scholarly journals Wearable xAI: A Knowledge-Based Federated Learning Framework

2021 ◽  
Vol 6 (1) ◽  
pp. 79
Author(s):  
Sara Nasiri ◽  
Iman Nasiri ◽  
Kristof Van Laerhoven
Keyword(s):  
Training Model ◽  
Heterogeneous Data ◽  
Case Based Reasoning ◽  
Training Process ◽  
Learning Framework ◽  
Knowledge Based ◽  
Private Data ◽  
User Acceptability ◽  
And Training ◽  
Past Conditions

Federated learning is a knowledge transmission and training process that occurs in turn between user models on edge devices and the training model in the central server. Due to privacy policies and concerns and heterogeneous data, this is a widespread requirement in federated learning applications. In this work, we use knowledge-based methods, and in particular case-based reasoning (CBR), to develop a wearable, explainable artificial intelligence (xAI) framework. CBR is a problem-solving AI approach for knowledge representation and manipulation, which considers successful solutions of past conditions that are likely to serve as candidate solutions for a requested problem. It enables federated learning when each user owns not only his/her private data, but also uniquely designed cases. New generated cases can be compared to the knowledge base and the recommendations enable the user to communicate better with the whole system. It improves users’ task performance and increases user acceptability when they need explanations to understand why and how AI algorithms arrive at these optimal solutions.

scholarly journals Education/Training of Cultural Neuropsychology at the Postdoctoral Residency Level: Integration of a Competency-Based Model into Practice

2019 ◽  
Vol 34 (7) ◽  
pp. 1295-1295
Author(s):  
G Berrios-Siervo ◽  
C Salinas ◽  
J Janusz
Keyword(s):  
Training Model ◽  
Education And Training ◽  
Clinical Neuropsychology ◽  
Knowledge Based ◽  
Basic Competencies ◽  
Competency Based ◽  
Education Training ◽  
Barriers And Challenges ◽  
Research And Education ◽  
And Training

Abstract Objective In recent years, much attention has been focused on the delineation of basic competencies for education and training in clinical neuropsychology. Simultaneously, neuropsychology as a field has recognized the increasing need for the inclusion of cultural neuropsychology practices (AACN Relevance 2050). Method The Clinical Neuropsychology Synarchy (CNS) released a taxonomy for education and training in clinical neuropsychology in 2017, with individual and cultural diversity identified as an essential foundational competency across all specialties. Recommendations from the Education/Training workgroup of the 2017 Cultural Neuropsychology Summit provide initial guidance regarding the training of directors for the inclusion of cultural neuropsychology across the professional lifespan: including clinical, research, and education/training. Based on these recommendations, our program has developed a post-doctoral residency track focused on bilingual/multicultural neuropsychology. Outcomes The process by which our program integrates specific, knowledge-based, and applied competencies in cultural neuropsychology is presented. Discussion Suggestions on how to integrate recommendations into the existing education/training model for postdoctoral residency are provided, as well as a discussion of barriers and challenges in creating such a program.

scholarly journals Personalized Federated Learning with Semisupervised Distillation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xianxian Li ◽  
Yanxia Gong ◽  
Yuan Liang ◽  
Li-e Wang
Keyword(s):  
Model Performance ◽  
Personal Data ◽  
Training Model ◽  
Heterogeneous Data ◽  
Global Model ◽  
Model Parameters ◽  
Quality Model ◽  
Learning Framework ◽  
Class Distribution ◽  
Adaptive Aggregation

Heterogeneous data and models pose critical challenges for federated learning. However, the traditional federated learning framework, which trains the global model by transferring model parameters, has major limitations; it requires that all participants have the same training model architectures, and the trained global model does not guarantee accurate projections for participants’ personal data. To solve this problem, we propose a new federal framework named personalized federated learning with semisupervised distillation (pFedSD), which ensures the privacy of the participants’ model architectures and improves the communication efficiency by transmitting the model’s predicted class distribution rather than model parameters. First, the server adopts the adaptive aggregation method to reduce the weight of low-quality model predictions for the model’s predicted class distributions uploaded by all clients, which helps to improve the quality of the aggregation of the prediction class distribution. Then, the server sends it back to the clients for local training to obtain the personalized model. We finally conducted experiments on different datasets (MNIST, FMNIST, and CIFAR10), and the results show that the model performance of pFedSD exceeds the latest federated distillation algorithms.

