquake catalog. Using such deteriorated catalog may cause misevaluation of ongoing aftershock activity. Since aftershock activity is usually most intense in the early period after a large earthquake, requirement of early aftershock forecast and deterioration of the aftershock catalog are impatient.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Several methods for aftershock forecast, using deteriorated automatic earthquake catalog (Omi et al., 2016, 2019) or continuous seismic envelopes (Lippiello et al., 2016), have been proposed to overcome such a situation. In this study, I propose another method that evaluates excess probability of maximum amplitude (EPMA) due to aftershocks using a continuous seismogram. The proposed method is based on the extreme value statistics, which provides probability distribution of maximum amplitudes within constant time intervals. From the Gutenberg-Richter and the Omori-Utsu laws and a conventional ground motion prediction equation (GMPE), I derived this interval maximum amplitude (IMA) follows the Frechet distribution (or type &amp;amp;#8545; extreme-value distribution). Using the Monte-Carlo based approach, I certified that this distribution is well applicable to IMAs and available for forecasting maximum amplitudes even if many seismograms are overlapped.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Applying the Frechet distribution to the first 3 hour-long seismograms of the 2008 Iwate-Miyagi Nairiku earthquake (M&amp;lt;sub&amp;gt;W&amp;lt;/sub&amp;gt; 6.9), Japan, I computed the EPMAs for 4 days at 4 stations. The maximum amplitudes due to experienced aftershocks proceeded following mostly within the 10 % to 90 % EPMA curves. This performance may be acceptable for a practical use.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Differently from the catalog-based method, the proposed method is almost unaffected by overlap of seismograms even in early lapse times. Since it is based on a single station processing, even seismic &amp;amp;#8220;network&amp;amp;#8221; is not required, and can be easily deployed at locations of poor seismic network coverage. So far, this method is correctly applicable for typical mainshock-aftershock (Omori-Utsu-like) sequence only. However, potentially, it could be extended to multiple sequences including secondary aftershocks and remotely triggered earthquakes.&amp;lt;/p&amp;gt;
‘-잖아’에 의한 인과 표현 고찰

The purpose of this paper is to examine the properties of causality expressed by -canha. With -canha, the speaker assumes that the listener already knows the proposition. This meaning is closely related to the function of expressing reason in discourse. The causality represented by -canha has several properties. First, -canha is included in the implicative causality established by the listener’s inference. Second, -canha depends on the situational context which the speaker and the listener share. Third, -canha can express the content domain, the epistimic domain and the speech-act domain of the causal relationship. The property explains why the speaker chooses -canha when it expresses causality.
블록체인에 대한 사람들의 인식과 블록체인 활용 방법 분석

The purpose of this study is to help students be able to understand the blockchain easily without using blockchain. The result of this study is an app can show the advantages of blockchain and an methods of blockchain visually. The app that we made for these reasons is combined with the originally used books transaction system. This system can maximize the advantages of blockchain. Therefore, the people who use our application can realize the ease of the blockchain and blockchain can be used in many ways by the people’s attention.
CCP Goes Beyond Traditional Archives

Women in Higher EducationVolume 30, Issue 7 p. 12-15 Colored Conventions Project CCP Goes Beyond Traditional Archives Nyasha Junior, Nyasha JuniorSearch for more papers by this author Nyasha Junior, Nyasha JuniorSearch for more papers by this author First published: 24 June 2021 https://doi.org/10.1002/whe.21014Read 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. Volume30, Issue7July 2021Pages 12-15 RelatedInformation
ARTIFICIAL INTELLIGENCE AND MEDICINE: PAST AND FUTURE

