Monitoring and Mapping of Crop Fields with UAV Swarms Based on Information Gain

2022 ◽  
pp. 306-319
Author(s):  
Carlos Carbone ◽  
Dario Albani ◽  
Federico Magistri ◽  
Dimitri Ognibene ◽  
Cyrill Stachniss ◽  
...  
Keyword(s):  
Information Gain ◽  
Crop Fields

PENENTUAN DAERAH PRIORITAS PELAYANAN AKTA KELAHIRAN DENGAN METODE K-NN DAN K-MEANS

2020 ◽  
Vol 17 (1) ◽  
pp. 319-328
Author(s):  
Ade Muchlis Maulana Anwar ◽  
Prihastuti Harsani ◽  
Aries Maesya
Keyword(s):  
Nearest Neighbor ◽  
Information Gain ◽  
Birth Certificate ◽  
Population Data ◽  
Community Services ◽  
Birth Certificates ◽  
Similar Data ◽  
K Nearest Neighbor ◽  
Civil Registration ◽  
The Family

Population Data is individual data or aggregate data that is structured as a result of Population Registration and Civil Registration activities. Birth Certificate is a Civil Registration Deed as a result of recording the birth event of a baby whose birth is reported to be registered on the Family Card and given a Population Identification Number (NIK) as a basis for obtaining other community services. From the total number of integrated birth certificate reporting for the 2018 Population Administration Information System (SIAK) totaling 570,637 there were 503,946 reported late and only 66,691 were reported publicly. Clustering is a method used to classify data that is similar to others in one group or similar data to other groups. K-Nearest Neighbor is a method for classifying objects based on learning data that is the closest distance to the test data. k-means is a method used to divide a number of objects into groups based on existing categories by looking at the midpoint. In data mining preprocesses, data is cleaned by filling in the blank data with the most dominating data, and selecting attributes using the information gain method. Based on the k-nearest neighbor method to predict delays in reporting and the k-means method to classify priority areas of service with 10,000 birth certificate data on birth certificates in 2019 that have good enough performance to produce predictions with an accuracy of 74.00% and with K = 2 on k-means produces a index davies bouldin of 1,179.

The Weed Flora Of Some Crop Fields In Al- Oylia Region, Al-Marj, Libya

2017 ◽  
pp. 1
Author(s):  
Sabah M. Al Hasi ◽  
Yacoub M. El Barasi
Keyword(s):  
Crop Fields ◽  
Weed Flora

Feature Selection Algorithm for High-dimensional Biomedical Data Using Information Gain and Improved Chemical Reaction Optimization

2021 ◽  
Vol 15 (8) ◽  
pp. 912-926
Author(s):  
Ge Zhang ◽  
Pan Yu ◽  
Jianlin Wang ◽  
Chaokun Yan
Keyword(s):  
Feature Selection ◽  
Chemical Reaction ◽  
Information Gain ◽  
Feature Selection Method ◽  
Search Space ◽  
Neighborhood Search ◽  
Biomedical Data ◽  
Chemical Reaction Optimization ◽  
Search Mechanism ◽  
Reaction Optimization

Background: There have been rapid developments in various bioinformatics technologies, which have led to the accumulation of a large amount of biomedical data. However, these datasets usually involve thousands of features and include much irrelevant or redundant information, which leads to confusion during diagnosis. Feature selection is a solution that consists of finding the optimal subset, which is known to be an NP problem because of the large search space. Objective: For the issue, this paper proposes a hybrid feature selection method based on an improved chemical reaction optimization algorithm (ICRO) and an information gain (IG) approach, which called IGICRO. Methods: IG is adopted to obtain some important features. The neighborhood search mechanism is combined with ICRO to increase the diversity of the population and improve the capacity of local search. Results: Experimental results of eight public available data sets demonstrate that our proposed approach outperforms original CRO and other state-of-the-art approaches.

