In this article we consider Bayesian parameter inference for a type of partially observed stochastic Volterra equation (SVE). SVEs are found in many areas such as physics and mathematical finance. In the latter field ...
详细信息
This thesis presents methods and approaches to image color correction, color enhancement, and color editing. To begin, we study the color correction problem from the standpoint of the camera's image signal process...
详细信息
Foreign Exchange or FOREX trading is not only done on foreign currencies but, FOREX also can be done on several commodities such as Gold, Silver, Oil. Gold is one of the most valuable commodities in the world. Investo...
详细信息
This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential...
详细信息
This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.
To develop the biomedical application using magnetic nanoparticles, the magnetization properties associated with the magnetic relaxation with respect to magnetic nanoparticles internalized into cells were important. I...
To develop the biomedical application using magnetic nanoparticles, the magnetization properties associated with the magnetic relaxation with respect to magnetic nanoparticles internalized into cells were important. In this study, magnetization properties of magnetic nanoparticles internalized into the cultured adherent cells were measured by evaluating harmonic intensities derived from the magnetization response, which were compared to the magnetization of magnetic nanoparticles dispersed in liquid and fixed with epoxy resin. In particular, the nano-volt harmonic signals were obtained in intracellular magnetic nanoparticles. It is indicated that the particle aggregation reduced the magnetization, and the particle physical rotation was inhibited in the intracellular environment.
This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter o...
详细信息
The Internet of Things (IoT) has grown rapidly in recent years, intending to affect everything from everyday life to large industrial systems. Regrettably, this has attracted the attention of hackers, who have turned ...
详细信息
Origami structures have been widely explored in robotics due to their many potential advantages. Origami robots can be very compact, as well as cheap and efficient to produce. In particular, they can be constructed in...
详细信息
Data communications within the smart power grid components are susceptible to cyberattacks due to the inter-connected nature of the grid and reliance on communication networks. Such cyberattacks can exploit the integr...
详细信息
ISBN:
(数字)9789464593617
ISBN:
(纸本)9798331519773
Data communications within the smart power grid components are susceptible to cyberattacks due to the inter-connected nature of the grid and reliance on communication networks. Such cyberattacks can exploit the integrity of the exchanged data and result in operational instability. Existing data-driven cyberattack detection systems (CDSs) are proposed in the literature but their effectiveness is only verified against one type of cyberattacks. In reality, a smart grid system could encounter more than one attack type at once. Thus, in this paper, we investigate the resilience of state-of-the-art data-driven CDSs against replay false data injection, adversarial evasion, and adversarial data poisoning attacks on a realistic IEEE 118-bus system model. It turns out that a convolutional recurrent graph autoencoder-based CDS offers an attack detection rate of 96 – 97.5%, which outperforms other machine learning and deep learning-based data-driven CDSs by 16 – 54% since it captures the recurrent and spatial aspects of the data without being trained on attack data.
Generative Artificial Intelligence (GenAI) represents a significant milestone in the development of artificial intelligence, bringing sophisticated AI capabilities into daily life and work. As we approach the era of H...
详细信息
ISBN:
(数字)9798331532093
ISBN:
(纸本)9798331532109
Generative Artificial Intelligence (GenAI) represents a significant milestone in the development of artificial intelligence, bringing sophisticated AI capabilities into daily life and work. As we approach the era of Hyper Intelligence (Hyper-I), a variety of critical challenges and emerging issues have come to light, ranging from computational complexity to ethical concerns. This paper explores the evolution of AI from the perspective of human learning, comparing machine and human intelligence, and identifying key considerations for the development of future AI systems. It also highlights the growing importance of regulating advanced AI models, such as Reinforcement Learning-based Long-Term Planning Agents, to ensure that Hyper-I remains under human control. Additionally, the paper discusses the computational complexity of transformer-based models, their applicability to intractable problems, and their role in cognitive building systems and resource-constrained environments through TinyML. By analyzing these pressing challenges, this work provides insights into the future of AI and the path toward responsible innovation in generative and hyper-intelligent systems.
暂无评论