nils-herrmann/clean_scirepeval huggingface dataset:
Determining the radiometric response function from a single grayscale image

A method is presented for computing the radiometric response function of a camera from a single grayscale image. While most previous techniques require a set of registered images with different exposures to obtain response data, our approach capitalizes on a statistical feature of graylevel histograms at edge regions to gain information for radio-metric calibration. Appropriate edge regions are automatically determined by our technique, and a prior model of radiometric response functions is employed to deal with incomplete data. With this single-image method, radiometric calibration becomes possible to perform in many instances where the camera is unknown.
Distributed coordination regulation marginal cost control strategy for automatic generation control of interconnected power system

The area-level coordination of regulation capacity by automatic generation control (AGC) is an effective approach to mitigate wind power fluctuations in interconnected power system with high wind penetration. However, the applicability of this method is restricted by the existing AGC strategy. For this reason, power systems in China are experiencing serious wind curtailments to meet the power balance. In this study, a distributed coordination AGC strategy based on regulation marginal cost (RMC) is proposed for coordinating regulation capacity in different areas to remove frequency deviations. Detailed regulating characteristics of the AGC strategy in the existing power systems are discussed. Based on the above analysis, a distributed coordination RMC controller is designed to meet the proposed multi-area coordination rule using a partial primal-dual sub-gradient algorithm. In this proposed controller, the coordination signal containing RMC is exchanged with adjacent controllers through communication networks. The simulation results prove that the distributed coordination RMC strategy can economically coordinate the regulation capacity of an interconnected power system and satisfy the frequency control performance standard.
Behavioral Analysis and Optimization of CMOS CML Dividers for Millimeter-Wave Applications

Current-mode logic (CML) dividers are widely used in radio-frequency and millimeter-wave transceivers and frequency synthesizers for its wide division range. In this brief, a general analysis and optimization methodology of complimentary metal-oxide-semiconductor CML dividers based on the second-order approximation of transconductance is presented for the first time. Mechanisms of asymmetric sensitivity curves around self-oscillation frequency over wideband and inherent cutoff frequency above the self-oscillation are revealed, while corresponding design flow is presented based on the analysis. Following the proposed flow, a better tradeoff between division range and power than the reported arts is obtained by virtue of the proposed optimization method.
Design of Lock-In Amplifier in the Optical Fiber Methane Harmonic Detection

A new safety system of optical fiber detection for methane measurement is described based on the near-infrared absorption mechanism. An optical fiber methane gas detector is designed for methane gas concentration below 5% v/v. The detector bases on tunable diode laser absorption spectroscopy, scans the methane gas absorption lines locate at 1653.722 nm, uses the orthogonal lock-in amplifier technology to extract weak first harmonic signal and second harmonic signal, eliminates light intensity disturbance by using the ratio of the second harmonic peak and the first harmonic average value, realizes the gas concentration measurement. This paper mainly analyzes the principle and key technology of orthogonal lock-in amplifier in the optical fiber methane gas detector. Experimental results show that the response time is 1s, the measurement accuracy up to 500ppm.
A transformer-based filtering technique to lower LC-oscillator phase noise

Phase noise of oscillators can be improved through noise filtering. This paper presents a transformer-based harmonic filtering technique to improve the phase noise performance of the fully differential CMOS LC oscillators. The primary and secondary of the transformer are placed at the sources of NMOS and PMOS differential pairs, respectively. Due to the extra degree of freedom introduced by the transformer, the filter can resonate at two different frequencies, which are designed to be the second and fourth harmonics. The analysis of the filtering method is presented and principles of operation are discussed in details. The performance is compared with other filtering techniques, and the simulation results show improved FoM compared to published literature.
Comparison of electrohysterogram characteristics during uterine contraction and non-contraction during labor.

Uterine contraction is one of the most important indication in the labor progression. Electrohysterogram (EHG) is a promising method for monitoring uterine contraction and discriminating efficient and inefficient contractions. This study aims to analyze the difference of EHG signals between two groups. EHG signals are recorded with abdominal electrodes from 20 pregnant women, including 10 in term labor group and 10 in non-labor group. Typical linear and nonlinear characteristics of EHG signals, including root mean square (RMS), peak frequency (PF), median frequency (MDF), mean frequency (MNF), parameters from wavelet decomposition (W4, W5) and time reversibility (Tr) are extracted. These characteristics are compared between contraction and non-contraction in term labor group and non-labor group. The result shows that RMS, W4 and W5 of contraction are significantly larger than non-contraction both within term labor group and between two groups (all p<;0.001). However, MDF and MNF are significantly smaller (all p<;0.05). Furthermore, all characteristics of non-contraction show no significant difference between two groups, except MNF. The variability of RMS, W4, W5 and Tr of contraction are significantly larger than non-contraction both within term labor group and between two groups (all p<;0.05, with p<;0.001 for W5 and Tr). However, the variability of MDF, PF and MNF are significantly smaller (all p<;0.05). Moreover, the variability of all characteristics of non-contraction shows no significant difference between two groups, except MNF. We have shown that characteristics of EHG signals and their variability during contraction are quite different from non-contraction. Therefore, it is feasible to separate uterine contractions and monitor uterine activity with EHG signals.
A new active vibration isolation control method based on CMAC neural network

