nils-herrmann/clean_scirepeval huggingface dataset:
A Quality-of-Experience Database for Adaptive Video Streaming

The dynamic adaptive streaming over HTTP provides an inter-operable solution to overcome the volatile network conditions, but its complex characteristic brings new challenges to objective video quality-of-experience (QoE) measurement. To test the generalizability and to facilitate the wide usage of QoE measurement techniques in real-world applications, we establish a new database named Waterloo Streaming QoE Database III (SQoE-III). Unlike existing databases constructed with hand-crafted test sequences, the SQoE-III database, so far the largest and most realistic of its kind, consists of a total of 450 streaming videos created from diverse source content and diverse distortion patterns, with six adaptation algorithms of diverse characteristics under 13 representative network conditions. All streaming videos are assessed by 34 subjects, and a comprehensive evaluation is conducted on the performance of 15 objective QoE models from four categories with regards to their efficacy in predicting subjective QoE. Detailed correlation analysis and statistical hypothesis testing are carried out. The results of this paper shed light on the future development of adaptive bitrate streaming algorithm and video QoE monitoring system. The subjective database is available online at
SSIM-Motivated Two-Pass VBR Coding for HEVC

We propose a structural similarity (SSIM)-motivated two-pass variable bit rate control algorithm for High Efficiency Video Coding. Given a bit rate budget, the available bits are optimally allocated at group of pictures (GoP), frame, and coding unit (CU) levels by hierarchically constructing a perceptually uniform space with an SSIM-inspired divisive normalization mechanism. The Lagrange multiplier <inline-formula> <tex-math notation="LaTeX">$\lambda$ </tex-math></inline-formula>, which controls the tradeoff between perceptual distortion and bit rate, is adopted as the GoP level complexity measure. To derive <inline-formula> <tex-math notation="LaTeX">$\lambda$ </tex-math></inline-formula>, Laplacian distribution-based rate and perceptual distortion models are established after the first pass encoding, and the target bits are dynamically allocated by maintaining a uniform Lagrange multiplier level for each GoP through <inline-formula> <tex-math notation="LaTeX">$\lambda$ </tex-math></inline-formula> equalization. Within each GoP, rate control is further performed at frame and CU levels based on SSIM-inspired divisive normalization, aiming to transform the prediction residuals into a perceptually uniform space. Experiments show that the proposed scheme achieves high accuracy rate control and superior rate-SSIM performance, which is further verified by subjective visual testing.
CW-SSIM based image classification

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a promising image similarity measure that is robust to small geometric distortions such as translation, scaling and rotation of images, but how to make the best use of it in image classification problems has not been deeply investigated. In this paper, we propose a novel “feature-extraction free” image classification algorithm based on CW-SSIM and use handwritten digit recognition as an example to demonstrate it. First, a CW-SSIM based unsupervised clustering method is used to divide the training images into clusters and to pick a representative image for each cluster. A supervised learning method based on support vector machines is then employed to maximize the classification accuracy based on CW-SSIM values between an input image and the representative images. Our experiments show that such a conceptually simple image classification method, which does not involve any registration, intensity normalization or sophisticated feature extraction processes, and does not rely on any modeling of the image patterns or distortion processes, achieves competitive performance with reduced computational complexity.
Design of a new type of broadband antenna with indoor distribution

Based on the principle of discone antenna, a new type of broadband omnidirectional antenna is presented. According to antenna loading technology, introducing the cone surface profile of the broken line structure and short-circuit load of ways which use three short-circuit branches improve the low-frequency electrical characteristics of the antenna and the bandwidth. A very good miniaturization is achieved which reduces the total size. The physical antenna is produced. The calculated and measured VSWR patterns seem to be in good agreement with each other. The VSWR is less than 1.5 at 800MHz-2600MHz. H plane has an ominidirectional radiation pattern. As to small size and low cost, it will have good market prospects.
A linear programming method for interval-valued intuitionistic fuzzy multiattribute group decision making

Multiattribute group decision making (MAGDM) problems often involve both quantitative and qualitative attributes, where assessment values are expressed as imprecise data. This paper entertains interval-valued intuitionistic fuzzy sets (IVIFSs) to characterize fuzziness and uncertainty contained in imprecise decision data and processes such as subjective factors of linguistic terms and satisfaction degrees for decision-makers (DMs). Group consistency and inconsistency indices are defined based on pairwise comparison preference relations with respect to alternatives provided by the DMs. An auxiliary linear program is proposed for deriving the interval-valued intuitionistic fuzzy positive ideal solution (IVIFPIS) and weights. The distance of each alternative to the IVIFPIS is calculated to determine the ranking for all alternatives. An illustrative example is provided to demonstrate the applicability and effectiveness of this method.
Adaptive QRD-M detection with variable number of surviving paths for MIMO systems

