nils-herrmann/clean_scirepeval huggingface dataset:
Complex Event Detection by Identifying Reliable Shots from Untrimmed Videos

The goal of complex event detection is to automatically detect whether an event of interest happens in temporally untrimmed long videos which usually consist of multiple video shots. Observing some video shots in positive (resp. negative) videos are irrelevant (resp. relevant) to the given event class, we formulate this task as a multi-instance learning (MIL) problem by taking each video as a bag and the video shots in each video as instances. To this end, we propose a new MIL method, which simultaneously learns a linear SVM classifier and infers a binary indicator for each instance in order to select reliable training instances from each positive or negative bag. In our new objective function, we balance the weighted training errors and a l1-l2 mixed-norm regularization term which adaptively selects reliable shots as training instances from different videos to have them as diverse as possible. We also develop an alternating optimization approach that can efficiently solve our proposed objective function. Extensive experiments on the challenging real-world Multimedia Event Detection (MED) datasets MEDTest-14, MEDTest-13 and CCV clearly demonstrate the effectiveness of our proposed MIL approach for complex event detection.
A novel method of planar three dimensional synthetic aperture radar imaging

A fully novel three-dimensional (3-D) microwave image reconstruction algorithm is presented, which based on echo data of stepped-frequency sweeping radar system. The algorithm is not restricted by far field as the traditional imaging algorithm. By synthetic aperture processing for radar data, the high resolution of the image can be achieved. The algorithm belong to a new three dimensional back-projected method, which can hold good accuracy of interpolation, 3-D image of target can be achieved through fast Fourier transform and integrating after interpolation. The imaging results from simulation and experiment were presented. These results show that the algorithm is correct, 3-D image reconstruction based on this back-projected method can provide a microwave 3-D image with high resolutions effectively.
A robust decoder for distributed turbo codes in relay channel

In this paper, a decoder based on log-MAP (maximum a-priori) algorithm for distributed turbo codes in relay channel is designed. The structure of the proposed turbo decoder is similar to the standard turbo iterative decoder with two soft-input soft-output (SISO) modules. However, the inputs to the decoder as well as the extrinsic signals between the two SISO modules are differently calculated. The principle of the proposed decoder is to get inputs to each SISO module that comes from one specific transmitter. Simulation results show that the proposed decoder has faster convergence and better BER performance than the standard decoder when the input from source and relay are with mismatched signal strength. The proposed decoder is also robust against this signal quality mismatch.
Improved PSO-based S Plane Controller for motion control of underwater vehicle

Based on the analysis of fuzzy control, combined with the form of PID control, the S plane control has been applied. For the default that particle swarm optimization (PSO) presents the phenomenon of precocity and getting in local minima, the basic PSO algorithm is improved. Based on the self-adaptive idea, a concept of dynamic learning factor is introduced. This method could improve the coordination between global and local searching ability and apt to search out global optimum quickly. Another concept of chasten factor is also introduced, the optimizing ability in PSO algorithm which applied in the S plane algorithm in parameter optimization. Finally, the improved PSO algorithm is applied to the S curve motion control of underwater vehicle. The feasibility and advantages of this method are demonstrated by simulation test results.
Development of the Maintenance Robot with Electrification Used in Substation

The insulators of open-type substation are exposed to the outdoors for a long time. The surfaces have been affected by atmospheric environment such as SO2, nitrogen oxides and granular dust, and it is prone to flashover accidents in wet weather. The steel core aluminum strand of lines in open-type substation which exposed to the outdoor environment for a long time would be broken. The breakage of the transmission lines could reduce the mechanical strength, and then lead to safety accidents when it is serious. The maintenance robot with electrification used in substation works in 110 kV to 220 kV open-type substations. The robot adopts a crawler walking mechanism to move, an insulated arm of folding and telescopic with multi-level combination to and a high power density hydraulic manipulator to work. Different operating tools could be installed at the end of the robot's arm to complete the electrified maintenance tasks, such as the electrified cleaning of the insulators, the dry ice cleaning of the insulators, and repairing the broken wires with electrification.
Implementation of time offset estimation with General Cell

Satellite flying formation missions are being prepared by more and more aerospace centers for the potentials they have. They also bring challenges like clock synchronization. This paper introduces a dedicated hardware device, General Cell (GC), which is a general micro-platform of spacecraft C&DH system, fully fits to formation flying space circumstance, and aims at relative attitude location and time synchronization among satellites. With support of it, this paper implements time calibration with a two-stage solution, and recurs to linear Kalman filter to filter out variations of message delays further. GC is equipped with only ordinary frequency stability crystal oscillator, and experiment shows it achieves time precision less than plusmn20 mus
Design of Ultra-Low Noise and Low Temperature Usable Power System for High-Precision Detectors

