Reviewerly/exHarmony huggingface dataset:
Motivation, Attitude, Role Of Drug Control (Pmo) With Drug Compliance In Patients Tb

Pulmonary tuberculosis is a direct infectious disease caused by TB (Mycobacterium Tuberculosis) bacteria. The level of compliance with the use of pulmonary TB drugs is very important and requires a long time that is 6-8 months, because if treatment is not carried out regularly or is not compliant and does not correspond to the specified time then there will be resistance (resistance) of tuberculosis germs against drugs Widespread Anti Tuberculosis (OAT) or Multi Drugs Resistance (MDR). The purpose of this study was to determine the relationship between motivation, attitudes, the role of supervisors taking medication (PMO) in TB sufferers. The design of the study used an Analytical Observational design using the Cross-Sectional approach. The population in this study were all TB sufferers in Bulukumba District with a sampling technique using cluster sampling. The number of samples in this study were 60 respondents. Data were obtained through questionnaire sheets made by researchers to respondents. Data analysis used Fisher's alternative Chi-square Test, with significance level α = 0.05. The results of the data analysis show that the motivation variable p = 0.023, the attitude variable p = 0.012, and the role of the supervisor for taking medication (PMO) p = 0.017. So it can be concluded that there is a relationship between motivation, attitude, the role of supervisors taking medication (PMO) with adherence to taking medication in TB patients in Bulukumba Regency.
Probabilistic modelling and attack simulations on AWS Connected Vehicle Solution : An Application of the Meta Attack Language

This work is focused on investigating if the Meta Attack Language (MAL) can be used to create an integrating layer between two different applications of the MAL, and thus being able to model a new ...
Aprendizajes clave y su impacto en el ámbito socioemocional del estudiante de nivel secundaria

The progressive advancement of societies as a result of globalization establishes a competitive scenario in which the individual must seek continuous improvement and compliance with professionalization standards. Therefore, the objective of this research is to know the repercussions of the application of the new educational model in secondary education institutions on educational quality. The sample consisted of 50 secondary school teachers, aged between 23 and 45 years. An instrument was applied with 4 signalitic variables and 36 variables of the study phenomenon, considered with a scale of decimal ratio; which were processed in the statistical programs SPSS and Statistica. The main results show that the evaluation of teaching performance is significant to highlight the application of didactic procedures that ensure student learning. In addition, as long as human development and socio-emotional education are promoted, satisfactory results will be obtained in the application of the new educational model. Therefore, it is proposed to carry out continuous improvement forums where students, teachers, executives, parents and social agents that derive in the creation of public policies participate.
Model-Based Clustering

This chapter deals with the model-based approach to clustering based on a probability model, specifically the Finite Mixture Model (FMM). Within such a framework, the crucial problems of determining the number of clusters and choosing an appropriate clustering method can be seen as a problem of model selection. In this chapter, after a brief introduction to the model-based clustering framework, FMMs will be introduced with particular emphasis on the most commonly used family, namely, the Gaussian, for continuous data. Then, we briefly mention some approaches to model-based clustering for non-continuous data. The analysis of several real-world data will also be discussed.
the voice of grass

Author(s): Polglase, John | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Composition in the age of AI.

This article considers the plight of the contemporary composer, and various options they have to engage with AI beyond simply sticking their head in the sand, from writing software to deliberate subversion of corpora and moving social goalposts. If composers aren't intimately involved with next generation music AI, they may find themselves on the sidelines, at the mercy of the musical representational decisions of the software should be engineers, whose musical and/or commercial preferences often favour more popular and Western idioms.
UCD model in agile software processes

Software development field is becoming more productive day by day with the wonderful model name Agile. Agile is the main focus of research now a days. It is because of its abilities of handling changes in efficient way through iterative and incremental practices. Although it became famous because of its capabilities still there are some issues in it, which is ignorance of usability engineering in different phases of agile that is an important aspect to understand the software. Usability has deep roots in software quality and is a core construct of HCI. To develop interactive and usable systems there is a need of such a model which can integrate HCI with Agile. To address this issue. To solve this issue we have proposed a model which will work with both User Centered (main focus of HCI) and Agile by assembling different practices from both fields which will result useable products. It will enhance software life with user satisfaction by giving them running software with usability.
Teaching and learning guide for: Dynamical systems theory in cognitive science and neuroscience

