Reviewerly/exHarmony huggingface dataset:
Pre-Travel Training And Real-Time Guidance System For People With Disabilities In Indoor Environments

Public transportation provides people with access to education, employment, health and community activities. However, navigating inside public hubs for people with disabilities such as cognitive or mobility impairments can be very challenging and dangerous. With the rapid development of digital technology such as Smartphones and sensors, there are unprecedented opportunities to assist people with disabilities to conquer these challenges. In this research, we aim to create a two-step indoor navigation solution for users with different mobility and orientation abilities. In the first step, we developed a virtual reality-based pre-travel training module that enables users to familiarize themselves with the virtual environment which represents the physical environment. After users feel confident and familiar enough with the environment, they proceed to the second step in which they visit the physical environment and use our real-time navigation assistance module. The pre-travel training module is developed using a Unity-based 3D game and includes a virtual indoor environment that represents the physical environment. The game provides a navigation function that highlights the path between the user location and the chosen destination. Considering the unique needs of cognitive impaired users, we designed action training modules in the game environment which train the user to use the ticket machine, fare gate and call boxes. Such training modules help cognitive impaired users familiarize themselves with the environment as well as gain confidence to experience the physical environment. When the users are ready to visit the physical environment, they use our real-time navigation assistance module which includes the same 3D virtual environment developed for the pre-travel training module. This approach is particularly important for people with cognitive impairment since they cannot organize navigation cues effectively. Using the Bluetooth Low Energy (BLE) infrastructure in the environment, our localization algorithm can track the user location in real-time. Subsequently, the user’s location will be integrated into the game environment so that the navigation path between the user’s current location and the selected destination can be generated and visualized by the user on the fly.
Integración de un planificador de trayectorias parametrizado en la arquitectura robótica ROS

espanolEn este trabajo se presenta la integracion de un nuevo planificador reactivo de movimiento dentro de la arquitectura robotica ROS. Este planificador, desarrollado originalmente como parte de la libreria MRPT y basado en el Espacio de Trayectorias Parametrizado (TP-Space), amplia las posibilidades de navegacion de las plataformas roboticas actuales mediante la generacion de trayectorias tanto circulares como no-circulares, asi como la posibilidad de contemplar la geometria 3D del robot (no restringiendose a formas prismaticas). La integracion se ha realizado garantizando la compatibilidad con el stack de navegacion autonoma mas popular de la plataforma ROS, adaptando el funcionamiento de dicho reactivo a la interfaz de comunicacion est´andar de ROS, siendo este compatible con los planificadores globales existentes. Para validar este trabajo, se han realizado multiples pruebas de navegacon en entornos de interior (tanto simulados como reales), con presencia de obstaculos y donde la plataforma robotica es equipada con diversas camaras RGB-D y un escaner laser. EnglishThis paper presents a new reactive movement planner integration within ROS robotic architecture. Said planner, originally developed as a part of MRPT library and based on Trajectory Parameter Space (TP-Space), broadens current robotic platforms’ navigation possibilities through both circular and non-circular trajectories generation, as well as an option to contemplate the robot’s 3D geometry (not being restricted to prismatic forms alone). This integration has been carried out guaranteeing compatibility with the most popular autonomous navigation stack in the ROS platform, fitting reactive operation to the standard ROS communication interface, while being compatible with existing global planners also. As validation, multiple navigation tests have been performed in obstacle-populated indoor environments (both simulated and real) by a robotic platform equipped with various RGB-D cameras and a laser scanner.
KOMPARATIVNA ANALIZA ANDROID I WINDOWS PHONE OPERATIVNIH SISTEMA

Operating systems of mobile devices represent operating systems on which devices such as smartphones, tablets or other digital mobile devices are based. The most popular operating systems of today’s mobile devices are Android, iOS, KaiOS, Windows. With the advent of smart devices, competition has started between Internet giants such as Android, iOS, and Windows, which has launched a struggle to dominate the market for mobile devices and operating systems that support them. In this paper, two operating systems for mobile devices, Android and Windows Phone are analyzed, as well as in which segments they are different and in which they are similar. When and how the world-renowned Microsoft company launched a new smartphone operating system, and after a long and fair knightly struggle with other operating systems on the market, announced its withdrawal from the same. The characteristics of the mentioned operating systems and the statistics on the world level areindicated, which indicates the intuitive victory of one of them.
EFEKTIVITAS PENGGUNAAN MEDIA GRAFIS DALAM MENINGKATKAN MOTIVASI BELAJAR SISWA

