nils-herrmann/clean_scirepeval huggingface dataset:
How many users should be turned on in a multi-antenna broadcast channel?

This paper considers broadcast channels with L antennas at the base station and m single-antenna users, where L and m are typically of the same order. We assume that only partial channel state information is available at the base station through a finite rate feedback. Our key observation is that the optimal number of on-users (users turned on), say s, is a function of signal-to-noise ratio (SNR) and feedback rate. In support of this, an asymptotic analysis is employed where L, m and the feedback rate approach infinity linearly. We derive the asymptotic optimal feedback strategy as well as a realistic criterion to decide which users should be turned on. The corresponding asymptotic throughput per antenna, which we define as the spatial efficiency, turns out to be a function of the number of on-users s, and therefore s must be chosen appropriately. Based on the asymptotics, a scheme is developed for systems with finite many antennas and users. Compared with other studies in which s is presumed constant, our scheme achieves a significant gain. Furthermore, our analysis and scheme are valid for heterogeneous systems where different users may have different path loss coefficients and feedback rates.
A Novel Rate Control Technique for Multiview Video Plus Depth Based 3D Video Coding

This paper presents a novel rate control technique for multiview video plus depth (MVD) based 3D video coding. In the proposed rate control technique, an image-stitching method is first utilized to simultaneously encode video and depth, and then a joint rate control algorithm for MVD is presented. The joint rate control algorithm is performed on three levels, namely view level, video/depth level and frame level. In the view level, different proportions of rates are allocated for different types of views according to the pre-statistical rate allocation. In the video/depth level, the target rates for video and depth are discriminatorily assigned to guarantee the high quality of video for the backward-compatible display. In the frame level, the hierarchical rate allocation is used to regulate the target bits for each frame. In addition to the above mentioned rate control strategies, according to the special characteristics of multiview hypothetical reference decoder (HRD), the buffer-related rate control is also considered to prevent the decoder buffer from overflow or underflow even outputting multiple views. Experimental results show that the proposed rate control technique can accurately control the bit-rate to satisfy the requirements of 3D video systems.
Electrified Vehicles and the Smart Grid: The ITS Perspective

Vehicle electrification is envisioned to be a significant component of the forthcoming smart grid. In this paper, a smart grid vision of the electric vehicles for the next 30 years and beyond is presented from six perspectives pertinent to intelligent transportation systems: 1) vehicles; 2) infrastructure; 3) travelers; 4) systems, operations, and scenarios; 5) communications; and 6) social, economic, and political.
Neural network adaptive state feedback control of a magnetic levitation system

Magnetic levitation system is a typical nonlinear and instable system. Based on the complexity and inaccuracy of modelling, in this paper identified magnetic levitation system using the speciality that neural network(NN) can approach any nonlinear function. A Radial Basis Function neural network (RBFNN) controller is designed based on the neural network adaptive control principle. This paper proposes a control method which combine neural network adaptive control method and state feedback control method based on RBFNN. A simulation of the system is proposed, and the result shows that RBFNN could approach magnetic levitation system very well, neural network adaptive state feedback controller has a good effect on this nonlinear system; this control system has a preferable stability and control property.
A comparison of fractional-pel interpolation filters in HEVC and H.264/AVC

The fractional-pel interpolation filter adopted in H.264/AVC improves motion compensation greatly. Recently, a new DCT-based fractional-pel interpolation filter is adopted in the oncoming standard HEVC. We are interested in the differences between these two types of fractional-pel interpolation filters. In this paper we describe the derivations of fractional-pel interpolation filters in HEVC and H.264/AVC in detail, and compare them on properties of frequency responses. We find that the half-pel interpolation filters in HEVC and H.264/AVC are very similar, but the low-pass properties of quarter-pel interpolation filters in HEVC are much better than those in H.264/AVC. Experimental results validate this phenomenon, the fractional-pel interpolation in H.264/AVC tends to increase BD-rates by more than 10% compared with that in HEVC, and this performance loss mainly comes from quarter-pel interpolation filters. On the other hand, the complexity of fractional-pel interpolation filtering in HEVC is greatly increased than that in H.264/AVC.
Deformable model-based generation of realistic 3-D specific human face

This paper presents a new human face generation method using a three-dimensional deformation technique. The deformation technique allows interactive alignment of features in the general geometric face model with the features of the multi-direction images of the specific human face which are pre-provided by the animator. The deformation result is a 3D face model of the specific human face; it precisely reflects the corresponding features of the specific human face. This deformation technique also provide an available approach to obtaining models of facial expression. To enhance the realism, we employ a new multi-direction texture mapping technique which gets photometric information from multi-direction images of the specific human face to diminish the texture distortion.
Steganalysis of data hiding techniques in wavelet domain

