nils-herrmann/clean_scirepeval huggingface dataset:
Performance analysis of full duplex relaying in multicell environment

This paper analyzes the performance of the full duplex relaying (FDR) based cooperative communication system in a multi-cell environment. In multi-cell environment the FDR is prone to co-channel interferers due to higher reuse of the frequency. Owing to the possibility of imperfect mitigation at the relay we, in this paper, model the self-interference (or echo-interference) channel, which exists between the transmitting and the receiving antennas of the relay, as a fading channel with Nakagami-m fading distribution. For the decode and forward (DF) relay, we analyze the error performance and derive an exact closed form expression of the average bit error rate (BER). Further, an exact closed form expression for outage probability of the considered system is also obtained.
Optimal nonnegative color scanning filters

In this correspondence, the problem of designing color scanning filters for multi-illuminant color recording is considered. The filter transmittances are determined from a minimum-mean-squared orthogonal tristimulus error criterion that minimizes the color error in estimates obtained from noisy recorded data. Nonnegativity constraints essential for physical realizability are imposed on the filter transmittances. In order to demonstrate the significant improvements obtained, the resulting filters are compared with suboptimal filters reported in earlier literature.
Refractive index modulation in lithium niobate slab using lamb wave

Refractive index modulation in Y-X Lithium Niobate slab through GHz Lamb wave is theoretically analyzed. Dispersion curves and generated displacement field pattern for acoustic waves in slab have been calculated using Rayleigh-Lamb frequency relations and the displacement potentials techniques respectively. Variation in refractive index of slab due to mechanical strain generated by Lamb wave is estimated using photo-elastic effect. It is found that the maximum change in refractive index for S0 mode at 5 GHz of acoustic frequency is 0.027 along X-direction of wave propagation and 0.012 along Y-transverse polarization of wave.
Distributed calibration of pan-tilt camera network using multi-layered belief propagation

In this paper, we present a technique for distributed self-calibration of pan-tilt camera network using multi-layered belief propagation. Our goal is to obtain globally consistent estimates of the camera parameters for each camera with respect to a global world coordinate system. The network configuration changes with time as the cameras can pan and tilt. We also give a distributed algorithm for automatically finding which cameras have overlapping views at a certain point in time. We argue that using belief propagation it is sufficient to have correspondences between three cameras at a time for calibrating a larger set of (static) cameras with overlapping views. Our method gives an accurate and globally consistent estimate of the camera parameters of each camera in the network.
Moving towards HSUPA (high speed uplink packet access): a complete 3.5G wireless system

Current 3G systems do not provide the much needed throughput for high data rate applications. To enhance downlink performance, high speed downlink packet access (HSDPA) technology is introduced which is often referred as a 3.5G system. HSDPA relies on a new downlink shared channel HS-DSCH. Enhancement in the downlink is considered assuming that for most of the applications, e.g., surfing, data download, etc; downlink traffic is far greater than uplink. HSDPA provides high throughput in downlink but uplink data has a limitation in 3G systems. For some applications, like video telephony, data flows equally in both directions. Thus, enhancement of uplink capability is a key to make a complete 3.5G system. High speed uplink packet access (HSUPA) is a technology being considered for this purpose. This paper discusses in detail the various technological aspect of HSUPA. Changes required in UMTS node B and UE to support HSUPA are also discussed.
Degenerate delay-capacity tradeoffs in ad-hoc networks with Brownian mobility

There has been significant recent interest within the networking research community to characterize the impact of mobility on the capacity and delay in mobile ad hoc networks. In this correspondence, the fundamental tradeoff between the capacity and delay for a mobile ad hoc network under the Brownian motion model is studied. It is shown that the two-hop relaying scheme proposed by Grossglauser and Tse (2001), while capable of achieving a per-node throughput of /spl Theta/(1), incurs an expected packet delay of /spl Omega/(logn//spl sigma//sub n//sup 2/), where /spl sigma//sub n//sup 2/ is the variance parameter of the Brownian motion model. It is then shown that an attempt to reduce the delay beyond this value results in the throughput dropping to its value under static settings. In particular, it is shown that under a large class of scheduling and relaying schemes, if the mean packet delay is O(n/sup /spl alpha////spl sigma//sub n//sup 2/), for any /spl alpha/<0, then the per-node throughput must be O(1//spl radic/n). This result is in sharp contrast to other results that have recently been reported in the literature.
Two-dimensional transforms for device color correction and calibration

