Fuzzy logic has been successfully deployed in many realworld automatic control systems including subway systems, autofocus cameras, washing machines, automobile transmissions, air-conditioners, industrial robots, aerospace, and autonomous robot navigation. In contrast, the use of fuzzy logic in telecommunication systems and networks is recent and limited. Fundamentally, Zadeh's fuzzy set theory provides a robust mathematical framework for dealing with "real-world" imprecision and nonstatistical uncertainty. Given that the present day complex networks are dynamic, that there is great uncertainty associated with the input traffic and other environmental parameters, that they are subject to unexpected overloads, failures and perturbations, and that they defy accurate analytical modeling, fuzzy logic appears to be a promising approach to address many important aspects of networks. This paper reviews the current research efforts in fuzzy logic-based approaches to queuing, buffer management, distributed access control, load management, routing, call acceptance, policing, congestion mitigation, bandwidth allocation, channel assignment, network management, and quantitative performance evaluation in networks. The review underscores the future potential and promise of fuzzy logic in networks. The paper then presents a list of key research efforts in the areas of fuzzy logic-based algorithms and new hardware and software architectures that are necessary both to address new challenges in networking and to help realize the full potential of fuzzy logic in networks.

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This paper presents the detection of brain tumors through the YOLOv3 deep neural network model in a portable electromagnetic (EM) imaging system. YOLOv3 is a popular object detection model with high accuracy and improved computational speed. Initially, the scattering parameters are collected from the nineantenna array setup with a tissue-mimicking head phantom, where one antenna acts as a transmitter and the other eight antennas act as receivers. The images are then reconstructed from the post-processed scattering parameters by applying the modified delay-multiply-and-sum algorithm that contains 416×416 pixels. Fifty sample images are collected from the different head regions through the EM imaging system. The images are later augmented to generate a final image data set for training, validation, and testing, where the data set contains 1000 images, including fifty samples with a single and double tumor. 80% of the images are utilized for training the network, whereas 10% are used for validation, and the rest 10% are utilized for testing purposes. The detection performance is investigated with the different image data sets. The achieved detection accuracy and F1 scores are 95.62% and 94.50%, respectively, which ensure better detection accuracy. The training accuracy and validation losses are 96.74% and 9.21%, respectively. The tumor detection with its location in different cases from the testing images is evaluated through YOLOv3, which demonstrates its potential in the portable electromagnetic head imaging system.

In this paper, a meander-lines-based epsilon negative (ENG) metamaterial (MTM) with a high effective medium ratio (EMR) and near-zero refractive index (NZI) is designed and investigated for multiband microwave applications. The metamaterial unit cell is a modification of the conventional square split-ring resonator in which the meander line concept is utilized. The meander line helps to increase the electrical length of the rings and provides strong multiple resonances within a small dimension. The unit cell of proposed MTM is initiated on a low-cost FR4 substrate of 1.5 mm thick and electrical dimension of 0.06λ × 0.06λ, where wavelength, λ is calculated at the lowest resonance frequency (2.48 GHz). The MTM provides four major resonances of transmission coefficient (S21) at 2.48, 4.28, 9.36, and 13.7 GHz covering S, C, X, and Ku bands. It shows negative permittivity, near-zero permeability, and near-zero refractive index in the vicinity of these resonances. The equivalent circuit is designed and modeled in Advanced Design System (ADS) software. The simulated S21 of the MTM unit cell is compared with the measured one and both show close similarity. The array performance of the MTM is also evaluated by using 2 × 2, 4 × 4, and 8 × 8 arrays that show close resemblance with the unit cell. The MTM offers a high effective medium ratio (EMR) of 15.1, indicating the design's compactness. The frequency hopping characteristics of the proposed MTM is investigated by open and short-circuited the three outer rings split gaps by using three switches. Eight different combinations of the switching states provide eight different sets of multiband resonances within 2–18 GHz; those give the flexibility of using the proposed MTM operating in various frequency bands. For its small dimension, NZI, high EMR, and frequency hopping characteristics through switching, this metamaterial can be utilized for multiband microwave applications, especially to enhance the gain of multiband antennas.

This paper addresses three key issues in buffer management in cell switching networks including asynchronous transfer mode (ATM) networks. First, it develops a model of fuzzy thresholding-based buffer management for a 50-switch representative cell-switching network, to study its performance under realistic conditions. Previous studies have been confined to a single switch and, consequently, the results are not necessarily applicable to a real-world cell-switching network consisting of multiple switches. Second, it presents an approach to reroute to their final destinations, the fraction of the selectively blocked cells that correspond to the difference of cell loss due to buffer overflow between the fixed and fuzzy schemes. While the fixed threshold, through its abrupt nature, causes a relatively higher cell drop through buffer overflow, intuitively, the fuzzy threshold may trade off cell loss through buffer overflow for increased selective blocking at the sending switch. While the goal of the second issue is to improve throughput and thereby achieve higher reliability, the delays incurred by the cells in the network are likely to increase. Third, this is the first paper to report on the influence of the buffer management scheme on the end-to-end delay performance of a representative cell switching network. The model is simulated on a testbed consisting of a network of 25+ Pentium workstations under linux, configured as a loosely coupled parallel processor. Simulation results reveal that, even for a large-scale representative cell-switching network, the fuzzy approach adapts superbly to different bursty input traffic distributions, yielding lower cell loss rates. A total of 10 000 user calls, generating between 1.0 and 1.5 million ATM cells, is stochastically distributed among the nodes. Performance analysis reveals that for different input traffic distributions ranging from light to moderate to heavy traffic, the fuzzy threshold scheme consistently succeeds in lowering the cell loss due to buffer overflow relative to fixed thresholding by blocking them at the sending switch. The re-routing approach, in turn, successfully routes these blocked cells, although it causes the average end-to-end cell delay in the network to increase compared to the fixed scheme by a factor ranging from 1.65 for relatively light traffic to 6.7 for heavy traffic.Index Terms-asynchronous transfer mode (ATM) networks, buffer management, cell-switching network, fuzzy thresholds, large-scale switching network.