Reviewerly/exHarmony huggingface dataset:
An Analysis of Difficulties in Comprehending English Reading Text at the Eleventh Grade Students of MA LAB UIN-SU Medan.

The objective of this research is to identify the difficulties faced by the eleventh grade students of MA LAB UIN-SU Medan, to identify factors of causing the students difficulties in comprehending English reading text at the eleventh grade students of MA LAB UIN-SU Medan in Academic year 2019/2020. This research is a qualitative research. The subject of research was the eleventh grade students of MA LAB UIN-SU Medan in Academic Year 2019/2020. The techniques of collecting the data are interview and test. The researcher uses the technique of analyzing the data from Miles and Huberman. The steps to analyzing the data for the first is data collecting, the researcher collecting the data from the students, such as test of students. The second is data reduction, the researcher classifies and reduces the data based on focus. The researcher deletes several data did not relate to the difficulties in comprehending English reading text. Third is data display, the researcher arranging the information described in order to draw the conclusion. The researcher presents the data from the difficulties in comprehending English reading text. The result of the research shows that there are 24.37% students who have difficulties in understanding to look for the main idea of the text with the total of incorrect is 29. Then, there are 18.49% students who have difficulties in understanding vocabulary of the text with the total of incorrect is 22. Then, there are 43.70% students who have difficulties in understanding making inference of the text with the total of incorrect is 52. Next there are 13.44% students who have difficulties in understanding to look for the detail information of the text with the total incorrect is 16. The factor of causing the students difficulties found in comprehending English reading text there are difficulty in understanding long sentence in the text, inadequate instruction presented by teacher, difficulty in understanding vocabulary, house environment and school environment.
RCC Research Guides: Life Sciences: Home

A basic introduction to the RCC Library resources which support study in the life sciences.
Library: Finding and reusing research datasets: Health & Medicine

Guide on finding secondary data for reserach and identifying suitable data archives for research dataset deposits.
Knowledge Distillation Based on Pruned Model

The high computational complexity of deep neural networks makes them challenging to deploy in practical applications. Recent efforts mainly involve pruning and compression the weights of layers to reduce these costs, and use randomly initializing weights to fine-tune the pruned model. However, these approaches always lose important weights, resulting in the compressed model performing that is even worse than the original model. To address this problem, we propose a novel method replaced the traditional fine-tuning method with the knowledge distillation algorithm in this paper. Meanwhile, With the Resnet152 model, our method obtained the accuracy of 73.83% on CIFAR100 data and 22x compression, respectively, ResNet110 SVHN achieve 49x compression with 98.23% accuracy and all of which are preferable to the state-of-the-art.
LibGuides: Community Needs Assessment: Home

Gathering information and data about the community happens before the planning process begins.
INTERNET OF THINGS (IoT) IN HEALTH INDUSTRY

In the digital age, IoT has become a part of our daily activity, which is linked with machines, people, time, locations, and required a network, which fully integrated into what is known as IoT (Internet of Things). The Internet of things has become the most significant technology that connected people and technology [3]. The goal of the IoT in healthcare is to monitor patient safety by using technology, it to avoid the critical quality of life by using intelligent IoT environments. The protection of data with IoT is highly complex and hard because IoT is the main issues of worldwide connectivity and availability. Design security and privacy must be part of any case, project, or installation of IoT use. Several articles have worked with various technology and energy efficiency on the access control system. Few reports suggested multiple kinds of authentication protocols. A scheme is needed to fuse the authentication protocol with the mechanism of effective access control and to counter other assaults on patient safety and privacy information. Following the methodology for the contract of authentication, access control, and the mechanism for energy- efficient access control, it is suggested to adopt mixed methods to balance the gap.
The Use of Dictogloss Technique to Improve Reading Skills in Shochukyuu Bunpou Courses for Second-Semester Students of the Japanese Language Education Study Program FKIP UHAMKA 2018/2019

Making language learning easy to learn is a challenge for language educators, therefore several learning techniques are needed. The purpose of this study is to improve the ability of students to use the grammar that has been learned. Learners not only understand grammar but use it in sentences or text reading. The learning technique in this study is the Dictogloss technique. This study uses a quasiexperimental method, with the design of the Pre-Post Test, samples and sources of research data are second-semester students, and the instruments used are in the form of tests. From the results of data analysis, it is known that there are differences in grammar skills, namely the reading skill after using the dictogloss technique. This is indicated by the acquisition of the average pre-test value of 53,3 and the post-test value of 73,3. By using the Dictogloss technique there is an increase in grammar understanding so that the reading skill of the second-semester students of Japanese Uhamka study programs is better than before. Keywords: Dictogloss technique, grammar, reading skill
Wavelet Based Video Denoising using Probabilistic Models

