Reviewerly/exHarmony huggingface dataset:
Pengaruh Pendidikan Etika, Self Efficacy, Religiusitas, dan Perilaku Kecurangan Terhadap Prestasi Akademik Mahasiswa Akuntansi (Studi Kasus pada Mahasiswa Akuntansi FEB Universitas Muhammadiyah Surakarta Tahun 2017)

This study aims to examine the effect of ethics education, self-efficacy, religiosity, and cheating behavior on the academic achievement of accounting students in the faculty of economics and business, Muhammadiyah University, Surakarta. This research uses quantitative methods using primary data obtained from questionnaires. The population in this study are accounting students in the economics and business faculties. The number of samples in this study were 79 respondents. Methods of collecting samples of convenience sampling techniques, the number of samples is determined by the Slovin formula. The analytical tools used include validity and reliability tests, normality tests, heteroscedasticity tests, multiple linear regression analysis tests, f tests, t tests, R² tests.Based on the results of data analysis, it can be concluded that: Self efficacy variable has a positive effect on academic achievement. While the variables of ethics education, religiosity, and cheating behavior did not affect academic achievement.
Fault Diagnosis of Resistance Network Based on Fault Dictionary Method

According to the experimental teaching practice process of circuit open experiment,this paper studies the fault dictionary method of fault diagnosis of resistor network. A fault dictionary of a single resistor in the circuit model is established by using the fault dictionary method for a simplified power system grounding network circuit model. After the fault voltage is known the fault resistance can be determined according to the fault dictionary. The resistance of the fault resistor can be calculated by KCL law and Ohm′s law. Finally,a general fault diagnosis software was designed with the help MATLAB Graphical User Interface (GUI). The experiment greatly stimulated students′ interest in experiment through the guidance of problem-discussion-discussion independent problem solving,and exercised students′ ability to comprehensively apply circuit knowledge to solve practical problems,and improved the students' self-learning ability and innovation consciousness.
The Effect Of Random Word Game In Improving English Vocabulary

The purpose of this study was determined whether the use of random word games could improved the ability of SMP N 2 Pancarijang students in vocabulary and whether students are interested in the method of this game. This study uses a mixed research method that was a quantitative research. The population of this study was seventh grade students of SMP N 2 Pancarijang in the 2018-2019 academic year. The total population was 87 students consisting of 4 classes. Class VII3 was taken as a sample using cluster sampling techniques, the total number of samples was 21. The instruments used in this study were vocabulary tests.The results of this study indicate that the pre-test got an average score (29,28) while the post-test got an average score (52,85). This shows that there was a significant difference between the pre-test and post-test. The p-value (0,00) is lower than the significant level (alpha (α) = 0,05). This means H1 was accepted. This study concluded that vocabulary teaching using the random word game improved students' ability to master vocabulary mastery in seventh grade students of SMP N 2 Pancarijang.
Research Guides: Perma.cc at Texas A&M: Home

Perma.cc is a free, open source tool developed at Harvard and offered by the Texas A&M University Libraries to prevent link rot in scholarship.
Code Behind Database

There are many times when it is necessary to establish a connection to a database and execute SQL commands against that database from the code behind of a page. For example, we may require the end user to click a Display button to display the contact information of his or her organization’s customers in a non-data-bound control like a multiline text box. Or we may require the end user to enter his or her login credentials and click a Login button to gain access to their application’s functionality. In both of these scenarios, we would need a page that interacts with a database from the button Click event handler method in the page’s code behind.
LibGuides: Library Support of Online Learning and Remote Services: Home

Hofstra University Library is working diligently to enable faculty teaching remote classes to directly engage with library faculty and staff to access the digital content and services they require to execute their courses.
The Role Of Information Technologies In Socializing And Studying Of Russian Students

The article investigates the problem of usage of digital technologies in the educational process by students in modern universities in Russia. The goal of the study is the investigation of the balance of time between purposes of education and socializing for students of Russian universities in the process of communication based on information technologies and discovering of ways to overcome barriers for eLearning. The study is based on the classical interviewing technology, using a survey developed for achieving the investigation goal. The survey consists of 4 sections and 21 questions and was presented in hard copies and on-line version in Google Forms. The total number of responding students was 300 from Murmansk region, St.Petersburg and Krasnodar Territory. The results of the study demonstrate that social networks are used by students in absolutely equal proportions for social communication and professional communication, fifty-fifty. The results are slightly different for students of Master and Bachelor level. The study results confirm the hypothesis that the main barrier in the use of digital technology in education is financial one. The results of the research highlight the important role of universities’ ICT infrastructure development for increasing of share of time for using digital technologies in professional purposes. The authors formulated the recommendations to make the barriers for students in the use of digital technologies in education lower.
A Study of Update Methods for BoND-Tree Index on Non-ordered Discrete Vector Data

