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A Qualitative Analysis of ML Method in Fruits Adultery and Focus on Fruit Adulteration Detection
Detecting formalin can be difficult and time- consuming without exact chemical knowledge. The presence of naturally occurring formalin in food products can additionally make it more difficult to distinguish between formalin that has been purposefully added. The method for dynamic and precise food and formalin identification described in this work is machine learning-based. Preserving food practises that put public nutrition in jeopardy include the unethical use of formalin. It was decided what kind of food to provide based on conductive characteristics. With the use of a VOC HCHO gas sensor and a Renesas, the gadget has the ability of detecting formalin concentrations of 1 to 50 ppm. Polynomial regression has been used in a number of investigations to simulate the application of formalin.
“Focus Flow” An approach to Distraction Free Environment
In the modern landscape of digital work environments, staying focused on tasks amidst a plethora of distractions has become a significant challenge. To address this issue, the "Focus Flow," a desktop application meticulously crafted to optimize productivity by minimizing interruptions from social media, games, and other potential distractions. The core feature, "Focus Mode," empowers users to isolate and prevent access to distracting applications, fostering an environment conducive to concentration. Technical implementation involves the strategic use of file permissions or firewall rules, ensuring a seamless and secure process running in the background. Beyond distraction control, Focus Flow integrates an array of functionalities. From straightforward to- do lists, local task management, and a documents viewer for seamless file accessibility to a unique Test Mode that transforms the system into a secure environment for standardized test- taking, the application aims to provide a holistic solution to enhance productivity. Moreover, the inclusion of an in-app chat feature enables communication within the application, fostering collaboration without external distractions. A central dashboard serves as a command center, offering quick access to Focus Mode, statistics, task management, and other essential features. The application also incorporates progress tracking, allowing users to visualize trends over time and set and monitor productivity goals. In summary, Focus Flow aspires to redefine the way users approach works, providing a comprehensive toolkit to create a distraction-free and productive work environment.
AI IMAGE GENERATOR
"This project explores the captivating realm of AI-generated image synthesis, leveraging cutting-edge technologies such as diffusion models and CLIP encoding. The central concept involves translating textual descriptions into lifelike images with remarkable precision and speed. By employing diffusion models, we ensure high- quality image generation, while effective text conditioning enhances the alignment between textual prompts and the resulting visuals. The incorporation of the CLIP model for text encoding further enriches the semantic associations between descriptions and images. The project not only aims to revolutionize image synthesis but also endeavors to bridge the communication gap between words and visuals in our increasingly text-centric world."
Effective Technique for Face Recognition System Using CNN in Attendance Applications
Face recognition is a personal identification system that uses individual characteristics of a person to recognize the person's identity. The software which is used for face recognition is MATLAB. The project area is image processing. Different types of ordinal measures are derived from magnitude and phase components of Gabor images. Two orientations and two wavelengths are used. Gabor filters are used in the pre-processing step. Array of Gabor filters is called as filter bank. Convolutional Neural Network (CNN) is used for face recognition, which outperforms the traditional techniques. It has three layers in which Convolution Layer is used for feature extraction. Pooling Layer is used, which crops the particular part of the image containing the object and then resizes it, because classification requires fixed size of an image. SoftMax Layer is used to normalize the un-normalized vectors and make the predictions into the probabilistic forms. Loss function is used to figure out the error. Finally, the face of a student is recognized by using CNN.
A Review of Metamaterials Cloaking for Military and Civilian Use
Metamaterials cloaking technology boasts a wide array of potential uses, spanning from military stealth applications to advancements in medical imaging. Metamaterials are specially engineered materials with unique characteristics absent in natural substances, such as negative refractive index, empowering them to manipulate electromagnetic waves in novel ways. The process of cloaking with metamaterials involves the bending of light or other electromagnetic waves around an object, effectively rendering it invisible or significantly reducing its detectability. This is accomplished through the intricate design of metamaterial structures capable of governing the flow of electromagnetic fields, diverting them away from the cloaked object. Among the most prominent applications of metamaterial cloaking is the development of invisibility cloaks. While primarily at the experimental stage, researchers have made substantial progress in crafting cloaking devices capable of concealing objects from specific wavelengths of light. These cloaks function by manipulating the path of light around an object, effectively creating the illusion of its absence. The potential applications of metamaterial cloaking encompass a broad spectrum, including invisibility, antennas and sensors, medical imaging, wireless communication, and stealth technology.
