Digital Image Processing (DIP) is the ability to manipulate digital photographs via algorithms for pattern detection, segmentation, enhancement, and noise reduction. In addition, the Internet of Things (IoT) acts as the eye and system for all DIP in various applications. It can possess a camera or another image sensor in order to capture real-time data from its environment. All vital data is processed by image processing in such a way that it recognizes the object, detects an anomaly, and automatically decides in real-time. In addition, in an IoT system, the median filter is the technique used for noise reduction by substituting the value of the pixel with the central value of the surrounding pixels. It provides speed and efficiency for quick analysis in all IoT systems. However, the images can get corrupted, especially in resource-constrained IoT devices with small cameras, because of random glitches. Moreover, using new quantum technology like atomic-scale silicon dangling bond (DB) logic circuits, which have advanced in fabrication and become a strong contender for field-coupled nano-computing, can solve previous problems in IoT systems. In this paper, we propose a unique quantum CSM based on two new proposed Mux and De-mux. The proposed CSM can be used for computational circuits like median filter circuits (MFC) in a wide range of digital circuits, specifically IoT devices. The proposed design is verified and validated using the powerful SiQAD tool. When comparing CSM to the newest designs, the suggested quantum circuit uses 85% less energy and takes up 61% less area.

Reversible logic has recently gained significant interest due to its inherent ability to reduce energy dissipation, which is the primary need for low-power digital circuits. One of the newest areas of relevant study is reversible logic, which has applications in many areas, including nanotechnology, DNA computing, quantum computing, fault tolerance, and low-power complementary metal-oxide-semiconductor (CMOS). An electrical circuit is classified as reversible if it has an equal number of inputs and outputs, and a one-to-one relationship. A reversible circuit is conservative if the EXOR of the inputs and the EXOR of the outputs are equivalent. In addition, quantum-dot cellular automata (QCA) is one of the state-of-the-art approaches that can be used as an alternative to traditional technologies. Hence, we propose an efficient conservative gate with low power demand and high speed in this paper. First, we present a reversible gate called ANG (Ahmadpour Navimipour Gate). Then, two non-resistant QCA ANG and reversible fault-tolerant ANG structures are implemented in QCA technology. The suggested reversible gate is realized through the Miller algorithm. Subsequently, reversible fault-tolerant ANG is implemented by the 2DW clocking scheme. Furthermore, the power consumption of the suggested ANG is assessed under different energy ranges (0.5Ek, 1.0Ek, and 1.5Ek). Simulations of the structures and analysis of their power consumption are performed using QCADesigner 2.0.03 and QCAPro software. The proposed gate shows great improvements compared to recent designs.

Abstract Complex networks represent various real‐world systems. Overlapping community detection is one of the critical tasks in studying these networks and has significance to a wide variety of applications, including the exploration of online social networks because of the natural attitude of persons to participate in multiple communities at the same time. Despite a large number of existing community detection algorithms for detecting disjoint communities, the efficient and fast uncovering of overlapping communities has remained a challenging problem. To provide an efficient solution, on the one hand, the balanced link density label propagation (BLDLP) algorithm, proposed by the authors of the current study, is a fast, stable, and efficient method for disjoint community detection. On the other hand, the fuzzy theory is a worthwhile approach for overlapping community detection since it provides the membership rate of the overlapping nodes as well as the detection of overlapping communities. Hence, in this paper, based on the synergy of the BLDLP algorithm and the fuzzy theory, a novel method, called fuzzy BLDLP, for overlapping community detection is proposed. Fuzzy BLDLP is fast and efficient. The proposed method needs no prior information about the number of network communities to discover them. The experiments on both synthetic and real‐world known networks, including Zachary, Dolphins, and COVID‐19 Co‐authorship, have revealed that the proposed method successfully detects the overlapping nodes and communities and hence is comparable with the state‐of‐the‐art overlapping community detection algorithms in terms of recall, precision, F‐score and overlapping normalized mutual information.

Summary Quantum‐dot cellular automata (QCA) is a very interesting nanoscale technology. Ultradense structure and ultralow power consumption are the most important features of QCA compared to CMOS. QCA circuits often suffer from various types of manufacturing defects and are therefore prone to fault. Hence, the design of fault‐tolerant circuits in QCA technology is considered a necessity. In this paper, a novel fault‐tolerant three‐input majority gate is presented using 12 simple and rotated cells in QCA technology. The proposed structure is investigated against all kinds of cell omission, extra‐cell deposition, and cell displacement defects. The simulation results are verified by QCADesigner 2.0.3, and it showed 100%, 89.29%, and 100% tolerance against single‐cell omission, double‐cell omission, and extra‐cell deposition, respectively. In addition, the proposed structure is robust against cell displacement defects. Finally, using the proposed structure, a novel coplanar full adder is presented. The results were compared and indicated that the proposed designs are more reliable than the existing designs. Furthermore, QCAPro power estimator tool was employed to estimate the energy dissipation of the proposed structure.

Summary Quantum‐dot Cellular Automata (QCA) is known as one of best alternative technologies for CMOS, on nano‐scale dimensions, which allows digital circuits to be designed with high speed and density. In this paper, a novel 2:1 multiplexer in QCA technology is proposed. This proposed QCA multiplexer uses a new formulation based on an introduced MV32 gate. The MV32 gate has three inputs and two outputs and operates based on cell interactions. A multi‐layer design for proposed 2:1 QCA multiplexer is provided. The simulation results obtained by the software, QCADesigner 2.0.3, confirm that the proposed multiplexer works well and can be applied as a high performance design, in QCA technology. Moreover, the 2:1 QCA multiplexer is used to create 4:1 and 8:1 QCA multiplexers. The results of comparisons show that the proposed structures have so better performance than many previous designs.

Rapid growth in information technology and computer networks has resulted in the universal use of data transmission in the digital domain. However, the major challenge faced by digital data owners is protection of data against unauthorized copying and distribution. Digital watermark technology is starting to be considered a credible protection method to mitigate the potential challenges that undermine the efficiency of the system. Digital audio watermarking should retain the quality of the host signal in a way that remains inaudible to the human hearing system. It should be sufficiently robust to be resistant against potential attacks. One of the major deficiencies of conventional audio watermarking techniques is the use of non-intelligent decoders in which some sets of specific rules are used for watermark extraction. This paper presents a new robust intelligent audio watermarking scheme using a synergistic combination of singular value decomposition (SVD) and support vector machine (SVM). The methodology involves embedding a watermark data by modulating the singular values in the SVD transform domain. In the extraction process, an intelligent detector using SVM is suggested for extracting the watermark data. By learning the destructive effects of noise, the detector in question can effectively retrieve the watermark. Diverse experiments under various conditions have been carried out to verify the performance of the proposed scheme. Experimental results showed better imperceptibility, higher robustness, lower payload, and higher operational efficiency, for the proposed method than for conventional techniques.