nils-herrmann/clean_scirepeval huggingface dataset:
Personal recognition using hand shape and texture

This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), /spl kappa/-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems.
Combining 2D and 3D hand geometry features for biometric verification

Traditional hand geometry based personal verification systems offer limited performance and therefore suitable only for small scale applications. This paper investigates a new approach to achieve performance improvement for hand geometry systems by simultaneously acquiring three dimensional features from the presented hands. The proposed system utilizes a laser based 3D digitizer to acquire registered intensity and range images of the presented hands in a completely contact-free manner, without using any hand position restricting mechanism. Two new representations that characterize the local features on the finger surface are extracted from the acquired range images and are matched using the proposed matching metrics. The proposed approach is evaluated on a database of 177 users, with 10 hand images for each user acquired in two sessions. Our experimental results suggest that the proposed 3D hand geometry features have significant discriminatory information to reliably authenticate individuals. Our experimental results also demonstrate that the combination of 3D hand geometry features with 2D geometry features can be employed to significantly improve the performance from 2D hand geometry features alone.
Blind watermarking techniques using DCT and arnold 2D cat map for color images

The modern era of digital communication facilities bring digital watermarking techniques which is required to copyright and authenticate owner's information which further tracks control of regeneration and redistribution of images over untrusted and public network. In this paper, a blind digital watermarking technique has been proposed using Discrete Cosine Transform (DCT) to embed information in mid-frequency. The Arnold 2D cat map is used to shuffle the original pixel positions of watermark color image. First, the watermark image is divided into its RGB components and Arnold 2D transformation has been applied. The original cover image is decomposed into its respective RGB components. The resulting watermark images are embedded into separate components of cover images using DCT. The intensity values of watermark images are hidden in mid frequency of DCT blocks of cover images. So, it doesn't scatter the original watermark to most visual parts of the image. The experimental results show that the algorithm is effective and robust.
Efficient iris segmentation using Grow-Cut algorithm for remotely acquired iris images

This paper presents a computationally efficient iris segmentation approach for segmenting iris images acquired from at-a-distance and under less constrained imaging conditions. The proposed iris segmentation approach is developed based on the cellular automata which evolves using the Grow-Cut algorithm. The major advantage of the developed approach is its computational simplicity as compared to the prior iris segmentation approaches developed for the visible illumination iris segmentation images. The experimental results obtained from the three publicly available databases, i.e. UBIRIS.v2, FRGC and CASIA.v4-distance have respectively achieved average improvement of 34.8%, 31.5% and 31.4% in the average segmentation error, as compared to the recently proposed competing/best approaches. The experimental results presented in this paper clearly demonstrate the superiority of the developed iris segmentation approach, i.e., significant reduction in computational complexity while providing comparable segmentation performance, for the distantly acquired iris images.
Matching Contactless and Contact-Based Conventional Fingerprint Images for Biometrics Identification

Vast databases of billions of contact-based fingerprints have been developed to protect national borders and support e-governance programs. Emerging contactless fingerprint sensors offer better hygiene, security, and accuracy. However, the adoption/success of such contactless fingerprint technologies largely depends on advanced capability to match contactless 2D fingerprints with legacy contact-based fingerprint databases. This paper investigates such problem and develops a new approach to accurately match such fingerprint images. Robust thin-plate spline (RTPS) is developed to more accurately model elastic fingerprint deformations using splines. In order to correct such deformations on the contact-based fingerprints, RTPS-based generalized fingerprint deformation correction model (DCM) is proposed. The usage of DCM results in accurate alignment of key minutiae features observed on the contactless and contact-based fingerprints. Further improvement in such cross-matching performance is investigated by incorporating minutiae related ridges. We also develop a new database of 1800 contactless 2D fingerprints and the corresponding contact-based fingerprints acquired from 300 clients which is made publicly accessible for further research. The experimental results presented in this paper, using two publicly available databases, validate our approach and achieve outperforming results for matching contactless 2D and contact-based fingerprint images.
Enhanced Power and Breakdown in III-N RF Switches With a Slow Gate

