nils-herrmann/clean_scirepeval huggingface dataset:
Short Term Traffic Flow Prediction Using Hybrid ARIMA and ANN Models

According to the complexity of the traffic historical data and the randomness of a lot of uncertain factors influence, a hybrid predicting model that combines both autoregressive integrated moving average (ARIMA) and multilayer artificial neural network (MLANN) is proposed in this paper. ARIMA is suitable for linear prediction and MLFNN is suitable for nonlinear prediction. This paper also investigates the issue on how to effectively model short term traffic flow time series with a new algorithm, which estimates the weights of the MLFNN and the parameters of ARMA model. Experimental results with real data sets indicate that the combined model can be an effective way to improve forecasting accuracy achieved by either of the models used separately.
A 115-mW, 0.5-/spl mu/m CMOS GPS receiver with wide dynamic-range active filters

This paper presents a 115-mW Global Positioning System radio receiver that is implemented in a 0.5-/spl mu/m CMOS technology. The receiver includes the complete analog signal path, comprising a low-noise amplifier, I-Q mixers, on-chip active filters, and 1-bit analog-digital converters. In addition, it includes a low-power phase-locked loop that synthesizes the first local oscillator. The receiver achieves a 2.8-dB noise figure (prelimiter), a 56-dB spurious-free dynamic range, and a 17-dB signal-to-noise ratio for a noncoherent digital back-end implementation when detecting a signal power of -130 dBm at the radio-frequency input.
Dynamic Route Guidance Using Neurodynamic Programming

This paper presents a dynamic route guidance method using neurodynamic programming based on the data of GPS-equipped taxies (probe vehicles). Specifically, approximate Q-learning is adopted and ineffective data were eliminated by observing the status of taximeters. The combination of the longitudes and latitudes of the intersections and the time were taken as the states of the algorithm. And the vehicles' running between the intersections was considered as the transition actions between the states. The neural network was adopted for approximating Q-factors, which denoted the travel time. By observing the probe vehicles' running in the road network, the neural network was trained so that the approximately optimal route-choice police could be obtained based on it. Finally, simulation on the basis of the electronic map data of Guangzhou city proves that the method is effective on the complex traffic conditions, even as the links' weights of the road network are unavailable and the state space is continuous
On-line visual inspection system for backside weld of tailored blanks laser welding

In tailored blanks laser welding, the quality of backside weld has a significant influence on mechanical properties of weldment. This paper deals with the issue of visual measurement, inspection of weld bead and defect detection in tailored blanks laser welding. An inspection system based on laser structured light vision has been established for backside weld bead measuring and defect detection. Image processing and extraction algorithms of structured light profiles and feature points are presented. Dimensional parameters are measured and weld defects are detected in the process of tailored blanks laser welding. The experiment results demonstrate that the proposed inspection system and method are suitable for backside weld quality inspection of tailored blanks laser welding.
A 115 mW CMOS GPS receiver

The Global Positioning System (GPS) provides accurate positioning and timing information that is useful in many applications. In particular, portable consumer GPS applications require cheap compact low-power receivers. This 115 mW receiver, implemented in an analog 0.5 /spl mu/m CMOS technology, comprises the entire radio-frequency (RF) and analog sections in addition to the local oscillator (LO) frequency synthesizer and a pair of oversampled A/D converters.
Conditional Diagnosability of Matching Composition Networks Under the PMC Model

In the work of Lai in 2005, they proposed a new measure for fault diagnosis of systems, namely, conditional diagnosability. It assumes that no fault set can contain all the neighbors of any vertex in the system. In the same paper, they showed that the conditional diagnosability of hypercube Qn is 4(n - 2) + 1 for n ges 5. In this brief, we generalize this result by considering a family of more popular networks, namely, matching composition networks (MCNs), which are a class of networks composed of two components of the same order linked by a perfect matching under PMC (Preparata, Metze and Chien) model. We determine in Theorem 7 the conditional diagnosability for some MCNs, from which we deduce that the hypercube Qn, the crossed cube CQn, the twisted cube TQn, and the MOumlbius cube MQn all have the same conditional diagnosability of 4(n - 2) + 1 for n ges 5. We show that the bijective connection (BC) networks in the work of Fan and He in 2003 and the work of Zhu in 2008 satisfy the conditions of Theorem 7, and thus, our conditional diagnosability result also applies to BC networks. Finally, we show that the MCNs satisfying the conditions of Theorem 7 are more general than the BC networks.
Locomotion and gait analysis of multi-limb soft robots driven by smart actuators

