In the electronic warfare environment, radars can be differentiated according to intra-pulse and inter-pulse modulations. Detection of intra-pulse modulation with negative SNR is a topic of interest to researchers. In this paper separation of intra-pulse modulation with frequency and time-frequency methods is presented. Using this method, we can categorize different types of LFM, 4FSK, 2FSK, BPSK, and NM modulations. The algorithm of this method is based on characteristics and it is able to classify all radar signals from these types of modulations. To detect the modulation, time-frequency characteristics based on the improved time-frequency transform, B, have been used. The innovation in this research, is the use of new characteristics of time-frequency distribution. The proposed algorithm uses time-frequency distribution to analyze radar signals. Dimension reduction is performed next, then for each frequency the maximum time value is considered and the characteristics are extracted from signal. The presented algorithm has 100% capability of separating radar signals for this number of intra-pulse signals up to-11dB of SNR whereas similar methods have less accuracy with SNR range between-5db to 5db.

Mathematical modeling based on a probabilistic approach for making decisions for organ transplantation can be successfully employed in cases when the choice of decisions can affect the results produced. In this study, the minimum Probability of success required for organ transplantation in case of multi-donors is determined. The governing equations are constructed in terms of probabilities and some other factors like quality adjusted life-years (QALYs) of recipients, donors, expected knowledge gain, medical benefit and expected fame of surgeon. The analytical results are obtained by solving equations and illustrated numerically.

One of the important tools has been recognized to identify patterns is the neural networks and the authors have investigated the application of PLN in this article. This structure was recommended in 1989 and it's capability for simultaneously saving of each pattern, was surveyed. For training this structure, a method called "A-Learning rule" is recommended and also convergence analysis is investigated. Training of the mentioned structure. "A-Learning rule" and "On-Line genetic algorithm (OGA)" premier presented by authors, are used for saving 0-9 Latin digit. Higher convergence speed and capability of saving space of the OGA in compare to the A-learning rule on the PLN, are the results of this article.

Background & Aims: Different scoring systems are used in order to assess the functional quality of intensive care units (ICU) and to predict the required costs and facilities of intensive cares. Variety of scoring systems has been explained that each has advantages and disadvantages. In this study Simplified Acute Physiology Score-III (SAPS-III) and Mortality Probability Model-III (MPM-III) were compared. Materials & Methods: The current cross-sectional study was conducted on 240 non-traumatic patients admitted at ICU of Al-Zahra Hospital in 2016-17. Patients' information including demographics, mean of systolic, diastolic and arterial pressure, pulse rate, respiratory rate, temperature, Glasgow Coma Scale(GCS), WBC, hematocrit, bilirubin, creatinine, arterial blood gas, and the presence of underlying diseases was gathered from the records for measurement of MPM-III and SAPS-III scores and then they were compared. Results: This study was conducted on 240 non-traumatic patients. Discrimination of MPM-III in cutoff point of 0. 17 was 0. 83(P<0. 001; 95%CI: 0. 765-0. 898), sensitivity and specificity of this test in prediction of non-traumatic mortality was 82% and 73%, respectively. Discrimination of SAPS-III in cut-off of 48. 5 was 0. 78(P<0. 001; 95%CI: 0. 72-0. 84), while its sensitivity and specificity was 83% and 70%, respectively. Duration of ICU hospitalization (P=0. 028 and 0. 002) and duration of intubation (P=0. 001 and <0. 001) had direct association with mortality based on both scoring systems while total duration of hospitalization was only significant in SAPSIII (P=0. 002). Conclusion: Comparison of SAPS-III and MPM-III in non-traumatic patients presented a higher discrimination ability for MPM-III. In addition, findings showed that mortality in MPM-III was in association with duration of ICU admission and intubation while for SAPS-III, in addition to previous factors, total duration of hospitalization was associated as well.

Background: Intensive care unit (ICU) is among the most important hospital wards. Variety of scoring systems for evaluation of patients' status and prediction of hospitalization outcomes in ICU has been raised that each has strong and weak points; assessment of these characteristics tends to promote new scoring systems. The current study compared scoring systems of Mortality Probability Model-III (MPM-III) and Simplified Acute Physiology Score-III (SAPS-III) in trauma patients in ICU. Methods: This randomized cross-sectional study was conducted on 200 patients admitted in ICU because of trauma in years 2016-17. Patients' information including demographics, mean of systolic, diastolic, and arterial blood pressure, pulse, respiratory rate, temperature, Glasgow coma scale (GCS), arterial gas analysis, white blood cell (WBC) counts, hematocrit, bilirubin, creatinine, type of admission, and presence of underlying diseases were extracted from records; MPM-III and SAPS-III were measured for these patients and compared. Findings: MPM-III scoring system had discrimination of 0. 935 [95% confidence interval (95%CI): 0. 89-0. 97; P < 0. 001) in cut-off point of 0. 13, and its sensitivity and specificity was 87% and 84%, respectively. For SAPS-III system, in cut-off point of 0. 13, the discrimination was 0. 77 (95%CI: 0. 69-0. 85; P < 0. 001), with the sensitivity of 80% and specificity of 68%. Based on both MPM-III and SAPS-III systems, mortality was in correlation with duration of ICU admission (P = 0. 001 for both systems) and duration of intubation (P < 0. 001 for both systems), while only for SAPS-III, total duration of hospitalization was in correlation with mortality (P < 0. 001). Conclusion: MPM-III scoring system was superior to SAPS-III regarding discrimination power in trauma patients. In addition, based on both systems, mortality rate was in direct association with days of ICU admission and intubation duration.