ASCNet-ECG: Deep Autoencoder based Attention aware Skip Connection network for ECG filtering

Currently, the telehealth monitoring field has gained huge attention due to its noteworthy use in day-to-day life. This advancement has led to an increase in the data collection of electrophysiological signals. Due to this advancement, electrocardiogram (ECG) signal monitoring has become a leading task in the medical field. ECG plays an important role in the medical field by analysing cardiac physiology and abnormalities. However, these signals are affected due to numerous varieties of noises, such as electrode motion, baseline wander and white noise etc., which affects the diagnosis accuracy. Therefore, filtering ECG signals became an important task. Currently, deep learning schemes are widely employed in signal-filtering tasks due to their efficient architecture of feature learning. This work presents a deep learning-based scheme for ECG signal filtering, which is based on the deep autoencoder module. According to this scheme, the data is processed through the encoder and decoder layer to reconstruct by eliminating noises. The proposed deep learning architecture uses a modified ReLU function to improve the learning of attributes because standard ReLU cannot adapt to huge variations. Further, a skip connection is also incorporated in the proposed architecture, which retains the key feature of the encoder layer while mapping these features to the decoder layer. Similarly, an attention model is also included, which performs channel and spatial attention, which generates the robust map by using channel and average pooling operations, resulting in improving the learning performance. The proposed approach is tested on a publicly available MIT-BIH dataset where different types of noise, such as electrode motion, baseline water and motion artifacts, are added to the original signal at varied SNR levels

Energy Efficient Cluster based Routing Scheme for WSN based IoT to Extend Network Lifetime

With the development and advancement of wireless sensor networks (WSN), the emergence of the Internet of Things (IoT) has achieved prominence in the modern era. With the increasing number of connected devices, WSN has become a key factor in the communication component of the IoT. In IoT-based WSN infrastructure, devices are equipped with intelligent sensors that sense the environment to collect data, process data, and deliver information to the sink or base station (BS). WSN-assisted IoT has become a key technology for various data-centric applications such as health care, smart cities, and the military. Sensor nodes in IoT devices are equipped with bound and irreplaceable batteries. An increased number of connected devices face serious issues of energy depletion, maintenance, and load balancing, which might result in device failure. Energy efficiency is considered a vital parameter in the design of an IoT based WSN, and this can be accomplished through clustering and multihop routing techniques. In this paper, we propose an energy-aware multihop routing scheme (EAMRS) for hierarchical cluster-based WSN-assisted IoT. EAMRS considers the improved low-energy adaptive clustering algorithm (I-LEACH) to select optimal cluster heads (CH). During data transmission, multihop routing is involved by considering routing metrics such as residual energy, distance to BS and optimal route choice to balance the energy load. However, conventional routing schemes fail to achieve the flexibility and adaptability prerequisites of load balancing mechanisms. EAMRS decreases computation overhead and restricts energy usage, resulting in a prolonged network lifetime

Parametric Study on Reinforced Concrete Beam using ANSYS

Concrete structural components such as beams, columns, walls exist in various buildings and bridges. Understanding the response of these components of structures during loading is crucial for the development of an efficient and safe structure. Recently Finite Element Analysis (FEA) is also used to analyze these structural components. In this paper, four point bending analysis is carried out using reinforced concrete beam. The results of the beam with respect to mesh density, varying depths, use of steel cushions for support and loading points, effect of shear reinforcement on flexure behaviour, impact of tension reinforcement on behaviour of the beam are analyzed and discussed. Finite element software ANSYS 13.0 is used for modeling and analysis by conducting non linear static analysis. Keywords: Material nonlinearity, Finite element analysis, Convergence, Steel cushion, Varying depths, ANSYS

Effective atomic numbers, electron densities, and tissue equivalence of some gases and mixtures for dosimetry of radiation detectors

Total mass attenuation coefficients, µm, effective atomic number, Zeff, and effective electron density, Neff, of different gases - carbon dioxide, methane, acetylene, propane, butane, and pentane used in radiation detectors, have been calculated for the photon energy of 1 keV to 100 GeV. Each gas has constant Zeff values between 0.10 to 10 MeV photon energies; however, these values are way far away from ICRU tissue. Carbon dioxide gas shows the closest tissue equivalence in the entire photon energy spectrum. Relative tissue equivalences of the mixtures of gases with respect to ICRU tissue are in the range of 0.998-1.041 for air, argon (4.5%) + methane (95.5%), argon (0.5%) + carbon dioxide (99.5%), and nitrogen (5%) + methane (7%) + carbon dioxide (88%). The gas composition of xenon (0.5%) + carbon dioxide (99.5%) shows 1.605 times higher tissue equivalence compared to the ICRU tissue. The investigated photon interaction parameters are useful for exposure and energy absorption buildup factors calculation and design, and fabrication of gaseous detectors for ambient radiation measurement by the Geiger-Muller detector, ionization chambers and proportional counters

