Reviewerly/exHarmony huggingface dataset:
AÇÕES DA ENFERMAGEM NO ENFRENTAMENTO ÀS DOENÇAS CRÔNICAS: HIPERTENSÃO E DIABETES

Systemic arterial hypertension is a multifactorial clinical condition characterized by elevated and sustained levels of systolic blood pressure and diastolic blood pressure. Diabetes mellitus is a metabolic disorder of multiple etiology due to lack of insulin and / or the inability of insulin to adequately exert its effects. The aim of the presente study is to describe the nursing actions that have been developed for the control and monitoring of chronic diseases such as hypertension and diabetes.This is a literature review of the literature on nursing actions related to the follow-up of patients with Hypertension and Diabetes, based on an analysis of scientific articles. It was possible to observe that nursing actions are related to health promotion, prevention and management of complications due to hypertension and diabetes, prior planning of these actions and elaboration of the intervention plan through individual and group health education such as hiperdia, nursing consultation, home visits and when necessary, referral of the patient to another level of health care.With the actions of nursing in coping with chronic diseases hypertension and diabetes the most important is the change in the patient's life habits, which is possible through the awareness of individuals. Even though there are effective initiatives in the process of coping with these diseases, there is still much to be done to reduce the statistics regarding the number of cases and complications of these diseases.
RECOGNITION OF INDIAN SIGN LANGUAGES

The focal point of this project is about developing a user interface to aid people who have hearing and speaking disabilities.This application would help in recognizing the different signs with respect to the single user.The real-time image is captured using a webcam and dynamically stored.The elements are initialized and saved in KN Neighbor classifiers.These classifiers are used to load the KN Neighbor model.This model predicts the signs dynamically and is built using machine learning techniques.Mobile Net is used as a machine learning package.This model was implemented in three phases.The first phase deals with the user interface where user images are captured using a webcam.In the second phase, the initialized elements are used by the KN Neighbor classifier and then stored as the KN Neighbor model.The third phase involves the prediction of signs.
The Power of One Clean Qubit in Communication Complexity

We study quantum communication protocols, in which the players' storage starts out in a state where one qubit is in a pure state, and all other qubits are totally mixed (i.e. in a random state), and no other storage is available (for messages or internal computations). This restriction on the available quantum memory has been studied extensively in the model of quantum circuits, and it is known that classically simulating quantum circuits operating on such memory is hard when the additive error of the simulation is exponentially small (in the input length), under the assumption that the polynomial hierarchy does not collapse.We study this setting in communication complexity. The goal is to consider larger additive error for simulation-hardness results, and to not use unproven assumptions.We define a complexity measure for this model that takes into account that standard error reduction techniques do not work here. We define a clocked and a semi-unclocked model, and describe efficient simulations between those.We characterize a one-way communication version of the model in terms of weakly unbounded error communication complexity.Our main result is that there is a quantum protocol using one clean qubit only and using O(log n) qubits of communication, such that any classical protocol simulating the acceptance behaviour of the quantum protocol within additive error 1/poly(n) needs communication Ω(n).We also describe a candidate problem, for which an exponential gap between the one-clean-qubit communication complexity and the randomized communication complexity is likely to hold, and hence a classical simulation of the one-clean-qubit model within constant additive error might be hard in communication complexity. We describe a geometrical conjecture that implies the lower bound.
EFFECT OF KNOWLEDGE MANAGEMENT PRACTICES ON PERFORMANCE OF MOBILE TELEPHONE COMPANIES

Purpose: Knowledge management practices in general were found to influence organization performance as there is increased awareness of information that is critical to achieving the organization’s mission. The general objective of the study was to establish the effect of knowledge management practices on performance of mobile telephone companies.&#x0D; Methodology: The paper used a desk study review methodology where relevant empirical literature was reviewed to identify main themes and to extract knowledge gaps.&#x0D; Findings: The study concludes that knowledge management practices in general influences organization performance in various ways including, knowledgeable employees, better decision making in the organization, improved service offering to client, reduced operational costs, improved organizational competitiveness. This is mainly so because there is increased awareness of information that is critical to achieving the organization’s mission. The order of significance of the effect of knowledge management practices on performance of mobile telephone companies in starting with the most significant to the least is; knowledge creation, knowledge sharing, knowledge acquisition, knowledge implementation and knowledge storage respectively.&#x0D; Recommendations: The study points out that for effective organization administration organizations need to create a central repository system to store and retrieve information on organization reports cards, feedback on student progression, coordination of organization schedules, organization suspension, finances and other professional development which will have an overall effect on organization performance. Organizations should also install internet services and computers in order to share knowledge and improve the organization’s efficiency, performance, and competitiveness
Android-Based Private Course Application

