Emotion recognition from speech signals is an important but challenging component of Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER), many techniques have been utilized to extract emotions from signals, including many well-established speech analysis and classification techniques. Deep Learning techniques have been recently proposed as an alternative to traditional techniques in SER. This paper presents an overview of Deep Learning techniques and discusses some recent literature where these methods are utilized for speech-based emotion recognition. The review covers databases used, emotions extracted, contributions made toward speech emotion recognition and limitations related to it. A Multilayer Perceptron (MLP) deep learning model has been described to recognize voice gender. The data set have 3,168 recorded samples of male and female voices. The samples are produced by using acoustic analysis. An MLP deep learning algorithm has been applied to detect gender specific traits.

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Author : N. HARSHAVARDHAN, G. VASISHTA, B. BALAJI ,SK. HASEENA , M. DEVA KUMAR

Title : Speech Emotion Recognition (SER) & Gender Detection Using Deep Learning

Volume/Issue : 2022;04(3)

Page No : 1-8

With advancement in artificial intelligence (AI), Deep learning models are used to imitate the actions of human beings. These activities of personage are controlled by their brain and similar to that, machines are capable of data processing, decision making, speech recognition and language translations just like human beings. One of the applications of deep learning includes Autonomous Vehicles design i.e., driver less cars. To implement this, we need an automatic traffic sign recognition (TSR) model. These models are designed with the use of convolutional neural networks (CNN). The main task of this model is to extract the various features of the different traffic sign images and classify according to unique categories. This paper includes a comprehensive review of various models that can be used for classifying traffic signs. Researchers have applied various CNN models to predict the class of traffic sign and these are proven to be better than machine learning algorithms. CNN works as a feed forward neural network which has been stimulated from animal visual cortex.

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Author : Dr. Ratna babu P, B. Kavitha, N. Venkata Lakshmi, S. Madhu, G. Sivan Narayana

Title : Traffic Sign Recognition Using Machine Learning

Volume/Issue : 2022;04(3)

Page No : 9-15

The e-marketplace has emerged as an efficient and important vehicle for transactions in the e-commerce industry and academia and industry alike have recognized trust as a central factor enabling e-commerce. We need to design and implement a system that will check both buyers and sellers so that both parties will have trust in one another when transacting. Our project operates an online marketplace for consumer-to-consumer sales, particularly targeting users in emerging markets, with a view to providing a safe, reliable and efficient way for consumers to buy and sell goods. The agricultural application provides its users with information about the nearby available products like plants, seeds, pesticides, agricultural machinery. Sometimes, these products may get abide due to surplus purchase. Collaterally, there are some people who may require the same quantity of products. The main features of this application includes information retrieval facilities and marketing from anywhere in the form of obtaining statistical information about fertilizers, pesticides, seeds, and plants.

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Author : P.Narayana, G.Sairam, K.Pavan Venkata Avinas Reddy, A.Akhila,

Title : AGRICULTURE RESOURCE MANAGEMENT SYSTEM

Volume/Issue : 2022;04(3)

Page No : 16-19

Diabetic retinopathy is becoming a more prevalent disease in diabetic patients nowadays. Diabetic Retinopathy is one of the leading causes of blindness and eye disease in the working age population of the developed world. This project is an attempt towards finding an automated way to detect this disease in its early phase. In this project we are using supervised learning methods to classify a given set of images into 2 classes to verify that the patient has a scope for Diabetic Retinopathy. For this task we are employing various image processing techniques and filters to enhance many important features and then using neural for classification.

Keywords : Microneurysm; Hemorrhage; convolutional neural networks, MobileNetV2.

Author : K.HarikiranReddy, B.NagaKavitha, Y.ManeendharReddy, M.Raju , D.Vinay Kumar

Title : DIABETIC RETINOPATHY USING DEEP LEARNING

Volume/Issue : 2022;04(3)

Page No : 20-24

A chatbot is emerged as an effective tool to address the user queries in automated, most appropriate and accurate way. Depending upon the complexity of the subject domain, researchers are employing variety of soft-computing techniques to make the chatbot user friendly. It is observed that chatbots have flooded the globe with wide range of services including ordering foods, suggesting products, advising for insurance policies, providing customer support, giving financial assistance, schedule meetings etc. However, public administration-based services wherein chatbot intervention influence the most, is not explored yet. This project discuses about artificial intelligence based chatbots including their applications, challenges, architecture and models. It also talks about evolution of chatbots starting from Turing Test and Rule-based chatbots to advanced Artificial Intelligence based Chatbots. AI-Chatbots are providing much kind of services, which this project outlines into two main aspects including customer based services and public administration based services. The purpose of this survey is to understand and explore the possibility of customer & public administration services based chatbot. The survey demonstrates that there exists an immense potential in the AI assisted chatbot system for providing customer services and providing better governance in public administration services. And even among the AI assisted chatbots conversational interfaces have been a trending topic in recent years. As of the last decade, CIs have emerged with the aim of simplifying human-machine interactions and found a wide use case in the market. For example, Siri and Google Assistant are some of the most well-known CIs developed by the tech giants Apple and Google. The digital landscape has evolved from web, to mobile apps, to recently CIs. Nowadays, CIs, in particular chatbots and voicebots, are becoming increasingly common. Whether navigating the web or messaging on a phone, it is likely that CIs have been confronted offering the user help. However, CIs have not managed to reach a large-scale use. Furthermore, the reasons regarding the challenges faced by CIs as well as their usability are not greatly explored. Here in our project we combine the features of an AI chatbot with the conversational interface to provide services to people in public and customer based services.

