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Mobile Health (m-Health) has become an integral part of modern healthcare, utilizing digital devices like laptops, smart phones, and tablets to facilitate the rapid exchange of real-time patient data through interconnected channels. However, the reliance on centralized cloud computing in m-health systems introduces potential security vulnerabilities. Among these threats, Distributed Denial of Service (DDoS) attacks pose a significant risk, capable of disrupting networks and compromising system reliability. The research paper addresses the vulnerability of m-healthcare systems to DDoS attacks and proposes a four-layered architecture to enhance security measures. The focus on recognizing and identifying DDoS attacks within the system is crucial for early detection and prevention of potential harm. Moreover, the exploration of different deterrence approaches in a virtualized cloud-based environment allows for a comprehensive assessment of their effectiveness. The analysis of performance metrics, particularly the maximum and mean values of DDoS attack success rates, provides valuable insights into the efficacy of the proposed architecture and defense mechanisms. This information will undoubtedly assist in refining and strengthening the system's security measures to mitigate the impact of potential DDoS attacks. Overall, the research paper delves into a critical aspect of m-healthcare system security, shedding light on the vulnerabilities and proposing feasible solutions. By adopting a proactive approach to counter DDoS attacks, the proposed architecture holds the potential to significantly enhance the reliability and privacy of m-health systems, ultimately benefiting patients and healthcare providers alike. The proposed approach taken is innovative and promising.

In this paper, a discussion on the forced vibration of a transversely isotropic piezoelectric plate with finite dimensions subjected to a time-harmonic force resting on a rigid foundation is carried out. Here, we assume that the plate is poled along the perpendicular surface and bi-axial initially stressed in their reference configuration. The three-dimensional linearized theory of electro-elastic waves in initially stressed bodies (TLTEEWISB) is applied to the initially-stressed piezoelectric plate. A general formulation of the governing equations of motions is provided according to the piece-wise homogeneous body model, and then the three-dimensional finite element modeling (3D-FEM) is developed as a solution procedure in terms of weak formulation and virtual work principle. The objective of this paper is to present the results regarding the frequency response of the piezoelectric rectangular plate and the influence of the initial stress factor on the system. Numerical examples imply that while the increasing aspect ratio of the plate prevents the resonance mode of the dynamic force, the increasing thickness ratio exceeds this mode. Further, it is also demonstrated and discussed in detail that the initial stress state has a considerable influence on this mode.

The localised heat addition and rapid temperature fluctuations during welding induces significant levels of residual stresses in thick-walled pipe welds. Residual stress so induced by welding, need to be stress relieved; in these thick walled pipes that are extensively used in power plant applications. While thermal stress relieving (SR) serves as a pivotal intervention, field-welded components and sizable weldments, exceeding furnace capacities, necessitate resistance-based, local post weld heat treatment (PWHT). Nevertheless, the local heating of pipes always results in a finite Through-Thickness Temperature Gradient (TTG). Though, heat treatment parameters are governed by standards, to limit TTG for effective SR; observations indicate limitations of these parameters in achieving desired TTG for specific pipe dimensions. Prior studies specify two alternatives viz. widening the heated band and reducing the heating rate to achieve the desired TTG. However, the preferred approach of widening the heat band for larger pipes; necessitate exorbitantly large capacity power sources and expose a wider zone of weldment to critical transformation temperatures which pose practical limitations and attract industrial apprehensions. Thus, to take informed decisions, the relative efficacies of alternatives over the standard governed approach in terms of relief and redistribution of residual stress, capacity of power source required and energy consumed are evaluated through Finite Element (FE) simulation. Valuable insights from FE results, considering the merits, demerits, logical advantages and financial implications facilitating selection of appropriate SR strategy in industrial applications for successfully relieving stress in difficult to SR pipes (thick-walled, SA335P91) are determined and discussed in detail.

Natural hazards like landslides can have devastating consequences. The study of landslide causes and their vulnerability assessment will assist in implementing appropriate mitigation approaches so as to protect lives and property. Landslides are complex phenomena that primarily depend on the geometry of the slope inclination and the soil properties. Soil characteristics are mostly determined by the shear modulus of the subsurface layers, which is often approximated from the observed shear wave velocity (V_s). This paper is focused on assessing the vulnerability status of a site, especially through applications of the multichannel analysis of surface waves (MASW) approach. Improvements in Landslide hazard safety will be aided by the identification of unstable slopes; hence it is necessary to create the quick and affordable method for safety evaluation that is envisioned in this study. The study displays a graphical relationship between V_H (average shear wave velocity) and Slope gradient (ϴ°) in order to detect the potentially unstable slopes. The proposed curve presented by inputting the Slope inclination and V_H will be helpful in identifying and categorizing the slope into high, low and medium risk zones. This graphical relationship was practically validated based on the data gathered from eight stations spread throughout the various areas of Itanagar capital complex, Arunachal Pradesh, India. It was found that the relationship developed showed good prediction performance. The vulnerability of a landslide hazard can therefore be assessed using that vulnerability assessment curve by keeping an eye on monitoring the shear wave velocity and slope gradients.

Image denoising deals with removal of unwanted noise from images. While there have been many techniques that can be applied to denoise a given input noisy image, the methods process an image in its entirety, assuming that the noise uniformly affects the entire image. For inputs where the noise affects a localised part of the image, applying methods that attempt to denoise the entire image can adversely affect the clean portions. To address this problem, we propose a deep reinforcement learning-based framework aiming to overcome this limitation and achieve better results for images with non-uniformly distributed noise. We propose a two-step procedure that first identifies the noisy patch and then denoises the extracted patch. We use a reinforcement learning-based approach for noise localization and use PixelRL for noise removal. We have prepared a comprehensive dataset specifically for the noise localization problem, and noise patches are induced in clean document images using various noise patterns, such as Gaussian noise, coffee stains, and ink bleeds.

In today’s digitally-driven world flooded with digital content and the widespread availability of images online, digital image watermarking is crucial. It ensures copyright protection, maintains content authenticity, and preserves the integrity of visual information. In this paper, a reversible watermarking technique is proposed based on splitting the gray scale image pixel’s intensity value and conventional prediction error expansion. To begin with, the pixel values of an image are split and posted into two distinct groups. The values in the hundred’s and ten’s place are categorized as the higher order pixel group ((alpha)), while the values in the units place are categorized as lower order pixel group ((beta)). Through this splitting process, it has been noticed that numerous adjacent pixels share identical values. In order to embed data, the conventional Prediction Error Expansion technique is employed specifically for the higher order pixel group. After determining the prediction error, it will be expanded and secret data is embedded into it. This scheme has been experimentally verified that it is superior than few existing state of art schemes. With a high embedding capacity of about 65335 bits in a single 512 (times) 512 image, the watermarked images exhibited a PSNR of approximately 36.34 dB and an SSIM of around 0.94. Payloads for 10,000 and 20,000 bits are tested and their PSNR values are 44.56 dB and 41.35 dB respectively.