Volume 11 | Issue 11 |

 Abstract

Automated and unmanned restaurant appeal has surged in recent times. Since there is no staff present, it is impossible to directly gauge what patrons think of the restaurant idea or learn about their experiences. This research provides a grading system based on pre-trained convolutional neural network (CNN) models for face expression identification. It consists of a web server, an AI server that has already been taught, and an Android mobile application. It is intended that both the cuisine and the setting be appraised. Restaurants that are both automated and staff-free are growing in popularity. It is unable to directly evaluate the opinions of the customers due to a staffing shortage, thus it is impossible to find out about their experiences with the restaurant concept. This study uses convolutional neural network (CNN) models that have already undergone training to produce a facial emotion recognition grading system. It consists of an AI server that has previously been trained, a web server, and an Android mobile application. It is intended that reviews would be left for both the food and the environment. Three expressions are now available in the grading system: neutral, dissatisfied, and satisfied.

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 Keywords

CNN, AI, DCNN, deep neural networks.

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Abstract The advancement of technology has revolutionized the way we communicate and exchange data. One of the key technologies that underpin modern communication networks is the Internet Protocol (IP). In this note, we will delve into the specific application of IP in Asynchronous Transfer Mode (ATM) networks, with a focus on the Bundelkhand region. Consider an IP ATM network scenario that is widely used today. In this scenario, Asynchronous Transfer Mode (ATM) is used as the backbone to provide high-speed transfer of Internet Protocol (IP) traffic. Telephone operators and Internet Service Providers (ISPs) that use ATMs as their backbone must model and specify IP traffic to plan and manage these networks to meet the specific needs of their customers. This paper describes the problem of modeling IP traffic over ATM network connections. It provides a mathematical model that can be used to capture measured data and transform this data into a format suitable for various planning and management tasks performed by grid operators.

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 Keywords

ATM , IP,

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Creative Commons Attribution 4.0 and The Open Definition

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Drug delivery through the skin is crucial for local and systemic effects. The physicochemical properties of the medicine, the patient's compliance, the ability to stick to outermost layer of skin during treatment in order to facilitate the drugs adsorption. Film-forming sprays provide several benefits over traditional topical therapies, includes uniform distribution of drugs and dosage, improved bioavailability, less irritation, prolonged drug release, and accelerated healing of wounds through moisture management. To effectively treat wounds and disorders of the body's tissues, the medication must be left at the treatment location for the whole duration of the injury. Drug delivery methods known as "topical film forming systems" are administered topically, adhere to the body, and create a delicate, transparent film that carries active components to bodily tissue. It is advised to use them as emollients or protective agents to skin. In film-forming sprays, polymers and excipients enhance preparation qualities and boost the durability of active components. Different properties will be produced in films depending on the polymer and excipient used. Consequently, various polymer and excipient kinds, in addition to them. The review states that in situ layer or viscoelastic polymers, whether natural or synthetic, can be used to maximise topical medication supply.

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 Keywords

Topical medication delivery, film-forming solution, polymer.

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 Abstract

This research paper provides a comprehensive review of deep learning techniques applied to natural language processing (NLP) for the evaluation of feedback. In today's digital age, feedback is ubiquitous, and its analysis is crucial for understanding user sentiments, improving products and services, and making informed business decisions. Traditional methods of feedback analysis often fall short in handling the complexity and nuances of human language. Deep learning, a subset of machine learning, has shown promising results in capturing intricate patterns and semantics in natural language. This paper begins by introducing the importance of feedback evaluation and the challenges associated with traditional approaches. Subsequently, it delves into an overview of deep learning techniques, including neural networks, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and transformer models, and their applications in NLP. The focus is on their ability to process and understand the context, sentiment, and semantics of textual feedback. The main body of the paper reviews recent research studies and applications of deep learning techniques in feedback evaluation. This includes sentiment analysis, opinion mining, and emotion detection, highlighting the strengths and limitations of various models. Additionally, the paper explores the use of pre-trained language models, such as BERT (Bidirectional Encoder Representations from Transformers), GPT (Generative Pre-trained Transformer), and their variants, in feedback analysis. The paper also discusses challenges and open research issues in applying deep learning to feedback evaluation, such as the need for labeled datasets, model interpretability, and ethical considerations. Furthermore, it provides insights into potential future directions for research in this domain, including advancements in model architectures, transfer learning, and the integration of multimodal data. To validate the effectiveness of deep learning techniques in feedback evaluation, the paper presents a case study or experimental results using a specific dataset. It evaluates the performance of different models and compares them with traditional methods, showcasing the advantages of deep learning in capturing complex linguistic features. In conclusion, this research paper consolidates the current state of the art in applying deep learning techniques to NLP for feedback evaluation. It provides a roadmap for researchers, practitioners, and industry professionals interested in leveraging advanced techniques to gain deeper insights from textual feedback in various applications.

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 Keywords

Deep learning, Natural Language Processing, Feedback Evaluation, Sentiment Analysis, Opinion Mining, Neural Networks, Transformer Models, BERT, GPT.