Animals provide inspiration for developing soft machines in bionics, robotics research as well as potential applications. This paper presents an integrated development of locomotive soft robot platforms: starfish-inspired robots with multi-limb bodies actuated by shape memory alloys (SMAs). The designs of these robots were based on the biological specifications of the locomotion and water-vascular systems of regenerating starfish. Multi-limb robot prototypes were fabricated with soft materials and 3D printing technology, satisfying modest movement requirements with SMA spring actuators. Experimental testing of multi-limb robots were conducted in accordance with biological locomotion principles. The robots vividly displayed typical starfish motion models. Animals provide inspiration for developing soft machines in bionics, robotics research as well as potential applications.
A novel empirical model for SiC MESFETs with self-heating effect

In this paper, a novel empirical model based on Angelov model for SiC MESFETs with self-heating effect is presented. Modifications of drain current and nonlinear capacitive model are proposed to adapt to the measured date without the thermal subcircuit. These new models could simplify the equivalent circuit topology and are easier to implement in CAD simulation tools. A good agreement has been obtained between simulated and measured results.
Radar velocity-measuring system design and computation algorithm based on ARM processor

The real-time monitoring of vehicles velocity has become essential for traffic safety. Therefore, in order to improve the method of monitoring the velocity of vehicles on road, this paper has designed a new radar velocity-measuring system which is based on ARM processor. This system is based on Doppler principle and spectral estimation algorithm, in its hardware design part, and it takes full use of the underlying resources of ARM processor, to achieve sample, digital signal processing and peripheral control in the separate ARM core. In the software design part, it analyses the main program flow, at the same time, since the ARM processor does not support hardware floating-point operations, it puts forward the usage of fixed-point numbers to store and calculate floating-point numbers, which makes the data loading and storage minimization; And it uses ARM assembly language to write the core algorithm and takes full advantage of the 5-stage pipeline of ARM processor, to achieve the right register allocation and instruction scheduling for fine-grained control, and also to avoid the pipeline interlocks. Experimental results indicate that the accuracy of this velocity measurement system can reach ±1km/h. It not only can be used in traffic enforcement agencies, but also has low cost, low power consumption advantages.
Heterogeneity-entropy based unsupervised feature learning for personality prediction with cross-media data

Personality prediction has broad prospects of application in real life. It can be accomplished by analyzing massive and variant data in social networks, which conveys one's personal traits through user generated contents, user's social relationships and behaviors. However, it is difficult to design an effective feature representation from such complex data to predict user's personality as well as high-level and abstract psychological concepts. In this paper, we propose a novel unsupervised cross-modal feature learning algorithm, named Heterogeneity Entropy Neural Network (HENN), to extract the common information between modalities and map it to the user's personality. HENN is constructed hierarchically on Deep Belief Networks (DBNs) and Auto-encoder (AE) with a modified loss function, in which an additional term named Heterogeneity Entropy (HE) is added to measure common information among different modalities. Experiments on a cross-media dataset collected from two famous Chinese social network platforms, i.e., Renren and SinaMicroblog, demonstrate the superiority of our method over several existing algorithms.
BIT: Bio-inspired tracker

Visual tracking is a challenging problem due to various factors such as deformation, rotation and illumination. As is well known, given the superior tracking performance of human vision, bio-inspired model is expected to improve the computer visual tracking. However, the design of bio-inspired tracking framework is challenging, due to the incomplete comprehension and hyper-scale of senior neurons, which will influence the effectiveness and real-time performance of the tracker. According to the ventral stream in visual cortex, a novel bio-inspired tracker (BIT) is proposed, which simulates shallow neurons (S1 and C1) to extract low-level bio-inspired feature for target appearance and imitates senior learning mechanism (S2 and C2) to combine generative and discriminative model for position estimation. In addition, Fast Fourier Transform (FFT) is adopted for real-time learning and detection in this framework. On the recent benchmark[1], extensive experimental results show BIT performs favorably against state-of-the-art methods in terms of accuracy and robustness.
A novel algorithm for HVDC line fault location based on variant travelling wave speed

This paper presents a novel fault location algorithm based on variant travelling wave speed for HVDC (High Voltage Direct Current) transimission line. The algorithm effectively reduces the large fault locating errors, casuused by adopting consitent wave speeds, under off-design conditions. Fistly, it is illustrated how travelling wave speed varies with fault distance, and then how the variant speed effect fault locating accuracy is analysized. At last, the new algorithm is proposed to gurrantee the accuracy at any fault distance. The validity of the algorithm is verified by the relevant simulation results in EMTDC.
Differential speed steering control for four-wheel independent driving electric vehicle

