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Early bruise detection, classification and prediction in strawberry using Vis-NIR hyperspectral imaging
The most frequent kind of damage to strawberries is bruising. However, most of the bruises are so barely perceptible at an early stage on the surface, that detection of them with the human eye is quite challenging. This study proposes a method for accurately detecting and classifying the damage using reflectance imaging spectroscopy. In order to carry out the study, an experiment was devised to artificially induce bruises and a dataset was generated at different bruise intervals. A model for detecting and classifying bruises at their latent stage was developed using machine learning classifiers, including support vector machines (SVM), k-nearest neighbors (KNN), linear discriminant analysis (LDA), random forest (RF), and decision tree (DT), to investigate the changes over time after bruise occurrence on the detection performance. Regression models for the prediction of bruising time were developed using partial least square regression (PLSR), RF, gradient boosting (GB), support vector regression (SVR), and DT. Among the compared models, both SVM and LDA could achieve 99.99 % classification accuracy. RF was regarded as being the most advisable for detection and prediction jobs due to its high performance. It achieved MSE of 0.052 and R2 of 0.989 for prediction. 2024 Elsevier Ltd -
Early detection of breast cancer using ER specific novel NIR fluorescent dye conjugate: A phantom study using FD-f-DOT system
Fluorescence diffuse optical tomography (f-DOT) is an imaging technique that can quantify the spatial distribution of fluorescent tracers in small animals and human soft tissues. Efficacy of f-DOT imaging can be improved by tagging a functional group to the dye. A novel estrogen receptor (ER) specific near-infrared (NIR) fluorescent dye conjugate was synthesized which can be effectively used for detecting breast cancer tissues at an early stage. Our novel dye, Near Infrared Dye Conjugate-2 (NIRDC-2), is a conjugate of 17?-estradiol with an analogue of Indocyanine Green dye, bis1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. Our present study focuses on imaging cylindrical silicone phantoms using Frequency Domain f-DOT system. Background absorption and scattering coefficients were 0.01mm-1 and 1mm-1 respectively. 10?M concentration of NIRDC-2 and Indocyanine Green (ICG) were administered separately into a cylindrical hole (target) of size 8mm diameter in the phantom. In-silico studies were performed to analyze the properties of dyes using experimental data. Absorption coefficient of 0.0002 mm-1 was recovered for the background. Fluorophore absorption coefficient at the target recovered were 0.000173 mm-1 and 0.000408 mm-1 for ICG and NIRDC-2 respectively. In comparison with ICG, our novel dye had a two fold higher target to background contrast. Recovered target position was accurate but size altered. In concurrence with the recovered fluorescent property and the cell lines studies carried out earlier, binding properties of NIRDC-2 makes it a potential probe for the early tumor detection using f-DOT system. COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. -
Early Detection of Cervical Cancer using Machine Learning Classifiers for Improved Diagnosis in Underserved Regions
One of the incurable diseases that affect women is cervical cancer. It is brought on by a protracted infection of the skin and the vaginal mucous membrane cells. The Human Papilloma Virus (HPV), is the main factor causing aberrant cell proliferation in the area around the cervix. There are no symptoms present when the illness first appears. Early detection of this malignancy may be used to prevent death. People in less developed countries cannot afford to periodically examine themselves due to a lack of awareness, poor medical infrastructure, and expensive medication. The EDA technique is applied to examine the data and understand its characteristics. Machine Learning algorithm has been used to diagnose cervical cancer. In order to spot the existence of cervical cancer, five machine learning classifiers are utilized, the algorithms to begin earlier. The Logistic Regression classifier's results validate the correct stage prediction. 2023 IEEE. -
Early diagnosis of COVID-19 patients using deep learning-based deep forest model
