Reviewerly/exHarmony huggingface dataset:
BSc Applied Physics: A physics degree for students with non-standard qualifications

&amp;lt;p&amp;gt;In the UK, the primary route to a physics degree is through studying for advanced level qualifications (known as A-levels) in both physics and mathematics. 38,958 students were entered for A-level examinations in physics in 2019, with the majority of these candidates also entered for A-level mathematics.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In recent years the UK has seen a growth of vocational, technical and wide entry qualifications. The vocational and technical qualifications are targeted at teenagers, and the latter targeting mature students returning to education later in life. These qualifications all cover a wider breadth of material, but in less depth than traditional A-levels. In order to ensure that these students can succeed at a physics degree, Nottingham Trent University developed a new course, BSc Applied Physics.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;BSc Applied Physics is designed to follow on directly from vocational, technical and wide entry courses, including the BTEC Extended Diploma in Applied Science and Diplomas in Access to Higher Education. In the first year of BSc Applied Physics students have extra workshops to support their studies, and extra sessions on mathematics for physics. The aim is that, at the end of the first year, these students should have the same mathematical ability as year 1 students on our main BSc Physics course. The BSc Applied Physics students then have a choice. They can either continue with BSc Applied Physics, which focusses on the applications of physics, or transfer to a more traditional BSc Physics programme.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The purpose of this poster is to showcase to teachers how this type of non-standard degree programme can benefit students studying for non-traditional qualifications.&amp;lt;/p&amp;gt;
An Intelligent Guiding System for Trekkers using WUSN

To design and develop an automated surveillance system to detect and intimate the presence of animals, monitoring the health parameters of the trekkers and to detect fire in the dense forest. Using sensors and wireless technology that communicate to the base station using wireless communication. In this project the image processing technique is explored for the detection of animals so that any change in pattern then the trekkers and base station are alerted. For the communication process, a wireless underground sensor network is employed which has a lot of interlinked nodes. This is because internet usage is not effective in the dense and reserved forest area. Node to node communication is performed for efficient information sharing with the base station and the communication process for trekkers is carried on with wireless sensor networks thus provides warning information to the trekkers. Animal detection based applications have a very important role in many real-life situations and also detection of forest fire in dense forest is hard and fast-spreading. Therefore there must be automation and faster means of communication.
Web-based E-diagnostic for Digestive System Disorders in Humans using the Demster Shafer Method

Digestive system disorders are dangerous diseases. Lack ofawareness of public health is still low, life habits, behavior and mindset that want to live practically, a means of delivering information about diseases that are still lacking, and the lack of medical personnel is a problem, therefore an expert system application is needed to diagnose disease on the web-based digestive system. By providing certainty in the form of a percentage, then using the calculation through symptoms chosen by the user of each symptom has a density value, the density value is obtained from the results of interviews with doctors. Web-based E-Diagnostics for digestive system disorders uses the Dempster Shafer method which is expected to help users by providing information on disease diagnosis and solutions that can be done to help cure it, the Dempster Shafer Method has the ability to provide a high level of accuracy or certainty, which method this has characteristics that are in accordance with the way an expert thinks. This web-based expert system application will display symptoms that can be selected by the user to get the final results in the form of rapid disease diagnoses and suggestions for prevention in order to find out information in the form of diagnoses of diseases of the digestive system. Based on the calculation of accuracy that has been done in this study, it can be seen that the Dempster Shafer Method is the method that has the highest value with 85% confidence compared to theCertainty Factor Method with a value of 60%.
Datasets

The use of datasets can be an important aid in research, for example, in the construction of an email parser, malware analysis, improve specific purpose algorithms or for the testing of tools. For datasets to be useful, they must possess three features: (1) quality to ensure that results are accurate and generalizable, (2) quantity to ensure that there are sufficient data to train and validate the tools and (3) availability for the research to be conducted and independently reproduced to ensure scientific validity. Further, funding agencies increasingly require that grantees make the results of their research available to the public. The current deficiencies in most databases that fail to meet these criteria present major weaknesses in assuring the reliability of research and testing and to the continued development in digital forensics. The majority of test databases are deficient as (1) many researchers produced their own datasets, (2) datasets are not released after the work has been completed and (3) there is a lack of labelled standardised datasets that can be used in research. These weaknesses lead to the disadvantages of low reproducibility, comparability and peer-validated research. Over half the datasets used to conduct published research were experiment generated, where researchers created specific scenarios to conduct their experiments due to the lack of available real-world datasets and datasets that have been created specifically to conduct experiments on new technology.
International science and technology conference for youth “Advanced Materials for Engineering and Medicine” (AMEM-2019)

