Reviewerly/exHarmony huggingface dataset:
AI supported Topic Modeling using KNIME-Workflows.

Topic modeling algorithms traditionally model topics as list of weighted terms. These topic models can be used effectively to classify texts or to support text mining tasks such as text summarization or fact extraction. The general procedure relies on statistical analysis of term frequencies. The focus of this work is on the implementation of the knowledge-based topic modelling services in a KNIME workflow. A brief description and evaluation of the DBPedia-based enrichment approach and the comparative evaluation of enriched topic models will be outlined based on our previous work. DBpedia-Spotlight is used to identify entities in the input text and information from DBpedia is used to extend these entities. We provide a workflow developed in KNIME implementing this approach and perform a result comparison of topic modeling supported by knowledge base information to traditional LDA. This topic modeling approach allows semantic interpretation both by algorithms and by humans.
Research on Resource Guarantee of Social Sports Specialty for Community Sports Development

Through using the method of documentation to analyze the development problems of community sports, this paper finds that school physical education cultivates excellent talents, provides infrastructure and lays a solid foundation for the development of community sports. That school physical education provides resource guarantee for community sports is the further popularization and development of national fitness campaign, the socialization of school physical education and the improvement of the practical social value of school physical education. School physical education is an inevitable demand, an important guarantee, an important way and an effective guarantee to alleviate and improve the deficiency of social sports resources.
Text Line Adjustment Based on Neural Network

With the development of artificial intelligence technology, many generation models have emerged. People generate words in various ways. For example, different forms of English characters and numbers can be generated through Generative Adversarial Network (GAN). Then, lines can be synthesized from words. However, most people only use some well-defined rules to synthesize text from single word. The result depends on people's experience. Therefore, the generated lines often seem inconsistent, especially when generating handwriting line. For example, it's hard to make the adjacent parts of the look real. Moreover, adjacent words may have different styles. These problems can not be solved by simply modifying the synthesis program. In this paper, we attempts to use neural networks to adjust the synthesized lines. The input of our model is a synthetic line, and then it can output a more coordinated line. Four different loss and a discriminator ensure the quality of the generated lines. In experiments, our neural network has successfully corrected many unnatural aspects of synthetic lines. Considering that no one has tried to adjust the word at the line level, our experiment offers novel and valuable insights.
Geological structural interpretation of Qinglong area in Hebei based on multi-source remote sensing data

The spatial resolution of multi-spectral remote sensing data can satisfy multi-scale structure interpretation. The authors took Qinglong area in Hebei as the study area, utilized the comprehens ive advantages of ETM+ , Spot6 and WorldView3 data of the study area to interpret the geological structures at two different levels from ETM+ data with 15 m resolution and Spot6 data with 6 m resolution to WorldView3 data with 0.5m resolution, and obtained a goo d result. Firstly, based on ETM+ data interpretation structure, the band operation results of SPOT6 data are used to indirectly reflect the structure informat ion, and the high resolution WorldView3 data is integrated to construct the interpretation analysis. Finally, the interpretation structure information is revised based on field validation. The results show that multi-source remote sensing data have the characteristics of high resolution, accuracy and high efficiency in geological structure interpretation.
Content Analysis of Library Consortia Websites

This study aims to analyse the contents of the services, search interfaces, e-resources and other facilities available on their respective library consortia websites by using a checklist. The results of this study revealed that the majority of library consortia websites are consisting of different content patterns and imparting diverse information regarding their respective consortia while only few library consortia websites are using very few web 2.0 applications. It was also found that some library consortia websites did not contain essential contents; therefore, such library consortia websites need improvement. This study will be helpful to judge the quality of the contents of the respective library consortia websites.
Elimination of Spatial Side-Channel Information for Compact Quantum Key Distribution Senders

For a compact quantum key distribution (QKD) sender for the polarization encoding BB84 protocol, an eavesdropper could take a side-channel attack by measuring the spatial information of photons to infer their polarizations. The possibility of this attack can be reduced by introducing an aperture in the QKD sender, however, the effect of the aperture on the QKD security lacks of quantitative analysis. In this paper, we analyze the mutual information between the actual keys encoded at this QKD sender and the inferred keys at the eavesdropper (Eve), demonstrating the effect of the aperture to eliminate the spatial side-channel information quantitatively. It shows that Eve’s potential on eavesdropping spatial side-channel information is totally dependent on the optical design of the QKD sender, including the source arrangement and the aperture. The height of compact QKD senders with integrated light-emitting diode (LED) arrays could be controlled under several millimeters, showing great potential on applications in portable equipment.
University science. Internal possibilities of stimulating scientific activity in Russian universities [Университетская Наука. Внутренние Возможности Стимулирования Научной Деятельности В Российских Университетах]

