Reviewerly/exHarmony huggingface dataset:
Virtual Learning Assessment: Practical Strategies for Instructors in Higher Education

Many universities have been designing and implementing online instruction for years, but the COVID-19 pandemic created an unexpected impetus for the expansion of virtual learning. Instructors and students who may not have previously chosen or experienced online instruction found themselves in need of safe, virtual options, and it appears that the general shift to virtual learning is here to stay. Strong, reliable assessment is a major component of virtual instruction, and instructors have several options for structuring student feedback. This article reviews the relevant literature regarding effective online assessment techniques and makes recommendations for the use of examinations and more authentic assessments, including video demonstrations, group projects, and discussion forums. Various data analytics within Learning Management Systems (LMS) are also explored. Discussion includes implications of online assessment and avenues for important research to strengthen response to this growing need. Keywords: virtual learning, virtual instruction, higher education institutions, online assessment
On the Conceptualization of Elastic Service Evaluation in Cloud Computing

Cloud computing is becoming an urgent technology in the enterprises. One key characteristic in the cloud computing is the elasticity. Then, it is urgent for the users how to rank the renting services reasonably. Considering the main features of the elasticity, this article gives classification on resource optimization. However, one of the major challenges is how to optimize resource allocation in an elastic manner. Due to the special pay-as-you-go manner, resource optimizing strategies are associated with the goal of minimizing the costs on the premise of service-level-agreement (SLA). Another challenge of resource optimizing strategies is to how to dynamically respond to the application demands. In this paper, the authors sketch the elastic definition more clearly. Secondly, different dimensions are described on elastic resource allocations. Thirdly, it is important to seek out the proper resource allocation strategy. Finally, the challenges and conclusions are discussed in this article.
Semantic genetic programming

tutorial Share on Semantic genetic programming Authors: Alberto Moraglio University of Exeter, Exeter, UK University of Exeter, Exeter, UKView Profile , Krzysztof Krawiec Poznan University of Technology, Poznan, Poland Poznan University of Technology, Poznan, PolandView Profile Authors Info & Claims GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2019 Pages 1032–1055https://doi.org/10.1145/3319619.3323378Published:13 July 2019Publication History 0citation50DownloadsMetricsTotal Citations0Total Downloads50Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Effective Resource Allocation, Millennium and Sustainable Development Goals in Nigeria

This study identifies the challenges of Millennium Development Goals (MDGs) attainment in Nigeria, analyses the Sustainable Development Goals (SDGs) enabling conditions and examines measures for attaining SGD-poverty eradication goal in the country.The study presents Cocoon Prototype research design method and employs descriptive analytical technique to carry out the research objectives of the study.Likerttype scaling structured questionnaire research instrument was applied for data collection from 300 respondents, randomly selected.The result of the study discovered government's priority on SDGs enabling conditions as panacea for attaining SDG poverty eradication goal in Nigeria.The study concluded further that reformation of failed programmes and abandoned projects has significant positive impact on achieving SGDs in Nigeria.The study therefore suggested that in order to achieve the SGD poverty eradication goal by 2030 in Nigeria, the government should ensure adequate provision of formidable enabling conditions as well as restructuring abandoned projects in her resources allocation policy implementation.
eSticky–An Advanced Remote Reminder System for People with Early Dementia

While the European population is aging, the number of people with dementia is dramatically rising. With this comes an increased need for products that help affected people to be more independent and able to live in their own home for as long as possible. ESticky addresses this need by providing a sophisticated reminder system that replaces the old-fashioned sticky-notes by electronic versions thereof, which can be programmed from near and far in a device-independent manner via the internet and using a standard web browser. For this purpose, a set of low-cost ePaper-displays are used, accompanied by a small and unobtrusive base station. The displays can be placed at several strategically useful places in a user’s home, to enable users and/or care persons to place reminders that will, based on the user’s daily routines, most probably be read. Active displays even enable the user to press a confirmation button to show that he or she has actually read the reminder. The system is developed using a user centred design approach, to take all stakeholders’ wishes and needs into account, in order to come up with a system that is easy to use and provides good service to many people.
Maturity in Health Organization Information Systems

Adapting maturity models to healthcare organization's needs is an issue that researchers and technicians should consider and a valuable instrument for IT managers because these models allow the assessment of a present situation as well as the identification of useful improvement measures. This paper discusses the practical utilization of maturity models, including different manners of exploring model's usefulness. For a more complete understanding of maturity models, the selection of criteria and processes of measurement, called metrics, is briefly reviewed in terms of indicators and daily procedures. Some issues of management information systems security are briefly addressed, along with a note on measuring security assessment. Finally some considerations are presented about the need for privacy of personal data to ensure the strategies to be pursued to sensitive data in order to establish a level of effective privacy which is included in the concerns of security of information systems.
Chapter 15: Suppositories and Inserts

