nils-herrmann/clean_scirepeval huggingface dataset:
A Feature-Free Flexible Approach to Topical Classification of Web Queries

The task of topical classification of Web queries is to classify Web queries into a set of target categories. Machine learning based conventional approaches usually rely on external sources of information to obtain additional features for Web queries and training data for target categories. Unfortunately, these approaches are known to suffer from inability to adapt to different target categories which may be caused by the dynamic changes observed in both Web topic taxonomy and Web content. In this paper, we propose a feature-free flexible approach to topical classification of Web queries. Our approach analyzes queries and topical categories themselves and utilizes the number of Web pages containing both a query and a category to determine their similarity. The most attractive feature of our approach is that it only utilizes the Web page counts estimated by a search engine to provide the Web query classification with respectable accuracy. We conduct experimental study on the effectiveness of our approach using a set of rank measures and show that our approach performs competitively to some popular state-of-the-art solutions which, however, make frequent use of external sources and are inherently insufficient in flexibility.
Convergent 2-D Subspace Learning With Null Space Analysis

Recent research has demonstrated the success of supervised dimensionality reduction algorithms 2DLDA and 2DMFA, which are based on the image-as-matrix representation, in small sample size cases. To solve the convergence problem in 2DLDA and 2DMFA, we propose in this work two new schemes, called Null Space based 2DLDA (NS2DLDA) and Null Space based 2DMFA (NS2DMFA), and apply them to the challenging multi-view face recognition task. First, we convert each 2-D face image (matrix) into a vector and compute the first projection matrix P 1 from the null space of the intra-class scatter matrix, such that the samples from the same class are projected to the same point. Then the data are projected and reconstructed with P 1 . Finally, we re-organize the reconstructed datum into a matrix and then compute the second projection direction P 2, in the form of a Kronecker product of two matrices, by maximizing the inter-class scatter. A proof of algorithmic convergence is provided. The experiments on two benchmark multi-view face databases, the CMU PIE and FERET databases, demonstrate that NS2DLDA outperforms Fisherface, Null Space LDA (NSLDA) and 2DLDA. Additionally, NS2DMFA is also demonstrated to be more accurate than MFA and 2DMFA for face recognition.
A design of PMMW camera for security scanning

From the request of the Customs house for detecting things hidden in the clothes, base on the specific characteristics of the different technical scheme on PMMW imaging system, an imaging scheme that uses broad-band multi-beam antenna in one dimension and machine scanning in another dimension has been selected. The experimental system has been designed and some examination has been done. The result shown the experimental system can be used for security scanning in the Customs house
Bluetooth Technology Applied in Theodolite

Theodolite data are recorded by person, there is human error and post-processing workload. Transmitted by USB data cable realized digital transmission and recording, but person activities are yoked by the cable, field operation is inconvenient and inflexible enough. Often plugging USB data cable, poor contact and the equipment damaged are easy caused, etc. Single-chip Microcomputer and Bluetooth technology are applied in wireless transmission and control of theodolite data, it is realized that mapping data are wirelessly transmitted and storaged to the PDA. The experiment indicated that the communication distance is more than 500 meters, which the error rate is 0%, and that it is also 0% to avoid obstacle transmission error rate.
An Adaptive User Selection Algorithm for Multiuser MISO Downlink Systems

Multiuser multi-input single-output (MISO) downlink systems, where one base station equipped with multiple antennas serves multiple single antenna mobile users, is of great interest recently. Significant capacity benefit can be obtained without extra time slots or spectrum. However, the number of simultaneously supportable users is limited by the number of transmit antennas. User selection is required for choosing the best subset in case of more users than transmit antennas. In this paper, we propose an efficient user selection algorithm aiming to maximize the sum rate capacity. The number of selected users can change adaptively according to current channel condition. Through simulation results, the very good performance of the proposed algorithm is shown, and it achieves near optimal performance while with low computational complexity.
Human Gait Recognition Using Patch Distribution Feature and Locality-Constrained Group Sparse Representation

In this paper, we propose a new patch distribution feature (PDF) (i.e., referred to as Gabor-PDF) for human gait recognition. We represent each gait energy image (GEI) as a set of local augmented Gabor features, which concatenate the Gabor features extracted from different scales and different orientations together with the X-Y coordinates. We learn a global Gaussian mixture model (GMM) (i.e., referred to as the universal background model) with the local augmented Gabor features from all the gallery GEIs; then, each gallery or probe GEI is further expressed as the normalized parameters of an image-specific GMM adapted from the global GMM. Observing that one video is naturally represented as a group of GEIs, we also propose a new classification method called locality-constrained group sparse representation (LGSR) to classify each probe video by minimizing the weighted l1, 2 mixed-norm-regularized reconstruction error with respect to the gallery videos. In contrast to the standard group sparse representation method that is a special case of LGSR, the group sparsity and local smooth sparsity constraints are both enforced in LGSR. Our comprehensive experiments on the benchmark USF HumanID database demonstrate the effectiveness of the newly proposed feature Gabor-PDF and the new classification method LGSR for human gait recognition. Moreover, LGSR using the new feature Gabor-PDF achieves the best average Rank-1 and Rank-5 recognition rates on this database among all gait recognition algorithms proposed to date.
Comprehensive Common Spatial Patterns With Temporal Structure Information of EEG Data: Minimizing Nontask Related EEG Component

