scholarly journals Inventory, Conservation Statement and Classification of Bird Trade in Cianjur based on Data Mining Methods

2019 ◽  
Vol 8 (2S7) ◽  
pp. 22-24
Keyword(s):  
Data Mining ◽  
Conservation Status ◽  
Bird Species ◽  
Dominance Status ◽  
Rule Based ◽  
Search Results ◽  
The Status ◽  
Mining Methods ◽  
Total Species

Currently in the community many who keep birds. To get the birds people are looking for in the bird market. Total species of birds traded (Kabupaten Cianjur) as many as 46 types of 23 tribes. From the search results were found by IUCN endangered bird species but by law in Indonesia excluding protected ones such as the species of ekelgeling (Cissathalassina) whose conservation status is highly endangered. The excavation of the rule based on available data using the c45 algorithm shows that the dominance status of bird species in the Cipanas area has a significant influence on the status of the dominance of bird species for the entire Cianjur region.

A data mining approach to the diagnosis of failure modes for two serial fastened sandwich composite plates

2016 ◽  
Vol 51 (20) ◽  
pp. 2853-2862 ◽  
Author(s):  
Serkan Ballı
Keyword(s):  
Data Mining ◽  
Random Forest ◽  
Failure Modes ◽  
Composite Plates ◽  
Study Data ◽  
Sandwich Composite ◽  
Support Vector ◽  
Geometrical Parameters ◽  
Mining Methods

The aim of this study is to diagnose and classify the failure modes for two serial fastened sandwich composite plates using data mining techniques. The composite material used in the study was manufactured using glass fiber reinforced layer and aluminum sheets. Obtained results of previous experimental study for sandwich composite plates, which were mechanically fastened with two serial pins or bolts were used for classification of failure modes. Furthermore, experimental data from previous study consists of different geometrical parameters for various applied preload moments as 0 (pinned), 2, 3, 4, and 5 Nm (bolted). In this study, data mining methods were applied by using these geometrical parameters and pinned/bolted joint configurations. Therefore, three geometrical parameters and 100 test data were used for classification by utilizing support vector machine, Naive Bayes, K-Nearest Neighbors, Logistic Regression, and Random Forest methods. According to experiments, Random Forest method achieved better results than others and it was appropriate for diagnosing and classification of the failure modes. Performances of all data mining methods used were discussed in terms of accuracy and error ratios.

scholarly journals Conservation status of birds on Mindoro, Philippines

1992 ◽  
Vol 2 (4) ◽  
pp. 303-325 ◽  
Author(s):  
Guy C. L. Dutson ◽  
Tom D. Evans ◽  
Thomas M. Brooks ◽  
Desiderio C. Asane ◽  
Robert J. Timmins ◽  
...  
Keyword(s):  
Forest Cover ◽  
Conservation Status ◽  
Bird Species ◽  
Concerted Action ◽  
Medium Term ◽  
Lowland Forest ◽  
Risk Of Extinction ◽  
Forest Remnants ◽  
The Status

SummaryFour weeks of fieldwork in the forests of Mindoro, Philippines, in 1991 has elucidated the status of the six bird species endemic to the island. Of these, Ducula mindorensis and Otus mindorensis are high-altitude species with restricted ranges and in need of active conservation in the medium term. Three of the four lowland species, Gallicolumba platenae, Centropus steerü and Penelopides mindorensis are under immediate threat of extinction through forest clearance and fragmentation, while the fourth, Dicaeum retrocinctum, s i not under immediate threat but is certainly at risk of extinction in the long term. Whilst deforestation is an enormous problem across the entire Philippines, Mindoro is the smallest centre of endemism with the least forest cover after the Sulu Islands. Extinctions are believed inevitable within the next 10 years unless concerted action is urgently taken. The Halcon range must receive attention in order to conserve the montane species, but more urgent by far is the preservation of lowland forest remnants, concentrating on central-west Mindoro.

scholarly journals The Status and Threats of Birds: A Case Study of Birds in Nayapul to Ghandruk Area, Kaski, Nepal

2021 ◽  
pp. 18-32
Author(s):  
Subhas Chandra Bastola
Keyword(s):  
Crop Production ◽  
Abiotic Factors ◽  
Bird Species ◽  
Habitat Destruction ◽  
Bird Population ◽  
Factors Affecting ◽  
Storage Devices ◽  
The Status ◽  
Total Species

The purpose of this study is to quantify species diversity of birds in the study area and to explore the biotic and abiotic factors affecting the bird population. This study was carried out by using the fixed point counting method. The study area was situated in Annapurna Rural Municipality of Kaski district. A total of 147 bird species belonging to 46 families and 14 orders were identified in the study area. It was found that Muscicapidae was the largest family and Passeriformes the largest order. Among the reported species, 50% were residents, 31% were full-migrants, 18% were altitudinal migrants and the remaining were 1% nomadic. Habitats of birds included the forest 68%, the scrubland 17 %, the grassland 7% and the wetland 6 % of the study area. Similarly, the rocky area and artificial area covered 1% of the total species. The results showed that most of the bird species i.e. 136 were least concerned, 4 of them were nearly threatened, 3 of them were endangered, 3 were critically endangered and only one species was vulnerable. The most important threats included hunting and trapping, killing for fun, shift in crop production, use of insecticides and pesticides, improved storage devices, habitat destruction, developmental activities, tourism, buried carcasses and predatory.

