nils-herrmann/clean_scirepeval huggingface dataset:
A thermal noise suppression method for increasing lossless compression ratio of the remote sensing images

In order to improve data transmission efficiency between ground and satellite, image compression methods have been implemented onboard for years. However, the thermal noise generated by charge-coupled device (CCD) will decrease the compression ratio of the onboard image data and there is few works to be undertaken on noise suppression oriented for increasing image compression ratio. Therefore, a Homogeneity and Insulation based Forward-And-Backward Anisotropic Diffusion (HIFABAD) method is proposed for increasing lossless compression ratio of the remote sensing images. Different from anisotropic diffusion methods which aim for over-smoothing the image, a novel noise estimation method based on local homogeneity measurement and insulated boundary extraction is proposed for terminating the iteration of HIFABAD. Furthermore, based on the result of homogeneity measurement, the proposed method adds an adaptive parameter for noise suppression of the images with different degrees of homogeneity. To assess efficiency of the proposed method, multispectral and panchromatic image data of the Beijing-1 small satellite are selected to be the data sources. The experimental results show that a higher lossless compression ratio and an acceptable quality of the denoised image can be obtained based the proposed HIFABAD method compared with other existing anisotropic diffusion methods.
A high efficiency and economical energy AC speed-governing experiment system with analogue load

A new kind of variable frequency speed-governing experiment system which has the structure of two parallel inverters at the DC bus and the output of the inverter driving two series asynchronous motors at the same shaft is presented in this paper. The results of the experiment show this creative AC variable frequency speed-governing experiment system can realize the load relationship of direct electromagnetic torque between the motor group, get the continuous control process easily for the reaction load and potential energy load during four quadrant operation, achieve total availability of the regenerative energy at any kind of load.
On the domain and error characterization in the singular perturbation modeling of closed kinematic chains

This paper addresses two important issues in modeling closed kinematic chains (CKC) as singularly perturbed systems, namely, the validity domain and the error characterization. The singular perturbation formulation (SPF) is obtained by replacing the algebraic constraint equation in an index-1 differential algebraic equations (DAE) model with an artificial fast dynamics. We first show that the SPF model has a larger validity domain than the DAE model, and boundaries of the domain are easy to determine. We then characterize the error between the SPF model and the DAE model by deriving explicit error bounds. Sufficient conditions that guarantee exponential convergence of the model error are established. We verify the analysis by simulating the dynamics of a CKC mechanism, the rice planar delta robot, and validating the simulation results with experimental data obtained on the real robot.
Synthetic Landsat data through data assimilation for winter wheat yield estimation

Emergency Response Mechanism (ERM) for remote sensed image sequential deficiency is extremely crucial and the concerned researches are in urgent need. STARFM (Spatial and Temporal Adaptive Reflectance Fusion Model, STARFM) is such a fusion method for image sequences prediction, which is a sound theoretical and valid applicable approach. Gao et al. have successfully produced synthetic Landsat imagery with the corresponding approach, and Hiker et al. have applied it in coniferous study. However, STARFM algorithm has limit modeling power, for it has not fully considered disturbance events occurring within the observation process, meanwhile this paper does not supply an accuracy of synthetic images with variance indicators. Currently, it is still a pending issue addressing the stated estimation and uncertainty existence of sensor measurement values. In this paper, it is assumed that multiple sources data cross-use could minimize the observation error by effective blending technology. Under this assumption, we propose to modify the existing STARFM model, to optimize the predicted imagery through data assimilation theory, and the resulting synthesis image after iterations will be close to the true image. This paper proposes a practical approach of dynamic assimilated STARFM algorithm (DASTARFM), and supplies an application of crop yield estimation by remote sensing technology. In this paper, we mainly: (1)discuss the limits of the current concerned image synthetic researches; and (2) give a description of the practical approach which is featured as adaptive to the dynamic optimization, namely the dynamic optimized STARFM. Besides, (3) based on the new model-DASTARFM, we give the concrete implementation example to present the optimal estimated achievement of this model and illustrate its benefits over the typical algorithm according to the prior and post variances.
Coastline extraction from remote sensing image based on improved minimum filter

