nils-herrmann/clean_scirepeval huggingface dataset:
Implementing indoor positioning system via ZigBee devices

A wireless indoor positioning system is developed with the ZigBee technology. ZigBee devices with chipset reference designs or design-in modules are used for hardware implementation. Using Jennic's JN5121 and Texas Instrument's CC2430 system-on-chip modules for 2.4 GHz IEEE 802.15.4 and ZigBee, we developed the indoor positioning system testbed. Channel measurements via the testbed verified the log-normal indoor channel propagation model and were used to calculate the model parameters. We proposed an effective cooperative localization algorithm that is tailored to the ZigBee profile. It uses the ZigBee link quality indicator, which is directly related to the received signal strength, to acquire the pair-wise distances between the nodes in the network. In order to yield positioning accuracy, the algorithm combines the multidimensional scaling with the maximum likelihood estimation, and overcomes their inherent drawbacks.
Multiple Description Coding for H.264/AVC With Redundancy Allocation at Macro Block Level

In this paper, a novel multiple description video coding scheme is proposed to insert and control the redundancy at macro block (MB) level. By analyzing the error propagation paths, the relative importance of each MB is determined. The paths, in practice, depend on both the video content and the adopted video coder. Considering the relative importance of the MB and the network status, an unequal protection for the video data can be realized to exploit the redundancy effectively. In addition, a simple and effective approach is introduced to tune the quantization parameter for the variable rate coding case. The whole scheme is implemented in H.264/AVC by employing its coding options, thus generating descriptions that are compatible with the baseline profile and extended profile of H.264/AVC. Due to its general property, the proposed approach can be employed for other hybrid video codecs. The results demonstrate the advantage of the proposed approach over other H.264/AVC multiple description schemes.
Multi-modal characteristics analysis and fusion for TV commercial detection

Automatic TV commercial detection has become an indispensable part of content-based video analysis technique due to the explosive growth in TV commercial volume. In this paper, a multi-modal (i.e. visual, audio and textual modalities) commercial digesting scheme is proposed to alleviate two challenges in commercial detection, which are the generation of mid-level semantic descriptor and the application of effective discrimination method. Compared with the general program, some unique semantic characteristics are purposely embedded in the commercial to grasp more attention from audience. Aiming at exploring the power of these semantic characteristics, a kind of novel commercial-oriented descriptor from textual modality is proposed, besides taking advantage of those commonly used description means in light of audio and visual modalities. To boost the ability of discrimination of commercial from general program in multi-modal representation space, Tri-AdaBoost, a self-learning method by an interactive way across multiple modalities, is introduced to form a final consolidated decision for discrimination. Moreover, a heuristic post processing strategy based on the temporal consistency is taken to further reduce the false alarms. The promising experimental results show the effectiveness of the proposed scheme with respect to large video data collections.
A Novel Image Annotation Scheme Based on Neural Network

Automatic image annotation (AIA) is an effective technology for improving the image retrieval. In this paper, a novel annotation scheme based on neural network (NN) is first proposed for characterizing the hidden association between two modalities, i.e. the visual and the textual modalities. Furthermore, latent semantic analysis (LSA) is employed to the NN based annotation scheme (noted as LSA-NN) for discovering the latent contextual correlation among the keywords, which is neglected by many previous annotation methods. Instead of region-level as most previous works do, the LSA-NN based annotation scheme is built at image-level to avoid the prior image segmentation. The experimental results reveal that the high annotation accuracy can be achieved at image-level.
Multiple description video coding using macro block level correlation of inter-/intra-descriptions

Multiple description coding (MDC) is a promising technology for robust transmission over error-prone channels, which has attracted a lot research interests. The basic idea of MDC is to how to utilize redundant information of the descriptions for robust transmission. In view of practical applications, many MDC approaches have been proposed compatible with a certain standard codec, especially H.264/AVC. In this paper, we attempt to develop a novel MD video codec with generalized compatibility, which aims to the effective redundancy allocation from inter-/intra-descriptions. In , the redundancy allocation may be not enough effective due to frame level. As a result, in this paper, the redundant information will be taken into account at MB level.
Reversible watermarking resistant to cropping attack

A reversible digital watermarking scheme based on a blockwise difference expansion (DE) method is proposed here. The proposed scheme differs from previous ones in its robustness against cropping and collage attacks. In order to easily detect the correct cropped position for a cropped image, a locating pattern is embedded into the carrier image by a modified patchwork algorithm. Incurred overhead, payload, and authentication information are then collected and embedded into the carrier image by a blockwise DE method. Within the proposed scheme, image ID and block index also serve as parts of the inputs to the hash function. This endows the scheme with capability in resisting collage attacks. The experimental results show that the scheme can achieve a good robustness against cropping attacks as well as collage attacks.
A fast region-level 3D-warping method for depth-image-based rendering

