nils-herrmann/clean_scirepeval huggingface dataset:
Fast fault recovery of a grid integrated wind farm based HVDC Light transmission system

Worldwide, wind energy is accepted as one of the foremost developed, cost-effective and proven renewable energy technologies to satisfy increasing electricity demands in an exceedingly sustainable manner. This paper investigates the fast AC fault recovery capability, fast and independent control of active and reactive power of the HVDC Light transmission system. These capabilities are most desired in future grids with high penetration of renewable energy sources like wind and solar. A negative sequence current controller is implemented for the wind turbine generator to mitigate the power oscillations and dc link voltage excursions within the HVDC Light system during fault conditions. Converters are controlled through adaptive neuro fuzzy inference system (ANFIS). The study system consisting of synchronous generator, a doubly fed induction generator (DFIG) based wind farm and voltage source converter based HVDC Light transmission system is modeled in Matlab/ Simpower Systems software. Simulation studies are carried out to demonstrate the effectiveness of the model for steady state and dynamic conditions.
Effect of dielectric engineering on analog and linearity performance of gate electrode workfunction engineered (GEWE) silicon nanowire MOSFET

This work demonstrates that with the incorporation of gate stack (GS) on GEWE-SiNW MOSFET, the analog and linearity performance of the device enhances in terms of transconductance, output conductance and device efficiency. The important Linearity figure of merits (FOMs) such as second order voltage intercept point (VIP2), third order voltage intercept point (VIP3), third order input intercept point (IIP3), third order intermodulation distortion (IMD3) and 1-dB compression point are studied with the help of 3D ATLAS and DEVEDIT device simulator for low power linear CMOS devices. Moreover, it has been observed that the zero-cross over point for GS-GEWE-SiNW MOSFET is reduced appreciably compared to its counterparts, which results into lowered optimum bias point for device operation.
Left Ventricular Systolic Dysfunction Identification by Motion Analysis

This paper presents a new technique for identification of regional dysfunctions in the left ventricle from 2-D echocardiography. It uses a novel left ventricular border tracking algorithm based on fuzzy inference system. In this paper we show how the regional dysfunction present in the left ventricle can be identified by tracking the movement of centre of mass of left ventricle in a 2D space. The path pattern of that point traced over the cardiac cycles shows variation between the two groups. The main advantage of this proposed approach is the smaller date handling in regional dysfunction identifications unlike other existing methods. The method is illustrated on the real 2D echocardiograph dataset that includes patients having dysfunctions in the left ventricular wall. The diagnostic potential of this method is explained in detail
Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification

In order to avail the benefits of higher user convenience, hygiene, and improved accuracy, contact less 3D fingerprint recognition techniques have recently been introduced. One of the key limitations of these emerging 3D fingerprint technologies to replace the conventional 2D fingerprint system is their bulk and high cost, which mainly results from the use of multiple imaging cameras or structured lighting employed in these systems. This paper details the development of a contact less 3D fingerprint identification system that uses only single camera. We develop a new representation of 3D finger surface features using Finger Surface Codes and illustrate its effectiveness in matching 3D fingerprints. Conventional minutiae representation is extended in 3D space to accurately match the recovered 3D minutiae. Multiple 2D fingerprint images (with varying illumination profile) acquired to build 3D fingerprints can themselves be used recover 2D features for further improving 3D fingerprint identification and has been illustrated in this paper. The experimental results are shown on a database of 240 client fingerprints and confirm the advantages of the single camera based 3D fingerprint identification.
Total reduction of leakage power through combined effect of Sleep stack and variable body biasing technique

Leakage power consumption has become a major concern for VLSI circuit designers. Leakage power will become dominant by the year 2020 as per the report of ITRS . We propose the new approach, named sleepy stack with variable body biasing (SSVBB), which reduces the leakage current thereby saving the state of art. It uses traditional sleep transistors which are placed parallel to PMOS/NMOS between the pull up/pull down device and VDD/gnd. Dual Vth can be also be applied to reduce sub threshold leakage current. It achieves exact same power reduction as zigzag approach along with saving the logic state of the circuit. Based on the experiments with the inverter as the benchmark circuit, it is found that there is 48% of reduction in delay but with the sacrifice of area. For the application which requires long idle/standby time while maintaining the logic state, the stack sleep with variable body biasing can be used.
Auction algorithm for Nonlinear Resource Allocation Problems

