Reviewerly/exHarmony huggingface dataset:
Previous studies have several limitations …: Indonesian Doctoral Students’, Indonesian Academics’, and International Authors’ Research Gap Strategies in ELT Research Article Abstracts and Introductions

Presenting research gap(s) in a research article (RA), particularly in the abstract and introduction, should be considered by authors, since it functions to show the novelty of the research. As there have been limited studies on the possible variations in authors' research gap strategies and the problems in identifying research gaps, this mixed-method study aimed to fill the gaps. Using genre analysis, this study compared the use of research gap strategies in English Language Teaching (ELT) RA abstracts and introductions by three groups of authors, namely, Indonesian doctoral students, Indonesian academics, and international authors. The results of the quantitative analysis in this study indicated that the three groups share similarities and differences in using the types of research gap strategy in their ELT RA abstracts and introductions. Then, the qualitative analysis using semi-structured interviews with ten doctoral students revealed some problems encountered by them in identifying research gaps during research activities. Finally, this study demonstrates the extent to which our findings have theoretical and practical implications concerning the use of strategies in presenting research gaps in RAs.
Maryland State Library LibGuides: Grants for Public Libraries: Acknowledging IMLS and MSL in your LSTA-Funded Grant

Information on LSTA grants and other funding opportunities. How to Acknowledge IMLS & MSL Grants
Smart Tech Study Table / Nur Amira Aminuddin

The problem statement is important to be listed and analysed. This is because this process let us aware and identifies the weakness of the current product. Therefore, the new product development can be planned and formed by thinking the best method to improve the current product becoming the preferable and greater product.The current product has the same functions with the other similar products from different production or company. The demand of the product can be assume as high because this product likely to be convenience and suitable for everyone despite of their ages. However, by having the similar product with the others can cause the demand for the certain company is lower since there are many competitors.Besides, the current products usually have the limited space. This problem is common since the current study table is created to be small to able it can be handled easily without much effort. The consumer uses the study table to do their tasks and work where the might be place their stuffs such as laptop, books, stationary and paper on it. Therefore, by having limited space causes the consumer unable to place their stuffs at the floor instead of on the table.Next, the current product is lacking at the implementation of the technology. Nowadays, the technology is necessary to help the people by making the tasks more convenience and easier. Without the technology, they will require to do the task manually which it can take some times and causes any problem or mistake. Thus, the error that has been made can cause the consumer to be in trouble especially if the error is massive. For instance, the consumer needs to make a calculation and there is no calculator is available at that moment in which leads him to do the calculation manually by using paper and pen.
PENGEMBANGAN BAHAN AJAR BERBASIS PREZI PRESENTATION PADA MATA KULIAH KAJIAN PUISI

This study is entitled the development of teaching materials based on Prezi Presentation in poetry study courses. The purpose of this research is to look at the feasibility of teaching materials based on prezi presentation in poetry study courses. The method used in this research is the development method. Results obtained Based on the results of the validation of media experts, obtained an average value of 4.41 with a very good category. Based on the results of the validation of linguists it is known that the average value of teaching materials in terms of language is 4.4 with a very good category. The percentage of student response questionnaires was 79.1% with an average value of 3.9. The percentage and average value is a good category. Based on the results of the calculation of the test, it can be seen the average value of students is 77, 9. In accordance with the academic skills calcification table, the value is categorized as good. Based on these things, it can be concluded that the teaching material in the Poetry Study course based on Prezi Presentation is declared appropriate for use.
Library Guides: Linking to Library Resources: Streaming Video

This guide will show you how to link to resources in the DiPietro Library How to link to streaming video platforms
Optimization of Dynamic Systems: A Comparative Study of Two Modified Differential Evolution Algorithms

Differential Evolution (DE) is a novel, efficient, effective and robust evolutionary optimization technique. DE algorithm is gaining popularity for solving complex optimization problems encountered in many engineering disciplines. This paper deals with the application and performance evaluation of two modified versions of DE [named as Modified Differential Evolution (MDE) and Trigonometric Differential Evolution (TDE)]. Three algorithms have been used for solving five dynamic optimization problems encountered in chemical engineering. Results indicate that MDE algorithm outperformed DE and TDE algorithms for solving problems with small number of control stages. But TDE algorithm is found to be faster and efficient than MDE and DE algorithms particularly for problems involving large number of control stages.
Neural methods for effective, efficient, and exposure-aware information retrieval

Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion.
Pengembangan Aplikasi Identifikasi Lagu Berbasis Kognitif Menggunakan Model Prototype

Now with the application of Snap videos or short videos, both those obtained from social media such as Instagram, Twitter, and Facebook, there are many pieces of audio and video files of short duration which contain songs that have meaning. When we are interested in knowing a song, we have a hard time finding out the title of the song or the source. We designed an application to identify cognitive-based songs using a prototype method to overcome these problems. The method we use is a prototype model, this method is a paradigm in software creation and development, we chose this method because the process is relatively faster because it uses mock ups in its application. From the test results, the song identification application that we made is very effective for identifying the types of songs with slow genres such as jazz, blues, and acoustic but less effective for hard rock and RnB songs.
An Intelligent System for Lung Cancer Diagnosis

Nowadays, lung cancer has become one of the important topics for researchers in medical technology. Lung cancer is one of the deadliest diseases in the world and is a subject of concern because no actual treatment has been found for this disease yet.Computer-aided diagnosis (CAD) is one of the widely used imaging techniques for detecting and grading lung cancer. This thesis presents a proposed system for classifying lung cancer after its detection with the help of machine learning algorithms, where several steps are used in the form of stages which include the stage of data acquisition, data pre-processing, and classification. The theater. The dataset used is obtained from the archive (data scientist), which contains 1,000 samples and 25 features. The first proposed model is based on the Support Vector Machine (SVM) classifier), and the second proposed model uses an artificial neural network (ANN) classifier and compares the accuracy and time taken for each model. Each model implements two types of preprocessing algorithms (standardization and normalization).The results showed that the first proposed model using (SVM) with normalization had an average accuracy of 98.21%, while with standardization the accuracy was 100.00%. The second proposed model using (ANN) with normalization and standardization with an accuracy of 100.0%.
Manfaat Learning Resources dalam Pembelajaran Student Centered Learning

This research to provide a description of the SCL learning process by utilizing information technology internet media with research library methods which is a method of searching, collecting and analyzing data sources to be processed and presented in the form of a report.The existence of information technology is a rapid progress in supporting the world of education as an economical, practical, and easy learning resource. Student Centered Learning (SCL) is learning that is in accordance with the current digital era, so that the role of lecturers in the learning and learning process is as a companion, motivator and facilitator. The activeness of students in the learning and learning process is an important factor, because with the direct involvement of students, the lecture material is easy to understand and understand.
Ethical issues in large-scale journalistic investigations

The advent of large-scale journalistic investigations based on “big data” is a relatively recent phenomenon. The exponential growth in the volume of data being stored and generated by state and private entities and the tendency to centralize that storage, while allowing too many people access to it, has created a structural vulnerability. This has enabled disgruntled employees or contractors to access, copy, and leak vast amounts of such data. Such leaks have resulted in information of huge public importance being published by journalists and media outlets, and have led to government inquiries, political resignations, tax reform, and numerous criminal prosecutions. Standing behind a journalist’s activity where use of big data is concerned is the public interest. It justifies a journalist accessing and interrogating that data, it underpins follow-up inquiries and investigations, and, ultimately, it justifies what is published. But the public interest is a singularly ill-defined concept. This chapter aims to examine, from a UK perspective, some of the ethical issues that arise for journalists working on “big data” leaks, including how such “big data” is obtained, stored, shared, searched, interrogated and analyzed, and published, and where the public interest sits in this process.
Complete Styler / Ainul Ashykeen Azmal

The Complete Styler is a high quality product that very efficient, friendly use and convenience because the combination of three hair styling which are blower, straightener and curler. The concept of this product is affordable and saving consumer money. From what customer needs is what we will build. This product have complete with the perfection of the design easy to handle, wireless, bladeless fan, light weight and also rechargeable. Target market is where the product will be focus on the population will need. The competitive spirit within others product will help us gaining the experience to provide more in product that consumer need, improve the lacking part of the product and learn how the business life. This shows from competition will determine the best product among all towards the consumer demand.
O papel da educação interprofissional no processo de reorientação da formação em saúde

