Reviewerly/exHarmony huggingface dataset:
Artificial intelligence in computer games

Today, the highly developed and competitive computer games industry needs to make better and better computer games and beat the competition. In order to keep the players entertained with computer games, manufacturers use a variety of techniques to make games interesting and challenging. This is largely aided by research in the field of artificial intelligence that is extremely well suited for computer games. Games need to be made as complex and unpredictable as possible to provide as much fun as possible. This article explores and gives an overview of all the most popular techniques that can be applied.
The Correction Rate and The Reaction Time of Math Anxiety Groups and Math Achievement Groups through Visual Tasks of Arithmetic and Function

In the previous research, students with high math anxiety(MA) were found to differ from their lower math anxiety peers on mathematical achievement. This study examines differences between the MA groups and between the achievement groups in the visual tasks of arithmetic and function areas where students solved with 20 items selected arbitrary out of 100 items, respectively. E-prime in the tasks measured correction rates and reaction times of 25 students from the 9th grade of one middle school in Gyeonggi province. Both MA groups and achievement groups significantly scored better on arithmetic tasks than function tasks and significantly took more time on function tasks than arithmetic tasks. This result implies that teachers should pay attention to their pedagogical approach in the process of teaching about these two adjacent areas of mathematics since the function is very different from the arithmetic. Also, the evidence that affective domain with MA related negatively with the cognitive domain with achievement was consistent with the previous studies.
A multi-parametric simulation study of Neural Networks Performance for non-linear data against linear regression analysis in Economics

Different mathematical and dynamic methods have been developed addressing the problem of forecasting, with the regression analysis to be one of the most frequently used statistical procedures. Meanwhile, neural networks (NNs) are considered to be well suited in finding accurate solutions in an environment characterised by volatility, noisy, irrelevant or partial information. In this chapter, a simulation study compares the performance of NNs against linear regression analysis is based on multiple combinations (421 in total) of five different factors providing those cases that the NN performs better than the LRM and defining the output bias as the main contributor to the NN outcome.
Communication and Technologies: Are All Modern Discourses Technical?

Communication, the Internet and computers. Communication and social networks. Communication under the conditions of information surplus. Communication and technologies.
LibGuides: Thesis Research 101: Citation Software

Slides and resources to accompany Booth Library's graduate research seminars: Researching the Literature; Citation Management software (Mendeley & Zotero); Presenting your Thesis.
Learning Bayesian Networks Parameters via Monotonicity Constraints

Learning Bayesian networks (BNs) parameter is a challenging task as it relies on a large amount of reliable and representative training data. However, the accuracy of parameter learning is critical. In this paper, we propose PML_margin method to enhance monotonicity to achieve better results. We apply Spearman rank correlation coefficient to detect monotonicity constraints and to adjust the margin of cumulative distribution. Experimental results on standard BNs show the effectiveness of the PML_margin, compared with the MLE, MAP and RHO_PML method, respectively.
UWM Libraries Research and Course Guides: Citation Managers: Importing to a new Manager

Includes information on how to select a citation management tool and how to transfer your library into it from RefWorks.
Multiplicative functions arising from the study of mutually unbiased bases

We introduce two families of multiplicative functions, which generalize the somewhat unusual function that was serendipitously discovered in 2010 during a study of mutually unbiased bases in the Hilbert space of quantum physics. In addition, we report yet another multiplicative function, which is also suggested by that example; it can be used to express the squarefree part of an integer in terms of an exponential sum.
Marina Chini e l'italiano L2: dalla linguistica acquisizionale alla linguistica educativa

Marina Chini’s contribution to the studies of Italian as a second language from an acquisitional and an educational perspective is revisited with the aim to highlight her innovative integrative approach in the framework of a typological functionalism.Particular attention is devoted to her investigation of the development of the category gender in Italian L2, of the strategies of textual organization in the Italian retellings of advanced learners with L1s with different typological distance from Italian, and of the interaction between teaching and acquisition.
A Flexible Live Broadcast Management System

Due to the real-time nature of live broadcast, we need to effectively prevent the rapid spread of harmful information. A set of live broadcast management system is designed and implemented based on MongoDB, which can meet the review status and deal with bad information quickly. The system permissions and resources are controlled by different roles, thus increasing the security and flexibility of the system.
Graph Processing with Different Data Structures

