Hasil untuk "Technological innovations. Automation"

Damian Dubis, Jolanta Baran

It is known from various studies that the choice of the drinkware could deeply affect consumer perception during beverage consumption. In our previous study we have demonstrated that there are a lot of differences in the ratings of taste, palatability bitterness and saturation were noted depending on the type of vessel in which beer was served. This study continues our previous research and expands it even further. In this study we test four different types of beer – each one with a different essence content. This is to determine whether glassware type affects customer experience from drinking each type of beer. Four types of beer purchased from different producers were used for the research. Beer samples for evaluation were served in beer mugs with a classic design and solid construction, tall glasses (wheatbeerglasses) with a characteristic elongated shape, and beer goblets (also called tulip glass), distinguished by a short stem and a very large bowl that tapers towards the top. The experimental results showed how the characteristics of a glass could affect beverage bouquet and flavour, and suggest that their rational optimization, based on experimental data, could enhance the consumer enjoyment of it. Taking into account the above studies, certain conclusions can be drawn regarding the research we conducted. Light beer with an essence content 12% served in a tulip glass has been assessed worse in every single tested trait. Odour, taste, saturation, palatability, bitterness and general quality index (GQI) have been perceived worst when the beer was served in tulip glass. It seems that tulip glass is particularly unsuitable for this type of beer. Moreover, sustainability considerations are becoming increasingly relevant in this context. Understanding the interactions between the drink and its container may foster more deliberate and responsible purchasing behavior. The above-mentioned factors also affect the consumer experience that can be created by combining a drink with the right glass.

Tao-Yuan Liu, Kun-Hua Lee, Arvind Mukundan et al.

Background/Objectives: Artificial Intelligence (AI) is improving dentistry through increased accuracy in diagnostics, planning, and workflow automation. AI tools, including machine learning (ML) and deep learning (DL), are being adopted in oral medicine to improve patient care, efficiency, and lessen clinicians’ workloads. AI in dentistry, despite its use, faces an issue of acceptance, with its obstacles including ethical, legal, and technological ones. In this article, a review of current AI use in oral medicine, new technology development, and integration barriers is discussed. Methods: A narrative review of peer-reviewed articles in databases such as PubMed, Scopus, Web of Science, and Google Scholar was conducted. Peer-reviewed articles over the last decade, such as AI application in diagnostic imaging, predictive analysis, real-time documentation, and workflows automation, were examined. Besides, improvements in AI models and critical impediments such as ethical concerns and integration barriers were addressed in the review. Results: AI has exhibited strong performance in radiographic diagnostics, with high accuracy in reading cone-beam computed tomography (CBCT) scan, intraoral photographs, and radiographs. AI-facilitated predictive analysis has enhanced personalized care planning and disease avoidance, and AI-facilitated automation of workflows has maximized administrative workflows and patient record management. U-Net-based segmentation models exhibit sensitivities and specificities of approximately 93.0% and 88.0%, respectively, in identifying periapical lesions on 2D CBCT slices. TensorFlow-based workflow modules, integrated into vendor platforms such as Planmeca Romexis, can reduce the processing time of patient records by a minimum of 30 percent in standard practice. The privacy-preserving federated learning architecture has attained cross-site model consistency exceeding 90% accuracy, enabling collaborative training among diverse dentistry clinics. Explainable AI (XAI) and federated learning have enhanced AI transparency and security with technological advancement, but barriers include concerns regarding data privacy, AI bias, gaps in AI regulating, and training clinicians. Conclusions: AI is revolutionizing dentistry with enhanced diagnostic accuracy, predictive planning, and efficient administration automation. With technology developing AI software even smarter, ethics and legislation have to follow in order to allow responsible AI integration. To make AI in dental care work at its best, future research will have to prioritize AI interpretability, developing uniform protocols, and collaboration between specialties in order to allow AI’s full potential in dentistry.

Haiping Du, Linping Chan, Jun Tong et al.

