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In image processing applications, image denoising is an emerging area that recovers the original image from noisy image, which is essential in the applications like pattern analysis. The main aim of this study is to propose an effective filtering technique with peer groups for effective image restoration processes. Existing bilateral filter has lower performance in smoothing the high curvature and high gradient regions due to nearby input signals are outliers that miss the filter window. In this research paper, a new approach is proposed that includes fuzzy-based approach and similarity function for filtering the mixed noise. In a peer group, the similarity function was adaptive to edge information and local noise level, which was utilised for detecting the similarity among pixels. In addition, a new filtering method modified trilateral filter (MTF) with improved generalised fuzzy peer group (IGFPG) is proposed to remove mixed impulse and adaptive white Gaussian noise from colour images. The modified trilateral filter includes Kikuchi algorithm and loopy belief propagation to solve the inference issues on the basis of passing local message. In this research work, the images were collected from KODAK dataset and a few real time multimedia images like Lena were also used for testing the effectiveness of the proposed methodology. The collected colour images were contaminated with adaptive white Gaussian noise (AWGN) of standard deviation σε[05,20] and impulse noise of probability pε[0.05, 0.20]. The proposed MTF-IGFPG method has the advantages of consider image photometric and geometric similarities. The local structural similarity and narrow spatial window is applied for smoothing the images to effectively preserve the images. From the simulation, the proposed MTF-IGFPG approach attained better performance related to the existing approaches in light of normalised colour difference (NCD), peak signal-to-noise ratio (PSNR), and mean absolute error (MAE). Hence, the proposed approach almost achieved PSNR of 36 dB, which shows 0.2 dB to 2 dB improvement than the existing methods.

Energy efficiency is one of the major challenges in the growing WSNs. Since communication offers a vast place in the consumption of energy, effective routing is the best solution to handle this problem. The lifetime improvement is an important problem since the majority of the WSNs function in an unattended environment, in which monitoring, as well as human access, is not possible in a practical manner. Clustering is one of the powerful approaches, which arranges the system operation for the enhanced lifetime of the network, improves energy efficiency, reduces the consumption of energy, and also attend the scalability of the network. To handle this issue, the present researchers have considered the usage of various clustering algorithms. Yet, the cluster head is burdened by the majority of the suggested algorithms in the process of cluster formation. To handle this problem, this paper plans to develop the energy-efficient clustering for WSN using the improved LEACH protocol. Here, the concept of a hybrid meta-heuristic algorithm is used for the optimal cluster head selection through energy-efficient clustering. The optimal solutions are rated based on the multi-objective function considering the objective constraints like energy, distance, delay, quality of service (QoS), load, and time of death. Communication between the sink node and cluster head uses the distance of separation as a parameter for reducing energy consumption. Two well-performing algorithms, like salp swarm algorithm (SSA) and grasshopper optimization algorithm (GOA) are merged to develop the proposed hybrid algorithm called salp-swarm grasshopper optimization (SS-GO). From the results, for 200 nodes, the normalized energy of SS-GO at 1400th round is 5.41%, 11.43%, 14.71%, and 25.81%, superior to GOA, SSO, O-EHO, and FU-CSA, respectively.Here, the performance of the proposed SS-GO is also higher in the other distance, delay, time of death node, and QOS. The performance of the introduced hybrid algorithm-based LEACH is evaluated in several different scenarios, and it is shown that the proposed protocol improves network lifetime in comparison to a number of the recent similar protocol.

The main intent of this paper is to implement the stability-aware energy-efficient clustering protocol in WSN. This paper plans to derive a multi-objective function with the constraints like energy, distance, delay, stability period, and intents to attain the objective by developing a new well-performing meta-heuristic algorithm called Opposition-based Elephant Herding Optimisation (O-EHO). The objective function diminishes the energy consumption of sensor nodes by optimum selection of cluster heads that leads to maintain the energy balance between the normal nodes. In this way, there is a remarkable enhancement in the performance parameters such as throughput, stability period, and network lifetime. It is proved that the network lifetime is enhanced by the stability period and thus it is considered as the most significant parameter. The experimental analysis proves the competitive performance of the proposed model over other heuristic methods.

In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.

Moving object detection is an essential step in several computer visions like salient object detection, visual object tracking, and video surveillance etc. Many existing methods have a drawback of low efficiency in the challenging scenes like dynamic background, camera jitter, and bad weather images. In this research, Unified model (Yolov3-Improved Non-Maximum Suppression (INMS)) method is proposed to increases the performance in moving object detection. The Change Detection net (CDNET) dataset was trained and also COCO 2014 and PascalVOC data sets were applied to analyse the performance of the developed model. The experimental analysis shows that the developed method has higher efficiency in detecting objects in camera jitter and dynamic background scene. The performance evaluation has been done using the precision, recall, IoU and the accuracy metrics for the proposed model. The results show that the developed model has the ability to effectively identify multiple objects in the dynamic background, while the existing method has the capacity to identify only single object.