The relationship between artificial intelligence and medicine has a long history. Artificial intelligence initially set out to replicate human reasoning starting with explicit “if then else” rules. One of the most interesting results dates back to the 1970s with the MYCIN system based on a set of 600 rules entered by physicians able to recommend antibiotic treatments. This direction, although promising, implied a long input process, a difficult consistency check and was computationally too heavy. These methodologies have continued over the years with episodes of small successes and large failures until it was realized that the way forward was to train artificial systems starting from real examples, through a methodology called machine learning and in particular deep learning. The direction was to start from digital model of the human brain based on artificial neurons, synapses and axons. Early work involves recognizing of cancer cells from histological images hand-annotated by physicians. Artificial neural networks are trained showing the artificial neural networks hundreds of “raw” bit by bit images so that the machine automatically learns how to identify (sometimes with superhuman performance) cancer cells in new, unannotated images. The path has then been laid out, with successful new applications ranging from diagnostics, drug development, effects of treatments predicting, patient classification, DNA analysis, personalized medicine, including robotics for surgery, and the construction of artificial prostheses to support patients with disabilities. In this content, it is increasingly important to manage big data without forgetting issues of privacy and anonymization. Of great importance are also new methodologies able to analyze texts and extract information automatically, thus allowing the integration of information of different nature and type, but also techniques usefull to manage uncertainty and lack of data, a phenomenon very often present in this domain. In this talk we focus on the recent trends and successes of artificial intelligence in the medical field, with practical examples in which artificial intelligence supports physicians in their work, without forgetting current and future challenges and opportunities, at scientific, application, business but also regulatory level, in an increasingly hybrid world where humans and artificial intelligence will increasingly interact to improve the quality of life and well-being of people. Keywords: Bioinformatics; Computational and Systems Biology No conflicts of interests pertinent to the abstract.
THE PERCEPTION OF PRIMARY SCHOOL TEACHERS OF ONLINE LEARNING DURING THE COVID-19 PANDEMIC: A CASE STUDY UPT SPNF SKB ENREKANG, INDONESIA

The online learning system is a solution for the teaching and learning process during the COVID-19 pandemic for all levels of education, including early childhood education (PAUD). The purpose of the study was to obtain an overview of the effectiveness of online learning at the Early Childhood Education (PAUD) level, to explain the obstacles and solutions for PAUD teachers in providing online learning, and to explain the efforts of teachers in developing PAUD learning in the Covid Era. The research subjects were two educators at PAUD UPT SPNF SKB ENREKANG. Qualitative research design using interview techniques in collecting data. The results of the study show that the teaching and learning process is carried out online even though the learning becomes ineffective due to obstacles including the lack of student motivation and lack of facilities such as cellphones and internet quotas. One solution is offline learning. Paying attention to aspects of learning as a teacher's effort to achieve learning.
Remote sensing of atmospheric winds using an infrared all-sky imager

&amp;lt;p&amp;gt;The motion of clouds at a given location can be detected using ground-based all-sky imagers that frequently acquire images of the sky dome. Motion flow is used for minute-scale forecasting of cloud cover and solar irradiance, for example in the case of forecasting photovoltaic power production. While visible-range sky cameras are often applied for this purpose, they neither allow to detect the altitude of clouds, nor accurately detect clouds at night time. However, thermal-infrared all-sky imagers, such as Reuniwatt&amp;amp;#8217;s Sky InSight, retrieve brightness temperatures with constant accuracy at day and night time. This allows for the retrieval of diverse cloud parameters such as cloud base height. Atmospheric wind vectors can be derived and geolocalised by combining cloud motion detection and cloud-base height retrieval. In this study, we evaluate the accuracy of atmospheric wind vector retrievals by the means of the Sky InSight. Radiosoundings and wind profiler observations are used as a reference.&amp;lt;/p&amp;gt;
Total Quality Management Practices and Organizational Excellence of Government Secondary Schools in Khyber Pukhtunkhwa

The study was designed to look into the importance of Total Quality Management TQM in refining the organizational excellence of government secondary schools in Khyber Pukhtunkhwa. The researcher developed a questionnaire to measure teacher performance, school leadership practices and organizational excellence of the secondary school. One hundred and fourteen principals working in the government secondary schools marked the questionnaire. The required data was analyzed using linear and multiple regressions. Teacher performance and school leadership practices contributed 64 and 30 percent respectively towards organizational excellence. The teacher performance and School administration taken together contributed eighty percent towards the organizational excellence of the secondary schools. It was found the teacher performance and School leadership possessing the excellent qualities /practices are the dominant predictors of organizational excellence. Some bold recommendations were suggested to implement the TQM regarding the performance of the teachers and principal positively.
Data Poisoning Won't Save You From Facial Recognition