Coronavirus disease-19 (COVID-19) has rapidly spread all over the world. It is found that the low sensitivity of reverse transcription-polymerase chain reaction (RT-PCR) examinations during the early stage of COVID-19 disease. Thus, efficient models are desirable for early-stage testing of COVID-19 infected patients. Chest X-ray (CXR) images of COVID-19 infected patients have shown some bilateral changes. In this paper, deep transfer learning and a deep forest-based model are proposed to diagnose COVID-19 infection from CXR images. Initially, features of X-ray images are extracted using the well-known deep transfer learning model (i.e., ResNet101), which does not require tuning many parameters compared to the deep convolutional neural network (CNN). After that, the deep forest model is utilised to predict COVID-19 infected patients. The deep forest is based upon ensemble learning and requires a small number of hyper-parameters. Additionally, the proposed model is trained on a multi-class dataset that contains four different classes as COVID-19 (+), pneumonia, tuberculosis, and healthy patients. The comparisons are drawn among the proposed deep transfer learning and deep forest-based models, the competitive models. The obtained results show that the proposed model effectively diagnoses COVID-19 infection with an accuracy of 99.4%. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Early Identification and Detection of Driver Drowsiness by Hybrid Machine Learning
Drunkenness or exhaustion is a leading cause of car accidents, with severe implications for road safety. More fatal accidents could be avoided if fatigued drivers were warned ahead of time. Several drowsiness detection technologies to monitor for signs of inattention while driving and notifying the driver can be adopted. Sensors in self-driving cars must detect if a driver is sleepy, angry, or experiencing extreme changes in their emotions, such as anger. These sensors must constantly monitor the driver's facial expressions and detect facial landmarks in order to extract the driver's state of expression presentation and determine whether they are driving safely. As soon as the system detects such changes, it takes control of the vehicle, immediately slows it down, and alerts the driver by sounding an alarm to make them aware of the situation. The proposed system will be integrated with the vehicle's electronics, tracking the vehicle's statistics and providing more accurate results. In this paper, we have implemented real-time image segmentation and drowsiness using machine learning methodologies. In the proposed work, an emotion detection method based on Support Vector Machines (SVM) has been implemented using facial expressions. The algorithm was tested under variable luminance conditions and outperformed current research in terms of accuracy. We have achieved 83.25 % to detect the facial expression change. 2013 IEEE. -
Early prediction of lungs cancer by deep learning algorithms from the CT images with LBP features
The early prediction of the any type of cancer can save the lives of many especially if it is lung cancer which is one of the deadly diseases in the world. Thus the early prediction is implemented we can increase life expectancy and bring the mortality level low. Although there are various methods to detect the lung cancer cells by X-ray and CT scans, however the CT images are more preferred. The 2D images like CT scans are used to get medical results more accurate. The proposed method here will discuss how the LBP features are used to analyze the CT images with the support of Deep Learning methods. In this research work we will discuss how the image manipulation can be done to achieve better results from the CT images through various image processing methods. LBP features helps in estimating the distribution of local binary pattern of an image. A final result with 93% is achieved after the training of the processed images by LBP features. 2020 SERSC. -
Early Prediction of Plant Disease Using AI Enabled IOT
India is an industrialized country, and about 70% of the residents rely on agriculture. Leaves are damaged by chemicals, and climates issues. An unknown illness is found on plants leads to the lowering of quality of produced. Internet of Things is a practice of reinventing the wheel agriculture by enabling farmers to tackle the problems in the industry with practical farming techniques. IoT helps to inform knowledge about factors like weather, and moisture condition. We proposed IoT, ML, and image processing based method to identify the infection. IOT enabled camera to capture the image then required region of interest is extracted. After ROI extraction, image is enhanced to remove the unwanted details form the image and to improve image quality. We compute image features. At the end we do the classification which is a twostep process training and testing and done by SVM. Our proposed method gives 92% accuracy. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Early stage detection of osteoarthritis of the joints (hip and knee) using machine learning
