nils-herrmann/clean_scirepeval huggingface dataset:
Estimating the Number of Clusters via System Evolution for Cluster Analysis of Gene Expression Data

The estimation of the number of clusters (NC) is one of crucial problems in the cluster analysis of gene expression data. Most approaches available give their answers without the intuitive information about separable degrees between clusters. However, this information is useful for understanding cluster structures. To provide this information, we propose system evolution (SE) method to estimate NC based on partitioning around medoids (PAM) clustering algorithm. SE analyzes cluster structures of a dataset from the viewpoint of a pseudothermodynamics system. The system will go to its stable equilibrium state, at which the optimal NC is found, via its partitioning process and merging process. The experimental results on simulated and real gene expression data demonstrate that the SE works well on the data with well-separated clusters and the one with slightly overlapping clusters.
Extended Monte Carlo algorithm to collaborate distributed sensors for mobile robot localization

This paper presents a probabilistic algorithm to collaborate distributed sensors for mobile robot localization. During robot localization given a known environment model, Monte Carlo method is extended to integrate the detection information coming from environmental sensors to localize robot as long as the sensors do detect the robot. Meanwhile, we present an implementation that uses color environmental cameras for robot detection. All the parameters of each environmental camera are unknown in advance and can be calibrated by robot. Once cameras' calibrated, their detection models can be trained using sensor data according to their parameters. As a result, the robot's belief can reduce its uncertainty in response to the detection effectively. A further experiment, obtained with the real robot in an indoor office environment, illustrates that drastic improvement in localization speed and accuracy when compared to conventional robot localization.
High-rate low-delay complex orthogonal space-time block codes for eight transmit antennas

Space-time block codes from orthogonal designs have two advantages, namely, fast maximum-likelihood (ML) decoding and full diversity. Complex orthogonal designs of maximum possible rate of full, 3/4, and 3/4 have been presented for two, three, and four transmit antennas respectively. For five, six, seven and eight transmit antennas, four generalized complex orthogonal space-time block codes of rates 2/3, 2/3, 5/8, and 5/8 were proposed recently. In this correspondence, the complex orthogonal designs with maximal rates and minimal decoding delays for eight transmit antennas are presented. Compared with the same rate code schemes, the proposed scheme has lower bit error rate (BER) due to the achievable minimum decoding delay on the condition of the same system throughput. Simulation results showed that the present space-time block code could achieve significant diversity gain.
A new neural network model for image segmentation

In this paper, the problem of image segmentation using artificial neural network ( ANN) is discussed. A new ANN model for image segmentation is proposed which consists of two sub-networks in cascade, i.e. the master sub-network (MSN) and the auxiliary sub-network (ASN). The dynamics of this model is studied in details and the corresponding algorithm is described in the paper. Finally, the simulations are carried out for the medical image using the moment-preserving thresholding and the proposed ANN model, and the corresponding results indicate that the image segmented by the proposed ANN model is much better than that obtained by the moment-preserving thresholding.<<ETX>>
A suboptimal user selection algorithm for multiuser MIMO systems based on block diagonalization

In this paper, we propose a suboptimal user selection algorithm based on block diagonalization (BD) with low complexity. An upper-bound of sum-rate capacity is deduced. And considering it as the selection criterion we get our proposed algorithm. Furthermore in simplification of the proposed algorithm it is regarded as the adaptive criterion instead of capacity formula. After that we analyze the computational complexity in detail, and then compare the proposed algorithm with optimal selection algorithm and maximum norm selection method. Simulation results show that the proposed algorithm and its simplification can achieve the same sum-rate capacity as the optimal exhaustive search method in lower SNR, and in higher SNR they are both very close to the performance of optimal method.
A homogeneous group bargaining algorithm in a smart grid

In this paper, we consider a smart grid incorporating numerous devices. In order to manage the energy distribution, we propose an algorithm that employs the group bargaining concept of game theory to efficiently allocate electricity resources among these devices. First, we divide the devices into non-overlapping groups, and allow devices to bargain both within and across groups. Second, we regard each group as homogeneous, so that the bargaining authority can be delegated to a representative device. Thus, the bargaining problem involves only the representatives, each of which bargains with other representatives on behalf of the group it belongs to. Third, we compare various bargaining results via a utility function that indicates the satisfaction level of a representative in terms of the bargaining result. Finally, the algorithm determines the optimal resource distribution pattern by maximizing the aggregated utilities of all representatives. Simulation results show that the proposed algorithm can reduce the complexity of energy distribution by distinguishing between inter- and intra-group bargaining processes, and can efficiently allocate resources to various devices according to their actual requirements.
Embedded control and management system for novel automatic platelet aggregometer

