Reviewerly/exHarmony huggingface dataset:
Research on the key technologies of the end-to-end intelligent dual live data center architecture

Abstract As a direction of the current government informatization,dual live data center can be understood as both have a high availability architecture of production system, also is a kind of disaster information system construction model. Dual live data center can not only solve the government information system of business continuity and data reliability, but also can reduce the load balance of business requests and the resource operation pressures on production part.It can improve the effect of system efficiency and the user experience. But most of current dual live data center architecture is “not real dual live”, it is only dual live in some aspects, it will not have negative impact on system external service when the specific failure occurs. In this paper, an end-to-end “full dual-activity" system architecture is proposed. By building a dual-activity system at various technical levels, two fully dual-activity data center architectures are realized. The data center constructed by this technical route can be backed up and switched intelligently, It can deal with the vast majority of failures and disasters, and provides a more reliable guarantee for the safe and smooth operation of the government information system.
Predicting Simplified Thematic Progression Pattern for Discourse Analysis

The pattern of thematic progression, reflecting the semantic relationships between contextual two sentences, is an important subject in discourse analysis. We introduce a new corpus of Chinese news discourses annotated with t... | Find, read and cite all the research you need on Tech Science Press
Analysis of the Information Security Risk Assessment Mechanism Based on the Power System

Abstract In the risk assessment of the traditional power system information security, the traditional assessment methods are inefficient and the accuracy needs to be further improved. This paper establishes the analytic hierarchy process (AHP), designs a new information security risk assessment model in combination with fuzzy mathematics in risk assessment, and describes the content of the model in detail.
Teaching Reform of Food Microbiology Experiment in Food Specialty of Applied College

It aims to fully mobilize students' enthusiasm for learning,effectively improve their mastery of theoretical knowledge and practical skills.Taking the food microbiology experiment course as an example,this paper explores and reforms the curriculum by integrating teaching content,enriching teaching methods,and strengthening practical operations.Teaching reform of food microbiology experiment course to achieve the knowledge,skills and quality of students engaged in food microbial development and testing,so that students can meet they can meet the requirements of the applicable unit.
Synthesis and Edition of Ultrasound Images via Sketch Guided Progressive Growing GANs

Ultrasound (US) is widely accepted in clinic for anatomical structure inspection. However, lacking in resources to practice US scan, novices often struggle to learn the operation skills. Also, in the deep learning era, automated US image analysis is limited by the lack of annotated samples. Efficiently synthesizing realistic, editable and high resolution US images can solve the problems. The task is challenging and previous methods can only partially complete it. In this paper, we devise a new framework for US image synthesis. Particularly, we firstly adopt a sketch generative adversarial networks (Sgan) to introduce background sketch upon object mask in a conditioned generative adversarial network. With enriched sketch cues, Sgan can generate realistic US images with editable and fine-grained structure details. Although effective, Sgan is hard to generate high resolution US images. To achieve this, we further implant the Sgan into a progressive growing scheme (PGSgan). By smoothly growing both generator and discriminator, PGSgan can gradually synthesize US images from low to high resolution. By synthesizing ovary and follicle US images, our extensive perceptual evaluation, user study and segmentation results prove the promising efficacy and efficiency of the proposed PGSgan.
Spatio-Temporal Outlier Detection: A Survey of Methods

With the advancement of mobile device and localization technology, the collection of Spatio-Temporal information from moving objects become much easier and easier than before, and outlier detection for Spatio-Temporal data is becoming increasingly attractive in data mining community. Frankly speaking, aSpatial-Temporal outlier is an observation whose attribute value significantly differ from those of other spatially and temporally referenced objects in a Spatio-Temporal neighbor.Discovering STOD is an important problem with many applications such as geological disaster monitoring, geophysical exploration, public safety and health etc. This paper has a briefly introduction of most popular Spatio-Temporal outlier detection methods in recent two decades and list, explain two most useful algorithms to STOD. We also discuss the methods of the spatial outlier detection and temporal outlier detection before the main content for the aim of having a better understand of data outlier detection field. Three tables show the visualized result of our research.
Detecting, Diagnosing, Deflecting and Designing Adversarial Attacks

