Denoising ECG Signal Using DWT with EAVO

Cardiovascular diseases are the leading cause of death across the world, and traditional methods for determining cardiac health are highly invasive and expensive. Detecting CVDs early is critical for effective treatment, yet traditional detection methods lack accessibility, accuracy, and cost-effectiveness – leaving patients with little hope of taking control of their own cardiac health. Noisy ECG signals make it difficult for health practitioners to accurately read and determine heart health. Unreliable readings can lead to misdiagnosis and needless expense. Despite the importance of ECG analysis, traditional methods of signal denoising are inefficient and can produce inaccurate results. This means that medical practitioners are struggling to obtain reliable readings, leaving them unable to accurately treat their patients and leading to a lack of confidence in the medical field. The Enhanced African Vulture Optimization (AVO) algorithm with Discrete Wavelet Transform (DWT) optimized by adaptive switching mean filtration (SMF) is proven to provide accurate denoising of the ECG signal. With this reliable method, medical professionals can quickly and accurately diagnose patients. Obtaining accurate ECG signals and interpreting them quickly is a challenge for healthcare professionals. Not only it takes a lot of time and skill but also requires specialized software to interpret the signals accurately. Healthcare professionals are facing a serious challenge when it comes to obtaining accurate ECG signals and interpreting them quickly. It requires them to spend extra time and effort, as well as specialize in the field with expensive software. Time is of the essence in healthcare and ECG readings can mean the difference between life and death. Specialized software can be expensive and time-consuming for those who don't have the resources or expertise. Our easy-to-use platform allows healthcare professionals to quickly interpret ECG signals, saving time, money, and lives! Get accurate readings. The EAVO algorithm and MIT-BIH dataset provide an effective solution to this problem. With the proposed filter built using EAVO, businesses can attain significant enhancements in reliable parameters and obtain accurate testing results in terms of SNR, MD, MSE and NRMSE

Optimal ECG Signal Denoising Using DWT with Enhanced African Vulture Optimization

Cardiovascular diseases (CVDs) are the world's leading cause of death; therefore cardiac health of the human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is a comprehensive non-invasive method for determining cardiac health. Various health practitioners use the ECG signal to ascertain critical information about the human heart. In this paper, the noisy ECG signal is denoised based on Discrete Wavelet Transform (DWT) optimized with the Enhanced African Vulture Optimization (AVO) algorithm and adaptive switching mean filter (ASMF) is proposed. Initially, the input ECG signals are obtained from the MIT-BIH ARR dataset and white Gaussian noise is added to the obtained ECG signals. Then the corrupted ECG signals are denoised using Discrete Wavelet Transform (DWT) in which the threshold is optimized with an Enhanced African Vulture Optimization (AVO) algorithm to obtain the optimum threshold. The AVO algorithm is enhanced by Whale Optimization Algorithm (WOA). Additionally, ASMF is tuned by the Enhanced AVO algorithm. The experiments are conducted on the MIT-BIH dataset and the proposed filter built using the EAVO algorithm, attains a significant enhancement in reliable parameters, according to the testing results in terms of SNR, mean difference (MD), mean square error (MSE), normalized root mean squared error (NRMSE), peak reconstruction error (PRE), maximum error (ME), and normalized root mean error (NRME) with existing algorithms namely, PSO, AOA, MVO, etc

A Novel Analytical Technique for Optimal Allocation of Capacitors in Radial Distribution Systems

In this paper, a novel analytical technique is proposed to determine the optimal size and location of shunt capacitor units in radial distribution systems. An objective function is formulated to reduce real power loss, to improve thevoltage profile and to increase annual cost savings. A new constant, the Loss Sensitivity Constant (LSC), is proposed here. The value of LSC decides the location and size of candidate buses. The technique is demonstrated on an IEEE-33 bus system at different load levels and the 130-bus distribution system of Jamawa Ramgarh village, Jaipur city. The obtained results are compared with the latest optimization techniques to show the effectiveness and robustness of the proposed technique

Classification Models for Plant Diseases Diagnosis: A Review

Plants are important source of our life. Crop production in a good figure and good quality is important to us. The diagnosis of a disease in a plant can be manual or automatic. But manual detection of disease in a plant is not always correct as sometimes it can be not be seen by naked eyes so an automatic method of detection of plant diseases should be there. It can make use of various artificial intelligence based or machine learning based methods. It is a tedious task as it needs to be identified in earlier stage so that it will not affect the entire crop. Disease affects all species of plant, both cultivated and wild. Plant disease occurrence and infection severity vary seasonally, regarding the environmental circumstances, the kinds of crops cultivated, and the existence of the pathogen. This review attempts to provide an exhaustive review of various plant diseases and its types, various methods to diagnose plant diseases and various classification models used so as to help researchers to identify the areas of scope where plant pathology can be improved

