Integration Of New Technologies Research Articles

Mountain Combat Operations in the Context of Contemporary Battlefield Requirements

The integration of new technologies into military operations has a significant impact on the entire process, resulting in specific features and shaping the character of warfare. The modern battlefield is characterized by the accuracy and long range of new weapon systems, the extensive use of multi-spectral sensors, the continuous improvement of the sensor-to-shooter relationship, and the development of unmanned capabilities. In this context, there is a question as to whether military operations executed in mountainous environments are still relevant in contemporary battlefield equations. These operations are typically spatially limited, static, and attritional, and are subject to transformation from a doctrinal and operational perspective in a paradigm shift in the maneuversupport- fire-protection relationship. This study aims to identify and describe key factors associated with the adaptation of mountain warfare forces and the operations they conduct through an interpretive analysis of land operations.

Productivity Improvement by Process Mapping in Sand and Casting Industry

Abstract: This research paper presents a comprehensive investigation into the efficacy of process mapping as a means of enhancing productivity within the sand and casting industry. Through the meticulous analysis of current state maps and the strategic development of future state maps, this study identifies and addresses inefficiencies in foundry operations, offering practical suggestions for the integration of new technologies, reduction of takt time, and alleviation of bottlenecks. Additionally, employing methodologies such as Time Study with Process Improvement, Rapid Upper Limb Assessment (RULA) analysis, and Rejection Analysis, this research provides a multifaceted approach to process optimization. By synthesizing empirical findings and industry insights, this paper not only underscores the importance of process mapping in enhancing efficiency but also offers actionable strategies to streamline operations and elevate productivity within the sand and casting sector.

Blockchain technology integration in service migration to 6G communication networks: a comprehensive review

<p>The next generation of wireless networks, 6G is being designed with data-intensive applications. One of the key technologies that will enable 6G is blockchain technology. The emergence of blockchain technology and 6G networks has revolutionized service migration. Service migration in 6G networks is a complex process that requires the integration of new technologies, such as artificial intelligence (AI), edge computing, and network slicing. Motivated by these facts, this comprehensive review includes an overview of blockchain and service migration integration in 6G. First, state of art, development frame work and related works were introduced. Then, we used content analysis by WordStat software and bibliographic analysis by VOSviewer to analysis the current status of service migration and blockchain integration in 6G networks. Next, patterns and characteristics, benefits and challenges and potential cases were reviewed. Then, we proposed an architectural blockchain-based model including decentralized architecture, edge computing, network slicing, software-defined networking, and 5G-6G interworking in 6G. Finally, we described potential application service migration-based in 6G networks including digital twin (DT), holograms, robot avatar, high density internet of things (IoT), AR and VR in 6G and collected open research and future directions of service migration and blockchain.</p>

The development status and trends of automotive interactive systems

Nowadays, as time passes and science and technology improve, the interactive system of autos becomes more common, and there are far-reaching changes from the original. As autonomous driving and other functions become more developed, people are increasingly focusing on the car's interactive system. This study investigates automobile development status and trends via the lens of automobile interaction systems, comparing them between previous and present periods, using BYDs electric vehicle interaction system as an example, and briefly exploring the current automobile interaction system. The development characteristics and influencing elements of some automobile interface systems are summarized, and the future development trend is anticipated using this information. Finally, it is determined that the automobile interaction system is progressing toward giving people a more comfortable and safe driving experience, which is a positive trend, and that more technologies may be merged into it in the future. The research in this paper that the vehicle interaction system is currently in development, and while it is merely a simple physical interaction, with the continual integration of new technologies, it has the potential to make significant progress.