Ahlam I. Almusharraf

This study investigates the complex duality of automation and its impact on sustainable development, encompassing the factors of economic growth, social equity, and environmental sustainability. Innovations in artificial intelligence, robotics, and machine learning are driving automation and transforming industries through improved production, operational efficiency, and resource optimization. However, the rapid integration of automation has created a paradox. While it offers opportunities for resource optimization and technological advancement, it exacerbates challenges such as income inequality, environmental degradation, and social displacement. These issues underline the need for balanced and inclusive approaches to automation’s implementation. Automation contributes substantively to GDP growth because it raises labor productivity, yet it has arguably enhanced income inequality by eliminating low-skilled jobs. Automation improves energy efficiency and aids in renewable energy integration but increases overall energy effectiveness, leading to concerns regarding ecological sustainability. This study applied a quantitative methodology using longitudinal data from 2000 to 2023 and regression models to examine sustainability metrics influenced by automation. The findings highlight the potential of automation to reform effective forms of manufacturing, encourage environmental innovation, and identify the need for systemic governmental policies. Specifically, the results indicate that automation has contributed to a 25% increase in labor productivity across sectors, a 15% reduction in energy intensity per unit of GDP, and a 12% rise in the Gini index, signaling growing income inequality. These quantitative outcomes emphasize both the opportunities and challenges posed by automation. By integrating technological advancements with sustainability goals, automation can act as a transformative instrument to promote ecological conservation, equitable economic development, and social justice. The paper concludes with recommendations for governments and industry leaders to incorporate automation into sustainable development objectives, ensuring the equitable distribution of its advantages, while alleviating socio-environmental hazards.

Donato Romano

Entomology has seen remarkable advancements through the integration of robotics, artificial intelligence (AI), and biomimetic engineering. These technological innovations are revolutionizing how scientists study insect behavior, ecology, and management. Robotics and AI offer unprecedented precision and efficiency in monitoring and controlling insect populations. Biomimetics provides new ways to understand and replicate insect abilities in bioengineered systems. This mini-review highlights recent developments in these fields, focusing on key studies exemplifying the transformative potential of these technologies. I explore their applications, benefits, and challenges, aiming at providing an overview of the current state and future directions in insect science and management.

Rubén Alonso, Tomás F. Sánchez, Diego A. Alfaro et al.

Pilot lines have become a key element in modern industry. The demands for resilience, human-centricity, and sustainability in Industry 5.0, combined with technological innovations, highlight the critical role of these lines in the new industrial paradigm. Pilot lines facilitate the validation of processes and the reduction in uncertainties, making them essential tools for future industries. This article examines the current state of pilot lines and evaluates their alignment with Industry 5.0 principles. As part of this analysis, the GAMHE 5.0 pilot line is presented as a line designed with a focus on automation and robotics, meeting the requirements of the industries of the future. This article also details a series of case studies conducted on the pilot line, demonstrating its flexibility and adaptability. Finally, the advantages and disadvantages of small-scale lines are analyzed within the context of Industry 5.0, emphasizing their importance in balancing technology, human factors, and sustainability.

O. Ibitoye, O. Ayeni, O. Ayanniyi et al.

Agha Shadab Ali, Ruhanita Maelah

Shared service centre is a transformative organizational approach that fuels operational efficiency, cost reduction, and elevated service delivery across diverse industries. Technological innovation is paramount for driving organizational success, fostering competitive advantage, and enabling sustainable growth in today's dynamic business landscape. The purpose of this research article is to investigate the impact of technological innovations on the sustainability performance of shared service centers. Semi-structured email interviews were conducted with eleven practitioners from multinational shared services in Malaysia. The data was analyzed using structural and pattern coding, and six phases of thematic analysis were applied. The results reveal several themes related to innovative technologies in shared services, including robotic process automation, efficiency in service delivery, remote access, cost-effectiveness, customer satisfaction, and paper waste reduction, that practitioners consider relevant for sustainable performance in shared services. The findings have theoretical and managerial implications, emphasizing the significance of technological innovation approaches and sustainable performance in supporting technologies. This study provides insights for SSCs to adopt innovative technologies for improving their sustainability performance and achieving business goals.

W. Syed, Abubakar Mohammed, Janamolla kavitha Reddy et al.

The accelerating adoption of artificial intelligence (AI) technologies in the banking sector has introduced transformative possibilities for enhancing security frameworks against increasingly sophisticated cyber threats. This research investigates the technical innovations driven by AI, such as machine learning algorithms, biometric authentication systems, and natural language processing, and their impact on improving fraud detection, cybersecurity monitoring, and compliance automation. The paper identifies how AI systems, through real-time analysis of large-scale transaction data, can locate abnormal behavioral patterns and respond proactively to potential threats, significantly reducing human error and response time. A detailed analysis of the current literature reveals a significant research gap in integrating explainable AI, secure data governance frameworks, and scalable models suited for diverse banking environments. The outcome of this research highlights the need for a balanced approach that fosters technological innovation while addressing regulatory compliance, ethical concerns, and operational constraints, paving the way for a secure and intelligent banking infrastructure.

