-Worldwide the rate of preterm birth is increasing, which presents significant health, developmental and economic problems. Current methods for predicting preterm births at an early stage are inadequate. Yet, there has been increasing evidence that the analysis of uterine electrical signals, from the abdominal surface, could provide an independent and easy way to diagnose true labour and predict preterm delivery. This analysis provides a heavy focus on the use of advanced machine learning techniques and Electrohysterography (EHG) signal processing. Most EHG studies have focused on true labour detection, in the window of around seven days before labour. However, this paper focuses on using such EHG signals to detect preterm births. In achieving this, the study uses an open dataset containing 262 records for women who delivered at term and 38 who delivered prematurely. The synthetic minority oversampling technique is utilized to overcome the issue with imbalanced datasets to produce a dataset containing 262 term records and 262 preterm records. Six different artificial neural networks were used to detect term and preterm records. The results show that the best performing classifier was the LMNC with 96% sensitivity, 92% specificity, 95% AUC and 6% mean error.

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A new algorithm based on track-beforc-detect (TBD) technology is proposed for the detection of dim moving point targets of unknown position and velocity in a sequence of digital images collected from a staring sensor. The algorithm using the transformation of the pixel statistics on a composite image produced by integrating a few of differential images, then perform the detection pro-ess followed by TBD target enhancement proccdure. This algorithm is applieo to variety of image sequences with terrestrial and celestial no moving clutter backgrounds that usually they are supposed to be non-Gaussian processes. Comparing with other algorithms, the new proposed algorithm is not only computationally simple, but also has high performance. Theoretical and experimental results are also given in this paper.

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