30 September – 5 October 2019, Tomsk, Russia The International science and technology conference for youth “Advanced Materials for Engineering and Medicine” (AMEM-2019) was held at Tomsk Polytechnic University (TPU) in 30 September – 5 October 2019. The scientific program consisted of plenary sessions and parallel sessions and included the following topics: • Problems of materials reliability • Functional materials • Surface and coating modification • Advanced materials for medicine We want to thank all members of the Organizing Committee, TPU and everyone who contributed to the organization of this event, for their contribution towards the conference and for their contributions to this proceeding. The Organizing Committee of AMEM-2019
A SecureVideo Watermarking using Encryptionwith Lossless Compression

The fundamental goal of building up a video-watermarking system is to fulfill both indistinctness and strength prerequisites. The video watermarking gives the firstdimension of security for the secrete communication. The videos have to be encrypted before compression to give high level security. Video compression is the technique of lessening the record measure of a video without compromising with the video quality at acceptable level. Now–a-days, video compression is one among the demanding and vast researches because high Quality video requires larger bandwidth. Raw videos need larger memory space. The altered SPIHT pressure method goes with the Huffman coding calculation in this proposition the Huffman coding is connected with the adjusted SPIHT calculation to improve the pressure proportion. Video pressure tends to the issue of decreasing the measure of information required to speak to a video. Huffman encoding and translating is lossless pressure method to execute and it lessens the unpredictability of memory.
Embedding with Pca Based Svd Framelet Transform with Visual Cryptography In Video

The goal of watermarking or steganography is not to restrict access to the original image, to ensure that embedded data remain recoverable. Digital watermarking is a technique providing embedded secure information in images, digital watermarking is the process of inserting data into an image in a way that it can be used to make an assertion about the image. But the proposed system studies a comprehensive approach of embedding secret information inside the video. A hybrid video steganographic scheme based on Framelet transform (FT) with Principal Component Analysis (PCA) is introduced. The main purpose of using PCA is to reduce correlation among wavelet coefficients from wavelet decomposition of each video frame. Using this decomposition, the secret message can be dispersed into the uncorrelated coefficients. Framelet transform helps to decompose video file into several frames. The secret message is embedded inside the principal components of low frequency wavelet coefficients. Achieving high bit rate data embedding is the main task. The proposed system is robust against numerous attacks like geometric attack, filtering, contrast adjustment. After embedding the secret information , (2,2_VSSS) as Visual cryptographic encryption is implemented to maintain the secrecy of this information against hackers.The main aim of this study is to obtain impercibility which is the human eye may not be able to detect differences between the original video and reconstructed image. Even after embedding, the quality of the stego image is good, which is proved by achieving better a PSNR value, and the stego image does not give much variation irrespective of different imaging conditions in the proposed VDWT mechanism. The proposed method achieves high PSNR than the existing methods, and nominal computational time is achieved for retrieving the secret information.
Calibration and Validation of the Angstrom-Prescott Model in Solar Radiation Estimation using Optimization Algorithms

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Earth and Space Science. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v3]Calibration and Validation of the Angstrom-Prescott Model in Solar Radiation Estimation using Optimization AlgorithmsAuthorsSeyedeh NafisehBanihashemi DehkordiBahramBakhtiariKouroshQaderiiDMohammad MehdiAhmadiSee all authors Seyedeh Nafiseh Banihashemi DehkordiShahid Bahonar University of Kermanview email addressThe email was not providedcopy email addressBahram BakhtiariShahid Bahonar University of Kermanview email addressThe email was not providedcopy email addressKourosh QaderiiDCorresponding Author• Submitting AuthorShahid Bahonar University of KermaniDhttps://orcid.org/0000-0001-8976-7272view email addressThe email was not providedcopy email addressMohammad Mehdi AhmadiShahid Bahonar University of Kermanview email addressThe email was not providedcopy email address
Observed Score Reliability Indices in Diagnostic Classification Models

Quantifying the reliability of latent variable estimates in diagnostic classification models has been a difficult topic, complicated by the classification-based nature of these models. In this study, we derive observed score reliability indices based on diagnostic classification models as an extension of classical test theory-based reliability. Additionally, we derive conditional observed sum- and sub-score distributions. In this manner, various conditional expectations and conditional standard error of measurement estimates can be calculated for both sum- and sub-scores of a test. The proposed methods provide a variety of expectations and standard errors for attribute estimates, which we demonstrate with an analysis of an empirical test. Moreover, a simulation study revealed the proposed sub-score based reliability index was correlated to a previously developed attribute mastery reliability index.
Cybercrime prevents former research students from getting a job

