nils-herrmann/clean_scirepeval huggingface dataset:
Classification of breast tumors in ultrasound using biclustering mining and neural network

Ultrasound imaging is now becoming a frequently used tool in clinical diagnosis. In this article, a novel diagnosis scheme is proposed to aid the identification of breast lesions. In this approach, feature scoring scheme is first applied to product feature data. Biclustering mining is then helpful to discover the effective diagnostic patterns, and those found patterns are utilized to transform the original features into advanced hidden features. Finally those advanced features are treated as the input data for back-propagation (BP) neural network algorithm to train an efficient classifier for recognizing benign and malignant breast tumors. The proposed approach has been validated using a database of 238 breast tumor instances (including 115 benign cases and 123 malignant cases) with its performance compared with other conventional approaches. Experimental results indicate our proposed method yielded good performance in tumor classification, with the accuracy, sensitivity, specificity of 96.1%, 96.7%, 95.7%, respectively.
Web-based training for radiologists of breast ultrasound

Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.
Barker coded excitation using LFM carrier for improving axial resolution in ultrasound imaging

Improving the axial resolution of ultrasound imaging system can have broad clinical impact. In this paper, a novel Barker coded excitation uses LFM carrier (LFM-Barker coded excitation) instead of sinusoid carrier (Sinusoid-Barker coded excitation). Pulse compression scheme of LFM-Barker coded excitation is developed that consists of LFM mismatched filter, Barker matched filter and sidelobe suppression filter. In simulation, the axial resolution is almost doubled with a slight decrease of SNR gain of less than 1 dB using LFM-Barker coded excitation compared to Sinusoid-Barker coded excitation. The -6 dB mainlobe width is 0.6 μs and 1.5 μs, respectively. Maximum range sidelobe level is observed at -35 dB. Additionally LFM-Barker coded excitation is robust for frequency dependant attenuation of tissue. Simulation of B-mode images is carried out to demonstrate the advantage of LFM-Barker coded excitation system of good axial resolution.
Power system decoupled simulation in MATLAB/SIMULINK

Modeling and simulation techniques are indispensable in every aspect of power system design. To provide a higher level of accuracy, models of power systems need to include complexity. Power system models need to be simulated in a longer period of time and more frequently especially when they are being analyzed using complex computer algorithms. This challenges the computation capability of one single common computer. Decoupled simulation combined with grid computing is a possible solution to release the computation burden for analyzing complex power systems using multiple computers. In addition, decoupled simulation is also a must for hardware in the loop simulation or long distance distributed simulation involving different physical locations. This paper proposes to perform decoupled simulation in MATLAB/SIMULINK combined with grid computing middleware. Grid computing helps make decoupled simulation scalable, flexible and secure with low cost. The results of decoupled simulation using grid computing middleware are shown in this paper. This paper also outlines the work that has previously been done by researchers at Mississippi State University on decoupled simulation in VTB.
Preparation and characterization of n-type Bi/sub 2/Te/sub 3/ thermoelectric nanowire array

The figure of merit can be improved greatly through reducing the size of thermoelectric materials into low dimension, and the studies on low dimensional thermoelectric materials have brought widely attention in the world. In our lab, n-type Bi/sub 2/Te/sub 3/ thermoelectric materials with nanowire array structure have been prepared by liquid electrodeposition in the solutions containing Bi/sup +3/ and HTeO/sub 2//sup +/ with alumina porous film as template. The electrochemical measurements show that the co-deposition of elements bismuth and tellurium can take place and the electrodeposition potential of Bi/sup +3/ is more positive than that of HTeO/sub 2//sup +/. ESEM and TEM analyses show that the diameter and length of Bi/sub 2/Te/sub 3/ nanowires are about 50nm and 50 /spl mu/m separately. The Seebeck coefficient /spl alpha/ of the Bi/sub 2/Fe/sub 3/ nanowire array is about - 188 /spl mu/ V/K at 307K.
An approach based on biclustering and neural network for classification of lesions in breast ultrasound

Breast cancer is now considered as one of the leading causes of death among women all over the world. It is broadly accepted that ultrasound imaging is an important and frequently used tool for breast cancer diagnosis. In this paper, we propose a novel computer-aided diagnosis scheme for breast lesions classification. In this scheme, the sonographic breast images are first used to produce Breast Imaging Reporting and Data System (BI-RADS) lexicon based feature scoring data. Biclustering mining is then used as a powerful tool to discover the effective local diagnosis patterns in training data, and those found biclusters are utilized to generate hidden features as new input data. Finally the back-propagation (BP) neural network algorithm is applied to produce an efficient classifier for recognizing benign and malignant breast tumors. Our experimental results show that the proposed method yielded good prediction performance, indicating its interesting potential in clinical applications.
Distributed Simulation Applied to Shipboard Power Systems

