Miracle-dz/UniFAR-FTUs huggingface dataset:
Android based Introduction of Dewata Nawa Sanga Virtual Reality Application

God manifestation in Hinduism which has a duty to look after the universe based on the cardinal points is called Dewata Nawa Sanga. Introduction to Dewata Nawa Sanga has usually started in elementary school or in junior high school. Over the years, the media that is used to learn Dewata Nawa Sanga is from tables and books which are not effective and not interesting. DewataVR application was developed using Virtual Reality (VR) technology as a new learning media in Android platform to overcome the problems. Technology in visualization and simulation field has begun to evolve with VR existence, which simulate a virtual environment. Each God in Dewata Nawa Sanga exists in 9 cardinal point, therefore it requires a Gyroscope Sensor and a Compass Sensor. Gyroscope Sensor is required to detect gravitation movements which rest on a disc that rotate on its axis, whereas Compass Sensor is used as a support sensor in showing cardinal points of each God. DewataVR application make the users as if they were on the cloud and looked at 3D objects of Gods, rides (vehicles), weapons, and information about colors, Aksara, and shrines ruled by each God. Further information about each God is also explained
Location Recommendation for Enterprises by Multi-Source Urban Big Data Analysis

Effective location recommendation is an important problem in both research and industry. Much research has focused on personalized recommendation for users. However, there are more uses such as site selection for firms and factories. In this study, we try to solve site selection problem by recommending some locations satisfying special requirements. There are many factors affecting it, including functions of architecture, building cost, pollution discharge etc. We focus on the specific site selection of meteorological observation stations in this paper with leveraging the factors of functions of architecture and building cost from multi-source urban big data. We consider not only recommending the locations that can provide more accurate prediction and cover more areas, but also minimizing the cost of building new stations. We design an extensible two-stage framework for the station placing including prediction model and recommendation model. It is very convenient for executives to add more real-life factors into our approach. We have some empirical findings and evaluate the proposed approach using the real meteorological data of Shaanxi province, China. Experiment results show the better performance of our approach than existing commonly used methods.
Using evidence from a Community Treatment Observatory (CTO) to enhance uptake of HIV services in Sierra Leone

Copyright: © 2019 The Authors. Published by Archetype Health Pty Ltd. This is an open access article under the CC BY-NC-ND 4.0 license. SUMMARY Sierra Leone has a low HIV prevalence (1.5 per cent) but is faced with low uptake of HIV services, including testing, treatment, and treatment monitoring. The Network of HIV Positives in Sierra Leone (NETHIPS) established a Community Treatment Observatory (CTO) with support from its partners to generate evidence and engage duty bearers in improving service delivery. The CTO provides the unique advantage of galvanising efforts of civil society actors and affected populations on ways to tackle new infections and improve care for selected key populations in Sierra Leone.
Hardware Co-simulation of Anaglyph 3D image Using Xilinx System Generator

In modern era the trend of 3D movies and 3D projection took a very intensive attention. Stereoscopic 3D images are elementarily obtained by overlapping left and right eye images in different color planes of a single image for successive viewing through colored glasses. Here we present a novel FPGA based reconfigurable architecture for 3D image color space conversion RGB to YCbCr for implementing real-time DSP applications using Xilinx System Generator (XSG) for MATLAB. The CSC design is implemented in hardware which is realized using the Xilinx Block Sets presented in Simulink. From the hardware software co-simulation block VHDL/Verilog code is generated and is tested on Atlys FPGA Spartan 6 (xc6slx45-2csg324).
A Phenomenographic Study on On-reserve First Nations, Metis and Inuit Students' Experiences in a One-year College Transition Programme

In an age when access to higher education is expanding, the literature shows that First Nations, Metis, and Inuit (FNMI) students are underrepresented. Those who manage to enter university experience challenges that hinder their success. Consequently, transitional programmes have been set up to support FNMI students as they move from high school to higher education institutions. To better understand the challenges of transitioning, I decided to embark on a phenomenographic study that explores six on-reserve Canadian FNMI students’ conceptions of their learning experiences in their community college. In addition, the study also examines two of their teachers’ perceptions of the students’ experiences as they prepared them for university. The findings show that some students adopted approaches to learning that do not define or characterize who they are as learners, but instead reflect how they coped with teaching and learning in their environment. These approaches, conceptualised in phenomenography as surface and deep approaches, are not truly the way that FNMIs are as learners. Surface and deep approaches do not mirror the cultural perspectives and holistic experiences evident in an indigenous view of learning. The surface approach (learning as primarily reproductive) refers to those who see learning as based on that, which is extrinsic to the real purpose of the task. By contrast, the deep approach (learning as primarily seeking meaning) is associated with students’ intentions to understand and engage in meaningful learning, focusing on principles, and using strategies that are appropriate for creating meaning.
Trends in International PISA Scores over Time: Which Countries Are Actually Improving?

