If the object, characterized by the intensity I(x), is vibrating at a natural frequency ?0 and without losing generality we can write x=Asin(��0t), hence the intensity value becomes I(x)=I(Asin(��0t)). If we want to consider the effect of the function I(x) on our measured peak frequencies we can write:F(I(x))=��?�ޡ�I(Asin(��0t))e?j��tdt(2)If I(x) is a linear function and by subtracting the DC term we are able to compute the exact pea
Advances in wireless, sensor design and energy storage technologies have contributed significantly to the expanded use of Wireless Sensor Networks (WSN) in a variety of applications. Integrated micro-sensors with onboard processing and wireless data transfer capability, the most important components of WSNs, have already existed for some time [1,2].

However, at present, more efficient designs have successfully integrated a wide range of sensors. These sensors can monitor a large variety of environmental factors that can affect health including temperature, humidity, barometric pressure, light intensity, tilt, vibration and magnetic field intensity among others, using short-distance wireless communications.The enormous cost of providing health care to patients with chronic conditions requires new strategies to more efficiently provide monitoring and support in a remote, distributed, and noninvasive manner. Diverse European projects such as the ��HealtService24 Project�� are trying to improve the quality of medical attention by Cilengitide providing remote medical monitoring.

These types of projects are currently developing mobile monitoring systems and integrating remote monitoring into their healthcare protocols to provide expanded healthcare services for persons who require monitoring and follow-up, but do not require immediate medical intervention or hospitalization.The importance of monitoring patient health is significant in terms of prevention, particularly if the human and economic costs of early detection can improve patient independence, improve quality of life, and reduce suffering and medical costs. The early diagnosis and treatment of a variety of diseases can radically alter healthcare alternatives or medical treatments. Prevention and effective control of chronic diseases has proven repeatedly to be more cost effective than conventional treatments at medical facilities. This is particularly true with chronic and incapacitating illnesses such as cardiovascular disease or diabetes. In the case of cardiovascular disease, 4% of the population over 60 and more than 9% of persons over 80 years of age have arrhythmias, or abnormal heart rates, which require occasional diminutive electrical shocks applied to the heart.

In addition, both the Haar and Gabor features selected in the first boosting stage were detected in the area between the pair of eyes, which show that the nosepiece of the frame of the glasses was the important feature for detecting the glasses [19]. However, the nosepiece is not included in the image that is captured by our gaze tracking system, and the part of glasses frame may not be seen in the image, as shown in Figure 3b. Hence, the method in [19] cannot be used for our study.Figure 3.Eye images that were captured at various exposure times (a) Image of naked eye at the normal (unreduced) exposure time; (b) Image of eye with glasses at the normal (unreduced) exposure time; (c) Image of naked eye of (a) at the reduced exposure time; …

Instead, the initial check that determines whether the user is wearing glasses or not is performed as follows. Firstly, the exposure time of camera is reduced and an image is acquired using the eye capturing camera in Figure 1. In general, if a user wears glasses, many reflections occur from the surfaces of the glasses as shown in Figure 3a,b. Since t
The proposed method is applied to monitor the translational axis of a high precision vertical machining centre. Experiments are conducted on the X- axis of this machining centre in an in-service environment, and the experimental time is the whole maintenance period of the X-axis. The experiment system is shown in Figure 5 and the illustration of the X-axis is shown in Figure 6.Figure 5.Experimental system.Figure 6.Illustration of the X-axis.

As shown in Figure 6, the translational axis system (X-axis) is composed of an AC servomotor, a reducer, a precision ball screw and a table. The actuation of this system is provided through the AC servomotor which is attached to the reducer using a diaphragm type coupling. The reducer is a three-stage gearbox attached to the precision ball screw also using a diaphragm type coupling (the teeth number of the each gear is shown in Figure 6). The precision ball screw with 16 mm pitch and 40 mm diameter is supported by two bearings, which drives a table supported on a guideway. Experiments are implemented during the whole maintenance period of the X-axis under the condition that the feed rate is 550 mm/min, when the table is fed steadily without cutting.

The three-phase AC current signals of the servomotor are measured synchronously by three current sensors, and then, the motor torque is obtained by Equations (1) and (2). The total experimental time is 192 days, and the data is collected with an interval of approximate Carfilzomib 26 days. Each data is sampled with sampling frequency 1,000 Hz. Actually, there are eight torque data samples, and each data sample is a collected data series containing 60,000 data points. The characteristic frequencies of the X-axis are given in Table 1.Table 1.The characteristic frequencies of X-Axis system.5.2.

