scholarly journals Automatic Rice Leaf Disease Segmentation Using Image Processing Techniques

2018 ◽  
Vol 7 (3.27) ◽  
pp. 182 ◽  
Author(s):  
K S. Archana ◽  
Arun Sahayadhas
Keyword(s):  
Image Segmentation ◽  
Detection Method ◽  
Research Work ◽  
Automatic Detection ◽  
Brown Spot ◽  
Environmental Condition ◽  
Hybrid Techniques ◽  
Wide Range ◽  
Rice Leaves ◽  
Processing Techniques

Agriculture productivity mainly depends on Indian economy. Hence, Disease prediction plays a important role in agriculture field. In image analyzing the symptoms is an essential part for feature extraction and classification. However, some of the challenges are still lacking to predict the disease. To meet those challenges, the proposed algorithm focuses on a specific problem to predict the disease from early symptoms. Bacterial Leaf Blight and Brown Spot are a major bacterial and fungal disease respectively in rice (Oryza sativa) crops, it causes yield loss and reduce the grains quality. This research work focused on automatic detection method for image segmentation on rice leaves under wide range of environmental condition for further analysis. Various hybrid techniques for image segmentation and classification algorithms were analyzed and an automatic detection method has been proposed for identifying the specified diseases in rice leaves under different environmental condition.  

scholarly journals Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy-Based Image Processing Techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 2251-2256
Keyword(s):  
Image Processing ◽  
Composite System ◽  
Detection Method ◽  
Research Work ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Sensitivity Specificity ◽  
Processing Techniques ◽  
Retinal Fundus ◽  
Retinal Drusen

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

Justification of the need to improve the legal, regulatory and methodological framework for the spread of parasitic infections in the provision of medical care

2020 ◽  
Vol 99 (5) ◽  
pp. 493-497
Author(s):  
M. M. Aslanova ◽  
T. V. Gololobova ◽  
K. Yu. Kuznetsova ◽  
Tamari R. Maniya ◽  
D. V. Rakitina ◽  
...  
Keyword(s):  
Medical Care ◽  
Research Work ◽  
Hospital Environment ◽  
Parasitic Infections ◽  
Infusion Therapy ◽  
Methodological Framework ◽  
Production Environment ◽  
Medical Institutions ◽  
Medical Network ◽  
Wide Range

Introduction. The purpose of our work was to justify the need to improve the legislative, regulatory and methodological framework and preventative measures in relation to the spread of parasitic infections in the provision of medical care. There is a wide range of pathogens of parasitic infestations that are transmitted to humans through various medical manipulations and interventions carried out in various medical institutions. Contaminated care items and furnishings, medical instruments and equipment, solutions for infusion therapy, medical personnel’s clothing and hands, reusable medical products, drinking water, bedding, suture and dressing materials can serve as a major factor in the spread of parasitic infections in the provision of medical care. Purpose of research is the study of the structure and SMP of parasitic origin, circulating on the objects of the production environment in multi-profile medical and preventive institutions of stationary type in order to prevent the occurrence of their spread within medical institutions. Material and methods. The material for the study was flushes taken from the production environment in 3 multi-profile treatment and prevention institutions of inpatient type: a multi-specialty hospital, a maternity hospital and a hospital specializing in the treatment of patients with intestinal diseases for the eggs of worms and cysts of pathogenic protozoa. Results. During the 2-year monitoring of medical preventive institutions, a landscape of parasitic contamination was found to be obtained from the flushes taken from the production environment objects in the premises surveyed as part of the research work. Discussions. In the course of research, the risk of developing ISMP of parasitic origin was found to be determined by the degree of epidemiological safety of the hospital environment, the number and invasiveness of treatment and diagnostic manipulations and various medical technologies. Conclusion. It is necessary to conduct an expert assessment of regulatory and methodological documents in the field of epidemiological surveillance and sanitary and hygienic measures for the prevention of medical aid related infections of parasitic origin, to optimize the regulatory and methodological base, to develop a number of preventive measures aimed at stopping the spread of parasitic infections in the medical network.

