Detection and classification of road signs in natural environments

An automatic road sign recognition system first locates road signs within images captured by an imaging sensor on-board of a vehicle, and then identifies the detected road signs. This paper presents an automatic neural-network-based road sign recognition system. First, a study of the existing road sign recognition research is presented. In this study, the issues associated with automatic road sign recognition are described, the existing methods developed to tackle the road sign recognition problem are reviewed, and a comparison of the features of these methods is given. Second, the developed road sign recognition system is described. The system is capable of analysing live colour road scene images, detecting multiple road signs within each image, and classifying the type of road signs detected. The system consists of two modules: detection and classification. The detection module segments the input image in the hue-saturation-intensity colour space, and then detects road signs using a Multi-layer Perceptron neural-network. The classification module determines the type of detected road signs using a series of one to one architectural Multi-layer Perceptron neural networks. Two sets of classifiers are trained using the Resillient-Backpropagation and Scaled-Conjugate-Gradient algorithms. The two modules of the system are evaluated individually first. Then the system is tested as a whole. The experimental results demonstrate that the system is capable of achieving an average recognition hit-rate of 95.96% using the scaled-conjugate-gradient trained classifiers.     

BSLPSDN: Base station location privacy via software-defined networking (SDN) in wireless sensor networks

Base station's location privacy in a wireless sensor network (WSN) is critical for information security and operational availability of the network. A key part of securing the base station from potential compromise is to secure the information about its physical location. This paper proposes a technique called base station location privacy via software-defined networking (SDN) in wireless sensor networks (BSLPSDN). The inspiration comes from the architecture of SDN, where the control plane is separated from the data plane, and where control plane decides the policy for the data plane. BSLPSDN uses three categories of nodes, namely, a main controller to instruct the overall operations, a dedicated node to buffer and forward data, and lastly, a common node to sense and forward the packet. We employ three kinds of nodes to collaborate and achieve stealth for the base station and thus protecting it against the traffic-analysis attacks. Different traits of the WSN including energy status and traffic density can actively be monitored by BSLPSDN, which positively affects the energy goals, expected life of the network, load on common nodes, and the possibility of creating diversion in the wake of an attack on the base station. We incorporated multiple experiments to analyze and evaluate the performance of our proposed algorithm. We use single controller with multiple sensor nodes and multiple controllers with multiple sensor nodes to show the level of anonymity of BS. Experiments show that providing BS anonymity via multiple controllers is the best method both in terms of energy and privacy.     

Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm

Wireless Networks - Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical wireless communications. The OFDM...     

A new method for detecting various variants of GoF design patterns using conceptual signatures

Software design patterns are well-known solutions for solving commonly occurring problems in software design. Detecting design patterns used in the code can help to understand the structure and behavior of the software, evaluate the quality of the software, and trace important design decisions. To develop and maintain a software system, we need sufficient knowledge of design decisions and software implementation processes. However, the acquisition of knowledge related to design patterns used in complex software systems is a challenging, time-consuming, and costly task. Therefore, using a suitable method to detect the design patterns used in the code reduces software development and maintenance costs. In this paper, we proposed a new method based on conceptual signatures to improve the accuracy of design pattern detection. So we used the conceptual signatures based on the purpose of patterns to detect the patterns’ instances that conform to the standard structure of patterns, and cover more instances of patterns’ variants and implementation versions of the patterns and improve the accuracy of pattern detection. The proposed method is a specific process in two main phases. In the first phase, the conceptual signature and detection formula for each pattern is determined manually. Then in the second phase, each pattern in the code is detected in a semi-automatic process using the conceptual signature and pattern detection formula. To implement the proposed method, we focused on GoF design patterns and their variants. We evaluated the accuracy of our proposed method on five open-source projects, namely, Junit v3.7, JHotDraw v5.1, QuickUML 2001, JRefactory v2.6.24, and MapperXML v1.9.7. Also, we performed our experiments on a set of source codes containing the instances of GoF design patterns’ variants for a comprehensive and fair evaluation. The evaluation results indicate that the proposed method has improved the accuracy of design pattern detection in the code.

     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Resource-constrained FPGA implementation of YOLOv2

Neural Computing and Applications - Progress is being made to deploy convolutional neural networks (CNNs) into the Internet of Things (IoT) edge devices for handling image analysis tasks locally....     

