nils-herrmann/clean_scirepeval huggingface dataset:
Adaptive Beamforming with Real-Valued Coefficients Based on Uniform Linear Arrays

A class of adaptive beamforming algorithms with real-valued coefficients is proposed based on the uniform linear array structure by introducing a preprocessing transformation matrix. It is derived from the beamformer with a minimum mean square error (MSE) or a maximum output signal-to-interference-plus-noise ratio (SINR), depending on the specific design criteria. The key parameter of the transformation matrix takes different values for different beamforming scenarios and three representative examples are studied: the linearly constrained minimum variance beamformer (and the generalized sidelobe canceller), the reference signal based beamformer, and the class of blind beamformers based on the constant modulus algorithm. Its advantage is twofold: 1) with real-valued coefficients, the computational complexity of the overall system is reduced significantly; 2) a faster convergence speed is achieved and given the same stepsize, the system arrives at a lower MSE (or a higher output SINR).
Directional interpolation of noisy images

Most of the existing image interpolation schemes assume that the image is noise free. This assumption is invalid in practice because noise will be corrupted in the image acquisition process. The conventional way is to denoise the image first and then interpolate the denoised image. The denoising process, however, may smooth much the image details and introduce some artifacts, which could be amplified in the interpolation process. This paper presents a directional estimation scheme to implement denoising and interpolation simultaneously. For each noisy sample, we compute multiple directional estimates of it and then fuse them for a more accurate output. The estimation parameters computed in the denoising process can be subsequently used for interpolation. Compared with the schemes that perform denoising and interpolation in tandem, the proposed method can better reproduce the image fine structures and reduce much the interpolation artifacts.
A forecasting method of air conditioning energy consumption based on extreme learning machine algorithm

This paper deals with the issue on air conditioning energy consumption and system monitoring of different data in building. Various environmental parameters inside the building are changed in real time, while the conventional air conditioning energy consumption forecasting with the load simulation software cannot adapt to these variations. Therefore, the air conditioning energy consumption forecasting model is established based on extreme learning machine (ELM) algorithm, within the interior environmental parameters of the building. These parameters are obtained through the building monitoring system which takes into account the environmental parameters, number of people, region area and energy consumption. The performance and effectiveness of the proposed forecasting model of air conditioning energy consumption are demonstrated through a case study of a building from practical engineering.
A RFID-Based Material Supply Management System in Automatic Vehicle Assembly Streamline

Material supply management for vehicle assembly workshops usually suffer from message delay and waste of stock, which seriously holdback the reactivity capability of production system. As a rapid, real-time, accurate information collection tools, Radio Frequency identification (RFID) technology has become an important driver in the production and logistics activities of today’s information-based industries. This paper presents a RFID-based material supply management system in automatic vehicle assembly streamline for monitoring and managing the material consumption of each work space real-timely. A prototype system is finished in detail eventually.
An improved analytical method for eddy-current losses and thermal analysis in permanent magnets of PMSMs

This paper researches the principles of eddy-current losses of permanent magnet synchronous motor. Firstly, the paper establishes an analytical model of the flux density in magnets and eddy-current density from the point of views of eddy field and harmonic model. At the same time, the comparison of FEA and analytical result are put forward. In order to analyze the influence of eddy-current losses to the stability of high power-density and different magnet structure to the temperature rise of PMSMs, the paper provides the thermal analysis of prototype motor. It is shown that the analysis results can provide directive value for motor design and stability analysis.
Capacity of Gaussian Channels With Duty Cycle and Power Constraints

In many wireless communication systems, radios are subject to a duty cycle constraint, that is, a radio can only actively transmit signals over a fraction of the time. For example, it is desirable to have a small duty cycle in some low power systems; a half-duplex radio cannot keep transmitting if it wishes to receive useful signals; and a cognitive radio needs to listen and detect primary users frequently. This paper studies the capacity of point-to-point scalar discrete-time Gaussian channels subject to a duty cycle constraint as well as an average transmit power constraint. An idealized duty cycle constraint is first studied, which can be regarded as a requirement on the minimum fraction of nontransmissions or zero symbols in each codeword. Independent input with a unique discrete distribution is shown to achieve the channel capacity. In many situations, numerically optimized on-off signaling can achieve much higher rate than Gaussian signaling over a deterministic transmission schedule. This is in part because the positions of nontransmissions in a codeword can convey information. A more realistic duty cycle constraint is also studied, where the extra cost of transitions between transmissions and nontransmissions due to pulse shaping is accounted for. The capacity-achieving input is correlated over time and is hard to compute. A lower bound of the achievable rate as a function of the input distribution is shown to be maximized by a first-order Markov input process, whose stationary distribution is also discrete and can be computed efficiently. The results in this paper suggest that, under various duty cycle constraints, departing from the usual paradigm of intermittent packet transmissions may yield substantial gain.
Application Method of JPEG2000 Wireless Standard

