Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Design of backpropagated neurocomputing paradigm for Stuxnet virus dynamics in control infrastructure

Neural Computing and Applications - In the present study, a novel application of backpropagated neurocomputing heuristics (BNCH) is presented for epidemic virus model that portrays the Stuxnet...     

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.     

Mobile-cloud assisted framework for selective encryption of medical images with steganography for resource-constrained devices

In this paper, the problem of outsourcing the selective encryption of a medical image to cloud by resource-constrained devices such as smart phone is addressed, without revealing the cover image to cloud using steganography. In the proposed framework, the region of interest of the medical image is first detected using a visual saliency model. The detected important data is then embedded in a host image, producing a stego image which is outsourced to cloud for encryption. The cloud which has powerful resources, encrypts the image and sent back the encrypted marked image to the client. The client can then extract the selectively encrypted region of interest and can combine it with the region of non-interest to form a selectively encrypted image, which can be sent to medical specialists and healthcare centers. Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.     

Topological evolution of laminar juncture flows under different critical parameters

Horseshoe vortex topological structure has been studied extensively in the past, traditional “saddle of separation” and new “attachment saddle point” topologies found in literature both have theoretical basis and experimental and computational evidences for support. The laminar incompressible juncture flows at low Reynolds numbers especially are observed to have new topology. Studies concerning the existence of the new topology though found in literature, the topological evolution and its dependency on various critical flow parameters require further investigation. A Particle Image Velocimetry based analysis is carried out to observe the effect of aspect ratio, δ*/D and shape of the obstacle on laminar horseshoe vortex topology for small obstacles. Rise in aspect ratio evolves the topology from the traditional to new for all the cases observed. The circular cross section obstacles are found more apt to having the new topology compared to square cross sections. It is noted that the sweeping effect of the fluid above the vortex system in which horseshoe vortex is immersed plays a critical role in this evolution. Topological evolution is observed not only in the most upstream singular point region of horseshoe vortex system but also in the corner region. The corner vortex topology evolves from the traditional type to new one before the topological evolution of the most upstream singular point, resulting in a new topological pattern of the laminar juncture flows “separation-attachment combination”. The study may help extend the understanding of the three-dimensional boundary layer separation phenomenon.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Enviro-Friendly Synthesis of Silver Nanoparticles Using Berberis lycium Leaf Extract and Their Antibacterial Efficacy

In the present study,an enviro-friendly synthesis of silver nanoparticles from Berberis lycium Royle leaf extract and their antibacterial efficacy against five pathogenic bacteria were investigated.This biosynthesis technique is proved to be advantageous over physical and chemical methods as no toxic chemicals are used.The structural and morphological characterization was made by UV-visible spectroscopy,scanning electron microscopy,and transmission electron microscopy.The synthesized nanoparticles were oval,rectangular,and spherical in shape,size ranges from 8 to 100 nm and exhibited an absorption peak at 458 nm.The biosynthesized silver nanoparticles have shown good antibacterial effect toward tested bacteria.It is believed that these biosynthesized silver nanoparticles can play a vital role in nano-based products in future.     

On Structural,Optical, and Electrical Properties of Chromium Oxide Cr2O3 Thin Film for Applications

Protection of Metals and Physical Chemistry of Surfaces - Chromium oxide thin films were grown on Al2O3 substrates by ablating a pure Cr2O3 target using a KrF excimer laser. The energy density on...