nils-herrmann/clean_scirepeval huggingface dataset:
The borehole-ground controlled source electromagnetic signal transmitter

Currently geophysical electromagnetic exploration for metal ores is facing some problems such as shallow probing depths, low accuracy and resolution, and poor anti-interference ability. To solve these difficulties, it is a feasible approach to make use of the existing mine tunnels, the electromagnetic transmitter on the ground and the recorders at the underground (borehole) or ground (prefecture) to compose a quasi-three dimensional arrangement of measurement technology. This combination method of ground exciting and underground receiving can carry out observations from different directions to obtain subsurface electrical conductivity of the large amounts of information, and conduct quasi-three-dimensional imaging, allowing us to increase detection depth and resolution, and to reduce non-uniqueness in data interpretation and provide a new method for metallic ore exploration. The high-power single frequency transmitter developed by our work can provide a single or multi-frequency inverter square wave, launching the signal frequency from DC to 9600Hz; the maximum emission voltage of 700V, and power supply current of 60A. This apparatus uses the GPS clock and real-time clock (RTC) module to ensure a regular and on time launching at scheduled frequencies. It can also make use of wireless Bluetooth and serial communication interface to control transmitting operation and edit the control parameter file and acquire a variety of supplementary status information. The experiment proves that the equipment is stable and reliable and can meet the requirements of conventional electromagnetic exploration and “tapping the deep and blind exploration of successive resources” for the exhausted mines.
Characterization of Intermodulation Distortion in Reconfigurable Liquid Metal Antennas

The intermodulation distortion produced by passive and tunable liquid metal (LM) antennas is investigated. Four kinds of monopoles, including a passive copper monopole, a varactor-tuned copper monopole, a passive LM monopole, and a tunable LM monopole using electrochemically controlled capillarity (ECC), are compared for their linearity and power-handling capabilities. Linearity is assessed using a two-tone distortion test, in which two fundamental tones close in frequency result in third-order intermodulation tones at frequencies above and below the original tones separated by the frequency difference. The passive LM monopole has comparable linearity to the passive copper monopole, while the linearity of the ECC-tuned LM monopole is at least 40 dB better than that of the active varactor monopole. The reconfigurable LM antenna also handles higher power (31 dBm) before failure than does the active varactor-tuned antenna (24 dBm).
Expert evidence document recognition integrating relationship of expert

Focus on the issue that the existing expert evidence document recognition method is not effective use of the relationship between experts, this paper proposed a method to recognize the expert evidence documents which integrate the feature of webpage content and the complex relationship between the experts. First of all, the method analyses characteristics of expert evidence document, to select Coauthors and organization as relationship feature, and then extracts feature values. Secondly, select 10130 expert evidence pages, and build data sets which integrate the feature values of and webpage content and the relationship, and then select different learning algorithms to build recognition model. Finally, experiment of expert evidence document recognition is carried out in the field of information processing. The experimental results shows that the proposed method achieves a good recognition effect. Using relationship can effectively improve the accuracy of the evidence document recognition. Its accuracy is improved by 4% compared to method using the page content feature recognition only.
Sparse recovery with graph constraints: Fundamental limits and measurement construction

This paper addresses the problem of sparse recovery with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgraph. We provide explicit measurement constructions for several special graphs. A general measurement construction algorithm is also proposed and evaluated. For any given graph G with n nodes, we derive order optimal upper bounds of the minimum number of measurements needed to recover any k-sparse vector over G (Mk,nG). Our study suggests that Mk,nG may serve as a graph connectivity metric.
Research on the application of ground-based optical image for slope rapid monitoring

This paper proposes a method for rapid and continuous monitoring of slope deformation by using terrestrial optical photogrammetry. This slope monitoring method is non-contact and has a high speed to calculate the position and displacement of slope points, which can be applied to the continuous observation and disaster warning of the problem area of the slope. The theory of this method is to obtain the sequence image of the slope through the ground observation platform, and then use the SURF algorithm to generate the 2D displacement field in image plane, and finally orthorectify by using the DTM to calculate the displacement of the slope points. When the displacement of slope point exceeds the threshold, it can be considered that the corresponding position may be unstable and will occur slope sliding.
A Compound Frequency- and Polarization- Reconfigurable Crossed Dipole Using Multidirectional Spreading of Liquid Metal

We present a crossed dipole with frequency and polarization agility using electrochemically actuated liquid metal. For the first time, this antenna uses multidirectional displacement of liquid metal to enable frequency and polarization reconfiguration without the need for mechanical pumps or semiconductor devices. The dipole arms are composed of liquid metal that can be shortened and lengthened within the capillaries by applying DC voltages to each arm. Varying the lengths of the dipole arms generates two independently tuned, linearly polarized resonances from 0.8 to 3 GHz and polarization that can be switched from linear to circular over a portion of this band (0.89–1.63 GHz). Moreover, a circuit model predicts the circular polarization frequency from the input impedance. Simulation and experimental results validate the antenna concept and analysis techniques.
Distributed Parallel Operation of Modified Deadbeat Controlled UPS Inverters

