nils-herrmann/clean_scirepeval huggingface dataset:
ESUR: A system for Events detection in SURveillance video

In this paper, we present our eSur (Event detection system on SURveillance video) system, which is derived from TRECVID'09 surveillance tasks. Currently, eSur attempts to detect two categories of events: 1) single-actor events (i.e., PersonRuns and ElevatorNoEntry) irrespective of any interaction between individuals, and 2) pair-activity events (i.e., PeopleMeet, PeopleSplitUp, and Embrace) involves more than one individual. eSur consists of three major stages, i.e., preprocessing, event classification, and post-processing. The preprocessing involves view classification, background subtraction, head-shoulder detection, human body detection and object tracking. Event classification fuses One-vs.-All SVM and rule-based classifiers to identify single-actor and pair-activity events in an ensemble way. To reduce false alarms, we introduce prior knowledge into the post-processing, and in particular, we apply a so-called event merging process over TRECVID dataset. Extensive experiments have been performed over TRECVid'08 and '09 ED data corpus involving in total 144 hours surveillance video of London Gatwick airport. According to the TRECVid-ED formal evaluation, our prototype has yielded fairly promising results over TRECVid'09 dataset, with top Act.DCR of 1.023, 1.025, 1.02, and 0.334 for PeopleMeet, PeopleSplitUp, Embrace, and ElevatorNoEntry, respectively.
Hyperspectral Image Restoration Via Total Variation Regularized Low-Rank Tensor Decomposition

Hyperspectral images (HSIs) are often corrupted by a mixture of several types of noise during the acquisition process, e.g., Gaussian noise, impulse noise, dead lines, stripes, etc. Such complex noise could degrade the quality of the acquired HSIs, limiting the precision of the subsequent processing. In this paper, we present a novel tensor-based HSI restoration approach by fully identifying the intrinsic structures of the clean HSI part and the mixed noise part. Specifically, for the clean HSI part, we use tensor Tucker decomposition to describe the global correlation among all bands, and an anisotropic spatial–spectral total variation regularization to characterize the piecewise smooth structure in both spatial and spectral domains. For the mixed noise part, we adopt the $\ell _1$ norm regularization to detect the sparse noise, including stripes, impulse noise, and dead pixels. Despite that TV regularization has the ability of removing Gaussian noise, the Frobenius norm term is further used to model heavy Gaussian noise for some real-world scenarios. Then, we develop an efficient algorithm for solving the resulting optimization problem by using the augmented Lagrange multiplier method. Finally, extensive experiments on simulated and real-world noisy HSIs are carried out to demonstrate the superiority of the proposed method over the existing state-of-the-art ones.
Lattice priority scheduling: Low-overhead timing-channel protection for a shared memory controller

Computer hardware is increasingly shared by distrusting parties in platforms such as commercial clouds and web servers. Though hardware sharing is critical for performance and efficiency, this sharing creates timing-channel vulnerabilities in hardware components such as memory controllers and shared memory. Past work on timing-channel protection for memory controllers assumes all parties are mutually distrusting and require timing-channel protection. This assumption limits the capability of the memory controller to allocate resources effectively, and causes severe performance penalties. Further, the assumption that all entities are mutually distrusting is often a poor fit for the security needs of real systems. Often, some entities do not require timing-channel protection or trust others with information. We propose lattice priority scheduling (LPS), a secure memory scheduling algorithm that improves performance by more precisely meeting the target system's security requirements, expressed as a lattice policy. We evaluate LPS in a simulated 8-core microprocessor. Compared to prior solutions [34], lattice priority scheduling improves system throughput by over 30% on average and by up to 84% for some workloads.
Study on three-phase four-wire wiring D-STATCOM control mode based on Instantaneous Symmetrical Components method

One of the main reasons causing unbalance wave of three-phase current and voltage in three-phase four-wire distribution grid is the three-phase unbalance load. This paper proposes a new control method of positive sequence, negative sequence and zero sequence direct current control based on the Instantaneous Symmetrical Components which can decompose the three-phase current and voltage into sequence components. The control method is used in the distribution grid which parallel with D-STATCOM to make three-phase current symmetry at grid side. The positive sequence current control is used to control the D-STATCOM to generate the three-phase positive sequence current that gird required. In order to maintain the three-phase current balance, negative sequence and zero sequence current should be transformed from the ABC coordinate system to the DQ0 synchronous rotating coordinate system and subtract with expected value 0. Simulation results are presented to verify the validity of the proposed control strategy. It can not only inhibit three-phase unbalance current, but also filter out high frequency harmonics in the distribution grid.
An investigation into the impacts of the crucial factors on EVs charging load

