Volume 12 | Issue 5

 Abstract

Sepsis is a potentially life-threatening condition that occurs when the body's response to an infection causes inflammation throughout the body. This inflammation can trigger a cascade of changes that can damage multiple organ systems, leading to organ failure and death if not treated promptly. Early recognition and aggressive treatment with antibiotics and supportive care are crucial for improving outcomes in septic patients. The " Accurate Prediction of Sepsis in ICU Patients" is a project that combines awareness and predictive modeling to address sepsis, a life-threatening condition commonly encountered in intensive care units (ICUs). This project is a robust awareness campaign designed to educate both the general public and healthcare professionals about sepsis. With focusing on generating awareness about sepsis, can lead to early detection and seeking medical help. By bringing the limelight on this disease, it can potentially save lives. Concurrently, advanced machine learning techniques, specifically random forest algorithms, are employed to construct a predictive model for sepsis. This model undergoes meticulous fine-tuning to ensure accurate identification of sepsis risk in ICU patients. It uses a dataset for training the predictive model. The integration of the Sequential Organ Failure Assessment (SOFA) score, including the quick SOFA (qSOFA) criteria, enhances predictive accuracy. The qSOFA criteria play a crucial role in rapid risk assessment for early intervention. Moreover, the project maintains a dedicated website that serves as an essential platform for sepsis education and the dissemination of the predictive model to the medical community.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sepsis, ICU, SOFA, qSOFA, Random Forest, Predictive Modelling, Awareness Campaign

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Pure essential oils are concentrated oils generated from a variety of natural plants, flowers, plant roots, seeds, resins, plant exterior tissue, trees or shrubs, and fruit rinds. These oils are well-known among humans for their benefits to the body, skin, and spirit. These oils are also commercially employed due to their superior medicinal or odoriferous characteristics. To research extraction strategies available to extract oils from plants and trees, to come across pros and disadvantages of a few extraction methods, selection and efficiency of a single method. The method used to extract essential oil from plants is critical, as some processes employ solvents that can harm the healing benefits of plants and trees. There are different extraction procedures, but the oil's quality and production never remain consistent. The Soxhlet apparatus technique was used in this investigation because of its mild extraction conditions and low operating cost. Steam is a critical component in the oil extraction process. Extraction of essential oils using diverse methods and innovative techniques reduces the risk of losing the vital component of plants and trees, reduces chemical risk, shortens extraction time, is environmentally friendly, and improves the quality and production of essential oils.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Eucalyptus oil, Steam Distillation using Soxhlet apparatus

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Railway track safety is of paramount importance to prevent accidents involving humans and animals trespassing onto the tracks, as well as natural hazards like landslides or rockfalls. To address these challenges, we propose RailGuard, an innovative system that combines computer vision and sensor technologies for enhanced safety measures. Utilizing a combination of Python, YOLOv3 algorithm, and a range of hardware components including a Raspberry Pi, Arduino Uno, LCD display, ultrasonic sensor, alarm, and DC motor, RailGuard detects and responds to potential threats in real-time. The YOLOv3 algorithm is trained to recognize specific entities such as "person", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", and "giraffe", enabling precise identification of trespassers and animals on the tracks. Upon detection, RailGuard activates the alarm and halts the movement of trains by stopping the DC motor, thereby averting potential collisions and ensuring passenger and animal safety

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Predictive Railway Safety, AI-powered Track Monitoring, Multi-sensor Obstacle Detection, Automated Train Response Systems, Self-regulating Railway Network.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract In recent years, the agricultural sector has witnessed a paradigm shift towards digitalization, driven by the integration of cutting-edge technologies such as edge and fog computing .Smart agriculture is often perceived as one key enabler when considering the twin objectives of eliminating world hunger and undernourishment. This survey delves into the transformative potential of edge and fog computing in revolutionizing smart agriculture practices. By pushing computational tasks closer to the data source, edge computing enhances real-time data processing, enabling timely decision-making and resource optimization on farms. Edge computing offers a potentially tractable model for mainstreaming smart agriculture. Additionally, fog computing extends this capability by leveraging intermediate nodes to further distribute computational tasks and manage data flows efficiently. Through a comprehensive analysis of existing literature, this survey explores the key challenges, opportunities, and emerging trends in the adoption of edge and fog computing in smart agriculture. Moreover, it investigates the integration of these technologies with other emerging technologies such as Internet of Things (IoT), artificial intelligence (AI), and block chain to create robust and sustainable agricultural ecosystems. By shedding light on the current state and future prospects of edge and fog computing in agriculture, this survey aims to provide valuable insights for researchers, practitioners, and policymakers to harness the full potential of these technologies for sustainable and efficient agricultural production.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart agriculture, Edge computing, Fog computing, Internet of Things (IoT), Digitalization.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Recent years have witnessed remarkable progress in agriculture sciences, driven by technological innovations and evolving research paradigms. This abstract provides an overview of key advancements shaping the agricultural landscape. Precision agriculture has emerged as a cornerstone, leveraging technologies like GPS, sensors, and AI to optimize resource use and enhance productivity while reducing environmental impact. Genetic engineering and genomics have revolutionized crop breeding, enabling the development of resilient varieties with improved traits. Vertical farming and controlled environment agriculture have redefined traditional farming practices, offering sustainable solutions for urban food production. Moreover, bioinformatics and big data analytics have empowered researchers to harness vast datasets for informed decision-making and predictive modeling. Agroecological approaches promote biodiversity and soil health, while remote sensing technologies enable real-time monitoring of crops and environmental conditions. Additionally, alternative protein sources and water management technologies address pressing challenges related to food security and resource sustainability. Collectively, these advancements underscore the transformative potential of agriculture sciences in addressing global challenges and fostering a more sustainable future.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agricultural Science, Enhancing Sustainability, Environmental Science

