Bearing mechanism of roof and rib support structure in automatically formed roadway and its support design method

Non-pillar mining technology with automatically formed roadway is a new mining method without coal pillar reservation and roadway excavation.The stability control of automatically formed roadway is the key to the successful application of the new method.In order to realize the stability control of the roadway surrounding rock,the mechanical model of the roof and rib support structure is established,and the influence mechanism of the automatically formed roadway parameters on the compound force is revealed.On this basis,the roof and rib support structure technology of confined lightweight concrete is proposed,and its mechanical tests under different eccentricity are carried out.The results show that the bearing capacity of confined lightweight concrete specimens is basically the same as that of ordinary confined concrete specimens.The bearing capacity of confined lightweight concrete specimens under different eccentricities is 1.95 times higher than those of U-shaped steel specimens.By comparing the test results with the theoretical calculated results of the confined concrete,the calculation method of the bearing capacity for the confined lightweight concrete structure is selected.The design method of confined lightweight concrete support structure is established,and is successfully applied in the extra-large mine,Ningtiaota Coal Mine,China.

Automatically positioning microseismic sources in mining by the stereo tomographic method using full wavefields

For microseisimic monitoring it is difficult to determine wave modes and their propagation velocity. In this paper, we propose a new method for automatically inverting in real time the source characteristics of microseismic events in mine engineering without wave mode identification and velocities. Based on the wave equation in a spherical coordinate system, we derive a tomographic imaging equation and formulate a scanning parameter selection criterion by which the microseisimic event maximum energy and corresponding parameters can be determined. By determining the maximum energy positions inside a given risk district, we can indentify microseismic events inside or outside the risk districts. The synthetic and field examples demonstrate that the proposed tomographic imaging method can automatically position microseismic events by only knowing the risk district dimensions and range of velocities without identifying the wavefield modes and accurate velocities. Therefore, the new method utilizes the full wavefields to automatically monitor microseismic events.

Comparative study of model tests on automatically formed roadway and gob-side entry driving in deep coal mines

Automatically formed roadway(AFR)by roof cutting with bolt grouting(RCBG)is a new deep coal mining technology.By using this technology,the broken roadway roof is strengthened,and roof cutting is applied to cut off stress transfer between the roadway and gob to ensure the collapse of the overlying strata.The roadway is automatically formed owing to the broken expansion characteristics of the collapsed strata and mining pressure.Taking the Suncun Coal Mine as the engineering background,the control effect of this new technology on roadways was studied.To compare the law of stress evolution and the surrounding rock control mechanisms between AFR and traditional gob-side entry driving,a comparative study of geomechanical model tests on the above methods was carried out.The results showed that the new technology of AFR by RCBG effectively reduced the stress concentration of the roadway compared with gob-side entry driving.The side abutment pressure peak of the solid coal side was reduced by 24.3%,which showed an obvious pressure-releasing effect.Moreover,the position of the side abutment pressure peak was far from the solid coal side,making it more beneficial for roadway stability.The deformation of AFR surrounding rock was also smaller than the deformation of the gob-side entry driving by the overload test.The former was more beneficial for roadway stability than the latter under higher stress conditions.Field application tests showed that the new technology can effectively control roadway deformation.Moreover,the technology reduced roadway excavation and avoided resource waste caused by reserved coal pillars.

Percutaneous endoscopic gastrostomy under steadypressure automatically controlled endoscopy:First clinicalseries

AIM: To elucidate the safety of percutaneous endoscopic gastrostomy(PEG) under steady pressure automatically controlled endoscopy(SPACE) using carbon dioxide(CO_2).METHODS: Nine patients underwent PEG with a modified introducer method under conscious sedation. A T-tube was attached to the channel of an endoscope connected to an automatic surgical insufflator. The stomach was inflated under the SPACE system. The intragastric pressure was kept between 4-8 mmH g with a flow of CO_2 at 35 L/min. Median procedure time, intragastric pressure, median systolic blood pressure, partial pressure of CO_2, abdominal girth before and immediately after PEG, and free gas and small intestinal gas on abdominal X-ray before and after PEG were recorded. RESULTS: PEG was completed under stable pneumostomach in all patients, with a median procedural time of 22 min. Median intragastric pressure was 6.9 mmH g and median arterial CO_2 pressure before and after PEG was 42.1 and 45.5 Torr(NS). The median abdominal girth before and after PEG was 68.1 and 69.6 cm(NS). A mild free gas image after PEG was observed in two patients, and faint abdominal gas in the downstream bowel was documented in two patients.CONCLUSION: SPACE might enable standardized pneumostomach and modified introducer procedure of PEG.

