Volume 10 | Issue 12 |

 Abstract

Saliva is a complex diagnostic fluid, which contains a variety of enzymes, hormones, antibodies, antimicrobial constituents and growth factors. In our body fluids like blood, saliva, tears, sweat and urine are crucial resources of pathological diagnosis. Changing in level of total cholesterol level in human female saliva was investigated in 60 women volunteers during various stages of reproduction (pre-pubertal, parous, non-parous, menopausal and diabetogenic). According to findings, level of total cholesterol level is significantly increased during ovulatory phase, which was due to hormonal metabolic changes in the period of menstrual cycle.

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 Keywords

Saliva, Total cholesterol, prepubertal, parous, non-parous, menopausal and Diabetogenic.

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 Abstract

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 Keywords

Human Rights, Terrorism, Fundamental Rights, Counter-Terrorism, Legal Framework, Psychological oppression of Terrorism, Terrorism in India, Counter Terrorism measures of India, Public safety, Protection of Human Rights

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 Abstract

Abstract The Scheduled tribes, since ages, have been victims of socio-economic exploitation and have been relegated to low income generating occupations, inferior trades, unhealthy environment and unclean unskilled occupations. Although clear untouchable practices may be declining in many parts of the country, caste rigidities continue to confine many Schedule Tribe workers in demeaning occupations, which put them at a disadvantage when compared to other communities. The forces of urbanization, social and protective legislations, positive discrimination and other measures taken by the Government, have led to gradual improvement in occupational mobility and living standards over the years, but the living conditions of the majority of Scheduled Tribes continue to show socio-economic backwardness. The introduction of money economy has left them to the tender mercies of money-lenders leading to their chronic indebtedness. However, these broad generalisations may not be applicable to all the tribes of a vast country like India. Therefore, a study of the impact of institutional finance on the economic development of tribals at a micro level, confined to a district, seem to be most appropriate. The micro study can mark out areas of success as well as failure and also point out the deficiencies in the formulation of policy and in the implementation of the programme. The present study attempts to examine the distribution of borrowers of the tribals of the Visakhapatnam district in Andhra Pradesh.

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 Keywords

Adivasi, indebtedness, credit, borrowings, shifting cultivation.

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The perfect, accurate and robust detection of the audio has been widely grown as the speech technology in the area of audio researches, audio forensics, speech recognition, and so on. However, in real time, it is a challenge to deal with the massive data arriving from distributed sources. Thus, the study introduces a method that effectively deals with the data from the different sources using the audio classification method. This method uses anywhere for our general purpose projects, Voice services are rapidly gaining popularity, with the use of virtual assistants such as Siri, Alexa, and Google Assistant becoming increasingly common. These systems rely on audio classification to understand and respond to user requests. Audio classification is the process of using machine learning algorithms to classify audio data into different categories or classes. This is a crucial component of voice services, as it allows the system to understand and interpret the user's spoken words

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 Keywords

Audio classification, Voice-based services, Voice recognition, Speaker identification, Natural language processing, Speech recognition, Language translation, Machine learning, Artificial intelligence, Human-computer interaction

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Exodontia or extraction of the tooth is defined as the painless removal of the entire tooth or the root with minimum trauma to the investing tissues, so that the wound heals normally and no postoperative prosthesis problems arise. A proper History of the patient is necessary before extraction for evaluating the patient. Many systemic diseases have direct or indirect relation with Exodontia. So, it is necessary for the practitioner to understand the indications, contraindications and management of the patient in case of emergency of these patients during extraction. The survey is conducted among the undergraduate students.

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 Keywords

Anticoagulant therapy, complications, Extraction, oral manifestations, oral-systemic connection.

