nils-herrmann/clean_scirepeval huggingface dataset:
Wide band dual circularly polarized aperture coupled microstrip patch antenna with bow tie shaped apertures

A wide band aperture coupled microstrip antenna with dual circular polarization operation is proposed. The antenna is designed and simulated to enable the transmission and reception of different circularly polarized wide band signals simultaneously with a single antenna. Instead of conventional rectangular apertures, two orthogonally placed bow-tie shaped apertures fed by a 3 dB branch line coupler are used to obtain wide band performance at S-band using a square radiating patch. A thick, low cost dielectric foam yields further improvement in bandwidth. In simulation, an impedance bandwidth of 28% and axial ratio bandwidth of 15% has been achieved with this geometry. An improvement of 5% in impedance bandwidth and 5.4% in ellipticity bandwidth is obtained over a conventional rectangular aperture. The use of dielectric foam makes the antenna lightweight and low cost. These features make it an ideal element for wide band application as required for personal, mobile satellite and wireless communication systems.
Dependence of CUTOFF values on pitch angle of circular helically cladded optical waveguide at its core cladding interface

This article includes dispersion characteristics of optical waveguide with helical windings, and compression of dispersion characteristics of optical waveguide with helical winding at core-cladding interface for five different pitch angles. In this article dispersion characteristic of conventional optical waveguide with helical winding at core - cladding interface has been obtained. The model dispersion characteristics of optical waveguide with helical winding at core-cladding interface have been obtained for five different pitch angles. Boundary conditions have been used to obtain the dispersion characteristics and these conditions have been utilized to get the model Eigen values equation. From these Eigen value equations dispersion curve are obtained and plotted for modified optical waveguide for particular values of the pitch angle of the winding and the effect of this winding has been discussed. The article also shows the effect in the Dispersion Curve with changing the Pitch Angle.
A Unified Scalable Quasi-Ballistic Transport Model of GFET for Circuit Simulations

A unified quasi-ballistic transport model is developed for single- and double-gate graphene field-effect transistors (GFETs) using the McKelvey flux theory approach. The proposed model is compact, scalable, and compatible for the simulation of <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula> characteristics of GFET for all regions of device operation. The drain current equation (<inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula>) incorporates the formulation of quasi-thermal velocity, quasi-ballistic mobility of charge carrier (describe the carrier transport of 2-D material like graphene), and source/drain backscattering coefficient. This model is also capable to describe the mobility of graphene material in degenerate and nondegenerate states. The GFET with different channel lengths, widths, and oxide thicknesses is simulated using this model for single- and double-gate devices. The proposed model synchronized with experimental results and explains the peculiar transport characteristics of GFET with normalized root-mean-square error less than 9%.
Improving Biometric Authentication Performance From the User Quality

The effectiveness of a biometric measurement and sensing system is directly related to the performance generated from sensed data. This paper investigates a new approach to quantify the quality of sensed data from the user templates. The objective is to incorporate the quality of sensed data to generate a reliable estimate on the matching scores. The proposed method of extracting user quality is based on the confidence of generating reliable matching scores from the user templates. We simultaneously extract the palmprint and hand-shape images from the single hand image and ascertain the performance improvement for the individual trait. The experimental results from the proposed approach are also presented when the biometric measurements from the finger knuckles are employed. The experimental results presented in this paper show significant improvement in performance while incorporating the proposed method of user quality in the matching stages. The proposed user-quality-based fusion of the two biometric modalities also achieves promising improvement in performance.
Designing and implementaion of smart LPG trolley with home safety

LPG cylinders have become an integral part of every home. Our kitchens are occupied with LPG cylinders which help us make delicious food. But it can be dangerous and life threatening. Therefore, it requires constant vigilance to reduce the danger. The aim of this paper is to design a safety oriented system which will alert the user about any threat in the kitchen through mobile and also capable of performing required action immediately. This system will detect leakage of LPG and send an alert message to the user, at the same time it will switch off the mains power supply and a mechanical design attached with it, can switch off regulator too. It ensures safety from any gas leakage accident like suffocation and explosion. As an additional advantage, this system has a weighing sensor which can measure the weight of the cylinder and regularly update user about gas left in the cylinder. This system will also help customers to know whether they are being cheated by gas agency by providing less amount of LPG. In the present time, everyone is busy in their daily life and it is difficult to know the status of the gas cylinder. Further, it will register your booking through GSM technology by sending SMS to the distributor company and also send an alert to user at the same time. It will be helpful for those aged people who live alone and are dependent on others, by making them independent and secure them from any kitchen hazardous.
Reliability Issues of In2O5Sn Gate Electrode Recessed Channel MOSFET: Impact of Interface Trap Charges and Temperature

