Real-Time Robotic Presentation Skill Scoring Using Multi-Model Analysis and Fuzzy Delphi-Analytic Hierarchy Process.

Existing methods for scoring student presentations predominantly rely on computer-based implementations and do not incorporate a robotic multi-classification model. This limitation can result in potential misclassification issues as these approaches lack active feature learning capabilities due to fixed camera positions. Moreover, these scoring methods often solely focus on facial expressions and neglect other crucial factors, such as eye contact, hand gestures and body movements, thereby leading to potential biases or inaccuracies in scoring. To address these limitations, this study introduces Robotics-based Presentation Skill Scoring (RPSS), which employs a multi-model analysis. RPSS captures and analyses four key presentation parameters in real time, namely facial expressions, eye contact, hand gestures and body movements, and applies the fuzzy Delphi method for criteria selection and the analytic hierarchy process for weighting, thereby enabling decision makers or managers to assign varying weights to each criterion based on its relative importance. RPSS identifies five academic facial expressions and evaluates eye contact to achieve a comprehensive assessment and enhance its scoring accuracy. Specific sub-models are employed for each presentation parameter, namely EfficientNet for facial emotions, DeepEC for eye contact and an integrated Kalman and heuristic approach for hand and body movements. The scores are determined based on predefined rules. RPSS is implemented on a robot, and the results highlight its practical applicability. Each sub-model is rigorously evaluated offline and compared against benchmarks for selection. Real-world evaluations are also conducted by incorporating a novel active learning approach to improve performance by leveraging the robot's mobility. In a comparative evaluation with human tutors, RPSS achieves a remarkable average agreement of 99%, showcasing its effectiveness in assessing students' presentation skills.

A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images.

Computerized brain tumor classification from the reconstructed microwave brain (RMB) images is important for the examination and observation of the development of brain disease. In this paper, an eight-layered lightweight classifier model called microwave brain image network (MBINet) using a self-organized operational neural network (Self-ONN) is proposed to classify the reconstructed microwave brain (RMB) images into six classes. Initially, an experimental antenna sensor-based microwave brain imaging (SMBI) system was implemented, and RMB images were collected to create an image dataset. It consists of a total of 1320 images: 300 images for the non-tumor, 215 images for each single malignant and benign tumor, 200 images for each double benign tumor and double malignant tumor, and 190 images for the single benign and single malignant tumor classes. Then, image resizing and normalization techniques were used for image preprocessing. Thereafter, augmentation techniques were applied to the dataset to make 13,200 training images per fold for 5-fold cross-validation. The MBINet model was trained and achieved accuracy, precision, recall, F1-score, and specificity of 96.97%, 96.93%, 96.85%, 96.83%, and 97.95%, respectively, for six-class classification using original RMB images. The MBINet model was compared with four Self-ONNs, two vanilla CNNs, ResNet50, ResNet101, and DenseNet201 pre-trained models, and showed better classification outcomes (almost 98%). Therefore, the MBINet model can be used for reliably classifying the tumor(s) using RMB images in the SMBI system.

Ultrawideband Polarization-Independent Nanoarchitectonics: A Perfect Metamaterial Absorber for Visible and Infrared Optical Window Applications.

This article presents numerical analysis of an ultrathin concentric hexagonal ring resonator (CHRR) metamaterial absorber (MMA) for ultrawideband visible and infrared optical window applications. The proposed MMA exhibits an absorption of above 90% from 380 to 2500 nm and an average absorbance of 96.64% at entire operational bandwidth with a compact unit cell size of 66 × 66 nm2. The designed MMA shows maximum absorption of 99% at 618 nm. The absorption bandwidth of the MMA covers the entire visible and infrared optical windows. The nickel material has been used to design the top and bottom layer of MMA, where aluminium nitride (AlN) has been used as the substrate. The designed hexagonal MMA shows polarization-independent properties due to the symmetry of the design and a stable absorption label is also achieved for oblique incident angles up to 70 °C. The absorption property of hexagonal ring resonator MMA has been analyzed by design evaluation, parametric and various material investigations. The metamaterial property, surface current allocation, magnetic field and electric field have also been analyzed to explore the absorption properties. The proposed MMA has promising prospects in numerous applications like infrared detection, solar cells, gas detection sensors, imaging, etc.

A Bibliometric Analysis of Low-Cost Piezoelectric Micro-Energy Harvesting Systems from Ambient Energy Sources: Current Trends, Issues and Suggestions.

The scientific interest in piezoelectric micro-energy harvesting (PMEH) has been fast-growing, demonstrating that the field has made a major improvement in the long-term evolution of alternative energy sources. Although various research works have been performed and published over the years, only a few attempts have been made to examine the research's influence in this field. Therefore, this paper presents a bibliometric study into low-cost PMEH from ambient energy sources within the years 2010-2021, outlining current research trends, analytical assessment, novel insights, impacts, challenges and recommendations. The major goal of this paper is to provide a bibliometric evaluation that is based on the top-cited 100 articles employing the Scopus databases, information and refined keyword searches. This study analyses various key aspects, including PMEH emerging applications, authors' contributions, collaboration, research classification, keywords analysis, country's networks and state-of-the-art research areas. Moreover, several issues and concerns regarding PMEH are identified to determine the existing constraints and research gaps, such as technical, modeling, economics, power quality and environment. The paper also provides guidelines and suggestions for the development and enhancement of future PMEH towards improving energy efficiency, topologies, design, operational performance and capabilities. The in-depth information, critical discussion and analysis of this bibliometric study are expected to contribute to the advancement of the sustainable pathway for PMEH research.

