Artificial Intelligence (AI) holds transformative potential for enhancing fairness, efficiency, and transparency within law-making and judicial processes. By automating routine tasks, analyzing vast amounts of legal data, and providing decision-making support, AI can contribute significantly to the legal system. However, its implementation raises concerns about fairness, accountability, and the potential for algorithmic biases that may perpetuate inequalities. This paper explores the responsible use of AI to ensure fairness in law-making and judicial processes, highlighting the ethical challenges and providing strategies for (...) mitigating bias. It emphasizes the importance of transparency, inclusivity, and regulatory frameworks to guide AI implementation, ensuring the protection of fundamental rights and the integrity of the legal system. (shrink)

This paper explores the development of a Flutter-based Digital Classroom App that serves as an educational platform for students and teachers on Android and iOS devices. The app leverages Flutter's capabilities to provide a seamless user experience across both platforms. It offers features like live classes, assignments, discussion boards, and notifications. The paper will cover the system architecture, user interface design, and the benefits of using Flutter for cross-platform development.

Generative AI is rapidly transforming the design industry by enabling the creation of innovative, original, and highly functional designs that would otherwise be difficult or time-consuming to produce. This paper explores the role of generative AI in revolutionizing design processes across various industries, including architecture, product design, graphic design, and fashion. The paper examines how AI algorithms, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and evolutionary design algorithms, are facilitating the generation of novel design solutions. Additionally, the paper (...) investigates how these technologies are enhancing the creative process, allowing designers to push boundaries, automate repetitive tasks, and collaborate with AI systems to unlock new possibilities. The ethical implications, such as intellectual property and the potential for job displacement, are also discussed. Finally, the future trajectory of generative AI in design is explored, including its potential to foster human-AI collaboration. (shrink)

The world in the 21st century is ever evolving towards automation. This upsurge seemingly has no decline in the foreseeable future. Image recognition is at the forefront of this charge which seeks to revolutionize the way of living of the average man. If robotics can be likened to the creation of a body for computers to live in, then image processing is the development of the part of its brain which deal with identification and recognition of images. To accomplish this (...) task, we developed an object detection algorithm using YOLO, and acronym for “You Only Look Once”. Our algorithm was trained on fifty thousand images and evaluated on ten thousand images and employed a 21 x 21 grid. We also programmed a text generator which randomly creates texts and URLs in an image. A record of useful information about the location of the URLs in the image is also recorded and later passed to the YOLO algorithm for training. At the end of this project, we observed a significant difference in the accuracy of URL detection when using OCR software or our YOLO algorithm. However, our algorithm would be best used to specify the region of interest before converting to texts which greatly improves accuracy when combined with OCR software. (shrink)

Augmented Reality (AR), driven by Artificial Intelligence (AI), is transforming how we interact with the world. Recent technologies, like AI-powered smart glasses, are increasingly blending the physical and digital realms. While AR presents exciting new possibilities, it also raises deeper philosophical questions about what we consider reality.

Different philosophers from ancient Greek philosophers to contemporary thinkers tried to present unique views on consciousness. But what consciousness actually is remains unknown. Scientists today study neural firing patterns, neurotransmitters, fMRI scans map neural constellations and brain circuits. Yet, the bridge between neurons and the fragrance of rain or the taste of chocolate remains elusive. How does a network of cells conjure the magic of qualia? This makes the hard problem of consciousness. In this situation, emergent illusionism proposes a new (...) paradigm for the hard problem of Consciousness. (shrink)