Philosophy CompassVolume 15, Issue 8 e12697 TEACHING AND LEARNING GUIDE Teaching and learning guide for: Dynamical systems theory in cognitive science and neuroscience Luis H. Favela, Corresponding Author Luis H. Favela luis.favela@ucf.edu University of Central Florida, Orlando, Florida, USASearch for more papers by this author Luis H. Favela, Corresponding Author Luis H. Favela luis.favela@ucf.edu University of Central Florida, Orlando, Florida, USASearch for more papers by this author First published: 30 August 2020 https://doi.org/10.1111/phc3.12697Read 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 onFacebookTwitterLinkedInRedditWechat Volume15, Issue8August 2020e12697 RelatedInformation
Library Guides: Library Skills: An Introduction: Video 1: Homepage and Help

The contents of this guide show you some basics about the Library's website and how to use the online research services.
Secure Messaging: From Systems to Theory

Author(s): Jaeger, Joseph Sumner | Advisor(s): Bellare, Mihir | Abstract: The standard view of cryptography is that secure systems should be built by implementing known primitives whose theoretical security guarantees are well understood. In this work we take the opposite approach, taking inspiration from existing systems and providing the theoretical basis with which to understand their security goals. Our particular inspirations are modern secure messaging apps (e.g. Signal, WhatsApp) which have deployed new techniques with the goal of maintaining some security against attackers which sometimes gain temporary access to honest users’ devices.We propose that these security goals should be studied in a modular manner where distinct cryptographic components are studied in isolation. Towards this we separately provide formal models for understanding the initial exchange of cryptographic secrets and their later use for the exchange of messages in this setting. We provide provable secure constructions of these separate components (often achieving better security than what is currently deployed by messaging apps) and a composition result which generically proves security when these isolated components are used together.
LibGuides: LIbrary Basics: Getting a Library Card

This guide is intended as an overview to the finding resources within the library to help you get started!
Penyuluhan Bank Sampah dan Pemilahan Sampah Bahan Baku Biogas Skala Rumah tangga

In the implementation of Tridharma Peguruan Tinggi activities, especially in the field of community service, Budi Luhur University collaborates with residents of Pondok Lakah Permai Ciledug housing, to collaborate in household scale waste management to be used as biogas raw material. The problems faced by residents and environmental managers are rubbish that is not transported then decomposed, the effects of rotting garbage in the open are certainly not good for health. If the waste processing is done by burning it will cause air pollution. To overcome these problems, the waste is processed into biogas through a fermentation process. The fermentation process is used to decompose organic waste into methane gas that can be used for cooking. The role of the community is very necessary to collect raw materials for waste and sort organic and inorganic waste. The purpose of this community service activity is to provide training to residents of Pondok Lakah Permai Ciledug to separate waste from household waste to be processed into biogas and form a waste bank to collect garbage from residential residents. The method used is to provide counseling and proceed with making biodigesters to process the waste. The results achieved in this activity are that the community has understood to protect the environment and can operate biodigesters so that the garbage that had piled up is now processed into biogas.
Search and Evaluation of Coevolving Problem and Solution Spaces in a Complex Healthcare Design Science Research Project

This research employs design ethnography to study the design process of a design science research (DSR) project conducted over eight years. The DSR project focuses on chronic wounds and how Information Technology (IT) might support the management of those wounds. Since this is a new and complex problem not previously addressed by IT, it requires an exploration and discovery process. As such, we found that traditional DSR methodologies were not well-suited to guiding the design process. Instead we discovered that focusing on search, and in particular, the co-evolution of the problem and solution spaces, provides a much better focus for managing the DSR design process. The presentation of our findings from the ethnographic study includes a new representation for capturing the co-evolving problem/solution spaces, an illustration of the search process and co-evolving problem/solution spaces using the DSR project we studied, the need for changes in the purpose of DSR evaluation activities when using a search-focused design process, and how our proposed process extends and augments current DSR methodologies. Studying the DSR design process generates the knowledge that research project managers need for managing and guiding a DSR project, and contributes to our knowledge of the design process for research-oriented projects.From a managerial perspective, studying the design process provides the knowledge that research project managers need for managing and guiding DSR projects. In particular, research project managers can guide the search process by understanding when and why to explore different search spaces, to expand the solutions investigated, and to focus on promising solutions and to evaluate them. Overall, this research contributes to our knowledge of design and the design process, especially for highly research-oriented problems and solutions.
The role of a laterally varying density contrast for gravity inversion of the Moho depth

