A new cellulose nanocrystal-reduced graphene oxide (CNC-rGO) nanocomposite was successfully used for mediatorless electrochemical sensing of methyl paraben (MP). Fourier-transform infrared spectroscopy (FTIR) and field-emission scanning electron microscopy (FESEM) studies confirmed the formation of the CNC-rGO nanocomposite. Cyclic voltammetry (CV) studies of the nanocomposite showed quasi-reversible redox behavior. Differential pulse voltammetry (DPV) was employed for the sensor optimization. Under optimized conditions, the sensor demonstrated a linear calibration curve in the range of 2 × 10-4-9 × 10-4 M with a limit of detection (LOD) of 1 × 10-4 M. The MP sensor showed good reproducibility with a relative standard deviation (RSD) of about 8.20%. The sensor also exhibited good stability and repeatability toward MP determinations. Analysis of MP in cream samples showed recovery percentages between 83% and 106%. Advantages of this sensor are the possibility for the determination of higher concentrations of MP when compared with most other reported sensors for MP. The CNC-rGO nanocomposite-based sensor also depicted good reproducibility and reusability compared to the rGO-based sensor. Furthermore, the CNC-rGO nanocomposite sensor showed good selectivity toward MP with little interference from easily oxidizable species such as ascorbic acid.
Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in cloud radio access networks (Cloud-RANs). The proposed algorithm employs a combinatorial multi-armed bandit model and minimizes the long-term energy cost at remote radio heads. The algorithm preschedules a set of cost-efficient energy packages to be purchased from an ancillary energy market for the future time slots by learning both from cooperative energy trading at previous time slots and by exploring new energy scheduling strategies at the current time slot. The simulation results confirm a significant performance gain of the proposed scheme in controlling the available power budgets and minimizing the overall energy cost compared with recently proposed approaches for real-time energy resources and energy trading in Cloud-RANs.
The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system.
The fabrication of lightweight, ultra-thin, low power and intelligent body-borne sensors leads to novel advances in wireless body area networks (WBANs). Depending on the placement of the nodes, it is characterized as in/on body WBAN; thus, the channel is largely affected by body posture, clothing, muscle movement, body temperature and climatic conditions. The energy resources are limited and it is not feasible to replace the sensor's battery frequently. In order to keep the sensor in working condition, the channel resources should be reserved. The lifetime of the sensor is very crucial and it highly depends on transmission among sensor nodes and energy consumption. The reliability and energy efficiency in WBAN applications play a vital role. In this paper, the analytical expressions for energy efficiency (EE) and packet error rate (PER) are formulated for two-way relay cooperative communication. The results depict better reliability and efficiency compared to direct and one-way relay communication. The effective performance range of direct vs. cooperative communication is separated by a threshold distance. Based on EE calculations, an optimal packet size is observed that provides maximum efficiency over a certain link length. A smart and energy efficient system is articulated that utilizes all three communication modes, namely direct, one-way relay and two-way relay, as the direct link performs better for a certain range, but the cooperative communication gives better results for increased distance in terms of EE. The efficacy of the proposed hybrid scheme is also demonstrated over a practical quasi-static channel. Furthermore, link length extension and diversity is achieved by joint network-channel (JNC) coding the cooperative link.
Neuromuscular electrical stimulation plays a pivotal role in rehabilitating muscle function among individuals with neurological impairment. However, there remains uncertainty regarding whether the muscle's response to electrical excitation is affected by forearm posture, joint angle, or a combination of both factors. This study aimed to investigate the effects of forearm postures and elbow joint angles on the muscle torque and MMG signals. Measurements of the torque around the elbow and MMG of the biceps brachii (BB) muscle were conducted in 36 healthy subjects (age, 22.24 ± 2.94 years; height, 172 ± 0.5 cm; and weight, 67.01 ± 7.22 kg) using an in-house elbow flexion testbed and neuromuscular electrical stimulation (NMES) of the BB muscle. The BB muscle was stimulated while the forearm was positioned in the neutral, pronation, or supination positions. The elbow was flexed at angles of 10°, 30°, 60°, and 90°. The study analyzed the impact of the forearm posture(s) and elbow joint angle(s) on the root-mean-square value of the torque (TQRMS). Subsequently, various MMG parameters, such as the root-mean-square value (MMGRMS), the mean power frequency (MMGMPF), and the median frequency (MMGMDF), were analyzed along the longitudinal, lateral, and transverse axes of the BB muscle fibers. The test-retest interclass correlation coefficient (ICC21) for the torque and MMG ranged from 0.522 to 0.828. Repeated-measure ANOVAs showed that the forearm posture and elbow flexion angle significantly influenced the TQRMS (p < 0.05). Similarly, the MMGRMS, MMGMPF, and MMGMDF showed significant differences among all the postures and angles (p < 0.05). However, the combined main effect of the forearm posture and elbow joint angle was insignificant along the longitudinal axis (p > 0.05). The study also found that the MMGRMS and TQRMS increased with increases in the joint angle from 10° to 60° and decreased at greater angles. However, during this investigation, the MMGMPF and MMGMDF exhibited a consistent decrease in response to increases in the joint angle for the lateral and transverse axes of the BB muscle. These findings suggest that the muscle contraction evoked by NMES may be influenced by the interplay between actin and myosin filaments, which are responsible for muscle contraction and are, in turn, influenced by the muscle length. Because restoring the function of limbs is a common goal in rehabilitation services, the use of MMG in the development of methods that may enable the real-time tracking of exact muscle dimensional changes and activation levels is imperative.
IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon is called task offloading. Researchers have developed efficient task offloading and scheduling mechanisms for IoT devices to reduce energy consumption and response time. However, most research has not considered fault-tolerance-based job allocation for IoT logistics trucks, task and data-aware scheduling, priority-based task offloading, or multiple-parameter-based fog node selection. To overcome the limitations, we proposed a Multi-Objective Task-Aware Offloading and Scheduling Framework for IoT Logistics (MT-OSF). The proposed model prioritizes the tasks into delay-sensitive and computation-intensive tasks using a priority-based offloader and forwards the two lists to the Task-Aware Scheduler (TAS) for further processing on fog and cloud nodes. The Task-Aware Scheduler (TAS) uses a multi-criterion decision-making process, i.e., the analytical hierarchy process (AHP), to calculate the fog nodes' priority for task allocation and scheduling. The AHP decides the fog nodes' priority based on node energy, bandwidth, RAM, and MIPS power. Similarly, the TAS also calculates the shortest distance between the IoT-enabled vehicle and the fog node to which the IoT tasks are assigned for execution. A task-aware scheduler schedules delay-sensitive tasks on nearby fog nodes while allocating computation-intensive tasks to cloud data centers using the FCFS algorithm. Fault-tolerant manager is used to check task failure; if any task fails, the proposed system re-executes the tasks, and if any fog node fails, the proposed system allocates the tasks to another fog node to reduce the task failure ratio. The proposed model is simulated in iFogSim2 and demonstrates a 7% reduction in response time, 16% reduction in energy consumption, and 22% reduction in task failure ratio in comparison to Ant Colony Optimization and Round Robin.
Resource bound security solutions have facilitated the mitigation of spatio-temporal attacks by altering protocol semantics to provide minimal security while maintaining an acceptable level of performance. The Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing protocol for Wireless Sensor Network (WSN) has been proposed to achieve a minimal selection of malicious nodes by introducing a dynamic collection window period to the protocol's semantics. However, its selection scheme suffers substantial packet losses due to the utilization of a single distance based parameter for node selection. In this paper, we propose a Fuzzy-based Geographic Forwarding protocol (FuGeF) to minimize packet loss, while maintaining performance. The FuGeF utilizes a new form of dynamism and introduces three selection parameters: remaining energy, connectivity cost, and progressive distance, as well as a Fuzzy Logic System (FLS) for node selection. These introduced mechanisms ensure the appropriate selection of a non-malicious node. Extensive simulation experiments have been conducted to evaluate the performance of the proposed FuGeF protocol as compared to DWSIGF variants. The simulation results show that the proposed FuGeF outperforms the two DWSIGF variants (DWSIGF-P and DWSIGF-R) in terms of packet delivery.
