Reviewerly/exHarmony huggingface dataset:
Convolutional recurrent neural network with attention for Vietnamese speech to text problem in the operating room

We introduce automatic Vietnamese speech recognition (ASR) system for converting Vietnamese speech to text on a real operating room ambient noise recorded during liver surgery. First, we propose applying a combination between convolutional neural network (CNN) and bidirectional long short-term memory (BLSTM) for investigating local speech feature learning, sequence modelling, and transcription for speech recognition. We also extend the CNN-LSTM framework with an attention mechanism to decode the frames into a sequence of words. The CNN, LSTM and attention models are combining into a unified architecture. In addition, we combine connectionist temporal classification (CTC) and attention's loss functions in training phase. The length of the output label sequence from CTC is applied to the attention-based decoder predictions to make the final label sequence. This process helps to decrease irregular alignments and make speedup of the label sequence estimation during training and inference, instead of only relying on the data-driven attention-based encoder-decoder for estimating the label sequence in long sentences. The proposed system is evaluated using a real operating room database. The results show that our method significantly enhances the performance of the ASR system. We find that our approach provides a 13.05% in WER and outperforms standard methods.
Using Graphic Organizers (GOs) for Developing EFL Critical Reading Skills among First Year Secondary Stage Students

The present study was carried out to develop EFL critical reading skills among first year secondary stage students through using graphic organizers.A quasi-experimental design was adopted, using an experimental group and a control one.Forty-eight students from AL-Shaheed Muhammad Ibrahim Al-Baqash Secondary School, Diarb-Negm Directorate, Sharkia, Egypt, were selected and divided into two groups; an experimental group (n=24) and a control one (n=24).A critical reading questionnaire and a pre-post critical reading test were used as instruments of the study.The researcher implemented the Graphic organizers on the experimental group while the control group was taught using the regular method.The current study was conducted through the second term of the academic year 2019-2020.Finally, the results of the study proved that Graphic organizers was effective in developing the EFL critical reading skills of first year secondary stage students.
Object Detection with Voice Sensor and Cartoonizing the Image

Object detection is a general term to describe a collection of related computer vision tasks that involve activities like identifying objects in digital photographs, identifying objects in live captured images.Object detection combines these two tasks and localizes and classifies one or more objects in an image.Object localization refers to identifying the location of one or more objects in an image and drawing abounding box around their extent.Image classification involves predicting the class of one object in an image.In this application SAPI.spVoice is used inorder to add voice.Voice sensor is used especially for the people who cannot see objects in a particular image.We present YOLO, a new approach to object detection.YOLO, is a technique for object recognition designed for speed and real-time use.YOLO model processes images in real-time at 45 frames per second.A smaller version of the network, Fast YOLO, processes an astounding 155 frames per second.Cartoonizing an image will transforms the image into a cartoon image.Today we can find countless numbers of photo editing applications on the internet that allow us to transforms images into cartoons on the internet.It's similar to BEAUTIFY or AI effect in cameras of modern mobile phones.It can be taken as smoothening of an image to an extent.It makes an image look vicious and like water paint, removing the roughness in colors.So, this application will allow us to detect and identify the objects in an image along with voice sensor which converts annotated text to speech and transforms an image into a cartoon image without using any external tool.
Pembangunan Dashboard untuk Mendukung Analisis Kartu Rencana Studi dan Kartu Hasil Studi Mahasiswa

At the beginning of every semester, students register for their classes resulting in KRS (student study plan) and at the end of the semester, they will receive KHS (academic transcript). KRS and KHS are recorded into the university’s system to be used for different kinds of analysis including strategic planning and accreditation. The purpose of this research is to create a dashboard to visualize data from KRS and KHS based on several Key Indicator Performance (KPI) using goal-directed design method. Performance metrics method is used to evaluate the user interface of the dashboard with 71% binary success. User Experience Questionnaire (UEQ) is also used to evaluate user experience showing scores of 1.96, 1.93, 1.77, 1.88 and 1.86 for attraction, stimulation, novelty, clarity and efficiency, respectively. These scores can be translated using the Comparison to Benchmark Scale table which shows good for both clarity and efficiency, and excellent for attraction, stimulation and novelty.
Topic Modelling

