Application Strategies of Virtual Reality Technology in the Teaching Design of Vocational Courses from the Perspective of Learning Transfer Theory

With the rapid development of virtual reality technology,it has been widely used in the field of education.It can promote the development of learning transfer,which is an effective method for learners to learn effectively.Therefore,this paper describes how to use virtual reality technology to achieve learning transfer in order to achieve teaching goals and improve learning efficiency.

Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

Cervical Cancer Prediction Empowered with Federated Machine Learning

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

Towards Automated Assessment of Learning Management Systems in Higher Education Institutions in Zambia

Zambia like any other country in most African regions is still grappling with the dynamics of harnessing technology for the betterment of Higher Education. The onset of the Covid 19 pandemic brought a test for the preparedness of the Zambian Higher Education Institutions (HEIs) in harnessing technology for pedagogical activities. As countries worldwide switched to electronic learning during the pandemic, the same could not be said for Zambian HEIs. Zambian HEIs struggled to conduct pedagogical activities on learning management platforms. This study investigated the factors affecting the implementation and assessment of learning Management systems in Zambia’s HEIs. With its focus on assessing: 1) system features, 2) compliance with regulatory standards, 3) quality of service and 4) technology acceptance as the four key assessment areas of an LMS, this article proposed a model for assessing learning management systems in Zambian HEIs. To test the proposed model, a software tool was also developed.

Deep Learning Recognition for Arabic Alphabet Sign Language RGB Dataset

This paper introduces a Convolutional Neural Network (CNN) model for Arabic Sign Language (AASL) recognition, using the AASL dataset. Recognizing the fundamental importance of communication for the hearing-impaired, especially within the Arabic-speaking deaf community, the study emphasizes the critical role of sign language recognition systems. The proposed methodology achieves outstanding accuracy, with the CNN model reaching 99.9% accuracy on the training set and a validation accuracy of 97.4%. This study not only establishes a high-accuracy AASL recognition model but also provides insights into effective dropout strategies. The achieved high accuracy rates position the proposed model as a significant advancement in the field, holding promise for improved communication accessibility for the Arabic-speaking deaf community.

CTCL范式下学习兴趣提升学生音乐核心素养的实证研究

我国素质教育已进入全面推进阶段,培养适应全球经济和社会发展需要的、具有创新精神和文化素养的高素质人才是时代所需,而音乐教育在培养人的审美能力与人文素养中发挥着独特而重要的作用.以小学5年级学生为研究对象,采用定量和定性相结合的方法,对CTCL范式下激发学生学习兴趣以提升他们的音乐核心素养进行了实证研究.结果表明:CTCL范式教学运用多种教育技术手段调节学习者和学习内容的关系,并对教学内容进行了个性化的设计,激发了学习者的学习兴趣,能够有效提升学习者对音乐的审美感知能力、艺术表现能力、创意实践能力和文化理解能力,为培养学生的个人修养、审美格调、社会关爱和家国情怀奠定了基础.

YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

Privacy and trust are significant issues in intelligent transportation systems(ITS).Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels,optical fiber,and blockchain technology.The Internet of Things(IoT)is a network of connected,interconnected gadgets.Privacy issues occasionally arise due to the amount of data generated.However,they have been primarily addressed by blockchain and smart contract technology.While there are still security issues with smart contracts,primarily due to the complexity of writing the code,there are still many challenges to consider when designing blockchain designs for the IoT environment.This study uses traditional blockchain technology with the“You Only Look Once”(YOLO)object detection method to accurately locate and identify license plates.While YOLO and blockchain technologies used for intelligent vehicle license plate recognition are promising,they have received limited research attention.Real-time object identification and recognition would be possible by combining a cutting-edge object detection technique with a regional convolutional neural network(RCNN)built with the tensor flow core open source libraries.This method works reasonably well for identifying any license plate.The Automatic License Plate Recognition(ALPR)approach delivered outstanding results in various datasets.First,with a recognition rate of 96.2%,our system(UFPR-ALPR)surpassed the previously used technology,consisting of 4500 frames and around 150 films.Second,a deep learning algorithm was trained to recognize images of license plate numbers using the UFPR-ALPR dataset.Third,the license plate’s characters were complicated for standard methods to identify because of the shifting lighting correctly.The proposed model,however,produced beneficial outcomes.

Using the Technology Acceptance Model to Analyze the Learning Outcome of Open Education Resources

Along with the development of information and communications technology,open educational resources were widely applied in training usage.The use of these resources facilitates the access to knowledge by enabling learners to transcend time and space.In this way,learners are able to obtain new knowledge more actively and efficiently than before.Using Technology Acceptance Model(TAM)as the theoretical foundation,this study aims to explore the learning outcome of using open educational resources with the perceived convenience as the external variable.In this study,the open educational resources were defined as online courses on the Open Course Ware(OCW)and Massive Open Online Courses(MOOCs),on which the learners choose courses themselves and study without the impact from people,matters,time,space,and things with the help of the Internet.To achieve the objectives of the study,the researchers conducted a survey with the participants who had already used the open educational resources.In total,124 valid samples were collected.The Partial Least Squares(PLS)statistical method was used to carry out the analysis.Overall,the model of this study has good prediction and explanatory power.After the data analysis,the study found that the perceived convenience exerts a positive impact on the use of the open educational resources.In addition,among the four TAM variables,the perceived usefulness does not exert a significant impact on the behavioral intention to use,but the other three TAM variables all have a significant impact on the behavioral intention.