There is an increasing demand from numerous applications such as bioinformatics and cybersecurity to efficiently process various types of queries on datasets in a multidimensional Non-ordered Discrete Data Space (NDDS). An NDDS consists of vectors with values coming from a non-ordered discrete domain for each dimension. The BoND-tree index was recently developed to efficiently process box queries on a large dataset from an NDDS on disk. The original work of the BoND-tree focused on developing the index construction and query algorithms. No work has been reported on exploring efficient and effective up- date strategies for the BoND-tree. In this paper, we study two update methods based on two different strategies for updating the index tree in an NDDS. Our study shows that using the bottom-up update method can provide improved efficiency, comparing to the traditional top-down update method, especially when the number of dimensions for a vector that need to be updated is small. On the other hand, our study also shows that the two update methods have a comparable effectiveness, which indicates that the bottom-up update method is generally more advantageous.
Distributed privacy preserving technology in dynamic networks

With the development of information technology, large-scale social network graph data have been produced and released to provide data analysis for scientific research and business structures, while traditional network privacy protection technology does not meet the actual requirements. In this paper, we address the privacy risks of link disclosure in sequential release of a dynamic network. To prevent privacy breaches, we proposed the privacy model km - number of mutual friend, where k indicates the privacy level and m is a time period that an adversary can monitor a victim to collect the attack knowledge. We present a distributed algorithm to generate releases by adding nodes in parallel. Further, in order to improve availability of anonymous graphs, distributed greedy merge noise node algorithm (DGMNNA) is designed to reduce the number of nodes added under the premise of satisfying the anonymous model. The experimental results show that the proposed algorithm can efficiently handle large-scale social network data while ensuring the availability of anonymous data.
MySQL Enterprise Monitor

Monitoring is one of the keystones of performance tuning whether you are looking at improving the performance at the system or query level. This chapter will look at one of the monitoring solutions available for MySQL, MySQL Enterprise Monitor, also known as MEM. The rest of the book uses graphs and reports from MySQL Enterprise Monitor to illustrate the use of a monitoring tool, but you can also use other monitoring solutions.
AN OVERVIEW OF THE VIRTUAL REALITY

Virtual Reality (VR) means experiencing objects or things through our computers that actually don't really exist. Virtual Reality is already becoming a very in demand concept, and with so many new cameras and devices, it can be easy to feel left behind. That's because VR is still relatively new technology.VR can also be defined as a believable, interactive 3D computer-created world for you to explore and to get the feel that you are really there, both physically and mentally.
The Learning Styles of Middle School Student for Solving Technological Problems

One of the current frontier points of learning evaluation is to focus on whether and how to use powerful digital technology to analyze digital data.This paper proposes a learning evaluation method based on big data.This paper constructs a new standard for the development of evaluation tools-metrolytic standards.The combination of standards used in the field of learning analytics and commonly used methods in educational measurement provides a framework for ensuring the reliability and validity of all educational evaluations.Measurement and analysis standards include quality requirements for the reliability, validity, accuracy, or interpretability of the test.These requirements are usually only applicable to high-risk, large-scale evaluations, such as PISA, SAT, or GMAT.The application of measurement analysis standards is based on a solid understanding of evaluation and its role in learning, combined with the advantages of learning analysis, artificial intelligence, and measurement science, and provides a choice for researchers in the frontier field of evaluation.
Between me, my younger self and the whole world: letters to one's younger self as epistolary genre

