This paper presents an energy-efficient standard-cell library design scheme: MEPNTC, targeting ultra-low-voltage near/sub- V th operation. MEPNTC exploits an alternative logic style and inverse-narrow-width-effect (I...
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ISBN:
(数字)9781728197104
ISBN:
(纸本)9781728197111
This paper presents an energy-efficient standard-cell library design scheme: MEPNTC, targeting ultra-low-voltage near/sub- V th operation. MEPNTC exploits an alternative logic style and inverse-narrow-width-effect (INWE) to extend the minimum energy point operation. A carefully engineered design style is presented to improve the PVT and glitch immunity of the cells while preserving balanced noise margins across a wider VDD range. The reduced parasitics and performance boost from both techniques have demonstrated up to 30 % -60 % of energy savings at 0.5V, typical near- V th level for general-purpose hardware accelerator benchmarks (32-bit Booth Multiplier, 25- Tap FIR Filter, Forward Discrete Cosine Transform and JPEG Image Compression Units) compared to standard CMOS and INWE aware CMOS designs in 65-nm bulk CMOS technology.
Detection of aerial activities, including drones and birds, has practical implications for automating bird surveys and developing radar systems for aerial object collision detection. Convolutional neural networks (CNN...
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The continuous operation of Earth-orbiting satellites generates vast and ever-growing archives of Remote Sensing (RS) images. Natural language presents an intuitive interface for accessing, querying, and interpreting ...
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The continuous operation of Earth-orbiting satellites generates vast and ever-growing archives of Remote Sensing (RS) images. Natural language presents an intuitive interface for accessing, querying, and interpreting the data from such archives. However, existing Vision-Language Models (VLMs) are predominantly trained on web-scraped, noisy image-text data, exhibiting limited exposure to the specialized domain of RS. This deficiency results in poor performance on RS-specific tasks, as commonly used datasets often lack detailed, scientifically accurate textual descriptions and instead emphasize solely on attributes like date and location. To bridge this critical gap, we introduce GAIA, a novel dataset designed for multi-scale, multi-sensor, and multi-modal RS image analysis. GAIA comprises of 205,150 meticulously curated RS image-text pairs, representing a diverse range of RS modalities associated to different spatial resolutions. Unlike existing vision-language datasets in RS, GAIA specifically focuses on capturing a diverse range of RS applications, providing unique information about environmental changes, natural disasters, and various other dynamic phenomena. The dataset provides a spatially and temporally balanced distribution, spanning across the globe, covering the last 25 years with a balanced temporal distribution of observations. GAIA’s construction involved a two-stage process: (1) targeted web-scraping of images and accompanying text from reputable RS-related sources, and (2) generation of five high-quality, scientifically grounded synthetic captions for each image using carefully crafted prompts that leverage the advanced vision-language capabilities of GPT-4o. We also release an automated processing framework developed for this purpose, enabling the broader research community to generate captions for RS images using the web-crawled image-text data. Our extensive experiments, including fine-tuning of CLIP and BLIP2 models, demonstrate that GAIA significan
The growing demand for location-based services in areas like virtual reality, robot control, and navigation has intensified the focus on indoor localization. Visible light positioning (VLP), leveraging visible light c...
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The rapid advancements in technology have led to a significant increase in the number of portable and wearable devices, driving the demand for efficient and reliable methods for bioimpedance analysis suitable for comp...
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ISBN:
(数字)9798331507626
ISBN:
(纸本)9798331507633
The rapid advancements in technology have led to a significant increase in the number of portable and wearable devices, driving the demand for efficient and reliable methods for bioimpedance analysis suitable for compact embedded-hardware platforms. In this paper, a method for complex bioimpedance curve fitting with the second order polynomial is derived and validated with synthetic datasets as well as experimentally obtained bioimpedance. The main advantages are independence of the frequency data (which results in reduction of the dataset by 1/3), and the elimination of dependence on characteristic frequency estimation. More importantly, it is possible to estimate parameters of the Cole-impedance model (R∞, R1 and $a$ ) from obtained polynomial coefficients in a very efficient micro controller-based realization. Raspberry Pi Pico-based execution time was around 9 ms for 256 datapoints, which is more than 1000 times shorter when compared to the relevant references. Moreover, here presented method required 22.05% less flash memory and 43.64% less SRAM. Experimental bioimpedance of human volunteer was obtained using the ImpediMed SFB7 device. Relative deviations of the estimated values of the Cole-impedance model with the proposed method and BioImp software were around 5%. The proposed method's suitability for applications involving portable and cost-effective bioimpedance measurement and processing units was demonstrated by achieving a mean relative deviation of less than 2 % between the fitted and measured bioimpedance of pear slices over a three-hour period.
This paper presents two novel circuit arrangements for an ultra-low voltage, low-power 4-to-2 compressor targeting typical near-V th application domain. A hybrid logic style is utilized to exploit energy efficiency b...
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ISBN:
(数字)9781728133201
ISBN:
(纸本)9781728133218
This paper presents two novel circuit arrangements for an ultra-low voltage, low-power 4-to-2 compressor targeting typical near-V th application domain. A hybrid logic style is utilized to exploit energy efficiency by means of parasitic reduction in circuit blocks. Proposed structures are evaluated against prevalent compressors in terms of their typical figure of merits and noise immunity. From extensive post-layout simulations in 65-nm bulk CMOS process technology, the most optimal arrangement was found to be 35% more power efficient, 3.4% faster, 8% more area efficient and 37% better in PDP at 0.4V DD compared to most appealing implementations in literature.
Vulnerabilities in privileged software layers have been exploited with severe consequences. Recently, Trusted Execution Environments (TEEs) based technologies have emerged as a promising approach since they claim stro...
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ISBN:
(数字)9781728195353
ISBN:
(纸本)9781728195360
Vulnerabilities in privileged software layers have been exploited with severe consequences. Recently, Trusted Execution Environments (TEEs) based technologies have emerged as a promising approach since they claim strong confidentiality and integrity guarantees regardless of the trustworthiness of the underlying system software. In this paper, we consider one of the most prominent TEE technologies, referred to as Intel Software Guard Extensions (SGX). Despite many formal approaches, there is still a lack of formal proof of some critical processes of Intel SGX, such as remote attestation. To fill this gap, we propose a fully automated, rigorous, and sound formal approach to specify and verify the Enhanced Privacy ID (EPID)-based remote attestation in Intel SGX under the assumption that there are no side-channel attacks and no vulnerabilities inside the enclave. The evaluation indicates that the confidentiality of attestation keys is preserved against a Dolev-Yao adversary in this technology. We also present a few of the many inconsistencies found in the existing literature on Intel SGX attestation during formal specification.
This paper describes the determination of the fault location in the power system. This problem is solved in two steps: by determining the line on which the fault occurred using the classification algorithm of the deci...
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ISBN:
(数字)9781728197593
ISBN:
(纸本)9781728197609
This paper describes the determination of the fault location in the power system. This problem is solved in two steps: by determining the line on which the fault occurred using the classification algorithm of the decision tree and determining the fault location on the line by linear regression. In the first step, the decision tree algorithm is used to classify the short circuit and to determine the faulted line based on the information about the residual voltages (voltage dips) on the buses due to the occurrence of a short circuit. In the second step, linear regression is used to find the fault location on the faulted line. The algorithm is tested using the 39-bus IEEE test system.
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