In terms of the nonlinearity in active vibration isolation system and the deficiencies of the generally used control methods, a new adaptive neuro-control method was proposed. In the new control structure, a CMAC (cerebellar model articulation controller) network was adopted as controller, and an improved simultaneous perturbation algorithm, which was proven a stochastic gradient approximation method, was proposed to update controller weights without modeling the secondary path. The performance of the control method was verified by numerical simulation, and simulation results showed that the proposed method has preferable isolation performance for system with nonlinearity when compared with filtered LMS method
A stochastic network calculus approach for the end-to-end delay analysis of LTE networks

The last decade has seen an explosive growth in wireless network services and consequently an increasing demand of high data rates on wireless networks, and the demand of users on real-time traffic is growing. The quality of service (QoS) requirements of different applications are different, for example, the real-time applications are delay-sensitive, yet can tolerant certain data loss. An intrinsic characteristic of radio communication is that the instantaneous radio-channel quality varies in time. Since stochastic network calculus takes the stochastic characteristics of traffic and service processes into consideration to make better use of their statistical multiplexing gains, so we take the 3GPP long term evolution (LTE) as the background, and construct a framework of analyzing the performance of the LTE networks by modeling the arrival model and the service model using stochastic network calculus. Numerical analyses are conducted to prove the effectiveness of the framework.
A fully integrated CMOS nanoscale biosensor microarray

This paper presents a fully integrated CMOS microarray for biosensor applications. A 64-pixel working electrode array with optimized reference and counter electrode structure is proposed to improve symmetry, and the feature sizes of electrodes have been scaled down to 600nm. The circuit utilizes the decoding scheme of memories to simplify the pixel design while shares potentiostat opamp and current amplifers, which allows the miniaturization of electrodes and enables large-scale integration of the microarray. The demo is fabricated in 0.18µm CMOS technology, and experimental results successfully demonstrated the biosensing detections on the nanoscale microarray. The circuit provides a current gain of 19.9dB, 3dB bandwidth of 15kHz, dynamic range of 141dB, sensing sensitivity of 37.6pA, and a driving capability of 0.46mA, respectively.
A Novel Algorithm for Finding Reducts With Fuzzy Rough Sets

Attribute reduction is one of the most meaningful research topics in the existing fuzzy rough sets, and the approach of discernibility matrix is the mathematical foundation of computing reducts. When computing reducts with discernibility matrix, we find that only the minimal elements in a discernibility matrix are sufficient and necessary. This fact motivates our idea in this paper to develop a novel algorithm to find reducts that are based on the minimal elements in the discernibility matrix. Relative discernibility relations of conditional attributes are defined and minimal elements in the fuzzy discernibility matrix are characterized by the relative discernibility relations. Then, the algorithms to compute minimal elements and reducts are developed in the framework of fuzzy rough sets. Experimental comparison shows that the proposed algorithms are effective.
Construction of a New Full-Rate Full-Diversity Space-Time Block Code in Correlated Channel

This paper introduces a full rate, full diversity orthogonal space-time block code for 4 transmit antennas. The codeword blocks can be viewed as quaternions which are drawn from the icosahedral group and no constellation expansion. We prove the full diversity of the proposed STBC and analysis the performance under the correlated MIMO channel. By utilizing the quaternionic form, we can find the decoding algorithm to reduce the complexity of maximum likelihood (ML) coherent decoding and introduce a non-coherent differential decoding rule.
Design of optimised multiple partial recovery LT codes

Existing rateless codes have a very low intermediate symbol recovery rate. Therefore, a new analysis method named iterative and small degree first (I-SDF) is presented for the design of optimised partial recovery Luby transform codes (PR-LTC) in this study. On the basis of I-SDF, the required number of encoded symbols with degree d in each decoding step is calculated by an iterative optimisation algorithm. Under the proposed design, R(R < k) input symbols can be recovered from as few encoded symbols as possible in PR-LTC with message length k. Furthermore, multiple PR-LTC (M-PR-LTC) is proposed to recover several partial recovery point (PRPs) efficiently. The analysis process is divided into multiple stages, and the required number of encoded symbols with degree d in each decoding step is calculated by a cross-stage iterative optimisation algorithm. In addition, the interaction of each stage is adjusted by introducing a weight for each PRP. The PR-LTC and M-PR-LTC are evaluated and compared with the existing schemes. The simulation results demonstrate that PR-LTC and M-PR-LTC outperform other existing schemes in terms of average overhead, average degree of encoded symbols, memory usage, bit error rate and energy consumption.
Bacterial community dynamics and its effects during biological activited carbon filter process for drinking water treatment

