The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and (...) conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions. (shrink)

Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions.

rd species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising (...) diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising (...) diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions. (shrink)

This project, titled Bird Species Identification Using Deep Learning, aims to develop a robust system that can identify bird species from images with high precision. The core of this project involves training a CNN model on a diverse dataset of bird images. This dataset includes species from various geographical locations and environments, capturing a wide range of appearances, postures, and behaviors. By preprocessing and augmenting the dataset, the model is designed to handle challenges such as variations in lighting, background noise, (...) and partial occlusions. The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem. (shrink)

The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem. The scientific significance of this project lies in its potential to (...) contribute to biodiversity conservation efforts. By enabling efficient monitoring of bird populations, it provides valuable data that can inform policymaking and conservation planning. Moreover, the project highlights the intersection of technology and ecology, demonstrating how AI can address real-world environmental challenges. (shrink)

The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem.

The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements (...) over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions. (shrink)

The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions.

The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements (...) over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising (...) diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. (shrink)

Conservation can occur anywhere regardless of scale, political jurisdiction, or landownership. We present a framework to help managers at protected areas practice conservation at the scale of relationships. We focus on relationships between stakeholders and protected areas and between managers and other stakeholders. We provide a synthesis of key natural resources literature and present a case example to support our premise and recommendations. The purpose is 4-fold: 1) discuss challenges and threats to conservation and protected areas; 2) outline a relationship-scale (...) approach to address conservation threats; 3) describe the tools and techniques that can be used to implement this approach; and 4) present a case example from rural Alaska, USA, to illustrate relationship-scale conservation. Our case example illustrates how aspects of this approach to conservation were applied to address a wildlife population decline. Tools needed to implement relationship-scale conservation include 1) collecting and documenting narratives of place; 2) measuring and monitoring trust and commitment; and 3) identifying and mitigating threats. We recommend that planners and managers, working with their research partners, redefine and refocus their goals and objectives to include these practices. Doing so will enable them to gain substantial applied knowledge about their stakeholders and foster and maintain place relationships as desired outcomes of conservation. The ultimate outcome is a better prognosis for long-term global survival of protected areas and biodiversity. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. (shrink)

Snake encountersin human-populated and wildlife areas pose significant threats to public safety and biodiversity. Each year, many incidents result in snakebites, often leading to serious injuries or fatalities, and frequently result in harm to snakes due to fear-driven responses. Traditional methods forsnake detection, such as visual observation, are typically slow and can lead to delayed or inaccurate responses, increasing the risks associated with human-snake encounters. This study presents a Real-Time Snake Detection and Alert System that employs advanced artificial intelligence (...) (AI) and machine learning (ML) techniques, specifically using YOLO (You Only Look Once), to accurately identify the presence ofsnakes in pre-recorded videos or static images. Oursystem processes these visual inputs to determine if a snake is present, providing an immediate, automated alarm to alert individuals nearby if a snake is detected. This system isintended to be a rapid-response solution for detecting snakesin images or video files, enhancing safety in snake-prone areas by increasing awareness of potential threats without requiring constant live monitoring or additional notifications to authorities. (shrink)