scholarly journals Training model for online nurse educators

2019 ◽  
Vol 9 (6) ◽  
pp. 82
Author(s):  
Mary Jo Stanley ◽  
Carolyn Martin
Keyword(s):  
Nursing Education ◽  
Online Education ◽  
Best Practice ◽  
Nurse Educators ◽  
Online Training ◽  
Training Model ◽  
Nurse Educator ◽  
Training Process ◽  
Online Pedagogy ◽  
And Training

Background and objective: Online instruction is very different from teaching in a face-to-face setting and educators may lack formal pedagogical training specific to online instruction; in addition, online instructors may feel isolated and have less access to direct support than their counterparts on campus. The objective of this study was to promote best practice in online education through faculty support and professional development; a structured online training process was created.Methods: Design: Instructors that teach in the online venue need teaching and training to feel comfortable with the technology and online pedagogy strategies that support best practice in online education. A structured training process was created to support novice online educators. Setting: Nursing faculty and Masters of Science in Nursing education track students co-taught one online class together. Participants: Faculty and senior level Masters of Science in Nursing education track students were asked to reflect on their one-year teaching and training experience as educators. Methods: Qualitative analysis using Denzin’s interpretive interactionism was used to elicit meaning from participant experiences.Results: Four themes emerged from the data; online pedagogy, knowledge acquisition, mentor-mentee role, and online nurse educator. These themes align with the scholarship of teaching, discovery, application, and integration, respectively. The Training Model for Online Nurse Educators was developed to show this relationship.Conclusions: Using Boyer’s model of scholarship as a framework for online training can prepare instructors for the online nurse educator role. Online instructional delivery is a mainstay in education necessitating nurse educators who are prepared to apply best practice strategies in online education.

The Research of the Training Model of Engineering Application Talents

2012 ◽  
Vol 268-270 ◽  
pp. 2001-2007
Author(s):  
Da Qi Xu ◽  
Shu Kai Cai
Keyword(s):  
Social Factors ◽  
Engineering Application ◽  
Training Model ◽  
Training Process ◽  
The Social ◽  
Training Quality ◽  
Process Factors ◽  
And Training ◽  
Logic Relationship

The development of economic society and the progress of technology call for a large number of engineering application talents. Allowing for the current situation of the training of engineering application talents, the thesis has made an analysis of the social factors and training process factors, brought forth foci of improving the training quality of engineering application talents, and the training model of engineering application talents. In addition, internal logic relationship between all the factors about the training of talents has been explored, which is beneficial to the reform of personnel training pattern in local engineering colleges, in training high quality engineering application talents to meet the demands of society.

Privacy-preserving Collaborative Training for Medical Image Analysis Based on Multi-Blockchain

2020 ◽  
Vol 23 ◽  
Author(s):  
Wanlu Zhang ◽  
Qigang Wang ◽  
Mei Li
Keyword(s):  
Medical Image ◽  
Data Privacy ◽  
Medical Image Analysis ◽  
Auxiliary Information ◽  
Training Process ◽  
Private Data ◽  
Medical Institutions ◽  
Model Training ◽  
Collaborative Training ◽  
Similar Task

Background: As artificial intelligence and big data analysis develop rapidly, data privacy, especially patient medical data privacy, is getting more and more attention. Objective: To strengthen the protection of private data while ensuring the model training process, this article introduces a multi-Blockchain-based decentralized collaborative machine learning training method for medical image analysis. In this way, researchers from different medical institutions are able to collaborate to train models without exchanging sensitive patient data. Method: Partial parameter update method is applied to prevent indirect privacy leakage during model propagation. With the peer-to-peer communication in the multi-Blockchain system, a machine learning task can leverage auxiliary information from another similar task in another Blockchain. In addition, after the collaborative training process, personalized models of different medical institutions will be trained. Results: The experimental results show that our method achieves similar performance with the centralized model-training method by collecting data sets of all participants and prevents private data leakage at the same time. Transferring auxiliary information from similar task on another Blockchain has also been proven to effectively accelerate model convergence and improve model accuracy, especially in the scenario of absence of data. Personalization training process further improves model performance. Conclusion: Our approach can effectively help researchers from different organizations to achieve collaborative training without disclosing their private data.