In high-precision detector systems, the power supply usually need to be ultra-low noise and stabilized. Design and implementation of an ultra-low noise power supply is described in this paper. We implemented and tested the power system actually in a scientific CCD (Charge-coupled device) detector system, but the design structure could be used in many high-precision detector systems as infrared detector or high-energy particles detectors. The power system uses DC-DC switching regulators and LDO regulators for power generating, uses multi-stage filters for noise reducing. Multi-output power supply with noise about 40 μVrms is achieved, the overall energy efficiency is 68.5%. Besides, the electronic system takes the low temperature as an important consideration, and the system has been tested in an extreme environment as low as 193 K.
Investigation on Diurnal Variation and Gender Difference in Human Urine Using NMR-Based Metabonomics

1H NMR-based metabonomics has shown considerable potential as a means of rapidly detecting and characterizing a myriad of metabolic components. The 1H NMR spectra obtained for human urine samples were visually inspected and analyzed using principal component analysis (PCA). Urine samples were collected eight times daily (8:00, 10:00, 12:00, 14:00,18:00, 20:00) from healthy volunteers with a standard diet and lifestyle for 2 consecutive days. Separation of urinary data according to time of sampling collection was achieved. The fluctuations of creatinine, citrate and observed between urine samples collected during the different time of day may be related to hormone levels. In addition, gender-difference was also investigated and the PCA score plots revealed several metabolites that were considered significant for distinguishing between male and female: creatinine, glycine and citrate. These results showed the value of metabonomic methods in the investigation of physiological variation and rhythms, and provided suggestions to collect significative metabonomics data in clinical studies.
A data analysis system based on MATLAB GUI for portable emission measurement

In terms of vehicle emission research, it is necessary to measure the real-time emission data of vehicle without affecting its normal operation. At present, portable emission measurement system is utilized to obtain vehicle emission parameters accurately under the actual operating conditions. This paper introduces a data analysis system based on MATLAB/GUI for portable emission measurement, which can process and analyze the data gained from each separated measuring unit. Thus the relations of the related parameters are acquired and shown using graphics. Verified by the experiment, this system can meet the requirement of portable emission measurement in respect of the accuracy and speed of data processing.
A learner based on neural network for cognitive radio

Intelligence is a very important characteristic for cognitive radios (CR). Design of cognitive engine and application of artificial intelligence (AI) techniques are key to the implementation of this characteristic. Machine learning is one of the disciples in AI. This paper will propose a scheme of cognitive engine design, and use a learning algorithm based on neural network (NN) to implement a learner in the cognitive engine. A multilayer perceptron (MLP) neural network model will be introduced to ensure the convergence of the network, and problems on stop condition and overfitting will also be discussed. Finally, performance of the algorithm will be analyzed by simulations.
Advanced nano-Ag thermal interface material for high thermal flip chip BGA

Flip chip ball grid array (FCBGA) has been found in wild range such as telecommunication, computer, and workstation application because it provided solutions for high speed demand, high input/output (I/0) density, and high electrical performance requirement. In the conventional FCBGA assembly, heat sink was laminated directly onto the chip surface via an epoxy base thermal interface material (TIM) filled with conductive metal particle as silver or aluminum for thermal conduction. For the high power FCBGA device, a sintering type nano-Ag TIM characterized with high thermal conductivity has been demonstrated. In order to achieve intimate sintering contact with the nano-Ag TIM, the Ag finalized multilayer deposited via the direct current (DC) magnetron sputtering was applied onto the surface of chip and heat sink, respectively. The nanolization of Ag particles enabled the Ag to be sintered at low temperature (220 °C). Therefore, continuous heat dissipation paths from the chip to the heat sink could be formed. Test vehicle of 50 × 50mm FCBGA bonded with 19 × 15mm thermal testing die was utilized for thermal performance evaluation, and the thermal resistance of junction-to-case (θ jc) of 0.03 °C /W was achieved. Finally, TIM coverage has been verified via scanning acoustic tomography (SAT) post reliability testing, including 500 cycles of temperature cycling B condition (-55 to +125 °C, liquid-to-liquid), and 96 hours unbiased highly accelerated stress test (130°C, 85% relative humidity) after JEDEC Level 4 preconditioning and three reflow simulations at 245 °C. Meanwhile, high temperature storage life test (150C) for 1000 hours was also implemented. In the end, a realizable manufacturing for high power FCBGA packages with great thermal dissipating characterization has been demonstrated.
Content-based 3-D Shape Retrieval for Pervasive Computing

3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment
A novel path planning algorithm based on twofold interpolations

