Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting

Despite the advancement within the last decades in the field of smart grids, energy consumption forecasting utilizing the metrological features is still challenging. This paper proposes a genetic algorithm-based adaptive error curve learning ensemble (GA-ECLE) model. The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach. A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy. This approach combines three models, namely CatBoost (CB), Gradient Boost (GB), and Multilayer Perceptron (MLP). The ensembled CB-GB-MLP model’s inner mechanism consists of generating a meta-data from Gradient Boosting and CatBoost models to compute the final predictions using the Multilayer Perceptron network. A genetic algorithm is used to obtain the optimal features to be used for the model. To prove the proposed model’s effectiveness, we have used a four-phase technique using Jeju island’s real energy consumption data. In the first phase, we have obtained the results by applying the CB-GB-MLP model. In the second phase, we have utilized a GA-ensembled model with optimal features. The third phase is for the comparison of the energy forecasting result with the proposed ECL-based model. The fourth stage is the final stage, where we have applied the GA-ECLE model. We obtained a mean absolute error of 3.05, and a root mean square error of 5.05. Extensive experimental results are provided, demonstrating the superiority of the proposed GA-ECLE model over traditional ensemble models.     

High‐melt‐elasticity poly(ethylene terephthalate) produced by reactive extrusion with a multi‐functional epoxide for foaming

A multi‐functional epoxide oligomer, Joncryl ADR‐4368 (ADR), is used as a modifier to prepare foamable poly(ethylene terephthalate) (PET) by reactive extrusion and compared with common tetra‐functional modifier pyromellitic anhydride (PMDA) as a reference. Torque evolution reveals that ADR has a faster reaction with PET than PMDA. The reactions generate long‐chain branches and gel structures, which are confirmed by rheological methods. Shear rheological studies show that PET modified with both ADR and PMDA display higher complex viscosity and lower loss tangent than unmodified sample. In particular, at a given viscosity level, ADR leads to a lower loss tangent than PMDA. Moreover, compared to PMDA, the addition of ADR results in a higher die pressure during extrusion and a more pronounced strain hardening during uniaxial elongation. These results indicate that ADR‐modified PET is less viscous but more elastic than PMDA‐modified PET. Owing to the higher elastic properties, ADR‐modified PET presents better foaming performance in batch foaming process with CO₂ as a blowing agent. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45805.     

Automatic brain tumor segmentation from magnetic resonance images using superpixel-based approach

Multimedia Tools and Applications - Cancer is the second leading cause of deaths worldwide, reported by World Health Organization (WHO). The abnormal growth of cells, which should die at the time...     

Simultaneous Use of Runs Rules and Auxiliary Information With Exponentially Weighted Moving Average Control Charts

Quality has become a key determinant of success in all aspects of industry. Exponentially weighted moving average control chart is an important tool of statistical process control used to monitor and improve quality of industrial processes. To enhance the performance of control charts, there are many strategies including the choice of an efficient plotting statistic, the choice of an efficient sampling design, the application of runs rules, and the use auxiliary information among many others. In this study, we propose nine different signaling schemes to enhance the performance of an exponentially weighted moving average control chart for location parameter, which is based on the exploitation of auxiliary information. Performance evaluation of the proposed schemes is carried out in terms of average run length. Comparisons of proposals are made with the classical as well as the auxiliary based exponentially weighted moving average and cumulative sum charts, which indicate that the proposed schemes perform better than the comparative counterparts under discussion. Copyright © 2016 John Wiley & Sons, Ltd.     

Diffusion of chemically reactive species in third grade fluid flow over an exponentially stretching sheet considering magnetic field effects

This article addresses the magnetohydrodynamics (MHD) flow of a third grade fluid over an exponentially stretching sheet.Analysis is carried out in the presence of first order chemical reaction.Both cases of constructive and destructive chemical reactions are reported.Convergent solutions of the resulting differential systems are presented in series forms.Characteristics of various sundry parameters on the velocity,concentration,skin friction and local Sherwood number are analyzed and discussed.     

