Reviewerly/exHarmony huggingface dataset:
Use of Virtual Reality Platforms in Design and Presentation Processes

Virtual technologies and their potential innovations have developed significantly in recent years.Virtual reality, which is the subject of stories and stories in the field of literature, has been in our lives since the 1950s.It is used in many areas, including our daily life, and has also potential use in new areas.Virtual reality, which is used in the fields of health, tourism, architecture, education, medicine, ecommerce and agriculture, in addition to video and game activities, greatly facilitates human life.The most important of the facilities it provides is the diversity of usage areas and the fact that virtual reality environments provide the closest presentation to the reality.In this study, information was given about virtual reality platforms, tools used and usage sectors.It is aimed to discuss not only leisure time activity, but also a technology that facilitates us in all areas of life and the present and future potential of this technology.
Opportunities for change and Daring Greatly through the prism of Action Research Study

The article deals with the result of the action research study aimed at exploring the impact of the epistemic position of the opportunity for the self-development critical and critical thinking, task-based performance, strategy training and reflection on the academic achievement of PhD students and development of their self-determined scientific-research competence in the educational process on the basis of the Matrix Programme. The participants were 33 PhD first-year students of Abylai khan Kazakh University and World Languages. The data obtained in the action research deepened our understanding of how the incorporation and increase of self-dependent work contribute to the development of PhD students' professional and scientific research competence, keen focus on the strategies and self-evaluation in the framework of cognitive linguacultural paradigm. Qualitatively all the students made a noticeable improvement in the course study. The results obtained confirmed our assumption that the most significant thing is daring greatly for changes and innovations that can provide high quality in FL education.
LibGuides: Personal and Professional Growth: Business Resources

A collection to help you personally and professionally grow A collection of business databases, books and resources
AN ERROR ANALYSIS OF USING COHESIVE DEVICES IN WRITING NARRATIVE TEXT MADE BY ELEVENTH-GRADE STUDENTS OF SMKN 2 SALATIGA IN THE ACADEMIC YEAR 2019/2020

Marisa, Maliyya. 2020. An error analysis of using cohesive devices in writing narrative text made by eleventh-grade students of SMKN 2 salatiga in the academic year 2019/2020. A Graduating Paper English Education Department. Teacher Training and Education Faculty. State Institute for Islamic Studies Salatiga. Conselor: Dr. Setia Rini, M.Pd.This study aims to investigate the error in using grammatical cohesive devices made by the eleventh-grade students of SMKN 2 Salatiga in the academic year 2019/2020 in writing narrative text. The objectives of the study were (1) To know the types of grammatical cohesive devices used by students (2) To know the types of grammatical cohesive devices errors (3) To quantity the error percentage of grammatical cohesive devices made by students in writing narrative text. There were 29 data that had been successfully analyzed by the researcher. The researcher used descriptive qualitative method to analyze students' narrative text. The instrument of this research is test. The researcher applied the theory from Halliday Hasan about cohesion taxonomy (1976) as the basis for conducting data analysis.The result shows that there are 2343 grammatical cohesive devices found in 29 students' narrative text. These grammatical cohesive devices were then sub-categorized as follows: a. Reference (1613) b. Conjunction (664) c. Ellipsis (62) d. Substitution (4).From the overall use of grammatical cohesive devices, there are 163 errors occurred in students’ narrative text, they are errors in ellipsis (40,32%), errors in reference (6,94%), and errors in conjunction (3,91%). These errors then were classified into 4 types of error based on surface strategy taxonomy as follow: Misinformation (65,38%), Omission (17,94%), Addition (14,10%), Misordering (2,56%).Key Words: grammatical cohesive devices; error analysis
Hyperparameter Optimization for Convolutional Neural Networks

Training algorithms for artificial neural networks depend on parameters called the hyperparameters. They can have a strong influence on the trained model but are often chosen manually with trial an ...
Solar Powered Drones: Control algorithm and Albedo map generation

With the strict Paris climate goals, all eyes are set on the development of sustainable solutions that can replace or improve commercial solutions. This thesis revolves around the design and implementation of a subsystem for the creation of a solar powered drone. The goal of the solar powered drone is increasing the flight range of a commercial drone with the addition of photovoltaic (PV) panels. The subsystem designed and implemented in this thesis is split up into two separate systems namely, the control part and the image processing part. The control part revolves around the design, implementation and validation of Maximum Power Point Tracking (MPPT) for the PV panels. The image processing part revolves around the design, implementation and validation of an albedo processing pipeline. For the MPPT, a variable step size perturb and observe algorithm has been implemented with a worse case tracking delay of 40 milliseconds during a change of irradiation from $900 W/m^2$ to $100 W/m^2$ and and more than 99\% power efficiency in steady state conditions. For the albedo pipeline, multiple RAW images are loaded one after another. Vignette correction is applied making the pixel values at the edges and the center of the image compatible with each other. The user can annotate a known reference target that is used to calibrate the albedo generation. Finally, the images are stitched together using Open Drone Map to create a complete albedo map. The results indicate accurate visible band albedo generation, however additional sensors would be needed to obtain wide band albedo generation.
Super-Resolution Using Dynamic Cameras

