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In this paper we discuss how does the input magnitude data setting influence the behavior of error-reduction algorithm in the case of the one-dimensional discrete phase retrieval problem. We present experimental results related to the convergence or stagnation of the algorithm. We also discuss the issue of the zeros distribution of the solution, when the solution of the problem exists.

In this paper we show how a bulky analog active filter, described only by its circuit diagram, can be converted to the corresponding digital filter, having the same frequency gain and phase characteristics. The state-space based approach has been implemented using Python high-level programming language. Experimental results are also presented.

Service robots are extensively used these days for industry and assisted living applications. In this work we present how the capabilities of the TIAGo robot can be extended. We show that it can handle tasks received through audio signals. Experimental results are provided to support our claims.

The goal of this paper is to detail the Analog Filter Netlist to Digital Filter Statements approach used to obtain the digital filter from the netlist of the analog filter. This method is done by replacing each component by its corresponding companion model and then discretizing the set of equations which describe in the time domain the behavior of all the circuit’s components. Finally, the software implementation of the digital filter consists in the transcription of the discrete-time system of equations. We show that the selection of step-size might be sensitive problem for this approach.

We consider the discrete form of the one-dimensional phase retrieval (1-D DPhR) problem from the point of view of input magnitude data. The direct method can provide a solution to the 1-D DPhR problem if certain conditions are satisfied by the input magnitude data, namely the corresponding trigonometric polynomial must be nonnegative. To test positivity of a trigonometric polynomial a novel DFT-based criterion is proposed. We use this DFT criterion for different sets of input magnitude data to evaluate whether the direct method applied to the 1-D DPhR problem leads to a solution in all explored cases.

—In this paper some approaches for pothole detection of roads, using morphological algorithms, are recalled and tested. For road anomalies detection, one of the key elements is the pavement pothole information. Any algorithm for pothole detection has certain advantages and limitations as well, due to the real world environment, which is highly unstructured and dynamic. For road segmentation, the road anomalies detection algorithm based on skeletonization is used.

In this paper we propose a new algorithm for extractive text summarization. The proposed method is based on convex minimization and the properties of the l1 norm. The algorithm has some advantages, like the extensibility and the ability to easy take into account additional information and constraints. It provides very good results, but its execution time is usually larger than that of other similar procedures.

Background: Mental disorders constitute a significant public health problem worldwide. Ensuring that those who need mental health services access them in an appropriate and timely manner is thus an important public health priority. We used data from 4 cross-sectional, nationally representative population health surveys that employed nearly identical methods to compare MHSU trends in the Canadian military versus comparable civilians. Method: The surveys were all conducted by Statistics Canada, approximately a decade apart (Military-2002, Military-2013, Civilian-2002, and Civilian-2012). The sample size for the pooled data across the surveys was 35,984. Comparisons across the 4 surveys were adjusted for differences in need in the 2 populations at the 2 time points. Results: Our findings suggested that first, in the Canadian military, there was a clear and consistent pattern of improvement (i.e., increase) in MHSU over the past decade across a variety of provider types. The magnitudes of the changes were large, representing an absolute increase of 7.15% in those seeking any professional care, corresponding to an 84% relative increase. Second, in comparable Canadian civilians, MHSU remained either unchanged or increased only slightly. Third, the increases in MHSU over time were consistently greater in the military than in the comparable civilian sample. Conclusions: Our findings point to advantages with respect to MHSU of the military mental health system over the civilian system in Canada; these advantages have widened substantially over time. These findings speak strongly to the potential impact of analogous changes in other health systems, both military and civilian.

Introduction Peu d’études ont traité, à l’aide de données populationnelles, des facteurs associés de façon indépendante au syndrome de fatigue chronique (SFC) et à la fibromyalgie (FM) ou des répercussions de ces affections sur l’état de santé. Méthodologie Nous avons utilisé les données de l’Enquête sur la santé dans les collectivités canadiennes de 2010 (n = 59 101), représentative de la population à l’échelle nationale, pour décrire les cas autodéclarés de SFC et de FM diagnostiqués par un professionnel de la santé et pour déterminer les associations de ces affections avec six indicateurs de l’état de santé. Résultats En 2010, 1,4 % (intervalle de confiance [IC] à 95 % : 1,3 % à 1,6 %) des Canadiens de 12 ans ou plus vivant à domicile ont déclaré avoir reçu un diagnostic de SFC, 1,5 % (IC à 95 %: 1,4 % à 1,7 %) de FM, et 0,3 % (IC à 95 %: 0,3 % à 0,4 %) a déclaré être atteinte à la fois de SFC et de FM. Les cas de SFC comme ceux de FM étaient plus fréquents chez les femmes, les adultes de 40 ans ou plus, les personnes à faible revenu et les personnes présentant certains facteurs de risque de maladie chronique (obésité, sédentarité et tabagisme). Après ajustement en fonction des différences existant entre les groupes, les personnes ayant déclaré être atteintes du SFC ou de FM ou des deux avaient un moins bon état de santé que les personnes atteintes d’aucune de ces affections pour cinq indicateurs de l’état de santé, mais aucune différence n'a été trouvée entre ces groupes par rapport à l’indicateur de santé mentale. Le fait d’être atteint à la fois du SFC et de FM et de présenter de multiples affections comorbides était associé à un moins bon état de santé. Conclusion La présence concomitante du SFC, de la FM et d’autres affections chroniques était étroitement associée au fait d’avoir un moins bon état de santé, et les différences relatives à l’état de santé étaient dues en bonne partie à la présence concomitante de ces affections. La compréhension des facteurs qui contribuent à l’amélioration de la qualité de vie des personnes atteintes du SFC ou de FM, et en particulier des personnes qui présentent ces deux affections ainsi que diverses affections comorbides, serait un champ important à explorer dans le cadre de travaux de recherche ultérieurs.