The increasing prospect of electric drive vehicles has led many different control schemes to apply on the driving system. Differential speed steering which do not use traditional steering mechanism is studied on a four-wheel-driving vehicle. By comparison with the traditional Ackerman-steered vehicle, differential-steered method shown its advantage on the simple structure. However, since the steering performance is coupling with the velocities of all wheels, the strategy of differential speed control is a technological challenge. With the analysis of kinematic model of the vehicle, the relation between the turning behavior and the wheel parameters are investigated. A steering speed control is proposed to get a steady turning performance. The control strategy is implemented in a simulation to verify its rationality.
Simplifying the Design of ΣΔModulators Using FGMOS Transistors

This paper presents the novel design of a second-order continuous-time low-power and low-voltage SigmaDelta modulator. The modulator illustrates a design philosophy based on taking advantage of the extended number of degrees of freedom of the floating-gate MOS transistor. The transistor is simultaneously used to fulfill the following: simplify the topology; accurately implement the modulator coefficients; compensate for gain losses in the integrator and several nonidealities in the comparator; increase the signal range; reduce distortion; shift signal levels according to the specific requirements of individual devices; implement an easy common-mode sensing and feedback strategy; and tune the loop filter and reset the comparator. The modulator operates at 1 V and consumes just over 5 muW of power for a signal-to-noise-and-distortion ratio of 60 dB and a maximum bandwidth of 2 kHz, which are typical of many biomedical applications.
A projection selection method to improve image quality in optical projection tomography

Optical projection tomography (OPT) is a very important imaging tool for a mesoscopic-scale. It can provide three dimensional (3D) transmission and emission imaging. However, high-resolution OPT is limited in depth of field (DOF) due to a high numerical aperture, which causes a poor performance of OPT in imaging large samples. Moreover, it is difficult to tune the focus plane (FP) to a fixed position where OPT always has the best image quality in different directions. To address these problems, we developed a projection selection method to improve DOF in OPT. In each direction, our method automatically selects the best projection from several projections with different FP. Then, we use a series of selected projections for 3D reconstruction. The experimental results demonstrate that our method can improve the image quality comparing to a fixed FP. Moreover, our method is flexible to be used in other OPT setups by adding a linear stage.
Design of a Reconfigurable Robot Controller Based on FPGA

With the development of the micro-electronics and computer technology, especially with the expansion of field programmable gate array (FPGA), the reconfigurable system technology is becoming the key issue of research and application. In this paper, the principle of the dynamically reconfigurable FPGA, the method and flow of the configurable design are introduced. Based on the application requirement of the modular reconfigurable robot (MRR), a designing method of reconfigurable robot controller is proposed, which is based on the Advanced RISC Machine (ARM) processor and FPGA. The design principle, internal logic function design and the design course of the reconfiguration method are presented. Finally, the experiments of the MRR prove the feasibility of the reconfigurable robot controller to different configuration requirement of MRR and the efficiency of the software and hardware resource.
Trajectory planning and 3-D image reconstruction of an ultrasound guided robot aiming radio frequency ablation surgery

The ultrasonic imaging guided radio frequency ablation surgery is an effective technique in liver tumour treatment. However, the traditional surgery imposes a constraint for surgeons to have high precision in their hand-eye coordination. This paper proposed an assisted medical robot system to reduce these requirements. For an effective surgery robot system, the trajectory planning and 3D ultrasonic image reconstruction are the key factors in designing a radio frequency ablation surgery robot, and so do other image-guided minimally invasive systems. By kinematics modeling and analysis, the quintic polynomial interpolation is adopted in trajectory planning for the robot locomotion control. The result shows that it can guarantee the continuous of joint angles, velocity and acceleration which is essential to the smooth running of motors and medical robotpsilas requirements including precision and safety. Further, 3D ultrasonic medical imaging is discussed in the paper. A whole solution of 3D image reconstruction, including ultrasonic image pre-treatment, image segmentation and 3D ultrasonic image reconstruction, are proposed, which contribute to carry out the tasks of ultrasound guided robot aiming radio frequency ablation surgery.
LogDC: Problem Diagnosis for Declartively-Deployed Cloud Applications with Log

Recently, as the evolution of application's development and management paradigms, the deployment declaration becomes a standard interface connecting application developers and Cloud platforms. Kuberenetes is such a system for automating deployment, scaling, and management of micro-service based applications. However, managing and operating such a cloud benefit with additional complexities from the declarative deployment. This paper proposes a log model based problem diagnosis tool for declaratively-deployed cloud applications with the full lifecycle Kubernetes logs. With the runtime logs and deployment declarations, we can pinpoint the root causes in terms of abnormal declarative items and log entries. The advantage of this approach is that we provide a precise log model of a normal deployment to help diagnose problems. The experimental results show that our approach can find out the anomalies of some real-world Kubernetes problems, some of which have been confirmed as bugs. Within the given fault types, our approach can pinpoint the root causes at 91% in Precision and at 92% in Recall.
Implementation of Simulation Platform for Craniofacial Surgery Based on COM

