Volume 12 | Issue 3 |

 Abstract

This project report presents a new approach, with the application of the storm water drainage system made by making use of pervious concrete for recharging of the groundwater table. Pervious concrete is a new type of concrete with high porosity, which is usually used for flatwork applications to allow water to pass through it, and by that, it reduces the volume of direct water run-off from a site and increases the quality of storm water. Due to the high flow rate of water through pervious concrete, rainfall can be captured and percolate into the ground, recharging groundwater, supporting sustainable construction, reducing stormwater runoff, and providing a solution for construction that is sensitive to environmental concerns. This study examines the advantages of using such material to maximize stormwater, minimize flooding, improve water filtration, effective drainage during monsoon and improved efficiency of pavement in Indore by constructing a storm-water drainage system. One of the major reasons for the deterioration of roads is rainwater. During rainfall, part of water flows on the ground surface and part of it percolates through soil mass until it reaches the groundwater below the water table. Due to the percolation of water in the pavement moisture content of soil increases which reduces the bearing capacity of the soil. Thus, the stability of the highway is reduced. Therefore, in this project report, we have shown the complete hydraulic and hydrological analysis for the design of the stormwater drainage system and the advantages of using pervious concrete in it.

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 Keywords

Stormwater, drainage, pervious concrete, porosity, bearing capacity, hydrologic and hydraulic analysis, filtration and percolation

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 Abstract

: In recent years, Artificial Intelligence (AI) has emerged as a transformative force in the field of medical diagnosis and imaging. Leveraging advanced machine learning algorithms and deep neural networks, AI systems have demonstrated remarkable capabilities in interpreting medical images, detecting abnormalities, and assisting healthcare professionals in making accurate diagnoses. However, the widespread adoption of AI in medicine also raises ethical and regulatory challenges, necessitating careful consideration of issues such as data privacy, algorithm bias, and accountability. As AI continues to evolve and integrate into clinical practice, collaborative efforts between AI developers, healthcare providers, regulators, and ethicists are essential to realize its full potential while ensuring patient safety and ethical integrity. With the offer assistance of Profound Learning (DL) algorithms, medical imaging innovation presently empowers restorative professionals to identify abnormalities and identify maladies with a higher level of exactness and speed than ever some time recently. This has contributed to critical changes in the exactness of diagnosis, the proficiency of treatment, and the in general quality of understanding care. AI- powered therapeutic imaging is trusted to be in the close future a significant improvement in symptomatic changes and applications that will bring considerable benefits for the medical specialists. Counterfeit insights (AI) procedures in later developments have appeared the potential to quicken the movement of conclusion and treatment of cardiovascular infections (CVDs), counting heart disappointment, hypertrophic cardiomyopathy, intrinsic heart illness and so on. AI has been demonstrated to apply well in CVD conclusion, upgrade adequacy of assistant apparatuses, malady stratification and writing, and result Breast mammograms for cancer location, Pap tests, colon cancer imaging, brain tumor imaging are utilized routinely to check individuals for signs of cancer or precancerous cells that can turn into dangerous tumors. In the last decade restorative professionals have created AI instruments to help screening tests for several sorts of cancer. Without question, fake insights (AI) is the most examined point nowadays in therapeutic imaging inquire about, both in demonstrative and restorative. For demonstrative imaging alone, the number of distributions on AI has expanded from almost 100-150 per year in 2007-2008 to 1000-1100 per year in 2017-2018. Analysts have connected AI to naturally recognizing complex designs in imaging information and giving quantitative appraisals of radiographic characteristics. In radiation oncology, AI has been connected on distinctive picture modalities that are utilized at diverse stages of the treatment. i.e. tumor depiction and treatment evaluation. Radiomics, the extraction of a expansive number of picture highlights from radiation pictures with a high-throughput approach, is one of the most prevalent inquire about subjects nowadays in restorative imaging inquire about. AI is the basic boosting control of handling gigantic number of therapeutic pictures and in this manner reveals illness characteristics that fall flat to be acknowledged by the bare eyes. The goals of this paper are to audit the history of AI in restorative imaging inquire about, the current part, the challenges require to be settled some time recently AI can be embraced broadly in the clinic, and the potential future

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 Keywords

Artificial Intelligence ,Deep Learning, Machine Learning, Medical Imaging, Radiomics