Testing Forms in Web Applications Automatically

Forms enhance both the dynamic and interactive abilities of Web applications and the system complexity. And it is especially important to test forms completely and thoroughly. Therefore, this paper discusses how to carry out the form testing by different methods in the related testing phases. Namely, at first, automatically abstracting forms in the Web pages by parsing the HTML documents; then, ohtai ning the testing data with a certain strategies, such as by requirement specifications, by mining users＇ hefore input informarion or by recording meehanism; and next executing the testing actions automatically due to the well formed test cases; finally, a case study is given to illustrate the convenient and effective of these methods.

Algorithm of Dynamic Operation Process of Hydraulic Automatically Operated Canals with Constant-Downstream Level Gates

On the basis of analysis the governing process of downstream water level gates AVIO and AVIS, a mathematical model for simulation of dynamic operation process of hydraulically automated irrigation canals instalIed with AVIO and AVIS gates is presented, the main point of this rnathematical model is firstly applying a set of unsteady flow equations （St. Venant equations here） and treating the condition of gate movement as its dynamic boundary, and then deeoupling this interaction of gate movement with the change of canal flow. In this process, it is necessary to give the gateg open-loop transfer function whose input is water level deviation and output is gate discharge. The result of this simulation for a practical reach has shown it has satisfactory accuracy.

Research on a Monte Carlo global variance reduction method based on an automatic importance sampling method

Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.

Measurement of Stone Diameter with Three Sizes of Automatically Fixating Stone Baskets

Background: Complications after endoscopic retrieval of kidney and ureter stones are obviously related to the size of the stones as well as the experience of the surgeon and other factors. During the procedure it is sometimes difficult for surgeons to estimate stone size and therefore give prognostic advises. The visual perception of the stone size depends on the shape, colour, distance to the renoscope and dilatation of the ureter. This is the so-called binding problem, because shape, color and direction of motion are processed separately by different population of optical neurons. In order to establish a better prognostic rational especially for less experienced surgeons, we established an intra operative semi-quantitative measurement of the stone size supported by a stone basket. Materials and Methods: We modified the tipped, nitinol stone baskets from the company Urotech with diameters of 2.5, 3.0 and 4 FR. The handle of this basket has a spring mechanism, which automatically closes the basket and provides a predefined fixation force of the stones within the basket. On the handle we established a non-linear scale in mm by grabbing standardized balls or standardized screws. Result: The scales are nonlinear because of the nonlinear relation between the diameter of the stone and the distance of the slider. Also the scales differ in between the basket size, because of the different strain conditions due to the different wire sizes and materials or the spring and basket. Conclusion: This scale could be an important orientation for a surgeon during endourological procedures to estimate stone sizes. After further clinical experience a semi-quantitative visualization like green, yellow and red colors could help to predict potential complications due to large stone sizes. Finally it could bevery interesting for other disciplines like gastroenterology.

An improved, SSH-based method to automatically identify mesoscale eddies in the ocean

Mesoscale eddies are an important component of oceanic features.How to automatically identify these mesoscale eddies from available data has become an important research topic.Through careful examination of existing methods,we propose an improved,SSH-based automatic identification method.Using the inclusion relation of enclosed SSH contours,the mesoscale eddy boundary and core(s) can be automatically identified.The time evolution of eddies can be examined by a threshold search algorithm and a tracking algorithm based on similarity.Sea-surface height(SSH) data from Naval Research Laboratory Layered Ocean Model(NLOM) and sea-level anomaly(SLA) data from altimeter are used in the many experiments,in which different automatic identification methods are compared.Our results indicate that the improved method is able to extract the mesoscale eddy boundary more precisely,retaining the multiple-core structure.In combination with the tracking algorithm,this method can capture complete mesoscale eddy processes.It can thus provide reliable information for further study of reconstructing eddy dynamics,merging,splitting,and evolution of a multi-core structure.

