Reviewerly/exHarmony huggingface dataset:
Complete Normal Bases and Generalized Cyclotomic Modules

In the present chapter, we consider a particular class of normal elements for extensions of finite fields. We introduce the topic by presenting two examples of normal elements for Galois extensions E/F which are not normal for some intermediate extension E/K of E/F. This suggests to study completely normal elements for E/F, that is, normal elements which are also normal over every intermediate field K of E/F. We first prove the existence of such elements in the more general setting of Galois extensions, before we focus on the construction of completely normal elements in the special case of finite fields. In fact, the main parts of this chapter may be viewed as variations on the themes encountered in Chap. 10; for instance, the class of regular extensions will again play a prominent role. As a result of these deeper investigations, we will obtain an interesting structure theory for extensions of Galois fields.
An Improved Template Representation-based Transformer for Abstractive Text Summarization

Text summarization plays an important role in various NLP applications. Using templates with generation methods is an effective way to address abstractive summarization. However, existing template-enhanced generation approaches use templates in a naive way and mainly adopt RNN-based Seq2Seq models, so they cannot make full use of valid information in the templates and suffer from templates' noise. To mitigate these problems, we propose a new abstractive summarization model called Summarization Transformer with Template-aware Representation (STTR), which uses a template-aware document encoding module and a document representation shifting loss to preserve the useful information and filter the noise of the template. The experiments on the Gigaword and LCSTS datasets show that our method outperforms baseline models and achieves a new state-of-the-art.
Extreme Learning Machine Based Defect Detection for Solder Joints

The quality of solder joints is essential for electronic products, and the detection of defects in solder joints is critical to the quality control of electronic products. A vision inspection is developed to detect defects of solder joints in automatic line. Extreme learning machine is applied to identify defective solder joints from qualified ones. Five low level features and three advanced features are employed as input features. The low-level features include roundness, roughness, entropy, contrast and histogram of oriented gradient. The advanced features include grey-level co-occurrence matrix, local binary pattern, and segmentation-based fractal texture analysis. To solve unbalanced samples problem, Gaussian mixture model based dense estimation scheme is proposed to adjust the classification super plane for extreme learning machine. The experimental results demonstrate that the proposed defect detection method is more efficient than neural network, support vector machines, common extreme learning machine and convolutional neural network-based methods, and it has real-time performance to meet the equirement of the actual production line.
Alfnoor: assessing the information content of Ariel's low resolution spectra with planetary population studies.

&amp;lt;p&amp;gt;In the next decade the Ariel Space Telescope will provide the first statistical dataset of exoplanet spectra, performing spectroscopic observation of about 1000 exoplanets in the wavelength range 0.5&amp;amp;#8594;7.8 &amp;amp;#956;m thanks to its Reconnaissance Survey. About one half of these 1000 targets will be then selected for more accurate observations with higher spectral resolution.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;We present a novel metric to assess the information content of the Ariel Reconnaissance Survey low resolution transmission spectra. The proposed strategy will not only allow us to select candidate planets to be re-observed in Ariel higher resolution Tiers, but also to classify exoplanets by their atmospheric composition and to put the basis for the statistical analysis of such a large exoplanetary sample.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;To test our metric we use Alfnoor, a new package combining the TauRex spectral modelling with the ArielRad payload performance model, to produce populations of hundreds of exoplanets matching those presented in the Ariel Mission Reference Sample. For each of the planets in the Ariel candidate targets list we create an atmosphere with a randomised quantity of H&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;O, CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt;, CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, NH&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; and clouds.&amp;amp;#160;&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;Our metric proves able to identify methane,&amp;amp;#160; carbon&amp;amp;#160; dioxide&amp;amp;#160; and&amp;amp;#160; water&amp;amp;#160; rich&amp;amp;#160; atmospheres in the cases of molecular abundances &amp;gt; 10&amp;lt;sup&amp;gt;&amp;amp;#8722;4&amp;lt;/sup&amp;gt; in mixing ratio,&amp;amp;#160; but it shows its limits in separating water from ammonia.&amp;amp;#160;&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;We compare our metric with four different Deep Learning algorithms, they show only &amp;amp;#8764;10% better performance in identifying the molecular content.&amp;lt;/p&amp;gt;
Toward a Decentralized Service Marketplace: The Interplay Between Blockchain and Algebraic Service Composition

