Volume 13 | Issue 4

 Abstract

Insomnia is a primary cause of sleep interruptions. It is a frequent sleep problem in those who are suffering from depression. Antidepressants are routinely used to treat insomnia, although their efficacy is low. Materials and methods :- A cross-section observation study was performed to get appropriate management for insomnia . A total of 279 patients were recruited in this study. Data were collected through clinical assessments, patient-reported sleep patterns, medication adherence, and treatment outcomes. The study also analyzed the role of non-pharmacological interventions such as cognitive behavioral therapy (CBT-I), circadian rhythm-based therapies, and lifestyle modifications in improving sleep quality. Results :- Some of their techniques include integrating treatment with cognitive behavioural therapy, treating based on circadian rhythms, identifying a new mechanism via the the hormone orexin system, sleep-specific treatments, and environmental and lifestyle factors. Research suggests that using sedative-hypnotic drugs as a supplemental therapy for insomnia may diminish patient adherence to recommended dosages. These novel approaches have the potential to enhance both patient satisfaction and treatment outcomes for sleep disorders. hence this study, gives a clear review on antidepressants in treatment of insomnia providing valuable information for physician's, researchers, and policymakers. Conclusion :- This review gives clear insights into novel methods to antidepressant-assisted insomnia management. Emerging research on sleep interventions continues to explore innovative treatments to help individuals achieve restorative sleep. By rigorously analysing the influence of various drugs on sleep quality, side effects, and patient outcomes, this project will address crucial gaps in sleep medicine research. As ongoing research continues to explore innovative therapies, rigorous evaluation of drug efficacy, patient adherence, side effects, and treatment outcomes will be essential in closing critical gaps in sleep medicine. This study serves as a foundation for future research and clinical recommendations, providing useful guidance for physicians, researchers, and policymakers in optimizing the management of insomnia.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

CBT: - cognitive behavior therapy, REM: - Rapid Eye Movement. GABA: - Gamma-aminobutyric acid, 5HT - hydroxy tryptamine

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper suggests an interactive dashboard that uses deep learning methodologies to enhance the online classroom environment through student emotion analysis. The main challenge in digital learning is occluded or partially hidden facial data, for which CNNs and Haar cascade come into play. Haar cascade is responsible for facial feature detection and extraction by which CNNs can classify emotions. Real-time emotion prediction is visualized on the interactive dashboard, combining inputs such as the subject, course, and instructor. Analytics on the dashboards are represented in charts and graphs and help inform teachers about student responses and how they should tweak their teaching to better engage students. It also assists in identifying students who may require extra support. The system was validated on the CK+ dataset and was found to be highly accurate in classifying emotions such as happiness, sadness, and surprise. Other than the occasional instances in which students' faces were not visible, the system proved to be robust and consistent. With real-time emotion-based feedback, this dashboard has transformed the dynamics of a virtual classroom into one that fosters adaptive and engaging learning, promoting the optimum achievement of educational objectives.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Convolutional Neural Networks (CNN), emotion analysis, online learning, interactive dashboard, facial expression recognition, student engagement, deep learning, real-time analytics, virtual classroom, dataset, teaching strategies, personalized learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research presents an IoT-based safety and alert system utilizing the ESP32 microcontroller to enhance vehicular safety and real-time monitoring. The system integrates various sensors to detect environmental and driver-related conditions. An alcohol sensor detects intoxication, while a DHT11 sensor monitors temperature and humidity. Ultrasonic and IR sensors enable obstacle and proximity detection, and a flame sensor alerts for fire hazards. Mobility is handled via BO wheels and DC motors controlled by a motor driver, with a buzzer providing instant audio alerts. A vision-based module detects driver drowsiness, triggering a Telegram chatbot alert with an audio message: "You are in drowsiness." In case of accidents, the system notifies emergency services through the chatbot. Critically, when any unsafe condition--such as alcohol consumption, drowsiness, or accident--is detected, the vehicle stops automatically to prevent further risk. This system demonstrates a robust combination of embedded systems, automation, and wireless communication for improved road safety and driver assistance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ESP 32 microcontroller, Road Safety, Accident Prevention, Drowsiness Detection, Alcohol Detection, Automatic Braking System, Emergency Alert System

