Volume 10 | Issue 11

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Mathieu series; generalized Mathieuseries; fractional calculus operators

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Electrocardiogram (ECG), a non-invasive technique is used as a primary diagnostic tool for cardiovascular diseases. A cleaned ECG signal provides necessary information about the electrophysiology of the heart diseases and ischemic changes that may occur. It provides valuable information about the functional aspects of the heart and cardiovascular system. The objective of the thesis is to automatic detection of cardiac arrhythmias in ECG signal. Recently developed digital signal processing and pattern reorganization technique is used in this thesis for detection of cardiac arrhythmias. The detection of cardiac arrhythmias in the ECG signal consists of following stages: detection of QRS complex in ECG signal; feature extraction from detected QRS complexes; classification of beats using extracted feature set from QRS complexes. In turn automatic classification of heartbeats represents the automatic detection of cardiac arrhythmias in ECG signal. Hence, in this thesis, we developed the automatic algorithms for classification of heartbeats to detect cardiac arrhythmias in ECG signal. QRS complex detection is the first step towards automatic detection of cardiac arrhythmias in ECG signal. A novel algorithm for accurate detection of QRS complex in ECG signal peak classification approach is used in ECG signal for determining various diseases. As known the amplitudes and duration values of P-Q-R-S-T peaks determine the functioning of heart of human. Therefore, duration and amplitude of all peaks are found. R-R and P-R intervals are calculated. Finally, we have obtained the necessary information for disease detection. For detection of cardiac arrhythmias; the extracted features in the ECG signal will be input to the classifier. The extracted features contain morphological l features of each heartbeat in the ECG signal. We have detected bradycardia and tachycardia. Massachusetts Institute of Technology Beth Israel Hospital (MIT-BIH) arrhythmias database has been used for performance analysis.

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Electrocardiogram (ECG), MIT-BIH database, Probabilistic Neural Networks (PNN), Wavelet toolbox.

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Battery chemistries plays a pivotal role for range enhancement and performance of electric vehicles. In the present research different battery chemistry used in Electric Vehicles (EVs) were analyzed. In the present work analysis is done on sodium ion, lithium ion, and metal air batteries chemistries for usage in EVs. Technical parameters and process for selection of battery for EV application is presented. Based on the review a comparative chart is prepared that help in selection of a battery chemistry for application in EV as per the requirement. Battery Management System (BMS) which is responsible for cell balancing, temperature monitoring at cell level, providing data on state of health (SoH) and State of Charge (SoC) of a battery is also studied.

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Battery, Lithium-ion battery, Metal air battery, Battery selection, Battery Management System

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In the field of medical Brain tumor is very risky, uneasy to detect and very harmful disease. The Brain Tumor is detected using MRI images by doctors. In this paper, the detection of Brain Tumor is done by using the MRI images by implementing different Machine Learning techniques. The CNN(Convolutional Neural Network) is performed by using keras whereas the SVM(Support Vector Machine), KNN(K Nearest Neighbor) are performed by using scikit, sklearn. The different techniques are used in this paper to get more accuracy and predictions in detecting the tumor accurately.

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Classification system, CNN, MRI, Medical, Brain Cancer, Machine Learning, SVM, KNN.

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The statistical analytic technique investigates the influence of the accident Severity Index (SI) on temporal-spatial patterns of accident hotspots related to specific time intervals.10 years of Andhra Pradesh (AP) Road Traffic Accident (RTA) data were used to analyze and test this approach. Finding the Accidents Hotspots according to the severity is the most crucial task. This study abridged to find the severity of the accident and map the locations. The model which we enact using supervised machine learning algorithms, such as Decision Tree (DT), Logistic Regression (LR), and Random Forests (RF) are implemented on traffic accident data. SMOTE algorithm is used for handling the data imbalance. An RF model can provide insights into the severity of traffic injuries, according to the result of this study. RF algorithm has shown better performance with 70% accuracy than LR with 72.5%, and RF with 63.6% accuracy.

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Decision Tree (DT), Logistic Regression (LR), Random Forests (RF), Severity Index (SI).