Automatically Mining Application Signatures for Lightweight Deep Packet Inspection

Automatic signature generation approaches have been widely applied in recent traffic classification.However,they are not suitable for LightWeight Deep Packet Inspection(LW_DPI) since their generated signatures are matched through a search of the entire application data.On the basis of LW_DPI schemes,we present two Hierarchical Clustering(HC) algorithms:HC_TCP and HC_UDP,which can generate byte signatures from TCP and UDP packet payloads respectively.In particular,HC_TCP and HC_ UDP can extract the positions of byte signatures in packet payloads.Further,in order to deal with the case in which byte signatures cannot be derived,we develop an algorithm for generating bit signatures.Compared with the LASER algorithm and Suffix Tree(ST)-based algorithm,the proposed algorithms are better in terms of both classification accuracy and speed.Moreover,the experimental results indicate that,as long as the application-protocol header exists,it is possible to automatically derive reliable and accurate signatures combined with their positions in packet payloads.

Method for Automatically Determining the Importance of Criteria in Multicriteria Decision-Making Problems

Multicriteria group decision-making problems （DMP） require criteria weights. Assigning weights of importance of the criteria Face Decision-maker （DM） means, in essence, a priori purpose variant of the winner. There are a number of problematic situations involving a large number of criteria： （1） problems where the evaluation of alternatives represent the degree of satisfaction of basic performance requirements object bidders. Matrix estimates with different low variability and a very large number of requirements （criteria）; （2） the use of cognitive maps for modeling problem situations. If the alternatives are considered not only divisible strategy （options impact on concepts）, matrix estimates accepts small size. If the task is allowed to use an alternative strategy mixtures fraction （e.g., 25% influences on the concept 1, 50% influences on the concept 2, 10% influences on the concept 3, etc.）, the matrix ratings also gaining greater dimension. It is clear that in such cases the appointment criteria weights DMP becomes a problem.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

A Method of Automatically Generating 2D Animation Intermediate Frames

This paper proposes the automatic generation of the middle frame and the middle frame automatic coloring method of two-dimensional animation process, users simply given starting key frames and end key frames, According to the algorithm proposed in this paper, the system can automatically generate all key frames that in the middle, and based on the starting key frame and termination of key frame color, the generated in the middle of the frame will been automatically chromatically. The experimental results show that, the automatic generation of intermediate frames and the middle frame automatic coloring method of two-dimensional animation is proposed in this paper production process can be successfully used in animation production, greatlyimproving the efficiency of animation.

A Method for Automatically Establishing a Mathematical Model of Kinematic Analysis to a Planar Mechanism with a Multiple Joint and Prismatic Pair

A method for automatically establishing a mathematical model of kinematic analysis to a planar mechanism with multiple joint and prismatic pair is presented. The breadth （ or depth ） first search spanning tree can be obtained based on an adjacency matrix of the mechanism. Then the kinematic chain （or mechanism）＇s basic loops can be obtained. On the basis of these basic loops, a mathematical model of kinematic analysis can be established and solved automatically. In the sense of a calculative mechanism, structural analysis of the kinematic chain relates to the kinematic analysis of a mechanism. Thus, an effective way is supplied to the given mechanism＇s kinematic analysis for automatic modeling and solving, and a method is supplied to the structural type to optimize kinematic synthesis.

Automatic fovea detection and choroid segmentation for choroidal thickness assessment in optical coherence tomography

AIM:To develop an automated model for subfoveal choroidal thickness(SFCT)detection in optical coherence tomography(OCT)images,addressing manual fovea location and choroidal contour challenges.METHODS:Two procedures were proposed:defining the fovea and segmenting the choroid.Fovea localization from B-scan OCT image sequence with three-dimensional reconstruction(LocBscan-3D)predicted fovea location using central foveal depression features,and fovea localization from two-dimensional en-face OCT(LocEN-2D)used a mask region-based convolutional neural network(Mask R-CNN)model for optic disc detection,and determined the fovea location based on optic disc relative position.Choroid segmentation also employed Mask R-CNN.RESULTS:For 53 eyes in 28 healthy subjects,LocBscan-3D’s mean difference between manual and predicted fovea locations was 170.0μm,LocEN-2D yielded 675.9μm.LocEN-2D performed better in non-high myopia group(P=0.02).SFCT measurements from Mask R-CNN aligned with manual values.CONCLUSION:Our models accurately predict SFCT in OCT images.LocBscan-3D excels in precise fovea localization even with high myopia.LocEN-2D shows high detection rates but lower accuracy especially in the high myopia group.Combining both models offers a robust SFCT assessment approach,promising efficiency and accuracy for large-scale studies and clinical use.

