nils-herrmann/clean_scirepeval huggingface dataset:
Intuitionistic fuzzy multiple attribute group decision making based on projection method

In decision making problems there may be cases in which decision makers do not have an in-depth knowledge of the problem to be solved. In such cases, more and more research has been conducted within a fuzzy or intuitionistic fuzzy framework. In this paper, we investigate the group decision making problems in which all the evaluation information provided by the decision makers is characterized by intuitionistic fuzzy decision matrices where each of the elements is expressed as intuitionistic fuzzy numbers (IFNs), and both weights of attributes and decision makers weights are incompletely known, which may be constructed by IFNs. By employing a projection model, fractional programming models are developed to determine the closeness interval values of alternatives. The interval values are subsequently used to aggregate into an overall interval value for each alternative, and the likelihood is applied to ranking and selection of alternatives. Feasibility and effectiveness of the developed models are illustrated with an example of investment decision problem.
Downlink transmission of broadband OFCDM systems-part III: turbo-coded

Orthogonal frequency and code-division multiplexing (OFCDM) systems have been introduced for high-speed data transmission in future wireless mobile communications. In this paper, a hybrid multicode interference cancellation (MCI) and minimum mean-square error (MMSE) detection scheme is presented for the turbo-coded OFCDM systems. Channel estimation based on a code-multiplexed pilot channel is employed. The weights of the hybrid detection are derived theoretically and an effective method to generate the weights in practical applications is proposed. By means of computer simulation, the effects of system parameters on the performance are studied extensively. It is shown that the hybrid detection outperforms pure MMSE detection in various channel conditions, especially for high-level modulation schemes. To carry out interference regeneration for the hybrid detection, the conventional turbo decoding algorithm which only decodes systematic bits should be extended to decode parity bits as well. Moreover, two iterations in turbo decoding are sufficient to provide good performance for the system with the multistage hybrid detection. Finally, given time-domain spreading factor N/sub T/, the system performance improves with frequency-domain spreading factor N/sub F/. However, the frequency diversity gain is saturated when N/sub F/ is large (i.e., N/sub F//spl ges/16).
Perceptual evaluation of single image dehazing algorithms

Images captured in outdoor scenes often suffer from poor visibility and color shift due to the presence of haze. Although many algorithms have been proposed to remove the haze, not much effort has been made on quality assessment of dehazed images. In this paper, we first build a database that contains 25 hazy images as well as dehazed images created by eight dehazing algorithms. A subjective user study is then carried out based on the database, from which we have several useful findings. First, considerable agreement between human subjects on the perceived quality of hazy and dehazed images is observed. Second, not a single dehazing algorithm performs the best for all test images. Third, existing objective image quality assessment (IQA) models are very limited in providing proper quality predictions of dehazed images.
ARMA Model identification using Particle Swarm Optimization Algorithm

In this paper, a new approach to ARMA model identification using evolutionary particle swarm optimization (PSO) algorithm has been proposed. ARMA is a popular method to analyze stationary univariate time series data. Stationarity checking, model identification, model estimation and model checking are usually four main stages to build an ARMA model and model identification is the most important stage in building ARMA models. However there is no method suitable for ARMA model that can overcome the problem of local optima, which is suitable for any ARMA model. The effectiveness of PSO Algorithm which is used to choose the parameters of ARMA Model automatically is tested for ARMA (2,2) model example. The identification of model ARMA(2,2): xt +0.1xt-1-0.2xt-2 = at+0.2at-1-0.5at-2. The simulation shows that the PSO-based model identification method can present better solutions than the MINIC model identification method.
Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index

We propose a multi-exposure image fusion (MEF) algorithm by optimizing a novel objective quality measure, namely the color MEF structural similarity (MEF-SSIM<inline-formula><tex-math notation="LaTeX">$_c$</tex-math></inline-formula>) index. The design philosophy we introduce here is substantially different from existing ones. Instead of pre-defining a systematic computational structure for MEF (<italic/>e.g.<italic/>, multiresolution transformation and transform domain fusion followed by image reconstruction), we directly operate in the space of all images, searching for the image that optimizes MEF-SSIM<inline-formula><tex-math notation="LaTeX">$_c$</tex-math></inline-formula>. Specifically, we first construct the MEF-SSIM<inline-formula><tex-math notation="LaTeX">$_c$</tex-math> </inline-formula> index by improving upon and expanding the application scope of the existing MEF-SSIM algorithm. We then describe a gradient ascent-based algorithm, which starts from any initial point in the space of all possible images and iteratively moves towards the direction that improves MEF-SSIM<inline-formula><tex-math notation="LaTeX"> $_c$</tex-math></inline-formula> until convergence. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality fused images both visually and in terms of MEF-SSIM<inline-formula> <tex-math notation="LaTeX">$_c$</tex-math></inline-formula>. The final high quality fused image appears to have little dependence on the initial image. The proposed optimization framework is readily extensible to construct better MEF algorithms when better objective quality models for MEF are available.
Cooperative performance and diversity analysis for wireless relay networks

