Reviewerly/exHarmony huggingface dataset:
Automatization in Vague Database Relations via Lukasiewicz Fuzzy Implication Operator

The needs of the modern world often require automatization of certain aspects of mankind activities.Science is no exception to this. In this paper we pay attention to vague functional dependencies as generalizedfunctional dependencies. These dependencies are considered as fuzzy formulas. We give strict proof of the equivalence: any two-element vague relation instance on given scheme (which satisfies some set of vague functionaldependencies) satisfies given vague functional dependency if and only if the attached fuzzy formula is a logicalconsequence of the corresponding set of fuzzy formulas. Thanks to this result, we put ourselves into position toautomatically verify if some vague functional dependency follows from some set of vague functional dependencies. An appropriate example which supports this claim is also provided.
LibGuides: Learning, Working and Parenting from Home: School from home resources

This guide offers a number of resources to individuals (namely student and/or working parents) who are performing most functions from home. It was created during the COVID-19 pandemic, during which time retainable non-essential work moved online, and on
LibGuides: Online Training Resources for Faculty/Staff: Learn a Language

Compilation of many of the online training sessions available while we are away from campus. Some sessions will be more applicable for library employees, many will be applicable for everyone
Memento hominibus : on the fundamental role of end users in real-world interactions with neuromorphic systems

In this contribution, we briefly examine the role of end users in the evaluation and characterisation of sophisticated AI-based systems, such as autonomous vehicles or near-future robots. Indeed, w ...
Effective Vulnerability Management for Small Scale Organisations in Ghana

Most Small and Medium scale Enterprises (SMEs) in Ghana are notparticularly anxious about the consequences of inadequacy or lack of anyform of vulnerability management operation in their normal bus ...
LibGuides: ESB SLS Tips and Tricks: 2020 - Kayla's Corner

Tips and tricks on a variety of resources found on the Virtual Reference Collection and the Digital Media Library
AN ANALYSIS OF PEDAGIGICAL TEACHER TALK AND STUDENT TALK IN TEACHING ENGLISH AT SMA BILINGUAL BOARDING SCHOOL

Keywords: Pedagogical,Classroom Interaction, Teacher Talk, Student TalkThe purpose of this research is to know the interaction between teachers and students in the process of learning English, and to know the use of teacher talk and student responses to teacher. Interaction is one of the important points in the learning process, because inetraction is the transfer of thoughts, feelings or collaborative ideas between two or morepeople. Specifically in the classroom, aspects of the teacher talk interaction and student learning.This study uses qualitative research with descriptive qualitative methods. The participants of this study were two English teachers at SMA Bilingual Boarding School. The instruments used were observation and interview. The observations was done three times and the interview was done in one time.The reseults of thus study are interaction in the classroom between teachers and students when the learning English process is applied into five types. Interaction that has been done by teachers and students goes well, based on the results of observations and interviewa that researchers have done, the role appears during te learning process as the teacher as a facilitator gives praise, encouragement, comment, motivation, and reinforcement of students who are less enthusiasm in learning. In addition, as students who learn to respond to the teacher.
Geodetic deformation rates and driving processes in metropolitan France and neighboring Western Europe

&amp;lt;p&amp;gt;We constrain present-day deformation rates and styles in metropolitan France and neighboring Western Europe using a dataset of ca. 1200 GNSS horizontal and vertical velocities from continuous and semi-continuous stations. The characterization and correction of network-scale common-mode noise, combined with two independent network analysis technics allow the resolution of very small horizontal velocities (resp. strain rates) with a 95% confidence ca. 0.1&amp;amp;#8211;0.2 mm/yr (resp. ca. 1 x 10&amp;lt;sup&amp;gt;-9&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-9&amp;lt;/sup&amp;gt;) on a spatial scale of 100&amp;amp;#8211;200 km. The resulting velocity and strain rate fields show regional coherent patterns that can be associated with features that have been previously identified (e.g., orogen-normal extension in the Pyrenees and Western Alps), but also with new deformation patterns such as North-South shortening in northeastern France - southwestern Germany north of the Alpine Front (Vosges - Rhine Graben - Black Forest). A joint analysis of these new geodetic data with seismicity and focal mechanism catalogs allows the definition of regional seismo-tectonic models that can be compared with the numerous models of deformation processes proposed for Western Europe, from plate tectonics to erosion or Glacial Isostatic Adjustment. We show that plate and micro-plate tectonics play a minor (probably negligible) role in present-day deformation in metropolitan France and that alternative non-tectonic processes must be considered to better understand the origin of recent moderate earthquakes such as the March 2019 Ml=4.9 Montendre earthquake in the Aquitaine Basin or the Nov. 2019 Mw=4.8 Teil earthquake in the Rhone Valley.&amp;lt;/p&amp;gt;
LibGuides: Exploring Personality Psychology: Databases

