In this paper, a new histogram-based method is introduced to make object detectors resistant to hostile attacks. In the following, this method was applied to two object detector models, YOLOV5 and FRCNN, and in this way, two models resistant to attacks were introduced. In order to verify the performance of the mentioned models, we performed the adversarial training process of these models with three targeted attacks TOG-vanishing, TOG-mislabeling, and TOG-fabrication and one untargeted attack, DAG. We have checked the efficiency of the introduced models on two data sets MSCOCO and PASCAL VOC, which are among the most famous data sets in the field of object recognition. The results show that this method, in addition to improving the adversarial ACCURACY, also improves the clean ACCURACY of the object detector models to some extent. The average clean ACCURACY of the YOLOv5-n model for the PASCAL VOC dataset, if adversarial attacks are applied to it, in the case where no defense method is applied, is 85.5%, and in the case where the histogram method is applied, the average ACCURACY is equal to with 87.36%. In the YOLOv5-n model, according to the results, the best adversarial ACCURACY of this model, which has increased compared to other models, is in TOG-vanishing and TOG-fabrication attacks, which are 48% and 52.36%, respectively.

This paper addresses the problem of fixed-time control for a class of SECOND-ORDER nonlinear systems in the presence of model uncertainty and external disturbance. By introducing a novel form of non-singular terminal sliding mode control, a fixed-time control is designed to obtain acceptable performance, rapid convergence of the system states, high robustness and singularity elimination. Guaranteeing fixed-time convergence is a significant feature of the proposed control law under which the convergence time of the proposed surface is independent of the initial conditions. Since the upper bound of the system uncertainty and disturbance is quite difficult to obtain, an adaptive mechanism is presented under which there is no need to know this upper bound. Lyapunov analysis proves that the system states converge to small neighborhood of the origin within a fixed time. To assess efficiency of the suggested method, a flexible spacecraft attitude control system is considered and a fixed-time attitude control system is derived. Simulation results verify the effectiveness and performance of the presented approach.

Objective: The purpose of this study was to apply the relative robust approach that minimizes the maximum regret to deal with the present uncertainty in the input data of the Markowitz mean-variance portfolio optimization model by reconstructing that model as a SECOND-ORDER conic program. Regret is defined as the difference between the obtained solution and the optimal solution under a specified input data set. This approach uses scenarios to consider the present uncertainty in the input data. Moreover, the robust portfolio optimization model introduced by Bertsimas and Sim, which considers uncertainty as an interval, was used to be compared with the relative robust approach and the Markowitz model. Methods: In this research, the return of 50 more active stocks of the Tehran Stock Exchange (TSE) was used to obtain the optimal portfolio using the minimax regret method based on the Markowitz Model. Then, using the out-of-sample Sharpe criterion, the results of the minimax regret method were compared with the classic methods. Results: Based on the research findings, the relative robust approach in the out-of-sample test on most corresponding points of the efficient frontier showed better performance in comparison with the Markowitz model. Also, the Bertsimas and sim approach delivered better performance than the Markowitz model in the out-of-sample test. The results did not prove any significant difference for out-of-sample outputs between the relative robust and Bertsimas and sim approaches. Conclusion: According to the obtained results, the relative robust approach can surpass the mean-variance approach for investors with almost all levels of risk-return preferences. The approach presented in this research can provide investors with a new risk criterion that can be considered in choosing the optimal portfolio. Furthermore, the results confirmed that investors act indifferently in choosing between the relative robust solution and the solution of Bertsimas and Sim's approach. This method can be applied as a portfolio optimization approach and also different markets can be considered under this technique to have a better understanding of its capability.

