Reviewerly/exHarmony huggingface dataset:
Determinants of Foreign Direct Investment Inflow to Ethiopia: Time Series Evidence (ARDL Approach)

In low income country foreign direct investment is taken as the next best alternative source to fill the gap between domestic savings and the required investment for economic growth.While its inflows to Ethiopia are the lowest by a wide margin both in actual quantity and as a proportion of gross national product (GNP).This study deals the empirical relation between FDI inflow and its determinants in Ethiopia by employing Autoregressive distributed lag model for the time period covering from 1981 to 2018.The stationarity properties of the data was detected using Augmented Dickey-Fuller (ADF) and Phillip-Perron (PP) unit root test and the result indicates all the variables are stationary at level and first difference calling the effectiveness of ARDL model.The ARDL bound test used to test the existence of long-run link among the variables and the result confirmed that there is long run relationship among FDI and independent variables.The results indicated that the FDI flows to Ethiopian economy are determined by the degree of trade openness; domestic market size proxied by per capita GDP; domestic bank credit; rate of inflation; human capital and official exchange rate in the long-run and trade openness; rate of inflation and official exchange rate in its short run dynamics.The policy which creates favorable environments for domestic credit institution; predictable official exchange market and uninflated domestic price situation enables to harvest the highest possible expected benefits from FDI inflow.
Elementary teacher's qualifications for using the communication model to teach literature

In the master’s thesis entitled Elementary teacher's qualifications for using the communication model to teach literature the problem of carrying out a teacher's lessons is presented. Teachers are supposed to follow certain methods and systems for achieving objectives, called communication model. Just as we have different pupils, not all teachers are the same, therefore the question concerning their qualifications for teaching literature arises. In the theoretical part we have presented theoretical knowledge concerning didactic literature, youth literature, youth literature in the classroom, communication model, stages of school interpretations and the importance of a teacher's role, which is crucial for teaching literature effectively. In the empirical part we have presented findings regarding the teachers' qualifications, which were obtained through online questions led by 100 primary teachers. The established current practice of teachers has shown us encouraging results regarding their qualifications for teaching literature using a communication model. Based on our findings we also created a model with guidelines for the use of the communication model of literature, which will enable the teachers to carry out their literature lessons even better.
Deep Ensemble Confidence Levels for Multi-hot Categorization

NOICE (Neural Optical Image Categorizer for the Elog) is a small collaboration tasked with categorizing the images in the Fermilab Accelerator Division electronic logbook by using Artificial Intelligence. To do so, we manually categorized a subset of the images in the E-log into nine independent labels. Each image was then multi-hot-encoded into a nine-dimensional binary vector because each image could have more then one label.
LibGuides: CRM 430: Correctional Systems: Databases

This course is designed to be a comprehensive overview of our government's response to convicted criminal offenders. The origins, evolution, processes, and current problems of correctional systems will be the topics of study. More specifically, the course
Intercultural Competence: Communication Across Cultures in the Digital Age

In the context of globalization and economic transnationalization, the development level of communicative and cross-cultural competence is one of the individual's social and professional success factors in modern society. The study purpose was to study the attitude of young people to the role of intercultural communication in the context of digital transformation and to measure the level of cross-cultural competencies development (or 3C) among respondents. The research results are based on the analysis of theories and models of intercultural communication, a statistical analysis of the empirical results of sociological and psychological research. The results showed a high level of cross-cultural competencies development among youth, however, studies have revealed the need for further development of students' motivation for intercultural communication and to increase their intercultural competence. Achieving these goals will be effective provided that a methodological model for the phased formation of interest in intercultural communications within the framework of professional education based on digital technologies is developed.
Generative Adversarial Networks to enhance decision support in digital pathology

Histopathological evaluation and Gleason grading on Hematoxylin and Eosin(H&E) stained specimens is the clinical standard in grading prostate cancer. Recently, deep learning models have been tr ...
Unleashing Animal-Computer Interaction : A Theoretical Investigation of the “I” in ACI

Non-human animals have had a long co-existence and relationship with human culture and society, and we interact with them in a number of ways, and for various reasons. Their involvement in technolo ...
Sonatina per violino e pianoforte

Author(s): Cantara, Niccolo | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Vivo, provocador, sorprendente: dimensiones emocionales de los materiales bio-sinérgicos para un diseño socialmente significativo

Novel materials with hybrid, dynamic, and interactive qualities are emerging due to the cross-pollination between biology and electronics. In this exploratory article, we propose an original and tentative definition and taxonomy of Bio-Synergistic materials. By analyzing the best examples within the taxonomy, we argue that they elicit emerging materials experiences related to being alive, provocative, and surprising, unfolding a unique set of emotions, feelings, and experiences for users. Such experiences promote a shift in values in society, addressing a complex system of values related to interdependence, environmental consciousness, multi-species collaborations, caring, transience, and imperfection, and re-centering design approaches from being anthropocentric to becoming more-than-human. The findings are articulated in an original framework of Bio-Synergistic materials for socially meaningful design. This preliminary investigation may be extended into a solid research theme, catalyzing positive implications for nature, technology, and society.
I've had a number of blogs, sites, ...