In this paper, reliability issues of In2O5Sn (indium–tin oxide: a transparent material) transparent gate recessed channel (TGRC)-MOSFET has been analyzed by considering the effect of interface trap charges (both positive and negative) present at the Si/SiO2 interface. Following device, characteristics are studied in terms of static, linearity, and intermodulation figure of merits. It is found that with the amalgamation of the transparent gate indium tin oxide on conventional recesses channel (CRC) MOSFET, it exhibits improved immunity against interface trap charges in comparison to CRC-MOSFET. In addition, the influence of ambient temperature (150–300 K) along with trap charges on TGRC-MOSFET has also been explored with an aim to analyze at which temperature of the device is more stable in the presence of interface defects (trap charges). Results obtained reveal that TGRC shows improved device performance at low temperature with trap charges being less influenced. Thus, this paper demonstrates that TGRC MOSFET can act as a promising candidate for low-power linear analog applications, where low temperature is required.
Impact of Wavelet Transform and Median Filtering on removal of Salt and Pepper Noise in Digital Images

Image acquisition is a common task in every image processing operation. Noise is entered (luring image acquisition from its source and once entered it degrades the image and is difficult to remove. In order to achieve the noise cancellation in an image, non-linear filter works better than linear. This paper presents the joint scheme of Wavelet Transform using iterative noise density and Median Filtering to remove Salt and Pepper Noise in Digital Images. The first part of the paper derives the wavelet coefficients with slight increase in noise density and in second part these coefficients are further modified by median filter. The algorithm shows the remarkable improvement over Gaussian noise model and removes most of the noisy part from the image and maintains the visual quality. The level of wavelet decomposition is restricted to three. The renowned indexes Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) demonstrate marked improvement of image denoising over Gaussian method.
A novel dual frequency wideband antenna for mobile communications

A double notch microstrip patch antenna for dual frequency, wideband operation is presented. Direct microstrip coupling with a proper matching transformer is used. The design is based on the optimum position of the feed location and notch dimensions for the two resonant frequencies. The impedance bandwidth, the VSWR measured on a network analyser confirm the theoretically predicted values. The radiation patterns in the E/H planes show the applicability of such type of antennas for mobile communications. There is an improvement in the impedance bandwidth compared to the rectangular patch antenna bandwidth. Also the beamwidth is very high.
Cloud computing - An emerging trend in information technology

The concept of cloud computing is based on the time-sharing of costly resources and advantages of the economies of scale. Cloud computing applies conventional supercomputing, or high-performance computing power, to perform computations in consumer-oriented applications. It is a result of exploring ways and means to ensure availability of computing power to users through sharing of resources and algorithms to optimize the usage of infrastructure, platform and applications. A large number of these cloud clients employ centralized servers for most of their applications. These applications do not require any specific applications on the client, but the clients interface with the cloud application merely through a web browser. IT departments spend a considerable amount of time on implementation, maintenance, and upgrade of their applications. CIOs are favoring cloud-computing technology to minimize the time spent on application support and focus on core activities of the business. Usage of Cloud computing enables the IT function to minimize the costs and issues associated with servers, network, applications, upgrades and maintenance.
Human identification from at-a-distance face images using sparse representation of local iris features

Automated human identification at-a-distance, using completely automated iris segmentation, is highly challenging and has wide range of civilian and forensics applications. Iris images acquired at-a-distance using visible and infrared imaging are often noisy and suffer from divergent spectral changes largely resulting from scattering, albedo and spectral absorbance selectivity. Therefore further research efforts are required to develop feature extraction techniques which are more tolerant to illumination changes and noise. This paper develops a new approach for the automated recognition from such distantly acquired iris images using sparse representation of local Radon transform (LRT) based orientation features. We model the iris representation problem as sparse coding solution based on computationally efficient LRT dictionary which is solved by widely studied convex optimization approach/strategy. The iris recognition and verification performance for the distantly acquired iris images are also evaluated using baseline 1-D log-Gabor filter and monogenic log-Gabor filter based approach. The experimental results are reported on the publically available UBIRIS V2, FRGC and CASIAV4-distance databases. The achieved experimental results on at-a-distance databases are highly promising and confirm the usefulness of the approach.
Human identification using KnuckleCodes

