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Uma,
- Feministic Perspective in Bharati Mukherjee's-'WIFE'
Abstract Views :150 |
PDF Views:1
Authors
Uma
1
Affiliations
1 Dayal Singh College, New Delhi, IN
1 Dayal Singh College, New Delhi, IN
Source
International Journal of Literary Studies, Vol 6, No 3-4 (2016), Pagination: 95-97Abstract
Bharati Mukherjee, caught between two different worlds, seeks synthesis, conciliation, compromise and sense of living together, absorbing different influences. Mindsets and traditions in a human reality.- Quantification of Carbon Stocks and Sequestration Potential through Existing Agroforestry Systems in the Hilly Kupwara District of Kashmir Valley in India
Abstract Views :255 |
PDF Views:80
Authors
Ajit
1,
A. K. Handa
2,
S. K. Dhyani
3,
G. M. Bhat
4,
A. R. Malik
4,
V. Dutt
4,
T. H. Masoodi
4,
Uma
1,
Amit Jain
2
Affiliations
1 ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi 110 012, IN
2 ICAR-Central Agroforestry Research Institute, Jhansi 284 003, IN
3 NRM-Division, ICAR, KAB-II, Pusa, New Delhi 110 012, IN
4 Camp-Wadura, Sher-e-Kashmir University of Agricultural Sciences and Technology, Srinagar 190 025, IN
1 ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi 110 012, IN
2 ICAR-Central Agroforestry Research Institute, Jhansi 284 003, IN
3 NRM-Division, ICAR, KAB-II, Pusa, New Delhi 110 012, IN
4 Camp-Wadura, Sher-e-Kashmir University of Agricultural Sciences and Technology, Srinagar 190 025, IN
Source
Current Science, Vol 113, No 04 (2017), Pagination: 782-785Abstract
The dynamic carbon accounting model CO2FIX was used for evaluating carbon stocks and estimate greenhouse gas mitigation through tree-based systems, outside the forest area, in Kupwara district of Kashmir valley India. Primary survey results revealed that on an average, there were about 135 trees per hectare, existing on farmers' field. Malus (33.75%), populus (29.91%), salix (14.32%), juglans (6.68%) and robinia (4.7%) were dominant tree species. Paddy and maize are the dominant kharif crops, whereas rabi season is dominated by oilseeds and fodder crops. The carbon sequestration potential, all the three pools simultaneously (viz. tree, crop and soil), of existing agroforestry systems (AFS) has been predicted as 0.88 Mg C ha-1 yr-1. AFS at district level are estimated to sequester 146,996 tonnes of CO2 equivalent annually, which may offset completely the greenhouse gas emissions from agriculture/irrigation sector on account of electricity consumption throughout the state of Jammu and Kashmir.Keywords
Agroforestry Systems, Carbon Sequestration Potential, GHG Mitigation, Soil Carbon, Tree Biomass.References
- Albrecht, A. and Kandji, S. T., Carbon sequestration in tropical agroforestry systems. Agric. Ecosys. Environ., 2003, 99, 15–27.
- Rao, K. P. C., Verchot, L. V. and Laarman, J., Adaptation to climate change through sustainable management and development of agroforestry systems. SAT eJournal, 2007, 4, 1–30.
- Sheikh, A. Q., Skinder, B. M., Pandit, A. K. and Ganai, B. A., Terrestrial carbon sequestration as a climate change mitigation activity. J. Pollut. Effects Control, 2014, 2, 110; doi:10.4172/jpe.1000110.
- Calfapietra, C., Gielen, B., Karnosky, D., Ceulemans, R. and Mugnozza, G. S., Response and potential of agroforestry crops under global change. Environ. Pollut., 2010, 158, 1095–1104.
- Wani, N. R. and Qaisar, K. N., Carbon per cent in different components of tree species and soil organic carbon pool under these tree species in Kashmir valley. Curr. World Environ., 2014, 9(1), 174–181; http://dx.doi.org/10.12944/CWE.9.1.24.
- Wani, N. R., Qaisar, K. N. and Khan, P. A., Growth performance, biomass production and carbon stocks of 19 year old Fraxinus floribunda (ash tree) plantations in Kashmir valley. Agric. Forest., 2014, 60(1), 125–143.
- Wani, N. R., Qaisar, K. N. and Khan, P. A., Biomass, carbon stocks and carbon dioxide mitigation potential of Cedrus deodara under temperate conditions of Kashmir. Can. J. Pure Appl. Sci., 2014, 8(1), 2677–2684.
- Nabuurs, G. J. and Schelhaas, M. J., Carbon profile of typical forest types across Europe assessed with CO2FIX. Ecol. Indicators, 2002, 1, 213–233.
- Masera, O. et al., Modelling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach. Ecol. Model, 2003, 164, 177–199.
- Schelhaas, M. J. et al., CO2FIX V 3.1 – a modelling framework for quantifying carbon sequestration in forest ecosystems. ALTERRA Report 1068, Wageningen, The Netherlands, 2004.
- Gaboury, S., Boucher, J. F., Villeneuve, C., Lord, D. and Gagnon, R., Estimating the net carbon balance boreal open woodland afforestation: a case study in Quebec’s closed crown boreal forest. Forest Ecol. Manage., 2009, 257, 483–494.
- Kaul, M., Mohren, G. M. J. and Dadhwal, V. K., Carbon storage and sequestration potential of selected tree species in India. Mitig. Adapt. Strateg. Global Change, 2010, 15, 489–510.