Writing this article aims to explain the explanation of learning media. Includes types, general criteria for learning media so that the benefits to be gained if using learning media are included in this article. However, this article focuses its study on the use of media that feels it can increase motivation to learn in the classroom. By using learning media the focus of the attention of students in the class will be more focused on one more concrete thing, this is one of the factors that will increase student learning motivation. The use of media is proven to increase student motivation because not only one reading source mentions this, but there are several books until several scientific articles mention that the use of instructional media can increase student motivation. There is also one study conducted in a school that states that the use of instructional media is proven to increase learning motivation in students at school. The source of this article comes from several books and scientific articles that have been quoted.
Evaluating an ASR Pipeline for a Social Robot

There has been a big increase in the use of social robots, such as Pepper, which use verbal communication as the main method of interacting with a human. Verbal communication with a robot is performed using Automatic Speech Recognition (ASR) to recognize words from an audio stream containing speech. These social robots are being more frequently used in noisy environments. As such, this thesis investigates 1) whether Pepper's built-in keyword spotter can be replaced by an ASR system able to recognize continuous speech in Dutch; 2) whether Pepper's ASR pipeline can be made more robust against noise, without changing its hardware. To that end, Pepper's built-in keyword spotter and Sound Source Localization (SSL) algorithm are evaluated against an ASR pipeline based on a Delay-and-Sum beamformer, MUSIC Sound Source Localization, and Google Cloud Speech-to-Text. The proposed pipeline showed a significant decrease in Keyword Error Rate of 6.2\% compared to Pepper's built-in keyword spotter, and a significant decrease of Word Error Rate (WER) of 21.4\% on Dutch continuous speech in clean listening conditions. A decrease in WER of 13.3\% was observed in an SNR of 8 dB, and a decrease in WER persisted throughout lower Signal-to-Noise ratios (SNR). As such, it has been shown that Pepper's speech recognition can be improved and made more robust against noise by preprocessing the audio using MUSIC SSL and a Delay-and-Sum beamformer, and transcribing the speech (in Dutch) using Google Cloud Speech-to-Text.
Pengaruh Ethanolamina (MEA) dalam Pembentukan TiO2 dari Bahan Awal Ti Butoksida

Titanium dioxide has been prepared through the sol gel method using the addition of ethanolamine. The research was conducted to study the effect of MEA on the formation of TiO2. The amount of MEA was varied to 0; 0.5; 1; 1.5; and 2 ml respectively. The samples were calcined at a temperature of 500 ºC. TiO2was characterized using X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and photocatalyst tests using UV lamps. The XRD characterization results showed that in the A sample an anatase phase was formed whereas in the Csample an anatase phase and a brookite phase were formed. The resultof TEM characterization using ImageJ software show that the particle size of TiO2 is26,1 nm, respectively. The results of the characterization of the fastest photocatalyst catalyst test occurred in sample C which the variation of MEA is 1 ml.
THE CORRELATION BETWEEN STUDENTS’ MASTERY IN VOCABULARY AND THEIR ABILITY IN COMPREHENDING AN ENGLISH FOR SPECIFIC PURPOSE (ESP) TEXT.

ABSTRACT Vocabulary is one of the important things in English learning that can’t be conveyed by people. For gaining a good ability in listening, speaking, reading, and writing, people need to have good vocabulary mastery. That’s the reason why this part becomes the basic need in language learning and when the researcher found that some of her students with good vocabulary mastery or poor vocabulary mastery find difficulty in comprehending a text especially an ESP text, then the correlation between vocabulary mastery and comprehending text was chosen to be the theme. The research was purposed to find out whether there was any significant correlation or not between students’ mastery in vocabulary and their ability in comprehending English for Specific Purpose (ESP) Text. The sample of this research was the first semester students. As the instrument of the research, the objective vocabulary test and comprehension test were used. To analyze the data, it used the Product Moment Correlation of Pearson formulae. The result showed that the students’ mean score in vocabulary mastery test was 26.25 while the comprehension test mean score was 41.05. The result also showed that there was a significant relation with the significant level of 0.7. So, the hypothesis proposed in this research was accepted. In conclusion, it can be said that there was a significant correlation between students’ mastery in vocabulary and their ability in comprehending an ESP text. Keywords : Vocabulary Mastery, Comprehending, an English for Specific Purpose text.
BLOCKCHAIN TECHNOLOGY - THE CONFIDENCE PROTOCOL FOR A NEW REVOLUTION IN KNOWLEDGE SOCIETY

The history of humanity has known many turning points in social order, marked by profound changes both in society structure and organization.They were brought on by unprecedented technological progress or by big changes in social thinking and consciousness.Considering their geographical impact, many of them were restricted to country level and only a few produced global changes.The propagation speed for planetary level changes was reduced, leading to slow changes with various consequences in each country.The development of Information and Communication Technology (ICT) has led during the last three decades to profound and extensive changes, marking a passing to a new type of society, based on information, communication and knowledge: the present day knowledge society.Each emergent ICT technology has led to a real revolution.The first four decades of internet have brought upon numerous such revolutions, from daily used electronic mail (e-mail), World Wide Web, social networks and mobile web to newer concepts, technologies and paradigms like big data, data mining, cloud and fog computing, IoT and IoV.All these, corroborated with the financial crisis of early 2000 were nothing but the premises for what is now known as blockchain revolution or internet trust protocol.Since this is a real revolution, in this paper we will show the way blockchain influences (in random order) business/ enterprise architectures, financial services, anti-plagiarism solutions, economy, society, electoral processes and democracy in general.This is why literature mentions "a second era of democracy" or "liquid democracy".
Automatically Validating the Effectiveness of Software Diversity Schemes