In the context of electroencephalogram (EEG)-based brain-computer interfaces (BCI), common spatial patterns (CSP) is widely used for spatially filtering multichannel EEG signals. CSP is a supervised learning technique depending on only labeled trials. Its generalization performance deteriorates due to overfitting occurred when the number of training trials is small. On the other hand, a large number of unlabeled trials are relatively easy to obtain. In this paper, we contribute a comprehensive learning scheme of CSP (cCSP) that learns on both labeled and unlabeled trials. cCSP regularizes the objective function of CSP by preserving the temporal relationship among samples of unlabeled trials in terms of linear representation. The intrinsically temporal structure is characterized by an $\ell_1$ graph. As a result, the temporal correlation information of unlabeled trials is incorporated into CSP, yielding enhanced generalization capacity. Interestingly, the regularizer of cCSP can be interpreted as minimizing a nontask related EEG component, which helps cCSP alleviate nonstationarities. Experiment results of single-trial EEG classification on publicly available EEG datasets confirm the effectiveness of the proposed method.
Highly parallel image coding for many cores

This paper proposes a pure line-by-line image coding scheme (LBC) for many-core computers. The proposed scheme can simultaneously use tens and even hundreds of cores to compress one HD image. In LBC, an input image is coded line by line sequentially and each line is divided into many short segments at equal length that are coded independently. Experimental results show that the proposed scheme can speed the encoding up to 14 times through 16 cores, whereas parallel H.264 intra-frame coding can only speed up less than 5 times. In terms of coding performance, efficient intra predictions are proposed to make full use of the strong correlations among neighboring lines. Experiments results also show that the proposed scheme can have a comparable and even better performance than H.264 high profile at middle bit rates. At high bit rates, the proposed scheme can outperform H.264 high profile more than 10dB.
Agent-based hardware-in-the-loop simulation for UAV/UGV surveillance and crowd control system

An agent-based hardware-in-the-loop simulation framework is proposed to model the UAV/UGV surveillance and crowd control system. To this end, a planning and control system architecture is discussed first, which includes various modules such as sensory data collection, crowd detection, tracking, motion planning, control command generation, and control strategy evaluation. The modules that are highly related with agent-based modeling (focus of this paper) are then discussed, which includes the UAV/UGV motion planning considering multi-objectives, crowd motion modeling via social force model, and enhancement of simulation environment via GIS 3D coordinates conversion. In the experiment, Repast Simphony is used as the agent-based modeling tool, which transmits sensory data and control commands with QGroundControl as hardware interface that further conducts radio communications with ArduCopter as a real UAV. Preliminary results show that finer grid scale and larger vehicle detection range generate a better crowd coverage percentage. Finally, conclusions and future works are discussed.
An energy measurement method of high-frequency narrow laser pulse based on FPGA

An energy measurement method used for high-frequency narrow laser pulses based on a high performance field-programmable gate array (FPGA) chip is introduced in this paper. There are two parts contained in this method: signal conditioning and data processing. The signal conditioning part will transform the incident narrow laser pulse to electrical signal which has an appropriate width and the amplitude is linear to the energy of the laser pulse. The electrical signal will be digitalized by a high speed ADC and input to the FPGA chip in the data processing part. The amplitude of the electrical signal will be obtained by real-time calculations in the FPGA. The test result shows that the method is suitable for the laser pulse with FWHW low level with 200ps and frequency up to 20MHz.
Model Checking UML Activity Diagrams in FDR

The Unified Modeling Language (UML) is the de-facto industrial standard for modeling object-oriented software systems. UML Activity diagrams (ADs) can be used for software modeling and they have under gone significant changes with UML 2.0 specification, and no longer been a special kind of diagrams of UML state machines. ADs, however, are lack of formal semantics like other diagrams in UML official specifications and therefore they cannot be performed formal system behavior analysis. Verify if a UML model meets the required properties by model checking has become a key issue. Many attempts have been made to provide formalization for UML State Diagrams, but little for ADs. This paper formalize the UML ADs and then employs the Hoare’s Communicating Sequential Processes to specify its operational and behavior semantics. The presented formalization makes it possible to reason about the behavior of a UML AD in CSP. A software tool for supporting to transfer an AD into CSPM specification has been implemented. Hence it provides an approach to model checking UML ADs by model-checker FDR. Finally, the formalisms and model checking are explicitly illustrated through a simple but non-trivial example.
A Compact Multipath Mitigating Ground Plane for Multiband GNSS Antennas