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AatmBodh Ev Tatvabodh Sadhna Ka Swaroop Ev Prakriya - Ek Vivechan

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AatmBodh Ev Tatvabodh Sadhna Ka Swaroop Ev Prakriya - Ek Vivechan

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The stock market plays a crucial role in a country's financial growth, but it is also highly dynamic and unpredictable. It can be influenced rapidly by various factors such as political developments, investor sentiment, media reports, company restructuring, and growth strategies. Every trading day, thousands of investors participate in the stock market--some gain profits, while others incur losses. However, predicting these gains or losses on any given day remains a significant challenge. This research presents a web-based application developed for predicting stock market trends through the implementation of machine learning techniques. The system integrates both historical stock data and real-time data obtained from APIs, and employs three robust predictive models--ARIMA (Auto Regressive Integrated Moving Average), LSTM (Long Short-Term Memory), and Linear Regression. These models are utilized to forecast the closing price for the next trading day, as well as to provide projections for the subsequent seven days. By analyzing historical patterns and trends in the data, the models aim to extrapolate future price movements with improved precision. The integration of numerical data analysis significantly enhances the overall accuracy and reliability of the stock price predictions generated by the system.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Market, ARIMA, LSTM, Linear Regression, Web Interface

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's online shopping world, many companies use AI powered chatbots to help customers. These chatbots are computer programs that talk to people like a human through text or voice. This research paper talks about how these chatbots are changing the shopping experience in online shopping. The study's primary objective is to understand if customers feel satisfied when they use these chatbots and if chatbots really help them while shopping. The paper starts with the background of AI and chatbot use in online stores. Then, it looks at past studies done by other researchers on this topic. Many of these studies say that chatbots help users by giving fast replies, helping them find products and giving 24/7 support. But there are also some problems. Sometimes, customers feel that chatbots are not personal and they don't always understand what the user wants. This research also explains the gap between what we know and what still needs to be explored. It shows the objectives, methods used and presents results based on collected data and past sources. The discussion tells how these findings match or differ from earlier research. The final part gives a conclusion and says that while chatbots are useful and improve customer experience in many ways, there is still a need to make them more human-like and smart. The paper also gives suggestions to improve chatbot use in online shopping.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Natural Language Processing, Frequently Asked Questions, User Interface, User Experience.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Medicinal plants have played an essential role in healthcare systems across the world for centuries, serving as the foundation of both traditional and modern medicine.(1) Among these, Curcuma longa (commonly known as turmeric) and Carica papaya (papaya) have emerged as two highly regarded botanicals due to their rich phytochemical profiles and broad spectrum of pharmacological activities. This review explores the therapeutic potential of these two plants by examining their phytochemical constituents, mechanisms of action, and evidence-based pharmacological properties. The aim is to bridge the gap between traditional knowledge and scientific validation, providing a comprehensive understanding of their medicinal relevance. Curcuma longa, a rhizomatous herb of the Zingiberaceae family, is native to South and Southeast Asia and is widely cultivated for its culinary, cosmetic, and medicinal properties. Its key bioactive constituent, curcumin, along with demethoxycurcumin and bisdemethoxycurcumin, are collectively referred to as curcuminoids. These compounds have been extensively studied for their potent anti-inflammatory, antioxidant, antimicrobial, and anticancer effects. Curcumin, in particular, acts by inhibiting nuclear factor-kappa B (NF-?B), downregulating pro-inflammatory cytokines, and scavenging reactive oxygen species (ROS).(2) Despite its promising therapeutic efficacy, curcumin's clinical utility is limited by its low bioavailability, leading to research into improved delivery systems and synthetic analogues.(3) Carica papaya, a fast-growing tropical plant belonging to the Caricaceae family, is commonly cultivated in tropical and subtropical regions for its nutritional and medicinal value. Various parts of the plant--including the fruit, seeds, leaves, and latex--have been used in traditional medicine to treat conditions such as digestive issues, fever, skin infections, and inflammatory diseases.(4) The primary bioactive compounds in papaya include papain, chymopapain, carpaine, flavonoids (such as quercetin and kaempferol), phenolic acids, and carotenoids (like lycopene and ?-carotene). These compounds exert antioxidant, antiviral, immunomodulatory, antidiabetic, and anticancer effects through multiple mechanisms, including free radical scavenging, inhibition of lipid peroxidation, and modulation of immune responses.(5) This review compares the mechanisms of action of the antioxidant properties of both plants. Curcuma longa primarily enhances the body's endogenous antioxidant defence by upregulating enzymes like superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPx), and by chelating metal ions that catalyse free radical production. In contrast, Carica papaya offers a wide range of direct antioxidant activities through its vitamins and carotenoids, which protect cellular structures such as DNA, lipids, and proteins from oxidative stress. The identification and authentication of both plants are critical in ensuring quality control in medicinal applications. Techniques such as morphological and microscopic analysis, phytochemical screening, and molecular authentication

