Recovery of business intelligence systems by Haraty, Ramzi A.

“…The efficiency of the data recovery algorithm is substantial for e-healthcare systems. …”
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Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …”
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HARDWARE DESIGN AND VLSI IMPLEMENTATION OF A BYTE-WISE CRC GENERATOR CHIP by Sait, Sadiq M.

“…These include areas such as error detection and correction in data comunication, signature analysis and mass storage devices for parallel information transfers.…”
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Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. …”
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Design and development of an embedded controller for roboticmanipulator by Bakhashwain, J.M.

“…MPA is capable of determining a simplified control law by selecting the most dominant terms from a library of nonlinear functions associated with the robot's equations of motion. …”
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CEAP by Abdel Wahab, Omar

“…We propose as well a propagation algorithm that disseminates only the final decisions (instead of the whole dataset) among clusters with the aim of reducing the overhead of either exchanging results between each set of vehicles or repeating the detection steps for the already detected malicious vehicles. …”
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Hardware design and VLSI implementation of a byte-wise CRCgenerator chip by Sait, Sadiq M.

“…These include areas such as error detection and correction in data communications, signature analysis, and mass storage devices for parallel information transfers…”
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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization by Majdi Mansouri (16869885)

“…The main idea behind the use of the PSO algorithm is to remove irrelevant features and extract only the most significant ones from raw data in order to improve the classification task using a neural networks classifier. …”

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)

“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”

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

“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”

Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Anonymizing multimedia documents by Haraty, Ramzi

“…We provide a sanitizing MD∗-algorithm to enforce de-linkability along with a utility function to evaluate the utility of multimedia documents that is preserved after the sanitizing process. …”
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Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

“…We propose the adoption of this publicly available large dataset, which is at least one order of magnitude larger than any other dataset, to systematically compare existing methods for the detection of sleep-wake stages, thus fostering the creation of new algorithms. …”

Downlink channel estimation for IMT-DS by Faisal, S.

“…The DL channel of an IMT-DS system consists of time-multiplexed pilot and data symbols to facilitate coherent detection. To obtain channel estimates during pilot symbols, we propose a chip level adaptive channel estimation which performs better than the conventional method. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation by Abdul Rahman, Sawsan

“…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …”
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications by Sharafeddine, Sanaa

“…Moreover, we derive an empirical energy model that analytically quantifies the energy consumed during data transmission as a function of the signal strength level and during data compression as a function of the data size. …”
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…The proposed work contains three significant phases: Preprocessing and Feature Selection, DNA Sequence Generation and Ransomware Detection. In the first phase, data preprocessing and feature selection technique is applied to the collected dataset. …”
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