Design considerations for implantable and wearable antennas

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Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

Deep learning has emerged as a promising avenue for automatic mapping, demonstrating high efficacy in land cover categorization through various semantic segmentation models. Nonetheless, the practical deployment of these models encounters important challen ...

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

At the conceptual stage, building performance simulation (BPS) based evaluations are being increasingly used for tasks such as ranking of competing massing design proposals. However, such conceptual stage evaluations suffer from information deficiency in b ...

Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...

The presence of conversational agents (or chatbots) in educational contexts has been steadily increasing over the past few years. Recent surveys have shown widespread interest in the use of chatbots in education, both for research and practice. Although th ...

Financial criteria in architectural design evaluation are limited to cost performance. Here, I introduce a method – Automated Design Appraisal (ADA) – to predict the market price of a generated building design concept within a local urban context. Integrat ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

Driven by the rising popularity of chatbots such as ChatGPT, there is a budding line of research proposing guidelines for chatbot design, both in general and specifically for digital education. Nevertheless, few researchers have focused on providing concep ...

To study the resilience of distributed learning, the “Byzantine" literature considers a strong threat model where workers can report arbitrary gradients to the parameter server. Whereas this model helped obtain several fundamental results, it has sometimes ...

Model and Data: Dujardin, J.; Lehning, M. Wind-Topo_model. EnviDat 2022 ...

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

With the application requirements of wireless technology in implantable bioelectronics, knowledge of the fundamental limits for implanted antennas becomes critical. In this work, we investigated the variation of maximum power density within simplified body ...

Flood prediction in ungauged catchments is usually conducted by hydrological models that are parameterized based on nearby and similar gauged catchments. As an alternative to this process-based modelling, deep learning (DL) models have demonstrated their a ...

The ability to forecast human motion, called ``human trajectory forecasting", is a critical requirement for mobility applications such as autonomous driving and robot navigation. Humans plan their path taking into account what might happen in the future. S ...

Thanks to Deep Learning Text-To-Speech (TTS) has achieved high audio quality with large databases. But at the same time the complex models lost any ability to control or interpret the generation process. For the big challenge of affective TTS it is infeasi ...

Forest maps are essential to understand forest dynamics. Due to the increasing availability of remote sensing data and machine learning models like convolutional neural networks, forest maps can these days be created on large scales with high accuracy. Com ...

Vocational education and training (VET) is the most popular form of upper-secondary education in Switzerland, with more than two-thirds of the teenagers enrolling in a VET program after finishing their compulsory education. The vast majority of the Swiss V ...

Design considerations for implantable and wearable antennas

Chattez avec Graph Search

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