nils-herrmann/clean_scirepeval huggingface dataset:
2-D VESPA Algorithm for Multiuser and Multipath DOA Estimation in DS-CDMA System

We propose an effective two dimensional (2-D) direction-of-arrival (DOA) estimation algorithm for the synchronous DS-CDMA systems in multi-user and multi-path channels. The algorithm can be applied in CDMA base station receiver with arbitrary array antenna. In order to effectively suppress multiple access interference (MAI), multiple parallel code-matched filters and a decorrelating multiuser detector are used to detect each path of desired signal for each mobile user. In the output of the detector, a cumulant-based 2-D Virtual ESPRIT Algorithm (VESPA) is employed to estimate each resolvable path direction-azimuth/elevation. In the method, 2-D DOA of each sub-path signal is accurately estimated with higher resolution than the previous methods because array aperture is extended by the use of higher order cumulants. It also has advantage of eliminating the spatially colored Gaussian noise and being available in arbitrary array geometry.
Effective Learning Rate Adjustment of Blind Source Separation Based on an Improved Particle Swarm Optimizer

Blind source separation (BSS) is a technique used to recover a set of source signals without prior information on the transformation matrix or the probability distributions of the source signals. In previous works on BSS, the choice of the learning rate would result in a competition between stability and speed of convergence. In this paper, a particle swarm optimization (PSO)-based learning rate adjustment method is proposed for BSS, and a simple decision-making method is introduced for how the learning rate should be applied in the current time slot. In the experiments, samples of four and ten source signals were mixed and separated and the results were compared with other related approaches. The proposed approach exhibits rapid convergence, and produces more efficient and more stable independent component analysis algorithms, than other related approaches.
Integrated registration of dynamic renal perfusion MR images

This paper presents an integrated image registration algorithm to correct the motion induced by patient breathing for dynamic renal perfusion MR images. Registration of kidneys through the MR image sequence is a challenging task due to rapidly changing image contrast over the course of contrast enhancement. Our algorithm achieves temporal image registration in a multi-step fashion. We first roughly register the images by detecting large-scale motion, and then refine the registration results by integrating region information and local gradient information with auxiliary image segmentation results. We have tested the proposed algorithm on several real patients and obtained excellent registration results.
A Review of Recent Advances in Registration Techniques Applied to Minimally Invasive Therapy

Minimally invasive and less invasive procedure is becoming more and more common in medical therapy. Image guidance is an indispensable component in minimally invasive procedures by providing critical information about the position of the target sites and the optimal manipulation of the devices, while the field of view is limited to naked eyes due to the small incision. Registration is one of the enabling technologies for computer-aided image guidance, which brings high-resolution pre-operative data into the operating room to provide more realistic information about the patient's anatomy. In this paper, we survey the recent advances in registration techniques applied to minimally and/or less invasive therapy, including a wide variety of therapies in surgery, endoscopy, interventional cardiology, interventional radiology, and hybrid procedures. The registration approaches are categorized into several groups, including projection-to-volume, slice-to-volume, video-to-volume, and volume-to-volume registration. The focus is on recent advances in registration techniques that are specifically developed for minimally and/or less invasive procedures in the following medical specialties: neuroradiology and neurosurgery, cardiac applications, and thoracic-abdominal interventions.
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation

The problem of estimating sparse eigenvectors of a symmetric matrix has attracted a lot of attention in many applications, especially those with a high dimensional dataset. While classical eigenvectors can be obtained as the solution of a maximization problem, existing approaches formulate this problem by adding a penalty term into the objective function that encourages a sparse solution. However, the vast majority of the resulting methods achieve sparsity at the expense of sacrificing the orthogonality property. In this paper, we develop a new method to estimate dominant sparse eigenvectors without trading off their orthogonality. The problem is highly nonconvex and hard to handle. We apply the minorization-maximization framework, wherein we iteratively maximize a tight lower bound (surrogate function) of the objective function over the Stiefel manifold. The inner maximization problem turns out to be a rectangular Procrustes problem, which has a closed-form solution. In addition, we propose a method to improve the covariance estimation problem when its underlying eigenvectors are known to be sparse. We use the eigenvalue decomposition of the covariance matrix to formulate an optimization problem wherein we impose sparsity on the corresponding eigenvectors. Numerical experiments show that the proposed eigenvector extraction algorithm outperforms existing algorithms in terms of support recovery and explained variance, whereas the covariance estimation algorithms improve the sample covariance estimator significantly.
Asynchronous P300 BCI: SSVEP-based control state detection