In digital image correlation, an optical full-ﬁeld analysis method that can determine displacements of an object under load, high-resolution images are preferable. One way to improve the resolution ...
ANALYSIS OF CLOUD COMPUTING BASED BLOCKCHAIN ISSUES AND CHALLENGES

Block chain is the technology that backs up cloud computing and internet of things in most cases such as cryptocurrency. It is often known as a public and decentralized ledger. The blockchain technology stores data in the form of blocks based on its type and data programming, these blocks are linked together, thus, named as blockchain. Some case studies where blockchain has been successfully used such as in the sectors of public health, public safety, smart cities, supply chains etc. but have revealed that blockchain remains at the heart of bitcoin. The compilation does not highlight the issues and challenges of blockchain despite its need. The data is retrieved with corresponding technology of IoT and Cloud Computing. This article discusses the ability of blockchain to facilitate various walks of life other than just banking and finance. The article builds strong foundation for blockchain by acknowledging its abilities and the phenomenal potentials that it holds.
Guides: Tutorials: How to Print Using the Papercut Website

This guide provides tutorials on how to navigate our Pepperdine Libraries website as well as how to use some of Pepperdine Libraries' valuable online resources.
The first five years of kiit journal of library and information management (KJLIM): A bibliometric study

The paper intends to explore patterns of publications of KIIT Journal of Library and Information Management during the period 2014 to 2018. The study analyses year wise distribution of papers, yearly distribution of citations, authorship pattern and degree of collaboration, ranking of authors, geographical distribution of papers, and highly cited papers. The study reveals that, during these 5 years, the journal has published a total number of 85 papers with 1064 citations. Multi-authorship patterns are dominated in the journal. The degree of collaboration among authors is less intensive as it is found to be 0.65. LIS authors from 21 states and union territories of India, and 5 countries across the globe have published their papers in different issues of the first five years of publications of KIIT Journal of Library and Information Management.
SQL Server on Azure Virtual Machine

In Chapter 2 , I described the Azure SQL lineup which includes SQL Server on Azure Virtual Machine (VM). SQL Server on Azure VM represents the primary IaaS deployment option for SQL in Azure.
Human Fall Detection Using Efficient Kernel and Eccentric Approach

Unintentional human falls are a very crucial problem in elderly people. If the fall goes unnoticed or undetected, it can lead to severe injuries and can even lead to death. Detecting falls as early as possible is very important to avoid severe physical injurious and mental trauma. The objective of this paper is to design the fall detection model using data of daily living activities only. In the proposed fall detection model, an eccentric approach with SVM based one-class classification is used. For the pre-processing step, fast fourier transformation has been applied to the data and seven features have been calculated using the preprocessed ADL dataset that has been calculated from the dataset of ADL (activities of daily living) activities acquired from the smartphones. An enhancement of the chi-square kernel-based support vector machine has been proposed here for classifying ADL activities from fall activities. Using the proposed algorithm, 98.81% sensitivity and 98.65% specificity have been achieved. This fall detection model achieved 100% accuracy on the FARSEEING dataset.
Construction of Neurosurgery Knowledge Graph Based on Bi-LSTM-CRF Model

Medical knowledge is complex. The knowledge graph provides an efficient solution for integrating medical knowledge and analyzing medical data. In this paper, the neurosurgery knowledge graph is constructed. First, the ontology pattern library is constructed, and then named entity recognition is performed based on the Bi-LSTM-CRF model. The entities are extracted from the text and the entity relationships are defined. The knowledge graph of the symptom-disease-department is integrated, and finally stored in Neo4j Graph database. As the basis of information retrieval, intelligent question answering, diagnosis and treatment system, knowledge graph can effectively transfer medical knowledge and provide intelligent medical assistance for doctors and patients.
Methodological Aspects of the Financial Stability of Iraq’s Banking System

This article discusses the methodology the Central Bank of Iraq developed to assess the financial stability of commercial banks. This topic is relevant because, in modern economic conditions, the Central Bank of Iraq is forced to tighten requirements to credit institutions. Banks use not only their own funds, but also the funds of the population, legal entities, so they must be reliable and stable. Financial stability directly characterises the reliability of banks, so it must be strictly controlled. The Central Bank of Iraq has created its own methodology for assessing the financial stability of the banking sector. Its use should improve the quality of the created banking system development strategies and the financial monitoring of these strategies’ implementation. The Iraqi banking sector has a high level of capital adequacy, which helps to reduce the likelihood of financial distress in it.
LibGuides: Earth Science: Databases

