nils-herrmann/clean_scirepeval huggingface dataset:
A synchronization of PV source by using bacterial foraging optimization based PI controller to reduce day-time grid dependency

Globally the pressure on the power utilities are growing day by day to meet the load demand during peak hours, that's why power bodies are showing great interest in renewable sources, despite their integration problems with the grid. Grid-tied solar power generating systems are gaining popularity because of abundance of solar power. This paper presents a synchronization mechanism of grid tied photovoltaic system using shunt active power filter (SAPF). The proposed scheme transfer power from solar to grid as well as improve the quality of power. Solar power generating system injects harmonics in to the system at point of common coupling. The indirect current control based synchronous reference frame (SRF) theory is used to mitigate current harmonics, neutral current, reactive power and also improves the overall power factor of the system. DC link voltage control plays a major role in the performance of SAPF. The control of DC link voltage becomes difficult by using PI controller as the load is continuously varying. The performance of PI controller is enhanced by using novel bacterial foraging algorithm (BFO) for optimizing PI parameters. Different MATLAB simulation results are depicted for transient and steady state analysis of grid-tied photo-voltaic (PV) system.
Forward and reverse auction algorithms for Nonlinear Resource Allocation

We study the problem of optimally assigning N divisible resources to M competing tasks, where the performance cost of each task is a convex function of the resources allocated. This is called the Nonlinear Resource Allocation Problem (RAP). This class of problems arises in diverse fields such as search theory, statistics, finance, economics, logistics, sensor and wireless networks. In our recent work, we proposed a class of algorithms, RAP Auction, which were based on extensions of Auction algorithms for linear assignment problems. RAP Auction was shown to find a near optimal solution in finite time and converge under asynchronous computation. However, major limitations of RAP auction were the lack of stronger complexity results and mediocre empirical performance compared to alternative algorithms. In this paper, we develop a new class of algorithms for the solution RAP problems, based on the use of forward and reverse auction principles, along with scaling techniques. The new algorithms can be shown to have pseudo-polynomial complexity and are significantly faster in standard benchmarks than competing special purpose and general purpose state of the art methods.
A novel efficient adiabatic logic design for ultra low power

With the continuously growing quest for miniaturization of circuit technology, one of the prime focuses of the research has shifted in the direction of ultra low power circuit designs. Over the years, adiabatic circuit designs have been studied and found to be effective in achieving low power in VLSI circuits. This paper briefs some of the adiabatic logic families such as ECRL, 2N-2N2P and PFAL. And presents a new adiabatic logic circuit based on PFAL logic family. This paper aims at comparing the effectiveness of proposed adiabatic logic circuit, in terms of power dissipation, over other adiabatic logic families by simulating different logic gates using these logic families. All the simulations are done using HSPICE Simulator at 65nm technology at different frequency range. Comparative results are presented by different bar graphs plotted at different frequencies, which shows least power dissipation for the proposed logic circuit.
Comparative analysis of backpropagation and RBF neural network on monthly rainfall prediction

Rainfall plays a major role in the economic growth of every country. It is an essential component in the human life cycle. Its accurate and predetermined forecast can prevent many natural hazards and helpful to the tourists for travelling beautiful destinations of the world. Due to the current climatic variations, the accuracy of forecasting rainfall is very important. In this paper, we have used back propagation and radial basis function neural network techniques for predicting the monthly rainfall values based on the data collected from the Coonoor region in the Nilgiri district (Tamil Nadu). Furthermore, mean square error and accuracy are the performance indices used for the comparative analysis. Experimental results showed that the radial basis function neural network acts as a better prediction model with smaller mean square error and higher accuracy values. Furthermore, we have used these techniques for predicting the future data based on the previously collected data.
Design of a novel compact planar monopole UWB antenna with triple band-notched characteristics

