Search Results - (( data extraction sensor algorithm ) OR ( data replication path algorithm ))

Abstract data extraction and reformation for IoT by Lim, Xin Hui

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A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

“…The system is then used in path prediction mode for reconstructing the missing parts of the trajectory when actual positioning data is unavailable. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

“…In this work, we focus our review on activity recognition implementation strategies by examining various sensors and sensing technologies used to collect useful data from IoT devices, reviewing preprocessing and feature extraction techniques, as well as classification algorithms used to recognize human activities in smart homes. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Re-engineering grid-based quorum replication into binary vote assignment on cloud: A scalable approach for strong consistency in cloud databases by Ainul Azila Che Fauzi, Ainul Azila, Noor Ashafiqa, Noor Ashafiqa, Asiah Mat, Asiah, Syerina Azlin Md Nasir, Syerina Azlin, A. Noraziah, Noraziah

“…Experimental results demonstrate that BVAC sustains fault tolerance, achieves cloud database replication efficiency, and sustains high data availability via multiple valid quorum paths. …”
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A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

“…Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. …”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”

Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring by Nordin N.D., Abdullah F., Zan M.S.D., Bakar A.A.A., Krivosheev A.I., Barkov F.L., Konstantinov Y.A.

“…Brillouin scattering; Concretes; Curve fitting; Data handling; Extraction; Fiber optic sensors; Fiber optics; Learning algorithms; Machine learning; Structural health monitoring; BOTDA; Brillouin frequency shift extraction; Brillouin frequency shifts; Brillouin gain spectrum; Correlation techniques; Distributed fiber-optic sensors; Frequency shift; Generalized linear model; Low signal-to-noise ratio; Prediction accuracy; Signal to noise ratio; algorithm; fiber optics; noise; signal noise ratio; Algorithms; Fiber Optic Technology; Noise; Signal-To-Noise Ratio…”

Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Proactive multi-copy routing protocol for urban vehicular ad hoc network by Hassan, Aslinda, Bahaman, Nazrulazhar

“…The paper emphases on replicating data packets and distribute them to different relays. …”
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Proactive multi-copy routing protocol for urban vehicular ad hoc network by Hassan, Aslinda, Bahaman, Nazrulazhar

“…The paper emphases on replicating data packets and distribute them to different relays. …”
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Design and development of prototype robot gripper for object weight measurement by Almassri, Ahmed M. M.

“…The proposed work also includes the development of new algorithm for data extraction and signal conditioning analysis that will be loaded into the microcontroller system. …”
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Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion by Ali, Mohammed A. H., Musa, Mailah, Jabbar, Waheb A., Moiduddin, Khaja, Ameen, Wadea, Alkhalefah, Hisham

“…A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…Specifically, this study focuses on investigating the optimal placement of smartphones to extract tri- axis accelerometer data from the inertial sensors during stair movement. …”
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Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

“…Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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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

“…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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