This paper presents the design of a novel multipath mitigating ground plane for global navigation satellite system (GNSS) antennas. First, the concept of a compact low multipath cross-plate reflector ground plane (CPRGP) is presented. In comparison with the choke ring and electromagnetic band gap (EBG) ground planes, the proposed CPRGP has compact size, low mass, wide operational bandwidth, and simple configuration. The proposed CPRGP is then integrated with a circularly polarized dual-band GNSS antenna in order to assess the multipath mitigating performance over two frequency bands. Measurement results of the proposed CPRGP with GNSS antenna achieves a front-to-back ratio (FBR) over 25 dB at L1 (1.575 GHz) and L2 (1.227 GHz) bands and maximum backward cross-polarization levels below -23 dB at both bands. Antenna phase center variation remains less than 2 mm across both L1 and L2 bands. Furthermore, the performance comparison of the proposed CPRGP with the commercially available pinwheel antenna and the shallow corrugated ground plane is presented, showing the advantages of CPRGP for high precision GNSS applications.
Fabrication of two- and three-terminal nanogap structure by using electron beam lithography

A high-quality device of aligned gold nanogap arrays is demonstrated by using a well-controlled method with electron beam lithography (EBL). Sub-30 nm nanogap arrays could be precisely fabricated with reproducibility. Importantly, the controllable method could allow us to readily construct varying nano-spacings and exhibit distinct FE properties. These studies clearly demonstrate that sub-30 nm vacuum channel can be readily achieved by coupling varying nanogaps into nanostructures or extended to additional functionalities, e.g. shape modification or multiple dimensional materials. It may pave the way for exploring the physics in tunneling transport devices, and therefore enable a new generation of high performance, high speed and low cost electronic devices.
A phased array antenna system for INMARSAT mobile ground terminal

This paper presented a design of phased array antenna system for INMARSAT mobile ground terminal. Using GPS and electronic compass, antenna can scan the communication satellite automatically from 300 to 900 in elevation and 3600 coverage in azimuth through the DSP module. antenna gain is better than 14dB, diameter is less than 550mm, height is less than 110mm. In this paper, we put emphasis on the introduction of the design of the single-feed dual-band circular polarization micro-strip antenna element, the antenna system components and system performance. Measured results show that the antenna system be able to meet the maritime mobile satellite ground terminal applications.
An adaptive method for image filtering with pulse-coupled neural networks

Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron can capture its adjacent neuron to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a very good mechanism for image filtering when the image is damaged with pet and salt type noise (PASN). An adaptive filtering method, in which the noisy pixels are first located and then filtered based on the output of the PCNN is presented. The threshold function of a neuron in the PCNN is designed for random PASN and extreme PASN contaminated image respectively. The filtered image has no distortion for noisy pixels and only less mistiness for non-noisy pixels, compared with the conventional window-based filtering method. Excellent experimental results show great effectiveness and efficiency of the proposed method, especially for the heavily noise contaminated images.
A novel test process modeling method for automatic test

In order to solve the implementation and maintenance problems of automatic test via filling the gap between test requirements and test programs with models, we developed a novel test execution process modeling method in this paper. The test execution process was abstracted as a test event chain by analyzing several test applications. The model of test execution process is viewed as a composition of lots of test events and the links among these events. Then, a metamodel was designed based on the classical metamodeling architecture to describe the modeling elements: test event set, test data and links, etc. We evaluated this modeling method on railway test application. Results of the example show that this method has good feasibility for test execution process modeling and can easily fill the cognitive gap between the test requirements and test programs.
Analysis of the Unstable Coal Mine Subsidence Areas Water Characteristics and Factors: Take Xieqiao and Zhangji Coal Mines Subsidence Areas for Example

The paper mainly analyzed the physicochemical indexes and got the situation of subsidence water by inspecting during unstable form stage. The physicochemical indexes were inspected including temperature, transparency, BOD5, CODCr, total alkalinity, total hardness, ions, etc. The result showed that all the subsided areas water were subjected to pollution, and the main pollution indexes were BOD5 and CODCr; dissolved oxygen was richer; the total alkalinity, total hardness, chloride, calcium and sulfate ion were growing with ages. For the difference of environmental influence factors, the quality of water in Xieqiao coal mine are worse than Zhangji coal mine. And through analyzing the environmental influence factors, the study provides a theoretical basis for utilization the resource of subsidence area.
Metamorphic HEMT Technology for Microwave, Millimeter-Wave, and Submillimeter-Wave Applications

