Reviewerly/exHarmony huggingface dataset:
Improving Speaking Skills: Development Of Speaking Models In Semester II Students Department Of Indonesian Language And Literature Education FBS UNIMA

The problem with this research is that the second semester students of the Indonesian Language and Literature Education Department are not yet skilled at speaking. The teaching methods provided have not been able to solve the problem. Therefore a learning model is developed which aims to improve speaking skills. The purpose of this study is to describe what efforts can be made to improve the speaking skills of second semester students of the Indonesian Language and Literature Education Department (2018). To describe what learning model can improve the speaking skills of the second semester students of the Indonesian Language and Literature Education Department (2018). The method used in this research is the R&amp;D (Research and Development) method. Of the six parallel classes, the test is only applied to one class because there is no difference in character between one class and another class. The number of students subject to test is 35 people. Quantitative data will be processed using percentage techniques. The value achieved in the pretest before using the model will be compared with the value achieved at the posttest that is after using the model. The results showed that students were ‘quite skilled’ in speaking because the average grade obtained was 7.3. Judging from the aspects assessed, the logical aspect of the proposition, the average grade obtained by students is 8.6. For aspects of text development, the average value obtained is 6.4. For the cohesiveness aspect, the average grade obtained was 8.4. While the aspect of intonation / accent, the average grade obtained is 6.5. It is clear that guided training techniques have not been able to maximize the speaking skills of second semester students, especially the development of texts and intonation / accent. Although the results of the study show that speaking skills have not been maximally achieved by students because they are still below the expected average value (80%), it does not mean that the application of guided training techniques cannot improve students 'speaking skills because the results of the pretest carried out indicate that students' speaking skills are still under the value which is 6.
Self-adaptive process optimisation method for SBS cloud application based on reinforcement learning

To solve the problem of poor comprehensive performance of the traditional SBS cloud application adaptive process optimisation method, a new SBS cloud application adaptive process optimisation method based on reinforcement learning was proposed. Establish the adaptive action type selection model, realise the optimal choice of operation type, build the cloud application adaptive process optimisation model for resource cost, convert the problem into the corresponding mathematical model, solve and make the mathematical model of the algorithm, and obtain the best adaptive process optimisation scheme SBS cloud application. The simulation results show that the predicted load value of the method is the closest to the actual load value, the relative error of the prediction is less than 21.03, and the average time is less than 2.3 s, indicating that the method has good performance and high practical application value.
Introduction

A complementary way of dealing with cyber risks through risk transfer is emerging. This involves the use of cyber insurance products, which have been introduced in recent years by companies like AXA, Generali, or Allianz. The growing cyber threat landscape, coupled with the shortcomings of current Cybersecurity Risk Management frameworks and the unrealised potential of cyber insurance for risk management, underscore the need for new cybersecurity risk management approaches. The cybersecurity portfolio includes security controls, which are put in place by the organisation and consist of measures to prevent, protect against, and counter cyber attacks, including threat detection and response. Cyber insurance products are focused on commercial business at present. They can be offered as a standalone product or added on to an existing policy as part of a package. Insurers face a multitude of challenges—many stemming from the difficulty of accurately assessing cybersecurity risk—that inhibit the development and accurate pricing of cyber insurance products.
Model of the state of threats to the Access Control System

This article is devoted to the presentation of the threat state model of access control, which allows calculating the probabilities of the impact of threats on the access control system and the probability of opening this system based on taking into account the generalized algorithm for the implementation of external threats, and determines the need to develop additional components of the access control system designed to identify and classify attacks.
Creating a Stand-Alone Web App, Part 2

In this chapter, I complete the stand-alone web application and prepare it for deployment, demonstrating the way that a TypeScript project dovetails with standard development processes for deployment. For quick reference, Table 16-1 lists the TypeScript compiler options used in this chapter.
Optimum design for an incomplete second degree mixture model

Mixture experiments form an important part of research in areas like pharmaceutical, biometrics, agriculture, etc. Optimum mixture designs have been derived by many authors for mixture models due to Scheffé (1958) and others. In most of these models, there is no discrimination among the components. However, in practice, the situation may be quite different. In this paper, we have considered a situation where some but not all of the interaction terms are present. Optimum designs have been determined for the estimation of parameters of a second degree model. Finally, optimum designs for prediction have also been considered.
Using Navier–Stokes modeling to design a better recorder

