<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns="http://purl.org/rss/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel rdf:about="http://nopr.niscpr.res.in/handle/123456789/64750">
    <title>NOPR Community:</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/64750</link>
    <description />
    <items>
      <rdf:Seq>
        <rdf:li rdf:resource="http://nopr.niscpr.res.in/handle/123456789/65333" />
        <rdf:li rdf:resource="http://nopr.niscpr.res.in/handle/123456789/65332" />
        <rdf:li rdf:resource="http://nopr.niscpr.res.in/handle/123456789/65331" />
        <rdf:li rdf:resource="http://nopr.niscpr.res.in/handle/123456789/65329" />
      </rdf:Seq>
    </items>
    <dc:date>2026-10-10T20:33:19Z</dc:date>
  </channel>
  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/65333">
    <title>Remote Sensing Technique- A Modern tool for Monitoring of Fire Problem in Coal Mines</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/65333</link>
    <description>Title: Remote Sensing Technique- A Modern tool for Monitoring of Fire Problem in Coal Mines
Authors: Pandey, Jitendra; Kumar, Dheeraj; Chaudhari, Sumit kumar; Khalkho, Ajay; Kumar, Aditya; Pandey, Jai Krishna
Abstract: Coal, a valuable non-renewable gift from nature, is the most widely used fossil fuel in the world. Coal has been formed in the past due to&#xD;
chemical and bacterial changes in various components of plants buried under the ground. Coal is rich in carbon, which we used as a pivotal&#xD;
source of energy. At present, spontaneous combustion / fire in coal mines has become a global problem. India's coal mines also have a long&#xD;
history of self-ignition/fire causing destruction of a valuable natural resource. It strongly and adversely affects the ecosystem as well as the&#xD;
social life, health and safety of the coalfield's populace. Remote-sensing technology is a modern and effective technique used to detect coal fire affected areas. It is an excellent and relatively economical method for locating and monitoring of a large fire-prone area viz. Jharia and Raniganj,&#xD;
coalfields of Jharkhand and West Bengal states respectively in a timely manner. It is the best technique to study periodical speed of fire&#xD;
spread, stage, extent and nature of fire over specific time period gap. In this research paper, the method of remote sensing monitoring of coal&#xD;
mine fires in Jharia coalfield has been discussed in detail.
Page(s): 53-61</description>
    <dc:date>2024-12-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/65332">
    <title>Indigenous and European Leafy vegetables cultivation under Modern farming- Hydroponics (Soil less)</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/65332</link>
    <description>Title: Indigenous and European Leafy vegetables cultivation under Modern farming- Hydroponics (Soil less)
Authors: Kumar, Harendra; Agarwal, Ankur; Dayal, Rameshwar; Kumar, Shiva; Prakash, Om; Ballabh, Basant; Singh, Devakanta Pahad
Abstract: Globally, rapid growth rate of population, day by day increasing greenhouse effects vis-a- vis increasing carbon foot print and urbanization&#xD;
these are challenges in front of us. So, there is urgent need to increase food production. The aim of present study was to standardiz the&#xD;
indigenous and exotic leafy vegetable crops under hydroponics, Nutrient film technology (NFT). Presently, increasing levels of insecticides and pesticides in commercial vegetables cultivation are challenging in conventional agriculture which are not only harmful for environment but&#xD;
also for human health. At present, rapid increase in growth rate of urban population and more demand of organically fresh produce have been&#xD;
attracting the global attention towards the use of intensive agriculture systems and that bring us towards a new direction for modern farming&#xD;
technique such as soilless culture and hydroponics. Hydroponics is a modern farming technique for crop cultivation without soil with the help&#xD;
of nutrient solution. Among vegetable crop, leafy vegetables play a vital role for human health. In various leafy vegetable categorys Indian&#xD;
leafy vegetable i.e. Spinach leaf (palak), leafy mustard, coriander, Amaranthus, Basella etc. are commercially cultivated. Nowadays, in our&#xD;
country unexploited European vegetables crops i.e., baby leaf vegetables (i.e., rocket, crisp head lettuce, endive, parsley, water cress) are also&#xD;
cultivated due to their increased consumption and people are aware about their nutritive value. These vegetables are mostly considered for&#xD;
salad. Present study revealed that higher production with better quality was found under hydroponics farming as compared to traditional&#xD;
farming. The result shows that green leafy vegetables grown under hydroponics had 2.0 to 3.0 times higher productivity than the crop grown&#xD;
in soil. Our study revealed that various vegetables can be cultivated in a hydroponics unit. This modern farming is beneficial for fresh produce&#xD;
and supply of evergreen vegetables to our armed forces at front line border areas as well as area where water scarcity and land shortage are main&#xD;
challenges. DIBER (DRDO) has been instrumental in standardizing the technique of hydroponics for various crop from snow bound hilly&#xD;
regions to Antarctica.