Software diversity promises to invert the current balance of power in cybersecurity by preventing exploit reuse. Nevertheless, the comparative evaluation of diversity techniques has received scant attention. In ongoing work, we use the DARPA Cyber Grand Challenge (CGC) environment to assess the effectiveness of diversifying compilers in mitigating exploits. Our approach provides a quantitative comparison of diversity strategies and demonstrates wide variation in their effectiveness.
PREDICTION OF GLOBAL SOLAR IRRADIATIONS ON INCLINED PLANES BY LIU & JORDAN MODELS AND THE ARTIFICIAL NEURAL NETWORK (RNA). APPLICATION SITE MAHAJANGA

The design and sizing of solar energy systems (photovoltaic solar panel, thermal solar panel, parabolic solar concentrators, aerovoltaic system, solar tower chimney, etc.) requires precise knowledge of the solar field at the site where the system will be installed. One of the major factors in the evaluation of the solar field at a given site is the availability of consistent and accurate global inclined irradiation data. This paper proposes the Liu and Jordan models and the artificial network for estimating global solar irradiations in an inclined plane, based on a single meteorological data, the monthly average daily global radiation striking a horizontal plane. The latter is determined from frequently measured meteorological data, solar insolation. These two models lead to almost similar results, confirming the ability of neural networks to accurately predict solar irradiation. Keywords: Sunstroke duration, solar field, Liu and Jordan models, global solar irradiation, estimation; artificial neural networks.
Future of Digital Research - Dr Thomas Etherington

Dr Thomas Etherington - a geoinformatician and ecologist at Manaaki Whenua - Landcare Research, a member of New Zealand Ecological Society, and a fellow of Software Sustainability Institute.His research is interdisciplinary, using computational methods to examine environmental questions and problems through the combination of theories and methods from geography and ecology. He has deep interest in sustainable software – reproducible and open science, and how researchers interact with data. He says that although recent colleagues probably wouldn’t believe it, in the distant past he even spent time in the field tracking badgers and bears.In this thought piece he shares the challenges of the future where the researchers must work with big data and data from various non-traditional sources. Some of these may be citizen science data where data is much less structured, and hence traditional forms of data analysis are inappropriate. There will be much effort required moving forward working with big data in non-conventional ways.He also shares the necessity of interdisciplinary nature of his research, and that it is crucial to build common vocabulary to be able to ask the right questions across people with different expertise.---BackgroundWhat are the opportunities and challenges around advanced computing for NZ's research communities 5 to 7 years in the future?NeSI has reached out to various research leaders in New Zealand for the answer to this question.This document is the first of many thought pieces to come. We have Dr Thomas Etherington, who has commented on the research being done with his colleagues at Manaaki Whenua – Landcare Research.---New Zealand eScience Infrastructure (NeSI) enables researchers across a wide range of communities and disciplines to tackle large or highly complicated problems and to investigate scientific challenges that were previously impossible. NeSI makes approaching these problems easier for researchers through offering a specialised platform of computational and analytics software and services powered by supercomputers, and placing a strong emphasis on support and training alongside the raw power of its technology platform. NeSI is a collaboration of the University of Auckland, the University of Otago, Manaaki Whenua - Landcare Research, NIWA, and MBIE.
AN OPTIMIZATION MODEL FOR SENSOR PROCUREMENT IN ELDERLY MONITORING

The rapid increase in the number of elderly population is forcing rapid rises in healthcare costs.The development of wireless communication technologies, sensing technologies, embedded systems and nanotechnologies makes it possible to develop systems that monitor activities of elderly continuously.Sensors or collections of sensors, forming sensor architectures constitute an important fraction of the cost of an elderly monitoring solution.However, the compromise between the cost of procurement and the performance of a set of sensors is not yet well studied.In the paper, we have developed an optimization model for sensors procurement in elderly monitoring.This model considers the types of sensors for monitoring the elderly, the cost of these sensors provided by different suppliers, the performance assessed by various criteria and the amount of money available for their purchase.This model aims at aiding health management decisions.For validation the optimization model is applied to a case study.
Social Media Utilization in the Teaching Library and Information Science Courses in Tertiary Institutions

