Graph mining is an active research area during these days. Graphs have become significant in the modeling of complicated structures such as circuit images, chemical compounds, protein structures, biological networks, social networks, web workflows and XML documents. A common framework is necessary to study various graph mining algorithms and their applications. In this paper, we present a review study of various algorithms based on their graph representation, subgraph generation, algorithm approach, frequency evaluation and search strategy.

The calculated anomaly of gravity includes effects – combinations of structures that have the different density and depth - of study area and beyond it. In this paper, a method for the separation of regional and residual fields is used, is the finite element method. This method has been used in the interpretation of potential field and can be easily resolved complex issues in the last few decades. The detected regional gravity anomaly is based on the interpolation functions of the elements that used in the finite element analysis. The first stage of FEM is selection of element and then the decision of boundary conditions. In this step, the solution space is divided into elements. After designation of the geometric structure of solution space, the most suitable elements must be selected for this structure. The compatibility between the geometry and the elements to achieve the best possible solution is important. Regional gravity will be approximated by weighted set from finite gravity values of eight stations according to eight nodes of one element that has similar second parameter which is located in the map The calculation is performed via interpolation functions, which act as weighting factors, in a reference space which has no dimension. In this study, the FEM method was used for gravity data of minoo salt dome, for calculating regional and residual anomaly. In conclusion, the results were obtained via FEM method, which is more accurate than other methods.

Proposals: The Supplementary effects of networks and clusters on firm innovation\nDesign /Methodology: We develop a conceptual model that how a firms network and cluster supplement each ‎other in improving the firm\'s possibility of technological innovations. We recognize innovation accelerators ‎consciousness, innovation obstacle, resource restriction, organizational inflexibility, and ambiguity. Our ‎conceptual model explains how some factors in the cluster such as competitive, social interaction, and cluster ‎energy and network factors such as resource, and network energy impact innovation accelerators and obstacles ‎and succeeding the firm\'s possibility of generating incremental and progress innovations.‎\nFinding: Result shows that the design and management of the firm’s network must be a key strategic ‎consideration of managers to ensure that the network continues to furnish innovation opportunities and ‎resources and it decreases underlying innovation obstacle. Competitive and collaborative outlook of cluster and ‎network have provided a differential roles of clusters and networks on innovation. Therefore, high competition ‎intensity and the firm’s knowledge base increases the co-located challenger\'s‎’ motivation to obtain the ‎knowledge from the central firm, and high social interaction intensity may furnish them with the means to do ‎so.‎\nResearch implication / limitation: Conceptual framework suggests our comprehension with clusters and ‎networks and explicates their limitations at the same time.‎\nOriginality/Value: we developed a conceptual model explaining how two important external factors cluster ‎and network determine the possibility of technological innovations. ‎

A feature of satellite images is the\npresence of noise, this noise often\nrequires preprocessing of the images by a\ndenoising method adapted prior to their\ncompression, storage and transmission.\nIn this work to improve the compression\nscheme, we are interested in image\ncompression by discarding noisy bits from\nthe satellite image and discrete wavelet\ntransform (DWT). This method was tested\non various satellite images; this type of\ncompression has allowed us to determine\nthe quality of the reconstructed images\n(PSNR) and the compression ratio (CR)\naccording to the corresponding of\ndenoising method. A comparative study\nwas conducted to determine the methods\nleading to the best possible results.

In patients of spinal muscular atrophy from different clinical types and with different copy numbers of the SMN2 gene the level of FL- SMN (Full length Survival of Motor Neuron) protein is reported to be same and even with same copy no. of the SMN2 gene the FL-SMN levels were reported to be different. We postulated that the difference in the promoter region of SMN2 gene might produce the different level of FL-SMN protein in SMA patients. To verify this hypothesis, the DNA samples of 69 SMA patients were analyzed for SMN1 deletion followed by the SMN2 copy no. analysis and NAIP deletion analysis to remove any clinical bias. Based on the bioinformatics analysis and the designed primers, PCR amplification was done for different regions in promoter of the SMN2 gene in SMA patients (n=10) followed by direct DNA sequencing. The molecular analysis confirmed the absence of any variation in the promoter region of the SMN2 gene between normal healthy individuals (n=2) and SMA patients. To the best of our knowledge, this is first study analyzing the promoter region of SMN2 gene in all clinical types of SMA.

The main purpose of this study was to investigate and analysis of attitude of agricultural extension experts towards organic farming in Kermanshah Township, Iran. The Statistical population in this study consisted of all agriculture extension experts of Jihad-e-Agriculture management and centres of agricultural services in Kermanshah Township (N=148), that 123 of them were selected as research sample using random simple sampling method. The main instrument in this study was questionnaire. Data was analyzed by SPSSWin20 and LISREL8.80 software. Results of Confirmatory factor analysis (CFA) confirmed the validity of measurement model of attitude towards organic farming in Kermanshah Township. Results showed that the attitude of the majority (57%) of agricultural extension experts toward organic farming in Kermanshah Township was at the neutral level. Findings of mean comparison showed that there were significant differences between attitudes of agricultural extension experts toward organic farming in Kermanshah Township based on field of study. In addition, the results of multiple regression analysis indicated that about 35 percent of attitudes of agricultural extension experts toward organic farming is explained by amount of study of research journal and amount using of internet. Results of this study have applications for managers of Jihad-e-Agriculture management and centers of agricultural services in order to increase attitudes of agricultural extension experts toward organic farming.