In this paper we shall present recent results of two applications for monitoring using acoustical signal classification. The first case study is the problem of context awareness based on acoustic analysis for a service robot. Then we discussed the acoustic classification for wildlife intruder detection. Previous results are briefly recalled and new experimental results are also provided.

In this paper, we study several audio classification schemes applied on different number of features for multiclass classification with imbalanced datasets. As features, we proposed the liftering Mel frequency cepstral coefficients, while for classification we use probabilistic methods, instance-based learning algorithms, support vector machines, neural networks, L∞-norm based classifier, fuzzy lattice reasoning classifier, and trees. The final goal is to find the appropriate number of liftering Mel frequency cepstral coefficients to provide the desired accuracy for audio classification purpose. The best results are obtained using 16 features and & k-Nearest Neighbor as a classifier. In this case, the correct classification rate is 99.79%, the false alarm rate is 0.05%, the miss rate is 0.21%, the precision is 99.80% and the F-measure is 99.79%.

The goal of this work is to present some possible intruder detection systems and the influence of impulse-like signals upon the overall classification accuracy. Two different scenarios are used: in the first scenario five sound classes are considered (last class belong to impulsive sounds — gunshots), while in the second scenario we dropped out the impulsive sound class. More classifiers are used in both scenarios and different number of features are considered. An improvement in the classification accuracy is obtained within the second scenario. The highest accuracy for the first scenario is for J48 classifier using 51 features, while for the second scenario the highest accuracy is attained for Simple Logistic classifier wit 101 features.

In this work we compare different classification algorithms applied on different number of features (linear predictive coding coefficients) in order to detect audio signals from wildlife areas. The final goal is to find the appropriate number of linear predictive coding coefficients to provide the desired accuracy for a certain framework. The experimental results prove that the best classifier is Logistic Model Trees regardless the number of features, having a constant classification accuracy greater than 95%. In the case of a reduced number of features, both Random Forest and Lazy IBk have good results; the classification accuracy is greater than 98%.

The iterative methods are well-known approaches to solve the one-dimensional phase retrieval problem. Amongst them, the error-reduction algorithm is often used since it can easily implement support constraints. Unfortunately this method often stagnates. Recently we have formulated the extended form of the one-dimensional discrete phase retrieval problem and we have assumed that the stagnation can be avoided by oversampling. Simulations have indicated that the conjecture is true. In this work we prove the convergence of the error-reduction algorithm in the proposed extended one-dimensional discrete phase retrieval framework.

This paper presents a grid search approach to optimize the kernel's parameters for the support vector machines classifier. The most encountered three kernels are considered: linear, radial basis, and sigmoid. We show that the optimization of parameters improves the recognition performance for audio signals classification, especially in the case of sigmoid kernel. The behavior of the model is very sensitive to kernel's parameters, which, in turn are sensitive to data and selected features. We consider the problem of multiclass classification with imbalanced datasets. We compare the accuracies obtain with and without kernel parameter's optimization. As features we use Mel frequency cepstral coefficients.

Efficacious work of the Li-ion battery (LIB) is strongly influenced by several factors as temperature, nominal voltage, capacity and charge/discharge current rate, determining its health and state-of-charge (SOC). SOC is an indicator mirroring the available charge stored in the battery relative to its maximum capacity when new, resembling the fuel gauge in the conventional, internal combustion engine (ICE) vehicles. As this parameter defines rather a condition than a physical quantity, direct measurement using classical means is not feasible. Hence, one needs to “precisely guess” the actual available charge within the battery, in order to operate the battery pack effectively. Among the many methods employed for estimating the batteries' SOC, the Extended Kalman Filter (EKF) stands out due to its intrinsic predictor-corrector mechanism, which makes the filter insensitive to various modeling deficiencies like poor impromptu initialization or noise. This paper presents a step-by-step design procedure of such a filter, based on a 2nd order Thevenin battery equivalent circuit model (ECM). The high performance of the filter estimator is validated against laboratory measurements.