Platelet aggregation assay is important in mediating platelet thrombus formation for both medical treatment and prevention. Therefore quick and accurate automatic analyzers for clinic are of urgent requirement all the time. In this paper, design and implementation of embedded control and management system for novel automatic platelet aggregometer is presented, which comes to rapid and quantitative measure of platelet aggregation and other platelet-function for assay. The system is based on ARM-DSP dual-core embedded processor framework for device control and management. Automatic control of testing process is introduced and a signal modulation and detection circuit is proposed for measuring blood cell's weak pulse signals, as well as principle of the control and management system software is given in detail which supporting a reliable system control and operation. The new system achieves effective and accurate platelet aggregation assay and overcomes the drawbacks of conventional manual operation of platelet-function assay. Experimental results validate the effectiveness and precision of the system.
Computer vision for RGB-D sensors: Kinect and its applications [special issue intro.]

Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use as an off-the-shelf technology. This special issue is specifically dedicated to new algorithms and/or new applications based on the Kinect (or similar RGB-D) sensors. In total, we received over ninety submissions from more than twenty countries all around the world. The submissions cover a wide range of areas including object and scene classification, 3-D pose estimation, visual tracking, data fusion, human action/activity recognition, 3-D reconstruction, mobile robotics, and so on. After two rounds of review by at least two (mostly three) expert reviewers for each paper, the Guest Editors have selected twelve high-quality papers to be included in this highly popular special issue. The papers that comprise this issue are briefly summarized.
Effects of evolutionary pressure on histone modifications

With the advent of next-generation sequencing technologies, a considerable effort has been put into sequencing the epigenomes of different species. The efforts such as “Encode” and “Roadmap” epigenomics projects provide an opportunity to compare epigenomes across species (especially between human and mouse). This study is an effort to understand how different histone modifications vary/co-appear between orthologous regions of the two species. In this work, we have used various measures of orthologous similarity between each pair of orthologous genes and explore how histone modifications are conserved with respect to changes in these similarity measures. These measures of similarity “codon usage frequency similarity” (CUFS), Ka/Ks ratio and gene expression similarity. Our simulation indicates that evolutionary selection pressure of an orthologous pair (Ka/Ks ratio) is more strongly correlated with its histone modification than any other similarity measure. We also found that genes with low Ka/Ks have more similar histone profiles across species than the ones with high Ka/Ks, suggesting more differential regulation for genes with higher selection pressure.
Memory-constrained 3D wavelet transform for video coding without boundary effects

Three-dimensional (3D) wavelet-based scalable video coding provides a viable alternative to standard MC-DCT coding. However, many current 3D wavelet coders experience severe boundary effects across group of pictures (GOP) boundaries. This paper proposes a memory-efficient transform technique via lifting that effectively computes wavelet transforms of a video sequence continuously on the fly, thus eliminating the boundary effects due to limited length of individual GOPs. Coding results show that the proposed scheme completely eliminates the boundary effects and gives superb video playback quality.
Investigation of dual-polarised printed slot antenna for folded reflectarray unit cells at Ka band

A novel dual-polarised slot type printed antenna with superior high beam scanning performance in a unit cell boundary condition for the folded reflectarray is presented and characterised. This antenna is intended for operation at Ka-band and designed using multi-layer printed circuit board (PCB) technology. The proposed design incorporates shorting vias around the slot as well as a dielectric grid on the top of the antenna in order to achieve improved performance at the higher scanning angles for both polarisations. The effectiveness of beam scanning of the proposed unit cell design, especially at higher scanning angle at 60°, is evaluated with incident waves at various angles in the periodical boundary. The simulation results have shown the proposed unit cell antenna has the capability of beam scanning with good performance up to 60° for both E-plane and H-plane at the designated operational band, indicating that a folded reflectarray with excellent beam scanning performance, designed on the basis of this novel unit cell antenna element, can be realized.
Human encoded miRNAs that regulate the inflenenza virus genome

MiRNAs can downregulate gene expression by mRNA cleavage or translational repression. Discovering human encoded miRNAs that regulate the influenza virus genome is important for molecular targets for drug development, and it also plays positive role in influenza control and prevention.  We propose a new method based on scoring to discover human encoded miRNAs that regulate the influenza virus genome. The scoring based on the same complementary sites, the secondary structure of the complementary sites and the binding sites of all sequences respectively. Among them, taking the secondary structure as a vital factor is a new attempt.  Has-miR-489, has-miR-325, has-miR-876-3p and has-miR-2117 are targeted HA, PB2, MP and NS of influenza A, respectively.
A framework for reducing ink-bleed in old documents

