nils-herrmann/clean_scirepeval huggingface dataset:
Memory-Optimized Re-Gridding Architecture for Non-Uniform Fast Fourier Transform

This paper proposes a power-efficient and memory-optimized FPGA-based solution for the memory and compute-intense re-gridding process used in implementing Non-uniform Fast Fourier Transform (NuFFT) algorithm. Re-gridding refers to mapping non-equispaced sampled data onto a uniform grid using an interpolation kernel function. Re-gridding is the most time-consuming step in the entire NuFFT computation. The proposed solution is based on better utilization of FPGA resources and minimizing the number of accesses to the external memory. We demonstrate high performance over a wide range of configurations and data-sizes. This paper targets a generic solution to arbitrary sampling trajectories and gives trajectory specific solutions for some well-known trajectories in NuFFT applications, such as magnetic resonance imaging and synthetic aperture radar. Compared with existing solutions, throughput is improved by over 9.6 when compared with the existing FPGA-based techniques, whereas computational power efficiency (in terms of MFLOPS/Watt) is improved by over 15 times. Compared with GPU-based technique, 9.59 times higher MFLOPS per watts are achieved. The proposed architecture is implemented using hardware description language as well as high-level synthesis (HLS)-based OpenCL framework and the comparison is reported. Hence, this paper also serves as a reference for the comparison of HLS-based solutions against optimized HDLs. Accuracy of the re-gridding process is also reported in terms of signal-to-noise ratio.
Performance evaluation of various parameters of Network-on-Chip (NoC) for different topologies

Network-on-Chip (NoC) is a promising approach for reducing the communication bottleneck of multicore System-on-Chip (SoC). As the number of cores are increasing on SoC due to high performance demand of the consumer electronics and processing systems like servers, the low power and low latency NoC is required. Topologies are one of the most important part of a NoC design, with considering the performance parameter as a constraint. The important parameters of networks are latency, throughput, injection rate and hop counts etc. In this paper most popular topologies performance like mesh, torus, c-mesh, fattree, are evaluated based on the above mentioned parameters. The comparative evaluation of topologies will help to explore and understand various topologies in detail which will be helpful in further developing new topologies for NoC. Booksim 2.0 simulator is used for simulation results which are given in detail.
Study the effect of ozone layer depletion on aircraft design at atmospheric region of Pakistan

Ozone is of considerable importance to mankind because of its role as a shield for the biosphere against the Ultraviolet (UV) radiation from the outer space, in particular from the sun. Due to a serious reduction of O3 content in the atmosphere, life-forms on the earth are exposed to a new hazard in the form of an increase of harmful solar UV radiation intensity at the sea level. Atmospheric scientists started taking serious notice of the development of ozone hole in early 1980s. One of the damages is embrittlement in the aircraft that is caused by exposure to UV radiation. Ultraviolet exposure also causes electrical changes in the form of resistively modified and optically affected changes both thermal characteristics and opacity. A particularly UV-sensitive element is the solar array. More specifically the solar cell cover glass and its attendant adhesive are subject to darkening. This results in reduced cell illumination and an enhanced operating temperature both being deleterious (harmful or lethal) to cell operation. In this communication our goal is to enumerate the effects of ozone layer depletion that results in the penetration UV radiation so that the damage of the material of aircraft can be estimated. This estimation may be useful for the characterization of air craft operation from the earth and loss of the earth protection shield. This kind of study also helpful for aeronautical engineers to select proper aircraft materials.
Device-to-Device Networking Meets Cellular via Network Coding

Utilizing device-to-device (D2D) connections among mobile devices is promising to meet the increasing throughput demand over cellular links. In particular, when mobile devices are in close proximity of each other and are interested in the same content, D2D connections such as Wi-Fi Direct can be opportunistically used to construct a cooperative (and jointly operating) cellular and D2D networking system. However, it is crucial to understand, quantify, and exploit the potential of network coding for cooperating mobile devices in the joint cellular and D2D setup. In this paper, we consider this problem, and: 1) develop a network coding framework, namely NCMI, for cooperative mobile devices in the joint cellular and D2D setup, where cellular and D2D link capacities are the same; and 2) characterize the performance of the proposed network coding framework, where we use packet completion time, which is the number of transmission slots to recover all packets, as a performance metric. We demonstrate the benefits of our network coding framework through simulations.
On the choice of filter orders in subband coding

