Reviewerly/exHarmony huggingface dataset:
Heuristic Dominant in Ch. Aitmatov’s Novel “Cassandra’s Brand”

The article for the first time theoretically justifies adequacy of using the term “heuristic literature” in relation to Ch. Aitmatov’s works. Originality of the analytical approach includes identifying similarity of the author’s biographical time, space and the text chronotope. The hypothesis that the American futurologist Alvin Toffler served as the main character’s prototype is discussed. The findings indicate that the novel’s dominant focus lies in artistic development of relevant problems of the modernity that constitute axiological foundation of modern aesthetic discourse.
An Analysis of Code Switching Used by an English Teacher in Teaching Process

This research is aimed to know the types and functions of code-switching that used by an English teacher at MAN 1 Pidie. The approach of this research was qualitative method. The data were gathered from direct and indirect observation of the English teaching process in the classroom. The writer used Jendra’s (2013) theory to analyze the types of code switching and Mattson and Burenhult’s (1999) theory to analyze the functions of code switching of the selected data. The findings of this research showed that the teacher used all three types of code switching in teaching English process which includes tag code-switching, inter-sentential code-switching and intra-sentential code-switching. Based on occurrence frequency tag code-switching was the most-used type, while inter-sentential code-switching was the least. The writer also found all three functions of code-switching those are topic switch function, affective function and repetitive function. In this research, topic switch function tend to be used more frequently among others function which makes it the highest percentage.
EDUCATION AND QUALIFICATION CHALLENGES FOR YOUNG PROFESSIONALS TO ADDRESS DIGITALIZED WORK AND LIFE CONTEXTS

M. Amorim, M. Ferreira Dias, M. Rodrigues, R. Madureira, M. Madaleno, A. Souza, R. Rivera, A. VitoriaUniversidade de Aveiro (PORTUGAL)
Research on Optimizing Training Strategies for Graduate Teaching Assistants in “Double First-Class” Higher Education Institutions

The teaching assistant program currently plays a common role in developing students’ overall qualities. Through nuanced analysis based on cases from graduate teaching assistants at “Double First-Class” HEIs, this paper shows how graduate teaching assistant programs work from the perspective of program administration and personnel training. In order to iron out problems in the present training system, implications for optimizing the two-year GTA training program are also explored.
Disruption of writing by irrelevant background speech: what role for number of voices and language?

Disruption of writing by irrelevant background speech: what role for number of voices and language?
A Framework for Word Segmentation in Images using Density-based Clustering

Word recognition is to identify words in images of printed or handwritten documents. It is especially challenging to recognize words from cursive handwriting documents. In this paper, we present a framework of using density-based clustering for word segmentation in printed or handwritten documents, including cursive handwriting. First, we performed various strategies for data preprocessing, including converting images to B/W images, adjusting the tilted images, and removing the background noises. K-means clustering and/or neighborhood density are used in finding parameters for the preprocessing steps. The preprocessing has shown to be very effective. For the word segmentation, we proposed density-based clustering to segment the words using multiple steps, including blurring, plotting, and clustering. We also developed a system for the framework, including preprocessing and clustering functionalities. Our approach works very well for printed documents. It works reasonably well for handwriting documents if words are relatively far from each other. The performance on handwriting documents can be further improved by using line segmentation.
A Graph-Based Tool to Embed the π-Calculus into a Computational DPO Framework

Graph transformation approaches have been successfully used to analyse and design chemical and biological systems. Here we build on top of a DPO framework, in which molecules are modelled as typed attributed graphs and chemical reactions are modelled as graph transformations. Edges and vertexes can be labelled with first-order terms, which can be used to encode, e.g., steric information of molecules. While targeted to chemical settings, the computational framework is intended to be very generic and applicable to the exploration of arbitrary spaces derived via iterative application of rewrite rules, such as process calculi like Milner's π-calculus. To illustrate the generality of the framework, we introduce EpiM: a tool for computing execution spaces of π-calculus processes. EpiM encodes π-calculus processes as typed attributed graphs and then exploits the existing DPO framework to compute their dynamics in the form of graphs where nodes are π-calculus processes and edges are reduction steps. EpiM takes advantage of the graph-based representation and facilities offered by the framework, like efficient isomorphism checking to prune the space without resorting to explicit structural equivalences. EpiM is available as an online Python-based tool.
Revisiting the digital noise reduction in automatic contouring of “ice-water” objects