The statistics of research funding are reviewed, the experience of organizing research activities in Russian universities is summarized, and a model of its system support is proposed by the university itself. It is stated that in university science there is a “customer crisis”: the demand of the business sector does not provide the necessary volume of large and long-term orders for scientific research and studies rely mainly on the state budget. Organizational measures are proposed for a gradual transition from teaching to research with step-by-step confirmation of productivity: the creation of a new university subject – a “scientific unit” consisting of two or more employees, regardless of their academic title, with administrative rights and corresponding responsibility.
Realidad Aumentada del Conocimiento del Medio Ambiente Social en el salón de clases de Primaria

The increased use of information and communication technologies is now a reality that cannot be ignored. The portals, blogs, videos, etc., that we can find on the internet about positive experiences of their use show that the teacher-mediated use of them can turn the curriculum into something that is more attractive to students. Therefore, subjects such as Mathematics, which have a significant degree of complexity for some students, can become appealing and “simple”. One of the so-called emergent technologies, which day by day has become more evident, is Augmented Reality. Saddled between virtual reality and scenic realism, its addition to classroom methodologies implies the possibility of experiencing the content first-hand. In this article, we present the results of a teaching innovation experiment conducted with Primary School students in Spain. Through the “Augment” program, the specific content named “The machines” was developed. This content corresponded to the school subject of Sciences. The starting hypothesis consisted on the use of Augmented Reality for the consolidation of content explained in the traditional manner. Afterwards, the students evaluated the experience developed. The main result obtained is the positive scoring of the tool by the students. Thus, we can conclude, plausibly, that its use in the classroom facilitates the learning of complex content.
Modular Addition and Multiplication

This chapter consists of two sections that cover algorithms and hardware architectures for modular addition and multiplication: (x + y) mod m and xy mod m. Subtraction and division are also included—as the addition of an inverse and as multiplication by an inverse. The underlying algorithms and hardware structures are those of Chap. 1 , modified for modular arithmetic. For both operations we shall consider generic algorithms and hardware structures for arbitrary moduli and also those for special moduli.
LibGuides: UBorrow Guide: Lending Statuses

This guide is the beginnings of comprehensive information about UBorrow and the AlephILL client.
Building a Culture of Assessment at Bucknell University

Assessment UpdateVolume 32, Issue 1 p. 10-15 Articles Building a Culture of Assessment at Bucknell University Kevork Horissian, Kevork HorissianSearch for more papers by this author Kevork Horissian, Kevork HorissianSearch for more papers by this author First published: 31 January 2020 https://doi.org/10.1002/au.30201Read 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 No abstract is available for this article. Volume32, Issue1January/February 2020Pages 10-15 RelatedInformation
Secure cryptographic protocol applied to the process of public tendering for contracting services

A tender is a regulated process through which an organization publicly discloses a contract, requests offers that satisfy it, evaluated these offers and selects one of them based on defined criteria. This article stablishes the necessary requirements in a secure tendering protocol, a proposal is performed using cryptographic primitives and the protocol is verified if it complies correctly with the security functions through an implementation in Maple mathematical software. The main objective is to maintain the integrity, authentication, non-repudiation and confidentiality of the documents involved as appropriate.
Illusion Garden: Space Manipulation for illusion with Projection Mapping

A exploration of integrating spatial augmented reality (mainly projection mapping) into space design to create spatial illusion. A method to compress the space and change audience's perception of space by mainpulation of these illusion, mainly including influence on some psychological cues of space cognition. The project is an immersive theater in Suzhou, China.
AN AGGREGATION OF SURVEY QUESTIONNAIRES IN A FUZZY ENVIRONMENT AND ITS APPLICATION