To achieve the reliable transmission of the JPEG2000 compressed images over an error-prone wireless channel, JPEG2000 part 11 namely JPEG2000 wireless (JPWL) defines a frame for error protection and correction. After introducing the JPWL standard, the application method of JPWL is proposed. According to the error sensitivity information of the codestream provided by Error Sensitivity Descriptor, the Error Protection Block is applied to perform header protection and then to perform unequal error protection for the codestream. In process of decoding, the error concealment technology is used based on the residual errors information provided by Residual Errors Descriptor. Experimental results show that, compared with the traditional method, the proposed method gives more protections of the important parts of codestream. It can not only effectively correct transmission errors, but also significantly improve the ability of decoding and the quality of the decoded images.
An empirical research on the voluntary disclosure of Chinese electronic listed companies' information

With data of Chinese electronic listed companies, this paper empirically analyzes the impact of corporate governance structure, operation situation and external environments on the voluntary disclosure of companies' information. The findings suggest that the share ratio of circulation stock, percentages of independent directors, separation of chairman of the board and CEO, company size and profitability are significantly positively related to voluntary disclosure level; shareholding percentage of the largest shareholder and percentage of the top ten shareholders are significantly negatively associated with voluntary disclosure level. According to the above conclusions, this paper gives some policy suggestion.
A two-stage low-power amplifier with switch-capacitor common-mode feedback circuits

A low-power amplifier is designed to improve the performances of ADCs. The two-stage construction is adopted to provide bigger gain and wider swing at a power supply lower than 3.3V. Besides, the differential architecture is adopted to double the output swing while suppressing common noises. Special common-mode feedback circuits are designed to stable the common-mode outputs of the first and second stages but not to degenerate the output swing. A private switch is designed for the common-mode feedback circuits to eliminate the charge injection effect on the common-mode signals. The measurement results show that the ADC using the proposed amplifier has a SNR which is 4dB better than the ADC without the proposed amplifier.
Analysis on the Performance Bound of Doppler Positioning Using One LEO Satellite

For GNSS receivers where ground aiding service such as AGPS is not available, space borne GNSS aiding based on LEO satellites is a meaningful alternative. For space-borne GNSS aiding, Doppler positioning is generally used for user position initialization. In extreme cases, Doppler positioning may be the only means for positioning. In this work, we analyzed the doppler positioning performance bounds based on the spherical-earth model which is an significant step forward than that based on the flat model in existing work. Extensive simulations are conducted and both theoretical error distributions and practical results based on original LING QIAO GPS (Int'l ID:40136) readings are given. The results show that:(1) Doppler positioning based on full one pass data can achieve a performance that less than 100m most of the time; (2) The results based on the sphericalearth model are different, but are believed to be more accurate than the results based on the flat model.
A vision positioning method for the opening of railway oil tank wagon based on shape matching

The opening positioning for railway oil tank wagon using machine vision technology is an effective way to load petroleum automatically. To overcome the adverse effects produced by illumination changes, various types of railway tank wagon and various positions of camera, a shape matching positioning method is proposed in this paper. Due to the shape of the opening of railway tank wagon is a standard geometry, the edge of the opening can be extracted from a standard image so that the shape of the opening can be described by shape fitting method, which is used as standard template of image recognition, then contour normalized correlation is employed to search the object in the image. To improve flexibility, scalable template is used so that various types opening image of railway tank wagon can be processed by the proposed method. To gain a speed-up, image pyramid is applied to reduce calculation amount. The experiments show that the proposed method fully meets the requirements of practical industrial applications.
A novel hybrid space-vector PWM control for medium and high voltage PMSMs

This paper presents a novel Hybrid Space Vector Control scheme for the vehicle IPMSM, possessing the advantages of both vector control and cascaded multilevel PWM. This scheme can provide the high-voltage vehicle IPMSM with the high-quality, approximate sinusoidal voltage source, meanwhile, it can realize various advanced closed-loop control methods, which is very fit for the vehicle inverters. Simulation and experiment results are also given to verify the high-performance and validity of this scheme.
A classification rule mining method using hybrid genetic algorithms

In this paper, a classification method using an improved hybrid genetic algorithms combining (HGAc) with genetic algorithm and tabu search is presented. A rule extraction approach to raise the classification accuracy as well as to condense the classification rule set is also given. Finally, HGAc is validated upon four benchmark datasets and experimental results are compared with other algorithms. These experiments show that HGAc has good performance and is capable of discovering a set of the succinct, efficient and understandable classification rules.
Design of pressure control system for a large freeform surface polishing robot