Many countries attempt to increase their Program for International Student Assessment (PISA) rankings and scores over time. However, despite providing a more accurate assessment of the achievement-based improvements across countries, few studies have systematically examined growth in PISA scores over multiple assessments. Using data from the 2006, the 2009, and the 2012 PISA, we analyzed which countries experienced significant increases in their country-level average PISA scores between 2006 and 2012. To facilitate improved policy decisions, we also examined what country-level conditions were associated with such increases. Contrary to expectations, we found that few countries significantly increased their PISA scores over time. Countries that did experience meaningful improvements in PISA scores were more likely to have had lower PISA scores in 2006 and experienced country-level foundational advancements more recently, such as advancing to a more democratic form of government and/or a higher income classification.
Mandatory Convertible Bonds and the Agency Problem

A large proportion of the academic literature about the agency problem focuses on corporate governance or the instruments that can be used to balance the incentives of shareholders and debt holders. Following the real options company valuation framework, one method to increase shareholder value involves increasing the intrinsic risk of the firm; however, such a practice reduces the bondholder value. We analyzed an innovative balance sheet instrument, the mandatory convertible bond, as a means to increase financial sustainability of companies, improving the value for shareholders without increasing the perceived default risk. The results of the empirical analysis illustrate that for companies in a weak credit position, the agency problem can be mitigated by the issuance of mandatory convertible bonds, which allows managers to increase company risk without being detrimental for bondholders. However, when the probability of distress is small, shareholders have less incentive to increase company risk than in a company funded by mandatory convertible bonds, being more aligned with bondholders. A better alignment of debt holders and shareholders incentives reduces inefficiencies, mitigates the probably of distress, and improves the long-term financial sustainability of companies and can promote stable growth and innovation.
The dynamic structure of phytoplankton community in Segara Anak Lake: a volcanic lake in Mount Rinjani National Park

Segara Anak is a volcanic lake located in the Mount Rinjani National Park, West Nusa Tenggara, Indonesia. It covers an area of ± 11.3 km2 with a maximum depth of 230 m at 2010 m.a.s.l. Segara Anak one of tourism object around Rinjani Mountain. The purpose of this research was to study the phytoplankton community structure and physical and nutritional factors correlation in Segara Anak spatially and temporally. The sampling technique used was a purposive sampling method. The samples were taken at five stations with an increasing depth of 1 m, 5 m, and 10 m respectively. The sample collection was started from October to December 2017. The data were analyzed using One-way ANOVA, Kruskal Wallis, Cluster Analysis and Principal Component Analysis. We identified 19 phytoplankton genera with 4 classes. The phytoplankton structure, nutrient, and physical factors are significantly different in spatial depth and temporal sampling. The abundance of phytoplankton in Segara Anak is dominated by the Cyanophyceae class.
Gradually increasing forest fire activity during the Holocene in the northern Ural region (Komi Republic, Russia)

In many boreal regions of Russia the past natural variability of forest fire activity remains largely undocumented, preventing accurate assessment of the impact of current climate warming on forest ecosystem dynamics. This study aims to reconstruct the Holocene fire history of the northern Ural mountain foothills, in the Komi Republic, based on analyses of charcoal particles from peatland deposits and coupled with dendrochronological investigations. The results show that there was a gradual increase in forest fire activity during the past 11,000 years. Between 11,000 and 5100 cal. yr BP, the mean fire return interval (FRI) oscillated between 600 and 200 years. During this period, regional data showed that cold temperature, humid climatic conditions, combined with steppe vegetation between 11,000–9000 cal. BP, and then the development of spruce-dominated forest between 9300 and 4600 cal. yr BP, were less conducive to fires. After 5100 cal. yr BP, a gradual increase in drought conditions through reduced precipitations, associated with the establishment of a Scots pine forest favored fire frequency, with a mean FRI under 200 years (range, 200–40 years). Nowadays (since CE 1500), human activity induces an unprecedented fire activity with a mean FRI below 100 years (range, 100–40 years).
Análisis de información e imágenes utilizadas para prevenir el virus del Zika en Puerto Rico: ¿Cómo se pueden mejorar los mensajes?