PreviousNext No AccessThe Art, Science, and Technology of Pharmaceutical Compounding, 6th EditionChapter 15: Suppositories and Insertshttps://doi.org/10.21019/9781582123578.ch15 SectionsAboutFull TextReferences ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinkedInRedditEmail Abstract: These solid dosage forms are used to administer medicine through the rectum (suppositories) and the vagina or urethra (inserts). They melt, soften, or dissolve in the body cavity. Rectal suppositories are cylindrical or conical and are tapered or pointed at one end. They generally weigh approximately 2 g and are about 1 to 1.5 inches long. Infant rectal suppositories weigh about half as much as adult suppositories. References1. Allen LV Jr. Suppositories. London: Pharmaceutical Press; 2008. Google Scholar, 2. Hidaka N, Suemaru K, Aimoto T, Araka H. Effect of simultaneous insertion of oleaginous base on the absorption and on the anticonvulsant effect of diazepam suppository. Biol Pharm Bull. 2006;29(4):705–8. Crossref, Medline, Google Scholar, 3. Coben LJ, Lieberman HA. Suppositories. In: Lachman L, Lieberman HA, Kanig JL, eds. The Theory and Practice of Industrial Pharmacy. 3rd ed. Philadelphia: Lea and Febiger; 1986:564–88. Google Scholar, PreviousNext Session Activity Recently Viewed Chapter 15: Suppositories and Inserts Loyd V. Allen Recently Searched No search history FiguresReferencesRelatedDetails Published: 17 November 2020eISBN: 1-58212-357-8 Copyright & Permissions© 2020 Loyd V. Allen Jr. All rights reserved© 2020 Loyd V. Allen Jr. All rights reserved Publisher American Pharmacists Association HistoryPublished: 17 November 2020 Citation Information (2020), "Chapter 15: Suppositories and Inserts," The Art, Science, and Technology of Pharmaceutical Compounding, 6th Edition https://doi.org/10.21019/9781582123578.ch15 Loading ...
Learning

The recognition performance, or the degree of consistency of the presented Gestalt operations with human perception, can be improved by introducing some parameters. To this end ground truth is needed on a set of representative images; i.e., Gestalten must be marked on each image that should be found. Not only the data should be representative, but also the set of observers, who do the labeling work. And they need to be instructed properly. Given such labeled data the parameter setting can be improved by supervised machine learning. Examples of parameters are weights corresponding to the different laws in the fusion, a preferred distance for the proximity law, tolerance parameters, etc. In the operations defined in the previous chapters continuous assessment functions are used. Most of these functions are differentiable. Here this property is utilized in order to perform gradient descent optimization on the parameter setting, i.e., learning with each labeled example a little bit. Other possibilities include collecting statistics over features or feature deviations of found positive and negative example Gestalten. Then the parameter setting is similar to estimating parametrized distributions based on empirical statistics.
An IMM-Enabled Adaptive 3D Multi-Object Tracker for Autonomous Driving

3D multi-object tracking (MOT) is a crucial part in the field of autonomous driving. Thanks to the recent advances in deep-learning-based detector, tracking-by-detection paradigm has become popular in 3D MOT, which consists of a front-end object detector and a back-end tracker. However, most existing methods only focus on the performance on particular data sets, ignoring the adaptiveness of the tracking algorithm to dynamically changing driving environment. Based on this, we design an adaptive 3D MOT algorithm, which can adapt its behavior to the complex changing environments in real driving scenarios. The system first utilizes a pre-trained 3D detector to produce the observations (detections) for the current frame. Then, a state estimator based on interacting multiple model (IMM), which takes the statistics of the data set into account and switches its state dynamically, provides the adaptive state estimation for target tracking. Experiments show that our algorithm can improve the performance of single-model-based methods, and adapt its behavior dynamically on nuScenes data set.
Exploration on curriculum reform of "power electronic technology" based on engineering education certification under the background of new engineering

