nils-herrmann/clean_scirepeval huggingface dataset:
An effective puncturing algorithm for QC-LDPC codes with dual-diagonal structure

Puncturing is an effective method to achieve rate compatible. However, the existing puncturing algorithms are complex and difficult to implement by hardware. This article researches on puncturing algorithm for QC-LDPC codes with dual-diagonal structure. Taking LDPC codes under IEEE802.16e standard as an example, this paper proposes a simple puncturing algorithm to achieve bit-rate compatible. Based on dual-diagonal structure, the puncturing algorithm chooses variable nodes with low degree for deletion and follows the rule that the deleted variable nodes should not be in the same calibration equation as far as possible. The simulation shows that the proposed puncturing algorithm is simple and effective, and the sub-codes obtained through the puncturing have better BER performance than that of random puncturing and order puncturing. In addition, because the puncturing matrix does not need to send to the receiver, it reduces a lot of overhead. Overall, the proposed puncturing algorithm is very practical to achieve rate compatible.
Research on spatial query by sketch

Spatial database contains a great deal of topological and directional semantics. But traditional spatial data query methods didn't make good use of these high level semantics. To overcome this conceptual gap, this paper proposes a spatial data query method based on sketch using 9-intersection model and Deep-Direction-Relation Matrix. This method integrates direction relations and topological relations and can handle all data types in geographical databases. This paper outlines an algorithm based on the solutions of Binary CSP and spatial neighborhood relations. A prototype has been developed to experiment the method this paper proposed.
The Application and Research of Noise Data Acquisition with Wireless Network

The paper applied the data acquisition technology based on wireless network to noise automatic monitoring, combined with the hot issue of remote data transmission, explored and researched the noise data acquisition technique in the environment acoustic GIS management system of Wuhan. And it designed and realized the encapsulation format of the sending data, stored the data into the database of remote Server by using GPRS to connect the Internet, and then implemented the real-time display of the noise data with programming. The paper provides a new method for environmental planning, monitoring, decision support and scientific evaluation, and it has very important reference value for environmental monitoring.
Robust object re-identification with Grassmann subspace feature for key points aggregation

Object Re-identification is a key technology for enabling mobile visual search, virtual reality and augmented reality, and a variety of security and surveillance applications. One key problem in re-identification is to have effective key point feature aggregation schemes that can preserve recall performance in short listing, while offering indexing and hashing efficiency.  Standardization effort, the Scalable Compressed Fisher Vector (SCFV) was proved to be most efficient in this role. In this paper we develop a novel aggregation scheme that captures the subspaces where key points reside, and uses the Grassmannian distance metric to discriminate the aggregated information. Simulation demonstrates that the proposed scheme captures discriminative information complementary to the Fisher Vector (FV) aggregation, and can significantly improve the matching performance.
An Efficient Four-Parameter Affine Motion Model for Video Coding

In this paper, we study a simplified affine motion model-based coding framework to overcome the limitation of a translational motion model and maintain low-computational complexity. The proposed framework mainly has three key contributions. First, we propose to reduce the number of affine motion parameters from 6 to 4. The proposed four-parameter affine motion model can not only handle most of the complex motions in natural videos, but also save the bits for two parameters. Second, to efficiently encode the affine motion parameters, we propose two motion prediction modes, i.e., an advanced affine motion vector prediction scheme combined with a gradient-based fast affine motion estimation algorithm and an affine model merge scheme, where the latter attempts to reuse the affine motion parameters (instead of the motion vectors) of neighboring blocks. Third, we propose two fast affine motion compensation algorithms. One is the one-step sub-pixel interpolation that reduces the computations of each interpolation. The other is the interpolation-precision-based adaptive block size motion compensation that performs motion compensation at the block level rather than the pixel level to reduce the number of interpolation. Our proposed techniques have been implemented based on the state-of-the-art high-efficiency video coding standard, and the experimental results show that the proposed techniques altogether achieve, on average, 11.1% and 19.3% bits saving for random access and low-delay configurations, respectively, on typical video sequences that have rich rotation or zooming motions. Meanwhile, the computational complexity increases of both the encoder and the decoder are within an acceptable range.
Experimental Study on Automatic Control Technology in Prestressed Concrete Structure

Prestressed concrete is wildly used on slope retaining(anchor bar or anchor rope), bridge, architectonics engineering and so on. Combined automatic control technology with tensioning device, the prestress was tensioned directly by data change between tensioning robot and programmable automatic controller in system, the automatized process of construction could be practiced. It is shown that the dual control of prestress tensioning can attain to high accuracy and efficiency by the prestressed robot, and fulfill the demand of practical application in prestressed concrete structures and has wide engineering background and good applying prospect.
A fuzzy MCDM model for knowledge service vendor evaluation and selection