The development of shipboard power systems for the new generation of all-electric ships is challenging in two aspects. First, all new equipment needs to be tested before being installed onboard; otherwise, the design and testing process would become increasingly costly and risky. Second, the complexity of a shipboard power system demands the use of significant computational resources for detailed computer-aided analysis. Distributed simulation techniques can help reduce the computational load that simulation of shipboard power systems requires by partitioning the system into smaller, more manageable subsystems. Distributed simulation can also facilitate remote testing of equipment and collaboration among research teams located in geographically distant institutions. The initial step in distributed simulation requires achieving software-to-software communication over a network. This paper outlines the progress done at the Mississippi State University in the distributed simulation application to shipboard power systems. Both natural and signal coupling models for distributed simulation are developed and validated. For natural coupling, a general coupling method, which considers transmission lines as suitable decoupling points, is proposed. Distributed simulation tests on several systems, including a shipboard power system, are documented and simulation results demonstrate the feasibility of applying distributed simulation techniques in advanced shipboard modeling and simulation.
Multi-Evaluation of the Healing at Bone-Tendon Junction with the Treatment of Mechanical Stimulation

Many trauma and reconstructive surgeries involve the re-establishment of bone-tendon junction (BTJ) tissues. A direct BTJ repair requires a long period of immobilization which may be associated with a postoperative weak knee. To enhance the tissue healing, researchers use postoperative mechanical stimulation, such as low intensity pulsed ultrasound (LIPUS), to accelerate the BTJ repair and the restoration of fibrocartilage zone. LIPUS has been proven to accelerate fracture healing and as demonstrated in this study, has beneficial effects on acceleration of BTJ repair. In our experiment, standard partial patellectomy was conducted on one knee of twenty four rabbits which were randomly divided into an ultrasound group and control group. The bony changes of BTJ complexes around the BTJ healing interface were measured by anteroposterior x-ray radiographs; then the volumetric bone-mineral density (BMD) of the new bone was assessed using a peripheral computed tomography scanner. After radiographic measurement, we utilized a novel ultrasound water jet indentation system to noninvasively measure the stiffness values of the patellar cartilage, fibrocartilage and the tendon, which have been usually difficult to evaluate in situ. Not only significantly more newly formed bone at the BTJ healing interface but also increased stiffness of the junction tissues were found in the ultrasound group compared with the controls at week 18. In addition, the ultrasound group also showed significantly 44% higher BMD at week 6 than controls. Ultrasound; ultrasound indentation; bone-tendon junction; mechanical stimulation; low intensity pulsed ultrasound; material property
Very Broadband GaAs HBT RF MIC Power Amplifier

A very broadband GaAs HBT RF monolithic IC power amplifier with working band from DC to 3.5 GHz is developed successfully. An improved circuit structure of Darlington circuit is proposed. The gain of the PA is obviously increased and the temperature effect of the PA is effectively compensated by using this improved circuit. The gain is more than 18 dB. The output power is more than 22 dBm. The noise figure is less than 3.6 dB
Modeling head-related impulse response based on adaptive Fourier decomposition

Three-dimensional (3D) audio rendering techniques employing head-related impulse responses (HRIRs) are currently used in many fields such as virtual reality (VR) devices and 3D games. The large data of HRIRs makes a high computation cost for the real-time spatial audio applications. Efficient methods for HRIR modeling are necessary for the real-time 3D audio rendering. In this paper, a low computational HRIR model based on adaptive Fourier decomposition (AFD) is presented. In the model, the HRIRs are represented as the sum of mono-components which determined by a small number of the selected atoms in the disc. However, we must sift a substantial of atoms to get the desired atom each decomposition. To further reduce the computation load, we propose an improved method for the AFD model. This method can make the procedure of atoms selection faster by reducing the undesired atoms to some extent. The experimental results show that the improved AFD model requires much less time consuming than the original AFD model.
Preliminary Study of Skeletal Muscle with Multi-signals during Isometric Contraction

Electromyography (EMG) has been widely used for the functional assessment of muscles. On the other hand, sonography has been commonly used to detect the morphological information of human muscles in both static and dynamic conditions. In this study, we demonstrated the feasibility to use the continuous signals about the architectural changes of muscles detected in real-time from ultrasound images to characterize muscles under isometric contraction. We named this signal as sonomyography (SMG). Synchronized ultrasound images and surface EMG (SEMG) signals were continuously collected from the right biceps brachii during the isometric contraction and subsequent relaxation periods together with the generated torque. The relationships among the SEMG, the muscle deformation SMG and the torque were investigated for the contraction phase. The results suggested that the SMG together with EMG signals may potentially provide a more comprehensive assessment for the muscle functions
Joint 2-D DOA estimation using gridless sparse method

