Reviewerly/exHarmony huggingface dataset:
A General Method for Composing an Engineering HB

As is also the case in other engineering disciplines, software engineering knowledge can be organised in the categories of engineering knowledge identified by Vincenti [84]:
FRAMEWORK FOR ENGLISH LANGUAGE LEARNING BASED ON SABUNESE FOLKLORE AS A MEANS FOR ENRICHING LEXICAL KNOWLEDGE RELATED TO SABUNESE TRADITIONAL ECONOMIC SYSTEMS

This research aims to develop a framework for English language learning based on Sabunese folklore as a means for enriching lexical knowledge related to traditional economic systems within the Sabunese culture. Theoretical framework on which this research is based on is applied cultural linguistic which empowers local cultural products and practices of  Sabunese people in form of folklores as the basis for modelling English language learning based on local culture.  This research is that of a descriptive study which blends analysis and its application in form of framework development. Research results develop the English language learning framework based on Sabunese folklore which functions as an approach to enrichment of lexical knowledge related to traditional economic systems which encompasses agriculture, farming, and trading systems. The framework development is that of a single entry – multiple outputs, as the model provides several outputs besides enrichment approach to lexical knowledge related to traditional economic systems embedded within the Sabunese culture as the main focus of this research. The developed framework is applicable to other fields with necessary modifications depending on specific aims and context.
End-to-End Estimation of Multi-Person 3D Poses from Multiple Cameras

We present an approach to estimate 3D poses of multiple people from multiplecamera views. In contrast to the previous efforts which require to establishcross-view correspondence based on noisy and incomplete 2D pose estimations, wepresent an end-to-end solution which directly operates in the $3$D space,therefore avoids making incorrect decisions in the 2D space. To achieve thisgoal, the features in all camera views are warped and aggregated in a common 3Dspace, and fed into Cuboid Proposal Network (CPN) to coarsely localize allpeople. Then we propose Pose Regression Network (PRN) to estimate a detailed 3Dpose for each proposal. The approach is robust to occlusion which occursfrequently in practice. Without bells and whistles, it outperforms thestate-of-the-arts on the public datasets. Code will be released athttps://github.com/microsoft/multiperson-pose-estimation-pytorch.
Consideration of Gravity Potential Energy and Energy-Mass Conservation Law

When two objects with a mass of m are d apart, convert the mass of this object into energy using E=mc^2, and 2mc^2 will come out. However, once you attach this object to gravity and convert it all into energy, with 2mc^2, gravity potential energy will be converted to as much energy as Gm^2/d. An object of the same mass emitted different energy. We need to rethink the potential energy and energy-mass conservation law.
LibGuides: IELTS: Key resources

This guide provides links to sources that will help with International English Language Testing System (IELTS)
Cirkuszművészeti központok tartalomszolgáltatási modelljei

Within the framework of a professional co-operation agreement between the National Circus Arts Centre and the Eotvos Lorand University Faculty of Humanities (concluded on September 6, 2019), the Institute of Library and Information Science takes part in establishing the Library of the Centre. This library will work at the same time as the Central European Research Centre and Data Store in the field of Circus Arts. By identifying and listing foreign circus arts institutions with important public collections, and analyzing their best practices, the parties intend to support the adaptation of state-of-the-art content delivery systems and community programmes organized by libraries in Hungary.
The Prospects of Expanding the Raw Materials Source of Gold-Silver Ore Occurrence in Sentyabrskoe SV (Chukotka Autonomous Area)

Abstract The Chukotka autonomous area of Russia holds one of the leading positions in Russia in the gold mining. Various formational types’ deposits are known to this region. Among the most industrially interesting types are bonanza gold-silver sites in Kupol, Dvoinoye, Sentyabrskoe and many others. This article studies the prospects of extending the raw materials’ source of the gold-silver ore occurrence in Sentyabrskoe on the basis of its comparison with the known sites of this type.
Sculptural sounds: a co-compositional approach