I've had a number of blogs, sites, infodumps and everything online for around 25 years, this is just the latest in that long line.My main
Guides: ORCID iD: Creating an ORCID

A guide to understanding what is an ORCID, why researchers should be interested and how to obtain one of these unique identifiers.
LibGuides: Electronic Resources: Find Library's Electronic resources

A complete guide to the Unizulu Electronic Resources. Multiple ways of accessing e-resources
Design Of Website-Based Height Waves Information System

One of the environmental parameters that need to be monitored is ocean waves. Waves that occur at sea have random, dynamic, and complex movements. Height measurements and wave periods are difficult to formulate accurate and simplification is needed through mathematical equations in the form of sinusoidal. Therefore, the marine information system is very important for data storage media, data processing, and visualization of measurement data so that it is monitored in real-time. This research was made to build a website-based coastal wave height monitoring information system for wave height data display data from the measurement of the wave buoy instrument. This research was conducted by utilizing data from a wave height measuring instrument that was transmitted to an online database. Wave height data is displayed in the form of real-time data, real-time graphs with data sampling of 30 minutes, average data for one day, and average data for one month.&#x0D; Keywords: Wave height, system information, real-time
An Analysis on Secondary Mathematics Qualification Training Curriculum for the First Grade Regular Teacher

Changes in the curriculum and education policy are accompanied by significant changes in the school field. To keep pace with this trend of the times, teachers are required to have various re-education, and teacher re-education is a duty and a right of teachers. The common method of teacher re-education is teacher training, and the most core one is the qualification training for the first grade regular teachers. Since the training course and the target trainees in each position were institutionalized in 1972, there have been many changes in the curriculum of the first grade regular teacher training, and related studies have been continuously conducted. However, since the qualification training courses for the first grade regular teachers were reduced to ‘more than 15 days (90 hours)’ in 2012, there have been no studies on the qualification training courses for the first grade regular teachers especially in secondary mathematics education. This study compared and analyzed the first grade regular teacher qualification training curriculum of 17 metropolitan and provincial offices of education conducted in 2019 to the standard curriculum for the teacher qualification training. As a result of the analysis, it was confirmed that the first grade regular teacher qualification training curriculum of each metropolitan and provincial offices of education is slightly different from the guidelines of the standard curriculum for teacher qualification training. Additionally, a number of problems have been drawn to the content and the core competency of the lectures opened. Through this, we suggested the improvement points of the standard curriculum and the implications for the organization of the first grade regular teacher qualification training curriculum.
Exploration of Korean Students’ Mathematics Achievement, School Climate, and Well-being in PISA 2018 Results

PISA was implemented in 43 countries and economics in the first assessment. But now it has become a representative international comparative study as the number of participating countries and the interest in PISA results have increased. At the end of last year, the OECD announced the PISA 2018 results, and Korea recorded a high level of achievement, similar to the PISA 2015 results of the previous cycle. However, considering that the mean score of the PISA 2015 mathematics declined by 30 points compared to the PISA 2012 mathematics, it is necessary to interpret the PISA 2018 results by trend analysis on the percentage of the correct response and the proficiency in mathematics in addition to the comparison of the mean scores. Meanwhile, PISA provides indices of the educational context variables as well as the results of student achievement. Thus, this study outlined the results of the PISA 2018 mathematics domain, analyzed the trend of the percentage of correct answer by subcategory of mathematics framework and the results of school climate and student well-being by mathematics achievement level and also derived the implications for improving students’ achievement.
Collisions in Different Viscosities

Author(s): Hennell-Foley, Nicholas | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Blockchain research: a bibliometric and text mining based review of literature

This study utilised two bibliometric analysis methods and a text mining method to provide a systematic and holistic review of blockchain related academic literature. A total of 91 publications related to blockchain were identified from the Scopus1 database. Citation analysis identified security, data integrity, and integration of blockchains as foundations of this area of research. The study then employed keyword analysis to identify themes in blockchain research. Foundation, application, and emerging trend were the themes identified. The emerging trend in blockchain research was identified as the integration of blockchain with internet of things. Text mining was employed to identify additional themes. Technological aspect, business perspective, application areas, security, integrity and trust, models and frameworks, and benefits of blockchains were the additional themes. Finally, the study called for a future research agenda on blockchain research.
Gendynish: Stochastic Synthesis on the Arduino