Data poisoning has been proposed as a compelling defense against facial recognition models trained on Web-scraped pictures. By perturbing the images they post online, users can fool models into misclassifying future (unperturbed) pictures. We demonstrate that this strategy provides a false sense of security, as it ignores an inherent asymmetry between the parties: users' pictures are perturbed once and for all before being published (at which point they are scraped) and must thereafter fool all future models -- including models trained adaptively against the users' past attacks, or models that use technologies discovered after the attack. We evaluate two systems for poisoning attacks against large-scale facial recognition, Fawkes (500,000+ downloads) and LowKey. We demonstrate how an oblivious model trainer can simply wait for future developments in computer vision to nullify the protection of pictures collected in the past. We further show that an adversary with black-box access to the attack can (i) train a robust model that resists the perturbations of collected pictures and (ii) detect poisoned pictures uploaded online. We caution that facial recognition poisoning will not admit an arms race between attackers and defenders. Once perturbed pictures are scraped, the attack cannot be changed so any future successful defense irrevocably undermines users' privacy.
Case Studies in Data Optimization Using Python

A large number of data science and machine learning problems ultimately reduce to optimizations problems. New advents in AI, data science, machine learning, and deep learning affect almost all business and technology. This, however, doesn’t change the fact that human and natural resources are still finite and bounded by legal and ethical constraints. Advanced practices of machine learning may be helpful to guide scientists to achieve better solutions based on optimization at a faster clip, but they should keep on solving the same or rather complex problems as they were previously. A cascade of new data will support this process, but the expectations will rise as time goes on. Otherwise, what’s the point of AI or Big Data? For example, if a scientific team processes 2 GB of data and produces an optimal solution at a cost of Rs. 1000, the team should reduce the cost to Rs. 7000/- (instead of Rs. 10000/-) if it processes a “bigger” dataset of 20 GB. In this chapter, the author discusses how to solve optimization problems using Python and other tools. The intention of the author is not to help the user become a skillful theoretician, but a skillful modeler. Therefore, little of mathematical principles related to the subject of optimization is discussed. Various aspects of optimization problems have been covered in the case studies mentioned in the chapter. The chapter can be effectively used to create easy yet powerful and efficient models.
Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric

The rapid development of such natural language processing tasks as style transfer, paraphrase, and machine translation often calls for the use of semantic similarity metrics. In recent years a lot of methods to measure the semantic similarity of two short texts were developed. This paper provides a comprehensive analysis for more than a dozen of such methods. Using a new dataset of fourteen thousand sentence pairs human-labeled according to their semantic similarity, we demonstrate that none of the metrics widely used in the literature is close enough to human judgment in these tasks. A number of recently proposed metrics provide comparable results, yet Word Mover Distance is shown to be the most reasonable solution to measure semantic similarity in reformulated texts at the moment.
An Analysis of the Writing Material in the English Textbook “Joyful English” for the Fourth Grade Students of Elementary School

Textbooks are important references used by teachers and students in the teaching and learning process. Considering such a situation it is important to conduct a study to describe the shortcomings of the textbook and increase its strength. This study aimed to analyze the presentation of the written material in the textbook “Joyful English” for the fourth grade of elementary school. This research was a descriptive qualitative research using content analysis based on the theory of Hutchinson and Totres (1994 : 315).The data were collected using questionnaires for the teacher of Elementary School and document readings focusing on the analysis of the writing materials. The results showed that in terms of writing materials, all writing assignments were in the form of guided writing, where students were asked to write responses and short texts. The result also showed that writing assignments in textbooks were proportionally covered as required in Kompetensi Dasar (Basic Competence) as required in the Lesson Plan.
A Comparative Study Between Team Games Tournament And Student Teams Achievement Divisions In Teaching Reading

This study aims at finding out  whether there is a significant difference in reading comprehension between students taught using Team Games Tournament (TGT) and students taught using Student Teams Achievement Divisions (STAD); and  which method has a better result in teaching reading between TGT and STAD. The research method used in this study is the quasi-experimental research design. This research was conducted at one of junior high school in Purwodadi. The population of the research was the eighth grade students in that school. The sam­ples were students of class VIII A as the experimental group which consisted of 32 students and students of class VIII D as the control group which consisted of 32 students. The research instru­ments used to collect the data in this study were tests, including pre-test and post-test. The data were analysed by using the t-test formula and the score improvement to determine the significant difference and the better method respectively. The data computation using the t-test shows that t observation (to) (3.11) was higher than t table (tt) (1.96). The post-test score shows that the mean score of the experimental group is 80.625, while the mean score of the control group is 74.625. It means that the mean score of the experimental group is higher than the mean score of the control group. In a nutshell, there is a significant difference in reading comprehension be­tween the students taught using STAD and the students taught using TGT and TGT is better than STAD to teach reading.
Waves in pipes