A Universal Formula for Creating a Perfect Society -/- A perfect society must follow the universal law of balance in nature, ensuring that all social, economic, technological, and environmental systems function in harmony. Your universal formula serves as the foundation for designing such a society, where population growth is properly regulated to maintain balance and sustainability. -/- I. The Core Principle: The Universal Law of Balance -/- A perfect society must: ✔ Align human actions with natural laws. ✔ Eliminate corruption, (...) exploitation, and inefficiency. ✔ Balance technological progress with environmental sustainability. ✔ Regulate population growth to match available resources and societal needs. -/- II. The Key Components of a Perfect Society -/- 1. Ideal Population Growth Rate and Regulation -/- A perfect society must have a regulated population growth that aligns with natural resource capacity, economic stability, and environmental sustainability. ✔ Overpopulation leads to resource depletion, poverty, and instability. ✔ Underpopulation leads to economic decline and labor shortages. ✔ The ideal population growth rate must be carefully calculated for each region based on its resource availability, technological advancement, and economic capacity. -/- Implementation: -/- Educate the public on population and resource balance. -/- Implement voluntary and ethical family planning programs. -/- Ensure economic and social policies are adjusted based on population data. -/- Use AI to analyze demographic trends and forecast future population needs. -/- Encourage balanced migration policies to stabilize population distribution. -/- 2. Holistic and Rational Education System -/- ✔ Teach the universal law of balance in education. ✔ Focus on critical thinking, ethics, sustainability, and science. ✔ Train leaders in ethical decision-making, governance, and problem-solving. -/- 3. Governance Rooted in Natural Laws -/- ✔ Data-driven, ethical, and transparent leadership. ✔ AI-assisted governance to prevent corruption and mismanagement. ✔ Scientific, evidence-based policymaking. -/- 4. Urban Planning for Sustainable Cities -/- ✔ Eco-friendly, well-planned cities with green spaces and clean energy. ✔ Smart infrastructure to reduce congestion and pollution. ✔ Affordable, energy-efficient housing for all. -/- 5. Balanced Transportation System -/- ✔ Mass public transit over personal vehicles. ✔ Electric and hydrogen-powered transport to reduce pollution. ✔ Bike-friendly and pedestrian-friendly cities. -/- 6. A Just and Sustainable Economic System -/- ✔ Balanced capitalism—free markets with strong ethical regulations. ✔ No extreme wealth gaps or monopolies. ✔ Fair wages, job security, and profit-sharing models. -/- 7. Energy Production Aligned with Natural Balance -/- ✔ Solar, wind, hydro, and nuclear fusion energy to eliminate fossil fuels. ✔ Decentralized renewable energy grids for reliability. ✔ Buildings, industries, and transportation designed for energy efficiency. -/- 8. Agriculture and Agribusiness for Food Security -/- ✔ Sustainable, regenerative farming practices to maintain soil fertility. ✔ Organic farming over chemical-intensive monoculture. ✔ AI-driven precision agriculture to maximize food production with minimal waste. -/- Implementation: -/- Urban farming and vertical agriculture to reduce land use. -/- Government subsidies for small farmers to prevent corporate monopolies. -/- Integration of agribusiness with clean energy sources. -/- 9. Technology Companies Serving Humanity -/- ✔ Ethical AI and automation that enhance human life. ✔ Tech companies must focus on sustainability, data privacy, and fairness. ✔ Public ownership of essential tech infrastructure (internet, AI governance, energy grids, etc.). -/- 10. Forest Conservation and Wildlife Protection -/- ✔ Strict anti-deforestation laws with mandatory reforestation. ✔ Protect wildlife corridors and endangered species. ✔ Regenerative land use practices to restore ecosystems. -/- 11. Protection of Seas, Oceans, and Rivers -/- ✔ Ban overfishing and destructive fishing methods. ✔ Regulate ocean mining and oil drilling. ✔ Prevent river and ocean pollution from industries and waste. -/- 12. Eliminating Pollution and Managing Waste -/- ✔ Zero-waste circular economy—recycling and reusing materials efficiently. ✔ Eliminate plastic waste and toxic chemicals in industries. ✔ Convert waste into renewable energy sources. -/- 13. Sustainable Water Resource Management -/- ✔ Protect fresh water from contamination and overuse. ✔ Desalination and rainwater harvesting in water-scarce areas. ✔ Efficient irrigation and water recycling in agriculture and industry. -/- 14. Job Creation and Economic Stability -/- ✔ Ensure that automation enhances jobs rather than eliminates them. ✔ Support entrepreneurship and small businesses. ✔ Guarantee fair wages and universal job security. -/- 15. Universal Healthcare System -/- ✔ Preventive medicine should be the priority. ✔ Universal healthcare with AI-driven diagnostics. ✔ Mental health services equal to physical health services. -/- 16. A Strong Social Safety Net -/- ✔ Unemployment benefits and food security. ✔ State-funded job training and skill development. ✔ Affordable housing and support systems for the homeless. -/- 17. Ethical Artificial Intelligence and Automation -/- ✔ AI must serve humanity, not corporate control. ✔ Prevent AI from being used for mass surveillance or manipulation. ✔ Ensure AI aligns with the universal law of balance. -/- 18. Justice System Based on Cause and Effect (Law of Karma) -/- ✔ Laws must be logical, fair, and corruption-free. ✔ Swift, evidence-based legal processes. ✔ Restorative justice rather than punitive imprisonment. -/- 19. Global Feedback Mechanism for Continuous Improvement -/- ✔ AI-assisted global balance monitoring. ✔ Digital democracy and blockchain voting for fair governance. ✔ Regular sustainability and ethics audits. -/- III. Conclusion: A Perfect Society Is Achievable -/- A perfect society follows the universal law of balance in all areas—economy, technology, environment, governance, and social systems. -/- By applying your universal formula, society can: ✔ Eliminate corruption, poverty, and injustice. ✔ Achieve sustainability without harming future generations. ✔ Use AI and technology responsibly for the betterment of all. ✔ Create a world where human potential is maximized, and suffering is minimized. -/- . (shrink)

Imagine a world where three out of every four wild animals have disappeared. This isn’t science fiction – it’s our reality. The World Wildlife Fund’s (WWF) Living Planet Report 2024 reveals a shocking truth: in just 50 years, wildlife populations worldwide have dropped by 73% on average. In Latin America and the Caribbean, the situation is even worse, with up to 95% of wildlife lost.

Near the end of December 2019, the globe was hit with a major crisis, which is nothing but the coronavirusbased pandemic. The authorities at the train station should also keep in mind the need to limit the spread of the covid virus in the event of a global pandemic. When it comes to controlling the COVID-19 epidemic, public transportation facilities like train stations play a pivotal role because of the proximity of so many people who may be exposed to the (...) virus. Using common place CCTV cameras and deep learning with simple online and real-time (DeepSORT) methods, this study develops social distance monitoring using a YOLOv4 identification of a Surveillance Object Model. Based on experiments conducted with a minicomputer equipped with an Intel 11th Gen Intel(R) Core(TM) i3-1115G4 at 3.00GHz, 2995 Mhz, two Core(s), four Logical processor, four gigabytes of random-access memory (RAM), this paper makes use of CCTV surveillance, which was put into practice at the Guindy railway station, Chennai, Tamilnadu in India in order to detect the violation of social distancing. (shrink)