In this paper a compact planar UWB antenna with triple band-notched characteristics has been presented. The design consists of a unique lamp post shaped radiator fed through a microstrip feedline with a pair of etched U-shaped slots and a C-shaped slot. The proposed antenna has been successfully simulated using CST MWS Suite. The proposed antenna of size 30 × 30mm2 is very compact and easy to integrate with hand held devices. The antenna reports a large bandwidth from 2.68 GHz to 10.65 GHz with VSWR ≤ 2 over the entire range except at three notched bands for WiMax systems at 3.3-3.7 GHz, WLAN systems at 5.15-5.85 GHz and 7.25-8.40 GHz for uplink and downlink of X-band satellite communication systems. The proposed antenna exhibits nearly omni-directional radiation pattern and a stable gain over the entire impedance bandwidth except for the three notched bands.
Low power high speed 1-bit full adder circuit design in DSM technology

In today's high-speed communication world the usage of electronics portable devices is increasing day by day, as the devices are portable and compact it has to satisfy the need of low power dissipation and minimum area requirement along with the high speed. A one bit full adder cell is one of the most frequently used digital circuit component in arithmetic logic unit (ALU) and it is the essential functional unit of all computational circuit. Till now many improvement has been done in this area to refine the architecture and performance of full adder circuit design. This paper mainly focus on two novel 1-bit full adder cells which is designed on 32 nm CMOS technology with different operating frequencies at 1 v supply voltage. The design of two novel 1-bit full adder cells along with three existing adder cells are incorporate in this paper and their complete comparison and verification has been done in terms of power dissipation, delay and power delay product (PDP) at different operating frequencies by using HSPICE tool. It is found that the existing Static Energy Recovery Full (SERF) adder and Gate Diffusion Input (GDI) full adder provides poor performance when compared with proposed adder cell and also its equivalent layout has been generated to calculate the area of existing and proposed adder cell by using Microwind 3.5 tool. From the simulation result it is observed that the first proposed adder circuit using XOR module has achieved maximum saving of PDP 46.71% & 96.61% when compared to existing SERF and GDI adder cells respectively. The second proposed circuit using XNOR module has achieved maximum saving of PDP 74.59% & 98.38% when compared to existing SERF and GDI 1-bit adder cells respectively.
UHD video transmission using adaptive SHVC in wireless networks

Scalable extension of High Efficiency Video coding (SHVC) is an ideal candidate for delivering Ultra High Definition (UHD) content to heterogeneous clients. In this work we propose a system architecture to deliver UHD content adaptively based upon bandwidth and end user device specifications over wireless network. For the adaptive transmission we need a Parametric rate model for bit rate adaptation. Hence, we study the effect of quantization, frame rate, and spatial resolution on bit rate in order to develop a Parametric rate model for SHVC videos. The rate model is developed in terms of quantization step size, frame rate, and spatial resolution. It is observed that the model fits into measured data with high Pearson Correlation. The rate model helps in deciding the quantization parameter, frame rate, and spatial resolution for the given bandwidth conditions so as to improve the user experience. The receiver sends the channel conditions and device capabilities (like device resolution support and processing power) to the transmitter. Based on this, the transmitter adaptively changes the transmitted bit stream. The overall system performance is evaluated in terms of the PSNR of the transmitted and received video sequence.
Multi-Siamese networks to accurately match contactless to contact-based fingerprint images

Contactless 2D fingerprint identification is more hygienic, and enables deformation free imaging for higher accuracy. Success of such emerging contactless fingerprint technologies requires advanced capabilities to accurately match such fingerprint images with the conventional fingerprint databases which have been developed and deployed in last two decades. Convolutional neural networks have shown remarkable success for the face recognition problem. However, there has been very few attempts to develop CNN-based methods to address challenges in fingerprint identification problems. This paper proposes a multi-Siamese CNN architecture for accurately matching contactless and contact-based fingerprint images. In addition to the fingerprint images, hand-crafted fingerprint features, e.g. minutiae and core point, are also incorporated into the proposed architecture. This multi-Siamese CNN is trained using the fingerprint images and extracted features. Therefore, a more robust deep fingerprint representation is formed from the concatenation of deep feature vectors generated from multi-networks. In order to demonstrate the effectiveness of the proposed approach, a publicly available database consisting of contact-based and respective contactless finger-prints is utilized. The experimental evaluations presented in this paper achieve outperforming results, over other CNN-based methods and the traditional fingerprint cross matching methods, and validate our approach.
Incorporating user quality for performance improvement in hand identification

