In recent years, distributed acoustic sensing has garnered significant interest in seismic monitoring due to its sensitivity to low frequencies, continuity of measurement in both time and space and the capacity to pro...
In recent years, distributed acoustic sensing has garnered significant interest in seismic monitoring due to its sensitivity to low frequencies, continuity of measurement in both time and space and the capacity to provide vast amounts of data regarding the conditions of large structures. This study aims to develop a metrological characterization system to evaluate the performance of the distributed acoustic sensing systems to reconstruct the mechanical wavefront and measure its propagation speed in polyurethane foams. The wave propagation speed measured using distributed acoustic sensing is compared with optical fiber Bragg grating sensors and piezoelectric accelerometer, and the difference is less than 1.5%. The results demonstrate that it is possible to reconstruct the mechanical wavefront using both instrumented sensors, thus validating the application of a distributed acoustic sensing system for mechanical wave measurement in polyurethane foams.
Filamentous-actin (F-actin) crosslinking within the cell cytoskeleton mediates the transmission of mechanical forces, enabling changes in cell shape, as occurs during cell division and cell migration. Crosslinking by ...
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Filamentous-actin (F-actin) crosslinking within the cell cytoskeleton mediates the transmission of mechanical forces, enabling changes in cell shape, as occurs during cell division and cell migration. Crosslinking by actin binding proteins (ABPs) generally increases the connectivity of the F-actin network, but also increases network rigidity. As a result, there is a narrow range in the concentration of crosslinker protein at which F-actin networks are both connected and labile. Another ABP, cofilin, severs F-actin filaments at high pH through increasing their bending flexibility and concentrating mechanical stress, inducing fragmentation. By contrast, at lower pH, cofilin increases filament flexibility yet does not sever. Instead, it forms disulfide bonds, which crosslink F-actin into bundles, and bundles into networks. Here, we combine light microscopy and rheology to determine the impact of two potentially opposing effects on the mechanics of F-actin networks—increased flexibility at the filament level, and increased connectivity at the network level. Indeed, by linear rheology, we find that these mechanisms are counterbalanced, such that cofilactin network moduli are only weakly dependent on cofilin concentration over a broad range, in contrast to the dramatic stiffening that occurs with F-actin crosslinking protein. Further, by nonlinear rheology, the network stiffens at a higher stress than crosslinking protein, indicative of a broader range in which the material remains flexible. These results may enable F-actin networks to increase connectivity without heavy penalties to rigidity, and thus provide a new route to modulating active polymer mechanics unseen using traditional F-actin accessory proteins.
This paper proposes an algorithm to optimize the walking of humanoid robots based on the inverse kinematic model combined with a Genetic Algorithm. The objectives are to improve the sagittal displacement of the robot ...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
This paper proposes an algorithm to optimize the walking of humanoid robots based on the inverse kinematic model combined with a Genetic Algorithm. The objectives are to improve the sagittal displacement of the robot and reduce possible lateral deviations during a predetermined path. The foot of the humanoid performs a tapered motion, an approximate ellipse. Horizontal and vertical speeds and the angulation of the humanoid trunk are the input parameters of the algorithm. The algorithm utilizes the input information to calculate the inverse kinematics, and then it submits the obtained result to an evaluation function. We develop a virtual simulator and a robotic platform with 14 degrees of freedom to validate the proposed algorithm. We then test a prototype using the best result obtained in the simulations.
This study presents a methodology for evaluating energy efficiency projects carried out in low-income communities in the scope of the largest Brazilian Energy Efficiency program, known as PEE. The methodology is based...
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Fleet operations have been one of the main concerns of a wide range of industries, particularly those industries in which transportation plays a pivotal role for operational continuity, such as logistics service provi...
