Some Coefficient Estimates for Polynomials on the Unit Interval

2000 Mathematics Subject Classification: 26C05, 26C10, 30A12, 30D15, 42A05, 42C05.In this paper we present some inequalities about the moduli of the coefficients of polynomials of the form f (x) : = еn = 0nan xn, where a0, ј, an О C. They can be seen as generalizations, refinements or analogues of the famous inequality of P. L. Chebyshev, according to which |an| Ј 2n-1 if | еn = 0n an xn | Ј 1 for -1 Ј x Ј 1

The Schwarz-Pick theorem and its applications

Various derivative estimates for functions of exponential type in a half-plane are proved in this paper. The reader will also find a related result about functions analytic in a quadrant. In addition, the paper contains a result about functions analytic in a strip. Our main tool in this study is the Schwarz-Pick theorem from the geometric theory of functions. We also use the Phragmen-Lindelof principle, which is of course standard in such situations

Classification of epilepsy using computational intelligence techniques

AbstractThis paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural network (ANN) and support vector machines (SVMs) combined with supervised learning algorithms, and k-means clustering (k-MC) combined with unsupervised techniques are employed to classify the three seizure phases. Different techniques to combine binary SVMs, namely One Vs One (OvO), One Vs All (OvA) and Binary Decision Tree (BDT), are employed for multiclass classification. Comparisons are performed with two traditional classification methods, namely, k-Nearest Neighbour (k-NN) and Naive Bayes classifier. It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise. Furthermore, SVM-based classifier with OvO provides the highest recognition accuracy, whereas ANN-based classifier overtakes by demonstrating maximum accuracy in the presence of noise

A prospective study of hearing impairment in school going children of Ghaziabad city attending a tertiary care hospital

Background:Overcrowding, poor hygiene, socio-economic status, climate, lack of resources to avail medical facilities, poor medical awareness have their bearing on the incidence of hearing loss. The family of each hearing-impaired child has its own cultural, social, educational, and financial background, and its own special needs. The aim of this study is to determine the percentage of hearing impaired school going children in Ghaziabad city.Methods:The material for the present study were a representative sample constituting 1000 school children selected from various localities of Ghaziabad city within age group of 6-12 years. The children belonged to all the strata of society and children from both sexes were evaluated for hearing loss and its underlying etiological factors. Children were subjected to detailed ENT examination in our OPD.  Results:In the present study sample the incidence of hearing loss is 9.3%. The maximum cases 60.22% belonged to the low socio-economic strata. A statistically significant difference of distribution by gender was noticed with a male preponderance (61.29%) as against 38.71% for females. The hearing loss in majority of cases was of a mild degree i.e., 26 to 45 dB (34.41%) of which majority of cases (87.10%) had conductive loss. Wax was the commonest cause of hearing loss (41.94%). CSOM was found in 21.50 % of all cases. Peak prevalence of hearing loss was found at 8 years of age, again declining after that from 20.43 % to 5.38 % by 12 years of age. Also it was observed that 59.14% children were living in crowded localities of city & 40.86% were living in non- crowded/open locality which is again statistically significant (P ≤0.05).Conclusion:The inferences drawn from the present study substantiates the view point of earlier workers that school screening is the most effective method of diagnosing deafness in school going children and should be extended to all schools in all the areas. Proper assessment and diagnosis of hearing loss in children at a very early age is important because an early diagnosis determines the efficacy of methods used for the correction of the hearing loss. Also early diagnosis of hearing impairment is a key to proper rehabilitation. The cases reporting to the hospital for treatment and rehabilitation can be regarded as the tip of the ice-berg and can have more management difficulties when compared to sub-clinical cases.

Heuristic-based programable controller for efficient energy management under renewable energy sources and energy storage system in smart grid

An operative and versatile household energy management system is proposed to develop and implement demand response (DR) projects. These are under the hybrid generation of the energy storage system (ESS), photovoltaic (PV), and electric vehicles (EVs) in the smart grid (SG). Existing household energy management systems cannot offer its users a choice to ensure user comfort (UC) and not provide a sustainable solution in terms of reduced carbon emission. To tackle these problems, this research work proposes a heuristic-based programmable energy management controller (HPEMC) to manage the energy consumption in residential buildings to minimize electricity bills, reduce carbon emissions, maximize UC and reduce the peak-to-average ratio (PAR). We used our proposed hybrid genetic particle swarm optimization (HGPO) algorithm and existing algorithms like a genetic algorithm (GA), binary particle swarm optimization algorithm (BPSO), ant colony optimization (ACO), wind-driven optimization algorithm (WDO), bacterial foraging algorithm (BFA) to schedule smart appliances optimally to attain our desired objectives. In the proposed model, consumers use solar panels to produce their energy from microgrids. We also perform MATLAB simulations to validate our proposed HGPO-HPEMC (HHPEMC), and results confirm the efficiency and productivity of our proposed HPEMC based strategy. The proposed algorithm reduced the electricity cost by 25.55%, PAR by 36.98%, and carbon emission by 24.02% as compared to the case of without scheduling

