Volume 14 | Issue 3 |

 Abstract

Bipolar disorder is a chronic and debilitating psychiatric illness characterized by recurrent episodes of mania and depression, significantly affecting an individual's emotional stability, cognitive functioning, and quality of life. Accurate diagnosis remains challenging due to symptom overlap with other mood disorders and reliance on subjective clinical assessments. This study presents a clinically driven deep learning framework for the automated prediction of bipolar disorder using a structured, symptom-based dataset reflecting common psychiatric indicators. Three deep learning models--Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM)--were designed and evaluated to analyze behavioral and clinical symptom patterns. Standard preprocessing techniques, including normalization and train-test splitting, were applied to ensure reliable model performance. The predictive capability of each model was assessed using classification accuracy and confusion matrix analysis. Results demonstrate that deep learning approaches effectively model complex clinical relationships within psychiatric data. The ANN model achieved the highest predictive accuracy, indicating its suitability for tabular clinical datasets. This work emphasizes the potential of deep learning as a supportive clinical decision-making tool for early bipolar disorder screening and improved mental health assessment.

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 Keywords

Artificial Intelligence, Deep learning, Psychiatric Illness, Bipolar Disorder, Mental health.

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Creative Commons Attribution 4.0 and The Open Definition

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S??khya's Philosophy, Yogic Path

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This paper is about cross-domain sentiment analysis for product reviews. People write reviews for products like electronics, books, and clothes on websites like Amazon. Sentiment analysis helps to find whether these reviews are positive, negative, or neutral. But sometimes, there are not enough labelled reviews in one domain to train the system. So, cross-domain sentiment analysis uses data from one domain to help another domain. In this paper, a web based system is implemented that collects reviews, processes text using NLP techniques, and classifies the sentiment using machine learning models. This helps to understand customer opinions and improve decision-making for products across different domains. Additionally, the system integrates an AI-powered chatbot that interacts with users in real time, answers queries about products, provides sentiment summaries, and guides customers in exploring product feedback efficiently.

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AI Chatbot interaction, Cross-domain sentiment analysis, Machine learning models, Natural language processing

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Creative Commons Attribution 4.0 and The Open Definition

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Cinnarizine, Dimenhydrinate, Orodispersible, SSG, Crospovidone

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social Media Ke Prabhav Se Hindi Media Ki Bhasha Me Badlav

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Social Media Ke Prabhav Se Hindi Media Ki Bhasha Me Badlav

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The two novels The Handmaid's Tale and Brave New World display their female characters which demonstrate how societies treat women as objects while governments use psychological techniques to dominate their populations. The two novels create two different dystopian societies which control female bodies through different time periods and locations to maintain their political power. The research investigates how women establish their identity through Gilead's religious authoritarianism and World State's technological hedonism which serve as two independent identity-building systems. The study uses feminist theory together with surveillance and biopower theories and trauma theory to study how systems of oppression function through two methods which operate as external conditioning and internalization of power systems. The Handmaid's Tale presents women as existing mainly for reproduction purposes while the heroine's fragmented narration shows how objectification damages women's emotional states. Offred's disjointed storytelling together with her broken memories show how traumatic experiences change a person's identity during times of oppression. The Brave New World society has created a system which permits women to seem socially self-sufficient while their inner feelings and desires undergo training to match established social norms.

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 Keywords

Female Objectification; Dystopian Fiction; Feminist Literary Criticism; Biopower; Psychological Control; Trauma; Gender Identity.

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For the good and efficient operation of the Indian Parliament, some unique rights have been given. These benefits enabled the elected members of parliament to do their duties more effectively, self-assuredly, and without needless intervention. In this review study, the researcher will analyse the meaning and genesis of the idea of parliamentary privilege. The researcher will also discuss the ways in which India and a few other countries have used parliamentary privileges. In order to ascertain how legislative privileges in India differ from those in the United Kingdom and the United States, the researcher will employ a comparative method when examining the issue. Since various nations have distinct laws governing parliamentary privileges and immunities, the laws of privilege in nations with continental systems, like France, Britain, and Australia, are pertinent when examining the theory of parliamentary privilege. Furthermore, like South Africa, India is an ancient democracy with a three-tiered structure of governance. The author has used comparative research analysis in this work to assist evaluate and analyse the scope of India's parliamentary privileges and immunities.

