Union Graduate College

ABSTRACT In the modern age of digital security, conventional door lock systems are creasingly susceptible to breaches. This paper proposes a robust, multi-factor door lock system that integrates fingerprint recognition, facial detection, and a PIN-based unlocking mechanism using a Raspberry Pi microcontroller. It enhances security by requiring three authentication methods before granting access. The system incorporates a fingerprint sensor via UART, a USB-connected webcam for facial recognition, and a keypad for PIN entry. A servo motor acts as the locking mechanism, controlled through GPIO pins of the Raspberry Pi. By combining biometric, visual, and numeric credentials, this system mitigates the weaknesses of single-layer authentication methods. Python scripts and OpenCV libraries are employed for facial recognition, while fingerprint templates are stored in a secure database. The system is energy-efficient, cost-effective, and can be integrated into existing home automation setups. The solution addresses key concerns office security, offering both reliability and scalability. This project thus presents a feasible alternative to expensive commercial smart lock systems, offering a customizable and user-friendly experience. Keywords: Raspberry Pi, Fingerprint Sensor, Webcam, Keyboard

ABSTRACT In the rapidly growing domain of wireless communication, data security has emerged as a critical requirement, especially in resource-constrained embedded systems. This paper proposes a secure wireless communication system based on ZigBee technology and Advanced Encryption Standard (AES), implemented using Arduino microcontrollers. The system comprises a transmitter that accepts data via a keyboard, encrypts it using AES-128, and transmits it wirelessly via ZigBee. The receiver decrypts the data and displays it on an LCD. Leveraging ZigBee’s low-power and low-data-rate characteristics, the design ensures secure, efficient, and scalable communication suitable for applications such as home automation, military systems, and industrial control. The integration of AES encryption ensures end-to-end data confidentiality without significantly impacting transmission speed or energy consumption. Performance evaluation confirms the system’s viability for Internet of Things (IoT) applications demanding both security and efficiency. Keywords: Wireless Communication, ZigBee Protocol, AES-128 Encryption, Arduino Microcontroller, Secure Data Transmission, End-to-End Encryption.

Prevalence of stress among the student population constitutes a significant concern that impinges upon their academic performance and overall psychological well-being. This research endeavour is centered on the examination of student stress levels through the application of machine learning methodologies. The dataset encompasses variables including student academic and personal details along with Stress levels which are classified into three distinct categories: low, moderate, and high, predicated on these various factors. The machine learning models employed in this study include Support Vector Machines (SVM), and Decision Trees, Artificial Neural Networks (ANN), Ada Boosting each chosen for their capacity to discern patterns and correlations within the dataset. Decision Tree is particularly adept at capturing intricate relationships and yields a high degree of accuracy. The results underscore that the number of study hours, duration of sleep, and GPA emerge as the most significant influences in predicting the stress level of students.

Agriculture is a major human economic activity. India is an agricultural country and agriculture consumes a lot of water. 60% of the total clean and useful water is used for irrigation, whether it is water from canals and rivers or groundwater. Due to excessive consumption of water, a crisis may arise in future, so water conservation is very important. From time to time, various programs have been implemented by the Indian government as well as Haryana government to conserve water, so that the economic condition of the farmer and the fertility of the land remain forever. If we see, according to the production in India, then the names of Haryana, Punjab and Uttar Pradesh of North India comes first, here we are talking about Haryana state. Haryana is a landlocked state in the northwestern part of India, which is situated on the banks of Yamuna River. The main crops here are wheat, rice, sugarcane, cotton, barley, corn, etc. The crops here are mainly sown Rabi and Kharif, in which wheat and rice are the main crops. It is believed about 68% of Haryana's population is engaged in agriculture. Haryana comes under Trans Gangetic plains and is placed under Agro Climatic Zone VI (1888-89). It is a fertile alluvial plain drained by the Ganga River and its tributaries. The average temperature of July month varies from 26°C- 41°C and that of January month 9°C-24°C.The amount of annual rainfall lies between 100 cm and 200 cm. The region has vast potential of groundwater and surface runoff in the form of perennial rivers which is utilized for irrigation through tube wells, canals and wells. Rice, maize, millets in Kharif season; wheat, gram, barley, peas, mustard and potato in Rabi season are important crops.

Analysis of electroencephalographic (EEG) data has shown to be a useful tool in the fields of Brain-computer interfaces (BCIs), and even business. Recently, deep learning architectures have been implemented, particularly in the interpretation of EEG readings and the knowledge it may impart about mental processes, thanks to the availability of huge EEG data sets and advancements in deep learning. In order to find useful data for brain classification and neuroimaging, Various Analytical Techniques utilized in EEG investigations have turned to machine learning. This research study combines sparse auto-encoders (SAEs) with a post-processing system, which is comprised of a linear system model dependent on the Particle Swarm Optimization (PSO) method as a unique data categorization framework. To boost classification precision, it is to prune datasets of superfluous characteristics. The Q-Learning method is used to built on reinforcement learning to reduce the overall number of features and have obtained the resulting accuracy. Evidence of this strategy leading to better classification performance is shown by experiments on both simulated and actual data. The PSO method provides a metaheuristic strategy for estimating the linear model's parameters. Using publicly available datasets, the suggested methodology is verified; When contrasted to current best practices, the results are favorable. With some adjustments to the input characteristics, hidden neurons, and output classes, the system may be utilized to address any data categorization problem.