Recent years have authenticated a dramatic increase in graph applications due to their advancements in their informative and social connectivity. In large-scale networks, graph data contains huge information and exhibits distinct characteristics. Traditional graph convolutional networks cannot handle the problem of covariate-shift in the neural-networks during analysing the patterns. This research presents an intelligence-based graph-classification model for citation networks by using normalised graph convolution networks to handle covariate-shift problem and provides greater regularisation with a decrement in loss to a greater extent. This problem is vanquished by utilising the normalisation constraint for the individual batch constructed as per network developed for graph-structures which eventually lead to building a robust model. The model classifies the underlying connectivity patterns of the structural and informative relationships with appropriate embeddings. This information is fed to neural-network and learns hidden layer representation that encode both local graphs and features of the nodes in the citation network.

Social media usage is one of the most popular online activities these days. In 2018, it is estimated that 2.65 billion people were using social media worldwide and these numbers are expected to reach almost 3.1 billion by 2021, the majority of whom are young people. With some notable exceptions, there are few studies that have been undertaken in the field of politics and social media. This study examines how usage of social media for political purpose influences the voting behavior of the voter in this realm. The authors test the proposition that using social media for political use offers a new pathway to their political participation, interest, and knowledge using path analysis. Results demonstrate that political use of social media impacted both levels of and growth in traditional political participation, interest, and knowledge during the 2019 election.

The paper proposes a complete modelling of finite state automata along with the associated classifier for texture classification. Pattern analysis of the texture image is performed by proposing a symbolic pattern-based algorithm. This algorithm is developed based on the symbolic dynamics and finite state automata theory for estimating the state transition of the texture variations. Texture image is divided into several partitions, i.e., texture, background of the texture, shadow of the texture, etc. Finite automata state transitions are used to extract the features from the symbolised image. A binary classifier is designed to classify the texture categories based on the feature extraction from the finite automata theory. Pattern analysis is performed on the KITH-TIPS dataset for ten varied categories of texture. 99.12% classification accuracy is achieved when compared with other state-of-art techniques. The experimental study shows the better efficiency of the proposed system when compared to other existing methods.

The nonlinear, steady state magnetohydrodynamics natural convection boundary layer flow, heat and mass transfer of an viscoelastic incompressible Jeffrey’s fluid from a vertical permeable cone with thermal radiation and heat generation/absorption effects is investigated in this article. The transformed conservation equations are solved numerically subject to physically appropriate boundary conditions using a versatile, implicit finite-difference Keller box technique. The Rosseland diffusion algebraic approximation is utilized to simulate thermal radiation effects. The surface of the cones is maintained at a constant temperature and concentration with mass flux present. Excellent correlation of the present results with previous studies is obtained to validate the numerical code. The influence of Deborah number (De), ratio of relaxation to retardation times ($$\lambda $$ λ ), radiation parameter (F), heat generation/absorption parameter ($$\Delta $$ Δ ), suction/injection parameter ($$f_{w}$$ fw ), magnetic parameter (M) and dimensionless tangential coordinate ($$\xi $$ ξ ) on velocity, temperature and concentration evolution in the boundary layer regime are examined in detail. Also, the effects of these parameters on local skin friction, heat transfer rate and mass transfer rateare investigated.

In this Viewpoint article, we asked four scientists working to target important, but so-called 'undruggable', proteins in cancer for their opinions on the most crucial advances, as well as the challenges and what the future holds for this important area of cancer research.

A numerical study is presented to analyze the nonlinear, non-isothermal, magnetohydrodynamic (MHD) free convection boundary layer flows of non-Newtonian tangent hyperbolic fluid past a vertical surface in a non-Darcy, isotropic, homogenous porous medium in the presence of Hall currents and Ionslip currents. The governing nonlinear coupled partial differential equations for momentum conservation in x and z directions, heat and mass conservation in the flow regime are transformed from an (x, y, z) coordinate system to ($$\upxi ,\upeta $$ ξ,η ) coordinate system in terms of dimensionless x-direction velocity ($$f^{\prime }$$ f′ ) and z-direction velocity (G), dimensionless temperature and concentration functions ($$\uptheta $$ θ and $$\upphi $$ ϕ ) under appropriate boundary conditions. Both Darcian and Forchheimer porous impedances are incorporated in both momentum equations. Computations are also provided for the variation of the x and z direction shear stress components and also heat and mass transfer rates. Increasing Weissenberg number (We) is observed to decrease primary and secondary velocity and concentration but increase temperature. It is found that the primary and secondary velocity is increased with increasing power law index (n) whereas the temperature and concentration are decreased. Increasing hall and Ionslip current ($$\beta _{e}$$ βe and $$\beta _{i}$$ βi ) is observed to increase primary velocity but decreases secondary velocity, temperature and concentration. Increasing magnetic parameter ($$N_{m}$$ Nm ) is seen to decrease primary velocity but decreases secondary velocity, temperature and concentration. Increasing Darcy number (Da) is found to increase primary and secondary velocity whereas decreases temperature and concentration. Increasing Forchheimer parameter (Fs) is seen to decrease primary and secondary velocity but increases temperature and concentration. The model finds applications in magnetic materials processing, MHD power generators and purification of crude oils.

