Sharif Digital Repository

This paper presents a multi-stage algorithm for QRS complex classification into normal and abnormal categories using an unsupervised sequential beat clustering and a cross-distance analysis algorithm. After the sequential beat clustering, a search algorithm based on relative similarity of created classes is used to detect the main normal class. Then other classes are labeled based on a distance measurement from the main normal class. Evaluated results on the MIT-BIH ECG database exhibits an error rate less than 1% for normal and abnormal discrimination and 0.2% for clustering of 15 types of arrhythmia existing on the MIT-BIH database. © 2001 IEEE  

In the binary majority voting problem, each node initially chooses between two alternative choices. The goal is to design a distributed algorithm that informs nodes which choice is in majority. In this study, the authors formulate this problem as a hypothesis testing problem and propose fixed-size and sequential solutions using classical and Bayesian approaches. In the sequential version, the proposed mechanism enables nodes to test which choice is in majority, successively in time. Hence, termination of the algorithm is embedded within it, contrary to the existing approaches which require a monitoring algorithm to indicate the termination. This property makes the algorithm more efficient in... 

Fault monitoring in internal-combustion engines is crucial for keeping the vehicle performance within the acceptable standards of emission levels and drivers' demands. This paper analyses how a vehicle's performance and engine variables are affected by a leakage fault in the exhaust manifold. The threshold leakage that causes the vehicle to exceed the emission standards is determined for a class M1 vehicle tested on a chassis dynamometer over the New European Driving Cycle. It is shown that, when a leakage of 6 mm diameter on the exhaust manifold is introduced, the vehicle emissions exceed those specified in the European 2013 on-board diagnostics standard. In addition, the effects of the... 

Object handover as continually tracking an object across disjoint-view cameras is a necessary part of video-based monitoring systems. While having nonoverlapping cameras is a requirement for monitoring a wide area, there is no common 3D location that can be used to detect multiple views of the same object, in contrast with overlapping cameras. Appearance features play an important role for object handover in such camera networks. This paper focuses on modeling appearance features of moving vehicles by a new major color representation called codebook representation. Toward this end, in each frame, the k-means algorithm is used to cluster major colors of an object. In the subsequent frames, a...