Penta band single negative meta-atom absorber designed on square enclosed star-shaped modified split ring resonator for S-, C-, X- and Ku- bands microwave applications.

This paper represents a penta band square enclosed star-shaped modified split ring resonator (SRR) based single negative meta-atom absorber (MAA) for multi-band microwave regime applications. FR-4 low-cost material has been used as a substrate to make the MAA unit cell with 0.101λ0 × 0.101λ0 of electrical size, where λ0 is the wavelength calculated at the lower resonance frequency of 3.80 GHz. There are two outer square split ring and one inner star ring shape resonator of 0.035 mm thickness of copper placed on the one side, and another side of the substrate has full copper to construct the desired unit cell. The MAA unit cell provides five absorption peaks of 97.87%, 93.65%, 92.66%, 99.95%, and 99.86% at the frequencies of 3.80, 5.65, 8.45, 10.82, and 15.92 GHz, respectively, which covers S-, C-, X-, and Ku- bands. The properties of MAA have been investigated and analyzed in the E-, H-fields and surface current. The EMR and highest Q factor of the designed MAA is 9.87 and 30.41, respectively, and it shows a single negative (SNG) property. Different types of parametric analysis have been done to show the better performance of absorption. Advanced Designed System (ADS) software has been used for equivalent circuit to verify the simulated S11 result obtained from the CST-2019 software. Experimental outcomes of the MAA unit cell have a good deal with the simulated result and measured result of the 24 × 20 array of unit cells also shown. Since the unit cell provides superior EMR, excellent Q-factor, and highest absorption so the recommended MAA can be effectively used as a penta band absorber in microwave applications, like notch filtering, sensing, reducing the unintended noise generated with the copper component of the satellite and radar antennas.

Distinctive accuracy measurement of binary descriptors in mobile augmented reality.

Mobile Augmented Reality (MAR) requires a descriptor that is robust to changes in viewing conditions in real time application. Many different descriptors had been proposed in the literature for example floating-point descriptors (SIFT and SURF) and binary descriptors (BRIEF, ORB, BRISK and FREAK). According to literature, floating-point descriptors are not suitable for real-time application because its operating speed does not satisfy real-time constraints. Binary descriptors have been developed with compact sizes and lower computation requirements. However, it is unclear which binary descriptors are more appropriate for MAR. Hence, a distinctive and efficient accuracy measurement of four state-of-the-art binary descriptors, namely, BRIEF, ORB, BRISK and FREAK were performed using the Mikolajczyk dataset and ALOI dataset to identify the most appropriate descriptor for MAR in terms of computation time and robustness to brightness, scale and rotation changes. The obtained results showed that FREAK is the most appropriate descriptor for MAR application as it able to produce an application that are efficient (shortest computation time) and robust towards scale, rotation and brightness changes.

Geometric feature descriptor and dissimilarity-based registration of remotely sensed imagery.

Image registration of remotely sensed imagery is challenging, as complex deformations are common. Different deformations, such as affine and homogenous transformation, combined with multimodal data capturing can emerge in the data acquisition process. These effects, when combined, tend to compromise the performance of the currently available registration methods. A new image transform, known as geometric mean projection transform, is introduced in this work. As it is deformation invariant, it can be employed as a feature descriptor, whereby it analyzes the functions of all vertical and horizontal signals in local areas of the image. Moreover, an invariant feature correspondence method is proposed as a point matching algorithm, which incorporates new descriptor's dissimilarity metric. Considering the image as a signal, the proposed approach utilizes a square Eigenvector correlation (SEC) based on the Eigenvector properties. In our experiments on standard test images sourced from "Featurespace" and "IKONOS" datasets, the proposed method achieved higher average accuracy relative to that obtained from other state of the art image registration techniques. The accuracy of the proposed method was assessed using six standard evaluation metrics. Furthermore, statistical analyses, including t-test and Friedman test, demonstrate that the method developed as a part of this study is superior to the existing methods.

Design and Experimental Evaluation of Modified Square Loop Feeding for UHF RFID Tags.

This paper addresses the performance evaluation of a modified square loop antenna design for UHF RFID applications that is excited through a narrow feed line connected to a square loop, an impedance matching network. The square loop dimensions are modified to reach a conjugate impedance matching. A gap is fixed between the feed-lines to link the chip. To achieve impedance matching, the structures of the feed-line are optimized accordingly. In addition, the antenna consists of a straightforward geometry. An 11.9-meter maximum read range is achieved using a compact size of 80 × 44 mm2 and 3.2 W for the effective isotropic radiated power. Additional findings reveal that the proposed tag antenna is able to provide a stable resonance response in the near field of a large metallic surface.