Gamma Photon Exposure Buildup Factors for Some Spin Ice Compounds Using G-P Fitting Method

Exposure buildup factors(EBF) for some spin ice compounds such as Dysprosium Titanate (Dy2Ti2O7), Dysprosium Stannate (Dy2Sn2O7), holmium Titanate (Ho2Ti2O7) and holmium Stannate (Ho2Ti2O7) useful in nuclear engineering have been computed for photon energy range 0.015 to 15 MeV upto penetration depth of 40 mean free path. The eBF for these compounds were found to be the largest at photon energy 15 MeV excepts in low energy. The eBF for the compounds containing tin were found to be the largest as well as shown a peak at 30 keV photon energy

COMPARATIVE STUDY OF COMMONLY PRACTICED ATROPINIZATION REGIMENS IN ACUTE ORGANOPHOSPHORUS COMPOUND POISONING

Aim of the study: Effect of atropinization with different methods. Outcomes in terms of duration of hospital stay and patients recovery. Methodology: An open-label randomized clinical trial was conducted in, Shri B M Patil Medical College Hospital and Research Centre, Vijayapura, Karnataka. 108 individuals with OPC poisoning .We compared two groups that used a titrated dosing protocol based on a structured monitoring sheet for atropine infusion with another group using an \u27ad hoc\u27 regime. The aim was to compare the efficacy and safety of conventional bolus doses with individualized incremental doses of atropine for atropinization followed by continuous atropine infusion for management of OPC poisoning. Result: Out of 108 patients, 54 patients received conventional bolus dose atropine (group A) and 54 patient received rapidly incremental doses of atropine followed by infusion (group B). 36 subjects analyzed in group A and 32 in group B for moderate to severe poisoning. The mortality in group A was 11.1% (4/36) and in group B was 6.3% (2/32).The mean duration of atropinization in group A was 5.8hrs (348) in minutes compared to time 26.9minutes for group B. Conclusion: Administration of atropine using a fixed algorithm is easy and effective in providing the atropine requirement in management of early phase of acute OPC poisoning. Rapid incremental dose atropinization followed by atropine infusion reduces mortality and morbidity from OPC poisoning and shortens the length of hospital stay and early recovery .Incremental atropine and infusion should become the treatent of choice for OPC poisoning. Keywords: Organophosphate compound; Atropine toxicity; Organophosphorus poisoning; Atropinization protocols

COMPARATIVE STUDY OF COMMONLY PRACTICED ATROPINIZATION REGIMENS IN ACUTE ORGANOPHOSPHORUS COMPOUND POISONING

Aim of the study: Effect of atropinization with different methods. Outcomes in terms of duration of hospital stay and patients recovery. Methodology: An open-label randomized clinical trial was conducted in, Shri B M Patil Medical College Hospital and Research Centre, Vijayapura, Karnataka. 108 individuals with OPC poisoning .We compared two groups that used a titrated dosing protocol based on a structured monitoring sheet for atropine infusion with another group using an 'ad hoc' regime. The aim was to compare the efficacy and safety of conventional bolus doses with individualized incremental doses of atropine for atropinization followed by continuous atropine infusion for management of OPC poisoning. Result: Out of 108 patients, 54 patients received conventional bolus dose atropine (group A) and 54 patient received rapidly incremental doses of atropine followed by infusion (group B). 36 subjects analyzed in group A and 32 in group B for moderate to severe poisoning. The mortality in group A was 11.1% (4/36) and in group B was 6.3% (2/32).The mean duration of atropinization in group A was 5.8hrs (348) in minutes compared to time 26.9minutes for group B. Conclusion: Administration of atropine using a fixed algorithm is easy and effective in providing the atropine requirement in management of early phase of acute OPC poisoning. Rapid incremental dose atropinization followed by atropine infusion reduces mortality and morbidity from OPC poisoning and shortens the length of hospital stay and early recovery .Incremental atropine and infusion should become the treatent of choice for OPC poisoning. Keywords: Organophosphate compound; Atropine toxicity; Organophosphorus poisoning; Atropinization protocols

Speckle Noise Reduction in Medical Ultrasound Images

Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising approach which combines logarithmic transformation and a non linear diffusion tensor. Since speckle noise is multiplicative and nonwhite process, the logarithmic transformation is a reasonable choice to convert signaldependent or pure multiplicative noise to an additive one. The key idea from using diffusion tensor is to adapt the flow diffusion towards the local orientation by applying anisotropic diffusion along the coherent structure direction of interesting features in the image. To illustrate the effective performance of our algorithm, we present some experimental results on synthetically and real echographic images