Volume 12 | Issue 12 |

 Abstract

The physiological parameters along with cell morphology and morphometry are useful for determining the health or general condition of birds and its environment. So, this study was conducted to determine the hematological and cytomorphometric parameters of three avian species; spotted munia, baya weaver, and redheaded bunting (N = 9 adult male birds/ species). For the hematology and erythrocyte cytomorphometry blood sample was drawn from each bird at sunrise time. We found that, the number of heterophils and body weight significantly differed among the three bird species. MCHC (Mean corpuscular hemoglobin Concentration) and H/L ratio were higher whereas lymphocyte count was lower in redheaded bunting compared to the other two species. Eosinophil count and erythrocyte's N/C area ratio (erythrocyte nucleus area and erythrocyte cytoplasm area ratio) were higher in baya weaver relative to redheaded bunting. The erythrocyte's nuclear area, body temperature, and hemoglobin % were significantly different in baya weaver than the other two species. Spotted munia exhibited a higher blood glucose concentration than redheaded bunting and baya weaver. No significant differences were observed in TLC (Total Leucocyte count), TEC (Total erythrocyte count), MCV (Mean corpuscular volume), MCH (Mean corpuscular hemoglobin), erythrocyte elongation ratio, erythrocyte cell area, basophils, monocytes, hematocrit %, and testicular volume. These results indicate the physiology, immunity, and health status along with baseline values about hematological, physiological, and cytomorphometrical parameters of three species; during the spring season when these birds were in the pre-breeding or non-breeding phase.

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 Keywords

Cytomorphometry, Hematology, H/L ratio, Immunity, Songbirds, Spring Season

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According to Richard Feynman "The next great era of human intelligence awakening may create a methodology for understanding the qualitative content of equations". However, he did not say how this goal could be achieved. In this paper, this goal was achieved by adopting the fundamental ideas of Descartes' scientific philosophy. That is, the idea that from the very beginning the equation of algebra and arithmetic was taken as the basis of the theory of thought. Then, when the problems of geometry, kinematics, physics are solved...And so that on this way the possibilities of the method of separation of variables and the method of abolition of variables were correctly used. The results which could be obtained on this way just turned out to be the results inherent for quantum geometry, quantum kinematics, quantum physics.... That is results on the basis of which it was really possible to put in order intellectual achievements of mankind.

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 Keywords

Algebra and Arithmetic , Quantum kinematics, Quantum physics

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The development of a road-following and collision-avoidance system uses the Jetson Nano-powered JetBot. JetBot is an open-source robot platform designed for learning and experimentation in robotics and AI, equipped with various sensors and cameras to facilitate autonomous navigation. This project focuses on developing a robust system for autonomous vehicles that can effectively follow roads and avoid collisions. The system integrates road detection with real-time obstacle avoidance using advanced machine learning and sensor technologies such as computer vision, LiDAR, and ultrasonic sensors. A convolutional neural network (CNN) identifies lane markings and road boundaries for accurate road following, while reinforcement learning and path planning algorithms ensure proactive collision avoidance. Simulations and real-world tests demonstrate significant improvements in navigation reliability across diverse environments, advancing the safety and efficiency of autonomous driving technologies. This project aims to develop an integrated system for autonomous vehicles focusing on road following and collision avoidance. Key components include: 1. Data Collection and Preprocessing: Gather diverse datasets of road images, LiDAR and ultrasonic data. 2. Road Following System: Train a CNN for lane and boundary detection. 3. Collision Avoidance System: Implement reinforcement learning and path planning for obstacle avoidance. 4. Sensor Fusion: Integrate data from cameras, LiDAR and ultrasonic for situational awareness. 5. Simulation and Testing: Validate system performance through simulations and real-world testing. 6. Optimization: Refine algorithms and parameters based on testing results. Finally, the outcome of this project is to Integrate the Road Following and Collision Avoidance models to allow Jetbot to autonomously work with an average speed while simultaneously avoiding collisions with obstacles. Furthermore, provide smooth system-to-system communication for effective operation and real-time decision-making. Use thorough testing procedures, including worst-case situations, to find any possible flaws. Use cutting-edge machine learning strategies to improve system performance over time. Create a cooperative atmosphere that promotes creativity and information exchange. Establishing a feedback loop with end users will also assist in quickly identifying and resolving any real-world issues. The Jetbot will handle the needs of dynamic and complicated settings by concentrating on these factors, which will lead to increased autonomy and safety.

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Road following, Collision Avoidance, Jetbot, Sensors, Convolutional Neural Network (CNN), Robot, Reinforcement learning

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 Abstract

This study has been undertaken to investigate the determinants of stock returns in Karachi Stock Exchange (KSE) using two assets pricing models the classical Capital Asset Pricing Model and Arbitrage Pricing Theory model. To test the CAPM market return is used, and macroeconomic variables are used to test the APT. The macroeconomic variables include inflation, oil prices, interest rate and exchange rate. For the very purpose monthly time series data has been arranged from Jan 2010 to Dec 2014. The analytical framework contains.