Wavelet based image processing techniques do not strictly follow the conventional probabilistic models that are unrealistic for real world images. However, the key features of joint probability distributions of wavelet coefficients are well captured by HMT (Hidden Markov Tree) model. This paper presents the HMT model based technique consisting of Wavelet based Multiresolution analysis to enhance the results in image processing applications such as compression, classification and denoising. The proposed technique is applied to colored video sequences by implementing the algorithm on each video frame independently. A 2D (Two Dimensional) DWT (Discrete Wavelet Transform) is used which is implemented on popular HMT model used in the framework of Expectation-Maximization algorithm. The proposed technique can properly exploit the temporal dependencies of wavelet coefficients and their non-Gaussian performance as opposed to existing wavelet based denoising techniques which consider the wavelet coefficients to be jointly Gaussian or independent. Denoised frames are obtained by processing the wavelet coefficients inversely. Comparison of proposed method with the existing techniques based on CPSNR (Coloured Peak Signal to Noise Ratio), PCC (Pearson’s Correlation Coefficient) and MSSIM (Mean Structural Similarity Index) has been carried out in detail.The proposed denoising method reveals improved results in terms of quantitative and qualitative analysis for both additive and multiplicative noise and retains nearly all the structural contents of a video frame.
LibGuides: Library Research Tips: Retrieving Articles

A short guide to retrieving articles in Bailey Library's databases and requesting them via Interlibrary Loan.
Chapter 7. Annotation tools for syntax

This chapter is devoted to the presentation of the tools and methods used for the different steps of the semi-automatic syntactic annotation: automatic preprocessing; microsyntactic parsing with the FRMG tool, correction of the parsing with the Arborator tool, agreement analysis, post-validation correction, and development of the final format of the Rhapsodie syntactic treebank. As FRMG is a parser for written French that was not configured to analyze disfluencies and reformulation, we used our manual pile marking to unfold the piles and produce a series of simplified “sentences” with only government relations. Despite having two annotators plus a validator for the corrections, we found a substantial number of errors in the post-validation procedure by using a set of rules to determine the well-formedness of the trees.
3D Average Common Submatrix Measure

This paper introduces a new measure for computing the similarity among 3D objects as the average volume of the largest sub-cubes matching in the objects. The match is approximate and only verified within a neighbourhood from the position of the sub-cubes. Preliminary tests performed on random and synthetic datasets prove the efficacy of the similarity measure in capturing the visual similarity among the 3D objects and a reduction in the execution time when the neighbourhood is considered.
Sentiment Analysis of Web Text Based on Deep Learning with a Attention Mechanism

The sentiment analysis of online commentary is a hot research topic in the field of network information mining. Traditional text sentiment analysis methods are mainly based on emotional dictionaries or machine learning. However, it relies on the structure of the sentiment dictionary and the artificial design and extraction features, which limits the generalization ability. In contrast, the deep learning model has a stronger ability to express complex mapping functions from data to emotional semantics. This paper proposes a model combining Bidirectional Gated Recurrent Unit(BGRU) neural network and Convolutional Neural Network(CNN), and introduces attention mechanism for text sentiment analysis. The experimental results show that compared with the traditional method, the method effectively improves the accuracy of text sentiment classification.
Histogram Publishing Algorithm Based on Sampling Sorting and Greedy Clustering

The data produced by differential privacy histogram publishing algorithm based on grouping has low usability due to large approximation error and Laplace error. To solve this problem, a histogram publishing algorithm based on roulette sampling sort and greedy partition is proposed. Our algorithm combines the exponential mechanism with the roulette sampling sorting method, arranges the similar histogram bins together with a larger probability by the utility function and the restriction on the number of sampled entity. The greedy clustering algorithm is used to partition the sorted histogram bins into groups, and the error among histogram bins in each group is reduced by optimizing the lower bound error of the grouping. Extensive experimental results show that the proposed algorithm can effectively improve the usability of published data under the premise of satisfying differential privacy.
What may or may not be certain : A Study of the Translation of Hedging Devices from English to Swedish in a Non-Fiction Text

Hedges, or hedging devices, are strategies that the writer or speaker can use in order to convey probability, impreciseness or vagueness. Hedges can appear in most parts of speech, for example as a ...
UWM Libraries Research and Course Guides: Evidence-Based Practice (EBP) Tutorial: Step 5: Audit/Re-Evaluate