Prediction of Cardiovascular Risk in Hemodialysis Patients by Data Mining

2004 ◽  
Vol 43 (01) ◽  
pp. 106-113 ◽  
Author(s):  
K. Weller ◽  
D. Woetzel ◽  
R. Guthke ◽  
K. Schroeder ◽  
G. Stein ◽  
...  
Keyword(s):  
Data Mining ◽  
Cardiovascular Risk ◽  
Interventricular Septum ◽  
Hemodialysis Patients ◽  
Left Ventricular ◽  
Performance Criteria ◽  
Individual Risk ◽  
Data Set ◽  
Rule Based ◽  
Mining Methods

Summary Objectives: The objective of this work was to contribute to the development, validation and application of data mining methods for prediction in decision support systems in medicine. The particular focus was on the prediction of cardiovascular risk factors in hemodialysis patients, specifically the interventricular septum (IVS) thickness of the heart of individual patients as an important quantitative indicator to diagnose left ventricular hypertrophy. The work was based on data from 63 long-term hemodialysis patients of the KfH Dialysis Centre in Jena, Germany. Methods: The approach applied is based on data mining methods and involves four major steps: data based clustering, cluster based rule extraction, rulebase construction and cluster and rule based prediction. The methods employed include crisp and fuzzy algorithms. At each step, logical and medical validation of results was carried out. Different sets of randomly selected patient data were used to train, test and optimize the clusterbases and rulebases for prediction. Results: Using the best clusterbase/rulebase combination designed, the IVS thickness cluster (‘small’ or ‘large’) was predicted correctly for 30 of the 35 patients with known IVS values in the training data set; no patient was predicted incorrectly and 5 were parity predicted. For the test data set, 4 of the 6 patients with known IVS values were predicted correctly, no patient incorrectly and 2 parity. These results did not substantially differ from those obtained using the second best clusterbase/rulebase combination which was finally recommended for use based on further performance criteria. The prediction of the IVS thickness clusters of the 22 patients with unknown IVS values also yielded good results that were (and could only be) validated by a medical individual risk assessment of these patients. Conclusions: The approach applied proved successful for the cluster and rule based prediction of a quantitative variable, such as IVS thickness, for individual patients from other variables relevant to the problem. The results obtained demonstrate the high potential of the approach and the methods developed and validated to support decision-making in hemodialysis and other fields of medicine by individual risk prediction.

Developing an intelligent trip recommender system by data mining methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Tamer Uçar
Keyword(s):  
Data Mining ◽  
System Framework ◽  
Related Area ◽  
Simple Task ◽  
Related Services ◽  
Search Results ◽  
Target User ◽  
User Groups ◽  
Mining Methods ◽  
Wide Usage

Internet has a very wide usage in almost every sector. People are continuously looking and searching for information through internet. Narrowing down relevant search results is not a very simple task. Recommender systems are being used in almost every search related area. Tourism domain is one of these sectors. This study proposes an implementation of an expert system framework which can accurately classify users and make predictions about user classifications for recommending tourism related services. Proposed approach predicts clusters for system users and according to these user clusters, trips, hotels and such services can be recommended individually or as a campaign to target user or user groups. Keywords:  Trip recommender, data mining, expert systems

scholarly journals Mistletoe as a keystone resource: an experimental test

2012 ◽  
Vol 279 (1743) ◽  
pp. 3853-3860 ◽  
Author(s):  
David M. Watson ◽  
Matthew Herring
Keyword(s):  
Species Richness ◽  
Bird Species ◽  
Small Scale ◽  
High Turnover ◽  
Total Species Richness ◽  
Before And After ◽  
The Status ◽  
Scale Experiment ◽  
Total Species ◽  
Keystone Resource

Various entities have been designated keystone resources, but few tests have been attempted and we are unaware of any experimental manipulations of purported keystone resources. Mistletoes (Loranthaceae) provide structural and nutritional resources within canopies, and their pervasive influence on diversity led to their designation as keystone resources. We quantified the effect of mistletoe on diversity with a woodland-scale experiment, comparing bird diversities before and after all mistletoe plants were removed from 17 treatment sites, with those of 11 control sites and 12 sites in which mistletoe was naturally absent. Three years after mistletoe removal, treatment woodlands lost, on average, 20.9 per cent of their total species richness, 26.5 per cent of woodland-dependent bird species and 34.8 per cent of their woodland-dependent residents, compared with moderate increases in control sites and no significant changes in mistletoe-free sites. Treatment sites lost greater proportions of birds recorded nesting in mistletoe, but changes in species recorded feeding on mistletoe did not differ from control sites. Having confirmed the status of mistletoe as a keystone resource, we suggest that nutrient enrichment via litter-fall is the main mechanism promoting species richness, driving small-scale heterogeneity in productivity and food availability for woodland animals. This explanation applies to other parasitic plants with high turnover of enriched leaves, and the community-scale influence of these plants is most apparent in low productivity systems.

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