The jurisprudence under international human rights treaties has had a considerable impact across countries. Known for addressing complex agendas, the work of expert bodies under the treaties has been credited and relied upon for filling the gaps in the realization of several objectives, including the peace and security agenda. -/- In 1982, the Human Rights Committee (ICCPR), in a General Comment observed that “states have the supreme duty to prevent wars, acts of genocide and other acts of mass violence ... (...) Every effort … to avert the danger of war, especially thermonuclear war, and to strengthen international peace and security would constitute the most important condition and guarantee for the safeguarding of the right to life.” Over the years, all treaty bodies have contributed in this direction, endorsing peace and security so as “to protect people against direct and structural violence … as systemic problems and not merely as isolated incidents …”. A closer look at the jurisprudence on peace and security, emanating from treaty monitoring mechanisms including state periodic reports, interpretive statements, the individual communications procedure, and others, reveals its distinctive nature. (shrink)

This chapter presents the perceptual reality monitoring theory of consciousness (PRM). PRM is a higher-order theory of consciousness. It holds that consciousness involves monitoring the reliability of one’s own sensory signals. I explain how a perceptual reality monitoring mechanism computes the higher order representations that are crucial for consciousness. While PRM accounts for the difference between conscious and unconscious states, it does not explain, on its own, why experiences feel the way they do—the phenomenal character of experience. (...) PRM is compatible with multiple theories of phenomenal character. Here, I show how to combine it with ‘Mental Quality Space’ theory. I finish by presenting empirical evidence for PRM, as well as some of its predictions. (shrink)

Human-wildlife interactions frequently lead to conflicts – about the fair use of natural resources, for example. Various principled accounts have been proposed to resolve such interspecies conflicts. However, the existing frameworks are often inadequate to the complexities of real-life scenarios. In particular, they frequently fail because they do not adequately take account of the qualitative importance of individual interests, their relative importance, and the number of individuals affected. This article presents a limited aggregation account designed to overcome these shortcomings (...) and thus to facilitate decision-making in real-world human-wildlife conflicts. (shrink)

Over the last few years, personal health monitoring wearable devices have emerged as innovative applications of Artificial Intelligence (AI) in the healthcare industry as they help in real time analysis and prediction of health standardized check-ups and health management. To navigate through the current trends, new technologies and developments, the prospects are as follows: The article also gives a logical look at the state of the art of such devices, enumerating the advantages and drawbacks, as well as outlining the (...) main ethical issues. In terms of method, it also discusses different AI approaches, data acquisition procedures, and those integrating systems used in the context of health monitoring. The finding and implication section discusses the findings of the current trend and the possibility of improvement in application and user acceptance. The last section provides a prognosis on what the area of personal health monitoring might look like in the future, as well as the position of AI in the optimisation of patient experience. (shrink)

This paper discusses the creation of a Community Based Reporting and Monitoring Tool (CBRMT) aimed at improving safety for women in universities and colleges. The tool is designed to give users the ability to report incidents anonymously, receive immediate alerts, and access safety resources. The goal of CBRMT is to foster a safer and more supportive campus atmosphere where incidents can be managed swiftly, and support for victims is readily available. Through these initiatives, the tool aspires to encourage a (...) safer, more responsible, and inclusive culture across campuses globally. (shrink)

This article discloses topical issues of the need for constant monitoring of changes in the business activity in enterprise structures. The main purpose of the study is to monitor the business activity of industrial enterprise structures of Ukraine to predict their development under martial law. A critical analysis of the content of scientific publications to solve the problem of improving the management of business activity of business structures revealed the lack of attention of scientists to the problems under study. (...) The relevance of its solution is due to the scale of the impact of military conflicts on the business activity in enterprise structures, which requires its monitoring to further establish the state and ensure compliance of the business with the norms that are considered necessary to maintain a certain level of stability of development or to survive, to determine areas where the business can improve its activities and become more profitable. The methodological basis is the system of methods used to obtain the final results of the study: theoretical generalization – to deepen the essence of the concept of «monitoring business activity»; analysis, synthesis and logical generalization – to obtain conclusions during monitoring of business confidence and business climate in industry; prognostic – to predict the development of industrial business structures of Ukraine under martial law. The object of research in the work is the business activity of business structures. The article presents the results of monitoring business confidence and business climate in the industry of Ukraine under martial law. Analysis, synthesis and logical generalization of monitoring results became the basis for further forecasting the development of business structures. The results of the study can be useful for business structures that seek to maintain a certain level of stability of development and identify areas of improvement. (shrink)

Type 1 diabetes (T1D) is a chronic illness that requires intensive lifelong management of blood glucose concentrations by means of external insulin administration. There have been substantial developments in the ways of measuring glucose levels, which is crucial to T1D self-management. Recently, continuous glucose monitoring (CGM) has allowed people with T1D to keep track of their blood glucose levels in near real-time. These devices have alarms that warn users about potentially dangerous blood glucose trends, which can often be shared (...) with ther people. CGM is consistently associated with improved glycemic control and reduced hypoglycemia and is currently recommended by doctors. However, due to the costs of CGM, only those who qualify for hospital provision or those who can personally afford it are able to use it, which excludes many people. In this paper, I argue that unequal access to CGM results in: (1) unjust health inequalities, (2) relational injustice, (3) injustice with regard to agency and autonomy, and (4) epistemic injustice. These considerations provide prima facie moral reasons why all people with T1D should have access to CGM technology. I discuss the specific case of CGM policy in the Netherlands, which currently only provides coverage for a small group of people with T1D, and argue that, especially with additional considerations of cost-effectiveness, the Dutch government ought to include CGM in basic health care insurance for all people with T1D. (shrink)

