Reviewerly/exHarmony huggingface dataset:
Creative Competence As A Forming Condition Of The New Type Of Teacher

The relevance of the research is due to the active processes of modernization. The major factor of these processes is a person which targeted on innovational activity, capable to self-improvement and self-development. Another factor is the society’s needs in the generation of the new type of teachers, which are ready to the work within the ideology of new educational paradigm, can understand the value of teacher’s creativity, and can develop the creativity in their students. The present article represents the methodical interpretation of the definition “teacher-philologist’s creative competence”. The author describes the component composition, structure, and essential characteristics of this term as a methodical category. This category, in turn, can expand the scientific image of the value-semantic, creative component of personal culture, and the creativity in the context of professional practice of teacher-philologist. It has been proved, that the development of teacher-philologist’s creative competence as an integrative multi-factor quality of personality can stimulate the effective self-realization of the teacher in professional creative activity. Creative competence is the key to development of artistic and literary abilities of the students, and their own creative abilities. Teacher-philologist’ creative competence is an independent personal complex which has complexity dialectical connections with professional competence suggesting the possibility of coincidence and divergence with it. According to the level of creativity, there were determined the next types of teachers: repeater, interpretator, improvisator, researcher. The validity of the present research is provided by sufficient duration of the experiment, its repeated reproduction with stable recurrency of the results, confirmed by mathematical and statistical methods of their processing.
Hubungan kadar leptin terhadap parameter trombosit pada pasien dengan obesitas

Background: Obesity is excessive and abnormal fat accumulation thus harmful to health. Increase in body mass index (BMI) in obesity, also accompanied by increase hormon which synthesized and released by adipose tissue informs the brain for controlling hunger and food intake that is Leptin. Leptin plays a role in chronic inflammatory process of obesity. Leptin receptor was detected in human platelets and high concentration of leptin reported to promote platelet aggregation. The platelet parameters examination is a cheap, easy, and routinly done in daily basis, which consist of platelet counts, mean platelet volume (MPV), platelet distribution width (PDW), platelet large cell ratio (PLCR), plateletcrit (PCT), which indicates platelet proliferation. The aim of research was to look the relationship of leptin with thrombocyte parameter in obesity people.Methods: Cross sectional study of 45 obese adults, based on RISKESDAS criteria Â with Â BMI&gt;27, on Mei-September 2018 was done. Venous blood collected in EDTA and plain tube. The EDTA sample was used for complete hematological examination to obtain platelet parameters by Hematology analayzer with impendace method. Serum from plain tube used for leptin examination was measured by ELISA. Data were analyzed by Pearson and Spearman correlation test. P-value &lt; 0,05 was consideres as significant.Results: There is no correlation between leptin and platelet count (r=0,051, p=0,740), MPV (r=0,021, p=0,891), PDW (r=-0,093, p=0,541),Â P-LCR (r=0,082,Â p=0,593), and PCTÂ (r=0,079, p=0,605).Â Conclusion: There is no correlation between leptin and platelet parameters in obesity. Further studies need to be done with adding another characteristic such as inflammation markers, metabolic syndrome parameters and platelet activation
Bipolar Fuzzy α-ideal of BP-algebra

In this paper, the concept of bipolar fuzzy α-ideal of BP-algebra is introduced. We introduced α-ideal and fuzzy α-ideal. Several theorems are presented in this regard. The homomorphic image and inverse image of the bipolar fuzzy α-ideal are studied.
Enhanced MRF based Super Resolution Method for Remote Sensing Images

In this paper, a learning based enhanced Markov Random Field (MRF) based super resolution reconstruction (SRR) method for remote sensing image with embedded Image Euclidean distance (IMED) is proposed. A robust and transformation invariant similarity metric IMED is integrated for modelling compatibility functions (CF) and finding the similarity between image patches. Unlike traditional Euclidean distance, IMED takes into consideration the spatial relationships of pixels as well as the smallest deformation and therefore provides reasonable result. Further, an iterative belief propagation (BP) algorithm is used to find the optimal candidate patches and therefore high resolution (HR) patches. The experimental results demonstrate that the proposed method outperforms some of the state-of-the-art methods.
The Existence of Staphylococcus Aureus at the Imported Clothing in Makassar City