First Detection of Tobacco Mosaic Virus in Tobacco Fields in Northern Lebanon

2020 ◽  
Vol 20 ◽  
Author(s):  
Rami Obeid ◽  
Elias Wehbe ◽  
Mohamad Rima ◽  
Mohammad Kabara ◽  
Romeo Al Bersaoui ◽  
...  
Keyword(s):  
Tobacco Mosaic Virus ◽  
Mosaic Virus ◽  
Viral Genome ◽  
Virus Genome ◽  
Enzyme Linked Immunosorbent Assay ◽  
Virus Family ◽  
Crop Fields ◽  
Wide Range ◽  
Almost All ◽  
Das Elisa

Background: Tobacco mosaic virus (TMV) is the most known virus in the plant mosaic virus family and is able to infect a wide range of crops, in particularly tobacco, causing a production loss. Objectives: Herein, and for the first time in Lebanon, we investigated the presence of TMV infection in crops by analyzing 88 samples of tobacco, tomato, cucumber and pepper collected from different regions in North Lebanon. Methods: Double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA), revealed a potential TMV infection of four tobacco samples out of 88 crops samples collected. However, no tomato, cucumber and pepper samples were infected. The TMV+ tobacco samples were then extensively analyzed by RT-PCR to detect viral RNA using different primers covering all the viral genome. Results and Discussion: PCR results confirmed those of DAS-ELISA showing TMV infection of four tobacco samples collected from three crop fields of North Lebanon. In only one of four TMV+ samples, we were able to amplify almost all the regions of viral genome, suggesting possible mutations in the virus genome or an infection with a new, not yet identified, TMV strain. Conclusion: Our study is the first in Lebanon revealing TMV infection in crop fields, and highlighting the danger that may affect the future of agriculture.

MANAJEMEN DATA SPASIAL: PENGGUNAAN TANAH WILAYAH PEDESAAN DI SUMATERA BARAT

2019 ◽  
Vol 5 (2) ◽  
pp. 48-53
Author(s):  
Afrital Rezki, S.Pd., M.Si ◽  
Erna Juita ◽  
Dasrizal Dasrizal ◽  
Arie Zella Putra Ulni
Keyword(s):  
Land Use ◽  
Paddy Field ◽  
Secondary Forest ◽  
Water Bodies ◽  
Primary Forest ◽  
Land Uses ◽  
Forest Land ◽  
Land Use Patterns ◽  
Crop Fields ◽  
Mixed Plantations

Perkembangan penggunaan tanah bergerak horisontal secara spasial ke arah wilayah yang mudah diusahakan. Penggunaan tanah juga bergerak secara vertikal dalam rangka menaikkan mutunya. Penelitian ini bertujuan untuk menganalisis pola penggunaan lahan, bagaimana manajemen penggunaan lahan di satu wilayah berdasarkan batas Nagari. Metode yang digunakan adalah analsisis spasial dengan interpretasi citra penginderaan jauh, survey lapangan, dan analisis deskriptif. Pertumbuhan pemukiman Nagari Sungai Sariak Kecamatan VII Koto Kabupaten Padang Pariaman mengakibatkan pemanfaatan ruang menjadi tumpang tindih. Diperlukan cara-cara pengelolaan dan managemen penggunaan tanah dalam rangka pembangunan berkelanjutan yang menaikkan taraf hidup masyarakat dan tidak menimbulkan kerugian lingkungan.Terdapat 9 jenis penggunaan lahan yang ada di Nagari Sungai Sariak. Penggunaan lahan tersebut adalah Primary Forest, Secondary Forest, Paddy Field, Settlement, Mixed Plantations, Crop Fields, Water Bodies, Bushes, dan Plantations. Penggunaan lahan yang paling luas di Nagari Sungai Sariak adalah jenis penggunaan lahan Primary Forest, sebesar 48% dari total luas wilayah Nagari Sungai Sariak. Pada tahun 2011 sampai tahun 2016, penggunaan lahan paling luas terjadi pada penggunaan lahan jenis Primary Forest yang kemudian menjadi Mixed Plantations. Land use Changes moved horizontally spatially towards areas that are easily cultivated. The land use also moves vertically in order to increase its quality. This study aims to analyze land use patterns, how land use management in one area is based on Nagari boundaries. The method used is spatial analysis with interpretation of remote sensing images, field surveys, and descriptive analysis. The growth of Nagari Sungai Sariak in Kecamatan VII Koto, Kabupaten Padang Pariaman resulted in overlapping use of space. Management methods are needed and management of land use in the framework of sustainable development that raises the standard of living of the community and does not cause environmental losses. There are 9 types of land use in the Nagari Sungai Sariak. The land uses are Primary Forest, Secondary Forest, Paddy Field, Settlement, Mixed Plantations, Crop Fields, Water Bodies, Bushes, and Plantations. The most extensive land use in Nagari Sungai Sariak is the type of Primary Forest land use, amounting to 48% of the total area of the Nagari Sungai Sariak. From 2011 to 2016, the most extensive land use occurred in Primary Forest land uses which later became Mixed Plantations.