The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message in multi-medium. This creates a potential problem when this technology is misused for planning criminal activities. In this paper, a new steganalysis technique is proposed on the basis of histogram analysis on the wavelet coefficients for the detection the very existence of wavelet domain information hiding techniques. And our approach lays particular stress on methods in which secret message was embedded via quantizating wavelet coefficients. Different statistical discrepancies are obtained by histogram analysis of sub-band wavelet coefficients from stego-images and innocent images. And FFT of these discrepancies are used to form a quantitative criterion to determine whether an image has been embedded secret message or not. Experimental results show that the proposed algorithm is comparable to previously existing techniques.
AVS 3D video streaming system over internet

The progresses on PC based 3D video display technology have made it feasible to provide 3D video streaming service over internet. Compared with 2D video streaming, 3D video streaming system demands more network bandwidth, computing power, and more complex transmission mechanism. There are rarely online 3D video services. In this paper, we describe a 3D video streaming services developed by our team cooperated with CNTV and NVIDIA. The main features of the proposed system are high compression performance of 3D video with low complexity both on processing and transmission. The system has been used to distribute 3D content for the 16th Asian Games Guangzhou.
Ant colony optimization for automated storage and retrieval system

In this work, we first propose an NP-hard combinatorial problem, that is, the storage and retrieve (S/R) machine travel path optimization for batch order picking (BOP). Successful solving this problem is valuable to many application areas such inventory items in logistics and work-in-process storage in manufacturing systems. And then, we investigate the feasibility of using ant colony optimization (ACO) meta-heuristics to address the proposed problem. Simulation tests are executed separately based on two ACO algorithms. Finally, the S/R machine operating performance measure index such as total travel distance and total travel time are employed to evaluate the experimental results achieved by different ACO algorithms. Experimental case study demonstrates the effectiveness and applicability of the selected ACO approaches to our proposed BOP problem.
A variable depth LSB data hiding technique in images

In this paper, a data hiding technique by variable depth LSB substitution is proposed. Firstly, pixels of cover-image are grouped according to themselves luminance values. Then the occurrence of pixel-values in each group is counted and sorted in monotone increasing. Finally, a bitplane-wise data hiding method is used to hide data in cover image. The worst-square-error between the stego-image and the cover-image is formulated. Theory analysis indicates that image quality of the stego-image hidden by this method can improve from 0 db to 4 db against simple LSB (least significant bit) substitution method. Experimental results show that the stego-image is visually indistinguishable from the original cover-image.
Cellular manufacturing system scheduling under fuzzy constraints: A group technology perspective

In this article, we attempt to solve cellular manufacturing system (CMS) scheduling problem from group technology point of view. Since the operations of a job in a CMS can be performed on more than one machine within a cell, the scheduling problem of the CMS is always considered as a computationally hard problem. Two approaches called fuzzy logic and fuzzy MAX-MIN ant system are employed respectively. Under the consideration of multiple criteria, the performance of different manufacturing cells in a CMS is improved by means of proposed methodologies.
A Novel Error Concealment Method for Stereoscopic Video Coding

A novel error concealment method is proposed for two-view based stereoscopic video coding to address the challenging problem of adaptively combining inter-view correlation and temporal correlation. First, the disparity vectors of the lost macroblocks' neighboring macroblocks are used to recover the lost or erroneously received motion or disparity vectors. Then we propose a novel error concealment method based on overlapped block motion and disparity compensation, whose weights are determined by the side match criterion and viewpoints. Simulation results show that the subjective and objective performances of the proposed technique are both superior to those of conventional temporal error concealment methods for stereoscopic video coding.
Low-Complexity FGS Coding for Interlaced SVC in Low-Delay Applications

JVT SVC has adopted AR-FGS (fine granularity scalability with adaptive reference) to efficiently encode the progressive sequences for low-delay applications. Generally, low-delay applications demand low complexity. However, to some extent, the significant gain of AR-FGS is achieved at the expense of much higher coding complexity. In this paper, we propose an efficient FGS coding scheme for low-delay applications that can more smartly compress the interlaced video sources by fully utilizing the special temporal correlation of interlaced sequences. Compared to AR-FGS in coding interlaced sequences, the new approach is able to significantly reduce both the encoding and decoding complexity while maintaining comparable compression performance. Moreover, benefited from the introduced open-loop MC, the proposed scheme can also support additional temporal scalability.
Novel example-based shape learning for fast face alignment