Knowledge service vendor selection is an important task for the decision makers of the company in the knowledge economics. The purpose of this study is to investigate a fuzzy multiple criteria decision-making method for evaluating and selecting knowledge service vendor. In the paper, the multiple criteria should consider in the evaluation and selection process is presented. Then, a fuzzy MCDM approach based on fuzzy TOPSIS is proposed. The linguistic evaluation information given by the decision makers are transformed into the form of triangular fuzzy numbers. Based on the extended TOPSIS, the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are determined. The relative closeness of each alternatives to the FPIS and FNIS is calculated to determine the ranking order of all alternatives. The evaluation results of the knowledge service providers can be obtained through the proposed fuzzy method and then the proper vendor can be selected. Additionally, an illustrating example is given to show the feasibility and practicability of the proposed approach.
Enhancing /spl epsiv/-approximation algorithms with the optimal linear scaling factor

Finding a least-cost path subject to a delay constraint in a network is an NP-complete problem and has been extensively studied. Many works reported in the literature tackle this problem by using epsiv-approximation schemes and scaling techniques, i.e., by mapping link costs into integers or at least discrete numbers, a solution which satisfies the delay constraint and has a cost within a factor of the optimal one, that can be computed with pseudopolynomial computational complexity. In this paper, having observed that the computational complexities of the epsiv-approximation algorithms using the linear scaling technique are linearly proportional to the linear scaling factor, we investigate the issue of finding the optimal (the smallest) linear scaling factor to reduce the computational complexities, and propose two algorithms, the optimal linear scaling algorithm (OLSA) and the transformed OLSA. We analytically show that the computational complexities of our proposed algorithms are very low, as compared with those of epsiv-approximation algorithms. Therefore, incorporating the two algorithms can enhance the epsiv-approximation algorithms by granting them a practically important capability: self-adaptively picking the optimal linear scaling factors in different networks. As such, epsiv-approximation algorithms become more flexible and efficient
Local stability of random exponential marking

Random exponential marking (REM) is an attractive adaptive queue management algorithm. It uses the quantity known as 'price' to measure the congestion in a network. REM can achieve high utilisation,small queue length,and low buffer overflow probability. Many works have used control theory to provide the stable condition of REM without considering the feedback delay. Recently,sufficient conditions for local stability of REM have been provided when the sources have a uniform one- or two-step feedback delay. Nevertheless,no work has been done for the case of arbitrary uniform delay. The authors propose a continuous time model to generalise the local stable condition for REM in a multilink and multisource network with arbitrary uniform feedback delay.
Pulse Optimization and Control of Quantum Cascade Laser via an All-Optical Approach

Pulse optimization and control are demonstrated in a standard middle-infrared quantum cascade laser by illuminating its front facet with two near-infrared lasers. The 1550- and 850-nm near-infrared lasers are used to optimize the pulse rise/fall time and the pulse shape, respectively, of the quantum cascade laser. Compared with the electric drive, the electron interband transition is directed by the all-optical approach. Simultaneously, the quantum cascade laser’s pulse width, amplitude, and repetition rate are controlled precisely by changing the two near-infrared lasers’ delay time, average power, and repetition rate. Such an all-optical approach is beneficial in the high-speed optimization and control of the quantum cascade laser pulse. It has the potential for application in free-space optical communication and high-speed frequency modulation spectroscopy.
An Improved Genetic Algorithm for Flow Shop Sequencing

Flow shop sequencing is one of the most well-known production scheduling problems and a typical NP-hard combinatorial optimization problem with strong engineering background. To efficiently deal with flow shop sequencing problems, an improved genetic algorithm using novel adaptive genetic operators is proposed. Researches are made in aspects such as problem modeling, encoding, decoding, crossover and mutation of genetic algorithms and so on. The proposed algorithm has been tested on scheduling problem benchmarks. Experimental results show that improved genetic algorithm is quite flexible with satisfactory results, and require fewer running time than pure genetic algorithms and simulated annealing
Free Vibration Analysis of Spatial Curved Beams with Variable Curvature and Torsion

For the purposes of investigating the free vibration response of the spatial curved beams, a set of deferential equations of motion are derived in matrix formats, considering the variable curvature and torsion. The theory includes all the effects of rotary inertia, shear and axial deformations. Frobenius’ scheme and the dynamic stiffness method are then applied to solve these equations. A further numerical analysis shows that only a limited number of terms in the resultant provide a relatively accurate solution.
Mining Complex Time-Series Data by Learning Markovian Models

