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Enhancement in Isolation among Collinearly Placed Microstrip Patch Antenna Arrays
Irfan Ali, Tunio,Hernan, Dellamaggiora,Umair, Saeed,Ayaz Ahmed, Hoshu,Ghulam, Hussain International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.1
Strong surface waves among collinearly arranged patch antenna arrays pose unwanted inter element coupling particularly when high permittivity dielectric materials are used. In order to avert those waves, a novel Defected Ground Structure (DGS) is carved out systematically between two E-plane patch antenna elements. The introduced low profile μ shaped structure consequently improves impedance bandwidth and reflection coefficient by suppressing surface waves considerably. Parametric simulation results are analyzed and discussed.
Irfan, Muhammad,Kwon, Tae-Hyung,Yun, Bong-Sik,Park, Nyun-Ho,Rhee, Man Hee Elsevier 2018 Phytomedicine Vol.40 No.-
<P>Conclusion: E. bicyclis inhibits agonist-induced platelet activation and thrombus formation through modulation of the P2Y12 receptor downstream signaling pathway, suggesting its therapeutic potential in ethnomedicinal applications as an anti-platelet and anti-thrombotic compound to prevent cardiovascular diseases.</P>
AutoFe-Sel: A Meta-learning based methodology for Recommending Feature Subset Selection Algorithms
Irfan Khan,Xianchao Zhang,Ramesh Kumar Ayyasamy,Rahman Ali 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.7
Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the meta-modeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.
LP−TYPE INEQUALITIES FOR DERIVATIVE OF A POLYNOMIAL
Irfan Ahmad Wani,Mohammad Ibrahim Mir,Ishfaq Nazir 강원경기수학회 2021 한국수학논문집 Vol.29 No.4
For the polynomial $P(z)$ of degree $n$ and having all its zeros in $|z| \leq k$, $k \geq 1$, Jain \cite{j} proved that \begin{align*} \max_{|z|=1} |P^{\prime}(z)|\geq n \frac{|c_0| + |c_n|k^{n+1}}{|c_0|(1+k^{n+1}) + |c_n| ( k^{n+1} + k^{2n})} \max_{|z|=1}|P(z)| . \end{align*} In this paper, we extend above inequality to its integral analogous and there by obtain more results which extended the already proved results to integral analogous.
GENERALIZATION OF SOME INEQUALITIES TO THE CLASS OF GENERALIZED DERIVATIVE
( Irfan Ahmad Wani ),( Mohammad Ibrahim Mir ),( Ishfaq Nazir ) 한국수학교육학회 2021 純粹 및 應用數學 Vol.28 No.4
In this paper, we obtain some inequalities concerning the class of generalized derivative and generalized polar derivative which are analogous respectively to the ordinary derivative and polar derivative of polynomials.
Irfan, M.,Pham, X. H.,Han, K. N.,Li, C. A.,Hong, M. H.,Seong, G. H. Korean BioChip Society 2014 BioChip Journal Vol.8 No.2
We report the development of a novel nonenzymatic glucose sensor based on single-walled carbon nanotube film electrodes coated with iridium nano-particles (IrNPs-SWCNT). The SWCNT film electrode was first loaded with iridium nanoparticles (IrNPs) by an easily controllable chronocoulometry technique. The SWCNT film electrode coated with IrNPs was characterized by field emission scanning electron microscopy and electrochemical techniques like cyclic voltammetry (CV) and amperometry. There was no current response for glucose oxidation in neutral and acidic media, but a couple of oxidative and reductive peaks were observed when the IrNPs-SWCNT electrode was scanned in alkaline media, showing the strong electrocatalytic activity toward glucose oxidation. Amperometric measurements showed a high sensitivity of 63 mu Acm(-2) mM(-1) and a detection limit of 17 mu M; further, the measurements showed a linear range of 0.59-14 mM. To improve the selectivity of the electrode, the prepared IrNPs-SWCNT film electrode was coated using a 1.0% Nafion aqueous solution. When the electrodes were exposed to interfering substances such as uric acid and ascorbic acid, there were no significant signals observed from these substances, indicating that Nafion is an effective permselective polymer barrier. The sensitivity of the Nafion-coated electrode was 23 mu Acm(-2) mM(-1) and the detection limit was 47 mu M. In addition, the electro-catalytic activity of the Nafion-coated electrode was still stable after 50 cycles in the presence of a 3.0 mM glucose solution. as measured by CV.