We study the problem of optimally assigning N divisible resources to M competing missions/tasks. We call this the Nonlinear Resource Allocation Problem (RAP). This simple yet powerful framework has found applications in diverse fields such as search theory, statistics, finance, economics, logistics, sensor and wireless networks. RAP is an instance of convex program but it has a bipartite structure like the assignment/transportation problem. In this paper, we propose a new algorithm, RAP Auction, for this problem which finds a near optimal solution in finite time. Unlike most existing methods in literature, we do not presuppose a particular cost function or assume differentiability or strict convexity. RAP Auction works for any monotonic convex cost function. It has a very simple computation structure amenable to distributed implementation.
ANFIS based coordinated control for an offshore wind farm connected VSC MTDC system

Offshore wind farms are becoming an attractive solution for wind power in many developed countries. The voltage source converter (VSC) based multi-terminal high voltage direct current (MTDC) transmission system is an attractive technical option to integrate these offshore wind farms with the onshore grid due to its unique performance characteristics and reduced power loss via extruded DC cables. In this paper, an adaptive neuro fuzzy inference system (ANFIS) based coordinated control design has been addressed for MTDC system in order to enhance the reliability and to balance the power. A four terminal VSC-MTDC system which consists of an offshore wind farm and oil platform is implemented in MALAB/SimPower Systems software. The proposed model is tested under different fault scenarios and simulation results show that the novel coordinated control design has great dynamic stabilities and also the VSC-MTDC system can supply Ac voltage of good quality to offshore loads during the disturbances.
A novel approach for test case generation from UML activity diagram

Software testing approaches are mainly divided into three types i.e. code based testing, specification based testing and model based testing. In model based testing, the testing can be started from the design process at the beginning phase. So, early detection of faults can be achieved by using this approach. An approach for the generation of test cases from UML (Unified Modelling Language) activity diagram using genetic algorithm has been presented in this paper. Early detection of faults can be achieved by this approach and will certainly reduce the time, cost and effort of the developer to a large extent. We propose a model to generate an Activity Flow Table (AFT) from an Activity Diagram and then convert it to Activity Flow Graph (AFG). Coverage criteria are very important in test case generation. By using activity coverage criterion we traverse the AFG and the test paths are generated. Finally, we generate the test cases from these paths. Genetic Algorithm has been applied to generate test cases and also to optimise them. The model is implemented on a case study of ATM Withdrawal system.
Can we use minor finger knuckle images to identify humans?

Biometric identification using finger knuckle imaging has generated lot of promises with interesting applications in forensics and remote biometrics. Prior efforts in the biometrics literature have only investigated the `major' finger knuckle patterns that are formed on the finger surface joining proximal phalanx and middle phalanx bones. This paper investigates the possible use of `minor' finger knuckle patterns which are formed on the finger surface joining distal phalanx and middle phalanx bones. The `minor' or `upper' finger knuckle patterns can either be used as independent biometric patterns or employed to improve the performance from the major finger knuckle patterns. This paper investigates a completely automated approach for the `minor' finger knuckle identification by developing steps of region of interest segmentation, image normalization, enhancement and robust matching to accommodate image variations. Comparative experimental results are presented for matching the normalized `minor' finger knuckle images using LBP, ILBP and 1D log Gabor filter. The efforts to develop automated `minor' finger knuckle patterns achieve promising results, with 1.04% equal error rate on the database of 202 subjects, and illustrate its simultaneous use to improve the performance for conventional finger knuckle identification.
Incorporating color information for reliable palmprint authentication

This paper investigates new approaches for improving the conventional palmprint authentication performance by integrating color information. We firstly propose a new approach for image level combination of multiple color components to generate more reliable palmprint representation than the conventional gray level representation. This investigation is motivated to develop more robust palmprint representation that can be employed to achieve better performance for the conventional palmprint identification, with the same computational complexity. Secondly, this paper presents a rigorous analysis of different color representations for the palmprint images to ascertain the performance improvement using different feature representations (OLOF and SIFT) and different databases (scanner and webcam). The rigorous experimental results from this study suggest that the influence of color information can differently alter the performance gain, which varies with the nature of employed feature representation.
Performance evaluation of routing protocols based on different models in MANET

