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Impact of 3D printed components and ventilators on COVID-19
The disease caused by a virus known as the novel Coronavirus, also known as "COVID-19" by the public, was classified as a major epidemic by the World Health Organisation in 2019. Each country across the globe is affected by COVID-19. While writing this, over 150 million people were affected by the fast-spreading deadly pandemic, and over 3.5 million deaths due to COVID-19 were reported worldwide as per WHO's official COVID-19 dash panel-https://covid19.who.int/Economy and social life of no territory on earth was left unaffected by the COVID-19. Now vaccines are ready, it may take a reasonable amount of time to complete the vaccination process. One major challenge was the need for more support equipment like Beds, Oxygen Cylinders, and Ventilators. Improvisation in the mass production of many critical components, especially those supporting 3D printing technology, has shown some well-managed results in handling the shortage of many critical components. This chapter examines and describes how 3D printing technologies were used during the dangerous pandemic. It aims to describe many 3D-printed devices like face masks, face shields, various valves, etc. It also makes an effort to point out the dominant drawbacks of additive manufacturing technology in this area and examines the options for a future pandemic. 2023 Bentham Science Publishers. All rights reserved. -
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Immortality and beyond: review of the film Seo Bok
[No abstract available] -
Immobilized proline-based electro-organocatalyst for the synthesis of bis-?-diketone via Knoevenagel condensation reaction
In the quest for more sustainable chemical processes, we devised a technique using electro-organocatalysis to synthesize bis-?-diketone compounds via Knoevenagel condensation of benzaldehyde and dimedone. Our approach involves a modified electrode fabricated via anchoring L-proline onto a carbon fiber paper electrode supported by poly-3,4-diaminobenzoic acid (PDABA), which enhances efficiency in addition to the simple catalyst separation from the reaction mixture in heterogeneous catalysis. The electrochemical and surface topographical studies for the fabricated electrode were carried out, revealing high efficiency in comparison to the bare carbon fiber paper electrode. This electrochemical reaction operates under mild conditions utilizing lithium perchlorate and acetonitrile, yielding high amounts of the desired product. This study showcases a promising pathway for producing valuable organic compounds in an environmentally friendly manner, marking a significant stride forward in sustainable synthesis practices. 2024 Elsevier Ltd -
Immersive Technologies: Navigating the Impacts, Challenges, and Opportunities
Immersive technology is going to govern the next generation in terms of education, health, military, tourism, and much more. Through its comprehensive exploration, didactic approach, and insightful analyses, this book provides an invaluable resource for understanding and harnessing the power of immersive technology. Immersive Technologies: Navigating the Impacts, Challenges, and Opportunities serves as a guiding compass through the immersive technology landscape and takes a multifaceted approach, addressing both the technical and human aspects. The book dissects the underlying methods and technologies that power immersive experiences, offering readers a clear understanding of how VR, AR, and MR function. The latest advancements, from cutting-edge hardware developments to revolutionary software applications are discussed in detail. The book also delves into the potential societal impacts and takes the reader on a journey from education to healthcare, entertainment to remote collaboration, so the reader can gain insights into the myriad of ways immersive technology is already shaping industries and human interaction. The ultimate benefit readers will derive from this book is a holistic grasp of the immersive technology landscape and they will be armed with knowledge about the challenges and opportunities presented by VR, AR, and MR. They will be well-equipped to navigate the future. This is a must-read for anyone interested in how this technology has the potential to reshape our world. Academicians will be enriched with the applications and practical perspectives. 2025 Sagaya Aurelia. -
Imidazopyridine Hydrazine Conjugates as Potent Anti-TB Agents with their Docking, SAR, and DFT Studies
Novel imidazopyridines hydrazine conjugates were designed and synthesized for their anti-tubercular (anti-TB) activity. A cytotoxicity assay was conducted with Vero cells to determine the safety profile of the most effective compounds. It was found that compound (IA3) (MIC=0.78 ?M) and (IA8) (MIC=1.12 ?M) were nearly 3.7 and 2.5 times more active than pyrazinamide. Based on Density functional theory (DFT), these molecules exhibited better charge transfer between molecular orbital's, which made them suitable for biological applications. Molecular docking on Mycobacterium tuberculosis InhA bound to NITD-916 (PDB: 4R9S) revealed that compounds possessed greater binding affinity towards proteins. In addition, the most active anti-TB compounds (IA3) and (IA8) exhibited high levels of interaction with the target protein and exceptional safety profile, suggesting they may prove to be effective leads for new drugs. 2024 Wiley-VCH GmbH. -