A polishing implementing mechanism control system of a large freeform surface polishing robot is designed in this paper. According to the structure characteristic of the implementing mechanism, the control process is composed of position control process and pressure control process. The control system has overcome nonlinear characteristic of the proportional reducing valve effectively and ensured the implementing mechanism can start quickly by using the position and pressure closed loops. For the purpose that the robot can polish on a large freeform surface, a mathematic model of valve control cylinder system is established. The factor of influencing polishing pressure is analyzed. The PID control algorithm is used into the system with the position and pressure of cylinder as the signal of feedback. The experiments prove that this control system can achieve constant pressure polishing while the robot polishes with a certain velocity.
Advanced Internet of Things

In this paper, we propose a standardization scheme for a new paradigm: Advanced Internet of Things (AIoT), which is based on our proposed Unified Object Description Language (UODL) and allows: 1) identifying and interconnecting every object with a standard format, 2) making it easier and flexible for the third party control and management. The purpose of AIoT scheme is to build a smart world of always-on, always-awareness, always-connected, always-controllable, and establish an "intelligent networking'' based relationship among the objects, service suppliers and the users.
Breaking a Chaotic Encryption Based on Henon Map

This paper analyzes a new image encryption scheme proposed in "A new encryption based on Henon mapping" and proves that this encryption algorithm is insecure in the image-known attack. By analyzing the properties of the round function, there are two weaknesses: on the one hand, the confusing process will not completely destroy the correlation of image pixels, on the other hand, because of the transform function’s unbalance, the adversary can use the bit-wise XOR operation as the right transform in a high probability. Experimental results indicate that the image encryption algorithm is insecure.
Cascaded quantization based progressive 3D mesh compression

We proposed an efficient progressive 3D mesh compression method supporting flexible quality scalability. In the proposed method, the mesh geometry prediction residuals are partitioned into a number of iterative layers. Each iterative layer is split into several quality layers using cascaded quantization and then encoded by context adaptive arithmetic codec (CABAC). All the quality layers are encoded and transmitted independently to enable better error resilience. To achieve better rate-distortion performance, the quantization parameter of the first quality layer is determined by the importance of the corresponding iterative layer. Simulation results demonstrate that the proposed method is able to provide better compression performance compared to the state-of-the-art coders.
An Adaptive Fast Factorized Back-Projection Algorithm With Integrated Target Detection Technique for High-Resolution and High-Squint Spotlight SAR Imagery

This paper deals with the problem of fast focusing the spotlight synthetic aperture radar (SAR) data in high-resolution and high-squint mode, which has shown its potential capacity in various military SAR applications. Fast factorized backprojection (FFBP) is considered as an ideal methodology for high-resolution and high-squint SAR imagery. However, FFBP performs pixel-by-pixel interpolation, yielding heavy computational burden and limiting its real-time processing. In this paper, target detection technique, which is used as a discrimination tool to retain the target pixels and reject the clutter and noise pixels, is integrated into the subaperture imaging chain during FFBP implementation, aiming to speed up the overall image formation time. Due to the characteristic of spotlight acquisition, an adaptive processing scheme is developed for multiple subaperture images detection. With the integrated target detection technique, only the target pixels need to be interpolated and accumulated coherently. Without loss of focusing performance, the number of interpolations is dramatically reduced. The proposed fast imaging algorithm is named as adaptive FFBP (AFFBP), and it has distinctive superiority for sparse scene reconstruction, such as the maritime target imaging. AFFBP has been successfully applied to two simulated scenes with high and low signal-to-noise ratios (SNRs), and two real measured datasets with squint angle high up to  $50^{\circ }$ and $70^{\circ }$ , respectively. All these experiments demonstrate the effectiveness and efficiency improvement of the proposed AFFBP algorithm.
Determination of Affinity and Kinetic Constants of the Biotin-Streptavidin Complex Using Microfluidic GMR Biosensors

Studies of the interactions between biological molecules are of highest importance in a vast number of areas of biomedicine and biotechnology. Herein, we present a microfluidic platform based on giant magnetoresistive (GMR) biosensor to study the affinity and kinetic constants of biological molecules. The GMR biochip combined with microfluidic system has high reaction efficiency. The GMR microfluidic biosensor has been successfully used to perform online kinetic measurements of biotin and streptavidin. The affinity and dissociation reaction rate constants are consistent with literature results. Furthermore, we studied the adsorption process of three different types of superparamagnetic nanoparticles with sizes ranging from 50 to 500 nm on the biosensor. Different adsorption models were used to fit the curves. This paper provides a useful guidance in detecting the thermodynamic and kinetic parameters of receptors-ligands, enzymes-substrates, and drug molecules, as well as in diagnosing some diseases.
An ARIMA Based Real-time Monitoring and Warning Algorithm for the Anomaly Detection

