With the expansion of network traffic and the increasing experiences of cyber threats, the need for flexible as well as systematic network traffic attack detection systems has become foremost. Conventional signature-b...
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Mobile phones and the Internet are the most popular modern technologies for life organization, especially in the field of education. Rapid advancements in mobile technology have made it possible for Internet-based mob...
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The current predominant issue in India is the escalating number of traffic accidents, primarily attributed to the burgeoning population. A significant contributing factor to this problem is the widespread disregard fo...
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The precise and timely identification of plant diseases plays a pivotal role in safeguarding crop health and optimizing agricultural yields. This paper introduces an innovative framework designed for plant disease det...
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In recent years, blockchain technology has gained immense popularity due to its decentralized and secure nature. However, traditional blockchain systems still face security challenges in terms of confidentiality, inte...
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In each school association, there is a constant need of meeting rooms for direct different occasions. It is discovered that there is one gathering hall in each institution, regardless of whether it is a school or univ...
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Li metal is widely recognized as the desired anode for next-generation energy storage,Li metal batteries,due to its highest theoretical capacity and lowest ***,it suffers from unstable elec-trochemical behaviors like ...
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Li metal is widely recognized as the desired anode for next-generation energy storage,Li metal batteries,due to its highest theoretical capacity and lowest ***,it suffers from unstable elec-trochemical behaviors like dendrite growth and side reactions in practical ***,we report a highly stable anode with collector,Li5Mg@Cu,realized by the melting-rolling *** Li5Mg@Cu anode delivers ultrahigh cycle stability for 2000 and 1000 h at the current densities of 1 and 2 mA cm-2,respectively in symmetric ***,the Li5Mg@Cu|LFP cell exhibits a high-capacity retention of 91.8％for 1000 cycles and 78.8％for 2000 cycles at 1 ***,we investigate the suppression effects of Mg on the dendrite growth by studying the performance of LixMg@Cu electrodes with different Mg contents(2.0-16.7 at％).The exchange current density,surface energy,Li+diffusion coefficient,and chem-ical stability of LixMg@Cu concretely reveal this improving suppression effect when Mg content becomes *** addition,a Mg-rich phase with"hollow brick"morphology forming in the high Mg content LixMg@Cu guides the uniform deposition of *** study reveals the suppression effects of Mg on Li dendrites growth and offers a perspective for finding the optimal component of Li-Mg alloys.
Ensuring the safe navigation of autonomous vehicles in intelligent transportation system depends on their ability to detect pedestrians and vehicles. While transformer-based models for object detection have shown rema...
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Ensuring the safe navigation of autonomous vehicles in intelligent transportation system depends on their ability to detect pedestrians and vehicles. While transformer-based models for object detection have shown remarkable advancements, accurately identifying pedestrians and vehicles in adverse weather conditions remains a challenging task. Adverse weather introduces image quality degradation, leading to issues such as low contrast, reduced visibility, blurred edges, false detection, misdetection of tiny objects, and other impediments that further complicate the accuracy of detection. This paper introduces a novel Pedestrian and Vehicle Detection Model under adverse weather conditions, denoted as PVDM-YOLOv8l. In our proposed model, we first incorporate the Swin-Transformer method, which is designed for global extraction of feature of small objects to identify in poor visibility, into the YOLOv8l backbone structure. To enhance detection accuracy and address the impact of inaccurate features on recognition performance, CBAM is integrated between the neck and head networks of YOLOv8l, aiming to gather crucial information and obtain essential data. Finally, we adopted the loss function Wise-IOU v3. This function was implemented to mitigate the adverse effects of low-quality instances by minimizing negative gradients. Additionally, we enhanced and augmented the DAWN dataset and created a custom dataset, named DAWN2024, to cater to the specific requirements of our study. To verify the superiority of PVDM-YOLOV8l, its performance was compared against several commonly used object detectors, including YOLOv3, YOLOv3-tiny, YOLOv3-spp, YOLOv5, YOLOv6, and all the versions of YOLOv8 (n, m, s, l, and x) and some traditional models. The experimental results demonstrate that our proposed model achieved a 6.6%, 5.4%, 6%, and 5.1% improvement in precision, recall, F1-score and mean Average Precision (mAP) on the custom DAWN2024 dataset. This substantial improvement in accuracy ind
In the realm of education, examinations play a very significant role. If writing an exam is considered tedious, the process of evaluating hundreds of answer scripts can be even more daunting. It usually takes weeks to...
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In order to increase the effectiveness and precision of cyber threat detection in computer networks, deep learning techniques are being applied in the construction of intelligent intrusion detection systems (IDS). The...
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