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Video Summarization, Deep Learning, Natural Language Processing, Machine Learning, OpenCV, YouTube Data API, Streamlit, Deep Neural Networks, Feature Extraction, Text Summarization, Automatic Speech Recognition, Extractive Summarization, Abstractive Summarization, Video Processing, Real-time Systems

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The Hindu Marriage Act of 1955 marks a significant legislative step in the regulation of matrimonial affairs among Hindus in India. This paper explores the evolution, framework, and contemporary issues surrounding Hindu marriages. Through the lens of landmark case laws, it analyses the application of the Act and its interpretation by Indian courts. The paper also discusses the implications of the Act on various aspects like divorce, maintenance, and succession, reflecting on the socio-legal impact on Indian society. Hindu marriage is a complex interplay of religious traditions, social norms, and legal reforms. From its origins as a sacramental union to its codification under the Hindu Marriage Act of 1955, Hindu marriage has evolved significantly, shaped by the forces of religion, colonialism, and modern legal thought. The Act itself marks a critical juncture in this evolution, bridging the gap between ancient customs and contemporary legal standards, and reflecting the ongoing transformation of Indian society. The Hindu Marriage Act, 1955, represents a significant milestone in the evolution of Hindu personal law. By codifying and reforming traditional practices, the Act has helped align Hindu marriage with modern legal principles of equality, justice, and individual rights. As Indian society continues to evolve, the Act will likely undergo further changes, reflecting the dynamic relationship between law and social norms.

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Marriage - Sacrament, Divorce, Void Marriage Voidable Marriage Restitution of Conjugal Rights, Bigamy, Customary Practices, Marriage Registration, Matrimonial Causes - Satpati -

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This paper dives into Decentralized Applications (DApps), powered by blockchain, where transparency, security, and user autonomy reign supreme. We navigate the intricate landscape of DApp development, uncovering challenges and opportunities amidst rapid evolution. From the bedrock of blockchain technology to the nitty-gritty of smart contracts and consensus mechanisms, we analyze it all. Discover existing frameworks, dissect design patterns, and understand how DApps scale and perform in the real world. The paper doesn't stop at theory. We showcase success stories across industries, explore regulatory hurdles, and delve into the future-proofing elements like decentralized storage and interoperability. Case studies reveal practical solutions to common problems, while community-driven governance models pave the way for continued growth.

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Decentralized Applications (DApps), Blockchain Technology, Smart Contracts, DApps Frameworks

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This paper presents a Voice Based Notice Board using an Android application, designed to simplify real-time notice management. The system leverages speech-to-text technology to convert voice commands into text, which is then displayed on a digital notice board. The Android app acts as a user-friendly interface, enabling seamless notice updates through wireless communication. This innovative solution is cost-effective, scalable, and accessible, making it suitable for educational institutions, offices, and public spaces. The implementation and testing demonstrate its efficiency, significantly reducing manual effort and improving communication

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Speech Recognition, Notice Board, Android Application, Wireless Communication, Real-Time Updates, Digital Display, Speech-to-Text Conversion.

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Due to machine learning progress in biomedical and healthcare communities, accurate study of medical data benefits early disease recognition, patient care and community services. When the quality of medical data is incomplete the exactness of study is reduced. Moreover, different regions exhibit unique appearances of certain regional diseases, which may result in weakening the prediction of disease outbreaks. In the proposed system, it provides machine learning algorithms for effective prediction of various disease occurrences in disease-frequent societies. It experiments the altered estimate models over real-life hospital data collected. To overcome the difficulty of incomplete data, it uses a latent factor model to rebuild the missing data. It experiments on a regional chronic illness of cerebral infarction. Using structured and unstructured data from hospital it uses Machine Learning algorithm. It predicts probable diseases by mining data sets. To the best of our knowledge in the area of medical big data analytics none of the existing work focused on both data types. Compared to several typical estimate algorithms, the calculation exactness of our proposed algorithm reaches 94.8% with a convergence speed which is faster than that of the machine learning disease risk prediction algorithm.

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 Keywords

Machine Learning, Deep Learning, CNN, Prediction, AI, Supervised, Analysis, Disease, Detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: The "Mobile App for Direct Market Access for Farmers" is intended to bridge the gap between farmers and potential buyers so that the products of agriculture are taken directly to consumers without any middleman intervention. This mobile application will help the farmer to directly get connected with the buyer, which includes wholesalers, retailers, and consumers. In return, the farmer can negotiate a price, showcase his product, and get real-time information regarding demand and market trends. The app also offers features such as logistics management, payment processing, and support for crop data analysis, which will help farmers make informed decisions and maximize their income. This solution is meant to improve the livelihoods of farmers and support sustainable agricultural practices by increasing transparency, reducing middlemen, and improving market access.

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 Keywords

Mobile Application ,Direct Market Access ,Agricultural Market ,Farmers.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition