Search Results - (( leaf classification tree algorithm ) OR ( java implementation modified algorithm ))

Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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Effective k-Means Clustering in Greedy Prepruned Tree-based Classification for Obstructive Sleep Apnea by Sim, Doreen Ying Ying, Ahmad I., Ismail, Chee Siong, Teh

“…Incorporation of prepruned decision trees to kmeans clustering through one to three types of tree-depth controllers and cluster partitioning was done to develop a combined algorithm named as Greedy Pre-pruned Treebased Clustering (GPrTC) algorithm. …”
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Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

“…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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Delineating mangrove forest zone using spectral reflectance by Abdul Whab @ Abdul Wahab,, Zulfa

“…The use of SID and SAM may provide the most promising classification algorithm for improving mangrove species mapping. …”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

“…The algorithms were tested to classify the leaf samples into four levels of disease severity. …”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi

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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques by Kayalvily, Tabianan, Denis, Arputharaj, Mohd Norshahriel, Abd Rani, Sarasvathi, Nahalingham

“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

“…The results indicated that LDA-based model resulted in high average overall classification accuracies of 92% (leaf samples) and 94% (trunk samples) when mid-infrared absorbance spectra were analyzed. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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FT-IR absorbance data for early detection of oil palm fungal disease infestation by Liaghat, Shohreh, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Ehsani, Reza, Md Nor Azam, Siti Hajar

“…At present study, we propose to apply a mid-infrared spectroscopy technique for detection of infected oil palm trees at three stages of infection. Leaf samples of healthy, mild, moderate and sever-infected trees were measured using Fourier transform infrared (FTIR) spectrometers system to obtain absorbance data from the range of 2.55-25.05 μm. …”
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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…The ReliefF feature selection technique was used to determine the most influential wavelengths for the classification of FLS disease severity in soybean. Next, machine learning (ML) methods (i.e. decision tree, gradient boosting, random forest, stacking, and neural network) were used to classify FLS of soybean. …”
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Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy by Al-Khaled, Alfadhl Yahya Khaled, Abd Aziz, Samsuzana, Bejo, Siti Khairunniza, Mat Nawi, Nazmi, Abu Seman, Idris

“…Thus, this paper investigated the feasibility of utilizing electrical properties such as impedance, capacitance, dielectric constant, and dissipation factor in early detection of BSR disease in oil palm tree. Leaf samples from different oil palm trees (healthy, mild, moderate, and severely-infected) were collected and measured using a solid test fixture (16451B, Keysight Technologies, Japan) connected to an impedance analyzer (4294A, Agilent Technologies, Japan) at a frequency range of 100 kHz–30 MHz with 300 spectral interval. …”
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Hyperspectral spectroscopy and imbalance data approaches for classification of oil palm's macronutrients observed from frond 9 and 17 by Amirruddin, Amiratul Diyana, Muharam, Farrah Melissa, Ismail, Mohd Hasmadi, Tan, Ngai Paing, Ismail, Mohd Firdaus

“…This paper highlights the application of hyperspectral sensing in conjunction with imbalance approaches and machine learning (ML) algorithms to monitor the nutrients status of mature oil palm. …”
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Feature Selection and Ensemble Meta Classifier for Multiclass Imbalance Data Learning by Sainin, Mohd Shamrie, Alfred, Rayner, Alias, Suraya, Lammasha, Mohamed A.M.

“…The aim of this paper is to investigate the effects of combining feature selection and ensemble classifiers on the prediction performance in addressing the multiclass imbalance data learning .This research uses data obtained from the Malaysian medicinal leaf images shape data and three other large benchmark data sets in which six ensemble methods from Weka machine learning tool were selected to perform the classification task.These ensemble methods include the AdaboostM1, Bagging, Decorate, END, MultiboostAB, and Rotation Forest.In addition, five base classifiers were used; Naïve Bayes, SMO, J48, Random Forest, and Random Tree in order to examine the performance of the ensemble methods. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

“…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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