Amongst invertebrates, molluscs show great variability in their nervous system ranging from primitive arrangement in Chitons to the complex mass of fused ganglia forming the ‘brain’ of cephalopods. Most of the effector organs used for pharmacological or physiological experiments. The neurosecretory cells (NSCs) with their combination of neuronal and glandular capabilities are perfectly suited to translate a neuronal input into the hormonal output best suited to long-term process. In this capacity, the NSCs may produce hormones, which act directly upon the (...) peripheral target or it may exert its effect indirectly by influencing the activity of other non-neural, endocrine organs. Neurosecretory cells have been detected in the cerebral, pedal and visceral ganglia of Lamellidens corrianus. The distribution and biology of freshwater bivalve like Lamellidens corrianus is influenced by local ecological factors (like temperature, pH, inorganic salts, type of soil etc.), water flow system and presence of micro-organisms, teleost fishes and seasonal variations in these parameters. Nitrogenous excretory changes which include ammonia in these molluscs is also influenced by these local ecological factors in which temperature is plays very crucial role. It is well known fact that the high stress conditions during drought or severe winter conditions have been conquered by several lineage of gastropods and sand bivalves and their ability to enter the resistant or dormant stages (low food) protein catabolism increased. Present investigation deals with the oxygen consumption and ammonia excretion ratio of these freshwater pelecypode Lamellidens corrianus. Study on Lemellidens corrianus directed in understanding the different behavioral and physiological aspects after cerebral ganglia removal and injection of their extracts revealed significant changes during summer (April-May). (shrink)

The nature of consciousness has perplexed humans for millennia. While traditional science has viewed consciousness as an emergent property of neural networks, pioneering research in quantum biology and neuroscience is challenging this assumption, suggesting that consciousness may arise from quantum processes happening inside our brains. The profound implications of this theory extend beyond biology, potentially connecting the mind to the universe itself.

Throughout history, humans have sought spiritual experiences to find meaning, solace, or answers to life’s complexities. In religious settings, particularly in charismatic gatherings, phenomena such as people falling to the ground, rolling over, or convulsing after being touched or waved at by religious figures have been reported across many traditions. While believers may interpret these occurrences as signs of divine intervention, the underlying reasons behind these phenomena could be deeply rooted in psychological, neurological, and social factors.

The present paper aims to study the origin and the development of karma and rebirth theory, which was the outcome of the collective historical experiment of multiple social groups under the socially shared ideological philosophical system of Ancient India. The existing historiography looked at it as a superfi- cial system dealing with certain ideas around religion and ritual. Therefore, it missed out on the other aspects related to it, which evolved around the notion of penance and punishment. That internalizes the (...) social order and justified the unaccounted inequalities by forcing individuals to self-surrender for violation of social and legal limitations of the concerned society. This present paper is going to look at this primary idea by focusing on multiple forms of karma and rebirth and the idea of the body in the same as depicted in Manusmrti. In addi tion to this, it will also check the inter-mixture of social and religious morality in the same through the historical process of ethnicization by making the base to the existing socio-economic environment of the concerned period. (shrink)

This philosophical article critically examines Ayurveda, highlighting its classification as a pseudoscientific practice and questioning its place in modern medicine. By integrating both Indian and Western philosophical perspectives, the article contributes to the broader discourse on tradition versus empirical science. It challenges the authority of ancient knowledge in the face of modern scientific rigor, while also exploring the potential for dialogue between holistic practices and evidence-based medicine. This work adds depth to the literature on alternative medicine, skepticism, and the philosophy (...) of science, encouraging critical reflection on the role of Ayurveda today. (shrink)

The increasing demand for secure and efficient voting systems has led to the exploration of online voting solutions. Traditional voting methods are often vulnerable to fraud, inefficiencies, and logistical challenges. This paper presents an online voting system that leverages machine learning techniques to enhance security, accuracy, and accessibility. The system employs facial recognition for voter authentication, anomaly detection to prevent fraudulent activities, and natural language processing (NLP) for user interaction. Experimental results indicate that the proposed model provides a reliable, tamper-resistant, (...) and user-friendly voting experience. (shrink)

“In death, life persists, transforms, and renews—what are the limits of our existence?” -/- What does it mean to be alive? From the moment we are born, our existence seems predicated on a simple dichotomy: life or death. And yet, recent developments in science, such as the creation of biobots from the cells of dead organisms, challenge this very binary. These discoveries force us to ask profound questions about the nature of existence, the essence of life, and what it truly (...) means to die. Can life persist after death? And if so, what implications does this have for our understanding of the world and ourselves? -/- . (shrink)