This Guide is specially created to help earth science faculty and students find the best resources in the library.
Media clips on social fear to regulate individual behavior in temporary involuntary isolation (quarantine)

The objective of the research was to study the manifestation of the emotion of fear in the context of the COVID-19 pandemic and to determine the details of its application in the clips of social networks. As a research method, the authors used the questionnaire survey to collect primary information. The novelty and originality of the study lies in the fact that the phenomenon of social fear in temporary forced isolation is investigated. For the first time, it is discovered that the overall goal of social media videos affecting the emotion of fear is to create a common problem that forces potential viewers to choose self-isolation. It is concluded that the analysis of the clips from social networks revealed four main directions to position the emotion of fear: fear associated with a direct threat to the life activity of individuals; fear caused by unforeseen situations; fear associated with situations that can be harmful to health; fear associated with non-conformity with certain values and norms accepted in society, with the fear of differing from established standards and benchmarks.
The Patient Organism Modeling for Diagnosis with the Usage of a Multi Agent Representation

The main ideas for building a multi-agent model of intelligent modeling for diagnosis are offered.The peculiarities of actions in a certain system of medical environment are indicated.The function of a medical agent is defined, which determines the actions that can be used by a medical agent in response to any sequence of acts of perception of medical data and knowledge.The problem of development of the specification of the problem medical agent is considered.The direction of development of the program of the medical agent is shown.Consider the requirements for the creation of reflex medical agents that respond directly to acts of perception.The requirements for the design of target-based agents are also considered.
Evaluation of the PsyCuraDat-Specification 2.0: Study description of the data referring to the second user study conducted in the BMBF-funded project PsyCuraDat

This research was funded by the Federal Ministry of Education and Research (BMBF), funding code: 16QK08.
Guides: Finding Datasets: Subscription-based Data Sources

Discover datasets for your class project or research Willis Library Subscribed Data Sources
Assessing the studies results in the discipline "Economics"

The article is devoted to the use of multiple choice questions and essay assignments as assessment tools during the economics training. The authors describe three levels of economics understanding. They provide examples of multiple-choice questions and essay assignments that can measure different levels of economics understanding. The authors conclude that multiple-choice questions can be used to measure some but not all levels of student understanding while higher levels cannot be accurately measured with this assessment tool. The essay has great potential to assess the higher levels of student understanding of economics.
Information Needs of Teachers in Second Cycle Institutions in Ghana: A Case of the Lower-Manya Krobo Municipality

This paper seeks to examine the information needs of teachers in second cycle institutions in the Lower Manya Krobo Municipality in Ghana. It adopted the mixed method approach with a population of three hundred and three (303). Questionnaire and interview guide were used to collect data for the study. The quantitative data was analysed using IBM SPSS Version 22.0 and the qualitative data was also analysed thematically. The study discovered that second cycle institution teachers need information for teaching, learning and for research. Also, teachers rely on information from several sources to plan their lessons, write their teaching notes and update themselves on the subject matter of what they teach. Considering the role teachers play in the lives of students and the community as a whole, they need relevant information which must be timely, accurate and reliable. Therefore, the government, Ministry of Education (MOE), Ghana Education Service (GES), Heads of second cycle schools, and all Stakeholders are to ensure that proper information as well as information sources are made available to them to make the process of imparting knowledge more efficient.
The Future of Mixed Reality Interactions

The vision of always-on Mixed Reality interfaces that can be used in a continuous fashion for an entire day, depends on solving many difficult problems including display technology, comfort, computing power, batteries, localization, tracking, and spatial understanding. However, solving all those will not bring us to a truly useful experience unless we also solve the fundamental problem of how to effectively interact in Mixed Reality (MR). I believe that the solution to the MR interaction problem requires that we combine the approaches from interaction design, perceptual science, and machine learning, to yield truly novel and effective MR input and interactions. Such interfaces will need to be adaptive to the user context, believable, and computational in nature. We are at the exciting point in the technology development curve where there are still few universally accepted standards for MR input, which leaves a ton of opportunities for both researchers and practitioners.
LibGuides: Education and Training: Finding Articles

Our Education and Training guide can help you find ways to manage your classroom, learn skills for online and face to face instruction, and with resources that focus on STEAM in Early Childhood Education, reading comprehension, and math concepts.
Link inference of noisy delay-coupled networks: Machine learning and opto-electronic experimental tests.