An AIoT-based hydroponic system for crop recommendation and nutrient parameter monitorization

Advancements in technology have revolutionized various sectors, including agriculture, which serves as the backbone of many economies, particularly in Asian countries. The integration of new technologies and research has consistently aimed to enhance cultivation rates and reduce reliance on manual labor. Two key technologies, Artificial Intelligence (AI) and the Internet of Things (IoT), have emerged as pivotal tools in automating processes, providing recommendations, and monitoring agricultural activities to optimize results. While traditional soil cultivation has been the preferred method, the increasing urbanization trend necessitates alternative approaches such as hydroponics, which replaces soil with water as the medium for crop cultivation. Having many significant advantages, hydroponics serves a crucial role in achieving efficient space utilization. To get a higher density of plants in a confined area hydroponic approach provides water, nutrients and other essential elements directly to the plant's root. To utilize the hydroponic system more effectively, our proposed method, integrating AI and IoT helps to provide suitable crop recommendations, monitor the parameters of the plants and also suggest the necessary changes required for gaining optimal parameters. To ensure optimal resource allocation and maximize yields we have used machine learning models and trained them to recommend suitable crops from the given parameters and also refer to the changes in parameters that are needed for better plant growth. We have used the crop recommendation dataset from the Indian Chamber of Food and Agriculture to train our proposed machine-learning model. Our selected machine learning algorithms to predict the best crops are Random forests, Decision trees, SVM, KNN, and XGBoost. Our research combines AI and IoT with hydroponic systems to streamline crop recommendations, automate monitoring processes, and provide real-time guidance for optimized cultivation. Among them, the Random forest algorithm outperformed other algorithms with an accuracy of 97.5%.

Application of Landscape Smart Lighting in Construction Projects

Currently, to effectively construct high-quality smart cities and achieve comprehensive governance goals, various industries must embrace the transformation and upgrading of traditional management methods through the integration of new technologies. Among these, landscape smart lighting serves as a crucial tool for advancing smart city development. By judiciously applying this technology, it is possible to enhance traditional lighting methods and offer people novel experiences in their daily lives. Recognizing this importance, this article analyzes and organizes the content of landscape smart lighting, delves into its system characteristics, and summarizes its principles and practices in the field of architectural engineering as practical references for application scenarios.

Transforming congenital heart disease management: Advances in fetal cardiac interventions.

This review addresses the transformative advancements in fetal cardiac interventions (FCI) for congenital heart diseases (CHD), with a particular focus on aortic stenosis with evolving hypoplastic left heart syndrome, pulmonary atresia with an intact ventricular septum, and HLHS with an intact atrial septum (HLHS-IAS). We outline the specific FCI techniques employed, the refined criteria for selecting appropriate fetal and maternal candidates, and the promising yet varied outcomes associated with these procedures. Procedural strategies and clinical decision-making are examined as we take into account the fetal pathophysiology and the benefits and risks of early intervention. We highlight the role of multidisciplinary teams in improving technical success and managing immediate procedural complications, which have led to significant improvements in procedural outcomes. Additionally, the review discusses the long-term outcomes, challenges, and future research directions in FCI, emphasizing the necessity for continuous innovation and collaboration across specialties to advance the management of CHD. The integration of new technologies and research findings holds the promise of further enhancing FCI success rates and patient outcomes.

Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors.

Precision medicine, characterized by the personalized integration of a patient's genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual's genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.

The Application of Bridge Monitoring Projects Exploiting Time Series Data of Structural Health Monitoring

Since the first attempts of Structural Health Monitoring the Vienna Consulting Engineers (VCE) have been involved to advance the BRIMOS technology which offers a wide range of services to engineers and operators of infrastructure networks. Over the last decade the dynamic behavior of hundreds of structures has been measured and evaluated. However, the current practice in Structural Health Monitoring is still a case to case approach which needs a lot of experience for proper interpretation and assessment of the investigated objects. The integration of new technologies is wanted to support and automate the evaluation process as well as increase the objectivity within the assessment routines. This paper shall indicate the need for innovate methods and tools from a user’s point of view and gives a short insight to the workflow and infrastructure of BRIMOS. The efforts which are undertaken within the BRIMOS infrastructure show the approach towards the application of data mining instruments to benefit for future and also from past monitoring projects. Datamining, Time Series Analysis, Knowledge Base, Structural Health Monitoring

