On–board pedestrian detection is a key task in advanced driver assistance systems. It involves dealing with aspect–changing objects in cluttered environments, and working in a wide range of distances, and often relies on a classification step that labels image regions of interest as pedestrians or non–pedestrians. The performance of this classifier is a crucial issue since it represents the mos...

Of interest was whether prior testing of related words primes false memories in the Deese/Roediger-McDermott (DRM) paradigm. After studying lists of related words, subjects made old-new judgments about zero, three, or six related items before being tested on critical nonpresented lures. When the recognition test was self-paced, prior testing of list items led to faster false recognition judgmen...

Since the advent of intrusion detection system (IDS) in the early 1980s, IDS has been suffering many problems until now. The detection of novel attacks and lower rate of false alarms must be realized in successful IDS. Misuse detection compares data against predefined patterns usually collected by an IDS signature database. It is hard for misuse detection to detect even slightly variation of kn...

An intrusion detection system refers to the systems which detect the security breaches in a network. The main goal of IDS is to detect the attacks and raise alarms if an attack is found. These IDS has limitation of raising false alarms and this limitation depends on improper classification of attacks due to high dimensionality of data on a network. Improper classification is due to improper fea...

In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, despite the tradeoff between the noise level and the speed of the detection. In this paper, an improvement is introduced in the Kalman filter, through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in th...

In computer networks, large scale attacks in their final stages can readily be identified by observing very abrupt changes in the network traffic, but in the early stage of an attack, these changes are hard to detect and difficult to distinguish from usual traffic fluctuations. In this paper, we develop efficient adaptive sequential and batch-sequential methods for an early detection of attacks...

In practice, faulty samples of wind turbine (WT) gearboxes are far smaller than normal during operation, and most the existing fault diagnosis methods for WT only focus on improvement classification accuracy ignore decrease missed alarms reduction average cost. To this end, a new framework is proposed through combining Spearman rank correlation feature extraction cost-sensitive LightGBM algorit...