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 Abstract

Machine learning is an emerging technique for building analytic models for machines to "learn" from data and be able to do predictive analysis. The ability of machines to "learn" and do predictive analysis is very important in this era of big data and it has a wide range of application areas. For instance, banks and financial institutions are sometimes faced with the challenge of what risk factors to consider when advancing credit/loans to customers. For several features/attributes of the customers are normally taken into consideration, but most of these features have little predictive effect on the credit worthiness or otherwise of the customer. Furthermore, a robust and effective automated bank credit risk score that can aid in the prediction of customer credit worthiness very accurately is still a major challenge facing many banks. In this paper, we examine a real bank credit data and conduct several machine learning algorithms on the data for comparative analysis and to choose which algorithms are the best fit for learning bank credit data. The algorithms gave over 80% accuracy in prediction. Furthermore, the most important features that determine whether a customer will default or otherwise in paying his/her credit the next month are extracted from a total of 23 features. We then applied these most important features on some selected machine learning algorithms and compare their predictive accuracy with the other algorithms that used all the 23 features. The results show no significant difference, signifying that these features can accurately determine the credit worthiness of the customers. Finally, we formulate a predictive model using the most important features to predict the credit worthiness of a given customer.

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 Keywords

Machine Learning algorithms

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 Abstract

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Neural Networks, Skin Melanoma Detection

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With the popularization of automobile and the progress of computer vision detection technology, intelligent license plate detection technology has gradually become an important part of intelligent traffic management. License plate detection is used to segment vehicle image and obtain license plate area for follow-up recognition system to screen. It is widely used in intelligent traffic management, vehicle video monitoring and other fields. In this paper, two license plate detection methods are studied, one is based on Sobel edge detection and the other is based on morphological gradient detection. Basing on OpenCV and PYTHON under Windows system, two methods of license plate detection are implemented, and the two algorithms are compared in detail from the aspects of license plate detection accuracy. These methods have high efficiency and good interactivity, which provide a reference for later license plate recognition.

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 Keywords

Image Processing, OPENCV, Number Plate Detection

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 Abstract

Aim and objectives: - To investigate the sample rejection rate of pre analytical errors in a clinical laboratory tertiary care centre. To identify the types, frequency of pre analytical error and to detect the percentage of pre analytical errors. Materials and methods: - This was the retrospective analytical study by collecting the data over the period from November 2020 to February 2022 at clinical biochemistry laboratory at Mahatma Gandhi Medical College and Research Institute. Data analysis was done on samples were received and tested which includes sample like blood, urine and other fluids. Types of errors were as follows: - inappropriate labelled samples, improper collection tubes, clotted sample, hemolysis, insufficient volumes, lipemic samples. Results: - Out of 2,39,327 total samples received from both OPD and IPD, 891 samples were found to be unsuitable for further processing. The majority of the sample rejected due to hemolysis (43%), the second most frequent pre analytical error encountered in insufficient volume (21%), clotted sample (16.2%), mislabelling of samples by the laboratory personnel was seen as caused of rejection is 9.9%, lipemic samples were also rejected is 5.3%, inappropriate container accounted for faulty results in 3.3% of samples. Conclusion: - The concept of TQM encompasses all the steps involved in sample processing, beginning from test ordering to the final interpretation of results by clinicians to reduce or eliminate the errors that may rise during various steps. The dependence on accurate lab results for diagnosis makes it mandatory for labs to ensure accountability and accuracy of results for diagnosis as a consequence of faulty reporting.

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Key words: Preanalytical errors, Covid-19, Total Quality Management, Total testing Process, Turnaround Time.

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 Abstract

Using renewable types of energy and Electric Cars (EVs) can reduce energy prices and minimize radiation to a substantial extent. The intermittent nature of renewable energy sources and their sporadic use, integrating renewable energy sources into the electric grid is a challenging process. If the supply of renewable energy is not adequate to fulfill the requirement, it is expensive to pull more energy from the power grid. This may also reduce the energy efficiency of the charging process. The focus of this study is to present methods for optimizing a controller for the charging of electric vehicle batteries using renewable energy sources for energy management. The output of the Dynamic Programming optimization and a variety of other approaches used in energy optimizing software are compared to determine which one would accurately minimize the cost of energy required for charging and yet fulfill the aggregate battery charge maintaining criteria. Based on this study it is evident that the Dynamic Programming based optimization strategy provides the highest level of accuracy while maintaining a consistently high level of fuel savings in EVs.

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 Keywords

Electric Cars, Battery, Electric Vehicles, Dynamic Programming, Renewable Energy Sources

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Creative Commons Attribution 4.0 and The Open Definition