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An intrusion detection system, or IDS, is designed to be a software program that keeps an eye on system or network activity and alerts users when anything suspicious is happening. Concerns regarding how to safely transmit and preserve digital information are raised by the internet's explosive expansion and use. In order to obtain important information, hackers today employ a variety of attack techniques. New things like viruses and worms being imported as the internet becomes more prevalent in society. In order to create system vulnerabilities, malicious individuals employ a variety of methods, such as password cracking and the detection of unencrypted information. As a result, users require security to protect their system from hackers. One of the most often used security methods is the firewall mechanism, which is intended to keep private networks isolated from public networks. IDS are utilized in credit card fraud, medical applications, insurance agencies, and network-related operations. These assaults are detectable with the aid of numerous intrusion detection techniques, methods, and algorithms. This paper's primary goal is to present a comparative analysis of intrusion detection methods utilizing different deep learning and machine learning approaches. In this paper we can

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

-- Intrusion detection, Machine learning, Deep learning, Convolutional neural network, Network datasets

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research outlines an incredibly easy-to-use and effective technique for identifying Malayalam text in color, natural scene photos captured offline using a mobile phone camera. Important phases in text understanding from natural scene photographs are Malayalam text detection, text segmentation, skew correction of the discovered text, and character recognition.For a variety of applications, including text translation in other nations and assistive technology for the blind, text understanding in natural scene photos is crucial.Malayalam's high degree of complexity in comparison to other languages has made it difficult to learn. The experimental findings demonstrate that our approach can effectively extract and recognize text with little complexity, making it suitable for usage in mobile devices with constrained capabilities.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skew angle estimation, text detection, text segmentation, text recognition

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Hydrophobic silica aerogel is known as "Frozen Smoke". Its lightweight porous materials exhibit exceptional properties. This abstract provides an overview of hydrophobic silica aerogel. It's synthesized through a sol-gel process where it's modified to hydrophobic properties by replacing -OH groups. This hydrophobicity also preserves the aerogel's low density, high porosity, and thermal insulating properties. These allergies have multiple applications due to their extraordinary properties. In aerogel properties low density and high porosity are applicable in lightweight materials such as in spacecraft technology. In this abstract, we get the details of the preparation method, characteristics, hydrophobicity of silica aerogel, Chemical Reaction, and their application in the future perspective research technology.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Silica aerogel, parameters, Hydrolysis and condensation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's world, where people are increasingly concerned about their health and dietary choices, the primary dilemma we face is the quantity and quality of the ingredients we add to our meals. As our understanding evolves, we recognize that eating isn't just about keeping hunger away; it's also about mindful intake, essential for maintaining health and fitness. In this endeavor, we use modern technologies such as machine learning and human pose estimation techniques to address these challenges. Our users receive personalized diet plans, carefully tailored to consider the nutritional content of the recommended foods, helping them in achieving their dietary objectives. Users provide information such as age, weight, height, food preferences, and goals, which is utilized to calculate their BMI and prescribe a customized diet plan, with the flexibility to adjust according to their preferences. However, a healthy diet alone is not sufficient for fitness; a proper workout regimen is also crucial. Thus, users are provided with a curated set of exercises, monitored through Human Pose Estimation technology. This technology enables the identification of key points and angles between landmarks, facilitating the monitoring of exercise execution to ensure correct form and repetitions, ultimately guiding users toward their fitness goals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