Background: Ovarian cancer is the fifth leading cancer-related cause of death in women worldwide and is often diagnosed at advanced stages. Regarding the low sensitivity and specificity of the currently available diagnostic techniques, in the present study, we aimed to evaluate the ACCURACY of RMI and ROMA indexes and comparing these two indexes with CA-125 and HE4 parameters for the diagnosis and differentiation between benign and malignant ovarian tumors. Also, we determined the optimal cut-off level of these markers in patients who attended Arash Women’ s Hospital. Methods: In this cross-sectional study, we included 137 women with ovarian mass who were attended the gynecology clinic of Arash Womenchr('39')s Hospital, Tehran, Iran (April 2017-April 2019), and were eligible according to the inclusion criteria. We included patients with an adnexal mass over 3 cm. Our exclusion criteria were as the following: pregnancy, age under 18 and over 90 years, taking hormonal agents, renal failure, suspected ovarian torsion, ovarian cancer and taking antibiotics, nitric oxide compounds, and heavy metals. Based on serum CA125, HE4, and ultrasound findings, ROMA and RMI indexes were determined for each patient, and the sensitivity and specificity of HE4, RMI, ROMA, and CA125 were compared with the result of the operative histopathologic assessment. Results: According to the area under the ROC curve, regardless of the patientschr('39') menopausal status, the highest diagnostic value was dedicated to RMI with 89% under the curve area and 95% confidence interval (81. 6-96. 4%). Diagnostic values of other markers were as the following: 87. 7%(95%CI=80. 3-95%) for HE4, 87. 3(95%CI=79. 1-95. 4%) for CA125, and 86. 2%(95%CI=78. 7-93. 6%) for ROMA. In terms of menopausal status, HE4 had the highest diagnostic value in premenopausal patients, while in the menopausal group CA125 had the highest diagnostic value. Conclusion: Measurement of HE4 before menopause and CA125 during menopause seems to be helpful in the early detection of ovarian cancers in women with ovarian masses.

Geophysical methods have been developed to study the particulars of physically diffusible fields in the ground. In geophysical studies, the goal is usually to detect inhomogeneities inside the earth using physical values measured at the earth's surface. Geophysicists attempt to reconstruct the Earth's interior structure using such data. The present study, which is known as the Third-order Moving Average, is the solution of an inverse problem for simultaneous estimation of the shape and depth of residual magnetic anomalies. The method was applied to the synthetic model, with and without noise, which Superiority this method will show over the SECOND-ORDER Moving Average. Also, tested by the instance of fi eld data in Geological Survey of Iran (GSI). This method, calculates a nonlinear relationship between depth and shape factor, at seven points with successive window length. Finally, the results showed that this method is very accurate for non-noise data and in has good agreement with the noisy data. which the problem, will showed the superiority of the Third-order Moving Average Method over the SECOND-ORDER Moving Average method for estimating the shape and depth of buried Magnetic Anomalies. It also showed that it is suitable for real data with 5% error.

in this work, some of the lattice plasmon quantum features are examined. Initially, the interaction of the far-field photonic mode and the nanoparticle plasmon mode is investigated. We probe the optical properties of the array plasmon that are dramatically affected by the array geometry. It is notable to mention that the original goal of this work is to examine the quantum feature of the array plasmon. For this reason, we consider a system containing array of the plasmonic nanoparticles and quantum dots. For a complete understanding, we analyze the system with the full quantum theory. Notably, the full quantum analyzing enables us to investigate the quantum fluctuation of the array field. Here, for instance, we study the SECOND-ORDER correlation function and report its modeling results.

Background and Objective: Intraoperative consultation by frozen section is a high – risk procedure with important consequences. Therefore, it is critical to determine efficiency of frozen section performance periodically. This study was performed to determine the ACCURACY of frozen section in Urmia University of Medical Sciences.Materials & Methods: In this cross sectional study, we compared the results of 200 consecutive cases of frozen sections with theirfinal permanent section diagnoses in teaching hospitals of Urmia University of Medical Sciences during March 2001 to March 2008.Results: A total of 155 neoplastic and 45 nonneoplastic specimens were studied. The overall ACCURACY of frozen sections was 96.5%. In diagnosis of neoplastic lesions, sensitivity, specificity, positive and negative predictive values and ACCURACY were 93.1%, 97.7%, 96%, 95% and 95.9%, respectively.Conclusion: In this university interpretation of frozen sections is done with high ACCURACY and is valuable to help surgeons to plan the best management of the operation.

Objective: Meta-comprehension is an important factor in improving students' performance; however, many students have problems in meta-comprehension and regulating their learning.This study aimed to investigate the effect of summarizing on meta-comprehension ACCURACY and regulation ACCURACY in students.Method: The research method was semi-experimental with a pretest-posttest design with an unequal control group. The statistical population was male students in the sixth grade of Tehran. 36 students were selected by available sampling method and assigned into control and experimental groups, randomly. In the pretest, after studying the text, the participants predicted their score in the exam and identified the paragraphs that need to be read again. Then, an exam was taken from the text to determine the ACCURACY of their predictions. In the post-test, the procedure was the same, except that the experimental group summarized the text, after studying the text, but the control group only studied the text.Findings: The results showed that the ACCURACY of monitoring and regulation in the experimental group was significantly higher than the control group in the post-test (p<0/01).Conclusion: It seems that presenting diagnostic cues in the form of producing an activity, by engaging the students in the monitoring process, makes realistic students' judgment of their comprehension and improves the regulation process in them.