Narrow Results

In today’s globalized world, cross-cultural communication skills are crucial for English learners. However, traditional English teaching often overlooks cultural differences among students, leading to difficulties in practical communication. The development of deep learning technology has provided new possibilities for English teaching, which can analyze students’ cultural background and learning needs through intelligent systems, and provide more personalized teaching plans. This study focuses on the application of intelligent system in English teaching from the perspective of intercultural education. By analyzing the characteristics of cross-cultural education and the advantages of deep learning technology, an intelligent system model of English teaching based on deep learning is proposed. The model can provide individualized English teaching programs according to students’ cultural backgrounds, learning needs and learning progress. A recommendation algorithm based on a cross-cultural education model comparison is proposed. For each student, retrieve similar teaching cases from the database based on their cultural background and learning needs. Compare the similarity between current students and cases in the database using similarity calculation algorithms. Based on the sustainable development teaching model of college English, the MAP algorithm is analyzed. The experimental results show that the intelligent English teaching system based on deep learning has a remarkable effect on improving students’ English achievement and intercultural communication ability. The model is trained and tested by the measured data. The error of the test results is less than 5%. The results of the experiment prove that the construction of a Chinese college English sustainable development education model can effectively enhance China’s cultural soft power.

With the advent of the era of big data, the teaching practice model of music major has also changed. The emergence and growth of social media allow users to act freely. Therefore, on the basis of social tagging, this paper makes full use of the personalized description information and project content information carried by tags in collaborative tagging. A personalized music recommendation algorithm based on social networks is proposed. In social networks, complex interactive relationships are formed between users and music content, as well as between users themselves. By analyzing users’ historical behavior data (such as receiving and listening to playlists, liking, and sharing), we can calculate the similarity between users. For example, if two users frequently listen to the same song or artist, then their similarity is higher. Restart type random walk is an algorithm that iteratively searches on a graph, adding a “restart” mechanism to the traditional random walk. Specifically, during each walk, the algorithm has a certain probability (usually a preset small value, such as 0.15) to return to the starting node, rather than continuing to randomly select the next adjacent node. This mechanism helps the algorithm to explore new nodes while maintaining attention to the starting node, thereby avoiding getting stuck in local optima. A personalized mobile music recommendation algorithm based on the music genome is proposed based on the similarity of the node structure of two graphs and the random walk of restart type. Based on the similarity of interests between different users, a personalized mobile music recommendation algorithm is proposed to realize the personalized service of mobile terminals.

An Intelligent Exam Management System (IEMS) improves education information and handles an important role in education administration and management. Test optimization is the practice of successfully reducing test execution time and expenses. However, this can come at the expense of accuracy, efficiency, and the quality of testing that existed prior to optimization. In addition to being time-consuming and labor-intensive for teachers, grading essay responses may lead to inequity since it is impossible to apply consistent requirements to all of the responses. Creating assessments is a challenging task that involves optimizing parameters while adhering to several limitations. The Genetic Algorithm (GA) has been enhanced to address the issues of speed and low paper quality in intelligent test paper development. Educational management at universities has been the suggested approach for IEMS-GA to facilitate smarter education, test and course management, promote the improvement of ideas related to school administration, and provide a more equal system of evaluation. Students rely on exams as a means of gauging their own academic strengths and weaknesses. Students’ test scores provide valuable information about their academic strengths and areas for improvement, allowing them to better plan for the future and attain their academic goals. Results are an important part of the educational process as they reveal a great deal about the way students are doing in class. Knowledge and skills necessary to succeed in the real world are evaluated by such assessments.

Introduction:A combination of internal characteristics, such as motivation, personality, beliefs, and dispositions that combine with external circumstances to affect student results is referred to as teaching efficacy. The English-speaking environment becomes a major problem as students learn by interaction. To communicate effectively, they do not acquire the speaking and listening abilities necessary in English.

Objective:This study examines the impact of computer programming courses and learning analytics on student’s computer programming skills.

Methods:In this study, we proposed a novel Dung Beetle Optimized Flexible Random Forest (DBO-FRF) to evaluate the teaching effectiveness. In this study, 175 students’ data were collected for teaching effectiveness. Using student data, prediction model was constructed based on the attributes of the students, their past academic records, their interactions with online resources, and their advancement in laboratory work related to programming. The proposed method is compared to other traditional algorithms.

Results and conclusion:The proposed method is implemented using Python software. The expected performance in the course and, in the instance that any submitted programs failed to meet the requirements, a programming recommendation from one of the class’s top students. The result shows the proposed method achieved better performance in terms of accuracy, precision, recall, and $F$1-score. This decreased the performance gap between students who performed lower and those who performed higher, enabling students who adjusted their programs to learn more.

