Volume 12 | Issue 4 |

 Abstract

This paper examines Sabiha Sumar's film Khamosh Pani, probing the intertwining of time, space, and narrative. It delves into the domestic and public spheres as symbolic arenas for exploring trauma and societal tensions post-Partition. Ayesha's personal space reflects internal turmoil, while public spaces like the barber's shop depict ideological clashes. Through characters like Mehboob, resistance against rising fundamentalism is portrayed. The film serves as a poignant exploration of silenced voices and warns against the dangers of extremism.

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 Keywords

Time, Space, Partition, Radicalism, Khamosh Pani

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Internet of Things (IoT)-enabled smart lighting solutions provide ground-breaking improvements in user comfort, environmental sustainability, and energy efficiency. These systems may dynamically change lighting levels, color temperatures, and patterns in response to occupancy, natural light, and user preferences by integrating sensors, actuators, and network connectivity. This flexibility improves user enjoyment and well-being in addition to lowering energy use. Additionally, IoT-enabled smart lighting systems allow for remote control and monitoring via centralized platforms or mobile devices, enabling real-time administration and data-driven insights. These features enable defect identification, performance optimization, and predictive maintenance, which lowers operating costs and boosts dependability. IoT-based smart lighting applications include retail settings, office buildings, outdoor lighting, and home automation in addition to applications in the commercial, industrial, and residential domains. Smart lighting transforms how we illuminate and engage with our surroundings and helps to create smarter cities and sustainable environments through seamless connection with other IoT devices and systems.

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 Keywords

Smart lighting, Internet of things, IoT-enabled lighting systems, Efficiency, Flexibility, Control

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: "Dehashya Rudhiram Mulam" i.e. the existence of life depends upon the quantity and quality of Rakta. Rakta is considered as a Dashavidha Pranayatana, it is produced from the Prasada Bhaga of RasaDhatu with the help of Bhutagni and RasaDhatwagni. Its Gunas are similar to Pitta Guna like Sneha, Ushna, Tikshna, Drava etc. It is Apa and Teja Mahabhuta predominant, circulates all over the body from Hridaya through Dhamanis. Jeevana, Varna Prasadana and Mamsapusti are the Prakruta karma of Raktadhatu. In Rakta Pradoshaja Vikara, Rakta plays a major role for the formation of the Vyadhi Samprapti (disease pathogenesis) either due to its Swatantra (i.e. Pitta Dosha) or Paratantra prakopa. This concept also plays an important role to understand the involvement of Rakta for the manifestation of either Ashukari (immediate) or Chirakari (chronic) diseases. For management of Raktapradoshaja Vikaras, Virechana, Upavasa, Raktamokshana and Raktapittahara chikitsa had been advised. Overall the Raktadusti chikitsa can be divided into Abhayantara and Bahya chikitsa. Abhaynatara can be again sub divided into Shodhana and Shamana chikitsa where as Bahya as Sthanik and Sarvadaihika chikitsa.

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 Keywords

Raktadushti, Raktapradoshaj vikara, Rudhira, shonita

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Creative Commons Attribution 4.0 and The Open Definition

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Sign language is the preferred method of communication for the deaf and hard of hearing community. It is a visual language that uses hand gestures, facial expressions, and body language to convey meaning. Sign language recognition (SLR) is a field of computer science that deals with the development of systems that can automatically recognize and translate sign language into spoken language or text. Sign language recognition systems have the potential to revolutionize the way deaf and hard of hearing people interact with the world around them. They could be used to provide real-time translation services in a variety of settings, such as education, employment, and healthcare. SLR systems could also be used to develop new educational tools and to improve the accessibility of existing technology. Harnessing cutting-edge computer vision and machine learning technologies, this system demonstrates the potential to recognize and interpret a wide array of sign language gestures with remarkable accuracy and efficiency. By employing deep neural networks and sophisticated algorithms, the SLRS aims to convert these gestures into both written text and spoken language, facilitating seamless interaction between deaf individuals and the hearing world.

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 Keywords

Sign Language, Deaf, Deep neural network, Computer vision

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Creative Commons Attribution 4.0 and The Open Definition

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The furniture sector has changed significantly as a result of e-commerce's explosive growth. This extensive project explores the creation and evaluation of a cutting-edge online furniture store. In this paper, we propose a website "E-commerce Furniture Website Using AR Technology" makes moderately cost, high-quality furniture more accessible to rural populations. By using this platform providing some special offer products especially for women's for giving them business opportunities. The paper goes into detail on some of the main aspects of the e-commerce platform, including an intelligent recommendation engine, augmented reality integration, and a 3D product visualization tool. This research explores the impact of AR integration on user engagement, conversion rats, and overall customer satisfaction, highlighting the potential of this technology to revolutionize the way consumers shop for furniture online.

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 Keywords

E-Commerce, furniture, integration tool, Customer satisfaction, user platform.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

??????? ?????? ?? ???? ???? ?? ??? ???? ??? ?? ?? ?????? ???? ?? ?????? ?? ???? ???? ??? ???? ??? ?? ??? ??? ???? 2020 ??? ???? ????? ?????? ???? ?? ?? ?? ?????? ???? ?? ?????? ????? ????? ?? ?? ??? ????? - 2020 ?? ??? ??? ????????? ???? ??? ??? ??????? ??????, ??????????? ?? ???? ??????????? ?? ?????? ??????? ??? ??????? ?? ?????????? ??????? ?????? ??????? ??? ????? - 2020 ?????? ?????????? ?? ??????????? ??? ?? ???????? ???? ??????????? ?? ???? ?????????? ??????? ?? ???? ????? ??? ???? ????????? ?? ????? ???? ?? ??? ????? ???? ??? ??? ?? ?? ?? ??? ????? ???? ??????? ?????? ??????? ?? ?????? ????? - 2020 13-18 ?? ????????? ?????? ?? ????? ?? ???? ?????-?????? ????? ?? ??????????? ???? ??, ????? ??????? ?? ????? ????????? ?? ????????????? ??????? ??? ??????? ????? ???? ?? ??? ????? ??? ???????? ?? ?????? ????? ??? ????? - 2020 ????? ???? ?? ???-??? ????? ???? ?? ?? ?????? ??????? ?? ???????? ???? ??? ??? ??? ?? ??? ????? ??? ?? ????? - 2020 ?? ??? ????????? ?? ????? ????????? ?? ???? ??? ???? ?????? ?? ???? ???????? ?? ???????? ???

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A metaphor is a figure of speech used to express a specific meaning or idea by drawing comparisons between two entities or ideas that are not necessarily related to one another. Without using the terms "like" or "as," metaphors use implicit comparisons. Instead, they substitute a word or phrase that doesn't directly relate to the topic at hand but instead makes an analogy or comparison. Understanding and processing metaphors is a difficult topic in natural language processing. Consequently, the current need for metaphor classification involves an innovative approach. In order to conduct tasks like entity linking and relation extraction, we employ a method known as Knowledge Graph Embedding to represent the data in a knowledge graph as numerical vectors. When examining metaphors, we notice a structural pattern where the source and target are linked by a relationship that depends on a specific attribute. The target, the attribute, and the source make up the metaphor triple that describes this pattern. We use dependency parsing to extract collocations of concepts and attributes. In our method, we jointly embed the metaphor Knowledge Graph and the Concept-Attribute collocations. After that, the goal of metaphor identification can be seen as representation-enhanced concept pair classification. We also work on prediction of the possible attributes when given two concepts i.e. target and source from knowledge graph. By improving metaphor detection accuracy, this technique will fill a research gap.

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Natural Languages, Computational Linguistics, NLP

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Creative Commons Attribution 4.0 and The Open Definition

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The Doctors Trustworthiness Assessment project aims to address a critical problem in the healthcare industry - the difficulty of patients in assessing the credibility of doctors accurately. Patients often rely on subjective metrics such as word-of-mouth recommendations and online reviews and ratings on various platforms to evaluate the trustworthiness of a doctor. However, these metrics are prone to biases and inconsistencies, and patients may not have all the information to make an informed decision. To address this issue, the Doctors Trustworthiness Assessment project seeks to develop a comprehensive, reliable, and automated method for assessing the credibility of doctors accurately. The project aims to leverage advanced technologies such as machine learning to provide a trust score that reflects the trustworthiness of a doctor accurately. Patients can use this trust score along with other factors such as the doctor's medical qualifications, specialization, reviews from other patients, and any history of malpractice to make informed healthcare decisions. Moreover, the project aims to encourage doctors to maintain high standards of professionalism and ethical behaviour by providing them feedback on their trust scores. By creating a more transparent and trustworthy environment in the healthcare industry, the Doctors Trustworthiness Assessment project hopes to improve patient outcomes and help patients make informed healthcare decisions.

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 Keywords

Doctors Trustworthiness Assessment, Healthcare industry, Credibility of doctors, Trust score, Medical qualifications, Specialization, Reviews from patients, Professionalism, Patient outcomes.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial intelligence, Mobile applications, Users Perception, Users Experience, Data Security, Privacy, Efficiency, AI Trends, AI Algorithm, Chat Bots, AI-driven Technology

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Creative Commons Attribution 4.0 and The Open Definition

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This paper introduces MedVista, titled "A Companion For Medication Insight," a web platform designed to streamline access to accurate medication insights. Among its core features are the Homepage for medication searches, symptoSurf for symptom-driven suggestions, and Image Insight, which compares uploaded images with the dataset to provide relevant medicine information. MedVista leverages advanced technologies like machine learning and natural language processing to enhance user experience, foster health literacy, and facilitate informed healthcare decisions. By bridging user gaps with precise medical knowledge, MedVista significantly contributes to improved healthcare outcomes and empowers users with invaluable insights for informed decision-making.

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 Keywords

Medication Insights, SymptoSurf, Image Insight, Machine learning, Natural language Processing, User Experience.

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Creative Commons Attribution 4.0 and The Open Definition