Reviewerly/exHarmony huggingface dataset:
Ethics of Information in the Digital Age

This study aims to present partial results on the research project Tecnologia da Informação em Biblioteca Digital e Sistemas Abertos – Estudos de Usuário da Informação na Web de Dados (Information Technology in Digital Library and Open Systems – Studies on Users of Information on Data Web), conducted by the School of Communications and Arts from University of São Paulo in cooperation with the Faculty of Letters of the University of Porto. The study presents reflections on ethical dimensions that accompany the current digital era. It discusses the importance of understanding the demands of the information user in the Data Web, with a view to teach a course named Ethics of Information at undergraduate programs in ibrarianship, Archivology, Museology, and Information Science, which condenses these reflections and problems, Developing skills for an ethical action in the formation of the information professional in the network society.
Security and Privacy of Data in Cloud Computing

The cloud computing paradigm is being used because there is no need to setup additional IT infrastructure such as hardware and software, its low up-front cost. Security and privacy of data is important in day to today life especially for applications that uses cloud computing such as social media. Customer information that is stored at Cloud is crucial that needs to be protected against potential intruders. There is threat to maintain the data in transit and data at cloud due to different possible attacks. Due to this there is growing need of privacy and security of data. In this paper, the privacy and issues, privacy preservation techniques are addressed. In addition to this, in order to protect the data, the secret sharing algorithm is implemented and analyzed. The shamir’s secret sharing (k,n) algorithm is used to split the data into n partial shares which can be distributed in cloud. The user collects at least k partial shares to reconstruct the complete data. It is observed that if the file size is increased, the data recovery time is also increased. The paper concludes with privacy preservation guidelines.
Masks must change the face of biometrics, says Institute

The widespread use of Covid-19 face masks must trigger a step-change in the way facial recognition systems are developed and applied, the Biometrics Institute has said. The association is calling on the biometrics community to ensure that they quickly implement best practices for managing identity.
Cloud computing

Cloud computing is a mode of acquisition of infrastructure where a cloud service provides on demand computing and on-demand storage, accessible over the web, with a matching business model, namely pay-per-use. Lower cost, sometimes a factor of five, is achieved by automating operations in warehouse-sized data centres, sharing the hefty burden of cooling, physical security, and power backup, and the use of commodity components. As access to storage managed by cloud service providers gained market acceptance, the phrase “the cloud” came into use to refer to the location of information stored with a cloud service provider to be shared (business documents and photos) or copied for backup (against losing a phone or deleting information on a laptop). Security, and to a lesser extent privacy, concerns are the major barriers to the adoption of cloud computing, but the leading cloud service providers have responded to the point that sensitive information, such as medical records and credit-card-holder data, is now held in the cloud.
Intake

OpflowVolume 47, Issue 4 p. 2-2 Departments Intake First published: 06 May 2021 https://doi.org/10.1002/opfl.1524Read 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 No abstract is available for this article. Volume47, Issue4May 2021Pages 2-2 RelatedInformation
Constructing Finite-State Devices for Text Rewriting

A common task arising in many contexts is rewriting parts of a given input string to another form. Subparts of the input that match specific conditions are replaced by other output parts. In this way, the complete input string is translated to a new output form. Due to the importance of text rewriting, many programming languages offer matching/rewriting operations for subexpressions of strings, also called replace rules. When using strictly regular relations and functions for representing replace rules, a cascade of replace rules can be composed into a single transducer. If the transducer is functional, an equivalent bimachine or (in some cases) a subsequential transducer can be built, thus achieving theoretically and practically optimal text processing speed. In this chapter we introduce basic constructions for building text rewriting transducers and bimachines from replace rules and provide implementations. A first simple version in general leads to an ambiguous form of text rewriting with several outputs. A second more sophisticated construction solves conflicts using the leftmost-longest match strategy and leads to functional devices.
Estimation of Power Spectral Density in SVPWM based Induction Motor Drives

