nils-herrmann/clean_scirepeval huggingface dataset:
Improved clustering Of spike patterns through video segmentation and motion analysis of micro electrocorticographic data

We have developed flexible, active, multiplexed recording devices for high resolution recording over large, clinically relevant areas in the brain. While this technology has enabled a much higher-resolution view of the electrical activity of the brain, the analytical methods to process, categorize and respond to the huge volumes of seizure data produced by these devices have not yet been developed. This paper examines a series of segmentation, feature extraction, and unsupervised clustering methods for interictal and itcal spike segmentation and spike pattern clustering. We first applied advanced video analysis techniques (particularly region growing and motion analysis) for spike segmentation and feature extraction. Then we examined the effectiveness of several different clustering methods for identifying natural clusters of the spike patterns using different features. These methdos have been applied to in-vivo feline seizure recordings. Based on both the similarity with a human clustering result and on the ratio of the intra-cluster vs. inter-cluster correlations, we found the best results by clustering using a Dirichlet Process Mixture Model on the correlation matrix of the spikes extracted using video segmentation. Effective clustering of spike patterns and subsequent analysis of the temporal variation of the spike pattern is an important step towards understanding how seizures initiate, progress and terminate.
The innovative application to traditional BT mode

With rapid development of society, construction upsurge appears in many cities. Under such background, the construction has changed greatly. As one new building mode, BT not only can solve government's capital shortage, but also can make best of private enterprises' advanced technology and management experience, so it is being applied more and more widely. But BT mode also has some shortcomings needing to be overcome. This paper first gives a review to traditional BT modes, and then introduces the application of BT in construction of Chong Qing's Chao Tian Men Yangtze River Bridge, which lasted from 2004 to 2009. In the construction process of this project, new innovative management structure and some management methods are put forward, which are improvement to traditional BT modes. Doing analysis to them has great practical sense to project construction and is good to enrichment of BT study.
Rate-distortion analysis of the multiple description motion compensation video coding scheme

Multiple description motion compensation (MDMC) is a multiple description video coding scheme that has shown good error resilience performance. MDMC enables one to vary coding parameters according to the desired trade-off between coding efficiency and error resilience. To fully utilize this advantage, one needs to establish a set of models, relating the rate, encoder distortion, and the end-to-end distortion after transmission, with the encoder parameters and channel parameters. Using these models, one can find the optimal coding parameters for given channel parameters and rate (or distortion) constraints. In this paper, we formulate and validate the rate and encoder distortion models.
Chip-to-wafer (C2W) 3D integration with well-controlled template alignment and wafer-level bonding

This paper presents on a novel chip-to-wafer (C2W) three-dimensional (3D) integration technology with well-controlled template alignment and wafer-level bonding, enabling precise alignment, few thermal cycles and high throughput of 3D system fabrication. The key processes are investigated and discussed in detail, including chip edge definition, template fabrication, C2W alignment and wafer-level bonding. The C2W 3D integration technology is successfully demonstrated using Cu daisy chains, a patterned thick benzocyclobutene (BCB) layer on the wafer as the alignment template, and wafer-level C2W Cu-Cu bonding. An alignment accuracy less than 2 μm is achieved. The FIB-SEM images reveal that Cu grains cross the original Cu-Cu bonding interface to form strong bonding. The measured I-V characteristics of daisy chains show a linear ohmic behavior, and the specific contact resistance of Cu-Cu bonding structures is on the order of 10−8 ohm-cm2, suggesting good electric contacts.
Second-order derivative-based smoothness measure for error concealment in DCT-based codecs

We study the recovery of lost or erroneous transform coefficients in image and video communication systems employing discrete cosine transform (DCT)-based codecs. Previously, we have developed a technique that exploits the smoothness property of image signals and recovers the damaged blocks by maximizing a smoothness measure. There, the first-order derivative was used as the smoothness measure, which can lead to the blurring of sharp edges. In order to alleviate this problem, we propose to use second-order derivatives as the smoothness measure. Our simulation results show that a weighted combination of the quadratic variation and the Laplacian operator can significantly reduce the blurring across the edges while enforcing smoothness along the edges.
Coded excitation methods in biomedical ultrasound

Peak acoustic power limits the signal to noise ratio of real-time ultrasound images. Since the average power of conventional scan formats is well below heating limits, the signal to noise ratio can be significantly increased using coded excitation. A coded system transmits a broadband, temporally elongated excitation pulse. The received signal must be decoded to produce an imaging pulse with improved signal to noise ratio resulting from the higher average power in the elongated excitation. A specific coding scheme appropriate for synthetic aperture imaging is presented. A 14.5 dB signal to noise ratio improvement is demonstrated on a forward-looking imaging system appropriate for intravascular applications.
Layered wireless video multicast using directional relays

