Continuous Wavelet Transform and Hidden Markov Model Based Target Detection

Standard tracking filters perform target detection process by comparing the sensor output signal with a predefined threshold. However, selecting the detection threshold is of great importance and a wrongly selected threshold causes two major problems. The first problem occurs when the selected threshold is too low which results in increased false alarm rate. The second problem arises when the selected threshold is too high resulting in missed detection. Track-before-detect (TBD) techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. Although TBD techniques eliminate the need for detection threshold at sensor’s signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Continuous Wavelet Transform (CWT) and Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not employ any thresholding

Data reduction methods for single-mode optical interferometry - Application to the VLTI two-telescopes beam combiner VINCI

The interferometric data processing methods that we describe in this paper use a number of innovative techniques. In particular, the implementation of the wavelet transform allows us to obtain a good immunity of the fringe processing to false detections and large amplitude perturbations by the atmospheric piston effect, through a careful, automated selection of the interferograms. To demonstrate the data reduction procedure, we describe the processing and calibration of a sample of stellar data from the VINCI beam combiner. Starting from the raw data, we derive the angular diameter of the dwarf star Alpha Cen A. Although these methods have been developed specifically for VINCI, they are easily applicable to other single-mode beam combiners, and to spectrally dispersed fringes.Comment: Accepted for publication in Astronomy & Astrophysics, 17 pages, 19 figure

Micro-doppler-based in-home aided and unaided walking recognition with multiple radar and sonar systems

Published in IET Radar, Sonar and Navigation. Online first 21/06/2016.The potential for using micro-Doppler signatures as a basis for distinguishing between aided and unaided gaits is considered in this study for the purpose of characterising normal elderly gait and assessment of patient recovery. In particular, five different classes of mobility are considered: normal unaided walking, walking with a limp, walking using a cane or tripod, walking with a walker, and using a wheelchair. This presents a challenging classification problem as the differences in micro-Doppler for these activities can be quite slight. Within this context, the performance of four different radar and sonar systems – a 40 kHz sonar, a 5.8 GHz wireless pulsed Doppler radar mote, a 10 GHz X-band continuous wave (CW) radar, and a 24 GHz CW radar – is evaluated using a broad range of features. Performance improvements using feature selection is addressed as well as the impact on performance of sensor placement and potential occlusion due to household objects. Results show that nearly 80% correct classification can be achieved with 10 s observations from the 24 GHz CW radar, whereas 86% performance can be achieved with 5 s observations of sonar

First Observational Tests of Eternal Inflation: Analysis Methods and WMAP 7-Year Results

In the picture of eternal inflation, our observable universe resides inside a single bubble nucleated from an inflating false vacuum. Many of the theories giving rise to eternal inflation predict that we have causal access to collisions with other bubble universes, providing an opportunity to confront these theories with observation. We present the results from the first observational search for the effects of bubble collisions, using cosmic microwave background data from the WMAP satellite. Our search targets a generic set of properties associated with a bubble collision spacetime, which we describe in detail. We use a modular algorithm that is designed to avoid a posteriori selection effects, automatically picking out the most promising signals, performing a search for causal boundaries, and conducting a full Bayesian parameter estimation and model selection analysis. We outline each component of this algorithm, describing its response to simulated CMB skies with and without bubble collisions. Comparing the results for simulated bubble collisions to the results from an analysis of the WMAP 7-year data, we rule out bubble collisions over a range of parameter space. Our model selection results based on WMAP 7-year data do not warrant augmenting LCDM with bubble collisions. Data from the Planck satellite can be used to more definitively test the bubble collision hypothesis.Comment: Companion to arXiv:1012.1995. 41 pages, 23 figures. v2: replaced with version accepted by PRD. Significant extensions to the Bayesian pipeline to do the full-sky non-Gaussian source detection problem (previously restricted to patches). Note that this has changed the normalization of evidence values reported previously, as full-sky priors are now employed, but the conclusions remain unchange

COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT

تستخدم الإشارات الصوتية التي يولدها جسم الإنسان بشكل روتيني من قبل التخصصين في البحوث والتطبيقات الصحية  للمساعدة في تشخيص بعض  الامراض أو تقييم تقدم المرض. وبالنظر إلى التقنيات الجديدة ، من الممكن في الوقت الحاضر جمع الأصوات التي يولدها الإنسان ، مثل السعال. ويمكن بعد ذلك اعتماد تقنيات التعلم الآلي المستندة إلى الصوت من أجل التحليل التلقائي للبيانات التي تم جمعها مما يوفر معلومات قيمة غنية من إشارة السعال واستخراج الميزات الفعالة من فترة زمنية محدودة الطول تتغير كدالة للوقت. في هذا البحث يتم اقتراح وتقديم خوارزمية  للكشف عن COVID-19 وتشخيصه من خلال معالجة السعال الذي يتم جمعه من المرضى الذين يعانون من الأعراض الأكثر شيوعًا لهذا الوباء. تعتمد الطريقة المقترحة على اعتماد مزيج من تحليل القيمة المفردة (SVD) وتحويل المويجات المنفصل (DWT).  وقد أدى الجمع بين هاتين التقنيتين لمعالجة الإشارات إلى اتباع نهج جيد للتعرف على السعال ، حيث يولد ويستخدم الحد الأدنى من الميزات الفعالة. وفي هذه الخوارزمية المقترحة يتم تطبيق الترددات المتوسطة (mean and median)، والمعروفة بأنها أكثر الميزات المفيدة في مجال التردد ، لإنشاء مقياس إحصائي فعال لمقارنة النتائج. بالإضافة إلى الحصول على معدل كشف وتمييز عاليين ، تتميز الخوارزمية المقترحة بكفاءتها حيث يتم تحقيق تخفيض 200 مرة، من حيث عدد العمليات. على الرغم من حقيقة أن أعراض الأشخاص المصابين وغير المصابين في الدراسة بها الكثير من أوجه التشابه ، فإن نتائج التشخيص التي تم الحصول عليها من تطبيق نهجنا تُظهر معدل تشخيص مرتفعًا، والذي تم إثباته من خلال مطابقتها مع اختبارات PCR ذات الصلة. نعتقد أنه يمكن تحقيق أداء أفضل من خلال توسيع مجموعة البيانات ، مع تضمين الأشخاص الأصحاء.Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopting a combination of Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT). The combination of these two signal processing techniques is gaining lots of interest in the field of speaker and speech recognition. As a cough recognition approach, we found it well-performing, as it generates and utilizes an efficient minimum number of features. Mean and median frequencies, which are known to be the most useful features in the frequency domain, are applied to generate an effective statistical measure to compare the results. The hybrid structure of DWT and SVD, adopted in this approach adds to its efficiency, where a 200 times reduction, in terms of the number of operations, is achieved. Despite the fact that symptoms of the infected and non-infected people used in the study are having lots of similarities, diagnosis results obtained from the application of the proposed approach show high diagnosis rate, which is proved through the matching with relevant PCR tests.  The proposed approach is open for more improvements with its performance further assured by enlarging the dataset, while including healthy people

Чувствительность напряжений по обводу контура фантома к изменениям комплексных сопротивлений неоднородностей в электроимпедансной томографии

Проведено аналіз впливу значень поверхневої провідності неоднорідностей на зміну значень комплексних напруг по обводу контуру фантома, порівняно з однорідним фантомом з комплексною поверхневою провідністю. Проведено аналіз впливу анізотропії скінченного елемента та всього фантома в цілому на обчислювані комплексні напруги. Отримано модель скінченного квадратного елемента, який складається з 1024х1024 скінченних елементів, отриманих по спрощеним наближеним формулам. Констатовано, що незалежно від різниці абсолютних значень напруг, виміряних при різних положеннях джерела струму, їх відносні прирощення залишаються незмінними. Для боротьби з такого роду анізотропією запропоновано разом з джерелом обертати сітки фантомів, як скінченних елементів, так і зон провідності. Остаточні висновки про межі чутливості вимірювальних пристроїв можна буде зробити лише після накопичення статистичних даних розв’язання зворотної задачі, обраним авторами методом зон провідності.Introduction. The analysis of surface conductivity influence of inhomogeneities to the changes of complex phantom contour voltages comparing with a homogeneous phantom with complex surface conductivity is carried out. The analysis of the influence of finite element and all phantom generally anisotropy on the calculated complex voltages is conducted. The results. The model of square finite element is obtained. It consists of 1024х1024 finite elements obtained by simplified approximate formulas. The relative increments of voltage values are unchanged regardless of the difference in the absolute values of voltages measured at different positions of the current source. It is proposed to rotate the phantom grids of finite elements and conductivity zones with the current source rotation to overcome this anisotropy. Conclusions. Final conclusions about the limits of the measuring device sensitivity could be done only after the data accumulation of solving the inverse problem by zones conductivity method.Проведен анализ влияния значений поверхностной проводимости неоднородностей на изменение значений комплексных напряжений по обводу контура фантома в сравнении с однородным фантомом с комплексной поверхностной проводимостью. Выполнен анализ влияния анизотропии конечного элемента и всего фантома в целом на вычисляемые комплексные напряжения. Получена модель конечного квадратного элемента, составленного из 1024х1024 конечных элементов, полученных по упрощенным формулам. Отмечено, что независимо от разницы абсолютных значений напряжений, вычисленных при различных положениях источника тока, их относительные приращения остаются неизменными. Для борьбы с такого рода анизотропией предложено вместе с источником поворачивать сетки фантомов, как конечных элементов, так и зон проводимости. Окончательные выводы о границах чувствительности измерительных устройств можно будет сделать после накопления статистических данных решения обратной задачи, выбранным авторами метода зон проводимости