nils-herrmann/clean_scirepeval huggingface dataset:
Robust Commercial Detection System

Automatic detection of commercials embedded in digital video materials is a challenging task. In this paper, a three-phase system of commercial detection is constructed. Firstly, video shots and audio cuts are detected respectively and scene boundaries are refined by fusing the audio and video information simultaneously. Then, a SVM classifier is applied to classifying these shots as program shots or commercial ones. Finally, in order to make the commercial segments more accurate, the identity of time-spatial content of commercial shots is fully exploited to eliminate those falsely classified commercial ones, based on which the individual commercial shots can be integrated into the commercial sequences ultimately. The final test results on 30 clips of TV videos verify the practicality of the constructed system.
Localization in 3D surface sensor networks: Challenges and solutions

This work aims to address the problem of localization in 3D surface wireless sensor networks. First, it reveals the unique hardness in localization on 3D surface in comparison with the well-studied localization problems in 2D and 3D space, and offers useful insight into the necessary conditions to achieve desired localizability. Second, it formulates the localization problem under a practical setting with estimated link distances (between nearby nodes) and nodal height measurements, and introduces a layered approach to promote the localizability of such 3D surface sensor networks. Crossbow sensor-based experiments and large-scale simulations are carried out to evaluate the performance of the proposed localization algorithm. The numeric results show that it can effectively improve localizable rate and achieve low location errors and computational overhead, with the desired tolerability to measurement errors and high scalability to large-size wireless sensor networks.
Analysis and suppression of the input second harmonic current in two-stage inverter

The instantaneous output power of a two-stage single-phase inverter pulsates at twice the output voltage frequency, generating second harmonic current (SHC) in the front-end dc-dc converter. Though reducing the SHC of the output filter inductor of the dc-dc converter (FIDC) can reduce the input SHC effectively, it depends on the capacitance of DC bus capacitor totally. In order to reduce the SHC of the input port more effectively, a control strategy is proposed in this paper, which extracts the SHC of the input port into the inductor current feedback path by a multiplier and a band-pass filter. The proposed control scheme can not only reduce the SHC significantly, but also is beneficial to improving the dynamic performance of the front-end dc-dc converter. Finally, a 1500-VA prototype is built, and the simulation results are presented to verify the effectiveness of the proposed control strategy.
Reversible Watermarking Based on the Invariant Sum Value

A novel reversible data hiding scheme based on the invariant sum values of pixel pairs is presented in this paper. For each pixel pair, if a certain value is added to one pixel while the same value is subtracted from the other pixel, then the sum of these two pixels will remain unchanged. This value is selected as the half of difference plus 1-bit watermark considering the distortion control and the reversibility of the algorithm. The watermark bit can be extracted by using the invariability of the sum values and the equality property between the parities of the sum values and the difference values. The experimental results reveal that the proposed method has comparable performance with the traditional difference expansion method in visual quality and embedding capacity.
Compatible Stereo Video Coding with Flexible Prediction Mode

Stereo video can bring people into more vivid and actual sense, but the video data is too huge to storage and transmit conveniently. In this paper, a compatible scheme which compresses stereo video with flexible prediction structure is proposed. In the proposed scheme, we define a group of picture (GOP) considering of the real time of the video. There are different prediction structures according to temporal correlation and interview correlation whether the length of GOP is fixed. In any possible prediction structures, temporal correlations and interview correlations are utilized effectively. H.264 which is the most advanced video compression standard at present is utilized to improve the coding efficiency. The proposed scheme is compatible with the present equipments which are based on H.264 and process traditional monoview video. Therefore, the present equipments can process stereo video sequences conveniently. At last, the efficiency of the proposed scheme is proved by the experiment
Three-Description Image Coding Using Optimal Dead-Zone Lattice Vector Quantization

Multiple description coding is an effective way to transmit images over unreliable network or multiple channels. In this paper, a three-description image coding scheme is proposed, involving an optimal index assignment to obtain a mapping table that can reduce side distortion and dead-zone lattice vector quantization to quantize different coefficients more efficiently. The aim is to provide more robustness and present a good reconstructed image quality with bit rate as low as possible for unreliable network. The simulation results of standard image show that with consideration of wavelet coefficients characteristic the proposed scheme can reduce side distortion and reduce expected distortion of the system at high loss rate and compression efficiency.
Finite Element Calculation of Residual Stress and Cold-work Hardening Induced in Inconel 718 by Low Plasticity Burnishing