Chemical analysis: Information contribution of results

1991 ◽  
Vol 56 (3) ◽  
pp. 505-559 ◽  
Author(s):  
Karel Eckschlager
Keyword(s):  
Analytical Chemistry ◽  
Information Theory ◽  
Set Theory ◽  
Fuzzy Set Theory ◽  
Information Gain ◽  
Analytical Signal ◽  
Point Of View ◽  
System A ◽  
Review Analysis ◽  
Theory Point

In this review, analysis is treated as a process of gaining information on chemical composition, taking place in a stochastic system. A model of this system is outlined, and a survey of measures and methods of information theory is presented to an extent as useful for qualitative or identification, quantitative and trace analysis and multicomponent analysis. It is differentiated between information content of an analytical signal and information gain, or amount of information, obtained by the analysis, and their interrelation is demonstrated. Some notions of analytical chemistry are quantified from the information theory and system theory point of view; it is also demonstrated that the use of fuzzy set theory can be suitable. The review sums up the principal results of the series of 25 papers which have been published in this journal since 1971.

Analysis of Feature Selection and Ensemble Classifier Methods for Intrusion Detection

2018 ◽  
Vol 7 (1) ◽  
pp. 57-72
Author(s):  
H.P. Vinutha ◽  
Poornima Basavaraju
Keyword(s):  
Feature Selection ◽  
Intrusion Detection ◽  
Detection Rate ◽  
Information Gain ◽  
False Positive Rate ◽  
Ensemble Classifier ◽  
Ensemble Classification ◽  
Chi Square ◽  
Traffic Pattern ◽  
Data Mining Algorithms

Day by day network security is becoming more challenging task. Intrusion detection systems (IDSs) are one of the methods used to monitor the network activities. Data mining algorithms play a major role in the field of IDS. NSL-KDD'99 dataset is used to study the network traffic pattern which helps us to identify possible attacks takes place on the network. The dataset contains 41 attributes and one class attribute categorized as normal, DoS, Probe, R2L and U2R. In proposed methodology, it is necessary to reduce the false positive rate and improve the detection rate by reducing the dimensionality of the dataset, use of all 41 attributes in detection technology is not good practices. Four different feature selection methods like Chi-Square, SU, Gain Ratio and Information Gain feature are used to evaluate the attributes and unimportant features are removed to reduce the dimension of the data. Ensemble classification techniques like Boosting, Bagging, Stacking and Voting are used to observe the detection rate separately with three base algorithms called Decision stump, J48 and Random forest.

scholarly journals Location of Biorefineries Based on Olive-Derived Biomass in Andalusia, Spain

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3052
Author(s):  
Diego Cardoza ◽  
Inmaculada Romero ◽  
Teresa Martínez ◽  
Encarnación Ruiz ◽  
Francisco J. Gallego ◽  
...  
Keyword(s):  
Rural Areas ◽  
Raw Materials ◽  
Value Added ◽  
Olive Tree ◽  
Point Of View ◽  
Industrial Wastes ◽  
Olive Pomace ◽  
Crop Fields ◽  
Lignocellulosic Feedstock ◽  
Olive Stones

A biorefinery integrated process based on lignocellulosic feedstock is especially interesting in rural areas with a high density of agricultural and agro-industrial wastes, which is the case for olive crop areas and their associated industries. In the region of Andalusia, in the south of Spain, the provinces of Jaén, Córdoba and Seville accumulate more than 70% of the olive wastes generated in Spain. Therefore, the valorisation of these wastes is a matter of interest from both an environmental and a social point of view. The olive biorefinery involves a multi-product process from different raw materials: olive leaves, exhausted olive pomace, olive stones and olive tree pruning residues. Biorefinery processes associated with these wastes would allow their valorisation to produce bioenergy and high value-added renewable products. In this work, using geographic information system tools, the biomass from olive crop fields, mills and olive pomace-extracting industries, where these wastes are generated, was determined and quantified in the study area. In addition, the vulnerability of the territory was evaluated through an environmental and territorial analysis that allowed for the determination of the reception capacity of the study area. Then, information layers corresponding to the availability of the four biomass wastes, and layers corresponding to the environmental fragility of the study area were overlapped and they resulted in an overall map. This made it possible to identify the best areas for the implementation of the biorefineries based on olive-derived biomass. Finally, as an example, three zones were selected for this purpose. These locations corresponded to low fragility areas with a high availability of biomass (more than 300,000 tons/year) in a 30 km radius, which would ensure the biomass supply.

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