The use of subband image coding for intrafield coding (compression) of high-definition television (HDTV) signals has been studied. Filter banks with low-order filters that have simple coefficients are attractive for these applications due to the ease in implementation. The results of a limited study to evaluate the impact of the choice of filter orders in HDTV coding are discussed. The study shows that the interplay between the filters and the quantization either in the sample or in the transform domain is very critical in determining the quality of the reconstructed picture. Subband signals that are generated by a four-band subband decomposition using exact reconstruction infinite-impulse-response (IIR) filter banks were considered. A comparison of the quality of reconstruction with approximately linear-phase IIR filters of different orders was made. The work showed that for signals with large high-frequency content the use of low-order filters in the filter bank provides less noticeable degradation compared with that in the case of higher-order filter banks when the same quantization parameters are used.<<ETX>>
A framework to predict outcome for cancer patients using data from a nursing EHR

With the rapid growth of electronic data repositories in diverse application domains, including healthcare, considerable research interest has been developed to solve issues related to extraction of hidden knowledge in these repositories. Electronic health record systems (EHRs) are the fastest growing in terms of size and data diversity. In this work, we focus on mining a high dimensional sparse dataset using nursing care data as an exemplar. To mine a high-dimensional and sparse dataset is a challenging task due to a number of reasons. There are several dimension reduction methods, however, they do not work well with contextual datasets. In our study, we have used association mining as a dimension reduction step and for extracting important features from the dataset. Our results show that association mining can be effectively used for dimension reduction and feature extraction step. Our predictive modeling results show that decision tree models generally have high accuracy and the results are easy to interpret and determine the influence of different variables.
Scalable multimedia-content integrity verification with robust hashing

We propose a scalable, robust and recovery-driven multimedia content authentication system which exploits content-based robust hashing and watermark embedding to provide effective integrity verification of multimedia content. In addition, we propose providing content recovery by exploiting the collaborative decentralized nature of P2P networks. In this paper, we focus on the issues pertaining to the competing requirements of authentication robustness and tamper-detection accuracy. To this end, we describe a hierarchal hashing scheme that combines both fragile and robust features to generate a versatile watermark. We implement a representative image hashing that is robust to JPEG2000 compression and embedding distortion while being sensitive to tampering. Experimental results are presented to show the schemepsilas effectiveness.
Skies, future and curricula: Content of Astronomy and Space Sciences material in pre-University level courses Karachi

In all the eras of known human civilization, the role of Astronomy and Space Science has been dominant. The fate of human beings was so much associated with the blessings of the skies that such topics became essential part of myth, legend, religion, philosophy, poetry and science in all the ages. Divine on one hand and most earthly on the other, these topics acclaimed paramount at all theological, philosophical, scientific and academic forums. Most of the modern developments are indebted in one or the other way to the developments in these areas. Irrespective of the importance of Astronomy and Space Science as individual subjects, their role in the development of intellect and academic enhancement cannot be ignored. Because of this, in developed countries it is managed to make these subjects part of the curricula as independent subjects. Otherwise, selected topics from these areas are included in the curricula of other related subjects. As is the case with most of the underdeveloped countries of the world, curricula in Pakistan too are deficient in this regard. This is most true in particular, at the school and college levels.
Automated respiratory phase and onset detection using only chest sound signal

The problem of non-invasive detection of respiratory phases and onsets without making direct airflow measurement is addressed here. Currently available techniques require the use of multichannel recorded sounds of both chest and trachea. In this paper, we propose a method which detects both respiratory phases and onsets using only chest sound data. Prior signal information in both time and frequency from the chest sound is exploited to isolate the lung component of the sound and the quasi-periodicity of its short-term energy is used to develop a configuration of nonlinear filters and bandpass filters to estimate the respiratory phase onsets. Performance results for the proposed method are reported for the case of low and medium flow rates. The average onset localizing accuracy of the proposed method is shown to be comparable to that obtained with data from more than one recording channel.
Audio-visual affect recognition through multi-stream fused HMM for HCI

Advances in computer processing power and emerging algorithms are allowing new ways of envisioning human computer interaction. This paper focuses on the development of a computing algorithm that uses audio and visual sensors to detect and track a user's affective state to aid computer decision making. Using our multi-stream fused hidden Markov model (MFHMM), we analyzed coupled audio and visual streams to detect 11 cognitive/emotive states. The MFHMM allows the building of an optimal connection among multiple streams according to the maximum entropy principle and the maximum mutual information criterion. Person-independent experimental results from 20 subjects in 660 sequences show that the MFHMM approach performs with an accuracy of 80.61% which outperforms face-only HMM, pitch-only HMM, energy-only HMM, and independent HMM fusion.
A model of ion noise in microwave tubes

