Reviewerly/exHarmony huggingface dataset:
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Written by a team of experienced teachers of Spanish, this textbook is designed to lead the adult beginner to a comprehensive knowledge of Spanish, giving balanced attention to the four key language skills (speaking, listening, reading and writing). It puts language learning into its real-life context, by incorporating authentic materials such as newspaper articles, poems and songs. It contains a learner and a teacher guide and is intended to complement study both inside and outside the classroom, by providing pair and group activities, as well as materials for independent learning. It also includes helpful reference features, such as a guide to grammatical terms, verb tables, vocabulary lists and a pronunciation guide. This extensively updated second edition features extra exercises to support the acquisition of good pronunciation, and is accompanied by a web companion that hosts expansion exercises, activities, solutions and useful links for each unit, as well transcripts, and access to brand new recordings of all the audio examples found in the book.
Vocabulary Lists

Written by a team of experienced teachers of Spanish, this textbook is designed to lead the adult beginner to a comprehensive knowledge of Spanish, giving balanced attention to the four key language skills (speaking, listening, reading and writing). It puts language learning into its real-life context, by incorporating authentic materials such as newspaper articles, poems and songs. It contains a learner and a teacher guide and is intended to complement study both inside and outside the classroom, by providing pair and group activities, as well as materials for independent learning. It also includes helpful reference features, such as a guide to grammatical terms, verb tables, vocabulary lists and a pronunciation guide. This extensively updated second edition features extra exercises to support the acquisition of good pronunciation, and is accompanied by a web companion that hosts expansion exercises, activities, solutions and useful links for each unit, as well transcripts, and access to brand new recordings of all the audio examples found in the book.
Semi-supervised Federated Learning Based Sentiment Analysis Technique Across Geographical Region

With fast globalization, the need for developing models that are suited to global data and not simply localized data is the need of the hour. However, collecting sensitive data globally gives rise to privacy restrictions and concerns. Privacy-preserving machine learning techniques like federated learning can be very effective in tackling the problem of privacy yet building a promising model with comparable accuracy which we have tried to depict in the paper. Additionally, we have discussed an algorithm that automates the labelling of the unlabelled mined tweets from seven different locations. In conclusion, we have provided a pipeline to develop a global model while ensuring the privacy of the data thus ensuring that sensitive and restricted information can be used to build machine learning models as well.
Intelligent Transportation Systems Applications: Safety and Transfer of Big Transport Data

The distributed ledger technology (Blockchain) offers a fast, scalable solution for data tracking and authentication. Implementation of Blockchain is expected to emphasize the use of technology to decrease or eliminate third-party costs, better protect devices and systems’ data, and enhance transparency and security. Blockchain also offers a highly secure platform that enables quicker operation and payments, and more precise data record of transportation vehicles (in all modes). This feature plays a significant role in the supply chain by providing access to shared information, to decrease or eliminate redundant communication and information, avoiding data transmission errors. Therefore, it becomes feasible to spend less time verifying data and more time analysing and managing data, which can improve the quality of the interaction between participants, control or reduce costs, or both. In the collection, analysis, and secure sharing of big data with relevant parties, technological advances and the efficient use of smart transportation systems in urban and rural transportation take priority. Particularly in recent years, the loss of data from hacker attacks or the inability to determine where data is transported demonstrates that Blockchain technology may be used successfully in this field. This paper examines the “Smart Cities Traffic Safety” project, which is one of the largest Intelligent Transportation Systems (ITS) projects in Turkey and is currently implemented by Samsun Metropolitan Municipality. In these ITS-based transportation applications, Blockchain technology is used to protect against cyber-attacks on the data of intelligent signalised intersections, average speed corridors, parking violation detection, and red-light violation detection systems. Additionally, this research focuses on the secure sharing of the transportation Big Data with third parties based on the step-by-step monitoring of data transfer history. In the context of this project, the first step is to propose a framework that is based on the technology of Blockchain. Then, a platform was developed with the objective to enable the authentication, validation, monitoring, and protection of information and to address the emerging challenges in the field of transportation systems.
Advanced Implementation of Robot Vision Functions