Natalia Wagner, M. Ingaldi

Abstract By introducing collaborative robots (cobots) and Autonomous Mobile Robot (AMR) technologies into a company’s production and logistics processes and fostering effective human-machine interactions, businesses can unlock the full potential of Industry 4.0 and strategically position themselves for the innovations of Industry 5.0. This paper aims to identify development trends of cobot and AMR technologies, invention patterns, the technological maturity of both solutions, and key application sectors. The study utilised a literature review, analysis of market reports, and patent analysis. A parallel analysis of patent collections obtained for cobots and AMRs was conducted, taking into account development trends, leading patent applicants, technological influence, patent power index, invention S-curve, and patent-based maturity rate. The results show that both cobot and AMR technologies have been developing extremely dynamically over the last ten years, and the rapid growth in interest in these technologies coincides with the popularisation of the Industry 4.0 concept. Comparing the dynamics of knowledge development for both solutions, cobots take the lead in this race. For cobots, the technical knowledge accumulated, defined by the number of patent families, is greater, and its annual growth is more dynamic. The development of technological knowledge and the increase in the use of cobots stimulate each other. AMRs, on the other hand, characterise a greater continuation of research and higher spillover of inventions to various technological fields. Both technologies are on the rising arm of the S-curve, and the saturation level is still far away, which means that further research in both areas is recommended.

Roly Gutarra Romero, Alma Gabriela Valente Mercado, Luis Ramírez Sirgo

In recent years, the topic of dynamic capabilities has acquired new content. As higher-order competencies, they allow one to constantly update oneself with new knowledge, flexibly recombine resources, and adapt to a rapidly changing environment. A key part of dynamic capabilities is working with the future, starting with basic skills - futures literacy (FL). Since this competence is key to the human resources of organizations, its development seems important, starting with university programs. For a long time, there were no objective tools for measuring the degree of their mastery. The authors of this article attempt to fill this problem by offering an innovative approach to identifying and standardizing the assessment of FL competence. Six theoretical dimensions of FL are proposed as a basis for grouping assessment criteria and compiling final assessments and their interpretation. The corresponding dimensions, such as FL sub-competencies that include foresight, the assessment of future scenarios, and decision-making under uncertainty, can be assessed independently of each other. The ability to measure the initial level of FL will allow for the development of more effective educational programs for the development of this competence.

Obinna Joshua, Ochulor, Obinna Joshua Ochulor et al.

This paper examines the technological advancements in onshore and offshore drilling operations, emphasizing their significance, challenges, and environmental considerations. Technological innovations, including automation, data analytics, and real-time monitoring, have transformed drilling practices, enhancing efficiency, safety, and environmental sustainability. By comparing onshore and offshore applications, the paper evaluates the effectiveness of these advancements in addressing the unique challenges of each environment. Key areas of focus include efficiency improvements, safety enhancements, environmental impacts, and regulatory compliance. Through case studies and analysis, the study aims to provide valuable insights into the current state of onshore and offshore drilling operations and identify opportunities for innovation and improvement. Ultimately, the findings contribute to advancing sustainable practices, mitigating environmental risks, and fostering responsible resource extraction in the oil and gas industry. This comparative study delves into the dynamic landscape of technological advancements within onshore and offshore drilling operations. It explores the evolving role of automation, data analytics, and real-time monitoring in revolutionizing drilling practices, offering insights into their implications for efficiency, safety, and environmental stewardship. By juxtaposing the unique challenges and operational requirements of onshore and offshore environments, the study underscores the importance of a nuanced understanding of technological applications. Through rigorous analysis and case studies, it illuminates the interplay between advancements and environmental considerations, shedding light on opportunities for innovation and sustainable development. The study's comprehensive scope encompasses efficiency gains, safety protocols, environmental impact mitigation, and regulatory compliance, providing a holistic view of the transformative potential of technology in the drilling industry. Ultimately, the study serves as a catalyst for informed decision-making, fostering dialogue, and driving forward-looking strategies for the future of onshore and offshore drilling operations.