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Curcumin, Carica papaya, morphological, microscopic, phytochemical, antioxidant, Medicinal.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

- Traditional manual sorting in industrial settings often suffers from inefficiency, high labor requirements, and error-proneness. This study introduces an automated sorting system utilizing a PLC with integrated metal detection to tackle these issues. The system's core is an S-TRONiX 8 I/O PLC, offering a dependable foundation for effective process management. A LX 101 color sensor is incorporated for product sorting based on color, while a metal detector sensor differentiates between metallic and non-metallic items. This combined sorting approach enhances accuracy in handling diverse materials across production lines.The setup includes three actuators driven by RDS 3115MG servo motors, which accurately direct objects to specific bins. A 30 RPM DC geared motor powers the conveyor system, ensuring steady object transport. An L298N motor drive efficiently controls motor functions, and an SMPS provides consistent power to the system's electrical components. NO/NC push buttons allow for secure manual control of the sorting process.The system follows a structured control protocol: objects on the conveyor are first assessed by the metal sensor. Metallic items are redirected to a dedicated container, while non-metallic objects move on to color detection. The LX 101 sensor identifies object colors, triggering the appropriate actuator to sort products into designated bins. This streamlined approach boosts sorting efficiency, minimizes human involvement, and improves production precision.By integrating metal detection and color sorting into a single framework, the proposed system shows marked improvements over conventional sorting methods. It is particularly suited for industries requiring precise material segregation, such as recycling facilities, food processing plants, and packaging sectors. Future enhancements may incorporate advanced sensors for size or weight-based sorting, further expanding the system's adaptability in industrial applications.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

PLC, Color Sensor, Automation, Servo Motors, Sorting System, Metal

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Air quality prediction using machine learning is a project that aims to provide accurate and reliable predictions of air quality in different regions. The project leverages advanced machine learning algorithms to analyze historical data on air quality and predict air quality index. By accurately predicting air quality levels, the project can help individuals and authorities take preventive measures to reduce exposure to pollutants and improve public health. The project utilizes various tools and technologies, including Python and Scikit-Learn to develop a robust and reliable system. Overall, this project has significant potential to positively impact public health and the environment, improving air quality and reducing the negative effects of pollution.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