COMPUTER NAVIGATION AND ROBOTIC SURGERY DURING TOTAL KNEE ARTHROPLASTY

Total knee arthroplasty (TKA) is a successful treatment for knee osteoarthritis. The emphasis on optimal sizing and alignment of the components has led to an increase in the use of tools that allow for preoperative planning and verification of intraoperative steps. Computer navigation and robotic surgery have emerged as valuable tools for planning and performing surgery with greater precision and consistency. Objective. The aim of this paper is to organise information on the use of robotic systems in total knee arthroplasty based on own personal experience and analysis of contemporary literature sources. Methods. This study analysed professional articles that discussed the advantages and disadvantages of using robotic systems during knee arthroplasty. The information was obtained from electronic databases including PubMed, Scopus, Web of Science and Google Scholar, with a search span of over 20 years. Computerised or navigation devices allow the surgeon to enter anatomical data via an interface and receive feedback on the alignment of the implant and the knee as a whole, but cannot be programmed to perform additional tasks. Currently, several patented systems are available, and rapid technological advances in computer processing power have allowed for the rapid development of robotic surgical systems. Robotic systems usually provide feedback similar to navigation systems, but they can also be programmed to assist in specific surgical tasks. It is expected that these systems will become more reliable and accurate in the future, potentially leading to a reduced role for physicians in certain aspects of the surgical process, limiting their involvement to supervision, and thus improving the workflow of the operating room. The integration of new technologies, such as mixed reality, which overlays simulated images on real-life images, is expected to further expand the range of capabilities of these devices. But for now, it is crucial to establish the long-term outcomes of robotic-assisted total knee arthroplasty as a process to determine the viability of widespread adoption of these devices.

Innovativeness of business models in B2C and B2B online education segments in the USA

Aim. To conduct a comprehensive analysis of the structural and functional composition of innovative business models in the B2C and B2B online education sectors, and to identify the unique elements and factors that determine the success and novelty of these models. Objectives. To identify key development trends and current trends in online education, especially in the B2C and B2B segments; to identify and compare innovative elements of business models in the pre-university and corporate segments based on the analysis of online education project websites; to assess the degree of novelty of business models using the method of frequency analysis of business model elements based on data obtained from online sources.Methods. The study is based on the industry approach to identifying unique business models, analyzing the structuring of business models according to A. Osterwalder and I. Piñe, and assessing the innovativeness of business model elements based on frequency analysis. A comparative analysis of the two segments was performed in order to understand their specific requirements and characteristics, and to identify opportunities for cross-pollination of successful practices and strategies, which can contribute to the creation of new innovative approaches in online education. Data were collected from online education project sites and aggregated using SimilarWeb tool to assess site traffic.Results. The authors found that business models in the B2B segment show a higher level of innovativeness compared to B2C. The main elements of innovativeness are personalization of learning, integration with corporate systems, and development of specialized courses. The components contributing to innovativeness are identified, and recommendations for managing the structural components of business models in each of the segments are offered.Conclusions. The study indicates the importance of innovation in online education business models and the need to adapt them to the changing needs of learners and organizations. Ways to improve business models, including the integration of new technologies and the development of customized educational products for different market segments, are suggested.

Implementation of blockchain for sustainable solar energy trading: a systematic review

PurposeBlockchain for energy trading is a trending research area in the current context. However, a noticeable gap exists in the review articles focussing on solar energy trading with blockchain technology. Thus, this study aims to systematically examine and synthesise the existing research on implementing blockchain technology in sustainable solar energy trading.Design/methodology/approachThe study pursued a systematic literature review to achieve its aim. The data extraction process focussed on the Scopus and Web of Science (WoS) databases, yielding an initial set of 129 articles. Subsequent screening and removal of duplicates led to 87 articles for bibliometric analysis, utilising VOSviewer software to discern evolutionary progress in the field. Following the establishment of inclusion and exclusion criteria, a manual content analysis was conducted on a subset of 19 articles.FindingsThe results indicated a rising interest in publications on solar energy trading with blockchain technology. Some studies are exploring the integration of new technologies like machine learning and artificial intelligence in this domain. However, challenges and limitations were identified, such as the absence of real-world solar energy trading projects.Originality/valueThis study offers a distinctive approach by integrating bibliometric and manual content analyses, a methodology seldom explored. It provides valuable recommendations for academia and industry, influencing future research and industry practices. Insights include integrating blockchain into solar energy trading and addressing knowledge gaps. These findings advance societal goals, such as transitioning to renewable energy sources (RES) and mitigating carbon emissions, fostering a sustainable future.