Used clothing is not good for use because it does not know the history of previous users so that there is a possibility for contracting a very large infectious disease from bacteria on the clothing. Previous research found that the most commonly isolated bacteria are Staphylococcus Aureus, Staphylococcus Aureus can survive on clothing. Indonesia is one of the developing countries in the world which is a destination for used clothing exports. This type of research is quantitative to identify the presence of Staphylococcus Aureus bacteria in imported used clothing that is sold in several markets in Makassar City. The population in this study were traders and used clothing sold in the Makassar City market in South Sulawesi Province consisting of 5 traders in the eggplant market and 5 traders and Gor Sudiang. The sampling technique used is random sampling. The results showed that the merchant's knowledge related to the problem of cleaning used imported clothing so that it is safe when used by consumers is quite good. The attitude of traders has a positive attitude related to the problem of cleanliness of imported used clothing so that it is safe when used by consumers. The actions of traders regarding the problem of cleaning imported second-hand clothing to be safe when used by consumers are quite good. Whereas the results of laboratory tests stated that there were no Staphylococcus Aureus bacteriafound in imported used clothing at the Terong and Gor Sudiang Markets. However, in this laboratory test found another bacterium in imported used clothing, the Bacillus Sp.
Computational Science and Intelligence Programming in Business with Genetic, Generic Algorithms and AI Software Products: An Adaptive Algorithmic Approach

In this research study the topic of Artificial Intelligence and Business is examined. AI methodologies and their usage in several organizations in various applications concerning staffing, careers etc. and hiring predictions are discussed. The concept of genetic and generic algorithms with their several important aspects are discussed and various related applications in a wide spectrum of topics are presented. Various genetic programming implementations with the corresponding related software products are given and several AI software packages, genetic algorithmic methodologies and related applications are presented.
3D phase microscopy with scattering samples (Conference Presentation)

This talk will describe new microscopy methods and computational algorithms that use computational imaging to enable 3D phase measurement in samples that are thick or incur multiple scattering, such as embryos or whole organisms. We use image reconstruction algorithms that are based on large-scale nonlinear non-convex optimization combined with unrolled neural networks to model the multiple scattering effects of light passing through the sample. This enables us to reconstruct 3D refractive index maps from angle-coded illumination, even with samples that incur significant scattering. We further discuss engineering of data capture for computational microscopes by end-to-end learned design.
Video protection by color watermark using a modified cyclic insertion scheme

This paper presents an original algorithm for copyrighting video content by inserting a color watermark. The optimal parameters of the algorithm allow lossless watermark extraction from H.264 encoded video are determined. The proposed algorithm is based on YCbCr transformation, block SVD decomposition, bitplane decomposition and modified reduced cyclic insertion scheme. The results obtained confirm the effectiveness of the proposed algorithm and it can be successfully applied in the protection of video content by color watermark without visible degradation of video content.
Daily predictions of solar radiation utilizing genetic programming techniques

&lt;span&gt;The solar radiation prediction in Kuala Terengganu located in Terengganu, Malaysia was investigated in this study to improve the solar system design. Solar radiation data and number of parameters such as solar radiation, temperature, humidity, wind speed and sunshine hours were obtained from Malaysian Meteorological Malaysia MMD. In order to predict the solar radiation, Genetic Programming Techniques (GP) models were develop and tested. Two scenarios were considered in this study in order to validate the efficiency of the proposed model. Coefficients of determination (R2) for the solar radiation during training and testing phases were ranged between 0.99402 to 0.98934 for all months of the year. This study confirms the ability of GP to predict solar radiation values precisely and accurately. The predictions from the GP models could enable scientists to locate &lt;br /&gt; and design solar energy systems in Malaysia.&lt;/span&gt;
Research Guides: Knowledge Organization and Metadata Services: Description and Organization

Outlines the mission and responsibilities of the department and provides access to the tools used to accomplish this work. Provides summary and links to the basic tools used for describing and organizing library resources
Case-Based Reasoning for Summarizing Simulation Results

Simulations can produce large quantities of data. To reason about the results of simulations, machine-learning methods can be helpful. We explored a case-based reasoning approach to summarizing the results of a probabilistic simulation of naval combat involving missiles. We used a tree structure to index the data and showed that it gave good accuracy in estimating the results of this simulation with new parameters. We are now extending these ideas to a more complex military simulation.
Assessing Potential Educational Use of Two 3D Scanners: Microsoft Kinect v2 and NextEngine 3D Scanner Ultra HD

An education use suitability analysis of two commercially available 3D scanners, Microsoft's Kinect v2 and NextEngine's 3D Scanner Ultra HD, is presented. The analysis includes focus on potential classroom / education use. Highpoints of this are evaluations of (1) accuracy when scanning real-world objects, (2) consistency between scans, and (3) impact of object color on scan quality. In addition, the compatible platforms and available application programming interfaces for each are discussed.
Machine learning in/with information fusion for infrastructure understanding, panel summary