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Parliamentary Privilege, Democracy, Member of Parliament,

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**ABSTRACT** Pricing plays a decisive role in determining the market acceptance and success of new-origin products, particularly in the absence of established brand recognition. This study examines the effectiveness of various pricing strategies--such as penetration pricing, skimming pricing, cost-plus pricing, value-based pricing, and freemium models--and their influence on consumer perception, purchasing behaviour, and overall product success. The research adopts a descriptive and quantitative approach, using primary data collected through a structured questionnaire from 80 respondents in the Kannur Downtown Mall area, supported by secondary data from journals, reports, and textbooks. The findings reveal that consumers are generally less price-sensitive when trying new-origin products; instead, they place greater emphasis on perceived value, trust, and risk reduction. A majority of respondents are unwilling to pay a premium for innovation alone and are not significantly influenced by discounts or introductory offers. Free trial/freemium and penetration pricing emerge as the most preferred strategies, while price skimming is the least favoured. The study also highlights the importance of online platforms as the primary source of information and underscores the role of financial and product literacy in shaping informed purchasing decisions. The study concludes that businesses should prioritize value communication, transparency, and low-risk entry pricing strategies to enhance adoption of new-origin products. By aligning pricing with consumer perceptions and market dynamics, firms can improve product acceptance, competitiveness, and long-term sustainability. The research contributes practical insights for marketers, entrepreneurs, and policymakers and aligns with Sustainable Development Goal 8 by supporting sustainable pricing practices that foster innovation and economic growth.

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NEW ORIGIN

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The Indian Real Estate Industry is contributing greatly towards the development of the economy by supporting other associated sectors. Delhi/NCR is a prime example of an excellent type of influential Real Estate Market that is dynamic in nature. The factors that have greatly affected the Real Estate Market include urbanization, innovations, changing consumer behaviours, etc. In addition, the study aims at assessing the future trends of the Real Estate sector in Delhi/NCR. It would highlight the key factors that affect its development. The analysis will incorporate this descriptive analysis along with some of the understanding derived from both primary and secondary sources of information. The primary information for this analysis was collected through a well-structured questionnaire intended for the developers within the Delhi NCR region. This was done to gather their views about demand trends, market stability, infrastructure, and their usage of technology and sustainability. The secondary information for this analysis was obtained through means such as published reports and documents accessible within government sources across various internet platforms. The findings bring into view that the enhancement pertaining to the road's connectivity, transparency at regulations, and strong demand at the end user level play a very important role in the direction to the enhancement seen in the Delhi NCR region. The study also highlights a continuously rising interest seen on affordable housing, medium level of income housing, higher adoption towards the application of technology, and focus on Green Buildings/development. The Commercial Real Estate segment also shows signs of enhancement with flexible offices and higher technology. The overall conclusion drawn in this study is that for a region such as Delhi NCR, where this report was generated, there are huge growth opportunities for a proper and well-thought-out growth pattern, subject to an appropriate and proactive response to upcoming policies and adaptability to new technologies and tastes and preferences.

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 Keywords

Urbanization Consumer Behavior Infrastructure Development Affordable Housing Sustainable Development Green Buildings Commercial Real Estate Market Trends and Growth Technology Adoption in Real Estate Regulatory Transparency Demand Analysis Primary and Secondary Data Future Trends

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The main aim of a Text to Speech (TTS/T2S) synthesis is to convert ordinary text into an acoustic signal that is indistinguishable from human speech. A Text to Speech synthesizer is an application that converts text into spoken word, by analysing and processing the text using natural language processing and then using digital signal processing technology to convert this processed text into synthesized speech representation of the text. Many current text to speech systems are based on the concatenation of acoustic units of recorded speech. Current concatenative speech synthesizers are capable of producing highly intelligible and natural speech, whose quality closely matches to the voice quality of the speaker who recorded the audio segments from which the concatenation units are drawn. Concatenative synthesis has the advantages of being simple to implement and requiring a relatively small database of speech. This is the easiest method to produce synthetic speech. It concatenates prerecorded acoustic elements and forms a continuous speech element. Here, we developed a real time text to speech synthesizer in the form of a simple application that converts inputted text into synthesized speech and reads out to the user which can then be saved as a wave (.wav/) file and/or text (.txt) file. The development of a text to speech synthesizer will be of great help to people with visual impairment and make making through large volume of text easier. Here a Vocally handicapped people can type the text from keypad and Using MATLAB R2015a, we can get voice output of input words, and output voice is heard through speaker. The proposed methodology may be use to provide assistance to people who lack the power of speech or non native speakers, to provide an artificial voice for a speech impairment person and many more application in multimedia ,telecommunication sectors. This thesis presents an algorithm, design and implementation of a text to speech synthesis for synthesizing unlimited vocabulary speech in real time for English language and and all other languages scripted in Roman using STM Discovery board (STM32F407VG) & MATLAB to overcome the barrier of different languages. The recording of voice is done in C using STM Discovery kit and A database of acoustic library is constructed, whereas implementation of text to speech synthesis is done using MATLAB R2015a.

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 Keywords

Text to Speech, TTS, T2S

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Creative Commons Attribution 4.0 and The Open Definition