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The attractive plant species Senna angustifolia belongs to the genus Senna. Herbal medicine utilizes it. It naturally grows in upper Egypt, particularly in the Nubian region, and is also commercially grown close to Khartoum. Additionally, it is grown worldwide, most notably in Somalia and India. This current review on Senna angustifolia contains the latest data related to isolated chemical constituents, structure, formulation, uses, side effects, dose etc.

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Senna, constituents, structure, formulation, uses

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Library, central libraries, collection, budget, user.

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Ayurvedic literature has vast description of Mutravaha srotovikaras in different contexts. Acharya Vaghbhata gave a unique explaination segregating into Mutra atipravritti and Mutra Apravrutti vikaras. Symptoms of both Mutrakricchra & Mutraghata seems to be overlapping. Acharya Chakrapani, Dalhana, & Vijayarakshita have demarcated both the entities. The difference is based on intensity of Vibhanda or Avarodha which is more pronounced in Mutraghata. Chronic Kidney Disease is a global threat to health and hence needs cost-effective treatment and Ayurvedic literature emphasized more ways to treat CKD in chronic condition where in Basti is highlighted as main stream of management.

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: MUTRAGHATA, CKD, BASTI

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Keywords: Employability Skill, Socio-Economic Status, Higher Education, Postgraduates.

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This study was conducted to investigate the parental perception of content and the effect of television programs on children. Multistage random sampling was used to collect the data from parents. The study consisted of 110 parents with children aged between 8-12 years as a sample of the study. A self-constructed questionnaire has been used to study the parental perception of television programs. For the analyses, collected data were tabulated and converted into percentages. Results indicate that parents believed that television programs have both appropriate and inappropriate content which affects children. Parents felt that boys watch more violent and aggressive programs in comparison to girls. Data also reveals that television viewing increases knowledge, curiosity, creativity, eating disorders, vision problem, aggression, and anti-social behavior. On the other hand, television viewing is responsible for decreasing study time, and physical and social activities. Television viewing did not affect verbal ability, sexual activity, attention span, inclusion toward substance abuse, and buying behavior of children.

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Television program, parental perception, television viewing, effect, children

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Universalization of Elementary Education (UEE), Absenteeism, Literacy Rate, School Enrolment, Elementary school Drop-out

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Postcolonial, Narration, Eurocentrism, Culture, Diaspora

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Marketing, Digital Marketing, Social media, e-mail marketing, content marketer.

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Jane Austen, Marxism, Capitalism, Class Struggle, Marriage, Materialism.

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Keywords: Yoga, Mind Sound Resonance Technique, cognitive functions.

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Various Distribution Systems (DS) have been developed the last couple of years to avoid costly grid upgrades. However, evaluation of these DS methodologies is usually restricted to a use-case specific example. This paper presents a novel, open source, load profile generator to evaluate DS. In addition to static load profiles for both active and reactive power, it also provides f flexibility information for various classes of controllable domestic devices. Load profiles and flexibility information are generated using a simple behavioural simulation. The output data uses 1-minute intervals and incorporates device measurements. The generated profiles are in sound with the measurement data obtained in a field test on both the household level and aggregated neighbourhood level. The same dynamics, such as unbalanced loading and rapid power consumption fluctuations, are observed in the generated model.

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Load modelling, simulation, load management, demand side management.

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Jackfruit is a member of the Moraceae family. According to reports, the fruit has a variety of nutrients. In addition to essential micronutrients like vitamin B and C, it provides a significant amount of macronutrients including fat, protein, and carbohydrates. Jackfruit flour absorbs a significant quantity of iron, dietary fibre, thiamine, riboflavin, and Vitamin A. It also contains anticancer, antifungal, antibacterial, anticancer, hypoglycemic, and wound-healing effects. Additional benefits of this food include it has gluten- free properties. The nutritional, sensory, and microbiological evaluation of jackfruit flour was done in an effort to make fried and baked snack items. Monitoring the effects of these two extremely strong nutrients was therefore the main objective. The finished product was a savoury snack with a dark brown colour, flaky, crunchy, crisp, and smooth texture. It also had a lot of nutritional value.

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millets, diabetes, patients, flour, bites, glycemic index, jackor

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Foreign Exchange Rate, Exports, ARDL

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