Learning Mathematics Online Using Information Technology Tools during COVID-19 in Kosove

The COVID-19 pandemic has brought significant challenges to higher education worldwide. Due to the COVID-19 pandemic, e-learning has begun to be widely used and applied in the teaching and learning processes. However, learning under technological circumstances has proven not always to be a proper solution in education. A highlight challenge, in this regard, is considered to be learning Mathematics online. While some support its positive impact, others greatly oppose it by arguing that neither teaching nor learning has proven successful. Thus, this study examines Kosovo selected universities to see the effectiveness of learning Mathematics online as a case study. Further, it compares the online and traditional learning methods and explores how teachers in higher education in Kosova Universities apply and integrate technology into learning mathematics. This study employed a methodology encompassing questionnaires for students. The results show that students are not overall satisfied with learning Mathematics online leading to the conclusion that online learning is not an effective educational method for learning Mathematics.

Research on the Teaching Design of Learning Situations in Information Technology Course in Middle Schools

The research on Information Technology in middle schools is a very important course.The arrangement and explanation of the course and the application of some teaching methods to promote the research of Information Technology are an integral part of education.Based on this,this article mainly explains the meaning and importance of learning situations,and how to create learning situations in the teaching of Information Technology in middle schools for related staff.

Application of Multimedia and Internet Technology in Learning Mould Design

With the use of multimedia which combines the use o f text, sound, images, motion video and animation, it is more efficient for studen ts to learn mould design interactively. A program is created using several multi media software to simulate the mechanism of moulding processes in order to let s tudents understand the concept of mould design. In addition, students can even access the program through the Internet. Therefore, the software is defined as Multimedia and Internet Technology (MIT) program. The MIT program consists of four sections: (i) simulation of mould mechanisms, ( ii) cooling system, (iii) material information and (iv) games for tutorials. Sec tion One covers the basic operations of different types of moulds such as two-p late mould, three-plate mould, split mould, side-core mould and mould with und ercuts. Section Two introduces different types of cooling systems such as bubble r, baffle, cooling circuits, etc. Section Three provides some useful material in formation for mould design. Section Four contains games of matching mould compon ents, mould design problem finding and multiple choice questions to test student s how much they understand mould design concept. Multimedia is highly effective particularly in teaching and learning. It changes the nature of learning itself. It makes reading dynamic by giving words an impo rtant new dimension. It allows students to see, hear and do simultaneously, thus significantly reducing average learning time. Furthermore, through cooperative learning on Internet, students can access the program, share data or search info rmation anytime anywhere. Therefore, Multimedia and Internet Technology is one o f the vital aspects to speed up the realization of information age in society.

FullChinese at MIT:A Non-Disruptive Integration of Technology for Intermediate Students

We describe here ten years of development of a Chinese learning technology and five years of practical experience in integrating this technology in MIT classrooms for intermediate-high and advanced-low students.Key results are as follows:There is no need to disrupt the classroom experience(both for the teacher and the students);Technology provides a sharp increase in learning efficiency and motivation,as confirmed by students;and This overall improvement in learning is achieved by focusing on the efficiency of personal study time.The most salient type of feedback from students falls into two categories:“I wouldn’t have been able to take a class at that level without FullChinese,”and“The use of technology allowed me to prepare for class two to three times faster.”Results were achieved through a slow iterative process during which our learning technology evolved to solve observed needs in acquiring complex new material.

Fostering Language Learning Autonomy via the Computer Technology in Tertiary Education

This paper will begin by discussing the concept of learning autonomy.What follows is the rationale why learning autonomy is needed in language learning.It then will focus on the ways in which computer technology can foster language learning autonomy by checking different aspects of computer technology against the criteria that characterize leaning autonomy,followed by the analysis why this is possible in tertiary education.The conclusion of this paper will be some considerations of fostering learning autonomy via the computer technology.

Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human beings.In the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital applications.The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 environment.The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification.Primarily,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based encryption.The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images.The secret images,encrypted by signcryption technique,are embedded into cover images.Besides,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax classifier.The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication.The proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects.The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.

Leveraging Geospatial Technology for Smallholder Farmer Credit Scoring

According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food consumed there;their farming activities are therefore critical to the economies of their countries and to the global food security. However, these farmers face the challenges of limited access to credit, often due to the fact that many of them farm on unregistered land that cannot be offered as collateral to lending institutions;but even when they are on registered land, the fear of losing such land that they should default on loan payments often prevents them from applying for farm credit;and even if they apply, they still get disadvantaged by low credit scores (a measure of creditworthiness). The result is that they are often unable to use optimal farm inputs such as fertilizer and good seeds among others. This depresses their yields, and in turn, has negative implications for the food security in their communities, and in the world, hence making it difficult for the UN to achieve its sustainable goal no.2 (no hunger). This study aimed to demonstrate how geospatial technology can be used to leverage farm credit scoring for the benefit of smallholder farmers. A survey was conducted within the study area to identify the smallholder farms and farmers. A sample of surveyed farmers was then subjected to credit scoring by machine learning. In the first instance, the traditional financial data approach was used and the results showed that over 40% of the farmers could not qualify for credit. When non-financial geospatial data, i.e. Normalized Difference Vegetation Index (NDVI) was introduced into the scoring model, the number of farmers not qualifying for credit reduced significantly to 24%. It is concluded that the introduction of the NDVI variable into the traditional scoring model could improve significantly the smallholder farmers’ chances of accessing credit, thus enabling such a farmer to be better evaluated for credit on the basis of the health of their crop, rather than on a traditional form of collateral.