A personal experience and advice are described in this piece as a former student and former victim of white collar organised whom it took over 5 years to find employment again after being victimised.
SIGNIFICANT DIRECTIONS IN EDUCATIONAL AND PROFESSIONAL ACTIVITIES OF PSYCHOLOGIST STUDENTS

The article deals with the question of life-meaning and value orientations, personality orientation and worldview of psychology students. Revealed significant indicators and analyzed the features of these integral personality characteristics. The results of the correlation analysis made it possible to identify and describe the relationship between life-meaning and value orientations with the characteristics of life and professional self-determination.
Automation Nation

IPPR Progressive ReviewVolume 26, Issue 4 p. 315-320 Article Automation Nation Asheem Singh, Search for more papers by this author Asheem Singh, Search for more papers by this author First published: 16 February 2020 https://doi.org/10.1111/newe.12177Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Volume26, Issue4Spring 2020Pages 315-320 RelatedInformation
Trees

Balancing a binary tree is the infamous interview problem that has all that folklore and debate associated with it. To tell you the truth, like the other 99% of programmers, I never had to perform this task for some work-related project. And not even due to the existence of ready-made libraries, but because self-balancing binary trees are, actually, pretty rarely used. But trees, in general, are ubiquitous even if you may not recognize their presence. The source code we operate with, at some stage of its life, is represented as a tree (a popular term here is Abstract Syntax Tree or AST, but the abstract variant is not the only one the compilers process). The directory structure of the filesystem is the tree. The object-oriented class hierarchy is likewise. And so on. So, returning to interview questions, trees indeed are a good area as they allow to cover a number of basic points: linked data structures, recursion, and complexity. But there’s a much better task, which I have encountered a lot in practice and also used quite successfully in the interview process: breadth-first tree traversal. We’ll talk about it a bit later.
Component Architecture

In this chapter, you will learn how to design components and make them work together in a web application. We are going to connect our web application to an application programming interface (API) and define a dataflow for our components.
Automated Digital Image Clustering Algorithm Based on Colour Distance and IDBSCAN

Data clustering is inevitable for crucial data analytic based applications. Though data clustering algorithms are capacious in the literature, there is always a room for efficient data clustering algorithms. This is due to the uncontrollable growth of data and its utilization. The data clustering may consider any of the data formats such as text, images, audio, video and so on. Due to the increasing utilization trend of digital images, this work intends t clustering algorithm for digital images, which is based colour distance and Improvised DBSCAN (IDBSCAN) algorithm. The proposed IDBSCAN completely weeds out the annoying process of setting the initial parameters such as 𝜺 and them automatically. The performance of the proposed work is analysed in terms of clustering accuracy, precision, recall, F measure and time consumption rates. The proposed work outperforms the existing approaches with reasonable time consumption.
Case Studies in Amalgamation of Deep Learning and Big Data

Deep learning is now more popular research domain in machine learning and pattern recognition in the world. It is widely success in the far-reaching area of applications such as Speech recognition, Computer vision, Natural language processing and Reinforcement learning. With the absolute amount of data accessible nowadays, big data brings chances and transformative possible for several sectors, on the other hand, it also performs on the unpredicted defies to connecting data and information. The size of the data is getting larger, and deep learning is imminent to play a vital role in big data predictive analytics solutions. In this paper, we make available a brief outline of deep learning and focus recent research efforts and the challenges in the fields of science, medical and water resource system.
Virtual Reality for Communication Neuroscience

Virtual Reality (VR) and human interaction with virtual worlds can greatly enhance communication neuroscience research. VR provides opportunities for novel approaches to empirical investigation. This chapter will discuss why VR and the varieties of virtual experience is of interest to communication neuroscientists. This leads to a discussion of multiple issues related to experimental implementation and cognition, and ways VR is useful to communication neuroscience. This includes multiple cognitive effects that provide opportunities for advancing research.
Understanding emotional AI_A research proposal

My PowerPoint presentation for a Ph.D. thesis on emotional AI.
Storage

This chapter dives into how the Android OS file system operates as well as how the internal storage for Android applications is structured and can be used.
How Blockchain Technology changes Government. A systematic analysis of applications