This paper analyzes the current situation and problems in the teaching of "power electronic technology" in our university according to the goal and orientation of talent training in Application-oriented Universities under the background of new engineering. Aiming at the specific objectives of engineering education certification and the requirements of new engineering education for talent cultivation, the teaching reform of power electronic technology course is explored, mainly including theoretical teaching reform and practice teaching reform. Through the exploration of teaching reform of this course, we hope to achieve the goal of engineering education certification, meet the requirements of new engineering education for personnel training, innovate the practical teaching of power electronic technology course, cultivate students’ innovative practice spirit, comprehensively improve students’ engineering practice ability, and cultivate high-level innovative applied engineering talents.
Combining Artificial Intelligence and NetMedicine for Ambient Assisted Living

World population is shifting towards older ages: according to recent estimates there will be 1.5 billion people over 65 years old in 2050. Local governments, international institutions, care organizations and industry are fostering the research community to find solutions to face the unprecedented challenges raised by population ageing. A combination of Artificial Intelligence and NetMedicine could be ideal to face these challenges: they provide the means to develop an intelligent system and simultaneously to distribute it over a network, allowing the communication over the internet, if needed. Hence, the authors present a Multi-Agent Architecture for Ambient Assisted Living (AAL): it is the model for a system to manage a distributed sensor network composed by ambient and biometric sensors. The system should analyse data and pro-actively decide to trigger alarms if anomalies are detected. The authors tested the architecture implementing a prototypical Multi-Agent System (MAS), based on Belief-Desire-Intention (BDI) paradigm: the Virtual Carer.
Study on the Effective Mechanism of Network English Independent Learning Platform Based on Multi Agent of Big Data

Big data and cloud computing are a new computing model, which plays a great role in promoting the education, teaching and colleges and universities in China. The Internet connects various fields, realizes information sharing through the network, and realizes the efficient integration of all kinds of resources. Independent learning in the online environment has been widely used in English education, which is also the basic requirement of English education. The English independent learning platform built by Agent agent is conducive to cultivating students' ability of individualization, unity and cooperation.This paper expounds the characteristics of online English independent learning, then expounds on the construction process of multi-Agent model building, puts forward the advantages of computer network independent learning, and provides a theoretical guarantee and experimental basis for the online English independent learning platform.
Meddoc Drive

Changing a doctor because of lack of satisfaction is a common phenomenon and this brings with it a plethora of problems for the patient. Every doctor would want all the tests to be conducted again and this is where the patient is left with no option but to conduct all the tests again. This is where a potential Medical Document Drive will come into the picture in which the patient will be allotted a unique number, i.e., a P.O number and all the tests and report of the patient will be saved online on a portal. While visiting a new doctor the doctor can check the reports, look at the symptoms and detect the disease without conducting the same tests again. This secure online application will be divided into three modules and those are the patient module, the admin module and the doctor module. The ultimate goal of this research is to create a secure portal that will have all the information of the patients and the admin will control the whole process.
Structure Optimization Method of Power Transformer based on Intelligent Algorithm

The optimal design of power transformer is a nonlinear problem solving process with multi variables, multi constraints and strong coupling. Because the transformer design variables are mostly integer and real discrete variables, they can be summarized as a constrained nonlinear mixed discrete programming problem in mathematics. At the same time, the design process is very complex, and it is impossible to obtain the analytical form of the optimal solution of the objective function. Therefore, the optimal solution of the objective function is obtained only on the premise of satisfying various constraints as much as possible. Taking the optimal design of 110kV power transformer as the actual background, combined with cloud computing big data and intelligent algorithm, this paper establishes the mathematical model of transformer optimal design based on the most basic cost (copper, silicon steel sheet), and processes the target function according to the idea of punishment. The test results show that the transformer optimization can be optimized not only in electromagnetic calculation, but also in structure. The measures to reduce stray loss can make the transformer more energy-saving. At the same time, the method of reducing noise can be considered to make the transformer more environmentally friendly.
Auto Associative Extreme Learning Machine Based Hybrids for Data Imputation

This chapter presents three novel hybrid techniques for data imputation viz., (1) Auto-associative Extreme Learning Machine (AAELM) with Principal Component Analysis (PCA) (PCA-AAELM), (2) Gray system theory (GST) + AAELM with PCA (Gray+PCA-AAELM), (3) AAELM with Evolving Clustering Method (ECM) (ECM-AAELM). Our prime concern is to remove the randomness in AAELM caused by the random weights with the help of ECM and PCA. This chapter also proposes local learning by invoking ECM as a preprocessor for AAELM. The proposed methods are tested on several regression, classification and bank datasets using 10 fold cross validation. The results, in terms of Mean Absolute Percentage Error (MAPE,) are compared with that of K-Means+Multilayer perceptron (MLP) imputation (Ankaiah &amp; Ravi, 2011), K-Medoids+MLP, K-Means+GRNN, K-Medoids+GRNN (Nishanth &amp; Ravi, 2013) PSO_Covariance imputation (Krishna &amp; Ravi, 2013) and ECM-Imputation (Gautam &amp; Ravi, 2014). It is concluded that the proposed methods achieved better imputation in most of the datasets as evidenced by the Wilcoxon signed rank test.
Enriching parallel corpora with multimedia and lexical semantics