Functional outcome of percutaneous screw fixation of intra-articular calcaneum fractures

Background: The treatment of displaced calcaneum fractures has been a subject of intense discussion. Displaced intra-articular calcaneum fractures gives poor result with conservative treatment and requires reduction and internal fixation for favourable long term results. Open procedures are more prone to complications regarding wound healing. Percutaneous fixation offers a middle pathway in treating simpler variety of displaced calcaneal fractures. The aim of the study was to access the functional outcome of intra articular fracture calcaneum managed with closed reduction by Essex-Lopresti technique and percutaneous screw fixation.Methods: This study was done in department of Orthopaedics Jhalawar medical college and SRG Hospital Jhalawar, Rajasthan from January 2015 to January 2018. 26 intra-articular calcaneal fractures treated with closed reduction and percutaneous screw fixation under image intensifier.Results: 25 cases evaluated (one patient had lost follow-up), all fractures were united, average time of union was 8 weeks. The mean AOFAS score was 80 (range from 45 to 96), 9 patients had excellent, 12 patients had good, 3 patients had fair and one patient had poor result for that subtalar arthrodesis was done after one year of follow-up. Average Bohler’s angle 24.5 and Gissane angle was 120 degree. No clinically significant varus or valgus in any case (less then 5 degree).Conclusions: Treatment of intra-articular fractures of calcaneum is challenging but close reduction and internal fixation with 6.5 cannulated cancellous screws yields favorable outcome in majority of cases

Image Processing based Plant Disease Detection and Classification

Generally, it has been observed that due to lack of proper knowledge of disease intensity, the farmer is not able to use the pesticide in proper quantity to treat the diseases. The use of pesticide mostly becomes more than necessary, due to which there is not only a loss of money, but also it causes soil and environmental pollution. If diseases severity-wise labelled data sets are available, it can be used to develop pesticide recommendation systems. Images with least infection severity can be used to train and validate a DL model to capture the plant diseases at very initial stage. Classification techniques may be viewed as variations of detection systems; however, instead of attempting to identify only one particular illness among several diseases, classification methods detect and name the diseases harming the plant. This presents various classification and plant disease detection methods based on image processing with results

Dissipative quantum dynamics, phase transitions and non-Hermitian random matrices

We explore the connections between dissipative quantum phase transitions and non-Hermitian random matrix theory. For this, we work in the framework of the dissipative Dicke model which is archetypal of symmetry-breaking phase transitions in open quantum systems. We establish that the Liouvillian describing the quantum dynamics exhibits distinct spectral features of integrable and chaotic character on the two sides of the critical point. We follow the distribution of the spacings of the complex Liouvillian eigenvalues across the critical point. In the normal and superradiant phases, the distributions are $2D$ Poisson and that of the Ginibre Unitary random matrix ensemble, respectively. Our results are corroborated by computing a recently introduced complex-plane generalization of the consecutive level-spacing ratio distribution. Our approach can be readily adapted for classifying the nature of quantum dynamics across dissipative critical points in other open quantum systems.Comment: 5 pages, 4 figures, and supplementary materia

Redesigning Shirley Ryan Ability Lab

The comprehensive integrative design studio involved designing a unique rehabilitation healthcare center where the primary focus is on providing premier facilities and unmitigated service through “translational” research. The project aims to achieve the program goals and design objectives by using limited means and employing integrative design process. The mission of Shirley Ryan Ability Lab is to optimize service through stimulating interaction between clinical care, research and therapy, thus enabling application of real time research to physical medicine and rehabilitation. Hence, the primary focus of this project has been the “Ability Labs” which is a pivotal part of the building. Our aim is to highlight and emphasize them, in planning as well as in form of the building. The main significance is given to the users of the building, by creating optimum and comfortable spaces, which would have a positive impact on the users, contributing to the healing process of the patients. We have extensively tried to integrate outdoors with the indoors, by providing healing gardens. We believe that this would enhance the recovery of the patients, as well as amplify the performance of the staff. The Shirley Ryan Ability Lab is located with a panoramic view of Lake Michigan.Ope

Novel molecular imaging platform for monitoring oncological kinases

Recent advances in oncology have lead to identification of a plethora of alterations in signaling pathways that are critical to oncogenesis and propagation of malignancy. Among the biomarkers identified, dysregulated kinases and associated changes in signaling cascade received the lion's share of scientific attention and have been under extensive investigations with goal of targeting them for anti-cancer therapy. Discovery of new drugs is immensely facilitated by molecular imaging technology which enables non-invasive, real time, dynamic imaging and quantification of kinase activity. Here, we review recent development of novel kinase reporters based on conformation dependent complementation of firefly luciferase to monitor kinase activity. Such reporter system provides unique insights into the pharmacokinetics and pharmacodynamics of drugs that modulate kinase signaling and have a huge potential in drug discovery, validation, and drug-target interactions