Technology Trends Research Articles

Medium and Long-term Carbon Emission Projections and Emission Reduction Potential Analysis of the Lingang Special Area Based on the LEAP Model

Based on the existing statistical data of the Lingang Special Area in Shanghai and considering its future socio-economic development， industrial structure， and technological development， a LEAP-Lingang model was developed to analyze the evolution trends of energy demand and carbon emissions under the baseline scenario， low-carbon scenario， and enhanced low-carbon scenario. To enhance the prediction accuracy of the model， the Logistic population growth model was used to predict future population data， and the learning curve model was used to simulate the cost evolution trend of related carbon reduction technologies. In addition， an economic evaluation model for carbon reduction technologies was developed， and the economic costs and emission reduction potential of typical carbon reduction technologies were evaluated by drawing a marginal emission reduction cost curve. The results showed that under the enhanced low-carbon scenario， the renewable energy accounted for 69% of the primary energy consumption， and the electric energy accounted for 91% of the terminal energy demand in 2060. The Lingang Special Area could achieve carbon peak by 2030， and the carbon emissions in 2060 were predicted to decrease by 94% compared to that in the baseline scenario. In terms of contribution to emission reduction， clean energy substitution， industrial structure optimization， and terminal energy efficiency improvement played a key role in reducing carbon emissions near the port. In the medium term （until 2035）， they were predicted to contribute 35.1%， 27.3%， and 16.2% of carbon emissions， respectively， and in the long term （until 2060）， they should contribute 50.6%， 8.75%， and 7.7% of carbon emissions， respectively. Regarding specific carbon reduction technologies， hydrogen power generation； water electrolysis for hydrogen； and carbon capture， utilization， and storage （CCUS） technology were of great significance for achieving net-zero emissions， but the costs of emission reduction were relatively high. The research results can provide ideas and references for the low-carbon and green development of the Lingang Special Area and related areas.

Exploring Current Trends in Artificial Intelligence Technology An Extensive Review

Artificial intelligence (AI) has become increasingly pervasive across various domains, including smartphones, social media platforms, search engines, and autonomous vehicles, among others. This study undertakes a scoping review of the current landscape of AI technologies, following the PRISMA framework, with the aim of identifying the most advanced technologies utilized in different domains of AI research. Three reputable journals within the artificial intelligence and machine learning domain, namely the Journal of Artificial Intelligence Research, the Journal of Machine Learning Research, and Machine Learning, were selected for this review. Articles published in 2022 were scrutinized against certain criteria: the technology must be tested against comparable solutions, employ commonly approved or well-justified datasets, and demonstrate improvements over comparable solutions. A crucial aspect of technology development identified in this review is the processing and exploitation of data collected from diverse sources. Given the highly unstructured nature of data, technological solutions should minimize the need for manual intervention by humans. The review indicates that creating labeled datasets is a labor-intensive process, leading to increased research focus on solutions leveraging unsupervised or semi-supervised learning technologies. Efficient updating of learning algorithms and the interpretability of predictions emerge as key considerations in the development of AI technologies. Moreover, in real-world applications, ensuring safety and providing explainable predictions are imperative before widespread adoption can be achieved. Thus, this review underscores the importance of addressing these factors to facilitate the responsible and effective integration of AI technologies into various domains.

Modernizing Occupational Safety in Industry 4.0: A Review of State-of-the-Art Safety Wearables

Industry 4.0 signifies a paradigmatic transformation in occupational safety, paving the way for the safety wearables (SWs) market, which is still in its early stages in Brazil. This study aims to comprehensively review the global state of the art of safety wearables, compiling pertinent technological trends for the country's reindustrialization debate. Articles were sourced from the Scopus platform, and VosViewer was utilized for keyword tracking. A global race of SWs research is evident, with the construction industry at the forefront, emphasizing monitoring employees' mental states. The emergence of local startups in Brazil within this theme is expected in the forthcoming years, potentially contributing to reducing the high rate of work-related accident mortality in the country.

