nils-herrmann/clean_scirepeval huggingface dataset:
Effect of channel-estimation error on QAM systems with antenna diversity

This paper studies the effect of channel estimation error and antenna diversity on multilevel quadrature amplitude modulation (M-QAM) systems over Rayleigh fading channels. Based on the characteristic function method, a general closed-form bit-error rate (BER) for M-QAM systems is presented. The effect of the inaccurate channel estimation on the performance for pilot-symbol-assisted modulation M-QAM systems with antenna diversity is investigated. Simulation results for M-QAM (M = 4, 16, 64, 256, etc.) show that the analytical method can accurately estimate the system performance. Moreover, numerical results show that with the antenna-diversity technique, the BER performance improves significantly, especially in perfect channel-estimation cases. It is also found that the channel-estimation error limits the benefit of antenna diversity. By increasing the length of the channel estimator and the amplitude of the pilot symbol, more accurate channel estimation can be achieved, so that the BER performance is improved.
OFCDM - A promising wireless multiple access technique for 4G mobile communications

Future mobile communication systems aim to provide extremely high speed data transmission, especially in downlink. The broadband orthogonal frequency and code division multiplexing (OFCDM) system with two-dimensional spreading (time and frequency domain spreading) is becoming a very promising technique for high speed wireless communications due to its advantages over OFDM. This talk presents the features, basic structure and main functions of the OFCDM system. It will be shown that the OFCDM is superior to OFDM. (11 pages)
Perceptual screen content image quality assessment and compression

Compression of screen content has recently emerged as an active research topic due to the increasing demand in many applications such as wireless display and virtual desktop infrastructure. Screen content images (SCIs) exhibit different statistical properties in textual and pictorial regions, and the human visual system (HVS) also behaves differently when viewing the textual and pictorial regions in terms of the extent of visual field. Here we propose a perceptual SCI quality assessment approach that incorporates visual field adaptation and information content weighting. Furthermore, we propose a perceptual coding scheme in an attempt to optimize the HEVC Screen Content Coding encoder. Experimental results show that the proposed quality assessment method not only better predicts the perceptual quality of SCIs, but also leads to an effective way to optimize screen content coding schemes.
Generic interface architecture supporting cognitive resource management in future wireless networks

The proliferation of different wireless technologies has led to fragmentation of interfaces and APIs that are used to control and manage air interfaces and wireless links. The emergence of new networking and application concepts that support increasingly heterogeneous access methods, especially when combined with future cognitive radio technologies, significantly increase the already high complexity of development projects and software architectures. Dissimilar wireless interfaces also complicate the development of middleware components for higher layers of the protocol stack. In this article we present a new generic interface and API architecture that has been developed and prototyped in several different wireless platforms to address these problems. We introduce the basic framework of the architecture, and explain how generic and open interfaces can significantly lower development and deployment costs. The developed interface architecture can be seen as a lower level middleware, or as an enabling technology to implement different technology transparent network middlewares. We also briefly comment about prototyping and standardization status of technology.
Perceptual aliasing factors and the impact of frame rate on video quality

High frame rate (HFR) videos have become increasingly popular in the past few years, and frame rate is one of the major parameters for adjusting video data rate in real-world video delivery services. To achieve the best trade-off between bandwidth saving and video quality preservation by way of frame rate adaptation, it is essential to understand the impact of frame rate on video quality. In this work, we look at the problem from the viewpoint of perceptual information loss by perceptual aliasing analysis. We propose several measures, namely temporal aliasing power, temporal aliasing factor, spatiotemporal aliasing factor, and perceptual spatiotemporal aliasing factor, and use them as quality predictors for videos under frame rate changes. We also construct a database and conduct a subjective test on videos of different frame rates. Our results suggest great potentials of the proposed perceptual aliasing analysis approach.
On the Mathematical Properties of the Structural Similarity Index

Since its introduction in 2004, the structural similarity (SSIM) index has gained widespread popularity as a tool to assess the quality of images and to evaluate the performance of image processing algorithms and systems. There has been also a growing interest of using SSIM as an objective function in optimization problems in a variety of image processing applications. One major issue that could strongly impede the progress of such efforts is the lack of understanding of the mathematical properties of the SSIM measure. For example, some highly desirable properties such as convexity and triangular inequality that are possessed by the mean squared error may not hold. In this paper, we first construct a series of normalized and generalized (vector-valued) metrics based on the important ingredients of SSIM. We then show that such modified measures are valid distance metrics and have many useful properties, among which the most significant ones include quasi-convexity, a region of convexity around the minimizer, and distance preservation under orthogonal or unitary transformations. The groundwork laid here extends the potentials of SSIM in both theoretical development and practical applications.
Temporal motion smoothness measurement for reduced-reference video quality assessment

