A multi-secret image sharing (MSIS) scheme facilitates the secure distribution of multiple images among a group of participants. Several MSIS schemes have been proposed with a (n, n) structure that encodes secret...
详细信息
With the increasing computing power, it is easier to develop machine learning and signal processing technologies. This led to massive significance in EEG-based Brain-Machine Interfaces that can be applied to a variety...
详细信息
Perovskite solar cells have shown great potential in the field of underwater solar cells due to their excellent optoelectronic properties;however,their underwater performance and stability still hinder their practical...
详细信息
Perovskite solar cells have shown great potential in the field of underwater solar cells due to their excellent optoelectronic properties;however,their underwater performance and stability still hinder their practical *** this research,a 1H,1H,2H,2H-heptadecafluorodecyl acrylate(HFDA)anti-reflection coating(ARC)was introduced as a high-transparent material for encapsulating perovskite solar modules(PSMs).Optical characterization results revealed that HFDA can effectively reduce reflection of light below 800 nm,aiding in the absorption of light within this wavelength range by underwater solar ***,a remarkable efficiency of 14.65%was achieved even at a water depth of 50 ***,the concentration of Pb^(2+)for HFDA-encapsulated film is significantly reduced from 186 to 16.5 ppb after being immersed in water for 347 ***,the encapsulated PSMs still remained above 80%of their initial efficiency after continuous underwater illumination for 400 ***,being exposed to air,the encapsulated PSMs maintained 94%of their original efficiency after 1000 h light *** highly transparent ARC shows great potentials in enhancing the stability of perovskite devices,applicable not only to underwater cells but also extendable to land-based photovoltaic devices.
In recent years, artificial intelligence has undergone robust development, leading to the emergence of numerous autonomous AI applications. However, a crucial challenge lies in optimizing computational efficiency and ...
详细信息
Multi-path avoidance routing for wireless sensor networks (WSNs) is a secure routing paradigm against adversaries with unbounded computational power. The key idea of avoidance routing is to encode a message into sever...
详细信息
Multi-path avoidance routing for wireless sensor networks (WSNs) is a secure routing paradigm against adversaries with unbounded computational power. The key idea of avoidance routing is to encode a message into several pieces by the XOR coding, and each piece is routed via different paths. Then, an adversary cannot obtain the original message unless she eavesdrops on all message pieces from all the paths. In this paper, we extend such an approach into secure multicast routing, which is a one-to-many communication primitive. To this end, we propose the multi-tree-based avoidance multicast routing protocol (AMRP) for WSNs, in which a set of adversary disjoint trees is discovered, i.e., a set of multicast trees with no common adversaries. When a set of multicast trees is adversary disjoint, no adversary can eavesdrop on all message pieces to recover the original message. In addition, optimized AMRP (OAMRP) is proposed in order to reduce the control overhead of AMRP, where additional multicast trees are used for only a subset of destination nodes with no single safe tree. The simulation results demonstrate that the proposed protocols achieve higher secure delivery rates than a simple extension of the existing unicast avoidance routing protocol. IEEE
Evaluation system of small arms firing has an important effect in the context of military domain. A partially automated evaluation system has been conducted and performed at the ground level. Automation of such system...
详细信息
Evaluation system of small arms firing has an important effect in the context of military domain. A partially automated evaluation system has been conducted and performed at the ground level. Automation of such system with the inclusion of artificial intelligence is a much required process. This papers puts focus on designing and developing an AI-based small arms firing evaluation systems in the context of military environment. Initially image processing techniques are used to calculate the target firing score. Additionally, firing errors during the shooting have also been detected using a machine learning algorithm. However, consistency in firing requires an abundance of practice and updated analysis of the previous results. Accuracy and precision are the basic requirements of a good shooter. To test the shooting skill of combatants, firing practices are held by the military personnel at frequent intervals that include 'grouping' and 'shoot to hit' scores. Shortage of skilled personnel and lack of personal interest leads to an inefficient evaluation of the firing standard of a firer. This paper introduces a system that will automatically be able to fetch the target data and evaluate the standard based on the fuzzy *** it will be able to predict the shooter performance based on linear regression ***, it compares with recognized patterns to analyze the individual expertise and suggest improvements based on previous values. The paper is developed on a Small Arms Firing Skill Evaluation System, which makes the whole process of firing and target evaluation faster with better accuracy. The experiment has been conducted on real-time scenarios considering the military field and shows a promising result to evaluate the system automatically.
Today cardiovascular diseases have been posing a serious threat to human lives all over the world. Various automated decision-making systems have been proposed by the researchers to help cardiologists to diagnose hear...
详细信息
In today’s evolving landscape of video surveillance, our study introduces SuspAct, an innovative ensemble model designed to detect suspicious activities in real time swiftly. Leveraging advanced Long-term Recurrent C...
详细信息
Surgical tool tip localization and tracking are essential components of surgical and interventional procedures. The cross sections of tool tips can be considered as acoustic point sources to achieve these tasks with d...
详细信息
High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation lear...
详细信息
High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.
暂无评论