In this chapter, I present the main characteristics of the CLUVI Corpus, an open collection of sentence-level aligned parallel corpora with over 44 million words in nine specialised domains (fiction, computing, popular science, biblical texts, law, consumer information, economy, tourism, and film subtitling) and different language combinations including Galician, Spanish, English, French, Portuguese, Catalan, Italian, Basque and Latin. Then, I present the methodology developed for extending the film subtitles section of the CLUVI Corpus with multimedia data. Finally, I discuss the resources and methods used to build the SensoGal Corpus, a SemCor-based English-Galician parallel corpus semantically annotated based on WordNet and aligned at the sentence and word levels.
Inferring Intent and Action from Gaze in Naturalistic Behavior

We constantly move our gaze to gather acute visual information from our environment. Conversely, as originally shown by Yarbus in his seminal work, the elicited gaze patterns hold information over our changing attentional focus while performing a task. Recently, the proliferation of machine learning algorithms has allowed the research community to test the idea of inferring, or even predicting action and intent from gaze behaviour. The on-going miniaturization of gaze tracking technologies toward pervasive wearable solutions allows studying inference also in everyday activities outside research laboratories. This paper scopes the emerging field and reviews studies focusing on the inference of intent and action in naturalistic behaviour. While the task-specific nature of gaze behavior, and the variability in naturalistic setups present challenges, gaze-based inference holds a clear promise for machine-based understanding of human intent and future interactive solutions.
Design Architecture of a Student Co-curricular Activity Management Platform

This paper introduces a design architecture of a co-curricular activity management platform for students. Because of the absence of features in existing learning management platforms to manage co-curricular activities that educational institutions have to offer, these learning management platforms are not fitted to be utilized. One of the essential circumstances for raising qualified and prepared students in this day and age is to guarantee their interest and participation in social activities. In the education aspect, social activities are co-curricular activities earlier known as extracurricular activities, which are components of non-academic curriculum that helps to create different facets of character improvement of students. Quantitative research particularly descriptive research using survey questionnaires and guided interviews, Intensive literature review on published studies and articles, and latest information technology reviews were conducted to come up with an appropriate design architecture to improve student’s engagement in co-curricular activities. Integrating the ideas and insights gathered on the conducted study, a new design architecture for a co-curricular activity management platform was proposed. In order to evolve architecture continually, the new design provided greater flexibility for development teams that decreases development cycle times by allowing them to update modules of the platform independently without affecting the other parts, and also the design responded to the needs of the users, and integrated emerging ICT trends. The tailor fitted design architecture of the platform addressed the specific needs of its end-users, thus providing students more convenient experience and opportunities to engage in co-curricular activities provided by higher educational institutions.
Research On Event-driven Scheduling Model

The existing task scheduling model can perform the scheduling and execution of timed tasks, but due to the problem that it relies on the database to ensure data consistency, there are problems with low model performance and difficulty in expansion. In order to solve the above problems, this article provides a distributed implementation of Quartz Researched on the design idea of the Actor model, added an event-driven controller, and alleviated the problem of low resource utilization and difficult expansion in the current timing task system under distributed deployment. Combining the actual timed task scenario and traditional development process, a high-performance, high-availability, and easy-to-expandable distributed concurrent scheduling model is designed, which decouples the two modules of scheduling and execution, effectively improving the scalability of the scheduling system.
CSCLab

This paper presents a platform to create and manage virtual computing laboratories using Cloud resources. Using this platform a professor can create a customized laboratory according to the class needs. The laboratory is composed of a set of virtual machines that students may use to get access to the necessary computing resources to attend the class. The platform aims at the creation of a solution to avoid proprietary lock in's, and it was designed to be agnostic to the cloud infrastructure. The machines of the lab can be accessed using some remote desktop protocol and managed by non-expert users.
An Application to Continuous Probability Distribution

First part of the paper is the brief description of previous work about estimating one of the distributions developed by smoothing techniques of the histograms and second part of the paper is the application of the distribution.