Reduced-reference (RR) video quality measures aim to predict the perceptual quality of distorted video signals using only partial information about the reference video. Existing RR video quality assessment models are mostly designed and/or trained for specific applications such as lossy compression, where the detectable distortion types are often fixed and limited. Here we propose a novel approach that measures temporal motion smoothness of a video sequence by examining the temporal variations of local phase structures in the complex wavelet transform domain. We show that the proposed measure can detect a wide range of well-known practical distortions, including noise contamination, blurring, line or frame jittering, and frame dropping. In addition, the proposed algorithm does not require a costly motion estimation process and has a low RR data rate, making it much easier to be adopted in real-world visual communication applications.
Optimal power control and opportunistic fair scheduling in TH-PPM UWB ad-hoc multimedia networks

*  Yang Liu;  This research was supported by a grant from the Research Grants Council of the HKSAR under project number HKU7157/04E. Abstract—Ultra wideband (UWB) systems are widely envisioned to be the next important wireless infrastructure for efficient short-range communications and mobile applications. Indeed, forming ad hoc networks among various UWB enabled devices is considered as an important mobile data exchange operating environment. In our study, we explore the problem of jointly optimizing the power level and data rate used in the devices in such a UWB based ad hoc network. We propose a practical optimization scheme and decompose the optimization problem into power control for real-time applications and opportunistic scheduling for non-real-time applications. Efficient optimization algorithms are designed to meet different fairness requirements and numerical results are obtained.
A Heuristic Algorithm for the Container Loading Problem with Heterogeneous Boxes

The container loading problem (CLP) is notoriously known to be NP-hard, an intrinsically difficult problem that is too complex to be solved in polynomial time on a system of serial computers. Heuristic algorithms are often the only viable option to tackle this type of combinatorial optimization problems. This article puts forward a heuristic algorithm based on a tertiary tree model to handle the CLP with heterogeneous rectangular boxes. A dynamic spatial decomposition method is employed to partition the unfilled container space after a group of homogeneous boxes is loaded into the container. This decomposition approach, together with an optimal-fitting sequencing rule and an inner-left-corner-occupying placement rule, permits a holistic filling strategy to pack a container. A comparative study with existing algorithms and an illustrative example demonstrate the efficiency of this heuristic algorithm.
The use of delay-locked loop signals in DS/CDMA receiver for multiple-access interference reduction

This paper presents a coherent demodulation scheme that reduces the multiple-access interference (MAI) considerably in a band-limited direct-sequence code-division multiple-access system. The despreading signal is obtained from a combination of the conventional despreading signal and its weighted early and late versions that are used in the delay-locked loop (DLL). It is shown that with appropriate choice of the weighting parameter of the early-late signals of the DLL, the signal-to-interference-plus-noise ratio of the decision variable is increased, which leads to improvement in the bit-error performance and hence the potential increase in the system capacity by about 25%. The analyses are performed in the frequency domain. The effect of imperfect synchronization on the system performance is also analyzed
A novel approach for reduction of blocking effects in low-bit-rate image compression

In this letter we propose a new approach for removing blocking artifacts in reconstructed block-encoded images. The key of the approach is using piecewise similarity within different parts of the image as a priori to give reasonable modifications to the block boundary pixels. This makes our approach different from traditional ones, which are often developed by applying some kinds of smoothing constraints on local regions. Experimental results show that our approach well achieves enhanced decoding for JPEG-decoded images both objectively and subjectively.
An improved new approach for electric capacity forecasting based on historical data of GDP

Prediction is important for the electricity capacity management. Accurate prediction can help the policymaker make correct decision and promote the decision making quality. For improving an accuracy of prediction, in this paper, we adopt the theory of grey prediction to develop a new forecasting approach that integrates historical data of the gross domestic products (GDP) into an electric capacity forecasting. We adopted grey prediction as a forecasting means because of its fast calculation with as few as four data inputs needed. As a result, our study considered that Wu and Chen proposed a modeling method of the improved grey relational analysis and main shows that the general grey model, GM (1,1), which is an especial case, is adequate to handle an electrical power system. In this study, the prediction is improved significantly by applying the transformed Grey model and the concept of average system slope. The adaptive value of a in the Grey differential equation is obtained quickly with the average system slope technique. In such a way, the wastage of electric consumption can be avoided. That is, it is another achievement of virtual electric power plant.
Short-Term Electricity Price Forecasting Based on Novel SVM Using Artificial Fish Swarm Algorithm under Deregulated Power