In this paper, coastline has been extracted from remote sensing image using the supervised classification method through the research of remote sensing image features. The coastline extraction can be very accurate when the seawater features are obviously consistent in image. For the calm sea image, the coastline can be extracted accurately based on supervised classification. But for the images that have large variation and obvious reflective waves, it will be under the influence of sea surface texture obviously. In order to solve this problem, it put forward an improved minimum filter method to avoid the impact of sea surface texture. The method added two thresholds, which were the PSNR (peak signal-to-noise ratio) and the correlation coefficient. It limited the filter range in sea area. At last, semiautomatic extracted the accurate coastline in ArcGIS. This method can extract most of the coastline in the high-resolution image.
Control of closed kinematic chains: a comparative study

Unlike in the case of open kinematic chains (OKCs), where the stability results for many control schemes are well established, for general closed kinematic chains (CKCs), rigorous stability results are rare. In this paper, we compare our recently developed control method, namely the singular perturbation formulation (SPF), to a control method based on input-output linearization (IOL) of a differential algebraic equation (DAE) model of CKCs. We show the advantages and disadvantages of each method from a theoretical as well as an implementation standpoint. The comparison indicates that our SPF approach is superior in terms of large validity domain, ease of control, implementation, and good performance of the closed-loop system
Exploratory Product Image Search With Circle-to-Search Interaction

Exploratory search is emerging as a new form of information-seeking activity in the research community, which generally combines browsing and searching content together to help users gain additional knowledge and form accurate queries, thereby assisting the users with their seeking and investigation activities. However, there have been few attempts at addressing integrated exploratory search solutions when image browsing is incorporated into the exploring loop. In this paper, we investigate the challenges of understanding users' search interests from the product images being browsed and inferring their actual search intentions. We propose a novel interactive image exploring system for allowing users to lightly switch between browse and search processes, and naturally complete visual-based exploratory search tasks in an effective and efficient way. This system enables users to specify their visual search interests in product images by circling any visual objects in web pages, and then the system automatically infers users' underlying intent by analyzing the browsing context and by analyzing the same or similar product images obtained by large-scale image search technology. Users can then utilize the recommended queries to complete intent-specific exploratory tasks. The proposed solution is one of the first attempts to understand users' interests for a visual-based exploratory product search task by integrating the browse and search activities. We have evaluated our system performance based on five million product images. The evaluation study demonstrates that the proposed system provides accurate intent-driven search results and fast response to exploratory search demands compared with the conventional image search methods, and also, provides users with robust results to satisfy their exploring experience.
DEM generation from stereo SAR images based on polynomial rectification and height displacement

This work introduces the algorithm on DEM generation from stereo SAR images based on polynomial rectification and height displacement, and experiments according to the algorithm on RADARSAT and airborne SAR images in mountain area. To generate DEM from stereo SAR image, there are three kinds of models mostly to be used: 1) the model of range and Doppler equations, 2) the equivalent line central projection model based on the photogrammetry theory, 3) the parallax and elevation relation model which uses the relation between parallax and elevation to calculate elevation difference and then getting the plane coordinates. The model used in This work can be one of the third ones. In our model, image distortion caused by factors other than elevation is corrected by polynomial rectification, and elevation is decided by the difference of height displacement in the pair of the stereo SAR images. As the first step, a certain elevation, for instance the mean elevation of the image pair, is given to the point in process. Secondly, the height displacement in the left image can be corrected, and then the plane coordinates can be gotten by polynomial rectification functions of the left image. Thirdly, by polynomial rectification functions of the right image, the image coordinates of the "same name point" in the right image are available. Finally, from the difference between the coordinates and the actual ones, a new elevation can be gotten by the model of the height displacement of the right image. These steps can be repeated until the new elevation is very close to the old one. According to the above algorithm, programme has been designed. And then, experiment has been down on RADARSAT image in a mountain area in China (Dali, Yunnan). The accuracy is about 3 pixels. For airborne SAR images, some experiments have been down in another mountain area of China (Zhengzhou, Henan) with 1 meter resolution SAR images, and the results are similar to that of the first experiment. So, the new algorithm on DEM created from SAR image pairs introduced by This work is efficient and practicable. After modification, this method can also be used for mixed pair of SAR and optical images.
Environmental Factors Analysis of Indoor Radon Pollution of the Residence in Uranium Ore District

