Volume 10 | Issue 5 |

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Meditation , Breath hold capacity, Treatment Group, Control group, Randomly.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As the usage of vehicles is increasing rapidly with the growing population the number of vehicle thefts are also increasing day by day. And also the number of deaths due to the accidents in the remote areas are also increasing. As accidents are one of the major causes of deaths the road safety has also became a challenging task. According to reports thousands of vehicles are being stolen every year and recovering of the vehicle had also became a tough job as most of the stolen vehicle parts are separated and sometimes they are sold to other persons as second hand vehicles. According to road accident report lakhs of accidents took place in the country every year. And hundreds of people are losing their lives everyday due to the accidents as there are not getting help at the right time. This project is used to provide solution for the vehicle theft situations and also to prevent the loss of lives due to accidents in the remote areas.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Vehicle theft, accident, Arduino, GSM, GPS

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an automatic method for obstructive sleep apnea screening and sleep (SL) - wake (WA) stages classification based on the whole night PSG (polysomnography) recording of subjects with sleep-disordered breathing during sleep. The proposed algorithm can identify apnea (AP), hypopnea (HY), and Onset of apnea (OA) events within a period of a respiration cycle. In this work, underlying dynamics embedded in each physiological state (i.e., SL, WA) and different pathological events (AP, HY, and OA) are identified with the help of trajectory formed by assigning three signals, i.e., respiration, EEG, and ECG into three orthogonal axes. The spatial distribution of the trajectory is found to be varied with the different stages and different events of OSA subjects. The discriminating information regarding different stages and events is extracted from the spatial distributions by dividing the whole hyperspace into equal-sized subspaces. The persistence of the trajectory in a particular subspace found to be sensitive to the physiological state and different pathological events. Application of standard Bayesian classifier revealed its ability to discriminate different stages. An encouraging detection accuracy of 95.28% is observed across all the subjects.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Apnea-Hypopnea Events, Bayesian classifier, sleep-wake, trajectory.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Because of the complicated structure of brain tumours, indistinct boundaries, and external influences such as noise, inferring tumour and edoema areas from brain magnetic resonance imaging (MRI) data remains difficult. This work proposes an effective hybrid clustering technique combined with morphological procedures for segmenting brain tumours to reduce noise sensitivity and increase segmentation stability. The following are the paper's main contributions: To begin, adaptive Wiener filtering is employed for denoising, then morphological processes are used to remove non-brain tissue, effectively lowering the method's noise sensitivity. Second, to segment images, K-means++ clustering is merged with the Gaussian kernel-based fuzzy C-means method. This clustering enhances the algorithm's stability while simultaneously lowering the sensitivity of the clustering settings. Finally, to acquire realistic representations of brain tumours, the retrieved tumour images are post processed utilising morphological procedures and median filtering. The suggested technique was also compared to other existing segmentation algorithms. The suggested algorithm outperforms the competition in terms of accuracy, sensitivity, specificity, and recall.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MRI, Kmeans, cluster, segmentation, morphological

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Equality, Female, Gender, Identity, Performativity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Tuberculosis is the principle purpose of morbidity in modern-day generation and got here to existence many decades in the past and has emerged as pandemic sickness. the use of allopathic medicinal drug in complicated sickness like tuberculosis is related to the hassle of pass resistance and natural pills have proven to be simplest in this context. The exploration of cures for the a success attenuation of the morbid circumstance associated with tuberculosis is the need of the day.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Acalypha indica , Adhatoda vasica , Allium cepa , Allium sativum , Aloe vera , Tuberculosis , Mycobacterium .

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India is an Agriculture based economy whose most of the GDP comes from agriculture and its allied sectors which accounts for 20% of total GDP. The motivation of this project comes from the increasing suicide rates in farmers which may be due to low yield in crops. Climate and other environmental changes have become a major threat in the agricultural field. Machine learning is an essential approach for achieving practical and effective solutions for this problem. Predicting yield of the crop from historical available data like weather, soil, rainfall parameters and historic crop yield. We aim to achieve this using the machine learning algorithm. We did a comparative study of various machine learning algorithms, i.e., ANN, K Nearest Neighbor, Random Forest, SVM and Linear Regression. In this project a mobile application will be developed which predicts the crop yield in general and also for a particular crop. Along with that, it will suggest to the user which crop to grow in that particular season.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crop Yield Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The goal of this study is to determine the impact of digital marketing on FMCG product purchasing behaviour in Greater Noida. There are several studies revealing causes to use social media and to assist firms in gaining a competitive advantage in the move; however, few plan to think from the perspective of consumers. Over the last few years, social media has revolutionized the way businesses do business using computers online, and as a result, social media marketing has earned its own identity in the business world. There are numerous online social networking platforms that influence customer behaviour. Like Google+, LinkedIn, and YouTube, for example. Nowadays, practically all ages of consumers use social media, including college students, working-class individuals, and even the elderly. In today's world, social media has evolved into a powerful tool that consumers can utilize to make purchasing decisions. Consumers' lives have been altered by technological advancements. In general, customers have unique feelings that differ from what marketers believe. For example, what "brand interaction" via social media looks like to shoppers may differ from what marketers believe. Digital technology has become a vital element of society's daily lives, both professionally and personally. In India, consumer demand for FMCG products has risen as a result of digitization. In the virtual world, digital technology has provided an interactive source of platform where people may buy things and services. In a customer-oriented market environment, consumer purchase patterns are evolving at a faster rate. The rise of digital marketing trends is having a significant impact on consumer purchasing behaviour.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Marketing, Online buying, Consumer behavior, FMCG products.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Diabetes is an illness that is caused by a hormone called insulin in our body which when not functioning properly or not efficiently will raise the level of glucose in our body. There are many individuals who suffer from high blood sugar levels in their body which has a severe effect on other human organs. This condition is caused by an unhealthy lifestyle or food habits and lack of physical exercise. This will also lead to other complications such as coronary failure, blindness, urinary organ disease, etc. In such instances, the individual must visit a diagnostic center to collect their reports. Due to this, there is a loss of time and money in this process. As a solution for this problem, we can use Machine Learning methods to arrive at a solution to this issue, we have got advanced system mistreatment information processing that has got the potential to inform us whether the individual has got the disease or not. In addition to this, an early prediction of this disease will help in controlling it as well as be able to take precautions for its after-effects. Information withdrawal has the pliability to delete unseen data from a large dataset of diabetes information. The aim of our project is to predict illness in its early stages with better accuracy so that the risk factor is comparatively less. The model is based on methods such as Decision Tree, Random Forest, and Support Vector Machine algorithms.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diabetes Disease Prediction, Support Vector Machine, Machine Learning, Random Forest, Decision Tree

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stroke, kinovea, knee joint kinematics, gait analysis.

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Creative Commons Attribution 4.0 and The Open Definition