Reviewerly/exHarmony huggingface dataset:
Improving the students’ ability in using the simple past tense through climbing grammar mountain game of grade eight at SMPN 1 Percut Sei Tuan

This research was aimed to improve the students’ ability in using the simple past tense through climbing grammar mountain game. The subjects of this study were 32 students at 8th grade at SMPN 1 Percut Sei Tuan. This research was conducted by using classroom action research that consisted of 2 cycles. The technique of analyzing qualitative data, the researcher used observation test and interview test. While, technique of analyzing quantative data, the reseacher used the mean of students’ score and t test. The result of pre test showed that the mean of the students’ score was 41,71 in which there were 5 students (15,625%) passed minimum passing grade. In the post test I, there were 11 students (34,375%) passed minimum passing grade and mean of the students’ score was 60,93. Then, in the post test II, there were 27 students (84,375%) passed minimum passing grade and mean of the students’ score was 80. It indicated that climbing grammar mountain game could improve the students’ ability in using the simple past tense. This result was strengthened by the observation and the interview that showed the students were enthusiastic and active in the learning process.
How VoIP Enhances Client Communications for Your Veterinary Clinic

In modern societies, veterinary clinics play a much different role than they did in the past. At the beginning of the 20th century, people contacted vets ...
Application Systems Available In UNIMED Language Skills Text

This study aims to describe the attitude appraisal system contained in the French thesis text at UNIMED. The method used in this study is a descriptive qualitative method. The research sample is the French thesis text at UNIMED on behalf of Ayokta Ghea M. Panjaitan, NIM. 21013001 where the type of thesis is linguistics with the title Analyze De Champ Lexical Des Activités Des Yeux En Français (Analysis of the Lexical Meaning of Eye Activity in French) totaling 58 pages with the highest GPA of 3.85 and Irna Fadillah Nasution, NIM. 2101131002 with a GPA of 3.45 with the title of the thesis Analyze Sémiotique De La Publicite Femme De Beauté Dans Le Magazine Femme Actuelle (Semiotic Analysis of Beauty Advertisements in the French Magazine Femme Actuelle) totaling 60 pages that have been validated by native speakers teaching at the French Language Education Study Program UNIMED in 2015 and also teaches at the Alliance Française (AF) called Marine Petite. Data were analyzed using the Simple Concordance Program (SCP) concordance program software using the Apraisal system, namely: Attitude Apraisal. The results showed that the Apraisal System in the French Thesis text at UNIMED was the Paradigmatic System because the Apraisal System in the French thesis text consisted of (a). Gender (le gendre), which consists of: masculine (masculin) and feminine (féminin) and (b). Total (le nombre), which consists of: single (singulier) and plural (pluriel).
Key ideas of Rostock pedagogical technology in the context of the New Ukrainian School

The article reveals the basic conceptual ideas of pedagogical technology «Rostock», developed and researched for many years and confirmed by its correlation with the principles of the New Ukrainian School. The basic ideas of Rostock technology can be defined in the acronym for the word IDEA, as an important tool for educational reform and considered in relation to its structural components: I - integration, D - activity, E - ecology, I - quality. It is shown that the performance of each of these components depends on their systematic interaction. The expediency of a competent approach to teaching, which positively influences innovative pedagogical design in the conditions of the New Ukrainian School, is substantiated.
Conceptual models for integration of Data Mining and SEO to Improve E-Commerce Performance

Since the initiation of online trading in Indonesia, the public trust getting higher in using e-business applications have a positive effect, in the form of more open markets and raised competition to gain consumer trust. This requires a concern of company management settling their product sales strategies to continue going up, mainly online trading. At some point, the technique used for online marketing is SEO (search engine optimizer), but in its use, SEO still has some drawbacks. Therefore, in this article it is proposed to carry out data mining integration with SEO, so that the results can be used to improve e- business performance support that can be used as an alternative decision-making by management. Keywords: SEO, data mining, e-commerce, management, marketing
Credit Card Fraud Detection Using Machine Learning

Now a day’s online payment gaining popularity because of easy and convenience use of e commerce. It became very easy mode of payment. People choose online payment and e-shopping; because of time convenience, transport convenience, etc. As the results of immense quantity of e-commerce use, there is a vast increment in credit card fraud also. Machine Learning has been successfully applied to finance databases to automate analysis of huge volumes of complex data. Machine Learning has also played a salient role in the detection of credit card fraud in online transactions. Fraud detection in credit card is a big problem, it becomes challenging due to two major reasons–first, the profiles of normal and fraudulent behaviors change frequently and secondly due to reason that master card fraud knowledge sets are extremely skew. This paper research and checks the performance of Random Forest on highly skewed credit card fraud data. Data set of credit card transactions is sourced from European cardholders containing 1 lakh transactions. These techniques are applied on the raw and pre processed data. The performance of the techniques is evaluated based on accuracy, sensitivity, and specificity, precision.
Attribute based Data Management in Crypt Cloud