Onyeka Franca Asuzu, Glory Ugochi Ebirim, Ifeyinwa Francisca Unigwe et al.

The landscape of accounting and auditing is undergoing a transformative evolution, driven by rapid technological advancements, regulatory changes, and shifting business paradigms. This comprehensive review delves into the contemporary innovations shaping the realm of accounting and auditing and assesses their profound implications for U.S. businesses. Technological innovations, particularly the integration of artificial intelligence and machine learning, have revolutionized traditional accounting processes. Automation tools and advanced data analytics are streamlining routine tasks, enhancing accuracy, and enabling accountants to focus on more strategic, value-added activities. The paper explores how these technological advancements are reshaping the skill sets required in the accounting profession and the consequent impact on professional development and education. Furthermore, the study investigates the evolving role of auditors in an era dominated by Big Data. The adoption of data analytics and blockchain technology is enhancing audit efficiency, transparency, and the overall quality of financial reporting. The analysis emphasizes the importance of auditors embracing these innovations to provide more timely, accurate, and insightful assessments of financial statements. Regulatory changes, such as the implementation of new accounting standards and reporting requirements, also feature prominently in this review. The study examines the challenges and opportunities arising from these regulatory shifts and assesses their impact on financial reporting practices in U.S. businesses. As businesses adapt to these innovations, the paper explores the broader implications for decision-making, risk management, and corporate governance. It sheds light on how the changing landscape of accounting and auditing influences the strategic decision-making processes of organizations, with a focus on fostering transparency and accountability. In conclusion, this comprehensive review synthesizes the multifaceted innovations in accounting and auditing, offering insights into the current trends shaping the industry and their far-reaching consequences for U.S. businesses. The research contributes to a deeper understanding of the challenges and opportunities associated with these transformations, guiding stakeholders in navigating this dynamic landscape effectively.

Naleen De Alwis, Hyung-Sik Nam

M. A. Lemay, Jeff Boggs

Automation and robotics technologies in agriculture promise to increase productivity with a smaller environmental footprint. However, adoption of agri-innovations is rarely a simple decision. The decision to adopt is determined by numerous factors. Employing a mixed methods narrative, interpretive knowledge synthesis, we review 72 unique studies between 2017–2021, and conduct a thematic analysis. Noting the innate complexity of agriculture, we identify 13 determinants of adoption of automation and robotic technologies in agriculture: data; farm characteristics and surrounding physical environment; farmer characteristics; policy and regulation; labour’s absorptive capacity; social elements; interoperability; standards; access to information; operational benefits; public infrastructure; technological characteristics; and uncertainty and risk. We conclude with seven observations. First, while automation and robotics are promising agri-innovations, they will not be appropriate or beneficial for all farms. There are other forms of agricultural innovation, and their uptake likely will always vary even within the same commodity and region. Second, taking a reductive approach to understanding adoption of agri-innovations may hinder the transformation to sustainable agriculture production systems; it is important to understand the role of complexity in shaping the dynamic interplay among determinants. Third, public infrastructure is more than just the Internet, yet there was little reference to other forms of public infrastructure in the dataset. Fourth, while many papers argue public policy is important for increasing the adoption of these innovations, few provide concrete policy suggestions or scalable examples. Fifth, trust and transparency are central to adoption. Technology developers need to take farmers concerns and needs seriously. Sixth, technology developers must offer practical solutions to real problems. Seventh, automation and robotics encompasses many technologies, and yet no standard or consistent terminology exists. This makes communication about these innovations more difficult. We propose a typology under the rubric of data-driven agricultural technologies.

A. Suychinov, Dinara Akimova, Aitbek Kakimov et al.

This thorough analysis traverses the ever-changing terrain of meat processing, revealing a story intertwined with technological innovations, environmentally friendly methods, and the revolutionary rise of cultured meat production. The amalgamation of sustainable polymers, sophisticated composite coatings, and potent antioxidant agents strikingly demonstrates the sector's dedication to novelty and ecological accountability. Diagrammatic depictions outline tactical approaches to lowering carbon emissions, highlighting the circular economy in terms of material recycling and the creative recycling of agricultural and food waste into environmentally acceptable packaging. Modern meat processing techniques, automation, and smart technology are all explored, emphasising waste minimization, energy efficiency, and sustainable practices.In terms of the future, the assessment offers a peek at how biotechnological developments and uses of nanotechnology will combine to transform how meat is produced. The integration of precision biotechnology, ethical concerns, and sustainability ushers a new era of responsible and creative food production, positioning the meat processing sector as a pathfinder in addressing consumer needs