A novel control scheme is proposed for the parallel operation of UPS modules. In this scheme, each UPS in parallel is controlled by a modified deadbeat control method. The traditional deadbeat control has a robust problem to parameter imprecision, which restricts its application. A proportional element is added in the proposed method to solve this problem. The modified deadbeat controlled inverter has good static performance and fast dynamic response and is insensitive to parametric deviation. A distributed control method is used here to realize parallel operation. All the UPS modules are connected by two common lines. One provides a phase signal to synchronize the output voltage. The other one provides the average current signal for the instantaneous average current-sharing control. Experiments are carried out on three 1 kVA on-line UPS modules. The theoretic analysis and experimental results show that the system acts satisfactorily both in steady state and dynamic process. The load distribution among UPS modules is precise in different load conditions, and the real abundance can be achieved.
Spectrum monitoring based on USRP2 receiver

The spectrum monitoring has gained new aspects with the development of cognitive radio and dynamic spectrum access technology. It is also one of the most challenging issues in spectrum management. In this paper, a spectrum monitoring technique using software defined radio is proposed. A prototype setup based on USRP2 with WBX and MATLAB/Simulink is designed and implemented. The spectrum of 50-2200 MHz band was measured. The results show that the prototype setup is capable of detecting the main radio signals within these bands, and spectrum in FM frequency band, digital TV band, GSM and 3G band can be observed.
Lp-TV model for structure extraction with end-to-end contour learning

Structure extraction is important for human perception. However, for various textured images, computers can hardly achieve this goal. Despite a plethora of studies to address the challenge, results from most previous methods contain unwanted artifacts and over-smoothed structures. Therefore, to address the weaknesses, we have proposed a variational model with end-to-end contour learning capability. Our formulation dwells in two observations: likelihood for representation of residual textures may be well abstracted using super Gaussian distribution, and edge metrics with semantic meaning may benefit structure preservation. The augmented Lagrangian method is adopted for optimal computation. Compared with classical approaches, our method offers a higher performance in structure extraction, including situations where the images have significant nonuniformity of the scale features.
TSV technology for 2.5D IC solution

TSV (Through Silicon Via) is the key enabling technology for 2.5D & 3D IC packaging solution. As the 2.5D interposer design pushing towards smaller & shorter via due to I/O density and electrical performance, the warpage of thinner interposer is therefore much more challenging in thin wafer handling and assembly process. In this presentation, a TSV structure is introduced with fabricated interposer prototype, and could be assembled together with single-die/multi-chip on a substrate. The demonstrated interposer assembled in FCBGA (Flip Chip Ball Grid Array) has covered features such as low temperature fabrication process, low warpage, and low leakage with minimized TSV parasitic parameters. Electrical and stress characterizations, current density characterization up to 1100mA and Shadow Moiré are performed and compared with simulation models for correlation study. Known-Good TSV and Si interposer are also reviewed and discussed in this presentation. Full validated reliability test, both die and package level, in conjunction with board level drop test, are presented to verify interposer fabrication, assembly process optimization, and interconnection stability.
Numerical analysis of MTMD by infilled-walls in frame structures

The Multi-functional filled-walls of frame structures based on MTMD which is a new vibration-absorption structure can overcome the shortcoming that the frame structures can't absorb energy continually under strong dynamic loads. In order to study vibration-absorption performance of the new damping filled-walls and apply the MTMD technology in structure design conveniently, damping parameters of vibration-absorption device are studied based on the vibration-absorption principle of MTMD systems and Parameter Optimal Design Method. The vibration performance of the new structure is calculated by using SAP2000 software. By the time-history analysis, a comparison of acceleration and displacement between the general frame model and the frame model-MTMD is carried out. The results indicate that: MTMD-steel frame based on the multi-functional filled-wall structure has a significant shock abortion effect. The periods of the Multi-functional filled-wall model are 2 or 2 times than those of the generals. And it could effectively reduce the vibration response based on the Time-history analysis. The analysis could provide the theory basis and reference for construction design.
Implementation of Internet of Things Oriented Data Sharing Platform Based on RESTful Web Service

Nowadays the Internet of Things is a new concept that attracts more and more attention of researchers. A large amount of smart objects with various communication interfaces will access the Internet of Things. Unique addressing schemes and unified communication mechanism are two basic issues. In this paper, we introduce our solutions. We designed a data platform which can work as the middleware between the physical objects and the virtual digital world. It provides RESTful Web Service, which means any physical object has the unique URI as its address and can be accessed through standard HTTP methods. We also introduce two advanced applications based on our platform, environmental perception and vehicular networks.
A Novel Multiple Instance Learning Approach for Image Retrieval Based on Adaboost Feature Selection