Data proprietors are going to store data of theirs to come down with a public cloud together with a particular set and encryption of characteristics to get into command on the cloud Data. While uploading the data into the public cloud they are going to assign a bit of attribute ready to the data of theirs. In case any kind of authorized cloud person really wants to obtain the data of theirs they need to type in that here specific feature placed to carry out additional steps on Data owner's information. A cloud person really wants to register the details of theirs below the cloud group to use the Data owner's information. Owners wish to publish the details of theirs as characteristics together with the designation of theirs. In line with the person specifics, Semi Trusted Authority makes decryption secrets to obtain command on the owner's information. An end-user is able to conduct a great deal of businesses with the cloud Data. In our proposed system, we have designed the attribute-based security schemes for managing the cloud data and achieving the security level on comparing with the existing system.
How to Learn Picture Languages

Analysis of sentences in a natural language is often based on similar methods as analysis of formal languages.Analogically, analysis of pictures could be based on analysis of formal picture languages.However, the field of formal picture languages is not developed enough for this purpose.This paper presents several models of automata accepting twodimensional languages and outlines their learning capabilities.Further, it examines the possibility of transforming a two-dimensional language into a one-dimensional language and applying machine learning techniques in a single dimension.In this paper, we propose a new representation for formal picture languages consisting of two components -a picture-tostring function and a string language.The function rewrites any twodimensional picture into a string.A picture language is then the set of all pictures that the function maps into the given string language.Using this representation, picture languages can be learned by applying methods of grammatical inference for string languages.
Text Categorization with Fractional Gradient Descent Support Vector Machine

Text documents on the web are an incredible resource including one example of big data, large size and so many variations that it becomes difficult for humans to choose meaningful information without the help of a computer.Text categorization job is to automatically classify text documents into standards class based on their content.The objective of this research is to implement a classifier with optimization based on the Fractional Gradient Descent in text classification.In our research, we propose using the Fractional Gradient Descent to optimize the SVM classifier so that it can increase the speed of training data.We explore a batch of different training data to compare the speed of the UCI ML text dataset training process with the SVM-SGD and SVM-FGD classifiers.This research concludes that using SVM-FGD will optimize the training time for text dataset in the activity of data classification.
Corpus linguistic analysis of prefix independence and substantiality.

The purpose of this study is to identify the independence and substantiality of prefixes. Affixes are bound morphemes, not free morphemes, and belong to grammatical morphemes rather than lexical morphemes. However, prefixes belonging to subcategories of affixes often have lexical meanings that are difficult to distinguish from general roots, and at the same time, they are used freely from the roots. The independence and substantiality of these prefixes have been the main cause for discussion of the categorization and scope of the prefixes. This paper attempts to quantitatively study the prefix’s independence and substantiality by analyzing the prefix appearing in The new Yonsei written corpus. A total of 34 prefixes were found in The new Yonsei written corpus. Twenty-one of the 34 prefixes have been segmented with nouns at least once, and in particular, all the high ten prefixes have been found to be segmented with nouns. And every prefix has substantial meaning. As a result, it turned out that independence is a concept of degree and that all prefixes have substantiality.
Marketing Your Library

Presentation slides for Marketing Your Library by Janet Dennis and Lisa Lansdale. Presented at MegaResource 2020.
Fast Hash Based High Secure Hiding Technique for Digital Data Security

In present time, data hiding emerges as one of the important issues in data embedding and security due to the increase of technology. To improve the quality of the video and the security of the data, this paper deals with data hiding technique using proposed SAJ encryption-decryption technique. The data is embedded in different video frames and it is embedded using a cryptographic hash function with a secret key to enhance the security of the data. We also compared different data hiding techniques to ensure the efficiency of algorithm such as codeword substitution, steganography, watermarking, LSB substitution and cryptography. Our focus is to enhance the security, reliability, and to keep the size of the data as low as possible. In this paper, we have proposed new data hiding technique, hash-based high secure hiding technique (HBHSHT) which is more reliable as estimated. It supports a well user-defined level of accessibility and security. As compared different techniques, it is found that the proposed algorithm is more efficient approximately 8%.
A generalized method for computation of n-dimensional Radon transforms

