nils-herrmann/clean_scirepeval huggingface dataset:
A Coarse-to-Fine Algorithm for Registration in 3D Street-View Cross-Source Point Clouds

With the development of numerous 3D sensing technologies, object registration on cross-source point cloud has aroused researchers' interests. When the point clouds are captured from different kinds of sensors, there are large and different kinds of variations. In this study, we address an even more challenging case in which the differently-source point clouds are acquired from a real street view. One is produced directly by the LiDAR system and the other is generated by using VSFM software on image sequence captured from RGB cameras. When it confronts to large scale point clouds, previous methods mostly focus on point-to-point level registration, and the methods have many limitations.The reason is that the least mean error strategy shows poor ability in registering large variable cross-source point clouds. In this paper, different from previous ICP-based methods, and from a statistic view, we propose a effective coarse-to-fine algorithm to detect and register a small scale SFM point cloud in a large scale Lidar point cloud. Seen from the experimental results, the model can successfully run on LiDAR and SFM point clouds, hence it can make a contribution to many applications, such as robotics and smart city development.
Discussion on overlay control for 2X nm technology node and beyond

Moving to the 28 nm technology node and beyond, contact to poly overlay requirement becomes more and more stringent in order to achieve manufacturable static random access memory (SRAM) yield. Typically, a 6 nm or even better on product overlay (OPO) performance have to be met . With the inception of metal gate process and the associated chemical mechanical planarization (CMP) process, it's more difficult to guarantee desired overlay performance. In this paper, potential source of overlay was analyzed and broken down according to our tool and process condition. Among quite a few overlay contributors, mask registration is playing a more and more important role. Besides mask, the upstream process impact on alignment mark was studied in this paper. In addition, reticle heating effect was studied and the compensation of it was assessed by simulation. Finally, we have also explored the capability of high order process control and metrology sampling optimization. If the overlay source can be properly broken down and each contributor can be squeezed to minimum level, overlay performance can fulfill manufacturing requirement.
The Design of a Large Point Reconfigured FFT Based on FPGA

In this paper, we present a design and implementation of a large points reconfigured FFT. This design utilizes one chip FPGA to implement FFT/IFFT operation of high-speed data stream, which adopts two-dimension, parallel and pipeline stream mode and implements the reconfiguration of FFT’s points. It adopts trigonometric function interpolation to compress the twiddle-factors, which can reduce the resources and depress the power of FPGA. This design can be used to implement reconfigured FFT operation which can be from 1K to 1M points. It reaches the requirement of high-speed digital signal process. This design implements large points and reconfigured FFT operation and the aim is to realize miniaturization and low-power.
Optimization for the measurement parameters of CD SEM for several specific situations

Different measurement parameter settings of CD-measuring scanning electron microscope (CD-SEM) can lead to deviations for identical patterns, especially for photoresist patterns with shrinkage effect. This deviation could not be neglected in the 28 nm and sub-28 nm processes. In this paper, we have studied the following cases: 1) Shrinkage effect of negative tone developing process photoresist; 2) Measurement parameter setting optimization for negative tone developing photoresist 1D&2D patterns; 3) Verification on FEM wafers.
A neural network for scheduling and allocation in VLSI design

Neural networks have shown success in solving some difficult optimization problems. Problems become more complex, it is increasingly difficult to find a suitable encoding of constraints into an energy function, which will effectively guide the network to a desired solution. In previous work by Gassen and Carothers (1993), a difficult scheduling problem in VLSI design was encoded into a Hopfield-type neural network. In this paper, we report significant enhancements which allow additional design constraints to be considered and more flexibility for considering the specific design under development.<<ETX>>
Content Authoring Using Single Image in Urban Environments for Augmented Reality

Content authoring is one of essentials of Augmented Reality (AR), which is to emplace an augmented content on a true part of a real scene in order to enhance users' visual experience. For the case of street view single 2D images, the challenge emerges because of clutter environments and unknown position and orientation related to camera pose. Although existing methods based on 2D feature point matching or vanishing point registration may recover the camera pose, the robustness is always challenging because of the uncertainty of feature point detection on texture-less region and displacement of vanishing point detection caused by irregular lines detected on the scene. By taking the advantages of characteristics of the man-made object (e.g. building) widely seen on the street view, this paper proposes a simple yet efficient content authoring approach. In this approach, the building dominant plane where the virtual object will be emplaced is detected and then projected to the frontal-parallel view on which the virtual object can be reliably emplaced. Once the virtual object and the true scene are embedded to each other on the frontal-parallel view, they are able to be converted back to the original view using inverse projection without any distortion. Experiments on public databases show that the proposed method can recover camera pose and implement content emplacement with promising performance.
Dynamic Workflow Management System Supported by Multi-Intelligent-Agent