Sensor-Based Discovery of Search and Palpation Modes in the Clinical Breast Examination.

Successful implementation of precision education systems requires widespread adoption and seamless integration of new technologies with unique data streams that facilitate real-time performance feedback. This paper explores the use of sensor technology to quantify hands-on clinical skills. The goal is to shorten the learning curve through objective and actionable feedback. A sensor-enabled clinical breast examination (CBE) simulator was used to capture force and video data from practicing clinicians (N = 152). Force-by-time markers from the sensor data and a machine learning algorithm were used to parse physicians' CBE performance into periods of search and palpation and then these were used to investigate distinguishing characteristics of successful versus unsuccessful attempts to identify masses in CBEs. Mastery performance from successful physicians showed stable levels of speed and force across the entire CBE and a 15% increase in force when in palpation mode compared with search mode. Unsuccessful physicians failed to search with sufficient force to detect deep masses ( F [5,146] = 4.24, P = .001). While similar proportions of male and female physicians reached the highest performance level, males used more force as noted by higher palpation to search force ratios ( t [63] = 2.52, P = .014). Sensor technology can serve as a useful pathway to assess hands-on clinical skills and provide data-driven feedback. When using a sensor-enabled simulator, the authors found specific haptic approaches that were associated with successful CBE outcomes. Given this study's findings, continued exploration of sensor technology in support of precision education for hands-on clinical skills is warranted.

Teacher Stress During Educational Processes with Physical and Remote Attendance Regarding the Covid-19 Pandemic – A Secondary Publication

The integration of new technologies and the increase in workload have influenced teaching performance, thereby affecting the development of teaching-learning activities. The balance between time dedicated to professional practice and time available for physical and psychological rest is analyzed based on the definition of stress as a collection of daily situations that impact the personal and professional development of an individual, which escalated during the COVID-19 pandemic with the rise of virtual educational practices. The study, conducted in two educational units in Quito, Ecuador, involved administering the Maslach Burnout Inventory questionnaire to 155 participants, alongside collecting data on sociodemographic variables. Statistical analysis was performed using the JASP 0.15 program. The results indicate the level of work stress experienced by teachers, depending on various sociodemographic variables including rural or urban setting, gender, age, level of education, marital status, and cohabitation arrangements. A statistically significant correlation (< 0.001) was observed, particularly regarding the challenge faced by over half of the participants (0.51) in finding time for postgraduate studies. Additionally, a moderate correlation was found between inattention and various symptoms: frustration (0.46), guilt (0.36), weariness (0.26), tiredness (0.51), lack of attention (0.26), and the importance of work (0.43). These findings prompt a discussion on the allocation of time and workload for teachers, irrespective of their location in rural or urban areas.

Generating Synthetic Electricity Load Time Series at District Scale Using Probabilistic Forecasts

Thanks to various European directives, individuals are empowered to share and trade electricity within Renewable Energy Communities, enhancing the operational efficiency of local energy systems. The digital transformation of the energy market enables the integration of decentralized energy resources using cloud computing, the Internet of Things, and artificial intelligence. In order to assess the feasibility of new business models based on data-driven solutions, various electricity consumption time series are necessary at this level of aggregation. Since these are currently not yet available in sufficient quality and quantity, and due to data privacy reasons, synthetic time series are essential in the strategic planning of smart grid energy systems. By enabling the simulation of diverse scenarios, they facilitate the integration of new technologies and the development of effective demand response strategies. Moreover, they provide valuable data for assessing novel load forecasting methodologies that are essential to manage energy efficiently and to ensure grid stability. Therefore, this research proposes a methodology to synthesize electricity consumption time series by applying the Box–Jenkins method, an intelligent sampling technique for data augmentation and a probabilistic forecast model. This novel approach emulates the stochastic nature of electricity consumption time series and synthesizes realistic ones of Renewable Energy Communities concerning seasonal as well as short-term variations and stochasticity. Comparing autocorrelations, distributions of values, and principle components of daily sequences between real and synthetic time series, the results exhibit nearly identical characteristics to the original data and, thus, are usable in designing and studying efficient smart grid systems.

