In this work, an optical fiber sensor based on surface plasmon resonance (SPR) is proposed for simultaneous measurement of relative humidity (RH) and temperature, which is constructed by connecting two segments of thi...
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This research analyzes cost account-level detail from ten similar satellite programs to assess the relationship between cost and schedule variances. A model is defined to break activity into two types: level of effort...
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Intelligent systems focused on traffic management have been in evidence in recent years, and applications related to vehicle detection and tracking, speed estimation, and traffic flow identification have become an int...
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ISBN:
(数字)9798350360868
ISBN:
(纸本)9798350360875
Intelligent systems focused on traffic management have been in evidence in recent years, and applications related to vehicle detection and tracking, speed estimation, and traffic flow identification have become an interesting research topic. For the previously mentioned tasks, a large number of data has to be gathered to train deep learning algorithms, but collecting that data can be a time and resource-consuming task. Therefore, the use of synthetic data has become a viable option that helps to minimize data acquisition problems, but when misused, it can negatively impact the model's quality. This paper presents a systematic literature review based on the use of synthetic images to train object detection models in urban scenarios, aiming at identifying the ideal ratio between real and synthetic images that can benefit those models and the best methods to produce synthetic images. This study identified that there is no consensus on the number of synthetic images that can help to generate a more accurate model, due to the low number of papers addressing this relationship, however, it was noted that the use of generative adversarial networks (GANs) can create synthetic images that are more similar to real images, bringing benefits for training detection models, although without identifying how the use of images generated by this method can help in the relationship between synthetic and real.
作者：
Gurganus, Jamie R.Malschutzky, Michael M.Do Carmo Santos, Joao CarlosZupan, MarcDos Santos, Abel Dias
Engineering & Computing Education Program & Graduate School Baltimore United States
Centre for Teaching Development and Innovation Department of Management Sciences Hochschule Bonn-Rhein-Sieg Sankt Augustin Germany
College of Engineering and Information Technology Department of Mechanical Engineering Baltimore United States
Departamento de Engenharia Mecânica Porto Portugal
Today's pluralistic and globalized society requires a global perspective in how we think, view ourselves, and relate to others to collaborate successfully with people with different cultural backgrounds. To suppor...
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This study investigates the determinant factors influencing consumers' intention to choose an e-commerce platform (online shop) through the lens of an extended Theory of Planned Behavior (TPB) approach. By examini...
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ISBN:
(纸本)9798400710742
This study investigates the determinant factors influencing consumers' intention to choose an e-commerce platform (online shop) through the lens of an extended Theory of Planned Behavior (TPB) approach. By examining key elements such as service quality, user interface design, customer support, transparency, personalization, and security measures, the research provides a comprehensive understanding of how these factors contribute to consumer behavior in the online shopping environment. The findings underscore the critical role of service quality in shaping consumer intentions, highlighting the need for online shopping platforms to prioritize and continuously enhance their service offerings. Additionally, the study emphasizes the importance of a user-friendly interface, responsive customer support, transparency in communication, personalized experiences, and robust security measures in fostering consumer trust and satisfaction. These insights offer practical recommendations for e-commerce platforms to improve their service quality, ultimately leading to increased consumer engagement and loyalty. The research concludes that a focus on delivering exceptional service quality, coupled with informed consumer decision-making, can significantly enhance the overall online shopping experience, benefiting both consumers and platform providers.
Abstract: With the development of Internet technology and the popularization of mobile devices and so on, e-commerce has entered a period of high-speed development, consumers are faced with a wealth of channel choices...
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ISBN:
(纸本)9798400710742
Abstract: With the development of Internet technology and the popularization of mobile devices and so on, e-commerce has entered a period of high-speed development, consumers are faced with a wealth of channel choices, and the competition for traffic in different channels is becoming more and more intense, which poses a great challenge to enterprises. From the perspective of PPM theoretical model to study the consumers' migration intention of different online channels, using SPSS software and Amos to construct structural equations for the influencing factors of consumers' migration intention of different online channels, the results show that the push force and pull force positively affect the consumers' migration intention, and the push force has the greatest influence on the consumers' migration intention. It provides a basis for the live e-commerce platform to propose measures to enhance user channel stickiness.
Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems c...
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Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems capable of identifying defects. This research proposes a framework for recommending machine learning algorithms that diagnose and detect broken bar defects in three-phase induction motors under transient operation based on artificial intelligence. Employing experimental data, features were extracted and selected based on current, voltage, and vibration. A protocol of insertion of white noise showed that the proposed framework admitted 80% of noise without losing the predictive capacity based on a multicriteria performance measure.
The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity management (Area-BCM). This prelimi...
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ISBN:
(数字)9798350353952
ISBN:
(纸本)9798350353969
The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.
This paper presents a framework for portfolio selection using the mean-variance model utilizing Australian fintech company stocks before and during the COVID-19 pandemic. The investment pool consisting of fintech comp...
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Cobalt titanate, CoTiO3, is a honeycomb antiferromagnet recently confirmed experimentally to host Dirac magnons, topological spin-orbit excitons, and chiral phonons. Here, we investigate a magnon gap at the zone cente...
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Cobalt titanate, CoTiO3, is a honeycomb antiferromagnet recently confirmed experimentally to host Dirac magnons, topological spin-orbit excitons, and chiral phonons. Here, we investigate a magnon gap at the zone center which calls for a refined spin Hamiltonian. We propose a microscopic model for the magnon gap and attribute it to a lattice-distortion (phonon)-induced higher-order spin interaction. Strong magnetoelastic coupling in CoTiO3 is also evident in Raman spectra, in which the magnetic order exerts a stronger influence on phonons corresponding to in-plane ionic motions than those with out-of-plane motions. We further examine the evolution of the zone-center magnons in a high magnetic field up to 18.5 T via THz absorption spectroscopy measurements. Based on this field dependence, we propose a spin Hamiltonian that not only agrees with magnon dispersion measured by inelastic neutron scattering but also includes fewer exchange constants and a realistic anisotropy term. Our work highlights the broad implications of magnetoelastic coupling in the study of topologically protected bosonic excitations.
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