A mobile adhoc network is an independent system of mobile stations associated by wireless link to form a system. This system can be modeled in the form of an uninformed graph. Adhoc networks are peer to peer, multihope networks were data packets are transmitted to a source to destination through intermediate nodes (which serve as router). The infrastructure is not the main issue to setup MANET and it can be setup anytime, anywhere. This paper presents the comparison of AODV, LAR1 and DSR routing protocols with three different models like increasing the number of nodes, increasing the pause time and increasing the speed of nodes. Performance of the above mentioned work are done on the attributes like throughput, packet delivery ratio, drop ratio and end-to-end delay). The performance of these three routing protocols is done on Glomosim Simulator and we concluded LAR1 has better throughput in comparison to both AODV and DSR routing protocols in all three scenario. Packet delivery Ratio behaves like throughput, LAR1 has better PDR in comparison to AODV and DSR. Drop ratio is also similar to PDR, actually it is reverse of PDR so we can say that LAR1 has lower drop ratio in comparison to AODV and DSR. AODV and DSR have lower delay in comparison to LAR1. LAR1 routing protocol has higher delay, and it is also seen that as we increase the nodes, pause time and mobility delay is also increase.
Correcting Infrared Focal Plane Array Sensor Non Uniformities Based Upon Adaptive Filter

The spatial and temporal non-uniformities in infrared focal plane array (IRFPA), which is called as fixed pattern noise, results a slowly varying pattern on the thermal image thus degrading the resolving capabilities of thermal imaging system considerably. An adaptive filter based technique is presented to correct fixed pattern noise. This method uses kalman filter and corrects both the additive and multiplicative types of fixed pattern noise thus eliminating the need of halting the operation of thermal camera for calibration. A FPGA based approach is presented for implementing the proposed method. The result obtained and the performance parameter of the algorithm is presented.
Analog Multiplier with High Accuracy

In this paper, a new technique is proposed for multiplication of two sampled analog signals and the output is in digital form. One analog signal is fed to the input of Delta sigma modulator (DSM1) after sampling. The sampled output of the second analog signal is negated or not negated depending on the bit state at the output of DSM1 and is fed to the input of second DSM (DSM2). The resulting bit stream at the output of DSM2 is the digital representation of the product of the two analog signals. For considered low frequency analog signals with amplitudes ranging from -2.5V to +2.5V, the maximum absolute value of error signal in the proposed multiplier is 0.05% of full scale (FS) when the sampling period of analog signals is 0.01sec. and the DSMs operating clock period is 0.1μsec., whereas the reported accuracy so far is only 0.5%.
Hybrid LZA: A near optimal implementation of the Leading Zero Anticipator

The Leading Zero Anticipator (LZA) is one of the main components used in floating point addition. It tends to be on the critical path, so it has attracted the attention of many researchers in the past. Most LZAs used today can be classified in two categories: exact and inexact. Inexact LZAs are normally preferred due to their shorter critical paths and reduced complexity; however, the inexact LZA requires an additional correct stage. In this paper we present a new LZA architecture that combines ideas taken from prior exact and inexact LZAs. Our new LZA improves the delay of floating point addition by 7–10% compared to state of art techniques as well as reduces hardware area in most cases. We also establish theoretical lower bounds on the delay of an LZA and we show that our LZA is very close to these bounds.
Pseudo-polynomial auction algorithm for Nonlinear Resource Allocation

We study the problem of optimally assigning N divisible resources to M competing tasks. This is called the Nonlinear Resource Allocation Problem (RAP). Recently, we proposed a new algorithm, RAP Auction , which finds a near optimal solution in finite time. It works for monotonic convex cost functions and has a simple computation structure. In this paper, we propose an elegant extension which enables RAP Auction to have pseudo-polynomial complexity.
A Novel Approach to Improve Biometric Recognition Using Rank Level Fusion

This paper proposes a novel approach for rank level fusion which gives improved performance gain verified by experimental results. In the absence of ranked features and instead of using the entire template, we propose using K partitions of the template. The approach proposed in the paper is useful for generating sequential ranks and survivor lists on partitions of template to boost confidence levels by incorporating information from partitions. The proposed algorithm iteratively generates ranks for each partition of the user template. Ranks from template partitions are consolidated to estimate the fusion rank for the classification. This paper investigates rank level fusion for palmprint biometric using two approaches: (1) fixed threshold and resulting survivor list, and (2) iterative thresholds and iteratively refined survivor list. The above approaches achieve similar performances as related manifestations of fusion architecture. The experimental results support the proposition of high in-template similarity of palmprint for a user and its relevance to the intra-modal fusion framework. Experimental results using proposed approach on real palmprint data from 100 users show superior performance with recognition accuracy of 99 % as compared to recognition accuracy of 95% achieved with the conventional approach.
1 × 8 signal router using cascading the Mach-Zehnder interferometers

In MZI, due to the application of the voltage across electrode present in one of the arms, the electric field changes, hence, phase change occurs. Depending upon the phase change introduced, the signal shifts from one waveguide to the another waveguide. In this paper, we describe the detailed description of 1×8 signal router, using cascading Mach-Zehnder interferometer (MZI), and its construction using the beam propagation method.
Timing analysis of combinational circuits using Weights Binary Decision Diagram (WBDD)