We describe a novel application framework to reduce the effects of ink-bleed in old documents. This task is treated as a classification problem where training-data is used to compute per-pixel likelihoods for use in a dual-layer Markov Random Field (MRF) that simultaneously labels image pixels of the front and back of a document as either foreground, background, or ink-bleed, while maintaining the integrity of foreground strokes. Our approach obtains better results than previous work without the need for assumptions about ink-bleed intensities or extensive parameter tuning. Our overall framework is detailed, including front and back image alignment, training-data collection, and the MRF formulation with associated likelihoods and intra- and interlayer cost computations.
Application of fuzzy fault tree analysis in the fault diagnosis for automobile engine system

Fuzzy Fault tree analysis is one of important means for analysis of reliability and safety and fault diagnosis of the system. It features a strong logical and visual image. It is a reliable analysis method for both qualitative and quantitative analysis of the typical fault of a system and thus provides a theoretical basis for fault analysis processing and system design. This paper presents a fault tree analysis used in the analysis of fault mode for automobile engine system, builds the fault tree of common fault mode. Through the qualitative and quantitative analysis of fault tree, the causal relationship between the faults can be fully reflected, and the combination of the common fault mode for the system can be obtained. It can provide powerful technical support and decision basis for maintenance staff to improve the integrity of fault analysis, the accuracy of fault location and the timeliness of fault exclusion.
An Improved Calculus for Secure Dynamic Services Composition

With the increased interest in the Web services composition, more and more enterprises and businesses depend on this paradigm. Open, distributed and dynamic properties of the schema, there is a pressing need for secure services in daily transactions. Orchestration and choreography language provide basic services standards and interaction, collaboration, and negotiation standards among services, but they are not give any secure manners or secure operation styles and specifications. Despite the interest of such security mechanisms, a formal module of them is still lacking. For giving general guide to implement secure orchestration and choreography language, we give a formal approach to carry out those goals. To this target, we emphasize on those by designing an extension of the Spi calculus with Secure Global Calculus. The Spi calculus precisely identifies orchestration secure properties of each principal from a local viewpoint. The secure global calculus describes an interaction secure choreography scenario from a vantage point of view. We called our method SpiG4WSC calculus. We believe that the combination of strong practical needs for dynamic secure Web services composition and the theoretical foundations will lead to a bridge between practice and theories. The contribution of this paper are (1) giving the syntax and semantic of SpiG4WSC calculus; (2)applying the calculus to give a model to presenting the secure orchestration, emphasizing on the formal basis for secure services; (3)describing the secure choreography, giving the formal frame for interaction processes.
Detection of JL-1 satellite's jitter using multimodal pushbroom cameras

Pushbroom cameras are widely used for earth observation application. This sensor capture 1D image over time and sweep out a region of space and build a 2D image using the straight motion of the satellite. The attitude variation is assumed to be constant during the acquisition process. However, this assumption has been weakened due to a tendency of miniature and lightweight of satellites. In this paper, we analyze the warps of remote sensing image and introduce an improved image registration method. Then the correct images are retrieved and the satellite variation is estimated. The performances of our algorithm are shown on JL-1 satellite datasets. The results shows the possibility of the improvement in geometric processing accuracy for JL-1 imagery products and provide a good reference for satellite platform jitter source analysis.
Dynamic Response of the Single-Layer Kiewitt-8 Reticulated Dome Subjected to the Airplane Crash

The dynamic response of large space structures under accidental impact has been the subject of intense research since the occurrence of the 9/11 incident. In the present paper, events of aircraft impact to the single-layer kiewitt-8 reticulated dome were simulated by using the 3D ANSYS/LS-DYNA. Impact loadings were carried out respectively by the Riera force history method and by modeling a real plane similar to Bombardier Challenger 850. Simulation results indicated that the impact by modeling a real plane directly is more reasonable than the method by Riera force history. Furthermore, a series of different impact events were added to investigate the effect of impacting position and the flight attitude of the airplane.
Gender recognition technology of whole body image

There are numerous potential applications for the Internet of Things (IOT) at the present stage. In the topic of image processing, the gender recognition usually adopts face information to identify the gender of a person. Therefore, if the input image loses face information, it will result in the wrong identification result. In this paper, we proposed a multiple-attributes (MA) recognition method. Not only facial parts, but also use gender of wearing characteristic for gender identification. The paper also develop an automatic segmentation algorithm to locate the wearing characteristic. The objects features will be effectively extracted, and classified into some object attributes by classifier. Finally, the attributes are given to the corresponding weights to obtain male scores and female scores. According the gender scores to determine the gender of people. This paper has multiple-attributes (MA) to solve the defects of the face attribute recognition.
Fabrication of SWNT device by self-assembly technology