The Gendynish algorithm is software that runs on Arduino-class microprocessors to produces sounds similar to Iannis Xenakis’ dynamic stochastic synthesis. This article outlines the origins of stochastic synthesis and describes the Gendynish algorithm and associated electronic instrument development and performance outcomes. This algorithm takes a somewhat unconventional approach to Arduino audio. In doing so it demonstrates how once cutting-edge computer music practices are now much more accessible and that the spirit of creative expression through audio technologies remains alive and well.
Mulit-Document Summarization Driven by Domain-Specific Embedding

Word embeddings are nowadays widely deployed in a large number of Natural Lan-guage Processing tasks. A word embedding is used to map each word belonging toa corpus, into a vector space, keeping semantic and syntactic properties. They areused in different implementations such as sentiment analysis, topic extraction, Part-Of-Speech tagging and of course document summarization. The focus of this thesisis towards this last job: the object is to extrapolate, given a collection of articles, themost relevant sentences to provide the reader only a limited set of information buthopefully the most meaningful.Particularly, the scope of this work is to empirically show that a domain-specific wordembedding is able to extract a better summary with respect to a general one. The ideabehind is that training a word embedding with documents of the same topic, will pro-duce a better representation of all the words related to that argument, because, withrespect to a non specific text, they are present more often and used in a more spe-cific context. Other than that, a domain-specific embedding is capable to handle betterwords having multiple meanings: instead of treating each meaning with the sameweight, the one linked to the precise topic will receive more relevance. This thesis issplit mainly in two parts: the first one is about producing a domain-specific word em-bedding and judging its quality; the second one is about applying the previous resultto a downstream task, the multi-document summarization indeed.
LibGuides: Social Media in the Classroom: Useful Platforms

This guide is meant to aid teachers in many ways social media can be used within the classroom setting.
InfoGuides: Library Reserves & Course Material Support for Faculty Guide: How to Request e-Reserves

This infoguide for Pepperdine faculty provides important information and highlights available support resources for the transition to electronic-only course reserves.
LibGuides: Resources for Remote Teaching & Learning: Ebooks

Library and Digital Learning remote teaching and learning resources for students and faculty
GATOR Library: Learning Commons Stats: Learning Commons Facts

This guide displays statistics collected about the GATOR Library of Northshore Technical Community College
Inversion of detrital zircon data to constrain spatially varying erosion rates

&amp;lt;p&amp;gt;Landscapes evolve through surface processes that are often transient in space and time. To understand the underlying geomorphic processes, one must assess how erosion rates vary spatially. This can be done using provenance analysis. Here, we introduce a formal inversion method to derive erosion patterns using detrital zircon age data as fingerprints. Zircons are omnipresent in Earth&amp;amp;#8217;s crust and contain information about the time since (re)crystallization in their U/Th-Pb ratio. For each geological unit having undergone a specific tectonic or magmatic history, one can find a unique age-frequency signature. Hence, erosion and sedimentation of grains originating from diverse source areas lead to a mix of the varying age-frequency signatures in sediments found at the outlet of a catchment. Considering that the age signal is not altered during erosion-transportation-deposition events, and given that recent technological advances enable precise dating of large amounts of grains, U/Th-Pb zircon ages provide an appropriate fingerprinting tool. Our inversion approach relies on the least-squares method with a priori information and model covariance to deal with non-uniqueness. We show with synthetic and natural examples that we are able to retrieve erosion rate patterns of a catchment when the age distribution for each geological unit is well known. Furthermore, relying on the nested form of catchments and their subcatchments, we demonstrate that adding samples taken at the outlet of subcatchments improves the estimation of erosion rate patterns. We conclude that the least squares inverse model applied on detrital zircon data has great potential for investigating erosion rates.&amp;lt;/p&amp;gt;
Towards an Open Access Data Policy for Deep Seismic Sounding data

Resumen del trabajo presentado en el 19th International Symposium on Deep Seismic Profiling of the Continents and their Margins (SEISMIX 2020), celebrado del 15 al 19 de marzo de 2020 en Australia
Research Guides: TCC Votes: Voter Registration

Information about how to register to vote, what's on the ballot, eligibility, ID requirements, and more. How to register to vote in Texas
Exploring the Factors That Contribute Towards Information Security Policy Compliance Culture