Autonomous systems, powered by machine learning (ML), have the potential to revolutionize various industries, including transportation, healthcare, and robotics. However, the integration of machine learning in autonomous systems raises significant challenges related to safety, ethics, and regulatory compliance. Ensuring the reliability and trustworthiness of these systems is crucial, especially when they operate in environments with high risks, such as self-driving cars or medical robots. This paper explores the intersection of machine learning and autonomous systems, focusing on the challenges of ensuring (...) safety, mitigating ethical concerns, and navigating evolving regulatory frameworks. We discuss key strategies for improving the transparency, fairness, and accountability of autonomous systems, as well as the role of machine learning in enabling safe decision-making. Additionally, we propose a roadmap for the future development of autonomous systems that incorporates robust safety measures, ethical guidelines, and regulatory compliance. (shrink)

The rise of the Metaverse as a virtual, interconnected world has captured significant attention in recent years. As businesses increasingly recognize the potential of the Metaverse to transform industries, Microsoft Azure stands out as a leading platform for integrating and scaling Metaverse solutions. This paper explores how Azure's cloud infrastructure, advanced computing capabilities, and digital transformation tools enable businesses to integrate with the Metaverse, opening new opportunities for collaboration, customer engagement, and innovation. Additionally, the paper discusses the challenges associated with (...) implementing Metaverse solutions, such as data privacy, interoperability, and infrastructure scalability. Through a comprehensive analysis of Azure's role in supporting the Metaverse, this paper presents key considerations for enterprises looking to build and sustain their ecosystems in this new digital frontier. (shrink)

The rapid advancement of artificial intelligence (AI) and machine learning (ML) has led to significant innovations in the healthcare sector. One such development is AI-powered healthcare chatbots, which assist patients and medical professionals by providing medical guidance, symptom assessment, and appointment scheduling. This paper presents the design and implementation of an AI healthcare chatbot using machine learning techniques. The chatbot leverages natural language processing (NLP) and deep learning models to understand and respond to user queries effectively. Experimental results demonstrate the (...) chatbot's efficiency in delivering accurate and context-aware medical information. (shrink)

Generative Artificial Intelligence (AI) is a powerful technological advancement that represents a significant leap forward in the field of machine creativity. Unlike traditional AI systems, which are designed to perform specific tasks or make decisions based on predefined rules, generative AI models are capable of producing novel, original outputs—ranging from art and music to written text and product designs—based on patterns learned from vast datasets. This paper explores the evolution of machine creativity, focusing on the development and application of generative (...) AI in various creative domains. By analyzing key generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models, this paper highlights how AI can augment human creativity and push the boundaries of artistic expression and innovation. Additionally, the ethical implications, challenges, and future directions of generative AI are examined, offering insight into how this technology will shape creative industries in the years to come. (shrink)

Artificial Intelligence (AI) offers transformative capabilities in enhancing public safety, such as improving crime detection, traffic management, and healthcare. However, as AI systems are increasingly employed by governments and organizations, they raise significant concerns regarding privacy, civil liberties, and ethical governance. The use of AI in surveillance, predictive policing, and data collection poses challenges in ensuring the protection of individual freedoms while maintaining security. This paper examines the responsible use of AI in balancing public safety with individual freedoms, analyzing key (...) ethical considerations, technological limitations, and frameworks for governance. It explores the importance of transparency, accountability, and stakeholder engagement in creating an AI ecosystem that respects human rights while addressing the needs of public safety. (shrink)

In the digital age, chatbots have emerged as essential tools for automating communication and improving user experiences across various sectors. This paper presents a Chatbot Assistant System powered by Natural Language Processing (NLP) to provide intelligent, context-aware, and real-time responses to user queries. The system incorporates NLP techniques, such as text preprocessing, intent recognition, and entity extraction, to facilitate effective interactions. We explore the architecture, working principles, and applications of the system, along with its performance evaluation in different domains.