In the history of information and technology the knowledge which was generated is stored in the form of digital technology. In present day the search engines will search based on terms and extract the list of similar documents from many topics. In this paper, the proposed Topic Modelling techniques will search based on the group of words from each document. The aim behind proposed topic modelling techniques is to comprise the topics from each of the document. The hidden topics from the list of collected text documents can be extracted using proposed probabilistic topic modelling.
The Slice Filtration and Slice Spectral Sequence

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A Corpus-based Appraisal of Doubts and Certitudes in Cameroon English Newspaper Writing: Attitudes and Prospects

Newspapers constitute an important medium of informational dispersal, especially in postcolonial multilingual Cameroon.Its language has direct implications on Cameroonians' interpretations and appreciations of events in their environments.Consequently, degree of truthfulness is extremely vital in news stories, in order to regulate facts, based on what is doubtful and what is certain, for purposes of civil order and serenity.In this paper, I investigated the effects of personal metadiscourse markers_ hedges and boosters_ in Cameroonian online newspaper writing and on readership.A corpus of 19 randomly selected inciting stories, from 9 leading newspapers in Cameroon, constituted the primary data.In addition, an interview was conducted for purposes of ascertaining authorship and readership.The corpus was subjected to the 2014 AntConc 3.4.4.w.software to obtain the frequencies, concordances and functions of pre-identified hedges and boosters.The findings revealed that Cameroon English newspapers are more likely to boost claims than hedge them and that such claims have significant effects on the Anglophone Cameroonians' interpretation and appreciation of events in the country.
A secure and reliable method to protect usb data

With technology advancement people have started using different type of memory devices for storing dataand keeping it secure has become concern in today’s world. Universal Serial Bus (USB) flash drives are leadingportable storage device for storage and easy transfer of data from one computer to another. The usage of USB hasgrown exponentially and without security the data on the disk is at risk. Nowadays USB manufacturers offer passwordprotection and fingerprint authentication to secure the USB data. In this paper, USB is devised as a highly securedportable boot medium with fingerprint authentication to secure the data.
Intake

OpflowVolume 47, Issue 6 p. 2-2 Departments Intake First published: 08 July 2021 https://doi.org/10.1002/opfl.1553Read 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 onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume47, Issue6July/August 2021Pages 2-2 RelatedInformation
Customizing Git

Git is an engineer’s tool, built by engineers. This means that while Git works a certain way out of the box, the real power is unleashed when we start customizing Git to match our way of working. With Git, we can do a lot in terms of simple configurations, creating shortcuts for the tasks that we often use, or have repository-specific configurations to help us manage the different contexts in which we work.
On the estimation of coefficients of irreducible factors of polynomials over a field of formal power series in nonzero characteristic

We discuss some problems and results related to the Newton-Puiseux algorithm and its generalization for nonzero characteristic obtained by the author earlier. A new method is suggested for obtaining effective estimations of the roots of a polynomial in the field of fraction-power series in arbitrary characteristic.
Innovation Teaching Practice Based on Collaborative Tabu Optimization under the Network

The innovative education is based on the development of innovative thinking and the training of innovative talents as the basic value orientation.It is necessary to recognize the problems encountered in innovative education, explore new ways and methods of innovative education with new ideas, and strive to implement innovative education in teaching.Tabu search algorithm is a combined optimization algorithm and an extension of local search algorithm.It is a successful application of artificial intelligence in combinatorial optimization algorithm, which is characterized by the use of tabu techniques.The taboo in the real sense is the prohibition of duplication of the previous work.Tabu search algorithm uses a tabu table to record the local best points which have arrived.In the next search, tabu list information is used to search these points no longer or selectively.In the course of teaching, the students' innovative ability is constantly improved so the comprehensive learning ability of the students will be improved.
Thoreau’s Extra-vagant Sublime and the Milder Majesty of Nature

In “Thoreau’s Extra-vagant Sublime and the Milder Majesty of Nature,” Ronald Wesley Hoag revisits Thoreau’s Ktaadn epiphany, which remains a Gordian knot to many scholars and readers. Hoag broadens and deepens insights first presented in his landmark 1982 essay on Thoreau’s peak experience on the high tablelands of Mount Ktaadn, “The Mark on the Wilderness: Thoreau’s Contact with Ktaadn.” Here, Hoag’s intent is to contextualize Thoreau’s understanding of the sublime in wider arcs, to include not only rugged mountain plateaus but also cultural and pastoral landscapes such as those of Thoreau’s native Concord. Marshalling evidence from the full spectrum of Thoreau’s writings, including his correspondence, college essays, and Journal, Hoag argues that Thoreau’s evocations of a harsher and unsettling sublime were always tempered by milder understandings of the concept—that, to Thoreau, not only distant peaks but familiar gardens, when properly perceived, generate awe and astonishment.
Chapter 15: Subspace Clustering