The EOG signal is based on the potential difference between the cornea and retina (also known as the corneo-retinal potential) and can be measured by using electrodes placed around the eyes. The amplitude of the EOG signal varies between 50 ... 3500 uV. The eye can be seen as a dipole with a positive pole in the retina and the negative one in the cornea. Thus, an electric potential field is created that is changing proportionally with the rotation of the eye. The movements can be assessed from a single eye, but because for a healthy human being the eye movements are coupled, in this paper the signal obtained from both eyes is used. Furthermore, this method allows assessing both vertical and horizontal signal simultaneously. One of the most complex algorithms used to detect steep slopes and peaks within medical signals is the Pan-Tompkins algorithm, but is especially used for ECG signals. This is the reason why the previous studies focused on the detection of the abrupt discontinuities in the EOG signal, from the wavelet transform perspective. In this manner, the points of discontinuity determined by the eye movement will generate high wavelet coefficients, regardless of scale. Starting from previous results regarding different technics used for eye movement investigation and electrooculogram signal (EOG), the paper presents a robust algorithm that is capable of performing real time eye movement detection. This algorithm was implemented in LabVIEW, based on virtual instruments and it was successfully tested in the laboratory of Biomedical Engineering from Technical University of Cluj-Napoca.

Objective To describe the exercise/physical activity and weight management efforts of Canadians with self-reported arthritis, to examine factors associated with their engagement in these strategies to help manage their arthritis, and to explore reasons for lack of engagement. Methods Data were from the arthritis component of the 2009 Survey on Living with Chronic Diseases in Canada. The responses (78% response rate; n = 4,565) were weighted to be representative of Canadians (ages ≥20 years) with arthritis. Logistic regression analyses were used to examine factors associated with engaging in exercise/physical activity and weight control/loss (among overweight/obese respondents) for arthritis management purposes. Results Individuals with arthritis were mostly women (63%), ages ≥45 years (89%), overweight/obese (67%), married (68%), and white (87%), with postsecondary education (69%). Sixty-three percent were exercising and of those who were overweight or obese, 68% were trying to control/lose weight; only 46% were engaged in both. Having received a clinical recommendation was the factor most strongly associated with engaging in exercise/physical activity and/or controlling/losing weight. The most common reason for not exercising was a coexisting health condition/problem (22%), while the most common reason for not controlling/losing weight among those who were overweight/obese was that it was felt not to be necessary (51%). Conclusion The provision of clinical recommendations from a health professional, providing advice on safe and suitable exercises/physical activities, as well as addressing misperceptions of the need to lose weight among the overweight/obese, may facilitate engagement in these health behaviors and ultimately reduce the consequences of arthritis.

In this work, a new set of features is presented for a biometric system based on speech and on-line signature. The feature vector is nonhomogeneous and it comprises using TESPAR DZ coefficients, wavelet energy coefficients and also some additional features resulted from the time domain analysis in the case of speech. A feature selection procedure is then applied to reduce the feature vector dimension. A modified symbols alphabet for the TESPAR DZ method is presented. Experimental results were reported using the SVC2004 database for signature and our own bimodal database BimDB10 (for on-line signature and speech). A feature level fusion strategy was adapted in order to achieve our goals. The results show that the fusion of biometric features brings improvement to the system performance.

In this paper some results on positive trigonometric polynomials related to one-dimensional discrete phase retrieval problem are presented. The closed forms of the z-transform and Fourier transform of the folded of circular autocorrelation are provided to show that whether scaling or biasing of the input magnitude data should have an effect on non-negativity. Some results to enlighten the relationship between the nearest autocorrelation method and the one-dimensional phase retrieval problem are also discussed.

Objective: More than 40,000 Canadian Armed Forces (CAF) personnel have deployed in support of the mission in Afghanistan since 2002. Over the same period, the CAF strengthened its mental health system. This article explores the effect of these events on the prevalence of past-year mental disorders over the period 2002-2013. Method: The data sources were 2 highly comparable population-based mental health surveys of CAF Regular Force personnel done in 2002 and 2013 ( n = 5155 and 6996, respectively). Data were collected via in-person interviews with Statistics Canada personnel using the World Health Organization’s Composite International Diagnostic Interview to assess past-year disorders. Results: In 2013, 16.5% had 1 or more of the 6 past-year disorders assessed in the survey, with the most common conditions being major depressive episode (MDE), posttraumatic stress disorder (PTSD), and generalized anxiety disorder (GAD), which affected 8.0%, 5.3%, and 4.7%, respectively. The prevalence of PTSD, GAD, and panic disorder has increased significantly since 2002 (adjusted odds ratios from logistic regression models = 2.1, 3.0, and 1.9, respectively), while no change was seen for MDE. The comorbidity of mood and anxiety disorders increased significantly over time, being seen in 27.4% and 41.0% of those with mental disorders in 2002 and 2013, respectively. Conclusion: There has been an increase in the prevalence of PTSD and other anxiety disorders and of the extent of comorbidity of mood and anxiety disorders in CAF personnel over the period 2002-2013.