In the previous chapter, we have gained an initial understanding of the implementation of the robot's vision functions, and in this chapter, we will explore in depth and implement more advanced vision functions of the robot, such as having the robot recognize and follow its owner's movement, recognize its owner's waving call action from multiple people, recognize and locate objects, recognize faces and genders within the field of view, and recognize handwritten numbers. Some of the functions will be implemented using OpenCV programming and some will require PCL for implementation. These functions are the basis for implementing intelligent service robots and should be mastered with emphasis.
Ensemble Feature Selection for Multi-label Classification: A Rank Aggregation Method

Multi-label classification is an important task in machine learning applications. However, today, these methods have more challenges due to high-dimensional data. Existing methods in the literature have not yet reached an acceptable performance, and as the number of labels in the dataset increases, their performance becomes weaker. Thus providing effective feature selection methods is necessary and is suitable for all data. Ensemble feature selection is also a new approach based on combining the results of several feature selection methods. Ensemble approaches have been used in many single-label applications and have provided adequate results. However, this technique is less considered in multi-label feature selection. For this purpose, in this article, we have presented a method based on an ensemble of feature selection methods. This paper presents an ensemble multi-label feature method using rank aggregation algorithms. Three filter rankers with different structures are utilized to obtain the final ranking. This rank aggregation process is treated like an election where the rankers are assumed to be the voters, and the features are the alternatives. The Weighted Borda Count (WBC) method conducts the election process. Finally, the performance and results obtained by the proposed method are compared with the nine filter-based algorithms used based on six multi-label datasets. Most of the selected datasets have a high number of class labels, and the proposed method has recorded the best classification performance in all these datasets. Also, the results show that this method is not well affected by the adverse effects of the algorithms used.
Query Strategies

In the previous chapter, strategies were discussed to identify potential indexes for a wide variety of tables. That is often only half of the story, though. Once indexes have been created, performance is expected to improve within a database, leading then to the next bottleneck. Unfortunately, coding practices and selectivity can negatively influence the application of indexes to queries. Sometimes how the database and tables are being accessed will prevent the use of some of the most beneficial indexes available.
Adaptive System to Manage User Comfort Preferences and Conflicts at Everyday Environments

Nowadays an actual problem on IoT adaptive systems is to manage user preferences and local actuators specifications. This paper uses a multi agent system to achieve a Adaptive Environment System, that supports interaction between persons and physical spaces, where spaces smartly adapt to their user preferences in a transparent way. This work has been developed using a multi agent system architecture with different features to achieve a solution that reach all the proposed objectives.
Index Analysis

In the previous chapter, we discussed what information should be collected when monitoring indexes. All of that information is necessary for the next process of indexing databases, which is determining which indexes to apply. In this chapter, we will take all the information gathered while monitoring and use it to analyze the state of performance and the value of the existing indexes. The end goal of the index analysis is to build a list of indexes to create, modify, and, potentially, drop from the databases. In some cases, the index analysis will appear to border on art. There are many decisions in which previous performance will be used to anticipate future indexing needs. Ultimately, though, with every change proposed, there will be supporting evidence before and after the indexing solutions to statistically confirm or disprove the value of the index. This helps to ensure that regardless of the complexity of an indexing challenge, it will and always should be more science than art.
Examining Index Contents

With an understanding of how indexes are stored at the physical and logical levels, a deeper view of index storage can be gained by more closely viewing the details and contents of an index.
Towards Highly Performant Context Awareness in the Internet of Things

Context awareness and adaption are an important requirement for data streaming applications in the Internet of Things (IoT). Concept drift arises under changing context and many solutions for drift detection and system adaption have been developed in the past. Even though the computing resources of these approaches are not negligible, performance aspects, e.g. runtime or memory usage and scalability have not been investigated adequately. The goal of this thesis is to fill this gap and to provide a mean for performance investigations of concept drift handling methods and other approaches that are developed in the research field Data Science. Therefore performance benchmarking of state-of-the-art solutions is conducted. Moreover the thesis discusses performance bottlenecks of the approaches and demonstrates possible improvements based on the knowledge gained by leveraging tools and methods from the performance analysis domain. Approaches are then implemented into an IoT application and deployed with stream processing engines for a final evaluation.
Securing Your Fleet