This article discusses a specific approach to sound from a sculptural perspective, based on an innovative process named "co-composition", in which physical and sonic material can be concurrently produced, rearranged and transformed in a solo environment. This approach investigates ways of working with the direct response of materials to performed actions by mapping actions of making in ways that can inform new actions through sound. I question the way sculptural sounds are caused and how sounds and their real-time transformation could influence the way I understand the process as a practitioner and researcher, and how this is experienced by the audience. How does the process change once sound is transformed to something different, new? How does this affect practising with sound as more than sound? To achieve this, I develop new ways of articulating aesthetic decisions from one medium to the other on the basis of their "stories" as they are manifested through traces of material manipulation.
Data Safeguarding in Cloud in AES using in Heroku Cloud

Cloud  computing data guarding is an evolving growing domain which operates on “PaaS” model  which uses the third party model Heroku cloud  as  storage and access, it supports various programming language which are new and old by using the codified algorithm, most of the old  techniques used the unmodified “Advance encryption standard” which is most consuming overall time for the data store in the cloud for avoid this issue there need simplify a lot in code of the algorithm, we on here implement” Altered Advance encryption standard as data security, encryption, pass key sending to the user and Heroku as the cloud platform to provide clients access and to reduce time taken in the decryption of the message.
Multi-Objective Evolutionary approach for the Performance Improvement of Learners using Ensembling Feature selection and Discretization Technique on Medical data

Biomedical data is filled with continuous real values; these values in the feature set tend to create problems like underfitting, the curse of dimensionality and increase in misclassification rate because of higher variance. In response, pre-processing techniques on dataset minimizes the side effects and have shown success in maintaining the adequate accuracy. Feature selection and discretization are the two necessary preprocessing steps that were effectively employed to handle the data redundancies in the biomedical data. However, in the previous works, the absence of unified effort by integrating feature selection and discretization together in solving the data redundancy problem leads to the disjoint and fragmented field. This paper proposes a novel multi-objective based dimensionality reduction framework, which incorporates both discretization and feature reduction as an ensemble model for performing feature selection and discretization. Selection of optimal features and the categorization of discretized and non-discretized features from the feature subset is governed by the multi-objective genetic algorithm (NSGA-II). The two objective, minimizing the error rate during the feature selection and maximizing the information gain while discretization is considered as fitness criteria.
Decline of Auditor's Financial Bias in Decision making by Professionalism in Auditing: Rough Set Analysis

The purpose of the research Decline of Auditors' Financial Bias in Decision making by Professionalism in Auditing: Rough Set Analysis. The research approach is of inductive-deductive type in terms of the data collection meth-od, because it was first determined based on the content analysis of the com-ponents and propositions related to the professional characteristics, then it was tried to confirm or delete the propositions based on the Delphi analysis. This research by participating 14 individuals of the audit partners with the academic degrees over a one-year period, 2018-2019. The results According to the formation of decision making matrix, the results showed that both propositions, the perceptual error of failure to separate the context from con-tent as the Halo bias and the perceptual error of the experience of fraud de-tection in the financial statement as memory bias were determined as the most influential perceptual errors in the audit profession in Iran. In addition, according to gray vikor theory analysis, it was found that the component of the audit's professional maturity was selected as the most important priority and the most effective feature for reducing the audit perceptual bias.
LibGuides: Humanities Research Guide : Databases

This guide was created to assist researchers in the Humanities by highlighting available resources at the Alma Jordan Library and pointing to other helpful tools and websites.
Research Guides: The Open Science Framework (OSF) at Virginia Tech: What is the Open Science Framework (OSF)?

