nils-herrmann/clean_scirepeval huggingface dataset:
Operating Point Optimization of Auxiliary Power Unit Based on Dynamic Combined Cost Map and Particle Swarm Optimization

Series hybrid electric vehicles improvements in fuel consumption and emissions directly depend on the operating point of the auxiliary power unit (APU). A new APU operating point optimization approach based on dynamic combined cost map (DCM) and particle swarm optimization (PSO) is presented in this paper. The influence of coolant temperature, catalyst temperature, and air/fuel (A/F) ratio on fuel consumption characteristics and HC, CO, NOx emission characteristics are quantitatively analyzed first. Then, the DCM is derived by combining the individual cost maps with predefined weighting factors, so as to balance the potentially conflicting goals of fuel consumption and emissions reduction in the choice of operating point. The PSO is utilized to search the optimum APU operating point in the DCM. Finally, bench experiments under three typical driving cycles show that, compared with the results of the traditional static steady-state fuel consumption map-based APU operating point optimization approach, the proposed DCM and PSO-based approach shows significant improvements in emission performance, at the expense of a slight drop in fuel efficiency.
Research on Leader-Member Exchange and Work Performance

This study was aimed at the relationship model between LMX and work performance. Hypotheses mode was set up, and Chinese edition of LMX scale, team cohesion scale and team performance evaluation scale were used in this paper. 342 survey questionnaires were sent and 231 valid accounting for 67% of the total were received, the samples came from many industries, such as finance, energy, scientific research, IT and telecommunications, representing the state-owned, joint ventures, and private enterprises. Then, multiply stepwise regression, intermediary effect and regulatory effect analysis are used. Through those studies, we found that LMX had significantly positive effects on work performance and the team type and team cohesion affected the relationship between LMX and work performance as regulation variable and intermediary variable respectively. The follows also be found that in order to achieve performance targets, managers should strengthen exchange and communication with staff, care for members’ feeling and special needs, show their care and support and build harmony subordinate relationship to promote team cohesion and work performance with good LMX.
Perceptual quality measurement of video frames affected by both packet losses and coding artifacts

This paper addresses the problem of perceptual quality measurement on individual coded video frames with distortions caused by both lossy source coding and lossy transmission. We focus on low bitrate H.264 coded video with error concealment and propagation due to packet losses. Identifying Human Visual System (HVS) masking effect as one of the most important factors affecting the perceptual quality, we investigate its impacts on the two aforementioned artifacts in individual video frames respectively, and then evaluate their corresponding Just-Noticeable-Difference (JND) based perceptual distortions. Finally, we combine the two distortions together and propose a block-wise full-reference quality metric for a single distorted video frame. Our subjective evaluation results show that the proposed metric correlates fairly well with actual subjective quality ratings.
Current-mode controlled single-inductor dual-output buck converter with ramp compensation

Sub-harmonic oscillation is a key factor causing instability for current-mode controlled single-inductor dual-output (SIDO) Buck converter. To inhibit the sub-harmonic oscillation of the converter and to extend its stable operating range, the ramp compensation technique is introduced in this paper. The discrete iterative map model of current-mode controlled SIDO Buck converter with ramp compensation is established at first. Then, the bifurcation behavior and Lyapunov exponent of the converter are emphatically studied based on the discrete iterative map. Finally, comparison frame-work is carried out based on the experiments of current-mode controlled SIDO Buck converter with and without ramp compensation unit to certificate the theoretical analysis results.
Multimedia content analysis-using both audio and visual clues

Multimedia content analysis refers to the computerized understanding of the semantic meanings of a multimedia document, such as a video sequence with an accompanying audio track. With a multimedia document, its semantics are embedded in multiple forms that are usually complimentary of each other, Therefore, it is necessary to analyze all types of data: image frames, sound tracks, texts that can be extracted from image frames, and spoken words that can be deciphered from the audio track. This usually involves segmenting the document into semantically meaningful units, classifying each unit into a predefined scene type, and indexing and summarizing the document for efficient retrieval and browsing. We review advances in using audio and visual information jointly for accomplishing the above tasks. We describe audio and visual features that can effectively characterize scene content, present selected algorithms for segmentation and classification, and review some testbed systems for video archiving and retrieval. We also describe audio and visual descriptors and description schemes that are being considered by the MPEG-7 standard for multimedia content description.
Collaborative design for young children with autism: Design tools and a user study