The growing use of artificial intelligence (AI) systems in decision-making across various domains has raised critical concerns about bias, fairness, and transparency. AI algorithms can inadvertently perpetuate biases based on the data they are trained on, resulting in outcomes that disproportionately affect certain groups. This paper proposes new methods for detecting and mitigating bias in AI systems while ensuring greater algorithmic transparency. The focus is on developing innovative approaches to identify bias at multiple stages of AI development, from data collection (...) to model deployment. Additionally, the paper emphasizes the need for transparent AI models that allow for explainability and accountability in decision-making. The proposed methods include novel fairness metrics, new tools for detecting biases in datasets, and frameworks for ensuring transparency through explainable AI (XAI) techniques. (shrink)

The advent of cloud computing has revolutionized the way organizations manage and deploy their IT infrastructure. Cloud services offer flexibility, scalability, and cost-efficiency, but they also consume a substantial amount of energy and contribute to environmental concerns. This abstract provides an overview of the research conducted on energy-efficient resource utilization in the cloud, focusing on strategies to reduce energy consumption while maintaining optimal performance and resource utilization. The primary objective of this research is to address the growing concern of the (...) environmental impact of cloud computing by proposing and evaluating various energy-efficient techniques and strategies. These strategies encompass multiple layers of the cloud infrastructure, including data centers, virtualization technologies, workload management, and resource allocation. In data centers, we explore techniques for optimizing cooling systems, power distribution, and server hardware, all aimed at reducing energy consumption. Virtualization technologies are a key component in cloud computing, and we investigate methods for efficient virtual machine placement, consolidation, and migration to make better use of the available resources and minimize energy consumption. Workload management strategies involve the dynamic allocation of resources to workloads based on demand. We propose intelligent resource allocation policies that consider factors such as workload characteristics, energy profiles of hardware components, and Quality of Service (QoS) requirements. These policies help in achieving an optimal trade-off between performance and energy consumption. (shrink)

In today's digital landscape, small-scale companies encounter significant challenges in safeguarding their sensitive data against threats due to limited financial resources. Traditional data loss prevention solutions often come with hefty price tags, rendering them inaccessible to such organizations. Our project addresses this issue by designing a user-friendly script that can be easily deployed and managed by non- experts, lowering the barrier to entry for enhancing data security. Our project proposes an innovative approach leveraging PowerShell and ADMX to develop a cost- (...) effective data loss prevention script. This script aims to fortify the security of employee systems without necessitating expensive licenses, offering small- scale companies a practical and affordable solution to enhance their data security posture. By implementing a preventative approach to data loss prevention, small- scale companies can mitigate risks more effectively and avoid the potentially catastrophic consequences of data breaches. This shift in mindset from damage control to risk prevention reflects a strategic investment in the long-term resilience and viability of small businesses in today's increasingly digitized economy. (shrink)

Serverless computing is changing the cloud application de- sign by removing the need to design, build, and manage infrastructure, and instead focusing on deploying code that can be elastic and rapid. However, while service meshes have recently been introduced to address the reliability of communication in microservices architectures, the grow- ing adoption of edge computing and multi-cloud strategies require new architectures that can cross different types of platforms. In this paper, we introduce a novel serverless mesh architecture that combines server- (...) less function platforms with a service mesh overlay that spans across clouds and edge sites. We give a brief overview of the serverless and service mesh technologies and review the related work in traditional cloud centric serverless, edge computing deployments and mesh-based microservice solutions. We then describe a framework where the server- less functions that are located in different cloud/edge environments are connected by a single service mesh that enables dynamic routing, inter- operability, and policy enforcement across the environments. The dia- grams show how the functions are deployed and invoked via the mesh. Simulated evaluation is described for video analytics, IoT sensor data in- gestion, and content delivery use cases, with the potential performance benefits shown in terms of end-to-end latency and throughput. Some of the key challenges of network latency, cold start delays, and data con- sistency issues in distributed serverless computing are identified, along with how the proposed architecture tackles or alleviates them. Last, fu- ture directions are outlined, which include AI/ML-based optimizations for function allocation and tuning, enhanced runtime portability via We- bAssembly (WASM), and open questions for secure, scalable serverless computing from edge to cloud. (shrink)