This paper reviews recent progress in the development of GaAs Metamorphic HEMT (MHEMT) technology for microwave, millimeter-wave, and submillimeter-wave applications. Short gate-length (50-100 nm) Metamorphic High Electron Mobility Transistors have been optimized for high gain and low noise performance. Efforts to further improve performance, manufacturability, and verify reliability will be reported. We also describe the design and performance of low noise MMIC amplifiers based on this technology.
A new mixing matrix identification algorithm for underdetermined blind source separation

In this paper we focus on the mixing matrix identification problem for underdetermined blind source separation. Based on the two-stage approach in sparse component analysis, we proposal a new algorithm that integrate with other blind signal processing methods like independent component analysis and model order selection. Compared with the DUET, the TIFROM and standard clustering methods, this algorithm can work adaptively in noisy environment and the required sparseness of sources can be considerably relaxed. Simulation results are presented.
Microfabricated breath sensor based on carbon nanotubes for respiration monitoring

A microfabricated breath sensor based on multi-walled carbon nanotubes (MWCNTs) has been designed, developed and tested. This sensor has a simple capacitor structure, including a pair of metal electrodes fabricated by micromachining, which are then coated by a layer of carbon nanotubes. This structure takes advantage of the unique electrical property of MWCNTs in the small gap space as a function layer. It is indicated that the sensor has much higher sensitivity to the exhaled gas flow than that of bald electrodes structure with the same size. Meanwhile, the sensor can operate steadily with low supply voltage and energy consumption, avoiding ambient interference of flowing air. It also performs a remarkable response and recovery time, as well as more consistent to the exhaled gas flow. A hybrid mechanism is modeled preliminary as an explanation.
A safety related analog input module based on diagnosis and redundancy

This paper introduces a safety-related analog input module to achieve data acquisition of 4-20mA current signals. It is an integral part of the safety-instrumented systems (SIS) which is used to provide critical control and safety applications for automation users. In order to ensure the performance of analog input circuit in good condition, a combination of hardware and software diagnosis should be carried out periodically. These kinds of internal self-diagnosis allow the device to detect improper operation within itself. If potentially dangerous process occurs, the AI has redundancy to maintain operation even when parts fail. The article presents special hardware, diagnostic software and full fault injection testing of the complete design. The test result shows that the safety-related AI is capable of detecting and locating of mostly potential faults and internal component failures.
Constructing clinical pathway ontology to incorporate patient state, intervention and time

Clinical Pathway has become a beneficial and well-accepted healthcare management tool in medical setting. During the execution of clinical pathway by multidisciplinary staff, a patient receives a set of medical interventions in an order of day by day until discharge. The determination of patient conditions is a key prerequisite to diagnostic decision making and treatment selection. Major patient states as well as underlying temporal information are preliminarily identified through consulting expert physician and referring to clinical pathway. A representational structure is designed and then realized by constructing a clinical pathway ontology. Two hierarchical bases that contain terms and knowledge are built and the ontology shows its ability to represent patient state, medical intervention and temporal information in clinical pathway. Further research needs be done based on our proposed clinical pathway ontology.
An Improved Median Filter Algorithm Based on VC in Image Denoising

In this paper, we propose an improved median filtering algorithm by adding filtration function before replacing the value of the median position with the median and doing multiple processing of median filtering to overcome the shortcoming of the traditional Median Filtering Algorithm. Experimental results are shown that an image after processed by the improved algorithm is hard to find image noise, and has good effect on saving the detail as well. It turns out that the improved algorithm is better than the traditional Median Filtering Algorithm.
Applying Visual Attention Computational Model and Latent Semantic Indexing to image retrieval

Latent Semantic Indexing(LSI), as a popular textual information retrieval approach, has been used heavily for many years. However, the use of the approach in image retrieval has been limited. In this paper, a method of using LSI in combination with the salient image representation based on a saliency-based bottom-up Visual Attention Computational Model(VACM) motivated by visual physiological experimental results was proposed. Firstly, VACM was used to detect the salient region of the image, which is composed of salient or interest points. Meanwhile, a method to select number of the salient points to be extracted for each image is presented. Then color and texture features of the pixels in a small window around each salient point was computed as the Visual Attention Descriptor(VAD). VADs of all images in the training data-set were to be clustered by K-Means algorithm to construct a codebook. The term-document matrix was to be built based on the codebook and VADs of all images in the test data-set. Then LSI with four weighting schemes were applied to the termdocument matrix for image retrieval. According to the preliminary experiment results, some conclusions can be drawn. The best weighting for the LSI technique appears to be applying both local and global weight. With experimental image database used in this paper, the optimal number of dimensions of the semantic space for the LSI model, i.e., the rank of the approximation matrix, was found to be about 21 and the optimal codebook's size should be 900.