International journal of health sciences
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How leadership style creates an impact on job satisfaction level of employees in an organization
Get PDFIn this study, we tried to show how a good leader positively impacts employees, which leads to job satisfaction while working in an organization/business. Under this study, we are trying to examine the meaning and importance of Leadership towards job satisfaction of employees, how good leadership help in helping their employees, and they feel satisfied with their current working job. This study is based on two leadership styles: Responsible Leadership Style and Ethical leadership Style. A reliable leadership style shows a relationship between the leaders and their stakeholders; under this style, a leader must analyze stakeholders' needs and wants. Ethical leadership style is when a leader has to do their moral duties and work with honesty; under this style, the leader tries to make fair decisions in the organization and make a positive environment for employees. Based on this study, we are wanted to highlight how a leader is essential for every organization. If there is a good leader in the organization, employees can feel comfortable to share their views and problems related to their job
Usage of drones as a medical applications
Get PDFUtilizing drone airplane to convey medical care also other wellbeing related administrations is a moderately new use of this innovation in North America. For wellbeing specialist co-ops, drones address a possible means to expand their productivity also capacity to offer types of assistance to people, particularly those in challenging to arrive at areas. This paper presents consequences of a perusing audit of examination writing to decide how robots are utilized for medical care also wellbeing related administrations in North America, also how such applications represent human working also machine configuration factors. Information were gathered from PubMed, CINAHL, Scopus, Web of Science, also IEEE Xplore utilizing a square quest convention that joined 13 equivalents for "robot" also eight wide terms catching medical care also wellbeing related administrations. 4,000 600 and-65 reports were recovered, also following a title, conceptual, also full-text screening method finished by all creators, 29 records were held for investigation through an inductive coding process
Analysis of customer churn prediction using machine learning and deep learning algorithms
Get PDFThe telecommunication industry need a customer churn prediction due to many competitors. The companies also lack of churn prediction to retain the customer. This problem not only affect the growth of the business but also affect the revenues. To retain the existing customer is very crucial task for the company. A rapid increasing in technology, the various machine learning and deep learning are tools are developed which can be used by telecoms companies to monitor the churn behaviour of customers. In this study, a brief idea on the customer churn problem on various machine learning techniques such as XGBoost, Gradient Boost, AdaBoost, ANN, Logistic Regression and Random Forest are analysed. Also the various deep learning techniques such as Convolutional Neural Network, stacked auto encoders to predict the customer churn problem are analysed by comparing the models in terms of accuracy
A comparative analysis of consensus algorithms in the health care sector using block chain technology
Get PDFAs Blockchain is a distributed digital ledger system, it focuses on various sectors such as bitcoin, the banking sector, the corporation sector, the real estate and the healthcare sector. Each block in the blockchain contains the hash value, timestamp and transaction data of their previous block. The consensus algorithms plays a major role in the blockchain framework. This consensus algorithm maintaining the safety and efficacy of blockchain. The consensus protocols determines how the agreement to add the updated block to all nodes in the network works. Every consensus protocols has its own set of performance and scalability features. It is essential to technically compare each consensus mechanism by highlighting their strengths and weaknesses. Consensus algorithms in blockchain can be divided into two types. They are Proof based consensus and voting based consensus. The Proof based consensus shows that they are more qualified than others to do mining work. Voting-based consensus explains that nodes are needed in a blockchain network to exchange decisions for mining a new block or transaction before reaching a final conclusion. Their effectiveness can be enhanced by manipulating the suitable consensus algorithm in the blockchain. Blockchain technology is recently implement in many domains, especially for healthcare Industry
Self-supervised learning based knowledge distillation framework for automatic speech recognition for hearing impaired
Get PDFThe use of speech processing applications, particularly speech recognition, has got a lot of attention in recent decades. In recent years, research has focused on using deep learning for speech-related applications. This new branch of machine learning has outperformed others in a range of applications, including voice, and has thus become a particularly appealing research subject. Noise, speaker variability, language variability, vocabulary size, and domain remain one of the most significant research difficulties in speech recognition. We investigated on self-supervised algorithm for the unlabelled data. In recent years, these algorithms have progressed significantly, with their efficacy approaching and supervised pre-training alternatives across a variety of data modalities such as image and video. The purpose of this research is to develop powerful models for audio speech recognition that do not require human annotation. We accomplish this by distilling information from an automatic speech recognition (ASR) model that was trained on a large audio-only corpus. We integrate Connectionist Temporal Classification (CTC) loss, KL divergence loss in distillation technique. We demonstrate that distillation significantly speeds up training. We evaluate our model with evaluation metric Word Error Rate (WER)