The paper describes graph algorithms performance when using different types of data structures. To achieve that, we developed a multi-level graph processing system, which allows to create graph applications independently of any implementation details such as graph data structure or underlying computational architecture. We measure the performance of breadth-first search, max flow and random graph building algorithms when using compressed sparse row and adjacency matrix data structures. Experiments reveal different graph processing rates for different data structures, which indicates the need of using specific data structures for specific algorithms to achieve highest performance.
Modelagem de previsão de resultado eleitoral dos partidos políticos utilizando abordagem de ARS

Considering the great importance that elections have in a democratic country, this work uses Social Network Analysis (SNA) to understand the majority election campaign funding of 2018 and the correlation with election performance. Attributes associated with the agents of this network may have influence on the outcome and after establishing the theoretical foundation these dimensions can be used as learning and testing data in a machine learning, which aims to predict the outcome achieved by political parties. The performance of a party in the majority elections impacts it’s financial and political trajectory for at least the next 2 years, such as access to party funding, TV and radio time, influence on the executive and legislative power at the state and federal level and of course, representativeness. Financial characteristics were considered as transaction values and measures of centrality of these parties as input in the result function and the total number of vacancies won as output. As a result, the hypotheses could not be confirmed, and the Neural Network algorithm was the most accurate with the smallest error measures.
Attention Guided Unsupervised Image-to-Image Translation with Progressively Growing Strategy

Unsupervised image-to-image translation such as CycleGAN has received considerable attention in recent research. However, when handling large images, the quality of generated images are not in good quality. Progressive Growing GAN has proved that progressively growing of GANs could generate high pixels images. However, if we simply combine PG-method and CycleGAN, it must bring model collapse. In this paper, motivated from skip connection, we propose Progressive Growing CycleGAN (PG-Att-CycleGAN), which can stably grow the input size of both the generator and discriminator progressively from $$256\times 256$$ to $$512\times 512$$ and finally $$1024\times 1024$$ using the weight $${\alpha }$$. The whole process makes generated images clearer and stabilizes training of the network. In addition, our new generator and discriminator cannot only make the domain transfer more natural, but also increase the stability of training by using the attention block. Finally, through our model, we can process high scale images with good qualities. We use VGG16 network to evaluate domain transfer ability.
LibGuides: Thesis Research 101: Presenting Your Thesis

Slides and resources to accompany Booth Library's graduate research seminars: Researching the Literature; Citation Management software (Mendeley & Zotero); Presenting your Thesis.
Creators and performers earnings from copyright

Copyright protects the work of creators and performers from being copied without their permission, enabling them to control its use and so to require payment for it. What that payment is – usually a royalty – depends upon conditions in the market in which it is used. The chapter discusses the outcome in terms of income from copyright, using evidence from one of the early surveys of copyright earnings, and shows how the results can be presented using the Lorenz curve to demonstrate both low and also how unequal earnings are.
LibGuides: New Technology on the Horizon: OpenAthens

A look at the technology and electronic resource advances coming to the Xavier University of Louisiana Library. A new remote service to access our resources
Role of Human Resource Management and Quality Management in Higher Educational Institutions Theme – “Innovative Functional Strategies for Gen Y “

In any manufacturing organization there are large number of processes in which raw materials are converted into finished product with the help of resources like manpower, machines, materials, method, environmental characteristics for value addition. Various departments like Production, Purchase, Research and Development, Quality Management(QM), Maintenance, Human Resource Management (HRM) etc. which have interdependence on each other work together to produce quality products .Similarly in an educational institution there are different departments classified based on their expertise in delivering education in their respective domain which develop skills in students for the roles they need to perform in future and to increase their salability quotient .It is disheartening as well as surprising to know that most of the colleges in India do not have a Human Resource Management (HRM) Department and Quality Management (QM) Department. Some colleges have these departments but they are only for namesake. In order to explore their presence in colleges the survey is designed to find out who is performing the activities related to functions of QM and HRM in Jaipur based higher educational institutions and whether it is affecting the work life balance of faculty members and administrative staff. The survey also consists questions to check the compliance to 12th Plan Guidelines for Establishment and Monitoring of the Internal Quality Assurance Cells in Colleges by the University Grants Commission .The third objective is to find out how the presence of these departments is affecting the trainings organized for faculties and students and skill development .Some specific cases are also taken to show the effect of absence of QM and HRM and ineffective HRM and QM .It is done to highlight the importance of QM and HRM role in present scenario where customer centric culture is the need of the hour for working towards the fulfillment of the unaddressed needs of the direct and indirect customers of the institution i.e. parents, students (direct ) recruiters and society (indirect ).The research methods used are multi stage sampling , survey and case studies and sampling frame is Jaipur based Higher Educational Institutions .The study reveals that if organizations can remove the deficiencies in their HRM and QM then they will be on their way to become a World-Class institutions .In the concluding section the applicability and feasibility of all parameters related to Quality Management and Human Resource Management defined in ZED MATURITY ASSESSMENT MODEL for MSME’s  is checked for Higher Educational Institutions .
LibGuides: Year 7 Home Link Parent Information: Home