Objective: Military personnel in Canada and elsewhere have been found to have higher rates of certain mental disorders relative to their corresponding general populations. However, published Canadian data have only adjusted for age and sex differences between the populations. Additional differences in the sociodemographic composition, labour force characteristics, and childhood trauma exposure in the populations could be driving these prevalence differences. Our objective is to compare the prevalence of past-year mental disorders and suicidal behaviours in the Canadian Armed Forces Regular Force with the rates in a representative, matched sample of Canadians in the general population (CGP). Methods: Data sources were the 2013 Canadian Forces Mental Health Survey and the 2012 Canadian Community Health Survey–Mental Health. CGP sample was restricted to match the age range, employment status, and history of chronic conditions of Regular Force personnel. An iterative proportional fitting method was used to approximate the marginal distribution of sociodemographic and childhood trauma variables in both samples. Results: Relative to the matched CGP, Regular Force personnel had significantly higher rates of past-year major depressive episode, generalized anxiety disorder, and suicide ideation. However, lower rates of alcohol use disorder were seen in Regular Force personnel relative to the matched CGP sample. Conclusions: Factors other than differences in sociodemographic composition and history of childhood trauma account for the excess burden of mental disorders and suicidal behaviours in the Canadian Armed Forces. Explanations to explore in future research include occupational trauma, selection effects, and differences in the context of administration of the 2 surveys.

This paper presents an overview of the work that has been done in the field of wildlife intruder detection using only acoustic sensors. The motivation of such an application is related to protection of large wildlife regions, such as forests, lakes, and other natural reservations. The sounds of interest are represented by humans, engines, birds and animals. In order to simulate various environmental situations, different types of noisy environments have been considered. Both low complexity and standard audio classification methods are presented. Standard audio classification methods prove to be more robust, but at an expense of significantly increased complexity. Since low complexity systems are more feasible for monitoring remote areas, the complexity issue is discussed and solutions are proposed.

Objective To estimate the prevalence of overweight and obese Canadians with arthritis and to describe their use of arthritis self-management strategies, as well as explore the factors associated with not engaging in any self-management strategies. Methods Respondents to the 2009 Survey on Living with Chronic Diseases in Canada, a nationally representative sample of 4,565 Canadians age ≥20 years reporting health professional–diagnosed arthritis (including more than 100 rheumatic diseases and conditions), were asked about the impact of their arthritis and how it was managed. Among the overweight (body mass index [BMI] 25–29.9 kg/m2) and obese (BMI ≥30 kg/m2) individuals with arthritis (n = 2,869), the use of arthritis self-management strategies (i.e., exercise, weight control/loss, classes, and community-based programs) were analyzed. Log binomial regression analyses were used to examine factors associated with engaging in none versus any (≥1) of the 4 strategies. Results More than one-quarter (27.4%) of Canadians with arthritis were obese and an additional 39.9% were overweight. The overweight and obese individuals with arthritis were mostly female (59.5%), age ≥45 years (89.7%), and reported postsecondary education (69.0%). While most reported engagement in at least 1 self-management strategy (84.9%), less than half (45.6%) engaged in both weight control/loss and exercise. Factors independently associated with not engaging in any self-management strategies included lower education, not taking medications for arthritis, and no clinical recommendations from a health professional. Conclusion Fewer than half of the overweight and obese Canadians with arthritis engaged in both weight control/loss and exercise. The provision of targeted clinical recommendations (particularly low in individuals that did not engage in any self-management strategies) may help to facilitate participation.

This study explores patterns of victimization and coping in a conservative Christian denomination. Four types of coping behaviors are identified: informal coping, professional help-seeking, negative coping and crisis outreach. While religious behaviors are less influential than expected for this particular population, current victimization and childhood victimization play a significant role in establishing a model of coping and help-seeking for intimate partner violence (IPV) survivors in faith communities. Childhood victimization acts as an aggravating factor, predicting negative coping with IPV. At the same time, childhood victimization significantly increases the likelihood of seeking professional help. The study adds to the body of knowledge by contributing to a better understanding of the impact of childhood victimization on coping and help-seeking.