At this time technology has developed rapidly, without exception in the field of education. One of the technological developments in education is tutoring. Many students still need tutoring or private lessons to improve their abilities and meet the set passing grade standards. In addition, the catching power of each child in receiving subject matter at school is different so that not all are able to understand the material using offline or online methods. The purpose of this application is to make it easier and help the difficulties experienced by students and teachers to connect with each other and carry out private lessons. This application uses the method of observation and literature study. The method of making this application is the SDLC (System Development Life Cycle) prototype model. The expected results from making this application are so that teachers and students can connect with each other and carry out course activities easily according to the criteria desired by both parties. From this application students can choose based on the level of education and subjects they want to take and the rates offered by the teacher. Students and teachers can also choose the place of learning they want, such as studying at home, on video cameras or at the teacher's place.
A Research Travelogue on Feature Sub Set Selection Algorithms

In machine learning as the dimensionality of the data rises, the amount of data required to provide a reliable analysis grows exponentially. To perform dimensionality reduction on high-dimensional micro array data, many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. Analyzing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. Feature selection has been an active and fruitful field of research area in pattern recognition, machine learning, statistics and data mining communities. The main objective of this paper is feature selection is to choose a subset of input variables by eliminating features.
MARG szenzor alapú pozíció becslés periodikus mozgásra

The research examined the fusion of signals from magnetometer, gyroscope and acceleration sensors (MARG sensor). The focus of the article is the sensor fusion by supervised learning, which is an estimate of the situation based on the parallel processing of different types of measured data in the case of periodic movements. The applicability of the learning algorithms was examined through a practical example of a pendulum.
Marketing and Future of Mobile Audio Apps - case study of the <i>Ximalaya FM</i>

This paper aims to study some characteristics of mobile audio APP in the mobile audio market and intends to analyze the market situation based on specific cases.The importance of this article to the media sector is that it can provide a partial reference for the marketing strategy of mobile audio apps.We have mainly used the analysis of Ximalaya FM company through the use of various online professional materials and academic papers as an example to reflect the marketing strategies and business models of the mobile audio industry and to further reflect on the differences between the business models of audio companies by comparison with those of Litchi and Dragonfly FM.We found that Xiamalaya FM becomes the top of the mobile audio industry by using its rich platform content, a combination of free and paid content, and accurate 4Ps marketing strategies.Therefore, the general pricing rule for the audio industry is to offer course-level pricing by studying different consumer groups and then adding various promotions and advertisements.Therefore, the results of this study tend to be specific to a case, but there are relatively general findings in this media field.Different audio stations should accept the general phenomenon of the market and adopt different marketing strategies and pricing according to their own business models to be successful.
Empirical Research on Mixed-mode Teaching of Practical Fundamental Courses Based on Deep Learning

Through the analysis of the problems in the teaching of practical fundamental courses, the article proposes a mixed-mode teaching method that promotes students' deep learning, and takes the course “make-up and styling foundation” as an example to analyzethe application of the teaching mode to promote deep learning in the mixed-mode teaching from the design of teaching strategies and course implementation. The results show that the online and offline mixed-mode teaching based on deep learning ensures the efficient implementation of classroom teaching and helps improve students' comprehensive ability.
Outlier Recognition via Linguistic Aggregation of Graph Databases

Datasets frequently contain uncertain data that, if not interpreted with care, may affect information analysis negatively. Such rare, strange, or imperfect data, here called “outliers” or “exceptions” can be ignored in further processing or, on the other hand, handled by dedicated algorithms to decide if they contain valuable, though very rare, information. There are different definitions and methods for handling outliers, and here, we are interested, in particular, in those based on linguistic quantification and fuzzy logic. In this paper, for the first time, we apply definitions of outliers and methods for recognizing them based on fuzzy sets and linguistically quantified statements to find outliers in non-relational, here graph-oriented, databases. These methods are proposed and exemplified to identify objects being outliers (e.g., to exclude them from processing). The novelty of this paper are the definitions and recognition algorithms for outliers using fuzzy logic and linguistic quantification, if traditional quantitative and/or measurable information is inaccessible, that frequently takes place in the graph nature of considered datasets.
Reflective Maternal Method Implementation in Improving Vocabulary Knowledge of Deaf Children in Class 1 of SLB-B Sumbersari Bandung