For our DIS parent community - when you want to help your child improve and succeed at school
Analysis of Universities’ Readiness for the Introduction of Digital Educational Technologies and Products

At the present stage of the information technologies development, the most important aspect of the eff ectiveness of higher education in Russia is the readiness of the higher education system in general and teachers of higher educational institutions in particular to work with digital technologies. The results of the monitoring presented in this article allow to evaluate important indicators such as the level of digital literacy of teachers, the presence of the necessary ICT competencies of teachers, and the level of development of the digital educational environment of Russian universities, including the degree of universities’ digital equipment, the use of educational software products and educational online services, the degree of development of eeducation. This study allows us to draw a number of signifi cant conclusions necessary for the development of the higher education system in Russia and the development of the necessary methodological tools for conducting a comprehensive assessment of the universities’ readiness to introduce digital educational technologies and products.
Various solution plans for exhibition and explanation for history education at the Museum -with priority given to Daegu Museum of Education-

Museum is one of the places that the history can be educated to the public the most. The best way to experience the quality of museum is to personally visit and view the exhibition yet there are several difficulties of practical and physical restriction. It is called history education at the museum in case that the articles of exhibition are historical relics and the school has affiliation with the museum by a history teacher. For the better implementation of history education, it is necessary not only to guide students around the exhibition or emphasize their literacy skills but also endeavor to make students appreciate the structural characteristics of the articles of exhibition. That means it is important to grasp the historical context when viewing the exhibition. Besides, the description method of the articles of exhibition should be changed. In order to implement the issues mentioned earlier, the two following solution plans were introduced to the exhibition at Daegu Museum of education. First, so as to grasp of historical context when viewing the exhibition, 9 historical relics were selected and the scenario, Smart Curator, was produced with assistance of history teachers. Also, ‘Manchuria-Chosun School trip Guide’ and ‘Tonggang-rok’ were written in expository writing with narratives. For it is an early phase research, its generalization and realization should be arranged through finding the varieties of method-exhibition panel, brochure, video.
Research on disturbance characteristics in high temperature DIC measurement due to heat flow and its correction method

Digital Image Correlation (DIC) is an optical measurement method that can measure the deformation and even the appearance of an object. Because of the superiority of non-contact, full field, and low environment requirements, DIC can be used to measure the high temperature mechanical properties of materials in extreme environment. However, there are still difficulties in applying DIC in high temperature displacement measurement, such as heat flow disturbance. It will distort the images acquired at high temperature and affect the measurement accuracy of DIC. In this paper, the disturbance characteristics caused by heat flow are studied and the corresponding correction method is proposed. Firstly, the causes of distortion and the distortion characteristics are analyzed and then verified by experiments. Second, a method for correcting the distortion caused by heat flow is proposed. Finally, the availability of the proposed correction method is verified by experiment.
PENGEMBANGAN INSTRUMEN TES BERBASIS KETERAMPILAN PROSES SAINS PADA MATERI RANGKA KELAS IV SDN 050 TARAKAN

