Design and Development of Flexible PDMS Antenna for UWB-WBAN Applications

Wireless Personal Communications - This paper presents the design and development of a flexible Ultra Wide Band (UWB) antenna using polydimethylsiloxane as a substrate. Copper foil having a...     

Detection of Malicious Profiles and Protecting Users in Online Social Networks

Wireless Personal Communications - Everyone today actively uses online social networks to get in touch with their friends, for career opportunities, and business also. Some of the most popular...     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Fusion of ANNs as decoder of retinal spike trains for scene reconstruction

Applied Intelligence - The retina is one of the most developed sensing organs in the human body. However, the knowledge on the coding and decoding of the retinal neurons are still rather limited....     

Synthesis and characterisation of neem leaf extract, 2, 3‐dehydrosalanol and quercetin dihydrate mediated silver nano particles for therapeutic applications

The utility of green silver nanoparticles (AgNPs) in veterinary medicine is steadily increasing as they have many therapeutic applications against pathogens and arthropods of livestock. In this study, green AgNPs using neem (N‐AgNPs), 2,3‐dehydrosalanol (2,3‐DHS‐AgNPs) and quercetin dihydrate (QDH‐AgNPs) were synthesised and characterised. Synthesised compounds were characterised by UV‐Vis spectroscopy and the peak absorbance was recorded at 370 nm for neem extract. For N‐AgNPs, 2,3‐DHS‐AgNPs and QDH‐AgNPs, the maximum absorbance peaks were at 430, 230 and 220 nm, respectively. The FTIR analysis confirmed the synthesis of green AgNPs. The XRD pattern of N‐AgNPs showed the peaks corresponding to whole spectra of 2 θ values ranging from 10–80. The relatively higher intensity of (111, 222) planes in face centred cubic crystalline structure supports the formation of synthesised AgNPs. In DLS analysis, the hydrodynamic diameter of neem leaf extract was found to be 259.8 nm, followed by 5.3, 6.7 and 261.8 nm for 2,3‐DHS‐AgNPs, N‐AgNPs and QDH‐AgNPs, respectively. Based on the transmission electron microscopy and scanning electron microscopy image analyses, confirmed the formation of N‐AgNPs, 2,3‐DHS‐AgNPs and QDH‐AgNPs. These eco‐friendly phyto‐AgNPs may be of use as an effective alternative to chemical control methods against the arthropods of livestock.Inspec keywords: nanoparticles, silver, nanomedicine, biomedical materials, nanofabrication, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, X‐ray diffraction, light scattering, transmission electron microscopy, scanning electron microscopy, aggregation, veterinary medicineOther keywords: 2,3‐dehydrosalanol mediated silver nanoparticles, quercetin dihydrate mediated silver nanoparticles, therapeutic applications, green silver nanoparticles, veterinary medicine, Azadirachta indica, UV‐visible spectroscopy, Fourier transformed infrared analysis, X‐ray diffraction, (111) planes, (222) planes, face centred cubic crystalline structure, dynamic light scattering, hydrodynamic diameter, aqueous neem leaf extract, transmission electron microscopy, hexagonal shape, pencil head shape, cuboid shape, scanning electron microscopy, aggregation, arthropod infesting livestock, Ag, in‐vivo antiectoparasitic activity, in‐vitro antiectoparasitic activity     