The study was conducted on subjects of deaf children in class 1 of SLB-B Sumbersari Bandung. As a result of their deafness, deaf children are limited in language and communication and have low vocabulary knowledge. Therefore, this study aimed to discover the reflective maternal method implementation in improving deaf children's vocabulary knowledge. This method stimulates deaf children to optimize their abilities in knowing vocabularies, i.e., nouns by conducting conversations, visualizations, word deposits, and reflections. Based on the problems, it is necessary to provide special treatments to improve vocabulary knowledge, especially on object uses. The method used in this study was the Single-Subject Research (SSR) experiment by a quantitative approach by using the A-B-A design. The data collection technique used was three test types, i.e., verbal test, action test, and written test. This study was carried out on two deaf children. Study findings based on baseline 1 and baseline 2 scores show that the baseline 2 result was higher and had a score increase post-intervention. It is proven by the two subjects who managed to mention object names, showing object names, and matching object names and object uses. The reflective maternal method is a method by the active learning process that triggers children to conduct a natural conversation, as they occur between mother and child. This study can be implemented as a recommendation for associated teachers in their learning method, particularly in using the reflective maternal method to improve object or other material vocabulary knowledge on deaf children.
Decision Support System for Profile Matching Methods in IOS-Based Mobile Applications

When someone is going to buy a used car, they will definitely be faced with the criteria for what kind of car the buyer wants to buy. Many things can be considered in choosing a used car, such as price, exterior, year of manufacture, kilometers travelled and others. This consideration becomes a crucial thing considering the price of the car is not cheap to avoid regrets in the future. Therefore, we need an easy and uncomplicated system to make it easier for buyers to buy cars. A decision support application for iOS-based car searches using the profile matching method compares alternative values and criteria to produce GAP or differences. The final result of this research is to implement a decision support system into a mobile application that can provide convenience and produce decision alternatives. With the application that is built, it is expected to be a solution for buyers so that they can be helped in choosing a car according to predetermined criteria.
The Why of Education

What do we hope for when we send children to school? This is the question Martin Luther King, Jr. posed in an essay entitled “The Purpose of Education,” published in the Morehouse student newspaper around the time of his 18th birthday. King's answer: “Intelligence plus character—that is the goal of true education.” But what, then, is character? This is the question child psychologist Diana Baumrind addressed, toward the end of an illustrious career, in an essay entitled “Reflections on Character and Competence.” Character, Baumrind writes, “provides the structure of internal law that governs inner thoughts and volitions subject to the agent's control under the jurisdiction of conscience.”
An Intelligent Multimedia Data Encryption and Compression and Secure Data Transmission of Public Cloud

Data compression is a method of reducing the size of the data file so that the file should take less disk space for storage. Compression of a file depends upon encoding of file. In lossless data compression algorithm there is no data loss while compressing a file, therefore confidential data can be reproduce if it is compressed using lossless data compression. Compression reduces the redundancy and if a compressed file is encrypted it is having a better security and faster transfer rate across the network than encrypting and transferring uncompressed file. Most of the computer applications related to health are not secure and these applications exchange lot of confidential health data having different file formats like HL7, DICOM images and other audio, image, textual and video data formats etc. These types of confidential data need to be transmitted securely and stored efficiently. Therefore this paper proposes a learning compression- encryption model for identifying the files that should be compressed before encrypting and the files that should be encrypted without compressing them.
Pengaruh Senam Otak Terhadap Tingkat Kejenuhan dan Tingkat Motivasi Belajar Mahasiswa STIKES Telogorejo Semarang

Community nursing care is a nursing service provided to improve the degree of health that focuses on the community including individuals, families, groups &amp; communities. Nurses as educators also play a role in the higher education environment with the youth community. Teenagers (students) have learning demands for self-development to prepare for the future. The demands faced today are bigger than what they had during high school. This demand often makes students bored, not interested in attending lessons (rowdy), and loses motivation. This study aims to determine whether brain exercise has an effect on the level of boredom and the level of learning motivation in STIKES Telogorejo Semarang students. The hypothesis in this study is that there is an effect of brain exercise on the level of boredom and the level of learning motivation in STIKES Telogorejo Semarang students. The subjects in this study were 47 students of the sixth semester of the S-1 Nursing study program at STIKES Telogorejo. The type of research used is Quasy Experiment with one group pretest - posttest. The data collection tools used were the MBI-SS (Maslach Burnout Inventory- Student Survey) questionnaire and the motivation scale. Data analysis was performed univariate and bivariate (using the Wilcoxon test p &lt;0.05). The results of this study indicate that the hypothesis is accepted, there is an effect of brain exercise on the level of boredom by obtaining a value of p =0.009 (&lt;0.05) and there is an effect of brain exercise on the level of learning motivation in STIKES Telogorejo Semarang students with p = 0.000 (&lt;0.05).
Aplikasi Pemesanan Ikan Di Tpi Palopo Berbasis Android

