Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12

Search results for: Teja Sai Puligadda

12 Remote Sensing through Deep Neural Networks for Satellite Image Classification

Authors: Teja Sai Puligadda

Abstract:

Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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11 Hull Detection from Handwritten Digit Image

Authors: Sriraman Kothuri, Komal Teja Mattupalli

Abstract:

In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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10 The Eloquent Importance of Knowing Fyodor Dostoevsky: An Understanding of The Dilettante

Authors: Ravi Teja Mandapaka

Abstract:

Literary assonance and lexical consonance have always put the readers pondering, shirking away, at times too, and beefing on the baffling question that hardly invited any answer. ‘Why should we read Fyodor Mikhailovich Dostoevsky today?’ Does he, during a surreal life beneath his bruised and broken soul, writhing in pain, toying with the affirmatives of pleasure in an innate way, draw the readers any sheath of support? Alexithymia has ruled the time and space for a quite a long time as many a reader spent more time than required on reading his works of art in literature. Do his swirling theories of deism and laconic gushiness when put in black and white push us towards reading the lost pieces of exuberant dilettantism? With a view of that, and a hallucinated panorama of another, its best to say, thoughts and droughts’ glorious uncertainties in literature have come forward towards putting the pen on the eloquent importance of knowing Fyodor Dostoevsky, the Socrates of Literature.

Keywords: Dostoyevsky, dilettantism, gushiness, hallucinations, puissance

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9 Tuning Cubic Equations of State for Supercritical Water Applications

Authors: Shyh Ming Chern

Abstract:

Cubic equations of state (EoS), popular due to their simple mathematical form, ease of use, semi-theoretical nature and, reasonable accuracy are normally fitted to vapor-liquid equilibrium P-v-T data. As a result, They often show poor accuracy in the region near and above the critical point. In this study, the performance of the renowned Peng-Robinson (PR) and Patel-Teja (PT) EoS’s around the critical area has been examined against the P-v-T data of water. Both of them display large deviations at critical point. For instance, PR-EoS exhibits discrepancies as high as 47% for the specific volume, 28% for the enthalpy departure and 43% for the entropy departure at critical point. It is shown that incorporating P-v-T data of the supercritical region into the retuning of a cubic EoS can improve its performance above the critical point dramatically. Adopting a retuned acentric factor of 0.5491 instead of its genuine value of 0.344 for water in PR-EoS and a new F of 0.8854 instead of its original value of 0.6898 for water in PT-EoS reduces the discrepancies to about one third or less.

Keywords: equation of state, EoS, supercritical water, SCW

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8 Can Bone Resorption Reduce with Nanocalcium Particles in Astronauts?

Authors: Ravi Teja Mandapaka, Prasanna Kumar Kukkamalla

Abstract:

Poor absorption of calcium, elevated levels in serum and loss of bone are major problems of astronauts during space travel. Supplementation of calcium could not reveal this problem. In normal condition only 33% of calcium is absorbed from dietary sources. In this paper effect of space environment on calcium metabolism was discussed. Many surprising study findings were found during literature survey. Clinical trials on ovariectomized mice showed that reduction of calcium particles to nano level make them more absorbable and bioavailable. Control of bone loss in astronauts in critical important In Fortification of milk with nana calcium particles showed reduces urinary pyridinoline, deoxypyridinoline levels. Dietary calcium and supplementation do not show much retention of calcium in zero gravity environment where absorption is limited. So, the fortification of foods with nano calcium particles seemed beneficial for astronauts during and after space travel in their speedy recovery.

Keywords: nano calcium, astronauts, fortification, supplementation

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7 Thermalytix: An Advanced Artificial Intelligence Based Solution for Non-Contact Breast Screening

Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

Abstract:

Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

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6 Using Deep Learning in Lyme Disease Diagnosis

Authors: Teja Koduru

Abstract:

Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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5 Measurement of Solids Concentration in Hydrocyclone Using ERT: Validation Against CFD

Authors: Vakamalla Teja Reddy, Narasimha Mangadoddy

Abstract:

Hydrocyclones are used to separate particles into different size fractions in the mineral processing, chemical and metallurgical industries. High speed video imaging, Laser Doppler Anemometry (LDA), X-ray and Gamma ray tomography are previously used to measure the two-phase flow characteristics in the cyclone. However, investigation of solids flow characteristics inside the cyclone is often impeded by the nature of the process due to slurry opaqueness and solid metal wall vessels. In this work, a dual-plane high speed Electrical resistance tomography (ERT) is used to measure hydrocyclone internal flow dynamics in situ. Experiments are carried out in 3 inch hydrocyclone for feed solid concentrations varying in the range of 0-50%. ERT data analysis through the optimized FEM mesh size and reconstruction algorithms on air-core and solid concentration tomograms is assessed. Results are presented in terms of the air-core diameter and solids volume fraction contours using Maxwell’s equation for various hydrocyclone operational parameters. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Algebraic slip mixture based multi-phase computational fluid dynamics (CFD) model is used to predict the air-core size and the solid concentrations in the hydrocyclone. Validation of air-core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted.

