Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand

This article focuses on developing both statistical and machine learning approaches for forecasting hourly electricity demand in Ontario. The novelties of this study include (i) identifying essential factors that have a significant effect on electricity consumption, (ii) the execution of a Bayesian optimization algorithm (BOA) to optimize the model hyperparameters, (iii) hybridizing the BOA with the seasonal autoregressive integrated moving average with exogenous inputs (SARIMAX) and nonlinear autoregressive networks with exogenous input (NARX) for modeling separately short-term electricity demand for the first time, (iv) comparing the model’s performance using several performance indicators and computing efficiency, and (v) validation of the model performance using unseen data. Six features (viz., snow depth, cloud cover, precipitation, temperature, irradiance toa, and irradiance surface) were found to be significant. The Mean Absolute Percentage Error (MAPE) of five consecutive weekdays for all seasons in the hybrid BOA-NARX is obtained at about 3%, while a remarkable variation is observed in the hybrid BOA-SARIMAX. BOA-NARX provides an overall steady Relative Error (RE) in all seasons (1~6.56%), while BOA-SARIMAX provides unstable results (Fall: 0.73~2.98%; Summer: 8.41~14.44%). The coefficient of determination (R2) values for both models are >0.96. Overall results indicate that both models perform well; however, the hybrid BOA-NARX reveals a stable ability to handle the day-ahead electricity load forecasts

Mathematical modeling of temperature effect on algal growth for biodiesel application

Microalgae biomass is promising feedstock for the industrial production of biodiesel. Hence, research and development are required in various domains especially optimizations of growth conditions including temperature effect for mass scale operation (production of biomass, harvesting, extraction of lipid, etc). Since in middle east region, seasonal temperature variation and more rapid daily fluctuations are amenable to alter the growth kinetics of microalgae in outdoor culture and hence affect algae biomass production efficiency. Therefore, in this study, a mathematical model was developed to calculate how the algae sp. (Chlorella kessleri) will react at different temperatures. The model integrates Monod model and Arrhenius equation, and as such it describes the relationship of algal growth rate with culturing temperature and limiting nutrient concentration. The apparent activation energy and pre-exponential factors were calculated to be 2537 cal/mol and 0.0077 day−1, respectively. The developed models could be useful to anticipate the effective impacts of temperature on outdoor algae culture

A low-profile flexible planar monopole antenna for biomedical applications

This article proposes a low profile planar monopole antenna on flexible substrate. The antenna is designed with an elliptical slot inserted in a rectangular patch by utilizing the coplanar waveguide (CPW) feeding technique on a polyimide substrate. The proposed antenna operates within 7–14 GHz (S11 < − 10 dB) with a minimum return loss is observed as low as – 58 dB by simulation, whereas the entire X-band is covered by the – 20 dB bandwidth while maintaining an excellent VSWR of almost 1. Also, the antenna exhibits an average gain of 4 dBi while the average radiation efficiency is 92%. The maximum SAR of the proposed antenna for 1 g mass is below 1.0 W/Kg throughout the entire bandwidth. To observe flexibility, four different bending conditions of the antenna have been analyzed. For experimentation, the antenna has been realized as a prototype by using a low-cost fabrication process. The measurement reveals that the prototype has a −10 dB bandwidth of 5.4 GHz. During In-Vivo test, over the variation of 0 ∼ 3 mm distance between the antenna-prototype and the human chest/chicken breast tissue, the best performance is obtained at 3 mm in terms of the return loss. One of the significant features of the proposed design is its measured average and peak gain of 4.4 dBi and of 6.33 dBi respectively with a measured average efficiency of 65%. The proposed antenna has a compact size of 13 13 mm2 (), and its performance remains nominally constant even under different bending conditions which makes the antenna suitable for biomedical imaging applications. A new figure-of-merit has been introduced to evaluate the overall performance based on different antenna key parameters. The fabricated antenna would contribute to the future biomedical research by utilizing X-band frequencies