This work describes the practical implementation of the method for digital noise suppression during processing images containing ice information to recognize automatically the contours of «ice-water» objects during aerial photography. Images containing ice information have special characteristic structural features related to noise, e.g. granularity, glare, ice crumbs. This makes difficult or even impossible to recognize automatically the contours of ice-water objects. It is known that the success of the application of edge recognition methods depends on how much image noise is reduced. The paper discusses the construction method for the management of noise. The method is based on the sequential application of the Haar wavelet transform denoising using thresholding, clustering by k-means method. For the subsequent automatic construction of ice floes contours the Sobel operator is applied. The aim of the work is to develop a method capable to process digital images effectively that contain ice information with strong digital noise. In this work we treated the images of one-year ice containing strong digital image noise in the form of granularity and in the form of ice crumbs. A description of the features of each of the steps of the proposed method and practical application is given. As a result, the method was developed for processing images of ice information containing digital noise in absolute value commensurate with the basic data. It was noted that the use of the k-means method expands the scope. The k-rare method allows more detailed processing of ice information and distinguishes not only the contours of ice-water objects, but also the contours of ice crumbs. The conclusion formulates the main advantages of the method and the possible application of the algorithm in the process of local exploration of the ice conditions of the Northern Sea Route channel using unmanned aerial vehicle for aerial photography. The usage of unmanned aerial vehicle for aerial photography will increase the frequency of weather forecast updates and predict the appearance of ice objects at the ship’s heading. That will allow us to select the safest and most economical efficient route along the Northern Sea Route. The authors have no competing interests.
A CASE STUDY OF COMPATIBILITY OF THE INDIAN HIGHER EDUCATION SYSTEM WITH EUROPEAN CREDIT ACCUMULATION AND TRANSFER SYSTEM IN 2020

There is a perceived need for reform in higher education in India. This is seen in juxtaposition to the general spirit of reform that has been synonymous with the European Higher Education Area by way of ECTS system. The reforms compatible with the ECTS system have been adopted in many other parts of the world. Ball (2003) states, “[a]n unstable, uneven but apparently unstoppable flood of closely inter-related reform ideas is permeating and reorienting education systems in diverse social and political locations which have very different histories”. Accordingly countries at different stages of industrial and technological developments, disparity in wealth and political economic systems are embarking with remarkable consistency in their educational reform agendas. Stemming from this perspective my paper is proposed to be in the nature of a report on my research completed as a dissertation as an Erasmus Mundus student for ‘European Masters in Lifelong Learning-Policy and Management’ at the University of Deusto, Bilbao.The issues that the paper raises is the perceived need for reform in higher education in India and drawing a parallel from the reform agenda in Europe in the higher education systems and processes that has been set rolling by the Bologna process examines the desirability and the possibility of building compatibility of the Indian higher education system with the European Credit Accumulation and Transfer System.Such studies have been carried out in the context of countries where significant progress has been made in terms of building systems for compatibility and comparability in the structures and processes of higher education such as the European Union (e.g. The Tuning Project) and “countries in transition” [Eastern Europe], Africa, Latin America and the Caribbean. However, very little has been written with this focus in the Indian context.The overall paradigm for conceptualizing the research was conceived with a ‘Pragmatic’ orientation using a mix of methods. Multiple stakeholder perspective was obtained using both qualitative and quantitative methods to obtain a 360 degree orientation. The approach being exploratory and descriptive, the model for the qualitative research design was kept interactive, adopting in depth interviews. This used broad areas of enquiry and questioning guidelines to provide adequate and pertinent exploration of various themes as the technique of preference. Likert scaling was used for the attitude survey. The overall approach was kept interconnected and flexible with reference to the Goals, Conceptual Framework, Research Question, Methods, and Validity. The study concludes that many of the features of ECTS currently have no equivalents in the Indian system, though wide ranging initiatives in the areas of mobility, NQF and Quality as a follow up to the Bologna declaration, can provide a response to some of the challenges facing Indian higher education. The study also revealed a palpable space and a perceived need for a policy push in these directions.
Learning Inverse Rendering of Faces from Real-world Videos