Ochrona dziedzictwa kulturowego a działania na dużych szybkozmiennych zbiorach danych – perspektywa kryminologiczna

2019 ◽  
pp. 5-22
Author(s):  
Szymon Buczyński
Keyword(s):  
New Technology ◽  
Big Data Analytics ◽  
Technological Innovations ◽  
Cultural Organizations ◽  
Econometric Methods ◽  
The Arts ◽  
Huge Data ◽  
Wide Range ◽  
Share Data ◽  
Processing Techniques

Recent technological revolutions in data and communication systemsenable us to generate and share data much faster than ever before. Sophisticated data tools aim to improve knowledge and boost confdence. That technological tools will only get better and user-friendlier over the years, big datacan be considered an important tool for the arts and culture sector. Statistical analysis, econometric methods or data mining techniques could pave theway towards better understanding of the mechanisms occurring on the artmarket. Moreover crime reduction and prevention challenges in today’sworld are becoming increasingly complex and are in need of a new techniquethat can handle the vast amount of information that is being generated. Thisarticle provides an examination of a wide range of new technological innovations (IT) that have applications in the areas of culture preservation andheritage protection. The author provides a description of recent technological innovations, summarize the available research on the extent of adoptionon selected examples, and then review the available research on the eachform of new technology. Furthermore the aim of this paper is to explore anddiscuss how big data analytics affect innovation and value creation in cultural organizations and shape consumer behavior in cultural heritage, arts andcultural industries. This paper discusses also the likely impact of big dataanalytics on criminological research and theory. Digital criminology supports huge data base in opposition to conventional data processing techniques which are not only in suffcient but also out dated. This paper aims atclosing a gap in the academic literature showing the contribution of a bigdata approach in cultural economics, policy and management both froma theoretical and practice-based perspective. This work is also a startingpoint for further research.

Character Reorganization and Categorization using Hybrid Algorithms by Scanned Documents

2019 ◽  
Vol 8 (6S2) ◽  
pp. 943-948
Keyword(s):  
Research Work ◽  
Hybrid Algorithms ◽  
Research Topic ◽  
Image Processing Techniques ◽  
Digital Books ◽  
Otsu Method ◽  
Challenging Research ◽  
Processing Techniques ◽  
Scanned Documents ◽  
Day By Day

Detection and reorganization of text may save a lot of time while reproducing old books text and its chapters. This is really challenging research topic as different books may have different font types and styles. The digital books and eBooks reading habit is increasing day by day and new documents are producing every day. So in order to boost the process the text reorganization using digital image processing techniques can be used. This research work is using hybrid algorithms and morphological algorithms. For sample we have taken an letter pad where the text and images are separated using algorithms. The another objective of this research is to increase the accuracy of recognized text and produce accurate results. This research worked on two different concepts, first is concept of Pixel-level thresholding processing and another one is Otsu Method thresholding.

Development and Evaluation of Sustained Release Lipid Nanocarriers for Curcumin

2020 ◽  
Vol 5 (3) ◽  
pp. 224-235
Author(s):  
Harshal A. Pawar ◽  
Bhagyashree D. Bhangale
Keyword(s):  
Drug Delivery ◽  
Sustained Release ◽  
Drug Delivery Systems ◽  
Biological Activities ◽  
Curcuma Longa ◽  
Research Work ◽  
Elimination Rate ◽  
Delivery Systems ◽  
Physicochemical Stability ◽  
Wide Range

Background: Lipid based excipients have increased acceptance nowadays in the development of novel drug delivery systems in order to improve their pharmacokinetic profiles. Drugs encapsulated in lipids have enhanced stability due to the protection they experience in the lipid core of these nano-formulations. Phytosomes are newly discovered drug delivery systems and novel botanical formulation to produce lipophilic molecular complex which imparts stability, increases absorption and bioavailability of phytoconstituent. Curcumin, obtained from turmeric (Curcuma longa), has a wide range of biological activities. The poor solubility and wettability of curcumin are responsible for poor dissolution and this, in turn, results in poor bioavailability. To overcome these limitations, the curcumin-loaded nano phytosomes were developed to improve its physicochemical stability and bioavailability. Objective: The objective of the present research work was to develop nano-phytosomes of curcumin to improve its physicochemical stability and bioavailability. Methods: Curcumin-loaded nano phytosomes were prepared by using phospholipid Phospholipon 90 H using a modified solvent evaporation method. The developed curcumin nano phytosomes were evaluated by particle size analyzer and differential scanning calorimetry (DSC). Results: Results indicated that phytosomes prepared using curcumin and lipid in the ratio of 1:2 show good entrapment efficiency. The obtained curcumin phytosomes were spherical in shape with a size less than 100 nm. The prepared nano phytosomal formulation of curcumin showed promising potential as an antioxidant. Conclusion: The phytosomal complex showed sustained release of curcumin from vesicles. The sustained release of curcumin from phytosome may improve its absorption and lowers the elimination rate with an increase in bioavailability.