The recorder family consists of several instruments of varying musical compasses. A musical tone is established by blowing into the mouthpiece of the instrument and a standing pressure wave is formed in the resonator of the instrument. Blowing harder into the instrument can cause a transition from the original (lower frequency) note to a higher (frequency) note. This transition is often referred to as “regime-change.” Recorder players have told us that regime-change in the bass recorder can happen at significantly lower blowing speeds for notes at the lower end of its musical compass. In this talk, regime-change is studied using Navier–Stokes based modeling in simplified models of sopranino and bass recorders. We show how the geometry beneath the labium of the recorder can be modified in order to alter regime-change behavior and extend the blowing range of the lowest notes in the bass recorder. In addition, these computational results are verified through experimental studies using 3D printed recorders and dimensions inspired by the modeling results.
A blockchain-based IoT trust model

The Internet of Things (IoT) is a heterogeneous network of interconnected objects or ‘things’ that are typically connected via the Internet. Trust in most IoT networks is presumed implicitly. This implicit trust assumption can be abused by adversaries to disrupt the network and manipulate reputations of trusted devices. To tackle IoT trust issues, we use permissioned blockchains that utilize Smart Contracts (executable policies) to evaluate and refine IoT devices’ trust. Blockchains replicate a permanent append-only record of all transactions occurring on a network on multiple devices. This prevents adversaries from modifying previous transactions to influence trust evaluations. In this thesis, we propose an IoT trust model that uses Blockchains to record and validate IoT devices’ identities and dynamically evaluates the trustworthiness of devices in the IoT network. Moreover, our model allows for different levels of security based on the sensitivity of data being transmitted across the IoT network.
The Influence of Stable Methodologies on Cyber Informatics

Lately, much research has been given to the blend of virtual machines; all things considered, few have examined the investigation of intrudes. Given the current status of homogeneous calculations, steganographers strongly want DHTs to be understood, encapsulating the multi-sided performance hypothesis structured norms. In this work we negate that while operators and the lookaside support are normally contrary, fortification learning and the Ethernet can synchronize to understand this point
Prime Generation: Algorithms and Analyses

In the era of fourth industrial revolution or Industry 4.0, Computational Intelligence, Data Science and smart Information and Communication technology (ICT) are gaining huge importance in our society.Governments around the world started relying heavily on information and communication technologies to build smart and hyper-connected infrastructures that allow cities to provide better services to people and reduce energy consumption, as the global urban population is growing substantially.These intelligent technologies allow cities to introduce new ways of monitoring the atmosphere, buildings, street lighting, traffic, crowds, crime, etc.In building a smarter and more intelligent city around the world, Computational intelligence and ICT are the underlying technologies; but if not wisely applied, ICT can be a major environmental problem.At present, about 2 percent of global greenhouse gas (GHG) emissions are accounted for by the global ICT industry.This footprint is expected to increase dramatically to about 14 percent by 2040, according to a recent report.Intelligent use of advances in ICT will assist in minimizing GHG while still achieving its goals.ICT is theoretically able to reduce the carbon footprint in other fields by a factor of 10, based on the Global e-Sustainability Initiative (GeSI) report.ICT technologies such as Green ICT, the Internet of Things (IoT) and Artificial Intelligence (AI) can play important roles, not just in making our environment smarter, but also greener and more sustainable.
A Hybrid Method to Shorten Congestion and Implement Data Guarantee in Cloud Computing

Distributed computing is used any place in light of the way that it gives on solicitation access of advantages and reduces cost, it offers dynamic task of benefits for guaranteed and trustworthy organizations. Customers store their data on a single virtual server, when customer needs to get to any data that data might be changed or balanced by unapproved people for malevolent reason since customer's don't have organize control of data So security is a noteworthy test for dispersed registering, to improve the immovable nature of organizations it is imperative to assemble the security level in the cloud where the customer should free from dependability, approval, rightness or protection. In this paper, I proposed another system for blockage control and data security in circulated figuring. Various makers have given their considerations on data security in cloud anyway no one gives the full control to the customer. This methodology control stop up by diminishing the proportion of data. In the present system cloud pro center uses weight strategy to diminish the degree of data after that scramble data that fabricates the proportion of ciphertext interestingly with compacted data. Another encryption framework is used to encode the pressed data that does not assemble the range of ciphertext. There are two rule ideal conditions of this methodology (I) it doesn't fabricate the range of ciphertext connection with existing strategy and (ii) reduce the blockage among server and customer by speedy transmission. In case we decline the range of data then data would be traded among customer and server in less proportion of time so for this circumstance this technique controls the blockage among customer and server.
Man City toasts Premiership win with beer made from stadium rainwater