Longitudinal waves in pipes are reflected at the ends, and thus form standing waves precisely as strings do, except that the relevant velocity is not the velocity of wave propagation along a string, but the velocity of sound in air. Pipes have fundamental and higher modes, which differ if the pipe is open at both ends, or only at one end, in which cases they are termed open and closed pipes. Open pipes have all the higher modes, closed pipes only the odd multiples of the fundamental.
Tendencias en la sumarización lingüistica de datos: LINGUISTIC DATA SUMMARIZATION AND OVERVIEW

Linguistic data summarization techniques have emerged to help discover complex relationships between variables and present information in natural language. In the development of these techniques, artificial intelligence, statistics, machine learning, among other areas of human knowledge, are combined. This research aims to carry out a study of the state of the art of the subject that allows researchers to analyze the evolution and trends in its development. Trends in abstract generation methods, validation strategies used in research, and main areas of application are analyzed. As conclusions, the need to improve validation methods, emerging techniques in the generation of summaries and the possibility of using summaries in prediction problems, among others, are identified.
Cultivating the Professional Ability of Musicology in Normal Universities under the Background of Double First

As one of the seven modern arts, music has strong artistic and cultural value [1]. Musicology is a comprehensive subject that integrates artistic, technical and theoretical aspects. This subject requires in-service college teachers to have a diversified teaching practice application ability to meet the knowledge needs of students for the content of the course. Due to the current lack of teaching practice ability, relatively weak teaching practice ability, backward talent training standards, and traditional teaching mode of musicology teachers in major domestic universities. Major colleges and universities should choose appropriate training methods, actively arrange teachers’ extracurricular tasks, innovate subject teaching models and increase the training of musicology teachers’ teaching ability to achieve continuous improvement of college musicology teachers’ teaching level [2].
Synergetic Paradigm of Personality Development of a Specialist in the Educational Process

This article is devoted to the consideration of synergetics as the basis of a new approach to designing the educational environment of a university. Various approaches to determining the educational environment are analyzed. The action of the seven basic principles of synergetics in the pedagogical sciences is analyzed and the principles of designing the educational environment of the university are formulated on their basis. A model of the educational environment is proposed, which can be used as the basis for the design and construction of an appropriate teaching system by a university teacher. In the aspect of the formation of a bilingual personality, then a trilingual, and then a multilingual personality. The article is aimed at presenting the logic of support for self-motivation and self-education of research abilities in developing skills and self-design skills of creative competitive specialists.
Contributo para a descrição da estrutura silábica do guineense

This work intends to contribute to a better understanding of syllabic structure of Guine-Bissau creole, namely with regard to: (i) the distribution of segments within the syllabic constituents, (ii) the establishment of syllabic boundaries in consonantal sequences that, at the phonetic level, do not respect the conditions of good syllabic formation and (iii) the description of phonological processes occurring in the syllable domain. The analysis of a corpus of oral productions allows to confirm that CV is the optimal syllabic pattern of Guine-Bissau creole, but the patterns V, VG, VC, CVC, CVG, CVGC, CCV, oC, Co and CCVC also occur. However, they are marked patterns, due to its low frequency. The definition of these structures as syllabic possibilities in the language results from the application of universal principles of good syllabic formation, as well as the activation of several phonological processes of assimilation. As to syllabic constituents, we observed that the onset (that can only be filled by [-vocalic] segments) can dominate one or two positions in the skeleton; rhyme may be branched or unbranched; the nucleus only admits [-consonantal] segments and can dominate one or two positions in the skeleton; the coda (the less frequent syllabic constituent) only dominates one position in the skeleton and only admits segments [+consonant], the number of segments allowed being restricted.
Open-Source: Attention-Based Neural Networks For Chroma Intra Prediction In Video Coding

Neural networks can be successfully used to improve several modules of advanced video coding schemes. In particular, compression of colour components was shown to greatly benefit from usage of machine learning models, thanks to the design of appropriate attention-based architectures that allow the prediction to exploit specific samples in the reference region. However, such architectures tend to be complex and computationally intense, and may be difficult to deploy in a practical video coding pipeline. The software presented in this paper introduces a collection of simplifications to reduce the complexity overhead of the attention-based architectures. The simplified models are integrated into the Versatile Video Coding (VVC) prediction pipeline, retaining compression efficiency of previous chroma intra-prediction methods based on neural networks, while offering different directions for significantly reducing coding complexity.