Enzyme-luminescence method: Tool for real-time monitoring of natural neurotoxins in vitro and l-glutamate release from primary cortical neurons

Novel enzyme-luminescence method is used for the rapid and sensitive in vitro detection of natural neurotoxins (e.g., shellfish and mushroom toxins) using model brain cells. Paralytic shellfish poisons gonyautoxins (e.g., GTX2,3 and GTX1,4) were detected at 1 nM level by their inhibition of glutamate release from C6 glioma cells upon drug stimulation (IC50: GTX2,3 = 30 nM and GTX1,4 = 8 nM). Activation of glutamate release from C6 cells by ibotenic acid (a mushroom toxin) was also evaluated (EC50 = 10 nM). The method was tested for real-time detection of glutamate release from primary rat cortical neurons. Dose-dependent effects of KCl (0–200 mM) and NMDA on glutamate release from primary cortical neurons were studied. The effects of different culture conditions on K+-depolarization-induced glutamate release were also investigated. The method may be applicable to screening of drugs and toxins, and finding glutamatergic neurons in brain slices without in situ staining

Mathematical modeling of temperature effect on algal growth for biodiesel application

Microalgae biomass is promising feedstock for the industrial production of biodiesel. Hence, research and development are required in various domains especially optimizations of growth conditions including temperature effect for mass scale operation (production of biomass, harvesting, extraction of lipid, etc). Since in middle east region, seasonal temperature variation and more rapid daily fluctuations are amenable to alter the growth kinetics of microalgae in outdoor culture and hence affect algae biomass production efficiency. Therefore, in this study, a mathematical model was developed to calculate how the algae sp. (Chlorella kessleri) will react at different temperatures. The model integrates Monod model and Arrhenius equation, and as such it describes the relationship of algal growth rate with culturing temperature and limiting nutrient concentration. The apparent activation energy and pre-exponential factors were calculated to be 2537 cal/mol and 0.0077 day−1, respectively. The developed models could be useful to anticipate the effective impacts of temperature on outdoor algae culture

Adjacent and diagonal coupling mechanism by even-branched resonator for adjustable radiometric filtering applications

Radio frequency-based measurement components utilize differently designed resonators to adjust various filtering characteristics. We introduce a unique coupling mechanism of a novel even-branched resonator that alone can adjust 6 radiometric filtering characteristics i.e., bandpass operation, harmonic suppression, quality-factor enhancement, switching ability, tunability, and digitized coupling. In our design, even-branched resonators have inter-resonator magnetic coupling while each end of their branch-lines has intra-resonator electrical coupling. Using the prominent magnetic coupling, adjacently coupled- and diagonally coupled- resonators are developed. A short-circuited stepped-impedance parallel technique is applied to achieve enhanced quality-factor and switchable/tunable bandpass filtering features. Characteristics of our radiometric resonator are determined by the odd/even dependency on its branch number. Our resonator couples with its another identical unit only when it has an even number of branches and is coupled by branch-lines that are also even-numbered. With novel digitized coupling characteristics, our resonator provides a 6-in-1 solution for intelligent radiometric systems

Plans For Planar: Phase-Noise Reduction Techniques In Voltage-Controlled Oscillators

To ensure spectral purity in modern RF signal sources, microwave oscillators and voltage-controlled oscillators (VCOs) must be designed to perform with low phase noise. Despite the growth of monolithic microwave integrated circuits (MMICs), microstrip planar technology is still used for developing low-phase-noise VCOs due to its design simplicity and low manufacturing cost. This article reviews the attributes of low-phase-noise VCOs and some recent techniques applied for phase-noise reduction in microstrip planar technology. The major challenge in designing VCOs in microstrip planar technology lies in improving the quality factor (Q) of resonators. Different methods to improve Q are presented here for techniques incorporated with microstrip lines and substrate integrated waveguides (SIWs). The tradeoff involved with the tuning range (TR) of VCOs is also emphasized to introduce the design selectivity for wideband applications