In image retrieval, the concepts are usually in region-level but annotated in image-level, which leads to a major difficulty in learning the target concepts. In this paper, we formulate region-based image retrieval as a multiple-instance learning (MIL) problem, and propose an efficient and effective algorithm, named MI-AdaBoost, to solve it. The algorithm firstly maps each bag into a new bag feature space using a certain set of instance prototypes, and then adopts AdaBoost to select the bag features and build classifiers simultaneously. Experiments on both COREL and MUSK datasets show the proposed scheme is much more efficient than some typical existing MIL algorithms while has comparable results.
Robust Non-negative Graph Embedding: Towards noisy data, unreliable graphs, and noisy labels

Non-negative data factorization has been widely used recently. However, existing techniques, such as Non-negative Graph Embedding (NGE), often suffer from noisy data, unreliable graphs, and noisy labels, which are commonly encountered in real-world applications. To address these issues, in this paper, we propose a Robust Non-negative Graph Embedding (RNGE) framework. The joint sparsity in both graph embedding and reconstruction endues the robustness of RNGE. We develop an elegant multiplicative updating solution that can solve RNGE efficiently and prove the convergence rigourously. RNGE is robust to unreliable graphs, as well as both sample and label noises in training data. Moreover, RNGE provides a general formulation such that all the algorithms unified with the graph embedding framework can be easily extended to obtain their robust non-negative solutions. We conduct extensive experiments on four real-world datasets and compared the proposed RNGE to NGE and other representative non-negative data factorization and subspace learning methods. The experimental results demonstrate the effectiveness and robustness of RNGE.
Study on the Radial-Sheet-Beam Electron Optical System

A new kind of radial-sheet-beam electron optical systems in W-band radial-sheet-beam traveling-wave tubes was described in this paper. A cylindrical cathode with an arc emitting surface was adopted to produce a 2-kV 2-A radial sheet electron beam. The effects of cathode size and anode size on the space-charge-limited current were studied. The electron-beam formation and transmission were discussed under the condition of the space-charge-limited current, and the radial Brillouin focusing magnetic field was obtained. This kind of electron optical systems was simulated by the particle-in-cell method to check up the design. The simulation results presented in this paper show that the beam transmission attained 100% over a distance of 35 mm with a fill factor of ~ 0.55.
RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian with Application to Material Recognition

Infinite dimensional covariance descriptors can provide richer and more discriminative information than their low dimensional counterparts. In this paper, we propose a novel image descriptor, namely, robust approximate infinite dimensional Gaussian (RAID-G). The challenges of RAID-G mainly lie on two aspects: (1) description of infinite dimensional Gaussian is difficult due to its non-linear Riemannian geometric structure and the infinite dimensional setting, hence effective approximation is necessary, (2) traditional maximum likelihood estimation (MLE) is not robust to high (even infinite) dimensional covariance matrix in Gaussian setting. To address these challenges, explicit feature mapping (EFM) is first introduced for effective approximation of infinite dimensional Gaussian induced by additive kernel function, and then a new regularized MLE method based on von Neumann divergence is proposed for robust estimation of covariance matrix. The EFM and proposed regularized MLE allow a closed-form of RAID-G, which is very efficient and effective for high dimensional features. We extend RAID-G by using the outputs of deep convolutional neural networks as original features, and apply it to material recognition. Our approach is evaluated on five material benchmarks and one fine-grained benchmark. It achieves 84.9% accuracy on FMD and 86.3% accuracy on UIUC material database, which are much higher than state-of-the-arts.
Development of New Low Melting Solder Alloys