Recently, subspace clustering has aroused great interest in researchers in the database community due to the new challenges associated with the high dimensionality of data sets in modern science and technology.
MEMETIC PROGRAMMING WITH THE ATOMIC REPRESENTATION FOR EXTRACTING LOGICAL CLASSIFICATION RULES

Classification is one of the most popular techniques of data mining.This paper presents an evolutionary approach for designing classifiers for two-class classification problems using an enhanced version of the genetic programming (GP) algorithm, called the Memetic Programming (MP) algorithm.MP can discover relationships between observed data and express them logically.MP aims to obtain a classifier with the largest area under the ROC curve, which has been proved a better performance than traditionally metrics.The proposed approach is being demonstrated by experimenting on some UCI Machine Learning data sets.Results obtained in these experiments reflect the efficiency of the proposed algorithm.
Error correction method of enterprise product cost accounting based on machine learning algorithm

In order to solve the problems of large error correction result and long-time consumption in traditional cost accounting methods, an error correction method of enterprise product cost accounting based on machine learning algorithm is proposed. By analysing the specific cost chain and accounting error sources of enterprise product production, the influence of uncontrollable factors on accounting error is preliminarily avoided. On this basis, the total error of cost accounting is determined by constructing error measurement model. Finally, the optimal solution of error calculation is obtained by using the support vector machine concept in machine learning algorithm, so as to realise error correction. The experimental results show that the correction time consumption of the proposed method is short, the accuracy is high, and the memory space is small, which indicates that the method has a certain application value and can be widely used in the field of enterprise cost accounting.
Improving Data Spillage in Multi Cloud Capacity Administrations

Multi copy Dynamic information possession in distributed computing be able to to put missing information in dynamic methodology to the cloud server. Multi copy means, information to be imitated in different servers. The undertaking proprietor transfers the information into cloud server and the information is duplicated, then that photocopies are place away in several servers. The information is stored in multiple servers in order to avoid data loss due to vulnerabilities like hacking or server crash. We presented a new strategy that is, Fully Homo morphic Encryption (FHE) algorithm for taking multiple copies of information. The FHE algorithm is used to enhance security to the information stored in the servers. When the data proprietor uploads the file, the FHE algorithm splits the file and takes multiple copies of the file. These copies are zipped in order to decrease memory size and are stored in multiple servers. The stored files are encrypted to provide maximum security. The FHE algorithm provides keygen, copygen and taggen, using these keys the data can be decrypted and retrieved.
Introduction

The fourth industrial revolution has emerged through the advancement of new technologies, innovative services, and modern business models, which often rely on the use and re-use of copyright-protected content. Although having the potential to enhance public welfare, these technologies and services challenge the limits of copyright law, especially in the European Union where the approach to defensive rules lacks flexibility. Under EU copyright law, exclusive rights are drafted in broad terms and with a high degree of generality, whereas the so-called exceptions and limitations to copyright are narrowly drafted and strictly interpreted, with the result that the breadth of permissible use is rather narrow. Because the fourth industrial revolution promises innovation and business growth—stated objectives of EU copyright—it invites an examination of defensive rules as a whole. The book adopts a holistic approach in its exploration of the limits of permissibility under EU copyright, including legislatively mentioned exceptions and limitations, doctrinal principles, and rules external to copyright, with a view to unveiling possible gaps and overlaps, offering a novel classification of defensive rules, and evaluating the adaptability of the law towards technological change. In this light, the work attempts to offer a measure of conceptual organization for defences to copyright infringement that may foster the development of a fresh understanding on how defensive rules against copyright infringement operate as a system; how they unveil their normative force; where instances of gaps or overlaps exist between defences; and how defences should be developed in light of future law reform or possible interpretative expansion.
DISCOVERING NEW MAPS FOR EXPLORING THE FUTURE OF WORK