BMI(Body Mass Index), K-Means Clustering, OpenCV, Media pipe

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social interaction impairments are core to Autism Spectrum Disorder (ASD), including atypical eye contact in social contexts. Early ASD screening remains challenging, while traditional methods like EEG or MRI can be impractical for young children. Eye-tracking offers a child-friendly alternative for investigating visual attention patterns in ASD. This study develops a low-cost eye-tracking system using WebGazer and heatmap.js libraries to facilitate early ASD screening. The system aims to improve accessibility and detection rates compared to existing methods by analyzing children's eye gaze patterns.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autism, Autism Spectrum Disorder, Eye-Tracking, Early Detection

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Semantic similarity measures play a crucial role in various natural language processing tasks, aiding in tasks such as information retrieval, text classification, and semantic search. This paper provides a comprehensive review of semantic similarity measures, examining their methodologies, applications, and performance. We discuss different approaches to measuring semantic similarity, including knowledge-based, corpus-based, and hybrid methods, highlighting their strengths, limitations, and comparative evaluations. Additionally, we explore the challenges and future directions in semantic similarity research, aiming to provide insights for researchers and practitioners in the field of natural language processing.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Semantic similarity, natural language processing, knowledge-based methods, corpus-based methods, hybrid methods.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the rapidly evolving field of artificial intelligence, the ability to generate data Visualizations through natural language queries represents a significant advancement. This presentation explores the capabilities of models like GPT-3, ChatGPT, and Codex in transforming textual descriptions into graphical data insights. By leveraging deep learning and transformer architectures, these models facilitate an intuitive interface for data interaction, enhancing decision-making and analytical processes.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

data Visualizations

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This work introduces a pioneering experiment in forest wildfire detection, merging digital image processing, machine learning, and deep learning. Unlike traditional methods, our approach addresses accessibility and accuracy issues by splitting the task into two modules: wildfire image classification and wildfire region detection. Introducing innovative algorithms like Reduce-VGGnet for classification and an optimized CNN for region detection, we achieve remarkable accuracies of 91.20% and 97.35% respectively. Notably, our framework bridges the gap between research and education, offering a practical and efficient experiment for Machine Vision courses. Furthermore, by extending traditional classifiers like VGG16 to VGG19, we elevate accuracy, paving the way for enhanced wildfire detection methodologies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

wildfire, deep learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rise in cross-border mergers and acquisitions (M&A) has significantly altered the global economic environment, with serious consequences for India's economy. This research study looks on the legal elements of cross-border M&A transactions and their impact on the Indian economy. The essential legal elements of cross-border M&A transactions are discussed, including regulatory approvals, competition law compliance, intellectual property rights, and tax implications. The paper investigates the difficulties and complexity of navigating numerous legal systems across jurisdictions, highlighting the importance of extensive due diligence and strategic preparation. Furthermore, the study paper examines the influence of cross-border mergers and acquisitions on the Indian economy. It balances the potential benefits, such as access to new markets, technology transfer, and greater competitiveness, against the challenges, which include regulatory scrutiny, cultural integration, and post-merger integration concerns. Case studies and statistics are utilised to show the real-world effects of cross-border mergers and acquisitions on the Indian economy. The article examines significant mergers and acquisitions involving Indian firms, concentrating on the results and lessons learned.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: Cross-border M&A, mergers, acquisitions, competition law, inbound, outbound

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study of judicial review in comparative constitutional law is often perplexing. At one level, the theory on judicial review has kept up with global developments, with scholars seeking to answer how judicial review can go beyond its traditionally understood role to address contemporary challenges .At another level, the age-old debate of whether judicial review by unelected judges should exist at all in a constitutional democracy rages on. This paradox is partly attributable to the fact that the study of judicial review has splintered into the study of judicial review of specific issues that arise in a constitution, such as the judicial review of socio-economic rights, judicial review of constitutional amendments, and judicial review of matters relating to federalism and democracy, with little attention to whether and how they all fit together to form a cohesive theory of judicial review. Literally the notion of judicial review means the revision of the decree or sentence of an inferior court by a superior court. Judicial review has a more technical significance in pubic law, particularly in countries having a written constitution which are founded on the concept of limited government. Judicial review in this case means that Courts of law have the power of testing the validity of legislative as well as other governmental action with reference to the provisions of the constitution. The doctrine of judicial review has been originated and developed by the American Supreme Court, although there is no express provision in the American Constitution for the judicial review. In Marbury v. Madison, the Supreme Court made it clear that it had the power of judicial review. Chief Justice George Marshall said," Certainly all those who have framed the written Constitution contemplate them as forming the fundamental and paramount law of the nations, and consequently, the theory of every such Government must be that an act of the legislature, repugnant to the Constitution is void". There is supremacy of Constitution in U.S.A. and, therefore, in case of conflict between the Constitution and the Acts passed by the legislature, the Courts follow the Constitution and declare the acts to be unconstitutional and, therefore, void. The Courts declare void the acts of the legislature and the executive, if they are found in violation of the provisions of the Constitution.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Judicial review , constitution ,court