This study explores the developing relationship between health care and technology, with a special emphasis on the use of machine learning (ML) algorithms to detect early stage osteoarthritis (OA) in the hip and knee joints. OA, a substantial worldwide health problem, requires improved diagnosis techniques. In this analysis, we illuminate the limitations of traditional methods, emphasizing the inherent subjectivity of clinical assessments and the delay in detection using routine imaging techniques. The research investigates the potential of ML to bring about significant changes. It focuses on combining various algorithms with extensive datasets and highlights the need to select relevant features and prepare the data to improve the accuracy of the models. The use of ML is closely connected to ethical issues, which include the protection of data privacy and the capacity to comprehend the models used. To bridge the gap between theory and practice, the chapter presents concrete examples of ML's practical use in detecting OA, opening possibilities for customized therapy and enhanced patient results. The chapter also highlights potential areas for future study, emphasizing the urgent requirement for additional progress in ML-based early detection techniques to alleviate the worldwide impact of OA. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Early strength of concrete amended with waste foundry sand - A potential for early open to traffic (EOT) pavements
The most predominant and widely practiced methods for waste disposal are Landfill, Incineration, and composting. There is a scarcity of land for waste disposal and because of increasing land cost, recycling and utilization of industrial by-products and waste materials has become an attractive proposition to waste disposal. There are several types of industrial by-products and waste materials. The utilization of such materials in concrete not only decreases the overall cost of construction but also helps in reducing disposal concerns. One such industrial by-product is waste foundry sand (WFS). The annual production is about 3 million tons from different industries in India. In the metal casting process, foundry industries dispose of huge quantities of waste sand into landfills, causing a harmful impact on the environment. The silica-based spent foundry sands from iron, steel, and aluminum foundries are evaluated in the risk assessment. This paper mainly focuses on achieving concrete for EOT (Early Open to Traffic) rigid pavements with WFS along with the use of accelerator and super-plasticizer. Effects of WFS on concrete properties such as compressive strength and split tensile strength are presented. Two types of mix proportions were investigated in this study. FDOT (Florida Department of transportation) and IRC (Indian Road Congress) recommendations were adopted for mix proportions using 5% & 10% of WFS replaced partially for M-Sand. 1-day compressive strength for FDOT mix with 10% WFS was 30MPa & for IRC mix with 10%, WFS was 20?MPa. The 3-days strength for mixtures with 10% WFS was 45MPa & 47MPa for FDOT & IRC mix proportions, respectively. Though the strength decreased with the inclusion of WFS, the 1-day and 3-days strength achieved for mixtures with 10% WFS surpassed the minimum strength requirements as per the slab replacement guidelines. Normally the pavement will be open to traffic after three to four days of laying asphalt, this method of using foundry sand enables the pavements to be open to traffic inless than a day. 2023 Author(s). -
Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration
Cervical cancer ranks as the fourth most common malignancy worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this study, we introduce an ensemble of machine learning and deep learning models, including DenseNet 121, ResNet 50, and XGBoost to classify the cervical intraepithelial neoplasia. A novel feature integration is proposed which ensembles the results of the individual models in five fold validation process. Our methodology is deployed on a dataset sourced from the International Agency for Cancer Research. The results from the proposed framework have shown to be accurate, robust and dependable. This method can be utilized for achieving automatic identification of cervical cancer in early stages so it can be treated appropriately. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Earthquake and flood resilience through spatial Planning in the complex urban system
Urban Communities are exposed to different disaster risks. The paper aims at understanding the interrelation of spatial planning and the resilience of the urban communities for earthquakes and floods. Various spatial planning components were used to evaluate the community resilience to earthquake and flood in the city of Pune of Maharashtra state in India. It has been identified that spatial planning contributes to a greater extent in determining community resilience. Spatial planning results in differential resilience among communities. In the study area, economically weaker households are found to be more vulnerable to disaster risk due to their spatial locations and limited accessibility to share the resources. These factors are found to be contributing to reduced resilience in the city. 2022 The Authors -
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