This guide is intended for undergraduate students taking courses in personality psychology or related topics.
An Entropy Based Decision Making Problem using Fuzzy Decision Tree Classification of Data Mining

Data mining is a process to discover hidden knowledge or connections among available huge data sets. In this study, we are dealing with structured data set and applying Decision Tree classification, a data mining technique for decision making from the available data set. We consider a data set with both linguistic and numerical attributes. We are applying the Decision Tree technique in fuzzy environment by considering attributes as fuzzy numbers. We consider a training data set for the shortlisting of candidates for the post of assistant professor with attributes: GPA in UG, GPA in PG, Experience, NET Qualified and Doctorate. We are using various forms of Renys entropy in formation of decision tree and we compare the result obtained from various forms of Reny;s entropy. Here the result provides a fuzzy decision tree for the given data set.
LibGuides: Library Resources For Online Classes: Research Help

This guide will take students and faculty through all off-campus accessible Library resources.
Virtual Classroom Sebagai Media Pembelajaran Berbasis Android Pada Ranah Kognitif Dan Penilaian Formatif Mahasiswa Diii Kebidanan Daerah Urban Dan Sub Urban

Objective : This study aims to determine the effect of virtual classroom as an Android-based learning media in the cognitive domain and formative assessment of midwifery students in urban and sub-urban areas. Method : This type of research used in this study is a quasi-experimental design (Quasi experiment) taken with a purposive sampling technique on Midwifery Urban and Sub-urban DIII Students in December 2019 - January 2020. The effect was tested using Chi-square. Results : The results of the analysis using the chi-squre test showed no relationship between the use of virtual classroom as an Android-based learning media in the cognitive domain and in the formative assessment of midwifery students in urban and sub-urban areas. Conclusion : The use of virtual classroom as a medium of learning does not affect cognitive abilities and the feasibility of formative assessment.
LibGuides at Priddy Library: COVID-19: Open Educational Resources (OER) Repositories

A guide for updates, library resources, information, and scholarly content during the coronavirus pandemic
ANALISIS HASIL BELAJAR DAN MASA STUDI MAHASISWA CALON GURU MATEMATIKA

The main objective of this research is to analyze the correlation between learning outcomes in the first year, the final results of study and the period of study of students. The research method used is quantitative (descriptive-associative) method. This research is an ex-post research. The sample of this study was 317 students of the Mathematics Education Study Program, Faculty of Science and Technology from 2006 to 2010. Data analysis techniques used in this study were the average difference test and the correlation test. Research data were collected using documentation. Learning outcomes data in the first year and final study data using IPK data, and study period data using the number of semesters taken by students. This study concludes that the learning outcomes in the first year and the final results of the study of mathematics teacher candidates at UIN Sunan Kalijaga are more than 3.00, but the study period is more than 8 semesters. In addition, this study also concluded that there was a positive correlation between learning outcomes in the first year and the final results of student studies, but there was a negative correlation between learning outcomes in the first year and the period of study of students and between the final results of study and study period of students.
Contributions to Structured and Unstructured Data Analysis: Liquid Association Computation Acceleration and Word Similarity via Folksonomy

Author(s): Wu, GuanI | Advisor(s): Li, Ker-Chau | Abstract: In this thesis, I organize two independent projects into five chapters. The first chapter introduces Liquid Association and our proposed method to accelerate its computation. The second chapter is related to the design of the computational structure for Liquid Association website (LAP3). The third chapter is regarding the application of Liquid Association to Global Health Observatory (GHO) data. The fourth chapter describes a novel method to model the distribution of human ratings on word-similarity. The last chapter focuses on the analysis of the relationship between the knowledge-based approach and the corpus-based approach.
APPLYING VARIOUS MACHINE LEARNING TECHNIQUES FOR THE CLASSIFICATION OF WEBSERVICES: A SURVEY

The task of allocating a category or class to a web service from the existing collection of webservices is known as web services classification. Currently, manually discovering the desired web services fromthe repository or manually organizing the web services as per category is a challenging job. The reason behind thisis the increasing number of web services that are registered to the repository. Hence, web service classificationplays a significant role in web service technology and service-oriented architecture. There are numerous methodsthat can be implemented for classification of web services. The main emphasis of this study is reviewing themachine-learning algorithms that can efficiently classify web services to their respective category. This paperreviews the available research methods of web services classification. The research papers published between2008 and 2020 are considered here for writing this survey paper. This paper explains various machine learningapproaches for the classification of web services.
Beyond the #justice hashtags: Understanding digital participation after police-involved Deaths