Personal authentication using hand images, especially with those acquired from the peg-free imaging, has very high user-acceptance and has invited lot of attention in the literature. This paper investigates a new approach to achieve the performance improvement by incorporating user quality into the matching stage. The proposed method of extracting user quality is based on the confidence of generating reliable matching scores from the user templates. The palmprint and hand-shape images are simultaneously extracted from the hand images and are used to ascertain the performance improvement for the individual trait. The experimental results presented in this paper show significant improvement in the performance while incorporating the proposed method of user quality in the matching stages. This user quality based fusion of two biometric modalities is also investigated and achieves significant improvement in the authentication performance.
Temperature stabilized CMOS ring oscillator

This paper presents a new technique to improve the frequency stability and amplitude stability with respect to temperature of ring oscillator using CMOS technology at 500nm technology using 3 volts supply voltage with 100fF load capacitance. There are several proposed architecture for the improvement in frequency stability and amplitude stability of sinusoidal output waveform. Proposed structure 1 based on addition of feed-forward path increases the frequency stability and amplitude stability whereas the proposed structure 2 based on the addition of feedback path increases the frequency stability and amplitude stability with respect to temperature.
Singular value decomposition using block least mean square method for image denoising and compression

Image denoising is a well documented part of Image processing. It has always posed a problem for researchers and there is no dearth of solutions extended. Obtaining a denoised and perfectly similar image after application of processes represents a mirage that has been chased a lot. In this paper, we attempt to combine the effects of block least mean square algorithm (BLMS) to maximizes the Peak Signal to Noise Ratio (PSNR), along with singular valued decomposition (SVD), so as to achieve results that bring us closer to our aim of perfect re construction. The results showed that the combination of these methods provides easy computation, coupled with efficiency and as such is an effective way of approaching the problem.
Low-Energy Equivalent Sized Location Aware Grouping in Wireless Sensor Networks

In this paper we present, design and implementation of a protocol for Low-Energy Equivalent sized Location Aware (LEELA) grouping in WSNs. The protocol enables proximal grouping of SNs with a scheduled ‘duty cycle’ employed over it to offer energy efficiency and provides location awareness without using any GPS device. This group is a “black box” for rest of the network and can be treated as a single node for any routing protocol applied at the abstract level.
Automated segmentation of iris images using visible wavelength face images

Remote human identification using iris biometrics requires the development of automated algorithm of the robust segmentation of iris region pixels from visible face images. This paper presents a new automated iris segmentation framework for iris images acquired at-a-distance using visible imaging. The proposed approach achieves the segmentation of iris region pixels in two stages, i.e. (i) iris and sclera classification, and (ii) post-classification processing. Unlike the traditional edge-based segmentation approaches, the proposed approach simultaneously exploits the discriminative color features and localized Zernike moments to perform pixel-based classification. Rigorous experimental results presented in this paper confirm the usefulness of the proposed approach and achieve improvement of 42.4% in the average segmentation errors, on UBIRIS.v2 dataset, as compared to the previous approach.
An annular-ring slot antenna with pair truncated corners for CP operation