Color device calibration is traditionally performed using one-dimensional (1-D) per-channel tone-response corrections (TRCs). While 1-D TRCs are attractive in view of their low implementation complexity and efficient real-time processing of color images, their use severely restricts the degree of control that can be exercised along various device axes. A typical example is that per separation (or per-channel), TRCs in a printer can be used to either ensure gray balance along the C=M=Y axis or to provide a linear response in delta-E units along each of the individual (C, M, and Y) axis, but not both. This paper proposes a novel two-dimensional color correction architecture that enables much greater control over the device color gamut with a modest increase in implementation cost. Results show significant improvement in calibration accuracy and stability when compared to traditional 1-D calibration. Superior cost quality tradeoffs (over 1-D methods) are also achieved for emulation of one color device on another.
Dynamics and kinematics of viral protein linear nano-actuators for bio-nano robotic systems

Dynamic and kinematic analysis is performed to predict and verify the performance of a new nanoscale biomolecular motor: The Viral Protein Linear (VPL) Motor. The motor is based on a conformational change observed in a family of viral envelope proteins when subjected to a changing pH environment. The conformational change produces a motion of about 10 nm, making the VPL a basic linear actuator which can be further interfaced with other organic/inorganic nanoscale components such as DNA actuators and carbon nanotubes. The proteins used in the motor are subjected to Molecular Dynamics simulation using the software called CHARMm (Chemistry at Harvard Molecular Mechanics). The results of dynamics are further verified by performing a set of kinematic simulations using direct and inverse kinematics methods.
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager

We consider optimal power allocation for wireless video sensors (WVSs), including the image sensor subsystem in the system analysis. By assigning a power-rate-distortion (P-R-D) characteristic for the image sensor, we build a comprehensive P-R-D optimization framework for WVSs. For a WVS node operating under a power budget, we propose power allocation among the image sensor, compression, and transmission modules, in order to minimize the distortion of the video reconstructed at the receiver. To demonstrate the proposed optimization method, we establish a P-R-D model for an image sensor based upon a pixel level sigma-delta ( ) image sensor design that allows investigation of the tradeoff between the bit depth of the captured images and spatio-temporal characteristics of the video sequence under the power constraint. The optimization results obtained in this setting confirm that including the image sensor in the system optimization procedure can improve the overall video quality under power constraint and prolong the lifetime of the WVSs. In particular, when the available power budget for a WVS node falls below a threshold, adaptive sensing becomes necessary to ensure that the node communicates useful information about the video content while meeting its power budget.
A joint approach to vector road map registration and vehicle tracking for wide area motion imagery

Modern aerial imaging platforms provide wide-area motion imagery (WAMI) at high spatial and moderate temporal resolutions making feasible a range of new applications. We consider the dual tasks of registering WAMI frames to geo-referenced vector road-maps and tracking vehicles through the progression of WAMI frames. We present a novel algorithm that performs these tasks jointly and offers improvements in both by exploiting the synergy between the tasks. Tracking for the large number of vehicles seen in urban-area WAMI is improved by auxiliary information that registration to the vector road-map provides by localizing roads within the scene. Similarly, registration of the WAMI frames to the vector map is improved by formulating the registration as a chamfer minimization between the vehicular trajectories and the road network, an approach that resolves challenges for registration posed by the fundamentally different data modalities between the aerial images and the vector road maps. Results obtained over our test datasets show the effectiveness of the proposed joint methodology. For both road network alignment and vehicle tracking, the proposed method offers a very significant improvement over available alternatives: the proposed approach yields better numerical metrics for quantification of registration accuracy and fewer false identification switches for tracked vehicles.
A novel method to predict die shift during compression molding in embedded wafer level package

The increased functionality of cellular phones and handheld devices requires system level integration. Thus there is a strong demand in cell phone maker to move to embedded micro wafer level packaging (EMWLP). But the major problem encountered is die shift during compression molding. This paper presents a novel method to predict the die shift during wafer level molding process. A series of parametric studies are performed by changing the die thickness, die pitch distance and top mold chaste compression velocity. The effect of thinning down the chip thickness affects the pressure difference and local shear rate on the chip surfaces. The rate of change of epoxy mold compound fluid pressure across the die top surfaces is not constant. The local shear rate is increasing linearly from the centre of the wafer to the outermost die. From the parametric studies, the die shift is inversely proportional to the die thickness for wafer level molding. Such a phenomenon will reduce the lithography alignment error in the next process. This paper also shows that by reducing die pitch distance of a 5 × 5 mm2, 500 µm thick chip, the die shift decreases by a factor of 12%. In addition, the top mold chaste compression velocity contributes to the die shift by as much as 28% when the velocity is reduced by 50% from 100 µm/sec to 50 µm/sec Finally it is observed from experiment result that the die shift is not constant in all directions.
Joint stochastic sampling for RNA secondary structure prediction

