Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

“…This article represents the classification of Electromygraphy (EMG) signal for the detection of different predefined hand motions (left, right, up and down) using artificial neural network (ANN). The neural network is of backpropagation type, trained by Levenberg-Marquardt training algorithm. …”
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Neural network classifier for hand motion detection from EMG signal by Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…This paper represents the detection of different predefined hand motions (left, right, up and down) using artificial neural network (ANN). A backpropagation (BP) network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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A novel palmprint segmentation technique by Rotinwa-Akinbile, M. O., Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka

“…In this paper, the acquired image undergoes color space conversion and the output is filtered using coefficients obtained from the training of an artificial neural network (ANN) based model coefficient determination technique. …”
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Feature extraction of speech signal and heartbeat detection in angry emotion identification by Mohamed, Masnani, Lee, Chee Chuan, Ahmad, Ida Laila

“…Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. …”
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Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network by K. G., Tay, Muwafaq, Hassan, Ismail, Shuhaida, Ong, Pauline

“…Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but most of their data is multivariate data. …”
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Extraction and microencapsulation of polyphenol-rich antioxidant from Clinacanthus nutans for controlled release formulation by Abdul Karim, Norsuhada

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Signature recognition using artificial neural network by Abushariah, Ahmad A. M., Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil, Jalel

“…For our application, off-line approach will be utilized.Neural Networks (NN) also known as Artificial Neural Networks (ANN) belong to the artificial intelligence approaches, which attempt to mechanize the recognition procedure according to the way a person applies intelligence in visualizing and analyzing[2]. …”
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Multibiometric systems based verification technique by Anwar, Farhat, Rahman, Md. Arafatur, Azad, Md. Saiful

“…Artificial Neural Network (ANN) is applied for feature learning and verification process. …”
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A new method of vascular point detection using artificial neural network by Kaderi, Mohd Arifin, Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka

“…Performance analysis of the system shows that ANN based technique achieves 100% accuracy on simulated images and minimum of 92% accuracy on RFI obtained from DRIVE database.…”
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An evaluation on offline signature verification using artificial neural network approach by Khalifa, Othman Omran, Alam, Md. Khorshed, Hassan Abdalla Hashim, Aisha

“…It addresses the offline signature verification technique using Artificial Neural Network (ANN) approach. It also explains the fundamental characteristics of offline signature verification processes and highlights the comparison among various offline signature verification approaches and various signature recognition issues.…”
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Optimization of ANPR algorithm on android mobile phone by Mutholib, Abdul, Gunawan, Teddy Surya, Chebil, Jalel, Kartiwi, Mira

“…For comparison purpose, the template matching based OCR will be compared to Artificial Neural Network (ANN) based OCR. The optimization on ANPR was performed as currently there is no image processing tool available on the standard Android mobile phone. …”
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Load distribution for an intelligent air-cushion track vehicle based on optimal power consumption by Hossain, Altab, Rahman, Mohammed Ataur, Mohiuddin, A. K. M.

“…Third, an artificial neural network (ANN) model has been developed which has been trained to predict the total PC for IACTV and to provide illustration how FES might play an important role in the prediction of PC of the vehicle’s intelligent air-cushion system.…”
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Power forecasting from solar panels using artificial neural network in UTHM Parit Raja by Mohd Fahmi, Natasha Munirah, Zambri, Nor Aira, Salim, Norhafiz, Sim, Sy Yi

“…The collected data are used in developing Artificial Neural Network (ANN) model. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) are the techniques used to forecast the outputs of the PV. …”
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Towards realizing the Maqasid Al-Shariah: a critique of Islamic banking and finance practices by Nor Azmi, Hamzah Syahir, Kayadibi, Saim

“…The HSBC, University Bank in Ann Arbor and Devon Bank in Chicago offer Islamic banking products in the United States. …”
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Artificial neural network model for predicting wet scrubber performance by Danzomo, Bashir Ahmed, Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

“…The performance fitness of the neural network (MSE = 0.00000107 and R-value = 0.9979) describes the effectiveness of the ANN model in predicting the performance of the scrubber system and the model follows the pattern of the theoretical data describing the scrubber performance at a higher efficiency range.…”
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Face recognition from single sample per person by learning of generic discriminant vectors by Hafiz, Fadhlan, Shafie, Amir Akramin, Mohd Mustafah, Yasir

“…This paper proposes a development of face recognition based on a combination of traditional eigenface with artificial neural network (ANN), having the face recognition performance boosted by the classification of discriminant vectors learned from a set of generic samples. …”
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Self-organizing map approach for determining mobile user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Nuraini, Asma, Amin, Sulafa Mohd

“…SOM as an unsupervised learning techniques of Artificial Neural Network (ANN) capable for summarizing high-dimensional data which cause region of the network to respond similarly to certain input patterns by analyzing the signal strength or signal-to-noise (SNR) of the wireless access points (AP) that enable a wireless networked device to infer the location of wireless client. …”
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RE: Semi‑rigid ureteroscopy – Proximal versus distal ureteral stone by Kamarulzaman, Mohd Nazli

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Electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS) by K.G., Tay, Muwafaq, Hassan, W. K., Tiong, Y. Y., Choy

“…The univariate data was converted to multivariate and ANFIS was chosen as it carries both advantages of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS). ANFIS yields the MAPE between actual and predicted electricity consumption of 0.4002% which is relatively low if compared to previous works of UTHM electricity forecasting using time series model (11.14%), and first-order fuzzy time series (5.74%), and multiple linear regression (10.62%).…”
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Investigation into participation of annexins in the response of Arabidopsis thaliana roots to lead (Pb) exposure: Preliminary study by Phang, Ing Chia

“…Primers for annexin 1 (AnnAt1) have been obtained and testing for RT-PCR is now underway.…”
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