For more than a decade it has been empirically known that the causal portion of the inverse Fourier transform of the magnitude spectrum of the speech signal behaves like a minimum-phase signal. Later on, this statement has been shown for an all-pole model. In this paper, we consider related results for both discrete-time Fourier and discrete Fourier transforms of arbitrary sequences. We indicate how the presence of aliasing in circular autocorrelation might be detected. The energy concentration property of zero-phase sequences is discussed.

In this paper some properties of spectrograms and sparsograms are reviewed. The framework addressed is acoustic based wildlife intruder detection. The spectral signatures are also recalled within this framework. The averaged binary sparsogram is introduced and it is shown that it can be considered an effective tool for classifying the possible intruders sounds into different classes.

Many zones, especially wild areas need surveillance systems in order to protect them against potential destroying actions. An attractive solution for automatic surveillance systems consists in audio based systems, which present some advantages compared with video or mixt surveillance systems. This paper proposes an alarming events detection system with two detection levels. On the first level the system detects only if the event is a dangerous one (alarm on) or a normal one (alarm off). On the second level, if it is the case, the system identifies exactly the nature of events in four classes: chainsaw, gunshot, human voice or tractors. The system uses a set of features of the audio signals associated with the events, as input data for two artificial neural networks that act as pattern recognition components. The experimental results prove that our system is a very reliable one, presenting the maximum possible correct recognition rate (100%) on the first level and very high correct recognition rates on the second level: 99.50% across all data set (training, validation and testing) and 95.0% in the independent testing data subset.

Few studies have considered the factors independently associated with chronic fatigue syndrome (CFS) and/or fibromyalgia (FM) or considered the impact of these conditions on health status using population-based data.We used data from the nationally representative 2010 Canadian Community Health Survey (n = 59 101) to describe self-reported health professional-diagnosed CFS and/or FM, and their associations with 6 health status indicators.In 2010, diagnosed CFS and FM are reported by 1.4% (95% confidence interval [CI]: 1.3%-1.6%) and 1.5% (1.4%-1.7%), respectively, of the Canadian household population aged 12 years and over, with comorbid CFS and FM affecting 0.3% (0.3%-0.4%) of that population. Prevalent CFS and/or FM were more common among women, adults aged 40 years and over, those with lowest income, and those with certain risk factors for chronic disease (i.e. obesity, physical inactivity and smoking). After controlling for differences between the groups, people with CFS and/or FM reported poorer health status than those with neither condition on 5 indicators of health status, but not on the measure of fair/poor mental health. Having both CFS and FM and having multiple comorbid conditions was associated with poorer health status.Co-occurrence of CFS and FM and having other chronic conditions were strongly related to poorer health status and accounted for much of the differences in health status. Understanding factors contributing to improved quality of life in people with CFS and/or FM, particularly in those with both conditions and other comorbidities, may be an important area for future research.Le syndrome de fatigue chronique et la fibromyalgie au Canada : prévalence et associations avec six indicateurs de l’état de santé.Peu d’études ont traité, à l’aide de données populationnelles, des facteurs associés de façon indépendante au syndrome de fatigue chronique (SFC) et à la fibromyalgie (FM) ou des répercussions de ces affections sur l’état de santé.Nous avons utilisé les données de l’Enquête sur la santé dans les collectivités canadiennes de 2010 (n = 59 101), représentative de la population à l’échelle nationale, pour décrire les cas autodéclarés de SFC et de FM diagnostiqués par un professionnel de la santé et pour déterminer les associations de ces affections avec six indicateurs de l’état de santé.En 2010, 1,4 % (intervalle de confiance [IC] à 95 % : 1,3 % à 1,6 %) des Canadiens de 12 ans ou plus vivant à domicile ont déclaré avoir reçu un diagnostic de SFC, 1,5 % (IC à 95 %: 1,4 % à 1,7 %) de FM, et 0,3 % (IC à 95 %: 0,3 % à 0,4 %) a déclaré être atteinte à la fois de SFC et de FM. Les cas de SFC comme ceux de FM étaient plus fréquents chez les femmes, les adultes de 40 ans ou plus, les personnes à faible revenu et les personnes présentant certains facteurs de risque de maladie chronique (obésité, sédentarité et tabagisme). Après ajustement en fonction des différences existant entre les groupes, les personnes ayant déclaré être atteintes du SFC ou de FM ou des deux avaient un moins bon état de santé que les personnes atteintes d’aucune de ces affections pour cinq indicateurs de l’état de santé, mais aucune différence n'a été trouvée entre ces groupes par rapport à l’indicateur de santé mentale. Le fait d’être atteint à la fois du SFC et de FM et de présenter de multiples affections comorbides était associé à un moins bon état de santé.La présence concomitante du SFC, de la FM et d’autres affections chroniques était étroitement associée au fait d’avoir un moins bon état de santé, et les différences relatives à l’état de santé étaient dues en bonne partie à la présence concomitante de ces affections. La compréhension des facteurs qui contribuent à l’amélioration de la qualité de vie des personnes atteintes du SFC ou de FM, et en particulier des personnes qui présentent ces deux affections ainsi que diverses affections comorbides, serait un champ important à explorer dans le cadre de travaux de recherche ultérieurs.