Firstly aiming at pure agent couldn’t construct virtual enterprise process in real-time, the paper puts forward using multi-intelligent-agent virtual enterprise architecture to implement DAE. Secondly with the help of complex data type in BPDL, STR and SOR, the system implements the business process specification and management. And then multi-intelligent-agent such as PUA, DRA, RPA, and so on interoperate with each other commonly establishes the dynamic VE WFMS. Finally the paper sums up the merits and faults of this system.
High Sensitive Z-Shaped Fiber Interferometric Refractive Index Sensor: Simulation and Experiment

A robust fiber-optic interferometer, which is formed by introducing two bends (i.e., z shape) to the standard telecommunication single mode fiber, is designed and analyzed theoretically and experimentally for the refractive index (RI) sensing. The first (second) bend couples (re-couples) the core (cladding) mode to the cladding (core) modes. The RI-sensitive phase difference between the core and cladding modes gives rise to the modulation of the transmitted intensity. The experimental results show that the z-shaped interferometric sensor possesses an RI sensitivity as high as 196 nm/RIU and fit well with the theoretical predictions. An investigation of the effect of perturbations of bent angle reveals that the sensor possesses relative high sensitivities as the bent angle ranges from 13° to 17° with the difference between the maximum and minimum sensitivities only 2.5% indicating the structure has a good fabrication tolerance to the inaccuracy of the bent angles. In addition, the sensor has advantages of low cost, simple structure, and an ease of fabrication, showing great potential in many sensing applications.
Extended depth-of-field using adjacent plane deblurring and MPP wavelet fusion for microscope images

Imaging specimens thicker than the depth-of-field of a microscope produces poor quality images as only a portion of the specimen is in focus. Therefore, even in the best focused image, there are always objects that are out of focus and thus blurred. It is difficult to accurately measure the size, shape, and boundary of a blurred object. As a result, several optical sections are often required to estimate accurately the entire intensity distribution of the specimen. To overcome this problem, we introduce a novel method of extending the depth-of-field by fusing several optical sections in the wavelet domain using multiscale point-wise product (MPP) criteria. Most existing fusion methods rely on criteria that are merely based on edges and do not distinguish signals from noise. However, our MPP criteria ensures that the signal content, rather than the noise, is collected. Instead of directly fusing optical sections, we preprocess the images by performing adjacent plane deblurring that removes blurred content and preserves the in-focus objects. The overall scheme provides superior quality images with extended depth-of-field and yet the fused images are insensitive to noise. The experimental results indicate both qualitatively and quantitatively that our approach outperforms existing schemes in the literature
Clinical Report Guided Retinal Microaneurysm Detection With Multi-Sieving Deep Learning

Timely detection and treatment of microaneurysms is a critical step to prevent the development of vision-threatening eye diseases such as diabetic retinopathy. However, detecting microaneurysms in fundus images is a highly challenging task due to the low image contrast, misleading cues of other red lesions, and the large variation of imaging conditions. Existing methods tend to fail in face of the large intra-class variation and small inter-class variations for microaneurysm detection in fundus images. Recently, hybrid text/image mining computer-aided diagnosis systems have emerged to offer a promise of bridging the semantic gap between images and diagnostic information. In this paper, we focus on developing an interleaved deep mining technique to cope intelligently with the unbalanced microaneurysm detection problem. Specifically, we present a clinical report guided multi-sieving convolutional neural network, which leverages a small amount of supervised information in clinical reports to identify the potential microaneurysm regions via the image-to-text mapping in the feature space. These potential microaneurysm regions are then interleaved with fundus image information for multi-sieving deep mining in a highly unbalanced classification problem. Critically, the clinical reports are employed to bridge the semantic gap between low-level image features and high-level diagnostic information. We build an efficient microaneurysm detection framework based on the hybrid text/image interleaving and validate its performance on challenging clinical data sets acquired from diabetic retinopathy patients. Extensive evaluations are carried out in terms of fundus detection and classification. Experimental results show that our framework achieves 99.7% precision and 87.8% recall, comparing favorably with the state-of-the-art algorithms. Integration of expert domain knowledge and image information demonstrates the feasibility of reducing the difficulty of training classifiers under extremely unbalanced data distributions.
A Systematic Approach for Cross-Source Point Cloud Registration by Preserving Macro and Micro Structures