We show that III-nitride radio-frequency switches with a composite slow/fast gate have higher maximum switching power and breakdown voltage compared with conventional switches of the same type. The composite gate design includes an additional “slow gate” electrode formed under the metal gate using a low-conducting InGaN layer. The “slow gate” covers the entire source-drain spacing. The addition of the “slow gate” layer not only offers a lower insertion loss and higher isolation but, as shown in this letter, also increases the power handling capability by “delaying” switch self-modulation under high-power stress. We also show that, the “slow gate” design increases breakdown voltage.
Optimization of radial distribution system losses with wind weibull distribution function integration using PSO and GA technique

Due to increasing per capita energy consumption and exponential rising population, power system losses increasingly and reliability decreasing. The distributed generator can improve the power system reliability and reduce losses. The most widely preferred DG which is large attracted by large scale as wind powers do not have pollution issue and consider as clean energy source. By the wind to its maximum extent it is necessary to place the wind turbine at the place where the losses of the system and the size of the turbine are minimum. In this paper the PSO (particle swarm optimization) technique is applied on IEEE 12 radial standard bus system to get reduced losses and optimum size of wind turbine. Backward/forward sweep method used to analyze the power flow in radial distribution systems. Weibull functions F(x) have been used to describe the best wind distribution which is one of the probabilistic modeling to select random variable. From the results optimum size of turbine is obtained and also obtains the location for placement of wind turbine to optimum the system losses. MATLAB/Simulink is used to simulate the optimization of power losses at power output of mean various wind turbine speed.
A Routing Protocol for Delay-Sensitive Applications in Mobile Ad Hoc Networks

The Ad hoc On Demand Distance Vector (AODV) routing protocol is intended for use by mobile nodes in ad hoc networks. To provide quality of service, extensions can be added to the messages used during route discovery. These extensions specifythe service requirements which must be met by nodes rebroadcasting a route request (RREQ) or returning a route reply (RREP) for a destination. In order to provide quality delivery to delay sensitive applications such as voice and video, it is extremely important that mobile ad hoc networks provide quality of service (QoS) support in terms of bandwidth and delay. In spite of using IEEE 802.11 as medium access control (MAC), most of the ad hoc routing protocols do not consider contention time which occurs in the medium reservation. Large contention times can be more critical than hop counts in determining the end-to-end delay. Most existing routing protocols for mobile ad hoc networks are designed to search for the shortest path with minimum hop counts. However, the shortest routes do not always provide the best performance, especially when there are congested nodes along these routes. In this paper we propose an on demand delay based quality of service (QoS) routing protocol (AODV-D) to ensure that delay does not exceed a maximum value for mobile ad hoc networks. This protocol will take into consideration MAC layer channel contention information and the number of packets in the interface queue in addition to minimum hops.
A survey on methodologies used for semantic document clustering

Document clustering is a traditional technique, and is used in multiple fields like data mining, information retrieval, knowledge discovery from data, pattern recognition etc. Large volumes of textual data being created in the modern world have resulted in the rise in importance of document clustering techniques. Although various document-clustering techniques have been studied in recent years, clustering quality still remains an area of concern. Particularly, majority of the present document clustering methods do not account for the semantic relationships and as a result give unsatisfactory clustering results. Semantic relationships consider the context of the usage of the term and do not solely rely on its isolated meaning. In the recent years, a lot of effort has gone into applying semantics to document clustering. This paper presents a survey of various research papers that have been studied and highlights the merits and demerits of each clustering algorithm. This will give a direction to future research in a more focused manner.
Receptor-mediated targeting of magnetic nanoparticles using insulin as a surface ligand to prevent endocytosis

Superparamagnetic iron oxide nanoparticles have been used for many years as magnetic resonance imaging contrast agents or in drug delivery applications. Tissue and cell-specific drug targeting by these nanoparticles can be achieved by employing nanoparticle coatings or carrier-drug conjugates that contain a ligand recognized by a receptor on the target cell. In this study, superparamagnetic iron oxide nanoparticles with specific shape and size have been prepared and coupled to insulin for their targeting to cell expressed surface receptors and thereby preventing the endocytosis. The influence of these nanoparticles on human fibroblasts is studied using various techniques to observe cell-nanoparticle interaction that includes light, scanning, and transmission electron microscopy studies. The derivatization of the nanoparticle surface with insulin-induced alterations in cell behavior that were distinct from the underivatized nanoparticles suggests that cell response can be directed via specifically engineered particle surfaces. The results from cell culture studies showed that the uncoated particles were internalized by the fibroblasts due to endocytosis, which resulted in disruption of the cell membrane. In contradiction, insulin-coated nanoparticles attached to the cell membrane, most likely to the cell-expressed surface receptors, and were not endocytosed. The presence of insulin on the surface of the nanoparticles caused an apparent increase in cell proliferation and viability. One major problem with uncoated nanoparticles has been the endocytosis of particles leading to irreversible entry. These results provide a route to prevent this problem. The derivatized nanoparticles show high affinity for cell membrane and opens up new opportunities for magnetic cell separation and recovery that may be of crucial interest for the development of cellular therapies.
Tetrahedron Based Fast 3D Fingerprint Identification Using Colored LEDs Illumination