How is justice expressed through tweets in the context of events that reflect police violence against citizens? What is the impact of using different methods for detecting relevant content?• Hashtags• Machine Learning
Library: MLA Style: MLA Style Guidelines

This guide covers the basics of the 8th edition of the MLA Style Manual and includes sample citations and additional resources. Find examples and information about how to use the MLA Guidelines and format your references
Loma Linda University Libraries: Citation Style Guide: Chicago

How to cite electronic documents in AMA, APA, MLA, and Chicago styles, plus links to further information on these style formats.
A Study on Operational Efficiency Analysis of Regional Art Center Using AHP/DEA-AR Model

The purpose of this study is to analyze the operation efficiency of the Art Centers by region by dividing our country by 17 regional units, and to present efficiency improvement measures for inefficiently operated areas. Through AHP analysis, quantitative variables were weighted and operational efficiency was analyzed through the DEA-AR model. The WINDOW model was used to analyze trends in the operation of local Art Centers. Based on the results of this study, it suggested which variables are important and which variables need to be improved to improve the efficiency of the operation of the Art Centers in areas where efficiency is deteriorating, and provided direction for what action is needed.
An Empirical Study on the Trial Operation of Criminal Justice Identification System

Civil proceedings; Judicial appraisal disputes; Appraisal disputes; Resolution mechanism
Patrimônio documental e acervos: políticas públicas através da formação do acervo documental da Biblioteca do Museu da Companhia Paulista

The article studies the documental collection of the Museu da Companhia Paulista in Jundiai and aims to identify how the formation of the documental collection took place in order to contribute to its valuation and organization as a documentary and railway heritage. It’s purpose is to identify, then, the origin of this set, the time and conditions under which it was gathered in a collection, the function and applicability of public policies in its specific case. It should be noted that the gathering of the documentary set in a collection and its historical conditions in the 1990s and 2000s reveals beyond the institution's history, the form of public management of the time. The relations established between the creation of this collection and the institutions that originated it, generate reflections on the way the patrimonial processes were managed during the privatization period.
Property Rights and Economic Growth in Africa: An Econometric Analysis

The purpose of this paper is to establish a positive correlation between property rights and economic freedom. It seeks to demonstrate that property rights lead to economic freedom. From a purely theoretical perspective, it has been assumed that greater access to property rights leads to economic freedom, consequently to sustainable economic growth. To establish this correlation in the case of Africa, we applied the use of statistical tools to substantiate the validity of our economic theory. We mainly used a simple linear regression to ascertain our hypothesis.
Momentas No.1

Author(s): Vdovinskyte, Dorote | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Method for Expert Search Using Topical Similarity of Documents

The article describes the problem of finding and selecting experts for reviewing grant applications, proposals and scientific papers. The main shortcomings of the methods that are currently used to solve this problem were analyzed. These shortcomings can be eliminated by analyzing large collections of sci-tech documents, the authors of which are potential experts on various topics. The article describes a method that forms a ranked list of experts for a given document using a search for documents that are similar in topic. To evaluate the proposed method, we used a collection of grant applications from a science foundation. The proposed method is compared with the method based on topic modeling. Experimental studies show that in terms of such metrics as recall, MAP and NDCG, the proposed method is slightly better. In conclusion, the current limitations of the proposed method are discussed.
Towards Learning Obstacles to Avoid Collisions in Autonomous Robot Navigation

Avoiding obstacles is one of the main tasks in robotic navigation. In this paper, robot navigation using monocular vision is presented. Therefore, an accuracy in the segmentation of obstacles is necessary to avoid collisions by estimating the Time-to-Contact. Our proposal in this research process is based on using YOLO so that through a training process, the robot identifies which regions of the image are potentially obstacles. The experimentation was performed in a real environment, with low daylight and without controlling lighting parameters. The first results of this approach are satisfactory although this project will continue with the learning of other obstacles.
Nature Inspired Algorithms multi-objective histogram equalization for Grey image enhancement