Mixotrophic cultivation of Scenedesmus dimorphus in sugarcane bagasse hydrolysate

Overuse of the fossil fuels to fulfill existing energy requirements has generated various environmental problems like global warming. Emergence of environmental issues due to burning of the fossil fuel resources has provoked researchers to explore alternative sources of fuel. In this scenario, microalgal biofuels could present a promising alternative fuel if produced cost-effectively without competing for freshwater resources and arable land. Aim of the present study was to grow microalgae by employing lignocellulosic waste for production of lipids. Scenedesmus dimorphus NT8c was chosen based on its ability to tolerate heat, rapid growth, and ease of harvesting by overnight settling. Biochemical composition and growth parameters of microalgae were analyzed when cultivated mixotrophically on sugarcane bagasse hydrolysate, a low-value agricultural by-product, that is, currently underutilized. Despite a slight increase in turbidity in the medium, S. dimorphus NT8c cultures raised mixotrophically in 5 g/L sugarcane bagasse hydrolysate displayed significantly higher growth rates compared to photoautotrophic cultivation with an overall biomass productivity of 119.5 mg L d, protein contents of 34.82% and fatty acid contents of 15.41%. Thus, microalgae cultivated mixotrophically are capable of photosynthesizing while metabolizing and assimilating organic carbon, significant increases of biomass and lipid productivity can be achieved. However, high supplementation with organic carbon can result in unfavorable levels of turbidity and bacterial growth, reducing microalgal biomass productivity

Bound, virtual and resonance SS-matrix poles from the Schr\"odinger equation

A general method, which we call the potential $S$-matrix pole method, is developed for obtaining the $S$-matrix pole parameters for bound, virtual and resonant states based on numerical solutions of the Schr\"odinger equation. This method is well-known for bound states. In this work we generalize it for resonant and virtual states, although the corresponding solutions increase exponentially when $r\to\infty$. Concrete calculations are performed for the $1^+$ ground and the $0^+$ first excited states of $^{14}\rm{N}$, the resonance $^{15}\rm{F}$ states ($1/2^+$, $5/2^+$), low-lying states of $^{11}\rm{Be}$ and $^{11}\rm{N}$, and the subthreshold resonances in the proton-proton system. We also demonstrate that in the case the broad resonances their energy and width can be found from the fitting of the experimental phase shifts using the analytical expression for the elastic scattering $S$-matrix. We compare the $S$-matrix pole and the $R$-matrix for broad $s_{1/2}$ resonance in ${}^{15}{\rm F}$Comment: 14 pages, 5 figures (figures 3 and 4 consist of two figures each) and 4 table

Sustainable manufacturing and parametric analysis of mild steel grade 60 by deploying CNC milling machine and Taguchi method

Design and manufacturing are the key steps in the sustainable manufacturing of any product to be produced. Within the perspective of injection molds production, increased competitiveness and repeated changes in the design require a complete optimized manufacturing process. Local and minor improvements in the milling process do not generally lead to an optimized manufacturing process. The goal of the new geometry and parametric analysis of the mould is to reduce the quality issues in mild steel grade 60. In this explicit research, the surface roughness (smoothness) of indigenously produced injection moulds in the local market in Pakistan is investigated. The CNC milling machine (five-axis) is used for the manufacturing of an injection mould, and the Taguchi method of the design of the experiment is applied for parameters optimization. Hence, the overall process is assisted in balancing the milling machine parameters to trim down the surface roughness issue in mild steel moulds and increase their sustainability. The spindle speed (rpm), the depth of cut (mm), and the feed rate (mm/rev) are considered as input variables for process optimization, and the experiments are performed on mild steel grade 60. It is deduced that the combination of a spindle speed of 800 rpm, feed rate of 10 mm/rev and depth of cut of 0.5 mm is the best case in case of minimum surface roughness, which leads to sustainable products. It is also deduced from ANOVA, that the spindle speed is a factor that affects the surface roughness of mild steel products, while the feed rate turns out to be insignificant

Copper Phthalocyanine Surface-type Photocapacitive Sensor

In this study the photocapacitive behavior of organic semiconductor, photosensitive material copper phthalocyanine (CuPc) were investigated. Thin film of the copper phthalocyanine was deposited by vacuum evaporation on glass substrate with silver surface-type electrodes and Ag/CuPc/Ag photo capacitive sensor was fabricated. It was shown that under filament lamp illumination up to 1000 lx the capacitance of the Ag/ CuPc/Ag photo capacitive sensor increased continuously up to 20% with respect of dark condition. It is assumed that photo capacitive response of the sensor is associated with polarization due to the transfer of photo-generated electrons and holes