In this paper we examine the problem of inverse rendering of real face images. Existing methods decompose a face image into three components (albedo, normal, and illumination) by supervised training on synthetic face data. However, due to the domain gap between real and synthetic face images, a model trained on synthetic data often does not generalize well to real data. Meanwhile, since no ground truth for any component is available for real images, it is not feasible to conduct supervised learning on real face images. To alleviate this problem, we propose a weakly supervised training approach to train our model on real face videos, based on the assumption of consistency of albedo and normal across different frames, thus bridging the gap between real and synthetic face images. In addition, we introduce a learning framework, called IlluRes-SfSNet, to further extract the residual map to capture the global illumination effects that give the fine details that are largely ignored in existing methods. Our network is trained on both real and synthetic data, benefiting from both. We comprehensively evaluate our methods on various benchmarks, obtaining better inverse rendering results than the state-of-the-art.
E-DIARY PAPER ASSISTANT

On average, a smart phone has 41 applications, and each day many numbers of new phones are being activated. Perhaps the foremost startling statistic is that currently, 1.3 million Android devices are activated a day which suggests that each 24 hours, quite fourfold as many new smart phones and tablets are found out than babies are born. And once the devices are activated, they're checked on the typical 150 times every day once every 6.5 minutes. The apps in both Apple’s and Google’s app store combined is over 2 million. Admittedly, the apps are the aim behind the smart phone. Furthermore, on the average every smart phone contains 41 apps which are used for normal needs. A calendar is a tool that keeps every aspect of our life focused in one place, allowing you to worry less and accomplish more. Using the calendar is the best way to avoid procrastination and general tardiness. Calendar app is that the most ancient and best way for time management. The first cellular device with the calendar app was Simon. Though, it's not called a sensible phone but it's the primary cellular device which has address book, calendar, and appointment scheduler apps with its touch screen display. Since then many works have been going on in improving the calendar app. Mobile Operating System is an operating system designed for smart phones, tablets and other mobile devices. It is just like a regular operating system for a computer but it combines other features along with camera, audio, video, radio, bluetooth, speech recognition and many others. E-diary is an android application which accesses the calendars of multiple users, for instance, members of a family or staff in a particular department and will pull out the events from every calendar. Hence, everyone in the group can see others’ events on one screen in customized format. It also helps the user to create, edit, and delete events of his/her calendar. Additionally, this application will use an efficient strategy to update data only if there is any change in the events, making it faster. There are many other applications in the Play store but they cannot get rid of redundant events and reminders of events belonging to other users. This causes tons of disturbance to the user. On the contrary, E-diary application will use an intelligent algorithm to compare the events in some ways supported the time, name, and place of event and this application will only generate reminders for the user scheduled events.
A Monitoring Framework for Side-Channel Information Leaks

Security and privacy in computer systems has always been an important aspect of computer engineering and will continue to grow in importance as computer systems become entrusted to handle an ever increasing amount of sensitive information. Classical exploitation techniques such as memory corruption or shell command injection have been well researched and thus there exists known design patterns to avoid and penetration testing tools for testing the robustness of programs against these types of attacks. When it comes to the notion of program security requirements being violated through indirect means referred to as side-channels, testing frameworks of quality comparable to popular memory safety or command injection tools are not available. Recent computer security research has shown that private information may be indirectly leaked through side-channels such as patterns of encrypted network traffic, CPU and motherboard noise, and monitor ambient light. This paper presents the design and evaluation of a side-channel detection and exploitation framework that follows a machine learning based plugin oriented architecture thus allowing side-channel research to be conducted on a wide-variety of side-channel sources.
Pemilihan Gaya Belajar untuk Meningkatkan Keaktifan Siswa dalam Pembelajaran Bahasa Indonesia

Every success in the learning process will affect environmental factors, schools, attitudes, or students themselves. Each student enhances cognitive, affective, and psychomotor development. Student trading has the uniqueness and character of each in the learning process to respond to and understand teaching material or information obtained. Student learning independence can be seen from the achievements of students in responding, solving, and processing information by completing various tasks. Every student has a learning style that is prominent in him, and the teacher must be able to accommodate it. That is to achieve the learning objectives well and effectively. Learning style is the key to student success in learning. There are models (Type) of learning styles (Fleming, 2001), VARK (Visual, auditory, Reading, Kinesthetic) that can increase student activity in learning Indonesian. Students can learn through the senses that they have with a visual learning style that learns from what is seen, students with an auditory learning style that is learning through what is heard, and a kinesthetic learning style that is learning through motion and opening.
Cross-project Classification of Security-related Requirements