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 Abstract

Abstract: In the Totalitarian sphere, literature is categorised in a dystopian register that is built around a system that imposes values that are upside down. A fictitious pattern on the social-political structure is woven by Marin Preda. A literary work like Life as Prey (1977), which entered the memorialist pattern, indicated both the novelist's worldview and the origins of the fictitious text. A fresh viewpoint on the work is born out of the separation between the world and the I. A phase of the axiological perversion experienced by the dilemmatic creator is represented by the alienation. Literary works typically become chronotypes of the abandonment before a constrictive system of ideas, or parables of the tragism of the modern human. The literary tactics that range from the parodic return to history, the un-solemnization of the discourse, the capitalization of prosaism, to the extravagant mythologizing of the prosaic, manifest the upside-down perspective on the link between logos and existence. Fiction appears to transcend historical narratives in its relationship to reality by crafting a dystopian cosmos that reflects the confines of the human imagination. During a period when political discourse dominated cultural and literary discourse, leading to significant limitations, writers wavered between following societal norms and opting for internal exile as a means of maintaining their dignity, rebelling against authority, and withdrawing from the citadel. In this way, the 1960s and 1980s saw the manifestation of a response to topicality and, with it, a concern for the issues upsetting the existence of a person prepared to constantly relate to history, against the backdrop of some radical shifts in perspective in the daily political theory and praxis, with obvious implications for ethics and aesthetics

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Key Words: Ideological discourse, Chronotope, Totalitarianism, Tragism

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Rice cultivation with ducks possibly offers biological assistance ,and efficient control of weeds. Present research was conducted to trace the the viability of coordinating duck in rice cultivation for controlling weed pervasions and their effects on efficiency and economic output of the framework. Examination on variety of weeds showed that lush weeds (Echinochola colona, Echinochola crusgalli) and sedges (Cyperus difformis, Cyperus iria, Fimbristylis miliaceae) were predominant in rice during tillering stages, while broad leaved weeds (Ludwigia adscendens, Sphenoclea zeylanica) and aquatic weeds (Marsilia quadrifolia, Hydrilla verticillata) were abundant during dynamic tillering and panicle commencement phases of rice. For two years in a row, field research was done at the experimental farm of Bharath University to trace the impact of duck integration in the transplanted rice crop. The purpose of the experiment was to trace the impact of duck integration performed in three different scenarios: duck herding in puddled fields, duck herding in transplanted fields, and duck herding in both transplanted and puddled fields. The field study was set up using a split plot design with three sub treatments that were replicated three times. All of the treatments utilizing different duck integration techniques led to significantly higher grain and straw yields as well as corresponding reductions in weed metrics attribute to the interactions that result from herding ducks. Duck herding under all procedures involving diverse duck integration techniques dramatically boosted grain and straw yield while concurrently lowering weed characteristics. The interactions that result from herding ducks, the overall weed population was lowered by the combined effects of duck herding in cropped and puddled conditions, cono-weeding, and one-handed weeding, recording 5.77 and 5.67 per m2 during I and II season, respectively. Similarly crop DMP, grain yield and straw yield increased by 15.03 t ha-1, 4.34 t ha-1, and 7.29 t ha-1 during the first season, and 15.3 t ha-1, 4.88 t ha-1, 7.58 t ha-1 during the second season respectively due to duck integration in rice production

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 Keywords

: (Cono weeding, growing rice, duck herding, , grain yield, straw yield and weed control.)

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 Abstract

Modern multilingual customer care systems are in high demand due to the world's growing interconnectedness. This study examines how generative artificial intelligence (generative AI) can be used to solve the problems associated with delivering smooth and efficient customer support in a variety of linguistic environments. Our suggested system intends to transform consumer interactions by integrating advanced language models, such as contextual understanding and translation capabilities. This paper explains the architectural details of our all-inclusive multilingual assistance system and provides an overview of its features, advantages, and practical uses. The study sheds light on the paradigm shift in the dynamics of customer assistance and highlights the contribution of generative AI to the development of a service environment that is both linguistically inclusive and responsive to global needs.

