Construction of Modem Educational Technology Strategies of boutique courses

An attempt study of fine course construction strategy of modern education technology, Starting from the modern education technology professional career goals, while, in curriculum setting, highlights the profession＇ s ＂Normal＂ , and ＂technical＂ and ＂managerial＂ character. And fully reflect the characteristics of higher vocational college and strengthen the ability of students to achieve a to job competency-based, employment-oriented training model. Through the construction of the core curriculum system, cultivating high-quality skilled training objectives Normal talents.

Just in Time Education: Educational Technology for Professional’s Health

Objective: Verify if the educational technology based on Just in Time Education is relevant to Permanent Health Education in Workers’ Health. Method: This study is exploratory and descriptive qualitative research. Were performed semi-structured interviews were carried out with the worker’s health team of a large company from the South of Brazil region. The collected data were carried out in 2021, between January and May, through the virtual environment, with eight participants from the Work Health Team of Eletrosul, located in Florianópolis, who agreed to participate in the research by signing the Free and Informed Consent Term, in accordance with the data saturation criterion. The research was approved by the Ethics Committee (n. 4079133) and the data were submitted to Bardin for thematic content analysis. Result: The results are presented from three categories: 1) Expansion and inclusion in Permanent Education needs;2) Tools adopted in educational processes;3) Just in Time Education: educational technology for workers’ health. Conclusion: The active methodology Just in Time Education helps the processes of Permanent Education in Health, which moved from a face-to-face model to e-learning and required the knowledge renewal in the technology area to maintain efficient communication. This methodology allows quick and accurate access to information from a reliable, adequate, and up-to-date source, causing a positive impact on the qualified and problem-solving work process, in line with the needs of the employer and the company. Therefore, Just in Time Education can provide standardization, organization, and informational and operational quality necessary in this context, in addition to serving as an indicator and data generator (management tool).

Education Technology Cloud Platform Framework Establishment and Security

With more educational business absorbed into information management system at universities, traditional information management platform seems unable to provide efficient service for teaching and research. Some universities then resort to cloud computing platform. In view of the problems existing in the traditional information platform, this study presented an information management framework designed with cloud technology, and introduced the security techniques for its protection.

Biological Communication Behavior through Information Technology Implementation in Learning Accelerated

The Biological Communication Behavior of the Left and the Right Brains have been constructed through the explanation of the phenomena of their specific part activities encompassing: Prefrontal, Frontal, Parietal, Central, Occipital and Parasagital which have been significantly tested in terms of their impacts in learning acceleration starting from Elementary School to University levels. This study is conducted by means of constructive approach and it employs both the quantitative and qualitative techniques. The result of the study shows that the biological communication of the left and the right brains are reliably tested scientifically from the viewpoint of science. The Problem Based Learning start from elementary school to university level of both social and science groups.

The Applied Research on Multimedia Technology in College Teaching

Elaborated the multimedia technologies in the teaching characteristic, definitely multimedia technical superiority at the same time, the union managed by the people university have used the question which in the multimedia technologies appears to propose some improvement method as well as in the multimedia technologies the question which should pay attention in the teaching. Proposed in the modem education media, the teacher reasonably chooses and utilizes the science teaching process through the teaching design which multimedia technical and the traditional teaching method organic synthesis forms, all played to the curriculum and the teaching method reform the positive role. The science uses the multimedia technologies, may avoid the multimedia technologies in classroom instruction application some erroneous zones, the realization teaching effect optimization.

Morphological and molecular evidence for natural hybridization between Sorbus pohuashanensis and S. discolor (Rosaceae)

In overlapping distribution areas of Sorbus pohuashanensis and S.discolor in North China(Mount Tuoliang,Mount Xiling and Mount Baihua),Sorbus indi-viduals were found with pink fruit,which have never been recorded for the flora of China.Fourteen morphological characters combined with four chloroplast DNA markers and internal transcribed spacer(ITS)were used to analyze the origin of the Sorbus individuals with pink fruits and their relationship to S.pohuashanensis and S.discolor.PCA,SDA and one-way(taxon)ANOVA of morphological characters provided convincing evidence of the hybrid ori-gin of Sorbus individuals with pink fruits based on a novel morphological character and many intermediate characters.Haplotype analysis based on four cpDNA markers showed that either S.pohuashanensis or S.discolor were maternal parents of Sorbus individuals with pink fruits.Incongru-ence of the position of Sorbus individuals with pink fruits between cpDNA and ITS in cluster trees supported by DNA sequence comparative analysis,implying former hybridiza-tion events between S.pohuashanensis and S.discolor.Mul-tiple hybridization events between S.pohuashanensis and S.discolor might have contributed to the generation of Sorbus individuals with pink fruits.This study has provided insights into hybridization between species of the same genus in sympatric areas,which is of great significance for the study of interspecific hybridization.