We present a novel method for prediction of common structures and alignment for two homologous RNA sequences. The method, termed joint sampling, is based on sampling from the structural alignment space of the sequences, i.e. the space of joint representations of common secondary structures and sequence alignments of the sequences. The structural alignment space is efficiently sampled by probabilistically generating structural alignments from building blocks termed structural alignment atoms. Structure and alignment predictions are obtained by clustering the samples of structures and alignments. The experimental results show that joint sampling offers improvements in structure prediction over a sampling method that generates structures from Boltzmann ensemble of single RNA sequence. In addition, the joint sampling offers more accurate estimate of alignment as compared to estimates from a hidden Markov model.
On the capacity of orientation modulation halftone channels

Clustered-dot halftones are extensively utilized in hardcopy printing. Modulation of the dot orientation in these halftones offers an avenue for data embedding which has been exploited in a number of different methods. We consider the capacity of these channels, modeling them as binary orientation input channels with vector valued output detection statistics. We derive upper bounds on the capacity for three channel conditional distributions corresponding to sub-Gaussian, Gaussian and super-Gaussian distributions. Using experimentally estimated channel parameters our bounds reveal that channel capacity has noticeable variations as a function of gray level. Highlights, shadows and mid-tones offer negligible capacity, on the contrary the regions between highlights and mid-tones or shadows and mid-tones offer high capacity for data embedding.
LOMo: Latent Ordinal Model for Facial Analysis in Videos

We study the problem of facial analysis in videos. We propose a novel weakly supervised learning method that models the video event (expression, pain etc.) as a sequence of automatically mined, discriminative sub-events (e.g. onset and offset phase for smile, brow lower and cheek raise for pain). The proposed model is inspired by the recent works on Multiple Instance Learning and latent SVM/HCRF - it extends such frameworks to model the ordinal or temporal aspect in the videos, approximately. We obtain consistent improvements over relevant competitive baselines on four challenging and publicly available video based facial analysis datasets for prediction of expression, clinical pain and intent in dyadic conversations. In combination with complimentary features, we report state-of-the-art results on these datasets.
Voltage control of the grid connected wind plant using energy storage and FACTS devices

Developments in wind turbine technology are facilitating the increase of power generation capacity from renewable energy resources. The utilization of the squirrel-cage induction generator for wind power generation has some advantages over that of conventional synchronous generators. In this paper an induction generator model driven by wind turbine and connected to the grid is simulated in SIMULINK / MATLAB. The simulation results confirm that the performance of the grid connected wind plant improves with the use of energy storage device i.e. (capacitor bank) & FACTS device i.e. (Static Var Compensator). However, better results are obtained by use of SVC.
Show-through cancellation in scans of duplex printed documents

In scanning pages with double-sided printing, often the printing on the back-side shows through in the scan of the front-side because the paper is not completely opaque. This show-through is an undesirable artifact that one would like to remove. In this paper, the phenomenon of show-through is analyzed using first physical principles to obtain a simplified mathematical model. The model is linearized using suitable transformations and simplifying approximations. Based on the linearized model, an adaptive linear filtering scheme is developed for the electronic removal of show-through using scans of both sides of the document. Experimental results demonstrating the effectiveness of the method developed are presented.
Design of power optimal, low phase noise three stage Current Starved VCO

This paper presents a method for designing of low power dissipation, low phase noise and high oscillation frequency based three stage Current Starved VCO (CS-VCO). In this design approach, 3-inverter stages are cascaded to achieve an optimal power dissipation of (7.48508 mW) for fundamental frequency of (3.9955 GHz). The simulation results depict that such VCO has linear voltage-frequency characteristics over a wide tuning range. The circuit performance is validated using 0.18μm CMOS technology. The analysis also shows that for 3-stage CS-VCO, the phase noise is -80.17dbc/Hz @1MHz offset frequency and -105.31dbc/Hz @10MHz offset frequency.
Demonstration of high quality and low loss millimeter wave passives on embedded wafer level packaging platform (EMWLP)

