Search Results - (( based voting method algorithm ) OR ( java application testing algorithm ))

Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…In a nut shell, we tried to introduce voting algorithms and structures suitable for large scale fault-tolerant systems which have optimal and proper time complexity (in parallel voting algorithms) and more reliability and availability (in enhanced m-out-of-n voting algorithm) compared to the basic types.…”
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Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems by Karimi, Abbas, Zarafshan, Faraneh, Jantan, Adznan, Ramli, Abdul Rahman, Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad

“…To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. …”
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Stability of individual object in construction of voting-merged approach by Shamsuddin, Norin Rahayu, Mahat, Nor Idayu

“…In this paper, we propose a voting-merged method - a combination of voting-based method and merging process. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Dense-cluster based voting approach for license plate identification by Asadzadehkaljahi, Maryam, Shivakumara, Palaiahnakote, Roy, Sangheeta, Olatunde, Mojeed Salmon, Anisi, Mohammad Hossein, Lu, Tong, Pal, Umapada

“…This paper presents a new method called Dense Cluster based Voting (DCV) for identifying an input license plate image as normal or taxi such that suitable recognition algorithms can be used to achieve better recognition rate. …”
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Ant system and weighted voting method for multiple classifier systems by Husin, Abdullah, Ku-Mahamud, Ku Ruhana

“…A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. …”
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University Voting System Using Facial Recognition Technology by Nur Amni Fatini Mohd Nain, Farida Hazwani Mohd Ridzuan, YS Yusoff

A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…To bridge this gap, this research embarks on developing a hybrid machine learning approach to identify credit card fraud cases based on both benchmark and real-world data. Standard base machine learning algorithms, which include a total of twelve individual methods as well as the AdaBoost and Bagging methods, are firstly used. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

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Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks by Adday, Ghaihab Hassan, Subramaniam, Shamala K., Zukarnain, Zuriati Ahmad, Samian, Normalia

“…The second stage will validate the voting process through a novel perspective based on the TMS. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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An improved multiple classifier combination scheme for pattern classification by Abdullah,

“…The most commonly used ensemble method is the random strategy while the majority voting technique is used as the combiner. …”
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Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

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Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

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A comparative study of the ensemble and base classifiers performance in Malay text categorization by Alshalabi, Hamood Ali, Sabrina Tiun, Nazlia Omar

“…This paper intends to compare the effectiveness of ensemble with that of base classifiers for Malay text classification. Two feature selection methods (the Gini Index (GI) and Chi-square) with the ensemble methods are applied to examine Malay text classification, with the intention to efficiently integrate base classifiers algorithms into a more accurate classification procedure. …”
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A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

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Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets by Abri K.Al., Sidhu M.S.

“…Despite these varying results, all methods had a consensus for just 44 outliers. Employing ensemble techniques, both averaging and voting methods identified 155 outliers, whereas the weighted method highlighted 151, with a consensus of 150 outliers across the board. …”