An asynchronous hybrid brain-computer interface (BCI) system combining the P300 and steady-state visually evoked potentials (SSVEP) paradigms is introduced. A P300 base system is used for information transfer, and is augmented to include SSVEP for control state detection. The proposed system has been validated through off-line and online experiments. It is shown to achieve fast and accurate control state detection without significantly compromising the performance. For the two subjects who participated in the online experiments, the system achieved an average data transfer rate of 20.13 bits/min, with control state classification accuracy of more than 97%.
Direct fuzzy backstepping control for turbine main steam valve

The problem of transient stability for a single machine infinite bus system (SMIB) with uncertain parameters in the turbine steam valve control is addressed by means of combining the direct fuzzy logic system and the backstepping method in this paper. Since the process of the controller design is without any linearization, the nonlinear property of the dynamic is preserved. The problem of parameter uncertainty is effectively resolved by fuzzy logic system. Finally, the results of simulation show the effectiveness of the proposed method.
Test method for the vibration response of a vehicle horn bracket

In order to solve the problem that trumpets of some vehicles during working lead to vibrations of steering wheel in cab, according to the power flow method, the model of vibration system is established. The vibration influence of holder's length to response points is analyzed by using the equivalent theorem of Norton. The acceleration responses and vibration frequency of junction for beam and carling are measured with installing holders of different lengths on the test-bed. The experimental data can be disposed using MATLAB. Results show that the vibration responses of junction for beam and carling is minimum when the length of trumpet holder is 65mm.
Efficient Population Utilization Strategy for Particle Swarm Optimizer

The particle swarm optimizer (PSO) is a population-based optimization technique that can be applied to a wide range of problems. This paper presents a variation on the traditional PSO algorithm, called the efficient population utilization strategy for PSO (EPUS-PSO), adopting a population manager to significantly improve the efficiency of PSO. This is achieved by using variable particles in swarms to enhance the searching ability and drive particles more efficiently. Moreover, sharing principals are constructed to stop particles from falling into the local minimum and make the global optimal solution easier found by particles. Experiments were conducted on unimodal and multimodal test functions such as Quadric, Griewanks, Rastrigin, Ackley, and Weierstrass, with and without coordinate rotation. The results show good performance of the EPUS-PSO in solving most benchmark problems as compared to other recent variants of the PSO.
Static hand gesture segmentation: Comparison and selection of existing methods

This paper focus on the introduction and summary of static hand gesture segmentation methods. Starting with the research of image segmentation method and the development of hand gesture recognition, we illustrated the most popular methods in static hand gesture segmentation and their advantages and applicable scope in each image processing steps, by comparing different processing methods used in different stages of static hand gesture segmentation, for example calibrating image color, choosing color space, choosing a certain skin color model and using different post-processing scheme. Finally, the static gesture segmentation methods are summarized and prospected, The conclusion provided researchers with certain theoretical basis for choosing static hand gestures segmentation method, in turn lay a good foundation for subsequent gesture recognition works.
An effective approach for forward vehicle detection with tracking

This study presents an effective vehicle detection and tracking approach to deal with forward collision warning (FCW) system. Based on robust lane-marking tracking and vanishing point, a regions of interest (ROI) is created for detecting whether vehicle in the front. The proposed method is implemented in TI DM648 DSP embedded system, and get very good result in the highway. In particular, when the rapid change of the input image color temperature, and road marking can still be ongoing tracking, therefore shows that the presented algorithm is very robust and stable.
The Study of Relations Between Commercial Development and Economic Growth

Commerce is an important part of national economy and it plays an influential role to national economic growth; our country (China) also pays more and more attention to commercial development, for example the commercial affairs department decided to start establishing works of the commercial network plans of cities in 2008. This article wants to explain the importance and present situation of commerce through the research to the law of commercial development and economic growth. The empirical study of this article mainly centers on the law of commercial scale and economic growth. By selecting national data and 4 sample provinces and cities' local commercial data-commerce and Gross Domestic Product rate, total retail sales of consumer goods, per capita Gross Domestic Product and other relative data, using the method of correlation analysis to verify the law of commercial scale and economic growth, and comparing our country's industrial structures with those in other countries, it draws an conclusion as follows: Our country's commercial scale and area commercial scale have both already developed to a relatively stable level, but this level is low, under such circumstance, if we want to increase commercial economic benefit further, we must adjust commercial internal structures and expand market demand or make use of other methods to promote commercial development.
Strategy Research of International Trade Financing of Small and Medium Foreign Trade Enterprises in Heilongjiang Province

