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2 2021

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Sequence-to-sequence deep neural network with spatio-spectro and temporal features for motor imagery classification

Rammy Sadaqat Ali, Abbas Waseem, Mahmood Syed Shahid, Riaz Haider, Rehman Haseeb Ur, Abideen Rao Zain Ul, Aqeel Muhammad, Zhang Wu

Biocybernetics and Biomedical Engineering

2021

Vol. 41, no. 1

97--110

Electroencephalography (EEG) is a method of the brain–computer interface (BCI) that measures brain activities. EEG is a method of (non-)invasive recording ofthe electrical activity ofthe brain. This can be used to build BCIs. From the last decade, EEG has grasped researchers' attention to distinguish human activities. However, temporal information has rarely been retained to incorporate temporal information for multi-class (more than two classes) motor imagery classification. This research proposes a long-short-term-memory-based deep learning model to learn the hidden sequential patterns. Two types of features are used to feed the proposed model, including Fourier Transform Energy Maps (FTEMs) and Common Spatial Patterns (CSPs) filters. Multiple experiments have been conducted on a publicly available dataset. Extraction of spatial and spectro-temporal features using CSP filters and FTEM allow the sequence-tosequence based proposed model to learn the hidden sequential features. The proposed method is trained, evaluated, and optimized for a publicly available benchmark data set and resulted in 0.81 mean kappa value. Obtained results depict the model robustness for the artifacts and suitable for real-life applications with comparable classification accuracy. The code and findings will be available at https://github.com/waseemabbaas/Motor-Imagery-Classification.git.

Evaluation of thermal performance factor for solar air heaters with artificially roughened channels

Siddique Waseem, Raheem Aneeq, Aqeel Muhammad, Qayyum Sualeh, Salamen Tareq, Waheed Khalid, Qureshi Kamran

Archive of Mechanical Engineering

2021

LXVIII, nr 2

195--225

Heat transfer augmentation has become the utmost industrial desire. Turbulence promoters seems to be a better option for better heat transfer but at the expense of enormous pressure drop. In the current study, experimental optimization of heat transfer and pressure drop in various configurations of ribbed and corrugated surfaces on the bottom wall of the Solar Air Heater channel, having aspect ratio of 26:5 was performed. The results were evaluated in terms of enhancement in heat transfer (Nu/Nu s), friction factor ratio (f/f s) and thermal performance factor ( η). Three different cases and nine configurations with a pitch to rib/corrugation height ratio of 4.0 were studied. Case A consists of a smooth, continuous square rib, inline and staggered broken ribs. Case B comprises 30°, 45°, 60° and 90° trapezoidal corrugated geometries while Case C is the comparison of smooth, wavy corrugated and the best configurations of cases A and B. The results show that rectangular duct with staggered broken ribs and trapezoidal corrugation at 45° are the best configurations for case A and B, respectively. The 45° corrugated configuration is the best one amongst all, with values of 1.53, 1.5 and 1.33% for Nu/Nu s, f/f s and η respectively.