nils-herrmann/clean_scirepeval huggingface dataset:
Signal Processing Challenges in Quantitative 3-D Cell Morphology: More than meets the eye

Modern developments in light microscopy have allowed the observation of cell deformation with remarkable spatiotemporal resolution and reproducibility. Analyzing such phenomena is of particular interest for the signal processing and computer vision communities due to the numerous computational challenges involved, from image acquisition all the way to shape analysis and pattern recognition and interpretation. This article aims at providing an up-to-date overview of the problems, solutions, and remaining challenges in deciphering the morphology of living cells via computerized approaches, with a particular focus on shape description frameworks and their exploitation using machine-learning techniques. As a concrete illustration, we use our recently acquired data on amoeboid cell deformation, motivated by its direct implication in immune responses, bacterial invasion, and cancer metastasis.
Tracking multiple articulated objects using physics engines: Improvement using multi scale decomposition and quadtrees

This paper presents a new method to accelerate the automatic tracking of multiple articulated objects in video sequences. The tracking method exploits the physics modeling of the articulated objects. The physics approach has numerous advantages such as the capability to let multiple models interact when tracking simultaneously multiple objects. Solving the tracking problem is generally done with an iterative scheme involving the computation of numerous forces, which usually turns out to be time consuming. This paper tackles the computational cost bottleneck by introducing a multi scale decomposition of the force maps. At each step of the tracking optimization scheme the multiple force maps are efficiently combined using a quadtree structure to recover the resulting forces. We demonstrate through multiple experiments that our results are both exact and drastically faster than the standard computation scheme.
Multiscale Variance-Stabilizing Transform for Mixed-Poisson-Gaussian Processes and its Applications in Bioimaging

Fluorescence microscopy images are contaminated by photon and readout noises, and hence can be described by mixed-Poisson-Gaussian (MPG) processes. In this paper, a new variance stabilizing transform (VST) is designed to convert a filtered MPG process into a near Gaussian process with a constant variance. This VST is then combined with the isotropic undecimated wavelet transform leading to a multiscale VST (MS-VST). We demonstrate the usefulness of MS-VST for image denoising and spot detection in fluorescence microscopy. In the first case, we detect significant Gaussianized wavelet coefficients under the control of a false discovery rate. A sparsity-driven iterative scheme is proposed to properly reconstruct the final estimate. In the second case, we show that the MS-VST can also lead to a fluorescent-spot detector, where the false positive rate of the detection in pure noise can be controlled. Experiments show that the MS-VST approach outperforms the generalized Anscombe transform in denoising, and that the detection scheme allows efficient spot extraction from complex background.
Coupled parametric active contours

We propose an extension of parametric active contours designed to track nonoccluding objects transiently touching each other, a task where both parametric and single level set-based methods usually fail. Our technique minimizes a cost functional that depends on all contours simultaneously and includes a penalty for contour overlaps. This scheme allows us to take advantage of known constraints on object topology, namely, that objects cannot merge. The coupled contours preserve the identity of previously isolated objects during and after a contact event, thus allowing segmentation and tracking to proceed as desired.
Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces

Cell migrations and deformations play essential roles in biological processes, such as parasite invasion, immune response, embryonic development, and cancer. We describe a fully automatic segmentation and tracking method designed to enable quantitative analyses of cellular shape and motion from dynamic three-dimensional microscopy data. The method uses multiple active surfaces with or without edges, coupled by a penalty for overlaps, and a volume conservation constraint that improves outlining of cell/cell boundaries. Its main advantages are robustness to low signal-to-noise ratios and the ability to handle multiple cells that may touch, divide, enter, or leave the observation volume. We give quantitative validation results based on synthetic images and show two examples of applications to real biological data.
Comparison of reconstruction algorithms in compressed sensing applied to biological imaging

In this paper, we propose a short presentation of the compressed sensing imaging framework, along with a review of recent applications in the biomedical imaging field. One of the critical issue that used to hinder the application of compressed sensing in a bioimaging context is the computational cost of the underlying image reconstruction process. However, some recently published algorithms manage to overcome this difficulty, leading to acceptable reconstruction computational times. We illustrate with simulations on biological images of fluorescence microscopy a comparison of three reconstruction algorithms, evaluating data fidelity and computational efficiency.
Biophysical Active Contours for Cell Tracking I: Tension and Bending