In the response process of survey questionnaires, respondents generally express their opinions (assessment) in a fuzzy environment, i.e., assessment with a degree of membership, and in many cases, an aggregation of survey questionnaires is generally computed mathematically. In this paper, we propose a new aggregation method using the FEV (Fuzzy Expected Value) in summarizing survey questionnaires. As an application of proposed aggregation method, to quantify accurately the current state of opinions and the reasons for national IT investment increasing the rate of economic growth, we decided to circulate a survey questionnaire on national IT investment to interested parties throughout the research institute, government, IT industry. Generally, as we have already known and experienced in most of survey questionnaires, there was a little response. Moreover, according to interested parties, the result was biased views on the government IT investment. So, we consider big data analysis on the selection of the proper IT items for national investment. Proposed aggregation method is consisted of 2-phases. In phase 1, keyword selection for the proper IT items based on big data such as Facebook, Twitter, blog, Google, etc. is achieved. This phase is not mandatory (optional and dependent on the characteristic of survey). In phase 2, aggregation by using the FEV is obtained. Proposed aggregation method on survey questionnaires is particularly useful to find current focal issues such as trend, what’s new, etc., on big data such as Facebook, Twitter, blog, Google, etc. Moreover, in many cases, aggregation using the FEV is a better representative value than the arithmetic mean. Generally, the FEV is more suitable than the value of averaging computation in searching for the representative value of fuzzy set.
Developing Multiple Linear Regression Models for the Number of Citations: A Case Study of Florida International University Professors

Research Gate (RG) is a social networking website where experts from different fields can share their research papers, ask questions that spark a dialogue regarding research related topics, and recommend useful papers to other researchers. This paper aims to examine what factors, or regressors, influence the number of citations that a Florida International University (FIU) professor receives on Research Gate (RG). The nine regressors considered are the Total Research Interest, the number of recommendations, the number of reads, the number of research items, the number of projects, the number of questions, the number of answers, the number of followers, and the number of following associated with each professor. After fitting a number of multiple linear regression models and implementing a variety of techniques to evaluate each models’ adequacy, we concluded that the number of citations that a FIU professor has on RG is influenced by the total research interest, the number of recommendations, the number of reads, the number of research items, and the number of followers that a professor has.
LibGuides: Library Resources Help: Videos

Videos & links to videos to aid in using Library and other electronic resources. Some items may be Panopto recordings.
Direct Adaptive Data Cloud based Fuzzy Control for NARMAX System

This work presents a novel nonlinear direct adaptive data cloud based fuzzy controller design method for a general class of NARMAX systems employing the evolving fuzzy approximation. In the proposed fuzzy controller, dynamic approximation capability is performed by the combined action of structure configuration and parameter adjustment using multiple strategies of recruiting, pruning and updating the data clouds, and self-tuning the consequent parameters. The normalization distance between two local densities is employed to measure the familiarity of each two data clouds, which is the criteria to trigger the pruning of redundant data cloud to further avoid the overlap or conflict. The simulation results demonstrate low computation cost and favorable tracking performance.
A comparative study of meta-heuristic optimisation techniques for prioritisation of risks in agile software development

Risks are in general termed as threats or uncertainties that influence the project performance and its outcomes to the greater extent. To ensure software quality and project success, every organisation should enforce a proper mechanism to efficiently manage the risks irrespective of the development model they follow. Risk prioritisation is a most critical step in risk management process that helps the organisation to resolve the risks in shorter duration of time. In this paper, a comparative study about different meta-heuristic optimisation techniques for prioritising the risks in agile environments is presented. The five most effective meta-heuristic optimisation algorithms such as Genetic Algorithm (GA), Particle Swarm Optimisation (PSO), Ant Colony Optimisation (ACO), Grey Wolf Optimisation (GWO) and Analytical Hierarchy Process (AHP) are considered and the results are evaluated based on four key criterion attributes such as error rate, accuracy, reliability, and running time. The result proves that GWO outperforms other four meta-heuristic optimisation techniques for the prioritisation of risks in agile environment.
SMART (Smart mathematic with augmented reality technology) application for preschool

The focus of this project is on Augmented Reality. This study is about the development of early mathematics education applications for preschool children by using the Augmented Reality technology approach. 2D illustrated books used by teachers in the classroom or parents at home as a medium of early mathematic learning for preschoolers are getting boring and not following the latest technology developments. The traditional 2D picture book is now more attractive with the existence of augmented reality technology which is capable to bring 3D objects on the 2D image. In addition, the delivery of learning content can also be delivered more easily without the adult full guidance. In line with current phenomenon where children prefer to use gadgets instead of books, this application combines both elements which is book and gadget to enhance the interactive and fun levels among preschoolers to explore the contents of pre-school math learning. The development of SMART (Preschool Early Mathematic) is based on the Preschool Standard Curriculum (KSPK) and has been developed using the ADDIE model method. Through this application, early math learning whether at preschool or home is certainly more fun. With the existence of this application, it is hoped that it can help to increase the mastery of numerical concepts and math skills among preschoolers.
BERT-Based Arabic Social Media Author Profiling.