Los mosquitos son insectos comunes que pueden formar parte de la cotidianidad y, además de crearles incomodidad a los seres humanos, también les causan enfermedades. Los mosquitos aedes aegyptis y aedes albopictus que estén infectados pueden transmitir el virus del Zika. La infección puede causar complicaciones de salud. En el 2015 surgió en Puerto Rico una epidemia del virus del Zika. Con el propósito de prevenir la propagación del virus, el Departamento de Salud de la Isla difundió anuncios de servicio público impresos y digitales para prevenir el virus del Zika. Debido al objetivo de dichos mensajes, es necesario analizar sus estructuras para determinar si la información fue creada de manera persuasiva. Por lo tanto, dentro del marco teórico del modelo de elaboración de probabilidad, este trabajo hace un análisis de contenido cualitativo para examinar la estructura de los mensajes de prevención del virus del Zika utilizados durante la epidemia en Puerto Rico. A través de este estudio se describen, analizan y evalúan los aspectos persuasivos de los mensajes y se incluyen recomendaciones para la creación de mensajes persuasivos futuros.
Pemanfaatan Gamifikasi pada Massive Open Online Course (MOOC)

Sejak dimulainya era Revolusi Industri 4.0 Gamifikasi dan Massive Open Online Course (MOOC) merupakan fenomena baru dalam pembelajaran terbuka dan dikenal sebagai strategi yang baik untuk meningkatkan kualitas pendidikan. Namun demikian, MOOC memiliki dua kelemahan utama: pertama, kurangnya pemahaman untuk mengetahui sasaran pribadi; dan kedua, tingkat penyelesaian yang rendah dibandingkan dengan jumlah pendaftaran ke MOOCs. Untuk dapat mengatasi dua kelemahan tersebut peneliti akan mengusulkan pemanfaatan Gamifikasi. Dalam tulisan ini akan diuraikan berbagai penelitian yang berkaitan dengan Gamifikasi dan MOOC. Metodologi penelitian ini menggunakan pendekatan kualitatif dengan menekankan pada analisis data. Hasilnya diketahui bahwa MOOC tidak memerlukan tingkat penyelesaian penuh seperti kursus tradisional yang biasanya dianggap sebagai keberhasilan. Kata Kunci : Gamifikasi, MOOC dan Tingkat Penyelesaian
A Study of Fragility, Entrepreneurship and Mental Health: Investing in Better Cognitive and Behavioral Skills for Small Medium Enterprise Entrepreneurs to Thrive in Conflict-Affected Areas of Pakistan

Mental health, well-being and lasting economic outcomes are intimately connected. However, in geographies marked by fragility, conflict and violence (FCV), entrepreneurs of small and medium size enterprises (SMEs) experience chronic stress and poor mental health on a regular basis. These issues can hamper performance and quality of life for the entrepreneurs, and can dampen the benefits of existing financial and business assistance programs. Few proven rigorous interventions are known. This study tests the hypothesis that a five-week group Cognitive Behavioral Therapy (CBT) training called Problem Management Plus for Entrepreneurs (PM+E) in combination with financial assistance could be more effective at reducing psychological stressors of SME entrepreneurs in FCV contexts than financial assistance alone. Meaningful and statistically significant improvements in mental health were achieved, with improvements persisting and increasing beyond the immediate post-intervention period. Three months after the intervention, based on analysis of pooled data across two follow-up rounds (at five weeks and three months post intervention), entrepreneurs in the treatment group experienced statistically significant reduction in the intensity and prevalence of depression and anxiety symptoms (measured by the Patient Health Questionnaire Anxiety and Depression Scale) and higher levels of well-being (measured by the WHO-5 Well-Being Index) compared with the control group. The effect was marked for those experiencing mild/moderate levels of depression and anxiety, indicating the clinical value of such low-touch early interventions. Overall, the study demonstrates that empirical research through Randomized Control Trials (RCTs) can be conducted in challenging, FCV settings through appropriate rapid training of local researchers and non-specialist providers (NSPs) at a low cost yielding scalable programmatic and policy level lessons.
Integration of cutting force control and chatter suppression control into automatic cutting feed adjustment system design

Abstract This study designed an automatic cutting feed adjustment system for computer numerical control (CNC) turning machine tools, which integrate the operational characteristics of cutting force control and chatter suppression control to shorten the machining time and maintain the quality of workpieces. The setting of appropriate machining conditions (such as cutting feed, spindle speed and depth of cut) to consider both machining quality and efficiency often causes difficulties for machine tool operators. Therefore, this study uses cutting force control to design an automatic cutting feed adjustment method for cutting tools, and then, the chatter suppression control design is used to modify the cutting force command to suppress cutting chatter. The experimental results of the CNC turning machine tool show that the use of the cutting force control to adjust the cutting feed can shorten the machining time; however, the cutting chatter results in larger surface waviness on the workpiece surface. When the cutting force command is properly modified by actuating the chatter suppression control, the workpiece shows better surface roughness with prolonged machining time. Therefore, the cutting tests demonstrate that the proposed system is feasible for satisfying the machining requirements of the manufacturing processes of mechanical parts for high speed and high accuracy.
The development of an educational checklist for individuals with CHARGE syndrome