This paper addresses the crucial task of automatic sleep stage classification to assist sleep experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed solution presents a novel attention-based deep learning model called, Efficient Attention-sleep Model (EASM), designed specifically for sleep apnea detection using EEG signals. EASM incorporates a streamlined architecture that includes a modified Muti-Resolution Convolutional Neural Network (MRCNN), Adaptive Feature Recalibration (AFR), and a simplified Temporal Context Encoder (TCE) module to reduce complexity. To mitigate overfitting, ridge regression is utilized, which incorporates a penalty term to enhance model generalization. Furthermore, the proposed EASM utilizes a class-balanced focal loss function to address data imbalance issues. The effectiveness of EASM is evaluated on two publicly available datasets, SLEEP EDF-20 and SLEEP EDF-78. Comparative analysis of EASM against state-of-the-art models demonstrates its superior performance in terms of accuracy, training time, and model complexity. Notably, the proposed model achieves a 50% reduction in training time and a 55.7% decrease in complexity compared to the Attnsleep model. The EASM achieves a classification accuracy of 85.8% with minimum loss when compared to the Attnsleep model. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
East West Interface In 20Th Century India: Analysis Of Western Women???S Responses
In the twenty-first century, the Western world is seeking a greater understanding of the people and nations of Asia, India in particular. The thesis, ???East West Interface in 20th century India: Analysis of Western women???s responses??? is an attempt to illuminate at least an aspect of that interface during a given period of the past, so as to help shed some light on the present day Western approach to India. Throughout the colonial period, Western women got attracted to India. However, during the 20th century, arrival of four eminent Western women from diverse backgrounds, with different intentions had far-reaching impact for India. Katherine Mayo, Margaret Elizabeth Noble, Annie Besant and Madeline Slade, not only got actively involved with the Indian society but in their own ways contributed towards transforming the Indian society. They left an overwhelming impact on the Indian political fabric. The thesis aims to analyze the contribution of these four outstanding Western women and attempts to understand how Indian socio-political and cultural structure got influenced by and drew inspirations from them. This work also attempts to add to the process of evolution of understanding the East by the West. -
East west interfaces in 20th century india:
In the twenty-first century, the Western world is seeking a greater understanding of the people and nations of Asia, India in particular. The thesis, East West Interface in 20th century India: Analysis of Western women s responses is an attempt to illuminate at least an aspect of that interface during a given period of the past, so as to help shed some light on the newlinepresent day Western approach to India. Throughout the colonial period, Western women got attracted to India. However, during the 20th century, arrival of four eminent Western women from diverse backgrounds, with different intentions had far-reaching impact for India. Katherine Mayo, Margaret Elizabeth Noble, Annie Besant and Madeline Slade, not only got actively involved with the Indian society but in their own ways contributed towards newlinetransforming the Indian society. newlineThey left an overwhelming impact on the Indian political fabric. The thesis aims to analyze the contribution of these four outstanding Western women and attempts to understand how Indian socio-political and cultural structure got influenced by and drew inspirations from them. This work also attempts to add to the process of evolution newlineof understanding the East by the West. newline -
Easy and swift cane juicer with augmented bagasse brick maker /
Patent Number: 202121042785, Applicant: Thomas K T.
Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery. -
Easy and swift cane juicer with augmented bagasse brick maker /
Patent Number: 202121042785, Applicant: Thomas K T.
Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery. -
Easy and swift cane juicer with augmented bagasse brick maker /
Patent Number: 202121042785, Applicant: Thomas K T.
Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery. -
Easy and swift cane juicer with augmented bagasse brick maker /
Patent Number: 202121042785, Applicant: Thomas K T.
Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery. -
Easy and swift cane juicer with augmented bassage brick maker /
Patent Number: 202121042785, Applicant: Thomas K T.Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery. -
Easy and swift cane juicer with augmented bassage brick maker /
"Patent Number: 202121042785, Applicant: Thomas K T.
Sugarcane being one of the largest agriculture-based industry in India, provides subsistence to a huge number of farmers whose life is completely dependent upon sugarcane cultivation and its related products. One major source of income is extraction of Juice from sugarcane by road side vendors and farmers through a traditional machinery which turns out to be old and tedious job to perform. This also results into increased waiting time for customers as the task requires repetition of similar activity of by vendors in order to extract satisfactorily amount of juice from sugarcane by obsolescence machinery.