Theoretical Investigation of Cubic BaVO<Subscript>3</Subscript> and LaVO<Subscript>3</Subscript> Perovskites via Tran–Blaha-Modified Becke–Johnson Exchange Potential Approach

The full potential linearized augmented plane wave method of density functional theory has been used to investigate the structural, electronic, magnetic and thermoelectric properties of cubic perovskites BaVO₃ and LaVO₃. The ferromagnetic ground state has been found to be stable by comparing the total energies of non-spin-polarized and spin-polarized calculations performed for optimized unit cells. For both compounds, the bond length and tolerance factor are also measured. From the band structures and density of states plots, it is found that both compounds are half-metallic. We found that the presence of V at the octahedral site of these perovskites develops exchange splitting through p-d hybridization, which results in a stable ferromagnetic state. The observed exchange splitting is further clarified from the magnetic moment, charge and spin of the anion and cations. Finally, we also presented the calculated thermoelectric properties of these materials, which show that half-metallic BaVO₃ and LaVO₃ materials are potential contenders for thermoelectric applications.     

Co‐condensation synthesis of well‐defined mesoporous silica nanoparticles: effect of surface chemical modification on plasmid DNA condensation and transfection

Chemically modified mesoporous silica nanoparticles (MSNs) are of interest due to their chemical and thermal stability with adjustable morphology and porosity; therefore, it was aimed to develop and compare the MCM‐41 MSNs functionalised with imidazole groups (MCM‐41‐Im) to unmodified (MCM‐41‐OH) and primary amine functionalised (MCM‐41‐NH₂) MSNs for experimental gene delivery. The results show efficient transfection of the complexes of the plasmid and either MCM‐41‐NH₂ or MCM‐41‐Im. Furthermore, following transfection of HeLa cells using MCM‐41‐Im, an enhanced GFP expression was achieved consistent with the noticeable DNase1 protection and endosomal escape properties of MCM‐41‐Im using carboxyfluorescein tracer.Inspec keywords: condensation, mesoporous materials, silicon compounds, nanoparticles, DNA, surface chemistry, porosity, gene therapy, cellular biophysics, biomedical materials, nanomedicine, nanofabrication, molecular biophysics, biochemistryOther keywords: co‐condensation synthesis, surface chemical modification, plasmid DNA condensation, plasmid DNA transfection, chemical modified mesoporous silica nanoparticles, chemical stability, thermal stability, adjustable morphology, porosity, MCM‐41 MSN functionalisation, imidazole groups, MCM‐41‐OH, primary amine functionalised MSN, gene delivery, HeLa cell transfection, GFP expression, DNase1 protection, endosomal escape properties, carboxyfluorescein tracer, SiO₂      

Mechanism study of silver nanoparticle production using Neurospora intermedia

Elucidation of the molecular mechanism of silver nanoparticle (AgNP) synthesis is necessary to control nanoparticle size, shape, and monodispersity. In this study, the mechanism of AgNP formation by Neurospora intermedia was investigated. The higher production rate of AgNP formation using a culture supernatant heat‐treated at 100° and 121°C relative to that with an un‐treated culture supernatant indicated that the native form of the molecular species is not essential. The effect of the protein molecular weight (MW) on the nanoparticle size distribution and average size was studied by means of ultraviolet–visible spectroscopy and dynamic light scattering. Using un‐treated and concentrated cell‐free filtrate passed through 10 and 20 kDa cut‐off filters led to the production of AgNPs with average sizes of 25, 30, and 34 nm, respectively. Also, using the permeate fraction of cell‐free filtrate passed through a 100 kDa cut‐off filter led to the formation of the smallest nanoparticles with the narrowest size distribution (average size of 16 nm and polydispersity index of 0.18). Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis of the fungal extracellular proteins showed two notable bands with the MWs of 15 and 23 kDa that are involved in the reduction and stabilisation of the nanoparticles, respectively.Inspec keywords: silver, nanoparticles, nanofabrication, proteins, molecular weight, ultraviolet spectra, visible spectra, cellular biophysics, electrophoresis, molecular biophysicsOther keywords: Neurospora intermedia, molecular mechanism, silver nanoparticle synthesis, nanoparticle shape, nanoparticle monodispersity, AgNP formation, untreated culture supernatant, molecular species, protein molecular weight, MW, nanoparticle size distribution, ultraviolet‐visible spectroscopy, dynamic light scattering, untreated cell‐free filtrate, concentrated cell‐free filtrate, cut‐off filters, permeate fraction, polydispersity index, Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis, fungal extracellular proteins, nanoparticle reduction, nanoparticle stabilisation, temperature 100 degC, temperature 121 degC, size 25 nm, size 30 nm, size 34 nm, size 16 nm, Ag     

Green synthesised zinc oxide nanostructures through Periploca aphylla extract shows tremendous antibacterial potential against multidrug resistant pathogens

To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO