Reviewerly/exHarmony huggingface dataset:
Kannada Text to Speech Conversion System

The following paper describes the design of a system which does text to speech generation for one of the regional language’s Kannada. The printed document of Kannada text is given as input to the system, the system then converts the document to an image format. Pre-processing is done to stabilize the intensity of the images and clear the artifacts. This process boosts the precision and interpretability of an image. Optical Character Recognition (OCR) is used to unsheathe the segmented characters from a particular image and are matched with the characters that have been stored in the dataset. Once the matched characters are extracted it is stored in a suitable format and then the TTS engine is deployed to convert the saved Kannada characters to a speech format. The obtained speech output corresponds to the characters which are collected after processing the input text.
Platforms for Incivility: Examining Perceptions Across Different Media Formats

This article investigates how the mix of attributes present across different media shapes perceptions of incivility. I argue that certain modalities, particularly the channel and structure of a media platform, facilitate the perception of media as more uncivil even if the content is kept the same. To test this argument, I conduct two survey experiments in which participants are randomly assigned to treatments in which the substantive content and text remains the same but is packaged to mimic different media types. Generally, audio and video increase awareness of incivility cues as well as participants’ evaluations of negative, emotional, and entertaining tone. There are also differences in the extent to which individuals notice incivility on Twitter than on other text-based media platforms. The social media platform is also particularly entertaining in comparison to the other platforms studied. This article demonstrates that media attributes interact to shape our understanding and identification of uncivil language. Furthermore, it suggests that more attention should be focused on identifying the different sets of characteristics that make incivility more or less likely or salient in political media.
The effect of learning condition on memory for and integration of related information

Although we often are tasked with learning pieces of information that are related in some way in educational settings, the learning conditions that promote learning of and connections across related information are still poorly understood. In this thesis, I asked: Which instruction methods promote learning of and connections across (integration of) related information? In the two experiments in this thesis, participants were presented related information in two different formats, and we assessed their memory for related information, in addition to how well they could integrate related information to derive new knowledge. The two presentation formats incorporated the same number of exposures of related information, but the sequence with which information was presented was manipulated: In one presentation format (blocked) participants strongly learn one set of information, before being confronted with a related set of information, whereas participants learn related information in parallel in the other (interleaved). In Experiment 1, we found that blocked presentation enhanced both memory for and integration of related information. However, given potential effects of testing order on our results, we more closely examined memory for related information in Experiment 2. In Experiment 2, we no longer found a difference in overall memory for related information between the two presentation formats. In fact, we found evidence that presence of shared information enhanced learning of related information after interleaved presentation only. Regardless, the results of both experiments demonstrated that manipulating just the sequence with which information is presented, without increasing the number of exposures, can enhance learning, an impactful finding in an era of increased pressures to maximize instructional time.
Ethereum Blockchain based Secure E voting S ystem

The security and accountability issues are a challenge to the traditional structure from still widespread elections. General e-voting system use a centralized system, where one organization manages overall system. These organisations have full control over the database and system, allowing manipulation of the database. There should be no e-voting system to secure data and potential attacks should be able to withstand. Blockchain technology should solve certain voting problems. In this paper we are implementing an ethereum blockchain based electronic voting system. Ethereum blockchain networks are used to transfer money and store data. Networks are organized by one or more machines. Every node is a machine that running an ethereum client. The eligible one can run the node. By adopting blockchain in e-voting system database distribution, one of the cheating sources of database manipulation and data loss can be reduced. This can be a better solution for the currently existing issues over rigging the electronic voting machines to win elections by the political parties in our government.
Bilinear pairings signcryption scheme for user authentication keys in heterogeneous networks

Heterogeneous network user authentication keys are vulnerable to plain text attacks, resulting in poor encryption performance. Therefore, a heterogeneous bilinear pairing signcryption scheme is proposed. The symbol frequency detection method is used to detect symbols of user authentication data, establish an ORK user protocol in a heterogeneous network, and perform a pairwise signcryption scheme to linearly encode user cognitive information in a heterogeneous network. Use Ryption technology to authenticate and re-sign users in heterogeneous networks, and use a bilinear pairing signature encryption scheme to control cipher text in user processes to encrypt identity authentication information in heterogeneous networks. Establish a statistical analysis model to encrypt user authentication information in a heterogeneous network to achieve intelligence. Simulation results show that the method has good scrambling ability and strong anti-attack ability. It is used for bilinear pairing signature encryption of user authentication keys in heterogeneous networks.
DECOMPOSITION