Service marketplaces are supposed to guarantee an open platform for sellers and customers of cloud services. But their potentials cannot be fully released, due to the widely known shortcomings including but not limited to central power of authority, data privacy, lack of customization, rigid and complex trading procedure. We argue that decentralized marketplaces, although not mature, are the most promising solution to address these issues. In this paper, we present our work in progress, which is oriented toward a blockchain-enabled marketplace for sharing services at different levels of granularity in a flexible and trustworthy manner.
Development of Ceramic Arts In-Service Training Program for Enhancing Artistic Expertise of Elementary School Teacher

학교 예술교육에 있어 교사의 예술 전문성은 매우 중요하며, 그 중에서도 초등학교에서의 예술교육은 전인 교육 관점에서매우 중요하다고 할 수 있다. 그러나 초등교사가 예술 전문성을 갖출 수 있는 기회는 턱없이 부족할 뿐만 아니라, 이를 중요하게 인식하지 않는 경향으로 인하여 도외시되고 있다. 도예를 통한 예술 전문성 신장은 미술문화에 대한 관점을 넓혀 예술과 함께 하는 삶으로 이끄는 데 일조할 수 있다. 이러한 필요성으로 본 연구에서는 초등교사의 예술 전문성 신장을 위하여직무연수 도예 프로그램을 개발하는 데 목적을 두었다. 이를 위하여 초등교사를 대상으로 예술 전문성의 개념과 도예 프로그램에 대한 설문조사를 실시하였으며, 2회에 걸쳐 전문가 면담을 실시하였다. 연구 결과 도예교육을 위한 초등교사 예술 전문성은 ‘정체성 확립’(‘초등교사 정체성 확립’, ‘초등미술교육 확립’), ‘도예문화 역량 및 학문적 지식’(‘도예문화의 이해’, ‘도예이론’), ‘도예 실기’(‘교과서 도예작품 제작’, ‘생활도자기 제작’, ‘도예 전통문양 제작-‘박지, 상감 문양’)로 제안하여 도예 프로그램을 개발하였다. 본 연구는 도예교육 관점에서 초등교사 예술 전문성을 진단하고 이를 기초로 직무 연수를 위한 도예프로그램을 개발을 모색했다는 데에 의의가 있다.Expertise of teachers in art is essential for the art education, especially crucial in elementary school in the aspect of the all-round education. However, there are insufficient opportunities to train elementary school teachers to obtain artistic expertise; moreover, the significance of artistic expertise is often neglected. Expanding artistic expertise particularly through the ceramic arts enlightens their insights in arts culture to enrich their lives. Regards to the needs, this study focuses on the development of the ceramic arts training program as a part of the in-service training to enhancing the artistic expertise of elementary school teachers. The result of this study concludes the three criteria for elementary school teacher’s expertise in the arts; ‘identity establishment (elementary teacher’s identity, elementary arts education settlement),’ ‘capability of the ceramic arts and academic knowledge (understanding of ceramic arts culture, ceramic arts theory),’ and ‘practical abilities of ceramic arts (realizing ceramic pieces in a textbook, crafting tableware, crafting traditional pattern in ceramic arts).’ Hence, the program is distinguishable from the existing in-service training program in that it is based on the expertise of elementary school teacher measured through the lens of the ceramic art education.
Normal Bases and Cyclotomic Modules