This paper provides an overview of a collaborative design effort that involves computer scientists, psychologists, and designers working together to investigate design methods to help in the creation of technology for people with neurodevelopmental disabilities. The focus of this effort was in developing techniques to help novice designers create technology interfaces to support anger management in young people with autism spectrum disorder (ASD). The primary output for designers is a card set for which each card has a claim about an anger management technique that can help young people. Design activities leveraging scenarios and personas are suggested that leverage the card set in the creation of technology interfaces. This paper introduces the card set and supporting techniques, describes a design session in an undergraduate classroom setting, and speculates about future directions for this work.
High-Efficiency Coding for Shaking Surveillance Videos Based on Global Motion Compensation

Due to the complex environment conditions, many surveillance videos are captured from cameras which are influenced by shaking more or less. This presents a significant challenge for background-modeling-based video coding since it is difficult to generate good background frames from such shaking videos. To solve this problem, this paper proposes a global motion compensation method using motion vectors (MV-GMC) for shaking surveillance video coding. In the proposed MV-GMC method, more accurate motion vectors (MVs) are extracted from HEVC encoder to estimate the global motion model in an efficient way, and we compensate each frame before background modeling. Then the compensated frames are used to model a good background frame for surveillance video coding. Compared with the optical-flow-based GMC (OPT-GMC) method which can be used to obtain more precise motion compensation, the proposed MV-GMC method has a comparable coding performance but a much lower computational complexity. Experiments on our surveillance video sequences show that the proposed MV-GMC method has significantly improved the coding performance by decreasing BD rate 49.83% over HM 12.0 on average while OPT-GMC can save 49.84% BD rate. The MVGMC method also saves 92.71% background modeling time compared with the OPT-GMC method.
The motion detection based on background difference method and active contour model

For the traditional moving target detection algorithm exists some problems such as determining threshold problems and more sensitive to noise, this paper presents a rapid extraction method based on variation level set of the edge blur moving objects. This method used the background difference method extract initial outline of moving target, and then used active contour model constraint edge detection; the final combined variation level set method with a second evolution to obtain accurate image segmentation. Experiments show that this method can rapidly and accurately segment moving object, for moving objects of different shapes and the rules of small-angle shot has a good adaptability and robustness.
Study on modeling and simulation of AC/DC sensitive residual current transformer

AC/DC sensitive residual current transformer (AC/DC RCT) is used to detect residual sinusoidal alternating currents, residual pulsating direct currents or residual smooth direct currents and the characteristics of AC/DC RCT is of great signification for residual current protection under complicated waveform conditions. An AC/DC RCT based on magnetic modulation principle is proposed. Modeling and simulation of the AC/DC RCT is studied. Firstly, the B-H curve of permalloy magnetic core is fitted accurately by using a mixed method of expressions and the least squares method (LSM), which can overcome the shortage of low accuracy of the traditional charting or piecewise approximation methods. Secondly, based on the analysis of operation principle of AC/DC RCT, the loop equation of AC/DC RCT is obtained and a computer based simulation model is established. Thirdly, on the basis of the simulation model, the effects of secondary winding turns on oscillation frequency of AC/DC RCT is studied when the material and geometric dimension of the magnetic core is defined. And the simulation results of output voltage under residual sinusoidal alternating currents or residual smooth direct currents conditions are given. Finally, the feasibility of the simulation model is verified by experiment. The research results are helpful for the design of AC/DC RCT.
Adaptive neural-fuzzy controllers for dynamic channel borrowing in wireless cellular networks

A neural-fuzzy controller for the dynamic channel-borrowing scheme (NFDCBS) is presented to provide multimedia services and to support the increasing number of users. In a cellular network, the calls arrival rate, the call duration, and the communication overhead between the base station and the control center are vague and uncertain. Therefore, we propose a new novel efficient dynamic channel borrowing for load balancing in distributed cellular networks based on neural-fuzzy controllers scheme. The proposed scheme exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with the other algorithms. It aims to efficiently satisfy their diverse quality of service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delays than the previous methods.
Nonlinear Current Detection Based on Magnetic Modulation Technology

This paper proposes a sensor for leakage-current detection based on the magnetic modulation technology. The sensor can measure both nonlinear current with an arbitrary waveform and linear current from dc to several kilohertz. The current sensor consists of only one magnetic core and one winding, which significantly reduces the sensor size. The structure and operating principle of the current sensor are introduced, and the dynamic process of the current sensor is analyzed. In addition, the mathematical model of dynamic process with hysteresis considered for the current sensor is presented. Both the simulation and the experimental results are presented to verify the effectiveness of proposed current sensor.
A self-calibration approach to hand-eye relation using a single point