A hybrid model has been developed in which the electron beam is treated as a 2D fluid using the beam envelope equation, and the ions generated by beam ionization are treated as discrete particles in 1D. The effect of secondary electrons is neglected in the present analysis. The ionization rate depends on the ambient gas pressure and species as well as on the electron beam current and energy. Based on this rate, ions are created and distributed on an axial grid on each time step. The ion charge is then mapped onto the grid, and Poisson's equation is then solved in 1D under the assumption that the transverse scale lengths are less than the betatron wavelength of the electron beam. The ion charge distribution is then used to integrate the beam envelope equation that updates the beam equilibrium. The ion motion is then integrated subject to the wall potential, the space-charge potential of the electron beam, and the self-consistent ion potential. This process is iterated over any desired pulse time. The coupling between the ionization and the electron beam equilibrium introduce oscillations on many time scales. The fastest time scale oscillation is related to the bounce motion of ions in the axial potential wells formed by the scalloping of the electron beam. Slower oscillations are observed to correlate with the well-to-well interactions induced by the ion coupling to the electron equilibrium. These oscillations have observable effects on ion dumping to the cathode or collector. A specific example relating to ion noise in a coupled-cavity TWT is discussed.
Automated reading of DNA autoradiogram images using lane profiling methods

Automated DNA sequencing involves computer interpretation of the chemical detection data, which may be in the form of 2-D autoradiogram images, and 1- or 2-D fluorescence data. The analysis of autoradiogram images generated by the multiplex DNA sequencing method is considered. An overall approach to obtaining sequence data from the autoradiogram images is outlined, and specific approaches for segmenting the image into sets of four lanes, obtaining 1-D profiles of the lanes, detecting peaks in the 1-D profiles using a multiscale approach, and aligning profiles across lanes using an interpolation method are discussed. Intermediate results are presented.<<ETX>>
Achieving Non-Inclusive Cache Performance with Inclusive Caches: Temporal Locality Aware (TLA) Cache Management Policies

Inclusive caches are commonly used by processors to simplify cache coherence. However, the trade-off has been lower performance compared to non-inclusive and exclusive caches. Contrary to conventional wisdom, we show that the limited performance of inclusive caches is mostly due to inclusion victims—lines that are evicted from the core caches to satisfy the inclusion property—and not the reduced cache capacity of the hierarchy due to the duplication of data. These inclusion victims are incorrectly chosen for replacement because the last-level cache (LLC) is unaware of the temporal locality of lines in the core caches. We propose Temporal Locality Aware (TLA) cache management policies to allow an inclusive LLC to be aware of the temporal locality of lines in the core caches. We propose three TLA policies: Temporal Locality Hints (TLH), Early Core Invalidation (ECI), and Query Based Selection (QBS). All three policies improve inclusive cache performance without requiring any additional hardware structures. In fact, QBS performs similar to a non-inclusive cache hierarchy.
COM2 SiGe modular BiCMOS technology for digital, mixed-signal, and RF applications

The COM2 SiGe modular BiCMOS technology has been developed to allow efficient design and manufacturing of digital, mixed-signal, and RF integrated circuits, as well as enabling system-on-chip (SOC) integration. The technology is based on the 0.16 /spl mu/m COM2 digital CMOS process which features 1.5 V NMOS and PMOS transistors with 2.4 nm gate oxide, 0.135 /spl mu/m gate length, and up to 7 metal levels. Technology enhancement modules including dense SRAM, SiGe NPN bipolar transistor, and a variety of passive components have been developed to allow the COM2 technology to be cost-effectively optimized for a wide range of applications.
Defect suppression from the compound semiconductor heterointerfaces

We report on the effect of inserting ultra-thin InAs layers at the heterointerfaces on physical properties of GaAs/InGaP on GaAs and InP/GaAs on InP grown by MOCVD and MOMBE, respectively. It is shown that the insertion of ultra thin InAs layers at the heterostructure interfaces has a significant effect in eliminating defects from the interfaces.
Comprehensive Control for Microgrid Autonomous Operation With Demand Response

Several situations in a microgrid (MG) cause unbalances leading to voltage and frequency variations. Conventionally MG power balance is ensured by storage battery units along with unscheduled load shedding. This paper presents control and management strategies to coordinate MG resources including generation, smart electric vehicles, and loads for frequency and voltage regulation to achieve optimal autonomous operation. MG control is designed in two layers of network, i.e., neighbour area network (NAN) and house area network (HAN). MG central controller operates at NAN layer, local load controllers operate at HAN layer, and smart electric vehicle controllers operate at both NAN and HAN layers. Two strategies—comprehensive control (CC) and vehicle aided CC—are developed and implemented in 11/0.4 kV urban residential four-feeder distribution system operating as MG. Both strategies enable calculative load manipulation for demand response (DR) considering customer load priority, thus maximizing customer satisfaction. The simulation results validate the proposed strategies providing frequency regulation and DR for MG autonomous operation. The proposed control and management strategy also provides an on-line tool for household maximum demand allocation and load management.
Error Analysis in Stereo Determination of 3-D Point Positions