PROCESS DEVELOPMENT IN MECHANICAL ENGINEERING: INNOVATIONS, CHALLENGES, AND OPPORTUNITIES

Process development in mechanical engineering encompasses a broad spectrum of innovations, challenges, and opportunities that drive advancements in various industries. This review delves into the multifaceted landscape of process development within mechanical engineering, highlighting key themes and trends. Innovations in process development are propelled by the continuous quest for efficiency, sustainability, and enhanced performance. Advances in additive manufacturing, automation, and digitalization have revolutionized traditional manufacturing processes, enabling the creation of complex geometries with unprecedented precision and speed. Additive manufacturing techniques such as 3D printing offer versatility in material selection and design freedom, facilitating rapid prototyping and customization while minimizing material wastage. Automation technologies, including robotics and AI-driven systems, optimize production workflows, augmenting productivity and reducing human error. Moreover, digital twins and simulation tools empower engineers to simulate and optimize processes virtually, accelerating product development cycles and minimizing costly experimentation. However, alongside these innovations, mechanical engineers face a myriad of challenges. The integration of new technologies often requires substantial investment in infrastructure and workforce training. Quality control and assurance remain critical concerns, particularly in additive manufacturing, where ensuring part integrity and repeatability is paramount. Furthermore, the sustainability implications of emerging processes must be carefully evaluated to mitigate environmental impact and resource depletion. Despite these challenges, process development in mechanical engineering presents abundant opportunities for growth and advancement. The rise of Industry 4.0 initiatives fosters collaboration between academia, industry, and government, driving research and development efforts towards sustainable and interconnected manufacturing ecosystems. The advent of advanced materials, including composites and biomaterials, unlocks new possibilities for lightweight structures, enhanced performance, and tailored functionalities. Additionally, the pursuit of circular economy principles promotes resource efficiency and waste reduction throughout the product lifecycle. In conclusion, process development in mechanical engineering is characterized by a dynamic interplay of innovation, challenges, and opportunities. By embracing emerging technologies, addressing key challenges, and leveraging collaborative partnerships, mechanical engineers can drive transformative change across industries, paving the way for a more efficient, sustainable, and interconnected future.
 Keywords: Process, Development, Mechanical, Engineering, Innovation, Review.

History of Agroengineering Science in Saint Petersburg

At the end of the 19th and beginning of the 20th centuries, there was a significant development in the field of domestic agricultural engineering science, which focused on the challenges associated with the creation of agricultural machinery. The integration of new technologies in agriculture necessitated a scientific foundation for these advancements, with a keen consideration for the traditional methods of land cultivation. It is posited that the origins of the scientific team at the Institute of Agroengineering and Environmental Problems of Agricultural Production can be traced back to the establishment of the Bureau of Agricultural Mechanics in Saint Petersburg in 1907. (Research purpose) The paper aims to provide a comprehensive overview of the historical and scientific foundations surrounding the emergence and evolution of agroengineering science in Saint Petersburg; and illustrate the continuity of scientific traditions in addressing production objectives within the realm of «Agroecology». (Materials and methods) The analysis was conducted by drawing upon publications that delve into the inception in Russia agricultural mechanization science, the chronicles of the State Agricultural Museum as well as materials prepared for the 100th anniversary of the Bureau of Agricultural Mechanics’ establishment. (Results and discussion) The paper outlines the primary stages and identifies the scientists who played pivotal roles in the operations of the Bureau during 1907-1917. Commencing its activities in Leningrad in 1930, the Institute was later relocated to Moscow. In Leningrad, branches of both VIM and VIESKH were established, where former members of the Bureau continued their work. Further, after various organizational changes, the Leningrad branches were amalgamated in 1962 to form an independent institution known as NIIMESKH of the North-West. This later evolved into the research and production association «Nechernozemagromash» with the workforce exceeding 1,200 employees. In 2018, the Institute once again became a branch of VIM, with a renewed focus on comprehensive scientific research aimed at ensuring the environmental sustainability of agricultural production. (Conclusions) The most significant outcome stemming from the team’s extensive history is the continuity of knowledge transmission. Presently, operating under the umbrella of the Federal Scientific Agroengineering Center VIM, the team at the Institute of Agroengineering and Environmental Problems of Agricultural Production continues the illustrious traditions of its inaugural predecessor—the Bureau of Agricultural Mechanics. It remains steadfast in its commitment to these traditions in tackling emerging challenges in agricultural science and practice.