A System of IoT Devices to Prevent Under-Loading Over-Loading of Cargo Vehicles
Efficient and safe cargo transportation is a cornerstone of modern logistics and the loading of cargo vehicle is a crucial aspect of this process. This project introduces a comprehensive system of IOT Devices designed to prevent both under-loading and overloading of CARGO VEHICLE.The system incorporates an Arduino UNO microcontroller, load cells for load detection, MEMS sensors to act as virtual doors for theft detection, IOT modules for sending SMS alerts and cloud data upload, GPS for location tracking and information sharing and an LCD display for data visualization.
Medication Dispensing Using Needle Free Injection
Needle-free injection techniques have advanced significantly and are now commonly used in many different industries. Modern technology has completely changed the way drugs are given, resolving typical problems with conventional hypodermic needles such needle anxiety, needle stick injuries, and the spread of infectious infections. In specialties including dermatology and dentistry, administering immunizations, peptides, proteins, and anesthetics has become common procedure with needle-free injectors. These injectors work on the basis of Lorentz force, air pressure, and spring technology. The specific application of the air-pressure technique to medicine administration is the topic of this study. An air compressor is used to create pressure, and a solenoid valve is used to control the pressure in order to accomplish this. A needle-free injector is then equipped with a tube that transfers the pressure, allowing the drug to be injected into the body via the skin's layers. Injectables are delivered to the intradermal level in an efficient manner using a variety of injection techniques, such as subcutaneous, intramuscular, and intradermal. Drug delivery technologies may progress as a result of this research, opening up new avenues for the treatment of a variety of diseases.
Soft s∗∗g-Locally Closed Sets
In the present paper, we continue the study of soft semi star generalized closed sets in soft topological spaces by introducing new concepts, namely soft s∗∗g-locally closed sets, soft s∗∗g-locally closed∗ sets, soft s∗∗g-locally closed∗∗ sets.
Soft Semi Star Star Generalized Continuous Functions
Recently soft generalized closed sets play important role in studying separation axioms in soft topological spaces. The aim of the present communication is to introduce the concepts of soft semi star star generalized continuous functions and soft semi star star generalized irresolute functions and study their basic properties in soft topological spaces.
Design of a Compact Wearable Antenna for IoT Enabled Bio-Telemetry in Diagnostic Health Monitoring System
The structure developed involves the etching of Moore’s curve onto a conventional rectangular patch and subsequently encasing it in a rectangular loop along with a defected ground structure. The proposed antenna exhibits dual-band Since the Internet of Things (IoT) enabled medical diagnostic system requires unprecedented precision and automation for better health care delivery, therefore in such systems, the performance of antennas for efficiently transferring data (vital functions of the human body) is an important task. To address these concerns, a mechanically robust, novel hybrid wearable on-body antenna inspired by Moore’s fractal based geometry and conventional rectangular loop for a diagnostic health monitoring system is proposed. with bandwidth ranging from 1.38 - 1.8 GHz and 2.25 - 4.88 GHz respectively, covering WMTS, ISM, and Personal Communication band besides covering a portion of UWB band also. The two operating bands of the antenna offer a fractional bandwidth of 38.5% and 73.7% respectively. It is observed that the average specific absorption rate (SAR) over the multi-layer phantom is 0.025 W/kg for an input power of ≈ 24 dBm. In comparison to the recently reported wearable antennas, the design proposed has a compact footprint of 0.135 λo x 0.093λo x 0.004λo besides offering a dual- band of operation, peak gain of 2.2 dBi, overall radiated efficiency of 95% and SAR below 0.025 W/kg. The design is fabricated using Rogers 5880 substrate (semi-flex) of thickness 0.75 mm.
AI Based Personalized Recommendation of Career Guidance for Students
This paper is devoted to solving the problem of determining the career guidance of student using Artificial Intelligence systems. This paper proposes an AI-based web application approach for personalized career recommendations, leveraging the strengths of Singular Value Decomposition (SVD) and XG Boost algorithms. By integrating these techniques, the proposed system aims to overcome limitations of existing methods and deliver more accurate, contextually relevant Career suggestions to students. The web application was developed by Python and uses Keras ,Numpy,Pandas libraries. Result of this paper can be used to inform the students with informed career choices that align with their unique attributes and aspirations, thereby enhancing their successful career.