With the expansion of foreign trade scale and the increasing of demand for capital of enterprise in Heilongjiang Province, we advance new demand of trade financing. However, compared to coastal developed cities, the trade financing in Heilongjiang province still has a long way to go. Because of enterprises' having not enough knowledge of trade financing, bank's lacking of creativity and imperfection of credit system, the foreign trade enterprises in Heilongjiang province have the problems of effective demand insufficiency and the obstruction of supply in trade financing. Based on the background of increasingly internationalization of financing and foreign trade enterprises' imperious demands for funds, this paper started from the current situation of trade financing of foreign trade enterprises of Heilongjiang province, explored the problems and obstacles existed in the trade financing cooperation between foreign trade enterprises and banks, proposed the conception about trade financing mode selection strategy and new enterprises' credit system for the first time. We pointed out that the bank's trade finance products and their pricing should be adapted to the actual needs of foreign trade enterprises, and stressed that the commercial banks should strengthen the risk control of trade financing and so on, in order to comprehensively promote foreign trade and economic sustainable development of Heilongjiang Province.
Study on optimization for vehicle power train parameters

The optimized theory is used in the electronic control of the power train in order to improve the performance of the car. Except that, the author explains the optimized theory and the method of using it in writing the computer program. And moreover, the author discusses the problems occurring in the object and gives the methods to solve them. The result of the object is expressed by figures and gives out the controlling parameters that are going to be used by executive mechanical device.
Active defects detection and localization using acoustic emission method

Acoustic emission (AE) is a dynamic nondestructive measuring and testing method, which is widely used in safety and integrity evaluation of structure and material. This paper investigates the relationship of micro cracking process of the pipeline material and acoustic emission phenomenon in detail, and establishes the connection between micro cracking of the material and AE counts. Experiments were carried out on a stainless steel pipeline with 100 mm outer diameter to show the relationship between micro cracking process of structure and material and acoustic emission signal. Nielsen-Hsu pencil break method was used to simulate the micro cracking process.
An adaptive interleaving scheme for MIMO-OFDM systems

In this paper, an adaptive interleaving scheme for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is proposed. The scheme could better exploit the instantaneous channel variation by rearranging the transmitted symbols according to the quasiinstantaneous channel SNR of the OFDM frame. The purpose is to break up a long burst channel error so that overall bit error probability is reduced. Extensive simulations show that significant SNR can be obtained with the proposed scheme and the MIMO-OFDM case has a performance improvement over the single antenna case. Compared with block interleaving, for 2Tx-2Rx case at a BER of 10/sup -/2, adaptive interleaving offers a 5dB improvement.
A Condition to the Existence of Periodic-3 Orbit and Implication of Chaos in a Kind of Roseneweig - Macorthur Discrete System

A condition to the existence of periodic-3 orbit and implication of chaos in a kind of Roseneweig-Macorthur discrete system is presented in the paper, and it's proven in this condition, the periodic-3 orbit of Roseneweig-Macorthur discrete system is not unique, and such researches will have important ecological significances on the prediction of ecological environment.
Dynamic Strain Model With Eddy Current Effects for Giant Magnetostrictive Transducer

Based on the Jiles-Atherton model and transducer's structural dynamics principle, the magnetoelastic dynamic strain model of giant magnetostrictive transducer is founded. This model takes into account the eddy current losses and the variety of stress. Simulation results are in a good agreement with the experimental ones. This indicates that the dynamic strain model can characterize the magnetization intensity and strain behavior at different frequency. The proposed model is suitable to describe the relation between the applied field and the output vibration at a wide range of exciting frequency
The Study of ZnO Photoconductive UV Detector

A ZnO photoconductive UV detector was fabricated on ZnO film grown by MOCVD based on Al/Au interdigital electrode. Nonalloyed Al/Au metallization scheme formed good ohmic contact on n-type ZnO. The dark and photoilluminated currents increased linearly with bias voltage. The cutoff wavelength of the detector was 368nm, and it was also in response to the blue and green light. Electrical and photoresponsive changes of the ZnO UV detector due to RF sputter deposition of antireflection coating (AR) were also studied
Segmentation of coronary arteriograms by iterative ternary classification

A segmentation algorithm for extracting arterial structures in coronary angiograms is presented. The algorithm mimics the process of interactive interpretation in human vision by iteratively implementing a ternary classification and learning process. Two gray-scale thresholds are computed to define three pixel classes: artery, background, and undecided. Then, two new thresholds for undecided pixels are computed using statistics conditioned by the current classification. The threshold adaptation is governed by a learning algorithm based on the line and consistency measurements around each pixel. The process converges and results in a binary image. The performance of this algorithm on human coronary arteriograms was compared qualitatively to that of a relaxation algorithm and of a scattering-based algorithm. Quantitative comparison was also made possible with computer generated images, which were obtained with the help of a model of the imaging chain and a process of interactive visualization of the modeled data. The iterative ternary classifier showed the best performance over a broad range of image quality. The study also demonstrated the use of visualization and user interaction in model building and algorithm development.<<ETX>>
Research on Influencing Factors of Near Miss Initiative Report in Coal Mine