Keywords: air-core, electrical resistance tomography, hydrocyclone, multi-phase CFD

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4 Association of Laterality and Sports Specific Rotational Preference with Number of Injuries in Artistic Gymnasts

Authors: Teja Joshi

Abstract:

Laterality has shown to play a role in performance as well as injuries especially in unilateral sports disciplines. Uniquely, Artistic Gymnastics involves combination of unilateral, bilateral and complex multi-planer elements as well as gymnastics specific rotational preference. Therefore, this study was conducted to explore if any such preferences are associated with number of injuries in artistic gymnasts. To explore the association between lateral preferences, rotational preferences and injuries incidence in artistic gymnastics. Artistic gymnasts above 16 years of age, were invited to participate in an online survey. The survey included consent, lateral preference inventory, injury data collection according to anatomical locations and rotational preference for selected gymnastics elements performed on the floor exercise. SPSS version 24 was used to analyse Non-parametric data using Kruskal-Wallis (K- independent test) test. Multiple regression was performed to identify the predictor for injuries and their side in gymnasts. Total number of injuries per gymnast was associated with handedness (p value-0.049) and no significant association was noted for footdness (p value-0.207), eyedness (p value-0.491) and eardness (p value-0.798). Additionally, rotational preferences did not influence number of injuries (p value-0.521). In multiple regression, eyedness was identified as a predicting factor to determine the number of injuries. Rotational preferences were neither determined as a national strategy nor a product of lateral preference. Dominant hand had higher number of injuries in artistic gymnasts. Rotational preference is independent of laterality, number of injuries and nationality.

Keywords: sports injury, rotational preference, gymnastics, handedness

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3 Recognition and Counting Algorithm for Sub-Regional Objects in a Handwritten Image through Image Sets

Authors: Kothuri Sriraman, Mattupalli Komal Teja

Abstract:

In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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2 The Influence of Guided and Independent Training Toward Teachers’ Competence to Plan Early Childhood Education Learning Program

Authors: Sofia Hartati

Abstract:

This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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1 Evaluation of Oral Biofilm Suppression by Carribean Herbal Extracts

Authors: Ravi Teja Chitturi Suryaprakash, Chandrashekhar Unakal, Haytham Al-Bayaty, Duraisamy Saravanakumar

Abstract:

Background and significance: Oral biofilm formation is a well-known causative factor for caries and periodontal diseases. Scientists over the years have been trying to find a solution against the formation of oral biofilms. Though several advances have been made to understand the microbial ecology and how the bio film survives, it is still an enigma to researchers to find a chemical product that not only can inhibit the formation of oral bio film but also not disturb the oral micro flora required for oral health and not to cause damage to the cells of the oral cavity. One such product that has never been investigated much are herbal preparations. Some of the microorganisms important in the formation of biofilm are Streptococcus mutans, Actinomyces naeslundi, Streptococuss oralis and Prevotella intermedia. The aim of this study was to study the antimicrobial property of some herbal extracts available in Trinidad and Tobago against these pathogens. The significance of this study is that identification of biologically effective plant extracts can result in indigenous development of mouth rinses and tooth pastes that the people can benefit from to not only develop effective but also a cheap solution. Methodology: The extracts from the leaves of Plectranthus ambonicus, Ocmium tenuiflorum, Azadirchata indica, Anacardium occidentale, Psidium guajava were prepared by dissolving them in water. The extracts from the roots of Curcuma longa were prepared similarly and the antimicrobial activity of these six plant extracts was determined by the agar well diffusion method using minimum inhibitory concentration (MIC) against Streptococcus mutans, Actinomyces naeslundi, Streptococuss oralis and Prevotella intermedia and compared with chlorhexidine. Results: The six plant extracts showed variable effect on the oral micro-organisms. Ocmium tenuiflorum (16.66 ± 0.44, 14 ± 0.58, 13.33 ± 0.88, 12.83 ± 0.60), Azadirchata indica (17.5 ± 0.28, 14.83 ± 0.17, 15 ± 0.58, 12.83 ± 0.6) and Curcuma longa (16.16 ± 0.44, 13.66 ± 0.88, 12.33 ± 0.88, 11.33 ± 0.67) were found to have highest inhibitory activity against all the four pathogens (Streptococcus mutans, Streptococuss oralis, Actinomyces naeslundi, and Prevotella intermedia) respectively. Conclusion: Although the extracts were not pure compounds we obtained antimicrobial results which determine that they are potent antimicrobial agents. Further derivation of pure compounds from these extracts could be lucrative as it might lead to the development of a cost effective and biologically safe medicine to act against oral biofilms. Acknowledgement: The authors would like to acknowledge the Campus Research and Publication Fund Committee, The University of the West Indies for funding this study and would also like to acknowledge Dr. Leonette Cox, Department of Chemistry, Faculty of Science and Technology, The University of the West Indies, St. Augustine Campus, Trinidad and Tobago for helping to prepare the plant extracts.

Keywords: agar well diffusion method, herbal extracts, minimum inhibitory concentration, oral biofilm forming microorganisms

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