Résultats de recherche pour « Technological advancements »

Public acceptance is critical to the adoption of Shared Autonomous Vehicles (SAVs) in the transport sector. Traditional acceptance models, primarily reliant on Structural Equation Modeling, may not adequately capture the complex, non-linear relationships among factors influencing technology acceptance and often have limited predictive capabilities. This paper introduces a framework that combines Machine Learning techniques with chord diagram visualizations to analyze and predict public acceptance of technologies. Using SAV acceptance as a case study, we applied a Random Forest machine learning approach to model the non-linear relationships among psychological factors influencing acceptance. Chord diagrams were then employed to provide an intuitive visualization of the relative importance and interplay of these factors at both factor and item levels in a single plot. Our findings identified Attitude as the primary predictor of SAV usage intention, followed by Perceived Risk, Perceived Usefulness, Trust, and Perceived Ease of Use. The framework also reveals divergent perceptions between SAV adopters and non-adopters, providing insights for tailored strategies to enhance SAV acceptance. This study contributes a data-driven perspective to the technology acceptance discourse, demonstrating the efficacy of integrating predictive modeling with visual analytics to understand the relative importance of factors in predicting public acceptance of emerging technologies.

Regional and local governments worldwide are working tirelessly toward effective ways of addressing the COVID-19 crisis. During this time, the government has had to ensure that they provide full usage of technological means to confront the pandemic and discourse a wide range of COVID-19 related problems. Herein, this article will discuss the application of technical means and the advancement of technology in different sectors as a consequence of the COVID-19 crisis. Further, it highlights how government and health organizations have introduced new policies intending to try to curb the spread of the coronavirus. These new policies, such as lockdowns and social distancing measures, have resulted in technological advancement and new means of interaction with government, businesses, and citizens. Such changes include increased online shopping, as well as robotic delivery systems, the introduction of digital as well as contactless payment systems, remote working, the role of technology in distance learning, Telehealth, 3D Printing, and online entertainment. These technological advancements have been embraced all the way during this pandemic by a few countries around the world, with its limitation in some underdeveloped and developing countries.

Technological understanding is not a singular concept but varies depending on context. Building on De Jong and De Haro's (2025) notion of technological understanding as the ability to realise an aim through the use of a technological artefact, this paper refines the concept as an ability that differs by context and degree. We extend the original specification developed for a design context by introducing two additional contexts: operation and innovation. Each context represents a distinct way of realising an aim through technology, yielding three types of technological understanding. To clarify the nature of technological understanding further, we propose an assessment framework based on counterfactual reasoning. Each type of understanding is associated with the ability to answer a specific set of what-if questions concerning changes in an artefact's structure, performance, or appropriateness. Distinguishing these different types helps focus efforts to improve technological understanding, clarifies the epistemic requirements of different forms of engagement with technology, and supports a pluralistic perspective on expertise.

Enhanced oil recovery (EOR) processes are well known for their efficiency in incrementing oil production; however, the selection of the most suitable method to adopt for specific field applications is challenging. Hence, this chapter presents an overview of different EOR techniques currently applied in oil fields, the opportunities associated with these techniques, key technological advancements to guide the decision‐making process for optimum applicability and productivity and a brief review of field applications.

The use of patent citation networks as research tools is becoming increasingly commonplace in the field of innovation studies. However, these networks rarely consider the contexts in which these citations are generated and are generally restricted to a single jurisdiction. Here, we propose and explore the use of a multilayer network framework that can naturally incorporate citation metadata and stretch across jurisdictions, allowing for a complete view of the global technological landscape that is accessible through patent data. Taking a conservative approach that links citation network layers through triadic patent families, we first observe that these layers contain complementary, rather than redundant, information about technological relationships. To probe the nature of this complementarity, we extract network communities from both the multilayer network and analogous single-layer networks, then directly compare their technological composition with established technological similarity networks. We find that while technologies are more splintered across communities in the multilayer case, the extracted communities match much more closely the established networks. We conclude that by capturing citation context, a multilayer representation of patent citation networks is, conceptually and empirically, better able to capture the significant nuance that exists in real technological relationships when compared to traditional, single-layer approaches. We suggest future avenues of research that take advantage of novel computational tools designed for use with multilayer networks.

