Reviewerly/exHarmony huggingface dataset:
User Interface Guidelines for Dyslexic Game-Based Learning on Selected Usability Test Method

Multimedia technology is constantly growing and benefitted every facet of our lives and has its impact felt to modern education.Despite many products that utilize multimedia technology for education such as e-Learning and learning courseware, there is a lack of development in the designs of educational products for students with Dyslexia.User Centred Design guidelines on developing software for Dyslexic user is still under investigation and most published guidelines are focusing more on web accessibility and not specific for game-based learning.This paper presents a set of practical interface design guidelines to improve learning process of a game-based learning for the dyslexic students.The guidelines are developed based on survey conducted and proposed elements in Human Computer Interaction (HCI) that is essential in improving learning process.Within the paper, we showed that using of the proposed guidelines can improved the learning process for Dyslexia students.
Deep Learning in Computer Vision: Methods, Interpretation, Causation and Fairness

Deep learning models have succeeded at a variety of human intelligence tasks and are already being used at commercial scale. These models largely rely on the standard gradient descent optimization of parameters W, which maps an input X to an output y ̂=f(X;W). The optimization procedure minimizes the loss (difference) between the model output y ̂ and actual output y. As an example, in the cancer detection setting, X is an MRI image, while y is the presence or absence of cancer. Three key ingredients hint at the reason behind deep learning’s power. (1) Deep architectures better adapt to breaking down complex functions into a composition of simpler abstract parts. (2) Standard gradient descent methods that attain local minima on a nonconvex Loss(y,y ̂) function that are close enough to the global minima. (3) Architectures suited for execution on parallel computing hardware (e.g., GPUs), thus making the optimization viable over hundreds of millions of observations (X,y). Computer vision tasks, where input X is a high-dimensional image or video, are particularly suited to deep learning application. Recent advances in deep architectures, i.e., inception modules, attention networks, adversarial networks and DeepRL, have opened up completely new applications that were previously unexplored. However, the breakneck progress to replace human tasks with deep learning comes with caveats. These deep models tend to evade interpretation, lack causal relationships between input X and output y and may inadvertently mimic not just human actions but human biases and stereotypes. In this tutorial, we provide an intuitive explanation of deep learning methods in computer vision as well as limitations in practice.
Data Subjects’ Control Over Their Personal Data

Referring to one of the objectives of the data protection reform, this article is dedicated to the analysis of the ways data subjects execute control over their personal data.The author identifies the personal data processing principles and examines tools provided by the General Data Protection Regulation that mandate this control.Following the overview of the requirements of the Regulation and their implementation by the EU market participants the author describes the features of this control.
Thai Catalogers’ Use and Perception of Cataloging Standards

Library-based metadata and knowledge organization standards, such as Resource Description and Access (RDA); Dewey Decimal Classification system (DDC); and Library of Congress Subject Headings (LCSH), are called “international” or “universal” as they are increasingly adopted by countries around the world. Yet, library knowledge organizations systems are created within given contexts representing the limited needs of specific communities in certain time periods. This article presents results from a cataloging study of Thai libraries. A focus group and interviews were used to gather data on Thai catalogers’ use and perception of cataloging standards in Thai libraries and how well they meet their needs.
Testing the Robustness of Manifold Learning on Examples of Thinned-Out Data

Manifold learning can only be successful if enough data is available. If the data is too sparse, the geometrical and topological structure of the manifold extracted from the data cannot be recognised and the manifold collapses. In this paper we used data from a simulated two-dimensional double pendulum and tested how well several manifold learning methods could extract the expected manifold, a two-dimensional torus. The experiments were repeated while the data was downsampled in several ways to test the robustness of the different manifold learning methods. We also developed a neural network-based deep autoencoder for manifold learning and demonstrated that it performed in most of our test cases similarly or better than traditional methods such as principal component analysis and isomap.
One-to-Three Silicon Photonic Grid Power Splitter for Optical Mesh Solver

Here we show a novel Silicon Photonic 1-to-3 power splitter design for grid topology, which can be applied to optical mesh network and emulate real-world problems such as Laplace’s equations and Poisson equations.
Investigations to digitizingof the gyro oscillation swing by a line camera