The aim of this chapter is to determine a normal element for every extension E/F of finite fields. For this, it will be convenient to work (theoretically) in an algebraic closure \(\widehat{F}\) of a fixed ground field F = GF(q) with q elements. While this will simplify the presentation, it is not actually required for constructing normal elements in specific cases: then all that is really needed are finite extensions of F. Recall from Chap. 4 that for every \(n \in {\mathbb{N}}^{*}\) there is exactly one intermediate field En of \(\widehat{F}/F\) with degree n over F. We will explicitly describe a normal element wn for the extension En/F in terms of certain roots of unity whose multiplicative orders depend on q and n. Moreover, we give an inductive construction for a trace-compatible sequence \((w_{n} )_{{n \in {\mathbb{N}}^{*} }}\) over \(\widehat{F}\) for which every wn is a normal element for En/F. Finally, we also present two reasonably efficient algorithms for computing a normal element for an arbitrary extension E = GF(qn) of F = GF(q).
Security Done Right: Start at the Heart of the SoC

In our fast-paced and evolving connected world, there is an increased demand for security solutions that are capable of adapting to an ever changing threat environment and are harder to break. This drives the need for higher-grade security solutions based on hardware Root of Trust embedded into the heart of SoCs to ensure protection at various stages of operation and communication.
Efficient Computing for AI and Robotics

Computing near the sensor is preferred over the cloud due to privacy and/or latency concerns for a wide range of applications including robotics/drones, self-driving cars, smart Internet of Things, and portable/wearable electronics. However, at the sensor there are often stringent constraints on energy consumption and cost in addition to the throughput and accuracy requirements of the application. In this talk, we will describe how joint algorithm and hardware design can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning, computer vision, autonomous navigation/exploration and video/image processing. We will show how energy-efficient techniques that exploit correlation and sparsity to reduce compute, data movement and storage costs can be applied to various tasks including image classification, depth estimation, super-resolution, localization and mapping.
Using Code Review at School and at the Programming Club

Educational code review is an activity that not only helps prepare future programmers into practice, but also teaches students to work with code in a different way. In the educational settings, activities focused on code review are mainly encountered at universities. In our research, we focused on lower levels of education and in our previous publications we presented the results of using code review at secondary school. Experimentally, we also tried to use the code review activities on the sessions at the leisure-time activities club. This paper provides a description of the research carried out. We compare the outcomes from the club with the results from the secondary school. We also give an overview of the benefits, as well as the problems such activities can bring to the classroom.
Graphical Interpretations of Data: Be Alert!

Abstract R. Allan Reese offers advice for TV producers as he proofreads some Peston graphs
An Efficient Action Recognition Framework Based on ELM and 3D CNN

Deep neural network is shown to be the most efficient method for video representation and has achieved state-of-art results on different datasets of action recognition. In this paper, we proposed a hybrid architecture which integrates deep convolutional neural networks and extreme learning machine. The hybrid structure makes the most of their advantages: in the first stage the deep residual 3D network learns the features from both temporal and spatial sequences, then the ELM, instead of traditional classifiers, classifies the actions without tuning the parameters. The resulting network can not only extract the representation fully, but also obtain more accurate results faster. We show the effectiveness and outperformance of the proposed strategy on experiments.
Irreducible Polynomials Over Finite Fields

In contrast to the theoretical construction of finite fields as splitting fields presented in Chap. 3, we now consider the explicit description of the extension field GF(qn) of F = GF(q) as the factor ring F[x] · (f) of the polynomial ring F[x] with respect to an irreducible polynomial f of degree n. Not surprisingly, this will require irreducibility criteria for certain types of polynomials, in particular, for binomials and trinomials. The closely related problems of testing an arbitrary monic polynomial f over F for irreducibility or, more generally, of decomposing f into irreducible polynomials will be postponed to Chap. 6. Thus the main topic of the present chapter is the construction of some irreducible polynomial of any given degree over any given Galois field GF(q), but we will also consider this problem for two important special types of polynomials (namely primitive and self-reciprocal polynomials) in the final two sections.
Pelatihan Penyusunan Bahan Ajar Berbasis Multimedia Bagi Guru-Guru Yayasan Ali Imron Pakamban Sumenep

Learning media is a useful tool and intermediary for facilitating the teaching and learning process to streamline communication between teachers and students. This community service activity is divided into three main activities, namely the delivery of concepts or theories of multimedia, types of multimedia, the use of multimedia, and making presentations using practical and interactive PowerPoints tools; second, training on how to use PowerPoint effectively; and third, evaluation on the ability of training participants in making multimedia-based teaching materials.
The impact of linguistic knowledge in different strategies to learn cross-lingual distributional models