A. Rahman, Hanif Bhuiyan

Visual data proliferation with technological innovations is progressively moving forward, bringing automation, digitization, and smartness to various aspects of daily lives. These visual data-dependent technologies need to be assessed during their development to ensure the quality of services. Consequently, when appropriate quality assessment metrics are unavailable, the advancement of image processing technologies is hindered. This preliminary work addresses the disparity between the rapid advancement of image processing-based algorithms and the lag in developing image quality assessment (IQA) methods while briefly discussing future prospects. The shortcomings in IQA development are discussed by broadly categorizing application areas into human visual system (HVS)-based and computer vision-based, while highlighting the trends and necessity of developing application-specific IQA methods. Despite the existence of several emerging IQAs, this preliminary communication indicates significant opportunities for objective IQA developments in both application areas to support technological advancements. Hence, this work can serve academic and industrial communities by providing guidance for expediting IQA developments.

Joseph Antwi Baafi, Michael Kwame Asiedu, P. Kumah

This theoretical paper investigates the impact of digitalization, automation, and artificial intelligence (AI) on environmental regulations, specifically through the lens of the Pollution Haven Hypothesis (PHH). It explores how these advancements influence pollution intensity and environmental compliance costs, challenging the traditional understanding of the PHH. Methodology. The study employs a Cobb-Douglas production function to model the relationship between technological innovations and environmental regulations. By integrating digitalization, automation, and AI into the model, the paper examines how these factors affect the economic incentives for firms to relocate to regions with lenient environmental standards. Findings. The analysis reveals that advancements in digitalization and automation reduce pollution intensity and lower the costs of complying with strict environmental standards. As a result, the economic incentive to relocate to pollution havens diminishes. In an open economy, the combination of stringent environmental policies and technological innovations leads to reduced pollution levels and a shift toward cleaner production processes. Practical Implication. The findings suggest that integrating technological innovations into environmental policy can make adherence to stricter regulations more economically viable, thereby weakening the appeal of pollution havens. This has significant implications for global sustainability efforts, as it highlights the potential for technology to support more effective and equitable environmental regulations. Originality. This study introduces a novel perspective by directly linking technological innovations to shifts in capital allocation and the efficacy of environmental policies. It offers a fresh understanding of the PHH in the context of modern advancements, providing new understanding into the relationship between innovation and environmental regulation.

Iacob Postavaru, Emilia Bunea, Crina Pungulescu et al.

This paper explores the potential of large language models to enhance economics education through computational humor. We employ OpenAI’s GPT-4 model to infuse humor into summaries of three Nobel laureates’ contributions to economics and conduct a small empirical exercise with undergraduate students to test the pedagogical efficacy of computational humor. The results suggest that computer-generated humor may be an effective learning aid: the results of the students who rate the humorous versions of the instructional texts as genuinely funny are significantly better than the results of their peers who are not amused. Encouragingly for teachers who try to be funny but fail, we do not find evidence that ineffectual humor is detrimental to learning.

Сергій Орищенко, Віктор Орищенко

Під час робочого процесу навантажувач перемішується на майже горизонтальних майданчиках, допустимий ухил яких. Розрахунок поздовжньої стійкості навантажувачів ведеться з умови перекидання вперед з урахуванням того, що деформуються пневматичні шини, якщо пневмоколісний хід. Кут додаткового нахилу навантажувача вперед внаслідок деформації опор визначається співвідношенням сили тяжкості навантажувача з вантажем жорсткість ґрунту під переднім та заднім котками гусеничного ходу або радіальна жорсткість передніх та задніх пневматичних шин навантажувача на пневмоколісному ході; відстань між центром ваги навантажувача та вертикальною віссю, що проходить через точку перекидання. Тому при розрахунку поздовжньої стійкості гусеничного та пневмоколісного навантажувачів. Найменший запас поздовжньої стійкості має навантажувач у разі руху під ухил з одночасним гальмуванням машини та робочого обладнання при його опусканні. Положення робочого обладнання відповідає максимальному вильоту.