In an era where digital interactions shape perceptions, sentiment analysis emerges as a powerful tool to decode emotions embedded in text. It empowers businesses, researchers, and decision-makers to transform raw opinions into actionable insights, fostering stronger connections with audiences. This project harnesses the potential of Google’s Vertex AI Auto ML to revolutionize sentiment analysis, delivering an intelligent, automated, and explainable system capable of deciphering emotional tones in reviews, social media posts, and beyond. This approach enhances sentiment-based insights for businesses, researchers, (...) and organizations, improving decisionmaking processes based on user feedback. By integrating cloud-based AutoML capabilities, this project enhances classification accuracy, scalability, and deployment efficiency, making sentiment analysis accessible for businesses, researchers, and organizations. The model’s ability to extract actionable insights from user-generated content supports real-time decision-making, social media monitoring, and customer feedback analysis across various industries. (shrink)

Moderasi beragama merupakan bagian dari Rencana Pembangunan Jangka Menengah Nasional (RPJMN) 2020-2024. Untuk itu, segala upaya yang dilakukan untuk mengimplementasikan Moderasi beragama dalam berbagai bentuk perlu dilakukan. Kami menyambut baik kehadiran buku Moderasi Beragama: Implementasi dalam Pendidikan, Agama dan Budaya Lokal, yang ditulis oleh akademisi dari berbagai perguruan tinggi ini. Karena kehadiran buku ini menjadi salah satu bagian penting dalam memperkuat pemahaman dan praktik beragama yang moderat di tengah-tengah masyarakat Indonesia yang multikultur.

This dissertation focuses on thread safety and concurrency management in the development of cloud native applications, and as such, highlights the necessity of strong policies to prevent the vulnerabilities that can lead to security breaches and deterioration of service delivery. Based on the review of the literature, this research identifies the existing thread-related problems and their solutions, and concludes that concurrency defects are widespread and affect various types of cloud-native applications. The results of the study show that poor thread management (...) increases the level of security threat, particularly in the healthcare sector where patient’s data is most sensitive. Through performance evaluations and analysis of the successful mitigation strategies, this study reveals how strengthening the thread safety can enhance the dependability of the cloud-native systems and protect important healthcare activities. In addition to the technical findings, the results of the study further indicate that better thread mitigation measures may improve the patient safety, the trust in the digital health solutions and the frameworks through which healthcare services are delivered. In this way, the research presented here contributes to the current discussion on the security of cloud-native healthcare applications, and paves the way for future work on the design of better, stronger and more robust digital health ecosystems. (shrink)

Today’s world cloud computing becoming so popular because of an effective and efficient way to provide computing resources and services to customers on demand. Cloud computing being an information technology paradigm enables access to shared pools of configurable system resources and higher-level services often over the Internet. The objective of providers is to maximize profits by their price schemes, while the main purpose of clients is to have quality of services for a reasonable price. Thus the vital aim is to (...) maximize the profit for service providers & get quality of service at best price for the client. In this we are going to allocate resources to the users dynamically, so that free space is also used by the broker. In this way also profit of our broker is also get maximized. Because of cloud computing development, choosing cloud services can be complicated & time-consuming for customers. To facilitate cloud service delivery, the authors propose a cloud service broker who provides automated selection of suitable cloud services, & assure the best performance, reliability, & cost efficiency. (shrink)