In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of pattern directly from the data, our approach extracts the temporal structure of the time-series data by learning Markovian models, and then uses well established methods to efficiently mine a wide variety of patterns from the topology graph of the learned models. We consolidate the approach by explaining the use of some well-known Markovian models on mining several kinds of patterns. We then present a novel high-order hidden Markov model, the variable-length hidden Markov model (VLHMM), which combines the advantages of well- known Markovian models and has the superiority in both efficiency and accuracy. Therefore, it can mine a much wider variety of patterns than each of prior Markovian models. We demonstrate the power of VLHMM by mining four kinds of interesting patterns from 3D motion capture data, which is typical for the high-dimensionality and complex dynamics.
Light Weight Content Fingerprinting for Video Playback Verification in MPEG DASH

Adaptive HTTP Streaming solutions are phasing out traditional online video distribution solutions such as progressive download. MPEG DASH is an open standardized solution that has been developed to minimize solution fragmentation and to ensure quick market adoption. However, the openness of the standard loosens the grip of content providers on the client behavior and may threaten the success of the whole ecosystem. This paper proposes a content fingerprinting and verification mechanism for restricting the client's playback behavior in such an open environment by using a very light weight Eigen thumbnail appearance differential fingerprinting. Simulation results demonstrate the effectiveness of the proposed solution.
Efficient Measurement of Thermal Coupling Effects on Multichip Light-Emitting Diodes

With the emerging market for multichip module based high-power LED systems, the demand for advanced thermal management techniques has been steadily growing. This paper presents a model developed by the authors for thermal coupling matrix that can calculate temperature distribution at a given heat power of each chip. The model significantly simplifies the task of measuring thermal coupling effect on multichip light-emitting diodes with symmetrical structure, while simultaneously preserving temperature accuracy. The modeling technique was validated experimentally on three-, four-, and six-chip rectangular modules, and a ten-chip circular module, by infrared thermography and transient thermal measuring system, respectively. The modeling technique was found to be more efficient especially for large systems. The model offers a rapid way to predict thermal coupling behaviors of multichip LED systems.
A point correlation based subpixel image registration algorithm

This paper presents a fast image registration algorithm with sub-pixel accuracy for IC package industry. The algorithm is based on point correlation method and improved mainly in two aspects. One is using entropy as correlation measure function and the other is proposing pair-wise exchange algorithm to obtain the pre-defined set of points. It also includes spline interpolation model that ensures the algorithm with sub-pixel accuracy. Simulation results confirm the validity of the presented algorithm.
Notice of RetractionComparative study of the nucleotide sequence of MyoG gene between pig and 11 different species

Utilizing direct sequencing technique, a consensus nucleotide sequence of pig MyoG gene was got from 63 individuals in this experiment. At the same time, the MyoG gene sequences of 11 different species were collected from Genbank. The coding sequence and deduced amino acid sequences of these species were compared to study the genetic diversity and phylogeny of MyoG gene between pig and other species. The results indicated that the identity of amino acid of MyoG gene was high, but compared with mammal in all of these 5 detected fishes there were three similar extra sequence fragments existing near 260, 300 and 740 site of the coding sequence. Phylogenetic tree of different species were constructed from the coding sequence of MyoG gene. The species grouped into two lineages, one consisted of mammalians include human being, swine, cattle and mouse; another consisted of 5 different kinds of fish. Chicken formed an independent branch on the tree but was closer to mammals. The results were coincident with the traditional taxonomy conclusion. From this study, we can conclude that some highly conservative sequence obtained from functional gene can be used in the phylogeny study to reconstruct the phylogenetic tree between some far species in the taxonomy.
Isotherm, Kinetic and Thermodynamic Analysis of Bromelain Adsorption on Reactive Blue 4 Immobilized Composite Membranes

The behavior of bromelain adsorption on the dyeligand affinity membrane was investigated at 277,298 and 310K, which was chitosan (CS) coated to decrease the non-specific adsorption of protein. Reactive Blue 4 was immobilized onto the CS-coated nylon membrane as an affinity ligand. In order to examine the rate limiting step of Reactive Blue 4-immobilized composite membrane adsorption, the two adsorption kinetic model: the pseudo-first-order and the pseudo-second-order were tested with the experiment data. Results indicated that Freundlich isotherm was able to adequately describe the adsorption of bromelain on dye affinity membranes. It was also found that the pseudo-first-order kinetic model described the bromelain adsorption process with a good fitting. Keywords-adsorption; bromelain; Reactive Blue 4; isotherm; kinetic; thermodynamic
Chinese Face: MIANZI and LIAN: And Their Influence on Chinese Consumer Behavior