Bus Navigation and Ticketing Solution
In the busy metropolitan cities people don't have time to invest in waiting for transport. Waiting time for transport in such crowded cities leads to less productivity on a whole. People face this problem in their daily life where they have no idea about the current status of their transport. So, the proposed solution is an android based application that will help the user to check out the Bus Ticket Reservation with Location Tracking System facilitates the passengers to enquire about the bus available on the basis of source and destination, booking of tickets, enquire about the status of the booked ticket, tracking the current position etc. The aim of case study is to design and develop a database maintaining the records of different trains, train status, and passenger. The current location of the bus and also will help the user to know how much time the bus will take to reach the current location of the user. The system will use GPS as the basis for the application and basic android application will be interfacing with the updated database to provide the real-time data to the user.
A Study on Talent Tech Transformation: Revamping HR with AI
This study delves into the transformative potential of talent tech integration, specifically focusing on the revitalization of Human Resources (HR) through the infusion of Artificial Intelligence (AI). As AI continues to revolutionize various industries, its application in HR holds significant promise for enhancing efficiency, productivity, and strategic decision-making. This research investigates the hurdles and opportunities associated with integrating AI into HR practices. Through a comprehensive research methodology comprising literature review, surveys, and expert interviews, this study identifies key challenges confronting HR departments, including talent acquisition, retention, performance management, and organizational development. Moreover, it explores how AI-powered solutions can address these challenges by streamlining processes, optimizing workflows, and augmenting decision-making capabilities. By leveraging insights from this research underscores the interconnected nature of challenges in HR and the cascading impact they can have on organizational effectiveness. Furthermore, it offers recommendations for the implementation of standardized AI-driven processes and procedures to enhance HR operations, mitigate challenges, and foster organizational growth. Ultimately, this study contributes valuable insights for HR professionals, policymakers, and stakeholders seeking to harness the transformative potential of AI in revamping talent management strategies, thereby driving economic growth and development.
Emergency Communication System for Hills and Forest Region Using IOT
This project presents an innovative approach to establishing robust communication systems in remote areas devoid of traditional network infrastructure. By harnessing the power of IoT and LoRa technology, the project proposes a Long Distance Communication System that not only facilitates connectivity but also supports critical emergency evacuation procedures. The cornerstone of this system is the LoRa Mesh Library, which enables a decentralized network topology, ensuring seamless communication even in the most challenging environments via ad hoc network. The project further explores QoS routing and traffic scheduling within 802.11 wireless mesh networks to guarantee consistent and quality communication links over long distances. Additionally, it integrates Secure IT, a security framework utilizing Firebase, Google Map, and Node.js, to provide real-time location-based alerts, enhancing the safety of individuals in emergency situations.Thisabstractencapsulatestheproject’smultifacetedapproach to overcoming the limitations of current communication infrastructures, offering a scalable, secure, and efficient solution that has the potential to revolutionize connectivity in isolated regions worldwide.
Design and Implementation of an Anti-Explosion System for Electric Vehicles Batteries
This research paper investigates the development and implementation of an innovative anti-explosion system designed to control the temperature of electric vehicles (EVs) during operation and parking. The system is designed to improve safety and efficiency by preventing overheating and minimizing the risk of thermal disturbances. This paper also outlines the significance and rising appeal of electric vehicles and explains the need for efficient cooling systems in electric vehicles to maintain optimal performance and safety. It introduces the concept of an explosion-proof cooling system and its potential benefits.
“EDUPLAY”- Interactive Game Based Learning Platform
This research introduces an innovative approach to inclusive education through the development of a game-based Learning platform tailored for Persons with Disabilities (PwDs). With a focus on fostering an accessible and engaging educational environment, the platform aims to break down barriers and promote equal learning opportunities for individuals with diverse abilities. The present study investigates the use of gamification to foster commitment and engagement among users with disabilities. Two case studies demonstrating the application of gamification are provided. The first is the development of an application to teach a blind person, and the second one is the creation of an application to aid individuals with Autism Spectrum Disorder (ASD) in navigating their environment. The study reveals that universal design for learning principles can be used indirectly to adjust apps for users to utilize the software consistently. This study provides preliminary evaluations for both case studies, which were undertaken with relatively small samples. The first case study revealed that three blind individuals who took part in the review scored an average of 91.7on the system usability scale. At the same time, the second case study involving the observation of a single individual with ASD also revealed that utilizing the designed app improved performance. Despite the limited sample size, the findings suggest that gamification may effectively encourage and generate commitment among the users with disabilities.