In this paper, the error rate performance and diversity gain of amplify-and-forward (AF) wireless relay networks are studied. The distributed space-time block code (DSTBC) in a synchronous relay network with multiple relay nodes is considered. The distributed linear dispersion code is used at the relays. The symbol (or codeword) error rate is studied in terms of upper and lower bounds through rigorous derivations, and the diversity gain of the DSTBC is derived, for any number of relay nodes. As a corollary, a necessary and sufficient condition is obtained for achieving full cooperative diversity. Arbitrary coding matrices at the relays, path loss and general linear power allocation are considered.
An approach to deriving interval weights from interval fuzzy preference relations based on multiplicative transitivity

The derivation of priority weights plays an important role in multi criteria decision making (MCDM) with preference relations. In this paper, interval fuzzy numbers are used to capture vagueness and uncertainty in imprecise judgment data by means of interval fuzzy preference relations. The criterion weights or priority weights of decision alternatives are characterized by normalized interval weights. Based on multiplicative transitivity, a geometric least squares model is developed to derive interval weights from interval fuzzy preference relations. A geometric-least-squares-based approach is then put forward for solving MCDM problems with a hierarchical structure. An online shopping customer satisfaction evaluation problem is furnished to show the effectiveness and applicability of the proposed method.
A Lower Error Arithmetic of Data Fusion

Arithmetic of data fusion and high-level error correcting applicable to sensor network are presented. These arithmetic can be updated and are universally applicable, so they can be applied to any kind and any size sensor networks. The process of data fusion has a remarkable effect on decreasing the data flux, as a result it can realize the real-time and remote monitoring to the message under the condition of lower bandwidth. By using a probability matrix and the statistical result of error correcting, the high-level error correcting is achieved. The sensor network assesses the arithmetic that mentioned above by tracking of moving subject, and the experimental result shows that these alignments can effectively decrease the data flux and avoid the error
Implied risk assessment model of earnings in Chinese listed companies

This article defines the meaning of the risk of earnings information, select Index from a statistical sense, then according to the model theory, create a general assessment model, and do the parameters set bias and stability test. The results show that accrual earnings quality information can be the most reasonable measure of the risk of earnings information; the use of a general model assessment of TA, GA accrual quality is of the higher validity, the model specification and structural stability are better, the assessment relevant explanatory variables are particularly significant.
Pre-supporting with Horizontal Piles of Jet Grouting in Weak Loess Tunnel

Considering the characteristics of surrounding rock of one highway tunnel discussed in this paper, pre-supporting with horizontal piles of jet grouting was used in portal section in order to improve the bearing capability of highway tunnel foundation. Diameter, length, longitudinal intervals of horizontal piles of jet grouting were determined preliminary based on calculation and references of some other projects. According to the geological conditions of surrounding rock, different water cement ratios, pressures of jet grouting, velocities of lifting and other construction parameters were put to use to large-scale field test. Diameter, length, 3 d and 28 d compressive strength of all test piles were checked, on which pre-design were adjusted and design indexes, construction parameters were get. Engineering application has proved the strong adaptability and maneuverability, and bearing capability and stability of highway tunnel foundation were improved through this method, therefore, this paper can be used for reference in design and construction of highway tunnel in weak loess.
High Dynamic Range Image Compression by Optimizing Tone Mapped Image Quality Index

Tone mapping operators (TMOs) aim to compress high dynamic range (HDR) images to low dynamic range (LDR) ones so as to visualize HDR images on standard displays. Most existing TMOs were demonstrated on specific examples without being thoroughly evaluated using well-designed and subject-validated image quality assessment models. A recently proposed tone mapped image quality index (TMQI) made one of the first attempts on objective quality assessment of tone mapped images. Here, we propose a substantially different approach to design TMO. Instead of using any predefined systematic computational structure for tone mapping (such as analytic image transformations and/or explicit contrast/edge enhancement), we directly navigate in the space of all images, searching for the image that optimizes an improved TMQI. In particular, we first improve the two building blocks in TMQI-structural fidelity and statistical naturalness components-leading to a TMQI-II metric. We then propose an iterative algorithm that alternatively improves the structural fidelity and statistical naturalness of the resulting image. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality tone mapped images even when the initial images of the iteration are created by the most competitive TMOs. Meanwhile, these results also validate the superiority of TMQI-II over TMQI.
The optimum rate of inter-frequency scan in inter-frequency HetNets