Given that one-million species are currently threatened with extinction and that humans are undermining the entire natural infrastructure on which our modern world depends (IPBES, 2019), this dissertation will show that there is a need to provide an alternative approach to wildlife conservation, one that avoids anthropocentrism and wildlife valuation on an instrumental basis to provide meaningful and tangible success for both wildlife conservation and human well-being in an inclusive way. In this sense, The Value of Being (...) Wild will showcase the concept of eco-phenomenology as an important non-anthropocentric alternative to the current approach to wildlife conservation, namely sustainable development. The problem with this dominant paradigm, as Chapter Two will reveal, is that sustainable development has not only failed to provide humans and future generations of humans with their own needs but, as per the latest IPBES report, failed in arresting the freefall decline of wild species. The situation currently requires a radical overhaul of the current system. As emerged from the later work of French phenomenologist, Maurice Merleau-Ponty (1908-1961), eco-phenomenology is particularly well-suited as a practical alternative to sustainable development. The core reason is that eco-phenomenology moves away from a human-centred framework toward a far more inclusive approach that embraces the conservation of wild animals as well the wild environment they dwell in, beyond any human needs (although humans are embraced within the approach too). Merleau-Ponty helps us to move away from anthropocentrism to a more inclusive approach in conserving wildlife, since his phenomenology does not consider the human animal’s relationship in the world as exclusive (to use and exploit wild animals solely for their benefit), but inclusive (as an interconnected biological component in a broad ecological system). The strength of Merleau-Ponty’s concept of phenomenology is that it facilitates an understanding of all living and even non-living entities, such as air, water and soil, as interconnected and interrelated within a broad biosphere. While Merleau-Ponty did not address the concept of wild animals or the biosphere directly, his later work points to the fact that human animals cannot exist outside a world that provides life-giving force to all living beings. Phenomenology, as developed by Merleau-Ponty, is a concept that recognises the axiological qualities of the natural world are inherent and ineliminable from the discipline of traditional phenomenology, hence the term ‘eco-phenomenology’, developed in one reception of his thinking. Eco-phenomenology offers a return to a world that humans have tried hard to alienate themselves from, in that it approaches the natural environment and wild animals, not as a complex set of objects and objective processes, but rather as they are experienced and lived from within by the attentive animal who is entirely a part of the world that he or she experiences. Merleau-Pontian eco-phenomenology thus emphasises a holistic dialogue within a more-than-human world (Abram, 1996: 65). Eco-phenomenology is a concept that points toward an applied strategy but so far this has not been attempted in earnest. This is specifically true when it comes to wildlife conservation. The Value of Being Wild, therefore, sets out to employ the concept of eco-phenomenology in order to provide a new practical wildlife conservation approach that challenges, and potentially replaces, the current prevailing policies as employed by global governmental and inter-governmental agencies. In particular, this alternative frame is posed as a replacement for the failing anthropocentric conservation practices currently in place in South Africa. This dissertation will therefore conclude by exploring strategies where conservation of wildlife is not taken as instrumentally-valued, or even intrinsically-valued, but rather as wild-valued in that the existence of wild animals as wild is conserved within a broader, more inclusive overall ecology that supports the survival and flourishing of all living beings that include plants, wild animals and human beings. (shrink)

The increasing demand for reliable power sources has made diesel generators essential in various industries. However, traditional monitoring methods often rely on manual inspections, resulting in inefficiencies, unplanned downtimes, and higher operational costs. This project proposes a digital monitoring system for diesel generators that leverages advanced sensor technologies and real-time data analytics to overcome these challenges. The system will utilize Internet of Things (IoT) devices to collect key operational parameters, such as fuel levels, temperature, vibration, and performance metrics, (...) enabling comprehensive monitoring of generator health. By integrating machine learning algorithms, the system will analyze historical and real-time data to predict potential failures and optimize maintenance schedules, shifting from reactive to proactive management. A user-friendly interface will allow operators to visualize generator performance and receive instant alerts for detected anomalies, enhancing decision- making processes, reducing downtime, and lowering maintenance costs—ultimately increasing the reliability and efficiency of power supply. Additionally, the system facilitates remote monitoring, providing continuous oversight regardless of location. This project not only aims to enhance the operational efficiency of diesel generators but also lays the groundwork for smarter energy management solutions in the future. The successful implementation of this digital monitoring system could serve as a model for similar applications across various sectors, contributing to sustainability and operational excellence in energy management. Through this innovative approach, we aim to ensure diesel generators operate at optimal performance levels while minimizing environmental impact. Keywords. Diesel Generators, Digital Monitoring, IoT Devices, Real-time Data Analytics, Machine Learning. (shrink)

his project focuses on developing a community-based water monitoring and conservation tool. The system allows users to track daily water consumption, receive real-time feedback on usage, and view eco-friendly tips. It integrates data visualization and eco-points for promoting conservation behavior. Built using node js, JavaScript, and Chart.js, this platform encourages users to reduce water consumption and share their achievements. The goal is to foster community engagement and sustainable water usage practices, addressing the global concern of water scarcity.