Most grid-based path planners use discrete state transitions that artificially constrain a robot's motion to a small set of possible headings to increments of 45 degrees. Consequently, even ldquooptimalrdquo grid-based path planning algorithms produce unnatural and suboptimal paths. In order to handle the problem, we present a twofold-interpolation-based path planning algorithm called T* for producing low-cost paths through uniform resolution grids. First, it starts at the goal node and propagates through four adjacent nodes, assigning monotonically increasing values to nodes using FMM (fast marching method) interpolation. Consequently, we obtain a goal-propagation map that is zero at the goal node and monotonically increasing along wavefront propagation from the goal node. Subsequently, it begins from robot's position and uses linear interpolation to generate near-optimal paths which eliminate unnecessary turnings. The experimental results demonstrate the performance of our approach.
General Congestion Control for High Bandwidth-Delay Product Networks

Existing congestion control protocols have significant limitations in achieving high throughput and reasonable fairness while maintaining fast convergence speed in high bandwidth-delay product networks. In this paper, we propose the General Congestion Control Protocol (GCCP) to address this limitation. GCCP allows for aggressive behavior in large underutilized links to achieve high throughput, but leverages only one ECN bit for network utilization feedback. Once the link is sensed to be highly utilized, the protocol dedicates to fair and rapid bandwidth allocation by requiring congestion window increment is conservative and monotone decreasing with congestion window increasing. The ns2 simulations show that GCCP achieves a pretty good tradeoff between high throughput and reasonable fairness while exhibiting fast convergence speed.
Demonstrating >1.4 kV OG-FET performance with a novel double field-plated geometry and the successful scaling of large-area devices

A normally off (V<inf>th</inf> = 4.7 V) vertical GaN OG-FET with a 10 nm UID-GaN channel interlayer and a 50 nm in-situ Al<inf>2</inf>O<inf>3</inf> gate dielectric has been successfully demonstrated and scaled for higher current operation. By using a novel double field-plated structure for mitigating peak electric field, a high off-state breakdown voltage over 1.4 kV was achieved with a low specific on-state resistance (RON, SP) of 2.2 mΩ.cm<sup>2</sup>. The MOCVD regrown 10 nm GaN channel interlayer enabled a channel resistance lower than 10 Qmm and an average channel electron mobility of 185 cm<sup>2</sup>/Vs. The fabricated large-area transistor with a total area of 400 μm × 500 μm offered a breakdown voltage of 900 V and an on-state resistance (R<inf>on</inf>) of 4.1 Q. Results indicate the potential of vertical GaN OG-FETs for over kV range of power electronics applications.
A novel method for multi-fault location utilizing fault fitting degree

A new algorithm is proposed to locate multi-fault based on fault fitting degree for complex large power grid. In the normal operating condition, the node admittance matrix is formed according to the network topology structure. When multiple faults occur, by analyzing the fault branch node voltage equation, the fault equivalent model of fault branches and node-branch correlation matrix are formed. Based on superposition theorem, the virtual fault location and fitting degree of each combination of faults can be calculated by the least square method. Then fault line and fault location are determined. The simulation results of 10-generator 39-bus system verify the validity and feasibility of this algorithm.
Asymmetrically Recessed 50-nm Gate-Length Metamorphic High Electron-Mobility Transistor With Enhanced Gain Performance

We report the design, fabrication and characterization of ultrahigh gain metamorphic high electron-mobility transistors. In this letter, a high-yield 50-nm T-gate process was successfully developed and applied to epitaxial layers containing high indium mole fraction InGaAs channels grown on GaAs substrates. A unique gate recess process was adopted to significantly increase device gain by effectively suppressing output conductance and feedback capacitance. Coupled with extremely small 10 mum times 25 mum via holes on substrates thinned to 1 mil, we achieved a 13.5 dB maximum stable gain (MSG) at 110 GHz for a 30-mum gate-width device. To our knowledge, this is the highest gain performance reported for microwave high electron-mobility transistor devices of similar gate periphery at this frequency, and equivalent circuit modeling indicates that this device will operate at frequencies beyond 300 GHz.
A new method of robust detection for speech stream

Based on the human auditory perceptual properties, a new method for speech detection was proposed. The new method consists of the classical RASTA-PLP filter in logarithmic power spectrum domain and a differential filter in time domain. In this manner, all kinds of noise can be removed efficiently. Proved by experiments, with mass data of these experiments come from the original real recording of wireless communication on spot, this method can detect speech stream efficiently and the new method outperforms the conventional detection method.
A novel reconfigurable on-board computer based on soft core CPU

To address the issues of single event upsets caused by radiation in outer space to micro-satellites, we proposed a novel reconfigurable on-board computer system with three soft core CPUs inside the Field Programmable Gate Array(FPGA), with the function of error detecting and restoring configuration. Two of the soft core CPUs act as the central processing unit, doing housekeeping of the satellite; and the third one includes a 32-bit floating-point mathematical co-processor core using the Coordinate Rotation Digital Computer(CORDIC) algorithm, dealing with complex mathematical operation. When SEU happens to our system, the system can detect it and send a message to trigger the restoring configuration. To verify our design, a semi-physical simulation platform consisting of the reconfigurable on-board computer, dSPACE simulating computer and laboratory display terminal is built, and capability of our design is proved on this platform. In the experiment, we inject errors artificially, and the errors can be detected and corrected by reconfiguring the whole system; when no errors are injected, the computer can take control of the satellite normally.
A Centrifugation-Enhanced High-Efficiency Micro-Filter with Spiral Channel