A novel example-based shape learning (ESL) strategy is proposed for facial feature alignment. The method is motivated by an intuitive and experimental observation that there exists an approximate linearity relationship between the image difference and the shape difference, that is, similar face images imply similar face shapes. Therefore, given a learning set of face images with their corresponding face landmarks labeled, the shape of any novel face image can be learned by estimating its similarities to the training images in the learning set and applying these similarities to the shape reconstruction of the novel face image. Concretely, if the novel face image is expressed by an optimal linear combination of the training images, the same linear combination coefficients can be directly applied to the linear combination of the training shapes to construct the optimal shape for the novel face image. Our experiments have convincingly shown the effectiveness and efficiency of the proposed approach in both speed and accuracy performance compared with other methods.
HandTalker II: a Chinese sign language recognition and synthesis system

This paper presents a Chinese sign language/spoken language dialog system based on the technique of large vocabulary continuous Chinese sign language recognition (SLR) and Chinese sign language synthesis (SLS), which is new development for HandTalker. In the SLR module, a fuzzy decision tree with heterogeneous classifiers is presented for large vocabulary signer-independent SLR, and then large vocabulary continuous SLR based on transition movement models is proposed. In SLS module, three key techniques: realistic 3D facial animation and gesture retargeting technique and synchronization modal on gesture and lip motion are employed to improve sign language synthesis vividness.
Rate-Distortion Optimized Sparse Coding With Ordered Dictionary for Image Set Compression

Image set compression has recently emerged as an active research topic due to the rapidly increasing demand in cloud storage. In this paper, we propose a novel framework for image set compression based on the rate-distortion optimized sparse coding. Specifically, given a set of similar images, one representative image is first identified according to the similarity among these images, and a dictionary can be learned subsequently in wavelet domain from the training samples collected from the representative image. In order to improve coding efficiency, the dictionary atoms are reordered according to their use frequencies when representing the representative image. As such, the remaining images can be efficiently compressed with sparse coding based on the reordered dictionary that is highly adaptive to the content of the image set. To further improve the efficiency of sparse coding, the number of dictionary atoms for image patches is further optimized in a rate-distortion sense. Experimental results show that the proposed method can significantly improve the image compression performance compared with JPEG, JPEG2000, and the state-of-the-art dictionary learning-based methods.
Facial feature tracking combining model-based and model-free method

We propose a novel facial feature tracker, which integrates model-free and model-based methods to track dense facial features reliably with complex non-rigid motions in low quality video sequences. The tracker consists of the mouth motion model part and the enhanced KLT (Kanade-Lucas-Tomasi) tracker part. There are three key elements in our algorithms: dense facial feature tracking; noise removal with global rank constraints; characteristic non-rigid motion description. Experiments show good results on tracking dense facial features under various expressions, even when some facial features have degenerate features.
A steganography strategy based on equivalence partitions of hiding units

This paper designs a novel hiding strategy based on an equivalence relation, which can remarkably enhance the quality of stego image without sacrificing the security and capacity of original steganography schemes. According to a constructed equivalence relation based on the capacity of hiding units, all hiding units can be partitioned into equivalence classes. Following that, the hiding procedure is performed in predefined order in equivalence classes as the traditional steganography scheme. Because of considering the relation between the length of message and capacity, the performance of the hiding method using proposed hiding strategy outperforms the original approaches when embedding the same length message. Experimental results indicate that the gain from the proposed strategy over existing hiding schemes can reach up to 4.0 dB.
Hybrid angular intra/template matching prediction for HEVC intra coding

In the latest HEVC video coding standard, angular intra prediction (AIP) applies 35 modes including 33 angular modes which can handle blocks with direction information well, and other 2 modes (DC and planar) which are used to predict smooth blocks. However, for blocks with complex texture, these modes may not give good predictions. Some complex blocks can be predicted well by template matching prediction (TMP) which was proposed to predict blocks having similar patterns in the coded regions of the same frame without the cost of large overheads. In this paper, a novel hybrid AIP/TMP is proposed to improve the prediction efficiency. Experimental results show that the proposed method can achieve a coding gain of about 2.5% for high resolution sequences on average compared to the AIP in HEVC. The gain can be up to 4.2%.
Nonlinear face recognition based on maximum average margin criterion

This paper proposes a novel nonlinear discriminant analysis method named by kernerlized maximum average margin criterion (KMAMC), which has combined the idea of support vector machine with the kernel fisher discriminant analysis (KFD). We also use a simple method to prove the relationship between both kernel methods. The difference of KMAMC from traditional KFD methods include: (1) the within-class and between-class scatter matrices are computed based on the support vectors instead of all the samples; (2) multiple centers are exploited instead of the single center in computing the two scatter matrices; (3) the discriminant criteria is formulated as subtracting the trace of within-class scatter matrix from that of the between-class scatter matrix, therefore, the tedious singularity problem is avoided. These features have made KMAMC more practical for real-world applications. Our experiments on two face databases, the FERET and CAS-PEAL face database, have illustrated its excellent performance compared with some traditional methods such as Eigenface, Fisherface, and KFD.
General schemes for blind watermark