Radon transforms allow to represent n-dimensional objects by all their possible (n-1)-dimensional integrals. They find broad usage in a variety of image processing topics, covering pattern recognition and tomographic imaging. Potentially the most frequently used version is the 2D Radon transform which is commonly computed by means of the ray tracing procedure (Siddon, Joseph etc.).<sup>1</sup> The problem comes down to a method of approximating a line integral through a 2D pixelized image. For higher dimensions, however, this problem becomes more and more complex and typically involves a substantial amount of case differentiation, making it particularly ill-suited for use in massively parallelized computation (e.g. on GPUs). Additionally, implementation effort is substantial and quite error-prone. Here, we propose a simple strategy to compute the (n-1)-dimensional integrals in a generalized manner by reducing the sampling problem to a single matrix multiplication. We further present OpenCL implementations for n=2 and n=3, making use of hardware interpolation methods on texture memory of GPU devices to provide a fast computation of the transform.
Calling all hackers—endangered wildlife needs you

[Extract:] Much of the illegal trade is happening online. That means that computer-literate folks have an exceptional opportunity to help combat the epic slaughter of Earth’srarest and most spectacular species by calling out, harassing and disrupting illegal traders.
LibGuides: 12 Month Children's Programming: Overview

Created by Jessica Jean Walker for INFO 260A: Children's Programming and Services (Fall 2019), Instructor Wrenn-Estes
Pengaruh Usia Terhadap Besarnya Dosis Serap Radiasi Sinar-X yang diterima Pasien Pemeriksaan Toraks

Thereâ€™s been research aimed at finding out the effects of age on the large absorbed dose of X-ray radiation received by the patientâ€™s thorax examination. The observation data used to figure out the absorbed dose received by the patient is exposure factor consisting of tube voltage (kV), current (A), time (s), and distance (m) of patient from radiation source. The age range of patient obtained in this research is from 17 years until 48 years old, then itâ€™s grouped by the age category set by Depkes. From the observation data of exposure factor and patients age, further do the test using Oneway Anova statistical method test, by taking a significance level of a 0,05. The results from Oneway Anova statistic test is obtained FCalculate value is 1,532 amd sig is 0,211 with FTable value is 2,70 and sig is 0,05 therefore based on test criteria in statistic the early hypothesis (H0) is accepted. Presumably that the age is not affect on the large absorbed dose X-ray radiation received by the patient thorax eximination of range 17 years until 48 years old.
RNC: Reliable Network Property Classifier Based on Graph Embedding

In the past two decades, analyzing the information network has been intensively studied from various disciplines. Small world property and scale-free property prevail in network science research. The comparison and classification of different kinds of graphs are extremely important. However, how to design a robust and accurate classification with deep learning techniques for network property still lack enough attention, which is a vital task in various application scenarios. In this paper, we proposed the reliable network property classifier based on graph embedding(RNC) to classify the network property (scale free or small world property). In order to process non-euclidean data, we embedded each network into an image and use dimensional reduction, rasterization, and convolutional neural networks to complete the classification problem. The method can effectively accomplish classification tasks in not only artificial networks but also real networks. Besides, RNC wins greatly in terms of robustness on real networks, showing the robustness of RNC against the incomplete structure of the network.
SOME INFILTRATION CAPACITY UNIT OF LAND IN MANADO STATE UNIVERSITY AS LECTURES REFERENCES

This study aims to 1) explore concepts and processes of the science of infiltration in a place that varies (slope and vegetation plants) at UNIMA 2) designing concepts and processes of the science of infiltration as lecture references.This study was carried out in June 2019 at the land of the State University of Manado.This study uses explorative research.The results of a measurement of infiltration are the land that has slope 10 0 and dampness 20% as well as in the dominance of grass has the highest rate of infiltration whereas the land that has the texture of the solid land (clay) and nothing plants has the lowest rate of infiltration.Exploring facts in the infiltration can be connected with concepts and processes of science in the form of a matrix.Designing concepts and process science of infiltration such as the material relating to infiltration, the description of the concepts of science on infiltration, and using 3 procedures of explorative in worksheets as a reference in learning processes and practical work in land science courses.The conclusions are concepts and process science of infiltration of covering physics (gravitation, capillarity, the collision on the ground, the mass of raindrops, the mass of the land, the intensity of light, free fall, the dampness of the land), chemistry (the content of rainwater chemicals, heat energy, soil pH), biology (evaporation, kinds of roots, hydrology).It can be in the form of a matrix as well as design concepts and process science of infiltration such as material and worksheets as lecture references inland science courses.
Multifaceted Analysis of Fine-Tuning in a Deep Model for Visual Recognition

