290 research outputs found
Management of Knowledge Representation Standards Activities
This report describes the efforts undertaken over the last two years to identify the issues underlying the current difficulties in sharing and reuse, and a community wide initiative to overcome them. First, we discuss four bottlenecks to sharing and reuse, present a vision of a future in which these bottlenecks have been ameliorated, and describe the efforts of the initiative's four working groups to address these bottlenecks. We then address the supporting technology and infrastructure that is critical to enabling the vision of the future. Finally, we consider topics of longer-range interest by reviewing some of the research issues raised by our vision
Infant’s MRI Brain Tissue Segmentation using Integrated CNN Feature Extractor and Random Forest
Infant MRI brain soft tissue segmentation become more difficult task compare with adult MRI brain tissue segmentation, due to Infant’s brain have a very low Signal to noise ratio among the white matter_WM and the gray matter _GM. Due the fast improvement of the overall brain at this time , the overall shape and appearance of the brain differs significantly. Manual segmentation of anomalous tissues is time-consuming and unpleasant. Essential Feature extraction in traditional machine algorithm is based on experts, required prior knowledge and also system sensitivity has change. Recently, bio-medical image segmentation based on deep learning has presented significant potential in becoming an important element of the clinical assessment process. Inspired by the mentioned objective, we introduce a methodology for analysing infant image in order to appropriately segment tissue of infant MRI images. In this paper, we integrated random forest classifier along with deep convolutional neural networks (CNN) for segmentation of infants MRI of Iseg 2017 dataset. We segmented infants MRI brain images into such as WM- white matter, GM-gray matter and CSF-cerebrospinal fluid tissues, the obtained result show that the recommended integrated CNN-RF method outperforms and archives a superior DSC-Dice similarity coefficient, MHD-Modified Hausdorff distance and ASD-Average surface distance for respective segmented tissue of infants brain MRI
A case report of Trivrut Leha Virechana and Rasottamadi Lepa in Indralupta
Acharya Vagbhata has explained about Indralupta regarding its Nidana, Lakshanas and Chikitsa in Uttaratantra. Indralupta is a Shiroroga characterized by patchy hair loss on scalp, itching and anxiety. This condition can be correlated with Alopecia areata due to similarities. Though there are many modalities described in modern science, still it is not possible to cease the permanent impairment. In Ayurveda, many modalities are being described for Urdhwajatrugata Rogas and for Shirogata Vikaras. Among them Virechana is best in Indralupta as it is a Pittapradhana Vyadhi and Virechana is Shreshtha for Pittaharana. The Virechana Karma is explained by Brihatrayis. The complete procedure of Virechana Karma includes Poorvakarma (Deepana, Pachana, Snehapana, Abhyanga and Swedana) which helps in mobilization of the Doshas to the site of elimination and causes vasodilatation in order to expel out the Doshas from the body, and provides better channel for absorption of the Oushadhi. Pradhanakarma (Virechana) eliminates the Doshas from the body. Paschatkarma (Sansarjana Krama and Rasottamadi Lepa) eliminates the remaining Doshas and causes better absorption of Oushadhi which ultimately eliminates the symptoms of the disease. A clinical observation has shown effective result in the treatment of Indralupta with Trivrut Leha Virechana and Rasottamadi Lepa and here we are revalidating the statement of our Acharyas. A case report of a female, aged 28 years with complains of patchy hair loss on scalp in crown and right temporal region, itching on scalp and anxiety has been presented here
Selection Criterion Based on Trait Linkages in African and Asian Pearl Millet [Pennisetum glaucum (L.) R. Br.] Populations to Enhance Productivity
Pearl millet [Pennisetum glaucum (L.) R. Br.]
is commonly grown in the arid and semi-arid regions
of Africa and Asia. It serves as staple food for the
people living in relatively dry tracts of the India and
Sub-Sahelian Africa and an important source of fodder/
feed for livestock and poultry. It can be cultivated even
in the poor infertile soils and drought prone
environments, where no other cereal crop can survive.