Emerging 3D fingerprint recognition technologies have attracted growing attention in addressing the limitations from contact-based fingerprint acquisition and improve recognition accuracy. However, the complex 3D imaging setups employed in these systems typically require structured lighting with scanners or multiple cameras which are bulky with higher cost. This paper presents a more accurate and efficient 3D fingerprint identification approach using a single 2D camera with multiple colored LED illumination. A 3D minutiae tetrahedron based algorithm is developed to more efficiently match recovered minutiae features in 3D space and address the limitations of 3D minutiae matching approach in the literature. This algorithm significantly improves the matching time to about 15 times than the state-of-art in the reference. A hierarchical tetrahedron matching scheme is also developed to further improve the matching accuracy with faster speed. The 2D images acquired to reconstruct the 3D fingerprints are also used to recover 2D minutiae and further improve matching performance for 3D fingerprints. A new two-session database acquiring from 300 different clients consists of 2760 3D fingerprints reconstructed from 5520 colored 2D fingerprints is also developed and shared in public domain to further advance much needed research in this area. Extensive experimental results presented in this paper validate our approach and demonstrate the effectiveness of proposed algorithms.
Personal Authentication Using Finger Knuckle Surface

This paper investigates a new approach for personal authentication using fingerback surface imaging. The texture pattern produced by the finger knuckle bending is highly unique and makes the surface a distinctive biometric identifier. The finger geometry features can be simultaneously acquired from the same image at the same time and integrated to further improve the user-identification accuracy of such a system. The fingerback surface images from each user are normalized to minimize the scale, translation, and rotational variations in the knuckle images. This paper details the development of such an approach using peg-free imaging. The experimental results from the proposed approach are promising and confirm the usefulness of such an approach for personal authentication.
A novel piezoelectric interdigital transducer for the excitation of high frequency surface acoustic waves

We propose a novel piezoelectric interdigital transducer (PIT) based on alternately poled domains of a ferroelectric thin film deposited on top of a single crystal substrate. This transducer offers an alternative to the interdigital transducer (IDT) for the excitation of very high frequency surface acoustic waves (SAW). An experimental validation of the approach is reported in a 1-4 GHz frequency range, confirming theoretical predictions.
Diagonal slotted diamond shaped dual circularly polarized microstrip patch antenna with dumbbell aperture coupling

Improvement in ellipticity bandwidth with a diagonal slotted diamond shaped microstrip patch antenna is analyzed in this paper. The antenna is electro-magnetically fed using two orthogonally oriented dumbbell shaped apertures fed by a 3dB 90/spl deg/ hybrid for dual polarization operation. The radiating element is a 45/spl deg/ rotated square patch (aspect ratio a/b = 1.015) forming a diamond. The antenna is designed to transmit and receive the two differently circularly polarized wide band signals simultaneously with a single antenna. It is observed that by cutting an electrically small rectangular slot along one of the diagonal of the square patch significantly improves the ellipticity bandwidth without altering its impedance bandwidth. The current distribution of the patch remains unaltered and hence the radiation pattern is also not affected. The use of a thick, low cost dielectric foam yields further improvement in bandwidth. A 2:1 impedance bandwidth of 26.5% and 3 dB axial ratio bandwidth of 20.4% has been achieved in simulation with the above geometry. An improvement of 5% in impedance bandwidth and 9% in ellipticity bandwidth is obtained over a patch of similar geometry with conventional rectangular shaped apertures. When compared to a non-slotted patch with dumbbell apertures the improvement in axial ratio bandwidth is of the order of 5% while the impedance bandwidth remains unaltered. The use of dielectric foam makes the antenna light weight and low cost. The above features make it an ideal element for wide band application as required for personal, mobile satellite and wireless communication systems.
A New Framework for Adaptive Multimodal Biometrics Management