We investigate the feasibility of using a classifier for security-related requirements trained on requirement specifications available online. This is helpful in case different requirement types are not differentiated in a large existing requirement specification. Our work is motivated by the need to identify security requirements for the creation of security assurance cases that become a necessity for many organizations with new and upcoming standards like GDPR and HiPAA. We base our investigation on ten requirement specifications, randomly selected from a Google Search and partially pre-labeled. To validate the model, we run 10-fold cross-validation on the data where each specification constitutes a group. Our results indicate the feasibility of training a model from a heterogeneous data set including specifications from multiple domains and in different styles. However, performance benefits from revising the pre-labeled data for consistency. Additionally, we show that classifiers trained only on a specific specification type fare worse and that the way requirements are written has no impact on classifier accuracy.
Image Enhancement Techniques: An Exhaustive Review

The various image enhancement techniques are used as a preprocessing step in the image processing task to make the image more productive to be processed in the computer. In this work, the brief study of the various image enhancement methods like Histogram Equalization, Adaptive Histogram Equalization, Contrast Limited Adaptive Histogram Equalization is done. These techniques are verified based on MATLAB an image processing toolbox along with their corresponding images and histograms. Different techniques have their own pros and cons so here the juxtaposition of the various methods have been done along with the calculation of the different image parameters like - Standard Deviation, Mean, Mode, Medians, Mean Squared Error for these enhancement techniques.
LibGuides: Education: Find Articles

A research guide to introduce you to the field of education. You'll find the materials, search tools, and other resources you need to start your research. If you need any assistance, please contact your librarian.
Differentially Private Formation Control

As multi-agent systems proliferate, there is increasing demand for coordination protocols that protect agents' sensitive information while allowing them to collaborate. To help address this need, this paper presents a differentially private formation control framework. Agents' state trajectories are protected using differential privacy, which is a statistical notion of privacy that protects data by adding noise to it. We provide a private formation control implementation and analyze the impact of privacy upon the system. Specifically, we quantify tradeoffs between privacy level, system performance, and connectedness of the network's communication topology. These tradeoffs are used to develop guidelines for calibrating privacy in terms of control theoretic quantities, such as steady-state error, without requiring in-depth knowledge of differential privacy. Additional guidelines are also developed for treating privacy levels and network topologies as design parameters to tune the network's performance. Simulation results illustrate these tradeoffs and show that strict privacy is inherently compatible with strong system performance.
A Study on Sampling-Based Parameter Estimation Techniques in Big Data Analytics Environment

In a big data environment, there are lots of large datasets are arising from the data processing complexity regarding the user’s query. We cannot imagine how many datasets are generating within a second. Those datasets are coming from different sources like social media, health sectors, weather department, insurance companies, share market, and more, in which the social media such as facebook, WhatsApp, Instagram are producing more and more data that is called big data. Basically big data have three very important pillars which are known as volume, variety, and velocity. It is also called as big data parameters. When the availability of data in huge volume then it is not possible to process all huge datasets, so in this case, we have opportunities to apply the sampling techniques and estimate the big data parameters. The sampling techniques are more powerful in capered to traditional techniques because the small dataset (sample) can select from entire data or population and then process it. Due to a small dataset, we can process easily and then can reduce process time and cost. In this paper, we have to study the different types of sampling techniques suitable for big data parameters. This paper has discussed sampling-based parameter estimation techniques in the big data environment. Furthermore, we have suggested one big data analytics model based on stratified sampling. The main objective of this paper is to find out the reliable sampling techniques for big data parameter estimation.
Meme-Based Computational Optimization Framework

From a computing perspective, a meme denotes information that represents knowledge, patterns, rules, or strategies used to solve complex problems. When applied on a problem, memes help a solver to arrive at good quality solutions more efficiently, guiding the search process according to certain procedures or rules, instead of randomly searching through the solution space. Depending on the complexity of the problems, evaluating the suitability of memes and selecting a set of effective memes for different problems, however, are not straightforward tasks. A meme that works well for some problems may not be effective for other problems. Besides, different memes might have different degrees of importance in solving a problem. The level of importance of each meme might also change at different stages of the search. In this paper, we discuss how multiple memes can be generated and applied to solve computational optimization problems. A case study in combinatorial optimization is also presented and discussed.