In India, currently pearl milletis cultivated on ~7.5 m
ha area with grain production of 9.7 Mt with an average
productivity of 1,305 kg ha-1(www.indiastat.com). The
ultimate aim in most plant breeding programs is the
improvement in the productivity of grains as
measured in terms of the yield per unit area. The
possibilities of achieving this goal through genetic
improvement have been elucidated by evolving high
yielding hybrids and varieties of pearl millet in Asia
and West Africa
Textual Query Based Image Retrieval
As digital cameras becoming popular and mobile phones are increased very fast so that consumers photos are increased. So that retrieving the appropriate image depending on content or text based image retrieval techniques has become very vast. Content-based image retrieval, a technique which uses visual contents to search images from large scale image databases according to users interests, has been an active and fast advancing research area semantic gap between the low-level visual features and the high-level semantic concepts. Real-time textual query-based personal photo retrieval system by leveraging millions of Web images and their associated rich textual descriptions. Then user provides a textual query. Our system generates the inverted file to automatically find the positive Web images that are related to the textual query as well as the negative Web images that are irrelevant to the textual query. For that purpose we use k-Nearest Neighbor (kNN), Decision stumps, and linear SVM, to rank personal photos. For improvement of the photo retrieval performance, we have used two relevance feedback methods via cross-domain learning, which effectively utilize both the Web images and personal images.
DOI: 10.17762/ijritcc2321-8169.15032
Panchakarma in Lifestyle Disorders
Panchakarma has immense potential in the context of tackling the lifestyle disorders. Lifestyle disorders are the diseases which occurs due to change in the environment, lifestyle including diet some of them are Hridaya Roga, Madhumeha, Sthoulya, Sandhivata, Pakshaghata etc. Panchakarma of Ayurveda are purificatory measures which cleanses the toxins from the cellular level and also prevents the production as well as the deposition of toxin in the body. It also rejuvenates the body cells. It plays a major role in prevention and cure of lifestyle disorders. Panchakarma or Shodhana therapy can be conducted as the initial line of treatment before starting the Shamana Oushadhi. It prevents or cures the diseases by correcting Dosha, Dushya, Agni, Srotas and by doing Samprapti Vighatana
The Role of Antimicrobial Peptides as Antimicrobial and Antibiofilm Agents in Tackling the Silent Pandemic of Antimicrobial Resistance
Just over a million people died globally in 2019 due to antibiotic resistance caused by ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). The World Health Organization (WHO) also lists antibiotic-resistant Campylobacter and Helicobacter as bacteria that pose the greatest threat to human health. As it is becoming increasingly difficult to discover new antibiotics, new alternatives are needed to solve the crisis of antimicrobial resistance (AMR). Bacteria commonly found in complex communities enclosed within self-produced matrices called biofilms are difficult to eradicate and develop increased stress and antimicrobial tolerance. This review summarises the role of antimicrobial peptides (AMPs) in combating the silent pandemic of AMR and their application in clinical medicine, focusing on both the advantages and disadvantages of AMPs as antibiofilm agents. It is known that many AMPs display broad-spectrum antimicrobial activities, but in a variety of organisms AMPs are not stable (short half-life) or have some toxic side effects. Hence, it is also important to develop new AMP analogues for their potential use as drug candidates. The use of one health approach along with developing novel therapies using phages and breakthroughs in novel antimicrobial peptide synthesis can help us in tackling the problem of AMR
Covid-19 : Scope of Ayurveda to make Swastha Bharatha
Ayurveda, being the science of life, propagates the gifts of nature in maintaining healthy and happy living. Ayurveda's extensive knowledge base on preventive care, derives from the concepts of Dinacharya- daily regimes and Ritucharya - seasonal regimes to maintain healthy life. It is a totally plant based science. The simplicity of awareness about oneself and the harmony each individual can achieve by uplifting and maintaining his or her immunity is emphasized across Ayurveda's classical scriptures. In present situation of Covid-19, one has to take care of himself and his family by following simple precautionary measures explained in Ayurveda. Before that one has to understand what is covid-19, its causative organism, its incubation period, it's signs and symptoms etc, and it's precautions in general. In the wake of the Covid-19 outbreak, entire mankind across the globe is suffering. Enhancing the body's natural defense system (Immunity) plays an important role in maintaining optimum health. We all know that 'Prevention Is Better Than Cure', while there is no medicine for Covid-19 as of now, it will be good to take preventive measures which boost our immunity in these times
Anomaly Extraction Using Histogram-Based Detector
Now a day’s network traffic monitoring and performance of the network are more important aspect in the computer science. Anomaly Extraction is a method of detecting in large set of flow observed during an anomalous time interval, the flows associated with the one or more anomalous event. Anomaly extraction is important problem that essential for application ranging from root cause analysis and attack mitigation and anomaly extraction is also important problem for several application of testing anomaly detector. In this paper, use a meta-data provided by histogram detector for detect and identify the suspicious flow after successfully detection suspicious flow then applying the association rule mining for finding the anomalous flow. By using the rich traffic data from the meta-data of the histogram-based detector we can reduce the classification cost. In this paper, Anomaly extraction method reduce the working time which is required for analyzing alarm, its make system more practically.
DOI: 10.17762/ijritcc2321-8169.15011
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