&amp;lt;p&amp;gt;We present a new inverse approach to invert satellite gravity gradients for the Moho depth under consideration of a laterally varying density contrast between crust and mantle. The inverse problem is linearized and solved with the classical Gauss-Newton algorithm in a spherical geometry. To ensure stable solutions, the Jacobian is smoothed with second-order Tikhonov regularization. During the inversion, the Moho depth is discretized into tesseroids by reference Moho depth and density contrast, from which the gravitational effect can be calculated. As a computational benefit, the Jacobian is calculated only once and afterwards weighted with the laterally varying density contrast. We look for a Moho depth model that simultaneously explains the gravity gradient field and a least misfit to existing seismic Moho depth determinations. We perform the inversion both on regional and global scale.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The laterally varying density contrast is based on different tectonic units, which are defined by independent global geological and geophysical data, such as regionalization of dispersion curves. This is beneficial in remote areas, where seismic investigations are very sparse and the crustal structure is to a large extent unknown. Applying the inversion to the Amazonian Craton and its surroundings shows a lower density contrast at the Moho depth for the continental interior compared to oceanic domains. This is in accordance with the tectono-thermal architecture of the lithosphere. The inverted values of the density vary between 300-450 kg/m&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt;. The inverted Moho depth shows a clear separation between the Sao Francisco Craton and shallower Amazonian Craton.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Gravity inversion with a laterally varying density contrast requires a uniform reference Moho depth. On a global scale, we utilize our inversion to estimate a reference Moho depth that is in accordance with crustal buoyancy. The inverted density contrasts show a similar trend like the regional study area. The inverted Moho depth shows expected tectonic features. Our method of computing the Jacobian once and weighting with lateral variable density contrasts is a valuable optimization of standard gravity inversion.&amp;lt;/p&amp;gt;
Digital forensics in cyber security - recent trends, threats, and opportunities

The rapid technological advancement has led the entire world to shift towards digital domain. However, this transition has also result in the emergence of cybercrimes and security breach incidents that threatens the privacy and security of the users. Therefore, this paper aimed at examining the use of digital forensics in countering cybercrimes, which has been a critical breakthrough in cybersecurity. The paper has analyzed the most recent trends in digital forensics, which include cloud forensics, social media forensics, and IoT forensics. These technologies are helping the cybersecurity professionals to use the digital traces left by the data storage and processing to keep data safe, while identifying the cybercriminals. However, the research has also observed specific threats to digital forensics, which include technical, operational and personnel-related challenges. The high complexity of these systems, large volume of data, chain of custody, the integrity of personnel, and the validity and accuracy of digital forensics are major threats to its large-scale use. Nevertheless, the paper has also observed the use of USB forensics, intrusion detection and artificial intelligence as major opportunities for digital forensics that can make the processes easier, efficient, and safe.
Research Guides: Social Emotional Learning Children's Books: Courage

This guide will help you to locate books in the children's collection which relate to topics of Social Emotional Learning, and is designed to align with the topics covered by the Toolbox SEL curriculum.
Advance-Fee Scams: A Corpus and Genre Analysis

Online scamming is on the increase at a global level. Its chances for success depend, to a large extent, on the ability of the scammers to advantageously exploit a knowledge asymmetry between themselves and their victims. Advance-fee frauds seem to achieve their purpose because the victims ignore the warning signals present in these communications. This paper analyzes a corpus of scam emails to identify the language used to manipulate the victims to the extent that they fail to acknowledge the indicators which clearly point to a fraud. For this purpose, the analysis is based on the notion of promotionalletter move structure (Bhatia 1993), the semi-formal representation of knowledge involved in fraud detection and prevention (Gao & Zao 2005), the model of judgment and choice according to preferences and attitudes (Kahneman 2003), as well as the persuasion strategies presented by Fischer et al. (2013). The results indicate that this genre is a variation of a sales promotion letter which offers greed as an incentive and generates credibility by referring to actual facts.
A Performance Evaluation Method for Machine Learning Cloud

In recent years, the application of machine learning algorithm is more and more extensive, and the combination of cloud platform and machine learning algorithm is closer. With the popularity of cloud platform, more and more cloud platform providers, the comparison of performance of different cloud platforms becomes crucial. The cloud platform performance benchmark can provide a relatively objective reference for consumers, However, the current mature cloud platform performance benchmarks cannot meet the requirements of testing the machine learning capabilities of cloud platforms, while the recent ones just only test the performance of machine learning. Based on the previous cloud platform performance testing methods, this paper designed a cloud platform performance evaluation method for machine learning applications based on the combination of AI-based testing benchmark and CPU-based testing benchmark, which can not only evaluate the performance of cloud platform in terms of CPU, but also test the performance of cloud platform in terms of GPU, running machine learning algorithms.
LibGuides: CRM 430: Correctional Systems: APA Help