Author(s): Qin, Yao | Advisor(s): Cottrell, Garrison | Abstract: There has been an ongoing cycle between stronger attacks and stronger defenses in the adversarial machine learning game. However, most of the existing defenses are subsequently broken by a more advanced defense-aware attack. This dissertation first introduces a stronger detection mechanism based on Capsule networks which achieves state-of-the-art detection performance on both standard and defense-aware attacks. Then, we diagnose the adversarial examples against our CapsNet and find that the success of the adversarial attack is proportional to the visual similarity between the source and target class (which is not the case for CNN-based networks). Pushing this idea further, we show how it is possible to pressure the attacker to produce an input that visually resembles the attack’s target class, thereby deflecting the attack. These deflected attack images thus can no longer be called adversarial, as our network classifies them the same way as humans do. The existence of the deflected adversarial attacks also indicates the lp norm is not sufficient to ensure the same semantic class. Finally, this dissertation discusses how to design adversarial attacks for speech recognition systems based on human perception rather than the lp-norm metric.
Similarity-based calibration method for zero-shot recognition in multi-object scenes

The objective of Zero-Shot Learning (ZSL) is to classify the class labels of unseen objects using external knowledge representing semantic information. Traditional zero-shot recognition models have the limitation that they rely only on the visual appearance of an unseen object. To alleviate this limitation, we propose a novel method that calibrates the visual prediction of an unseen object by using contextual information based on similarities between the unseen object and its surrounding seen objects in a multi-object scene. We incorporate the proposed method into each of the traditional models and conduct a comparative evaluation between the models with and without our calibration algorithm. The evaluation results show consistent performance improvements by a significant margin.
An Evaluation of English-to-Yoruba Translations of Some Concepts by Selected Radio News Bulletins in South-Western Nigeria

This study examines translations of selected official names/titles contained in news broadcasts in the Yoruba-speaking part of Nigeria, interrogating their adequacy and appropriateness. Sixty-five concepts/titles extracted from one hundred news bulletins presented by five radio stations across the Yoruba-speaking states of Nigeria are examined. The study is prompted by an intuitive feeling of inaccuracy and inappropriateness of important words in news broadcasts in Yoruba and predicated upon the fact that misinformation can be as pernicious as lack of information. The renderings of the concepts in Yoruba are compared with their original versions in English, revealing translation weaknesses such as semantic narrowing, expansion, wordiness, sometimes even unwitting distortions. It concludes by emphasising the adoption of appropriate translation strategies and a more rigorous engagement with the texts as a way of guarding against unintended distortions and misinformation. Keywords: Yoruba, English, translation, news broadcasts, accuracy, distortion, DOI: 10.7176/NMMC/88-05 Publication date: March 31 st 2020
vLookup Trio – Live Performance at Dutch Fretless Guitar Festival VIII

vLookup Trio (trumpet, percussion and fretless electric guitar) explore the sonic possibilities of an otherwise limited instrumentation by incorporating technological augmentation (including effects and live electronics.)In 2019 the ensemble produced a studio recording (EP/ Mini-Album) of original pieces, which demonstrate their latest discoveries in terms of instrumental techniques and soundscapes. The trio performed as one of the main acts at the 8th Dutch Fretless Guitar Festival, in Amsterdam (2019).
Guides: Music: Jazz

Study smarter. Research effectively. Your guide to library tools and research skills. Listen to, research, and keep up to date with jazz music.
Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation

Translation models based on hierarchical phrase-based statistical machine translation (HSMT) have shown better performances than the non-hierarchical phrase-based counterparts for some language pairs. The standard approach to HSMT learns and apply a synchronous context-free grammar with a single non-terminal. The hypothesis behind the grammar refinement algorithm presented in this work is that this single non-terminal is overloaded, and insufficiently discriminative, and therefore, an adequate split of it into more specialised symbols could lead to improved models. This paper presents a method to learn synchronous context-free grammars with a huge number of initial non-terminals, which are then grouped via a clustering algorithm. Our experiments show that the resulting smaller set of non-terminals correctly capture the contextual information that makes it possible to statistically significantly improve the BLEU score of the standard HSMT approach.
Investigating Some Characteristics and Features of the Gulf Cooperation Council Countries (GCC) Stock Markets

In this paper, some GCC stock markets' characteristics and features (volatility clustering, reversion to the mean, risk return relationship, leverage effect and weak-form efficiency) were investigated.For this purpose, the following tests and models were applied: augmented dickey fuller test and the models GARCH (1.1), EGARCH (1.1) and GARCH-M (1.1), using data over a period from 2010 until 2013 for all the markets except Kuwait stock markets (its data was until 2012).It was concluded after the implementation that the stock markets of Saudi Arabia, Dubai, Qatar, Kuwait and Oman were characterized by all studied features in this work, except for weak-form efficiency.Bahrain stock market was characterized by all the features except for leverage effect and weak-form efficiency whereas Abu Dhabi stock market was characterized by one feature only (i.e. the reversion to the mean).
Research on the Cognitive Teaching Development Ability of Lexico-grammar Chunks MOOCs and Practical Cultivation Mechanism of College English Teachers under the Transformation Background of Newly-rebuilt Universities

