A practical Equivalent Electrical Circuit model for Proton Exchange Membrane Fuel Cell (PEMFC) systems

An alternative Equivalent Electrical Circuit for Proton Exchange Membrane Fuel Cells is modelled in this study. Both I–V characteristics and H₂ consumptions corresponding to generated power under load and no-load conditions are investigated. For this purpose, H₂ consumptions and I–V characteristics of three different sized PEMFCs are tested. There is a very good harmony between the model results and measured values (relative error %0.7, %6.4 and %2.5 for FC-A, FC-B and FC-C respectively). In the proposed model current passes only on parallel resistance and not on serial resistance at no-load condition. Thus, a FC with higher parallel resistance should be preferred. Another key output of this study is that based on the proposed model, performance comparison of FCs can be performed with the parameters defined in this work. Proposals made in this study can easily be used for performance analysis of FCs under for both steady state and transient analysis.     

Colour and COD removal from textile effluent by coagulation and advanced oxidation processes

The aim of this study was to compare the performance of coagulation, Fenton's oxidation (Fe²⁺/H₂O₂) and ozonation for the removal of chemical oxygen demand (COD) and colour from biologically pretreated textile wastewater. FeSO₄ and FeCl₃ were used as coagulants at varying doses and varying colour removal efficiency was measured. For the Fenton process, COD and colour removal efficiencies were found to be 78% and 95% for the Fenton process, and to be 64% and 71% for the Fenton-like process (Fe³⁺/H₂O₂), respectively. Ozonation experiments were conducted at different initial pH values and fixed ozone doses. Ozonation resulted in 43% COD and 97% colour removal whereas these rates increased to 54% and 99% when 5 mg/l hydrogen peroxide was added to the wastewater before ozonation at the same dose. The operating costs of all proposed treatment systems were also evaluated in this study.     

Fusion of smartphone sensor data for classification of daily user activities

Multimedia Tools and Applications - New mobile applications need to estimate user activities by using sensor data provided by smart wearable devices and deliver context-aware solutions to users...     

Production of NiO,NiO/Ag,NiO/Au,and NiO/Pt hollow spheres by using block copolymer stabilized microspheres as a template

Hollow spheres of nickel oxide (NiO) and silver, gold, and platinum nanoparticle loaded NiO composites were successfully produced by using polystyrene (PS) latexes as hard template. Due to the presence of tertiary amine based diblock copolymer stabilizer on the surface of PS, the tertiary amine functional groups provided homogene deposition of nickel hydroxide, and then the precursor NiO salt production on the surface of PS latexes with a controlled precipitation technique. Then, NiO and NiO/metal NP hollow spheres were produced by calcination at 600 °C. Thermogravimetric analysis indicated that the amounts of NiO and NiO-composite after calcination were in the range of 21.1–29.7 wt%. The diameters of metal oxide spheres were in the range of 2.0–2.7 μm and the shell thickness were in the range of 250–350 nm. These structures had very low densities due to their porous and hollow structures and had outer layers with highly rough surfaces due to formation of nanosheets, which may offer important advantages for catalysis studies.     

Dynamic stability of a shaft system connected through a Hooke's joint

Dynamic stability of the torsional vibrations of a shaft system consisting of two torsionally elastic shafts interconnected through a Hooke's joint is investigated by means of a two degree-of-freedom model. The linearized equations of motion are shown to consist of a set of Mathieu-Hill equations and stability of their solutions is analyzed by means of a monodromy matrix method. Results are presented in the form of stability charts constructed on various parameter planes visualizing the effect of various selected pairs of system parameters on the stability.     

Revealing determinants of two‐phase dynamics of P53 network under gamma irradiation based on a reduced 2D relaxation oscillator model

This study proposes a two‐dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two‐phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53‐regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations’ effects using the phase space approach.Inspec keywords: physiological models, cellular biophysics, cancer, difference equations, delays, enzymes, biochemistry, molecular biophysics, gamma‐rays, radiation therapyOther keywords: two‐phase dynamics model, P53 network, gamma irradiation, 2D relaxation oscillator model, ATM model, Wip1 variables, p53‐regulators, cell fate decision, excitable relaxation oscillator, Wip1 time delay, state‐dependent delay differential equation, cell cycle arrest, cell apoptosis, cancer therapies, Wip1 overexpression, Wip1 downregulation, ATM deficiency, Mdm2 overexpression, Mdm2 downregulation, mutation effects, phase space approach     

Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

Human Activity Recognition (HAR) is an active research area due to its applications in pervasive computing, human-computer interaction, artificial intelligence, health care, and social sciences. Moreover, dynamic environments and anthropometric differences between individuals make it harder to recognize actions. This study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world applications. It uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural network. Moreover, the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information. Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction. For temporal sequence, this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short Term Memory (BiLSTM) to capture long-term dependencies. Two state-of-the-art datasets, UCF101 and HMDB51, are used for evaluation purposes. In addition, seven state-of-the-art optimizers are used to fine-tune the proposed network parameters. Furthermore, this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network (CNN), where two streams use RGB data. In contrast, the other uses optical flow images. Finally, the proposed ensemble approach using max hard voting outperforms state-of-the-art methods with 96.30% and 90.07% accuracies on the UCF101 and HMDB51 datasets.     

Signal transformation and interpolation based on modified DCT synthesis

This paper proposes a novel signal transformation and interpolation approach based on the modification of DCT (Discrete Cosine Transform). The proposed algorithm can be applied to any periodic or quasi periodic waveform for time scale and/or pitch modification purposes in addition to signal reconstruction, compression, coding and packet lost concealment. The proposed algorithm has two advantages:

• (i) 

  Since DCT does not have the explicit phase information, one does not need the cubic spline interpolation of the phase component of the sinusoidal model.

• (ii) 

  The parameters to be interpolated can be reduced because of the energy packing efficiency of the DCT. This is particularly important if signal synthesis is carried out on a remote location from the transmitted parameters.

The results are presented on periodic waveforms and on speech signal in order to appreciate the fidelity of the proposed algorithm. In addition, the proposed method is compared with TD-PSOLA, sinusoidal model and phase vocoder algorithms. The results are presented in objective PESQ scores for time scale modification and output files are provided as supplementary material,¹ for subjective evaluation, for packet lost concealment. Results prove that the proposed modification of the DCT synthesis provides a favorable algorithm for specialists working in the signal processing area.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.