CHARGE syndrome is a rare genetic disorder which can impact every sensory system and is often associated with significant medical, communicative, developmental, and behavioral difficulties. Due to the rarity and complexity of CHARGE syndrome, educators often lack the expertise required to effectively understand and accommodate the needs of these students. Therefore, an educational checklist (i.e. “Checklist”) was developed to provide a comprehensive tool that educators and related professionals can utilize to aid in the education of individuals with CHARGE syndrome. The Checklist was developed through collaboration with an international panel of experts; CHARGE Syndrome Research Lab at Central Michigan University (CMU); and a select group consisting of parents, professionals, and state deafblind project employees. The Checklist outlines major CHARGE characteristics, resulting educational needs, team members, consulting professionals, and suggested methods of accommodation. The Checklist may be utilized to develop and inform services for individuals with CHARGE syndrome in the schools.
Pilot Study Of Safe Sisters: A Sexual Assault Prevention Program For Sorority Women

ii LIST OF TABLES.iv LIST OF FIGURES.v INTRODUCTION.1 REVIEW OF LITERATURE.7 METHODOLOGY.33 RESULTS.48 DISCUSSION.62 REFERENCES.71 APPENDIX.87 APPENDIX A: MEASUREMENT TOOLS.88 APPENDIX B: RECRUITMENT EMAIL.95 APPENDIX C: CONSENT FORM.97 APPENDIX D: PROGRAM MATERIALS.99 VITA.111
The Impact of the Implementation of Cohesion Policy on the Sustainable Development of EU Countries

The impact of implementation of cohesion policy on the sustainable development of EU countries is of great interest and presents a number of actual challenges. This research aims to evaluate the impact and the effects of the cohesion policy among the Member States using hierarchical clustering analysis in order to identify how the selected variables affect the sustainable development adopted models. The variables used in the analysis were selected on the basis of official data provided by the European Commission, SDG Index and Dashboards Reports and the EU Cohesion Monitor. The results of the research have led to the grouping of the 28 Member States in a number of six clusters, identifying performers but also those countries that have a high potential for sustainable development or which require increased attention to be sustained in recovering existing gaps. The results of the study can be a starting point for policy makers and other stakeholders involved in their efforts to support sustainable development through effective and effective policies.
Deep Learning as a Tool for Image Denoising and Drift Correction

Drift of the microscope during imaging is an unavoidable and generally undesired attribute that impedes high quality imaging and spectroscopic studies. As a result, means for compensating drift have been developed [1,2] and utilized by the community for several decades. In some cases, the methods require knowledge of the crystal structure as inputs to the algorithm. Regardless, continual improvement in drift correction, especially during microscope operation, will be needed to make studies such as recent atomic manipulation efforts [3] possible at larger scales.
Summarizing Long Historical Documents Using Significance and Utility Calculation Using Wordnet

: The current technology of automatic text summarization confers a critical part in the information retrieval and text grouping, and it gives the best answer for the information over-burden issue. When mulling over the size and number of documents which are accessible on the Internet and from alternate sources, the necessity for a very effective device on which produces usable summaries is clear. We show a superior algorithm utilizing lexical chain computation. The algorithm one which makes lexical chains a computationally possible for the user. Furthermore, utilizing these lexical chains the user will produce a summary, which is a great deal more successful contrasted with the arrangements accessible and furthermore nearer to the human created summary
Optimising MV Network Development and Enhancement Using a Routing Algorithm and Cable Re-Rating

This paper outlines and illustrates the latest developments in ‘VOH’, an automatic network routing algorithm. The treatment of existing MV network is shown, which should prove invaluable in aiding the development of least cost investment plans. Following a brief discussion on the difference between component ratings when planning and ratings when considering the upgrade of existing components, the significant economic benefit of deferring upgrade by re-rating according to a cyclic load profile rather than a steady-state rating is shown. Forced backup to secondary substations that are supplying important loads while the rest of the network is only backed up where it is cost effective, and the ability of the user to force the algorithm to optimise around a stipulated trunk feeder are also demonstrated.
Spam, Fraud, and Bots: Improving the Integrity of Online Social Media Data

Online data contains a wealth of information, but as with most user-generated content, it is full of noise, fraud, and automated behavior. The prevalence of “junk” and fraudulent text affects users, businesses, and researchers alike. To make matters worse, there is a lack of ground truth data for these types of text, and the appearance of the text is constantly changing as fraudsters adapt to pressures from hosting sites. The goal of my dissertation is therefore to extract high-quality content from and identify fraudulent and automated behavior in large, complex social media datasets in the absence of ground truth data. Specifically, in my dissertation I design a collection of data inspection, filtering, fusion, mining, and exploration algorithms to: automate data cleaning to produce usable data for mining algorithms, quantify the trustworthiness of business behavior in online e-commerce sites, and efficiently identify automated accounts in large and constantly changing social networks. The main components of this work include: noise removal, data fusion, multi-source feature generation, network exploration, and anomaly detection.