Testing Ground for Revamping the EBP Tutorial How to Assess the success and continued functioning of the evidence in a clincical and academic environment.
Library: Finding and reusing research datasets: Code-Based Data

Guide on finding secondary data for reserach and identifying suitable data archives for research dataset deposits.
"Forming Teachers` Moral And Ethical Competences: Standpoint Of Hermeneutic Pedagogy And Psychology"

The relevance of the problem is due to the need for implementation of the process of forming teachers’ moral and ethical competencies from the standpoint of hermeneutics and insufficient development of theoretical, content-technological and scientific-methodological aspects of the formation concerning a new type of teacher in the process of teaching. The purpose of the article is to develop a model of the process of forming of moral and ethical competencies from standpoint of hermeneutics in the context of competence, hermeneutic, axiological and systemic approaches and its approbation. The main method of studying this problem is modeling, which makes it possible to consider the problem as a process of purposeful and conscious formation of moral and ethical competencies in the process of educational activities. The article presents a model of formation from the standpoint of hermeneutics, consisting of interrelated and interdependent structural value-semantic (axiological), meaningful and effective components; their features are identified; pedagogical conditions for the formation of moral and ethical competencies, an algorithm for the implementation of this model in the educational process of educational organizations is developed. The model is focused on the awareness and reconsidering of the conceptual values and priorities of pedagogic education, training a new type of teacher able to be competitive in the modern pedagogical market, possessing new professional competencies and high self-organization of professional development is developed.
Design Variables for Self-Directed Learning in MOOC Environment

Massive Open Online Courses (MOOCs) can meet education needs from diverse social, cultural, and access backgrounds and require a minimal cost of resources from learners.To successfully scaffold large and distributed populations to learn effectively in these MOOCs, the design needs to optimize self-directed learning.In this paper, the researchers investigated the design variables for MOOCs' learning environment that allowed learning choices made by learners.With this study, the researchers developed a 21-item questionnaire based on a review of the literature and their MOOC design and implementation practices, Massive Online Open Course Learning Environment Design Questionnaire (MOOC-LED).The researchers used the quantitative survey study and developed an initial examination of the MOOC-LED factor structure, validity, and internal reliability.The analyses were based on the anonymous data of 162 participants' perception of learning in MOOCs.The scholarly significance of the 21-item MOOC-LED questionnaire is discussed with its limitations, implications, and future directions.
The system of professional qualifications in the field of science [Система Профессиональных Квалификаций В Сфере Науки]

Examines approaches to the development of human potential in the field of science in the modern scientific and technological development and modernization of the system of higher education based on a system of professional qualifications in the field of research, development and higher education. The article presents organizational models of preparation for research, scientific and expert, scientific and entrepreneurial (innovative), scientific and pedagogical activities in the field of science. The article describes the practice of organizing research master’s programs and training in the field of science on the example of programs of academic institutions, University programs, network programs with corporate research programs of state corporations, programs of specialized school scientific and technological education.
LibGuides: Database Searching: Searching in Databases

Learn how to select a library database for your research topic and how to use the databases to find sources on your topic.
Weathering of metamorphic rocks and formation of planosols in semi-arid environment, Brazil.

The objective of this work was study the evolution of the weathering front in gneiss saprolites (felsic rocks) in two profiles of Planosols under different levels of severity of degradation (point 1 incipient degradation and point 2 degradaded area under desertified area in Pernambuco.
Large Scale Near-Duplicate Image Retrieval via Patch Embedding

Large scale near-duplicate image retrieval (NDIR) relies on the Bag-of-Words methodology which quantizes local features into visual words. However, the direct match of these visual words typically leads to unpleasant mismatches due to quantization errors. To enhance the discriminability of the matching process, existing methods usually exploit hand-crafted contextual information, which has limited performance in complicated real-world scenarios. In contrast, we in this paper propose a trainable lightweight embedding network to extract local binary features. The network takes image patches as inputs and generates the binary code that can be efficiently stored in the inverted indexing file and helps discard mismatches immediately during the retrieval process. We improve the discriminability of the code by elaborately composing the training patches for network optimization, which consists of a proper inter-class (non-duplicate) patches selection and a rich intra-class (near-duplicate) patch generation. We evaluate our approach on the open NDIR dataset, INRIA CopyDays, and the experimental results show that our method performs favorably against the state-of-the-art algorithms. Furthermore, with a relatively short code length, our approach achieves higher query speed and lower storage occupation.
Pre-emptive Culture Mapping: Exploring a System of Language to Better Understand the Abstract Traits of Human Interaction