The QR decomposition based M algorithm (QRD-M) is a sub-optimal detection algorithm which can achieve a tradeoff between bit error rate (BER) performance and computational complexity for multiple input multiple output (MIMO) systems. In this paper, an adaptive QRD-M algorithm with variable number of surviving paths is proposed for MIMO systems. The number of surviving paths at each detection stage is adaptively determined according to the instantaneous value and the statistics of channel conditions. The required statistics of the channel conditions is directly derived and given in closed form without a large number of training observations. The proposed algorithm is simple to implement and it is verified by computer simulations that the proposed algorithm has lower computational complexity than the fixed QRD-M algorithms thus can offer a better tradeoff between BER performance and computational complexity.
Adaptive dynamic surface controller design of variable-speed pump controlled motor system with parametric uncertainties

The constant speed control of variable speed pump controlled motor system is discussed in this paper. A dynamic surface controller is chosen to improve robustness of motor speed when rotational speed of variable pump is time-varying. In the presence of bounded parametric uncertainties, an adaptive control scheme with parameter estimation is presented. Load torque used in dynamic surface controller is observed via reduced order observer. The simulation results show that the proposed control scheme is robust to bounded parametric uncertainties. Adaptive dynamic surface control has a better rejection performance of pump speed variation and load torque disturbance than PID control.
Crosstalk-Free Integral Imaging Display With Wide Viewing Angle Using Periodic Black Mask

Two of the main limitations of integral imaging are the crosstalk and the narrow viewing angle. In this paper, a crosstalk free integral imaging display with wide viewing angle is proposed. A layer of transparent high refractive index packing medium is padded onto a display panel to enhance the viewing angle, and then a periodic black mask is coated on the top surface of the medium layer to avoid the crosstalk and image flipping. The proposed integral imaging display can provide us with crosstalk free 3D images within a wide viewing angle. Experiments are carried out and good results finally verify the feasibility of the proposed method.
Segmentation of the left ventricle in short-axis sequences by combining deformation flow and optical flow

To help the clinicians to segment the borders of the left ventricle (LV) efficiently during measurement of the heart, the authors come up with a semi-automatic approach in this study that is capable of identifying the endocardial borders robustly from cine magnetic resonance images. Firstly, the deformation flow is computed between the inputted boundary in the previous frame and the extracted edge of the LV in the current frame based on boundary minimum distance principle (BMDP). Then, the deformation flow is constrained by optical flow calculated by a partial differential equation model. A smooth deformation boundary is then formed by minimising the energy between the previously inputted boundary and the rough boundary obtained by BMDP and optical flow constraint. To extract edge of the LV as accurate as possible, a threshold selection method is used and improved based on the previous study. The proposed approach is tested on the open access dataset. The computed average perpendicular distance is 1.36 ± 0.24 mm and the computed Dice measure is 90.7% ± 0.15%. Experimental results show that the proposed approach is significantly more accurate than the referenced state of art methods.
A New Approach for Segmentation and Quantification of Cells or Nanoparticles

With the rapid development of microscopy imaging technology, the requirement for robust segmentation and quantification of cells or nanoparticles increases greatly. It remains challenging due to the diversity of the cell or nanoparticle types, the arbitrary shapes, and the large numbers of cells or nanoparticles. The most existing methods are only capable of segmenting some specific types of cells or nanoparticles. In this paper, we propose a more versatile approach that is capable of segmenting a variety of cells or nanoparticles. It consists of five parts: 1) automatic gradient image formation; 2) automatic threshold selection; 3) manual calibration of the threshold selection method for each specific type of cell or nanoparticle images; 4) manual determination of the segmentation cases for each specific type of cell or nanoparticle images; and 5) automatic quantification by iterative morphological erosion. After the parameter, N is calibrated and the segmentation case is determined manually for each specific type of cell or nanoparticle images with one or several typical images; only parts 1), 2), and 5) are needed for the rest of processing and they are automatic. The proposed approach is tested with different types of cell and nanoparticle images. Experimental results verified its effectiveness.
Electricity Demand Forecasting Based on Feedforward Neural Network Training by a Novel Hybrid Evolutionary Algorithm