We propose a systematic approach for registering cross-source point clouds that come from different kinds of sensors. This task is especially challenging due to the presence of significant missing data, large variations in point density, scale difference, large proportion of noise, and outliers. The robustness of the method is attributed to the extraction of macro and micro structures. Macro structure is the overall structure that maintains similar geometric layout in cross-source point clouds. Micro structure is the element (e.g., local segment) being used to build the macro structure. We use graph to organize these structures and convert the registration into graph matching. With a novel proposed descriptor, we conduct the graph matching in a discriminative feature space. The graph matching problem is solved by an improved graph matching solution, which considers global geometrical constraints. Robust cross source registration results are obtained by incorporating graph matching outcome with RANSAC and ICP refinements. Compared with eight state-of-the-art registration algorithms, the proposed method invariably outperforms on Pisa Cathedral and other challenging cases. In order to compare quantitatively, we propose two challenging cross-source data sets and conduct comparative experiments on more than 27 cases, and the results show we obtain much better performance than other methods. The proposed method also shows high accuracy in same-source data sets.
Study of 1 MHz /spl sim/ 30 MHz voltage-controlled LC oscillator

The required 1 MHz/spl sim/30 MHz 100 Hz step frequency sine signal is obtained by frequency mixing between 2 kHz and 100 Hz step sine signals generated by a voltage-controlled oscillator, MC1648, that is controlled by a PLL, MC145146. The MC145146 is a PLL large-scale IC using a double mode frequency synthesizer, and the frequency setting is realizing by programming a 4 bit data bit, 3 bit address code and 1 bit signal selection bit. The MC145146 includes a 12 bit programmable reference counter (frequency dividing range: 3/spl sim/ 095), a 10 bit main counter (counting range: A=0/spl sim/127), a two phase discriminator, double mode control logic and flip-latch which is used to receive input data and address code. Matched with a double mode frequency demultiplier, a 4 Hz frequency resolution can be obtained.
Linear RF power amplifier design for TDMA signals: a spectrum analysis approach

One of the critical and costly components in digital cellular communication systems is the RF power amplifier. Theoretically, one of the main concerns in an RF power amplifier design is the nonlinear effect of the amplifier. Quantitatively, so far, no explicit relationship or expression currently exists between the out-of-band emission level and the nonlinearity description related to the third-order intercept point ( IP/sub 3/). Further, in experiments and analysis, it was discovered that, in some situations, using IP/sub 3/ only is not accurate enough to describe the spectrum regrowth, especially when the fifth-order intercept point ( IP/sub 5/) is relatively significant compared to the third-order intermodulation. We analyze the nonlinear effect of an RE power amplifier in a TDMA (IS-54 standard) system, give an expression of the estimation of the out-of-band emission levels for a TDMA power spectrum in terms of the IP/sub 3/ and the IP/sub 5/, as well as the power level of the signal. This result will be useful in the design of an RF power amplifier for a TDMA wireless system.
Research on Image Matching Algorithm Based on Local Invariant Features

As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.
Application in Measuring the Microwave Complex Permittivity of Cylindrical Dielectric by Using a Terminal Loaded Coaxial Probe

A new terminal loaded probe which can measure the complex permittivity of dielectric has been proposed in this paper. We have analyzed the effect of some high order TM modes brought by the discontinuity of the dielectrics on the interface in the coaxial cable to the reflectance. According to the mode-matching method, the analysis of the electromagnetic in the coaxial and the dielectric loaded on the terminal of the probe is performed. With the result, we have measured some dielectrics (silicon and Teflon) at and under C band and have compared the metrical value with the computational value and they were nearly the same, and it can advance the precision. This method can be used in measuring the solid material and the liquid as well.
A hierarchical CDFG as intermediate representation for hardware/software codesign

A hierarchical CDFG model designed as an intermediate representation for hardware/software (HW/SW) codesign is presented in this paper. A new concept of transport node, which represents the communication resources of the system, is proposed in this model. Hierarchical feature can be straightly obtained through extending the definition of nodes, allowing them to nest sub-CDFG recursively. Then it is demonstrated how to build basic control constructs of branches and loops. Explaining in a short introduction to the translation process, such a hierarchical CDFG is suitable for HW/SW codesign as an intermediate representation. The hierarchical CDFG model can capture the design information from source file specified by VHDL or C language. It maintains relative simplicity while providing helpful features for HW/SW partitioning and High-level synthesis tools.
Pairwise Shape configuration-based PSA for gait recognition under small viewing angle change