The usage of finger knuckle images for personal identification has shown promising results and generated lot of interest in biometrics. In this work, we investigate a new approach for efficient and effective personal identification using KnuckleCodes. The enhanced knuckle images are employed to generate KnuckleCodes using localized Radon transform that can efficiently characterize random curved lines and creases. The similarity between two KnuckleCodes is computed from the minimum matching distance that can account for the variations resulting from translation and positioning of fingers. The feasibility of the proposed approach is investigated on the finger knuckle database from 158 subjects. The experimental results, i.e., equal error rate of 1.08% and rank one recognition rate of 98.6%, suggest the utility of the proposed approach for online human identification.
Improving Periocular Recognition by Explicit Attention to Critical Regions in Deep Neural Network

Periocular recognition has been emerging as an effective biometric identification approach, especially under less constrained environments where face and/or iris recognition is not applicable. This paper proposes a new deep learning-based architecture for robust and more accurate periocular recognition which incorporates attention model to emphasize important regions in the periocular images. The new architecture adopts multi-glance mechanism, in which part of the intermediate components are configured to incorporate emphasis on important semantical regions, i.e., eyebrow and eye, within a periocular image. By focusing on these regions, the deep convolutional neural network is able to learn additional discriminative features, which in turn improves the recognition capability of the whole model. The superior performance of our method strongly suggests that eyebrow and eye regions are important for periocular recognition, and deserve special attention during the deep feature learning process. This paper also presents a customized verification-oriented loss function, which is shown to provide higher discriminating power than conventional contrastive/triplet loss functions. Extensive experiments on six publicly available databases are performed to evaluate the proposed approach. The reproducible experimental results indicate that our approach significantly outperforms several state-of-the-art methods for the periocular recognition.
Finite element 2D steady-state time harmonic field analysis of induction motor

This work describes a method of calculating the steady state harmonic field distribution of an induction motor. A finite element based model, which predicts the magnetic field throughout in induction motor during steady state conditions, is established. The harmonic components of magnetic field and the spatial distribution corresponding to each of the frequency components are calculated for an induction motor by using this model. Apart from calculating the fundamental AC component, the time harmonic components of the magnetic field due to rotor slotting and discrete conductors are also obtained. Finite element grid is constructed by using first order triangular and quadrilateral elements and the material properties associated with grid are allowed to vary with tune to account for rotation of the rotor.
Personal Identification Using Minor Knuckle Patterns From Palm Dorsal Surface

Finger or palm dorsal surface is inherently revealed while presenting (slap) fingerprints during border crossings or during day-to-day activities, such as driving, holding arms, signing documents, or playing sports. Finger knuckle patterns are believed to be correlated with the anatomy of fingers that involve complex interaction of finger bones, tissues, and skin, which can be uniquely identify the individuals. This paper investigates the possibility of using lowest finger knuckle patterns formed on joints between the metacarpal and proximal phalanx bones for the automated personal identification. We automatically segment such region of interest from the palm dorsal images and normalize/enhance them to accommodate illumination, scale, and pose variations resulting from the contactless imaging. The normalized knuckle images are investigated for the matching performance using several spatial and spectral domain approaches. We use database of 501 different subjects acquired from the contactless hand imaging to ascertain the performance. This paper also evaluates the possibility of using palm dorsal surface regions, in combination with minor knuckle patterns, and provides finger dorsal image database from 712 different subjects for the performance evaluation. The experimental results presented in this paper are very encouraging and demonstrates the potential of such unexplored minor finger knuckle patterns for the biometrics identification.
Inspection of surface defects using optimal FIR filters

A new method of surface inspection for textured materials is investigated. The linear FIR filters that offer optimal energy separation between the defect and defect-free regions of texture have been utilized. The performance of different feature separation criteria with reference to fabric defects has been evaluated. The issues relating to the design of optimal filters for supervised and unsupervised web inspection are discussed. A general web inspection system based on optimal filters is proposed. Experiments with this new approach have yielded excellent results. The on-line computational simplicity of using the proposed scheme confirms the usefulness of the approach for industrial inspection.
Extraction and recognition of multi-oriented text from trademark images

This paper presents an application system to extract and recognize text in Trademark and Logo images. Many methods have been proposed to address image text detection and recognition problems, and some of them have achieved impressive results for some specific applications. But recognition of Multi-oriented characters and numerals in Trademark and Logo images is still a challenge due to the variations of text font, size, color, orientation and alignment, and it is often affected by complex background and non-textual objects. Also to prevent the trademark infringement cases and for an efficient trademark similarity matching system, accurate text recognition plays a vital role.
Energy efficient routing in Wireless Sensor Networks: A survey

