Volume-07 , Special Issue-03 , Feb - 2019 Go Back

Tecoma stans, member of family Bignoniaceae, is a popular ornamental plant grown for its bright yellow flowers. It is widely used for its medicinal properties in curing diabetes, digestive problems and yeast infections. Almost all parts (leaves, root, flower, seed, fruit, and bark) of the plant is have its medicinal use. In present study fruit extract was prepared and checked for its antioxidant, free radical scavenging ability and antiproliferative activities in cancerous cell line. Ethyl acetate and methanol extracts exhibited high antioxidant activity and free radical scavenging capacity. The expression of the pro-inflammatory gene(s) cox-2, IL1β, TNFα were checked in a cancerous cell line treated with the methanol extract in comparison to the untreated cells. The expression of all three genes was significantly reduced in the treated cancerous cells in comparison to untreated ones. Further when the cancerous cell line was treated with methanol extract it exhibited potent anti-proliferative activity and significantly changed the morphology of the cancerous cell.

Tecoma stans, fruit extract, Antioxidant, anti-inflammatory, Anti-proliferative. Malls

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Arun Kumar Kashyap, Loha, Mohammad Kashif , "Anti-Oxidant, Anti-Inflammatory and Antiproliferative Effect of Tecoma Stans Fruit", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.1-5, 2019.

The present study was conducted under the jurisdiction of Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.). The total 362 Final year (4th year) Under Graduate students have been selected randomly as respondents from 15 agricultural colleges. The primary data collected through pre tested structured interview schedule. Out of the total 362 respondents, majority of them (64.64%) were male and 35.36 per cent were female, majority (60.77%) of them were from the rural area, most (27.62%) of them had small size of land holding (up to 1 ha) and most (49.72%) of them had annual family income upto ₹ 1,00,000/-. Variables namely gender, family annual income, caste and size of land holding had significant and positive relationship with entrepreneurial behavior of respondents.

entrepreneurial behavior, Socio-economic, gender, agricultural students

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Dilip Kumar, R. S. Sengar, P. Shrivastava, P. R. Singh, "Critical Analysis on Student’s Entrepreneurship Development Influencing Factors", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.6-10, 2019.

The present study was conducted at Bilaspur district of Chhattisgarh state. Total 80 Anganwadi children were survey through structured interview schedule by the researcher. It was observed that out of total 80 respondents, majority of them (76.25%) were belonged to Hindu religion, majority of them (52.50%) were belonged to scheduled caste, 55 per cent were living in pakka house, 53.75 per cent had attendance more than 20 days in a month, children’s face (78.75%) observed normally, 43.75 per cet teeth appeared white, 32.5 per cent hairs were appeared rough, 27.5, 15 and 7.5 per cent of the respondent’s nails were observed easily break down, white spot and pale respectively.

ICDS, AWWs, Pre-school, Anganwadi

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Shirin Khan, Dilip Kumar, P R Singh, "Supply Chain Management of Icds Programme through Anganwadi and Their Impact on Child Health", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.11-14, 2019.

This paper analyses the hybridization of intelligent techniques for time series data prediction of FX rate INR/USD to alleviate the limitation of statistical methods for non-linear data. This paper uses the feature extraction to extract the new features, five new features are extracted from the one original feature of INR/USD i.e Next week FX. Wavelet technique has been used for pre-processing the chaotic data series and prepares the de-noised data to get accurate prediction result. ANFIS is uses the non-linear functions and identify the non-linear components to predict the time series data with its fluctuating behaviour. Result came from ANFIS is compare with ANN technique, Error Back Propagation Network (EBPN). The empirical result of Hybridization of Wavelet and Feature selection with ANFIS and ANN shows that ANFIS produces the best prediction result with MAPE 1.568, MAE0.0136 and RMSE 0.0174.

ANFIS(Adaptive Neuro-Fuzzy Inference System), ANN (Artificial Neural Network), Wavelet, Feature extraction

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Richa Handa, A.K. Shrivas, H.S. Hota, "Prediction of FX Data Using ANFIS and Ann with Combined Approach of Wavelet and Feature Extraction Technique", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.15-18, 2019.

Stock Index selection process is tough in financial domain and complicated in decision making process, especially when selected criterion is confecting in nature. Multi criteria decision-making (MCDM) methods like Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are most commonly used method for decision making process in financial domain. This paper utilizes AHP and TOPSIS method for ranking of indices. Three financial year data of five stock indices from Shanghai Stock Exchange (SSE) with four criteria are considered in stock index ranking process. Experimental result reveals that SSE IT TELECOMMUNICATION index is preformed consistently well for all three financial years in case of both AHP and TOPSIS method.

Analytical Hierarchy Process (AHP),Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)

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Sanjay Kumar Singhai, Vineet Kumar Awasthi, "Stock Index Ranking and Performance Evaluation of Shanghai Stock Exchange (SSE) Using AHP and TOPSIS Method", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.19-23, 2019.