Inter-frequency scan (IFS) is a process performed by the user equipment (UE) to discover small cells in heterogeneous networks (HetNets) for high data rate and boosting the spectral efficiency. It is anticipated that the role of IFS will have a significant impact on the quality of service (QoS) and the energy efficiency in the future cellular systems. In this paper, a framework is presented to model and evaluate the impact of IFS on the system performance by using stochastic geometry. The energy efficiency is derived as performance metric to obtain the optimum value of the IFS rate (optimum number of scans per unit time) by taking into consideration the tradeoff between the power consumption and exploiting the abundant frequency resources at the small cells efficiently. Considering the energy consumption for performing IFSs along with the energy consumption for maintaining the uplink (UL) transmission will help to find the optimum value of IFS rate that achieves the best energy efficiency. The analysis and results show that the optimum IFS rate depends on different system parameters such as the small cells' density, UE's speed and the transmit power of the small cells (small cells coverage).
Processing of Low Resolution Metal Transfer Images

Processing of images for real-time monitoring of metal transfer process is challenging. To address this challenge, the authors analyzed the characteristics of metal transfer images in a novel modification of GMAW (gas metal arc welding), referred to as double-electrode GMAW or DE-GMAW, and proposed an algorithm consisting of a system of effective steps to extract the needed droplet feedback information from high frame-rate low-resolution metal transfer images. Experimental results verified the effectiveness of the proposed algorithm in automatically locating the droplet and computing the droplet size with an adequate accuracy.
Quality assessment of images undergoing multiple distortion stages

In practical media distribution systems, visual content often undergoes multiple stages of quality degradations along the delivery chain between the source and destination. By contrast, current image quality assessment (IQA) models are typically validated on image databases with a single distortion stage. In this work, we construct two large-scale image databases that are composed of more than 2 million images undergoing multiple stages of distortions and examine how state-of-the-art IQA algorithms behave over distortion stages. Our results suggest that the performance of existing IQA models degrades rapidly with distortion stages, especially when the distortion types of different stages vary. We also find that full-reference and no-reference frameworks, though both readily applicable, have major drawbacks at predicting the quality of images at middle distortion stages. However, when the quality level of the previous stage is accessible, significantly improved quality prediction performance may be achieved. This study points out a new avenue of degraded-reference IQA research that is both practically desirable and technically challenging.
Quality-Aware Video

Development in network visual communications has emphasized on the need of objective, reliable and easy-to-use video quality assessment (VQA) systems. This paper introduces a novel idea of quality-aware video (QAV), in which extracted features about the original video sequence are invisibly embedded into the same video data. When such a QAV sequence is distributed over an error-prone network, a network user who receives it can decode the hidden messages and use them to evaluate the quality degradations between the original and the received video sequences. Our first implementation of QAV employs (1) a novel reduced-reference VQA method based on a statistical model of natural video, and (2) a 3D discrete cosine transform-based data hiding algorithm. The proposed approach does not assume any prior knowledge about image distortions, and the simulation results demonstrate its potentials to be generalized for different types and degrees of image distortions.
Frequency reuse in chunk-based multi-cell OFDMA systems

In OFDMA systems, chunk-based resource allocation is an effective approach to reduce the complexity of resource allocation by grouping a number of adjacent subcarriers into a chunk and allocating resources chunk by chunk. In this paper, chunk-based resource allocation is investigated in a multi-cell environment. To improve the spectral efficiency in the multi-cell system, fractional frequency reuse (FFR) is also adopted in the chunk-based OFDMA system. After theoretically analyzing the spectral efficiency of the chunk-based OFDMA system with FFR, the optimal value of the radius ratio, which is the ratio of the radius of the central area to the radius of the cell, to achieve the optimum system performance is given by numerical simulations. Numerical results show that the average spectral efficiency increases with increasing the number of users in the system. However, the value of the radius ratio to achieve the largest spectral efficiency is not affected by the number of users or the number of subcarriers per chunk.
Price Forecasting of Supply Chain Product Based on Dynamic Fractal Dimension

Supply chain management (SCM) is an emerging field that has commanded attention and support from the industrial community. Demand forecast taking inventory into consideration is an important issue in SCM. This paper presents a novel computerized system for implementing the forecasting activities required in SCM. It can help the supply chain enterprises find hidden forms, trends and relationships in the date of supply chain by the dynamic fractal dimension of fractal theory, find that dynamic fractal dimension not only can overcome the delay of the existing technical analysis on the price forecasts, and but also can instruct the supply chain product prices in advance.
Non-iterative signal processing for a new coded LSTF architecture in OFDM MIMO multiplexing

