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The output energy of the detection lter serves as a signal detection statistic and will be signi cant only if both the selected code delay and frequency translation match that of the signal When the energy exceeds a predetermined threshold b, a tentative decision is made that a signal is being received, subject to later con rmation The value chosen for the threshold b is a compromise between the con icting goals of maximizing the probability PD of detecting the signal when it is actually present at a given Doppler and code delay and minimizing the probability PFA of false alarm when it is not Searching in Code Delay For each frequency searched, the receiver generates the same PRN code as that of the satellite and moves the delay of this code in discrete steps (typically 0.

The differential diagnosis of an adnexal mass detected during pregnancy is similar to that of a nongravid reproductive-age female. The most common etiology is a functional cyst either of follicular or corpus luteum origin.2 The differential diagnosis must also include hemorrhagic cysts, mature cystic teratomas, serous cystadenomas, paraovarian cysts, mucinous cystadenomas, endometriomas, pedunculated leiomyomas, and malignant tumors. There are several other masses unique to pregnancy that, although much less common, should be considered. One example is hyperreactio luteneinalis, which is thought to result from hypersensitivity of the ovary to circulating human chorionic gonadotropin and has a similar appearance to that of a hyperstimulated ovary.13 Additionally, a luteoma is a rare solid ovarian lesion that occurs in pregnancy and is often associated with maternal hirsuitism or virilization.

5 chips) until approximate alignment with the received code (and also a match in Doppler) is indicated when the correlator output energy exceeds.

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Only by encouraging critical thinking and experimenting can a patient be helped to fully grasp the complexity of a notion and to understand what that notion means when adapted to his or her speci c problem (Ventura & Bauer, 1999) This is in contrast to the temptation to reduce the complexity of any human condition and change process to simplistic categories of good and bad, black and white (so typical of mass media information about eating and weight) that may encourage a false con dence and hinder real change The discussion during a group treatment, and the white space in a manual where patients are asked to register observations, allow therapists to follow the growth in this direction and monitor the change process through the different stages The therapist can then orient the treatment according to the information that seems to be needed.

Both these protocols were later extended to multiparty setting, which is referred to as group key agreement [5]. Researchers also considered the dynamic scenario [40]; that is, participants are allowed to join or leave the group at any time. A general approach of group key agreement is to arrange the participants in a tree structure for n participants this requires around n rounds. Constant round group key agreement protocol is also available in the literature [4]. The group key agreement protocols are usually implemented over elliptic curve groups [26]. Those requiring bilinear pairing further use modi ed Weil or Tate pairing [15] over elliptic curve groups. Operations over elliptic curve groups and implementation of bilinear pairing are computationally quite intensive. This severely restricts their application in smaller devices, especially sensor networks, though some encouraging result is available for elliptic curve cryptography in 8-bit processors [20]. For application is sensor networks, the target is to achieve some kind of optimum trade-off between computational and memory costs and communication bandwidth. In the absence of any trusted central authority, contributory group key agreement (CGKA) protocols that provide some kind of veri able trust relationship has been suggested [31] for this kind of situation. Some recent works [29] are available in this direction based on the tree-based approach of group key agreement in the elliptic curve settings.

In the right tail of the hazard function, generally both the numerator and the denominator are approaching 0. To avoid problems with the denominator approaching 0, we must compute the saddlepoint approximation much farther out in the tail than the largest value of t desired for accuracy. Figure 3.8 gives the hazard function for various values of TM , along with the exact hazard for comparison. For example, although TM = 10 is adequate for the density plot, it is clear from Figure 3.8 that a larger value of TM is required for the hazard computation. Example 3.7: R Code for Saddlepoint Approximation. This example presents the R code for computing the saddlepoint approximation to the density, survivor, and hazard functions in Example 3.6. Two functions are needed: a function to

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