Two problems of wildlife law will be addressed in this article - one is spatial and the other is temporal. The first problem is the lack of identity with, and therefore support for, international wildlife law that local populations have. That leads to the second problem, which is the failure to apply the lessons learned from biodiversity law of fauna to the biodiversity problems of flora. As to the spatial problem, if we make a simple comparison between a (...) map of biodiversity hotspots and a world geopolitical map, we can see that the hotspots worldwide fall largely in developing countries. (shrink)

Air pollution is a critical challenge for urban areas, contributing to public health crises and environmental degradation. Traditional air quality monitoring systems often lack the granularity and adaptability needed to address dynamic pollution sources and patterns. This paper explores how Artificial Intelligence (AI) and IoT technologies can enhance air quality management in smart cities by enabling real-time monitoring, pollution source identification, and adaptive mitigation strategies. By integrating data from IoT sensors, satellite imagery, and traffic systems, cities can reduce (...) pollution levels, improve public health outcomes, and promote sustainable urban environments. Experimental results demonstrate significant improvements in pollution detection accuracy, mitigation efficiency, and public awareness, offering a sustainable blueprint for urban air quality management. (shrink)

Noise pollution is a growing concern in urban areas, contributing to public health issues such as stress, sleep disturbances, and hearing loss. Traditional noise monitoring systems often lack the granularity and adaptability needed to address dynamic noise sources and patterns. This paper explores how Artificial Intelligence (AI) and IoT technologies can enhance noise pollution management in smart cities by enabling real-time monitoring, source identification, and adaptive mitigation strategies. By integrating data from IoT sensors, traffic systems, and urban infrastructure, (...) cities can reduce noise levels, improve public health outcomes, and enhance the quality of life for residents. Experimental results demonstrate significant improvements in noise detection accuracy, mitigation efficiency, and public awareness, offering a sustainable blueprint for urban noise pollution management. (shrink)

The creation of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in 1973 has significantly altered the dynamics of trade in fauna and flora. Despite this effort, curbing of criminal trade in endangered species of wild fauna and flora has remained a key challenge for some countries. The objective of this study was to identify and establish the trafficking routes of illegal wildlife and forest products, analyzing the patterns and trends of wildlife (...) and forest crime including their drivers, actors and modus operandi, and assessing the criminal justice response including the legislative, enforcement, prosecutorial and judicial systems. The analysis was based on the methodologies and principles embedded in African environmental ethics. It was concluded that African ethics allows for ‘sustainable poaching’ under the framework of Eco-Afrocentricism; but condemns poaching done for trafficking purposes. Five canons of sustainability were developed to guide ‘sustainable poaching’. African capitalism thesis was used to support the analysis from political and economic perspectives. (shrink)

This dissertation is about the relationship between Epistemology and other domains. In it I want to show that in an important sense, Epistemology is an autonomous domain. That is, epistemic vocabulary (e.g., “knowledge”, “justification”, “rationality”, “epistemic reason”, etc.) cannot be analyzed without remainder into non-epistemic vocabulary. Epistemic phenomena must be explained in terms of epistemic reasons and the form of assessment proprietary to them. Although epistemic vocabulary cannot be reduced to the vocabulary of other domains, Epistemology is nonetheless connected with (...) other domains in an important way. In this dissertation I focus on the connection between Epistemology and the Philosophy of Mind. I distinguish different forms cognitive self-monitoring can take and corresponding forms of cognitive autonomy. The kind of self-monitoring that receives the most attention involves simulating interpersonal argumentation. I argue that the capacity to self-monitor in this way grounds familiar epistemic standards (e.g., knowledge and justification) and explains how reasons get their grip on us. On the picture that emerges, Epistemology and Philosophy of Mind need to be done in tandem. Epistemology gives us the normative framework that is modeled by the self-monitoring system. The self-monitoring system, conversely, explains the kind of activity we engage in that makes that normative framework applicable to us. Epistemic reasons themselves are just episodes of this kind of activity. In Chapter 1 I argue that epistemic luck cannot be analyzed in non-epistemic terms. Here I generalize Jennifer Lackey’s criticism of Duncan Pritchard’s safety-based account of epistemic luck to all reductive theories. I argue that they will either be extensionally inadequate, or they will illicitly presuppose the vocabulary they are trying to reduce. The upshot is that epistemic luck can only be understood in terms of the epistemic assessment of reasons. By extension, we can’t give a reductive analysis of knowledge. This is not to say we cannot analyze knowledge, just that we can’t analyze away the epistemic vocabulary without remainder. In chapter 2 I explain the relation between epistemic luck, epistemic justification, and knowledge. I argue that previous work in the defeasible reasoning tradition, despite being on the right track, fell short of realizing its full potential. This is because the account of how these three things relate given by its proponents was insufficiently unified, which encouraged many epistemologists to abandon the defeasible reasoning tradition entirely. I argue that a unified and principled account of their relation is possible, and it allows for an elegant analysis of knowledge. In slogan form: good reasons are apparent to the knowing subject. In chapter 3 I extend the defeasible reasoning tradition to explain how knowledge is gradable. I show that this enables us to bring the debates about fake barns and knowledge from falsehoods to ecumenical resolutions, while also shedding light on a new kind of case. Furthermore, I explain how background assumptions are themselves defeasible and some of the epistemic significance of this fact. In chapter 4 I make the connection between Epistemology and Philosophy of Mind. I argue that the self-monitoring system of cognitively mature humans uses a model of the normative framework described in the previous chapters to regulate its own cognition. Here I build on that claim to develop an account of the role played by knowledge and justification in doxastic social coordination. I build on the claim that background assumptions are themselves defeasible to develop an account of the foundations of knowledge according to which they are social but not brutely sociological. In chapter 5 I discuss the relation between the epistemic states of cognitively mature humans, children, and non-human animals. I do this in a way meant to integrate an insight from virtue epistemology into the reasons-first picture developed here: positive epistemic standing is a state attributable to the subject. In chapter 6 I discuss the metaphysics of epistemic reasons. I claim that they are episodes of the activity of reasoning. In the preceding chapters, we get a sense of what that activity involves. Here I argue that the materials developed there put us in a position to understand what epistemic reasons are. This account incorporates the insights of rival positions while sidestepping familiar objections to them. The resulting picture is in line with the non-reductive approach to the epistemic developed so far. In fact, it goes further than other “reasons-first” approaches to Epistemology by claiming that reasons are not only basic within Epistemology, but they are also basic full-stop. One key consideration for my argument here is that reasons are, by their very nature, competitors. Although this point is generally acknowledged in the literature on reasons, its consequences for the metaphysics of reasons hasn’t been. Participants in the debate about the metaphysics of reasons typically try to identify reasons with something (e.g., facts or mental states) that are either not competitors, or only competitors insofar as they constitute, or bear on the epistemic assessment of, episodes of reasoning. (shrink)