Keywords :

Author : Bikki Supriya, Dasari Sai Prem Charan, Gade Gopi Reddy, Mohammed Arshad

Title : ARTIFICIAL INTELLIGENCE BASED CHATBOT

Volume/Issue : 2022;04(3)

Page No : 25-28

This paper is aimed to process properties of the conventional hardness and microstructure of Al-Sic nano composites with graphene flakes. It is planned to use various combinations with weight percentage of grapheme and Sic and to produce the Aluminum matrix composites by Compression Process. The first nano powered material is 100% pure Aluminum (Al). The other composition is Aluminum Al (70%),Silicon Carbide Sic (30%)The mixtures are to be mixed with nano Aluminum (70%) by weight percentages of adding nano Sic (25%), Graphene nano particles (GNP)(5%) followed by a Compression process to make a rigid form. Graphene and Sic nano particles predominantly are homogeneously distributed on the grain boundaries of Al matrix and Sic nano particles are distributed between GNP. Lot of work has been carried on synthesis of Al–Sic-Graphene composites for various engineering applications. Graphene has endowed with excellent physical and mechanical properties such as Tensile strength, elastic modulus and thermal conductivity and has got attention in the field of electronics, automobile industries, aerospace projects and other engineering applications. The prepared compacts must undergo microstructure evaluation by Metallurgical microscope and also find the Conventional hardness.

Keywords : Metallurgical microscope, hardness, Powder metallurgy, graphene.

Author : Srinivasulu Dorasila, M.Sai Manikanta Reddy SK.Aleem Baig , G.Gopi Krishna, and SK.Abdul Shabaz

Title : SYNTHESIS AND MECHANICAL PROPERTIES OF ALUMINIUM METAL MATRIX COMPOSITES

Volume/Issue : 2022;04(3)

Page No : 29-34

Today's undergraduates are expected to have 21st-century skills as part of learning and developing critical thinking abilities. Indeed, the “National Education Policy 2020” seeks to establish an educational system founded on the rich diversity of India's linguistic, cultural, and creative traditions. Refusing to recognize English as an Indian language in the National Education Policy is a sly attempt to impose Hindi. Local languages, particularly tribal ones, are being lost, and this paper expresses worry about their dwindling space. The English and English-aware elites blame the marginalization of other Indian languages as naive. This research paper explains that the value of language cannot be overstated when discussing education. Because of the diversity of Indian languages, the NEP encourages multilingualism and bilingual education while emphasizing the need to improve proficiency in Indian languages. Regarding acquiring a job, "English" is still up for debate regarding its cultural values and ethos. However, the policy's instructions for language usage must be examined in the language classroom. The students of undergraduate Engineering degrees need to be taught about Indian culture and the arts to create a strong sense of cultural identity and an appreciation for art, as they are more prone to migration for higher studies or for better career opportunities (software) but not as a compulsion. Ancient India's language and education were caste-based. The English educational system helped people escape constrained knowledge systems. This attribute improved the country's appeal when the British left. Many middle-class Indian parents believe that sending their children to an English-medium school will help them in the employment market. English is crucial to our global commercial and social competitiveness.

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Author : Mr. SHAIK ILIYAS ALI,Dr. R. VEERA SUDARSANA REDDY

Title : ENGLISH LANGUAGE AND DIASPORA STUDIES FOR ENGINEERING STUDENTS UNDER NEP-2020

Volume/Issue : 2022;04(3)

Page No : 35-44

Surpassing human capability in most domains, the upgrading of Artificial Intelligence (AI), has ushered healthcare from reactive treatment approach to predictive and personalized care paradigm. AI-powered clinical intelligence utilizes machinelearning, deep learning, natural language processing and predictive analytics to draw actionable insights from conventional healthcare data like electronic health records (EHRs), medical imaging scans, laboratory reports, genomic information and even wearable sensor data. In this paper, we propose a seamless framework for the provision of holistic patient care by integrating data acquisition, intelligent integration of multi-modal data sources (including chronic disease risk factor monitoring), prediction modeling, and clinical decision support applications along with personalized interventions in an unified patient-centered healthcare ecosystem. The framework leverages multimodal healthcare data to enhance disease risk prediction, early diagnosis, treatment optimization and continuous patient monitoring while aiding proactive management of health care. The study also emphasizes the imperative of explainable AI in improving interpretability, bolstering clinician trust, and facilitating shared decision-making. A systematic review of current AI implementations shows that predictive medicine provides an excellent opportunity to improve diagnostic accuracy, strengthen preventive health strategies, optimize population health management and decrease healthcare costs. The Framework is also a first step for addressing crucial challenges to implementation such as data privacy, interoperability, algorithmic bias, and ethical and regulatory issues that must be met to ensure responsible governance of the use of these technologies in health care. For instance, such results suggest that AI oriented clinical intelligence can radically change the practice of health care affecting personalized treatment pathways, proactive interventions and evidence based clinical decisions. In summary, brining together AI technologies and clinical intelligence creates a new approach to deliver comprehensive patient care that will enable improved healthcare outcomes while leading the way towards sustainable, efficient and patient-centered healthcare systems in the years ahead.

Keywords : Artificial Intelligence, Clinical Intelligence, Predictive Medicine, Machine Learning, Personalized Healthcare, Electronic Health Records, Clinical Decision Support Systems, Complete Patient Care.

Author : Srivenkata Gantikota Senior Software Engineer | Application Security and Enterprise Systems Specialist University of California San Diego (UC San Diego) California, USA

Title : AI-Driven Clinical Intelligence for Predictive Medicine: A Comprehensive Framework for Complete Patient Care

Volume/Issue : 2022;04(3)

Page No : 45-68