For developing a surgical simulation platform that not only accords with software design standards but also conforms with clinical professional requirements; proposed designing and developing surgical simulation platform using COM (Component Object Model) component technology. Surgical simulation platform based on COM designed three core module: model management; surgical planning; surgical evaluating; implemented WRL model reading and storing, displaying and controlling , models separation and hierarchical correlative, model cutting and measuring; used teamwork pattern which cut down the period of developing platform; was language-independent; easy to upgrade; expansibility; encapsulation; and really achieved separation of data model and behavior simulation. Finally examples verified practicality and good prospects of platform by presenting several examples.
A Novel Full Phase-Coherent Frequency Synthesis Method for SFWF Radar Application

A novel method of full phase-coherent synthesis is proposed in this paper, which uses the frequency-converting technology and the phase-locked loop to fulfill the transmission and tracking of the frequency and phase between the main loop and secondary loops. This method, which differs from the traditional converting-filtering scheme, can solve the tradeoff between the frequency difference and the bandwidth of the full phase-coherent outputs, and it can have a high isolation between the outputs. A Ka-band full phase-coherent frequency synthesizer is implemented based on the idea. The measured results show that this novel full phase-coherent frequency synthesis method proposed in this paper is correct. The frequency synthesizer has full phase-coherent characteristics along with a very low phase noise, fast hopping time, high spurious rejection, and very high isolation between the main output and the secondary output.
Visualization of multiple anatomical structures with explicit isosurface manipulation

In medical image analysis and surgical planning, it is an essential task to visualize and differentiate multiple anatomical structures. The traditional approaches require expensive 3D segmentation steps during pre-processing stage, which defeats the purpose of real-time interaction with the data. In this paper, we propose an interactive method for visualization of multiple anatomical structures. In our results, we show that the new method is a promising technique for visual analysis of medical datasets and a helpful tool for surgical planning. It can be very efficient for a wide range of visualization and analysis tasks.
A miniature Ka-band transceiver with two channels

A compact Ka-band transceiver module with two channels has been developed. This transceiver module consists of two DRO resources, E-plane waveguide filter, coupler, power dividers, over 200 components and 15 MMICs which conclude one mixers, one frequency multiplier, one low noise amplifier, five amplifiers and seven switches, and has superior performance of switch rise-time and fall-time less than 4 ns, greater than 500 mW output power, phase noise of better than -76dBc/Hz at 10 kHz offset and noise figure of receiving ports lower than 9.2 dB. The transceiver module is integrated in a 120 mm x 60 mm><20 mm metal housing.
Gait planning and gait transition of AmphiHex-I

Amphibious robots often utilize collections of gait patterns to locomote over a variety of surface. Each gait of amphibious robots is generally tuned for a specific environment and a set of working conditions. To achieve steady locomotion across a changing environment, a robot should be capable of transition between gaits while keeping on moving. This paper describes the gait patterns, gait parameters and gait transition technique that allow a developed amphibious robot, AmphiHex-I, to transfer from one gait to another. By understanding the characteristics of gaits, we present methods to perform different gaits and accomplish smooth transition between several gaits. A series of locomotion experiments of AmphiHex-I that adopts defined gaits across various environments are presented.
Research of a dual stage bending dexterous robotic hand with EMG control

This Paper presented a new dual stage bending dexterous robotic hand whose soft composite finger (SCF) was consisted of a soft composite structure and a solid hinge both driven by shape memory alloy (SMA) wires. There are three layers of the soft composite structure: an equivalent natural plane with elastic PVC plate, an actuation layer with SMA wires and the basal structure using soft material polydimethylsiloxane (PDMS). The designation of the SCF was inspired by human fingers whose dimension information and movement principle determined the parameters of the bionic finger. The bending principle of the SCF can be describe as below: the hinge provides relative rotation between phalanx and metacarpal bone; the soft composite structure bends on this basis and provides a soft touch. The dual stage bending structure enhances deformation and force output. Several SCFs of different length form the dexterous robotic hand. Various gestures are achieved by the dexterous robotic hand through controlling the kinestate of the actuators. Electromyography (EMG) was used to control the bionic hand.
Secure communication in PCS

We present a new method to provide secure communication in PCS. Our method is based on Data Encryption Standard (DES) encryption/decryption implemented on the mobile handset. It is shown that the proposed algorithm yields higher security compared to GSM authentication protocol at the expense of using more computational time at call setup, which is still negligible. However, in long run transmissions, the time taken to transmit data using our approach is less than that using GSM approach. Our approach is simple, easy to implement, and it can be very useful in present and future wireless communications.