We devise a machine learning technique to solve the general problem of inferring network links that have time-delays. The goal is to do this purely from time-series data of the network nodal states. This task has applications in fields ranging from applied physics and engineering to neuroscience and biology. To achieve this, we first train a type of machine learning system known as reservoir computing to mimic the dynamics of the unknown network. We formulate and test a technique that uses the trained parameters of the reservoir system output layer to deduce an estimate of the unknown network structure. Our technique, by its nature, is non-invasive, but is motivated by the widely-used invasive network inference method whereby the responses to active perturbations applied to the network are observed and employed to infer network links (e.g., knocking down genes to infer gene regulatory networks). We test this technique on experimental and simulated data from delay-coupled opto-electronic oscillator networks. We show that the technique often yields very good results particularly if the system does not exhibit synchrony. We also find that the presence of dynamical noise can strikingly enhance the accuracy and ability of our technique, especially in networks that exhibit synchrony.
Reversi Game in Facebook Chatbot

Supervisor: Dr. Tan, Chee Wei; First Reader: Dr. Chan, Antoni Bert; Second Reader: Prof. Wang, Jianping
Short-term Power Load Forecasting Based on Machine Learning

Short-term power load forecasting is an important part of power system management.It is the premise of network structure planing, electricity tradingand load scheduling. The accuracy of power load ...
LibGuides: Education and Training: Finding Books

Our Education and Training guide can help you find ways to manage your classroom, learn skills for online and face to face instruction, and with resources that focus on STEAM in Early Childhood Education, reading comprehension, and math concepts.
Application of Human Body Recognition Technology in Scientific Research Sites

Abstract In schools and various scientific research institutes, there are a lot of confidential places, such places usually have a person in charge of the management of the scientific research platform. It is an effective method to detect people entering the secret place by video surveillance and give early warning and warning to outsiders. In the video monitoring in normal use, the recognition method of human body is a kind of dynamic pattern recognition, in order to be able to quickly form to the variety of the human body for effective identification, this paper uses the fuzzy clustering method to filter the static image elements in the video image, in view of the dynamic pixel area, by using convolutional neural network to identify the human form, improve the system recognition robustness for optimized recognition effect.
Information Flow

Access control and information flow are the two building blocks in the design of secure software. Of the two, access control seems ubiquitous, being widely used in operating systems, databases, firewalls, servers, web applications, and so on. The successes of information flow seem less obvious, and its benefits and potential underappreciated. Yet, when it comes to defending against malicious code, access control based defenses have proved susceptible to evasion, or they end up being so restrictive as to interfere with legitimate use. In this talk, I will argue that defenses based on information flow can be more discerning, as they utilize not only the operations performed but also their context, e.g., whether malicious actors could be exerting control over these operation or their key arguments. I will then describe successful applications of information flow to defend against every stage of a cyber attack campaign, including: (a) exploit mitigation for a wide range of software vulnerabilities, (b) malware containment across diverse OSes, including Linux, BSD, and Windows XP through Windows 10, and (c) attack campaign reconstruction, where we achieve a five to six orders of magnitude data reduction by applying our techniques.
Development Of The IPS Learning Module Using A Mind Mapping Approach For Class IV Elementary School Student

DEVELOPMENT OF INDONESIAN LANGUAGE LEARNING MODULE BASED ON CONTEXTUAL LEARNING IN CLASS IVSD NEGERI 03 ALAI PADANGJ.E. Regita Hasri Pertiwi¹, Wirnita¹, Hidayati Azkiya¹Elementary School Teacher Education Study ProgramFaculty of Teacher And EducationBung Hatta Universitye-mail : j.e.regitaa@gmail.comABSTRACTThis research aims to produce contextual-based Indonesian language learning modules in grade IV of SD Negeri 03 Alai Padang that meet valid criteria. This type of research is research and development. The research model used is a 4D development model that is define, design, develop, and disseminate, but because of the National Disaster (Covid-19) then in accordance with circular letter number 3494/UM-1/KP/VI-2020 this research is only done with 3 stages namely define, design, and develop (development). Research instruments in the form of validation sheets. Contextual-based Indonesian language learning module is validated by 2 lecturers/experts consisting of 1 language/material expert and 1 design expert. The results of the development of contextual-based Indonesian language learning modules in grade IV meet very valid criteria with an assessment percentage of 97.14% of the material/language aspect and 88.33% of the design aspect with valid criteria so that it is obtained an average percentage of 92.74% with very valid criteria. Thus, it can be concluded that contextual-based Indonesian language learning module can be used in Indonesian language learning in grade IV Elementary School as teaching material for learning independently at home and in school.Keywords: Indonesian language learning module, contextual
Autonomous landing of multicopters on mobile platforms : Design of an autonomous landing solution for multicopters on mobile platforms, based on a ultrasonic local positionning technology

This work studies the use of an ultrasonic 3D positioning system in multicopter landing applications. Its aim is to develop a solution for autonomous landing of rotary wings systems on mobile platf ...