ESRC Review

2020 ◽  
pp. 657-698
Author(s):  
Simeon J. Yates ◽  
Jordana Blejmar
Keyword(s):  
Social Research ◽  
Social Science Research ◽  
Research Work ◽  
Science Research ◽  
Wide Range ◽  
The Us ◽  
Levels Of Automation ◽  
The Uk ◽  
Technological World ◽  
Ways Of Being

Two workshops were part of the final steps in the Economic and Social Research Council (ESRC) commissioned Ways of Being in a Digital Age project that is the basis for this Handbook. The ESRC project team coordinated one with the UK Defence Science and Technology Laboratory (ESRC-DSTL) Workshop, “The automation of future roles”; and one with the US National Science Foundation (ESRC-NSF) Workshop, “Changing work, changing lives in the new technological world.” Both workshops sought to explore the key future social science research questions arising for ever greater levels of automation, use of artificial intelligence, and the augmentation of human activity. Participants represented a wide range of disciplinary, professional, government, and nonprofit expertise. This chapter summarizes the separate and then integrated results. First, it summarizes the central social and economic context, the method and project context, and some basic definitional issues. It then identifies 11 priority areas needing further research work that emerged from the intense interactions, discussions, debates, clustering analyses, and integration activities during and after the two workshops. Throughout, it summarizes how subcategories of issues within each cluster relate to central issues (e.g., from users to global to methods) and levels of impacts (from wider social to community and organizational to individual experiences and understandings). Subsections briefly describe each of these 11 areas and their cross-cutting issues and levels. Finally, it provides a detailed Appendix of all the areas, subareas, and their specific questions.

scholarly journals The exploration of an automatic detection method for the wind-storage and combined power generation monitoring system

2019 ◽  
Author(s):  
Jinxiong Zhao ◽  
Bo Zhao ◽  
Yanbin Zhang ◽  
Zhiru Li ◽  
Hui Yuan ◽  
...  
Keyword(s):  
Power Generation ◽  
Monitoring System ◽  
Detection Method ◽  
Automatic Detection

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

Development and characterization of electrospun curcumin-loaded antimicrobial nanofibrous membranes

2020 ◽  
pp. 004051752092551
Author(s):  
Javeed A Awan ◽  
Saif Ur Rehman ◽  
Muhammad Kashif Bangash ◽  
Fiaz Hussain ◽  
Jean-Noël Jaubert
Keyword(s):  
Biological Activities ◽  
Research Work ◽  
Medical Applications ◽  
Electrospinning Technique ◽  
Naturally Occurring ◽  
Wide Range ◽  
Nanofibrous Membranes ◽  
Antimicrobial Barrier ◽  
Anti Hiv

Curcumin is a naturally occurring hydrophobic polyphenol compound. It exhibits a wide range of biological activities such as antibacterial, anti-inflammatory, anti-carcinogenic, antifungal, anti-HIV, and antimicrobial activity. In this research work, antimicrobial curcumin nanofibrous membranes are produce by an electrospinning technique using the Eudragit RS 100 (C19H34ClNO6) polymer solution enriched with curcumin. The morphology and chemistry of the membrane are analyzed using scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy. Kirby Bauer disk diffusion tests are carried out to examine the antibacterial effectiveness of the membrane. Experimental results show that the nanofibers produced are of uniform thickness morphology and curcumin is successfully incorporated into the nanofibrous mat, while no chemical bonding was observed between curcumin and the polymer. The antimicrobial curcumin nanofibrous membranes can be effectively applied as antimicrobial barrier in a wide variety of medical applications such as wound healing, scaffolds, and tissue engineering.

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