The present article discusses design and development of Information System for monitoring ecology within the Black Sea basin of Georgia. Sea parameters, river, estuary, vulnerable district, water sample, etc. were considered as the major parameters of the sea ecosystem. A conceptual schema has been developed for the Black Sea ecosystem based on object-role model. The experimental database for the Black Sea ecosystem has been constructed using Ms SQL Server, while the object-role model NORMA has been developed using graphical instrument Ms Visual Studio within the integrated environment of .NET Framework 4.5. Web portal has been designed based on Ms SharePoint Server. The server database connection with web-portal has been carried out by means of External List of Ms SharePoint Server Designer.
This research aimed to find amount of heavy metal in herb used in Dusit community and compare of heavy metal in each part by quantity in herb and standard determination in Thai herb books to develop a sustainable quality of life, the result of study in 14 herbs do not find sample of heavy metal., by quantity of heavy contamination of 4 kinds: Cd, Co, Fe and Pb have lower than standard of 2 organizations: Thai herb standard, and World Health Organization, from the test 14 herbs have Fe in every part of herbs and all 14 kinds has Fe that is necessary for our health.
A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency subband of the DWT of the suspicious image thereby leaving valuable information in the other three subbands, the proposed algorithm simultaneously extracts features from all the four subbands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.
A novel copy-move image forgery, CMIF, detection method is proposed. The proposed method presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilized to extract robust features. The extracted features are invariant to additive noise, JPEG compression, and affine transformation. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. SATS is a better option than the common shift vector method because SATS is insensitive to affine transformation. Consequently, the proposed CMIF algorithm is not only fast but also more robust to attacks compared to the existing related CMIF algorithms. The experimental results show high detection rates, as high as 100% in some cases.
Paddy being cultivated since about 10,000 years B.C in Ganga Valley in India, its production reached up to 99 million tons in the year 2012. BGA are of much ecological importance for maintaining the soil fertility and reclaiming the alkalinity. In present investigation attempts were made to identify the local cyanobacterial genera from the paddy fields, BGA application for green farming enabling the paddy to utilize more amount of nitrogen released and to examine its impact along with Urea upon growth and yield responses of the Paddy crop. It was observed that combined treatment of BGA with Urea proved better response in almost all growth parameters and yield attributes except number of tillers/ Plant and grains/ panicle as compared to application of either Urea or BGA alone. The Paddy growers should be encouraged to adopt BGA along with Urea as source of Nitrogen for Paddy cultivation.