This paper presents a new evolutionary approach for adaptive combination of multiple biometrics to ensure the optimal performance for the desired level of security. The adaptive combination of multiple biometrics is employed to determine the optimal fusion strategy and the corresponding fusion parameters. The score-level fusion rules are adapted to ensure the desired system performance using a hybrid particle swarm optimization model. The rigorous experimental results presented in this paper illustrate that the proposed score-level approach can achieve significantly better and stable performance over the decision-level approach. There has been very little effort in the literature to investigate the performance of an adaptive multimodal fusion algorithm on real biometric data. This paper also presents the performance of the proposed approach from the real biometric samples which further validate the contributions from this paper.
Comparative analysis of various Domino logic circuits for better performance

In this paper, basically the delay and the noise margin parameter associated in the circuit has been analyzed. The paper gives a better approach for the reduction in delay variation and compares the result with different-different types of domino logic circuits. The other domino logic circuits used to discriminate the result of proposed circuit are footed domino logic circuit, footless domino logic circuit, high speed domino logic circuit and conditional keeper domino logic circuit. The simulation process here has been done in 65nm CMOS technology using Cadence Virtuoso at 270C operating temperature and 0.8 V supply voltage. In this paper the parameters like delay, average power, no. of transistors and UNG has been calculated and after simulation it is found that the proposed paper gives better output if it is compared with the other circuits.
Biometric Recognition using Entropy-Based Discretization

The biometrics based recognition systems proposed in the literature have not yet exploited user-specific dependencies in the feature level representation. This paper suggests and investigates the performance improvement of the existing biometric systems using the discretization of extracted features. The performance improvement due to the unsupervised and supervised discretization schemes is compared on verity of classifiers; KNN, naive Bayes, SVM and FFN. The experimental results on the hand-geometry database of 100 users achieve significant improvement in the recognition accuracy and confirm the usefulness of discretization in biometrics systems.
Slot Loaded Microstrip Patch Antenna for WLAN and WiMax Applications

A slot loaded micro strip antenna with an aperture coupled feed is proposed. The basic radiator is a square patch with a 'dual loop' shaped slot cut into the patch area. The usable bandwidth of the slotted antenna is 840 MHz (2.37-3.21 GHz) which is appropriate for WLAN application in the 2.4-2.484 GHz band and WiMax application in 2.5-2.69 GHz band. The antenna is designed, simulated and optimized for wideband RF performance using HFSS. The simulated 2:1 VSWR bandwidth of the antenna is 30.10% with respect to the mid-band frequency of 2.79 GHz. The proposed antenna gain is greater than 6.5 dBi in the WLAN band and more than 7.3 dBi in the WiMax band. The antenna presents a patch size reduction of 44% when compared to a conventional square micro strip patch antenna. The antenna has an overall dimension of 70 x 70 x 11.58 mm3.
Speed Up Technique for Fractal Image Compression

Fractal Image compression is a novel technique in the field of image compression; it is based on affine contractive transforms and utilizes the existence of self-symmetry in the image. This technique has grabbed much attention in recent years because of manifold advantages, very high compression ratio, high decompression speed, high bit-rate and resolution independence. Since 1990 a lot of techniques and improvements have been published in this field. This review represents survey of most significant advances in the field of fractal image compression.
Computer-Vision-Based Fabric Defect Detection: A Survey

The investment in an automated fabric defect detection system is more than economical when reduction in labor cost and associated benefits are considered. The development of a fully automated web inspection system requires robust and efficient fabric defect detection algorithms. The inspection of real fabric defects is particularly challenging due to the large number of fabric defect classes, which are characterized by their vagueness and ambiguity. Numerous techniques have been developed to detect fabric defects and the purpose of this paper is to categorize and/or describe these algorithms. This paper attempts to present the first survey on fabric defect detection techniques presented in about 160 references. Categorization of fabric defect detection techniques is useful in evaluating the qualities of identified features. The characterization of real fabric surfaces using their structure and primitive set has not yet been successful. Therefore, on the basis of the nature of features from the fabric surfaces, the proposed approaches have been characterized into three categories; statistical, spectral and model-based. In order to evaluate the state-of-the-art, the limitations of several promising techniques are identified and performances are analyzed in the context of their demonstrated results and intended application. The conclusions from this paper also suggest that the combination of statistical, spectral and model-based approaches can give better results than any single approach, and is suggested for further research.