A biological activated carbon (BAC) filter was designed for treatment of micro-pollutants in Songhua River. The goal of the study was to characterize bacterial diversity over time and in different spatial regions of the filter and evaluate the effects on BAC performance. The bacterial activity varied over time and the length of the filter. SEM results showed biomass of BAC filter increased during operation and corresponding biological activity reached to 1023.5 (ng ATP g−1 carbon). PCR-DGGE results showed that bacterial composition differed in different spatial regions of the filter and competition between bacterial populations existed. Bacterial dynamics might affect bacterial activity and BAC performance. With bacterial populations reduced, increase of bioactivity, TOC and ammonium removal rate became lower. The phylogenetic results showed BAC filter was colonized by diverse population of bacteria at the end of operation, which played an important role in the performance and reliability of this biofilter system.
3D Geometry and Motion Estimations of Maneuvering Targets for Interferometric ISAR With Sparse Aperture

In the current scenario of high-resolution inverse synthetic aperture radar (ISAR) imaging, the non-cooperative targets may have strong maneuverability, which tends to cause time-variant Doppler modulation and imaging plane in the echoed data. Furthermore, it is still a challenge to realize ISAR imaging of maneuvering targets from sparse aperture (SA) data. In this paper, we focus on the problem of 3D geometry and motion estimations of maneuvering targets for interferometric ISAR (InISAR) with SA. For a target of uniformly accelerated rotation, the rotational modulation in echo is formulated as chirp sensing code under a chirp-Fourier dictionary to represent the maneuverability. In particular, a joint multi-channel imaging approach is developed to incorporate the multi-channel data and treat the multi-channel ISAR image formation as a joint-sparsity constraint optimization. Then, a modified orthogonal matching pursuit (OMP) algorithm is employed to solve the optimization problem to produce high-resolution range-Doppler (RD) images and chirp parameter estimation. The 3D target geometry and the motion estimations are followed by using the acquired RD images and chirp parameters. Herein, a joint estimation approach of 3D geometry and rotation motion is presented to realize outlier removing and error reduction. In comparison with independent single-channel processing, the proposed joint multi-channel imaging approach performs better in 2D imaging, 3D imaging, and motion estimation. Finally, experiments using both simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.
Design and implementation a high performance communication library based on commodity Ethernet NICs

A high performance communication library independent of hardware called HPCL/Ethernet is implemented based on commodity Ethernet NICs on the Linux. HPCL/Ethernet supports commodity Ethernet NICs by using the network device interface on the Linux kernel. Reliable message delivery is guaranteed in the software layer. Channel is adopted for simplifying buffer management and fixed-buffer policy is adopted for avoiding message copy. Both interrupt reaping technology and the policy of message processing in link layer are also used to optimize communication. The experimental results show that the HPCL/Ethernet is characteristic of low latency with short payload message and high bandwidth with long payload message. It provides 1.18E+08 bytes/s of bandwidth for 1196 bytes message which is 94.4% of hardware-level bandwidth.
DBF-NELT: A novel unambiguous tracking technique for Galileo E1 signal

BOC(m,n) modulation is now widely adopted in secondary Global Navigation Satellite System(GNSS) signals. The new generation modulation is equipped with greater multipath mitigation and anti-jamming performance than traditional BPSK modulation. However, the autocorrelation function multi-peaks of BOC(m,n) signals induce serious tracking errors for GNSS receiver design. This article presents a novel method nominated DBF-NELT to overcome the problem. The simulation to process Galileo E1 signals proves that the thermal performance of DBF-NELT outperforms conventional unambiguous tracking methods. Moreover, the code loop discriminator is improved by a look-up table which is more linear in pull-in range.
A Study on Random Autonomous Algorithm for Service Survivability Scheduling

We present in this paper a scheduling algorithm towards the service migration uncertainty that aims to enhance the service survivability in the server cluster system. Survivable scheduling algorithm is one of the important aspects of survivability study. This paper introduced the stochastic mechanism in the server cluster systems, which made it uncertain of the services migration among the servers, so as to increase the difficulty for the intruders penetrating the systems, and enhanced the system survivability. In this work, we introduced the layers of survivability study, illustrated the function of the survivable scheduling algorithm; then, analyzed the advantages and disadvantages of the exist scheduling algorithms; promoted a pseudo-random autonomous algorithm for service survivability scheduling, including generating the scheduling sequence and the Markov-based autonomous competition mechanism, the performance of the algorithm is investigated at last.
A constrained constant modulus algorithm based on uniform linear arrays

