Enhancing Estimates of Breakpoints in Genome Copy Number Alteration using Confidence Masks

Chromosomal structural changes in human body known as copy number alteration (CNA) are often associated with diseases, such as various forms of cancer. Therefore, accurate estimation of breakpoints of the CNAs is important to understand the genetic basis of many diseases. The high‐resolution comparative genomic hybridization (HR‐CGH) and single‐nucleotide polymorphism (SNP) technologies enable cost‐efficient and high‐throughput CNA detection. However, probing provided using these profiles gives data highly contaminated by intensive Gaussian noise having white properties. We observe the probabilistic properties of CNA in HR‐CGH and SNP measurements and show that jitter in the breakpoints can statistically be described with either the discrete skew Laplace distribution when the segmental signal‐to‐noise ratio (SNR) exceeds unity or modified Bessel function‐based approximation when SNR is <1. Based upon these approaches, the confidence masks can be developed and used to enhance the estimates of the CNAs for the given confidence probability by removing some unlikely existing breakpoints

Analysis and Smoothing of EMG Signal Envelope Using Kalman and UFIR Filtering under Colored Measurement Noise

This article describes some filtering methods to remove artifacts from the EMG signal envelope. Diverse EMG waveforms are studied using the Kalman filter (KF) and unbiased finite impulse response (UFIR) filter. The filters are developed in discrete-time state-space for Gauss-Markov colored measurement noise (CMN) and termed as cKF and cUFIR. It is shown that a choice of a proper CMN factor allows extracting the EMG waveform envelope with a high robustness. Extensive investigation have shown that the cKF and cUFIR filter are most efficient when the density is low of the motor unit action potential (MUAP) of the EMG and the Hilbert transform is required. Otherwise, when the envelope is well-pronounced and well-shaped with sharp edges due to a high MUAP density, the filters can be applied directly without using the Hilbert transform

Development of a Robust UFIR Filter with Consensus on Estimates for Missing Data and unknown noise statistics over WSNs

Wireless sensor networks (WSN) are often deployed in harsh environments, where electromagnetic interference, damaged sensors, or the landscape itself cause the network to suffer from faulty links and missing data. In this paper, we develop an unbiased finite impulse response (UFIR) filtering algorithm for optimal consensus on estimates in distributed WSN. Simulations are provided assuming two possible scenarios with missing data. The results show that the distributed UFIR filter is more robust than the distributed Kalman filter against missing data

An Analysis of Sawtooth Noise in the Timing SynPaQ III GPS Sensor

This paper addresses a probabilistic analysis of sawtooth noise in the one pulse per second (1PPS) output of the timing SynPaQ III GPS Sensor. We show that sawtooth noise is uniformly distributed within the bounds caused by period of the Local Time Clock of the sensor and that the probability density function (pdf) of this noise is formed with 1ns sampling interval used in the sensor to calculate the negative sawtooth. We also show that the pdf has at zero a spike of 1ns width caused by roll-off. It is demonstrated that an unbiased finite impulse response filter is an excellent suppresser of such a noise in the estimates of the time interval errors of local clocks

Desarrollo de un horno solar para el secado de plantas y vegetales usando control difuso

<p>Recientemente, el aprovechamiento de la energía solar en el deshidratado de productos agrícolas se ha vuelto cada día más común debido a los altos rendimientos en los productos post-cosecha. La inversión en tecnologías propias para contribuir con los productores del sector agroalimentario es un factor importante para el desarrollo de las cadenas produc­tivas de nuestro país. En este trabajo se presenta el desarrollo de un horno solar para el secado de plantas y vegetales utilizando control difuso. Este es un sistema térmicamente controlado que permite disminuir el tiempo de secado de varios días a unas horas. Se reali­zaron pruebas de secado usando flor de jamaica, en las cuales se pudo disminuir el tiempo de secado de cuatro días a aproximadamente 5 h. Se presentan tanto la parte de diseño conceptual, como resultados experimentales del mismo. Los resultados obtenidos permiten ver la viabilidad del diseño propuesto.</p><br>Recently, the use of solar energy in the dehydration of agricultural products is becomingmore common as high yields in the post-harvest products. Investment in technologies forcontributing to the producers of food products is an important factor for the development ofthe productive chains of our country. This paper presents the development of a solar oven fordrying plants and vegetables using fuzzy control. This is a heat-controlled system that allowsdecreasing the drying time from several days to hours. Drying tests were conducted usingjamaica flower, which could decrease the drying time from four days to about 5 h. We presentboth the conceptual design of the experimental results. The results obtained allow us to seethe feasibility of the proposed design

ECG Signal Denoising and Features Extraction Using Unbiased FIR Smoothing

Methods of the electrocardiography (ECG) signal features extraction are required to detect heart abnormalities and different kinds of diseases. However, different artefacts and measurement noise often hinder providing accurate features extraction. One of the standard techniques developed for ECG signals employs linear prediction. Referring to the fact that prediction is not required for ECG signal processing, smoothing can be more efficient. In this paper, we employ the p-shift unbiased finite impulse response (UFIR) filter, which becomes smooth by p<0. We develop this filter to have an adaptive averaging horizon: optimal for slow ECG behaviours and minimal for fast excursions. It is shown that the adaptive UFIR algorithm developed in such a way provides better denoising and suboptimal features extraction in terms of the output signal-noise ratio (SNR). The algorithm is developed to detect durations and amplitudes of the P-wave, QRS-complex, and T-wave in the standard ECG signal map. Better performance of the algorithm designed is demonstrated in a comparison with the standard linear predictor, UFIR filter, and UFIR predictive filter based on real ECG data associated with normal heartbeats