An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful activity.The DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS research.The model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation accuracy.Thus,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in validation.Furthermore,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 scores.The macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are 0.942.Furthermore,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies precisely.The research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network security.The study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this field.Upcoming research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

Privacy Preservation in IoT Devices by Detecting Obfuscated Malware Using Wide Residual Network

The widespread adoption of Internet of Things(IoT)devices has resulted in notable progress in different fields,improving operational effectiveness while also raising concerns about privacy due to their vulnerability to virus attacks.Further,the study suggests using an advanced approach that utilizes machine learning,specifically the Wide Residual Network(WRN),to identify hidden malware in IoT systems.The research intends to improve privacy protection by accurately identifying malicious software that undermines the security of IoT devices,using the MalMemAnalysis dataset.Moreover,thorough experimentation provides evidence for the effectiveness of the WRN-based strategy,resulting in exceptional performance measures such as accuracy,precision,F1-score,and recall.The study of the test data demonstrates highly impressive results,with a multiclass accuracy surpassing 99.97%and a binary class accuracy beyond 99.98%.The results emphasize the strength and dependability of using advanced deep learning methods such as WRN for identifying hidden malware risks in IoT environments.Furthermore,a comparison examination with the current body of literature emphasizes the originality and efficacy of the suggested methodology.This research builds upon previous studies that have investigated several machine learning methods for detecting malware on IoT devices.However,it distinguishes itself by showcasing exceptional performance metrics and validating its findings through thorough experimentation with real-world datasets.Utilizing WRN offers benefits in managing the intricacies of malware detection,emphasizing its capacity to enhance the security of IoT ecosystems.To summarize,this work proposes an effective way to address privacy concerns on IoT devices by utilizing advanced machine learning methods.The research provides useful insights into the changing landscape of IoT cybersecurity by emphasizing methodological rigor and conducting comparative performance analysis.Future research could focus on enhancing the recommended approach by adding more datasets and leveraging real-time monitoring capabilities to strengthen IoT devices’defenses against new cybersecurity threats.

Speed limit effect during lane change in a two-lane lattice model under V2X environment

Speed limit measures are ubiquitous due to the complexity of the road environment,which can be supplied with the help of vehicle to everything(V2X)communication technology.Therefore,the influence of speed limit on traffic system will be investigated to construct a two-lane lattice model accounting for the speed limit effect during the lane change process under V2X environment.Accordingly,the stability condition and the mKdV equation are closely associated with the speed limit effect through theory analysis.Moreover,the evolution of density and hysteresis loop is simulated to demonstrate the positive role of the speed limit effect on traffic stability in the cases of strong reaction intensity and high limited speed.

CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online threats.The goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify anomalies.The NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection strategy.Furthermore,maintaining operating efficiency while improving detection accuracy is the primary goal of this work.Moreover,typical NIDS examines both risky and typical behavior using a variety of techniques.On the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel attention.Compared to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection performance.Moreover,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this field.Subsequent efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

Multi-Timescale Distributed Approach to Generalized-Nash-Equilibrium Seeking in Noncooperative Nonconvex Games

Dear Editor,The distributed generalized-Nash-equilibrium(GNE)seeking in noncooperative games with nonconvexity is the topic of this letter.Inspired by the sequential quadratic programming(SQP)method,a multi-timescale multi-agent system(MAS)is developed,and its convergence to a critical point of the game is proven.To illustrate the qualities and efficacy of the theoretical findings,a numerical example is elaborated.