An annular-ring slot antenna with pair of slits and truncated corner for CP operation is proposed. The proposed antenna is fabricated and simulated to analysed the radiation characteristic. Simulated results show a good agreement with experimental results. A pair of slits and truncated corners are used to enhance axial ratio bandwidth. Antenna also shows much larger CP bandwidths than earlier reported results. The measured impedance bandwidth and 3-dB Axial Ratio band width of the proposed antenna are 94.2% and 73.8%, respectively. The proposed antenna shows consistent return loss and radian pattern for entire frequency range.
An 80 MHz noise optimized continuous-time bandpass filter in 0.25 μm BiCMOS

An 80 MHz bandpass filter with a tunable quality factor of 16-44 using an improved transconductor circuit is presented. The noise optimized biquad structure achieves SNR of 45 dB at IMD of 40 dB. The P-ldB compression point and IIP3 of the filter are -10 dBm and -2.68 dBm, respectively. The proposed filter gives an output of 1.87 Vpp at -ldB compression point in 3.3V supply and consumes 66 mW. It is fabricated in 0.25 μm BiCMOS.
Robust hybrid adaptive perceptual wavelet packet threshold to enhance speech in adverse noisy environment

A new robust hybrid method has been proposed by combining the Ephraim-Malah filtering method with subband adaptive time adaptive perceptual wavelet packet based threshold technique for enhancement of speech from adverse noisy environment. It is obtained by applying Ephraim-Malah filtering (EM) method for preprocessing the signal to initially reduce the noise. Because EM method enhances the signal but still remains musical noise. Hence, to further enhance the signal, a new approach sub-band adaptive time adaptive perceptual wavelet packet based threshold technique has been proposed (SATA-PWPT). This method is very simple and estimates the noise level from noisy signal without using complicated V/UV detection algorithm. Experimental results show that the proposed method works better than the other wavelet based threshold approaches for enhancing the speech signal. This method is analyzed in frequency domain analysis. The objective results are measured by global Signal to Noise Ratio (SNR) and Mean Square Error (MSE) with NOIZEUS database sentences corrupted by various types of colored noise. Spectrograms are also used to show the visual results.
Scale and Scope Externalities in Growth of IT Industries in India: An Agglomeration Perspective

Externalities occur among agglomerated firms. Scale externalities occur between firms in an industry with similar activities. Scope externalities occur when heterogeneous activities are placed in proximity. Combined scale-and-scope externalities exist when the scale of one industry is beneficial to the growth of another collocated industry. We use the agglomeration perspective to explain the growth of IT industries in India. We study growth patterns of four IT industries: computer and peripheral equipment manufacturing, semiconductor and other electronic components manufacturing, software and IT-enabled services. Our analysis suggests the existence of scale, scope and combined scale-and-scope externalities in IT industry growth. We also find that the growth of IT industries has had a significant positive effect on national development
Semicircular multiband ACS feed antenna for IoT

In this communication, design and analysis of a semicircular multiband asymmetrical coplanar strip (ACS) feed antenna operating over the frequency range of GSM 1800, Bluetooth (2.4–2.484 GHz)/Wi-Fi (2.4 GHz) for IoT (Internet of Things) has been investigated. The proposed antenna consists of two semicircular arcs which provide services in the GSM 1800, Bluetooth and Wi-Fi in ISM frequency band facilitating the multiband behavior. The antenna is fabricated on a low cost FR4 substrate of thickness 1mm and has the most compact dimension of 24 × 10 mm2. The fabricated prototype yields a measured impedance bandwidth of 1.725–1.9115 GHz, 2.25–2.6555 GHz covering operating frequencies of GSM, Bluetooth and Wi-Fi frequency bands respectively. Good electrical characteristics in frequency domain makes the antenna suitable for IoT application deployment.
Convergence Analysis of Complex Valued Multiplicative Neural Network for Various Activation Functions

In a complex valued neural network (CVNN) the weights, threshold, inputs and outputs are all complex numbers. Researchers have proposed many complex activation functions which can approximate a continuous complex valued function for CVNN node processing. The choice of an activation function determines the convergence of the complex back propagation algorithm and its generalization characteristics. In this paper we have compared the performance of various activation functions on the complex XOR problem for the complex multiplicative neural network.
Impact of various mobility model and judgment for selecting mode of network in different mobility situation for Mobile Ad-Hoc Network (MANET)