Imidazopyridine chalcones as potent anticancer agents: Synthesis, single-crystal X-ray, docking, DFT and SAR studies
New imidazopyridinechalcone analogs were synthesized through the ClaisenSchmidt condensation reaction. The newly synthesized imidazopyridine-chalcones (S1S12) were characterized using spectroscopic and elemental analysis. The structures of compounds S2 and S5 were confirmed by X-ray crystallography. The global chemical reactivity descriptor parameter was calculated using theoretically (DFT-B3LYP-3-211, G) estimated highest occupied molecular orbital and lowest unoccupied molecular orbital values and the results are discussed. Compounds S1S12 were screened on A-549 (lung carcinoma epithelial cells) and MDA-MB-231 (M.D. Anderson-Metastatic Breast 231) cancer cell lines. Compounds S6 and S12 displayed exceptional antiproliferative activity against lung A-549 cancer cells with IC50 values of 4.22 and 6.89 M, respectively, compared to the standard drug doxorubicin (IC50 = 3.79 ?M). In the case of the MDA-MB-231 cell line, S1 and S6 exhibited exceptionally superior antiproliferative activity with IC50 of 5.22 and 6.50 ?M, respectively, compared to doxorubicin (IC50 = 5.48 ?M). S1 was found to be more active than doxorubicin. Compounds S1S12 were tested for their cytotoxicity on human embryonic kidney 293 cells, which confirmed the nontoxic nature of the active compounds. Further molecular docking studies verified that compounds S1S12 have a higher docking score and interacted well with the target protein. The most active compound S1 interacted well with the target protein carbonic anhydrase II in complex with pyrimidine-based inhibitor, and S6 with human Topo II? ATPase/AMP-PNP. The results suggest that imidazopyridine-chalcone analogs may serve as new leads as anticancer agents. 2023 Deutsche Pharmazeutische Gesellschaft. -
Imagining the sustainable future with Industry 6.0: A smarter pathway for modern society and manufacturing industries
Industry is defined as the production of goods and services through the transformation of raw materials and resources into valuable products. It involves the creation of finished products or services through various stages of production that may include manufacturing, processing, assembly, packaging, and distribution. Industries have played a significant role in the economic growth and development of nations throughout history. They have contributed to the creation of employment opportunities, the development of new technologies, and the improvement of living standards. Over the years, the industrial sector has gone through numerous changes, and each of these changes has been termed as an "Industry Revolution." 2024, IGI Global. All rights reserved. -
Image Steganography Using Discrete Wavelet Transform and Convolutional NeuralNetwork
The practice of steganography involves concealing messages within another thing, which is referred to as a carrier. Is thus performed in order to build up a covert communication channel in a rather way that any observers whom has access to such a channel will not be able to detect the act of communication itself. In this research, using the process of stenography, a secret text is transferred across a communication channel using an image as a cover. Discrete Wavelet Transform (DWT) and Convolutional Neural Network (CNN) is used in the above process. The encoding and decoding operation is done by using DWT while the preprocessing and training of images is done by CNN. The training and prediction rate of CNN is 72.4 %. 2022 IEEE. -
Image Recognition, Recusion Cellular Classification Using Different Techniques and Detecticting Microscopic Deformities
Deep convolutional neural networks (CNNs) have turn out to be one of the most advanced approaches trendy distinguishing snapshots in extraordinary fields. White blood cell classification is crucial for diagnosing anaemia, leukaemia, and a variety of other hematologic illnesses. Transfer learning with CNNs is frequently used in biological image categorization. Traditional methods for WBC classification is costly is terms of time and money. In the paper three convolutional neural network architectures are proposed which is based on transfer learning for microscopic image classification and compare the performance of models. The paper compares Transfer learning models like VGG-16, VGG-19, VGG-19 SVM hybrid and AlexNet. VGG-16 gives the best classification performance in comparison. VGG-16 model is which has a train accuracy of 0.9538 and train loss of 0.1322. 2022 IEEE. -
Image Processing and Artificial Intelligence for Precision Agriculture