This paper is readied the product programming of the SVPWM and half of breed PWM basically based DTC of recognition engine manipulate for assessing the strength Spectral Density (PSD) and the overall consonant mutilation (THD) of the road flows. The PWM set of guidelines utilizes three beautiful PWM methodologies like traditional SVPWM, AZPWM3 and combination PWM for the evaluation of the vitality spectra and consonant spectra. In quality spectra appraisal the extents of the power accrued at express frequencies and inside the consonant spectra the problem band sizes at one among a type replacing frequencies are taken into consideration for the assessment. To confirm the PWM calculations, numerical activity is performed making use of MATLAB/simulink Telugu (తెలుగు) is one of the Dravidian languages which is morphologically rich. As in the other languages it too contains polysemous words which have different meanings in different contexts. There are several language models exist to solve the word sense disambiguation problem with respect to each language like English, Chinese, Hindi and Kannada etc. The proposed method gives a solution for the word sense disambiguation problem with the help of ngram technique which has given good results in many other languages. The methodology mentioned in this paper finds the co-occurrence words of target polysemous word and we call them as n-grams. A Telugu corpus sent as input for training phase to find n-gram joint probabilities. By considering these joint probabilities the target polysemous word will be assigned a correct sense in testing phase. We evaluate the proposed method on some polysemous Telugu nouns and verbs. The methodology proposed gives the F-measure 0.94 when tested on Telugu corpus collected from CIIL, various news papers and story books.The present methodology can give better results with increase in size of training corpus and in future we plan to evaluate it on all words not only nouns and verbs
The Knowledge Management Maturity Model for Indonesian Hospital

The hospital is a primary health care institution in a country, so the hospital must be able to offer optimum performance services for every citizen. In this study, efforts will be made to improve the performance of hospital services through an implementation method for knowledge management system that is of course adapted to current hospital conditions, so the authors propose the Knowledge Management Maturity Model to determine which strategies are appropriate for hospital use based on their maturity level. The author collects data from 33 hospitals to verify this model, where the collected quantitative data has been verified (validity and reliability test). The results of this study are a framework for identifying knowledge management maturity for hospitals and also strategic recommendations for improving the performance of hospital services.
Predicting COVID-19 Disease Progression and Patient Outcomes based on Temporal Deep Learning

Abstract Background: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. Methods : We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Specifically, our method predicted the outcome of COVID-19 patients by T-LSTM, considering both the biomarkers and the irregular time intervals. Then, we used the patient representations, extracted from T-LSTM units, to subtype the patient stages and describe the disease progression of COVID-19. Results: Using our method, the accuracy of the outcome of prediction results was more than 90% at 12 days and 98%, 95% and 93% at 3, 6, and 9 days, respectively. Most importantly, we found 4 stages of COVID-19 progression, with different patient statuses and risks, such as mortality and length of illness. Predicting which of the 4 stages the patient is currently in can help doctors better assess and cure the patient. Conclusions: To combat the COVID-19 epidemic, this paper aims to help clinicians better assess and treat infected patients, provide relevant researchers with potential disease progression patterns, and enable more effective use of medical resources. Our method predicted patient outcomes with high accuracy and identified a four-stage disease progression. We hope that the obtained results and patterns will aid in fighting the disease.
Designing an Application for Analyzing Consumer Spending Patterns Using the Frequent Pattern Growth Algorithm

In this modern era, the market has been growing rapidly which can be seen from the navel shopping that is lined up in the hearts of big cities such as supermarkets, grocery stores and others that are provided to meet people's needs for primary goods that are always needed at all times. One of them is Giant Express Tamalanrea, a supermarket in the city of Makassar that serves the sale of household goods and general needs. With the use of customer data analysis to determine the customers' purchasing patterns, Giant Express can optimize the collation of goods, by positioning goods at closer shelves based on the level of frequency of goods purchased together by customers. Therefore, this study suggests the creation of an application to analyze consumer spending patterns using the frequent pattern growth algorithm method to ensure appropriate placement of goods to increase sales at Giant Express Tamalanrea. The purpose of this study is to develop an application that can analyze consumer spending patterns to increase sales by positioning goods based on consumer shopping patterns, as well as implementing the Frequent Pattern Growth Algorithm method to determine customer spending patterns to increase sales. Stages of research methods conducted begin with data collection at the study site, system requirements analysis, system design with UML, and system testing with the Black Box method.
A Music Makerspace Course Development, Implementation, and Reflection