In 2008, a Position Statement of the Society of University Surgeons (SUS) recommended the creation of institutional surgical innovation committees (SICs) to ensure appropriate oversight of surgical innovations. The purpose of this study was to determine the level of awareness of the position statement, and how innovations are handled in academic departments of surgery. An electronic survey was designed to determine the level of awareness of the SUS recommendations among members of the Society of Surgical Chairs; the existence and characteristics of SICs; and alternative means of oversight of surgical innovations. The survey was distributed to 150 persons, and 65 (43%) surveys were returned; 84% reported their institution promoted innovative surgery as a strength, but 55% were unaware of the SUS recommendations; 23% reported that their institution has an SIC, and 20% said their institution has discussed or plans an SIC. Existing SICs have a median of 7 members; 57% reviewed 3 or fewer procedures in the prior year; and only 7% reviewed 10 or more. The majority of respondents reported alternative mechanisms of oversight, including morbidity/mortality conferences (88%), peer review (77%), and outcomes registries (51%). A minority of Surgery Department Chairs is aware of the SUS Position Statement. Although most reported surgical innovation was an institutional strength, only 23% had an SIC and most rely on other mechanisms of oversight. It is unclear whether academic surgical departments are committed to providing education and awareness of the appropriate development and implementation of surgical innovations.

A decade ago some members of the American Society for Bioethics and the Humanities (ASBH) concluded that the society's reluctance to develop a code of professional ethics, although a tolerable anom...

Abstract Critically reflecting upon the role of and integrative function that relocalisation of agri-food plays in the development of what we call rural and regional ‘webs’ of interconnection, this chapter revisits two regional case studies in Devon and Shetland, UK. Exploring the challenges and continuities in the unfolding of the rural web, we pay particular attention to the role that agri-food initiatives play in mobilising distinctive rural and regional development processes. Although we point in both cases to the marginalisation of agri-food and its potential centrality in rural development, it is clear that this fails to disappear completely. The trends in these two rural regions, at either ends of the UK archipelago, suggest that the combinational effects of declines in multi-functional agri-food support, on the one hand, and a neo-liberalised retraction of non-agricultural rural development support on the other, are providing a potential and chaotic new governance squeeze which is likely to severely reduce the massive but latent adaptive capacity embedded in the rural eco-economy. Indeed, a more multi-functional governance and policy-based approach, based upon creating conditions for the eco-economic rural web to flourish needs to find ways of harmonising different aspects of the post-carbon landscape such that its various segments (energy, tourism, agriculture, creative industries, etc.), can work in synergy with one another. To conclude, we argue that such fragmented and competing conditions as those revealed in both case study areas are unlikely to be sufficiently capable of meeting the new national and global demands for food security which have risen up the political agenda since our earlier phases of field work.

Recent research suggests that HIV transmission and acquisition may increase with the use of some forms of hormonal contraception. Current data are not conclusive, but should it be determined that use of hormonal contraception can promote HIV spread, one consequence will be a competition between two important public health goals. The laudable goals of preventing HIV transmission and reducing rates of unintended pregnancy, particularly important in developing regions of the world like sub-Saharan Africa, will be in conflict. In this article we examine the different challenges raised by these competing goals and explore the broad range of factors at play using the six-part ethical framework developed by Baum et al . for managing ethical challenges in public health practice. We conclude that given the array of considerations required prior to restriction of hormonal contraceptive methods in resource-poor regions of the world, such restrictions should not be imposed, even if it were proven that some of these methods could exacerbate the spread of HIV among at-risk individuals. Of the estimated 33 million people living with HIV/AIDS worldwide, 16 million are women, and infection rates are increasing in women even as the epidemic stabilises globally.1 The countries with the highest rates of HIV also have low rates of contraception use and thus high rates of unintended pregnancy.2 Improving family planning services in these countries has been a key public health goal, as preventing unintended pregnancy reduces maternal and child mortality, reduces rates of mother-to-child (vertical) transmission of HIV, reduces poverty and improves educational and gender equity. Until recently, researchers and policymakers have often overlooked the impact of pregnancy on HIV prevention research and practice. Due to a number of biological and socioeconomic factors, current HIV prevention tools – abstinence, male or female condoms, male circumcision and monogamy – are inaccessible …