This libguide introduces you to the free research management platform, the Open Science Framework. To access OSF, visit https://osf.io/institutions/vt/
Multimedia Learning Introduction to Animal Development in Primary School Students Using Adobe Flash Cs 3

The media is one of the factors that also determines the success of teaching because it helps students and teachers deliver the subject matter in connection with the teaching objectives. In this condition the use of instructional media in the form of multimedia can improve the efficiency of the process and the quality of teaching and learning outcomes. the use of media in the teaching and learning process can arouse new desires and interests, generate motivation and stimuli for learning. In dealing with students who can be said to not be able to motivate themselves, this becomes a challenge for a teacher. So that the application of multimedia applications can help students in learning, training and directing students in primary schools in the introduction of animal development
Comparative Analysis of Saemaul Education Based on Experiential Learning Model

본 연구는 근거이론으로 분석한 70년대 새마을교육의 특성에 관한 선행연구 결과물을 Kolb의 경험학습과 비교분석하여 새마을교육의 이론적 배경을 탐색하는 것을 목적으로 두고 있다. 이를 위해 경험학습의 단계별 특성과 유사한 새마을교육의 특성을 확인하였다. 경험학습의 구체적 경험 측면에서 연수생들은 정서적 개방상태에서 교육에 임하였고, 교육적 자극에 대해 적극적으로 반응하였다. 반성적 관찰 측면에서 연수생들은 경험공유적인 활동과 연수원 임직원들의 솔선수범 등을 통하여 기존 관념과 행태에 대해 성찰하고, 새마을지도자로서의 정체성을 인식하게 되었다. 추상적 개념화 측면에서 연수생들은 의미를 부여했던 경험들을 새마을운동 실천기법과 생활철학 등의 형태로 개념화하였다. 적극적 실험 측면에서 연수생들은 새마을운동 실천기법을 가정, 마을, 조직에 적용하고, 현실의 문제들을 해결해 나갔던 것으로 관찰되었다. 또한 LDA 토픽모델링을 통한 정합성 검증결과, 학습자의 변화구조면에서 새마을교육 특성과 경험학습 순환구조는 유사한 변화형태 범주를 나타내는 것으로 분석되었다.The purpose of this study is to examine the theoretical background of Saemaul education in the 1970 s through Kolb s experiential learning theory. The characteristics of Saemaul education that were identified from the perspective of Kolb s experiential learning are as follows. With respect to specific experience, the trainees took part in the training activities with an emotional open-heartedness, and actively responded to educational stimulus. From the perspective of reflective observation, Saemaul education did not precisely coincide with the notion of reflection described in experiential learning, similarities were found in the serial process of attaching meanings through educational experience. In case of abstract conceptualization, the concepts that the trainees attached meaning to through a systematic process were drawn from problems found in real life, and the conceptualization process did have similarities with the process described in experiential learning as their own meanings were constructed as internal concepts. With respect to active experimentation, the process of applying the practice standards was found to have similarities with the active experimentation of experiential learning in the sense that the process displayed the characteristics of decision making and problem solving in real life. As a result of LDA Topic Modeling verification, Saemaul education and experience learning models were analyzed to show similar patterns in learner s change.
Chinese Story Generation Using Conditional Generative Adversarial Network

Natural language processing has become popular considerably in a wide range of applications, but it still has been rarely applied to automatic text generation. In this paper, we focus on allowing the user to determine which content the machine is to narrate and the user can just give a summary to generate a complete paragraph. Based on the attention mechanism, we propose a Syntax-Guided Machine Reading Comprehension (SG-Net) to accept Chinese word vectors, learn from Chinese data sets, and semi-supervised self-growing generative adversarial network (SG-GAN) generate sequences with more realistic sequences. In order to reasonably evaluate the quality of the text produced by the machine, we also design a set of experiments by manipulating the content of the input sequence semantic information. It can be seen from the experimental results that both SG-Net and SG-GAN can understand the basic semantics and grammar and write a readable article. In summary, SG-Net may only recite the statements that have been read and SG-GAN can understand more semantic and grammar than SG-Net.
Villa Tiburtina: storia di un servizio di psicoterapia all’Università

This article deals with the story of an “External mental health unit” at the University of Rome, where the Analisi Collettiva’s seminars started in 1975. Over the years, this Unit changed location and was renamed Psychotherapeutic Operational Department Unit (U.O.D) “Villa Tiburtina”. In this latter seat, physically far from the Psychiatric department and the University hospital, the psychiatrists managed to turn into daily clinical practice what experienced in their personal formation during the Analisi Collettiva. They succeeded in carrying out a psychotherapeutic practice which enabled the patient’s cure and also psychiatrists’ personal training. This realization was further accomplished thanks to clinical supervision, and research opportunities which through national and international collaborations laid the groundwork to acquire the scientific research methodology.
LibGuides: Research Basics: Research Steps

This guide illustrates the basic steps of the research process. Follow these steps to search for library resources related to your topic.
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions

We report a previously unidentified issue with model-free, value-based approaches to multiobjective reinforcement learning in the context of environments with stochastic state transitions. An example multiobjective Markov Decision Process (MOMDP) is used to demonstrate that under such conditions these approaches may be unable to discover the policy which maximises the Scalarised Expected Return, and in fact may converge to a Pareto-dominated solution. We discuss several alternative methods which may be more suitable for maximising SER in MOMDPs with stochastic transitions.
Tic-Tac-Toe: Understanding the Minimax Algorithm

In this paper we deduce a new mathematical technique to define the winning game Tic-Tac-Toe. The results were placed in a 3x3 matrix and initial conversions were performed on the rows to find all possible win states. Programming languages were used to find the matrix to determine the diagonal wins. A simulation algorithm is presented to predict the win, or draw of a game by knowing the first move of a player. The game of Tic-Tac-Toe is simulated by using a Min-max algorithm.
Library Guides: Omeka: What is Omeka?

Omeka is a free, flexible, and open source web-publishing platform for the display of library, museum, archives, and scholarly collections and exhibitions.
ILI IS LOOKING FOR SPEAKERS

Internet Librarian International (ILI) celebrates innovation. Every year, hundreds of library and information professionals from around the world come together at ILI to exchange ideas, knowledge and experience. You are invited to play a part by sharing your library stories with the global ILI audience. As we continue to monitor the coronavirus outbreak, we send good wishes to our ILI friends, families and colleagues and to all those affected by COVID-19 around the world. We are proud of the community that has developed around the ILI conference over the past twenty-two years and we remain committed to the event and the wider endeavours it represents.
Learning To Re-Rank For Multistakeholder Recommendations

Abstract Recommender Systems are personalized applications aiming to assist decision making by a list of tailored recommendations. Traditional recommender systems only focus on addressing the objective of the end users whose decisions ultimately determine the deal of the recommendation systems. However, the customer of the recommendations is not the only party whose needs should be represented. The needs of multiple stakeholders should be taken into account. In this paper, we are considering re-rank functions that are designed to balance end-user and online retailer needs. A variety of methodological approaches of different complexities are explored to incorporate profit information into recommenders and to balance preference and profitability. Taking the above factors into consideration, we tackle the problem balancing two sides by proposing a novel algorithm-Preference with Revenue Recommendation (PRR). Extensive experiments conducted on real world dataset indicate our method can be done with a marginal or no loss in ranking accuracy.
LibGuides: Libraries and STEM: Home

Making the case for STEM in your library? Setting up your own MakerSpace in the library. This guide is here to guide you in research and resources.
Link Prediction with Deep Learning Models

Author(s): Aksakal, Ahmet Salih | Advisor(s): Al Faruque, Mohammad | Abstract: Deep Learning has been used extensively in many applications by researchers. With the increased attraction to Deep Learning, more and more unique models are created each year. However, sometimes some of the model details are not included in the publications. This makes using new Deep Learning models for research a time-consuming task for researchers. In order to tackle with this problem, we propose a prediction mechanism for the missing information in the model. By creating a dataset where the Deep Learning models are represented as knowledge graphs, we made it possible to use knowledge graph embedding algorithms which are specifically designed for eliminating missing information in a given data. We inspected 6 different algorithms and compared their performances on a small-scale experiment. After the comparison, we picked the most promising algorithm and used it for link prediction in Deep Learning models.
Assessing the Impact of Brand Equity and Customer Experience on Brand Loyalty in the United Arab Emirates Hotel Industry

Contributing to the existing literature regarding the hotel industry of the United Arab Emirates, this research study aimed to assess the impact of brand equity and the quality of customer experience on brand loyalty. In particular, the study examined the relationship between brand equity and the quality of customers' experiences with some of the prominent players in the hotel industry of the United Arab Emirates. The sample for the study included a total of 694 participants. Five hotel chains were included in the data collection: Atlantis, The Palm, Movenpick Hotel, Sheraton Hotel, Crowne Plaza Hotel, and Hotel Ibis. Study findings revealed a significant impact of the brand equity and customer experience on the development of brand loyalty among consumers.
Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method

Abstract Aiming at the problem of dimensionality disasters in the spam filtering system, a spam filtering model based on content feature selection random forest algorithm is proposed. The method combines the Naïve Bayesian algorithm and effectively reduces the influence of redundant information on classification performance through feature selection filtering of Gini impurity. The improved algorithm takes advantage of decision tree integration and naive Bayesian algorithm. The experimental results show that compared with the naive Bayesian algorithm, the improved algorithm has been improved in the classification performance indicators of spam filtering, which is more feasible and effective in practical applications.
LibGuides: Continuity of Learning Services at Sawyer library: Copyright Considerations

This guide provides information about the Library's online services for faculty, staff and students during the Covid-19 disruptions.
Mobile Learning among Physiotherapy Undergraduates:An Evaluation of Current Status, Dispositions and Performance

Mobile phones have become an almost essential part of daily life since their inception. They offer a lot of advantages especially offering participatory learning for the students. Their ability to provide learning apparatuses beyond the time and space dimension makes them all the more acceptable for current millennial generation. Thus this study tries to find out whether physiotherapy students are inclined towards the usage of mobile leaning and how is it affecting their academic performance. Method: The study was conducted on 120 Bachelor of Physiotherapy students who were using smart phones from at least a year through a self reported questionnaire. Result: Majority of the participants perceived m learning as advantageous though there were some disadvantages and barriers perceived as well. As anticipated, both by users and from the literature, universal internet access and screen size were a major limitation to device use. Conclusion: M-learning devices can have a positive impact on the learning experiences of physiotherapy students. The results supported the feasibility of providing mLearning devices to support learning. However, universal internet and screen size are the fundamental limitation to optimal device utilization.
Research on the Application of Computer Deep Learning in Image Processing

Abstract The rapid development of Internet technology has made the whole society enter the era of big data. In recent years, the development trend of artificial intelligence and machine learning has also risen sharply. Informatization has become an important feature of the current era. As an indispensable common information carrier, images not only facilitate people’s communication, but also promote the development of deep learning processing image technology. Based on this, this paper analyzes the application of computer deep learning in image processing. Firstly, the deep learning is summarized, its concept and origin are briefly introduced, and then the technical classification, development process and processing purpose of image processing are expounded. Finally, the application of computer deep learning in four aspects is analyzed in detail in image recognition, image denoising, image classification and image enhancement, and it has certain significance for promoting the research and application of deep learning.
LibGuides: Video Tutorials: Technical Assistance Videos

Quick video guides to help you access, and use, Library resources remotely. Instructional videos on how to use the Pierce Library
An underwater laser three-dimensional imaging system

An underwater laser imaging system is introduced in this paper. The system has demonstrated underwater imaging capabilities in excess of 3 times the range of visible camera with lights, having three-dimensional (3D) imaging and range gated imaging ability. It also has small size and no gravity in water, can be manually handheld and carried on underwater unmanned platform.