Digital pathways in education: analysis of the evolution and future trends of educational technologies among teachers in the basic education network

This study delves into the intricate issue of implementing educational technologies in primary education, with a detailed focus on the challenges and opportunities that arise in this ever-evolving landscape. The main objective of the research is to analyze the past trajectory and future trends of educational technologies, with a special emphasis on the pivotal role played by teachers in the teaching-learning process. The adopted methodology involved a comprehensive literature review, allowing for a meticulous analysis of the extensive existing literature on the subject. The results obtained reveal that, despite the hurdles faced, such as inadequate technological infrastructure and resistance to change from some educators, educational technologies offer significant opportunities for innovation in the field of education. Furthermore, the analysis highlighted the pressing need for integrated strategies addressing both teacher training and curriculum adaptation to effectively incorporate these technologies. In conclusion, this study underscores the vital importance of a balanced and well-planned approach to the integration of educational technologies in primary education. This entails recognizing and addressing the challenges that arise while capitalizing on the opportunities offered by these tools, with the ultimate goal of enhancing the quality of education and student development. Therefore, the research emphasizes the need for a strategic and collaborative approach to maximize the positive impact of technologies in education.

Digital Electronic System-on-Chip Design: Methodologies, Tools, Evolution, and Trends.

This paper reviews the evolution of methodologies and tools for modeling, simulation, and design of digital electronic system-on-chip (SoC) implementations, with a focus on industrial electronics applications. Key technological, economic, and geopolitical trends are presented at the outset, before reviewing SoC design methodologies and tools. The fundamentals of SoC design flows are laid out. The paper then exposes the crucial role of the intellectual property (IP) industry in the relentless improvements in performance, power, area, and cost (PPAC) attributes of SoCs. High abstraction levels in design capture and increasingly automated design tools (e.g., for verification and validation, synthesis, place, and route) continue to push the boundaries. Aerospace and automotive domains are included as brief case studies. This paper also presents current and future trends in SoC design and implementation including the rising, evolution, and usage of machine learning (ML) and artificial intelligence (AI) algorithms, techniques, and tools, which promise even greater PPAC optimizations.

Older adults' perceptions of online physical exercise management.

The study addresses the challenges of digitally transforming physical exercises for older adults (aged more than 55 years) to be performed in virtual environments (during the COVID-19 pandemic) as a long-term proactive strategic initiative in response to the global ageing society and technological development trend. A focus group with a sample of 24 older adults and three trainers were used as part of a 3-month physical exercise pilot conducted by the Jožef Stefan Institute to identify the skills and well-being gained and identify factors that influence success with online exercises for older adults on the individual and organisational levels. First, on the individual level, communication differences were identified when comparing face-to-face exercises with online exercises. Second, on the organisational level, the study identified several challenges arising from the digital transformation of exercises (i.e., onboarding, technical, structural, isolation and motivational). Finally, recommendations are proposed to transform older adults' exercises when performed in a virtual environment. The study results can also benefit health management practices and theory in the work environment to ensure that older workers can still utilise their strengths to perform successfully while remaining healthy. Online physical exercises tailored to older adults' needs and specifications could be provided as part of corporate wellness programmes in organisations.

A Dynamic Evaluation Method for the Development of Intelligent Construction Technology in the Construction Field Based on Structural Equation Model–System Dynamics Model

In order to explore the development trends of intelligent construction technology in the field of construction, this paper constructs a system dynamics (SD) model of the application and development of BIM and the new-generation information technology in the construction industry based on SD theory and a structural equation model (SEM). Vensim DSS is used to explore the relationship between the SD model and six subsystems. The dynamic simulation and the sensitivity analyses are also conducted. Results show that during 2023–2050, as the time series advances, the effect value of the dynamic simulation gradually increases. From 2035, intelligent construction technology shows a trend of rapid development between various subsystems and the SD model. The adjusted model and the status of the subsystem are consistent with the SD model simulation curve. It is verified that intelligent construction technology has good development prospects in the construction field.

Application of Big Data in Tourism Destination Management: A Case Study of Changsha City

In the era of information technology, the utilization of big data technology is rapidly growing, leading to significant changes in the tourism industry. Big data not only creates more business opportunities for the industry but also drives the transformation and enhancement of tourist destinations and the implementation of efficient management. This study employs two research methods: literature review and case analysis. Firstly, by reviewing relevant literature, the latest research findings and trends in big data technology for tourism destination management are summarized. Secondly, through case analysis, a comprehensive understanding of the current situation and challenges in the application of big data technology in tourism destination management in Changsha is obtained. Leveraging the Changsha cultural and tourism data platform, this study retrieves information such as tourist reception data of tourism destinations in Changsha and assesses the impact of Changsha’s big data technology on tourism destination management. The research reveals limitations and challenges in the application of big data technology in Changsha’s tourism destination management, including data privacy protection and technical security, which require further exploration in future practices. The goal of this study is to offer insights for the application of big data in tourism destination management in Changsha and provide guidance for destination managers in similar cities.