In 3D video, depth-image-based rendering (DIBR) is widely employed in view synthesis to generate virtual views. However, the processing of this algorithm is based on the frame-level, and the characteristics in different regions cannot be fully taken into account before rendering. This drawback will lead to the unnecessary and redundant information in some regions being abused, which increases extra computation. This paper proposes a region-level 3D-warping method for DIBR, where regions are divided according to their characteristics. Then, only the necessary information in some important regions is utilized warping so that the redundant information could be avoided in the computation. Experimental results show that our approach is almost 4 times faster than VSRS-1D-fast, while declines 0.12 dB PSNR in the performance of synthesis views averagely. Hence, our method can achieve a good trade-off between the computation and view synthesis and will be especially useful for applications where the computation is the concern.
Investigation of fault-tolerant capability of five-phase doubly salient electromagnetic generator

A new topology of five-phase fault-tolerant doubly salient electromagnetic generator (FTDSEG) is proposed for high reliability applications in this paper. The analysis of no-load and loading operations shows the potential fault-tolerance capability. On the basis of comparative analysis on structure characteristics between five-phase non-FTDSEG (NFTDSEG) and five-phase FTDSEG, the variation of rotor pole number from NFTDSEG to FTDSEG is revealed. Meanwhile, the flux linkage and electromotive forces (EMFs) of five-phase NFTDSEG and five-phase FTDSEG are investigated with finite element method and five faults of five-phase FTDSEG are analysed in detail. Especially when single phase short-circuit fault happens, the magnetic field of the motor, flux linkage of short-circuit phase and short-circuit currents without load are investigated in four different short-circuit moments and the fault is in consideration of armature winding resistance. The ultimate variation trend of flux linkage is irrelevant to moment when the short-circuit fault happens. The flux linkage and EMF of short-circuit phase are also analysed. The laws of fault operating influence on external and power characteristics of FTDSEG are researched in five faults with different exciting currents. The fault-tolerant ability of five-phase FTDSEG has been demonstrated by the experimental results.
Modeling and state feedback control of Z-source inverter

This paper proposes an average model for the Z-source inverter with inductive load without ignoring the inductor resistance in the Z-source network using state space averaging. Based on this model and state feedback control, a controller is designed. This method conducts united control with the shoot through duty ratio and modulation index directly. The simulation results and the experimental results proved that the controller has the characteristic of tracing fast, accurately and small overshoot by conducting united control with the shoot through duty ratio and modulation index directly.
TD-AIM-MOD method for simulating large-scale electromagnetic transients

This paper reports on a new hybrid TD-AIM-MOD scheme for analyzing transient scattering from the perfect electrically conducting structures. The scheme reduces the computational complexity of a classically formulated MOD solver from N<sub>o</sub><sup>2</sup>N<sub>s</sub><sup>2</sup> to N<sub>o</sub>log<sup>2</sup>N<sub>o</sub>N<sub>s</sub><sup>1.5</sup>log<sup>2</sup>N<sub>s</sub> - here N<sub>o</sub> is the maximum order of the Laguerre polynomials used to expand the temporal current signature. Just as in MOT-TD-AIM solvers, the scatterer is embedded in a 3D regular grid and sources are projected onto this grid via moment matching. Next, fields are propagated on this grid by using a 3D spatial FFT and a blocked 1D “temporal” (order) FFT. Finally, fields at observers are obtained by interpolating their values from the regular spatial grid, followed by a near field correction operation. The accuracy and stability characteristics of the TD-AIM-MOD method are demonstrated via its application to large-scale scattering problems.
Wavelet Video Coding Combining Pyramidal Lattice Vector Quantization with Wyner-Ziv Coding

The paper presents a new video coding scheme combining pyramidal lattice vector quantization (PLVQ) with distributed video coding (DVC). Our scheme firstly applies lattice A2 with side information to quantify the lowest coefficients in the discrete wavelet transform (DWT); and utilizes D4 PLVQ to deal with the rest of wavelet coefficients. DVC respectively treats nonzero lattice vectors and zero lattice vectors after D4 quantization. LVQ can extract the intra-frame dependences of wavelet coefficients; DVC can exact inter-frame dependences at the decoder. So, though intra-frame structure is used in our scheme, it has better performance than intra-frame coding
Electromagnetic performance of three-phase doubly fed doubly salient electromagnetic generator

