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Universal interconnection networks are prime performance tailback for high performance SoCs (Systems-on-Chip). Since shrinking the size of the ICs (Integrated Circuits) is the main aim, NoC (Network-on-Chip), being a segmental and mountable design tactic is a propitious substitute to outmoded bus-mode architectures. NoC combined with 3D-Routers and label switching technique can guarantee low power consumption, QoS along with less latency. In the proposed work, 3D NoCs are proven to be more advantageous by achieving 39.9% reduction in Area, 1.7% reduction in Power Consumption, and 11.3% reduction in Memory usage.

In the present study, an effort was made to identify the anti hyperglycemic potential of ethanolic extract of Cadaba fruticosa leaves concentrating the enteric system. The glucose-lowering potential was studied by using the in vitro methods such as α amylase inhibitory activity, inhibition of glucose diffusion, glucose adsorption and uptake by yeast cells. In silico methods comprising of the molecular docking of the selected phyto constituents as antagonistic ligands to the disaccharide digesting enzyme α glucosidase and glucose level maintaining enzyme dipeptidyl peptidase IV. The plant extract inhibited α amylase enzyme and the glucose diffusion considerably, which was found to be concentration-dependent. The uptake of glucose by the yeast cells in the presence of the extract was also found to be increased. In the molecular docking analysis based on the docking score, iso quercetin was found to be a potential antagonistic ligand for both enzymes α glucosidase and dipeptidyl peptidase IV since they exhibited similar amino acid interactions shown by the acarbose and Sitagliptin which are the standard competitive inhibitors of these two enzymes. It can be concluded that the leaves of Cadaba fruticosa may serve as a potential anti hyperglycemic drug in future for the management of diabetes mellitus.

Cardiac arrhythmia is an abnormal heartbeat or rhythm. The heartbeat rate becomes too fast or when the heartbeat rate is irregular, the ability of the heart to pump blood will be affected. This will eventually reduce the blood flow through the brain which may result in loss of consciousness, dizziness, or even death if the required procedures are not carried out in time. The main aim of the proposed work is to alert some person or people nearby when a patient has an irregular heartbeat. The proposed work implemented Electrocardiogram integrated with micro-controller that monitor the heartbeat of a person and detects the type of arrhythmia, bradycardia or tachycardia based on the heart rate. The threshold set for bradycardia is 60bpm and for tachycardia is 100bpm. The system detects for the irregularity in heartbeat, which could later lead to an unanticipated event. Since the patient experiencing the attack is powerless during his/her sleep, an alarm is provided which is triggered and SMS is sent to registered mobile number with temperature, pulse rate and SpO2 values with type of arrhythmia in case of abnormality. This would alert people around the patient and then necessary immediate would be taken. The vital values are displayed on LCD.

Introduction During the COVID-19 pandemic, mental health services have been presented with the unique challenge of providing effective and safe patient care whilst maintaining safety regulations. Telepsychiatry has emerged as a potential solution to this and is now being used across the UK to diagnose and manage mental health conditions. Evidence has shown that its effectiveness is comparable to face to face consultations, however, is much less clear regarding patient satisfaction. We therefore initiated a systematic review to establish whether patients are satisfied with tele-delivery of psychiatric care, and to identify the predictors of a positive experience with telepsychiatry. Methods A preliminary search was performed using five databases (MEDLINE, EMBASE, Cochrane Library, CINAHL, PsycINFO), with a date restriction between 2010-2020 to reflect advances in technology over the past decade. Results Preliminary data shows that patient views on telepsychiatric services are largely positive. Factors that arose in literature potentially affecting this include location, cost, privacy, digital literacy and technological issues including audio/video quality. Conclusion Our study so far shows that patient views on telepsychiatry are generally positive. The review is still in process, however, we anticipate that it will only further support our preliminary findings. These findings will be used to improve patient-centred delivery and provision of telepsychiatric services. We intend to produce a checklist of factors affecting patient satisfaction and test this in a national multicentre study. We are hoping that the study results and the resulting checklist will encourage greater patient involvement in setting up and delivering telepsychiatric services.

This paper proposes a cheap and effective method to interface the concept of FUZZY LOGIC and (Antilock Braking System) ABS system used in cars and bikes for preventing the condition of wheel locking and wheel slipping and if wheel slipping occurs then how much of intensity of brake should be applied to keep the vehicle in control of the user. This decision is taken by Fuzzy System which makes decision based on user inputs namely Obstacle, Brake force and Slip ratio. The Fuzzy system gives an Pulse Width Modulation output based on three intensity levels of brake will be applied such as High Brake , Medium Brake and No Brake. Hardware Implementation consists of an MCU which is interfaced with an LCD and DC Series motor which displays intensity of brake applied and motor represents the motion of the actual wheel of a vehicle respectively.

In dis paper, we introduce a new subclass of uniformly convex functions wif negative coefficients defined by Gegenbauer polynomials. We obtain teh coefficient bounds, growth distortion properties, extreme points and radii of close-to-convexity, starlikeness and convexity for functions belonging to teh class $TS( \upsilon, \varrho , \lambda, t ).$ Furthermore, we obtained modified Hadamard product, convolution and integral operators for dis class.

Interfaced embedded technology is evolving in current world. Hospitals and diagnostic centers emerge day by day as people have less awareness of their health issues. For Patients with Specific health issues and old age, monitoring the patients for optimal care and keeping track of the health status at anywhere is extremely tedious. Monitoring should be periodically done and their health status need to be informed to their loved ones from time to time while they are not around. This work propose an innovative system that automated the check system for Pulmonary Fibrosis. The heart and lung can be sources of breathing problems as they work together to bring out the Oxygen rich blood to the body. An ECG sensor trace various physiological and abnormal conditions of the heart. Respiration sensor measures person’s breath/minute. This heart beat sensor measures the heart beat rate. The system also helps to inform the person whether he/she has ILD or not. ILD ends up with heart disease. Whether to check the range of all parameters, AVR controller is used. If the values are not in range, the alert will be sent to the concerned persons using Arduino platform with programming c. The system Speed Rate is very high., the Error rate is less and the Duration is absolutely less. Hence the proposed system has high significance in real time medical applications.

Heart disease has turned into the most critical human disease and Heart failure rate has been increased. Accurate diagnosis and timely treatment is needed to prevent deaths. In this work, the heart disease is effectively predicted by a Machine Learning (ML) model, which is trained with the UCI datasets. Univariate and Multivariate analysis of the dataset is performed using statistical methods and checked for data - imbalanced, skewness/kurtosis in the distribution of data, and the correlation between the features. As distributions of few features show skewness and are not normally distributed, Power transformation technique is used to transform the dataset into normal distribution. Before performing the transformation, outliers are detected in the dataset and removed using the Turkey Fence algorithm. The best features among all features of the dataset are selected based on the correlation matrix and several Feature selection approaches, including Extra Trees Classifier. Random Search and Grid Search techniques are used in tuning Hyperparameters of Logistic Regression algorithms. Performance is evaluated using metrics such as confusion matrix, Accuracy score, precision-recall curve (PRC), and Receiver operating curve (ROC). Seven models are developed with various combinations, among which the model for which power transform, Kernel Principal Component Analysis (PCA) performed on the dataset and finally Gridsearch method used to tune hyperparameters gives the 100% accuracy.