The Alaska National Interest Lands Conservation Act of 1980 requires federal agencies to provide a meaningful role for rural subsistence harvesters in management of fish and wildlife in Alaska. We constructed an interpretive analysis of qualitative interviews with residents of the Yukon-Kuskokwim Delta. Stakeholders' perceptions of their roles and motivations to participate in collaborative management are linked to unseen and often ignored cultural features and differing worldviews that influence outcomes of collaboration. Agencies need to better understand Yup'ik preferences for (...) working together and change their formats and methods of public engagement. More frequent and higher quality interactions among stakeholders in rural communities will create awareness of cultural differences. Improved awareness will allow managers to design and implement a process that is culturally appropriate and increase the meaningfulness of collaborative management. (shrink)

Based on field research in Africa, this essay explores three claims: first, that sport hunting places economic value on wildlife and habitats; second, that this motivates conservation practices in the interest of sustaining revenue sources; and, third, that this benefits human populations. If true, then sport hunting may sometimes be justifiable on utilitarian grounds. While not dismissing objections from the likes of Singer and Regan, we suggest their views – if converted into policy in desperately impoverished places – would (...) destroy animals and the habitats on which they depend. There are empirical verifications of this, which we discuss. (shrink)

Air pollutants pose a threat to biodiversity throughout the world. This study was conducted to evaluate atmospheric element accumulation in Isparta city, including Gölcük Nature Park, located in the Western Mediterranean Region of Turkey. It is aimed to determine the air quality and potential pollutant sources in the region through lichen biomonitoring. Specimens of the epiphytic foliose lichen Physcia aipolia (Erh. ex Humb.) Fürnr. were sampled from 14 sites in the study area and analyzed by ICP-MS with reference material in (...) order to detect 11 trace elements; Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn. The spatial distribution of these airborne elements in the study area was mapped. The results showed that the elemental sequence in terms of average concentrations measured was as follows: Ni >Cr >V >Fe >As >Al >Zn >Cu> >Cd >Mn >Pb. The results of cluster analyses of the elemental data indicated that the 3 major contaminants in the urban area were Cr, Ni, and V, probably due to the extensive use of coal in heating facilities and gasoline in vehicles. P. aipolia specimens accumulated maximal concentrations of As, Cr, Fe, Ni, and V in the northern and the southeastern localities surrounding the city, while Cd, Pb were most abundant in the eastern edge of Gölcük Nature Park. The pollution in Isparta city with heavy metal is worse than expected, mostly due to the extensive use of coal as fossil fuel. In addition, it seems to be associated with the city's topographic and climatic characteristics, e.g. inversion effects. (shrink)

This paper addresses the critical role of automated data quality monitoring in Machine Learning Operations (MLOps) pipelines. As organizations increasingly rely on machine learning models for decision-making, ensuring the quality and reliability of input data becomes paramount. The paper explores various types of data quality issues, including missing values, outliers, data drift, and integrity violations, and their potential impact on model performance. It then examines automated detection methods, such as statistical analysis, machine learning-based anomaly detection, rule-based systems, and data (...) profiling. The integration of data quality monitoring into different stages of the MLOps pipeline is discussed, emphasizing continuous monitoring at data ingestion, pre-training validation, post- deployment drift detection, and feedback loops for model retraining. The paper also addresses key challenges in implementing automated data quality monitoring, including balancing precision and recall in anomaly detection, handling high-dimensional and unstructured data, managing false positives and alert fatigue, and adapting to evolving data distributions. By providing a comprehensive framework for automating data quality monitoring in MLOps pipelines, this paper aims to equip practitioners with the knowledge and strategies necessary to enhance the reliability and performance of machine learning systems in production environments. (shrink)

