Integrated particle sensors have been developed using thin-film on ASIC technology. For this purpose, hydrogenated amorphous silicon diodes, in various configurations, have been optimized for particle detection. These devices were first deposited on glass substrates to optimize the material properties and the dark current of very thick diodes (with thickness up to 50 μm). Corresponding diodes w...

A novel algorithm, termed a Boosted Adaptive Particle Filter (BAPF), for integrated face detection and face tracking is proposed. The proposed algorithm is based on the synthesis of an adaptive particle filtering algorithm and the AdaBoost face detection algorithm. An Adaptive Particle Filter (APF), based on a new sampling technique, is proposed. The APF is shown to yield more accurate estimate...

Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-k...

Real-time detection of low-concentration pathogenic/ toxic bioparticles is important for deterring infectious diseases and bioterrorism, which is difficult to achieve for lab-on-a-chip. Currently, sensitivity is achieved through time-consuming culturing or sophisticated processing, often unfeasible under field conditions. Real-time particle enrichment will improve sensor capability. This paper ...

We extend previously defined particle filters for lane detection by using a more general lane model supporting the use of two independent particle filters for detecting left and right lane borders separately, by combining multiple particles, traditionally used for identifying a winning particle in one image row, into one superparticle, and by using local linear regression for adjusting detected...

The Particle Swarm Optimization is very efficient in intrusion detection in the networks. However, many intrusion detection systems either fail to detect or falsely detect the intrusions. This paper proposes a technique for intrusion detection using Particle Swarm Optimization with Genetic Algorithm based feature selection and using Adaptive Mutation for slow convergence of optimization algorit...

In order to overcome the defects of the slow convergence rate of the traditional Genetic Algorithm and basic Particle Swarm Optimization drops into local optimum easily, an improved Particle Swarm Optimization algorithm based on hybrid algorithm is proposed and applied to the signal detection for MIMO-OFDM system. The algorithm optimizes the basic Particle Swarm Optimization algorithm and some ...

Leak detection and location play an important role in the management of a pipeline system. Some model-based methods, such as those based on the extended Kalman filter (EKF) or based on the strong tracking filter (STF), have been presented to solve this problem. But these methods need the nonlinear pipeline model to be linearized. Unfortunately, linearized transformations are only reliable if er...

We detect errors in Korean post-positional particle usage, focusing on optimizing omission detection, as omissions are the single-biggest factor in particle errors for learners of Korean. We also develop a system for predicting the correct choice of a particle. For omission detection, we model the task largely on English grammatical error detection, but employ Korean-specific features and filte...