Automatic segmentation and tracking of biological objects from dynamic microscopy data is of great interest for quantitative biology. A successful framework for this task are active contours, curves that iteratively minimize a cost function, which contains both data-attachment terms and regularization constraints reflecting prior knowledge on the contour geometry. However the choice of these latter terms and of their weights is largely arbitrary, thus requiring time-consuming empirical parameter tuning and leading to sub-optimal results. Here, we report on a first attempt to use regularization terms based on known biophysical properties of cellular membranes. The present study is restricted to 2D images and cells with a simple to skeletal cortex underlying the membrane. We describe our new active contour model and its implementation, and show a first application to real biological images. The obtained segmentation is slightly better than standard active contours, however the main advantage lies in the self-consistent and automated determination of the weights of regularization terms. This encouraging result will lead us to extend the approach to 3D and more complex cells.
Contactless and Pose Invariant Biometric Identification Using Hand Surface

This paper presents a novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations. The proposed method utilizes a 3-D digitizer to simultaneously acquire intensity and range images of the user's hand presented to the system in an arbitrary pose. The approach involves determination of the orientation of the hand in 3-D space followed by pose normalization of the acquired 3-D and 2-D hand images. Multimodal (2-D as well as 3-D) palmprint and hand geometry features, which are simultaneously extracted from the user's pose normalized textured 3-D hand, are used for matching. Individual matching scores are then combined using a new dynamic fusion strategy. Our experimental results on the database of 114 subjects with significant pose variations yielded encouraging results. Consistent (across various hand features considered) performance improvement achieved with the pose correction demonstrates the usefulness of the proposed approach for hand based biometric systems with unconstrained and contact-free imaging. The experimental results also suggest that the dynamic fusion approach employed in this work helps to achieve performance improvement of 60% (in terms of EER) over the case when matching scores are combined using the weighted sum rule.
Towards MuGFETs: A power reduction perspective

The progress towards making efficient chips, in terms of area, speed and power continues to remain a major concern of every silicon industry. The various effects that become prominent at nanometer level hinders this progress. This is a paper that looks into: scaling, its effects (short-channel effects, as it is called) and compares scaled single gate and scaled multiple gate FETs on important properties. The use of scaled multiple gate MOSFETs (MuGFETs) ensures better gate control and alpha-power model demonstrates reduction in time delay in MuGFETs, than in scaled single gate FETs. This shows that the short-channel effects are overcome by scaled MuGFETs, thereby not only facilitating higher packaging density, but also reducing power consumption and at the same time improving switching performance.
Image denoising using wavelet transform and wiener filter based on log energy distribution over Poisson-Gaussian noise model

Generally Gaussian noise model is used in image processing applications due to its presence in electronic circuitry used in image acquisition devices like Charge Coupled Device (CCD) cameras. Off let due to discrete nature of electromagnetic radiation in image acquisition process, due to photon noise that follows poison distribution is also exist with Gaussian noise. In this paper we present an algorithm based on Wavelet transform and wiener filter using log energy distribution to denoised digital images corrupted by Poisson-Gaussian noise. Our results clearly demonstrate the robustness of the algorithm over a large range of variance. We have used peak signal to noise ratio (PSNR) for comparison based on filter outlet.
Dual band half-mode substrate integrated waveguide leaky wave antenna with wide backward scanning

A novel half-mode substrate integrated waveguide (HMSIW) leaky wave antenna is presented. The HMSIW loaded with periodic horizontal T shaped slots produces dual-band characteristics with backward scanning capability in each band. The obtained return loss bandwidths are 1.65 GHz in the upper band (10.95 GHz to 12.6 GHz) and 0.9 GHz in the lower band (9 GHz to 9.9 GHz). The achieved scanning ranges are 27° in the upper band (from −8° to −35°) and 30° in the lower band (from −38° to −68°). The simulated gain is 13.2 dBi and 16.5 dBi in the lower and upper band respectively. The proposed structure has inherent band rejection filtering capability from frequency 10 GHz to 10.9 GHz.
High speed and high throughput 8×8 bit multiplier using a Shannon-based adder cell

The adder circuit is used as a main component in the multiplier circuits. The Baugh-Wooley, Braun and CSA multipliers are designed by using our proposed adder cell. The proposed adder circuit is designed by using Shannon theorem. The multiplier circuits are schematised by using DSCH2 VLSI CAD tool and their layouts are generated by using Microwind 3 VLSI CAD tool. The proposed adder based multiplier circuits are simulated and results are compared with MCIT and CPL based adder cell in terms of power, area, delay, EPI, Throughput, and Latency. The proposed adder based multiplier circuits are simulated by using 90nm feature size and corresponding supply voltage 1V. The Shannon full adder circuit based multiplier circuits gives better performance than other published results in terms of power dissipation, propagation delay, throughput and latency due to less number of transistor used in Shannon adder circuit. Since the maximum drain current is also not increasing significantly with temperature in our multiplier circuits, therefore, power dissipation of the circuit is less.
Defect detection in textured materials using optimized filters

