Scientia Iranica
Volume:31 Issue: 14, Jul-Aug 2024

The contagious and pandemic COVID-19 disease is currently considered as the main health concern and posed widespread panic across human-beings. It affects the human respiratory tract and lungs intensely. So that it has imposed significant threats for premature death. Although, its early diagnosis can play a vital role in revival phase, the radiography tests with the manual intervention are a time-consuming process. Time is also limited for such manual inspecting of numerous patients in the hospitals. Thus, the necessity of automatic diagnosis on the chest X-ray or the CT images with a high efficient performance is urgent. Toward this end, we propose a novel method, named as the ULGFBP-ResNet51 to tackle with the COVID-19 diagnosis in the images. In fact, this method includes Uniform Local Binary Pattern (ULBP), Gabor Filter (GF), and ResNet51. According to our results, this method could offer superior performance in comparison with the other methods, and attain maximum accuracy.

The issue of Automatic License Plate Recognition (ALPR) has been a challenging one in recent years, with various factors such as weather conditions, camera angle, lighting, and different characters on license plates. However, thanks to the advances made in deep neural networks, it is now possible to use specific types of neural networks and models to recognize Iranian license plates. In the proposed method, license plate recognition is done in two steps. Firstly, the license plates are detected from the input image using the YOLOv4-tiny model, which is based on the Convolutional Neural Network (CNN). Secondly, the characters on the license plates are recognized using the Convolutional Recurrent Neural Network (CRNN) and Connectionist Temporal Classification (CTC). With no need to segment and label the characters separately, one string of numbers and letters is enough for the labels. The successful training of the models involved using 3065 images of license plates and 3364 images of license plate characters as the desired datasets. The proposed method boasts an average response time of 0.0074 seconds per image and 141 frames per second (fps) in the Darknet framework and 0.128 seconds per image in the TensorFlow framework for the License Plate Detection (LPD) part.

Some business process management systems (BPMSs) have been developed in the field of smart factories. These systems are typically based on technical or production areas and technical processes. However, many existing systems, with respect to technologies used in smart factories and also the dynamic nature of the processes in these environments, are not able meet requirements of smart factories in the business process execution. The present study presents a new prototype of BPMS architecture based on smart factories’ characteristics. This prototype has several components. In the monitoring component, process management can take place through process mining techniques inside a defined data analysis system for collecting event logs from big data. This component could operate based on control and optimization modules. The control module is applied to discover process models and their conformity with models extracted from business process analysis using Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Adaptive Boosting (AdaBoost) algorithms. Also, the optimization module can improve the processes model based on Business Process Intelligence (BPI) technique and Key Performance Indicators (KPIs). The results of the new prototype execution on a case study indicate that the proposed architecture is highly accurate, complete, and optimal in process management for smart factories.

Given a set $P$ of $n$ points in the plane, the maximum triangle problem asks for finding a triangle with three vertices in $P$ that encloses the maximum number of points from $P$. While the problem is easily solvable in $O(n^3)$ time, it has been open whether a subcubic solution is possible. In this paper, we show that the problem can be solved in $o(n^3)$ time, using a reduction to min-plus matrix multiplication. We also provide some improved approximation algorithms for the problem, including a 4-approximation algorithm running in $O(n \log n \log h)$ time, and a 3-approximation algorithm with $O(nh \log n + nh^2)$ runtime, where $h$ is the size of the convex hull of $P$.

This paper investigates an infinite buffer capacity fluid queueing model driven by a state-dependent birth-death process prone to catastrophes. We employ the Laplace-Stieltjes transform and the continued fraction techniques to determine explicit expressions for the joint probability of the number of customers in the background queueing model and the content of the buffer in the steady state. The importance of the proposed system is that, in numerous practical situation, the service facility possesses defence mechanisms versus long waiting lines. The servers may increase their rate of service under the pressure of a large backlog of work. Therefore, it is of interest to discuss queueing systems taking into regard the state dependent nature of the systems. For example, the congestion control mechanisms deny the formation of long queue in computer and communication systems by controlling the transmission rates of packets based on the queue length (of packets) at source or destination. Numerical illustrations are added to uphold the theoretical results.