Microwave Imaging Sensor Using Compact Metamaterial UWB Antenna with a High Correlation Factor.

The design of a compact metamaterial ultra-wideband (UWB) antenna with a goal towards application in microwave imaging systems for detecting unwanted cells in human tissue, such as in cases of breast cancer, heart failure and brain stroke detection is proposed. This proposed UWB antenna is made of four metamaterial unit cells, where each cell is an integration of a modified split ring resonator (SRR), capacitive loaded strip (CLS) and wire, to attain a design layout that simultaneously exhibits both a negative magnetic permeability and a negative electrical permittivity. This design results in an astonishing negative refractive index that enables amplification of the radiated power of this reported antenna, and therefore, high antenna performance. A low-cost FR4 substrate material is used to design and print this reported antenna, and has the following characteristics: thickness of 1.6 mm, relative permeability of one, relative permittivity of 4.60 and loss tangent of 0.02. The overall antenna size is 19.36 mm × 27.72 mm × 1.6 mm where the electrical dimension is 0.20 λ × 0.28 λ × 0.016 λ at the 3.05 GHz lower frequency band. Voltage Standing Wave Ratio (VSWR) measurements have illustrated that this antenna exhibits an impedance bandwidth from 3.05 GHz to more than 15 GHz for VSWR < 2 with an average gain of 4.38 dBi throughout the operating frequency band. The simulations (both HFSS and computer simulation technology (CST)) and the measurements are in high agreement. A high correlation factor and the capability of detecting tumour simulants confirm that this reported UWB antenna can be used as an imaging sensor.

A novel user classification method for femtocell network by using affinity propagation algorithm and artificial neural network.

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation.

Design and realization of a planar ultrawideband antenna with notch band at 3.5 GHz.

A small antenna with single notch band at 3.5 GHz is designed for ultrawideband (UWB) communication applications. The fabricated antenna comprises a radiating monopole element and a perfectly conducting ground plane with a wide slot. To achieve a notch band at 3.5 GHz, a parasitic element has been inserted in the same plane of the substrate along with the radiating patch. Experimental results shows that, by properly adjusting the position of the parasitic element, the designed antenna can achieve an ultrawide operating band of 3.04 to 11 GHz with a notched band operating at 3.31-3.84 GHz. Moreover, the proposed antenna achieved a good gain except at the notched band and exhibits symmetric radiation patterns throughout the operating band. The prototype of the proposed antenna possesses a very compact size and uses simple structures to attain the stop band characteristic with an aim to lessen the interference between UWB and worldwide interoperability for microwave access (WiMAX) band.

Circularly polarized S band dual frequency square patch antenna using glass microfiber reinforced PTFE composite.

Circularly polarized (CP) dual frequency cross-shaped slotted patch antenna on 1.575 mm thick glass microfiber reinforced polytetrafluoroethylene (PTFE) composite material substrate is designed and fabricated for satellite applications. Asymmetric cross-shaped slots are embedded in the middle of the square patch for CP radiation and four hexagonal slots are etched on the four sides of the square patch for desired dual frequency. Different substrate materials have been analysed to achieve the desired operating band. The experimental results show that the impedance bandwidth is approximately 30 MHz (2.16 GHz to 2.19 GHz) for lower band and 40 MHz (3.29 GHz to 3.33 GHz) for higher band with an average peak gain of 6.59 dBiC and 5.52 dBiC, respectively. Several optimizations are performed to obtain the values of the antenna physical parameters. Moreover, the proposed antenna possesses compactness, light weight, simplicity, low cost, and circularly polarized. It is an attractive candidate for dual band satellite antennas where lower band can be used for uplink and upper band can be used for downlink.

Gain enhancement of a multiband resonator using defected ground surface on epoxy woven glass material.

A multiband microstrip resonator is proposed in this study which is realized through a rectangular radiator with embedded symmetrical rectangular slots in it and a defected ground surface. The study is presented with detailed parametric analyses to understand the effect of various design parameters. The design and analyses are performed using the FIT based full-wave electromagnetic simulator CST microwave studio suite. With selected parameter values, the resonator showed a peak gain of 5.85 dBi at 5.2 GHz, 6.2 dBi at 8.3 GHz, 3.9 dBi at 9.5 GHz, 5.9 dBi at 12.2 GHz, and 4.7 dBi at 14.6 GHz. Meanwhile, the main lobe magnitude and the 3 dB angular beam width are 6.2 dBi and 86°, 5.9 dBi and 53.7°, 8.5 dBi and 43.9°, 8.6 dBi and 42.1°, and 4.7 dBi and 30.1°, respectively, at the resonant frequencies. The overall resonator has a compact dimension of 0.52λ × 0.52λ × 0.027λ at the lower resonant frequency. For practical validation, a lab prototype was built on a 1.6 mm thick epoxide woven glass fabric dielectric material which is measured using a vector network analyzer and within an anechoic chamber. The comparison between the simulated and measured results showed a very good understanding, which implies the practical suitability of the proposed multiband resonator design.