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Creative Commons Attribution 4.0 and The Open Definition

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Heart disease is a prominent cause of death among people. These diseases are preventable if treated in time. We propose a system that can allow users to assess their heart health and ensure they realise when to visit the doctor. We utilise Machine Learning algorithms prominently to determine the risk of heart diseases to a particular user. We use Classification algorithms for the prediction as they offer the best result as well as fit the use case. Data mining is crucial in feature selection to build better models. We use the UCI Cleveland dataset of heart disease to train our models.

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Machine Learning, Classification Algorithm, Data Mining, feature Selection

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Creative Commons Attribution 4.0 and The Open Definition

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Design Thinking is a process that aims to modify the whole thinking mechanism and it channelizes to refresh the thinking mechanism. The main aim of design thinking is to challenge the existing assumptions and give innovative solutions as output. It paves way for an entirely different way to think. In the field of Law, design thinking has been rarely applied and there exists a huge vacuum in this area of research. But, if we go into the roots of the Law - making process, we would realise the necessity of design thinking in the legal field. Moreover, it is in the areas of Law, where design thinking is really required. Tax Laws are formulated keeping in mind the interests of various stakeholders involved. This process involves lengthy brainstorming sessions, analysing benefits and burden of the proposed Laws on these stakeholders upon whom the Laws are to be implemented, gathering feedback, tabling them in the legislature, debating upon them and then passing them. To illustrate and emphasise the need for Design Thinking in Tax Law Reforms two examples - Fat Tax and Exclusion of Petroleum Products from the ambit of Goods and Services Tax have been highlighted. This Article seeks to establish the importance of design thinking in reforming Tax Laws, moving forward with its applicability in maintaining the ethics of progressive taxation and also explains how various obstacles and deadlocks can be eliminated in the course of implementation of Laws in the future.

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 Keywords

Tax Law, Design Thinking, Law Reforms, Fat Tax

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Creative Commons Attribution 4.0 and The Open Definition

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There are 5 types of Vata Prana, Udana, Samana, Vyana, Apana. It stimulates for all types of actions. It controls and guides the Manas. Stimulates all the Indriyas.(1) Prakruta Karma of Vata Dosha is Vega Pravaratana. Hence Vega Dharana leads to Vata Prakopa and Vata Prakopa leads to various diseases. Vata, Purisha, Mutra, Kshavatu, Trushna, Kshudha, Nidra, Kasa, Shrama Shwasa, Jrumbha, Ashru, Chardi, Shukra, these are the Adharaniya Vega according Ashtanga Hridaya.(2) Instead of Kasa, Udgara is told in Charaka Samhita. These are the Adharaniya Vega which should not be suppressed. Suppression of these urges leads to various types of diseases.

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Key words - Vata Dosha, Adharaniya Vega, relation between Vata Prakopa and Vegadharana Janya Vyadhi.

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Disengagement from the social and physical environment is a result of the increasing number of environmental catastrophes and resource-depleting upheavals. The purpose of the study was to investigate in human subjects the link among intelligence, emotion, and ecology. A random sample of 304 job seekers men in their 20s and 25s was taken. The variables eco-sensory intelligence, emotional intelligence, and general intelligence were measured using the psychological instruments environmental awareness ability measure, emotional intelligence scale, and test of general intelligence, in that order. The parametric test assumptions were tested using descriptive statistics. The study employed inferential statistics, specifically product-moment correlation, univariate ANOVA, and multivariate ANOVA, to assess the null hypothesis at the significance level of 0.05. The findings showed that general intelligence was adversely correlated with emotional intelligence and had no discernible relationship with ecological sensory intelligence. There was a significant positive association between emotional intelligence and eco-sensory intelligence

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 Keywords

Ecological-Sensory Intelligence, Emotional Intelligence, General Intelligence, ecological literacy,

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"Tracing Paths and Perspectives: Western Explorers in Ladakh and Their Insights into Trade, Economy, and Culture" examines the rich narratives of 19th and early 20th-century Western explorers in Ladakh. This paper scrutinizes their detailed accounts, focusing on the region's pivotal role in trans-Himalayan trade networks and its socio-economic landscape. It highlights how these explorations illuminated Ladakh's trade practices, economic exchanges, societal norms, customs, and religious beliefs. By analyzing travelogues, journals, and letters, this study reveals the multifaceted interactions between Western explorers and Ladakh, offering a nuanced understanding of the region's historical significance in trade and cultural exchange within the broader context of Central and South Asia.

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 Keywords

Travel Writings, Ladakh, Western Explorers, Trade, Economy, Himalaya

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The majority of the characters have an identity crisis as a result of their inability to reconcile their American and Indian identities. This causes cultural isolation, which in turn causes personal isolation. The tales eloquently demonstrate the components of diasporic preoccupation, namely the desire for a place where diasporans may live comfortably. Keywords: Immigrants, identity crisis, self-exile, cultural isolation. The lives of Indian immigrants are the subject of Jhumpa Lahiri's stories. Interpreter of Maladies is a collection of nine stories that address the difficulties faced by immigrants living in foreign countries. The first story, "A Temporary Matter," among the nine collections of stories, depicts the marriage dilemma of a young couple named Shoba and Shukumar. Readers are made ready for the challenges of self-exile by the deterioration of their bond while living apart in Boston.

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 Keywords

Immigrants, identity crisis, self-exile, cultural isolation

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Creative Commons Attribution 4.0 and The Open Definition