Desulfurization of Model Oil through Adsorption over Activated Charcoal and Bentonite Clay Composites

Adsorption of dibenzothiophene (DBT) from model oil was investigated using composites of pure activated charcoal and pure bentonite clay. DBT adsorption was carried out in batch mode experiments at laboratory scale, where the developed composite materials showed a synergistic effect in removal of DBT from the model oil in terms of improved surface acidity of the pure activated charcoal and mesoporous structure of the pure bentonite clay. Thermodynamics, kinetics, and optimization of various adsorption parameters were investigated. Kinetic analyses proved that DBT adsorption followed pseudo-second-order kinetics. To study the thermodynamics of the adsorption, different isotherm adsorption models were applied. The Langmuir isotherm best fitted to the adsorption data. Various thermodynamic parameters were evaluated, including Gibbs free energy, entropy, and enthalpy.     

Modeling the effect of weave structure and fabric thread density on the barrier effectiveness of woven surgical gowns

Surgical gowns are the shielding cloths worn by the surgical team throughout a surgery to save them from blood pathogens of the patient being operated, and to avoid bacterial infections. Barrier effectiveness of a fabric depends upon the liquid penetration resistance and pathogen resistance of the fabric. The objective of this study was to analyze the effect of different weave structures and fabric thread densities on the barrier effectiveness of the woven surgical gowns. Twelve fabric samples were produced using three different weave structures, i.e. 1/1 plain, 2/2 z-twill, and 3/3 z-twill, and four different fabric constructions and then completed with a water repellent finish. Water repellency spray test and air permeability test were conducted on each of the 12 woven samples. The results of fabric samples were analyzed in Minitab statistical software. The coefficients of determinations (R² values) of the regression equations show good prediction ability of the developed statistical models. The findings of the study may be helpful in deciding appropriate manufacturing specifications of surgical gowns to attain maximum barrier effectiveness.     

Micronutrient Food Supplements in Patients with Gastro-Intestinal and Hepatic Cancers

Colorectal carcinogenesis is the second most common cause of mortality across all types of malignancies, followed by hepatic and stomach cancers. Chemotherapy and radiotherapy are key approaches to treating cancer patients, but these carry major concerns, such as a high risk of side effects, poor accessibility, and the non-selective nature of chemotherapeutics. A number of natural products have been identified as countering various forms of cancer with fewer side effects. The potential impact of vitamins and minerals on long-term health, cognition, healthy development, bone formation, and aging has been supported by experimental and epidemiological studies. Successful treatment may thus be highly influenced by the nutritional status of patients. An insufficient diet could lead to detrimental effects on immune status and tolerance to treatment, affecting the ability of chemotherapy to destroy cancerous cells. In recent decades, most cancer patients have been taking vitamins and minerals to improve standard therapy and/or to decrease the undesirable side effects of the treatment together with the underlying disease. On the other hand, taking dietary supplements during cancer therapy may affect the effectiveness of chemotherapy. Thus, micronutrients in complementary oncology must be selected appropriately and should be taken at the right time. Here, the potential impact of micronutrients on gastro-intestinal and hepatic cancers is explored and their molecular targets are laid down.     

Tunable Mismatch Shaping for Quadrature Bandpass Delta-Sigma Data Converters

This paper presents an architecture for quadrature bandpass mismatch shaping that allows the center frequency of the mismatch suppression band to be tunable over the entire Nyquist range. The approach is based on the previously reported complex-valued tree-based mismatch shaper, and extends this to allow tunable operation. The proposed design has been implemented using VHDL and synthesized to logic gates. The hardware complexity and mismatch shaping performance of the proposed architecture are compared to that of a reference architecture, which uses separate tunable mismatch shapers for each complex component path. Simulation results show consistent mismatch shaping performance across the entire tuning range.