Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

Get full text

An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM by Al-Naffouri, T.Y.

Get full text
Get full text

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. …”
Get full text
Get full text
Get full text
Get full text

A forward-backward Kalman for the estimation of time-variant channels in OFDM by Al-Naffouri, T.Y.

Get full text
Get full text

An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
Get full text

Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
Get full text
Get full text

Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

“…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …”
Get full text

Bridge Structural Health Monitoring Using Mobile Sensor Networks by Amin, Fouad

Get full text

DNA Base-Calling Techniques by Odeh, Fadi

Get full text

PERF solutions for distributed query optimization. (c1999) by Fany, Roula

Get full text
Get full text

Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

Get full text
Get full text

A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”

Vehicular-OBUs-As-On-Demand-Fogs by Sami, Hani

“…For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. …”
Get full text
Get full text
Get full text
Get full text

Digital Image Watermarking Using Balanced Multiwavelets by Ghouti, L.

Get full text

Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
Get full text
Get full text
Get full text

Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…However, the improved performance is achieved at the expense of higher computational complexity and data requirements.…”
Get full text

Indoor Localization Schemes for Mobile Robots by Al-Jarrah, Islam Mohammad-Amin

Get full text

A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Here, the Quantized Identical Data Imputation (QIDI) mechanism is implemented at first for data preprocessing and normalization. …”

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.…”