With the increasing demand for system integration to cater for continuously increasing I/Os as well as higher operating frequencies, EMWLP is emerging as a promising technology for integration. This platform allows integrated passives to be designed in the redistribution layers using the mold compound as a substrate, which significantly improves the passives performance compared to those of on-chip. In this paper, we present the results of high quality passives on EMWLP platform that are benchmarked against high resistivity silicon (HiRSi). The passives were then demonstrated in two band pass filters targeted to operate in the IEEE 802.11a band, with electrical performances comparable to that of commercial IPDs. Using the same platform, the measured loss characteristics of transmission lines up to 110 GHz is reported. We also demonstrate for the first time a low loss narrowband 77-GHz band pass filter on EMWLP platform, with a good correlation obtained between simulation and measurement results.
Probabilistic Methods for Improving Efficiency of RNA Secondary Structure Prediction across Multiple Sequences

Prediction of common secondary structure across multiple RNA sequences is known to significantly increase accuracy in comparison with single-sequence based prediction methods. However, the computational requirements for joint prediction can often be daunting in comparison to single-sequence prediction. As a result, heuristic simplifications are often necessary for this joint estimation problem in order to perform computations on current hardware in reasonable times. In this paper, principled heuristics are presented for the purpose of computation reduction based on probabilistic methods. The methods presented eliminate the computations over extremely improbable alignments and structures, thereby reducing computation with little or no degradation in accuracy. Experimental results over databases of RNA families with known secondary structure validate our methods, demonstrating over a two-fold computational speed up in tests over the 5 S rRNA family, without any compromise in accuracy.
Improved color barcodes via Expectation Maximization style interference cancellation

Encoding data independently in cyan, magenta, and yellow (CMY) print colorant channels with detection in complementary Red, green, and blue (RGB) image capture channels offers an attractive framework for extending monochrome barcodes to color with increased data rates. The undesired absorption of colorants in regions of spectral sensitivity of the noncomplementary capture channels, however, gives rise to cross-channel color interference that significantly deteriorates the performance of the color barcode system. In this paper, we propose an Expectation Maximization (EM) style algorithm to estimate and cancel this color interference and improve the overall performance of the barcode system. Our method utilizes a physical model for print-capture process where the model parameters vary depending on printer, capture device, and illumination. We estimate the model parameters using an iterative EM-style approach and obtain an estimate of CMY colorant channels from the scanned RGB barcode by using the estimated model parameters. Our experimental results show that the proposed method mitigates the effect of color interference and significantly reduces the bit error rates for the recovered data.
HazeRD: An outdoor scene dataset and benchmark for single image dehazing

In this paper, a new dataset, HazeRD, is proposed for benchmarking dehazing algorithms under more realistic haze conditions. HazeRD contains fifteen real outdoor scenes, for each of which five different weather conditions are simulated. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory. All images are of high resolution, typically six to eight megapixels. We test the performance of several state-of-the-art dehazing techniques on HazeRD. The results exhibit a significant difference among algorithms across the different datasets, reiterating the need for more realistic datasets such as ours and for more careful benchmarking of the methods.
UR-SolarCap: An Open Source Intelligent Auto-Wakeup Solar Energy Harvesting System for Supercapacitor-Based Energy Buffering

Energy harvesting systems that couple solar panels with supercapacitor buffers offer an attractive option for powering computational systems deployed in field settings, where power infrastructure is inaccessible. Supercapacitors offer a particularly compelling advantage over electrochemical batteries for such settings because of their ability to survive many more charge-discharge cycles. We share UR-SolarCap-a versatile open source design for such a harvesting system that targets embedded system applications requiring power in the 1-10 W range. Our system is designed for high efficiency and controllability and, importantly, supports auto-wakeup from a state of complete energy depletion. This paper summarizes our design methodology, and the rationale behind our design and configuration decisions. Results from the operation and testing of a system realized with our design demonstrate: 1) an achievable harvester efficiency of 85%; 2) the ability to maintain sustained operation over a two week period when the solar panel and buffer are sized appropriately; and 3) a robust auto-wakeup functionality that resumes system operation upon the availability of harvestable energy after a period in which the system has been forced into a dormant state because of a lack of usable energy. To facilitate the use of the system by researchers exploring embedded system applications in environments that lack a power infrastructure, our designs are available for download as an archive containing design schematics, Printed Circuit Board (PCB) files, firmware code, and a component list for assembly of the system. In addition, a limited number of pre-assembled kits are available upon request.