Low Plasticity Burnishing (LPB), a mechanical surface enhancement technology was developed to produce a deep layer of highly compressive residual stress comparable to laser shot peening, but with minimal cold-work hardening, LPB produces the most thermally stable compression to hot sections of gas turbine engines made by superalloy like Inconel 718. Literatures detailing the experimental effects of LPB are comprehensive, however, there is still a special need for a reliable Finite Element (FE) calculation to provide a fundamental understanding of LPB mechanism. The paper establishes a three-dimensional non-linear FE model, where the flow stress is taken as a function of strain, strain rate and temperature, and the Zienkiewics-Zhu adaptive plastic strain remeshing method is used. Calculated results show that LPB can produce the maximum compressive residual stress about 1000 MPa to a depth more than 1.6 mm, but the cold-work hardening can be controlled to less than 2.5%, the predicted results is validated by the experimental data obtained by X-ray diffraction measurements.
Mercaptopropionic acid capped ZnS:Mn/ZnS core/shell quantum dots as fluorescence probe for folic acid detection

In this work, high quality 3-mercaptopropionic acid (MPA) capped ZnS:Mn/ZnS quantum dots (QDs) have been synthesized via chemical precipitation approach. Structure analysis done by XRD and TEM shows that the prepared QDs are mono-dispersed with with a size distribution of 3-5nm. Optical features of the core/shell QDs have been characterized by UV-Visible spectroscopy and photoluminescence spectrometer (PL). The addition of folic acid (FA) to ZnS:Mn/ZnS QDs solution leads to a linear range of quenching of PL with the concentration of FA from 2μM/L to 60μM/L. It thus provides an opportunity to apply MPA capped ZnS:Mn/ZnS QDs as a sensitive fluorescence probe for FA detection. The detection limit is 0.48μM/L. The fluorescence quenching mechanism caused by FA was also studied.
3-D Surround View for Advanced Driver Assistance Systems

As the primary means of transportations in modern society, the automobile is developing toward the trend of intelligence, automation, and comfort. In this paper, we propose a more immersive 3-D surround view covering the automobiles around for advanced driver assistance systems. The 3-D surround view helps drivers to become aware of the driving environment and eliminates visual blind spots. The system first uses four fish-eye lenses mounted around a vehicle to capture images. Then, according to the pattern of image acquisition, camera calibration, image stitching, and scene generation, the 3-D surround driving environment is created. To achieve the real-time and easy-to-handle performance, we only use one image to finish the camera calibration through a special designed checkerboard. Furthermore, in the process of image stitching, a 3-D ship model is built to be the supporter, where texture mapping and image fusion algorithms are utilized to preserve the real texture information. The algorithms used in this system can reduce the computational complexity and improve the stitching efficiency. The fidelity of the surround view is also improved, thereby optimizing the immersion experience of the system under the premise of preserving the information of the surroundings.
Two-Stage Diversity-Based Multiple Description Image Coding

In this letter, a diversity-based two-description image coding scheme is firstly presented and analyzed, for which a two-stage coding is introduced to facilitate the tuning of central/side distortion tradeoff. By subsampling the central decoded errors from the first stage to constitute the second part for each description, respectively, we show that not only the central distortion but also the side distortion can be reduced with the second stage information. We further generalize the proposed scheme to 4-description coding. Experiment results demonstrate that the proposed scheme outperforms the state-of-the-art techniques in terms of both central and side coding performance.
Detecting Stealthy Spreaders Using Online Outdegree Histograms

We consider the problem of detecting the presence of a sufficiently large number of hosts that connect to more than a certain number of unique destinations within a given time window, over high-speed networks. We call such hosts stealthy spreaders. In practice, stealthy spreaders can be symptomatic of botnet scans or moderate worm propagation. Previous techniques have focused on detecting sources with an extremely large outdegree. However, such techniques fail to detect spreaders such as bot scans in which each scanning host scans only a moderate, fixed number of destinations. In contrast, our scheme maintains a small, fixed size memory usage, and is still able to detect stealthy spreader scenarios by approximating outdegree histograms from continuous traffic. To the best of our knowledge, we are the first to study the efficient outdegree histogram estimation and stealthy spreader detection problems. Evaluation based on real Internet traffic and botnet scan events show that our scheme is highly accurate and can operate online.
Analysis and Evaluation on the Rear-End Crash of the Car with a Dummy

Based on a certain type car, the finite element model for whole car was developed in which the space occupied by the 50th percentile Hybrid III dummy and safety-belt restraint system. According to the basic principle of the dynamic explicit non-linear FEM, an equation describing the rear-end crash process and finite element discretization equation were given. Then the rear-end crash was simulated and analyzed, Solving the responses of structure deformation, the time curve of acceleration and energy absorption and dissipation during the whole crash process , as well as the response of dummy and the performance indicators including head, chest, thigh etc.. The energy absorption effect of the main energy-absorption components, and the state of fuel tank safety and driving safety during the rear-end crash process were analyzed. A more comprehensive evaluation of the car during the rear-end crash process and crash performance was achieved.
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach

We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. Classification networks are only responsive to small and sparse discriminative regions from the object of interest, which deviates from the requirement of the segmentation task that needs to localize dense, interior and integral regions for pixel-wise inference. To mitigate this gap, we propose a new adversarial erasing approach for localizing and expanding object regions progressively. Starting with a single small object region, our proposed approach drives the classification network to sequentially discover new and complement object regions by erasing the current mined regions in an adversarial manner. These localized regions eventually constitute a dense and complete object region for learning semantic segmentation. To further enhance the quality of the discovered regions by adversarial erasing, an online prohibitive segmentation learning approach is developed to collaborate with adversarial erasing by providing auxiliary segmentation supervision modulated by the more reliable classification scores. Despite its apparent simplicity, the proposed approach achieves 55.0% and 55.7% mean Intersection-over-Union (mIoU) scores on PASCAL VOC 2012 val and test sets, which are the new state-of-the-arts.
Sensorless control of doubly salient electromagnetic machine based on coordinate transformation

The sensorless control technology is widely adopted for various applications. In this paper, a novel sensorless control based on coordinate transformation is proposed for doubly salient electromagnetic machine (DSEM). Based on the characteristics of the back electromotive force (EMF), the rotor position signals would be constructed. In order to acquire the commutation instant accurately, two different coordinates are defined and named as original coordinate and transformed coordinate. The detection of three-phase terminal voltages and coordinate transformation are realized in the digital signal process chip of DSP2812, and the estimated position signal is gained by the zero-crossing point of the terminal voltage in the transformed coordinate. The terminal voltage in the transformed coordinate is shifted from the terminal voltage in the original coordinate which is detected by DSP2812. Detailed analysis of DSEM's terminal voltage and the transform angle between two 3-phase coordinates at different speeds are involved in this paper. The sensorless control method is independent with the PWM technologies. A 18kW DSEM prototype is built and the above analysis is verified by the experimental results.
On-demand multicast routing protocol with multipoint relay (ODMRP-MPR) in mobile ad-hoc network

protocol is an on-demand multicast routing protocol in mobile ad hoc network. This paper presents the on-demand multicast routing protocol with multipoint relay (ODMRP-MPR) which is based on ODMRP. ODMRP-MPR induces the multipoint relay technique to reduce the control overhead, obtain high scalability and effectively solve the unidirectional link problem of wireless communication. At the same time, ODMRP-MPR reserves the key merits of ODMRP such as high throughput and energy efficiency in conditions with frequently changing topology. We evaluate ODMRP-MPR performance with ODMRP for ad hoc networks via extensive and detailed simulation.
Characteristics analysis of five-phase fault-tolerant doubly salient electro-magnetic generators

Five-phase fault-tolerant doubly salient electromagnetic generator (FTDSEG) is proposed for high reliability applications in this paper. On the basis of comparative analysis on structure characteristics between five-phase non-fault-tolerant doubly salient electro-magnetic generator (NFTDSEG) and five-phase FTDSEG, the variation of stator and rotor pole number from NFTDSEG to FTDSEG is revealed and the phase width of back electromotive force (EMF) of five-phase FTDSEG approaching 144°is deduced. Then the flux linkage and EMF of five-phase NFTDSEG and five-phase FTDSEG are investigated using finite-element method with two dimensions and four fault modes of five-phase FTDSEG are analyzed in detail. The laws of fault operating influence on external and power characteristic of motor and output voltages of rectifier are researched in four fault modes with different exciting currents. Meanwhile, the reason why the output voltage of rectifier of single phase short circuit fault is bigger than open circuit fault is given. Finally, the fault-tolerant characteristic of five-phase FTDSEG is verified by the experimental results.
M-channel multiple description coding based on uniformly offset quantizers with optimal deadzone

This paper proposes an improved source-splitting-based two-rate M-channel multiple description coding scheme, where the source is split into M subsets. In each description, one subset is coded at a high rate, and others are predictively coded at a low rate. Uniform offsets among low-rate quantizers of different descriptions are achieved by employing unequal deadzones and by quantizing the predictions. When several descriptions are received, the optimal reconstruction of each subset is achieved by finding the intersection of all received quantization bins. The closed-form expression of the expected distortion is obtained. The proposed scheme is applied to lapped transform-based multiple description image coding and achieves improved performance. The optimal deadzone selection and its impact are also given in this paper.
An Anamnestic Semantic Tree-Based Relevance Feedback Method in CBIR System