This paper is focused on the study of layered space-time-frequency (LSTF) architectures with channel coding for orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) multiplexing systems for high speed wireless communications over a frequency-selective fading channel. In order to achieve the available spatial, temporal and frequency diversities, and also make the system implementation feasible for high speed OFDM MIMO multiplexing, a novel LSTF architecture with multiple channel encoders is proposed with each independently coded layer being threaded in the three-dimensional space-time-frequency transmission resource array. Non-iterative receiver is adopted which consists of list sphere detector and irregular low-density parity-check (LDPC) codes as the constituent codes. Simulation results show that the performance of the proposed multiple-encoder LSTF architecture is very close to that of the conventional single-encoder LSTF where coding is applied across the whole information stream. However, due to the use of multiple parallel encoders/decoders with a shorter codeword length, the proposed LSTF architecture has much lower hardware processing speed and complexity than the conventional LSTF.
Quality assessment of multi-view-plus-depth images

Multi-view-plus-depth (MVD) representation has gained significant attention recently as a means to encode 3D scenes, allowing for intermediate views to be synthesized on-the-fly at the display site through depth-image-based-rendering (DIBR). Automatic quality assessment of MVD images/videos is critical for the optimal design of MVD image/video coding and transmission schemes. Most existing image quality assessment (IQA) and video quality assessment (VQA) methods are applicable only after the DIBR process. Such post-DIBR measures are valuable in assessing the overall system performance, but are difficult to be directly employed in the encoder optimization process in MVD image/video coding. Here we make one of the first attempts to develop a perceptual pre-DIBR IQA approach for MVD images by employing an information content weighted approach that balances between local quality measures of texture and depth images. Experiment results show that the proposed approach achieves competitive performance when compared with state-of-the-art IQA algorithms applied post-DIBR.
Steady-State Analysis of Circuits with Multiple Adaptive Grids

This paper explores an effective adaptive algorithm to obtain the steady-state response of circuits with periodic excitation. This algorithm offers an alternative to conventional steady-state simulation techniques such as harmonic balance or shooting method. One of the contributions of this paper is the generic formulation of nonlinear circuit equations in terms of transformation matrices. This algorithm is especially advantageous to circuits showing high nonlinearity. In the proposed method, each circuit variable is represented by a linear combination of a set of adaptive basis functions (ABF). Waveform samples are obtained by multiplying a vector of coefficients times a transformation matrix. Furthermore, in order to improve the output resolution, the positions of the basis functions for each variable are adaptively controlled. In other words, we start the analysis with a uniform grid and increase the resolution where needed by adjusting the position of the grid points independently for each variable. The least squares method is used to find the set of coefficients that minimizes the error function defined by the formulation. We present for the first time simulation results with different grids in each state variable.
Study of tribological properties of graphite/copper-ferrum matrix self-lubricating composites prepared by induction sintering at elevated temperature

The graphite/copper-ferrum matrix self-lubricating composites with various amounts of graphite additives were prepared by induction heating sintering method combined with the alloying of the copper-ferrum matrix with various metallic elements. As the temperature was increased from room temperature to 500°C, the mechanical properties of the composites were measured using the mechanical tester, while the friction and wear properties were evaluated by MRH-3 friction-wear tester. The worn surface morphologies of the composites were analyzed by means of scanning electron microscopy. It was found that the mechanical and friction/wear properties of the self-lubricating composites were related to the induction frequencies and the contents of the graphite as the solid lubricant. The increased graphite content resulted in reduced mechanical properties and increased friction/wear properties. The composites with proper graphite contents and induction frequencies have the lower the friction coefficients and wear volume loss at room temperature to 500°C. Meanwhile, wear mechanism of composites have been changed from abrasive wear to ploughing wear.
A unified drain current model for nanoscale double-gate and surrounding-gate MOSFETs incorporating velocity saturation

A unified drain current model for undoped or lightly doped double-gate (DG) and surrounding-gate (SRG) MOSFETs incorporating velocity saturation effect are presented in this paper. The unified charge-based core model for undoped or lightly doped DG and SRG MOSFETs is presented first. Caughey-Thomas engineering mobility model with exponent factor n=2 is then integrated self-consistently into the unified drain current model derivation of the two device structure. Extensive two dimensional (2D) and three dimensional (3D) device simulations are performed to validate the proposed model. Symmetry property of the proposed unified current model is obtained with the exponent factor n=2 in Cauhey-Thomas Model.