This paper describes a self-calibration approach to hand-eye relation using a single point in the scene. Camera is required to observe one point in the scene at five (or more) pure translational motions and two (or more) pure rotational motions of manipulator. The motions of manipulator are accurately controlled and read, and the motions of camera are estimated from the disparity and the depth value of the point. Thus, constraint equations are set up between the manipulator and the camera coordination. The intrinsic parameters of camera and hand-eye relation are solved linearly. It is characteristic by conveniently controlling motions of manipulator and succinct implement of algorithm due to the utility of a single point in the scene, requiring neither matching, nor orthogonal motions. Results of experiments on computer-generated and real image data show that the proposed method is effective and feasible.
Layered randomized cooperation for multicast

Cooperation of wireless users is known to provide substantial improvements in channel reliability and in end-to-end distortion. User cooperation is especially attractive for multicast since the relays are also part of the intended recipients. In this paper, we consider a randomized distributed cooperation scheme for multicasting a source signal. Using end-to-end distortion as a performance metric and assuming a delay constraint, we investigate the relation among the decoding SNR threshold, number of hops, coverage range and the distribution of end-to-end quality over users in the coverage range. In order to provide differentiated quality to users with different channel strengths, we further employ layered cooperation and illustrate the benefits.
High performance transmission protocols for WDM multi-channel slotted ring networks

This study evaluates a high performance transmission protocol for WDM multi-channel slotted ring networks. The evaluated protocol can utilize the bandwidth of networks efficiently and reduces the implementation complexities that constrain other related protocols such as SRR. The protocol allows every node to inspect the usage status of all channels. According to these status, a node can select an appropriate channel for transmitting packets from among the free channels through appropriate selection schemes. The evaluated network architecture is similar to HORNET. This study also proposes and evaluates two selection schemes. In addition, to resolve the fairness problem frequently encountered in ring-type networks, a fairness mechanism based on the multi-metaring protocol is used to provide fair access to the network between nodes. Simulation results demonstrate that the evaluated protocol with the proposed selection scheme can achieve nearly optimal channel utilization under balanced traffic. Moreover, the incorporation of the fairness mechanism also reveals excellent throughput.
Ambiguous Game Models Based on Nonadditive Probabilities for Decision Forecast in Real Conflict Situations

Although traditional game theory has put an important role in economics, it is often blamed for its weak descriptions and analyses in real-world conflicts mainly for its complete rationality presumptions. Thus it is difficult to forecast the players' strategy selection and the outcomes in real conflict situations, the field which the authors named as decision forecast. We introduce nonadditive probabilities into modeling of ambiguous games, which aims to describe players' attitude of ambiguity-aversion in strategy selections in real conflict situations. We present a payoff function which can be considered as a balance of v-N-M utility and max-min decision criterion, and introduce it into modeling of an ambiguous game in strategic form. And then, we show the existence of equilibrium under such payoffs. We also introduce nonadditive probabilities into two-phase extensive games and give diagrammatic representations of an ambiguous game tree.
The feasibility about logistics park being set up in the source of agricultural product industry chain

Countryside is the source of agricultural product industry chain, but agricultural product logistics park usually be located in cities. The agricultural product has its own features; its logistics sets higher level and special request for the service processes. After analyzing the advantages and disadvantages of urban and countryside for location of agricultural product logistics park, the result shows that countryside is more suitable for the logistics park construction and management, it could reduce cost, improve agricultural product quality, and raise logistics efficiency. Moreover, the establishment of modern agricultural logistics park in countryside will bring benefits to rural economy, rural condition and the quality of farmers. Based on the result, this article focuses on logistics park contents, investment subject, management method, and co-operation between the countryside government and large retailers to participate in the construction and operation of logistics parks is a reasonable way.
A Microcalorimeter Integrated With Carbon Nanotube Interface Layers for Fast Detection of Trace Energetic Chemicals

Detection of trace explosives is still a challenging task because of the extremely low vapor concentrations. This paper reports a new microcalorimeter for detection of trace explosives with low detection limit and fast detection rate. The microcalorimeter consists of a suspended micromembrane with integrated heaters and thermistors and a carbon nanotube (CNT) interface layer in-situ synthesized on the membrane surface. Due to the large surface areas, the CNT interface layer improves adsorption to target chemical molecules. By operating the microcalorimeter in differential scanning calorimetry mode and differential thermal analysis mode, trace chemical detection is achieved through heating the adsorbed chemicals to deflagration and measuring the induced thermal response features and the total heat. The microcalorimeter is verified by explosive detection, and an equivalent limit of detection of 2.6 pg has been achieved by extrapolating the measurement results. Theoretically, detection is distinguishable upon 10-s fast exposure to saturated explosive vapors. These preliminary results demonstrate the ability of the microcalorimeter in detection of trace energetic chemicals.
Control for nonlinear chaos based on radial basis function neural networks

