Scientia Iranica
Year:2023 | Volume:30 | Issue:Transactions on Computer Science & Engineering and Electrical Engineering (D)6|Papers Count:6

In this manuscript, a generalized class of estimators has been developed for estimating a finite population means in ranked set sampling scheme. The expressions for bias and mean square error (MSE) of the proposed class of estimators have been derived up to the first order of approximation. Some estimators are shown to be a member of the proposed class. The proposed class of estimators has been compared through the MSE criterion over the other existing member estimators of the proposed class of estimators. The theoretical conditions are obtained under which the proposed class of estimators has performed better. Efficiency comparisons, empirical study, and simulation study also delineate the soundness of our proposed generalized class of the estimators under ranked set sampling (RSS).

The smart manufacturing in the context of a smart factory is allowed through different uncertain processes which make big challenges. In this case, smart manufacturing should be applied reliably, interoperable, and consistently. Thus, it faces the requirement for orchestrating services provided by uncertain processes to satisfy the challenges. These uncertain processes are commonly managed by an uBPMS which is specifically designed to address unknown conditions. The current uBPMS architecture does not consider the business process orchestration and the objective of this paper is to achieve an extension of uBPMS architecture with business process orchestration feature to make a response in real time and satisfy the uncertainty conditions in smart factory. The proposed extension can perform autonomous orchestration of business processes inward traditional uBPMS architecture based on desired values of different objectives optimization. This new architecture operates based on a robust bi-level optimization approach. The Rousselot smart factory in Belgium as a simulated case study was studied. The results show the robustness of the new architecture for process orchestration design in this case. Also, uncertain business process management based on the process orchestration feature presents efficiency and accuracy improvement in smart manufacturing systems.

For $0<\gamma<180^{\circ}$, a geometric path $P=(p_1,\ldots, p_n)$ is called angle-monotone with width $\gamma$ from $p_1$ to $p_n$ if there exists a closed wedge of angle $\gamma$ such that every directed edge $\overrightarrow{p_ip_{i+1}}$ of~$P$ lies inside the wedge whose apex is $p_i$. A geometric graph $G$ is called angle-monotone with width $\gamma$ if for any two vertices $p$ and $q$ in $G$, there exists an angle-monotone path with width $\gamma$ from $p$ to $q$. In this paper, we show that for any integer $k\geq 1$ and any $i\in\{2, 3, 4, 5\}$, the theta-graph $\Theta_{4k+i}$ on a set of points in convex position is angle-monotone with width $90^\circ+\frac{i\theta}{4}$, where $\theta=\frac{360^{\circ}}{4k+i}$. Moreover, we present two sets of points in the plane, one in convex position and the other in non-convex position, to show that for every $0<\gamma<180^\circ$, the graph $\Theta_4$ is not angle-monotone with width $\gamma$.

This paper recovers optical soliton solutions with $\chi^{(2)}$--nonlinear susceptibility. Bright, dark, singular, bright--dark combo solitons are recovered. A variety of algorithms are implemented. These include Riccati equation approach, exp--function expansion, modified simple equation method, sine-Gordon equation scheme, $F$--expansion, trial function and functional variable approaches.%This paper recovers optical soliton solutions with $\chi^{(2)}$--nonlinear susceptibility. Bright, dark, singular, bright--dark combo solitons are recovered. A variety of algorithms are implemented. These include Riccati equation approach, exp--function expansion, modified simple equation method, sine-Gordon equation scheme, $F$--expansion, trial function and functional variable approaches.%This paper recovers optical soliton solutions with $\chi^{(2)}$--nonlinear susceptibility. Bright, dark, singular, bright--dark combo solitons are recovered. A variety of algorithms are implemented. These include Riccati equation approach, exp--function expansion, modified simple equation method, sine-Gordon equation scheme, $F$--expansion, trial function and functional variable approaches.

The heating, ventilation, and air conditioning (HVAC) control system is responsible for the efficient building energy system. Indoor energy consumption patterns can be monitored and reduced intelligently. Occupancy information plays a vital role to save a reasonable amount of energy. Traditional energy monitoring and control systems can be improved with the installation of the occupancy monitoring system which will consist of a network of sensors and cameras. In this research work, we propose a new and revolutionary convolutional neural network (CNN) based on real-time camera occupancy detection and recognition techniques across different sorts of sensors that provide realistic low-cost energy-saving solutions with robust graphical processing units (GPUs). This occupancy information will decide the energy behaviour inside buildings. Decision-making tools can be used to select the appropriate occupancy detection and recognition alternative for indoor environment and energy monitoring and management. In this research work, we introduce and develop the "Fermatean fuzzy prioritized weighted average and geometric operator". These aggregation operators (AOs) are a modern approach to modelling complexities in decision-making. In the end, we give an algorithm for an intelligent decision support system (IDSS) using proposed AOs to compare our CNN based method with other existing sensors techniques.

I propose a new electro-optical system for sequencing single-stranded DNA molecules. The localized plasmons in graphene combined with the nanopore-based DNA translocation have been suggested for sequencing DNA molecules and decreasing the translocation speed. These localized surface plasmon resonances in the graphene nanopore have three dominant modes. Every-mode peak wavelength is shifted while the DNA nucleobases are presented to the nanopore. The ultraviolet photodiodes with narrow-band filters can separate each mode individually. Then, the electrical-current to voltage convertor, differential pairs based on the bipolar transistors, combine all modes in the effective output voltage. The output voltage level of the circuit is sensitive to the DNA presence and is unique for each DNA nucleobase. Analyzes have been performed for different central wavelengths and spectral width of the light source. Results show that the best sensitivity to the DNA molecule is 6.04, and the best selectivity is 1.1. These factors are directly related to the method's applicability for DNA translocation sensing and DNA sequencing; they are enormously improved. The proposed method and results shed light on a higher selectivity for DNA nucleobases which is the main bottleneck for nanopore DNA sequencing.