This paper considers the practical asymptotic stabilization of adesired equilibrium point in discrete-time switched affine systems.The main purpose is to design a state feedback switching rule forthe discrete-time switched affine systems whose parameters can beextracted with less computational complexities. In this regard,using switched Lyapunov functions, a new set of sufficientconditions based on matrix inequalities are developed to solve thepractical stabilization problem. For any size of the switched affinesystem, the derived matrix inequalities contain only one bilinearterm as a multiplication of a positive scalar and a positivedefinite matrix. It is shown that the practical stabilizationproblem can be solved via a few convex optimization problems,including Linear Matrix Inequalities (LMIs) through gridding of ascalar variable interval between zero and one. The numericalexperiments on an academic example and a DC-DC buck-boost converter,as well as comparative studies with the existing works, prove thesatisfactory operation of the proposed method in achieving betterperformances and more tractable numerical solutions.

Optimal planning and management of electric vehicle parking lots (EVPLs) can be an effective approach for improving the operation of both the distribution system and traffic networks. However, the limited land areas of cities can be an obstacle for constructing a large number of parking lots (PLs). This paper proposed a model for optimal siting and sizing of EVPLs as well as their charging schedule to maximize the total profit of their owners, while maximum parking demand of plug-in electric vehicles (PEVs) can be satisfied. In the proposed model, the purpose of trips, number of PEVs, plus their arrival and departure time in different urban areas are considered. Distribution network constraints are also taken into account using linearized load flow equations. The proposed model is implemented in a 37-bus distribution system coupled with a 25-node transportation network which includes four different areas in terms of PEV travel type. The simulation results show the effectiveness of the proposed model to cover the parking demand of PEVs with a limited number of PLs.

The article presents a high gain metamaterial integrated modified golden spiral antenna for THz (Terahertz) applications. THz is well suited to the development of a next-generation wireless telecommunication system capable of firing at a tremendous rate of 100 Gb/sec. The Golden spiral patch antenna is integrated with six decagon metamaterial (MTM) unit cells in the ground plane. The (MTM) unit cell is designed by two decagon SRRs (Split Ring Resonator).The proposed antenna has the dimensions of 100 x 100µm2 with metamaterial decagon rings on the ground.The metamaterial integrated antenna resonates at 2.80THz, 3.15THz, and 3.46 THz with impedance bandwidths of 2.77 THz -2.88THz and 3.00-3.70THz.

In this paper, as the main contribution, three sensorless control structures are presented for the control of the grid-connected PMSG-based wind turbine (WT) employing boost converter and diode rectifier as the machine-side converter. Then, detailed control structures of the boost converter and grid-side converter at the three mentioned control strategies are extracted, and next, features of the abovementioned control strategies are investigated and compared against wind speed variation and grid voltage dip. The boost converter, in the first control strategy, controls the generator speed at the MPPT mode, and in the second control strategy, it regulates the PMSG active power to its set point value. Also, the boost converter, in the third control strategy, adjusts the voltage of the dc link capacitor to its set point value. In this paper, steady-state performance and transient/LVRT behavior of the WT system are examined for each mentioned control strategy in the Matlab-Simulink environment. It is shown that WT steady-state responses are relatively identical for all three control strategies. However, as an interesting result, at the fault conditions, the third control strategy has superior performance, and thus, the WT fault ride-through behavior enhances significantly with the third control structure without any hardware protection.

The hybrid excitation flux switching permanent magnet (HEFSPM) motor with magneticbridge is a topology of hybrid excitation flux-switching PM machines. Despite its excellent performancesuch as high torque/ power density, high flux enhancing/ weakening capability and so on, it has receivedless attention due to its complicated structure. Therefore, its optimal design and performance all need tobe further investigated. This paper presents an optimal design of a HEFSPM motor with magnetic bridge.At first, the machine structure and basic working principle are discussed briefly. Then, a design sensitivityanalysis for geometric optimization is carried out to improve the motor performance. This optimizedmotor is compared with initial design. Finally, a prototype of the optimized proposed motor is built andtested to validate the simulation results.