Recent Technological and Intellectual Property Trends in Antibody-Drug Conjugate Research.

Antibody-drug conjugate (ADC) therapy, an advanced therapeutic technology comprising antibodies, chemical linkers, and cytotoxic payloads, addresses the limitations of traditional chemotherapy. This study explores key elements of ADC therapy, focusing on antibody development, linker design, and cytotoxic payload delivery. The global rise in cancer incidence has driven increased investment in anticancer agents, resulting in significant growth in the ADC therapy market. Over the past two decades, notable progress has been made, with approvals for 14 ADC treatments targeting various cancers by 2022. Diverse ADC therapies for hematologic malignancies and solid tumors have emerged, with numerous candidates currently undergoing clinical trials. Recent years have seen a noteworthy increase in ADC therapy clinical trials, marked by the initiation of numerous new therapies in 2022. Research and development, coupled with patent applications, have intensified, notably from major companies like Pfizer Inc. (New York, NY, USA), AbbVie Pharmaceuticals Inc. (USA), Regeneron Pharmaceuticals Inc. (Tarrytown, NY, USA), and Seagen Inc. (Bothell, WA, USA). While ADC therapy holds great promise in anticancer treatment, challenges persist, including premature payload release and immune-related side effects. Ongoing research and innovation are crucial for advancing ADC therapy. Future developments may include novel conjugation methods, stable linker designs, efficient payload delivery technologies, and integration with nanotechnology, driving the evolution of ADC therapy in anticancer treatment.

Workshop Strategi Revolusioner Pembelajaran Modern Melalui Integrasi Teknologi Cerdas dan Platform Media Sosial bagi Pendidikan Generasi Digital

Education in the current digital era demands the use of smart technology and social media platforms in the learning process to suit the character of the digital generation. However, the competence of lecturers in Indonesia in this regard is still limited. Therefore, the workshop "Revolutionary Strategies for Modern Learning Through the Integration of Smart Technology and Social Media Platforms for Digital Generation Education" is important to implement. This workshop aims to provide understanding and skills to 187 lecturers in implementing technology and social media for learning innovation for digital generation students. Workshop material includes smart technology trends, use of social media platforms, digital evaluation and assessment strategies, as well as discussion of challenges and opportunities for integrating technology and social media in digital era learning. Participants' enthusiasm was quite high and the evaluation results showed that 91% were interested in implementing modern learning strategies after the workshop.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things (IoT) is a significant trend in technology and a requirement for national strategic development. With the deepening digital transformation of the power grid, China’s power system has initially built a power IoT architecture comprising a perception, network, and platform application layer. However, owing to the structural complexity of the power system, the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment, diverse IoT protocol access methods, high concurrency of network communications, and weak data security protection. To address these issues, this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT, comprising cloud, pipe, edge, and terminal parts. It further reviews and analyzes the key technologies involved in the power IoT, such as the unified management of the physical model, high concurrent access, multi-protocol access, multi-source heterogeneous data storage management, and data security control, to provide a more flexible, efficient, secure, and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

High precision map crowdsource update technology and SLAM technology - Application in autonomous driving

In response to the challenges faced by real-time dynamic updates of high-precision maps for autonomous driving in terms of high precision, high reliability, and high safety, this paper summarizes the difficulties and challenges currently faced by high-precision map updates. Accelerate the large-scale commercialization of autonomous driving high-precision maps. Thus, improving the safety and stability of intelligent vehicles and providing critical support for high-level autonomous driving. Firstly, the definition and connotation of autonomous driving maps were described, and the data characteristics and functional applications of autonomous driving maps were pointed out. Secondly, the development status and trends of high-precision map updates were reviewed, and the advantages and disadvantages of centralized map updates and crowdsourced map updates were summarized. Pointing out that crowdsource updates have become a new trend in the development of map updates. Once again, the basic architecture and key core modules of current crowdsource updates were summarized, and an analysis was conducted on key core technologies, summarizing the current status and trends of key technologies involved in crowdsource updates. The results indicate that the current technology still faces 7 main challenges, including map modeling, high-precision positioning, 3D reconstruction, fusion updates, data security, rapid review, and standard laws and regulations to address these challenges.