It is widely argued that Blockchain Technology (BCT) is one of the most promising trends nowadays. The most prominent characteristic of this technology is the improved sense of trust to the shared information provided by BCT applications as well as the ubiquitous access to the data ledger. At the same time governments pursue amplified trust from their citizens increasing transparency through shared information and open data. Since BCT supports this strategic goal of governments worldwide, numerous governments try to capitalize on the advances of this technology through testing the results of pilot applications in different vertical governmental sectors. Even though there are several implementations in the Government sector, there is no comprehensive study towards the analysis of the major characteristics of these developments. This paper moves towards the fulfillment of this gap by conducting a thorough analysis of e-Government pilot applications of BCT at a European level providing information to policymakers and practitioners about the grey areas of this technology.
An Exhaustive Requirement Analysis Approach to Estimate Risk Using Requirement Defect and Execution Flow Dependency for Software Development

Requirement defects are one of the major sources of failure in any software development process as they prevent smooth operation and is taxing both in terms of tracking and validation. The objective of this article is to make requirement analysis phase exhaustive by estimating risk at requirement level using requirement defect information and execution flow dependency as early as possible to inhibit them from being incorporated in design and implementation. The proposed approach works as a two-fold process which computes risk involved with each requirement twice. The whole process is divided into a three-layered framework to finalize requirements with clear vision and scope of a project. The entire process has been supported by a software case study. The results of the proposed work are promising and will help software engineers in ensuring that all business requirements are captured correctly with clear vision and scope. It will also help in decreasing the chances of failure, risk, and conflicts between stakeholder and developer and other challenges involved to develop the project.
Security Operations

In this chapter, you will learn tips about incidents, digital crime, incident management, investigations, digital forensics, eDiscovery, disaster recovery, business continuity planning and backup, and recovery strategies.
What Should I Do?

I find myself asking, "What should I do?" in many situations such as when I want to go out to eat; I want to decide about my vacation; decide on spending some free time on the weekend; and numerous other decisions. All these decisions are really personalized contextual decisions that may be addressed by a contextual recommendation engine that knows me. For knowing me well, the engine should prepare my model based on all events in my life. By retrieving and mining events of various types computed using different multimodal data streams, such a personal model may be prepared and then used to help in making decisions ranging from trivial to critical. We discuss important challenges in organizing life events that may be used for building personal models and for accessing characteristics of such events as may be needed in various applications. We will demonstrate our ideas using some applications related to lifestyle and health.
Web Apps

In this chapter we will learn how to set up user-friendly mobile apps for Lightning Network users. Undoubtedly, Lightning Network is a powerful platform, but like any other technology, it can only be of use to others if applications exist, that are user-friendly, intuitive, and abstracting away all the minute details only specialists should know.
THE EFFECT OF COMMUNITY LANGUAGE LEARNING AND EMOTIONAL INTELLIGENCE ON STUDENTS’ SPEAKING SKILL

Abstract: The research objective is to find out the effect of the Community Language Learning method and the Emotional Intelligence on students’ speaking skill at the eighth grade of SMP Darussalam Ciputat. This research used a quasi-experimental with factorial design which involved 60 students as the sample, (as the experimental and the control group), who were chosen by using purposive sampling technique. The research data were collected through test of speaking skill, and the questionnaire to test emotional intelligence. The data were analyzed by factorial ANOVA test. This study’s findings revealed that: (1) Community Language Learning (CLL) method is more effective in enhancing students’ English speaking skill than the conventional method. (2) The students who have a high level of emotional intelligence are better in speaking skill than those who have a low level of emotional intelligence. (3) There is no interactional effect between teaching method and emotional intelligence (EI) on the students’ speaking skill.Abstrak: Tujuan penelitian ini untuk mengetahui pengaruh metode Pembelajaran Bahasa Komunitas dan Kecerdasan Emosional terhadap Keterampilan Berbicara Siswa Kelas VIII SMP Darussalam Ciputat. Penelitian ini menggunakan eksperimen semu dengan desain faktorial yang melibatkan 60 siswa sebagai sampel (kelompok eksperimen kontrol), dengan teknik purposive sampling. Instrumen terdiri dari tes keterampilan berbicara percakapan, dan angket kecerdasan emosional. Analisis data dilakukan dengan uji ANOVA faktorial. Hasil penelitian menunjukkan bahwa: (1) Metode Community Language Learning (CLL) lebih efektif dalam meningkatkan keterampilan berbicara bahasa Inggris siswa daripada metode konvensional. (2) Siswa yang memiliki kecerdasan emosional tingkat tinggi memiliki keterampilan berbicara yang lebih baik daripada siswa yang memiliki kecerdasan emosional tingkat rendah. (3) Tidak ada pengaruh interaksional antara metode pengajaran dan kecerdasan emosional (EI) terhadap keterampilan berbicara siswa. Artinya, siswa tingkat IE tinggi pada metode CLL maupun konvensional lebih baik daripada tingkat IE rendah.