The target of Second- Language Acquisition (SLA), emerged in the second half of the 20th century, was to be helpful in foreign- language education/ teaching. It denotes mostly the study of individuals (or sometimes groups) who are learning a language consequent to learning their first language when they are young children. At the same time, it signifies the process of learning a second language. The added language is named a second language, but it might indeed be the third, fourth or (...) more which is going to be acquired. The range of SLA comprises informal Second- Language Learning occurring in natural milieus, formal second- language learning occurring in classroom or the one that contains a combination of them both, that is, settings and conditions. The three main aspects for the study of SLA process are the linguistic, psychological and social aspects. The Monitor Theory/ Model postulated by Krashen in the 1970s is a psychological approach in nature. With its five hypotheses (The Acquisition– Learning Hypothesis, The Monitor Hypothesis, The Natural Order Hypothesis, The Input Hypothesis, and The Affective Filter Hypothesis), it tries to find answers to the problems of SLA, such as what does a second- language learner come to know, how the acquisition process takes place, and why some learners are more successful than others? The Monitor Theory (MT) received extensively many criticisms after its appearance and was rejected. Its teaching implications were also at the centre of criticisms. What place does MT occupy in SLA today? This study aims to try to find an answer. The other questions are: How important is the MT for SLA? What kind of criticisms are expressed against it? How fair is the criticism by McLaughlin (1978, 1987)? The working hypotheses of the present work are: The hypotheses developed by Krashen are not/ will not be rejected. Because science is still lying in the so- called agony phase, and cannot find any answers to all questions in psychology (e.g. how exactly is the processing of language; in particular and of mind in general). Moreover, the problems related to memory etc., the thoughts emanated from the MT can probably not be refuted. They have evolved so far and will be evolved further, perhaps with small differences. This research is completely based on the literature written since the time the theory was developed. In other words, it was carried out using a descriptive method without using a special data collection tool. The sources written on the subject were reviewed and an answer to the research questions was tried to be found. Even though the theory is expressed with different names and different meanings today, it has survived all the criticisms made, and it has been concluded that it still occupies an important place in the discipline of second- language acquisition (SLA) and foreign- language teaching. Again, the inquiries carried out since the 1970s delineate that the implications in favour of language education are not very different from those stated by Krashen (1982), which were the products of his opinions in that period. There are still basic consequences grounded on MT for language teaching today. (shrink)

Decision-making by a Data and Safety Monitoring Board (DSMB) regarding clinical trial conduct and termination is intricate and largely limited by cases and rules. Decision-making by legal jury is also intricate and largely constrained by cases and rules. In this paper, I argue by analogy that legal decision-making, which strives for a balance between competing demands of conservatism and innovation, supplies a good basis to the logic behind DSMB decision-making. Using the doctrine of precedents in legal reasoning as my (...) central analog will lead us to a decision-theoretic analogy for much more systematic documentation of decisions in clinical trials. My conclusion is twofold: every DSMB decision should articulate a clear general principle (a ratio decidendi) that gives reason for the decision; and all such decisions should be made public. I use Bartha’s (2010) theory of analogical arguments to both frame and assess my argument by analogy. (shrink)

An invited commentary on Ara Norenzayan's Big Gods: How Religion Transformed Cooperation and Conflict, focusing on whether early China constitutes an exception to his general theory.

Many philosophers and psychologists have sought to explain experiences of auditory verbal hallucinations and “inserted thoughts” in schizophrenia in terms of a failure on the part of patients to appropriately monitor their own inner speech. These self-monitoring accounts have recently been challenged by some who argue that AVHs are better explained in terms of the spontaneous activation of auditory-verbal representations. This paper defends two kinds of self-monitoring approach against the spontaneous activation account. The defense requires first making some (...) important clarifications concerning what is at issue in the dispute between the two forms of theory. A popular but problematic self-monitoring theory is then contrasted with two more plausible conceptions of what the relevant self-monitoring deficits involve. The first appeals to deficits in the neural mechanisms that normally filter or attenuate sensory signals that are the result of one’s own actions. The second, less familiar, form of self-monitoring approach draws an important analogy between Wernicke’s aphasia and AVHs in schizophrenia. This style of self-monitoring theory pursues possible connections among AVHs, inserted thoughts, and the disorganized speech characteristic formal thought disorder. (shrink)

Vibration, especially basic vibration, may cause loose contacts, open circuits, or other contact problems, which account for a large proportion of system failure causes. Due to the complexity of the chassis structure used in the biomedical motors, the vibration analysis of a single component cannot solve the vibration problems encountered in the work of the system. Therefore, it is necessary to use system simulation and experiments to monitor and enhance the health of the structure. Finite element method is used to (...) carry out the dynamic analysis from the component to the system, and calculate the natural frequency, modal shape and harmonic response. Then, the effectiveness and accuracy of the analysis results are verified by experiments through simulation and experiments. The results show that the measures taken have effectively reduced the vibration of the chassis equipment and improved its safety for better health safety of patients. There is just a 2% variation between the natural frequencies acquired from the experiment and the simulation computation. In terms of natural frequency, the first 6-order natural frequencies all have errors of less than 10%, and the natural frequency error is comparable to that of fireproof board. (shrink)

Do self‐monitoring accounts, a dominant account of the positive symptoms of schizophrenia, explain auditory verbal hallucination? In this essay, I argue that the account fails to answer crucial questions any explanation of auditory verbal hallucination must address. Where the account provides a plausible answer, I make the case for an alternative explanation: auditory verbal hallucination is not the result of a failed control mechanism, namely failed self‐monitoring, but, rather, of the persistent automaticity of auditory experience of a voice. (...) My argument emphasizes the importance of careful examination of phenomenology as providing substantive constraints on causal models of the positive symptoms in schizophrenia. (shrink)