The research treats letters to one’s younger (usually teen) self posted on the Internet as epistolary genre marked with peculiar linguistic and pragmatic features. Though the letters to one’s self imply intrapersonal communication, i.e. the sender is identical to the addressee, it is not how the sender perceives the situation, which is revealed by the use of pronouns (I for the sender and you for the younger self). However, these two may merge and then we appears to refer to the author’s younger and current selves. Another feature of the letters is roles assumed by the addressors. They may occur as a mentor to their rebellious and anxious younger self, which correlates with the purpose of the letter – giving advice. Alternatively, the authors may position themselves as omniscient fortune-tellers who step in in times of trouble to offer support to their teen self by telling what is there to come. Each of the two roles and purposes correlates with specific language means. The mentor role turns the letter into a lesson where the Imperative Mood prevails. The role of a fortune-teller transforms the letter into an autobiographical sketch told in a bizarre way: the author shifts past events into the future with the help of deictic markers (e.g., today, this) and tenses (e.g., future tenses or their synonyms such as constructions to be about to and to be going to). The letters to one’s younger self that contain an autobiographical component provide the researcher with an insight into the process of identity construction, since they show how one endows identity with continuity and bridge the divide between one’s teen and adult selves. In addition, the letters meant as advice deliver the culture specific idea of what ‘a good life’ is: they are written to guide their actual intended audience, i.e. Internet (teen) users, in modern society and inform them of true values and right choices.
Hey #edu106 Here are the notes from today's Design Studio about adding an h-card to your @glitch website. Remember it is like a "business card" both people and websites can read

In Design Studio, our one hour drop in to hack on anything you want, Lilly had a question about adding an h-card to her website.So
IMPACT OF ELECTRONIC BANKING ON THE PERFORMANCE OF MONEY DEPOSIT BANKS IN NIGERIA

E- banking enable banks to speed up their retail and wholesale banking services; as the banking industry believes that adopting the new technology will help to improve customer service level and tie their customers closer to the bank. An understanding of the implications of electronic banking has therefore become crucial. It is on this basis that this study examined the impact of electronic banking on the performance of money deposit banks in Nigeria from 2006 to 2017 using time series quarterly data. The study adopted Ordinary Least Squares as main tool of analysis. The estimated regression equation showed that in the long-run, all the variables are correctly signed, except inter-bank transfer that is negatively signed. The policy implication of the findings is that e-banking has gradual positive impacts on performance of banks in Nigeria and hence could contribute to the process of economic growth. The research therefore suggests that banks must be focused in terms of their needs and using the right technology to achieve goals and objectives, rather, than acquiring technology of internet banking for having sake or because other banks have it and regulatory authorities like Central Bank of Nigeria must enforce fully the new standards and policy on electronic banking transactions.
Applying R-spatiogram in Object Tracking for Occlusion Handling

Object tracking is one of the most important problems in computer vision.The aim of video tracking is to extract the trajectories of a target or object of interest, i.e. accurately locate a moving target in a video sequence and discriminate target from non-targets in the feature space of the sequence.So, feature descriptors can have significant effects on such discrimination.In this paper, we use the basic idea of many trackers which consists of three main components of the reference model, i.e., object modeling, object detection and localization, and model updating.However, there are major improvements in our system.Our forth component, occlusion handling, utilizes the r-spatiogram to detect the best target candidate.While spatiogram contains some moments upon the coordinates of the pixels, r-spatiogram computes region-based compactness on the distribution of the given feature in the image that captures richer features to represent the objects.The proposed research develops an efficient and robust way to keep tracking the object throughout video sequences in the presence of significant appearance variations and severe occlusions.The proposed method is evaluated on the Princeton RGBD tracking dataset considering sequences with different challenges and the obtained results demonstrate the effectiveness of the proposed method.
Research Guides: Tips and Tricks for Teaching Remotely: Assessment Tools

This guide is intended to introduce you to material and resources that may help you when teaching a class remotely.
An Empirical Study of Schema Theory and Its Application in Improving University Students’ Writing Ability

The present study aimed at enhancing university students' writing ability through using schema theory.The study adopted the quasi-experimental pre-posttest experimental-control group design.The participants consisted of 58 English foreign language (EFL) students and 51 EFL professors who had taught essay writing.The students were divided into two groups: 29 students in a control group and 29 students in an experimental group.To gather the data, the researcher used pre and post-essay writing tests, interviews, and a five-point Likert scale questionnaire.The results of the study showed that there was a statistically significant difference between the performance of the experimental group and the control group on the posttest in favor of the experimental group.This indicated that applying schema theory has a positive effect on improving university students' writing ability.Finally, this study recommended that EFL teachers should encourage EFL students to share their prior experiences, knowledge, and information in the pre-writing phase in order to help them improve their writing skills.
DISERTO: Semantics-Based Tool for Automatic and Virtual Data Integration