In Mobile Ad-hoc Network (MANET) the mobility of nodes is challenging issue for designer, In this kind of network there are lot of possibilities of mobility of nodes. In this work three different kind of node mobility is taken in consideration are source node mobility, destination node mobility and third one is whole network nodes mobility. For all these mobility issues both reactive mode of packet transformation and proactive mode of packet transformation is taken for comparison, based on this comparison, judgment is taken that on which mode of operation which packet transformation technique is work better. Parameter for comparing these modes of network End to End delay, throughput, load generation by network and packet loss in the network are taken. These all parameter defines can be used as the Quality of Service (QoS) judgment. So the work of this paper is the judgment of QoS[1] for Different mode of Mobile Ad-hoc Network[3].
Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification

Human identification using fingerprint impressions has been widely studied and employed for more than 2000 years. Despite new advancements in the 3D imaging technologies, widely accepted representation of 3D fingerprint features and matching methodology is yet to emerge. This paper investigates 3D representation of widely employed 2D minutiae features by recovering and incorporating (i) minutiae height z and (ii) its 3D orientation φ information and illustrates an effective matching strategy for matching popular minutiae features extended in 3D space. One of the obstacles of the emerging 3D fingerprint identification systems to replace the conventional 2D fingerprint system lies in their bulk and high cost, which is mainly contributed from the usage of structured lighting system or multiple cameras. This paper attempts to addresses such key limitations of the current 3D fingerprint technologies bydeveloping the single camera-based 3D fingerprint identification system. We develop a generalized 3D minutiae matching model and recover extended 3D fingerprint features from the reconstructed 3D fingerprints. 2D fingerprint images acquired for the 3D fingerprint reconstruction can themselves be employed for the performance improvement and have been illustrated in the work detailed in this paper. This paper also attempts to answer one of the most fundamental questions on the availability of inherent discriminableinformation from 3D fingerprints. The experimental results are presented on a database of 240 clients 3D fingerprints, which is made publicly available to further research efforts in this area, and illustrate the discriminant power of 3D minutiae representation andmatching to achieve performance improvement.
Biometric Authentication using Finger-Back Surface

This paper investigates a new biometric system based on texture of the hand knuckles. The texture pattern produced by the finger knuckle bending is highly unique and makes the surface a distinctive biometric identifier. Hand geometry features can be acquired from the same image, at the same time and integrated to improve the performance of the system. The finger back surface images from each of the users are used to extract scale, translation and rotational invariant knuckle images. The proposed system, especially on the peg-free and non-contact imaging setup, achieves promising results when tested over a database of 105 users.
Load balanced multicast routing protocol for wireless mobile ad-hoc network

A Mobile Ad hoc NETwork (MANET) is an interconnected of mobile nodes without any fixed base station in the network. Due to the high mobility of nodes, the network topology of MANETs changes very fast, making it more difficult during data transmission of data packet from source node to destination node. Because mobile nodes have limited battery power, it is therefore very important to use energy in a MANET efficiently. Due to the dynamic topology and limited resources of mobile nodes, the routing scheme in MANETs presents important challenges. In this study, load balancing multicast routing protocol (LBMRP) for MANETs is proposed. In the proposed scheme, all mobile nodes are randomly classified into three types, group-1, group-2 and group-3. To achieve the load balance, three multicast trees (TREE-1 for group-1, TREE-2 for group-2 and TREE-3 for group-3) are constructed. Simulation results show that the proposed LBMRP scheme outperforms multicast ad hoc on-demand distance vector routing protocol (MAODV), reliability of the multicast ad hoc on demand distance vector (RMAODV) and Parallel multiple nearly-disjoint trees multicast routing (Parallel MNTMR) schemes.