A comprehensive survey on digital twin for future networks and emerging Internet of Things industry

The rapid growth of industrial digitalization in the Industry 4.0 era is fundamentally transforming the industrial sector by connecting products, machines, and people, offering real-time digital models to allow self-diagnosis, self-optimization and self-configuration. However, this uptake in such a digital transformation faces numerous obstacles. For example, the lack of real-time data feeds to perform custom closed-loop control and realize common, powerful industrial systems, the complexity of traditional tools and their inability in finding effective solutions to industry problems, lack of capabilities to experiment rapidly on innovative ideas, and the absence of continuous real-time interactions between physical objects and their simulation representations along with reliable two-way communications, are key barriers towards the adoption of such a digital transformation. Digital twins hold the promise of improving maintainability and deployability, enabling flexibility, auditability, and responsiveness to changing conditions, allowing continuous learning, monitoring and actuation, and allowing easy integration of new technologies in order to deploy open, scalable and reliable Industrial Internet of Things (IIoT).A critical understanding of this emerging paradigm is necessary to address the multiple dimensions of challenges in realizing digital twins at scale and create new means to generate knowledge in the industrial IoT. To address these requirements, this paper surveys existing digital twin along software technologies, standardization efforts and the wide range of recent and state-of-the-art digital twin-based projects; presents diverse use cases that can benefit from this emerging technology; followed by an in-depth discussion of the major challenges in this area drawing upon the research status and key trends in Digital Twins.

Кросс-культурная компетентность как элемент профессиональной подготовки специалистов в области иностранных языков

This scientific article focuses on cross-cultural competence in education, highlighting the interdependent relationship between language proficiency and intercultural understanding. The authors synthesize theoretical foundations and pedagogical techniques to reveal the multifaceted aspects of integrating cross-cultural nuances into language education. The study presents cross-cultural competence as an essential element of effective communication in a globalised world, rather than a secondary skill. The authors use a holistic approach to examine the complexities of pedagogical strategies that aim to develop cross-cultural communicative competence. These concepts involve the use of innovative technologies and multimedia resources to overcome traditional educational frameworks and model authentic cross-cultural encounters. The article examines the challenges associated with developing flexible competences. The intangible nature of cultural norms and the diversity of students' biographies complicate the process of building soft skills. The article concludes by offering recommendations for improving cross-cultural education and outlining promising trajectories for future research. This study contributes to the debate on the proposed interdisciplinary approach to building cross-cultural competence, combined with the integration of new technologies, which heralds a new era in pedagogy.

NORTH MACEDONIA AS AN EMERGING INNOVATOR

Innovation plays a vital role in advancing economic growth, benefiting consumers, businesses, and the overall economy. Economically, it involves the creation of new products and/or services, the implementation of novel ideas to enhance goods and services, or the integration of new technologies into production processes. Therefore, to thrive in the business world, organizations must innovate. Their survival hinges on the ability to introduce innovations, essential for maintaining a stable and attractive position in the market. Innovations can happen in any area or level of an organization – from manufacturing a tiny electronic component, to introducing a groundbreaking product line, to creating a disruptive business model. Another significant aspect to consider is the impact of government policies on innovation. Hence, its support for businesses is crucial. The purpose of this paper is to examine North Macedonia’s innovation standing within the EU relative to other countries in the region. It aims to analyze the trends over the years, identify the factors influencing performance, assess the reasons behind the results, highlight the country’s strengths, and pinpoint areas that need improvement to align with countries with higher innovation scores, as assessed by the European Innovation Scoreboard (EIS). The EIS offers a comparative evaluation of the research and innovation performance among European countries. North Macedonia’s indicator (46.3) ranks among the lowest, although there has been a significant improvement in the last year, narrowing the difference performance and that of the EU. However, there is still much work to be done. The study’s purpose is to identify the areas on which businesses and the government should focus in the future.