In the competition paradigm of the electric power markets, both power producers and consumers need some price prediction tools in order to plan their bidding strategies. This paper studies the problem of modeling market clearing price forecasting in deregulated markets. And electricity price forecasting with support vector machines based on artificial fish swarm algorithm is provided. Except considering market clearing price (MCP) price influential factors such as previous competitive load, making-up price, competitive generating capacity etc, the past price data have been included as attributes in input parameters. Based on these influential factors, a novel optimization support vector regression (OSVR) forecasting model is presented. The proposed algorithm is more robust and reliable as compared to traditional approach and neural networks. The effectiveness of the proposed model is demonstrated with actual data taken from the Australia Power Grid, and the actual data are compared with the presented and neural networks methods.
Spatial Pooling Strategies for Perceptual Image Quality Assessment

Many recently proposed perceptual image quality assessment algorithms are implemented in two stages. In the first stage, image quality is evaluated within local regions. This results in a quality/distortion map over the image space. In the second stage, a spatial pooling algorithm is employed that combines the quality/distortion map into a single quality score. While great effort has been devoted to developing algorithms for the first stage, little has been done to find the best strategies for the second stage (and simple spatial average is often used). In this work, we investigate three spatial pooling methods for the second stage: Minkowski pooling, local quality/distortion-weighted pooling, and information content-weighted pooling. Extensive experiments with the LIVE database show that all three methods may improve the prediction performance of perceptual image quality measures, but the third method demonstrates the best potential to be a general and robust method that leads to consistent improvement over a wide range of image distortion types.
Analysis in start-up performance of SRM based on direct instantaneous torque control

The structure of Switched Reluctance Motor is simple, high reliability and efficiency and excellent speed adjusting performance, thus paid widespread attention in recent years. But its unique double salient poles structure leads to serious torque ripple. Especially in Starting Process of the motor torque ripple is particularly evident, The thesis applies direct instantaneous torque control in Starting Process of SRM. And compare with the current chopping control. The results show that the direct instantaneous torque control to achieve minimum torque control.
Distributed antenna system based frequency switch scheme evaluation for high-speed railways

High-speed railway (HSR) has witnessed a huge growth globally, and now is reaching a maximum speed of 575 km/h. This record of speed makes mobile communications difficult for HSR since the handover (HO) frequency increases which results in a high loss of connectivity. Based on distributed antenna systems (DASs), this paper utilizes the two-hop network architecture for HSR broadband wireless communication systems. With the target of achieving high system capacity, superior transmission reliability, and consequently high-quality broadband wireless communication service for passengers in HSR. Moreover, a Frequency Switch (FSW) scheme is proposed for the two-hop network architecture to alleviate the frequent HO issue in traditional HSR wireless communication systems where HO generally happens between the successive remote antenna units (RAUs) connecting to the same central unit (CU) control. The FSW scheme provides mobility robustness signalling process that guarantees a successful frequency switching instead of HO, and reduces the probability of radio link failure (RLF) compared to HO process in traditional HSR systems, where the HO failure (HOF) rate is about 21%. The analytical results show that the proposed scheme outperforms traditional HO schemes.
Perceptual Depth Quality in Distorted Stereoscopic Images

Subjective and objective measurement of the perceptual quality of depth information in symmetrically and asymmetrically distorted stereoscopic images is a fundamentally important issue in stereoscopic 3D imaging that has not been deeply investigated. Here, we first carry out a subjective test following the traditional absolute category rating protocol widely used in general image quality assessment research. We find this approach problematic, because monocular cues and the spatial quality of images have strong impact on the depth quality scores given by subjects, making it difficult to single out the actual contributions of stereoscopic cues in depth perception. To overcome this problem, we carry out a novel subjective study where depth effect is synthesized at different depth levels before various types and levels of symmetric and asymmetric distortions are applied. Instead of following the traditional approach, we ask subjects to identify and label depth polarizations, and a depth perception difficulty index (DPDI) is developed based on the percentage of correct and incorrect subject judgements. We find this approach highly effective at quantifying depth perception induced by stereo cues and observe a number of interesting effects regarding image content dependency, distortion-type dependence, and the impact of symmetric versus asymmetric distortions. Furthermore, we propose a novel computational model for DPDI prediction. Our results show that the proposed model, without explicitly identifying image distortion types, leads to highly promising DPDI prediction performance. We believe that these are useful steps toward building a comprehensive understanding on 3D quality-of-experience of stereoscopic images.
Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization

We propose a perceptual video coding framework based on the divisive normalization scheme, which is found to be an effective approach to model the perceptual sensitivity of biological vision, but has not been fully exploited in the context of video coding. At the macroblock (MB) level, we derive the normalization factors based on the structural similarity (SSIM) index as an attempt to transform the discrete cosine transform domain frame residuals to a perceptually uniform space. We further develop an MB level perceptual mode selection scheme and a frame level global quantization matrix optimization method. Extensive simulations and subjective tests verify that, compared with the H.264/AVC video coding standard, the proposed method can achieve significant gain in terms of rate-SSIM performance and provide better visual quality.
Short-Term Load Forecasting by Integration of Phase Space Reconstruction,  Support Vector Regression and Parameter Tuning System

Forecasting electricity consumption is an important index for system planning, operation and decision making. In order to improve the accuracy of the forecasting, we apply an integrated architecture to optimize the prediction. Based on an integration of two machine learning techniques: artificial fish swarm algorithm search approach based on test-sample error estimate criterion (AFSAS-TEE) and support vector regression (SVR), we proposed a novel forecasting model for future electricity load forecasting. On the one hand the theory of phase space reconstruction (PSR) technique was used for nonlinear dynamic system analysis with the chaotic load series and on the other hand a AFSAS-TEE tuning system is proposed to choose the parameters of SVR automatically in time series prediction. The effectiveness of the proposed model is demonstrated with actual data taken from the Australia Power Grid, and the actual data are compared with the presented and neural networks (NN) methods.
Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems

This paper addresses the beam allocation problem in a switched-beam based massive multiple-input-multiple-output (MIMO) system working at the millimeter wave frequency band, with the target of maximizing the sum data rate. This beam allocation problem can be formulated as a combinatorial optimization problem under two constraints that each user uses at most one beam for its data transmission and each beam serves at most one user. The brute-force search is a straightforward method to solve this optimization problem. However, for a massive MIMO system with a large number of beams N, the brute-force search results in intractable complexity O(NK), where K is the number of users. In this paper, in order to solve the beam allocation problem with affordable complexity, a suboptimal low-complexity beam allocation (LBA) algorithm is developed based on submodular optimization theory, which has been shown to be a powerful tool for solving combinatorial optimization problems. Simulation results show that our proposed LBA algorithm achieves nearly optimal sum data rate with complexity O(K log N). Furthermore, the average service ratio, i.e., the ratio of the number of users being served to the total number of users, is theoretically analyzed and derived as an explicit function of the ratio N/K.
Video saliency incorporating spatiotemporal cues and uncertainty weighting

We propose a method to detect visual saliency from video signals by combing both spatial and temporal information and statistical uncertainty measures. The main novelty of the proposed method is twofold. First, separate spatial and temporal saliency maps are generated, where the computation of temporal saliency incorporates a recent psychological study of human visual speed perception, where the perceptual prior probability distribution of the speed of motion is measured through a series of psychovisual experiments. Second, the spatial and temporal saliency maps are merged into one using a spatiotemporally adaptive entropy-based uncertainty weighting approach. Experimental results show that the proposed method significantly outperforms state-of-the-art video saliency detection models.
Study on NTC thermistor characteristic curve fitting methods

Thermistor characteristic equation directly determines the temperature measurement accuracy. Three fitting equation of NTC thermistors and their corresponding mathematic solutions are introduced. An adaptive algorithm based on cross-validation is proposed to determine the degree of chebyshev polynomials equation. The experiment indicates that the method of least squares for Steinhart-Hart equation and chebyshev polynomials equation has higher accuracy, and the equation determined by adaptive algorithm for the chebyshev polynomials method has better performance.
On the use of SSIM in HEVC

The Structural SIMilarity (SSIM) index has been attracting an increasing amount of attention recently in the video coding community as a perceptual criterion for testing and optimizing video codecs. Meanwhile, the arrival of the new MPEG-H/H.265 High Efficiency Video Coding (HEVC) standard creates new opportunities and challenges in perceptual video coding. In this paper, we first elaborate what are the attributes that make SSIM a good candidate for perception-based development of HEVC and future video coding standards for both testing and optimization purposes. We then address the computational issues in practical applications of SSIM in HEVC, in particular the trade-off between efficient computation and accurate estimation of SSIM when working with video codecs that have sophisticated block partitioning structures and aim for encoding videos with a wide range of spatial resolutions.