Precision agriculture is a novel approach to increase the productivity of crops that employs recent technologies such as Artificial Intelligence, WSN, cloud computing, Machine Learning, and IoT. This paper reviews the development of different techniques effectively used in precision agriculture. The paper details the technological impact on precision agriculture followed by the different image processing schemes such as Satellite imagery and unmanned aerial vehicle (UAV). The role of precision agriculture is disease detection, weed detection from UAV images, and detection of trees and contaminated soils from satellite imagery is discussed. It reviews the impact of artificial intelligence (AI) namely machine learning &deep learning in precision agriculture. The performance of the recent image processing schemes in precision agriculture is analyzed. The paper also discusses the challenges that exist in implementing the precision agriculture system. 2022 IEEE. -
Image Pre-Processing Algorithms for the Quality Detection of Tea Leaves
This Identification and prediction of the tea quality is the essential research focus nowadays in the field of agriculture. Nowadays the Artificial Intelligence has become the latest topic in the region of pattern recognition. The various combination and permutation of the different techniques has resulted in proper solving the problem as well as have better accuracy in recognition. Therefore, there is urge need of a detailed survey AI techniques used for the identification of the tea leaf quality for the different grades of tea plants. In this paper, we aim on the various methods used for the pre- processing of the input image to extract the processed image which will further be useful for the feature extraction and the classification of the proposed image. It is very important to get the effective and accurate processed data which will further act as an input for the next level modules. This paper shows various methods of edge detection are applied on the image like Canny, Sobel and Laplacian are used. The further results are compared for quality metrics parameters such as the Mean Square Error (MSE) & Structural Similarity Index Metric (SSIM). The main agenda of this paper is to perform the edge detection and to check the quality measure of the processed image. The software used here is python. 2022 IEEE. -
Image Exhibits
Pride of India stamp collection and palm leaves collection. The Pride of India Collection is the first and most important stamp Ingot collection ever produced for India.Palm leaf bound manuscripts were the original mode of preserving stories and records in ancient Kerala. The technique used palm tree leaves that were processed by boiling and dyeing before being engraved (usually in Sanskrit) using an Ezhuthani (Metal Pen). Palm leaf manuscripts were written in ink on rectangular-cut, cured palm leaf sheets. -
Image Encryption and Compression using Embedding Technique
Encryption is used to securely transmit data in open networks. Each type of data has its own features; therefore different techniques should be used to protect confidential image data from unauthorized access. Most of the available encryption algorithms are mainly used for textual data and may not be suitable for multimedia data such as images. For secure transmission, various compression and encryption techniques are proposed to satisfy a fast and secure transmission. However these two techniques must be studied separately. In this paper we propose a method combining encryption and compression based on Embedding and Extracting and Discrete Cosine Transform (DCT). For encryption, target images are covered with an insignificant image to hide them and it is transmitted to destination. The receiver reconstructs the original images by extracting the insignificant image. For compression process, using DCT the size of transmission can be reduced. Through several computer simulations, the performance of the proposed method is confirmed. -
Image contrast enhancement by scaling reconstructed approximation coefficients using SVD combined masking technique
The proposed method addresses the general issues of image contrast enhancement. The input image is enhanced by incorporating discrete wavelet transform, singular value decomposition, standard intensity deviation based clipped sub image histogram equalization and masking technique. In this method, low pass filtered coefficients of wavelet and its scaled version undergoes masking approach. The scale value is obtained using singular value decomposition between reconstructed approximation coefficients and standard intensity deviation based clipped sub image histogram equalization image. The masking image is added to the original image to produce a maximum contrast-enhanced image. The supremacy of the proposed method tested over other methods. The qualitative and quantitative analysis is used to justify the performance of the proposed method. 2015 The Science and Information (SAI) Organization Limited. -
Image captcha cropping using symbols (ICS) /
Patent Number: 202041010986, Application: Dr.K.Suresh Kumar.