In recent years, with the emergence of neural networks and word embeddings, there has been a growing interest in working on cross-lingual distributional models learned from monolingual corpora to induce bilingual lexicons However, interest in these models existed prior to the emergence of deep learning. In this article, we will study the differences between the recent strategies, which are based on the alignment of models, as opposed to the old methods focused on the use of bilingual anchors aligning the text itself. We will also analyze the impact of including different levels of linguistic knowledge (e.g. Lemmatization, PoS tagging, syntactic dependencies) in the process of building cross-lingual models for English and Spanish. Our experiments show that syntactic information benefits traditional models based on text alignment but harms mapped cross-lingual embeddings.
Modern model of physical education teacher's professional activity

Introduction. In this article we analyzed the current characteristics of the professional activity of physical education teachers. We considered the main components of vocational training of specialists in physical education. Purposes and tasks. The main purpose of the study was to develop a model of professional activity of a physical culture teacher based on the identification of the most important qualities. Materials and methods. Questionnaire survey and correlation analysis. Main results. Based on the data of the questionnaire survey, we identified the main most important components that lead to the success of the professional activity of the physical education teacher. We determined the expression of professionally important qualities depending on the length of pedagogical activity of teachers. There is a mismatch between the level of importance and the degree of expression of professionally important qualities in respondents surveyed. Conclusion. The obtained data can be useful for improving the educational process in faculties of physical culture.
High Level Modeling and Hardware Implementation of Image Processing Algorithms Using XSG

Design of Systems-on-Chip has become very common especially with the remarkable advances in the field of high-level system modeling. In recent years, Matlab also offers a Simulink interface for the design of hardware systems. From a high-level specification, Matlab provides self-generation of HDL codes and/or FPGA configuration codes while providing other benefits of easy simulation. In addition, a large part of the Systems-on-Chip use at least one image processing algorithm and at the same time border detection is one of the most used algorithms. This paper presents a study and a hardware implementation of various algorithms of borders detection realized under Xilinx System-Generator. The various algorithms are implemented using Xilinx FPGA device, the simulation and synthesis results are also compared. We use the Xilinx Zed-Board for physical implementations in-the-loop.
Electronic Media and Impact of Advancement in Information Technology

The present study shall discuss and explore the advancement of Information Technology and its usage in electronic media. It will also elaborate the technological advancement, and development has impacted media particularly electronic media including radio, newsreels, television, and film, etc. Information Technology has been influential due to its rapid advancement and progression. It has also reshaped the way information is disseminated on different forms of electronic media. To gauge the impact of advancement in Information Technology on electronic media, a survey method was used and interviews were conducted from IT professionals, journalists students, etc. All forms of information technology have virtually created an impact on society. However, the electronic media industry has taken some time to adopt technological advancements, changes, and development. The emergence of new ways, techniques resultantly increased the viewership, and resultantly transmission of electronic media has gone up dramatically.
ISCAS 2020 CAS Transactions Paper; Random Number Generators Based on Irregular Sampling and Fibonacci-Galois Ring Oscillators

This brief presents a random number generator (RNG) based on irregular sampling of regular waveform method where the irregular signal is obtained by combining Fibonacci-Galois ring oscillators with an XOR gate. The RNG is implemented on a FPGA (field-programmable gate array). The regular waveform generated by the digital clock manager of the FPGA, is sampled at times corresponding to certain number of rising edges of the irregular signal, and the resulting bit stream is subjected to statistical tests of randomness. It is demonstrated that the resulting bit sequence from the proposed RNG satisfies NIST 800-22 test suit and Rabbit and SmallCrush batteries from TestU01 library without any need for post-processing such as Von Neumann or XOR. A comparison between the methods regular sampling of irregular waveform and irregular sampling of regular waveform is given in terms of robustness against external interference. The impact of selection of Fibonacci-Galois polynomials is discussed. Using digital design flow for TSMC 65nm process, an asic implementation of the proposed RNG is given having 1115 gates and 4.811 mW estimated power.
Multiple Factor Authentication as a Security Measure in Credit Card Fraud