Relevance feedback is a usually used technique to narrow the gap between high-level concepts and low-level visual features in the content-based image retrieval. In this paper, a novel long-term learning mechanism is proposed to grasp the retrieval intention as much as possible. With more retrieval sessions going on, an anamnesis semantic tree is constructed to record the semantic relationship between the query and the retrieved back images on the high level concepts. In the dynamic updating process of the anamnesis semantic tree, both the mean shift based query refining and clustering techniques are adopted. The final experimental results show that the proposed approach greatly improves the retrieval performance
Co-channel interference cancellation for MIMO CDMA wireless communications

Multiple-input and multiple-output (MIMO) systems have been shown to have a tremendous capacity in environments where no external interference exists. However, such a superior performance of MIMO channel is degraded in code-division multiple access (CDMA) communications, where co-channel interference (CCI) becomes the dominating channel impairment. In this paper, we explore CCI cancellation in CDMA communication systems adopting MIMO channels (MIMO CDMA). Our investigation is focused on a simple and effective interference cancellation (IC) technologies based on correlations. To further improve the system's reliability, turbo coding is combined into MIMO channel with IC to combat CCI. Simulation results are presented to show the excellent performance and implementation feasibility of the CCI combating algorithms investigated in this paper.
A New Transform with Extended Product to Exploit Different Scale Redundance

Fractal image coding (FIC) can exploit redundance at different scale in spatial domain. But there is no scheme presented to exploit the different scale redundance in frequency domain. In this paper, we extend the H product defined by Kou et al. Using the extended product, a new transform is constructed to exploit redundance at different scale in frequency domain. Meanwhile, a quantization method is proposed for the new transform. At last a new coder is constructed based on the new transform and quantization method. Experimental results suggest that the coder based on our transform can achieve better decoded image quality than FIC and JPEG, and the coding time of our coder is shorter than FIC
Debug of implant angle deviation based on SIMS analysis

The accuracy of ion implantation is very important in semiconductor manufacturing and will directly affect the performance of the individual devices and even the whole chip. The deviation of IMP energy, dose and angle are often encountered because of the abnormality of implant equipment or process design limit. The ion implantation energy, dose and angle information can be qualitatively and quantitatively analyzed through SIMS , which provides a way to diagnose the issue of ion implanter. Based on SIMS analysis results, we can judge whether ion implant results meet the requirements and whether the process design achieves the expected goal. In this paper we report a SIMS data processing method for the analysis of the deviation of ion implantation angle. A term of deviation rate was defined and the related calculation method was introduced, which is proportional to the deviation angles of the ion implanter. And then, a statistical analysis of a large number of data on deviation rates and ion implantation angles showed that the whole sampling data followed normal distribution, and thus the corresponding 3 sigma could be obtained. Using the determined 3 sigma range of the deviation rates, we can define the acceptable range for deviation rate. Further, we can use the actual deviation rate to judge if the implant equipment needs maintenance or not, or suggest the direction for improvement. The equipment's maintenance time and cost can thus be minimized. This method can be used as an early detection to find an abnormity in an ion implant tool.
Coarse-to-fine based matching for audio commercial recognition

In this paper, an automatic audio commercial recognition based on coarse-to-fine matching strategy is proposed. First, to index audio commercials in the database efficiently, the locality sensitive hash (LSH) is applied to accelerating the initial retrieval procedure. Second, with respect to the collision occurred in the initial LSH matching, a fine matching procedure based on Fine Granularity Successive Elimination (FGSE) is triggered out to eliminate rapidly those irrelevant candidates which have passed the initial coarse matching. At last, an elaborate post processing with correlation in time domain is presented for further decreasing false alarms following fine matching. The promising experiment results show that satisfactory precision and recall related to audio commercial recognition are obtained, achieving 99.4% and 97.5% respectively.
EKMPC: Enhanced KMP Allocation for Virtual Network Service Provision in Cloud

Virtualization is one of major capabilities in cloud. Computing and Storage virtualization is widely used in cloud. Networking virtualization becomes a trend of cloud computing. In past, user can only request a networking resource offline, virtual network can be allocation as needed. Allocating the network on demand will become a challenge for network. In this work in progress study, we propose an Enhanced KMP (Knuth-Morris-Pratt) algorithm for Virtual Network Allocation in cloud (EKMPC), which use the concept of KMP.
Efficient Solution of Time-Domain Surface-Wire Integral Equation for Predicting Electromagnetic Responses of Complex Structures

An efficient marching-on-in-time (MOT) scheme is proposed to solve the time-domain surface-wire integral equation (TD-SWIE) for complex structures. A suitable set of approximate prolate spheroidal wave functions (APSWFs) is chosen as the temporal basis functions. Moreover, a novel integration approach for handling weakly singular inner integrals, along with some new smoothing techniques for treating the outer surface integrals, is applied to the TD-SWIE solver. The proposed algorithm is successfully implemented for a variety of problems involving surface-wire antennas on platforms.