Abstract The study is on social media utilization in the teaching of library and information science courses in tertiary institutions. Survey design was adopted for the study. Three research questions were raised and answered while one null hypothesis was tested. The population of the study consisted of 41 Library and Information Science lecturers. A structured and questionnaire was used for data collection. The instruments yielded a reliability coefficient of 0.75. Mean and standard deviation were used to answer the research questions while t-test was used to test the null hypothesis at 0.05 level of significance. The findings from the study revealed that social media were not adequately available in Delta State University, Abraka, Nnamdi Azikiwe, Awka, Madonna University, Okija and Federal Polytechnic Oko. The study also revealed that male and female Library and Information Science lecturers were not significantly different in their ratings regarding availability of social media in Delta State University, Abraka, NnamdiAzikiwe, Awka, Madonna University, Okija, and Federal Polytechnic Oko. Keywords: Social Media, Library and Information Science, Utilization, and Tertiary
Data Hiding and Compression Encryption through Discrete Wavelet Transform and Block Coding

The ubiquitous nature of digital network systems means that digital documents can be copied and distributed easily to large numbers of people with no cost.Individuals can download sound, picture and video records, and they can impart them to companions and they can control or adjust their unique substance.This is the reason there is an earnest need to ensure the copyright of such media.There are various advances that will give insurance from unlawful replicating.Advanced watermarking calculations were created to take care of this issue.To secure and less space data hiding and compression encryption through discrete shearlet transform (DST) and block based coding algorithm is present paper.According to efficient scheme is increase PSNR (peak signal to noise ratio), SSIM (similarity index) and decrease mean square error (MSE).
COMPARISON AND ANALYSIS OF RESULTS OF FNAC AND FROZEN SECTION IN DIAGNOSIS OF BREAST LESIONS

Background: Breast lesions encompass a wide spectrum of diseases, both neoplastic and non-neoplastic. However, effective treatment of breast lesions necessitates early and conclusive diagnosis. This calls for a multidisciplinary approach which includes clinical assessment, radiological examination and pathological tools like FNAC, Frozen section and Histopathology. The present study was conducted to determine and compare the accuracy of FNAC and intraoperative frozen sections in diagnosis of breast lesions by keeping histopathology as gold standard.&#x0D; Method: This comparative study included 50 samples of breast lesions during the period of two year and that were subjected to FNAC, frozen section and histopathological evaluation.&#x0D; Results: Among 50 cases, 21 (42%) were benign and 29 (58%) were malignant cases according to gold standard. According to FNAC diagnosis, 24 cases were benign and 26 were malignant while according to frozen section diagnosis, 22 cases were benign and 28 were malignant. Among benign category, maximum cases (15;30%) were of fibroadenoma whereas among malignant category maximum cases (27;54%) were of infiltrating duct carcinoma according to gold standard, one case each of tubular and lobular carcinoma. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of FNAC was 89.66%, 100%, 100%, 87.5% and 94% respectively while the sensitivity, specificity, PPV, NPV and accuracy of frozen section was 96.55%, 100%, 100%, 95.45% and 98% respectively.&#x0D; Conclusion: Both FNAC and frozen section have a high diagnostic accuracy in the evaluation of breast lesions; therefore both should be used as tools for the assessment of breast lesions.&#x0D; Keywords: Breast Lesions, Diagnosis, FNAC, Frozen section, Histopathology, Benign, Malignant, Fibroadenoma, Carcinoma
Image Features for Content Based Image Retrieval System in Image Mining

The digital images are used in multiple applications, such as Geographical image, medical image, architecture design, advertising and military. Image retrieval that is user-defined image from a large image database is a critical image processing technique. The main objective of this research paper is supporting the image features for content based image retrieval system in image mining. The capability of present CBIR systems has been limited by their use of only primitive features, so they cannot satisfy most semantic-level query demands. The CBIR system extracts the stored images from the database by comparing the features of the query image with the images in the collection. The implemented system only used RGB and HSV color model for color feature extraction. Other color models such as HIS, CMYK, CMY, etc.; can also be incorporated to extract color feature for image retrieval to improve the accuracy of the system.
DATA WEB MINING IN E-COMMERCE: PROGRESS AND PERSPECTIVES

The move from traditional to online services and the spectacular increase in the number of online customers bring great challenges to the field.Analysing the Internet flow, valuable insights about the traffic coming and leaving an e-commerce site can be found, helping them to become more effective and increasing their competitiveness.This is what Web mining does, as it deals with the mining of remarkable knowledge from the Internet, studying the way users interact.Web mining is used in e-commerce to find the browsing habits of customers, helping in understanding their preferences.This paper examines the main processes of data mining (Web Content, Web Structure and Web Usage information) and the various types of web data mining technologies, emphasizing their use in the online business.An overview of the latest developments is presented and the main challenges are outlined.As a final point, possible perspectives of web data mining in the e-business domain are analysed.