Plasmonic antennas are attractive optical components of the optoelectronic devices, operating in the far-infrared regime for sensing and imaging applications. However, low optical absorption hinders its potential applications, and their performance is limited due to fixed resonance frequency. In this article, a novel gate tunable graphene-metal hybrid plasmonic antenna with stacking configuration is proposed and investigated to achieve tunable performance over a broad range of frequencies with enhanced absorption characteristics. The hybrid graphene-metal antenna geometry is built up with a hexagon radiator that is supported by the Al2O3 insulator layer and graphene reflector. This stacked structure is deposited in the high resistive Si wafer substrate, and the hexagon radiator itself is a sandwich structure, which is composed of gold hexagon structure and two multilayer graphene stacks. The proposed antenna characteristics i.e., tunability of frequency, the efficiency corresponding to characteristics modes, and the tuning of absorption spectra, are evaluated by full-wave numerical simulations. Besides, the unity absorption peak that was realized through the proposed geometry is sensitive to the incident angle of TM-polarized incidence waves, which can flexibly shift the maxima of the absorption peak from 30 THz to 34 THz. Finally, an equivalent resonant circuit model for the investigated antenna based on the simulations results is designed to validate the antenna performance. Parametric analysis of the proposed antenna is carried out through altering the geometric parameters and graphene parameters in the Computer Simulation Technology (CST) studio. This clearly shows that the proposed antenna has a resonance frequency at 33 THz when the graphene sheet Fermi energy is increased to 0.3 eV by applying electrostatic gate voltage. The good agreement of the simulation and equivalent circuit model results makes the graphene-metal antenna suitable for the realization of far-infrared sensing and imaging device containing graphene antenna with enhanced performance.
Exceptional advancement has been made in the development of graphene optical nanoantennas. They are incorporated with optoelectronic devices for plasmonics application and have been an active research area across the globe. The interest in graphene plasmonic devices is driven by the different applications they have empowered, such as ultrafast nanodevices, photodetection, energy harvesting, biosensing, biomedical imaging and high-speed terahertz communications. In this article, the aim is to provide a detailed review of the essential explanation behind graphene nanoantennas experimental proofs for the developments of graphene-based plasmonics antennas, achieving enhanced light-matter interaction by exploiting graphene material conductivity and optical properties. First, the fundamental graphene nanoantennas and their tunable resonant behavior over THz frequencies are summarized. Furthermore, incorporating graphene-metal hybrid antennas with optoelectronic devices can prompt the acknowledgment of multi-platforms for photonics. More interestingly, various technical methods are critically studied for frequency tuning and active modulation of optical characteristics, through in situ modulations by applying an external electric field. Second, the various methods for radiation beam scanning and beam reconfigurability are discussed through reflectarray and leaky-wave graphene antennas. In particular, numerous graphene antenna photodetectors and graphene rectennas for energy harvesting are studied by giving a critical evaluation of antenna performances, enhanced photodetection, energy conversion efficiency and the significant problems that remain to be addressed. Finally, the potential developments in the synthesis of graphene material and technological methods involved in the fabrication of graphene-metal nanoantennas are discussed.
Fifth-generation (5G) networks offer high-speed data transmission with low latency, increased base station volume, improved quality of service (QoS), and massive multiple-input-multiple-output (M-MIMO) channels compared to 4G long-term evolution (LTE) networks. However, the COVID-19 pandemic has disrupted the achievement of mobility and handover (HO) in 5G networks due to significant changes in intelligent devices and high-definition (HD) multimedia applications. Consequently, the current cellular network faces challenges in propagating high-capacity data with improved speed, QoS, latency, and efficient HO and mobility management. This comprehensive survey paper specifically focuses on HO and mobility management issues within 5G heterogeneous networks (HetNets). The paper thoroughly examines the existing literature and investigates key performance indicators (KPIs) and solutions for HO and mobility-related challenges while considering applied standards. Additionally, it evaluates the performance of current models in addressing HO and mobility management issues, taking into account factors such as energy efficiency, reliability, latency, and scalability. Finally, this paper identifies significant challenges associated with HO and mobility management in existing research models and provides detailed evaluations of their solutions along with recommendations for future research.
This paper demonstrates the performance of a potential design of a paper substrate-based flexible antenna for intrabody telemedicine systems in the 2.4 GHz industrial, scientific, and medical radio (ISM) bands. The antenna was fabricated using 0.54 mm thick flexible photo paper and 0.03 mm copper strips as radiating elements. Design and performance analyses of the antenna were performed using Computer Simulation Technology (CST) Microwave Studio software. The antenna performances were investigated based on the reflection coefficient in normal and bent conditions. The total dimensions of the proposed antenna are 40 × 35 × 0.6 mm³. The antenna operates at 2.33⁻2.53 GHz in the normal condition. More than an 8% fractional bandwidth is expressed by the antenna. Computational analysis was performed at different flexible curvatures by bending the antenna. The minimum fractional bandwidth deviation is 5.04% and the maximum is 24.97%. Moreover, it was mounted on a homogeneous phantom muscle and a four-layer human tissue phantom. Up to a 70% radiation efficiency with a 2 dB gain was achieved by the antenna. Finally, the performance of the antenna with a homogeneous phantom muscle was measured and found reliable for wearable telemedicine applications.