Innovative Techniques and Strategies of Skill Building for Human Resource Development in SMEs, India

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
Arti Awasthi
Keyword(s):  
Human Capital ◽  
Human Resource Development ◽  
Skill Development ◽  
Education And Training ◽  
Global Competitiveness ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
Key Factor ◽  
Skill Building ◽  
And Training

India has gradually evolved as knowledge based economy due to the abundance of capable, flexible and qualified human capital. With the constantly rising influence of globalization, India has immense opportunities to establish its distinctive position in the world. However, there is a need to further develop and empower the human capital to ensure the nations global competitiveness. Despite the empathetic stress laid on education and training in this country, there is still a shortage of skilled manpower to address the mounting needs and demands of the economy. Skill building can be viewed as an instrument to improve the effectiveness and contribution of labor to the overall production. It is as an important ingredient to push the production possibility frontier outward and to take growth rate of the economy to a higher trajectory. This paper focuses on skill development in Small and Medium Enterprise (SMEs) which contribute nearly 8 percent of the country's GDP, 45 percent of the manufacturing output and 40 percent of the exports. They provide the largest share of employment after agriculture. They are the nurseries for entrepreneurship and innovation. SMEs have been established in almost all-major sectors in the Indian industry. The main assets for any firm, especially small and medium sized enterprises are their human capital. This is even more important in the knowledge based economy, where intangible factors and services are of growing importance. The rapid obsolescence of knowledge is a key factor of the knowledge economy. However, we also know that for a small business it is very difficult to engage staff in education and training in order to update and upgrade their skills within continuous learning approach. Therefore there is a need to innovate new techniques and strategies of skill development to develop human capital in SME's.

AUTOMATION OF THE DEAN'S OFFICE FUNCTIONS IN ELECTRONIC INFORMATION-EDUCATIONAL ENVIRONMENT OF THE SOUTHWEST STATE UNIVERSITY

2017 ◽  
Vol 21 (6) ◽  
pp. 44-50 ◽  
Author(s):  
E. I. Anikina ◽  
A. S. Babkov ◽  
A. V. Malyshev
Keyword(s):  
Educational Environment ◽  
Federal State ◽  
Educational Standards ◽  
State University ◽  
Web Portal ◽  
Training Process ◽  
Electronic Information ◽  
State Educational ◽  
The University ◽  
And Training

Russian Federal State Educational Standards of 3+ generation impose serious requirements to resource support of educational and training process, including electronic information-educational environment of the University. In the Southwest State University (SWSU), a unified multimedia information and educational environment based on Internet-broadband access technologies was created; it successfully operates and keeps developing. The main concept of this environment construction is the idea of integrating data, applications, and business processes. SWSU Electronic information-educational environment (EIEE) is designed to provide information transparency of the University activities in accordance with the requirements of the current legislation of the Russian Federation in the sphere of education, to organize educational activities of the University and to ensure access of students and research and academic-staff of the University to information and educational resources. The main components of SWSU EIEE are: the actors of the education and training process (teachers, students, etc.), external digital library systems, internal automated information library system, “SWSU academic courses” subsystem, “Southwest State University Web portal” subsystem, and the official web site of the Southwest State University. “Southwest State University Web portal" subsystem makes it possible to automate traditional basic functions of Dean's office of the University, such as managing student conduct systems for students of Bachelor and Master Degree Programs of full-time and correspondence forms of training; recording and statistical processing of the data on students’ progress; recording students’ achievements; managing Dean's office workflow. As prescribed in Federal State Educational Standards of 3+ generation, Portal Modules are used to record the results of formative and summative assessment of students in accordance with SWSU current score rating system for learning outcomes.

scholarly journals Digital Tools as an Enabler for Educational and Training Processes: The Case Study of REFUGEEClassAssistance4 Teachers Project

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 14
Author(s):  
Ourania Areta ◽  
Karel Van Isacker
Keyword(s):  
Social Interactions ◽  
Education And Training ◽  
Working Environment ◽  
Digital Tools ◽  
Training Process ◽  
Training Activities ◽  
And Training

Digitalization has transformed all aspects of life, from social interactions to the working environment and education, something that accelerated with the emergence of COVID-19. The same stands for education and training activities, where the use of digital tools has been gradually advancing and become merely online because of the virus. This brought forth the need to discuss further the applications, benefits, and challenges of digital tools within the framework of the education and training process, and the need to study examples of successful applications. This study aims to support both these requirements by presenting the case study of REFUGEEClassAssistance4Teachers project and its outcomes.

Sign in / Sign up

Export Citation Format

Share Document