What’s really a threat on an Apple device? That’s often according to who you ask. But in order for Apple devices to be allowed on corporate networks, there’s a few criteria that must be met, and rarely have I seen an auditor who is willing to budge on these requirements. If you disagree that something is necessary, then you should absolutely speak up; however, a second or third effort is really just likely to make them dig into their position and trust you less. And sometimes, they’re right.
Indexing Strategies

Indexing databases is often thought of as an art where the database is the canvas and the indexes are the paints that come together to form a beautiful tapestry of storage and performance. A little color here, a little color there, and paintings will take shape. In much the same way, a clustered index on a table and then a few non-clustered indexes can result in blazingly fast performance as beautiful as any masterpiece. Going a little too abstract or minimalist with indexing might feel good, but the resulting performance will be a reminder that it may not be practical.
Towards Ontology-Based End-to-End Domain-Oriented KBQA System

Knowledge Base Question-Answering (KBQA) systems have a number of benefits over Question-Answering over Text (QAT) systems: the ability to process complex, multi-hop questions and the absence of the need for answers containing texts. However, to develop a KBQA system, a knowledge base (KB) and a dataset for training is required. This fact is a significant drawback in the domain and non-English language conditions. We propose the end-to-end domain-oriented KBQA system concept consisting of two methods: filling in the ontology using weak-supervision methods based on the BERT model and KBQA training methods based on graph data. This approach requires only an ontology, raw texts, and a small amount of labeled data. We also analyze the robustness of the KBQA system in conditions of limited data.
Index Maintenance

Like anything in life, indexes require maintenance. Over time, the performance benefits of indexes can wane or, through data modifications, their sizes and the underlying statistics can drift and bloat. To prevent these issues, indexes must be maintained. Doing so will help ensure that a database will remain a lean, mean query-running machine!
Profiles

A profile is an xml file. This file, when installed on a device, configures the device to act in a certain way. Profiles began back in the iPhone Configuration Utility (the precursor to Apple Configurator) and have since moved to being the way you manage various settings on Apple operating systems like iOS, iPadOS, macOS, and tvOS.
Introduction

Lots of attention in the Ethereum ecosystem is paid to smart contracts: how to write them well, how to design their mechanisms, and how to deploy and manage them safely. These are important tasks, but they only express the responsibilities of one role: the protocol engineer. There are other roles that are equally important, and, in this chapter, we’ll look at these roles and how their relative status may change. Understanding the role of the product engineer, especially, will help frame the rest of the book. We’ll also look at an important principle that motivates much of the subsequent discussion: the Principle of Trust.
Monitoring Indexes

Throughout this book, many topics have been discussed, such as what indexes are, what they do, patterns for building them, and many other aspects for determining how a SQL Server database should be indexed. All of that information is necessary for the final piece in indexing your databases: analyzing databases to determine which indexes are required. The final three chapters in this book will pull together the information needed to implement an indexing methodology.
A Method of Colour-Histogram Matching for Nigerian Paper Currency Notes Classification.

In this paper a new algorithm for classification of three Nigerian paper currency notes, namely 200, 500, and 1000 Naira (N) denominations is presented. The work examines the effectiveness of using only colour histograms to differentiate between the classes or denominations of the three Nigerian paper currency notes. The bin-heights of the histograms of the HSI component images for the paper currencies are used as features while a rule-based classifier designed to take advantage of the changes or variations in the histogram patterns is used to classify the paper currencies into the right denomination class. The algorithm involves the utilization of a simple and effective comparison strategy as opposed to the existing, too-rigid metrics for histogram-comparison used by other authors for color indexing in content-based image retrieval systems. Over a testing data-set of 300 samples, the algorithm achieved an average classification accuracy of 98.66%, and classification accuracies of 100%, 99% and 97% for the N=200, N=500 and N=1000 denominations, respectively. The proposed algorithm does not require extensive preprocessing of the paper-currency images and as such is fast in implementation.
Two Ways to Scare a Gruffalo

This paper applies and extends the results from [22] on agent-update frames and their logic. Several interesting examples of actions for forgery and deception, agent-upgrade and agent-downgrade are considered. Going on from the earlier paper, a second interesting children’s story is modelled using these ideas. A dynamic epistemic logic is defined with all these actions and provided with a complete axiomatization. Decision procedures for satisfiability and model checking follow. A planning-oriented approach is also discussed.
Entity Relationship Extraction Based on Knowledge Graph Knowledge