Introduction: In Brazil, in recent years, an effort has been verified to incorporate interprofessional education into policies that induce professional reorientation in health. In this context, the Program of Education through Work for Health stands out, based on the triad of teaching-service-community. Objectives: To describe experiences and knowledge collectively constructed in the implementation of PET-I in the context of interprofessional education practices in the municipality of Jataí, Goiás. Methods: Descriptive exploratory study, with a qualitative approach, based on the theoretical-conceptual and methodological bases of interprofessional education, carried out between August 2019 and November 2020.Results: All participants of each stage of the research presented a positive and receptive attitude towards interprofessional work, mentioning that it promotes beneficial results, especially for the resolution of attention and safety of users. At times, however, there were stereotyped views about the professions. It was remarkable the thought that IPE is something very good, which has advantages, but it is very difficult to do it and be able to disseminate it to all professionals or actually work as a team. Conclusions: When analyzing the participants' perceptions, we realized that the skills and knowledge proposed by PET-I for interprofessional training can overcome mechanization and fragmented views of health care, resulting in a humanized, integrated training that can generate new responses to current needs.
LibGuides: Scholarly Communications: Creative Commons

Includes information on Copyright, Creative Commons, Fair Use, Public Domain, Open Access Resources and More.
A study for application of item change sensitivity to longitudinal academic achievement tests

학생 능력의 변화를 측정하는 검사를 개발할 때, 문항이 변화/성장을 얼마나 잘 감지하는지 확인하는 것은 검사 목적의 타당성을 높이기 위해 중요하다. 본 연구는 종단 데이터에 적용된 다차원 문항반응모형의 모수가 변화에 민감한 정도를 나타낼 수 있음을 소개하고, 모수 추정의 정확성을 살펴보았다. 구체적으로, 1년의 시간 간격을 두고 시행된 능력검사 데이터를 이용하여 변별도와 변화에 민감한 정도를 나타내는 모수가 별개의 특성임을 확인하였다. 또한 세 가지 조건(요인 간 상관, 기울기 모수 간 차이, 피험자 수)을 고려한 모의 데이터를 생성하여, 두 문항 특성이 안정적으로 분리되어 추정되는지 확인하였다. 연구 결과, 문항 모수는 대체로 안정적으로 추정되었으나, 요인 간 상관이 부적일 때와 사례수가 적을 때는 추정성이 떨어졌다. 두 문항 모수 간의 차이가 클수록 문항 모수의 추정성은 높아지나, 잠재특성 모수의 추정성은 낮아지는 경향이 있었다.When developing test items that measure changes in student abilities over time, it is important to increase the validity of the test objectives to determine how well the items detect changes/growth. In this study, three conditions of the multidimensional item response model (correlation between factors, difference between slope parameters, and the number of subjects) are considered for simulation study by referring to the characteristics of the actual longitudinal ability test data used to grasp how much students have grown at a time interval of one year. First, we introduced that the item parameter of the multi-dimensional item response model can provide information about the degree of sensitivity to ability change, and examined its function through the accuracy of parameter estimation. As a result of the study, the latent trait parameter and the item parameter were generally estimated to be stable, but the accuracy was poor when the correlation between the two latent factors was negatively related and the number of cases was small. The greater the difference between the two slope parameters, the higher the accuracy of the item parameter, but the lower the accuracy of the latent trait parameter.
Evidence for and against Zauner's MUB conjecture in C^6

The problem of finding provably maximal sets of mutually unbiased bases in $\CC^d$, for composite dimensions $d$ which are not prime powers, remains completely open. In the first interesting case,~$d=6$, Zauner predicted that there can exist no more than three MUBs. We explore possible algebraic solutions in~$d=6$ by looking at their~`shadows' in vector spaces over finite fields. The main result is that if a counter-example to Zauner's conjecture were to exist, then it would leave no such shadow upon reduction modulo several different primes, forcing its algebraic complexity level to be much higher than that of current well-known examples. In the case of prime powers~$q \equiv 5 \bmod 12$, however, we are able to show some curious evidence which --- at least formally --- points in the opposite direction. In $\CC^6$, not even a single vector has ever been found which is mutually unbiased to a set of three MUBs. Yet in these finite fields we find sets of three `generalised MUBs' together with an orthonormal set of four vectors of a putative fourth MUB, all of which lifts naturally to a number field.
Developing a Model of Return on Investment in Knowledge Management