This article presents the nonlinear, steady boundary layer flow and heat transfer of an incompressible Tangent Hyperbolic non-Newtonian fluid from a Horizontal Circular Cylinder in the presence of magnetic field and Biot number effects. The transformed conservation equations are solved numerically subject to physically appropriate boundary conditions using a second-order accurate implicit finite-difference Keller Box technique. The numerical code is validated with previous studies. The influence of a number of emerging non-dimensional parameters, namely the Weissenberg number (We), power law index (n), Prandtl number (Pr), Biot number $$(\upgamma )$$ (γ) , the magnetic parameter (M) and dimensionless tangential coordinate ($$\xi $$ ξ ) on velocity and temperature evolution on the boundary layer regime are examined in detail. Furthermore, the effects of these parameters on surface heat transfer rate and local skin frictionare also investigated. Validation with earlier Newtonianstudies is presented and excellent correlation achieved. It is found that the velocity, skin friction and heat transfer rate reduce with increasing We. Whereas, there is slight increase in temperature. Increasing nis observed to increase the velocity and heat transfer rate but decreases temperature and skin friction. An increasing $$\upgamma $$ γ is seen to increase velocity, temperature, local skin friction and heat transfer rate. And an increasing Mis found to decrease velocity, skin friction and heat transfer rate but increases the temperature. The study is relevant to chemical materials processing applications.

Waste heat recovery is one of the energy conservation options. About 30% of heat produced by diesel engines that are coupled to electric power generators are carried away by exhaust gases as waste part of the heat energy produced. In the present work, CFD and experimental analysis was made to study the utilisation of the waste heat energy carried by exhaust gases to obtain hot water used for various purposes in commercial buildings, hostels, etc. The effect of fins arranged on the outer periphery of inner cylinder is also studied. Fin arrangement increases the heat transfer rate by reducing the charging time of TESS. Theoretical, numerical and experimental results were compared and found that the values are closer about 10%. The performance of the TESS is evaluated by calculating performance characteristics such as charging and discharging rates and 14% of heat can be recovered from the 30% energy being wasted.

In depth understanding of dental caries progression and improved diagnostic methodologies to assess early demineralization has enabled development of novel remineralizing therapeutics. Hence, an emerging goal of modern dentistry is to manage non-cavitated carious lesions non-invasively through remineralization.

Research outcome on merger of discrete short length fibres like steel fibre, polypropylene fibre (PPF), alkali resistant fibre (ARF) etc. to produce fibre reinforced concrete (FRC) gave a momentous thrust to FRC to use it for shrinkage resistance, crack bridging as well as improving the tensile load carrying resilience. Continuous research is going on FRC by incorporation of various size/shape combinations of similar fibre material or combinations of different fibre material to further improve the performance of FRC. The challenge of using combinations of various industrial by products having reactive and slow pozzolanic nature as part replacement of cement to reduce greenhouse gas emissions is also experimented world over for achieving sustainability in concrete construction activities. These pozzolanic materials [supplementary cementitious materials (SCM)] are also useful in proportioning self compacting concrete (SCC) which offer higher quantities of powder size material (0.125 mm size) as required for achieving qualifying characteristics of SCC. Innovations for improving the SCC to use it in fast track construction and repair projects is being made by several researches, by the way of incorporating various reactive material to attain fast setting, early strength and combine different fibres in to the SCC to have resistance to shrinkage, cracks and develop enough tensile strength in early age for opening the structure to users. Hence there exists a vast scope for research in FRC for improvement of performance by the way of incorporation of compatible materials and fibre combinations. In this study two types of hybrid fibre reinforced self compacting concrete were proportioned with part replacement of cement with metakaolin as reactive SCM and ground granulated blast furnace slag as normal reactive SCM. Various combinations of PPF and ARF investigated in SCC mix with a target to achieve 1 day compressive strength of 25 N/mm2and split tensile strength of 2 N/mm2for use in fast track construction and repair works. Mechanical strength tests and durability tests at early ages as well as up to 56 days conducted.