KNN, Classifiers, Regressors, Randomforest

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The neonatal period is the most vulnerable time for a child's survival, and appropriate newborn care practices are essential to reduce morbidity and mortality. Postnatal mothers play a pivotal role in ensuring the well-being of their newborns. However, knowledge gaps related to newborn care practices persist, particularly in low- and middle-income countries.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Newborn care, Postnatal mothers, Knowledge.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In contemporary criminal investigations, forensic science has emerged as a crucial component, providing scientific precision, impartiality, and dependability in legal proceedings. This study examines the acceptance of forensic evidence in Indian courts, drawing comparisons with international benchmarks in the United States, United Kingdom, Germany, and Australia. Despite the widespread use of forensic science in Indian courtrooms, its efficacy is often compromised by the lack of a uniform admissibility framework, inadequate forensic infrastructure, and judicial inconsistencies. A comparative evaluation of global forensic legislation underscores India's requirement for structured forensic reforms. Nations such as the U.S. employ scientific admissibility criteria (Daubert Test), while the U.K. enforces rigorous forensic regulation through autonomous oversight. Germany prioritizes judicial forensic education to ensure scientific accuracy in court rulings, and Australia maintains a nationally certified forensic framework. In contrast, India lacks a National Forensic Science Regulator, standardized forensic protocols, and formal judicial forensic training, resulting in delayed forensic reporting, expert prejudice, and discrepancies in forensic interpretation. This research proposes critical reforms to enhance India's forensic laws, including the creation of a National Forensic Science Regulator, adoption of a scientific admissibility test, standardization of forensic procedures, and expansion of judicial forensic training initiatives. Additionally, progress in AI-driven forensic analysis, digital forensics, and block chain technology offers new avenues for improving forensic accuracy and evidence security. The study concludes that while forensic science in India is progressing, legal modernization, scientific validation, and regulatory supervision are vital for ensuring forensic reliability in courts. Bolstering forensic laws will improve the credibility of forensic evidence, reduce wrongful convictions, and uphold the principles of justice with greater scientific rigor.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Forensic science, Digital & AI Revolution, criminal justice, DNA evidences, Narco-Analysis & Polygraph Tests, Fingerprint & Ballistics Evidence, admissibility of forensic evidence, Digital Forensics and Cyber Evidence

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research highlights the potential of MAML in developing intelligent image classification systems that can perform reliably in data-constrained environments. The findings contribute to the growing body of work in meta-learning and its practical applicability in computer vision, especially in domains like medical imaging, wildlife monitoring, and security surveillance where annotated data is often limited.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image classification, Few-shot learning, MAML, Meta learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Adler's perspective on personality was broad and open; he saw the person as a whole, unified organism and underlined the need for the individual's relationship with the rest of society. This study thoroughly examines Adlerian theory compared to psychoanalytic, cognitive-behavioural, and humanistic methods, showing its clinical uses using thorough case studies and empirical research. The current study offers a critical debate meant to improve the knowledge of Adlerian psychotherapy using systematic and narrative review techniques. Adlerian psychotherapy is still a relevant and valuable therapeutic tool for dealing with the need for social relationships, human purpose, and personal development. Modern critiques of its theory underline the need to know the person's lifestyle and the social setting in which they function. Adlerian therapy keeps evolving, including contemporary methods, while keeping its fundamental values of support and community spirit. Adlerian psychotherapy provides a complete framework that tackles personal problems and the larger social forces in play. Future studies should investigate its use in various cultural settings and its integration with other therapeutic approaches to guarantee its adaptation to the evolving scene of mental health treatment. In the end, Adlerian psychotherapy is a monument to the ongoing relevance of Alfred Adler's observations on human conduct and interpersonal interactions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Adlerian psychotherapy, social interest, lifestyle, cognitive-behavioural therapy, psychoanalysis, clinical case studies, integrative approaches.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT The COVID-19 pandemic and the subsequent lockdown imposed by the government in 2020-2021 also impacted the peafowl's ecology and behavior. This study aimed to compare the population and distribution of Indian peafowl in a specific site in Bharatpur, Rajasthan. This site is Village, Saman-Penghore in Tehsil Kumher, Bharatpur city, from September 2020 to August 2023. The results showed that the peafowl population increased significantly during the lockdown period at this site. The main reasons for the population increase and distribution expansion were reduced human disturbance, increased food availability, decreased poaching, and improved habitat quality. But after the Lockdown (in 2021-22,2022-23), there was a progressive decrease in the population.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

KEYWORDS: COVID-19, Distribution, Pavo cristatus, population, Bharatpur city

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Rastriya Siksha Niti 2020 Me Varnit Parathmik Siksha Ke Pravdhano Ke Prati Sikshako Me Jagrukata Ka Adhayan

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rastriya Siksha Niti 2020 Me Varnit Parathmik Siksha Ke Pravdhano Ke Prati Sikshako Me Jagrukata Ka Adhayan