With the urgent demands of multi-parameter testing under the extreme environment,such as the deep water, upper air and deep underground etc., the fiber mechanical and thermal multi-parameter instrument is developed with its redominant advantages of accuracy, reliability, sensitivity and convenience. Most existing system usually defined a fixed threshold for the accident warning, which delayed reactions to the emergency. Thus, selecting an appropriate and adjustable threshold for anomaly detection is very necessary. In order to tackle this problem, a modified time series prediction model M-ARIMA is proposed in this paper. M-ARIMA can detect the emergency and achieve high real-time alarm rate. M-ARIMA is based on the dynamic variance and reduces the error rate of early warning caused by the normal fluctuations. Experimental results show that M-ARIMA can detect abnormities with a median accuracy of more than 92% and a median error of less than 10%.
Cost-effectiveness analysis of ICT project in university based on DEA model

In this paper, we studied the ICT application in university and the importance of cost-effectiveness analysis of ICT Projects. It attempted to summarize a suit of indexes for cost-effectiveness analysis and then studied the input-output data of a university's ICT projects by C2R model and cross-efficiency model in DEA. The results showed the main problems in ICT constructions of that school and the efficiency of them also. At last the paper pointed out this method could be used not only in landscape orientation analysis, but also in longitudinal direction analysis.
A temperature-robust analog baseband chain for automotive radar

This paper presents an analog baseband chain for automotive radar applications. The baseband chain consists of a fifth-order Butterworth filter with a reconfigurable bandwidth and a 3-stages programmable gain amplifier (PGA) with DC offset cancellation (DCOC). To achieve robust temperature stability, an amplifier with resistive feedback topology is employed, while temperature compensation technique is also proposed and realized. The chip was implemented in a 65-nm CMOS technology with a 5.6mW power consumption from a 1.2V supply. The simulation results show that the analog baseband achieves a reconfigurable gain range from 18dB to 72dB with 6dB per step, and a reconfigurable 1-dB bandwidth range from 100kHz to 5MHz. The gain of the entire baseband changes by less than 1.4dB from −40°C to 125°C for all steps, while the 1-dB bandwidth changes 0.9MHz at 5MHz step.
Improved VoIP Design for the Advertisement Service

VoIP (Voice over IP), so called Internet phone, provides several unique advantages, for instance, inexpensive long distance call service than the existing wire telephone network and various multimedia services from Internet network added to voice call service. The paper is intended to describe the results of the VoIP system designed and realized by using SIP, which was suggested to create, modify and end multimedia sessions. The VoIP system was developed as an Ads-receiving VoIP terminal, which may receive and save multimedia advertisement and the advertisement service model was suggested. The VoIP phone may save the advertisements received from a PUSH server of common carriers in its internal storage while it saves only the information necessary for a user and delivers it promptly at any time. Regarding the performance of the Ads-receiving VoIP phone, its processing time per kernel instruction, which is the time elapsed to form a packet and transmit it, was 18 ms. As a result of running the software, the receiver only accounted for 4 ms of the software processing time and connecting and disconnecting an outbound call took 93 ms, suggesting the result of 10 ~ 12 calls processed per second.
A peer-to-peer architecture for on-demand video streaming on Internet

A new peer-to-peer (P2P) architecture is developed for streaming stored video on the Internet. In the proposed media streaming architecture, a P2P forwarding chain is constructed. To maintain continuous playback at the peer, a standby FEC server is maintained to provide the FEC coded media stream to peers when their buffered content is almost exhausted. A parent-child exchange (PCX) routing mechanism is proposed to adjust the P2P chain. Our simulation results show that the PCX scheme can greatly improve the system performance and make efficient use of peers' bandwidth. It is also shown that the backup FEC data support from the server can reduce the number of stalled playbacks at the peers with a reasonable cost.
Adaptive super twisting control of linear induction motor considering dynamic end effects

This paper presents an adaptive super twisting control scheme for linear induction motor (LIM), considering dynamic end effects. The designed control strategy is based on cascaded adaptive super twisting controllers (ASTCs) which regulate the stator currents in response to LIM speed error. Based on indirect rotor field oriented control (IRFOC) strategy, the adaptive time varying switching gains are designed and adopted in external loop and internal loop control scheme. The adaptive super twisting algorithm can eliminate the influence of external disturbances and uncertainties. The designed controller shows better results than fixed parameter super twisting controller (STC) with better transient performance and less chattering. Simulation results prove the effectiveness of the proposed control scheme.