Digital watermark is a very active research area that has received a considerable amount of attention in many multimedia applications. For most watermark applications, it is often desired to retrieve the embedded information without reference to the host data; this is known as blind watermark. Some of previous blind watermark schemes either suffer significantly from host data interference or require expensive cost of storage. In this paper, we attempt to resolve the question. Here, we present three general schemes for blind watermark. The first two based on lattice principle and property of periodic function, respectively. The host data interference is eliminated by only a little of cost of storage in the third scheme. They have considerable advantages over previous proposed schemes.
Novel Statistical Modeling, Analysis and Implementation of Rate-Distortion Estimation for H.264/AVC Coders

In H.264/advanced video coding, the encoder employs the rate-distortion optimization (RDO) to select the optimal coding mode of each block. Although it is effective to employ the RDO technique for mode decision, the computation load increases drastically. To reduce the computation complexity of the RDO technique, in this paper, we propose efficient algorithms for the estimation of block-level rate and distortion. For rate estimation, we model the transform coefficients with accurate generalized Gaussian distributions, and the weighted sum of absolute quantized transform coefficients is proposed as an efficient rate estimator, where the weights provide an implicit mechanism for evaluating different contributions of different frequency components to the coding bits. For distortion estimation, we first analyze the origins of distortion thoroughly. Then a direct relationship between the discarded bits in quantization and the distortion is explored. According to this investigation, a simple and efficient algorithm is proposed for the distortion estimation. With above proposed algorithms, the RDO technique can be efficiently implemented in a low-complexity way. Extensive experimental results demonstrate that, compared with the original RDO implementation, the proposed algorithms achieve about 32% reduced total encoding time with ignorable coding performance degradation.
Comparison of pd detection methods for power transformers - their sensitivity and characteristics in time and frequency domain

Partial discharge (PD) detection is an important method for detecting defects in power transformers, and several PD detection methods reported in literature have their respective advantage and disadvantages. In this paper, a simplified PD coupler attached to the tap of the bushing, whose reliability is verified by the EMTP simulation, is proposed in order to extend the application of on-site tap PD detection. Experiments were carried out on 110 kV transformer models to compare the sensitivity of the sensor with some other popular PD detection methods. The characteristics of the detected signals suggest that the proposed coupler has satisfactory sensitivity as well as potential to solve some on-site noise-rejection problems by introduction of ultra-high frequency amplifiers, and thus could be suitable in future for online PD monitoring applications in substations.
On a Highly Efficient RDO-Based Mode Decision Pipeline Design for AVS

Rate distortion optimization (RDO) is the best known mode decision method, while the high implementation complexity limits its applications and almost no real-time hardware encoder is truly full-featured RDO based. In this paper, first, a full-featured RDO-based mode decision (MD) algorithm is presented, which makes more modes enter RDO process. Second, the throughput of RDO-based MD pipeline is thoroughly analyzed and modeled. Third, a highly efficient adaptive block-level pipelining architecture of RDO-based MD for AVS video encoder is proposed which can achieve the highest throughput to alleviate the RDO burden. Our design is described in high-level Verilog/VHDL hardware description language and implemented under SMIC 0.18- μm CMOS technology with 232 K logic gates and 85 Kb SRAMs. The implementation results validate our architectural design and the proposed architecture can support real time processing of 1080P@30 fps. The coding efficiency of our adopted method far outperforms (0.57 dB PSNR gain in average) the traditional low-complexity MD (LCMD) methods and the throughput of our designed pipeline is increased by 11.3%, 19% and 17% for I, P and B frames, respectively, compared with the existed RDO-based architecture.
A economic dispatch method of energy storage systems under time-of-use pricing in microgrids

The energy storage system (ESS) plays a vital role in the reliable operation of a micro-grid. In the autonomous mode operation, the energy storage system is expected to support the difference in power requirements and maintain the frequency and voltage. In grid-connected mode, the economic dispatch of ESS achieves peak load shaving and maximum economy. A detailed analysis shows the power management strategies of energy storage systems for a micro-grid in grid-connected and islanded mode, and based on this analysis, this paper presents a economic dispatch method under time-of-use pricing. The proposed power management strategies, based on a combination droop control and a economic dispatch method, increase the power supply reliability and realize peak load shaving and maximum economy. A study case is presented to investigate the economic benefits of the ESS, and the results contribute to discuss the applications of the economic dispatch method under various operating conditions and market policies.