Applications often lead to large-scale optimization problems because of the sheer number of variables and constraints that are needed to model a particular situation and this is also the case for more general variational problems. The presence of unknown parameters tends to increase the problem size further. In fact, we might find that the only viable path forward is to solve a series of smaller subproblems. There are also situations when the data for a problem is distributed among several agents, which are unable or unwilling to share their data despite a common goal of solving the problem.
Introduction

In this book, we dive into the realms of deep learning (DL) and cover several deep learning concepts along with several case studies. These case studies range from image recognition to recommender systems, from art generation to object clustering. Deep learning is part of a broader family of machine learning (ML) methods based on artificial neural networks (ANNs) with representation learning. These neural networks mimic the human brain cells, or neurons, for algorithmic learning, and their learning speed is much faster than human learning speed. Several deep learning methods offer solutions to different types of machine learning problems: (i) supervised learning, (ii) unsupervised learning, (iii) semi-supervised learning, and (iv) reinforcement learning.
A Validation Study for Medical Research Based on Synthetic Hospital Data (Preprint)

<sec> <title>BACKGROUND</title> Privacy restrictions limit access to protected patient-derived health information for research purposes. Consequently, data anonymization is required to allow researchers data access for initial analysis before granting Institutional Review Board approval. A system implemented in our institution enables synthetic data generation that mimics data from real electronic medical records, wherein only fictitious patients are listed. </sec> <sec> <title>OBJECTIVE</title> This paper studies the validity of results obtained when analyzing synthetic data for medical research. A comprehensive validation process concerning meaningful clinical questions and various types of data was conducted to assess the accuracy and precision of statistical estimates derived from synthetic patient data. </sec> <sec> <title>METHODS</title> A cross-hospital project was conducted to validate results obtained from synthetic data produced for five contemporary studies on various topics. For each study, results derived from synthetic data were compared to those based on real data. In addition, repeatedly generated synthetic data sets were used to estimate the bias and stability of results obtained from synthetic data. </sec> <sec> <title>RESULTS</title> This study demonstrated that results derived from synthetic data were predictive of results from real data. When the number of patients was large relative to the number of variables used, highly accurate and strongly consistent results were observed between synthetic and real data. When small populations were accounted for, prediction was of moderate accuracy. </sec> <sec> <title>CONCLUSIONS</title> The use of synthetic data provides a close estimate to real data results and is thus a powerful tool in shaping research hypotheses and accessing estimated analyses, without risking patient privacy. Synthetic data enables broad access to data, including for out-of-organization researchers, and rapid, safe, and repeatable analysis of data in hospitals or other health organizations where patient privacy is a primary value. </sec>
Communication Skills

Communication refers to the act of exchanging information, ideas, needs and desires. Communication plays a central role in human development and behaviour throughout life. Academically, language and/or communication disorders are strongly linked to learning difficulties, particularly in the area of reading and writing. Non-linguistic aspects that contribute to the effect of the spoken message include facial expression, eye contact, gestures, body posture, head and body movement, distance from the listener, manual sign, writing, drawing, or representational symbols. Morphology is concerned with the internal organisation of words. Phonology is the sound system of spoken language. Linguistic competence refers to individuals’ underlying knowledge about this complex system of rules. Speech involves the use of an auditory-articulatory code to represent spoken language. Children have a need to communicate long before they have the ability to use language. In many cultures, including English-speaking ones, there is an expectation that babies will communicate from the earliest age.
Internet Traffic Analysis: MapReduce based Traffic Flow Classification in Hadoop Environment