The purpose of this research is to build an Android-based TPI Palopo Fish Ordering Application which is later expected to be able to assist and minimize the time used and facilitate the delivery of information. The type of research used is descriptive. The results of the study are in the form of an Android application consisting of several pages containing the order of TPI PALOPO fish, product information, product category information and product prices, all of which have been functionally tested using the black box testing method, and of course user friendly interface The software that supports this application uses the Windows 10 Android Studio operating system, XAMPP, Sublime Text, Photoshop CC 2015, Android emulator with UML as the system designer, which includes use case diagrams, activity diagrams, and sequence diagrams. The system development method applied is the waterfall, which is carried out step by step and must be passed sequentially. So that with this application that has been built, it is expected to improve the performance of an institution/agency/company, especially in TPI Palopo.
INVESTIGATION OF PARAMETERS OF THE PROBLEM OF SPLINE APPROXIMATION OF NOISY DATA BY NUMERICAL METHODS OF OPTIMAL CONTROL

Currently, the problems of distortion of measurement data by noise and the appearance of un-certainties in quality criteria have caused increased interest in research in the field of spline approx-imation. At the same time, existing methods of minimizing empirical risk, assuming that the noise is a uniform distribution with heavier tails than Gaussian, limit the scope of application of these studies. The problem of estimating noise-distorted data is usually based on solving an optimi-zation problem with a function containing uncertainty arising from the problem of finding optimal parameters. In this regard, the estimation of distorted noise cannot be solved by classical methods. Aim. This study is aimed at solving and analyzing the problem of spline approximation of data under uncertainty conditions based on the parametrization of control and the gradient projec-tion algorithm. Methods. The study of the problem of spline approximation of noisy data is carried out by the method of approximation of the piecewise constant control function. In this case, para-metrization of the control is possible only for a finite number of break points of the first kind. In the framework of the experimental study, the gradient projection algorithm is used for the numerical solution of the spline approximation problem. The proposed methods are used to study the parameters of the problem of spline approximation of data under conditions of uncertain-ty. Results. The numerical study of the control parametrization approach and the gradient projec-tion algorithm is based on the developed software and algorithmic tool for solving the problem of the spline approximation model under uncertainty. To evaluate the noise-distorted data, numerical experiments were conducted to study the model parameters and it was found that increasing the value of the parameter α leads to an increase in accuracy, but a loss of smoothness. In addition, the analysis showed that the considered distribution laws did not change the accuracy and convergence rate of the algorithm. Conclusion. The proposed approach for solving the problem of spline approx-imation under uncertainty conditions allows us to determine the problems of distortion of measure-ment data by noise and the appearance of uncertainties in the quality criteria. The study of the model parameters showed that the constructed system is stable to the error of the initial approxima-tion, and the distribution laws do not significantly affect the accuracy and convergence of the gra-dient projection method.
Model Approximation of Fuzzy Switched Systems

In this chapter, the model approximation issue of a T-S fuzzy switched system with stochastic disturbances is considered. Considering a high-order system, we constructing a reduced-order model, which can approximate the original system with a Hankel-norm performance and convert it to a lower-order switched system. Sufficient conditions are derived using the ADT method and piecewise Lyapunov function to ensure the resulting error system is mean-square exponentially stable and satisfies the Hankel-norm performance sense.
Color Texture Description with Diagonal Local Binary Patterns Using a New Distance Metric for Impressive Image Retrieval

With the reliability and dependence of the world over the digitalization of information in all spectrums of professional and personal life, the volume of digital data is increasing exponentially.With such a huge database, retrieving information, and images from the storage media pose serious challenges.In this paper, a diagonal local binary pattern for color images (DLBPC) and a new distance metric are proposed for the retrieval of data with high accuracy and speed.The descriptor employs the deviceindependent L*a*b* color space.The discriminative quality of DLBPC is enhanced by combining local features with the (color moment) global feature of the image for effective image retrieval.To assess the efficacy, the suggested system was implemented on challenging datasets: Wang -1K and GHIM-10K.The analysis findings demonstrate the efficacy of the suggested system over other reported systems.