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1
An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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Thesis -
2
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Thesis -
3
Text normalization algorithm for facebook chats in Hausa language
Published 2014“…It was found that our proposed algorithm was able to normalized Hausa NSWs with an accuracy of 100%. …”
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Proceeding Paper -
4
Towards the utilization of normalized LMS algorithm in adaptive filter
Published 2014“…In this paper, we focused on how the development of algorithms helped reduce the level of noise. This in turn led us to utilize the Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms in order to do so. …”
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Article -
5
Algorithm for calculation of cephalometric soft tissue facial traits
Published 2007“…Up to now Malaysia does not have any source for normal trait values of human face. This algorithm can be used to calculate facial traits for building a nationwide database that can be used to compare normal traits with abnormal ones and then plan the surgery procedures. …”
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Conference or Workshop Item -
6
JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation
Published 2008“…This novel algorithm applies coefficients scrambling using Combined-Reverse-and-Normal-Direction (CRND) scanning together with Distorted DC permutation (DDP). …”
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Thesis -
7
Time normalization of LPC feature using warping method
Published 2005“…Another task is to align the input frames (test set) to the reference template (training set) using DTW fixing frame (DTW-FF) algorithm. This proper time normalization is needed since NN is designed to compare data of the same length whilst same speech can varies in their length. …”
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Article -
8
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
Conference paper -
9
Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Thesis -
10
The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Monograph -
11
Scheduling tight deadlines for scientific workflows in the cloud
Published 2018“…The performance evaluation is done using two different performance metrics, success rate and normalized cost. …”
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Thesis -
12
Design and analysis of sequence generator module using eulerian path algorithm for DNA fragment assembly / Mustaqim Mohd Subri
Published 2013“…This project is to design and analysis the sequence generator module using Eulerian Path algorithm for DNA fragment assembly. …”
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Student Project -
13
Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…Before training, the dataset is normalized using the min-max normalization technique to reduce the influence of noise. …”
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Article -
14
Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach
Published 2017“…This study aimed to validate a panel of reference genes commonly used for normalization of canine OS gene expression data using the geNorm algorithm. qPCR analysis of nine canine reference genes was performed on 40 snap-frozen primary OS tumors and seven cell lines. …”
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Article -
15
Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural
Published 2006“…The neural network is trained using two types of learning algorithms, which is Levenberg-Marquardt and Back Propagation. …”
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Monograph -
16
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Monograph -
17
Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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Thesis -
18
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
19
DTWFF-pitch feature and faster neural network convergence for speech recognition
Published 2007“…Another task is to align the input frames (test set) to the reference template (training set) using DTW fixing frame (DTW-FF) algorithm. This is a time normalization process in which it is needed for data with unequal length. …”
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Article -
20
Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…Based on its simplicity, the K-means algorithm has been used in many fields. This paper proposes improved normalization and standardization techniques for higher purity in K-means clustering experimented with benchmark datasets from UCI machine learning repository and it was found that all the proposed techniques’ performance was much higher compared to the conventional K-means and the three classic transformations, and it is evidently shown by purity and Rand index accuracy results.…”
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