A detailed documentation of processes taken from inception to implementation through reflection of a Music Makerspace course where students design, code, build, and perform on MIDI controllers of their own design.A special focus to transparency of process was given while constructing the course with the goal of continuing development into a refined platform for creative education using, music, technology, art & sculpture, and performance.The process follows the narrative from the point of view of a music educator who seeks to reinvent the role of music education within schools through critique of the established norms, practices, and expectations while framing the direction of reinvention around relevancy, making, and creative expression. 3.Requirements (optional, especially for the performance on-site)* This section does not need to be filled out for each item; if your work involves relevant items, please fill out the appropriate section.If you will be presenting performance on-site, each section needs to be filled out in detail.The vision for this on-site showcase is a display of information, artifacts, and documentation of the process with running audio/video commentary.
A Low Overhead Image Registration Algorithm using DWT and WIPSO for Resource Constrained SBC based Embedded System Application

Image registration is a vital but integral component of any image processing application. Fundamentally, image registration involves transforming two or more sets of image data derived from different sources, collected at different instant of times, taken from different perspectives and from different viewpoints, all from different frames of reference into an image in a single coordinate system, a single frame of reference. Over the years, there have been many image registration techniques developed and used in variety of application fields. This paper proposes a computationally low overhead image registration technique that has been tested with variety of images using weight improved particle swarm optimization (WIPSO) algorithm integrated with discrete wavelet transform (DWT). Fundamentally, the proposed scheme comprises of a two-step approach, where the first step involves extraction of the random image from the source image which will serve as an ingredient for the formation of the particle swarm to be used in the WIPSO and the second step involves an explorative search for the target image in the area of interest from the selected population using WIPSO technique. Extensive simulation has established the effectiveness of the proposed soft-computing technique for variety of image registration application; even suitable for deployment in many resource-constrained single board computer based embedded system applications.
A Multidimensional Data Fusion Model Based on Deep Learning for a Patient Similarity Network (Preprint)

<sec> <title>BACKGROUND</title> Precision medicine is a novel approach for patient care. It allows the prescription of the appropriate drug as well as suitable treatments to the right patient at the right time. It can be envisioned as the comparison of a new patient with existing patients having similar characteristics, which can be referred to as patient similarity. Several statistical, data mining, and deep learning models have been used to build and apply patient similarity network (PSN) for various purposes. However, the challenges associated with data heterogeneity and dimensionality make it difficult to use a single model that addresses both the challenges of reducing data dimensionality and capturing features of diverse data types, including contextual and longitudinal data. Furthermore, when applying multiple models, we can observe the additional challenges associated with the development of an optimum aggregation scheme that maintains high accuracy and preserves data veracity. </sec> <sec> <title>OBJECTIVE</title> In this study, we propose a multi-model PSN that considers heterogeneous data with static and dynamic characteristics for disease diagnosis for improving prediction accuracy. The static data model manages the data obtained from patient profiles, whereas the dynamic data model manages longitudinal data from patient treatment pathways and clinical data. </sec> <sec> <title>METHODS</title> We propose a combination of deep learning models and patient similarity network to obtain abundant clinical evidence and extract relevant information based on which similar patients can be explored and compared, thereby obtaining more accurate and comprehensive diagnosis and recommendations. We use the bidirectional encoder representations from transformers (BERT) to process and analyze the contextual data and generate word embedding, where semantic features are captured using a CNN. Dynamic data is analyzed using a long–short-term memory (LSTM)-based autoencoder, which reduces data dimensionality while preserving the temporal features of the data. Furthermore, we propose an aggregation-based fusion approach in which temporal data and clinical narrative data are combined for estimating the patient similarity. </sec> <sec> <title>RESULTS</title> We evaluated our proposed method through a series of experiments. The obtained results proved that our proposed deep learning-based PSN fusion model provides higher classification accuracy in determining various patient health outcomes when compared with other traditional classification algorithms. </sec> <sec> <title>CONCLUSIONS</title> Our multi-model highlights the intensity of the similarity between pairs of patients, thereby realizing precise diagnosis and recommendations for a new patient. </sec>
Database Security and Security Patterns