Research on Curriculum Design of Data Mining in Different Majors

With the increasing attention paid to the application value of big data, data mining has become an important major course not only in big data, computer and information technology, but also in most majors in colleges and universities. This course involves the explanation of classic algorithms of data mining as well as the application of classical algorithms of data mining, so it usually has both theoretical and practical hours in the composition of teaching form. Because of the differences in the knowledge structure of students in different majors, there should be differences in the theoretical teaching and practical teaching design of data mining courses among different majors. The teaching content should be selected according to the characteristics and needs of students in different majors, and should also consider the development and trends of big data technology. In addition, in order to improve the teaching quality and effectiveness of data mining courses, it is also necessary to use modern teaching methods and technologies to support teaching, such as online teaching resources, flipped classroom teaching, etc. In short, it is necessary to carry out targeted teaching design for data mining courses in different majors to match the basic situation of students in different majors, ensure better teaching effect and play a better role in different fields of specialization.

Smart Classroom in the Era of Education Informatization 2.0

The advent of the era of education informatization 2.0 has brought challenges and opportunities to the educational technology work of colleges and universities. As an important part of education informatization, smart classroom has an important theoretical framework and technical support system. This paper analyzes the characteristics of the era of education informatization 2.0, discusses the concept and importance of smart classrooms, and compares them with traditional classrooms. At the same time, through innovative practices and case studies, the innovative achievements and effect evaluation of educational technology work in colleges and universities are demonstrated. In addition, this paper also introduces the technical support system of the smart classroom, including the functions and architecture of the smart education platform, and the application of big data, artificial intelligence, cloud computing, and mobile learning Xi in the smart classroom. Finally, this paper looks forward to the future-oriented development trend of educational technology in colleges and universities, and puts forward suggestions for the development of smart classrooms and the future prospects of educational technology work in colleges and universities.

New developments and trends in 5G technologies: applications and concepts

Fifth-generation (5G) wireless technology is the most up-to-date iteration of mobile data networks. This research analyzes the effectiveness of next-generation mobile networks in tandem with mobile communication technologies. Various difficulties encountered at each stage are discussed. With the advent of 5G networks, users may connect to the internet at lightning speeds from almost any location. 5G is one of a kind because of its new characteristics, which allow it to link people and enable them to operate gadgets, machines, and things. 5G mobile technology’s varying speed and capabilities will allow for new user experiences and link new businesses. Companies must know where they can best put 5G to use. This research paper examines and analyzes various topics in great detail, demonstrating how mmWave, massive multiple-input and multiple-output (massive MIMO), microcells, mobile edge computing (MEC), beamforming, diverse antenna technologies, and so on can all work together to improve cellular networks. The primary goals of this article are to demonstrate some of the most recent technical developments and to analyze potential future research directions for the 5G mobile system.

The school psychologist-parent partnership in the development of language in young schoolchildren

In contemporary society, the language of primary schoolchildren is influenced by technological and digital trends, cultural diversity and online communication. Understanding the linguistic-communicative specifics during the early school years is essential in language development, representing a source of knowledge and guidance for parents. At the same time, parents are primary factors in adapting to this varied and constantly changing linguistic reality. The present article reflects the specificity of language in primary school pupils and the importance of the development of this mental process in ensuring a harmonious balance between mental functions, school success and effective communication in the child’s social environment. In this sense, it is necessary to collaborate between the school psychologist and the parent, who are educational agents directly involved in the harmonious development of the student. The article outlines the main aspects related to the parent-school psychologist partnership, providing recommendations and examples of games for parents, aimed at facilitating communication between the child and the parent, and at the same time developing the child’s language.

Advanced Manufacturing in Industry 5.0: A Survey of Key Enabling Technologies and Future Trends

A revolution in advanced manufacturing has been driven by digital technology in the fourth industrial revolution, also known as Industry 4.0, and has resulted in a substantial increase in profits for the industry. In a new paradigm of Industry 5.0, advanced manufacturing will step further and be capable of offering customized products and a better user experience. A number of key enabling technologies are expected to play crucial roles in assisting Industry 5.0 in meeting higher demands of data acquisition and processing, communications, and collaborative robots in the advanced manufacturing process. The aim of this survey is to provide novel insights into advanced manufacturing in Industry 5.0 by summarizing the latest progress of key enabling technologies such as Artificial Intelligence of Things (AIoT), beyond 5G communications, and collaborative robotics. Finally, key directions for future research to enable this vision to become a reality, such as the industrial metaverse, are outlined.