In this paper, we explore the use of directional antennas in relay transmission to improve the performance of video multicast with omni-directional relays in infrastructure- based wireless networks. We describe the system setup with directional relays and determine the user partition along with transmission time scheduling that can optimize a multicast performance criterion. We demonstrate that directional relays significantly improve the multicast system performance compared to omni-directional relays. Furthermore, it also provides larger coverage area.
Error resilience property of multihypothesis motion-compensated prediction

The multihypothesis motion-compensated prediction (MHMCP) approach has shown significant gain in terms of coding efficiency both in theory and practice. However, the fact that it also enhances the error resilience of a codec has not been fully realized. This paper analyzes the error resilience gain of MHMCP. Models for the decoder distortion induced by transmission errors and the rate-distortion function of the encoder in a codec using MHMCP are presented and their accuracy is validated by simulation studies. Using these models, we show how to design the multihypothesis predictor to jointly consider the coding gain and the error resilience gain for given channel error characteristics.
High-Speed Compressed Sensing Reconstruction in Dynamic Parallel MRI Using Augmented Lagrangian and Parallel Processing

Magnetic resonance imaging (MRI) is one of the fields that the compressed sensing theory is well utilized to reduce the scan time significantly leading to faster imaging or higher resolution images. It has been shown that a small fraction of the overall measurements are sufficient to reconstruct images with the combination of compressed sensing and parallel imaging. Various reconstruction algorithms have been proposed for compressed sensing, among which augmented Lagrangian based methods have been shown to often perform better than others for many different applications. In this paper, we propose new augmented Lagrangian based solutions to the compressed sensing reconstruction problem with analysis and synthesis prior formulations. We also propose a computational method which makes use of properties of the sampling pattern and the singular value decomposition of the system transfer function to significantly improve the speed of the reconstruction for the proposed algorithms in Cartesian sampled MRI. The proposed algorithms are shown to outperform earlier methods especially for the case of dynamic MRI for which the transfer function tends to be a very large matrix and significantly ill conditioned. It is also demonstrated that the proposed algorithm can be accelerated much further than other methods in case of a parallel implementation with graphics processing units.
CNUSVM: Hybrid CNN-Uneven SVM Model for Imbalanced Visual Learning

Recently, deep Convolutional Neural Networks (CNNs) have been used to achieve state-of-the-art performance on a wide range of visual learning tasks. However, when facing some imbalanced learning tasks where the training samples are unevenly distributed among different classes, CNNs tend to produce performance bias toward the majority class, making them not suitable for applications in which the recognition ability on the minority class is highly valued. To address the problem, this paper proposes a hybrid classification model by combining CNN with Support Vector Machine (SVM) that has uneven margins. In this model, CNN works as a feature extractor and the extracted features are then sent into a L2-SVM with linear uneven margins. We also develop a gradient-descent learning approach for this hybrid CNN-uneven SVM (CNUSVM) model by minimizing an uneven margin based L2-hinge loss. Our experiments on two benchmark datasets show that the CNUSVM model can make more favorable decisions for imbalanced visual learning tasks in comparison with the standard CNN and the hybrid CNN-SVM model.
Production of a Novel Bioflocculant by Culture of Pseudomonas Alcaligenes Using Brewery Wastewater and Its Application in Dye Removal

In this study, the optimal conditions of production of bioflocculant by the culture of Pseudomonas alcaligenes PS-25 were examined, using brewery wastewater to replace glucose as carbon source and energy source in the culture medium. Results showed that the COD concentration in brewery wastewater favorable for the production of the bioflocculant was 5000 mg•L-1, and an optimal culture condition of inoculum size of 5%(v/v), 30 ¿C, initial pH 6.0 and shaking speed of 160 r•min-1, under the optimal culture conditions, the highest flocculating activity achieved for Kaolin suspension was 96.8% and 2.89 g bioflocculant per liter broth was obtained after 72 h cultivation. The bioflocculant produced using brewery wastewater substrate possesses flocculating activity comparable or superior to that of bioflocculant produced using conventional substrate. The bioflocculant was mainly composed of sugar (86.5%) and protein (11.2%), and an average molecular weight of 3.56×106 Da. Fourier transform infrared (FTIR) spectra showed that hydroxyl and carboxylate groups were present in the bioflocculant molecules. The bioflocculant was effective in flocculating some soluble reactive dyes in aqueous solution, reactive Light-Yellow K-4G and reactive Turquoise Blue KN-G with a decolorization efficiency of 92.1 and 90.5%, respectively¿using 25 mL of the flocculant in 500 mL of 100 mg•L-1 dye solution. The decolorization efficiency was dependent on the flocculant dosage and solution pH. The hydroxyl and carboxylate groups in the bioflocculant molecule are believed to play an important role in flocculation from the viewpoint of electrostatic interaction.
Semi-Blind Adaptive Spatial Equalization for MIMO Systems with High-Order QAM Signalling