Nowadays, remote monitoring systems have developed gradually to respond for particular needs in healthcare sector, which is an essential pillar in the modern concept of smart living, we propose a smart health monitoring system to monitor patient health conditions, as a smart healthcare system based on the widely spread and evolved technologies. Statistics show that severe Falls, hypertensive heart disease and blood pressure are risk factors for high death rate. To decrease it a preventive measure should be applied providing a (...) real-time health monitoring system, to save patients life at acceptable time. The objectives of this project are to provide an effective system model that will track, trace, and monitor patient’s movement, location, vital readings like heartbeat pulses, body temperature in order to provide efficient medical services in time. In proposed system data will be captured using sensors and compared with a predefined threshold. After processing it will send the Message for support to Relatives/Caretakers which will contain the Location, Heartbeat Values and Body temperature. (shrink)

To enhance resilience and to avoid vendor lock-in, modern enterprises are increasingly deploying microservices across multiple cloud providers. But, coordinating workloads across clouds has remained com- plex, even as Kubernetes has emerged as a de facto standard for con- tainer 1orchestration. This paper proposes a novel multi cloud orchestra- tion framework for microservices using Kubernetes as a unifying layer. An architecture is presented for a single control plane to manage mi- croservices across AWS, Azure and Google Cloud Platform clusters. The (...) framework is presented, which includes cross-cloud service discovery, net- work connectivity, and intelligent scheduling of microservices to clusters based on latency, cost, and failover policies, respectively. In early 2020, we compare Kubernetes support in major clouds, highlight their strengths and limitations, and evaluate how our approach leverages their features. Benefits in high availability and load bursting are shown through real- world use cases. Pseudocode is provided for the orchestration logic for de- ploying a microservice across clouds and for handling cross-cloud failover. We find that a multi cloud Kubernetes model can combine the best fea- tures of each provider and, at the same time, avoid their worst pitfalls, to create robust and flexible microservice deployments. (shrink)

Software-Defined Networking (SDN) is transforming network management by offering centralized control and programmability. As SDN environments grow more complex, effective monitoring and analytics become crucial to ensure the performance, reliability, and security of networks. This paper explores the tools and techniques used for monitoring and analyzing SDN networks, emphasizing the importance of real-time data, traffic analysis, and anomaly detection. The paper reviews a variety of existing tools and techniques used to monitor SDN networks, such as OpenFlow monitoring, SNMP (Simple Network (...) Management Protocol) based tools, and machine learning approaches for predictive analytics. Challenges such as network visibility, scalability, and the integration of SDN monitoring with traditional network management systems are discussed. The paper also presents case studies of SDN monitoring implementations and offers recommendations for organizations seeking to optimize their SDN monitoring practices. (shrink)

Artificial Intelligence (AI) offers transformative capabilities in enhancing public safety, such as improving crime detection, traffic management, and healthcare. However, as AI systems are increasingly employed by governments and organizations, they raise significant concerns regarding privacy, civil liberties, and ethical governance. The use of AI in surveillance, predictive policing, and data collection poses challenges in ensuring the protection of individual freedoms while maintaining security. This paper examines the responsible use of AI in balancing public safety with individual freedoms, analyzing key (...) ethical considerations, technological limitations, and frameworks for governance. It explores the importance of transparency, accountability, and stakeholder engagement in creating an AI ecosystem that respects human rights while addressing the needs of public safety. (shrink)

The increasing demand for portable, cost-effective, and energy-efficient computing solutions has led to the development of compact mini computers. In this paper, we’ve designed and built a compact mini computer using the BusyBirds chip. The system includes a built-in power bank for better portability, an HDMI port for connecting to high-definition displays, and Bluetooth 5.0 for reliable wireless communication. It’s developed as a simple, affordable computing option for students, developers, and professionals who need a small, efficient system for different tasks. (...) The BusyBirds Chip is used as the main processing unit, offering better performance while keeping power usage low. One of the standout features of this mini computer is that, unlike regular desktops or laptops that rely on being plugged in all the time, this one can run on battery power. That makes it a handy option for working in places where there’s no easy access to electricity. The in-built power bank helps keep the system running smoothly without interruptions, which makes it especially useful for learning activities and IoT projects. Modern systems need strong connectivity options, and this setup includes both HDMI and Bluetooth 5.0 to improve usability. The HDMI output lets you connect to highquality displays, while Bluetooth 5.0 makes it simple to pair devices like a mouse, keyboard, or speakers. After testing its performance, results showed that the mini computer works as expected offering a good mix of portability, efficiency, and low cost. (shrink)

