Volume 11 | Issue 5 |

 Abstract

Too many people today rely on emails and messages sent by strangers. Since anyone can leave emails and messages, spammers have a great opportunity to spam about our diverse interests. Spam fills your inbox with a bunch of ridiculous emails. Your internet speed will drop significantly. It steals useful information such as contact list details. Identifying these spammers and spam content can be a hot topic for research and tedious work. Spamming is the act of sending a large number of messages via email. Since the cost of spam is primarily borne by the recipient, it is effectively postage-based advertising. Spam is an economically viable type of commercial advertising as email can be a very cheap medium for senders. Using Bayes' theorem and a naive Bayesian classifier, this proposed model can declare whether a given message is spam or not, and often finds the sender's IP address as well.

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 Keywords

Term Frequency, Naive Bayes, spam, ham, Language Toolkit.

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 Abstract

Music Genre Classification using Deep Learning based pre-trained convolutional neural networks

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Music Genre Classification using Deep Learning based pre-trained convolutional neural networks

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The Chenchus are Adivasi, their habitat is confined to the rocky hills and forested plateau of the Nallamala forest Range, extending on both sides of the Krishna River. They are the overwhelming majority of the speakers of the Dravidian tongue of Telugu. The Chenchus are characterized by a strong sense of independence and personal freedom. The current investigation delineates literacy and health practices prevalent among Chenchu group of Tribals in the state of Telangana. The main objective was to appraise the literacy and health practices among the tribal children. A sample of 120 was included from six tribal villages of Achampet region in Nagarkurnool District of Telangana State. Purposive sampling technique was used to identify the sample. An Interview schedule was prepared for Parents to elicit required information. The findings of the study demonstrated that there was no significant difference was found among the Parents on the literary and health practices among tribal children in the state of Telangana. Educational Implications as well as suggestions for further research were also portrayed.

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 Keywords

Literacy; Health Practices; Tribal Children; Management; Health issues

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 Abstract

Machine learning and deep learning have become increasingly important as a result of technological advancement. Handwriting recognition, robotics, artificial intelligence, and many more industries are now using machine learning and deep learning approaches. Such systems require data training, allowing our machine to learn and make the necessary predictions. In this research, a Handwritten Equation solver with a respectable accuracy of 98 percent is demonstrated. It was trained on handwritten digits and mathematical symbols using a Convolutional Neural Network and certain image processing techniques. The images of the digits 0 to 9, plus and minus signs (+), and handwritten symbols * make up the dataset. For the purpose of extracting the features, we shall use contour extraction. In this Project we build the model using convolutional neural network and train the model to evaluate the equations written by hand in this we use the dataset of numbers and operators written by hand. The input image of hand written equation is given the image is converted into gray background for this we use contour extraction for obtaining the features. The output is produced by the model by evaluating the equation.

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 Keywords

Machine learning; Artificial Intelligence; Contour extraction

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 Abstract

The sewage system must be monitored in order to maintain the city clean. Uneven sewage system monitoring causes drainage to become clogged. Blockages in the sewer system are a major source of sewer flooding and pollution. Workers may be involved in an accident as a result of their ignorance of the situation inside the manhole. To get the necessary output from the module, this model uses a regulator circuit, sensor driver circuit, microcontroller, serial communication devices, and IoT module. Our answer to this problem is an IoT system that warns municipal officials about overflowing drains immediately by notification at the city control centre, as well as citizens via a mobile app. The essential component of this system is a low-power IoT-based portable gadget that is mounted below the manhole cover. Nowadays, accidents due to broken and missing manhole covers are quite frequent. Manholes are not monitored properly in developing countries. These accidents can lead to serious injuries and also death. Hence, here we propose a system to overcome this problem. We have included an array of sensors for complete monitoring of the manhole cover so that such accidents can be prevented. This project includes a Tilt sensor, Level sensor for to measure the level of water which could need to crack information, a tilt sensor is introduced to indicate whether the manhole can tilt, in case of any alert due to any of the parameters we send an SMS to an APP trough wifi. Also, all the parameters are continuously updated on the APP.

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Manhole, Sewage, microcontroller, Atmega328P, Tilt Sensor, Level Sensor

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 Abstract

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PhosphoGypsum, dihydrate (CaSO4.2H2O), Hemihydrate (CaSO4.5H2O), Triple, superPhosphate