Technological advances in wireless communication paved way to the development of tiny low-cost, low-power and multifunctional sensor nodes in wireless sensor networks. Wireless Networks are becoming popular due to the concept of “3 any”- any person, anywhere and anytime. The design of sensor network is influenced by factors like scalability, energy consumption, environment etc. and depends on the application. Of the three activities: sensing, processing and communication, most of the energy is spent on communication purposes. Energy conservation is thus a dominant factor in wireless sensor networks. Routing strategy selection is very important for proper delivery of packets. Ongoing research aims in extending network lifetime by designing protocols that requires less energy during communication. An energy harvesting wireless sensor networks is a solution against the drainage of energy in battery powered networks since renewal of energy is too expensive. Energy harvesting make use of nodes that are able to harvest energy from the environment. This paper provides a survey on energy efficient routing in wireless sensor networks and introduces the concept of energy harvesting in wireless sensor networks.
Can We Use Second Minor Finger Knuckle Patterns to Identify Humans?

Human hand possesses some of the most distinctive anatomical features which have been extensively used for the biometrics identification. However there are several hand features which results from complex interaction among bones, muscles, skin and tissues (therefore these are expected to be anatomically unique to individuals) which remain relatively unexplored for their potential in biometrics especially for forensic applications. This paper explores the possibility of using lowest finger knuckle patterns formed on the joints between metacarpal and the proximal phalanx bones for the biometrics identification. We automatically segment such region of interest from the hand images and normalize/enhance them to accommodate illumination, scale and pose variations resulting from the contactless imaging. The normalized knuckle images are used to match using several matchers popular in the literature. We use database of 110 different subjects acquired from the contactless hand imaging to ascertain the performance. We also evaluate the performance from matching of such lowest finger knuckle patterns using two session data acquired after an interval of at least two years. The experimental results are very encouraging and demonstrate potential of such unexplored finger knuckle patterns for the biometrics applications.
Recognizing human faces under disguise and makeup

The accuracy of automated human face recognition algorithms can significantly degrade while recognizing same subjects under make-up and disguised appearances. Increasing constraints on enhanced security and surveillance requires enhanced accuracy from face recognition algorithms for faces under disguise and/or makeup. This paper presents a new database for face images under disguised and make-up appearances the development of face recognition algorithms under such covariates. This database has 2460 images from 410 different subjects and is acquired under real environment, focuses on make-up and disguises covariates and also provides ground truth (eye glass, goggle, mustache, beard) for every image. This can enable developed algorithms to automatically quantify their capability for identifying such important disguise attribute during the face recognition We also present comparative experimental results from two popular commercial matchers and from recent publications. Our experimental results suggest significant performance degradation in the capability of these matchers in automatically recognizing these faces. We also analyze face detection accuracy from these matchers. The experimental results underline the challenges in recognizing faces under these covariates. Availability of this new database in public domain will help to advance much needed research and development in recognizing make-up and disguised faces.
Performance and simulation analysis of single-phase grid connected PV system based on Z-source inverter

This paper presents photovoltaic (PV) grid-connected power conditioning systems based on Z-source inverter. Using Z-source network, the system can work within a range of PV array output voltage wider than that of the conventional boost converter. It allows the use of the shoot-through switching state for boosting the input voltage, compensates dead-time effect which causes serious output voltage distortions and avoids the risk of damaging the inverter circuit. This condition cannot be obtained in the traditional inverters. The whole system is designed, modeled and simulated in a Matlab/Simulink environment. The simulation results demonstrate that the photovoltaic grid-connected power conditioner based on Z-source inverter can perform maximum power point tracking (MPPT) even in very fast changing environmental conditions and voltage boosting when needed to interface with the utility grid.
Comparison of superconducting fault current limiter topologies based on power electronic devices

Fault current limiter (FCL) technology regulates fault current along with capability to cut down voltage sag problems raised by faults in system. A superconductor fault current limiter (SFCL) technology has a high efficiency and compressed design. Silicon controlled rectifier (SCR) based technology limits the fault current during whole fault operation but it requires milliseconds of time to begin with fault protection. A fast response metal oxide semiconductor field effect transistor (MOSFET)/ insulated gate bipolar transistor (IGBT) based SFCL limits the fault current successfully. A thorough analysis and comparison of SFCL topologies on basis of switching elements has been presented in this paper. Simulation results shows that MOSFET based SFCL has fast response.