In order to analyze the influencing factors of near-miss initiative report in coal mine, a random questionnaire survey was designed based on nine factors that affect the miners un-initiative report near-miss that were identified by interviews and literature review. Then using AMOS 7.0 the influencing factors of near-miss initiative report in coal mine were analyzed by confirmatory factor analysis (CFA). The results show that near-miss initiative report has three influencing dimensions: near-miss cognition, near-miss management and reported have harmful effects on oneself. Coal mine managers should improve the miner's positivity of near-miss initiative report from paying great attention to near-miss management, strengthen miners' education and training, advocating "initiative report, non-punitive" and establishing scientific and concise reporting process.
Marine Coastal Ecosystem Health Assessment: A Case Study in Jiaozhou Bay, China

In this paper, a marine coastal ecosystem health assessment indicators system is established, and it covers hydrographic, geographical, physical, chemical, biological, system-level and ecosystem-severe-functional aspects of coastal ecosystem health. The indicators system was used in a case study in Jiaozhou Bay. The assessment results showed that Jiaozhou bay was healthy in the time series from 1980s to 2000s, but the health evaluation index showed a decline trend. The main influencing factors of Jiaozhou Bay's health are macrobenthic community, phytoplankton community, coastal land indicators , water quality, and main human activities that have threatened the bay's health are land reclamation and sewage discharge.
Resource allocation for multimedia CDMA wireless system with soft target SIR thresholds

Power control and data rate allocation are two fundamental techniques for improving the spectral efficiency of wireless multimedia communications. In this paper, we study the relation of data rates and target SIR thresholds by minimizing the total transmitted power for given system throughput using DS-CDMA technology. The law that governs the dynamic data rate allocation is analyzed by adjusting target thresholds. Computer simulation results show that user has to sacrifice its target SIR threshold to obtain more resource from the system.
Vehicle warning system for land departure and collision avoidance: Using fuzzy decision making

This paper focuses on vehicle warning system based on fuzzy decision making for lane departure and forward collision avoidance for dealing with driver assistant system. The proposed system is composed of vision-based preprocessing and a fuzzy decision making. The objective of vision-based preprocessing part is lane tracking and forward vehicle detection, and provides the necessary information for fuzzy decision making to trigger the warning device. The fuzzy decision making unit can adjust the fuzzy decision rule base follow the driving behavior to increase the warning strength for lane departure and/ or forward collision.
A self-organized neural network for blind separation process with unobservable sources

A self-organized rule is proposed to process the separation of unknown number of sources of blind signal. The rule is applied to the feed-forward neural network (FFNN) which is based on a mean weighting gradient (MWG) function. The algorithms adjust the architecture of neural network. For both, the performances are the mixture of node number and MWG threshold /spl xi/.The separating number of sources estimated accurately by experiment of computer simulations.
Intelligent path planning for unmanned vehicle automatic guidance

This paper focuses on the development of intelligent path planning algorithm for unmanned vehicles automatic guidance such as the shortest path, the stable path in a terrain with a single destination and multiple waypoints. The experiment results show that the proposed algorithm can not only reduce the uncertainty of the evolutionary computation caused by the probability model, but also avoid the problem of particles falling into the local optimal area effectively. The proposed algorithm for multiple waypoints path planning is also more efficient than other route planning methods.
The Neuron Emulator: an undergraduate Biomedical Engineering design project

The Neuron Emulator was a team project by undergraduate Biomedical Engineering students in a neuroengineering course at the University of Rhode Island. It is an analog electronic apparatus that simulates the passive and active electrical properties of a neuron. Areas of application include testing of neurophysiological measurement and control instruments, and education in electrophysiology. Proposed uses of the device include working in conjunction to form a reciprocally inhibitory oscillator and to calibrate a voltage clamp amplifier.
Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis

A class of algorithms has been developed which detects QRS complexes in the electrocardiogram (ECG). The algorithms employ nonlinear transforms derived from multiplication of backward differences (MOBD). The algorithms are evaluated with the American Heart Association ECG database, and comparisons are made with the algorithms reported by Okada (1979) and by Hamilton and Tompkins (1986). The MOBD algorithms provide a good performance tradeoff between accuracy and response time, making this type of algorithm desirable for real-time microprocessor-based implementation.<<ETX>>