Objectives: In this research, it has been tried to determine the local priorities of urban green space development in Mahmoud Abad city in order for correct locating of this land use. Methods/Statistical analysis: The local priorities of the development of green space in the city have been determined by using Analytical Hierarchy Process Analysis technique (AHP). After collecting data, we analyzed them and investigated the current status of urban green spaces in Mahmoudabad city by using Geographic Information System (GIS). And finally In the Expert Choice software, the effective criteria in locating green space are weighted and their priority by each other is specified. Findings: The current per capita status of this land use is 0.66 square meters, which is much lower than its standard per capita, so there is a need to build new green spaces. In this paper, population density, land value, air pollution, distance from existing urban parks, proximity to the center of the area, proximity to residential centers and accessibility are considered as locating criteria of green spaces. Among these criteria land value and centrality were identified as the most important criteria for locating green space in Mahmoudabad Nemuneh city. Application/Improvements: It is suggested that the optimal placement and distribution of this land use should be addressed up with considering mentioned in order to increase the citizens' access to this land use and following that improve the quality of urban environment.
Background/Objectives: Tropical coastal areas are characterized by dynamic seascapes which encompass interconnected ecosystems such as wet land, mangroves, sea grass beds and corals. These ecosystems provides are highly productive, aquatic and terrestrial biodiversity as well as for the functioning of economic sectors such as tourism and fisheries. The near shore waters are exhibiting the seasonal variations. Fresh water inflow is influence the nutrient cycle in environments. Methods/Statistical analysis: The sediment samples was collected in Nagapattinam coastal waters from July’ 2016 – June 2017 to collect the polychaete and analyze the species distribution. Findings: The total numbers (nos) of 80123 nos/ m² were distributed in this station. The total numbers of 42 polychaete species were recorded during the study period. All the 42 species were recorded in summer and minimum of 21 species were recorded at monsoon. Among them 9 species of polychaetes ( Capitella capitata, Nereis virens, Polydora ciliata, Perinereis cultrifera, Eunice tentaculata, Terebellides stroemi, Amphinome rostrata, Syllis gracilis and Glycera alba) were dominated in all seasons. Application/Improvements: Benthic macrofauna play an important role in the coastal ecosystems such as scavenging, biological indicator, nourishment and nutraceutical values for fin and shell fishes. Among this, the Polychaetes are predominant group among the macro-benthic forms. They are also often used as live feed for aquaculture industry and also bio-prospecting.
Objective : To focus on classification algorithms to arrive better prediction model for Lung Disease Severity. Methods/Statistical analysis : In therapeutic analyses, the part of information mining methodologies is being expanded. Especially Classification calculations are exceptionally useful in arranging the information, which is critical for basic leadership prepare for therapeutic experts. In this paper the analysis is done in the WEKA apparatus on the spiro informational index. Findings : The paper embarks to make relative assessment of classifiers, for example, J48, Random forest and proposed Hybird Decision Tree(HDT) Algorithm with regards to Spiro dataset to amplify genuine positive rate and limit false positive rate of defaulters as opposed to accomplishing just higher grouping exactness utilizing WEKA instrument. The tests comes about appeared in this paper are about grouping exactness, affectability and specificity. Application/Improvements : The outcomes created on this dataset likewise demonstrate that the productivity and exactness of J48 is superior to anything other choice tree classifiers. J48 develops purge branches, it is the most urgent stride for govern era in J48. In more often than not this approach over fits the preparation cases with boisterous information. The proposed Hybird Decision Tree (HDT) Algorithm demonstrates great exactness in less time.
Objectives : To be familiar with the kinds of coronary illness, and information mining procedures to fight them. Methods/Statistical analysis : To handle this, data mining concepts and techniques used were discussed to discover hidden patterns from medical domain. Findings : The purpose of predictions in data mining is to discover trends in patient data through patterns generation to improve the health strategy. The algorithms presented here are with a specific end goal to anticipate the coronary illness which includes some constraint.
Objectives : To analysis various similarity join techniques to improve the data mining process. Findings : Similarity join is an evaluation of similarity between any two objects. Many applications such as data cleaning, data integration, near duplicate detection and all data mining process can extensively benefit from the similarity join measure. Thus the similarity join can be performed between objects or strings or nodes etc. It finds all pairs of objects whose similarity is not smaller than the similarity threshold. There are different techniques and approaches are used to find the similarity join between objects in homogeneous information network. This paper provides detailed information about the different similarity join techniques. Results : In this paper various similarity join techniques are compared through parameters to prove path based similarity join is better than other techniques. Application/Improvements : The findings of this work prove that the path based similarity join provides better result than other approaches.