The problem of automated defect detection in textured materials is investigated. A new approach for defect detection using linear FIR filters with optimized energy separation is proposed. 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 addressed. A general web inspection system based on the optimal filters is proposed. The experiments on this new approach have yielded excellent results. The low computational requirement confirms the usefulness of the approach for industrial inspection.
Adaptive Security for Human Surveillance Using Multimodal Open Set Biometric Recognition

In most human surveillance and forensic applications, key requirement is often to achieve highest possible true positive identification accuracy with a judicious compromise in accepting false positive identities. However with such scenario's in mind, there has been lack of any effort to develop adaptive security management for open set biometric recognition and most of the available prior work in literature has been focused on performance improvement for the rank-one recognition. This paper investigates the multimodal open set biometric recognition to address the conflicting requirements between the offered identification rate and high false positive identification rate while admitting possible unknown subjects/suspects in the higher rank (more than rank-one) list. The proposed approach attempts to offer accurate open set rank-K recognition which can automatically select a decision threshold to the desired/requested security level using ant colony optimization and provide a useful solution to a range of dynamic security problems in surveillance and high security applications. The performance evaluation of the proposed framework is ascertained through rigorous experimentation on three multimodal matchers from publicly available NIST BSSRlandXM2VTS databases.
Low-power stack pseudo domino logic using contention-alleviated precharge keeper

The dynamic circuits propose superior speed and low power dissipation over static CMOS circuits. The domino logic circuits are used for high system performance but these circuits suffer from the degradation of the precharge pulse. Therefore, this article provides different design topologies on the pseudo domino circuits to overcome the charge sharing and charge leakage with reference to the power dissipation. The circuit analysis of the power dissipation have been done on Tanner EDA tool for 45 nm technology. The proposed pseudo domino techniques are proffered to economize power dissipation and delay up to 32% and 20% in half adder circuit respectively.
Effect of Substrate Concentration on Methane Fermentation of Cattle Dung

Methane fermentation of cattle manure (CM) with different total solid contents were conducted in the laboratory-scale batch reactors (2.5 L volume) in order to determine the substrate concentration performance and potential energy recovery at the optimal mesophilic (35 oC) and thermophilic (55 oC) temperatures. The three reactors containing CM and water in the ratios (w/w) of 1:1 (wet fermentation), 2:1 and 1:0 (undiluted manure, dry fermentation) were utilized for the both conditions. The work was performed for a period of 63 days to compare the volatile solids and dissolved organic carbon degradation, COD removal, and VFAs. The results showed that the specific biogas yields, in terms of per kilogram of CM, were 41.68, 43.72 and 44.98 L/kg with 22.61, 23.69 and 24.96 L/kg methane contents respectively for the ratios of 1:1, 2:1 and 1:0 at 35 oC, while 43.03, 44.89 and 45.71 L/kg biogas with 23.45, 24.15 and 25.57 L/kg methane contents respectively for the ratios 1:1, 2:1 and 1:0 at 55 oC. The volume of the digester was increased in the wet fermentation for the same loading rate. Though water and thermophilic condition could promote the startup process and the biodegradability of the substrate, the total biogas and methane yields in the dry fermentation were found comparable to the conventional process (wet fermentation).
Structural and electrical characterization of Al/ZrO2/Si capacitors

ZrO2/Si thin films were fabricated using sputtering technique and the deposited films were annealed at temperatures of 873 K and 1073 K. From HRTEM analysis, it is observed that the as-deposited ZrO2 layers are partly amorphous and fully crystallize after post-deposition annealed at 1073 K. The dielectric constant of the as-deposited films was 15.0 and it increased to 29.0 with increase of annealing temperature to 873 K there after it decreased to 24.5 at higher temperature of 1073 K. The leakage current through the gate stack is reduced by several orders of magnitude after air annealing, consistent with the increase of SiOx layer thickness, as well as the reduction in trap density revealed by the reduced hysteresis effect observed in the C-V characteristics. The interfacial quality was improved notably for the devices annealed at a temperature of 1073 K. The plausible reason for the variations in the observed electrical characteristics could be due to the significant growth in the SiO2 at the interface between ZrO2 and Si substrate, which was also confirmed by the EELS/EDS analysis.
Performance of isolated generating system with multilevel inverter using photovoltaic source