The purpose of this work is to develop a technology for an automatic measurement process for determining the azimuth by the "Gyromax AK-2M" gyroscope.The accuracy of determining the principal values should be higher than by manual procedure.A method for digitizing the gyro oscillations using a camera with a linear sensor and programming code is proposed in this work.The working possibility of the line camera from Coptonix™ company was investigated, as well as the possibility of its connection to a single board computer Raspberry Pi 3B for data transmission and processing.The possibility of using the Python 3.0 programming language for these tasks was tested.Methodology.To implement this project, an integrated approach was used, using devices such as a camera with a linear sensor, a single board computer and facility, that simulates gyroscope oscillations.This research includes investigations in digitizing of data, computing the azimuth values and automatizing these processes.For automatized data computation were used the same two methods as in the regular manual measurements -Turning point method (TPM) and Pass-Through method (PTM).Results.The result of this work is an automated oscillation measurement system, that can be applied in gyroscopes.The system includes developed software, which connects the user to the linear camera and processing computer, records the necessary data, transfers them to the client-computer and calculates the necessary values.For the convenience of using the program by other users, the program is provided with a graphical user interface.The result of the program is a file with the extension XML, which contains data about measurements.Scientific novelty and practical significance.The new method of digitizing the gyroscope oscillations is proposed in this work.Application of a line camera and a single board computer for the digitization of measurements opens a lot of possibilities for improving the automation processes of the geodetic devices, which could increase the accuracy of measurement and decrease its duration.By developing this method of digitization, it is possible to start production of an improved version of gyro add-on GYROMAX AK-2M.
Healthcare Monitoring System using IoT

Medication has become a very necessary factor for the survival of human species and many scientists are continuously working on improving our medical advancements, as a tribute to those scientists, our team is working on a device which will monitor heartbeat, temperature, blood pressure, glucose levels and invasive blood group identification using heartbeat sensor, temperature sensor, node mcu and Mems.As we are using invasive blood group identification there is no need to puncture human body to identify blood group. It sends notification to the nearest doctor and family members in case of any emergency or abnormal situations. It stores all the data in cloud which helps to access the data from anywhere by family members or doctors to analyse the situation and past medical history. The add on advantage of this application is we can store past medical prescriptions and all other health details of medicines being used by patients which might be needed during his visit to other hospitals or in emergency conditions.
Multiphoton quantum metrology without pre-and post-selected measurements

We demonstrate the first protocol for quantum-enhanced phase estimation without pre- and post-selected measurements. Our experiment, with an overall efficiency of 82%, utilizes two-mode squeezed vacuum states and photon-number-resolving detection to surpass the standard quantum limit.
Application of Integrated Geophysical Technologies to the Exploration of Polymetal Deposits: Case study in Fufang, Jiangxi, China

Prior research has confirmed that the Fufang prospecting area exhibits good mineral anomalies.The geochemical anomaly that pertained to copper content was delineated within a wide range; hence, the deployment of boreholes and trenches was hindered for further prospecting work.To shrink this anomaly range and identify favourable areas for mineralization, a combination of geophysical methods based on electrical and magnetic theories was proposed.First, magnetic and induced polarization (IP) mappings were utilized to characterize the distribution of anomalies horizontally.Then, the major structures were identified using IP and audio magnetotelluric sounding measurements.The integrated geophysical anomalies with good spatial consistency were also delineated.Results demonstrate that the main strike of the regional fault is in the direction of NE 50°, and some parallel secondary faults are also inferred.The dykes in this area are well developed in the strata due to rock mass intrusion.Several geophysical anomalies are highly superposed.This condition indicates good prospecting of copper and polymetals.The found anomalies delineate a new prospecting area that is 62% smaller than the previous one.This study provides a good prospect in the designated anomaly area.
Implementing Innovative Lean Educational Method to Enhance English Language Achievement

