A biological signal is a weak signal, so it is necessary to find new or improve methods of its processing. The paper proposes the implementation of the modular signal processing system for processing and further analy...
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A biological signal is a weak signal, so it is necessary to find new or improve methods of its processing. The paper proposes the implementation of the modular signal processing system for processing and further analysis of the most commonly used biological signals in diagnostics, such as electrocardiogram, electromyogram, electroencephalogram, phonocardio-gram or pulse wave but it is possible to employ it also in other signal processing areas. Based on contemporary literature, a wide range of the processing and filtering methods are embedded (digital filters, adaptive filters, wavelet transform, independent and principal component analysis etc.) into user-friendly interface, serving for the testing of the accuracy and suitability of the individual techniques for the signal processing. The software is designed to ensure as greatest as possible area of the biological signal processing so that basic modifications or analysis of any one-dimensional biological signal can be made.
This paper deals with the using of adaptive filtering in the area of telecommunication technology. The study focuses on the possibilities of design and implementation of adaptive filters based on virtual instrumentati...
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This paper deals with the using of adaptive filtering in the area of telecommunication technology. The study focuses on the possibilities of design and implementation of adaptive filters based on virtual instrumentation in the LabVIEW development environment from the American company National Instruments. The selected adaptive algorithms (LMS, NLMS, RLS, QR-RLS) are implemented both in LabVIEW and C# programming language in the form of dynamically linked DLL (Dynamic-Link Library) libraries. The experiments test the reliability and speed of the implemented algorithms using them for the suppression of the echo in sound signal. Based on the findings from the implementation, a comparison of both options is made by evaluation of the computation time and improvement of signal-to-noise ratio (SNR).
This study aimed to develop an interpretable prognostic model with a nomogram for Non-Small Cell Lung Cancer (NSCLC) recurrence prediction following complete resection, using multi-modality PET/CT fusion radiomics and...
This study aimed to develop an interpretable prognostic model with a nomogram for Non-Small Cell Lung Cancer (NSCLC) recurrence prediction following complete resection, using multi-modality PET/CT fusion radiomics and patients’ clinical features. Retrospectively, 181 NSCLC patients who had undergone 18 F-FDG PET/CT scan were enrolled and split into training (2/3) and testing (1/3) partitions. Before image fusion, PET and CT images were registered, resized to equal isotropic voxel size, and clipped and normalized. Guided Filtering Fusion GFF algorithm was used for image fusion. Two hundred eighteen radiomic features were extracted from each PET, CT, and fused image, including morphological, first-order statistical, and texture features. Clinical features included age, sex, smoking status, weight, radiation, chemotherapy, pathological stage, etc. Feature selection and univariate and multivariate modeling were performed using the CoxBoost algorithm. Harrell’s Concordance index (C-index) was used to evaluate the performance of the models, and compare C test was used to statistically compare the performance of the models (p-values < 0.05 were considered significant). Clinical, Clinical+PET, Clinical+CT, and Clinical+GFF resulted in c-indices (confidence interval) of 0.701 (0.589-0.812), 0.757 (0.647-0.867), 0.706 (0.607, 0.807), and 0.824 (0.751-0.896), respectively. Statistical comparison of the performance of different models with the Clinical model revealed that while PET and GFF features can significantly increase the performance (p-values 0.009 and 0.001, respectively), CT features did not significantly improve the performance of the Clinical model (p-value 0.279). Therefore, the nomogram was developed based on the Clinical+GFF model (with the best performance). Radiomic features extracted from PET and PET/CT fusion images can improve the recurrence prognosis in NSCLC patients compared to the conventional clinical factors alone.
作者:
Bin LiDepartment of Electrical
Computer and Biomedical Engineering University of Rhode Island Kingston Rhode Island USA
With the rapid growth of wireless compute-intensive services (such as image recognition, real-time language translation, or other artificial intelligence applications), efficient wireless algorithm design should not o...
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ISBN:
(数字)9781728109626
ISBN:
(纸本)9781728109633
With the rapid growth of wireless compute-intensive services (such as image recognition, real-time language translation, or other artificial intelligence applications), efficient wireless algorithm design should not only address when and which users should transmit at each time instance (referred to as wireless scheduling) but also determine where the computation should be executed (referred to as offloading decision) with the goal of minimizing both computing latency and energy consumption. Despite the presence of a variety of earlier works on the efficient offloading design in wireless networks, to the best of our knowledge, there does not exist a work on the realistic user-level dynamic model, where each incoming user demands a heavy computation and leaves the system once its computing request is completed. To this end, we formulate a problem of an optimal offloading design in the presence of dynamic compute-intensive applications in wireless networks. Then, we show that there exists a fundamental logarithmic energy-workload tradeoff for any feasible offloading algorithm, and develop an optimal threshold-based offloading algorithm that achieves this fundamental logarithmic bound.
This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological...
This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient's breath, thereby augmenting future diagnostic and therapeutic initiatives.
This paper covers our second version of visible light communication system, which was based on orthogonal-frequency division multiplexing. Whole platform is implemented in LabVIEW and is running on National Instrument...
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This paper covers our second version of visible light communication system, which was based on orthogonal-frequency division multiplexing. Whole platform is implemented in LabVIEW and is running on National Instruments software defined radios. Its design is thoroughly explained, and a number of measurements is presented. Certain limitations are described, and upgrade paths are mentioned as well.
Modern cars are full of embedded systems that control cars' components. For diagnostics purposes On-Board Diagnostics (ODB) is used. ODB can be used to read variety of car parameters. The paper describes how such ...
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Increased coastal erosion rates have forced communities to rethink how to manage vulnerable coastlines. In many locations there is a trend towards implementing temporary engineering solutions, such as geotextile sand ...
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There is a rich theory and plethora of algorithms in the literature aiming at the efficient scheduling of stochastic networks. These solutions are predominantly designed under the assumption of traffic demands that ar...
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