As a complex social and psychological phenomenon, MIANZI, Known as Chinese face, has attracted much attention in the field of sociology and psychology. But in the field of marketing, research on how MIANZI (FACE) affecting consumer behavior is not abundant. Moreover, research on the connotations of sub-dimension of MIANZI (FACE), that is, LIAN and MIAN as well as their influences on consumer behavior is seldom seen. By using open-ended and close-ended questionnaire and focus group interview, this study extracts hundreds of scenario sentences of LIAN and MIAN, initially forming a preliminary scale with 14 positive items and 20 negative items concerning with LIAN and MIAN. Studies validate the discrepancy between "FACE"(MIANZI) and "LIAN". Moreover, the discrepancy between "FACE"(MIANZI) and "LIAN" also appears in consumer perception about product category and Country-of-Origin Image. In respect to product category buying behavior, in which automobile ranks the first place affected by face, followed by cosmetics, milk is the least-affected in this study; In addition, there is significant discrepancy in the cognition of LIAN and MIAN on Country of Origin Image. As for automobile buying behavior, Buying German car is regarded as the most face-earning behavior; Buying Japanese car is regarded as LIAN-losing (shameful) but face-earning (graceful) behavior; Buying Chinese car is somehow considered as purchase of no-face but having- LIAN.
Visual query compression with locality preserving projection on Grassmann manifold

For a variety of visual search and visual key points based navigation applications, compression of visual key point features like SIFT is an important part of the overall system that can directly affect the efficiency and latency. In this work, we examine a new approach in visual key points compression, that utilizes subspaces that optimized for preserving key point feature matching properties than the reconstruction performance, and allows for a set of optimal subspaces on Grassmann manifold that can better adapt to the local manifold geometry. The simulation demonstrates that such scheme has very low overhead in signaling subspaces, and has very much improved performance on the repeatability of the keypoint matching subject to bit rate constraints.
Content-Aware Distortion-Fair Video Streaming in Congested Networks

Internet is experiencing a substantial growth of video traffic. Given the limited network bandwidth resources, how to provide Internet users with good video playback quality-of-service (QoS) is a key problem. For video clips competing bandwidth, we propose an approach of Content-Aware distortion-Fair (CAF) video delivery scheme, which is aware of the characteristics of video frames and ensures max-min distortion-fair sharing among video flows. CAF leverages content-awareness to prioritize packet dropping during congestion. Different from bandwidth fair sharing, CAF targets end-to-end video playback quality fairness among users. The proposed CAF approach does not require rate-distortion modeling of the source, which is difficult to estimate. Instead, it exploits the temporal prediction structure of the video sequences along with a frame drop distortion metric to guide resource allocations and coordinations. Experimental results show that the proposed approach operates with limited overhead in computation and communication, and yields better QoS, especially when the network is congested.
Design and development of a Resource Management System for Cable TV network

With the popularizing of digital TV, Cable TV(CATV) network develops rapidly in the recent years. More large scale resource involved in the CATV network makes demands of the more effective management system. This paper analyses the characteristics of CATV network resources, offers a hierarchical model and gives the architecture, development principles, and implementation of a comprehensive CATV Network Resource Management System (CATV NRMS) based on Geographical Information System(GIS) and database technologies.
Coil Voltage Pulse at the Beginning of the Fast Discharge Operation of No-Insulation REBCO Coils

This paper presents a study on the coil voltage of the no-insulation (NI) high-temperature superconductor (HTS) pancake coils during fast discharging operations. Fast discharging tests are performed on both a double pancake (DP) and an single pancake (SP) NI coil. The measured coil voltages are compared with that from an equivalent circuit model, which has been widely used in previous studies. A voltage pulse is observed on both the NI coils at the beginning of the fast-discharging operation. It is much higher than that from the modeling. The peak value of the voltage pulse increases linearly with the initial current. Comparison tests show that the coupling iron core has little influence on this coil voltage pulse though the inductance of the coils is enlarged seven times by coupling iron core. This coil voltage pulse shows that, during the fast discharging operation, the NI coil has a much higher turn-to-turn resistivity at the beginning stage than that in following process. Since the coil voltage pulse can be 600 times of the modeling estimation, it may be a potential risk to the coil protection system and measuring instruments. Therefore, special attentions are required on this aspect in the design of NI magnets.
Performance of wavelet packet modulation-based multicarrier spread spectrum system over a rayleigh fading channel

The wavelet packet modulation (WPM)-based multicarrier spread spectrum (MC-SS) communication system is introduced in this paper. The bit error rate (BER) performance of the WPM-based MC-SS system with different transceiver configurations is investigated over a Rayleigh fading channel. Different types of mother wavelet, different data multiplexing modes, different wavelet packet tree structures, including a special wavelet packet structure, the WPM with virtual terminals, and wavelet packet with different tree depth are considered. Simulation results show the WPM-based multicarrier system is superior to conventional discrete Fourier transform (DFT)-based multicarrier system. The WPM with virtual terminals along with spread spectrum is capable of improving the performance of the system in Rayleigh fading environment.