Department of Defense (DoD) military systems designed to attack, protect, and provide tactical advantages to the warfighter increasingly push technological advances. systems and subsystems share data at high rates to ...
Department of Defense (DoD) military systems designed to attack, protect, and provide tactical advantages to the warfighter increasingly push technological advances. systems and subsystems share data at high rates to make quick decisions. Because of the rapid advancements in technology, the DoD Family of Testers (FoT) are unable to validate units under test (UUT) that use high-speed digital buses. Current and developing solutions to solve this problem are done in a closed architecture designed specifically for one DoD automatic test system (ATS). Technology Service Corporation's Automatic Test system (TSCATS) is being developed as a high-speed digital bus augmentation capability to the DoD FoTs leveraging IEEE standards to provide an open architecture framework. The discrete system can be remotely triggered and applicable to a wide range of DoD FoTs. The TSCATS utilizes a commercial off-the-shelf (COTS) PXIe hardware platform and a software Test Executive (TE) capable of parsing an automatic test mark-up language (ATML IEEE Std. 1671) test description (TD) document and using synthetic instruments to deliver and test high-speed communication protocols. Benefits to this approach include reduced life-cycle, TPS development, and re-host costs while providing DoD an augmented test capability for their ATS environment. The DoD is increasingly incorporating ATML as its standard language in describing all aspects of automated test systems and automatic testing. The sub-standard for IEEE Std. 1671, IEEE Std. 1671.1 - Standard for Automatic Test Markup Language Test Description, identifies and documents the necessary components for describing the testing procedure for a UUT. For a Test Program Set (TPS) developer, the test description provides important test information in developing software to validate a DoD UUT. The TSCATS hardware platform TE, Test Forge, provides test sequencing, parameter validation, data reporting, error handling, and UUT and ATE monitoring solutions.
Conventional iris identification systems have failed to manage environmental variables and changes in iris patterns, sometimes depending on handmade characteristics that may lack the delicate details required for reli...
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ISBN:
(数字)9798350367720
ISBN:
(纸本)9798350367737
Conventional iris identification systems have failed to manage environmental variables and changes in iris patterns, sometimes depending on handmade characteristics that may lack the delicate details required for reliable identification. The paper offers a revolutionary iris identification system based on deep learning, especially pre-trained Convolutional Neural Networks (CNNs) such as ResNet and VGG, which are fine-tuned utilizing transfer learning methods. The system is trained and verified using a variety of iris datasets, taking into account illumination fluctuations, occlusions, and other environmental conditions. Using these pre-trained CNN models, the proposed system intends to dramatically improve the accuracy and reliability of iris detection, even under difficult settings. The proposed system attains significant gains in recognition accuracy, even under challenging circumstances, thorough preprocessing, transfer learning, fine-tuning, and data augmentation. testing and validation show how effective the proposed system is; it has better performance metrics than existing systems, with 98.5% accuracy, 97.8% precision, 98.9% recall, and 98.3% F1-score, which are all higher than those of existing systems. The methodology also guarantees scalability and computing efficiency, confirming the proposed system's potential for accurate and dependable iris detection in practical settings. The reliability and efficiency of iris recognition technology have been significantly improved by these advances.
This article is based on the needs of the data transmission of UVA system design. Confliction between high speed on board gyroscope and low speed external wireless data transmission module is increasingly serious, bad...
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ISBN:
(纸本)9781845649302
This article is based on the needs of the data transmission of UVA system design. Confliction between high speed on board gyroscope and low speed external wireless data transmission module is increasingly serious, badly restricting the development of UVA. In order to solve this problem, this article use high-speed FIFO as data buffer, build up an interface of the UVA gyroscope. Gyroscope data is transferred accurately to ground station via high-speed FIFO which is built in FPGA. By this way we can highly improve the quality of data transmission, and achieve the communication between high-speed chips and low-speed equipments. The design works perfect in practical application, Stable and reliable data with low error rate and high stability is transmitted. After massive tests and validation, the entire FIFO based UVA interface works well.
Recent advances in medical imaging techniques have led to significant improvements in the management of prostate cancer (PCa). In particular, multi-parametric MRI (mp-MRI) continues to gain clinical acceptance as the ...
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ISBN:
(数字)9781728150239
ISBN:
(纸本)9781728150246
Recent advances in medical imaging techniques have led to significant improvements in the management of prostate cancer (PCa). In particular, multi-parametric MRI (mp-MRI) continues to gain clinical acceptance as the preferred imaging technique for non-invasive detection and grading of PCa. However, the machine learning-based diagnosis systems for PCa are often constrained by the limited access to accurate lesion ground truth annotations for training. The performance of the machine learning system is highly dependable on both quality and quantity of lesion annotations associated with histopathologic findings, resulting in limited scalability and clinical validation. Here, we propose the baseline MRI model to alternatively learn the appearance of mp-MRI using radiology-confirmed negative MRI cases via weakly supervised learning. Since PCa lesions are case-specific and highly heterogeneous, it is assumed to be challenging to synthesize PCa lesions using the baseline MRI model, while it would be relatively easier to synthesize the normal appearance in mp-MRI. We then utilize the baseline MRI model to infer the pixel-wise suspiciousness of PCa by comparing the original and synthesized MRI with two distance functions. We trained and validated the baseline MRI model using 1,145 negative prostate mp-MRI scans. For evaluation, we used separated 232 mp-MRI scans, consisting of both positive and negative MRI cases. The 116 positive MRI scans were annotated by radiologists, confirmed with post-surgical whole-gland specimens. The suspiciousness map was evaluated by receiver operating characteristic (ROC) analysis for PCa lesions versus non-PCa regions classification and free-response receiver operating characteristic (FROC) analysis for PCa localization. Our proposed method achieved 0.84 area under the ROC curve and 77.0% sensitivity at one false positive per patient in FROC analysis.
In order to promote the acceptance of cell-based toxicity testings, the accuracy of cytotoxicity test must be determined when compared to in vivo results. Traditional methods of cytotoxicity analysis, such as LC50 (co...
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In order to promote the acceptance of cell-based toxicity testings, the accuracy of cytotoxicity test must be determined when compared to in vivo results. Traditional methods of cytotoxicity analysis, such as LC50 (concentration where 50% of the cells are killed) can be problematic since they have been found to vary with time. Technological advances in cytotoxicity testing make it easy to record the dynamic data on changes in cell proliferation, morphology, and damage. To effectively and reasonably analyze the dynamic data, we present a new in vitro toxicity assessed method using the discrete-time Fourier transform (DTFT) which maps the measured cell index from the time domain to the frequency domain. The direct current (DC) component of the DTFT is extracted as a feature which reflects the intensity of cytotoxicity. The smaller the value, the higher the cytotoxicity. Then, a novel toxicity index, as expressed in terms of DC50, is calculated. Results generated with selected test chemicals are compared favorably with data obtained from The Interagency Coordinating Committee on the validation of Alternative Method (ICCVAM) report concerning the prediction of acute systemic toxicity in rodents. The method can be applied with the standard and high throughput to estimate acute rodent oral toxicity which reduces the number of animals required in subsequent pharmacological/toxicological studies.
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