Automated dynamic detection of busy–wait synchronizations

With the advent of multicores, multithreaded programming has acquired increased importance. In order to obtain good performance, the synchronization constructs in multithreaded programs need to be carefully implemented. These implementations can be broadly classified into two categories: busy–wait and schedule‐based. For shared memory architectures, busy–wait synchronizations are preferred over schedule‐based synchronizations because they can achieve lower wakeup latency, especially when the expected wait time is much shorter than the scheduling time. While busy–wait synchronizations can improve the performance of multithreaded programs running on multicore machines, they create a challenge in program debugging, especially in detecting and identifying the causes of data races. Although significant research has been done on data race detection, prior works rely on one important assumption—the debuggers are aware of all the synchronization operations performed during a program run. This assumption is a significant limitation as multithreaded programs, including the popular SPLASH‐2 benchmark have busy–wait synchronizations such as barriers and flag synchronizations implemented in the user code. We show that the lack of knowledge of these synchronization operations leads to unnecessary reporting of numerous races. To tackle this problem, we propose a dynamic technique for identifying user‐defined synchronizations that are performed during a program run. Both software and hardware implementations are presented. Furthermore, our technique can be easily exploited by a record/replay system to significantly speedup the replay. It can also be leveraged by a transactional memory system to effectively resolve a livelock situation. Our evaluation confirms that our synchronization detector is highly accurate with no false negatives and very few false positives. We further observe that the knowledge of synchronization operations results in 23% reduction in replay time. Finally, we show that using synchronization knowledge livelocks can be efficiently avoided during runtime monitoring of programs. Copyright © 2009 John Wiley & Sons, Ltd.     

A computational method of forecasting based on high-order fuzzy time series

This paper presents a computational method of forecasting based on high-order fuzzy time series. The developed computational method provides a better approach to overcome the drawback of existing high-order fuzzy time series models. Its simplicity lies with the use of differences in consecutive values of various orders as forecasting parameter and a w-step fuzzy predictor in place of complicated computations of fuzzy logical relations. The objective of the present study is to examine the suitability of various high-order fuzzy time series models in forecasting. The general suitability of the developed method has been tested by implementing it in the forecasting of student enrollments of the University of Alabama and in the forecasting of crop (Lahi) production, a case of high uncertainty in time series data. The results obtained have been compared in terms of average error of forecast to show superiority of the proposed model.     

A compact ACS-fed dual-band monopole antenna for LTE,WLAN/WiMAX and public safety applications

In this paper, a compact asymmetric coplanar strip (ACS)-fed printed monopole antenna for dual frequency operation is presented. The proposed antenna is composed of an ACS-fed monopole structure and two semi circle shaped radiating branches, which occupies a very small size of 13.4 × 22.7 mm² including the ground plane. By properly selecting the length and position of these branches, two desired operating bands can be achieved and tuned independently. The simulated and measured return loss results shows that the proposed antenna can be used for long term evolution 2500 (2500–2690 MHz), WLAN 5.2 GHz (5.15–5.35 GHz)/5.8 GHz (5.725–5.825 GHz), WiMAX 5.5 GHz (5.28–5.85 GHz) and 4.9 GHz (4.94–4.99 GHz) public safety applications. The omnidirectional and bidirectional radiation pattern characteristics in H-plane and E-plane of the proposed antenna along with acceptable peak gain make the best suitable candidate for the above intended applications.     

Top-down proteomic analysis by MALDI-TOF profiling: Concentration-independent biomarkers

Although numerous protein biomarkers have been correlated with advanced disease states, no new clinical assays have been developed. Goals often anticipate disease-specific protein changes that exceed values among healthy individuals, a property common to acute phase reactants. This review considers somewhat different approaches. It focuses on intact protein isoform ratios that present a biomarker without change in the total concentration of the protein. These will seldom be detected by peptide level analysis or by most antibody-based assays. For example, application of an inexpensive method to large sample groups resulted in observation of several polymorphisms, including the first structural polymorphism of apolipoprotein C1. Isoform distribution of this protein was altered and was eventually linked to increased obesity. Numerous other protein isoforms included C- and N-terminal proteolysis, changes of glycoisoform ratios and certain types of sulfhydryl oxidation. While many of these gave excellent statistical correlation with advanced disease, clinical utility was not apparent. More important may be that protein isoform ratios were very stable in each individual. Diagnosis by longitudinal analysis of the same individual might increase sensitivity of protein biomarkers by 20-fold or more. Protein changes that exceed the range of values found among healthy individuals may be uncommon.     

Modeling expert problem solving in a game of chance: a Yahtzee© case study

Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem-solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.