A novel constant modulus algorithm (CMA) is proposed based on a uniformly spaced linear array by constraining its weight vector to a specific conjugate symmetric form. The constraint is derived from the beamformer with an optimum output signal to interference plus noise ratio (SINR). The effect of the additional constraint is equivalent to adding a second step to the original adaptive algorithm. With this constraint, the modified CMA will always generate a weight vector in the desired form for each update and the number of variables is effectively reduced by half, leading to a faster convergence rate and an improved SINR performance. The proposed idea is general and can be extended to many other variations of the standard CMA.
Continuous attractors of a class of recurrent neural networks without lateral inhibition

Researches on neural population coding have revealed that continuous stimuli, such as orientation, moving direction, and the spatial location of objects could be encoded as continuous attractors in neural networks. The dynamical behaviors of continuous attractors are interesting properties of recurrent neural networks. This paper proposes a class of recurrent neural networks without lateral inhibition. Since there is no general rule to determine the stability of the network without specifying the excitatory connections, individual conditions can be calculated analytically for some particular cases. It shows that the networks can possess continuous attractors if the excitatory connections are in gaussian shape. Simulation examples are employed for illustration.
Analytic Scoring of Landscape CAD Course Based on BP Neural Network

Course Scoring is the major criteria for measuring the teaching effect and a basis for improving the education quality. Analytic scoring of landscape CAD (Computer-Aided Design) course is influenced by various factors. Relationships among these factors are complex, some are nonlinear, even some are random and fuzzy. It is difficult to explain their internal relationships with traditional method. This research combines Back-Propagation neural network and DPS software to establish a three-layer BP neural network model, which took 60 examination papers of landscape CAD course as samples and made predictions on the score in accordance with five factors, including landscape design standard, landscape design innovation, computer cartography standard, drawing effect and workload. The results show that BP neural network model has strong nonlinear approximation ability, could truly reflects the nonlinear relationships between global score of landscape CAD course and main controlling factors of analytic scoring, with small error between predicted values and the measured values, relative error lower than 5%. In the future, when analytic scoring of the landscape CAD course obtains from the teachers, the global scoring can be calculated by BPNN model automatically. This method showed wide application prospect to the courses need analytic scoring.
A large width SAR image registration method based on the compelex correlation function

SAR complex image registration is one of the key steps of the interferometirc SAR and tomographic SAR. The complex correlation function based method is an common registration method. Generally in the application, the adopted SAR complex image is large width, however, the complex correlation functions of registration accuracy can only be guaranteed the high precision of a small scale registration in an image. This paper puts forward a complex correlation function based method of large width SAR image. First of all, we take a large width SAR image into blocks, and obtain registered offsets according to the complex correlation functions of every block. And then we advocate ten times interpolation for the master image and the slave image. With the master image as reference, we resample for the slave image according to registered offsets of each block. Finally, we present the detailed steps of registration method. We use The ALOS data for real data processing, and the processing results demonstrate the effective method.
An infrared radiation based thermal biosensor for enzymatic biochemical reactions

In this paper, a thermal biosensor based on the infrared radiation energy is proposed for calorimetric measurement of biochemical reactions. Having a good structure design combined with MEMS technology as well as employing the Si/SiGe quantum well sensing material with a high TCR and low 1/f noise, the sensor shows potentials to be high sensitive and real-time. The urea enzymatic reaction was tested to verify the performance of sensor, which demonstrates a linear detection range from 0.5mM to 150mM and a relative standard deviation less than 1%. For the sensor fabrication, wafer-level transfer bonding is a key process, which makes the integration of quantum well material and a free standing structure possible. It reduces the heat loss from the sensor to the surrounding environment.
Compensation Strategy of Levitation Forces for Single-Winding Bearingless Switched Reluctance Motor With One Winding Total Short Circuited

In order to take advantage of conventional switched reluctance motors (SRMs), the SRM is integrated with the bearingless motor technology and then a reluctance type of bearingless motor is created, named as bearingless SRM (BSRMs). Not only electromagnetic torque but also the levitation forces should be controlled in BSRMs, which is different from SRMs. The levitation forces should always exist even when winding fault occurs. Therefore, the absent levitation forces that ought to be produced by the fault winding should then be compensated by other winding. This paper proposes the compensation strategy of levitation forces for BSRMs when one stator winding is short circuited. The short-circuit fault is investigated and the short-circuit current is expressed for the derivation of radial forces. Then, the winding compensation rule and the mathematical model of levitation forces are developed to facilitate the compensation control for the motor levitation. After that, the proposed compensation strategy is verified by simulation results in MATLAB/Simulink. Experimental results are also presented to demonstrate the performance.