A method for control of nonlinear chaotic dynamical systems based on radial basis function neural networks is presented. Combining input-output data obtained from a perturbation parameter model with a linear learning algorithm, neural networks are trained to generate the small disturbance control, then to stabilize the chaotic system. The unstable periodic orbit in the Henon map is directed to a stable fixed point by the method. The simulations show the proposed scheme has great effectiveness.
Storage life prediction method of optical fiber spool

The optical fiber spool is one of the key components of fiber-optic guidance technology. Hence, the storage life prediction of optical fiber spool is essential to the reliability estimation of the fiber-optic guidance system. The theory of the traditional optical fiber fatigue life prediction method which is recommended in the standards of FOTP-28 and IEC 793-1-3 is reviewed and concepts of scale extrapolation and time extrapolation are underlined. Based on these, the storage life prediction method of optical fiber spool is proposed, which extends the life prediction under constant temperature to dynamic temperature. The process and theory of the method is described in details. In the case study, the result demonstrates the proposed method is able to provide corresponding predictions depending on different storage locations, which are more accurate compared to the traditional method.
Heat integration of the azeotropic distillation system with ANN and GA

In this paper, an effective method with artificial neural networks (ANN) and a genetic algorithm (GA) was suggested for modeling the azeotropic distillation system with unknown or complex mechanisms and optimizing its operating parameters to save energy. The satisfactory results of this investigation demonstrated the feasibility and effectiveness of the suggested method. Furthermore, the azeotropic distillation system after optimization results in reduction of heat use by 54.03%. Thus, the study provides means for further optimization of the azeotropic distillation system, and directs practical production for process optimization.
Application of IMM in the Control of Vehicular Turret

The vehicular fire control system has the uncertainty problem in target tracking. This paper uses the CA model and IMM respectively as the target motion model, and explores the UKF algorithm to estimate the state of the moving target, which keeps the vehicular turret and the moving target servo in the air. The simulation results show that the algorithm using IMM to describe the target motion has smaller errors and higher precision than that using the CA model in MATLAB, which can meet the need of maneuvering target tracking, and better realize the control of turret in vehicular fire control system. Furthermore, measured results in hardware environment demonstrate that the execution time of IMM-UKF is short, which can meet real-time requirements in vehicular fire control system.
Dynamic inhomogeneous finite element method for dynamic response analysis of the 1D inhomogeneous media with the variable section area

Dynamic response problem in the inhomogeneous media is a hot topic. In this paper, dynamic inhomogeneous finite element formulations are given for dynamic response analysis of 1D inhomogeneous medium with variable section area. The dynamic equilibrium equation is given first. Then, the equation's weak formation is derived by weight residual method. The expressions of inhomogeneous element stiffness and mass matrices are observed. Then, two equivalent relationships about stiffness and mass are presented. The same equivalent coefficients, initial and boundary conditions lead to the same response solution. In addition, the results of the example show that this dynamic inhomogeneous finite element approach has a high degree of accuracy and high efficiency.
The Design of Two-Step-Down Aging Test for LED Lamps Under Temperature Stress

In this paper, the step-down aging test for light-emitting diode (LED) lamps is designed according to the stopping rule of the IESTM-28 standard and experimental data. The step-down aging experiment is under the temperature stresses of 90 °C, 80 °C, 70 °C, and 60 °C, from which the temperatures for two-step-down aging test are selected. A Nelson model is used to calculate the equivalent time from one temperature to another, and a two-stage method is adopted to establish the reliability model of LED lamps under accelerated temperature. Then, the lifetime at the ambient temperature of 25 °C is deduced by the use of Arrhenius model. It is shown that the temperatures of 90 °C and 80 °C for two-step-down aging test are the best choice, with standard deviation of reliability and standard deviation of relative lifetime less than 11% and 20%, respectively. The accelerated aging time is <;1200 h, which meets the requirement of quick lifetime prediction of LED lamps.
An efficient power modeling approach for embedded memory using LIB format

Embedded memories have been used extensively in modern SoC designs. In order to estimate the power consumption of entire design correctly, the more accurate memory power model is needed. However, the memory power model which is commonly used in commercial EDA tools is too simple to estimate the power consumption accurately. In this work, we propose two methods to improve the accuracy of memory power estimation. Our enhanced memory power model can consider the switching activity for both control and non-control signals thus can raise the accuracy of traditional memory power models. The proposed dummy modular approach links our enhanced memory power model to commercial power estimation flows. The experimental results have shown that our memory power model is more accurate than the traditional memory power model.