Weights Binary Decision Diagram (WBDD) based timing analysis of combinational circuit is proposed. Here we express the combinational circuit as a directed graph. We compute and store the delay of combinational circuits for all combination of inputs for the range of delay values based on controlling values. Hence it is possible to look up the built in library and calculate the output delay of any combinational circuit. The output delay computation is much faster when compared to normal method of calculating the delay at each level of the combinational circuits. This can be used in the synthesis of network for low power consumption.
Importance of Being Unique From Finger Dorsal Patterns: Exploring Minor Finger Knuckle Patterns in Verifying Human Identities

Automated biometrics identification using finger knuckle images has increasingly generated interest among researchers with emerging applications in human forensics and biometrics. Prior efforts in the biometrics literature have only investigated the major finger knuckle patterns that are formed on the finger surface joining proximal phalanx and middle phalanx bones. This paper investigates the possible use of minor finger knuckle patterns, which are formed on the finger surface joining distal phalanx and middle phalanx bones. The minor finger knuckle patterns can either be used as independent biometric patterns or employed to improve the performance from the major finger knuckle patterns. A completely automated approach for the minor finger knuckle identification is developed with key steps for region of interest segmentation, image normalization, enhancement, and robust matching to accommodate image variations. This paper also introduces a new or first publicly available database for minor (also major) finger knuckle images from 503 different subjects. The efforts to develop an automated minor finger knuckle pattern matching scheme achieve promising results and illustrate its simultaneous use to significantly improve the performance over the conventional finger knuckle identification. Several open questions on the stability and uniqueness of finger knuckle patterns should be addressed before knuckle pattern/image evidence can be admissible as supportive evidence in a court of law. Therefore, this paper also presents a study on the stability of finger knuckle patterns from images acquired with an interval of 4-7 years. The experimental results and the images presented in this paper provide new insights on the finger knuckle pattern and identify the need for further work to exploit finger knuckle patterns in forensics and biometrics applications.
Current mode biquadratic universal filter

A current mode universal filter using current controlled differential difference current conveyor transconductance amplifier (CCDDCCTA) is discussed. The filter provides important and desirable features : (i) Uses only one CCDDCCTA and two capacitors, (ii) One can get low pass (LP), band pass (BP), high pass (HP), notch (NF) and all pass (AP) current responses using the same configuration without any alteration, (iii) Passive components are grounded, which eases the integrated circuit implementation, (iv) Responses are electronically tunable, and (v) Sensitivity is low. Simulation results agree well with theory.
Theoretical study of mask haze formation

Studies on the haze formation mechanism in deep ultraviolet (UV) lithography were carried out. A nucleation and growth model on haze formation was proposed based on Gibbs energy change analysis. Haze formation is a nucleation and growth process. For a spontaneous process, Gibbs energy change in nucleation results from surface energy increase and volume energy decrease; the former tends to prevent nucleation and the latter to enhance it. Then, a critical dimension of nuclei exists, i.e. when a nucleus is larger than critical dimension, it can grow with a system Gibbs energy decrease. The study shows that it is thermodynamically spontaneous for small haze to merge with large haze. A critical distance exists, beyond which nuclei grow independently. The haze formation region on a plot of composition versus temperature was proposed based on the equilibrium constant calculation and a haze growth mechanism postulated. Photochemical dissociation of molecular oxygen to atomic oxygen by excimer laser less than 246 nm wavelength plays an important role in the oxidation of sulfur dioxide. The proposed mechanism agreed well with previously published experimental results.
Human hand identification with 3D hand pose variations

Several recent research efforts in the hand biometrics have focused on developing contact-free personal identification system. However, the acquisition of images from the unconstrained hands can introduce significant hand pose variations which severely limits the performance and applicability of these approaches. This paper presents a new approach to achieve significantly improved performance even in the presence of large hand pose variations. The proposed approach firstly estimates the orientation of the hands in 3D space and then attempts to normalize the pose of the simultaneously acquired 3D and 2D hand images. A new feature representation, namely SurfaceCode, is proposed for matching a pair of 3D palms. Multimodal (2D as well as 3D) palmprint and hand geometry features, which are simultaneously extracted from the texture details of the normalized 3D hands, are used for the matching. Individual matching scores are then consolidated using the weighted sum rule. Our experiments on the database of 114 subjects, with significant pose variations, achieve consistent performance improvement, both for palmprint and hand geometry features considered in this work.