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid evolution of technology has led to a growing demand for personalized, efficient learning solutions. In response, this project proposes an AI-Based Learning Management System (AI-LMS) that caters to three distinct user profiles: students or learners, teachers, and hiring managers. The system's primary feature is its ability to predict and generate a personalized learning roadmap for a student based on the subject they enter and the time they are willing to dedicate to learning. The AI-LMS optimizes learning by analyzing the input subject and time constraints to produce a three-step learning path, helping students achieve their goals within the given time frame.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-Based Learning, (LMS) Learning Management System, Personalized Learning Roadmap, Roadmap Prediction, Roadmap Generator, Time-Specific Learning, Student Profile, Teacher Supervision, Recruiter Access, User Authentication, Dynamic Learning Updates

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

By monitoring trains and spotting track items, this project seeks to create an automated railway gate control system improving safety. The system uses an Arduino Uno as the core controller interfaced with a set of IR sensors to detect an oncoming train. The technology turns on servo motors to automatically close the railway gate when a train is spotted; a red signal light is lit to stop the train. Placed next to the tracks, extra sets of IR sensors identify any objects or barriers that put out a buzzer to notify the nearby personally for prompt intervention and automatically change the signal to red to avoid risk. By use of efficient automation, this technology lowers human error, guarantees safe passage, and prevents accidents, hence enhancing railway safety.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Railway Crossing System with Automated Gate Control and Object Monitoring

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper is a study of Stoicism, Code Hero and Epic Battle in Ernest Hemingway's celebrated novel The Old Man and the Sea published in the year 1952. The study is based on the argument that Santiago, the protagonist in Hemingway's The Old Man and the Sea represents Hemingway's concept of stoicism and code hero. The study examines the trials and tribulations of Santiago and confirms the Hemingway's concept of a masculine hero who can be destroyed but cannot be defeated.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: stoicism, code hero, epic battle, argument, protagonist, vision

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Kerala's film society movement, spanning six decades, wove art and activism into a vibrant cinematic tapestry, transforming Malayalam cinema and joining global film debates. This study traces its path through three eras, revealing how cinema became a communal force amid tensions of taste and access. In the 1960s and 1970s, societies like Chitralekha sparked a love for world films, fostering the Malayalam New Wave with works like Swayamvaram, yet faced claims of urban elitism. The 1980s saw collectives such as Odessa carry political tales like Amma Ariyan to villages, redefining cinema as a call for justice, though debates over artistry's role simmered. By the 2000s, festivals like IFFK and digital platforms like M Sone revived cinephilia, showcasing Ee.Ma.Yau and nurturing bold voices, but new divides through passes and connectivity persisted. Drawing on Pierre Bourdieu's taste framework, archival records from India's film vaults, and voices of activists and festival goers, the research shows cinema's power to unite and challenge. Kerala's story echoes global cinephilia, from Susan Sontag's theater reverence to Third Cinema's revolt, offering a postcolonial lens on film's social role. Its resilience, adapting from reels to streams, highlights a model for cultural survival, yet gaps in rural reach and women's roles urge further study. For scholars of film and culture, this saga probes how cinema bridges local lives and universal questions, pointing to new paths in digital access, gender, and global comparisons.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Film Society, Malayalam Cinema, Cinephilia, Film Festival, Aesthetics, Activism

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The dual impact of dams and reservoirs, acknowledging their benefits in flood control, water supply and energy generation while emphasizing their significant negative effects on the environment and communities. This study seeks to establish a methodological framework for assessing, predicting and mitigating these adverse impacts, with a focus on environmental preservation and sustainable alternatives for affected communities. The negative consequences include environmental degradation, habitat destruction, altered ecosystems and community displacement leading to social upheaval and livelihood losses. The study underscores the importance of sustainable and inclusive planning on environmental aspects and socio-economic, highlighting long-term challenges like shifting cultivation, deforestation and spatial advocacy for comprehensive approaches integrating sustainable land use practices and community-focused development strategies and provide insight to planners to draw the best mitigation measures to cope with the long-term post-effect of dam towards the environment and people.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dam catchment, Environmental sustainability, Displaced communities, Shifting cultivation, Inclusive planning.

  License

Creative Commons Attribution 4.0 and The Open Definition