Purpose: To our knowledge, the present study is the first experimental example of the application of innovative Lean Educational Method (LEM) in middle school English classes in Turkey. How to learn and teach foreign languages has become the preoccupation of teachers, researchers, educational authorities, parents, and students. All of the stakeholders in the education processes want to satisfy the learning needs of the students ideally. As a result of the relevant efforts, many teaching methods emerged in the field of English Language Teaching (ELT). In this regard, this study primarily aims to introduce LEM and present its efficiency through an experiment.  Methods: To question the effects of LEM in English lessons, this experimental study was conducted. A control group (40 students), and an experimental group (40 students) were chosen through random cluster sampling in a public middle school. The experimentation process continued for 19 weeks. Statistical analyses of the collected data were conducted using descriptive statistics and the variance analyses carried out using one-way ANOVA. Findings : The findings showed that there was a statistically significant difference between the experimental and control groups (control group’s pre-test mean=8.9, sd=3.801 / post-test mean=8.775, sd=4.293; experimental group’s pre-test mean=8.45, sd=4.437 / post-test mean=13.375, sd=3.998). Variance analyses of the pre-test and the post-test showed a statistically significant difference in the dependent variable (F=27.197, p<.05). Implications for Research and Practice: The results showed that the implementation of LEM in middle school contexts is quite possible. LEM has the potential to bring many innovations to ELT and it also increases the foreign language achievement in nation-wide public exams. LEM can be applied in other educational contexts such as; primary schools, high schools and universities.
PERAN INFOGRAFIS SEBAGAI PENUNJANG DALAM PROSES PEMBELAJARAN SISWA

Easy information access supports students to find resources in learning. However, excess information caused students to face difficulty processing information well. Infographics becomes a solution to presenting the information in visual format. Infographics is expected to help students to process the information, especially for academic purposes. It is difficult to create infographics manually. This training aimed to teach students in high school to create infographics with Piktochart. Piktochart is one of the online tools to help people create infographics. The training was divided into three sessions, namely the preparation session, material introduction session, and creative session. In the last session, students created infographics from one of their subjects in school. Afterwards, the students presented their infographics to other students and trainers in class.
Running Perl 6

Perl 6 is a programming language, and as such it is a part of a development ecosystem that includes a series of applications. Some of them will be used throughout this book, so here are a few things that you might want to install before you get to Perl 6 itself.
Modeling Interactive Systems at the Business Level: Inter-Action Diagram

This paper presents the Inter-Action diagram as an element to capture useful information in the design of interactive systems. The Inter-Action diagram allows designers to enrich the modeling of interactive systems at the business abstraction level. This paper shows how Inter-Action Modeling has been enriched since it emerged as a proposal to provide a high-level model, which can be subdivided and, which represents the evolution, according to time, of the processes of the system. The components that support this Inter-Action Modeling and its importance for the development of interactive systems are also exposed.
Managing Access to Library E-Resources When Institutional IP Ranges Change: A Strategic and Practical Approach

The article uncovers the problems encountered by libraries when Internet Protocol (IP) ranges change at institutions with or without notice to library and research centers. This article provides practical tips for preparation and overcoming challenges that often occur when IP ranges change at an institution. Possible solutions, such as a recovery plan, which can be used to manage and communicate the whole process strategically to stakeholders, are also discussed. This research article covers two typical scenarios where entire IP ranges are replaced in an institution and a second scenario where additional IPs get added to an existing range at institutions with or without notice to libraries and restoring the access for e-resources in both scenarios at a fast pace. Based on the lessons learned and knowledge sharing with the e-resource librarian community, the article recommends best practices and strategies to keep the transition period the least disruptive to all library stakeholders.
Algorithms for Neural Networks

In current years, net and computer systems are used through many of us everywhere the planet at intervals numerous fields. So as to come back up expeditiously or up to persimmon problems, nearly firms rest their functions and repair gadgets over net. On the opposite hand, network intrusion or data safety issues square measure ramifications on the utilization of net. The increasing network intrusions have added firms and businesses at a ton’s larger risk on loss. The first operate of Intrusion Detection System is to shield the resources beside threats. It analyses and predicts the behaviours regarding users, and subsequently it behaviours are going to be regarded an attack or a standard behaviour. There square measure many techniques that exist nowadays to produce further protection to the network, however these techniques square measure static.
Computable Proximity of $\ell_1$-Discs on the Digital Planet

This paper investigates problems in the characterization of the proximity of digital discs. Based on the $l_1$-metric structure for the 2D digital plane and using a Jaccard-like metric, we determine numerical characters for intersecting digital discs.
Hash Hardware Generator Based on Mutual Perturbed Logistic Map

In this paper, a hash code generator based on logistic map mutual perturbation is implemented on the Field Programmable Gate Array (FPGA) device. The performance of chaotic system under a finite precision is improved by the perturbation method, and a novel hash code generation scheme is constructed by using the improved chaotic system. Due to the good randomness of the perturbation scheme, the generated hash codes have a uniform distribution when implemented on FPGA. The proposed hash generator is sensitive to the input text message, has confusion/diffusion characteristics and excellent anti-collision capabilities. Experimental results show that the proposed hash generator has a lower resource occupation than existing hash hardware systems on FPGAs. It can be used for real applications, especially for these with low resource usage requirements.
Two-Stage Method for Kidney and Tumor Segmentation Based On Cascade Res-VNet