The social and ideology education, focus instruction, hands-on learning, and a variety of means, students are cultivated in their political quality, moral character, and sense of social responsibility while it is being guided in understanding the nation’s important policies and social current affairs. Ideological and political disciplines are implementing the problem of transformation within the framework of the major criteria of the new curriculum reform. In the conventional teaching process, students face several challenges in achieving the essential quality of ideological and political education. The artificial intelligence-assisted interactive modeling on the Internet of Things platform (AI-IM-IoT) is able to generate a smart system for ideological and political education, addressing various problems in the current situation. Performance in conventional ideological and political learning platforms, an investigation on the construction of intelligent media ideological and political learning platforms are based on AI technology. Hence AI-IM-IoT has been the Ideology of ideas and beliefs that influence social behavior and can possess an effect on educational achievements. Ideological viewpoints on education can influence educational institutions’ aims, values, and priorities, as well as how resources and opportunities are allocated. Students are encouraged to develop an understanding of social, economic, and political issues via ideological and political education programs.

This paper provides a survey of the variety of computer vision [CV] and image processing [IP] courses being taught at institutions around the world. The survey shows that, in addition to classic survey courses in CV/IP, there are many focused and multidisciplinary courses being taught that reportedly improve both student and faculty interest in the topic. It also demonstrates that students can successfully undertake a variety of complex lab assignments. In addition, this paper includes a comparative review of current textbooks and supplemental texts appropriate for CV/IP courses.

This paper describes a course in image computation that is designed to follow and build up an established course in computer graphics. The course is centered on images: how they are generated, manipulated, matched and symbolically described. It builds on the student's knowledge of coordinate systems and the perspective projection pipeline. It covers image generation techniques not covered by the computer graphics course, most notably ray tracing. It introduces students to basic image processing concepts such as Fourier analysis and then to basic computer vision topics such as principal components analysis, edge detection and symbolic feature matching. The goal is to prepare students for advanced work in either computer vision or computer graphics.

Leadership Education Development (LED) teaching results in criticism and debate in the learning atmosphere for students. The significant challenges in LED are analyzing how research can successfully be applied to benefit the students’ teaching, the political essence of education, identifying education research as a science, and the dislocation between educational research and education practice. Teaching and research are two critical ties to tertiary education programs. Two psychological tools have been built from archived research data and show how this form of reuse allows pedagogue to directly link research and teaching. This manuscript proposed an Optimized Learning Strategy (OLS) to improve curriculum development. OLS provides strategies for learning that increase learning ability, learning experience, boost understanding, and connect with previous knowledge of new information. This paper presents the real practice of the development of LED teaching programming. Finally, the results show the students highly recommended OLS based on case study analysis to measure teaching and learning methods.

Bioinformatics plays an important role for in the research and development of the life science and biotechnology. This paper intends to give an overview of the activities of bioinformatics service, research and education at the Center of Bioinformatics, Peking University; the national node of the European Molecular Biology Network and the Asia Pacific Bioinformatics Network.

Government Effort to Cheaper AIDS Drugs and More Education in China.

TV Indulgence: Are Your Kids at Risk?

Singapore's Biomedical Sciences Clusters Shows Growth Results.

The article provides a perspective of the status of complementary and alternative medicine in the US. Scientists from the John Hopkins Hospital discusses about the complementary and alternative medicines in the US.

Dennis Gillings receives SCRIP Lifetime Achievement Award, Quintiles named CRO of the Year.

IMCD to distribute TPE-S, TPE-V compounds.

Selecta Biosciences and Sanofi sign global collaboration to develop antigen-specific immunotherapies.

Verisante Aura named finalist for 2013 SPIE Prism Award.

Direvo introduces BluCon™ for the conversion of non-food biomass to biofuel and chemical building blocks.

China’s Tencent Develops a Robot Journalist to Write News Stories

Huawei and Beijing Genomics Institute Signed Partnership Agreement to Boost Gene Technology Efficiency over 30%

Chang-Chun Institute of Applied Chemistry Research Progress in Cell Membrane Structure

Conserving Orchids in Xishuangbanna

Chinese and Arab Leaders to Boost Tech Transfer

Universal Health Acquired Increase of Shares of HK$50 Million by Chairman Jin Dongtao, Further Increase Expected

Testicular Xenografting Shortens Reproduction Cycle of Transgenic Monkeys

The Three Gorges Dam Affects Eco-hydrological Environment and Vegetation Distribution of East Dongting Lake

Why Rhabdolaimus Dominates Nematode Communities in Karst Mountain Peaks in Southwest China?

Research Uncovers Molecular Mechanism for Inflammatory Cell Death

Large Polyglutamine Repeats Cause Muscle Degeneration

The Shanghai Prosthodontics Symposium Returns to DenTech China 2015

Infinitus and Cambridge Jointly Establish International Research Centre

Neurological Soft Signs Show Robust Heritability and Familiality in Healthy Twins, Patients with Schizophrenia and Non-psychotic First-degree Relatives

Education created Feminism, or vice versa? Madame Peng Liyuan’s tour in the United States

Mundipharma and Helsinn Group Expand Exclusive Licensing and Distribution Agreements for Leading Anti-emetic Products in Middle East, Africa, Latin America and Indonesia.