Objectives To assess the risk of on-screen death of important characters in children’s animated films versus dramatic films for adults. Design Kaplan-Meier survival analysis with Cox regression comparing time to first on-screen death. Setting Authors’ television screens, with and without popcorn. Participants Important characters in 45 top grossing children’s animated films and a comparison group of 90 top grossing dramatic films for adults. Main outcome measures Time to first on-screen death. Results Important characters in children’s animated films were at an increased risk of death compared with characters in dramatic films for adults (hazard ratio 2.52, 95% confidence interval 1.30 to 4.90). Risk of on-screen murder of important characters was higher in children’s animated films than in comparison films (2.78, 1.02 to 7.58). Conclusions Rather than being the innocuous form of entertainment they are assumed to be, children’s animated films are rife with on-screen death and murder.

Background Up to 20% of US military personnel deployed to Iraq or Afghanistan experience mild traumatic brain injury (mTBI) while deployed; up to one-third will experience persistent post-concussive symptoms (PCS). The objective of this study was to examine the epidemiology of deployment-related mTBI and its relationship to PCS and mental health problems (MHPs) in Canadian Armed Forces (CAF) personnel. Methods Participants were 16153 personnel who underwent post-deployment screening (median =136 days after return) following deployment in support of the mission in Afghanistan from 2009 – 2012. The screening questionnaire assessed mTBI and other injuries while deployed, using the Brief Traumatic Brain Injury Screening Tool. Current MHPs and PCS were assessed using items from the Patient Health Questionnaire, the Patient Checklist for PTSD, and the Cognitive Failures Questionnaire. Log-binomial regression explored the association of mTBI, other injuries, and MHPs with PCS, using the presence of 3 or more of 7 PCS as the outcome. Results are expressed as adjusted prevalence ratios (PR). Results mTBI while deployed was reported in 843 respondents (5.2%). Less severe forms of mTBI (associated only with having been dazed or confused or having “seen stars”) predominated. Blast was reported as a mechanism of injury in half of those with mTBI. Multiple PCS were present in 21% of those with less severe forms of mTBI and in 27% of those with more severe forms of mTBI (i.e., mTBI associated with loss of consciousness or post-traumatic amnesia). After adjustment for confounding, mTBI had no statistically significant association with PCS relative to non-TBI injury. In contrast, MHPs had a strong association with reporting 3 or more PCS (adjusted prevalence ratio (PR) =7.77). Conclusion Deployment-related mTBI prevalence was lower than in many US reports; most of those who had had mTBI were free of multiple PCS. PCS was strongly associated with MHPs but not with mTBI. Careful assessment of MHPs is essential in personnel with a history of combat-related mTBI and PCS.

The goal of this work is to show how the argument principle together with discrete Fourier transform (DFT) can be used to determine some properties of finite-length complex-valued sequences, precisely the localization of zeros with respect to unit circle of their related Z-transform. An upper bound of the DFT (in one step) length to exactly calculate the increase of the argument is also provided.

The problem of reconstructing a one-dimensional signal from only the magnitude of its Fourier transform is known as the phase retrieval problem. This problem emerges when the phase of a signal is apparently lost or impractical to measure. In this paper, we introduce new solutions that compute the phase by directly using the magnitudes of the samples in nepers. These solutions use relationships between the phase and the gain differences, or gain samples. From the obtained minimum phase solution, the non-minimum phase solutions are derived. The advantages consist in simplicity and stability. We compare our solutions by using some numerical examples. The performances under noisy conditions for the two approaches are also considered.

One of the oldest and most useful techniques available in network theory states that the phase can be approximated using the slope of the logarithmic gain characteristic. The goal of this paper is to present some results concerning the analytical properties of logarithmic gain. We also show that a better phase approximation can be obtained in certain situations if the third derivative is taken into account.