The development and cultivation mechanism of College English teachers are very prominent, Under the strategic deployment of the State Council’s request for the transformation of undergraduate universities to application-oriented universities and from the requirement of the Ministry of Education’s speeding up the revitalization, improving the quality of undergraduate education, eliminating “water courses” and creating “MOOCs”. The teaching of College English lexicogrammar has become a major obstacle for College English teachers. The author constructs the teaching model of College English lexicogrammar chunks from three branches of Cognitive Linguistics: Prototype Category Theory, Conceptual Metaphor Theory and Image Schema Theory, and applies the cognitive teaching model to the specific teaching practice of lexicogrammar chunks, so as to promote the development of lexicogrammar chunks teaching ability and practical cultivation mechanism for College English teachers.
Itogi realizatsii federal'nogo proekta po rannei professional'noi orientatsii uchashchikhsia 6-11-kh klassov obshcheobrazovatel'nykh organizatsii Chuvashskoi Respubliki "Bilet v budushchee"

This material describes the implementation of the Federal project "Ticket to the Future", which includes familiarizing students of 6-11th grades of general education institutions with modern professional occupations, determining children’s professional interest, forming recommendations for building an individual educational trajectory in accordance with the selected professional competencies (professional areas of activity) and in accordance with the control point 3.1. The action plan for the implementation of the Federal project "Success of every child" which is "Education" National Project Charter. The organizer of the project "Ticket to the future" in 2019 is the Union "Young professionals (WorldSkills Russia)", the operator of the project for the Chuvash Republic for 2 years in a row is the budget institution of the Chuvash Republic of additional professional education "Chuvash Republican Institute of Education" of the Ministry of education and youth policy of the Chuvash Republic.
On Universality and Training in Binary Hypothesis Testing

The classical binary hypothesis testing problem is revisited. We notice that when one of the hypotheses is composite, there is an inherent difficulty in defining an optimality criterion that is both informative and well-justified. For testing in the simple normal location problem (that is, testing for the mean of multivariate Gaussians), we overcome the difficulty as follows. In this problem there exists a natural hardness order between parameters as for different parameters the error-probailities curves (when the parameter is known) are either identical, or one dominates the other. We can thus define minimax performance as the worst-case among parameters which are below some hardness level. Fortunately, there exists a universal minimax test, in the sense that it is minimax for all hardness levels simultaneously. Under this criterion we also find the optimal test for composite hypothesis testing with training data. This criterion extends to the wide class of local asymptotic normal models, in an asymptotic sense where the approximation of the error probabilities is additive. Since we have the asymptotically optimal tests for composite hypothesis testing with and without training data, we quantify the loss of universality and gain of training data for these models.
Closure of special atomic subsets of semantic model

Closure of special atomic subsets of semantic modelThe present paper concerns some properties of the so-called small models, generally speaking, not necessarily complete theories and their relationship with each other.In the well-known paper [1], R. Vaught have proved the fundamental theorem-criterion on the behavior of countable prime and atomic models for complete theories in countable language.The essence of this criterionis that in a complete theory any countable prime model is at the same time an atomic model of this theory.The result obtained in this paper is related to the classical problem of Vaught about countably prime models of complete theories but in more general formulation of the notion of countable atomicity.The main result of this paper is that it focuses on the syntactic properties on special subsets of a fragment of the semantic model the specific Jonsson theory.The concept of the so-called model-theoretic rheostat was also used to obtain results related to the refinement of the concept of atomicity in the framework of Jonsson's theories.
Quantification and Speciation of Lead, Cadmium and Chromium in Dandora Dumpsite Soils

Open dumpsites are one of the main sources of heavy metals and as a result, lots of research has been undertaken on the pseudo-total content of heavy metals in dumpsite soils, but little research on the forms in which they exist. The current research was carried out to determine levels of chromium, lead and cadmium in the various fractions of Dandora dumpsite soil and how they are fractionated in the topsoil and subsoil horizons. Samples were obtained from eight sites with depths of (0-30 cm) and (30-60 cm) for topsoil and bottom soils respectively. The modified Community Bureau of Reference (BCR) sequential extraction procedure was used and metal analysis performed using flame atomic absorption spectrophotometry. The metals (lead, chromium and cadmium) total concentration (µg/g) in the upper soil profile ranged from 42.22 to 1096.21, 38.26 to 180.60 and 11.23 to 44.22 while the lower soil profiles were 54.19 to 239.28, 30.56 to 76.48 and 9.47 to 22.56, respectively. The concentration of lead in various fractions of the upper soil profile followed the order; reducible &gt; oxidisable &gt; residual &gt; exchangeable, while that of chromium was residual &gt; oxidisable &gt; reducible &gt; exchangeable. Cadmium followed the order exchangeable &gt; residual &gt; reducible &gt; oxidisable. The percentage of the metals in non-residual fraction were Pb (78%), Cr (58.7%) and Cd (70%). Their mobility factors were (Pb) 39.7 (Cr) 7.75 and (Cd) 5.02 in the upper soil profiles. Thus, the results suggest that Dandora dumpsite is highly polluted with the selected heavy metals.
Projection Pursuit Gaussian Process Regression