Leader to LeaderVolume 2021, Issue 100 p. 56-57 FROM THE FRONT LINES DISCOVERING NEW MAPS FOR EXPLORING THE FUTURE OF WORK First published: 18 June 2021 https://doi.org/10.1002/ltl.20569Read 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 onEmailFacebookTwitterLinked InRedditWechat Volume2021, Issue100Spring 2021Pages 56-57 RelatedInformation
Improving SQL Query Response Time thru Client Side Processing in Client-Server Environment

Queries executed by a client in the database server were profiled, managed and reused to respond to future subdued queries to be executed in the client.This technique not only reduced the number of queries to be processed by the database and the server but also contributes in decreasing the utilization of network, database and server resources because future subdued queries to be executed that are subdued from the previous executed query were responded locally.Conditions in the query were removed before sending to the database for evaluation in order to increase its effectiveness for its intended purpose.Profiled queries that are subdued by incoming query were purged including its corresponding result set while the incoming query was profiled in the repository.This was implemented as a technique to avoid storing redundant data in the repository as well as to avoid query capability duplication.Tests showed that utilization of a local repository of previous executed queries to respond to a subdued requested query decreased the latency incurred in fetching data both in small, medium and large number of records as compared to a requested query responded by a database and server where the data still travelled thru the network.
Medical Image Security - the State-of-the-Art

In clinical diagnosis, the medical images act as a significant role and also in therapy, research and teaching and so on, Medical imaging is assumed as a biological imaging part, that had been build from 19th century. For each year, the medical image-based researches have increased at a standard rate of 3%-5%, the need for data-storage has hiked by 10%-25% majorly. To preserve the medical data of patient, the Health Insurance Portability and Accountability Act (HIPAA) needs insurance companies and medical providers to execute some policies and processes. The present standard based on numerous relative studies is done in this paper
IPL SB RAS: 30th anniversary

The article covers the stages of formation and development of the Institute of philosophy and law of the Siberian branch of the Russian Academy of Sciences. It received the status of an independent organization in 1990, when the Institute of history, Philology and philosophy (IHPP) of the SB as of the USSR, established in 1966, was restructured.
New multi-secret sharing scheme based on superincreasing sequence for level-ordered access structure

A new multi-secret sharing scheme (MSSS) that uses a superincreasing sequence and realizes level-ordered access structure (LOAS) is proposed. The novelty of the scheme is that not only a single share for all the secrets is sufficient but also the secrets can be changed without renewing the shares of the participants. The proposed scheme has low communication cost and less overhead for the participant.
Analysis of Big Data Cloud Storage Technology Based on Information Fusion Technology

Compared with traditional storage technology, cloud storage technology is more advanced, mainly relying on server clusters to manage related information on the basis of network software coordination.This technology has strong applicability and convenient operation, which greatly improves the quality of people's work.However, due to the openness of this technology, all its security issues are more prominent.For this reason, the author mainly discusses the cloud storage technology under the big data scenario, and focuses on the analysis and exploration of its specific applications, in order to help people make full use of the technology.
Enhancing Image Security by employing Blowfish Algorithm further embedding text and Stitching the RGB components of a Host Image

‘Privacy, privacy everywhere but not a safety method to implement it’: a harsh reality of today’s world. With the precipitation of more data (2 x 1019 bits of data is created in every 86400 seconds) in computer networks, involvement of meta-data in the form of images is essential. To keep data safe and secure in order to inculcate privacy, to eradicate any kind of eavesdropping, and to maintain confidentiality, integrity and availability of it, certain security measures are needed to make in account for. So in order to make it available, we required a technique through which we can securely transfer any kind of data over a network. In practise the information security can be achieved either by using Cryptography or Steganography. The process described in this paper is not a mediocre it is more scrupulous towards the security because it involves image encryption, steganography and image stitching. Initially we are encrypting an image using Blowfish algorithm then we are embedding the secret text into this encrypted image by modifying the least significant bit (LSB) of the image by our data. Moreover, to enhance the privacy and security we are stitching the above resultant image with the red, green and blue (RGB) components of a host image and thereby producing an image more secure than the one which the existing systems can form for data transmission..
An Absolute Phase Estimation Method for Interferometry Imagery

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.
The case for manual analysis

This chapter discusses the advantages of manually analysing the networks before entering the data into a computer for a fuller report on early and late starts and finishes.