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Shock absorbers are a critical part of a suspension system, connecting the vehicle to its wheels. The need for dampers arises because of the roll and pitches associated with vehicle maneuvering, and from the roughness of road. This led to make the ride quality for the people very uncomfortable which led to invention and innovation of shock absorbers. Shock absorbers are devices that smooth out an impulse experienced by a vehicle, and appropriately dissipate or absorb the kinetic energy. Shock absorbers have become such an essential component of an automobile. Suspension system is the main part of the vehicle which is used for comfort and for better ride through rough roads. It absorbs shocks and vibration by providing smooth functioning to the vehicle. Currently there are different types of suspension in the market. In this study, mono suspension and dual suspension was considered. Comparing the ride quality of mono suspension and dual suspension of two-wheeler vehicles to know how they differ from each other by performing static structural analysis under different loading conditions by designing 3D model of suspension system using software like CATIA V5 and ANSYS for performing analysis.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Suspension system, Mono suspension, Twin suspension, Ansys, Catia, Maximum shear stress, Factor of safety, Total deformation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper investigates the vulnerability of Deep Neural Networks (DNNs) to adversarial attacks, focusing on facial recognition systems. Despite their robustness, DNNs can be manipulated using specific triggers like facial characteristics without compromising overall performance on legitimate inputs. We propose using these triggers to compromise backdoored facial recognition systems, demonstrating real-time attack capabilities. Furthermore, we extend this research by implementing an advanced VGG16 algorithm. Our findings reveal that while VGG16 achieves impressive accuracy of 95-100% on original images, it shows susceptibility with 85% accuracy on tricked images. This study underscores the importance of enhancing DNNs' resilience against such targeted attacks to ensure the security and reliability of facial recognition systems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

FaceHack, DNNs

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Education shapes, modifies and builds an individual. In the system of education, the teachers play crucial roles in the growth and development of a child. Therefore, the perspectives of teachers are very important for the social, emotional, intellectual and overall development of a child. There are many children who are challenged and differently abled, and need special care and education. It has been seen that inclusive education helps them to adapt and reconcile in society. Inclusive education class is one in which the students, regardless of their disabilities, study in the same classroom with normal students. This study is designed to glimpse the perspectives of the teachers towards challenged children. A self-constructed questionnaire was administered for studying the perspective of the teachers. The result shows that though the teachers are aware of the concept of inclusive education they are not knowledgeable enough to handle the challenged children in an inclusive school. Therefore, professional training programme are essential for the teachers for the success of inclusive system of education.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Education, perspectives, inclusive, disabilities, challenged children, professional training.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

While often perceived as a safer alternative to conventional cigarettes, emerging evidence suggests e-cigarettes are far from harmless. This review examines the link between e-cigarette use and both acute lung injury and sub-clinical lung dysfunction. Though long-term consequences remain under investigation, current findings reveal concerning effects. E-cigarettes trigger blood vessel constriction, immune system hyperactivity, and a thinning of the lung's inner lining. Notably, their design facilitates efficient nicotine delivery, comparable to conventional cigarettes, raising concerns about nicotine dependence in non-smokers and increased severity in existing users. The composition of e-liquids and the hardware itself can further influence nicotine exposure. In conclusion, a growing body of evidence challenges the myth of e-cigarette safety, urging further research and potential re-evaluation of public health policies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

e-cigarette, vaping, e-liquid, nicotine retention , addiction

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study delves into how student engagement with Blackboard, a prevalent Learning Management System in higher education, shapes their academic achievements. Employing a mixed-methods approach, it examines four deep learning models to predict student performance using Key Performance Indicators (KPIs) derived from Blackboard data. Analyzing data from seven courses, potential predictive KPIs are identified through documentary analysis. Correlational studies unveil significant associations between these factors and student performance metrics. The study demonstrates the efficacy of a combined CNN-LSTM predictive model in accurately forecasting outcomes. These findings advocate for the utilization of such models to optimize Blackboard's utility and bolster educational interventions in universities. Additionally, the integration of BI-LSTM extends the study's accuracy range to 95-100%, showcasing its potential in refining predictive capabilities further.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Learning Outcomes, CNN, LSTM

  License

Creative Commons Attribution 4.0 and The Open Definition