A primary goal of computer experiments is to reconstruct the function given by the computer code via scattered evaluations. Traditional isotropic Gaussian process models suffer from the curse of dimensionality, when the input dimension is relatively high given limited data points. Gaussian process models with additive correlation functions are scalable to dimensionality, but they are more restrictive as they only work for additive functions. In this work, we consider a projection pursuit model, in which the nonparametric part is driven by an additive Gaussian process regression. We choose the dimension of the additive function higher than the original input dimension, and call this strategy "dimension expansion". We show that dimension expansion can help approximate more complex functions. A gradient descent algorithm is proposed for model training based on the maximum likelihood estimation. Simulation studies show that the proposed method outperforms the traditional Gaussian process models. The Supplementary Materials are available online.
Grayscale Feature Based Multi-Target Tracking Algorithm

Aiming at the problem of multi-target tracking accuracy decreasing and target SNR unknown in clutter environment, a multi-target tracking algorithm based on target grayscale feature is proposed. In this algorithm, the grayscale likelihood function based on SNR estimation and the grayscale likelihood function based on SNR prior information are constructed by using historical measurement information. When the tracking algorithm updates the target state, the grayscale likelihood function is introduced into the original likelihood function, and the grayscale likelihood function is used to increase the discrimination between the target and the clutter, so as to filter out more clutter and improve the tracking accuracy. Simulation results show that the algorithm can achieve better tracking effect in clutter environment, and has higher tracking accuracy and stability than the traditional algorithm.
Introducing a Hierarchical Attention Transformer for document embeddings : Utilizing state-of-the-art word embeddings to generate numerical representations of text documents for classification

The field of Natural Language Processing has produced a plethora of algorithms for creating numerical representations of words or subsets thereof. These representations encode the semantics of each ...
Improving Student Learning Ability Through Communicative Language Learning Approach

This study aims to find out how students' speaking skills are developed through the Communicative Language Teaching approach. The significance of this research is to provide information for readers, especially for Pamona people as native speakers of the language, about the tenses in the Pamona language. Researchers used the Communicative Language Teaching (CLT) theory by Richard and Rodgers to develop students' speaking skills. The results of this study indicate that the objectives of this study have been achieved. The ability to speak English students successfully developed through the application of communicative language teaching approaches, through learning that triggers students to speak actively in the classroom through conversations as an exercise. In the first cycle all students attend the test. The results of the test in the first cycle were 12 students failed (33.3%) and 24 students (66.7%) passed. Achievement of the average grade of the class is also still low with a score of 65.8 grades C. Researchers then reflect on the learning process in this first cycle to be applied in the second cycle. In the second cycle, all students attend the test. The results of this test were 33 students (91.6%) successfully passed the test and 3 students (8.4%) failed. From the explanation of the results of the second cycle above, it appears that in this cycle the completeness criteria for class has been reached, in which 80% of the total number of students must achieve grades A, B or C or a value of more than 65. Students succeed in developing their English speaking skills because supported by teaching approaches that trigger students to speak and practice the functions of the language being learned.
Reid, G. &amp; Guise, J. 2017. The Dyslexia Assessment. London: Bloomsbury Education.

Support for LearningVolume 34, Issue 1 p. 121-122 Book Review Reid, G. & Guise, J. 2017. The Dyslexia Assessment. London: Bloomsbury Education. Lynda Hine, Corresponding Author Lynda Hine lynda.hine@chester.ac.uk Senior Lecturer: Programme Leader: Dyslexia Research and Practice & Special Educational Needs and Disability Postgraduate Programmes, Faculty of Education and Children's Services, University of Chester Email: lynda.hine@chester.ac.ukSearch for more papers by this author Lynda Hine, Corresponding Author Lynda Hine lynda.hine@chester.ac.uk Senior Lecturer: Programme Leader: Dyslexia Research and Practice & Special Educational Needs and Disability Postgraduate Programmes, Faculty of Education and Children's Services, University of Chester Email: lynda.hine@chester.ac.ukSearch for more papers by this author First published: 25 March 2019 https://doi.org/10.1111/1467-9604.12242Read 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume34, Issue1February 2019Pages 121-122 RelatedInformation