With the rising global prevalence of cardiovascular diseases and the growing need for accessible healthcare solutions, there is a critical demand for systems that can provide both continuous monitoring and early diagnosis. This project presents a Smart Health Monitoring System with Real-Time Vital Tracking and Predictive Diagnostics, a comprehensive and intelligent health management platform that combines Internet of Things (IoT) technology with machine learning- based predictive analytics. The system integrates a heartbeat sensor and DS18B20 temperature sensor connected to an ESP32 (...) microcontroller, which continuously captures vital physiological parameters. This data is transmitted wirelessly to a Flask-powered web server, where it is logged, visualized in real time through an interactive dashboard, and stored for further analysis. Users can monitor trends over time, download data in CSV format, and reset logs as needed. (shrink)

In today’s digital era, effective financial management is paramount for both individuals and businesses to ensure financial stability, informed decision-making, and long-term growth. The Expense Tracker project is designed as a comprehensive solution to streamline the process of tracking, managing, and analyzing expenditures. This system provides users with a structured, automated, and user-friendly platform to monitor their financial activities efficiently. By allowing users to record transactions, categorize expenses, set budgetary limits, and generate insightful spending reports, the application empowers them to (...) make informed financial decisions in real time. The Expense Tracker is built using React.js for an interactive and responsive front-end experience, Spring Boot for robust and scalable backend processing, and SQL for efficient and secure database management. This technology stack ensures seamless performance, secure data handling, and a smooth user experience. The system aims to eliminate manual errors associated with expense tracking while offering advanced analytics that provide valuable insights into spending habits. By leveraging data visualization and categorization techniques, users can identify unnecessary expenditures, optimize their budgets, and work toward financial goals more effectively. One of the key objectives of this project is to enhance financial planning by offering real-time analytics and notifications to help users stay within their budget limits. Additionally, the application is designed to be scalable and future-ready, with potential integrations of AI-driven financial insights to offer predictive expense recommendations and banking API integrations to automate transaction logging. These features will further enhance the system’s ability to assist users in maintaining financial discipline and improving their overall financial health. The Expense Tracker contributes to the rapidly evolving FinTech industry by delivering an innovative, intuitive, and secure financial management solution. By equipping users with comprehensive tools to oversee their financial activities, the application fosters better financial awareness, reduces overspending, and helps users gain full control over their monetary decisions. With a commitment to continuous improvement and adaptation to emerging financial technologies, this project serves as a stepping stone toward a more intelligent, automated, and data-driven financial ecosystem. (shrink)

Phishing sites which expects to take the victims confidential data by diverting them to surf a fake website page that resembles a honest to goodness one is another type of criminal acts through the internet and its one of the especially concerns toward numerous areas including e-managing an account and retailing. Phishing site detection is truly an unpredictable and element issue including numerous components and criteria that are not stable. On account of the last and in addition ambiguities in arranging (...) sites because of the intelligent procedures programmers are utilizing, some keen proactive strategies can be helpful and powerful tools can be utilized, for example, fuzzy, neural system and data mining methods can be a successful mechanism in distinguishing phishing sites. We applied Random Forest (RF), one of the different types of machine learning based algorithms used for detection of Phishing websites. Finally we measured and compared the performance of the classifier in terms of accuracy. (shrink)

Larry Moss and Rohit Parikh used subset semantics to characterize a family of logics for reasoning about knowledge. An important feature of their framework is that subsets always decrease based on the assumption that knowledge always increases. We drop this assumption and modify the semantics to account for logics of knowledge that handle arbitrary changes, that is, changes that do not necessarily result in knowledge increase, such as the update of our knowledge due to an action. We present a (...) system which is complete for subset spaces and prove its decidability. (shrink)