The importance of knowledge management as a competitive advantage is evident to everyone, and it is considered one of the critical factors of successful organizations. The capitalist view of knowledge management has led to the measurement of the return on investment resulting from it, and the return on investment has been recognized as a financial indicator for measuring knowledge management. What are the main components of knowledge management? Have components the same coefficients? The impact of the components is different and has different values. In order to achieve this importance, the present study was conducted to develop a return on investment model in knowledge management. This Practical research is mixed method, and in the form of exploratory schema in three stages, qualitative (using grounded theory and the use of interview tools), quantitative (using a descriptive method, a survey using questionnaire tool), quantitative (using a descriptive method, a survey using questionnaire tool) has been done. Each method is analyzed using, respectively, MAX QDA and SPSS software. The findings of the first stage of the study include identifying the benefit and costs of knowledge management. Then, the components validity is obtained, and then in the third stage, a coefficient is assigned to each of them. Identifying costs and benefit Components is a first stage achievement. Experts measured the validity of each component to identify components accurately. Furthermore, finally, in the third stage, each of these components was assigned a coefficient. The development of a new formula, taking into account each of these coefficients, is considered research innovation. https://dorl.net/dor/20.1001.1.20088302.2021.19.2.9.7
CCS Libraries: DVC 485: The "Art" of Research: Overview

This guide for students taking The 'Art' of Research serves as a starting point different modes and types of research
STUDY OF Þ - ANTI FUZZY SUBALGEBRAS USING RIGHT SEGMENT Ɋ

The concept of Þ - Anti fuzzy subalgebras, for Anti fuzzy relations on fuzzy sets, and for anti fuzzy compatibility are defined. Also the above concepts are generalized and improved. The unit interval is replaced here by a partially ordered algebra. Their connection with the crisp concepts using newly defined Ɋ -cuts are discussed.
Penerapan Data Mining Untuk Memprediksi Jumlah Data Pasien Di Puskesmas Haekesak Menggunakan Metode ARIMA

ABSTRACTThe purpose of this study was to determine the Arima method equation model, to find out the resultsof the analysis to predict the number of patients in the haekesak health center using Minitab tools. and knowingthe results of predicting the number of patients treated at the Hasekesak health center from 1 January to 10February and the method used in this study was the ARIMA method. The results of the prediction of the totalnumber of patients who will come to the Haekesak Health Center using the ARIMA method, this analysis endswith the number of patients who will come on the 26th-35th day where the total number of patients does notincrease or decrease significantly so that the puskesmas does not need to increase their mental health. or theaddition of excessive drug stock.Keywords: Forecasting, ARIMA, Disease
X-Aevol

X-Aevol is the GPU port of the Aevol model, a bio-inspired genetic algorithm designed to study the evolution of micro-organisms and its effects on their genome structure. This model is used for in-silico experimental evolution that requires the computation of populations of thousands of individuals during tens of millions of generations. As the model is extended with new features and experiments are conducted with larger populations, computational time becomes prohibitive.
Interpolation of scientific image databases

This paper explores how recent convolutional neural network (CNN)-based techniques can be used to interpolate images inside scientific image databases. These databases are frequently used for the interactive visualization of large-scale simulations, where images correspond to samples of the parameter space (e.g., timesteps, isovalues, thresholds, etc.) and the visualization space (e.g., camera locations, clipping planes, etc.). These databases can be browsed post hoc along the sampling axis to emulate real-time interaction with large-scale datasets. However, the resulting databases are limited to their contained images, i.e., the sampling points. In this paper, we explore how efficiently and accurately CNN-based techniques can derive new images by interpolating database elements. We demonstrate on several real-world examples that the size of databases can be further reduced by dropping samples that can be interpolated post hoc with an acceptable error, which we measure qualitatively and quantitatively.
On avoiding 1233

In this paper, we establish a recurrence relation for finding the generating function for the number of k-ary words of length n that avoid 1233 for arbitrary k. Comparable generating function formulas may also be found counting words where a single permutation pattern of length three is avoided in addition to 1233.