In recent years, convolutional neural networks (CNNs) have achieved impressive performance for various visual recognition scenarios. CNNs trained on large labeled datasets not only obtain significant performance on most challenging benchmarks but also provide powerful representations, which can be used for a wide range of other tasks. However, the requirement of massive amounts of data to train deep neural networks is a major drawback of these models, as the data available are usually limited or imbalanced. Fine-tuning is an effective way to transfer knowledge learned in a source dataset to a target task. In this article, we introduce and systematically investigate several factors that influence the performance of fine-tuning for visual recognition. These factors include parameters for the retraining procedure (e.g., the initial learning rate of fine-tuning), the distribution of the source and target data (e.g., the number of categories in the source dataset, the distance between the source and target datasets), and so on. We quantitatively and qualitatively analyze these factors, evaluate their influence, and present many empirical observations. The results reveal insights into what fine-tuning changes CNN parameters and provide useful and evidence-backed intuition about how to implement fine-tuning for computer vision tasks.
Influence Prediction Using Bayesian Belief Networks For Real Life Networks

Influential node identification could soon become a key practice to define the flow of information throughout any network. It has already been frequently attempted using graph theory approaches and optimization techniques approaches such as node centrality measures, label propagation, Naive-Bayes approaches and a lot more. In this paper, we try to use the generalised Bayesian Belief Networks to classify data from an open source data repository using the basic probability distribution of multiple variables. The intent is to accurately predict influential repositories from a collection of repositories after data cleaning, data processing and modeled semi-supervised learning. We also use Naive Bayes algorithm and and Simple Logistic Regression on the same data and found that the underlying mask of Belief functions in Bayesian Belief Networks predicts the influence of a given new data more accurately than the other two algorithms.
A Comparison Between Field User Research Methods in a Redesign Context : A Comparison Between Field User Research Methods in a Redesign Context

As aging softwares can require a redesign to keep up with competitors or interaction trends, usability practitioners are challenged with choosing methods for usability evaluation and user research. ...
LibGuides: Login To ICC Library Databases: Login Information

OpenAthens is an access management platform, allowing libraries to enable and monitor access to subscribed online content. Access and authentication are managed simply, securely, and effectively while providing insight and data that supports the informati
Adjustable Panoramic Inspection System forSub-Millimeter Fasteners

Fasteners are critical and indispensable locking components in mechanical assembly. Submillimeter fasteners are massively and widely used in electronic devices. This study proposed an adjustable panoramic inspection system for M2 to M0.8 submillimeter fasteners. The system mainly consists of a panoramic imaging module, a back-light module, and an image grabbing and computing module. The panoramic imaging module would form four equal optical path lengths to keep the same imaging amplification between the different directions of the field of view. The back-light module was designed to provide uniform illumination and enhance the contrast of the pitch edge between the fasteners and the background. The image grabbing and computing module with a high-speed camera was designed to be adjustable for different sizes of submillimeter fasteners. The realized system can offer the function of four images in one shot to make a panoramic scene, independent illumination for recognizing, inspect screws from M0.8 to M2.0 screws, and short time consumption of image processing, such as 3.284 ms for M0.8 screws and 2.384 ms for M2.0 screws, to achieve examination of 6000 pieces in 1 min.
An Analysis of a Randomized Local Search Algorithm for the Entropy Space

In previous work, we proposed a randomized local search algorithm to determine the distribution associated with a vector given in the entropy space. The algorithm also finds the nearest vector and corresponding distribution if the given vector is non-entropic. The utility of the algorithm for entropy optimization has been shown. A trade-off between entropy functions is observed. The convergence is better in comparison to the other algorithms used in the entropy region. Finally, the time and space complexities have been computed.
LibGuides: Library FAQ Video Guide: FAQs

Training videos on various library and research-related topics, such as online resources, textbook rentals, and citations.
Literature as a Medium of Exposing Social Problem through Thomas Gray’s “Elegy Written in A Country Churchyard

Apart from being an entertainment medium, literature has also an important role in exposing social problems, as basically literature is born and is intended for the community. Through the disclosure of social problems, the role of literature is increasingly developing, among others, as a medium of teaching, reference, reflection, character building and also criticism. Thus, it is clearly illustrated that literature has multifunctional roles. The message conveyed through literature can be effectively absorbed by the community owing to the entertainment factor. Through the poem Elegy Written in a Country Churchyard, Thomas Gray tells the story of the lives of marginal people, always having to face problems. Through descriptive qualitative research method, referring to social phenomena, supported by sociology of literature approach, the results of the study show that there are three social problems that always arise in the community, especially in the lower class one: poverty, right to get proper education and equality to obtain opportunities in the line of life. These three social problems are closely interrelated so that they become a unification undermining the lives of marginalized people.