Smart Antennas and Intelligent Sensors Based Systems: Enabling Technologies and Applications

open access articleThe growing communication and computing capabilities in the devices enlarge the connected world and improve the human life comfort level. The evolution of intelligent sensor networks and smart antennas has led to the development of smart devices and systems for real-time monitoring of various environments. The demand of smart antennas and intelligent sensors significantly increases when dealing with multiuser communication system that needs to be adaptive, especially in unknown adverse environment [1–3]. The smart antennas based arrays are capable of steering the main beam in any desired direction while placing nulls in the unwanted directions. Intelligent sensor networks integration with smart antennas will provide algorithms and interesting application to collect various data of environment to make intelligent decisions [4, 5]. The aim of this special issue is to provide an inclusive vision on the current research in the area of intelligent sensors and smart antenna based systems for enabling various applications and technologies. We cordially invite some researchers to contribute papers that discuss the issues arising in intelligent sensors and smart antenna based system. Hence, this special issue offers the state-of-the-art research in this field

5D Parameter Estimation of Near-Field Sources Using Hybrid Evolutionary Computational Techniques

Hybrid evolutionary computational technique is developed to jointly estimate the amplitude, frequency, range, and 2D direction of arrival (elevation and azimuth angles) of near-field sources impinging on centrosymmetric cross array. Specifically, genetic algorithm is used as a global optimizer, whereas pattern search and interior point algorithms are employed as rapid local search optimizers. For this, a new multiobjective fitness function is constructed, which is the combination of mean square error and correlation between the normalized desired and estimated vectors. The performance of the proposed hybrid scheme is compared not only with the individual responses of genetic algorithm, interior point algorithm, and pattern search, but also with the existing traditional techniques. The proposed schemes produced fairly good results in terms of estimation accuracy, convergence rate, and robustness against noise. A large number of Monte-Carlo simulations are carried out to test out the validity and reliability of each scheme

An Application of Artificial Intelligence for the Joint Estimation of Amplitude and Two-Dimensional Direction of Arrival of Far Field Sources Using 2-L-Shape Array

An easy and efficient approach, based on artificial intelligence technique, is proposed to jointly estimate the amplitude, elevation, and azimuth angles of far field sources impinging on 2-L-shape array. In these proposed artificial intelligence techniques, the metaheuristics based on genetic algorithm and simulated annealing are used as global optimizers assisted with rapid local version of pattern search for optimization of the adaptive parameters. The performance metric is employed on a fitness evaluation function depending on mean square error which is optimum and requires single snapshot to converge. The proposed approaches are easy to understand, and simple to implement; the genetic algorithm specifically hybridized with pattern search generates fairly good results. The comparison of the given schemes is carried out with 1-L-shape array, as well as, with parallel-shape array and is found to be in good agreement in terms of accuracy, convergence rate, computational complexity, and mean square error. The effectiveness and efficiency of the given schemes are examined through Monte Carlo simulations and their inclusive statistical analysis

Cytotoxic Evaluation and Molecular Docking Studies of Aminopyridine Derivatives as Potential Anticancer Agents

Background: The development of resistance to available anticancer drugs is increasingly becoming a major challenge and new chemical entities could be unveiled to compensate for this therapeutic failure. Objectives: The current study demonstrated whether N-protected and deprotected amino acid derivatives of 2aminopyridine could attenuate tumor development using colorectal cancer cell lines. Methods: Biological assays were performed to investigate the anticancer potential of synthesized compounds. The in silico ADME profiling and docking studies were also performed by docking the designed compounds against the active binding site of beta-catenin (CTNNB1) to analyze the binding mode of these compounds. Four derivatives 4a, 4b, 4c, and 4d were selected for investigation of in vitro anticancer potential using colorectal cancer cell line HCT 116. The anti-tumor activities of synthesized compounds were further validated by evaluating the inhibitory effects of these compounds on the target protein beta-catenin through in vitro enzyme inhibitory assay. Results: The docking analysis revealed favorable binding energies and interactions with the target proteins. The in vitro MTT assay on colorectal cancer cell line HCT 116 and HT29 revealed potential anti-tumor activities with an IC50 range of 3.7-8.1µM and 3.27-7.7 µM, respectively. The inhibitory properties of these compounds on the concentration of beta-catenin by ELISA revealed significant percent inhibition of target protein at 100 µg/ml. Conclusion: In conclusion, the synthesized compounds showed significant anti-tumor activities both in silico and in vitro, having potential for further investigating its role in colorectal cancer

Deep eutectic solvent coated cerium oxide nanoparticles based polysulfone membrane to mitigate environmental toxicology

In this study, ceria nanoparticles (NPs) and deep eutectic solvent (DES) were synthesized, and the ceria-NP’s surfaces were modified by DES to form DES-ceria NP filler to develop mixed matrix membranes (MMMs). For the sake of interface engineering, MMMs of 2%, 4%, 6% and 8% filler loadings were fabricated using solution casting technique. The characterizations of SEM, FTIR and TGA of synthesized membranes were performed. SEM represented the surface and cross-sectional morphology of membranes, which indicated that the filler is uniformly dispersed in the polysulfone. FTIR was used to analyze the interaction between the filler and support, which showed there was no reaction between the polymer and DES-ceria NPs as all the peaks were consistent, and TGA provided the variation in the membrane materials with respect to temperature, which categorized all of the membranes as very stable and showed that the trend of stability increases with respect to DES-ceria NPs filler loading. For the evaluation of efficiency of the MMMs, the gas permeation was tested. The permeability of CO2 was improved in comparison with the pristine Polysulfone (PSF) membrane and enhanced selectivities of 35.43 (αCO2/CH4) and 39.3 (αCO2/N2) were found. Hence, the DES-ceria NP-based MMMs proved useful in mitigating CO2 from a gaseous mixture