Nowadays, the development of electric vehicles (EVs) is encouraged in China to address the issues about the energy security and the environment. In this study, the impacts of some crucial factors on the total charging load are investigated, such as the charging rate of the charging infrastructures, the battery capacity, the preference of the charging behavior and the penetration level of the charging infrastructures in public places. A methodology is presented to estimate the charging load which needs a sample consisting of the charging schedules of a great number of EVs. As the sample isn't available at present, a real-world travel dataset of conventional vehicles is taken advantage of to generate the sample by simulating EVs considering the factors mentioned above. Thereby, the estimations of the charging load corresponding to the different values of the factors are attained, which is used for investigating the impacts of these factors in turn. Some conclusions are: 1) the charging rate of the charging infrastructures in public places has a small impact on the charging load; 2) although the larger battery capacity leads to the larger power demand, the increment is minor; 3) the preference of the charging behavior of the owners influences the charging load significantly.
Multiview video sequence analysis, compression, and virtual viewpoint synthesis

This paper considers the problem of structure and motion estimation in multiview teleconferencing-type sequences and its application for video-sequence compression and intermediate-view generation. First, we introduce a new approach for structure estimation from a stereo pair acquired by two parallel cameras. It is based on a 2-D mesh representation of both views of the imaged scene and a parametrization of the structure information by the disparity between corresponding nodes in the image pair. Next, we describe a novel image alignment approach which can convert images captured using nonparallel cameras to coplanar-like images. This approach greatly eases the computational burden incurred by the nonparallel camera geometry, where one must consider both horizontal and vertical disparities. Finally, we present a coder for multiview sequences, which exploits the proposed alignment and structure estimation algorithm. By extracting the foreground objects and estimating the disparity field between a selected view and a reference view the coder can compress the image pair very efficiently. In the meantime, by using the coded structure information, the decoder can generate virtual viewpoints between decoded views, which can be very helpful for telepresence applications.
Coding of motion compensation residuals using edge information

In most current video coders, a block is first predicted from its best matching block in a previous frame, and the prediction error is then coded using discrete transform coding (DCT). Because of the inadequacy of the block-wise translational motion model, edges in the predicted block are often shifted from their true positions, leading to errors that are clustered around edges in the predicted block. DCT is inefficient for coding such errors. Independent searching of block motion vectors also lead to discontinuities of edges across block boundaries. Existing coders ignore such correlation between error location and edge discontinuity. We describe a coder that corrects edge-misalignment before applying DCT coding. The correlation between edge-discontinuity and edge-misalignment is exploited in the coding of the misalignment parameters.
Polymer Liner Formation in High Aspect Ratio Through-Silicon-Vias for 3-D Integration

Replacing silicon dioxide with polymers that have low dielectric constants as the insulation (liner) materials is of great help in reducing the capacitive coupling of throughsilicon-vias and improving the reliability. This paper presents the fabrication of uniform poly propylene carbonate (PPC) polymer liners in high aspect ratio trenches by addressing the difficulty in coating PPC layers on via inner walls. A unique spin-coating method is developed by using vacuum treatment and solvent refill techniques for PPC liner formation for circular and annular trenches. Vacuum treatment and solvent refill facilitate PPC filling in high aspect ratio vias by preventing formation of air bubbles in the vias. By investigating the flow behaviors of PPC precursors and optimizing the spin-coating parameters, an optimal fabrication process is achieved. Using this newly developed technique as well as the optimized processing parameters, uniform PPC liners are successfully fabricated on the inner walls of circular vias with coating aspect ratio greater than 9:1 and the annular vias with filling aspect ratio of 24:1.
Effect of transverse force on the performance of quartz resonator force sensors.