Electricity demand forecasting is an important index to make power development plan and dispatch the loading of generating units in order to meet system demand. In order to improve the accuracy of the forecasting, we apply the feedforward neural network for electricity demand forecasting. Inspired by the idea of Artificial Fish Swarm Algorithm, in this paper we proposed one hybrid evolutionary algorithm which based on PSO and AFSA methods through crossing over the PSO and AFSA algorithms to train the feedforward neural network. This proposed method has been applied in a real electricity load forecasting, the results show that the proposed approach has a better generalization performance and is also more accurate and effective than the feedforward neural network trained by particle swarm optimization.
New progress in deriving cloudy-sky land surface longwave radiation based on multiple remotely sensed data

Land surface longwave (LW) radiation (or longwave radiative flux), including longwave upwelling (LWUR), downward (LWDR) and net radiation (LWNR), are key components of the total energy that drives the surface energy balance at the interface between the earth's surface and the atmosphere. The importance of LW radiation in regulating air temperature and balancing surface energy is enlarged especially under cloudy-sky conditions. Unfortunately, to date, a tremendous attempts have been made to derive LW radiation from space only valid under clear-sky conditions leading to difficulty of utility of remote sensing-based LW radiation products in most land models due to their spatial discontinuity. Although few studies focused on LW radiation estimation under cloudy-sky conditions, while their global application are still problematic. In this paper, novel strategies are proposed aiming to derive high resolution cloudy-sky LWDR and LWUR by fusing collocated optical and microwave satellite data. The results reveal that the new approaches work rather well, thus, more importantly, providing unprecedented possibilities for generating high resolution global LW radiation datasets.
Uplink Spectral Efficiency Analysis of In-Building Distributed Antenna Systems

Providing high data rate wireless transmissions has been difficult in indoor environments, particularly in multi-floor buildings. One way to achieve high data rate wireless transmissions is to reduce the radio transmission distance between the transmitter and the receiver by using distributed antenna systems (DASs) and employing frequency reuse. However, due to the reuse of the limited available spectrum, co-channel interference can severely degrade system capacity. In this paper, the uplink spectral efficiency of an in-building DAS with frequency reuse is studied, where remote antenna units (RAUs) deployed on each floor throughout the building are connected to a central unit (CU) where received signals are processed. The impact of co-channel interference on system performance is investigated by using a propagation channel model derived from multi-floor, in-building measurement results. The proposed scheme exploits the penetration loss of the signal through the floors, resulting in frequency reuse in spatially separated floors, which increases system spectral efficiency and also reduces co-channel interference. A comparative analysis with conventional co-located antenna deployment at the floor center is provided. Location based RAU selection and deployment options are investigated. System performance is evaluated in terms of location-specific spectral efficiency for a range of potential mobile terminal (MT) locations and various in-building propagation characteristics.
No-reference perceptual quality assessment of JPEG compressed images

Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available. This research aims to develop NR quality measurement algorithms for JPEG compressed images. First, we established a JPEG image database and subjective experiments were conducted on the database. We show that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality. Therefore, tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics. Furthermore, we propose a computational and memory efficient NR quality assessment model for JPEG images. Subjective test results are used to train the model, which achieves good quality prediction performance.
Packet retransmission using frequency diversity in OFDMA

In orthogonal frequency division multiple access (OFDMA) systems, efficient resource allocation is very important to improve the performance of the OFDMA system. The general principle of resource allocation in an OFDMA system is to assign each subcarrier to the user with the best channel condition for that subcarrier. However, in delay tolerant traffic, current work did not consider that packets on retransmissions may have different allocation criteria from those on their first transmissions. In this paper, the resource allocation scheme is investigated by considering different criterions to packets on first transmissions and on retransmissions. Under a bit error rate (BER) constraint, the objective is to maximize the throughput of packets on first transmissions, meanwhile decreasing the longest packet delay caused by retransmitted packets and guaranteeing all packets on retransmissions to be sent out. A low-complexity suboptimal algorithm that separates allocation for packets on retransmissions and on first transmissions is proposed. Adaptive modulation scheme is adopted to guarantee the BER constraint, except the modulation for each retransmitted packet remains the same. In order to improve retransmission liability, the retransmitted packets are combined with its failed packets in previous transmission.
Simultaneous imaging and measurement of weld pool surface and metal transfer from weld pool reflected laser lines