In this paper, the ontology design of the schema layer of the knowledge graph is carried out, and the design of the RDF database storage scheme based on the existing knowledge graph is completed. Meanwhile, the named entity recognition and relationship extraction techniques are used to identify the entity pairs from the novel corpus through the idea of remote supervision and extract the knowledge triads from the sentences and add them to the knowledge graph to finally complete the construction of the knowledge graph of novel character relationships.
Transactions

Ethereum is both a platform and a protocol: it is a place where something (accounts, code, state) is hosted and a set of rules for communicating between those things. Smart contracts are to Ethereum the platform as transactions are to Ethereum the protocol.
Decentralization

By now, we’ve seen how Ethereum’s idiosyncratic execution model presents challenges for people trying to build products. A lot of these idiosyncrasies come from the decentralized nature of the Ethereum blockchain. And a lot of these idiosyncrasies do not serve the best interests of our companies, our products, and most importantly our customers. We need to rethink what decentralization means in practice, face some harsh truths, and be more flexible and open to centralization where it is suitable and useful and aligned with our goals. In this chapter, we’ll step away from the technical focus of previous chapters and instead consider how decentralization affects building with Ethereum.
Relations among elementary school preservice teachers' teaching beliefs, student understanding competencies, teaching competencies, teacher development levels, and future teacher job competencies

본 연구는 초등 예비교사의 교직신념, 학생이해역량, 수업역량, 교사발달수준 및 미래교사직무역량 간 관계를 살펴보기 위해 수행되었다. 구조방정식을 통한 매개모형 검증 결과 첫째, 교직신념은 수업역량, 교사발달수준에 정적 영향을 미치는 것으로 나타났고, 학생이해역량도 수업역량, 교사발달수준에 정적 영향을 미치는 것으로 나타났다. 또한 수업역량은 교사발달수준에, 교사발달수준은 미래교사직무역량에 유의한 정적 영향을 미치는 것으로 나타났다. 둘째, 예비교사의 교직신념과 미래교사직무역량 간 관계에서 수업역량과 교사발달수준의 순차적 매개효과, 학생이해역량과 미래교사직무역량 간 관계에서 수업역량과 교사발달수준의 순차적 매개효과가 나타났다. 본 연구는 초등 예비교사의 개인내적 특성과 관련 역량 간 관계를 구조적으로 파악함으로써 미래직무역량 향상을 위한 방안을 제시하였다는 점에서 의의가 크다. 연구결과를 토대로 시사점과 제언이 제시되었다.This study was conducted to examine the relationship among teaching beliefs, student understanding competencies, teaching competencies, teacher developmental levels, and future teacher job competencies of elementary school preservice teachers. As a result of verifying the mediation model through the structural equation, first, it was found that teaching beliefs have a positive effect on teaching competency and teacher development level. In addition, it was found that student understanding competency also had a positive effect on teaching competency and teacher development level. Also, it was found that teaching competency had a significant positive effect on teacher development level, and teacher development level had a significant positive effect on future teacher job competency. Second, in the relationship between preservice teachers' teaching beliefs and future teaching competency, the sequential mediating effect of teaching competency and teacher development level was found. In addition, in the relationship between student understanding competency and future teacher job competency, there was a sequential mediating effect of teaching competency and teacher development level. The significance of this study is that it suggests a plan to improve future job competency by structurally identifying the relationship between the individual characteristics and related competencies of preservice elementary school teachers.
Turn-taking analysis of small group collaboration in an engineering discussion classroom

This preliminary study focuses on using voice activity detection (VAD) algorithms to extract turn information of small group work detected from recorded individual audio stream data from undergraduate engineering discussion sections. Video data along with audio were manually coded for collaborative behavior of students and teacher-student interaction. We found that individual audio data can be used to obtain features that can describe group work in noisy classrooms. We observed patterns in student turn taking and talk duration during various sections of the classroom which matched with the video coded data. Results show that high quality individual audio data can be effective in describing collaborative processes that occurs in the classroom. Future directions on using prosodic features and implications on how we can conceptualize collaborative group work using audio data are discussed.