In various domains, the continually increasing volume of heterogeneous data generated from different sources is overwhelming. However, the exploitation of this data is still limited while, in most cases, sources are not interoperable, and hence, data are not linked. These issues are due to the semantic, syntactic, and schematic heterogeneity of the data. In this work, we propose a semantic virtual Data Integration TOol based on Semantic Enhancement and RML (RDF Mapping Language) mappings called DISERTO. It automatically generates RML mappings through domain ontology and thesaurus to categorize the semantics behind the data. It follows three main steps: (1) extracting relevant metadata (data schema), (2) mapping metadata to a domain ontology by taking advantages of RDF quads, and finally (3) generating RML mappings. To validate the tool, we provide a case study based on real data provided by the Sahara and Sahel Observatory (OSS) and the National Oceanic and Atmospheric Administration (NOAA). It shows a semantic annotation followed by an RML mapping generation of a raster input image and CSV files.
LibGuides: Remote Resources for Library Users : Research & Library Support

Use this guide to access library resources and services off-campus to assist with your online courses.
Learning with imperfect supervision for language understanding

Humans learn to solve complex problems and uncover underlying concepts and relations given limited, noisy or inconsistent observations and draw successful generalizations based on them. This rests largely on the poverty of the stimulus argument, or what is sometimes called Plato’s problem: “How do we know so much when the evidence available to us is so meagre?” In contrast, the success of today’s data-driven machine learning models is often strongly correlated with the amount of available high-quality labeled data and teaching machines using imperfect supervision remains a key challenge. In practice, however, for many applications, large-scaled high-quality training data is not available, which highlights the increasing need for building models with the ability to learn complex tasks with imperfect supervision, i.e., where the learning process is based on imperfect training samples. When designing learning algorithms, pure data-driven learning, which relies only on previous experience, does not seem to be able to learn generalizable solutions. Similar to human’s innately primed learning, having part of the knowledge encoded in the learning algorithms in the form of strong or weak biases, can help learning solutions that better generalize to unseen samples. In this thesis, we focus on the problem of the poverty of stimulus for learning algorithms. We argue that even noisy and limited signals can contain a great deal of valid information that can be incorporated along with prior knowledge and biases that are encoded into learning algorithms in order to solve complex problems. We improve the process of learning with imperfect supervision by (i) employing prior knowledge in learning algorithms, (ii) augmenting data and learning to learn how to better use the data, and (iii) introducing inductive biases to learning algorithm. These general ideas are, in fact, the key ingredients for building any learning algorithms that can generalize beyond (imperfections in) the observed data. We concentrate on language understanding and reasoning, as one of the extraordinary cognitive abilities of humans, as well as a pivotal problem in artificial intelligence. We try to improve the learning process, in more principled ways than ad-hoc and domain or task-specific tricks to improve the output. We investigate our ideas on a wide range of sequence modeling and language understanding tasks.
LibGuides: Library Emergency Remote Support: Free Textbooks: Digital Content Unlocked During the COVID-19 Crisis

Library support and information for Fisher students studying remotely and faculty teaching remotely. Get free online access to your textbooks. Some publishers are making their digital textbooks available for free right now. You can check to see if your course's textbooks are now available, and faculty, you can share this information with your students.
Low-Resource Convolution Neural Network for Keyboard Recognition of the User

The article is devoted to the improvement of neural network tools for recognizing the user's identity by their keyboard handwriting. It is shown that the most promising recognition tools are based on convolutional neural networks, and its drawback is high resource consumption of the network. It is proposed to reduce resource consumption by using modern types of convolutional neural networks that are adapted to the expected conditions of the analysis of keyboard handwriting. As a result of the studies, it was possible to effectively analyze keyboard handwriting using a convolutional neural network of the SqueezeNet type, the main advantages of which are a small amount of memory consumed, high recognition speed, availability of a pre-trained model, the possibility of implementation using proven tools, and also sufficient recognition accuracy. The SqueezeNet model, adapted to the task of recognizing the identity of 10 users by their keyboard handwriting, is implemented using the MATLAB application package. As the analyzed parameters of the keyboard handwriting, the ASCI code of the entered character, the key holding time, and also the time between successive pressing of two keys are used. To encode the input parameters of the neural network model, a special procedure was used to represent the parameters of the keyboard handwriting in the form of a color three-channel square-shaped pattern 227x227 in size. Experimental studies have shown that, along with a fairly low resource consumption, the SqueezeNet model allows for the error in recognizing the user's identity by keyboard handwriting at the level of the best modern systems for this purpose. It is proposed to correlate the paths of further research with the development of a method for adapting the architectural parameters of convolutional neural networks to the recognition of the user's personality and emotional state based on an integrated analysis of several biometric parameters.