A Retrodirective Array Enabled by CMOS Chips for Two-Way Wireless Communication with Automatic Beam Tracking

This article proposes and demonstrates a retrodirective array(RDA)for two-way wireless communication with automatic beam tracking.The proposed RDA is enabled by specifically designed chips made using a domestic complementary metal-oxide semiconductor(CMOS)process.The highly integrated CMOS chip includes a receiving(Rx)chain,a transmitting(Tx)chain,and a unique tracking phaselocked loop(PLL)for the crucial conjugated phase recovery in the RDA.This article also proposes a method to reduce the beam pointing error(BPE)in a conventional RDA.To validate the above ideas simply yet without loss of generality,a 2.4 GHz RDA is demonstrated through two-way communication links between the Rx and Tx chains,and an on-chip quadrature coupler is designed to achieve a nonretrodirective signal suppression of 23 dBc.The experimental results demonstrate that the proposed RDA,which incorporates domestically manufactured low-cost 0.18 lm CMOS chips,is capable of automatically tracking beams covering±40with a reduced BPE.Each CMOS chip in the RDA has a compact size of 4.62 mm^(2) and a low power consumption of 0.15 W.To the best of the authors’knowledge,this is the first research to demonstrate an RDA with a fully customized CMOS chip for wireless communication with automatic beam tracking。

A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation signals.The proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed model.The proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to LWNet.Furthermore, the model also has a moderate computation complexity compared with several state-of-the-art methods.

Research on Automatic Test System of Engine Blade Natural Frequency

Blades are one of the important components on aircraft engines.If they break due to vibration failure,the normal operation of the entire engine will be offected.Therefore,it is necessary to measure their natural frequency before installing them on the engine to avoid resonance.At present,most blade vibration testing systems require manual operation by operators,which has high requirements for operators and the testing process is also very cumbersome.Therefore,the testing efficiency is low and cannot meet the needs of efficient testing.To solve the current problems of low testing efficiency and high operational requirements,a high-precision and high-efficiency automatic test system is designed.The testing accuracy of this system can reach ±1%,and the testing efficiency is improved by 37% compared to manual testing.Firstly,the influence of compression force and vibration exciter position on natural frequency test is analyzed by amplitude-frequency curve,so as to calibrate servo cylinder and fourdimensional motion platform.Secondly,the sine wave signal is used as the excitation to sweep the blade linearly,and the natural frequency is determined by the amplitude peak in the frequency domain.Finally,the accuracy experiment and efficiency experiment are carried out on the developed test system,whose results verify its high efficiency and high precision.

Automatic detection method of bladder tumor cells based on color and shape features

Bladder urothelial carcinoma is the most common malignant tumor disease in urinary system,and its incidence rate ranks ninth in the world.In recent years,the continuous development of hyperspectral imaging technology has provided a new tool for the auxiliary diagnosis of bladder cancer.In this study,based on microscopic hyperspectral data,an automatic detection algorithm of bladder tumor cells combining color features and shape features is proposed.Support vector machine(SVM)is used to build classification models and compare the classification performance of spectral feature,spectral and shape fusion feature,and the fusion feature proposed in this paper on the same classifier.The results show that the sensitivity,specificity,and accuracy of our classification algorithm based on shape and color fusion features are 0.952,0.897,and 0.920,respectively,which are better than the classification algorithm only using spectral features.Therefore,this study can effectively extract the cell features of bladder urothelial carcinoma smear,thus achieving automatic,real-time,and noninvasive detection of bladder tumor cells,and then helping doctors improve the efficiency of pathological diagnosis of bladder urothelial cancer,and providing a reliable basis for doctors to choose treatment plans and judge the prognosis of the disease.

Design of Fully Automatic Specification Selection System for Resistance Welding Equipment

A system for fully automatic selection of welding specifications in resistance welding equipment has been developed to address the problem of workers frequently choosing the wrong specifications during manual welding of multiple parts on a single machine in automobile factories. The system incorporates an automatic recognition system for different workpiece materials using the added machine fixture,visual detection system for nuts and bolts,and secondary graphical confirmation to ensure the correctness of specification calling. This system achieves reliable,fully automatic selection of welding specifications in resistance welding equipment and has shown significant effects in improving welding quality for massproduced workpieces,while solving the problem of specification calling errors that can occur with traditional methods involving process charts and code adjustments. This system is particularly suitable for promoting applications in manual welding of multiple parts on a single machine in automobile factories,ensuring correct specification calling and welding quality.