A Study on E-Commerce Warehousing Dynamics Navigating Order Fulfilment and Returns
The e-commerce over the past decade has experienced remarkable growth, reshaping shopping habits and challenging traditional supply chain methods. This surge in online shopping has compelled e-commerce firms to enhance their warehousing and order fulfilment strategies to meet rising consumer expectations for swift deliveries and hassle-free returns. Effective management of order fulfilment and reverse logistics has become essential for competitiveness in this industry. This study investigates e-commerce warehousing dynamics, emphasizing the optimization of order speed, delivery times, operational costs, and return management. Through industry reports, academic literature, and case studies, we identify best practices in five key areas: warehouse design and automation, demand forecasting, inventory control, order picking and packing processes, transportation strategies, last-mile delivery models, and reverse logistics for returns. Our research underscores the significance of highly automated warehouses equipped with advanced technologies such as robotics, automated storage and retrieval systems (ASRS), automated guided vehicles (AGVs), and intelligent software for material flow management. These innovations empower e-commerce firms to boost throughput, enhance operational flexibility, and adapt to changing demands effectively.
Application to Detect Fake Social Media Profile & Verification Using Block Chain Technology
This paper proposes a novel social media platform that leverages blockchain technology to address the rising concerns of fake profiles and privacy violations. Our system prioritizes robust identity verification through a decentralized approach and immutable user data storage on a blockchain ledger. By eliminating centralized control and single points of failure, the platform enhances trust and security in online interactions. Additionally, we integrate government-issued ID verification (e.g., Aadhaar card) through smart contracts to add an extra layer of trust and strengthen user profiles. This paper details the design, implementation, and functionalities of the proposed system, aiming to showcase its effectiveness in revolutionizing online identity verification within social media applications
Examining the Benefits and Drawbacks of Open Network Architectures in E-Commerce
The advent of digital commerce has revolutionized the way businesses operate and interact with customers. One of the key factors contributing to this transformation is the emergence of open network architectures, which facilitate seamless communication and data exchange between various entities within the e-commerce ecosystem. This research aims to provide a comprehensive analysis of the benefits and drawbacks associated with open network architectures in the context of digital commerce. And to investigate how open network architectures promote accessibility and interoperability among diverse systems, enabling seamless integration and collaboration within the e-commerce landscape. Explore the potential of open networks to foster innovation and scalability, empowering businesses to rapidly adapt to changing market demands and technological advancements. Evaluate the economic advantages of open network architectures, including reduced infrastructure costs, improved resource utilization, and streamlined operational processes. Examine the potential vulnerabilities and risks associated with open network architectures, such as data breaches, cyber threats, and privacy issues, and propose strategies to mitigate these challenges. Investigate the role of governance frameworks and industry standards in facilitating the effective implementation and management of open network architectures within the e-commerce domain. Identify and analyze the potential barriers to the widespread adoption for overcoming these challenges. This paper aims to provide a comprehensive analysis of the benefits and drawbacks associated with open network architectures in the context of e-commerce. Through real-world case studies, theoretical frameworks, and a multi-faceted approach encompassing technical, business, and strategic perspectives, we strive to equip e-commerce stakeholders with the insights necessary to navigate this complex landscape and make informed decisions that align with their organizational goals and market dynamics.
Experimental Investigation on Partial Replacement of Cement by Granite Powder on Mortar
This paper intends to investigate the possibility of producing low costs enhanced mortar by Granite powder. By taking the enormous amount of cement, it affects the environment badly and demand for cement was increasing day by day. So, by partially replacing Granite powder with cement in construction field. It can fulfill the objectives of catering to the needs of the construction sector while simultaneously promoting an eco-friendly and pristine atmosphere. Partial replacement of cement by using granite powder in mortar gives sufficient strength. The conventional mortar mix consists of cement, fine aggregate, and water. In this experimental study granite powder was used with different percentage, such as 20% 25%, 30% 35%. The mixture was prepared and mortar cubes were made and allowed for curing. It is concluded that, he immersion of cement mortar in magnesium sulphate is better when compared to sodium sulphate and the sulphate attack is lesser in magnesium sulphate. The residual compression strength for the cement mortar in the proportion of granite content 30% is higher.