- Ajit, et al., Modelling analysis of potential carbon sequestration under existing agroforestry systems in three districts of IndoGangetic plains in India. Agroforest. Syst., 2013, 87, 1129–1146.
- Ajit, et al., Estimating carbon sequestration potential of existing agroforestry systems in India. Agroforest Syst., 2016, 1–20; doi: 10.1007/s10457-016-9986-z (published online 12 August 2016).
- Liski, J., Palosuo, T., Peltoniemi, M. and Sievanen, R., Carbon and decomposition model YASOO for forest soils. Ecol. Model, 2005, 189, 168–182.
- Dar, J. A. and Sundarapandian, S., Variation of biomass and carbon pools with forest type in temperate forests of Kashmir Himalaya, India. Environ. Monitor. Assess., 2015, 87(2), 55; doi: 10.1007/s10661-015-4299-7.
- Jana, B. K., Biswas, S., Majumder, M., Roy, P. K. and Mazumdar, A., Carbon sequestration rate and above ground biomass carbon potential of four young species. J. Ecol. Natural Environ., 2009, 1, 15–24.
- Yadava, A. K., Biomass production and carbon sequestration in different agroforestry systems in Tarai region of central Himalaya. Indian Forester, 2010, 136, 234–244.
- Performance Analysis, Comparative Survey of Various Classification Techniques in Spam Mail Filtering
Abstract Views :175 |
PDF Views:0
Authors
Affiliations
1 D.C.S.A., M.D.U. ,Rohtak, IN
2 D.C.S.A., M.D.U., Rohtak, IN
1 D.C.S.A., M.D.U. ,Rohtak, IN
2 D.C.S.A., M.D.U., Rohtak, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 3 (2017), Pagination: 698-702Abstract
One of the most common methods of communication involves the use of e-mail for personal messages or for business purposes. One of the major concerns of using the e-mails is the problem of e-mail spam. The worst part of the spam e-mails is that, these are invading the users without their consent and bombarding of these spam mails fills up the whole e-mail space of the user along with that, the issue of the wasting the network capacity and time consumption in checking and deleting the spam mails makes it even more concerning issue. With the increasing demand of removing the e-mail spams the area has become magnetic to the researchers. This paper intends to present the performance comparison analysis of various pre-existing classification technique. This paper discusses about spam mails in section (I), In section (II) various feature selection methods are discussed , In section (III) classification techniques concept in spam filtering has been elaborated, In section (IV) existing algorithms for classification are discussed and are compared. In section (V) concludes the paper giving brief summary of the work.Keywords
Classification, E-mail Threats, Spam Filtering, Efficiency , Feature Selection.References
- Omar Saad, Ashraf Darwish and Ramadan Faraj: “Asurvey of machine learning techniques for Spam filtering”, IJCSNS ,International Journal of Computer Science and Network Security, VOL.12 No.2, February 2012.
- I. Androutsopoulos, J. Koutsias, “An evaluation of naïve Bayesian anti-spam filtering”, 11thEuropean Conference on Machine Learning (ECML 2000),pp 9–17, 2000.
- Androutsopoulos, G. Paliouras, “Learning to filter spam E-mail: A comparison of a naïve Bayesian and a memory based approach”, 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp 1–13, 2000.
- K. Schneider, “A comparison of event models for naive bayes anti-spam e-mail filtering”, 10th Conference of the European Chapter of the Association for Computational Linguistics, pp.307-314, 2003.
- N. Cristianini, B. Schoelkopf, “Support vector machines and kernel methods, the new generation of learning machines”. Artificial Intelligence Magazine, pp 31–41, 2002 6. S. Amari, S. Wu, “Improving support vector machine classifiers by modifying kernel functions”. Neural Networks, pp 783–789, 1999.
- C. Miller, “Neural Network-based Antispam Heuristics”, Symantec Enterprise Security (2011), www.symantec.com Retrieved December 28, 2011
- Anirudh Harisinghaney, Aman Dixit, Saurabh Gupta, and Anuja Arora , “Text and image based spam e-mail classification using KNN, Naïve Bayes and reverse DBSCAN Algorithm, “ ICROIT 2014, India, Feb 6-8 2014.
- Masurah Mohamad and Ali Selamat, “An evaluation on the efficiency of hybrid feature selection in spam e-mail classification,” IEEE International Conference on Computer Communication, and Control Technology (14CT 2015), April. 2015.
- Rushdi Shams and Robert E. Mercer, “Classification spam e-mails using text and readability features,” IEEE 13th International Conference on Data Mining, pp. 657-666, 2013.
- Megha Rathi and Vikas Pareek, “Spam E-mail Detection through Data Mining-A Comparative Performance Analysis,” I.J. Modern Education and Computer Science, pp. 31-39, 2013.
- Ms.D. Karthika Renuka, Dr.T. Hamsapriya, Mr.M. Raja Chakkaravar t h i , Ms.P. Lakshmisurya, “Spam Classification based on Supervised Learning using Machine Learning Techniques,” IEEE, pp.1-7, 2011
- V. Vaithiyanathan , K. Rajeswari , Kapil Tajan , Rahul Pitale, “Comparison Of Different Classification Techniques Using Different Data sets” , IJAET , ISSN: 2231-1963 ,Vol. 6, Issue 2, pp. 764-768 , May 2013