Preface

The International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) is an interdisciplinary scientific event which aims to promote the knowledge and the development of high-quality research in mathematical fields that have to do with the applications of other scientific fields and the modern technological trends that appear in them, these fields being those of Physics, Chemistry, Biology, Medicine, Economics, Sociology, Environmental sciences etc.The 12th IC-MSQUARE took place in Belgrade, Serbia between August 28 and 31, 2023. In addition, (because in previous years the conference, due to the pandemic, took place only with online presentations), the possibility of participation via the internet was also adopted this time. Thus, apart from the talks and workshops held on site, we also had a large collection of pre-recorded presentations that were available to the participants through the conference website.The Conference was attended by more than 350 participants and hosted about 320 oral and virtual presentations while counted more than 1000 pre-registered authors. The 12th IC-MSQUARE consisted of different and diverging workshops and thus covered various research fields where Mathematical Modeling is used, such as Theoretical and Mathematical Physics, Neutrino Physics, Non-Integrable Systems, Dynamical Systems, Computational Nanoscience, Biological Physics, Computational Biomechanics, Complex Networks, Stochastic Modeling, Fractional Statistics, DNA Dynamics, Macroeconomics, Social Modeling etc.The scientific program was rather heavy, however, according to all attendees, the program was excellent with high level of talks and the scientific environment was fruitful, thus all attendees had a creative time.All papers submitted to the Conference have been reviewed using a single-blind peer-review process. The review process adopted a scoring system (0-5 points) who rated the Relevance, Scientific quality, Contribution, Title and paper presentation, Tables and figures, Language and the References of each paper. The threshold for an article to be accepted was a score above 4 for the majority of the evaluated papers. Additionally, each paper was tested for similarity with already published content using the Turnitin software. All sources of similarities were checked and only original content was accepted. In this way, out of 308 papers that were evaluated for this volume, only 167 were accepted for publication.We would like to thank the Reviewers, the Members of the International Scientific Committees as well as the Members of the Organizing Committee.The Conference ChairmanDimitrios VlachosUniversity of PeloponneseList of International Scientific Committee, Organizing Committee are available in this pdf.

Emerging Scientific Topic Discovery by Analyzing Reliable Patterns of Infrequent Synonymous Biterms

Emerging scientific topics are those topics that the number of related articles was small in the past but has grown dramatically in recent years. Automatic discovery of emerging scientific topics has become increasingly necessary because of the exponentially increasing of research papers. Such discovery enables broad applications, such as optimizing resource allocations for promising research areas, predicting future technology trends, finding knowledge gaps and new concepts, and recommending personalized research directions. In this paper, we provide a framework of emerging topic discovery methods using Infrequent Synonymous Biterm (ISB), which automatically extracts the dedicated knowledge from the infrequent patterns of synonymous biterms in a corpus (e.g., paper titles); each term in a synonymous biterm represents a collaborating supertopic, whose collaboration originates an emerging topic. In particular, we propose an Analyzing Reliable Patterns of Infrequent Synonymous Biterms (ARPISB) method, which guarantees the quality of the result emerging topics by adaptively giving larger weights to more reliable ISB. Extensive experiments on five subfields' scholarly papers demonstrate the significant and robust improvement of the accuracy of emerging scientific topic discovery.

Fiber Optics Communication: Evolution of Guided Media

Abstract: Fiber Optic Communication system is a key element in modern day telecommunication network used all around the globe. Larger bandwidth signal transmission where data received with lowest possible delay serves as a big edge to both, the telecommunication industry and consumer. Recently, optical fiber communication technology has made great progress, where constantly exploring new technologies has greatly enhanced communications capabilities in the traditional sense. This paper gives an overview of fiber optic communication systems including their key technologies, and also discusses their technological trend towards the next generation. The recent developments in the area of fiber optic communication as well as the advances in different Fiber types, their properties, optical sources, detectors, system limitations and applications are also discussed in the paper.