There are so many threats to your security that it is essential to remain ever vigilant—though not so vigilant that you end up with your server in a bunker of lead, wearing a tinfoil hat and keeping data completely inaccessible to even your users. Business needs connectivity to customers, and customers need connectivity to their data. With that having been said, security is a very important task when setting up and deploying a new application, yet it is often overlooked and dealt with late in the application building process. Whether or not this is acceptable is generally up to your requirements, the sensitivity of your data, and how your application will be built; but at one point or another, your application team must take the time to get serious about security. Over and over, news stories report data being stolen, and the theft is inevitably due to poor security. Several editions of this book ago, I used an example of an election official’s stolen laptop in my then home city of Nashville, Tennessee; names, addresses, and partial Social Security numbers were stolen. It was mildly shocking at the time, but by now we all just roll our eyes at such things because of the continual stream of such stories, be them from financial institutions or adultery-oriented websites.
Developing 3Dmetric Media Prototype through a Hypothetical Learning Trajector to Train Students Spatial Skill

Currently, the transformation industry 4.0 was going thoroughly, so that education must also transform to prepare students reaching standards technology industry. Augmented Reality (AR) is one of the major technological revolution. The purpose of this research is to develop a media-based 3Dmetric AR through Hypothetical Learning Trajectory, making students more easily develop their spatial abilities. The research method used is Design research in instructional materials development theorist based problems. The results of this research are the prototype of the 3Dmetric media through HLT right used to develop the ability of students in the spatial dimensions of rotation, constructive space, reconstruction, visualization, and orientation. By using the media 3Dmetric, students can perform spatial geometry activity hypothesis 6. 3DMetric media through HLT is a constructivist and meets AR design principles, i.e. giving challenge, give fantasy, and look at the part that is not visible to the user.
AMBIGUISTAS OF INDONESIAN LANGUAGE ON THE STUDENTS OF IQRA BURU UNIVERSITY

ABSTRACK Ambiguity is a meaningful thing or has more than two meanings. Most people misinterpret what is read and hear. This can occur both in spoken speech and writing. This interpretation of more than one can raise doubts and confusion in making decisions about meaning referred to, so that the reader must be observant in grasping the meaning of that intended by the writer. Ambiguity at this level occurs because of the sounds of spoken language. sometimes it can be misinterpreted the meaning of a word or phrase because during a conversation the phrase or word is said too quickly. This study aims to describe the ambiguity of the Indonesian language used by Iqra University students in composing narratives and papers. This type of research is qualitative research that is naturally or in the context of a wholeness. by using descriptive collected in the form of words and not numbers. The data in this study are data that contain ambiguity using the theories of experts when analyzing. Data collection techniques namely after describing the form of words and phrases in Indonesian written by students after that are analyzed according to theory. the results showed that in students' essays there were words and phrases that contained ambiguity. Keyword: Ambiguitas, Narasi, Student
Dynamic Speckle Interferometry of Technical and Biological Objects

The theory of speckle dynamics in the image plane of a reflecting and thin transparent object is considered. It was assumed that the optical paths of the reflected and probing transparent object waves vary due to (1) translational motion, (2) oscillations with a period T, and (3) random relative displacements of pairs of scattering centers Δ u (reflecting object) and random changes in the refractive index Δ n (transparent object). The formulas relating the mean value, dispersion, and relaxation time of Δ u and Δ n values with the time-averaged radiation intensity at the observation point and the time autocorrelation function of this intensity are obtained. It is shown that at the averaging time multiple of T, the technique in real time allows to determine plastic deformations of the order of 10−3 on bases of the order of 10 microns, which is suitable for the control of elastic deformations on bases of the order of 100 microns. The possibilities of the method of averaged speckle images for the study of (1) features of the nucleation, start, and movement of the fatigue crack, and (2) the activity of living cells infected and not infected with the virus are demonstrated.