Solar PV is one of the demanding nonconventional sources for generation of electricity but it has its own limitation due to non-linear characteristics. Solar PV needs MPP tracker to extract maximum power form solar PV source. Furthermore, multilevel voltage source inverter (VSI) is used for converting dc voltage into closed to sinusoidal ac supply. In this paper, incremental conductance (IC) technique for tracking maximum solar power is proposed with five-level VSI for converting solar PV dc voltage into three phase ac output voltage. Moreover, a unipolar PWM technique is proposed for VSI to producing gating pulses for Insulated gate bipolar transistor (IGBT) used in the VSI. Multilevel inverter is used to reduce filtering requirements and to reduce amplitude of all harmonics in inverter output. The complete model is simulated in MATLAB/SIMULINK and extensive simulations are carried out to validate the proposed system.
Security of SIP-based infrastructure against malicious message attacks

Nowadays Session Initiation Protocol (SIP) has become the most widely used signaling protocol by the vendors in the Voice over Internet Protocol (VoIP) communication. As the SIP is gaining popularity, open architecture of VoIP often makes SIP vulnerable to so many threats. The paper introduces SIP along with its different security mechanisms with the focus on attack signatures generation technique to identify the malformed SIP messages. It aims to generate various malicious SIP messages and to verify the limitations of the existing classical Intrusion Detection System (IDS) in identifying the malicious messages. Then it sets out to implement an improved detection framework using the rules as regular expression. The experiments were carried out using SER as an open source SIP server, Kphone and X-lite as SIP clients and the SIPSAK as an attacking tool on a testbed architecture which was in a form of virtual environment created with VMware. The platforms used were BackTrack7 and Windows 7. The test was first performed on SNORT, an open source IDS and later by adding the improved detection rules in the configuration file of the SIP server. The successful attacks on the classical attack-signatures generation framework proved that the existing IDSs couldn't identify logical errors in the malicious SIP messages. The proposed detection module identified and rejected all kind of malicious SIP messages with acceptable processing overheads. Moreover the associated signatures database can also be incorporated into other VoIP protocols and open source IDSs like SNORT. This paper has provided the effective mechanism in creating well-formed defense against malicious SIP message attacks to ensure the integrity and security of VoIP subsystems.
Arithmetic transformations to maximise the use of compressor trees

Complex arithmetic computations, especially if derived from bit-level software descriptions, can be very inefficient if implemented directly in hardware (e.g., by translation of the relevant C section in VHDL or Verilog). In this paper we show that known arithmetic optimisation techniques are in some cases insufficient to achieve the high-performance implementation that a designer could produce through an attentive study of the computation. We therefore introduce an algorithm to restructure dataflow graphs so that they can be synthesized in high-quality arithmetic circuits, especially when arithmetic operations are interspersed with logic operations. On typical software benchmarks, the new technique reduces the critical path by around 20-40% and generally achieves the quality of manual implementations. In many cases, our algorithm also manages to reduce the cell area by 10-20%.
Contactless palm vein identification using multiple representations

This paper investigates some promising approaches for the automated personal identification using contactless palmvein imaging. We firstly present two new palmvein representations, using Hessian phase information from the enhanced vascular patterns in the normalized images and secondly from the orientation encoding of palmvein line-like patterns using localized Radon transform. The comparison and combination of these two palmvein feature representations, along with others in the palmvein literature, is presented for the contactless palmvein identification. We also evaluate the performance from various palmvein representations when the numbers of training samples are varied from minimum. Our experimental results suggest that the proposed representation using localized Radon transform achieves better or similar performance than other alternatives while offering significant computational advantage for online applications. The proposed approach is rigorously evaluated on the CASIA database (100 subjects) and achieves the best equal error rate of 0.28%. Finally, we propose a score level combination strategy to combine the multiple palmvein representations. We achieve consistent improvement in the performance, both from the authentication and recognition experiments, which illustrates the robustness of the proposed schemes.
A study on ocean wave power and utilization for Indian coastal region

Indian costal region has low ocean wave flux density but it has a vast seashore area due to which the overall potential of ocean wave energy is extremely high. In addition, harnessing of ocean wave energy has minimum environmental impact. Till date only one project based on oscillating water column has been established in India. The project covers huge constructional area with high complexity. Therefore an uncomplicated technique covering a minimum space is required to harness optimum wave energy. This paper finds out the best possible method among existing Ocean Wave Energy Converter (OWEC) technologies and a direct drive permanent magnet linear generator is proposed to convert ocean wave energy into electrical energy. The aim is to trap the time-varying ocean wave in the simplest way and supply a good quality AC power for domestic appliances. A modified Parallel-Connected Pulsewidth Modulated Inverter with Current Sharing Reactors Topology is proposed to convert DC power to AC power. The simulation and experimental results for proposed modified inverter topology are presented. A constant voltage algorithm is developed to control DC-link voltage. The proposed OWEC requires lesser construction area and is simple to operate along with it being cost effective. A brief survey of Indian costal wave power is also discussed for the selection of an appropriate site in India.