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.

In this paper, a new mechanism is proposed to transform the structural modeling elements of the UML class diagram and object-Z specifications into each other. A set of bidirectional rules is defined to transform the mentioned elements into each other. Bidirectional transformation of the UML class diagram, as one of the most useful diagrams of UML, and object-Z specifications into each other prepares the ground for the use of the unique advantages of both formal and visual modeling methods. The feasibility of the proposed approach is evaluated using the multi-lift case study. The results of conducting the multi-lift case study show that the proposed mechanism is feasible.

In this paper, the problem of signal detection based on suboptimum-constant false alarm rate (CFAR) detector, in the presence of a mixture of K-distributed clutter, is studied. In this case, a new suboptimum detector named generalized likelihood ratio test and maximum a posteriori (GLRT-MAP) is proposed and compared with generalized likelihood ratio test and linear quadratic (GLRT-LQ) suboptimum detector. The CFAR properties of the GLRT-MAP detector are investigated and compared with that of the GLRT-LQ detector. The simulation results show that the GLRT-MAP is a completely CFAR detector regardless of the clutter distribution and correlation in covariance matrix, whereas the GLRT-LQ is only CFAR detector regardless to clutter distribution. The performance analyses of the GLRT-MAP and GLRT-LQ are investigated by means of Monte Carlo simulation, and results are provided in results section.

According to the prevalent beliefs, comitative object, cognate object and object of purpose are not present in the syntactical functions of Persian language. However, there is lack of scientific research on this subject. Not only has it been ignored in grammar books, but also it has not been discussed in the essays and articles. The present study seeks to investigate the above mentioned functions in Persian syntax and to show their Persian equivalents by bringing several instances from Persian texts of prose and poetry. Subsequently, the paper aims to show the differences between these functions in Arabic and Persian. Influenced by Arabic, the article introduces new terminology, which did not formerly exist in Persian language.

Aesthetic object has always been a challenging theme for philosophers of art. The overall aim of this paper is to revise a very specific phenomenological approach to this theme. It includes a talk about artwork and its relationship with aesthetic object and ends with a reconsideration of the being of aesthetic object which is vital for the phenomenology of art.

An important parameter of Geiger Muller detectors is their lengthy dead time which causes a nonlinear response at high counting rates of the detector. Dead time depends on the detector’s nature (size, geometry and material) and its connected electronics (detection, counting, and quenching circuits) plus detection settings. A very important and efficient method of dead time cancelation is time to first count method of measurement at the expense of a complicated electronic circuitry for active quenching of the Geiger Muller detector. In this paper, based on FPGA, a fast and efficient active quenching circuit is developed. Moreover, the time to first count (named as time intervals in this paper) is also acquired at the same time by the system on a chip (SoC) architecture. The time resolution of the system is 10 ns which is pretty enough for Geiger Muller detectors regarding their timing characteristics (the dead time of the Geiger Muller detectors ranges from several microseconds to more than 200 microseconds). ZP1210 Geiger Muller detector is taken as a case study. The dead time of the detector is about 200 µs according to the manufacturer datasheet. This active quenching circuit which is implemented on a single chip, is experimentally tested on this detector. Details of the work is explained in the text.