This study describes the characterization of a novel kinase inhibitor, ON123300, which inhibits CDK4/6 (cyclin-dependent kinases 4 and 6) and phosphatidylinositol 3 kinase-d (PI3K-d) and exhibits potent activity against mantle cell lymphomas (MCLs) both in vitroand in vivo. We examined the effects of PD0332991 and ON123300 on cell cycle progression, modulation of the retinoblastoma (Rb) and PI3K/AKT pathways, and the induction of apoptosis in MCL cell lines and patient-derived samples. When Granta 519 and Z138C cells were incubated with PD0332991 and ON123300, both compounds were equally efficient in their ability to inhibit the phosphorylation of Rb family proteins. However, only ON123300 inhibited the phosphorylation of proteins associated with the PI3K/AKT pathway. Cells treated with PD0332991 rapidly accumulated in the G0/G1phase of cell cycle as a function of increasing concentration. Although ON123300-treated cells arrested similarly at lower concentrations, higher concentrations resulted in the induction of apoptosis, which was not observed in PD0332991-treated samples. Mouse xenograft assays also showed a strong inhibition of MCL tumor growth in ON123300-treated animals. Finally, treatment of ibrutinib-sensitive and -resistant patient-derived MCLs with ON123300 also triggered apoptosis and inhibition of the Rb and PI3K/AKT pathways, suggesting that this compound might be an effective agent in MCL, including ibrutinib-resistant forms of the disease.

In this article, we investigate the non-linear steady free convection heat and mass transfer of an incompressible Jeffrey’s non-Newtonian fluid from a permeable horizontal isothermal cylinder in a non-Darcy porous medium. A non-Darcy drag force model is employed to simulate the effects of linear porous media drag and second-order Forchheimer drag. The transformed conservation equations are solved numerically subject to physically appropriate boundary conditions using a versatile, implicit, finite difference technique. The numerical code is validated with previous studies. The influence of a number of emerging non-dimensional parameters, namely Deborah number (De), surface suction parameter (fw), Prandtl number (Pr), ratio of relaxation to retardation times (λ), Darcy number (Da), Forchheimer inertial parameter (Λ) and dimensionless tangential coordinate (ξ) on velocity, temperature and concentration evolution in the boundary layer regime are examined in detail. Furthermore, the effects of these parameters on surface heat transfer rate, mass transfer rate and local skin friction are also investigated. It is observed that velocity decreases with increasing Deborah number and Forchheimer parameter, whereas temperature and concentration are enhanced. Increasing λand Daenhances velocity but reduces temperature and concentration. The heat transfer rate and mass transfer rate are found to decrease with increasing Deborah number, De, and increase with increasing λ. Local skin friction is found to decrease with a rise in Deborah number whereas it is elevated with increasing values of relaxation to retardation time ratio (λ). Increasing suction decelerates the flow and also cools the boundary layer, i.e., reduces temperature and also concentration. With increasing tangential coordinate, the flow is decelerated; whereas, the temperature and concentration are enhanced.

From early history, builders, manufacturers, and engineers continued to develop composites of wide assortments of materials. Furthermore, chemical upheaval changed the composite development of plastics such as polyvinyl, polystyrene, etc., and reinforcement was reinforced essential to provide strength and rigidity. At present composites finds many applications in every aspects of day to day life. The utilization of raw materials like coal, baggase and agricultural wastes are used in large scales in industries for power generation and food production. The utilization of these fuels causing huge environmental pollution liberating in the form of ashes. These ashes can be utilized in effective way for manufacturing and structural applications with their incorporation in polymer matrix composites. To enhance the mechanical properties and in reducing the manufacturing cost, these industrial wastes plays a major role. The present research work mainly focuses on the influence of Coal Fly Ash (CFA), Silicon Carbide (SiC) and a mixture of CFA & SiC as filler materials on the mechanical behavior of Epoxy Glass fiber composite. Various types of composites are fabricated by manual hand lay-up process with varying weight percentages of the filler materials and epoxy resin as matrix material. The filler materials weight proportions are taken as 5%, 10% and 15%. The prepared composites are cut into tests specimen as per the ASTM standards of mechanical characterization. The mechanical properties of the composites (like Tensile strength (ASTM D3039/D3039M: 2017), Flexural strength (ASTM D790: 2015), Impact strength (ASTM D 229 el: 2019), Interlaminar shear strength (ASTM D2240: 2015), Hardness (ASTM D2240: 2015)) are determined by using corresponding testing machines and it is observed that the properties exhibited by the composites are enhanced with the incorporation of CFA, SiC & mixture of CFA and SiC when compared with the unfilled composites. So, these composites are considered a multifunctional composite material where the individual fillers are used in some applications and the combined proportions are used in different applications. They replace the existing materials that are very high in cost and cause more pollution at the time of manufacturing. These composites give the ability to improve and increase the efficiency, autonomy, and life expectancy of a structure.