The average level of indoor radon concentration for the residence in the uranium ore district is 282Bq/m3 and the maximum value can up to 570 Bq/m3 which exceed the national top limited value (200Bq/m3). Indoor radon pollution of the residence is very serious. In order to find out the reason of radon pollution, the main environmental factors are investigated. Through the calculations of Gaussian atmospheric diffusion model and simulation verificationthe it is found that the contribution of airborne pollution source terms including uranium mine ventilation shaft, heap leaching field and waste rock yards to indoor radon concentration is only 38.08Bq/m3, accounting for 16.3% of the total indoor radon concentration. But the average value of indoor radon exhalation rate from the ground surface is 0.06 Bq/m2•s. By calculating, radon concentration caused by it is 154Bq/m3, whose contribution to indoor radon concentration is 65.8%. It can be seen that indoor radon of the residence mainly comes from radon precipitation of the soil, followed by the radon in the atmospheric environment. The study can provide a reference to reducing radon pollution of the housing and radiation protection of the residents.
Content-Based Image Retrieval in P2P Networks with Bag-of-Features

Recently, the Bag-of-Features (BoF) model has emerged as a popular solution to scalable content-based image retrieval (CBIR), due to great success of the Bag-of-Words (BoW) model in textual information processing. While most of the existing algorithms on CBIR in P2P networks focus on indexing high dimensional low level features, we propose to address such an issue by employing the BoF model. However, it is not straightforward due to the fact that the BoF model depends on a global codebook and it is very challenging to create and maintain such a global codebook across the whole P2P network. We design a novel online sampling mechanism to create a codebook with low network cost. Since the number of features in each image is large, compared to a text query generally consisting of several keywords, information exchange between nodes for each query image generates high network cost. In order to further reduce the network cost, we implement two static index pruning policies to limit the document length and the returned term weights. Our comprehensive experimental results show that our proposed approach is able to scale up to medium size networks with performance comparable to the centralized environment.
Reverse-Time Migration Based Optical Imaging

We theoretically demonstrated a new optical imaging technique based on reverse-time migration (RTM) for reconstructing optical structures in homogeneous media for the first time. RTM is a powerful wave-equation-based method to reconstruct the image of the structure by modeling the wave propagation inside the media with both forward modeling and reverse-time extrapolation. While RTM is commonly used with acoustic seismic waves, this paper represents the first effort to develop optical RTM imaging method for biomedical research. To refine the image quality, we further developed new methods to suppress the low-wavenumber artifact (LWA). When compared with the conventional means for LWA suppression such as Laplacian filtering, illumination normalization, and the ratio method, our new derivative-based and power-image methods are able to significantly reduce LWA, resulting in high-quality reconstructed images with sufficient contrasts and spatial resolutions for structure identification. The optical RTM imaging technique may provide a new platform for non-invasive optical imaging of structures in deep layers of tissues for biomedical applications.
Optimal monobit digital receiver for QPSK modulation with phase rotation

High-speed high-resolution analog-to-digital converter (ADC) is a key bottleneck in large-bandwidth systems such as 60 GHz communication of wireless personal area networks (WPANs), due to its large power consumption and high complexity. Hence, monobit ADC has been previously proposed to address this problem. In this paper, we propose a receiver architecture with monobit sampling and carrier phase rotation for quadrature-phase-shift-keying (QPSK) modulation. The optimal rotation phase is derived from the achievable-rate point of view. Then, a suboptimal but low-complexity monobit receiver is obtained, and the impact of different rotation phases is investigated. The optimal rotation phase is found to be π/4. Simulation results show that there is only about 1dB signal-to-noise ratio (SNR) loss with a rotation phase deviation of 15° from the optimal value, providing a pretty good robustness to implementation imperfection.
Joint channel estimation and pre-equalization for monobit transmission system

High date rate is one of the important targets in future communication systems, which requires large bandwidth. However, the multibit analog-to-digital converter (ADC) with such a high rate and large bandwidth will have a large power consumption and high implementation complexity. Therefore, monobit receivers have been proposed. In this paper, we concentrate on the channel estimation and equalization for monobit transmission system, which is not investigated up to now. To our surprise, the channel state information (CSI) can be estimated accurately in the condition of one bit quantization, with the proposed greedy pursuit algorithm and iterative method. The minimum mean square error (MMSE) pre-equalizer is then applied to suppress the effect of inter symbol interference (ISI) of the multipath channel. The bit error rate (BER) performance of the proposed algorithm is presented and compared with that of full CSI acknowledge. With the pre-equalizer, the ISI effect is canceled almost completely and “error floor” is eliminated as well. The BER performance can be boosted significantly.
Application of Content-Based Network for Sensor Data Distribution System

This paper proposes and evaluates a new sensor data distribution system, based on the content based network technology. This system is an overlay XML-based content-based routing system over the plain unicast IP network. As the application of the prototype system, we have selected Live E! project, whose object is collecting the weather information from various weather stations and distributing these digital data to the appropriate receiver nodes using the XML-based content-based multicast service. We have designed (1) the representation format of sensor information with XML, (2) content-based multicast routing algorithm using XPath. We have implemented the proposed system for its technical and functional validation
InSAR technology processing and result analysis

InSAR (synthetic aperture radar interferometry) is currently a hot topic that is rapidly evolving thanks to the spectacular results achieved in various fields, especially in the construction of digital elevation models (DEMs) of the Earth's surface. This paper goes deep into the interference imagery mechanism, and from the application requirement of surveying and mapping, stresses solving InSAR key technology. A phase unwrapping method based on the principle of mean field annealing (MFA) is put forward. Finally, we testing this algorithm on some InSAR data, the result shows that this algorithm can obtain DEM correctly and efficiently. Then we analysis the result and display it through 3D. The display effect looks better.
Sparse equalizer design under a quadratic constraint

Sparse equalizers which have fewer nonzero coefficients can significantly reduce the cost of the implementation and computational complexity. The performance of the sparse equalizers heavily depends on the tap selection algorithms. In this paper, a low complexity algorithm based on the forward greedy selection is proposed. The objective of the sparse equalizer design is to reduce the number of nonzero equalizer coefficients under a quadratic constraint with a given tolerance of the performance loss. Furthermore, the performance of the proposed algorithm is analyzed and we obtain the terminal condition for the iteration number of the forward selection algorithm. Simulation results show that the proposed algorithm can reach the same performance or outperform the conventional sparse equalizer schemes, offering a low computational complexity at the same time.
Retinex based motion estimation for sequences with brightness variations and its application to H.264

Conventional motion estimation does not take inter-frame brightness variations into consideration, which causes inefficient video coding for sequences involving brightness variations. H.264 provides a specific mode called weighted prediction targeting to improve the coding efficiency for this case. In this paper, we propose a Retinex based motion estimation scheme which effectively removes the inter-frame de-correlation factor resulting from brightness variations. We also propose to use some DCT techniques to generate the Retinex images for both current and reference images and apply conventional motion estimation and compensation procedures for coding. We applied the scheme to the H.264 testing the efficiency in the multiple reference frame motion compensation environment. Experimental results show that our proposed scheme outperforms the H.264 system with weighted prediction enabled. It allows the system to use a smaller number of reference frames for coding, e.g. 2, to achieve a similar (or slightly better) compression efficiency of the H.264 system using 5 reference frames.
Exposure adjustment of satellite cameras

This paper gives a systematic exploration for exposure adjustment of satellite cameras. First, theories of satellite exposure adjustment are summarized and the affecting factors are discussed. Then, based on defects of current adjustment method adopted on Beijing-1 small satellite, an improved exposure adjustment method that combines sun elevation angle and type of imaged target is proposed, a lookup table that consists of the parameters for exposure setting of different land cover types is provided based on DN statistics and apparent radiance simulation, and the exposure adjustment strategy is also discussed. Serial experiments are conducted for testament of the proposed method, results show that the proposed strategy is applicable and can improve quality of the acquired images.
New methods of the filtering the phase noise in the interferometric SAR

Because of the existence of the noise in the fringe, it influences the computing efficiency and precision of the algorithms of the unwrapping, and then influences the precision of the generation of digital elevation models. This paper firstly analyzes the sources of the phase noise in the fringe. Then introduces several methods used to filter the phase noise in the fringe. For the phase jump in the fringe, it proposes a method of sine & cosine transformation to solve the problem of phase jump. At the basic of the method of sine & cosine transformation, it puts forward two new methods - sine & cosine mean filter (SCMeanF) and sine & cosine median filter (SCMedianF). Lastly, we carried out the contrast test.
A reweighted zero-attracting/repelling LMS algorithm for sparse system identification

A reweighted zero-attracting/repelling least-mean-squares (LMS) algorithm is proposed in this paper for sparse system identification, which attracts zero and near-zero coefficients towards zero, and repels large coefficients against zero. Specifically, an l1-norm constraint on the deviation between the unknown coefficient vector and its estimate is integrated into the original cost function of the LMS algorithm. This generates a correction term in the update equation, which always attracts the coefficients in the estimate towards their optimal values, instead of zero, as is the case in the existing zero-attracting type LMS algorithms. Simulation results demonstrate that the proposed algorithm outperforms the existing l1-norm-constraint sparsity-aware LMS algorithms in the identification of sparse systems.