The collaboration of machine learning (ML) algorithms and cognitive psychological frameworks supports the enhancement of emotional intelligence. In light of Plutchik's emotional wheel, this study investigates how ...
详细信息
Transient execution attacks like Spectre and its vari-Ants can cause information leakage through a cache hierarchy. There are two classes of techniques that mitigate speculative execution attacks: delay-based and invi...
详细信息
ISBN:
(纸本)9798350350579
Transient execution attacks like Spectre and its vari-Ants can cause information leakage through a cache hierarchy. There are two classes of techniques that mitigate speculative execution attacks: delay-based and invisible speculation. Invisible speculation-based techniques like GhostMinion are the high-performing yet secure techniques that mitigate all kinds of spec-ulative execution attacks. Similar to a cache system, hardware prefetchers can also cause speculative information leakage. To mitigate it, GhostMinion advocates on-commit prefetching on top of strictness ordering in the cache system. Our experiments show that the GhostMinion cache system interacts negatively with the hardware prefetchers leading to redundant traffic between different levels of cache. This traffic causes contention and increases the miss latency leading to performance loss. Next, we observe that on-commit prefetching enforced by GhostMinion leads to nerformance loss as it affects the prefetcher timeliness. We perform the first thorough analysis of the interaction between state-of-The-Art prefetching techniques and the secure cache system. Based on this, we propose two microarchitectural solutions that ensure high performance while designing secure prefetchers on top of secure cache system. The first solution detects and filters redundant traffic when updating the cache hierarchy non-speculatively. The second solution ensures the timeliness of the prefetcher to compensate for the delayed triggering of prefetch requests at commit, resulting in a secure yet high-performing prefetcher. Overall, our enhancements are secure and provide synergistic interactions between hardware prefetchers and a secure cache system. Our experiments show that our filter consistently improves the performance of secure cache systems like GhostMinion in the presence of state-of-The-Art prefetchers (by 1.9% for single-core and 19.0% for multi-core for the top-performing prefetcher). We see a synergistic behavior of
Deep learning models have been applied in various fields and continue producing exceptional results. However, these models are vulnerable to adversarial attacks, which are modified data samples maliciously crafted to ...
详细信息
In the economy where trade and finance are closely linked it is essential to accurately identify and authenticate various currencies, especially in industries such, as banking, tourism and retail. Conventional methods...
详细信息
Andhra Pradesh is a well-known agricultural state with a major contribution to the production of rice, cotton, and chilies it is also known as the 'Rice Bowl of India'. Unpredictable weather events have been a...
详细信息
ISBN:
(数字)9798350384246
ISBN:
(纸本)9798350384246
Andhra Pradesh is a well-known agricultural state with a major contribution to the production of rice, cotton, and chilies it is also known as the 'Rice Bowl of India'. Unpredictable weather events have been a concern to the state, it is proving to show a negative impact on the state's farming population, nevertheless the state still contributes materially to the country's cultivation production. on thorough research and historical analysis, it is stated that the food diffidence and conservationist problems arise from the established age-old agricultural methods, these methods are being followed without any systematic scientific pursuit. this study pursues to solve the mentioned problem by transitioning agricultural practices with the use of Internet of Things (IoT) technologies. A preferred multi-class classification model leveraging IoT data. the data primarily includes meteorological parameters such as soil NPK values, temperature, humidity, and more. The hypothesized model, a hybrid of Long Short-Term Memory (LSTM) and Time Series - Convolutional Neural Networks (TSC-NET), which recommends suitable crops for the cropland location, it is accomplished by integrating Time-space data. the food grain acreage in Andhra Pradesh is seen dwindling by 4.2 % in 2022-2023, underscoring the susceptibility of farmers to monsoon failures. In addition, macroeconomically speaking, the slowdown in agrarian development disrupts economy's advancement as a whole, advocating for agrarian development. The IoT -driven crop classification model provides the novel approach to enhance crop selection and optimize production potential. therefore, improving the precision and efficacy of crop forecasting while enabling farmers to make well-informed decisions accounting for soil conditions and climate data. It intends to tackle both macro-level economic concerns and micro-level farmer vulnerabilities, this research levels to improve the sustainability and efficiency of agriculture in Andhra Pr
Imagined speech electroencephalogram (EEG) signals are often collected for longer durations than necessary, leading to a difficulty in understanding the generation of EEG during the task as it is likely that most of t...
详细信息
One of the most challenging jobs in image processing techniques is image segmentation. To identify the objects of interest in an image, we segment the image into different parts and extract the interesting objects. Pr...
详细信息
Stress significantly affects the learning, academic performance, and health of university students. Traditional detection methods often rely on subjective self-reports, that can be stigmatized. In this study, we devel...
详细信息
The project 'Enhancing Dietary Monitoring Using Deep Learning:Food Recognition And Calorie Estimation' introduces an innovative method aimed at improving dietary tracking and fostering healthier eating habits....
详细信息
ISBN:
(纸本)9798350370249
The project 'Enhancing Dietary Monitoring Using Deep Learning:Food Recognition And Calorie Estimation' introduces an innovative method aimed at improving dietary tracking and fostering healthier eating habits. By employing cutting-edge deep learning techniques, its core objective is to precisely identify various food items and rapidly estimate their caloric content, offering users advanced and personalized monitoring capabilities. Utilizing the Python programming language alongside the MobileNet architecture model, the project underwent rigorous training and evaluation using the expansive Food 101 dataset, comprising 37,046 food images distributed across 101 distinct classes. Notably, the model demonstrated exceptional performance, achieving a training accuracy of 97.02% and a validation accuracy of 98.17%, highlighting the efficacy of this approach in accurately categorizing a wide array of food items. This system provides users with several crucial functionalities. Furthermore, it furnishes users with essential insights by estimating the caloric content of recognized foods, facilitating effective monitoring of dietary intake. The intelligent diet monitoring capabilities enabled by Food Recognition and Calorie Estimation empower users to make informed choices regarding their dietary preferences. Through the continuous tracking and analysis of their daily food consumption, users can glean valuable insights into their nutritional habits, set personalized goals, and make necessary adjustments to achieve a well-balanced and healthy diet. Enhancing Dietary Monitoring Using Deep Learning:Food Recognition And Calorie Estimation stands as a prominent illustration of successful implementation of deep learning techniques, particularly with the utilization of the MobileNet architecture, for food recognition and calorie estimation. With its remarkable accuracy, real-time processing capabilities, and intelligent monitoring features, this project has the potential to revolutioni
Face recognition is a fast-growing technology that is widely used in forensics such as criminal identification, secure access, and prison *** contrasts from other classification issues in that there are normally a mor...
详细信息
暂无评论