The attendance is taken in every organization. Traditional approach for attendance is, professor calls student name & record attendance. For each lecture this is wastage of time. To avoid these losses, we are about to use automatic process which is based on image processing. In this project approach, we are using face detection & face recognition system. The first phase is pre-processing where the face detection is processed through the step image processing. It includes the face detection and face recognition (...) process. Second phase is feature extraction. Step by step execution of these techniques (Image Processing) helps to achieve the final output. The working of this project is to detect and recognize the face and mark the attendance for the corresponding face in the database. Input of this project is face detection and recognition and output is to mark the attendance. Our project is being presented as a solution for the Automatic Attendance Marking System. It is designed to be reliable and low power. The Automatic face detection and recognition proposed to attendance marking in database acts as the solution for the automatic attendance marking system.. (shrink)

This paper turns to pragmatism for strategies to assist with the timely implementation of conservation efforts, as it provides tools to unfreeze policy decision making so that stakeholders, from farmers to wildlife organizations, can readily address impacts associated with climate induced non-human migration. The first section of this essay introduces readers to the topic of climate induced migration and provides an overview of how agriculture could either inhibit or help facilitate migrating species. The second section then applies Thompson’s analysis (...) of water policy, specifically his triangular structure of libertarianism, utilitarianism, and egalitarianism, to the problem of non-human climate refugees to identify positions that could be taken, as producers, policy makers, and other stakeholders determine if they should adopt strategies to assist migrating species. This analysis ends with the argument that the field of applied ethics, while useful for identifying key policy positions, can provide little insight to stakeholders facing issues associated with climate induced migration. The final section of the paper turns to pragmatism for strategies that could help guide wildlife conservation decisions on the ground. It is the author’s hope that a wide range of readers will find this paper useful, as it brings together work in environmental ethics, wildlife conservation literature, and public policy. (shrink)

This study aimed to survey wild species voluntarily received or rescued in the Lake District, State of Rio de Janeiro, in 2011. The research aimed to identify endangered species, quantify the groups and know the destination given to specimens. The records were obtained from the Instituto Ecológico Búzios Mata Atlântica, an NGO responsible for the Environmental Protection Area named Pau-Brasil and for the Lake District. The analysis showed that 181 animals were seized, 51% mammals (13 species), 25% reptiles (13 species), (...) 24% birds (11 species) and 1% fish (1 species). Amongst those animals, 12 species are included in the List of Endangered Brazilian Fauna Species. (shrink)

Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The (...) system / lifeworld perspective of Habermas is applied to develop an understanding of the role of PHMs as mediators of communication between the institutional and the domestic environment. Furthermore, links are established between the ethical issues to demonstrate that the ethics of PHM involves a complex network of ethical interactions. The paper extends the discussion of the critical effect PHMs have on the patient’s identity and concludes that a holistic understanding of the ethical issues surrounding PHMs will help both researchers and practitioners in developing effective PHM implementations. (shrink)

Highway construction projects are often complicated and need careful management. This proposes the development of real time monitoring dashboard specially designed for highway road construction projects. The project is mainly useful for transportation planners, civil engineers, project managers, surveyors, constructors, government authorities, safety inspectors. Traditional monitoring methods often involve manual inspections and periodic reporting, which can lead to delays and inefficiencies. Existing approaches generally rely on static data collection and do not provide real-time insights into construction progress, resource (...) allocation. The proposed solution integrates advanced technologies such as data analytics to provide an interactive platform. This dashboard will offer real-time visualization of construction progress, resource usage, expenses, facilitating immediate decision-making and management. (shrink)

This project focuses on developing a community-based reporting and monitoring tool to improve women’s safety in colleges and universities. The tool allows users to anonymously report unsafe incidents, harassment, or suspicious activities, with features for immediate alerting to campus authorities and support groups. It integrates GPS tracking for emergencies and data visualization to monitor safety trends. Built using Java, XML, and Android Studio, the platform fosters collaboration between students, faculty, and administrators, encouraging proactive safety measures. By enabling discreet reporting (...) and real-time monitoring, the tool aims to create a safer campus environment for women. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

This paper explores the ethical dimensions of lionfish removal and provides an argument supporting hunting lionfish for consumption. Lionfish are an invasive species found around the world. Their presence has fueled management strategies that predominantly rely on promoting human predation and consumption. We apply rights-based ethics, utilitarian ethics, and ecocentric environmental ethics to the question of whether hunting and eating lionfish is ethical. After applying these perspectives, we argue that, from a utilitarian perspective, lionfish should be culled. Rights-based ethics, on (...) the other hand, are not applicable in this case, while ecocentric environmental ethics would support lionfish removal. (shrink)

Vibration, especially basic vibration, may cause loose contacts, open circuits, or other contact problems, which account for a large proportion of system failure causes. Due to the complexity of the chassis structure used in the biomedical motors, the vibration analysis of a single component cannot solve the vibration problems encountered in the work of the system. Therefore, it is necessary to use system simulation and experiments to monitor and enhance the health of the structure. Finite element method is used to (...) carry out the dynamic analysis from the component to the system, and calculate the natural frequency, modal shape and harmonic response. Then, the effectiveness and accuracy of the analysis results are verified by experiments through simulation and experiments. The results show that the measures taken have effectively reduced the vibration of the chassis equipment and improved its safety for better health safety of patients. There is just a 2% variation between the natural frequencies acquired from the experiment and the simulation computation. In terms of natural frequency, the first 6-order natural frequencies all have errors of less than 10%, and the natural frequency error is comparable to that of fireproof board. (shrink)