This contribution investigates semi-blind adaptive spatial filtering or equalisation for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. A minimum number of training symbols, equal to the number of receivers (we assume that the number of transmitters is no more than that of receivers), are first utilized to provide a rough least squares channel estimate of the system is MIMO channel matrix for the initialization of the spatial equalizer is weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm, originally derived for blind equalization of single-input single-output and single-input multiple-output systems employing high-order QAM signalling, is then extended to adapt the spatial equalizers for MIMO systems. This semi-blind scheme has a low computational complexity, and our simulation results demonstrate that it converges fast to the minimum mean-square-error spatial equalization solution.
Implementing a Cooperative MAC Protocol for Wireless Video Multicast

Wireless video multicast enables delivery of popular events to many wireless users in a bandwidth efficient manner. However, providing good and stable video quality to a large number of users with varying channel conditions remains elusive. In our previous work, we integrated layered video coding with cooperative communication to enable efficient and robust video multicast in infrastructure-based wireless networks . Through simulation and analysis, we showed that cooperative multicast improves the multicast system performance and the coverage area. In this work, we integrate the proposed system with packet level Forward Error Correction (FEC) and evaluate the viability of the system in a realistic environment. We implement the system at the MAC layer and report the experimental results in a medium size (i.e., 8 stations) testbed. The experimental results confirm that the new cooperative MAC protocol for multicast, delivers superior performance.
Analytical rate model for compressed video considering impacts of spatial, temporal and amplitude resolutions

Rate-control (RC) algorithm is highly desirable for networked video applications. Almost all existing RC methods are only adapting the quantization stepsize (QS) to meet the target bit rate at fixed video frame size (FS) and frame rate (FR) using the rate-quantization (R-Q) model. Recent mobile video applications demand more advanced rate adaptation with different FS, FR and QS, rather merely quantization adjustment, to meet rapid wireless network bandwidth switch. Towards this goal, it requires an accurate rate model with respect to the FS, FR and QS. Hence, we investigate the impacts of spatial, temporal and amplitude resolution (STAR) on the bit rate of a compressed video. We propose a rate model as the product of power functions of the FS, FR and QS, respectively. The proposed rate model is analytically tractable, requiring only four content dependent parameters. The same model works for different coding scenarios (including scalable and non-scalable video, temporal prediction using either hierarchical B or IPPP structure, etc.) with very high accuracy using both H.264/AVC and HEVC. Using the proposed rate model and a quality model, we show how to optimize the STAR for a given rate constraint, which is important for both encoder rate control and network video adaptation.
Dynamic Diagnosis for Defective Reconfigurable Single-Electron Transistor Arrays

Single-electron transistor (SET) at room temperature has been demonstrated as a promising device for extending Moore’s law due to its ultralow-power consumption. Previous works proposed mapping approaches to implement Boolean functions on SET arrays. However, these approaches were based on an ideal assumption that the SET arrays are defect-free. Recently, a diagnosis method was proposed targeting at defective SET arrays. However, the approach was static, such that the performance is inefficient. As a result, in this paper, we propose a dynamic diagnosis approach that can efficiently identify the locations and the types of the defects in the SET arrays. The experimental results show that the proposed dynamic diagnosis approach can achieve the same results as the previous work with much less CPU time on a set of benchmarks. Furthermore, the proposed method spent a few seconds while the previous work exceeded the CPU time limit of 3600 s on some benchmarks.
Design and realize of 3D integration of a pressure sensor system with through silicon via (TSV) approach

Nowadays, three-dimensional (3D) integration has been widely applied in semiconductor and electronics industry. When 3D integration applied in MEMS (micro electromechanical system) packaging, it is possible to stack host MEMS chip/wafer with other chips/wafers (such as ASIC) to lower package profile and realize area array sensor system. In this paper, a miniaturized piezoresistive pressure sensor system with TSV structure has been designed to demonstrate the application of TSV in MEMS packaging. TSV in pressure sensor chip is designed to provide communication paths for electrical signals. Cu/Sn bump is electroplated after exposing TSV from backside and backside metallurgy. Signal read-out chip contains redistribution circuits and Au studs. The pressure sensor chip and signal read-out chip are flip chip bonded using Au-Sn eutectic bonding. To realize this pressure sensor system, a systematic process flow including piezoresistors fabrication and circuits patterning, TSV process, flip chip bonding, polymer hermetic sealing is designed and implemented experimentally.
A method to choose kernel function and its parameters for support vector machines