In this paper, a novel spiral-channel micro-filter with high throughput and compact layout, taking advantages of the centrifugation effect, has been developed. Numerical results indicate that the flux, which penetrates through the filtration wall, in a circle channel device is 2.25 times than that in the straight channel filter at the same conditions. The higher flow velocity allows higher filtration efficiency. The experimental results show that large particles are completely separated from original mixtures, and small particles are remarkably enriched by several filtration cycles.
A parabola fitting edge operator by the moments

This paper presents a moment-based method for two-dimensional (2D) edge detection. A quadratic curve (e.g. parabola) is used to fit the image boundary. The edge parameters including the background level, the gray level step along the contour, distance of the edge from the center of the mask, and the orientation of the edge are estimated by computing the moments up to the second order. Experimental results are presented to valid the effectiveness of the proposed method.
Analysis on Harmonic Current of Three-phase Bridge Uncontrolled Rectifier

With the development of Power Electronic Load (PEL), which enables to simulate various loads, especially harmonic current load generated by uncontrolled rectifier, it is necessary to gain the precise harmonic current command according to different parameters of uncontrolled rectifier. Owing to the wide application of three-phase bridge uncontrolled rectifier, in this paper, the specific analysis on harmonic current of three phase bridge uncontrolled rectifier is presented. At first, theory analysis on harmonic current in continuous domain and discrete domain is deduced, and then simulation results testify the accuracy of the former analysis, finally, the program flow of obtaining the harmonic current command by using DSP is described.
Image Clustering Using Local Discriminant Models and Global Integration

In this paper, we propose a new image clustering algorithm, referred to as clustering using local discriminant models and global integration (LDMGI). To deal with the data points sampled from a nonlinear manifold, for each data point, we construct a local clique comprising this data point and its neighboring data points. Inspired by the Fisher criterion, we use a local discriminant model for each local clique to evaluate the clustering performance of samples within the local clique. To obtain the clustering result, we further propose a unified objective function to globally integrate the local models of all the local cliques. With the unified objective function, spectral relaxation and spectral rotation are used to obtain the binary cluster indicator matrix for all the samples. We show that LDMGI shares a similar objective function with the spectral clustering (SC) algorithms, e.g., normalized cut (NCut). In contrast to NCut in which the Laplacian matrix is directly calculated based upon a Gaussian function, a new Laplacian matrix is learnt in LDMGI by exploiting both manifold structure and local discriminant information. We also prove that K-means and discriminative K-means (DisKmeans) are both special cases of LDMGI. Extensive experiments on several benchmark image datasets demonstrate the effectiveness of LDMGI. We observe in the experiments that LDMGI is more robust to algorithmic parameter, when compared with NCut. Thus, LDMGI is more appealing for the real image clustering applications in which the ground truth is generally not available for tuning algorithmic parameters.
A New Multi-attribute Optimal Selecting Method for Weapon System through Trapezoidal Fuzzy Analytic Hierarchy Process and Delphi

The evaluation and selection of weapon system is one of the most important decision issues for military logistic managers. Owing to vague concept frequently represented in decision data, a new group fuzzy multi-attribute decision-making approach is proposed to solve the weapon system optimal selection problem. In the proposed method, the experts' opinions are described by trapezoidal fuzzy numbers, and the fuzzy Delphi method is adopted to adjust each expert's opinion to achieve the consensus condition. By using the logarithmic least square method and trapezoidal fuzzy number arithmetic operations to estimate the normalized fuzzy priority weights, a new trapezoidal fuzzy analytic hierarchy process (AHP) is presented and consequently the consistency check of fuzzy judgment matrix is avoided. Finally, a practical example of selecting the best unmanned combat air vehicles (UCAV) demonstrated its engineering practicability and examined its effectiveness. The results show that the method is flexible and credible and provides references in intelligent battle command decision-making
High-Rate Complex Orthogonal Space-Time Block Codes for Multiple Transmit Antennas

Space-time coded modulation has been shown to efficiently use transmit diversity to increase spectral efficiency. Such high-rate orthogonal designs are available for complex symbol constellations only for two, three, and four transmit antennas. For five and six transmit antennas, two generalized complex orthogonal space-time block codes of rates 7/11 and 3/5 were proposed recently. In this correspondence, the complex orthogonal design for eight transmit antennas is presented. This code achieves the theoretically maximal rates and improved decoding complexity compared to known codes. Simulation results are provided to corroborate the analytical studies.