Search Results - (( java implication based algorithm ) OR ( event extraction process algorithm ))

“Analysis of EEG Recordings During Grasp and Lift (GAL) Trials by Musa, Huwaida

“…There are two types of investigation which are classification with feature extraction and without feature extraction. Throughout this project, we managed to get the classification accuracy of 6 events for 26.6% and 58.5% while for 2 events of up to 67.4% and 96% using 6 channels for both algorithms respectively.…”
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Event Detection and Information Extraction Strategies from Text: A Preliminary Study Using GENIA Corpus by Abdullah, M.H.A., Aziz, N., Abdulkadir, S.J., Akhir, E.A.P., Talpur, N.

“…However, data that are present in an unstructured form such as text documents are difficult to be processed by conventional machine learning algorithms. …”
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Event Detection and Information Extraction Strategies from Text: A Preliminary Study Using GENIA Corpus by Abdullah, M.H.A., Aziz, N., Abdulkadir, S.J., Akhir, E.A.P., Talpur, N.

“…However, data that are present in an unstructured form such as text documents are difficult to be processed by conventional machine learning algorithms. …”
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Leveraging Web Scraping in Predictive Modelling of Supply Risk Detection by Ng, Shi Ya

“…The significance of the extracted output is evaluated with the topic modelling algorithm (LDA model algorithm) for the purpose of predictive supply risk. …”
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Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model by Afsoon Badiei, Saeed Meshgini, Ali Farzamnia

“…A subset of the features is then applied into the probabilistic neural network optimized by Gases Brownian Motion Optimization (GBMO) algorithm. The set of EEG and ECG signals are samples of the SHHS sleep database that have been incorporated into the learning model with some pre-processing. …”
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Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

“…For extracting moments, a mathematical model of block processing that requires low computational cost is proposed. …”
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3D human heart modeling (self-organizing Map Neural Network) / Mohd. Tharmezy Md. Tajuddin by Mohd. Tharmez, Md. Tajuddin

“…Heart images from the source can be processed t become the signal for the Self-Organizing Maps (SOM) network and the output neuron that have adapted to the images, present interesting features such as contour-extractions and edge detections. …”
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Trace analyzer for NS-2 by Salleh A.U., Ishak Z., Din N.Md., Jamaludin M.Z.

“…However, the trace file is just a block of ASCII data in a file and quite cumbersome to access using some form of post processing technique. In order to ease the process of extracting data for performance study, the NS-2 Trace Analyzer is proposed. …”

Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Walking gait event detection based on electromyography signals using artificial neural network by Nazmi, Nurhazimah, Abdul Rahman, Mohd Azizi, Yamamoto, Shin Ichiroh, Ahmad, Siti Anom

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Framework for mining XML format business process log data by Ang, Jin Sheng

“…However, many existing FSM algorithms and methods often neglect or fail to preserve structural information, which hinders extracting meaningful insights from such data. …”
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Video image processing for traffic analysis by Che Puan, Othman

“…This tape is typical of tapes from which data have been extracted manually using event recorders. Although the performance of the implementation algorithms needs to be further assesed, the preliminary results have demonstrated the success of collecting data for vehicle counts, speeds and headways with reasonable accuracy.…”
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REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT by MOHAMED AMIN, SITI NUR AZIMAH

“…There are various algorithms available to identify and classify the abnormal event sound. …”
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Development of a wearable human fall detection system by Chua, Kean Hong, Sai, Siong Jun, Chan, Chi Yen, Kamsani, Noor Ain, Che Soh, Azura, Raja Ahmad, Raja Mohd Kamil

“…In this study, an accelerometer and gyroscope sensors were installed in a wearable fall detector. A fall detection algorithm was developed using MATLAB. This algorithm will extract features from the signal sent by the sensors and conduct a series of decision-making and classification process to determine whether a fall has actually occurred. …”
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Comparative analysis of spatio/spectro-temporal data modelling techniques by Abdullah, Mohd Hafizul Afifi, Othman, Muhaini, Kasim, Shahreen

“…Despite the difficulties to process information from SSTD, several works on predictive modelling have been published, including applications on brain data processing [3], stroke data [4-5], forecasting of weather-driven damage in electrical distribution system [6], and ecological or environmental event prediction [7]. …”
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Forward scattering radar for real-time detection of human activities and fall classification by Abdulhameed, Ali Ahmed

“…Support Vector Machine (SVM) algorithm modified by kernel linear function was used for classifying the fall event from the other activities. …”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…By reduction of recording EEG channels in the single trial based algorithms, the processing time of P300 detection decrease dramatically. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Islanding detection method using ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud, Hizam, Hashim, Othman, Mohammad Lutfi, Mohd Radzi, Mohd Amran

“…A modified differential evolution (MDF) algorithm with a new mutation phase, crossover process, and selection mechanism is proposed to train the RPNN. …”
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