Objective: An important minority of military personnel will experience mental health problems after overseas deployments. Our study sought to describe the prevalence and correlates of postdeployment mental health problems in Canadian Forces personnel. Method: Subjects were 16 193 personnel who completed postdeployment screening after return from deployment in support of the mission in Afghanistan. Screening involved a detailed questionnaire and a 40-minute, semi-structured interview with a mental health clinician. Mental health problems were assessed using the Patient Health Questionnaire and the Posttraumatic Stress Disorder Checklist—Civilian Version. Logistic regression was used to explore independent risk factors for 1 or more of 6 postdeployment mental health problems. Results: Symptoms of 1 or more of 6 mental health problems were seen in 10.2% of people screened; the most prevalent symptoms were those of major depressive disorder (3.2%), minor depression (3.3%), and posttraumatic stress disorder (2.8%). The strongest risk factors for postdeployment mental health problems were past mental health care (adjusted odds ratio [AOR] 2.89) and heavy combat exposure (AOR 2.57 for third tertile, compared with first tertile). These risk groups might be targeted in prevention and control efforts. In contrast to findings from elsewhere, Reservist status, deployment duration, and number of previous deployments had no relation with mental health problems. Conclusions: An important minority of personnel will disclose symptoms of mental health problems during postdeployment screening. Differences in risk factors seen in different nations highlight the need for caution in applying the results of research in one population to another.

The paper aims to emphasize the possibilities offered by Virtual Instrumentation (LabVIEW) in the field of biomedical engineering. Thus, it proposes a low cost and flexible wireless transmission (between two equipments) and ECG signals processing architecture. Since during acquisition the signal may be corrupted by noise, in the first stage of the application the signal is filtered by implementing a designed mean averaged filter, followed by a Butterworth filter. The second stage of the application is represented by the infrared transmission of the signal between two infrared “in range” compatible devices. Finally, for an accurate R-peak detection, the Pan-Tomkins algorithm was implemented.

This paper presents a new risk analysis methodology coming from the measuring process of the medical device characteristics. Thus, one can determine the acceptance criteria for the functioning parameters of the medical device undergoing trials in order to be introduced to the market. We point out the fact that the proposed methodology is complementary to the medical device certification process and provides a technical support for its quality assessment.

BACKGROUND: An estimated 5.4 million Canadian adults have been diagnosed with sleep apnea or are at high risk of experiencing obstructive sleep apnea (OSA). There are no recent Canadian data regarding access to and predictors of referral for diagnostic testing in these populations.METHODS: The Sleep Apnea Rapid Response survey sampled 8647 Canadian adults and captured information about risk, testing, diagnosis and treatment of sleep apnea. Predictors of sleep laboratory test referrals were assessed using log-linked binomial regression modelling. Information regarding sleep testing facilities was updated at the provincial and regional levels.RESULTS: Approximately 76.8% (95% CI 70.1% to 83.6%) of adult Canadians with sleep apnea and 5.1% (95% CI 3.4% to 6.7%) of those at high risk for OSA reported being referred to a sleep laboratory. Significant predictors of sleep laboratory referral in the general population were male sex, middle age, overweight or obese, a chronic condition, having a regular medical doctor and reporting symptoms of sleep apnea. Region of residence was also a predictor of reported sleep laboratory referral, with individuals from Ontario being more likely to report being referred to a sleep laboratory versus individuals from other regions.CONCLUSION: Individuals reporting risk factors and symptoms associated with OSA were more likely to report a sleep laboratory testing referral compared with those without risk factors or symptoms. However, Canada’s diagnostic sleep laboratory testing capacity varies across regions and is believed to be inadequate given the number of individuals at high risk for OSA who did not report testing referral.

Recently, there were proposed few stochastic gradient algorithms which are based on cost functions that have exponential dependence on the chosen error. However, in certain framework the convergence of the cost function based on exponential of the squared error is not always satisfactorily. Thus this cost function has been modified and the Exponentiated Convex Variable Step-Size (ECVSS) algorithm has been obtained. It has been shown that with an optimal selection of one tuning parameter the ECVSS algorithm provides attractive results. In this brief we present some performances of the ECVSS stochastic gradient algorithm (time constants, misadjustment, computational complexity) in data echo cancellation framework when the tuning parameter has different values.

The quality of the ultrasound medical images is usually degraded by two important problems - the transducer influence and the speckle noise. To remove the multiplicative speckle noise, in this paper it is presented a method based on a blind, time-domain, deconvolution algorithm. The proposed approach uses the envelope of the acquired radio-frequency signals for the numerical implementation. It is a two steps blind deconvolution, where firstly, the point spread function is automatically estimated from the measured data, and secondly, the data are reconstructed in a non-blind way using proposed algorithm. It has a nonlinear implementation which at each step intends to eliminate the most important part of speckle noise and blur as possible. The results on real image tests are compared with Tikhonov regularization. Our method shows better results for scatters detection and speckle noise removal.

The main objective of this work is the implementation of a new type of spectral analysis, that is more efficient and that can be more easily read than the spectrogram. This analysis should be used for detecting the intruders from a wildlife environment. It is called sparsogram and its main advantage is that it displays only the important spectral components of a given sound. In this way, one can easily see the dominant frequency bands of different audio signals. Later on, a classification method is implemented based on these frequency measurements on the sparsogram, which assigns the sounds from a natural environment to different classes and subclasses of intruders.