To celebrate Manchester City's Premier League title win, Xylem Inc has teamed up with the football club and Heineken Manchester to produce ‘Raining Champions’, a limited edition beer made with purified rainwater collected from the roof of the Etihad Stadium.
Cybersecurity 101

Before we can begin to discuss security, we really have to define some key computer terms and concepts. You do not have to memorize this stuff, and it’s okay if you don’t follow everything here. There’s a glossary at the end of this book that you can refer to for quick help, or you can return here if you want to refresh your memory. But for the rest of this book to make sense, I need to get you up to speed on the basics of how computers and the Internet work. I’m trying to cover all the bases here, so if you see a topic you already understand, feel free to skip it or just skim it. I’ve also taken the liberty of throwing in some fun little tidbits that will help to keep things interesting. There will be a wide range of people reading this book, and I just can’t take the time to fully explain everything. But in this chapter, I give you a solid base to work from.
SportsStore: A Real Application

In Chapter 2 , I built a quick and simple Angular application. Small and focused examples allow me to demonstrate specific Angular features, but they can lack context. To help overcome this problem, I am going to create a simple but realistic e-commerce application.
Using Service Providers

In the previous chapter, I introduced services and explained how they are distributed using dependency injection. When using dependency injection, the objects that are used to resolve dependencies are created by service providers, known more commonly as providers. In this chapter, I explain how providers work, describe the different types of providers available, and demonstrate how providers can be created in different parts of the application to change the way that services behave. Table 20-1 puts providers in context.
Laptop Assistant (Ubuntu) using Python

AI Publications is an open access peer review international journal to publish the article in the field of Agriculture, Horticulture, Food science, Rural Development, Environment and Health Research, Chemistry, Mathematics,Physics.
A Real Time Virtual Dressing Room Application using Opencv

The real time clothes trying having long waiting queues for trial rooms is a problem faced at many places and store. In this system, by using real time system cloth processing is done by data drive approach which is worn by human. To give exact look to skeleton, by using height, skin color, it starts creation of clone person which is prior to real-time simulation. We use hardware sensors like motion, light, camera sensors which are controlled by using GUI (Graphical User Interface) software. Hardware uses latest depth camera of Kinect Sensing element along Unity SDK. We use operating system which can communicate with the user friendly software which should manage the controllers. This proposed approach can offer good GUI which is user friendly to end user and also to retailer. Because of this user friendly system, it should increase the level of marketing more than current system. Proposed system should provide not only good solution for dressing but also can solve the issues which are related to retailer and end user.
Scheduling communication-intensive applications on Mesos

In recent years, the widespread use of container technologies has significantly altered the interactions between cloud service providers and their customers when developing and offering services. The shift away from Virtual Private Server scenarios in Infrastructure-as-a-Service environments requires drastic changes to the deployment strategies adopted by service providers. This also opens many questions to what information must be supplied by customers and how to improve the performance of user applications, especially in the case of communication-intensive applications. In this work, the authors propose the adoption of a new framework for Mesos clusters that aims to improve the deployment strategies of communication intensive applications. Coope4M is based on the partitioning of the user application graph via the Isolation Index parameter obtained through user-knowledge on the degree of the communication between its components.
Scanning the Issue

Remote sensing has evolved into a multidisciplinary field involving many different areas such as sensor technology, computing, and advanced applications. Information extraction now plays a fundamental role in the exploitation of the massive amount of data collected by earth observation instruments. In this Point of View, the authors analyze the evolution of this field, identifying three main phases in its development. The first period, which was marked by advances in digital signal processing, led to a significant development of statistical processing methods. The second phase was based on advances in physical models and brought an era of quantitative remote sensing which lasted until the first decade of this century. In the third and current period, information extraction techniques are gradually adopting advanced artificial intelligence models in an effort to cope with the tremendous increase in data volume. This article describes some of these recent advances and addresses challenges caused by the 4Vs (volume, velocity, variety, and veracity) of big data. Finally, the authors offer insight into future directions in this multidisciplinary field.
R Programming