Two main components of Procrustes Shape Analysis (PSA) are adopted and adapted specifically to address gait recognition under small viewing angle change: 1) Procrustes Mean Shape (PMS) for gait signature description; 2) Procrustes Distance (PD) for similarity measurement. Pairwise Shape Configuration (PSC) is proposed as a shape descriptor in place of existing Centroid Shape Configuration (CSC) in conventional PSA. PSC can better tolerate shape change caused by viewing angle change than CSC. Small variation of viewing angle makes large impact only on global gait appearance. Without major impact on local spatio-temporal motion, PSC which effectively embeds local shape information can generate robust view-invariant gait feature. To enhance gait recognition performance, a novel boundary re-sampling process is proposed. It provides only necessary re-sampled points to PSC description. In the meantime, it efficiently solves problems of boundary point correspondence, boundary normalization and boundary smoothness. This re-sampling process adopts prior knowledge of body pose structure. Comprehensive experiment is carried out on the CASIA gait database. The proposed method is shown to significantly improve performance of gait recognition under small viewing angle change without additional requirements of supervised learning, known viewing angle and multi-camera system, when compared with other methods in literatures.
A feasible policy to extend CDMA capacity

In this article we present a two-staged policy to extend CDMA capacity, which can reduce the engineering complexity and reach optimum after two stages. In the first stage we place the new base stations at separate points of the cells and complete a cell splitting by the ratio of l:2, which is non-optimal (non-cellular) and extend the total capacity of this area by 1.6-1.8 times. In the second stage, we place the new base stations at the rest of the points of the original cells and complete a cell splitting by the ratio of 1:3 together with the first stage. Through these two stages, optimal cell splitting can be reached and total capacity is tripled.
A new kind of adaptive frequency shift filter

In this paper, two types of adaptive FREquency SHift filters are proposed. One is LMS adaptive FRESH filter. The other is blind adaptive FRESH filter. By exploiting the spectral correlation of cyclostationary signals, these adaptive filters can separate the signals which overlap in both frequency and time domain. Theoretical development and simulations of these filters are given in this paper. The results show that for signals which spectrally overlap, the adaptive FRESH filters can perform very well while ordinary adaptive filters fail.
Surface texture mapping and its application in 3D modeling system

In this paper, a technique is discussed for surface texture mapping in 3D modeling system. An ideal work-flow approach to texture mapping is designed by analysis texture mapping and its key technique. An index table is firstly constructed, including index No., filename of texture image, size of texture image, etc. A class approach for the data of solid-model is used to distinguish which unit of the model will be textured, and what image will be mapped onto the unit. We provide two modes for texture mapping, namely patch mapping and block mapping, which are implemented in C using the OpenGL library. Finally, a 3D scene can be drawn based on defined texture coordinate and geometry coordinate. Furthermore, we present a concrete example to demonstrate the application of the proposed method. The result shows that 3D model can be displayed more vividly and naturally.
A neural structure for direction finding with sensor array uncertainties

The authors present an auto-calibration technique to estimate the directions-of-arrival (DOAs) of unknown signals in the presence of sensor gain and phase errors. Compared with other autocalibration algorithms, this algorithm is computationally more efficient and has a unique solution for a linear array with the imposed constraints. Furthermore, the complex computation in the objective likelihood gradients is performed by neural networks. An analog scheme encompassing neural networks has been proposed for the algorithm's implementation.<<ETX>>
Runtime resource allocation in multi-core packet processing systems

Packet forwarding operations in network systems are often performed in software so that routers can be updated as new protocols and service features are developed. To meet the processing demands of high-performance networks, multi-processor systems-on-a-chip with dozens of cores are employed to provide raw processing power. Management of these processors and other system resources to achieve high forwarding rates is a key challenge. In particular, the allocation of processing workloads and the placement of data structures in memory have an enormous impact on system performance. Our work proposes a runtime system that manages these system resources. Much related work has proposed the use of cache memory hierarchies in packet processors. In this work, we show that our dynamic placement strategy can outperform a conventional cache memory and achieve up to 1.77 times higher hit rates for small memories, which are typically found in packet processing systems.
Planar Lightwave Circuit Technology-based Optical Interleavers

We review our recent works on the realization of planar lightwave circuit (PLC) technology-based optical interleavers. Commercially available polymer materials were used to fabricate the devices and we implemented our designs using two different configurations. The first is based on a folded two-stage-cascaded Y-junction MZI interleavers which offers a flat-top 100 GHz channel spacing over the entire C-band. The second is based on a three-dimensional structure which allows selectable channel spacing and adjustable flat-top using thermooptic effect. This interleaver is made of two waveguides laid in two different but parallel layers.