The relationship between the geometry of a stereo camera setup and the accuracy in obtaining three-dimensional position information is of great practical importance in many imaging applications. Assuming a point in a scene has been correctly identified in each image, its three-dimensional position can be recovered via a simple geometrical method known as triangulation. The probability that position estimates from triangulation are within some specified error tolerance is derived. An ideal pinhole camera model is used and the error is modeled as known spatial image plane quantization. A point's measured position maps to a small volume in 3-D determined by the finite resolution of the stereo setup. With the assumption that the point's actual position is uniformly distributed inside this volume, closed form expressions for the probability distribution of error in position along each coordinate direction (horizontal, vertical, and range) are derived. Following this, the probability that range error dominates over errors in the point's horizontal or vertical position is determined. It is hoped that the results presented will have an impact upon both sensor design and error modeling of position measuring systems for computer vision and related applications.
Cointegration of In Situ Doped Silicon–Carbon Source and Silicon–Carbon I-Region in P-Channel Silicon Nanowire Impact-Ionization Transistor

The p-channel impact-ionization nanowire multiple- gate field-effect transistors (I-MuGFETs or I-FinFETs), which have a multiple-gate/nanowire-channel architecture, were demonstrated. The superior gate-to-channel coupling reduces the breakdown voltage VBD for enhanced device performance. For the first time, an in situ doped source was incorporated with the impact-ionization MOS transistor. The in situ phosphorus-doped Si source with improved dopant activation and very abrupt junction profile reduces VBD and enhances the on-state current Ion. An additional improvement was also achieved by incorporating a strained Si1-yCy impact-ionization region (I-region) and an in situ doped Si1-yCy source, leading to reduction in Vbd and enhancement in Ion. This is due to strain-induced reduction of the impact-ionization threshold energy Eth. Furthermore, an excellent subthreshold swing of below 3 mV/decade at room temperature was achieved for all devices.
Efficient sparse representation based image super resolution via dual dictionary learning

Super resolution is of great use in many visual media related scenarios, such as displaying low resolution contents on High-Definition TV(HD-TV). In these scenarios, the efficiency of the super resolution process is of vital importance. This paper presents a fast learning based super-resolution method. The proposed method speeds up the sparse representation based super-resolution method by learning a dual dictionary, and replaces the sparse recovery step by simple matrix multiplication, which is much more computationally efficient. Experiments demonstrate that the proposed method can generate desirable super-resolved images with significant computational advantages.
Compressive energy detection for blind coarse wideband sensing: Comparative performance study

Wideband signal acquisition and spectrum sensing play a crucial role in a number of applications. In this work we discuss the task of blind spectrum sensing of frequency-sparse wideband signals sampled at sub-Nyquist rates. We show how in a generic sub-Nyquist sampling framework the results of the support recovery can be directly used for coarse multichannel energy detection. We numerically study the performance of the proposed compressive energy detector and compare it with that of the related approaches. Our results demonstrate that it outperforms its closest counterpart that operates on the recovered power spectral density and provides a comparable performance to the Nyquist-rate energy detector in the high SNRs.
Automatic Video Annotation by Mining Speech Transcripts

We describe a model for automatic prediction of text annotations for video data. The speech transcripts of videos, are clustered using an aspect model and keywords are extracted based on aspect distribution. Thus we capture the semantic information available in the video data. This technique for automatic keyword vocabulary construction makes the labelling of video data a very easy task. We then build a video shot vocabulary by utilizing both static images and motion cues. We use a maximum entropy criterion to learn the conditional exponential model by defining constraint features over the shot vocabulary, keyword vocabulary combinations. Our method uses a maximum a posteriori estimate of exponential model to predict the annotations. We evaluate the ability of our model to predict annotations, in terms of mean negative log-likelihood and retrieval performance on the test set. A comparison of exponential model with baseline methods indicates that the results are encouraging.
A battery-free multi-channel digital neural/EMG telemetry system for flying insects

Most recently reported multi-channel wireless neural telemetry systems are not suitable for studying insects in flight because of mass and battery limitations. We present preliminary results toward the development of a digital neural/EMG telemetry system with a measured flight package mass of only 38 mg. This system includes a single-chip telemetry system employing RF power harvesting for battery-free operation, with communication via modulated backscatter in the UHF (902–928 MHz) band. An on-chip 11-bit ADC digitizes 10 neural channels with a sampling rate of 26.1 kSps and 4 EMG channels at 1.63 kSps. We also present a companion base station transceiver including an RF transmitter of +36 dBm (4 W) output power to wirelessly power the IC, and a digital receiver with a threshold sensitivity of −70 dBm for 10−5 BER at 5.0 Mbps to receive the data stream. The chip was fabricated in a commercial 0.35 µm 4M1P (4 metal, 1 poly) CMOS process. The die measures 2.36 × 1.88 mm, and is 250 µm thick. Measurements to date indicate that the chip is fully functional as designed.