In word spotting, one of the main difficulties is the false alarms, especially for small words. A model is presented for predicting the false alarm rate on the basis of the phonemic content of a word. This model is tested for a word spotter that has been used in the TREC Spoken Document Retrieval (SDR) track. Finally, results are presented for the retrieval task.

K. J. Malmberg, J. Holden, and R. M. Shiffrin (2004) reported more false alarms for low- than high-frequency words when the foils were similar to the targets. According to the source of activation confusion (SAC) model of memory, that pattern is based on recollection of an underspecified episodic trace rather than the error-prone familiarity process. The authors tested the SAC account by varyin...

Monitoring systems in intensive care units have a high false alarm rate. Machine learning techniques can be applied to improve existing alarm systems. We present two approaches, a filtering approach and a classification approach, and demonstrate their potential in reducing false alarms.

Moving object detection is a key to intelligent video analysis. On the one hand, what moves is not only interesting objects but also noise and cluttered background. On the other hand, moving objects without rich texture are prone not to be detected. So there are undesirable false alarms and missed alarms in many algorithms of moving object detection. To reduce the false alarms and missed alarms...

In this project we are working with a security company that is a mayor player in secure alarm transmission. Alarms can be triggered by devices installed at banks, jewelry stores, private homes, etc. As already stated initially, around 90% of alarms are so-called false alarms and are due to technical reasons or unwanted human error. The challenge of our project is to significantly reduce the amo...

In classification problems, the goal is often to maximize the probability of a true positive while satisfying a system design constraint on the number of false alarms. Current classifiers, which are based on minimizing classification error, achieve this goal indirectly by either shifting the bias of the resulting solution or via tuning of an asymmetry parameter. While these approaches may be us...

FOREST FIRES CAUSE MANY ENVIronmental disasters, creating economical and ecological damage as well as endangering people’s lives. Heightened interest in automatic surveillance and early forest-fire detection has taken precedence over traditional human surveillance because the latter’s subjectivity affects detection reliability, which is the main issue for forest-fire detection systems. In curre...

Pattern matching plays a significant role in ascertaining network attacks and the foremost prerequisite for a trusted intrusion detection system (IDS) is accurate pattern matching. During the pattern matching process packets are scanned against a pre-defined rule sets. After getting scanned, the packets are marked as alert or benign by the detection system. Sometimes the detection system genera...