Cyber-crime is not a recent crime as it began in the year 1820 and started catching people's attention by the year 2000. Due to the increase in cyber-crime, there is a huge demand for cyber-security, and organizations feel the need to protect themselves from any kind of attack, to keep their image and reputation clear and above all to protect users ' confidential information and sensitive data. People are losing a lot in terms of data, privacy as well as financial. In this paper, we will talk about credit/debit card fraud and see how multiple-factor authentication as a security measure can be helpful to reduce this crime.
Case Study on Arts Teaching and Learning for Adults with Disabilities by Cultural Arts Instructors

본 연구는 성인 장애인 대상 문화 예술 교육 중 6 사례의 미술 교수 학습을 연구대상으로 삼아 문화 예술 교육에 시사점을도출하고자 하였다. 연구 결과로 여섯 개의 범주와 21개의 주제가 도출되었다. 범주와 그에 따른 주제의 의미는 다음과 같다. 첫째, 성인 장애인을 위한 문화 예술 교육의 목표는 예술 향유 이상의 성인 장애인의 건강하고 독립적인 삶을 촉진하고자하였다. 둘째, 성인 장애인에 대해 비장애인의 관점에서 탈피한 학습 기대, 있는 그대로의 장애 수용이 나타났다. 셋째, 사례들은 경험에서 발달한 교수 학습 전략을 사용하였다. 주요 전략은 강사, 그리고 학습자의 역할이 강조되는 교수 학습, 개별화, 재료 탐색 등이다. 넷째, 수업의 결과물에 대한 인식은 결과물 중시와 과정 체험을 중시하는 태도로 나타났다. 다섯째, 규정인원 초과, 과다한 중도·중복장애인, 재료 미비는 수업의 어려움의 요인이었다. 연구는 결과의 시사점과 함께 제언하였다.This study aimed to draw implications for culture and arts education by using 6 cases of art teaching and learning among culture and arts education for adults with disabilities. As a result of the study six categories and 21 subjects were drawn. The meaning of category and related topics are as follows. 1. The goal of arts and cultural education for adults with disabilities was to promote more healthy and independent lives of adults with disabilities. 2. The cases accepted the adults with disabilities as-is and expected learning accordingly. 3. The cases used teaching and learning strategies developed from experience. The main strategies are teaching and learning with emphasis on the role of the instructors, teaching and learning with emphasis on the role of the learner, IEP etc. 4. The perception of the outcome of the class was prepared with an emphasis on outcomes and process experience. 5. The cases commonly had excess participants excessive severe/redundant disabilities. The study was suggested with implications of the results.
Online Testing in Machine Learning Approach for Fall Detection

Robust fall detectors are needed to reduce the time in which a person can receive medical assistance, and mitigate negative effects when a fall occurs. Robustness in fall detection systems is difficult to achieve given that there are still many challenges regarding performance in real conditions. Fall detection systems based on smartphones present good results following a traditional methodology of collecting data, training and evaluating classification models using the same sensors and subjects, yet fail to experiment and succeed in different realistic conditions. In this paper, we propose a methodology to build a solution for fall detection, and online testing changing the sensors and subjects of evaluation in order to provide a more flexible and portable fall detector.
Automatic Detection of Semantic Clusters in Glossaries

To define the services that a software system will provide, in terms of the business process needs, is a rather important task. As a first step, the requirements engineer must deeply understand the peculiarities of the context in which the future software system will run. There have been proposed several approaches to elicit and model such knowledge. The research whose main results are presented in this chapter, was carried out in a process that models all the information acquired in natural language. The advantages of the use of natural language are somehow shadowed by its ambiguity and the way models are arranged. This chapter deals with some techniques developed to visualize hidden information in this sort of models. This is mainly done by means of the use of directed graphs and the finding of clusters on them. This chapter enhances a previous one, by improving the visualization technique and by adding an automatic cluster detection technique.