Internet is the global network that interconnects entities all over the world.This unparalleled network has occupied the mandatory part in the life of every individual.In recent days, due to the increase in the number of flow, the internet traffic is increased.The increasing traffic is flooding with the DDoS flows from multiple DDoS attackers.If DDoS flow traffic enters the internet, then there will be a drastic increase in the utilization of resources.Due to this, the legitimate traffic will not get proper service.In order to address the above issues, this paper has proposed an approach that classifies the internet traffic as Normal traffic flow or DDoS traffic flow.A huge volume of traffic flows is analyzed in this paper and the results are presented.The MapReduce is implemented for the classification as it accurately maps the flow features and reduces them into the appropriate traffic type.The incoming traffic is classified into one of the three categories as Web Traffic, DDoS Traffic (Heavy User) or DDoS Traffic (Spoofed IP).The main objective of this paper is to classify structured as well as unstructured data of IP, TCP, HTTP and NetFlow analysis.The experimental observations were carried out in the Hadoop 2.7.2 environment.The dataset is obtained from Wireshark, which consists of traffic flow based on latest traffic pattern.Hadoop Distributed File System (HDFS) and Map Reduce components of Hadoop are used under the metrics as Work Completion Time, Throughput and Accuracy.
Multi-scale dilated convolutional network for knowledge graph embedding

It aims to learn how to represent the low-dimensional vectors of entities and relations using observed triplets. KGE can benefit a variety of downstream tasks, such as KG completion and triplet classification. Deep models achieve state-of-the-art performance by leveraging the powerful nonlinear fitting ability of neural networks. However, most existing methods ignore multi-scale interaction features between entities and relations except InceptionE, which is hard to train because of high computation costs. In this paper, we propose a new KGE model called MDCE, that uses multi-scale dilated convolution to capture rich interaction features at different scales. Meanwhile, MDCE has lower computation costs than InceptionE. We perform extensive experiments on multiple benchmark datasets; results on the link prediction task show that the proposed model MDCE not only significantly outperforms existing state-of-the-art models but is also efficient and robust.
Peer review declaration

All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single-blind • Describe criteria used by Reviewers when accepting/declining papers. Was there the opportunity to resubmit articles after revisions? Initial scrutiny has been done by checking the plagiarism percentage of the paper in iThenticate. We have maintained this plagiarism rate at 20% excluding reference and author details portion. Once the paper passed in this limit then the paper was sent for technical review. Paper was assigned to minimum 2 reviewers. Based on the decision received from the reviewers, paper was Accepted or Rejected or given Revision. • Conference submission management system : Easychair • Number of submissions received : 93 • Number of submissions sent for review : 93 • Number of submissions accepted : 54 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100) : 58% • Average number of reviews per paper : 2 • Total number of reviewers involved : 20 • Any additional info on review process (i.e. plagiarism check system) : iThenticate is used for plagiarism check • Contact person for queries : Dr. Silvia Liberata Ullo University of Sannio, Benevento, Italy silvullo@unisannio.it
Malaysia International NDT Conference and Exhibition 2018

Preface Organizing conference on a very specialize field in this country is really challenging effort. This fact is also true when organizing the ‘Malaysia International NDT Conference and Exhibition 2018 (MINDTCE’18) on 12 and 13 November 2018. Persuading national and international members of NDT experts to participate and to share their knowledge and experience in such a conference is considered as the biggest challenge that has to be overcome by members of organizing committee. For this reason, when the event was successfully held with an excellent response from the presenters, exhibitors and normal participants, every individual involved on the organization of this event were so relieve and delighted. Thanks and congratulation to all especially members of Steering Committee who has spent days and nights making efforts to ensure that the event executed in the best possible manner. Members of Organizing Committees thanks all presenters who has agreed to have their papers that contain extremely valuable information and data that took years for them to collect and produce. In order to enhance their quality, these papers were edited by a number of national and international experts. The organizers thanks the publisher, IOP Publishing who values these papers qualified to be published in Scopus indexed journals of Material Science and Engineering. We hope this publication add to one more source of rarely published knowledge in the field of NDT that are needed by researchers and practitioners throughout the world in their strive to enhance the role of NDT in creating safer and cleaner work environment for all mankind.
Boltzmann Machines

In this chapter, we will introduce Boltzmann machines, restricted Boltzmann machine, and deep Boltzmann machine. We will generalize our deep neural networks from networks to general graphs, we will use probabilistic graphical models to model the deep learning. Meanwhile, we need to depict functional analysis in mathematics for deep learning.
Aquas PowerFlow Tube Set

