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Keyword: Principal Component AnalysisPrincipal Component Analysis Application on Flavonoids Characterization
Flavonoid is one of the bioactive compounds that are currently used in pharmaceutical and medicinal industries due to their health benefit. The focus of current research is mainly on the extraction and isolation of bioactive compounds; however non to date has explored on the identification of flavonoids classes under the Fourier Transform Infrared spectroscopy (FTIR).…
Read MoreAnalysis of Wireless Traffic Data through Machine Learning
The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data…
Read MoreEarly Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction
This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…
Read MoreDevelopment of an EEG Controlled Wheelchair Using Color Stimuli: A Machine Learning Based Approach
Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…
Read MoreEnterprise Resource Planning Readiness Assessment for Determining the Maturity Level of ERP Implementation in the Industry in Indonesia
The textile industry is one of the prioritized industries, because it contributes to the country’s foreign exchange, absorbs a large number of workers, and fulfills the need for national clothing. To increase work efficiency and productivity, the textile industry must use ERP. However, ERP implementation still has a relatively high failure rate. ERP readiness assessment…
Read MoreProjection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques
Advances in channel modeling allow wireless communication designers to accurately model and understand the channel’s phenomena within different propagation scenarios. A precise channel model results in the wireless system’s optimized performance while considering trade-offs due to the effects of the channel. The geometric-based stochastic channel model considers different interacting objects affecting the parameters using the…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreImproved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read MoreApplication of Fractal Algorithms to Identify Cardiovascular Diseases in ECG Signals
The aim of this article was the identification of cardiovascular diseases, after applying Katz and Higuchi fractal algorithms on 4 databases of ECG signals downloaded from the Physionet website: heart failure (HF), hypertension (H), ischemic heart disease (IHD) and normal sinus rhythm (NSR). For this purpose, initially the ECG signals passed through a filtering stage…
Read MoreDevelopment of Wavelet-Based Tools for Event Related Potentials’ N400 Detection: Application to Visual and Auditory Vowelling and Semantic Priming in Arabic Language
Neurological signals are generally very weak in amplitude and strongly noisy. As a result, one of the major challenges in neuroscience is to be able to eliminate noise and thus exploit the maximum amount of information contained in neurological signals (EEG…). In this paper, we aimed at studying the N400 wave of the Event-Related Potentials…
Read MoreDevelopment of Application Specific Electronic Nose for Monitoring the Atmospheric Hazards in Confined Space
The presence of atmospheric hazards in confined space can contribute towards atmospheric hazards accidents that threaten the worker safety and industry progress. To avoid this, the environment needs to be observed. The air sample can be monitored using the integration of electronic nose (e-nose) and mobile robot. Current technology to monitor the atmospheric hazards is…
Read MoreComputational Techniques to Recover Missing Gene Expression Data
Almost every cells in human’s body contain the same number of genes so what makes them different is which genes are expressed at any time. Measuring gene expression can be done by measuring the amount of mRNA molecules. However, it is a very expensive and time consuming task. Using computational methods can help biologists to…
Read MoreHuman Sit Down Position Detection Using Data Classification and Dimensionality Reduction
The analysis of human sit down position is a research area allows for preventing health physical problems in the back. Many works have proposed systems that detect the sitting position, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an…
Read MoreClassifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks
Breast cancer is one of the most common cancers among female diseases all over the world. Early diagnosis and treatment is particularly important in reducing the mortality rate. This research is focused on the prevention of breast cancer, therefore it is important to detect micro-calcifications (MCs) which are a sign of early stage breast cancer.…
Read MoreDeep venous thrombus characterization: ultrasonography, elastography and scattering operator
A thrombus or a blood clot is the result of blood coagulation which is a natural process to prevent bleeding. An inappropriate formation of a thrombus in a deep vein is known as Deep Venous Thrombosis (DVT). The main complication of a DVT is a Pulmonary Embolism (PE) which occurs when a thrombus breaks loose…
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