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 Abstract

Background: Psychoactive substance use disorder is one of the most common psychiatric disorders that has deleterious consequences not only the patient with psychoactive substance users but also hampers social, financial ,and legal matters of his family hence could be considered as a disorder of the family spouses of patients with psychoactive substance use disorder , a key member of dysfunctional family system, are most vulnerable to have significant psychiatric disorders like adjustment disorders, mood disorders, anxiety disorders and psycho-social problems. Hence, we have undertaken this study in order to understand and address such issues which is largely neglected in psychiatric research. Materials and Method: Quantitative research approach, research design in this study is Experimental study design, non-probability convenient sampling technique used. A study conducted on caregivers of psychoactive substance users. The sample size was 95. By using the self-structured questionnaire knowledge regarding psychoactive substances and home care management was assess ed. Time given to fill the questionnaire was 30 minutes. Result: Percentage wise distribution of pre-test and post-test knowledge of caretaker depicts that highest percentage in pretest (64.22) had average knowledge, (32.63%) of them had poor knowledge and in post-test (70.53%) of the respondents had good knowledge. Hence it can be interpreted that self-instructional module was effective in improving the knowledge regarding psychoactive substances and homecare management of caretaker. Hypothesis testing was done by using 't' test and chi-square test. t value was calculated to analyze the difference in pre-test and post-test knowledge score of caretakers. Highly significant difference was found between pre and post-test knowledge score of caretakers (17.100). Hence the stated null hypothesis is rejected as it is interpreted that there was significant difference between pre-test and post-test knowledge score regarding psychoactive substances and homecare management. Chi-square test is applied for association between pre-test study findings and selected demographic variables. Chi-square values for this test are respectively for Age is (?2=4.591), Gender is (?2=10.671), educational qualification is (?2=3.972), Occupation is (?2=1.585), Family income is (?2=13.971), Type of family is (?2=2.587), relation with patient is (?2=16.080) and for drug does your patient consume is (?2=5.621) Conclusion: The focus of this study was to assess effectiveness of self-instructional module on knowledge regarding psychoactive substances and homecare management among caretakers of psychoactive substances users in tertiary care hospital of the city. In this study One group pretest post-test design with quantitative research approach was used. 95 samples were selected from selected hospitals of the city by using non-probability convenient sampling technique. The data was collected by using Self- structured Questionnaire on knowledge of caretakers of psychoactive substances and home care management. Self-Instructional module on psychoactive substances and home care managements. Data was analyzed and interpreted by applying statistical method. The researcher felt deep sense of satisfaction and fulfilment at having undertaken the study. The study provided deeper insight and empathy towards the needs of the expert guidance from the guide and cooperation of teachers has made the study a fruitful and pleasant experience.

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 Keywords

Psychoactive substances, homecare management, caregivers

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 Abstract

Transportation has a crucial impact on a country's growth, with roads being a vital component. They play a major role in people's daily lives as many individuals travel from one place to another via roads. Neglect in maintaining the existing road infrastructure, combined with environmental changes and heavy rainfall, can lead to the formation of potholes on roads. The Ministry of Road Transport and Highways reports that potholes have resulted in numerous road accidents and fatalities in recent years. To tackle this problem, our project aims to develop an automated pothole detection and dimension measurement system. Our proposed solution uses Mask Region-based Convolutional Neural Network (M-RCNN) deep learning algorithm to detect dry and wet potholes, and image processing techniques to estimate the size of the potholes. The implementation of this system will enhance road maintenance, reduce road accidents caused by potholes, and support the overall development of the country.

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Pothole Detection, Area Estimation, Deep Learning, MRCNN, Road Accident.

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Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia and altered metabolism of carbohydrates, lipids and proteins. It is a condition that impairs the body's ability to process blood glucose as result of this increased blood glucose level occurs in our body, which causes a diabetes mellitus. The present study reveals to develop a Polyherbal anti-diabetic herbal syrup by using an extract of a leaves of Gymnemasylvestre and dried seeds of Syzygium cumini. Three formulation of herbal syrup were formulated (F1, F2, F3) Herbals plants used in the formulations shows a potent anti-diabetic action over synthetic ones.F1, F2, F3 formulation were prepared and evaluated. Evaluation parameters of these formulation was found to be within the standard limits and in vitro studies were performed for detection of anti- diabetic activity

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Polyherbal syrup, Diabetes mellitus, Gymnemasylvestre ,Syzygiumcumini

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This research paper explores the relationship between attachment style, emotional intelligence, and life satisfaction among young adults. The aim of the study is to investigate how different attachment styles and emotional intelligence levels contribute to overall life satisfaction in this demographic. The research design employed a quantitative approach, utilizing standardized questionnaires to measure attachment style, emotional intelligence, and life satisfaction. A sample of 200 young adults aged between 18 and 25 years was recruited from various educational institutions and community settings. Statistical analyses, including correlation and regression analyses, were conducted to examine the associations between the variables. The findings revealed significant correlations between attachment style, emotional intelligence, and life satisfaction. Secure attachment style was positively associated with higher levels of emotional intelligence and life satisfaction. In contrast, insecure attachment styles, such as anxious and avoidant, showed negative associations with emotional intelligence and life satisfaction. Emotional intelligence was identified as a mediator in the relationship between attachment style and life satisfaction. Individuals with higher emotional intelligence were found to have greater life satisfaction, regardless of their attachment style. Moreover, emotional intelligence played a compensatory role, attenuating the negative impact of insecure attachment styles on life satisfaction. Overall, this thesis contributes to the growing body of literature on attachment theory and emotional intelligence, providing valuable insights into their impact on life satisfaction among young adults. The findings offer implications for interventions and support systems aimed at enhancing the psychological well-being and overall satisfaction of this population.

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 Keywords

Attachment style, emotional intelligence, life satisfaction, young adults, mental health

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