Leading Regional Medical Technology Trade Associations Reinforce their Commitment to Evidence-based Healthcare.

Lonza Expands Airway Disease Portfolio with Addition of IPF Airway Cells.

Boston Scientific Launches Interventional Cardiology Online Education Portal for Physicians.

Pfizer Presented Data from PALOMA-2 Phase 3 Study Demonstrating Clinical Benefit of IBRANCE^® (palbociclib) in Asian Women with ER+, HER2- Metastatic Breast Cancer.

Global Healthcare Systems at Pivotal Point as Technology Offers Solutions to Industry Challenges – The Economist Intelligence Unit.

Cellectricon and Censo Biotechnologies Introduce a Joint Technology Access Program Utilizing High-Quality Human iPSC-based Discovery Services for CNS and Pain Research.

Shire Championing the Cause for Patients with Rare Diseases.

ASEAN⁺ Rare Disease Network: Unifying Voices of Patients.

Rainbow Across Borders.

Genetic Counselling Services in Malaysia.

Healthcare heads into the digital future.

Digital technology improves research and management of functional gastrointestinal disorders in babies.

Welcome to the healthcare revolution.

Doctor Robot will see you now.

Maximising human potential in the age of AI.

The Internet of Things in healthcare - A double-edged sword?.

Data could help Asia cope with its ageing population.

A vision of connected healthcare delivery in Asia.

For the month of February 2021, APBN takes a look into the future. Our Features section highlights the key points from the STEM Conference 2020organised by the Science Centre Singapore where experts in the field discuss the future of STEM education. In the Spotlights section APBN interviewed Fabrice Leguet, Managing Director and President, Southeast Asia for Siemens Healthineers to gain insight to the company's efforts in bridging technology gaps in the healthcare industry as well as its COVID-19 response. For the Columns section, we take a look at the future of digital technology in the healthcare industry and how the internet of things (IoT) and blockchain technology could pave the way for new innovations.

Socially, politically, and morally, the world of sport is still changing. On the other hand, technology has been the most prevalent transition in the sport over the last century. Thanks to modern science, athletes can now go higher, run quicker, and, most importantly, remain healthy. Although academics, agencies, and policymakers had already urged physical education teachers to use technology in their classrooms, in many of these situations, technology is used for administrative purposes, including tracking enrolment and measuring, documenting, and reporting students’ work. Thus, this paper suggests an intelligent Student Actions Evaluation System using Deep Learning (iSAES-DL)for student monitoring in physical education. This model uses the deep convolution neural network for the classification of risky actions. This model further evaluates the learners’ degree of learning, retention, and achievements and suggests improvements and corrective measures. It highlights the benefits, uses, and limitations of applying deep learning techniques and IoT devices to develop learning analytics systems in the physical, educational domain. Eventually, output criteria such as comprehension, concentration, retention, and learner attainment are given a feature-by-feature analysis of the proposed methodology and traditional teaching-learning approaches. Finally, the classification algorithm is contrasted to other deep learning algorithms with an F1-score of 97.86%.

A social activity that uses certain ideas, concepts, political views, and moral values in a society or social group enriches students’ ideology and allows learners to form ideological and moral qualities that correspond to their social and political establishment. The continuous improvement of their complete quality and technical skills is at the heart of social and economic growth. In ideological and political education, risk factors are widely influenced, including the impact of educational purposes and education providers. In this paper, Deep Learning-Based Innovation Path Optimization Methodology (DL-IPOM) has been proposed to strengthen data awareness, improve the way of thinking in ideological and political education. The political instructional collaborative analysis is integrated with DL-IPOM to boost Ideological and political education excellence. The simulation analysis is conducted at (98.22%). The consistency of the proposed framework is demonstrated by efficiency, high accuracy (98.34%), overshoot index rate (94.2%), political thinking rate (93.6%), knowledge retention rate (80.2%), reliability rate (97.6%), performance (94.37%) when compared to other methods.

As increasingly more research efforts are geared towards creating robots that can teach and interact with children in educational contexts, it has been speculated that endowing robots with artificial empathy may facilitate learning. In this paper, we provide a background to the concept of empathy, and how it factors into learning. We then present our approach to equipping a robotic tutor with several empathic qualities, describing the technical architecture and its components, a map-reading learning scenario developed for an interactive multitouch table, as well as the pedagogical and empathic strategies devised for the robot. We also describe the results of a pilot study comparing the robotic tutor with these empathic qualities against a version of the tutor without them. The pilot study was performed with 26 school children aged 10–11 at their school. Results revealed that children in the test condition indeed rated the robot as more empathic than children in the control condition. Moreover, we explored several related measures, such as relational status and learning effect, yet no other significant differences were found. We further discuss these results and provide insights into future directions.