The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences anda prioriLaplacian distribution for deconvolved signal. The algorithm is executed in two steps. Firstly, the point spread function is automatically estimated from the measured data. Secondly, the data are reconstructed in a nonblind way using proposed algorithm. The algorithm is a nonlinear blind deconvolution which works as a greedy algorithm. The results on simulated signals and real images are compared with different state of the art methods deconvolution. Our method shows good results for scatters detection, speckle noise suppression, and execution time.

The quality of the reproduced tissues in the ultrasound medical imaging is reduced by the imperfections in tissues and the finite frequency bandwidth and pulse width of the ultrasound transducer. Constrained by these constructive limitations, for improvement of details in the final image, the post processing methods are usually applied. In this paper we present a two step 1D blind deconvolution method based on the well known time domain CLEAN algorithm. In the first step the Point Spread Function is estimated and secondly, we use this estimation to extract the reflectivity function of the tissues. The simulations was oriented to evaluate statistically the method according to the percentage of real detection of scatters, the number of false alarms - which represent the quantity of the artefacts in the final result and the means square error. Also, the algorithm is compared with the classical Tikhonov regularization in term of above presented criteria and mean square error (MSE) - a global estimator between reflectors position and their amplitude.

A variety of related stochastic gradient algorithms can be specified by modifying the minimum mean square error cost function. A part of them have been previously known as cost function adaptation algorithms, though they actually have implemented a kind of variable error exponent algorithms. Besides, the adaptive filtering literature contains many variable step-size methods. In this paper we reconsider former cost function adaptation algorithms and the goal is to integrate variable error exponent and variable step-size algorithms into a unifying framework, i.e. cost function adaptation algorithms. Finally some comments on implementation of variable error-exponents are delivered.

To describe the exercise/physical activity and weight management efforts of Canadians with self-reported arthritis, to examine factors associated with their engagement in these strategies to help manage their arthritis, and to explore reasons for lack of engagement.Data were from the arthritis component of the 2009 Survey on Living with Chronic Diseases in Canada. The responses (78% response rate; n = 4,565) were weighted to be representative of Canadians (ages ≥20 years) with arthritis. Logistic regression analyses were used to examine factors associated with engaging in exercise/physical activity and weight control/loss (among overweight/obese respondents) for arthritis management purposes.Individuals with arthritis were mostly women (63%), ages ≥45 years (89%), overweight/obese (67%), married (68%), and white (87%), with postsecondary education (69%). Sixty-three percent were exercising and of those who were overweight or obese, 68% were trying to control/lose weight; only 46% were engaged in both. Having received a clinical recommendation was the factor most strongly associated with engaging in exercise/physical activity and/or controlling/losing weight. The most common reason for not exercising was a coexisting health condition/problem (22%), while the most common reason for not controlling/losing weight among those who were overweight/obese was that it was felt not to be necessary (51%).The provision of clinical recommendations from a health professional, providing advice on safe and suitable exercises/physical activities, as well as addressing misperceptions of the need to lose weight among the overweight/obese, may facilitate engagement in these health behaviors and ultimately reduce the consequences of arthritis.

For many years it has been known that having a piecewise linear fitting of a function, one can obtain a good approximation of its Hilbert transform. There are few ways to determine the slopes of a broken line approximation, but the most popular approaches need to specify the breakpoints. In this paper we determine the breakpoints using a divide-and-conquer approach, then the Hilbert transform can be computed in two different ways. Simulations results provided here show that the piecewise linear approximation of function and the resulting Hilbert transform approximation are relatively accurate, and the complexity of implementation is not large.

Inertial sensors have found widespread use in various applications. Recently, we have proposed an inertial navigation system based only on Micro-Electro-Mechanical Systems (MEMS) technology. The motivation for implementing such a system was to determine with high accuracy the user position inside a building without the use of any additional systems or infrastructure. In this paper we propose a compensation method for the gyroscope angular rate data based on the ambient temperature. As a result, the errors were reduced while the accuracy of the system increased. Furthermore, by using an additional barometer sensor, the navigation solution can be computed in 3D coordinates.

In this paper we evaluate the effect of the emotional state of a speaker when text-independent speaker identification is performed. The spectral features used for speaker recognition are the Mel-frequency cepstral coefficients, while for the training of the speaker models and testing the system the Gaussian Mixture Models are employed. The tests are performed on the Berlin emotional speech database which contains 10 different speakers recorded in different emotional situations: happy, angry, fear, bored, sad and neutral. The results show an important influence of the emotional state upon text-independent speaker identification. In the end we try to give a possible solution to this problem.

The paper aims to analyze the time and frequency domains of EMG signals coming from healthy patients and from patients with muscular disorders (muscular myopathy and neuropathy). The study of these signals can reveal some features in time domain or in frequency domain, that can serve as a basis for diagnosis.