In advanced 3D IC assembly, one of the key processes is to thin down the wafer for multiple-layer stacking vertically. Warpage is commonly seen in the IC chips due to the differences in coefficient of thermal expansion of the materials. The conventional peak temperatures for reflowing Sn-base Pb-free solders are above 230 °C. High temperature thermal processes would further induce severe warpage issues of the chips with thin wafers and cause failure and degrade the reliability. The development of new Pb-free alloys for low temperature assembly is important for the applications. In the previous years, Sn, In and Bi are the most common elements that are used for low temperature alloys. Setting the melting temperature at around 100°C for the alloy is ideal for practical applications. The two alloys reported in this study show possible applications for the advanced packaging technology. Gallium has a melting temperature of 29.8°C. Alloying Ga in Sn-Bi based solders could reduce the melting temperature to 128°C when the composition is Sn62Bi32Ga6. The alloys reflowed on Cu substrates to investigate the microstructure. The microstructure of the cross-sectioned images and the electron probe micro-analyzer (EPMA) analysis show that the initially formed intermetallic compound (IMC) is CuGa2. The IMCs became basin-type due to fast dissolution of Cu into molten solders. The basin-type IMC eventually became a continuous layer. The thermal aging tests at different temperatures yields the calculation of the activation energy, 2.82 kJ/mol. The relatively low value implies fast IMC growth and could be a possible candidate for the transient liquid phase bonding technique. Another low melting alloy, eutectic In-50wt% Bi (InBi), is developed for its melting temperature at around 95.7°C. This study compares the properties with eutectic Sn-52wt% In (SnIn), melting point of 118°C. Both alloys were reflowed on Cu substrates for cross-sectional microstructure investigation. The scanning electron microscopy (SEM) images revealed that the interfacial compounds were Cu6Sn5, Cu11In9 in eutectic Sn-In and In-Bi alloys, respectively. Shear tests were conducted on the samples with the alloys reflowed on OSP substrates. The results showed that InBi has almost twice the joint strength than the eutectic SnIn solders.
Object Detection and Tracking Under Occlusion for Object-Level RGB-D Video Segmentation

RGB-D video segmentation is important for many applications, including scene understanding, object tracking, and robotic grasping. However, to segment RGB-D frames over a long video sequence into globally consistent segmentation is still a challenging problem. Current methods often lose pixel correspondences between frames under occlusion and, thus, fail to generate consistent and continuous segmentation results. To address this problem, we propose a novel spatiotemporal RGB-D video segmentation framework that automatically segments and tracks objects with continuity and consistency over time. Our approach first produces consistent segments in some keyframes by region clustering, and then propagates the segmentation result to a whole video sequence via a mask propagation scheme in bilateral space. Instead of exploiting local optical, flow information to establish correspondences between adjacent frames, we leverage scale-invariant feature transform (SIFT) flow and bilateral representation to solve inconsistency under occlusion. Moreover, our method automatically extracts multiple objects of interest and tracks them without any user input hint. A variety of experiments demonstrates effectiveness and robustness of our proposed method.
Antenna Pattern Measurement of the Large-Size Radio Telescope by Correlation Techniques and GNSS

It is a challenge to measure the antenna pattern of a large-sized radio telescope with a high resolution because it hardly rotates. This letter presents a simple and efficient method to measure the large-sized radio antenna pattern based on correlation techniques and the Global Navigation Satellite System (GNSS). We estimate the normalized pattern function of the electric field by utilizing correlation properties of the navigation signal in the auxiliary antenna and the radio antenna. The method avoids obtaining a large number of accurate pseudo-code information. Compared to the traditional methods based on the energy detection, the proposed method extends the measurement range and improves the measurement accuracy of the antenna pattern. At the same time, the method also has a better performance in anti-variation of channel and anti-interference.
Development of low temperature solder alloys for advanced electronic packaging: Assessment of In-Bi alloys on Cu substrates

When the advanced electronic packaging technology involves the processes that are incorporated with bio-related devices or integrating the chips on flexible substrate, low temperature materials are needed to reduce the risk of damaging the devices during assembly. This study focuses on developing new alloys that have the melting temperatures not exceeding 120 °C. The new alloys should have comparable functionality to the traditional Pb-free solder alloys. Three In-Bi alloys, 33InBi, 50In50Bi and 68In32Bi, were used to study the interfacial reactions with Cu substrates. Grazing incidence X-ray diffraction (GIXRD) and electron probe X-ray microanalyses (EPMA) were used to characterize the intermetallic compound (IMC) formed at the interfaces. A low-temperature metastable phase, CuIn2, was identified during long-time aging in 68In32Bi/Cu. Shear tests were conducted on the joints of 17Sn-26In-57Bi/Cu and 50In50Bi/Cu due to the similar melting point of the two alloys. Due to high indium content, the deformation energy of 17Sn26In57Bi/Cu drastically decreased while the deformation energy of 50In50Bi/Cu decreased slightly. 50In50Bi/Cu also exhibits higher shear strength than the 17Sn-26In-57Bi/Cu at high-speed shear test.
Application of extension method and chaos theory in ECG identity recognition system

An ECG process based on Einthoven principle was developed for this study. A circuit and DAQ card were incorporated in a human machine interface using LabVIEW to detect the PQRSTpoints in ECG and display the processed ECG signals of the test subjects. The ECG data saved were plotted into dynamical map of chaotic dynamic error using a master-slave chaos system. Chaos eye was selected as the feature and an identity database was built using an element model. Personal identity was identified by categorizing with extension method. Finally, the design was tested on 35 subjects to yield 94.3% of positive identification rate. The results suggested that the identity identification method developed in this study features quick identification, high positive identification rate and good reliability.