During the 2019 SPIE DSS conference, panelists were invited to highlight the trends and use of artificial intelligence and machine learning (AI/ML) for information fusion. The common themes between the panelists include leveraging AI/ML coordinated with Information Fusion for: (1) knowledge reasoning, (2) model building, (3) object recognition and tracking, (4) multimodal learning, and (5) information processing. The opportunity for machine learning exists within all the fusion levels of the Data Fusion Information Group model.
Modified Illumination Invariant Algorithm Based Human Face Detection

Face recognition systems are adversely affected by multiple external factors like illumination, pose, quality of image etc. Illumination is one of the main factors that hinders the performance of the system, the proposed methodology minimizes the effects of varied lighting conditions on the images. The algorithm uses Histogram of Oriented Gradients (HOG) technique for feature extraction and Error correcting output Codes (ECOC) Multi class Support Vector Machines (SVM) for classification. The results are verified using ORL and Extended Yale Face Database B image sets and goodaccuracy was obtained in the classification of poor and well illuminated images.
Comparison of Complex Behavior via Event Sequences

Simulation-based training would benefit from direct exploitation of observational data obtained during operations. The goal of current research is to develop algorithms and software that transfers data captured in operational settings to training simulation, enabling learners to experience in simulation training a scenario that mimics a real-life situation. In prior work, we explored the direct application of deep learning to this challenge. In this paper, we outline a refined approach that adopts a formally-defined knowledge representation that is used to encode observed changes in state ("events") that occur during operations. The event representation enables explicit comparisons of events and event sequences between observed and generated missions and it allows more tractable application of machine learning for capturing the properties of individual events (in comparison to an entire mission).
Recursive Undersampling-Based Decision Boundary Alignment for Imbalanced Radiology Image

The data imbalance problem is a huge obstacle in radiology field. Although the accuracy of the classifier is very high due to the number of data in the majority class, the classifier is not sufficiently reflected the information of the minority class. In this paper, we proposed a recursive undersampling method that can classify minority class well by shifting decision boundaries from near minority class to near majority class. In this method, iterative sampling is performed on the majority class with the same size as the minority class, but the decision boundary was shifted by reducing the influence of the sampled data near the decision boundary. Through this, the problem of imbalance in the radiology field was partially solved, and the learning of the classifier using all the high-cost medical image data was made possible.
CONDITIONAL PROBABILITY DENSITY AND REGRESSION FUNCTION ESTIMATIONS WITH TRANSFORMATION OF DATA

This study extends 'empirical transformation' in kernel smoothing to conditional probability density and regression function estimations.We propose nonparametric conditional probability density and regression function estimators, which are based on an extension of Ćwik and Mielniczuk (1989)'s method.We derived asymptotic properties of the proposed estimators and conducted a simulation that showed mean squared errors of conditional probability density and regression function estimators.
Differentiable Feature Selection by Discrete Relaxation

In this paper, we introduce Differentiable Feature Selection, a gradient-based search algorithm for feature selection. Our approach extends a recent result on the estimation of learnability in the sublinear data regime by showing that the calculation can be performed iteratively (i.e., in mini-batches) and in linear time and space with respect to both the number of features D and the sample size N. This, along with a discrete-to-continuous relaxation of the search domain, allows for an efficient, gradient-based search algorithm among feature subsets for very large datasets. Our algorithm utilizes higher-order correlations between features and targets for both the N > D and N
Encoding Newton’s Alchemical Library: Integrating Traditional Bibliographic and Modern Computational Methods

The Chymistry of Isaac Newton (http://chymistry.org) project team has digitized and encoded, following the TEI Guidelines, the complete corpus of Newton's alchemical manuscripts, which total more than two thousand pages and over one million words. Newton cited more than five thousand published and unpublished works in these manuscripts; many of his annotations reference items in his own library, as he was an exceptionally dedicated reader of alchemical texts. Newton's extensive citations and annotations provide a window into his alchemical research and practices, and serve as the basis for our authoritative bibliography of his alchemical sources. The bibliography is being developed as both a stand-alone reference work and an integrated resource with the alchemical manuscripts, providing additional context for Newton's citations and florilegia. Once finished, the bibliography will provide complete, structured citations—which often would appear very abbreviated or incomplete in the manuscripts—that can be formatted to comply with modern bibliographic conventions and bibliographic management systems. Our bibliography will also link to digitized online versions of the source texts available through Early English Books Online, HathiTrust Digital Library, and other digital repositories. The citations include quasi-facsimile title page transcription, a technique used for bibliographic description of rare books, to enable richer forms of citation analysis. By analyzing the citations, we will be able to date Newton's manuscripts, cluster manuscripts that cite the same or related sources, and, ultimately, generate network graphs that will reveal connections between the cited authors and texts and how they influence Newton's own ideas and work.
LibGuides: Continuity of Library Research & Services: Expanded Access to Online Resources