The support vector machines are the new statistical learning algorithm which is developed in recent years. They have some advantages in many regions like pattern recognition. The kernel function is important to its classification ability. This paper presents a crossbreed genetic algorithm based method to choose the kernel function and its parameters. The crossbreed genetic algorithm uses two fitness functions which are produced according to the two criterion of SVM's performance. The experiments proved that this algorithm can find effectively the optimal kernel function and its parameters, and it is helpful to increase the support vector machines' performance in fact.
Consideration and application of smart broadcasting

In this paper, a novel smart broadcasting system is proposed to realize efficient and reliable data distribution. Basically, the system combines the broadcasting and broadband, consisting of Brower server, middleware server, database server, broadcast server, as well as many distribution servers, FTP servers, and is based on one content recommendation algorithm in which Uniform Content Locator technique is also introduced. Besides, intelligent terminal is also presented as an output for the system. Finally, a campus based deployment of our system is described to show a case of real application.
A hybrid intelligent control for industrial rotary kiln plant

This paper presents a new hybrid intelligent control (HIC) scheme that combines the techniques of expert control and fuzzy neural networks. The HIC consists of a knowledge base, information pre-processor and intelligent coordinator in an hierarchical structure. The basic idea is to give an effective control strategy to complex controlled plant using a knowledge-based coordinator so as to achieve the desired performance. The results of simulation as well as temperature control for an industrial rotary kiln furnace were performed to demonstrate the feasibility and effectiveness of the proposed scheme.
Notice of RetractionEffect of pH and Temperature on Activity of Immobilized Lactonase

This work presents as a main objective to study influences of the pH and temperature on the activity of immobilized lactonase which converts D-pantoyl lactone stereospecifically to D-pantoic acid. The result indicated that the optimum pH of immobilized and free lactonase was 7.5. However we found that the change of free enzyme activity with the pH was faster than the immobilized enzyme. And the pH stability range of immobilized enzyme was 6.5 ~ 8.5, which was broader than that of free enzyme (pH 7-8). The result indicated that immobilization of free enzyme led to a shift of catalysis optimal temperature towards higher values. The optimum temperature of free lactonase and the immoblized enzyme were 30°C and 40°C respectively. The thermostability of the immobilized enzyme was obviously better than free enzyme.
Application model of Small Containerized Cargo Units in integrated transportation: A case study

Concerning the current increasing demand for cargo shipment in small-batches with high-security and fast-delivery service performance that railway transportation enterprises faced with, this paper analyzes the rail express logistical processes from a systematic perspective in order to improve its service quality and efficiency. Based on supply chain integration, standardization and containerization theory, this paper designs a new application model utilizing small containerized cargo units (SCCU) placed on pallets for fast and easy handling, and puts forward a proposal for the unitization of such SCCU in order to achieve seamless transport operations from shippers to logistics services providers and then to the final cargo destination. Design principles of SCCU are specified as well. We also provide a case study of our model with the pilot project of China railway express, the biggest domestic railway express company. This best practice testifies the effect and feasibility of the SCCU model.
Low Capacitance Through-Silicon-Vias With Uniform Benzocyclobutene Insulation Layers

Low capacitance is critical to the electric performance of through-silicon-vias (TSVs). This paper reports the development of a low capacitance TSVs by replacing silicon dioxide insulation layers (liners) with benzocyclobutene (BCB) polymer. The BCB liner TSVs are fabricated by etching deep annular trenches on substrates, void-free filling the trenches with BCB polymer, selective etching the silicon post in the annular trenches, and filling the via with copper. Key fabrication processes including void-free BCB polymer filling in deep trenches, BCB chemical mechanical planarization, and selective etching of silicon post to BCB are developed. TSVs with BCB liners are successfully fabricated and the electrical performance is measured. The measurement results show that the capacitance of the BCB liner TSVs is around 42 fF, and the leakage currents to substrates and to neighboring TSVs are 2.2 pA and 1.1 pA at 10 V voltage, respectively. These preliminary results demonstrate the feasibility of the proposed fabrication technology and the efficacy of BCB liners in reducing TSV capacitance.
Development and Application of a New Sulfur Dioxide Sorbent Based on Sewage Sludge

Sewage sludge-derived materials and two sorts of industrial solid waste were used to produce a sorbent for sulfur dioxide adsorption at low concentration. The sulfur dioxide capacity was measured according to a laboratory-developed breakthrough test. Uniform Design Method was used to formulate the different ratios of the three main raw materials and the desulfurizer HN04 was chosen as the optimal sorbent due to the highest sulfur dioxide capacity8.8 mg¡¤g-1 and the largest BET 13.1771 m2¡¤g -1. The effects of a few conditions on the SO2 removal behavior of the sorbent were studied. The results evince that the sorbent HN04 under the best conditions of 5714 mg¡¤m-3 inlet SO2 concentration, 2000h-1 space velocity and 473K desulfurization temperature in steam has the maximum breakthrough sulfur dioxide capacity 9.7 mg¡¤g-1.