This course is designed to be a comprehensive overview of our government's response to convicted criminal offenders. The origins, evolution, processes, and current problems of correctional systems will be the topics of study. More specifically, the course
University of Glasgow Electronic Research Notebook Case Study

In 2018-2019 the University of Glasgow used a Jisc grant to run a package of work to provide evidence of user requirements for electronic research notebook tools for the Jisc Open Research Hub project and to inform longer-term plans for the University of Glasgow.
Symmetric and Asymmetric Based Encryption Model for Mobile Commerce

Secure information exchange in a mobile commerce environment has become a difficult task due to the involvement of sensitive financial information and the tremendous development in information technology in recent years. This poses a great threat while conducting transaction in a mobile commerce environment. Cryptography has been employed to eliminate this using symmetric and asymmetric cryptography. However, in symmetric cryptography, secret key distribution can create a performance bottleneck, while asymmetric ciphers consume significant computational resources. This paper proposed symmetric and asymmetric based encryption model so as to achieve robust security and faster processing speed, by employing Advanced Encryption Standard (AES) as symmetric algorithm and Rivest-Shamir-Adleman (RSA) as asymmetric algorithm. In this model, RSA was used to encrypt AES secret key in order to secure the exchange of the key, while the rest of the sensitive data was encrypted using AES. The proposed model was implemented using Java programming language. Performance evaluation of the proposed model was carried out in terms of encryption/decryption time and the results show that the proposed model takes a little longer time than the RSA algorithm. This is as a result of the AES key encryption being introduced into the model. It is therefore recommended that the model be implemented in mobile commerce applications as an added layer of security in order to strengthen the applications against numerous security threats due to the robust security and faster processing speed provided by the proposed model.
Creating the report

The technique of report writing can be learned by anyone who possesses two basic qualities: fundamental communication skills and a trained ability to observe. To be a competent investigator, you must write reports clearly so that everyone who reads them will know what you did and why. Often the report is needed long after the crime and must be interpreted by many people unfamiliar with the crime. Interviewers must write the report so that the prosecutor and courts can fully understand what took place.
A Machine Learning Technique for Predictive Maintenance and Quality in Cut Glass Machinery

The study presented in this thesis work is based on the development of a machine learning project applied to the particular case of the 548 Lam machine, a cut glass machine produced by the company Bottero s.p.a., which collaborates with this thesis. The work describes how to develop a project based on machine learning and how it can be applied in a real case. The thesis is in fact divided into two distinct parts, the first more didactic in which are explained the various steps to be followed to prepare the data and apply different algorithms of machine learning to maximize the results, the second instead shows how to use in a concrete way the results of the study of machine learning in order to effectively increase productivity. To do this, two problems have been selected to be solved, indicated by the company. The first study tries to predict machine stops and anomalous failures. The work includes an accurate understanding of the machine and the starting dataset, and then concentrate on the data preparation. Therefore, all the various steps to be followed during the pre-processing phase are listed: how to perform data merging, correlational and statistical analysis to find important information from the data, feature selection, how to manage categorical features. When the initial data have been properly manipulated, we proceed to the evaluation phase of the selected algorithms based on the characteristics of the dataset, evaluating which model obtains the best results in predicting machine errors. The results obtained show that the probabilistic algorithms based on the tree classification are those that best predict errors. In details, the Random Forest Classifier proves to be the best model obtaining an F1 score of about 50% on the positive prediction. The second part deals with the prediction of machining times based on the characteristics of the work to be performed. This second part want to show how a machine learning model can be transposed from the mere field of study to a real application, so there is a reconstruction of the prediction function inside the machine itself, in order to make real time predictions based on the data selected by the user. The linear regression model was first trained on a PC thanks to the data contained in the dataset and then reconstructed in the software interface of the machine thanks to the coefficients listed in an orderly JSON file that is first created during the training of the model and then passed to the machine that is at this point able to make predictions. The results show that the time prediction based on this model achieves an error of less than 10% with respect to the actual measured values.
LibGuides: Westchester County Tech Mobile: Where does the Tech Mobile go?

All about the Westchester County LIbraries traveling library and technology mobile Map and schedule for Tech Mobile stops, form to request a stop
Op. 3,14

Author(s): Hartl, Bence | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.