A sustainable and ethical future, rich with technology, requires an abstract human framework of ideation in order to understand the reality of user experience (UX) and the context design will live in. The layer between the human and object needs to be better understood – early on. We too quickly replace one interaction with another. However, critical human traits often remain hidden until the product is in situ. Their appearance can have terrible consequences. These traits, and the behavioral codes that underscore them, can be understood early on by looking at language.
Professional Training Of A Literary Teacher: From Risks To Finding Resources

The relevance of the search for resources and technologies for the preparation of a literary teacher in the information era of the higher pedagogical education reform is due to the needs of science and society for teachers ready to work in the digital educational environment under conditions of uncertainty. The leading competencies of teachers are communication, corporativity, creativity and critical thinking. The search for harmony, a reasonable combination of online and offline education determines the risks of organizing professional training of a literature teacher, updates the technological possibilities of studies and methodological resources of all academic disciplines. The leading methodological approach of the research is an integrative approach, which realizes interdisciplinary, intra-subject, interpersonal and intrapersonal integration of the training of future literature teachers. The research methods are theoretical analysis and pedagogical experiment aimed to develop modern technologies for the professional and personal development of students in the information environment of the university. The results of the research are presented in the article as technological universal algorithms reproduced during the training of future teachers. The search for modern reserves of professional training for literary teachers continues in the era of risks, uncertainty and the digital educational environment. The path from risk to finding resources in the digital age of educational development is promising.
A replication of a cost-sensitive decision tree approach for fraud detection

Payment card fraud poses a problem with widespread implications. However, the class imbalance between genuine and fraudulent transactions presents a challenge to traditional learning methods. Cost-based methods address this problem by assigning different costs to the misclassification of each class. Sahin et al. [7] define a cost-sensitive decision tree algorithm, and this study attempts to both replicate and build on their findings. The results presented here do not support the hypothesis that the cost-sensitive algorithm provides an improvement over traditional decision tree algorithms. However, the results do suggest that different methods of prioritizing alerted transactions can lead to performance improvements over some measures.
TEACHERS ROLE AS MENTOR TOWARD STUDENTS LEARNING MOTIVATION

The problem in this research is the influence of teachers' role as a guide towards learning motivation for students in the state of Junior high School 2 Tanjung Lubuk District in the OKI Regency? The purpose of this research is to know the influence of teacher role as a mentor towards student motivation to study in the state Junior high School 2 Tanjung Lubuk in OKI district. The method used is a quantitative descriptive method with a correlation approach. The research technique uses a poll that is spread to 54 researches, documentation to obtain the data of students. The poll consists of two variables: variable (X) teacher role as mentor and variable (Y) Learning motivation. Where the variable (X) consists of 20 items and the variable (Y) consists of 20 items. Analysis of the data used is product moment analysis and significant test (Test T). Based on the research analysis, the significant test calculation (T-Test) of T_ value obtained is greater than R_tabel (3, 5293 > 1.67469). So it can be concluded that the role of teacher as a mentor has a significant influence on motivation to learn students. It is advised that teachers should besides teach; provide guidance to improve student motivation. Students are expected to motivate themselves in learning to be able to achieve maximum achievement.
Desktop Application Learning System: Multimedia Interactive Learning Online (MiLO) for Teaching and Learning Tool for Hotel Front Office Management

The rise of learning innovation suggested that distance learning include the use of technologies such as video, audio, computer and multimedia communications in support of extended teaching and learning. However, despite an increasing number of learning innovation, there has been little detailed documentation of the processes involved in this format for the animation production process. More specifically, there has been little documentation and analysis of the key considerations and issues encountered by practitioners when integrating 3D animation production process with teaching and learning tools. This study aims to examine the 3D animation production process of Desktop Application Learning System: MiLO. The Kemmis and McTaggart Action Research Model is adapted for the purpose of this study while utilizing qualitative method of analysis in developing the 3D animation desktop application for teaching and learning. Findings of this paper proposed a new framework of animation production process for teaching and learning application using the iClone software. This study has also provided a new framework in the animation production process that can be applied in teaching and learning either for researchers or designers alike in various fields.
Behind the Chatbot : Investigate the Design Process of Commercial Conversational Experience

The messaging-based conversational interfaces, commonly called Chatbots, have seen massive growth lately. With the proliferation of Chatbots, there is a growing demand for a better understanding of ...