Land use is a primary indicator of the extent and degree to which man has modified the land resources. For the present study Takhatpur nagar panchayat of Bilaspur district of Chhattisgarh state was selected randomly. The Google earth, satellite images and GIS software (QGIS /SAGA) were used for the development of land use and land cover classes and subsequently for change detection analysis of the study area. From the findings, it was observed that the agricultural land of Takhatpur nagar panchayat was decreased upto27.883 hectare. The total 4.283 hectare rural build up and total 23.30 hectare urban build up area of Takhatpur nagar panchayat was increased during last 10 years span of time.

LULC, GIS, Remote Sensing, Buildup area

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Sanjeev Kumar Bhagat, P. R. Singh, Dilip Kumar, "Spatial Analysis of Land Use Land Cover Change At Takhatpur Nagar Panchayat of Bilaspur District In Chhattisgarh", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.24-26, 2019.

The present study was conducted in the Kawardha district of Chhattisgarh state, because in this district Baiga population is highest as compare to other district of state. For primary data collected the researcher surveyed three gram Panchayat namely, Bairak, Dholbazza and Borakhakar of Kawardha district. On the basis of discussion with Baigas, it may be said that Baigas living on higher hill, have retained more of their traditional features then the ones in lower areas who have mostly migrated from the top in search of cultivable land, when Bewar practice was forcibly stopped by the government. The 1912 Mandla Gazeteer noted that the ‘principal habitat’ of Baiga lie in the ‘recesses of the Maikal range’, which stretches from Kawardha district of Chhattisgarh to some part of Madhya Pradesh.

PVTGs, Baiga, Baiga Chak, Tribal

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Durgesh Dixena, Dilip Kumar, P R Singh, D K Patel, "Identification of PVTGS (Particularly Vulnerable Tribal Groups) Habitat at Kawardha District in Chhattisgarh State", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.27-30, 2019.

The total production in India is around 280 million tonnes of food grains annually, which includes rice, wheat, cereals, pulses, vegetables and other. The quantum of storage loss and other wastage of foodgrains is very much high. India is the second most heavily populated country after China in the world. It is estimated that India will supersede China by 2025 and will become the most populous country in the world. To feed this huge population is a challenging task and the wastage and losses in foodgrains are taking this challenge to another level of difficulty. According to United Nation Development Programme (UNDP), almost 40 percent of the foodgrains production in India is wasted every year. The reasons behind the wastages are lack of scientific storage structures, lack of storage space, in transit losses, wastage by the users and many more. The wastage quantum of food is the loss of food addition to the loss of resources. The amount of loss not only includes the cost of foodgrains loosed but also includes the cost of resources as well as the loss of the opportunity cost. In India, one major body, who deals with the storage of foodgrains, is Food Corporation of India (FCI). FCI procures and stores the foodgrains like wheat and rice on behalf of the Government of India. FCI uses the scientific methods to prevent the losses in storage and make sure that the stored foodgrains remain in the good condition. Based on the advice from Government of India, FCI releases the foodgrains for the welfare schemes like Public Distribution System, Mid Day Meal or for military quota. In this research work, researcher has studied the quantum of storage loss in FCI, Nagpur Area Office for the year 2015-16. The aim of this research work is to compare the actual losses and prescribed losses limits. The data for this study is collected through the secondary data sources.

FCI, Food Corporation Of India, Storage Loss, Rice , Wheat

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Rekha Bora, "Study of Storage Losses in Food Corporation of India, Nagpur Area Office for Financial Year 2015-16", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.31-35, 2019.

The improvement of sight and sound and web takes into consideration wide conveyance of computerized media information. It turns out to be significantly less demanding to alter, adjust and copy advanced data. In extra, advanced report is likewise simple to duplicate and appropriate, along these lines it might confront numerous dangers. It ended up plainly important to locate a suitable security because of the centrality, exactness and affectability of the data. Besides, there is no formal technique to be taken after to find shrouded information. In this paper, we proposed an approach amongst Steganography and Watermarking. In this paper, another data concealing framework is introduced. The point of the proposed framework is to shroud data (information document) inside watermark picture. This paper covers three fundamental standards of security: Confidentiality, Integrity and Authentication (CIA).

Steganography, Watermarking, Hidden data, CIA

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Upendra Verma, R.K. Rambola, Pratiksha Meshram, "Design and Development of a technique for Hidden data in Watermark Image using Steganography: An Exploration", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.36-40, 2019.

Health is precious for every life. But there are many diseases which fall under the category of dangerous or critical due to it mortality rate. Such diseases can be cured or at least prevented if they are identified in their earlier stages. For the proper diagnosis of these diseases, data mining techniques using machine learning methods- k-NN, Naïve Base, Decision trees, Support Vector Machine plays very significant role. In this paper the focus was on finding techniques applied for the common disease classifications, the accuracy of methods reported, dataset used and pros and cons of these methods and concluded with the open challenges and opportunities for further research in health care sector.

Machine Learning, Data, classification

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Nishant Behar, Manish Shrivastava, "Machine Learning: An Effective Technique for Health Data Classification", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.41-47, 2019.