BACKGROUND: Cancer is characterized by the rampant proliferation, growth, and infiltration of malignantly transformed cancer cells past their normal boundaries into adjacent tissues. It is the leading cause of death worldwide, responsible for approximately 19.3 million new diagnoses and 10 million deaths globally in 2020. In the United States alone, the estimated number of new diagnoses and deaths is 1.9 million and 609 360, respectively. Implementation of currently existing cancer diagnostic techniques such as positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance spectroscopy (MRS), and molecular diagnostic techniques, have enabled early detection rates and are instrumental not only for the therapeutic management of cancer patients, but also for early detection of the cancer itself. The effectiveness of these cancer screening programs are heavily dependent on the rate of accurate precursor lesion identification; an increased rate of identification allows for earlier onset treatment, thus decreasing the incidence of invasive cancer in the long-term, and improving the overall prognosis. Although these diagnostic techniques are advantageous due to lack of invasiveness and easier accessibility within the clinical setting, several limitations such as optimal target definition, high signal to background ratio and associated artifacts hinder the accurate diagnosis of specific types of deep-seated tumors, besides associated high cost. In this review we discuss various imaging, molecular, and low-cost diagnostic tools and related technological advancements, to provide a better understanding of cancer diagnostics, unraveling new opportunities for effective management of cancer, particularly in low- and middle-income countries (LMICs). RECENT FINDINGS: Herein we discuss various technological advancements that are being utilized to construct an assortment of new diagnostic techniques that incorporate hardware, image reconstruction software, imaging devices, biomarkers, and even artificial intelligence algorithms, thereby providing a reliable diagnosis and analysis of the tumor. Also, we provide a brief account of alternative low cost-effective cancer therapy devices (CryoPop®, LumaGEM®, MarginProbe®) and picture archiving and communication systems (PACS), emphasizing the need for multi-disciplinary collaboration among radiologists, pathologists, and other involved specialties for improving cancer diagnostics. CONCLUSION: Revolutionary technological advancements in cancer imaging and molecular biology techniques are indispensable for the accurate diagnosis and prognosis of cancer.

During the 1990s, while exploring the impact of the collapse of the Soviet Union on developments in future warfare, a number of authors offered forecasts of military technology appearing by the year 2020. This paper offers a quantitative assessment of the accuracy of this group of forecasts. The overall accuracy - by several measures - was assessed as quite high, thereby pointing to the potential value of such forecasts in managing investments in long-term research and development. Major differences in accuracy, with strong statistical significance, were found between forecasts pertaining primarily to information acquisition and processing technologies, as opposed to technologies that aim primarily at physical effects. This paper also proposes several recommendations regarding methodological aspects of forecast accuracy assessments. Although the assessments were restricted to information available in open literature, the expert assessors did not find this constraint a significant detriment to the assessment process.

Purpose: The purpose of this study is to check the impact of technological advancement on employee performance in banking sector.Methodology: This paper was completed with the help of extensive literature on technological advancement and employee performance available on the databases and websites. Primary data has been used in this paper to check the impact of technological advancement on employee performance. SPSS 16 software package is used to analyze the employee responses and statistical technique Regression analysis is used to check the impact of technological advancement on employee performance.Findings: Total of 140 questionnaires has been distributed among different banks and out of which 100 were get completed and returned. After analyzing the data very efficiently, we find that technological advancement has significant impact on motivation and training of employees. Motivation has significant impact on employee performance but training has no significant impact on employee performance. Moreover as the concerned for technological advancement and employee performance, there is significant relationship among them.Research limitations / Implications: More research will be require on this theory “impact of technological advancement on employee performance in banking sector”

The purpose of this work is to offer a methodology that allows to construct a standard in Knowledge Management and Technological Innovation which may be used in various organizations in México to improve the operation of their resources and productivity. Based on the review of the existing literature, a model is offered including several elements to enable organizations to establish their position in relation to both concepts. The following proposal is based on a systematic effort to understand and integrate models of Knowledge Management and Innovation published in recent years as well as the results of the experiences to propose standards of Knowledge Management and Technological Innovation. In order to elaborate the proposal, factors and their associated components have been analyzed through a review of the literature in order to build and validate a standard proposal. To test the research study, a six-stage research model has been constructed. For this purpose, an in-depth exploratory research study has been carried out in a public sector organization, in an area that allows the replicability of the model. The results have been analyzed to construct and empirically validate the Mexican Standard of Knowledge Management an Technological Innovation. Finally, after the statistical analysis, results obtained from the application of the validated instrument are shown , which supports the definition of the model.

Technology plays a pivotal role in shaping cultural identities and practices across the globe. This paper explores the complex relationship between technology and cultural transformation, recognizing both its opportunities and challenges in diverse cultural contexts. We employ key theoretical frameworks, including cultural diffusion, technological determinism and the digital divide, to examine how technological advancements contribute to cultural development. Our findings reveal that technology acts as a catalyst for cultural exchange, innovation and adaptation, enabling unprecedented global communication and the exchange of ideas. For example, the rapid spread of the internet and mobile technologies has facilitated cross-cultural interactions, leading to the blending of cultural values and practices on a global scale. However, the research also highlights the challenges posed by technology, such as the digital divide, which exacerbates inequalities in access to digital resources, and the risk of cultural homogenization, where dominant global cultures overshadow local identities. This study underscores the dual nature of technological influence: while it fosters cultural enrichment and connectivity, it also poses risks to cultural diversity and equity. By analyzing empirical case studies, we show how these dynamics unfold in real-world contexts. Ultimately, this paper advocates for inclusive, mindful approaches to technological integration that respect and preserve cultural diversity. Our findings offer valuable insights for policymakers, educators and technologists, emphasizing the need for culturally sensitive strategies to ensure that technological progress enhances, rather than erodes, cultural heritage in the digital age.