Page(s): 62-68</description>
    <dc:date>2024-12-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/65331">
    <title>Prediction of Diabetes Using Various Machine Learning Techniques</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/65331</link>
    <description>Title: Prediction of Diabetes Using Various Machine Learning Techniques
Authors: Gupta, Vaishali; Patel, Ruchi
Abstract: Diabetes is a life-threatening disease marked by unusually high blood sugar levels. It is the leading cause of death in the globe. According&#xD;
to rising morbidity in recent years, the number of diabetic patients globally will reach 642 million by 2040, or approximately one out of every&#xD;
ten persons. It is true that this requires a lot of focus. On the diabetes dataset, a number of data mining and machine learning techniques were&#xD;
utilized to predict disease risk. The goal of this work is to investigate several machine learning algorithms for diabetes categorization,&#xD;
early-stage identification, and prediction using a feature-based dataset. A benchmark PIMA Indian Diabetes dataset is used for experimental&#xD;
evaluation, which includes 768 patients, 268 of whom are diabetic and 500 of whom are not. At the end, the accuracy of various machine&#xD;
learning approaches is measured in order to assess their performance.
Page(s): 69-79</description>
    <dc:date>2024-12-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/65329">
    <title>Pakvashyagata Vata : A Review</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/65329</link>
    <description>Title: Pakvashyagata Vata : A Review
Authors: Sharma, Balyogeshwar; Mehta, Ashish
Abstract: Pakvashyagata Vata is the condition of aggravation of Vata in the large intestine. Aggravation of Vayu in Pakvashaya causes Antrakujana&#xD;
(gurgling sound in the intestine), Shula (stomach pain), Atopa (flatulence), Krichha-mutra-puris (difficulty in passing urine, constipation),&#xD;
Aanah (flatulence), Trikapradesh Vedana (pain in the waist region). In the modern era, the number of Vata diseases is constantly increasing&#xD;
because people give less importance to proper physical, mental exercise and food habits. Symptoms of Pakvashyagata Vata are found in many&#xD;
patients alone or with other complaints. Proper management of Pakvashyagata Vata is very important to normalize Vata and prevent the&#xD;
disease from progressing. When the condition of Vata aggravates in the Pakvashya, which is especially the Vata place, then Sneha Virechana,&#xD;
Shodhani Vasti and the diet enriched with saindhavalavana should be given in Pakvashyagata Vata. Sneha Virechana is indicated for the&#xD;
management of aggravated Vata in the Pittasya, which helps to eliminate the aggravating factors and produce beneficial effects. Shodhana Vasti&#xD;
gives beneficial effects when Vayu is obstructed by Mala, Pitta and Kapha. Sneha Virechana and Shodhana Vasti are the best option for safe&#xD;
and effective management of aggravated Vata in the Pakvashya.
Page(s): 80-83</description>
    <dc:date>2024-12-01T00:00:00Z</dc:date>
  </item>
</rdf:RDF>