Web Security invention has grownup extremely vital over the years as the internet has become the place for the behavior of business in today's world. Numerous attacks stated worldwide that hamper web security by creating a substantial threat to appreciate user data. One amid them is a phishing attack. It is a technique by which an attacker attempts to snip vital data such as user names, PINs, and other private facts by constructing fake websites and cover them as if they remained legitimate ones. -
Image and signal processing in the underwater environment
To handle submerged action recognition, researchers must first understand the fundamental principles of photonic crystals mostly in the liquid phase. Deterioration effects are produced by the mediums physical attributes, which are not present in typical pictures captured in the air because light is increasingly reduced as it passes through water, submarine pictures are characterized by low readability. As a consequence, the sceneries are poorly contrasting and murky. Its vision capability is limited to approximately twenty meters in clear blue water and five meters or less in muddy water due to light dispersion. Absorbing (the removal of incident light) and dispersion are the two factors that produce light degradation. So the actual quality of submersible digital imaging is influenced by the destructive interference processes of light in water. Longitudinal scattered (haphazardly diverted light traveling from objects to the cameras) causes picture details to be blurred. 2021, SciTechnol, All Rights Reserved. -
Image Analysis of MRI-based Brain Tumor Classification and Segmentation using BSA and RELM Networks
Brain tumor segmentation plays a crucial role in medical image analysis. Brain tumor patients considerably benefit from early discovery due to the increased likelihood of a successful outcome from therapy. Due to the sheer volume of MRI images generated in everyday clinical practice, manually isolating brain tumors for cancer diagnosis is a challenging task. Automatic segmentation of images of brain tumors is essential. This system aimed to synthesize previous methods for BSA-RELM-based brain tumor segmentation. The proposed methodology rests on four fundamental pillars: preprocessing, segmentation, feature extraction, and model training. Filtering, scaling, boosting contrast, and sharpening are all examples of preprocessing techniques. When doing segmentation, a clustering technique based on Fuzzy Clustering Means (FCM) is used to breakdown the overall dataset into numerous subsets. The proposed approach used the region of filling for feature extraction. After that, a BSA-RELM is used to train the models with the input features. The proposed technique outperforms BSA and RELM, two of the most common alternatives. There was a 98.61 percent success rate with the recommended method. 2023 IEEE. -
IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indi-cator of diabetic retinopathy. With that in mind, the purpose of this work is to cre-ate an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine (SVM)-based classification to separate normal and abnormal fundus images at the first level. The input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix (GLCM). Furthermore, the presence of Exudate and Diabetic Retinopathy (DR) in fundus images is detected using the Adaptive Neuro Fuzzy Inference System (ANFIS) classifier at the second level of classification. Exudate detection, blood vessel extraction, and Optic Disc (OD) detection are all processed to achieve suitable results. Furthermore, the second level processing comprises Morphological Component Analysis (MCA) based image enhancement and object segmentation processes, as well as feature extraction for training the ANFIS clas-sifier, to reliably diagnose DR. Furthermore, the findings reveal that the proposed model surpasses existing models in terms of accuracy, time efficiency, and precision rate with the lowest possible error rate. 2023, Tech Science Press. All rights reserved. -
ILeHCSA: an internet of things enabled smart home automation scheme with speech enabled controlling options using machine learning strategy
Nowadays, communication schemes and the related automation logics have improved drastically, and people are moving from classical to intelligent applications. This naturally raises the growth ratio of the automation industry and enables researchers to work accordingly. The field of automation is essential in specific unavoidable environments such as hospitals, industrial units, individual residences, disaster areas, etc. In this paper, a novel machine-learning enabled speech-based home automation system is designed, called Intelligent Learning-enabled Home Controlling with Speech Assistance (ILeHCSA). This scheme integrates several latest technologies to control the home intelligently, including machine learning, speech assistance technology, and Internet of Things (IoT) support. Based on these advanced technologies, the logic of smart home automation systems has been designed in this approach, and it provides intellectual home controlling options to people. The following are the devices and sensors which are essential to control the electronic devices embedded into the home environment: Node Microcontroller Unit (MCU) Wi-Fi enabled Microcontroller, Relay Unit, Voice Capture Module with Mic, Speech-to-Text (STT) Converter Module, and Global Positioning System (GPS) to identify the location of the device. The machine-learning logic is utilized to provide a statistical analysis of device usage and to provide a clear summary and traces to maintain the device accordingly. These smart technologies can innovatively change the living atmosphere with sufficient support and comfort. The main intention of this paper is to provide a robust home automation system to support people efficiently, especially the people who are physically suffering from illness and the aged ones. The proposed work provides a 96.5% accuracy ratio when compared with other methods. 2021 Nismon Rio Robert et al.