Vision based intelligent traffic light management system using Faster R‐CNN

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

The WhatsApp Application as a Teledentistry Tool in Oral and Maxillofacial Surgery in Cameroon

Introduction: Technological advances have greatly influenced the healthcare sector. The ability to transmit information and deliver services using telecommunication tools continues to transform the way healthcare is delivered around the world. The aim of this study was to highlight the epidemiological, clinical and therapeutic profile of oral and maxillofacial surgery patients consulted using the WhatsApp application. Methodology: This was a three-year descriptive study with a retrospective data collection, from 2021 to 2023, of WhatsApp communications between our team and oral and maxillofacial surgeons in Cameroon. In this study, the type/content of messages received, the epidemiological data of practitioners and patients, the various pathologies diagnosed and the procedures performed were evaluated. Results: 319 communications were received for a total of 146 cases. Written messages associated with images (photographs and/or X-rays) were the most frequently received, at 85.62%. Hospitals in urban areas were the most represented at 93.84%. Oral health professionals in the private sector sent more messages (65.75%). In terms of diagnoses, tumour and cystic pathologies were the most common (28.08%), followed by impacted/retained teeth (22.6%). Patients were referred to our hospital for treatment in 62.33% of cases. Conclusion: The WhatsApp application is an easy-to-use telecommunications tool. It facilitates exchanges between practitioners and improves patient care in oral and maxillofacial surgery.

The Current Situation and Improvement of Informatization Construction in Universities in the Era of Digital Education—Taking the Nanchong Campus of Southwest Petroleum University as an Example

Digitization of education is an important component of Digital China Strategy. China is deeply implementing the digitalization of education strategy, promoting educational reform and innovation, and accelerating the construction of a learning society and a learning country where everyone can learn, learn everywhere, and learn at all times [1]. As the cradle and gathering place of talent cultivation, universities should be at the forefront of educational informatization construction. As a comprehensive energy university in the northeastern region of Sichuan, the Nanchong Campus of Southwest Petroleum University plays an irreplaceable role in the local economic development. This article summarizes the current situation of educational informatization construction on this campus and proposes suggestions for its improvement path, providing constructive reference opinions for the development of similar universities.

A Study on Aligning Nursing Curriculum with Hospital Clinical Competency Requirements

The purpose of this study is to coordinate the alignment between the nursing curriculum and hospital clinical competencies,identify the reasons for the gaps,evaluate the impact of these gaps on the nursing profession,and propose strategies to bridge these gaps.This study will help strengthen nursing education,improve nursing students’skills,and help students adapt to complex clinical environments.

Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining Algorithm Apriori

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching effects.With the help of IBM SPSS Modeler data mining software,this paper uses Apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core courses.Lastly,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

Analysis of Information Leadership and Digital Campus Management Strategy

In the information age,the development of schools needs to be integrated with information education,and the principal,as the leader of the school,has a positive significance for the development of the school.Therefore,in the process of school informatization development,principals should continuously improve their informatization leadership,and take digitalization as the guide to build schools,accelerate the construction and improvement of campus management,and then promote the school to continuously optimize the overall management and business processes under the immersion of digital culture.Based on this,this paper is based on information leadership and digital campus,and explores the way to improve the information leadership of principals based on the construction of digital campus.

Development of an Information-Based Leadership Evaluation Index System for School Management Teams:A Comprehensive Approach

In the context of educational informatization reform,there are many uncertain factors in the process of education development.To optimize the educational environment so that it can be effectively combined with information technology,teachers need to change their teaching ideas,strengthen the school’s own adaptability to informatization,and promote the development of informatization construction in schools.As a branch of information leadership,the management team should establish an evaluation index system for information leadership in order to ensure the construction of school informatization,so as to provide a boost for the integration of school resources and information technology.Based on the overview and connotation of information-based leadership of the management team,this paper explores the construction of an evaluation index system of information-based leadership of the school management team,aiming to provide references for the research of relevant personnel in the future.

Research and Analysis on the Application of Strategic Performance Management in Enterprises

In today’s competitive business environment,strategic performance management(SPM)is crucial for continuous growth and innovation.Therefore,it is important to realize the advantages of SPM in enterprise applications.This paper analyzes the theoretical basis,implementation framework,and application effects of SPM in enterprises by examining actual cases from different industries.It reveals the core elements of an effective performance management system,including clear goal setting,reasonable performance indicators,and periodic performance evaluations.Additionally,the paper examines the impact of China’s specific economic policy environment on the implementation of SPM and proposes strategies to optimize performance management practices,ultimately promoting the achievement of strategic goals.This paper provides specific and personalized practical guidance for enterprises.