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients suffering from various cardiovascular diseases (CVDs). This research aims to develop a robust algorithm that can accurately classify the electrocardiogram signal even in the presence of environmental noise. A one-dimensional convolutional neural network (CNN) with two convolutional layers, two down-sampling layers, and a fully connected layer is proposed in this work. The same 1D data was transformed into two-dimensional (2D) images to improve the model's classification accuracy. Then, we applied the 2D CNN model consisting of input and output layers, three 2D-convolutional layers, three down-sampling layers, and a fully connected layer. The classification accuracy of 97.38% and 99.02% is achieved with the proposed 1D and 2D model when tested on the publicly available Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. Both proposed 1D and 2D CNN models outperformed the corresponding state-of-the-art classification algorithms for the same data, which validates the proposed models' effectiveness.
An electrochemical microbiosensor for DNA has been fabricated based on new acrylic microspheres modified with reactive N-acryloxysuccinimide (NAS) functional groups. Hydrophobic poly(n-butylacrylate-N-acryloxysuccinimide) microspheres were synthesized in an emulsion form with a simple one-step photopolymerization technique. Aminated DNA probe was attached to the succinimde functional group of the acrylic microspheres via covalent bonding. The hybridization of the immobilized DNA probe with the complementary DNA was studied by differential pulse voltametry using anthraquninone-2-sulfonic acid monohydrate sodium salt (AQMS) as the electroactive hybridization label. The influences of many factors such as duration of DNA probe immobilization and hybridization, pH, type of ions, buffer concentrations, ionic strength, operational temperature and non-complementary DNA on the biosensor performance were evaluated. Under optimized conditions, the DNA microbiosensor demonstrated a linear response range to target DNA over a wide concentration range of 1.0 × 10(-16) and 1.0 × 10(-8) M with a lower limit of detection (LOD) of 9.46 × 10(-17) M (R(2) = 0.97). This DNA microbiosensor showed good reproducibility with 2.84% RSD (relative standard deviation) (n = 3). Application of the NAS-modified acrylic microspheres in the construction of DNA microbiosensor had improved the overall analytical performance of the resultant DNA microbiosensor when compared with other reported DNA biosensors using other nano-materials for membranes and microspheres as DNA immobilization matrices.
New acrylic microspheres were synthesised by photopolymerisation where the succinimide functional group was incorporated during the microsphere preparation. An optical biosensor for urea based on reflectance transduction with a large linear response range to urea was successfully developed using this material. The biosensor utilized succinimide-modified acrylic microspheres immobilized with a Nile blue chromoionophore (ETH 5294) for optical detection and urease enzyme was immobilized on the surface of the microspheres via the succinimide groups. No leaching of the enzyme or chromoionophore was observed. Hydrolysis of the urea by urease changes the pH and leads to a color change of the immobilized chromoionophore. When the color change was monitored by reflectance spectrophotometry, the linear response range of the biosensor to urea was from 0.01 to 1,000 mM (R2 = 0.97) with a limit of detection of 9.97 μM. The biosensor response showed good reproducibility (relative standard deviation = 1.43%, n = 5) with no interference by major cations such as Na+, K+, NH4+ and Mg2+. The use of reflectance as a transduction method led to a large linear response range that is better than that of many urea biosensors based on other optical transduction methods.
In recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP) on a microfluidic compact disk platform. The developed detection system utilizes a monochromatic ultraviolet (UV) emitter for excitation of fluorescent labeled LAMP amplicons and a color sensor to detect the emitted florescence from target. Then it processes the sensor output and displays the detection results on liquid crystal display (LCD). The sensitivity test has been performed with detection limit up to 2.5 × 10(-3) ng/µL with different DNA concentrations of Salmonella bacteria. This system allows a rapid and automatic endpoint detection which could lead to the development of a point-of-care diagnosis device for foodborne pathogens detection in a resource-limited environment.
An attractive electrochemical sensor of poly(3,4-ethylenedioxythiophene)/reduced graphene oxide electrode (PrGO) was developed for an electrochemical technique for uric acid (UA) detection in the presence of ascorbic acid (AA). PrGO composite film showed an improved electrocatalytic activity towards UA oxidation in pH 6.0 (0.1 M PBS). The PrGO composite exhibited a high current signal and low charge transfer resistance (Rct) compared to a reduced graphene oxide (rGO) electrode or a bare glassy carbon electrode (GCE). The limit of detection and sensitivity of PrGO for the detection of UA are 0.19 μM (S/N = 3) and 0.01 μA/μM, respectively, in the range of 1-300 μM of UA.