Precision control of gas metal arc welding process requires both weld pool surface and developed/detached droplet be simultaneously measured from the same sensor. To this end, laser lines are projected onto the weld pool surface and the reflected laser lines are intercepted and imaged. It is found from the images that the reflected laser lines are intercepted periodically by the droplets. While this interception adds complexity to the clustering of laser lines but it also provides sources to simultaneously detect the geometry of the droplet. This paper aims at extracting the laser lines from images that contain the reflected laser lines and extracting the droplet from the interception points. Experimental results verified the effectiveness of both the proposed image processing algorithms and modelling methods. Since the weld pool surface and droplet are extracted from the same image, a method thus has been developed to simultaneously image and measure the weld pool surface and metal transfer process.
Perceptual quality assessment of HDR deghosting algorithms

High dynamic range (HDR) imaging techniques aim to extend the dynamic range of images that cannot be well captured using conventional camera sensors. A common practice is to take a stack of pictures with different exposure levels and fuse them to produce a final image with more details. However, a small displacement between images caused by either camera or scene motion would void the benefits and cause the so-called ghosting artifacts. Over the past decade, many HDR deghosting algorithms have been proposed, but little work has been dedicated to evaluate HDR deghosting results either subjectively or objectively. In this work, we present a comprehensive subjective study for HDR deghosting. Specifically, we create a database that contains 20 dynamic image sequences and their corresponding deghosting results by 9 deghosting algorithms. A subjective user study is then carried out to evaluate the perceptual quality of deghosted images. The experimental results demonstrate the performance and limitations of existing HDR deghosting algorithm as well as no-reference image quality assessment models. In the future, we will make the database available to the public.
Performance of a Two-hop Non-regenerative Wireless Relaying System Employing Distributed LDC

In order to combat multipath fading in the wireless networks and increase the system capacity, the idea of space-time coding devised for multiple antenna systems is applied to the two-hop non-regenerative (NR) relaying system. The proposed cooperative relaying system (CRS) is based on two-hop protocol, in the 1st hop the transmitter encodes original information into distributed linear dispersion codes (LDC) and in the 2nd hop, the relaying nodes amplify the received signals and forward them to the receiver. Besides the capacity analysis of two-hop NR relaying system in the presence of LDC, we present some conditions based on maximum LDC capacity to optimize the proposed CRS performance. Theoretic analysis and numeric results show that the proposed CRS performance not only outperforms that of earlier proposed methods, but also obtains the maximum channel capacity
Lifted-Rollout for Approximate Policy Iteration of Markov Decision Process

Sampling-based approximate policy iteration, which samples (or "rollout") the current policy and find improvement from the samples, is an efficient and practical approach for solving policies in Markov decision process. Such an approach, however, suffers from the inherent variance of sampling. In this paper, we propose the lifted-rollout approach. This approach models the decision process using a directed a cyclic graph and then lifts the possibly huge graph by compressing similar nodes. Finally the approximate policy is obtained by inference on the lifted graph. Experiments show that our approach avoids the sampling variance and achieves significantly better performance.
Multiple hops/symbol FFH-SSMA with MFSK modulation and Reed-Solomon coding for indoor radio

A multiple-hopes-per-symbol fast-frequency-hopped spread-spectrum multiple-access (FFH-SSMA) system for indoor radio communication is treated. The data are Reed-Solomon (RS) encoded and then modulate a carrier by means of M-ary frequency-shift-keying (MFSK) The indoor radio channel is described as a multipath (Rayleigh or Rician) slowly fading channel. The receiver uses predetection diversity by linearly combining the squared enveloped of the different hops of the same MFSK symbol. The bit error rate (BER) performane is evaluated, and how the performance is influenced by various parameters, such as the number of hops per symbol, the size of the symbol alphabet, the ratio of specular power to fading power, and the ratio of nonreference user power to reference user power, is investigated.
Downlink Transmission of Broadband OFCDM Systems-Part V: Code Assignment

To provide high speed mobile services, orthogonal multi-code transmission is employed in the orthogonal frequency and code division multiplexing (OFCDM) system. However, in a wireless frequency selective channel either with or without Doppler shift, code orthogonality is distorted and multi-code interference (MCI) is caused. The variance of the MCI is dependent on which codes to be used. This paper investigates the code assignment in the OFCDM system, aiming to mitigate the MCI. The code assignment can be explored in terms of the code distance defined in this paper. Generally, the codes with large code distances to each other should be assigned with high priority. Moreover, to avoid large interference from the powerful code-multiplexed pilot channel, the time spreading code adjacent to the pilot code in the code tree (Adachi et al., 1998) is suggested not be used when the time domain spreading factor is large. The performance of the proposed non-sequential code assignment scheme is analytically evaluated. It has been shown that the system performance can be improved significantly by the non-sequential scheme under various channel conditions, especially when a low to medium system load is assumed.