Prediction of Parkinson’s disease using machine learning classification from voice analysis
Get PDF“PARKINSON SYNDROME PREDICTION BASED ON AUDIO MEASURES” is to analyze and find the prediction efficiency that would be beneficial for the patients who are suffering from Parkinson and the percentage ratio will be reduced. Generally, in the first stage Parkinson can be cured by the proper treatment. So, it is important to identify the PD at the early stage for the betterment of the patients. The main purpose of this project work is to find the best prediction model i.e., the best machine learning technique which will distinguishes the Parkinson’s patient from the healthy person. The techniques investigated are Random Forest, SVM, Logistic Regression and Adaptive Boosting
The spectrum of magnetic resonance imaging (MRI) patterns in hospitalised hypoxic ischemic encephalopathy babies in a tertiary care hospital of Odisha
Get PDFBackground: Hypoxic ischemic encephalopathy (HIE) refers to the CNS dysfunction associated with Perinatal Asphyxia (PA) which is an important causes of permanent damage to CNS tissue. MRI imaging methods attributes to better understanding of pathological events and disease progression that may provide decision regarding intervention. MRI has a higher sensitivity and is extremely valuable in assessing the extent of hypoxic-ischemic brain damage during the early postnatal period and later infancy. It is also more specific which clearly differentiates fluid filled cavities, oedema, gliosis and hemorrhage. On this background this study was undertaken to evaluate the MRI changes of all grades of HIE patients. They were also followed up at different time intervals for upto 1 year to correlate the MRI changes and neurodevelopmental outcome. Objectives: To find out different MRI findings in hypoxic ischemic encephalopathy babies. Assesment of severity of HIE from MR imaging and correlate these findings with clinical & neurodevelopmental outcome. Methods: All hemodynamically stable HIE babies irrespective of their severity were subjected to MRI between day 7 and day 21 of life and their findings were interpreted. 
Introduction and overview of recreational therapy
Get PDFRecreational therapy programmes have grown in popularity with adolescents who have psychological, physical, sociological, and emotional difficulties. The literature, on the other hand, has largely concentrated on the advantages of recreation programmes, rather than on the impact of recreation therapy interventions on this vulnerable group. The purpose of this review was to conduct an examination of the literature about the impact of recreation therapy programmes. The purpose of this study was to review about the efficacy and execution of recreational therapy programmes for improving mobility outcome (e.g., balance, functional performance, fall incidence).Recreation therapy has a number of advantages. It has the potential to increase physical functionality, strengthen neuronal connections related with processing activities, and open doors to inclusion. Spending time engaging in recreational activities that interest you reduces the likelihood of depression, loneliness, and frustration. Indeed, Recreation Therapy can help individuals develop a higher feeling of self-worth and accomplishment
Evaluation and invivo studies of solid lipid nano carrier mediated drug delivery system of perinodopril
Get PDFHigh BP is one of the most predominant causes of heart diseases and cerebrovascular problems. Perinodopril is an ACE inhibitor that is a non sulfhydryl derivative that is used for the treatment of hypertension. To enhance the effect of the drug it was formulated into Lipid based nano carrier system (NLC) to improve the bioavailability and thereby the therapeutic potential. So the objective of the current work was to evaluate the NLC of perinodopril formulation and to evaluate the same. The invivo estimation of the activity was carried out on Albino wistar rats that are maintained under room conditions and the formulation was investigated for the Pharamcokinetic and pharmacodynamic paramteres in rat plasma. Also they were tested for their stability invitro. Results show that the nano particles measured as 0.207nm in size. The invitro drug release studies suggest that the formulations were releasing the drug in controlled fashion during 23 hrs. stability studies proves the drug is very stable in the formulation. With R2 = 0.9683, the in vitro-in vivo correlation research clearly shows good agreement between in vitro drug solubilization during lipolysis and in vivo drug absorption during pharmacokinetic studies. 
ECG signal PQRS detection and comprehensive estimation of signal noise
Get PDFAutomated bioelectric signal analysis has an important application in the wisdom medical care. In this work, we focus on ECG-signal and address a novel approach for cardiac arrhythmia diseases classification. We designed a novel analysis framework which extract different feature transformations from ECG signals. And we trained the ANN model for multi-feature to obtain the prediction. Finally, we tested our approach on the public database of MIT-BIH arrhythmia. And the results of experiments on the database demonstrate our model has better classification performance than other approaches