In this work, We proposed a two-stage method for segmentation of kidneys and kidney tumors in CT images based on cascade Res-VNet.In the first stage, we consider the kidney and tumor as a whole region and use a cascade Res-VNet to do the segmentation.In the second stage, we firstly extract patches of ROIs based on the results of the first stage and use some tricks to improve precision.Then, we use another cascade Res-VNet to segment the tumor.Ouput from each stage are combined together as the final results.
A Comparison of Relational and Graph Databases for CRM Systems

In an age of increasing usage of heavily interconnected platforms, graph databases have increased in popularity due to their ease of modelling these systems. This thesis will evaluate if the graph database Neo4j can be used to model Lime's CRM System efficiently by comparing the performance of Neo4j and MS SQL on queries similar to those existing in Lime CRM. To benchmark the databases, they were created with the core entities of the Lime CRM system. The databases are created with the same structure and schema as in Lime CRM. Thereafter, the databases were populated with randomly generated data. These databases were then queried a large amount of times with random values in every query to prevent caching. Our results show that MS SQL was 4-10 times faster for insertion queries. Furthermore, MS SQL was also 2-5 times more efficient at handling queries that return many rows/nodes of data. (Less)
Need Analysis of Speaking Skill by Using Simulation for Students of Primary School Teacher Education

There are several types of activities carried out to improve student speaking skills in English, one of which is simulation. Simulations of speaking skills in learning English must also be tailored to the needs of PGSD students. This study aims to find out and describe the student needs of Primary School Teacher Education in English speaking skills using simulation. Data obtained from questionnaires and interviews. The results of the analysis of learning needs obtained are that students need speaking skills fluently and communicatively in order to prepare them to meet their professional demands as an elementary school teacher later. Needs analysis data designed to reveal a) The current process of speaking English skills in the Muhammadiyah Elementary School Teacher Education Study Program, b) Student needs and difficulties in learning activities using simulation, c) Student needs and desires in speaking skills learning using simulation. Needs analysis reveals that (1) Learning activity activities needed by students are simulations (2) Student's difficulties in speaking skills in learning activities using the most dominant simulation is the lack of confidence and grammar, (3) Desired material in learning activities using simulation in the form of materials relating to elementary school material. The results of this study are expected to be a reference for preparing syllabi and developing teaching material.
User Evaluation of a Multi-dimensional Statistical Dialogue System

We present the first complete spoken dialogue system driven by a multi-dimensional statistical dialogue manager.This framework has been shown to substantially reduce data needs by leveraging domain-independent dimensions, such as social obligations or feedback, which (as we show) can be transferred between domains.In this paper, we conduct a user study and show that the performance of a multi-dimensional system, which can be adapted from a source domain, is equivalent to that of a one-dimensional baseline, which can only be trained from scratch.
Optimal ELM-RBF model and SERS Analysis of Saliva for Classification of NS1

Extreme Learning Machine (ELM) with Radial Basis Function (RBF) Kernel has demonstrated strong capability in pattern recognition and classification problems. NS1 is a biomarker for flavivirus related diseases, where current detection methods are serum based and hence invasive. Our previous work has captured NS1 molecular fingerprint in saliva using Surface Enhanced Raman Spectroscopy (SERS) that could amount to non-invasive detection method. SERS is an improved Raman spectroscopic technique, which can amplify spectral intensity by 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> to l0 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7</sup> times, to yield usable spectra of low concentration NS1 in saliva. The spectra produced contain 1801 features for each of the 284 samples collected. Principal Component Analysis (PCA) transforms a high dimensional data to a lower dimension principal components (PCs), at no sacrifice of important information of the original data. Both termination criteria of PCA and kernel parameters of ELM have effect on performance of the classifier models. This paper aims to unravel an optimal ELM-RBF classifier model for classification of NS1 salivary SERS spectra. Performance of a total of 864 classifier models are examined and compared in terms of [accuracy, kappa, precision, sensitivity and specificity]. Results show that CPV- and EOC-ELM-RBF classifier models are on par and outperform the Scree-ELM-RBF classifier models.