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Fleet operations have been one of the main concerns of a wide range of industries, particularly those industries in which transportation plays a pivotal role for operational continuity, such as logistics service providers and public transportation. In addition, accentuated by the social and economic globalization, new scenarios and higher requirements were introduced to the transportation sector and, therefore, the need for advanced techniques, such as optimization, traffic modeling, and machine learning, to improve fleet operations, is growing. As for machine learning, although an increasing number of data-driven methods are observed in manufacturing and mobility solutions, there is still a gap in terms of literature reviews related to machine learning applications in fleet operations. Based on this gap, a systematic literature review was conducted, and several applications related to machine learning in fleet operations were identified, most of them encompassing aspects related to predictive maintenance of mechanical systems and components. It was also identified that most of the studies were based on a single data source and did not approach aspects related to the deployment of the machine learning models and data analysis workflows. Therefore, based on the findings from this literature review, the present paper aims to present an overview of the main machine learning applications in fleet operations and propose a data analysis workflow for the connectivity monitoring of heavy vehicles based on multiple data sources.
An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets subm...
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Industrial prognostics aims to develop data-driven methods that leverage high-dimensional degradation signals from assets to predict their failure times. The success of these models largely depends on the availability...
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With the rise of interconnected systems, security has become a crucial concern. As a result, there has been a growing interest in developing low-cost embedded cryptographic algorithms that are lightweight and can be i...
With the rise of interconnected systems, security has become a crucial concern. As a result, there has been a growing interest in developing low-cost embedded cryptographic algorithms that are lightweight and can be integrated into System-on-Chip (SoC) devices. Digital chaotic systems have emerged as a promising approach for building secure communication systems, where various cryptosystems utilize chaotic dynamics to encrypt images into noise-like representations. Recent studies have demonstrated that finite-precision error can be used to derive chaos, which can be systematically applied to encrypt images. However, there is a lack of research on how SoC-based design constraints affect the overall performance of image encryption systems, especially for applications that are sensitive to latency. This study aims to address this gap by presenting an efficient architecture that explores a hardware/software co-design for image encryption based on finite-precision error, specifically designed for resource-limited devices and latency-sensitive applications. Our platform performs the capture and encryption of images with a size of 320 × 240. Using a benchmark image, results show that the developed cryptosystem architecture can encrypt images efficiently while offering low hardware occupation.
This study investigates how artificial intelligence (AI) can transform audit processes, including how AI can be used in businesses to execute non-technical audit tasks and what effect this will have on those tasks. A ...
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ISBN:
(数字)9798331539603
ISBN:
(纸本)9798331539610
This study investigates how artificial intelligence (AI) can transform audit processes, including how AI can be used in businesses to execute non-technical audit tasks and what effect this will have on those tasks. A qualitative case study methodology is used in the research design to give detailed insights into how AI is being adopted by businesses. This study aims to analyze the aspects that impact AI implementation from the viewpoints of managers, auditors, and other stakeholders. The findings show that artificial intelligence (AI) has a great deal of promise for non-technical audit procedures in businesses. AI can automate tedious jobs, evaluate large data sets to identify hazards and enhance teamwork and communication. These developments may lead to increased productivity, maybe better audit quality, and more effective processes. But there are still difficulties. Data quality is essential to the success of AI integration, and auditors may exhibit bias in favor of human professionals. Careful thought must also be given to ethical issues about transparency and possible job displacement. All things considered, this study adds significant knowledge to both the academic literature and real-world auditing applications. It improves our comprehension of the function of AI in the industry and provides useful information for people involved in information technology development, audit, and legislation.
In the current day, digital transformation is imperative; both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One dif...
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ISBN:
(数字)9798350363104
ISBN:
(纸本)9798350363111
In the current day, digital transformation is imperative; both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One difficulty that has to be addressed is the desire from customers for quick and useful services. Traditional procedures need to be replaced with digital ones. Furthermore, banking organizations will have a competitive edge in the current market if they are successful in this digital transformation process. Successful transformation, however, does not happen by accident; in fact, the likelihood of completing this change is seen to be very low, necessitating rigorous planning for a company that is ready for the future. There are several components to the preparation in question, both internal and external. In this situation, the company's ability to combine and rearrange its resources quickly is essential for adapting to the ever-changing business environment.
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