In this paper, a three-phase dual armature-winding doubly fed doubly salient electromagnetic generator (DAW-DFDSEG) is proposed. The reason for using different numbers of turns in the two sets of armature windings is presented. On the basis of the finite-element method (), two different DAW structures (DAW1 and DAW2) with different turn numbers of armature windings are analysed and compared. The DAW2 structure outputs more power than DAW1 under the same turn number of armature windings, due to the stronger flux-weakening armature reaction under heavy magnetic saturation. However, the manufacturing technique of DAW2 is more complex than that of DAW1 in the limited stator slot. The DAW1 with two set armature windings of 11 and 12 is researched in detail in terms of flux linkage, induced voltages, winding voltages, winding currents, self-inductances and mutual inductances by simulation and the equivalent rectifier circuit patterns of two time zones are also presented. Meanwhile, its commutation procedure is analysed in detail. To validate the analysis, a 12/8-pole DAW-DFDSEG prototype has been designed and the simulated waveforms agree well with the measured ones.
TV Commercial Categorization Based on Sparse Visual Bag of Words

Automatic TV commercial categorization is the key component of a smart commercial content analysis and understanding system. In this paper, we focus our research on commercial categorization by mining the temporal-spatial context of TV commercial. To boost the discrimination ability of the traditional VBoW in commercial categorization, a more flexible representation, i.e. sparse coding based VBoW (sVBoW), is presented to describe the co-occurrence of semantic units in different kinds of commercials. Meanwhile, both the temporal and spatial cues are fully exploited to reflect the context characteristics of TV commercial. The promising experimental results show the effectiveness of the proposed scheme on commercial categorization.
Local stereo matching algorithm using rotation-skeleton-based region

This paper proposes a local stereo matching algorithm for accurate disparity estimation by using 45° rotation-skeleton-based region (RSBR). For local stereo matching, an adaptive local region is important for the performance of the disparity estimation. In order to generate more accurate regions, we use a skeleton with 45° rotation to divide an initial window that achieved by mean-shift segmentation into four parts. All the pixels in the same height level are judged simultaneously, and the valid pixels in the four parts construct the 45° RSBR. Compared with the common local support region based on orthogonal skeleton, 45° RSBR enables to maintain the consistency in images and have the advantage of error tolerance. The local stereo matching algorithm with RSBR is improved in two aspects. First, the hybrid cost aggregation using the RSBR helps to remove some noise caused by outliers and improve the subjective performance. Second, the candidate values in the refinement step are selected from the RSBR, which ensures the validity of candidates. The experiment results demonstrate a good performance in Middlebury Stereo datasets, both in objective and subjective performance.
Virtual-View-Assisted Video Super-Resolution and Enhancement

A 3-D multiview video gives users an experience that is different from that provided by a traditional video; however, it puts a huge burden on limited bandwidth resources. Mixed-resolution video in a multiview system can alleviate this problem by using different video resolutions for different views. However, to reduce visual uncomfortableness and to make this video format more suitable for free-viewpoint television, the low-resolution (LR) views need to be super-resolved to the target full resolution. In this paper, we propose a virtual-view-assisted super-resolution algorithm, where the inter-view similarity is used to determine whether the missing pixels in the super-resolved frame need to be filled by virtual-view pixels or by spatial interpolated pixels. The decision mechanism is steered by the texture characteristics of the neighbors of each missing pixel. Furthermore, the inter-view similarity is used, on the one hand, to enhance the quality of the virtual-view-copied pixels by compensating the luminance difference between different views and, on the other hand, to enhance the original LR pixels in the super-resolved frame by reducing their compression distortion. Thus, the proposed method can recover the details in regions with edges while maintaining good quality at smooth areas by properly exploiting the high-quality virtual-view pixels and the directional correlation of pixels. The experimental results demonstrate the effectiveness of the proposed approach with a peak signal-to-noise ratio gain of up to 3.85 dB.
Rake: Semantics Assisted Network-Based Tracing Framework

The ability to trace request execution paths is critical for diagnosing performance faults in large-scale distributed systems. Previous black-box and white-box approaches are either inaccurate or invasive. We present a novel semantics-assisted gray-box tracing approach, called Rake, which can accurately trace individual request by observing network traffic. Rake infers the causality between messages by identifying polymorphic IDs in messages according to application semantics. To make Rake universally applicable, we design a Rake language so that users can easily describe necessary semantics of their applications while reusing the core Rake component. We evaluate Rake using a few popular distributed applications, including web search, distributed computing cluster, content provider network, and online chatting. Our results demonstrate Rake is much more accurate than the black-box approaches while requiring no modification to OS/applications. In the CoralCDN (a content distributed network) experiments, Rake links messages with much higher accuracy than WAP5, a state-of-the-art black-box approach. In the Hadoop (a distributed computing cluster platform) experiments, Rake helps reveal several previously unknown issues that may lead to performance degradation, including a RPC (Remote Procedure Call) abusing problem.
Investigation on prediction of steel slab heating characteristics in a walking beam heating furnace