This paper discusses the effect of transverse force on the performance of quartz crystal resonator (QXR) force sensors that use symmetrical incomplete circular QXRs as sensing elements. Based on Lee's vibration theory and the transverse force-induced stress distribution, frequency changes are derived. This result and finite element method (FEM) are applied to investigate the performance of two metal-quartz combined sensors under the action of transverse force. Analytical and experimental results show that transverse force affects the sensitivity and linearity of QXR force sensors.
CSL: Coordinated and scalable logic synthesis techniques for effective NBTI reduction

Negative Bias Temperature Instability (NBTI) has become a major reliability concern in nanoscale designs. Although several previous studies have been proposed to address the NBTI effect during logic synthesis, their performance is limited because of focusing on a certain logic synthesis stage. Additionally, their complicated algorithms are not scalable to large designs. To tackle this, we propose a coordinated and scalable logic synthesis approach, which integrates techniques at different logic synthesis stages, ranging from subject graph to technology mapping and mapped netlist, to achieve an effective NBTI reduction. To our best knowledge, this is the first work that considers and mitigates NBTI impact in subject graphs, the earlier stage of logic synthesis. Experimental results on industry-strength benchmarks show that our approach can achieve 6.5% NBTI delay reduction with merely 2.5% area overhead on average, while a previous work barely gets NBTI delay reduction when the circuits are optimized beforehand, the circuit sizes are large, and standard cell libraries are richer.
QoE assessment and prediction method for high-definition video stream using image damage accumulation

The accuracy of the traditional assessment method of the quality of experience (QoE) has been facing challenges with the growth of high-definition (HD) video streaming services. Image display-quality damage is the main factor that affects the QoE in HD video services through UDP network transmission. In this paper, we introduce a novel objective factor known as image damage accumulation (IDA) to assess user's QoE in HD video services. First, this paper quantitatively analyzed the effect on user quality of experience by IDA and established a mapping relationship between mean opinion scores and IDA. Furthermore, the probability of image damage caused by compression and transmission were analyzed. Based on this analysis, an objective QoE assessment and prediction method for HD video stream service that evaluated the user experience according to IDA are proposed. The proposed method can achieve assessment and prediction accuracy on three distinct subjective tests.
Iris recognition using scattering transform and textural features

Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all biometric features, iris is known to possess a rich set of features. Different features have been used to perform iris recognition in the past. In this paper, two powerful sets of features are introduced to be used for iris recognition: scattering transform-based features and textural features. PCA is also applied on the extracted features to reduce the dimensionality of the feature vector while preserving most of the information of its initial value. Minimum distance classifier is used to perform template matching for each new test sample. The proposed scheme is tested on a well-known iris database, and showed promising results with the best accuracy rate of 99.2%.
Face detection and tracking in video using dynamic programming

Face detection and tracking are important in video content analysis since the most important objects in most video are human beings. This paper proposes a new approach for combined face detection and tracking in video. The face detection algorithm is a fast template matching procedure using iterative dynamic programming (DP). Although the face detection algorithm is designed for frontal face, the same mechanism can also be applied to track non-frontal faces with online adapted face models. Due to the essence of template matching, the algorithm is capable of comparing the similarity among different faces, which makes it suitable for tracking the same face that occur at disjointed temporal locations in video. While the proposed face detection method provides comparable accuracy as the neural network based approach, it is much faster.
Constant frequency turn-on time control dynamic voltage scaling boost converter

Constant On-Time (Constant On-Time, COT) control technique has been widely used for industry application. It regulates output voltage of switching converter by adjusting variation of switch frequency. In this paper, input voltage feed-forward and output reference voltage feedback based Constant Frequency Turn-On Time (CFOT) control technique is proposed. By introducing input voltage feed-forward and output reference voltage feedback compensation, CFOT control technique avoid the variation of switching frequency under the variation of input voltage and /or output voltage. Similar to COT control technique, CFOT also has simple control loop and fast transient response. Moreover, error amplifier and its corresponding compensation network are not needed. Simulation results verify the validity of the proposed CFOT control technique.
A Compact-Area Low-VDDmin 6T SRAM With Improvement in Cell Stability, Read Speed, and Write Margin Using a Dual-Split-Control-Assist Scheme

Previous 6T SRAMs commonly employ a wordline voltage underdrive (WLUD) scheme to suppress half-select (HS) disturbs in read and write cycles, at the expense of reduced cell read current (<inline-formula> <tex-math notation="LaTeX">$I_{\mathrm {CELL}}$ </tex-math></inline-formula>) and degraded write margin (WM). This paper proposes the dual-split-control (DSC) scheme, including split WLs and split cell VSS (CVSS), for 6T SRAM to maintain a compact cell area and improve HS cell stability during the read and write cycles without degrading <inline-formula> <tex-math notation="LaTeX">$I_{\mathrm {CELL}}$ </tex-math></inline-formula> and WM. A segmented CVSS-strapping scheme is developed to suppress the ground bounce on the split-CVSS lines. The CVSS voltage for S6T can be generated by either a constant voltage source or a charge-sharing-based CVSS generation scheme. A 28-nm 256-kb DSC6T SRAM macro was fabricated and achieves a 280-mV lower VDDmin than a conventional 6T SRAM.
An intelligent high-frame-rate video logging system with real-time image processing at 1000 fps

