Search Results - (( java application sensor algorithm ) OR ( frequency classification _ algorithm ))

Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

“…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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A study of frequency radiation of human torso for gender classification by Siti Zura, A. Jalil, Mohd Nasir, Taib, Prof. Dr., Hasnain, Abdulllah@Idris, Megawati, Mohd Yunus

Subjects: “…Frequency…”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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An accurate infant cry classification system based on continuos hidden Markov model by Abdulaziz Y., Ahmad S.M.S.

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Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Rough set discretization: Equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Classification Analysis Of High Frequency Stress Wave For Autonomous Detection Of Defect In Steel Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yahya, Syed Yusaini

“…Interpretation of propagated high frequency stress wave signals in steel tubes is noteworthy for defect identification.This paper demonstrated a successful new approach for autonomous defect detection in steel tubes using classification analysis of high frequency stress waves.Classification analysis using Principal Component Analysis (PCA) algorithm involved feature extraction to reduce the dimensionality of the complex stress waves propagation path.Two defective tubes containing a slot defect of different orientation and a reference tube are inspected using Vibration Impact Acoustic Emission (VIAE) technique.The tubes are externally excited using impact hammer.The variation of stress wave transmission path are captured by high frequency Acoustic Emission sensor.The propagated stress waves in the steel tubes are classified using PCA algorithm.Classification results are graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of the stress wave signals.The inspection of steel tubes showed good recognition of defect in circumferential and longitudinal orientation.This approach successfully classified stress wave signals from VIAE testing and provide fast and accurate defect identification of defective steel tubes from non-defective tubes. …”
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Implementation of Frequency Drift for Identification of Solar Radio Burst Type II by Roslan, Umar, Nur Zulaikha, Mohd Afandi, Zamri, Zainal Abidin

“…The results of the frequency drift implementation in classification algorithm show that the algorithm developed gave almost similar determination as in manual detection. …”
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Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”

An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…First, features selection algorithms (genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS)) were used to select the most significant frequencies. …”
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An enhanced feature selection technique for classification of group based holy Quran verses by Abdullahi Oyekunle, Adeleke

“…The textual data (Quranic verses) were preprocessed using StringtoWordVector with weighted Term Frequency-Inverse Document Frequency (TF-IDF). Meanwhile, the classification phase has involved four algorithms: Naïve Bayes (NB), k-Nearest Neighbor (k-NN), Support Vector Machine (LibSVM), and Decision Trees (J48). …”
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Implementation of Frequency Drift for Identification of Solar Radio Burst Type II by Afandi, N.Z.M., Abidin, Z.Z., Umar, R., Sabri, N.H., Ibrahim, Z.A., Monstein, C.

“…The results of the frequency drift implementation in classification algorithm show that the algorithm developed gave almost similar determination as in manual detection. …”
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An enhanced feature selection technique for classification of group-based holy quran verses by Oyekunle, Adeleke Abdullahi

“…The textual data (Quranic verses) were preprocessed using StringtoWordVector with weighted Term Frequency-Inverse Document Frequency (IF-IDF). Meanwhile, the classification phase has involved four algorithms: Nai've Bayes (NB), k-Nearest Neighbor (k-NN), Support Vector Machine (LibSVM), and Decision Trees (148). …”
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Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

“…Based on the undertaken experiment the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm. Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study by Mujtaba, Ghulam, Shuib, Liyana, Raj, Ram Gopal, Rajandram, Retnagowri, Shaikh, Khairunisa

“…Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. …”
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Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

“…The classification is done based on features derived from the frequency and time domain processing using the Support Vector Machines (SVM) algorithm. …”
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Artificial intelligence for spectral classification to identify the basal stem rot disease in oil palm using dielectric spectroscopy measurements by Khaled, Alfadhl Yahya, Abd Aziz, Samsuzana, Bejo, Siti Khairunniza, Mat Nawi, Nazmi, Abu Seman, Idris

“…This study investigated the feasibility of applying genetic algorithm (GA) as a feature selection algorithm to select the most significant frequencies of dielectric spectral data for identifying BSR disease in oil palms. …”
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Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

“…The Goertzel's Algorithm is used to estimate the seven fundamental DTMF carrier frequencies. …”