In product development design, not only functional aspects but also human factors such as emotional, psychological, and affective elements need to be considered. Kansei engineering (KE) is a methodology that integrate...
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Background: The Internet of Things (IoT) is an embryonic model that converts real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains, including healthcare, smart grid, a...
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Numerical analysis of few-atom cavity quantum electrodynamics (QED) is challenging due to the exponentially scaling size of the Hilbert space when multiple quantized electromagnetic modes are considered. To overcome t...
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Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains. Current methods for feature a...
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Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains. Current methods for feature attribution, which rely on "explaining" the predictions of end-to-end classifiers, suffer from imprecise feature localization and are inadequate for use with small sample sizes and high-dimensional datasets due to computational challenges. We introduce prospector heads, an efficient and interpretable alternative to explanation-based attribution methods that can be applied to any encoder and any data modality. Prospector heads generalize across modalities through experiments on sequences (text), images (pathology), and graphs (protein structures), outperforming baseline attribution methods by up to 26.3 points in mean localization AUPRC. We also demonstrate how prospector heads enable improved interpretation and discovery of class-specific patterns in input data. Through their high performance, flexibility, and generalizability, prospectors provide a framework for improving trust and transparency for ML models in complex domains. Copyright 2024 by the author(s)
In the context of printed circuit board (PCB) manufacturing, accessibility and affordability are pivotal, especially for individuals and institutions with limited financial resources. The advent of ultra-low-cost and ...
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Biomedical devices are indispensable in modern healthcare, significantly enhancing patients' quality of ***, there has been a drastic increase in innovations for the fabrication of biomedical devices. Amongst thes...
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Biomedical devices are indispensable in modern healthcare, significantly enhancing patients' quality of ***, there has been a drastic increase in innovations for the fabrication of biomedical devices. Amongst these fabrication methods, the thermal drawing process has emerged as a versatile and scalable process for the development of advanced biomedical devices. By thermally drawing a macroscopic preform, which is meticulously designed and integrated with functional materials, hundreds of meters of multifunctional fibers are produced. These scalable flexible multifunctional fibers are embedded with functionalities such as electrochemical sensing, drug delivery, light delivery, temperature sensing, chemical sensing, pressure sensing, etc. In this review, we summarize the fabrication method of thermally drawn multifunctional fibers and highlight recent developments in thermally drawn fibers for modern biomedical application, including neural interfacing, chemical sensing, tissue engineering, cancer treatment, soft robotics and smart ***, we discuss the existing challenges and future directions of this rapidly growing field.
MediVision revolutionizes medical imaging by integrating Augmented Reality (AR) and Virtual Reality (VR) with traditional 2D data. This platform transforms standard DICOM images into immersive 3D models, enhancing dia...
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Agriculture is one of the sources of income a region can rely on to support its economy. Traditional agriculture relies primarily on human performance and observation, resulting in greater production costs and, subseq...
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ISBN:
(纸本)9781665410205
Agriculture is one of the sources of income a region can rely on to support its economy. Traditional agriculture relies primarily on human performance and observation, resulting in greater production costs and, subsequently, higher selling prices. Artificial intelligence-based technology can be used to reduce production costs, increase productivity, and provide consumer convenience. An indicator that is easy to interpret in measuring the quality and optimization of plant growth is the visualization of the condition of the leaves. The artificial intelligence technique that can be implemented in this regard is the object detection model. However, the challenge is the complex, multi-object, and multi-intersection condition of the leaves, which causes the model to be less optimal in conducting classification and detection tasks regarding whether the leaf condition is good or not. A YOLOv7 model will be employed in order to detect leaf quality, whether in an 'optimal' or 'not optimal' condition. To enhance the model's performance by improving accuracy through feature extraction enhancement, YOLOv7 will be integrated with the attention module, called the convolutional block attention module (CBAM). The case study in this research is detecting a mango plant which is one of the plants that can provide a high economic impact and the object observed is the mango plant leaf. Several previous studies related to the implementation of attention modules in object detection include the improved pest-YOLO for real-time pest detection by combining YOLOv3 with efficient channel attention (ECA) and a transformer encoder. The ECA module and transformer encoder were integrated into the backbone and neck block systems of YOLO [1]. The lightweight YOLO model combined with SE-CSPGhostnet by improving the backbone block which employs squeeze-and-excitation networks (SENet) and a convolution technique consisting of regular convolution and ghost convolution [2]. There is a highlighted improvem
An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound stat...
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An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound states in the continuum metasurfaces,which is essential for the geometric design of intrinsically chiral structures.
Anger affects muscle tension, cognitive performance, and overall well-being. Gait and balance are possible indicators of many emotional states. computer models can be used to study their relationship with anger. This ...
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