This paper introduces an intelligent high-frame-rate video logging system that can automatically detect high-speed unpredictable behavior and record video comprising images with dimensions of 512 × 512 pixels at 1000 fps. To capture high-frame-rate video of crucial moments of abnormal behavior in high-speed periodic motion, a real-time abnormal behavior detection algorithm is implemented on a highspeed vision platform, IDP Express, which can record both input images and processed results at 1000 fps for video logging. Several experiments were performed using a machine with repetitive operation at a frequency of 15 Hz and video of the abnormal behavior was automatically recorded to verify the effectiveness of our system.
A platform for seamless interworking among conventional LANs and ATM networks

Internetworking of FDDI, Ethernet or other local area networks including the ATM-LAN to the public ATM networks will involve the development of the ATM hub. Taking the performance and cost-effective factors into account, a scalable two-stage switching hub platform is proposed for private network environment with ATM-ready capabilities. Packet as well as cell switching architectures are adopted for the design of the switching fabrics. The architecture applies the concept of each source/destination port pair with dedicated input and output queues. A generalized multisubsystem interconnect adapter (MIA) is also proposed for heterogeneous subsystems to a common switching fabric. The design complexity versus performance of the I/O queues' number and length are analyzed. Finally, an implementation-leading approach of the MIA is presented.
Implementation of Air-Gap Through-Silicon-Vias (TSVs) Using Sacrificial Technology

Using air-gaps to replace conventional silicon dioxide as the insulators of through-silicon-vias (TSVs) has the possibility to improve the electrical performance and some thermal reliability issues of TSVs. This paper reports the implementation of TSVs with air-gap insulators by developing a polymer sacrificial technology. The sacrificial technology and the key fabrication processes are investigated in detail, including spin-coating of poly propylene carbonate (PPC) on the sidewalls of blind vias, copper chemical-mechanical polishing, PPC grinding, and PPC pyrolysis to form air-gaps. To address the technical challenge in coating thin and conformal PPC sacrificial claddings in blind vias, a vacuum-assisted solvent refilling technique is developed. Air-gap TSVs are successfully fabricated and the electrical performances are characterized. The accumulation capacitance of the air-gap TSVs is 48 fF, and the leakage current is as low as 1.22 pA at bias voltage of 20 V. Finite element simulation shows that air-gaps are able to reduce thermal stresses. The preliminary results demonstrate the feasibility of the sacrificial technology and the good electrical performance of air-gap TSVs.
A Machine Vision Intelligent Inspector for Injection

A machine-vision-based intelligent Inspector for injection is presented. The rotating detection wheel mechanical structure and electric control system based on motion card and data I/O card are illustrated in detail. The inspection flow and optical structure are described. A method using the high-speed camera is applied for obtaining the image sequences. The second-order difference and accumulative energy method are used for identifying the small moving targets. Finally, the arithmetic of separate bubbles and foreign substances based on support vector machine (SVM) is proposed. It can accurately determine whether there are tiny foreign substances in injection. The experiments demonstrate that the detection algorithm is effective and the device of inspector is feasible.
Access mode of EVs to grid based on VPP

The rapidly increasing amount of Electric Vehicles has attracted more and more concerns of both the auto industry and the power industry. The complex interactions between electric vehicles on a large scale with the power grid constitute a considerable challenge regarding the feasibility, the efficiency and the stability of the grid. On one hand, as the capacity of a single EV is rather small compared to the grid, its visibility in the grid, thus regulating effect of it is not apparent. Therefore, large-scale electric vehicles which are integrated together through an aggregator could be effective. On the other, the VPP concept aims to integrate distributed generations, storage devices and controllable loads to participate in the electricity and ancillary service makets. So it is possible and meaningful to combine VPP and EVs. This paper analyses the characteristics of EVs and summaries several possible access modes of EVs to Grid. After a detailed introduction of VPP concept and its participation mechanism, the paper aims to propose an accessing mode based on the VPP concept. In addition, the advantages of the mode is summarized in this paper.
Multispectral code excited linear prediction coding and its application in magnetic resonance images

This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.