The QuikSCAT satellite was launched into a sun-synchronous, 98.6�� inclination, 803 km circular orbit with a local equator crossing time at the ascending node of 6:00 am �� 30 min and a swath width of 1800 km (Callahan 2006). It uses a rotating dish antenna with two pencil beams that sweep in a circular pattern at incidence angles of 46�� (horizontally polarized) and 52�� (vertically polarized). QuikSCAT carries the SeaWinds instrument, the first satellite-borne scanning radar Ku-band scatterometer which measures the surface roughness of the ocean, affected by the wind magnitude and direction, by transmitting microwave pulses (13.4 GHz) and receiving the backscatter.

Multiple and simultaneous normalized radar cross section (��o) values are obtained from the backscatter power at a single geographical location or wind vector cell (WVC) and converted to wind speed and direction measurements (10 m neutral winds) using a Geophysical Model Function (GMF) (Callahan 2006; M. H. Freilich, SeaWinds Algorithm Document). Up to four solutions are obtained at each WVC, with different goodness-to-fit (residual) between the ��o and model function, with approximately the same wind speed but different wind directions. The final measurement from these solutions is chosen using the ambiguity removal algorithm, the Maximum Likelihood Estimator (MLE) (Shaffer et al. 1991). MLE incorporates the Numerical Weather Prediction (NWP), by the National Centers of Environmental Prediction (NCEP), output as the initial field, or ��first guess��, to choose the best solution (nudging technique).

The NWP wind field is spatially interpolated, 2.5�� resolution 1000 mb (��100 m) global data analysis model Batimastat outputs closest in time to the QuikSCAT pass. The issue of degraded ambiguity removal at far swath and decrease in directional accuracy near nadir are addressed using two algorithms, namely the Direction Interval Retrieval (DIR) and Threshold Nudging (TN) algorithms, combined to form the DIRTH algorithm (Stiles 1999). DIRTH calculates a range of wind directions that is representative of the selected ambiguity in each wind vector cell. DIR then applies a median filter over the entire swath to determine the final wind vector selections (Stiles 1999; Callahan 2006).

The process generates Level 2B ocean wind vectors at 25 km and 12.5 km swath grid Carfilzomib products. The 12.5 km resolution Level 2B winds are produced from ��slices�� of the ellipsoidal instantaneous antenna footprint with a simplified 1|]# backscatter averaging scheme and different land contamination criteria that is particularly useful to resolve the coastal winds (Tang et al. 2004).

The following hypotheses were tested:For each contaminated site and PCB congener: the content of PCB in fresh leech tissue is higher at the monitored site than at the control site.For each site and PCB congener: the content of PCB in fresh leech tissue decreased at the site during the time period.For each year and PCB congener: the content of PCB in fresh leech tissue decreased with distance from the source of pollution.2.?Material and methodsMonitoring was carried out at 11 locations on the River Skalice between years 1992 and 2003 (Table 1, Figures 3,,4).4). Sample site 1 was a control site located two km above the pollution source. Leeches of the genus Erpobdella (prevailing species E. octoculata) were collected every year except 2002. These collections were performed once a year in June.

Due to the low abundance of leeches it was not possible to collect samples every year from each site. Leeches were dried slightly on filter paper, packed into microtone bags, immediately chilled, and frozen to ?20?C. One sample from each site weighed 50 g (corresponding to a composite sample of 600�C700 leeches from one site together). This composite sample was analyzed.Figure 3.Collection of leeches in the Skalice River.Table 1.Sample sites on the River SkaliceA homogenous leech sample weighing 30 g was mixed with 100 g of anhydrous sodium sulphate to form a flowing powder and then extracted for 8 hours in a Soxhlet apparatus with 340 mL of a hexane-dichloromethane (1:1, v/v) solvent mixture.

The crude extract was carefully evaporated and dissolved in 10 mL of a cyclohexane-ethyl acetate mixture (1:1, v/v) containing PCB 112 (this congener is not present either in commercial mixtures or environmental samples), employed as an internal standard.A clean-up of crude extracts was carried out by an Carfilzomib automatic gel permeation chromatographic system (GPC) employing S-X3 Bio Beads. As a mobile phase, cyclohexane-ethyl acetate (1:1, v/v) was used at a flow rate 0.6 mL/min and the fraction corresponding to the elution volume of 14�C30 mL was collected. The eluate was evaporated by a rotary vacuum evaporator at 40��C and the residual solvent was carefully removed by a gentle stream of nitrogen. The residue was then dissolved in 1 mL of isooctane and treated with concentrated sulphuric acid to eliminate any co-extracted residues. An aliquot of the upper isooctane layer was transferred into a glass vial for following GC analysis.An HP 5890 Ser. II, gas chromatograph (Agilent Technologies, USA) equipped with an electronic pressure control (EPC), a split/injector, two parallel 63Ni electron capture detectors (ECDs) and two parallel columns possessing a different selectivity (DB-5 and DB-17, both J&W Scientific, USA) were employed for all analyses of PCBs and OCPs.