Abstract: The type of research used is Research and Development design Formative Evaluation (Tessmer in Rahayu, 2008). The subject of the study was class IV. The result of the research is 30 item in the form of multiple choice. The first stage of expert validation is the first validation of the content experts of 80% in effective category, the second validation of the construction expert of 80% in effective category, the third validation of linguists by 93% in the very effective category. In one-to-one trials student’s response of 83% in the effective category. The results of small group trials in the form of student responses by 89% included in the category very effective. Based on the inputs and comments of small group of test instruments improved and then field test was conducted on 60 students of grade IV SDN 050 Tarakan. Result of analysis by using SPSS 21 program showed 24 item in valid category, reliability value that is r11=0,650 > r tabel=0,254 in high category in criterion of reliability. Data analysis using AnatesV4 program showed difficulty level with easy criteria of 1 items about (3,3%), medium criterion 26 items about (86,7%), difficult criterion 3 items about (10%), different with bad 4 item about (3.33%), different power with sufficient criteria 14 items about (46.67%), different with good criterion 9 items about (30%), different with very good criterion 3 items about (10 %), produces effective deception as many as 26 items about (86.7%).
LibGuides: ENGL 100 Jones (Spring 2020): Background Research

Research guide for Barbara Jones' ENGL 100 course. Focuses on refining research questions, selecting keywords for searching, and evaluation of resources.
LibGuides: Remote Library Services: Coronavirus Information

When you need or prefer to work remotely, there are many ways the Libraries can provide you with expert help and services. Always check the Libraries’ website for the latest information about our hours and services.
Improved salient object detection via boundary components affinity

Referring to the existing model that considers the image boundary as the image background, the model is still not able to produce an optimum detection. This paper is introducing the combination features at the boundary known as boundary components affinity that is capable to produce an optimum measure on the image background. It consists of contrast, spatial location, force interaction and boundary ratio that contribute to a novel boundary connectivity measure. The integrated features are capable to produce clearer background with minimum unwanted foreground patches compared to the ground truth. The extracted boundary features are integrated as the boundary components affinity. These features were used for measuring the image background through its boundary connectivity to obtain the final salient object detection. Using the verified datasets, the performance of the proposed model was measured and compared with the 4 state-of-art models. In addition, the model performance was tested on the close contrast images. The detection performance was compared and analysed based on the precision, recall, true positive rate, false positive rate, F Measure and Mean Absolute Error (MAE). The model had successfully reduced the MAE by maximum of 9.4%.
Evaluation of the Aggregate Potential of the Northern Kocaeli Province with the Help of a Geographical Information System (GIS)

In this study, existing and potential aggregate areas in the north of the province of Kocaeli in Turkey were determined by using a geographic information system (GIS). In order to perform the analysis, the status of the existing quarries and geological units where quarries were operated, and identification of areas that are suitable to be operated in the future were considered in the process as five basic criteria. These criteria were classified as the geology, land use, altitude, roads and settlement factors. Each criterion in the study represented a layer within the geographic information system. Overlaying these layers in the system, a map showing potential areas was created. According to this map, areas that could be considered as crushed rock aggregate potential areas in the North of the Province of Kocaeli were classified as low, medium, good and high zones.
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Purpose : This study is a one group pre-post designed experimental study, which was conducted to identify the effects of simulation-based integrated...
A Study of the Optimality of PCA under Spectral Sparsification

Principal component analisys (PCA) is a data analysis technique for mapping points in Rn to a two or three dimensional space. This dimensionality reduction preserves the natural grouping of points and information of data. [...]
LibGuides: UL Library Systems, Applications and Online Services: Known Access Issues

A guide on how to access and utilise UL Library Systems, Applications and electronic resources
Extracting Keywords from Open-Ended Business Survey Questions

Open-ended survey data constitute an important basis in research as well as for making business decisions. Collecting and manually analysing free-text survey data is generally more costly than collecting and analysing survey data consisting of answers to multiple-choice questions. Yet free-text data allow for new content to be expressed beyond predefined categories and are a very valuable source of new insights into people's opinions. At the same time, surveys always make ontological assumptions about the nature of the entities that are researched, and this has vital ethical consequences. Human interpretations and opinions can only be properly ascertained in their richness using textual data sources; if these sources are analyzed appropriately, the essential linguistic nature of humans and social entities is safeguarded. Natural Language Processing (NLP) offers possibilities for meeting this ethical business challenge by automating the analysis of natural language and thus allowing for insightful investigations of human judgements. We present a computational pipeline for analysing large amounts of responses to open-ended questions in surveys and extract keywords that appropriately represent people's opinions. This pipeline addresses the need to perform such tasks outside the scope of both commercial software and bespoke analysis, exceeds the performance to state-of-the-art systems, and performs this task in a transparent way that allows for scrutinising and exposing potential biases in the analysis. Following the principle of Open Data Science, our code is open-source and generalizable to other datasets.