Nature is a very rich source of inspiration. Many algorithms have inspired from nature and source of algorithms inspiration development are diverse with different quality.  Nature–inspired optimization techniques play an essential role in the field of image processing. It reduces the noise and blurring of images with improves the image enhancement, image segmentation, image pattern recognition. The Image enhancement is a process to make image ready for further uses in certain applications. The image quality is individually related with its contrast by rising the contrast, further disfigurements can be produced. In this paper covers current equalization enhancement technique some nature inspired algorithm for medical images. In addition, proposed an image enhancement method built by using two natures inspired algorithms Particle Swarm Optimization (PSO) and Bat Optimization Algorithms (BOA) combined to produce better enhancement. Here an objective criterion for measuring image enhancement is used which considers the Discrete Entropy (DE), the Structural Similarity Index Matrix (SSIM) and Executing Time (ET). The results showed the Bat Algorithm has produced a batter enhanced images when comparing with Particle Swarm Optimization images and the existing histogram-based equalization methods. The final results showed proposed image enhancement method can not only improve the contrast of the image, but also preserve the details of the image, which has a good visual effect.
LibGuides: Interlibrary Loan: How ILL Works

Interlibrary Loan (ILL) Office borrows materials from and lends materials to other libraries in the United States and many other countries.
REAL-TIME ENTITY DETECTION AND IDENTIFICATION USING IMAGE PROCESSING AND DEEP LEARNING

Computer vision is a field of deep learning that makes use of webcam from which real time object detection and identification is done via image processing. It is used to detect various objects, human beings, animals. There is a remarkable need for a lightweight model for multiple object detection for devices which are not capable of computational power like laptops and mobile phones. This paper proposed a model for live multiple object detection based on CNN called as Single time Multiple Detection (STD) which is a lightweight model used in proposed work. Keras is a powerful tool that is used for training the model and quickly enabled to build and deploy as an image recognition software. This paper mostly focuses on detecting multiple objects in single time to ease multiple object detection, we have got keras used to train models and we have used CNN algorithms for implementation. This model is experimented on coco dataset for detecting single time multiple objects. Experimental results reveal that use of STD models increases the accuracy level in identifying the real time multiple objects.
Exploring Voice-Controlled System : Services and Consumer Preferences towards future usage within the Food Industry

As voice assistants and voice-controlled devices continue to gain traction, companies worldwide are exploring the potentials that voice-controlled systems can offer - an ability to connect with use ...
Integrated Approach for Waste Management

To understand the various types of waste and where the world facing problems to all these wastes and fighting with the help with different weapons and still not achieved goal to overcome on it. This paper gives some blinks towards the facts of the waste and its impacts. Moreover, paper concentrates on Ocean waste which is the biggest dangerous enemy of humankind and sea animals and ecosystem.
Analysis of key points and corresponding effects of the construction of water-saving institutions

Abstract The construction of water-saving institutions is an important part of the implementation of the priority policy of water-saving. In view of the current situation of the construction of water-saving institutions in Zhejiang province, the main problems in the constructions were summarized, and the key points of the constructions were put forward, which is of important reference significance to construct the water saving institutions. The main progress and experience was introduced and the water saving effect was analysed based an application case, which has a promising future for application.
A Markov Chain Representation of Human Reasoning and Scientific Thinking

Reasoning is the most important human brain operation that leads to creative methodologies, algorithms and deductions giving way to sustainable research and development. Since the basis of reasoning in the Artificial Intelligence’s expert systems is human notions and concepts, the success of those systems depends upon the correspondence between human reasoning and their formalization. The paper at hands studies human reasoning in general and scientific thinking in particular with the help of the theory of finite Markov chains. Examples are also presented illustrating the applicability of the developed Markov chain models to real life situations.
PLAY: A Profiled Linear Weighting Scheme for Understanding the Influence of Input Variables on the Output of a Deep Artificial Neural Network

Recently, deep artificial neural networks (DANNs) have been successfully applied to various pattern recognition tasks with high industrial impact. Their results are so convincing that neural nets are already tested in heavily regulated fields like medicine or finance. However, these autonomous systems are often deployed without evaluating the reasoning behind their decisions. Thus, recent research has shifted towards methods that increase the interpretability of DANNs. The goal of this paper is to explain the influence of input variables on the decision of a DANN. More precisely, we aim at improving the linear weighting scheme for the contribution of input variables (LICON), a previously introduced method which estimates the contributions of inputs in a local neighborhood, by combining it with the gobal sensitivity approach(GSA), which uses sampling to examine multiple values of an input. This allows the local influence estimation of LICON to be assessed in relation to estimates obtained from sampled input values. The effectiveness of the proposed approach is assessed via a comparative study of the involved explanation methods. Despite the computational complexity, which has to be dealt with in the future, it is shown that the proposed approach generates reasonable estimates for input contributions.
Social and Musical Effects of Co-writing : Performing and analyzing six co-writes

This study examines social factors in songwriting collaborations with the aim to understand the inner workings of co-writes. Previous research indicates significant benefits with songwriting collab ...