This paper presents a method for the prediction of temperature distribution in a walking beam furnace chamber and slabs, this method is realized by coupling the steady thermal process in the furnace chamber and transient heat conduction process in the slab, these two processes exchange heat flux and temperature conditions on the surface of slabs. The movement of the slab is taken into account by changing boundary condition at different time, transient radiative heating characteristics is predicted by the finite-volume method for radiation. The three-dimensional entity model is imported from 3D software Solid Edge. Iterations are simulated in the commercial program Fluent respectively. Visual Basic language is developed to generate batched file and control the alternate execution of steady and transient processes. When temperature of a slab does not change, calculation is considered to have converged and is stopped. A reasonable agreement is found between this method and previous work for the prediction of thermal behavior of the slab in the heating furnace. Heating characteristics of a slab during the residence time inside the heating furnace are described precisely.
Estimation of sparse signal by non-convex optimization

It is standard in compressed sensing scenarios to assume that the signal ƒ can be sparsely represented in an orthonormal basis. Whereas, in some sense this isn't very realistic. Indeed, allowing the signal to be sparse with respect to a redundant dictionary adds a lot of flexibility and significantly extends the range of applicability. In this paper, we address the problem of recover signals from undersampled data where such signals are not sparse in an orthonormal basis, but in an overcomplete dictionary. We show that if the combined matrix obeys a certain restricted isometry property and if the signal is sufficiently sparse, the reconstruction that rely on ℓp minimization with 0 &#60; p &#60; 1 is exact.
Load Balanced and Efficient Hierarchical Data-Centric Storage in Sensor Networks

Several new sensor network applications build on scalable, energy-aware data-centric storage. Data-centric storage is typically achieved by hashing a high-level data name to a well-known routable node address. Despite significant work on any-to-any routing for sensor networks, most schemes do not provide a node address space that is amenable to the needs of data-centric storage. Our work focuses on the problem of designing a routing primitive suitable for data-centric storage that also meets typical sensor network goals of scalability, energy-efficiency and load-balance. In this paper, we present a new hierarchical Voronoi graph based routing algorithm (HVGR) that simultaneously achieves good scalability, efficiency in routing, and load balance in both routing and data storage. The region oriented routing scheme avoids overloading cluster headers by "short-cutting" routes before they actually hit cluster headers. The storage load balancing algorithm achieves uniform distribution of storage load.
Priority Encoding Transmission Based Multiple Description Video Coding over Packet Loss Network

In this paper, we attempt to overcome the limitation of specific scalable video codec and apply FEC-MDC to a common video coder, such as the standard H.264. The proposed scheme is explained as follows. Firstly, according to motion vector changes, an original video sequence is divided into several sub-sequences as messages, so in each message better temporal correlation can be maintained for better estimation when information losses occur. Secondly, the standard H.264 encoder is used to encode the messages. Thirdly, based on priority encoding transmission, unequal protections are assigned in each message. Lastly, at the decoder, the segments whose priorities are not higher than the fraction of packets received can be recover totally.
Scalable Bit Allocation Between Texture and Depth Views for 3-D Video Streaming Over Heterogeneous Networks

In the multiview video plus depth (MVD) coding format, both texture and depth views are jointly compressed to represent the 3-D video content. The MVD format enables synthesis of virtual views through depth-image-based rendering; hence, distortion in the texture and depth views affects the quality of the synthesized virtual views. Bit allocation between texture and depth views has been studied with some promising results. However, to the best of our knowledge, most of the existing bit-allocation methods attempt to allocate a fixed amount of total bit rate between texture and depth views; that is, to select appropriate pair of quantization parameters for texture and depth views to maximize the synthesized view quality subject to a fixed total bit rate. In this paper we propose a scalable bit-allocation scheme, where a single ordering of texture and depth packets is derived and used to obtain optimal bit allocation between texture and depth views for any total target rates. In the proposed scheme, both texture and depth views are encoded using the quality scalable coding method; that is, medium grain scalable (MGS) coding of the Scalable Video Coding (SVC) extension of the Advanced Video Coding (H.264/AVC) standard. For varying target total bit rates, optimal bit truncation points for both texture and depth views can be obtained using the proposed scheme. Moreover, we propose to order the enhancement layer packets of the H.264/SVC MGS encoded depth view according to their contribution to the reduction of the synthesized view distortion. On one hand, this improves the depth view packet ordering when considered the rate-distortion performance of synthesized views, which is demonstrated by the experimental results. On the other hand, the information obtained in this step is used to facilitate optimal bit allocation between texture and depth views. Experimental results demonstrate the effectiveness of the proposed scalable bit-allocation scheme for texture and depth views.