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Language translation, Contextual understanding, Sentiment analysis

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This study explores emotion recognition in speech using Long Short-Term Memory (LSTM) networks on the Toronto Emotional Speech Set (TESS) dataset. Mel-frequency cepstral coefficients (MFCC) features are extracted, and an LSTM model is trained with a specific architecture, including Rectified Linear Unit (ReLU) and Linear activation functions in dense layers to get the membership of an audio sample in all the 7 labels and also compare them.The compiled model, utilizing mean squared error as the loss function and the Adam optimizer, achieves a training accuracy of 99% and a validation accuracy of 100%. Notably, our approach includes feature membership analysis, providing insights into the contribution of individual features to each emotion label.This comprehensive analysis demonstrates the efficacy of the proposed LSTM architecture in accurately identifying emotional states in speech, while the feature membership analysis adds a nuanced layer of interpretability to the model's predictions. The success of our approach suggests potential applications in emotion-aware technologies and interactive systems.

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 Keywords

Speech Emotion Recognition, Emotive Speech dataset, Audio data Visualization, MelFrequency Cepstral Coefficients, Feature Extraction, Long-Short Term Memory Neural Network, Emotion Classification, One Hot Encoding, Loss and accuracy matrices, Prediction Probabilities, Emotion identification, Virtual Assistants, Mental Health Screening, Computer-Human interaction

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 Abstract

This essay presents the current innovation, which pertains to smart sole shoes for correcting human posture, consists of a microprocessor inside the sole compartment and a sole with an upper and lower sole. The sole of the shoe may have a vibrator and several weight pressure sensors positioned inside. As a result, while the user is wearing the shoe, the multiple pressure sensors continually gather pressure from all of the weight pressure locations on each foot. The vibrator alerts the user that they are exerting extra pressure on a specific foot when the pressure stays above the threshold value for a predetermined amount of time.

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Arduino ESP-32, Pressure Sensors, Vibrators, Smart Sole, Posture Correction.

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Fossil fuels are currently the primary source of energy needed by the planet. The hunt for renewable, less harmful energy sources has been fueled by the world's rapidly increasing need for energy and the carbon dioxide emissions that come with using fossil fuels. Among them is regarded as ethanol. It is really regarded as one of the best biofuels for transportation since it can be mixed with gasoline or burnt straight to increase fuel combustion in cars, which lowers CO2 emissions and lowers atmospheric gasses. As a result, research has shifted to the creation of increasingly sophisticated technologies in order to achieve energy sustainability and reduce greenhouse gas emissions. These factors led to the development of two additional production techniques that concentrate on the fermentation of cellulose and hemicellulose mostly from second-generation agricultural wastes and third-generation algae. The facts on the possibilities and applications of producing bioethanol from first, second, and third generation feedstock have been critically analyzed and presented in this chapter.

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Ethanol, petrol

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Abstract This article explores the potential benefits of mindfulness-based treatments, acceptance and commitment therapy (ACT), compassion-focused therapy (CFT), and cognitive-behavioral therapy (CBT) for married couples seeking to improve their mental health and resilience. The usage of the therapies may help couples become more self-aware, self-compassionate, empathic, communicative, and problem-solving-capable. They may also assist people in developing coping mechanisms to deal with challenging emotions and circumstances. Yet, the effectiveness of these treatments will depend on a person's characteristics, such as their level of sadness or interpersonal problems, as well as their cultural background. In order to best serve each couple's needs and objectives, interventions should be customized. The efficacy of the therapy can be increased by collaboration in its creation and through continual evaluation and monitoring of the outcomes.

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Mindfulness-based interventions, cognitive-behavioral therapy, married couples, mental health, and resilience

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 Abstract

The Multiple Camera Network (MCN) paradigm revolutionizes visual data capture through strategically positioned interconnected cameras. Deployed in sectors like security, cinematography, and research, MCNs offer panoramic insights. The abstract explores vital MCN components, encompassing synchronization, data fusion, and real-time processing. It sheds light on applications like crowd monitoring, 3D reconstruction, and immersive video production. Despite challenges like calibration and computational needs, the grid-organized MCN excels in synchronized data capture. Surveillance benefits from PTZ and smart cameras, enhancing control and coordination. Object tracking in surveillance hinges on feature extraction and background subtraction, with increasing interest in video surveillance. Embracing edge computing and AI, MCNs gain on-the-fly analysis and predictive modeling. The abstract concludes, highlighting MCNs' adaptability and scalability, positioning them as pivotal in reshaping surveillance and imaging standards from security to entertainment.

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 Keywords

grsxgrx

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