We report our models for detecting age, language variety, and gender from social media data in the context of the Arabic author profiling and deception detection shared task (APDA). We build simple models based on pre-trained bidirectional encoders from transformers (BERT). We first fine-tune the pre-trained BERT model on each of the three datasets with shared task released data. Then we augment shared task data with in-house data for gender and dialect, showing the utility of augmenting training data. Our best models on the shared task test data are acquired with a majority voting of various BERT models trained under different data conditions. We acquire 54.72% accuracy for age, 93.75% for dialect, 81.67% for gender, and 40.97% joint accuracy across the three tasks.
Formal specification and validation of refinement from WS-CDL to BPEL

Service composition is a primary task in the development of service-oriented systems. The Web Service Process Execution Language (WS-BPEL) and the Web Service Choreography Descriptor Language (WS-CDL) are two major languages for Web services modeling and implementation. Although these two composition models are of a different nature, they are complementary. WS-CDL serves as a behavioral modeling language for collaboration between multiple participants (web services) within the same business process from a global point of view. However, WS-BPEL allows a service composition process to be described at different levels of abstraction. At a high level, the description follows a global point of view and deals only with the exchange of messages between participating abstract services (represented abstractly by roles). WS-CDL descriptions are thus considered as a specification of the abstract service composition from which more concrete WS-BPEL processes are extracted. In this article, we present a formal modeling and analysis approach based on sequential communication process (CSP) in order to verify the behavioral consistency between abstract choreographic descriptions and executable BPEL processes, thereby proving the correctness of the translation process.
On the Letac-Massam conjecture and existence of high dimensional Bayes estimators for graphical models

The Wishart distribution defined on the open cone of positive-definite matrices plays a central role in multivariate analysis and multivariate distribution theory. Its domain of parameters is often referred to as the Gindikin set. In recent years, varieties of useful extensions of the Wishart distribution have been proposed in the literature for the purposes of studying Markov random fields and graphical models. In particular, generalizations of the Wishart distribution, referred to as Type I and Type II (graphical) Wishart distributions introduced by Letac and Massam in Annals of Statistics (2007) play important roles in both frequentist and Bayesian inference for Gaussian graphical models. These distributions have been especially useful in high-dimensional settings due to the flexibility offered by their multiple-shape parameters. Concerning Type I and Type II Wishart distributions, a conjecture of Letac and Massam concerns the domain of multiple-shape parameters of these distributions. The conjecture also has implications for the existence of Bayes estimators corresponding to these high dimensional priors. The conjecture, which was first posed in the Annals of Statistics, has now been an open problem for about 10 years. In this paper, we give a necessary condition for the Letac and Massam conjecture to hold. More precisely, we prove that if the Letac and Massam conjecture holds on a decomposable graph, then no two separators of the graph can be nested within each other. For this, we analyze Type I and Type II Wishart distributions on appropriate Markov equivalent perfect DAG models and succeed in deriving the aforementioned necessary condition. This condition in particular identifies a class of counterexamples to the conjecture.
Students’ Enthusiasm For Learning General English At Language Development Unit

. Enthusiasm in one's life and self is very important, especially for learningand the world of work, because without enthusiasm in every human being we willnot be able to support the achievements to be achieved, enthusiasm becomes animportant part of human life for example enthusiasm in learning in order to achievevalue and become the best graduate so that it is easy in the world of work or can becalled will get a job easily and according to what they want, the reason is interestedin doing research on students' enthusiasm in learning English by analyzing theirlevel of enthusiasm in learning and seeing their enthusiastic relationship withachivement they have achieved.The research subjects took from the UPB class groups one and group twowhich consisted of all departments and faculties. The author examines theirenthusiasm by observing in class, and interviewing. The design of this study isqualitative research. To collect data, the author uses several techniques such asinterviews. Data processing in this study was divided into four phases: datacollection, data reduction, data display, and drawing conclusions. Then, all data areanalyzed and concluded descriptively.The results of this study indicate that: 1. Enthusiasm students are veryinfluential on themselves and also the teacher is very influential on the anthusiasmof their learning in the classroom