Primary plant nutrients modulate the reactive oxygen species metabolism and mitigate the impact of cold stress in overseeded perennial ryegrass

Overseeded perennial ryegrass (Lolium perenne L.) turf on dormant bermudagrass (Cynodon dactylon Pers. L) in transitional climatic zones (TCZ) experience a severe reduction in its growth due to cold stress. Primary plant nutrients play an important role in the cold stress tolerance of plants. To better understand the cold stress tolerance of overseeded perennial ryegrass under TCZ, a three-factor and five-level central composite rotatable design (CCRD) with a regression model was used to study the interactive effects of nitrogen (N), phosphorus (P), and potassium (K) fertilization on lipid peroxidation, electrolyte leakage, reactive oxygen species (ROS) production, and their detoxification by the photosynthetic pigments, enzymatic and non-enzymatic antioxidants. The study demonstrated substantial effects of N, P, and K fertilization on ROS production and their detoxification through enzymatic and non-enzymatic pathways in overseeded perennial ryegrass under cold stress. Our results demonstrated that the cold stress significantly enhanced malondialdehyde, electrolyte leakage, and hydrogen peroxide contents, while simultaneously decreasing ROS-scavenging enzymes, antioxidants, and photosynthetic pigments in overseeded perennial ryegrass. However, N, P, and K application mitigated cold stress-provoked adversities by enhancing soluble protein, superoxide dismutase, peroxide dismutase, catalase, and proline contents as compared to the control conditions. Moreover, N, P, and, K application enhanced chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids in overseeded perennial ryegrass under cold stress as compared to the control treatments. Collectively, this 2−years study indicated that N, P, and K fertilization mitigated cold stress by activating enzymatic and non-enzymatic antioxidants defense systems, thereby concluding that efficient nutrient management is the key to enhanced cold stress tolerance of overseeded perennial ryegrass in a transitional climate. These findings revealed that turfgrass management will not only rely on breeding new varieties but also on the development of nutrient management strategies for coping cold stress

Joint Angle-Amplitude Estimation for Multiple Signals with L-Structured Arrays Using Bioinspired Computing

The aim of this work is to estimate jointly the elevation and azimuth angles along with the amplitudes of multiple signals impinging on 1-L- and 2-L-shape arrays. An efficient mechanism based on hybrid Bioinspired techniques is proposed for this purpose. The global search optimizers such as Differential Evolution (DE) and Particle Swarm optimization (PSO) are hybridized with a local search optimizer called pattern search (PS). Approximation theory in Mean Square Error sense is exploited to develop a fitness function of the problem. The unknown parameters of multiple signals transmitted by far-field sources are estimated with the strength of hybrid DE-PS and PSO-PS. The effectiveness of the proposed techniques is tested in terms of estimation accuracy, proximity effect, convergence, and computational complexity

Sidelobe Reduction in Non-Contiguous OFDM-Based Cognitive Radio Systems Using a Generalized Sidelobe Canceller

In orthogonal frequency division multiplexing (OFDM), sidelobes of the modulated subcarriers cause high out-of-band (OOB) radiation, resulting in interference to licensed and un-licensed users in a cognitive radio system environment. In this work, we present a novel technique based on a generalized sidelobe canceller (GSC) for the reduction of sidelobes. The upper branch of the GSC consists of a weight vector designed by multiple constraints to preserve the desired portion of the input signal. The lower branch has a blocking matrix that blocks the desired portion and preserves the undesired portion (the sidelobes) of the input signal, followed by an adaptive weight vector. The adaptive weight vector adjusts the amplitudes of the undesired portion (the sidelobes) so that when the signal from the lower branch is subtracted from the signal from the upper branch, it results in cancellation of the sidelobes of the input signal. The effectiveness and strength of the proposed technique are verified through extensive simulations. The proposed technique produces competitive results in terms of sidelobe reduction as compared to existing techniques

Suppression of Mutual Interference in Noncontiguous Orthogonal Frequency Division Multiplexing Based Cognitive Radio Systems

Orthogonal frequency division multiplexing (OFDM) is a favourable technology for dynamic spectrum access (DSA) due to the flexibility in spectrum shaping. In spite of that, high sidelobes of OFDM subcarriers bring in considerable interference to the nearby users, particularly in OFDM based cognitive radio (CR) networks, where the secondary users (SUs) are capable of accessing the spectrum opportunistically. In this paper, two new techniques for the suppression of high sidelobes are proposed. The proposed techniques composed of an optimization scheme are followed by generalized sidelobe canceller. The proposed techniques can be considered as a two-level suppression technique in the sense that in the first level the sidelobe is reduced by using cancellation carriers (CCs), whose amplitudes are determined using genetic algorithm (GA) and differential evolution (DE), while in the second level further reduction of sidelobe is achieved using generalized sidelobe canceller (GSC). Simulation results show the power spectral density (PSD) performance of the proposed techniques in comparison with already existing techniques, demonstrating that the proposed techniques minimize the out-of-band radiation (OOBR) significantly, thus qualifying for more effective spectrum sharing