The single-walled carbon nanotubes (SWNTs) were randomly deposited on pre-treated silicon substrate by a self-assembling method. By this method, the SWNTs film with uniform distribution and random structure were formed and the density of SWNTs could be controlled by the concentration of the SWNTs suspension and the assembling time. Also, Cr interdigitated electrodes were patterned on the assembled SWNTs by traditional lift-off process. The results show that SWNTs films made by self-assembly can adhere firmly to the substrate.
Automated protein NMR resonance assignments

NMR resonance peak assignment is one of the key steps in solving an NMR protein structure. The assignment process links resonance peaks to individual residues of the target protein sequence, providing the prerequisite for establishing intra- and inter-residue spatial relationships between atoms. The assignment process is tedious and time-consuming, which could take many weeks. Though there exist a number of computer programs to assist the assignment process, many NMR labs are still doing the assignments manually to ensure quality. This paper presents (1) a new scoring system for mapping spin systems to residues, (2) an automated adjacency information extraction procedure from NMR spectra, and (3) a very fast assignment algorithm based on our previous proposed greedy filtering method and a maximum matching algorithm to automate the assignment process. The computational tests on 70 instances of (pseudo) experimental NMR data of 14 proteins demonstrate that the new score scheme has much better discerning power with the aid of adjacency information between spin systems simulated across various NMR spectra. Typically, with automated extraction of adjacency information, our method achieves nearly complete assignments for most of the proteins. The experiment shows very promising perspective that the fast automated assignment algorithm together with the new score scheme and automated adjacency extraction may be ready for practical use.
A novel artificial lateral line sensing system of robotic fish based on BP neural network

Lateral line is the typical sensory organ for aquatic vertebrates. And many scientists have done a lot of studies on combining artificial lateral line with robotic fish. However, the research in this filed is relatively immature and many involved approaches are backward. In this paper, we set up a system of bionic robotic fish virtual lateral line based on several pressure sensors and put up with a novel design for it to classify different types of flow field using BP neural network. To simplify the experiment, the system is set up in Computational Fluid Dynamics (CFD) softwares to obtain experiment data which is used for following research. After extracting some features from the raw data, we built up a flow field classifier. And it proves that the accuracy of the flow recognition is in a good performance. This paper proposes a new idea on the design of lateral line system and it's useful for the future works on it.
A surface plasmon resonance(SPR)sensor chip integrating prism array based on polymer microfabrication

The prototype of a prism-coupled Kretschmann surface plasmon resonance (SPR) chip was fabricated by suing bulk silicon micromachining and polymer replication, and the chip is constructed with the polymer-prism array, metal layer and micro-channel. The performance of PDMS SPR chip was investigated at different incident wavelengths, when the chip is applied to test samples, including air, water and ethanol. As the light source was at 650nm the resonance angles in air, water and ethanol were about 48.14°, 76.6° and 77.1°, respectively. Resonance angles decrease almost in linearity with refractive index of PDMS increasing. The obtained SPR angles are approximately consistent with the theoretical ones. This polymer micro-prism array-coupled SPR chip continues to evolve as an elegant and powerful analytical method with unique capabilities in biosensors.
A novel method for RCN s-t reliability analysis based on multipoint Pade approximation

Computing the reliability of a radio-communication network (RCN) is computationally difficult, and an exact solution is unattainable for many problems. Faced with this computational difficulty, we propose a novel approximant method to perform the s-t reliability analysis of RCN based on multipoint Pade approximant theory. We model the RCN by a probabilistic graph with reliable edges and unreliable nodes. An appropriate transformation is obtained using the recursive decomposition algorithm. And then the algorithm for s-t reliability analysis of RCN is presented using Werner algorithm. The efficiency of the method is illustrated by a numerical example.
Domain Transfer SVM for video concept detection

Cross-domain learning methods have shown promising results by leveraging labeled patterns from auxiliary domains to learn a robust classifier for target domain, which has a limited number of labeled samples. To cope with the tremendous change of feature distribution between different domains in video concept detection, we propose a new cross-domain kernel learning method. Our method, referred to as Domain Transfer SVM (DTSVM), simultaneously learns a kernel function and a robust SVM classifier by minimizing both the structural risk functional of SVM and the distribution mismatch of labeled and unlabeled samples between the auxiliary and target domains. Comprehensive experiments on the challenging TRECVID corpus demonstrate that DTSVM outperforms existing cross-domain learning and multiple kernel learning methods.