The humidity sensing characteristics of different sensing materials are important properties in order to monitor different products or events in a wide range of industrial sectors, research and development laboratories as well as daily life. The primary aim of this study is to compare the sensing characteristics, including impedance or resistance, capacitance, hysteresis, recovery and response times, and stability with respect to relative humidity, frequency, and temperature, of different materials. Various materials, including ceramics, semiconductors, and polymers, used for sensing relative humidity have been reviewed. Correlations of the different electrical characteristics of different doped sensor materials as the most unique feature of a material have been noted. The electrical properties of different sensor materials are found to change significantly with the morphological changes, doping concentration of different materials and film thickness of the substrate. Various applications and scopes are pointed out in the review article. We extensively reviewed almost all main kinds of relative humidity sensors and how their electrical characteristics vary with different doping concentrations, film thickness and basic sensing materials. Based on statistical tests, the zinc oxide-based sensing material is best for humidity sensor design since it shows extremely low hysteresis loss, minimum response and recovery times and excellent stability.
Armalcolite, a rare ceramic mineral and normally found in the lunar earth, was synthesized by solid-state step-sintering. The in situ phase-changed novel ceramic nanocrystals of Ca-Mg-Ti-Fe based oxide (CMTFOx), their chemical reactions and bonding with polydimethylsiloxane (PDMS) were determined by X-ray diffraction, infrared spectroscopy, and microscopy. Water absorption of all the CMTFOx was high. The lower dielectric loss tangent value (0.155 at 1 MHz) was obtained for the ceramic sintered at 1050 °C (S1050) and it became lowest for the S1050/PDMS nanocomposite (0.002 at 1 MHz) film, which was made by spin coating at 3000 rpm. The excellent flexibility (static modulus ≈ 0.27 MPa and elongation > 90%), viscoelastic property (tanδ = E″/E': 0.225) and glass transition temperature (Tg: -58.5 °C) were obtained for S1050/PDMS film. Parallel-plate capacitive and flexible resistive humidity sensors have been developed successfully. The best sensing performance of the present S1050 (3000%) and its flexible S1050/PDMS composite film (306%) based humidity sensors was found to be at 100 Hz, better than conventional materials.
Despite the many attractive potential uses of ceramic materials as humidity sensors, some unavoidable drawbacks, including toxicity, poor biocompatibility, long response and recovery times, low sensitivity and high hysteresis have stymied the use of these materials in advanced applications. Therefore, in present investigation, we developed a capacitive humidity sensor using lead-free Ca,Mg,Fe,Ti-Oxide (CMFTO)-based electro-ceramics with perovskite structures synthesized by solid-state step-sintering. This technique helps maintain the submicron size porous morphology of the developed lead-free CMFTO electro-ceramics while providing enhanced water physisorption behaviour. In comparison with conventional capacitive humidity sensors, the presented CMFTO-based humidity sensor shows a high sensitivity of up to 3000% compared to other materials, even at lower signal frequency. The best also shows a rapid response (14.5 s) and recovery (34.27 s), and very low hysteresis (3.2%) in a 33%-95% relative humidity range which are much lower values than those of existing conventional sensors. Therefore, CMFTO nano-electro-ceramics appear to be very promising materials for fabricating high-performance capacitive humidity sensors.
Since humidity sensors have been widely used in many sectors, a suitable humidity sensing material with improved sensitivity, faster response and recovery times, better stability and low hysteresis is necessary to be developed. Here, we fabricate a uniformly porous humidity sensor using Ca, Ti substituted Mg ferrites with chemical formula of CaMgFe1.33Ti₃O12 as humidity sensing materials by solid-sate step-sintering technique. This synthesis technique is useful to control the grain size with increased porosity to enhance the hydrophilic characteristics of the CaMgFe1.33Ti₃O12 nanoceramic based sintered electro-ceramic nanocomposites. The highest porosity, lowest density and excellent surface-hydrophilicity properties were obtained at 1050 °C sintered ceramic. The performance of this impedance type humidity sensor was evaluated by electrical characterizations using alternating current (AC) in the 33%-95% relative humidity (RH) range at 25 °C. Compared with existing conventional resistive humidity sensors, the present sintered electro-ceramic nanocomposite based humidity sensor showed faster response time (20 s) and recovery time (40 s). This newly developed sensor showed extremely high sensitivity (%S) and small hysteresis of <3.4%. Long-term stability of the sensor had been determined by testing for 30 consecutive days. Therefore, the high performance sensing behavior of the present electro-ceramic nanocomposites would be suitable for a potential use in advanced humidity sensors.