Biomedical Safety & Standards: December 15, 2020 - Volume 50 - Issue 22 - p 171 doi: 10.1097/01.BMSAS.0000724964.19691.f0
Improving students’ speaking achievement through the implementation of blended learning using YouTube media at UPT SMAN 3 Empat Lawang

The objectives of this research were to find out the significant improvement of students’ speaking achievement after the implementation of blended learning through YouTube media and to investigate the students’ responses toward it. This research was conducted at UPT SMAN 3 Empat Lawang and XI Science 1 consisting of 36 students was chosen as the sample of this research. This research used One Group Time Series Design of Quasi-Experimental as the research design. A series of pre-test and post-test was conducted to get the findings and answer the research question. The result of pre and post-tests showed that the students’ scores increased with the highest scores came from post-test 3 after the third treatment using YouTube. This result indicated that there was a significant improvement in students’ speaking achievement after the use of blended learning through YouTube media since the significant value is lower than 0.05 (0.00 &lt; 0.05). Besides, this research also used a close-ended questionnaire with 4 scales (strongly agree, agree, disagree, and strongly disagree) to know the students’ responses to the implementation of blended learning through YouTube media in speaking class. The findings showed that the percentage of students’ choices in most items of the questionnaire was categorized as positive. The positive responses support the result of the improvement in students’ speaking achievement and prove the use of blended learning through YouTube is not only help the students to improve but also meet students’ need. In conclusion, the implementation of blended learning through YouTube media in speaking class facilitates students to improve their speaking achievement and satisfied them.
Preface

The 37 th UIT Heat Transfer Conference was organized by the Department of Industrial Engineering at University of Padova (Italy) and held at Centro Linguistico di Ateneo, Padova, on June 24-26, 2019. The annual UIT Conference, which has grown over time, was held in Padova for the first time since the foundation of this conference. The scope of the conference covers a range of many topics in theoretical, numerical and experimental heat transfer and related areas, ranging from energy efficiency to nuclear plants. This time the UIT Conference included an International Symposium on “Refrigerants: heat transfer and applications”. This Symposium was held on June 26, 2019, which was the first World Refrigeration Day, and was organized in collaboration with CNR, Istituto per le Tecnologie della Costruzione. In this conference edition, 99 papers were contributed plus three keynote lectures. The keynote lectures were given by Srinivas Garimella (Georgia Institute of Technology, USA), Alberto Cavallini (Emeritus professor at University of Padova) and Enrico Nobile (University of Trieste). For the Symposium on Refrigerants, invited lectures were given by Pega Hrnjak (University of Illinois at Urbana-Champaign, USA), Bjorn Palm (Royal Institute of Technology, Sweden), Petter Neksa (Norwegian University of Science and Technology, Norway) and José Miguel Corberan (Universidad Politecnica de Valencia, Spain). These proceedings collects two keynote lectures and 58 papers selected from those presented and discussed during the Conference. The conference was an important occasion to stimulate discussion, improve the understanding of heat transfer and related phenomena, present the state of the art of some topics, discuss emerging trends and promote collaborations. A special thank is due to the Organizing and Scientific Committees, to the Sponsors, to the Reviewers of the papers and to all the Participants. Davide Del Col, Luisa Rossetto and Stefano Bortolin - Editors List of Scientific Committee, Organizing Committee and Sponsors are available in this PDF.
System Complexity and the Probability of Flaws in the Post Sarbanes Oxley Era

understand accounting information systems infrastructures and the programs that access our valuable data. Systems that we believe are secure and protecting our data may be opening themselves to various risks caused by the very components that we have added for security purposes. The thousands of lines of code and additional processes we add to create a more secure environment may be leading us down a road of security vulnerabilities because of the added complexity to these systems. Accountants, auditors and business professionals in general should take steps to ensure that their data is secure; not only from the typical computer security risks such as hackers, viruses, natural disasters and theft, but from the risks arising from the system itself where the data resides. With this study, I hope to encourage a more strenuous approach to information security through the prospect of also looking at the implementation of components and complexity as causing flaws in accounting information system applications.