In this last chapter, we are going to go over the basic concepts that you need to know to do R programming. This tutorial is in no way comprehensive or meant to be your first experience with programming. However, if you have programmed before, this should provide you with enough to get started in R. Readers that are completely new to programming may want to consider taking an intensive course on this subject perhaps with Data Camp or Coursera.
Secure Cloud Data Audit using Protocol and Digital Signature Techniques

Cloud computing is one of the important business models in the modern Information Technology. It provides various services (hardware, software) to the users with minimal interaction and low-cost. Storage service is one of the most useful services in cloud computing, which move data owners data from local computing system to the cloud. In this paradigm, once the data moves from the local computing system to the cloud, the data owner lost the physical control of the outsourced data on the cloud. So that, storage service creates data security challenges. Therefore, the integrity of the outsourced data has to be verified frequently using public or private verification method. In this paper we focus on two data security concern such as data confidentiality and remote data integrity on cloud storage system. In order to ensure the data integrity and reduce the data owners computational resources, in this work we have proposed a remote data integrity auditing methods such as Remote Data Audit using Protocol(RDAP) and Remote Data Audit using Digital Signature (RDADS) methods. To analyze the performance of the system, first, we define the single data owner on multiple servers and then multiple data owners on a single server for public data verification. Besides, these methods not only verify the integrity of data, but also detect the invalid data block during the verification process.
#ThinkTwice: Social Media Continues to Vex Executives

Within the past year, there has been an increasing frequency of cases involving executives misusing social media during union activity. As recently addressed in Management Report , expressions of threats or suggestions of retaliation by company executives in social media posts can be unlawful and, further, attributable to the company.
User-Managed Backup and Recovery

All DBAs should know how to back up a database. Even more critical, a DBA must be able to restore and recover a database. When media failures occur, everybody looks to the DBA to get the database up and running. There are two common, yet very different, Oracle approaches for backup and recovery:
Putting Angular in Context

In this chapter, I put Angular in context within the world of web app development and set the foundation for the chapters that follow. The goal of Angular is to bring the tools and capabilities that have been available only for server-side development to the web client and, in doing so, make it easier to develop, test, and maintain rich and complex web applications.
Solving the Imbalanced Class Problem in Software Defect Prediction using GANS

Prediction of software defects is a highly researched and important domain for cost - saving advantage in software development. Different methods of classification using attributes of static code were used to predict defects in software.However, the defective instances count is very minimal compared to the count of non - defective instances and this leads to imbalanced data, where the ratio of data class is not equal. For such data, conventional machine learning techniques give poor results.While there are different strategies to address this issue, normal oversampling methods are different versions of the SMOTE algorithm, These approaches are based on local information,instead of the complete distribution of minority class.GANs is used to approximate the true data distribution of minority class data used for software defect prediction.
Optimal Bayesian Transfer Learning

The theory of optimal Bayesian classification assumes that the sample data come from the unknown true feature-label distribution, which is a standard assumption in classification theory. When data from the true feature-label distribution are limited, it is possible to use data from a related feature-label distribution. This is the basic idea behind transfer learning, where data from a source domain are used to augment data from a target domain, which may follow a different feature-label distribution (Pan and Yang, 2010; Weiss et al., 2016). The key issue is to quantify relatedness, which means providing a rigorous mathematical framework to characterize transferability. This can be achieved by extending the OBC framework so that transfer learning from the source to target domain is via a joint prior distribution for the model parameters of the feature-label distributions of the two domains (Karbalayghareh et al., 2018b). In this way, the posterior distribution of the target model parameters can be updated via the joint prior probability distribution function in conjunction with the source and target data.
Dritter Teil: Erfahrungen und Erlebnisse der deutschen LSRM- und RF-Fellows von der Ausreise bis zur Rückkehr

No AccessDritter Teil: Erfahrungen und Erlebnisse der deutschen LSRM- und RF-Fellows von der Ausreise bis zur Rückkehrhttps://doi.org/10.7788/9783412514884.461SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous chapter Next chapter FiguresReferencesRelatedDetails Download book coverIndustrielle WeltVolume 97 1. AuflageISBN: 978-3-412-51486-0 eISBN: 978-3-412-51488-4HistoryPublished online:June 2019 PDF download