There is over-reliance on information systems to run virtually all aspects of modern institutions.This has put more burden on information security managers to come up with more robust and efficient ways to enhance information security policy compliance.Therefore, despite existing efforts in the area of information security management, there remains a critical need for more research to be done.The existing research has also concentrated on hypothesis testing rather than a qualitative approach.So, there is an existential methodology gap that can give another alternative result that still needs to be covered.That is why we embarked on exploring the factors that influence information security compliance in organizations.The research was conducted in two universities with a diverse population.The research design was exploratory, encompassing qualitative in-depth case interviews with grounded theory as the analysis strategy.A total of 20 interviews were conducted and each analysis was done after every few batches of interviews in line with grounded theory principles.A theoretical model was generated and discussed.Implications for the research were also discussed and recommendations made.The study found individual factors, organizational factors, and external influence to be important factors in strategizing how to increase compliance with policies.The results also showed that practitioners need to factor in a combination of elements in their strategies in order to enhance compliance with information security policies.
Research Guides: TCC Votes: Home

Information about how to register to vote, what's on the ballot, eligibility, ID requirements, and more.
Driver License Field Detection Using Real-Time Deep Networks

We present an automatic system for real-time visual detection and recognition of multiple driver’s license fields using an effective deep YOLOv3 detection network. Driver licenses are essential Photo IDs frequently checked by law enforcement and insurers. Automatic detection and recognition of multiple fields from the license can replace manual key-in and significantly improve workflow. In this paper, we developed an Intelligent Driving License Reading System (IDLRS) addressing the following challenging problems: (1) varying fields and contents from multiple types and versions of driver licenses, (2) varying capturing angles and illuminations from a mobile camera, (3) fast processing for real-world applications. To retain high detection accuracy and versatility, we propose to directly detect multiple field contents in a single shot by adopting and fine-tuning the recent YOLOv3-608 detector, which can detect 11 fields from the new Taiwan driver license with accuracy of 97.5%. Our approach does not rely on text detection or OCR and outperforms them when tested with large viewing angles. To further examine such capability, we perform evaluations in 4 large tilting view configurations (top, bottom, left, right), and achieve accuracies of 93.3%, 90.2%, 97.5%, 94.3%, respectively.
The Chaos-Based Whale Optimization Algorithms Global Optimization

Whale optimization algorithm (WOA) is one of the methods used effectively and efficiently to solve optimization problems in various fields. In the study, 5 different discrete chaotic maps were used in the aim of increasing the efficacy and efficiency of the WOA algorithm. CBWOA 1, CBWOA 2, CBWOA 3 and CBWOA 4 algorithms based on chaotic maps and whale optimization algorithm have been proposed for global optimization. In order to adjust the parameters contained in the WOA, random number sequences from Tinkerbell, Sine, Logistic, Tent and Henon chaotic maps were used. In order to test the accuracy of the developed algorithms and do the performance analysis, six different unimodal and multimodal benchmark functions were used. According to the simulation results, all the chaotic maps used in the study significantly improved the performance of the WOA algorithm.
NAISC-L: An Authoritative Linked Data Interlinking Approach for the Library Domain

A fascinating feature on Linked Data (LD) for libraries, archives and other cultural heritage institutions. Lucy McKenna is in the final year of her PhD in the ADAPT Centre, Trinity College Dublin. The Centre, funded by Science Foundation Ireland, ‘focuses on developing next generation digital technologies that transform how people communicate by helping to analyse, personalise and deliver digital data more effectively for businesses and individuals. ADAPT researchers are based in four leading universities: Trinity College Dublin, Dublin City University, University College Dublin and Dublin Institute of Technology. ADAPT's transformative tools allow you explore video, text, speech and image data in a natural way across languages and devices, helping companies unlock opportunities that exist within digital content to re-imagine how to connect people, process and data to realise new economic value.’ Lucy invites library and information professionals to evaluate an LD interlinking framework that she has developed as part of her research. She is also looking for information professionals who would like to trial the framework locally to create interlinks from their organisation’s LD datasets.
Flexible Learning of Temporal Causal Sequence Relationships from Time-Series

We aim to mine temporal causal sequences that explain observed events (consequents) in time-series traces. Causal explanations of key events in a time-series has applications in design debugging, anomaly detection, planning, root-cause analysis and many more. We make use of decision trees and interval arithmetic to mine sequences that explain defining events in the time-series. We propose modified decision tree construction metrics to handle the non-determinism introduced by the temporal dimension. The mined sequences are expressed in a readable temporal logic language that is easy to interpret. The application of the proposed methodology is illustrated through various examples.