This guide will help you locate and access library research and instructional support resources that are available in the event that the University is experiencing cancellation of in-person courses or a campus closure.
Computer vision learning techniques for sports video analytics: removing overlays

Big data has been driving professional sports over the last decade. In our data-driven world, it becomes important to find additional methods for the analysis of both games and athletes. There is an abundance of videos taken in professional and amateur sports. Player datasets can be created utilizing computer vision techniques. We propose a novel approach by creating an autonomous masking algorithm that can receive live or previously recorded video footage of sporting events. This procedure can identify graphical overlays to optimize further processing by tracking and text recognition algorithms for real-time analysis.
Adopting the Appropriate Performance Measures for Soft Computing-based Estimation by Analogy

Soft Computing based estimation by analogy is a lucrative research domain for the software engineering research community. There are a considerable number of models proposed in this research area. Therefore, researchers are of interest to compare the models to identify the best one for software development effort estimation. This research showed that most of the studies used mean magnitude of relative error (MMRE) and percentage of prediction (PRED) for the comparison of their estimation models. Still, it was also found in this study that there are quite a number of criticisms done on accuracy statistics like MMRE and PRED by renowned authors. It was found that MMRE is an unbalanced, biased, and inappropriate performance measure for identifying the best among competing estimation models. The accuracy statistics, e.g., MMRE and PRED, are still adopted in the evaluation criteria by the domain researchers, stating the reason for “widely used,” which is not a valid reason. This research study identified that, since there is no practical solution provided so far, which could replace MMRE and PRED, the researchers are adopting these measures. The approach of partitioning the large dataset into subsamples was tried in this paper using estimation by analogy (EBA) model. One small and one large dataset were considered for it, such as Desharnais and ISBSG release 11. The ISBSG dataset is a large dataset concerning Desharnais. The ISBSG dataset was partitioned into subsamples. The results suggested that when the large datasets are partitioned, the MMRE produces the same or nearly the same results, which it produces for the small dataset. It is observed that the MMRE can be trusted as a performance metric if the large datasets are partitioned into subsamples.
Secure Electronic Medical Record (EMR) System

Personal information protection has emerged as a sensitive issue since General Data Protection Regulation (GDPR), and medical information is sensitive but it has to be used as data for research and other statistical analysis. In this respect, medical information has special attention, unlike other general information. Especially for the medical information in the EMR and EHR systems, the information subject is a patient, but the information generator is a medical staff, not a patient, which is a unique characteristic in that the information subject and the information generator are not the same. However, some security researchers overlooked the characteristics of these medical information and proposed patient-controlled medical information systems, which were not applicable to the current medical law and medical system. To solve this problem, we classify the hospital patient's treatment process step by step, identify the type and characteristics of information generated in each step and apply the appropriate encryption key, and propose a secure protocol that applies cryptographic methods to the entire process from patient treatment to providing information to external organizations.
Sistem Informasi Penjualan Sparepart Mobil Berbasis Web Pada Cv.Cipta Mandiri Jaya

The spare parts that are currently running are less efficient because during the process of selling and recording the spare parts that require a long time, the management of the unbalanced company that is taking place in Cipta Mandiri Jaya is one of the companies that sell car parts. The existence of a debate, then we need an information system that can help smooth operational processes. The purpose of designing this system is to provide the required report information quickly for CV. Cipta Mandiri Jaya. Information systems for sales of goods are designed using the PHP programming language and MySQL as the database. The application that can reduce and minimize the problem of counting, makes it easier to make purchases, sales and purchase transactions more effectively and efficiently and is supported by a high level of data security
MATHEMATICAL MODELING AS THE DIGITAL WORLD BASIS

The article reveals the project idea of creating a city circle "Mathematical modeling as the basis of the digital world", which received grant support in the open competition of the Ministry of education of the Russian Federation in 2019.This competition was held to ensure the implementation of the activity «Creation and support of the organizations of children and (or) children's unions' additional education at schools for in-depth studying of mathematics and informatics" within the Federal project's framework "Personnel for the digital economy national program "Digital economy" state program of the Russian Federation "Development of education"».The project involves the development, testing and implementation of a new model for working with intellectually disabled children and children with high motivation to study in the mathematical and information computer sciences' field.
Research Guides: Earth Day: Participate

To celebrate the 50th anniversary of Earth Day (and the first ever Virtual Earth Day), NYU Libraries has assembled this guide to online books and videos, as well as virtual events, tours, and participatory projects.