A novel gridless sparse method (GSM) is proposed to estimate two-dimensional (2-D) direction-of-arrival (DOA) using L-shaped arrays. The angular space is transformed to a frequency one and a new model is constructed in the frequency field. Based on the new model, the covariance matrix is reparameterized by a positive semidefinite Toeplitz matrix. Covariance fitting criterion and semidefinite programming are used to estimate DOAs in the continuous range. Compared with traditional 2-D DOA estimation methods, there is no need to discretize the whole angular space which can cause modeling error and increase computation loads. Moreover, the proposed method can get pair-matching automatically.
Influences of Electric Parameters of Pulsed Power Supply on Electromagnetic Railgun System

To analyze the electric parameters of a pulsed power supply (PPS) system and their influence on muzzle velocity, a stable and reliable 200-kJ compact PPS system used for electromagnetic railgun system has been developed. The PPS system consists of ten modules, and each module is comprised of a high energy density capacitor (3270 μF/3.5 kV), 4-in thyristor, a pulse shaping inductor (1.5 μH), and a crowbar diode. At the same time, a railgun circuit model for simulation was established. In this model, velocity skin effect, current skin effect, and friction were taken into consideration. Some electromagnetic launching experiments were carried out to verify the correctness of the railgun circuit model. Influence of different electric parameters of PPS on muzzle velocity was analyzed by the computer aided circuit design program PSPICE based on this model. The parameters include capacitance, equivalent series resistance (ESR) of the capacitor, inductance, and jitter time of the thyristor. The simulation results show that the ESR is the most critical influencing factor (the deviation of velocity is -4.286% when the ESR is 5 mQ). The following is the change of the capacitance (the deviation of velocity is -3.827% when the capacitance decreases to 95%C0). In the meantime, the changes of the resistance of inductor do have an influence on muzzle velocity (the deviation of velocity is -0.908% when the resistance of inductor is 1 mQ). However, the changes of inductance and the jitter time of the thyristor impose no significant effect on muzzle velocity. The conclusions provide reference to the overall optimization of PPS design and quality control of the manufacturing process.
A novel method for 2-D DOA estimation using L-shaped array in the presence of mutual coupling

In this paper, a novel self-calibration algorithm is proposed for two-dimensional (2-D) direction-of-arrival (DOA) estimation based on L-shaped array (LSA) with mutual coupling. In this method, we construct a transformation matrix to eliminate the mutual coupling between subarrays, and then the DOA estimation problem of LSA is transformed into that of uniform linear arrays (ULAs). Then we only need to consider the mutual coupling in each subarray and use the rank-reduction (RARE) method to estimate DOAs. In contrast to other methods, the proposed approach not only solves the mutual coupling problem, but also estimates the mutual coupling coefficients. The simulation results show that the proposed approach has better DOA estimation performance under unknown mutual coupling.
Rotating spherical arrays for DOA estimation based on real-valued covariance matrix

The performance of direction-of-arrival (DOA) estimation based on spherical arrays is constrained by the number of the elements. In this paper, we propose a novel rotating spherical array, which can form more virtual elements. However, more elements will cause more cost of computation. In order to decrease the computation load, a real-valued covariance matrix is constructed by the unitary transformation. Therefore, a real-valued signal subspace can be obtained by the eigenvalue decomposition of the real-valued covariance matrix. Based on this signal subspace, we use covariance-assisted matching pursuit (CAMP) to obtain DOA estimation. Simulation results demonstrate the effectiveness of the proposed method.
Development of a Synchronized System for Continuous Acquisition and Analysis of Ultrasound Joint Angle, and EMG

Ultrasound and electromyography (EMG) are two of the most often used diagnostic tools for muscles. However, there is lack of a system for continuously capturing both signals with a synchronized procedure. This study presents a new system for this purpose. The system comprises an ultrasound scanner, a pulser/receiver, an EMG amplifier, and a PC with A/D converter cards for data acquisition and analysis. The A-mode and B-mode ultrasound data, which were digitized by the A/D converter and a video capture card respectively, could be simultaneously captured by the PC together with the surface EMG (SEMG) signal, which was digitized by another data acquisition card. Time markers for all frames of ultrasound and SEMG signals were recorded to synchronize the two data streams. The tissue deformation was extracted inform the ultrasound signals or images using cross-correlation algorithms. The RMS and spectrum of SEMG was calculated to study the muscle activity. In addition, the joint angle signal was also be synchronized with ultrasound and SEMG signals. The experiments involving 5 subjects were carried out to test the performance of the system. Preliminary results showed that the muscle deformations extracted from the ultrasound data were well correlated with the changes of SEMG RMS. The system may have potential values in the investigation of muscle properties and activities
A Novel Method to Obtain Modulus Image of Soft Tissues Using Ultrasound Water Jet Indentation: A Phantom Study

The alteration of tissue stiffness is generally known to be associated with pathological changes. Ultrasound indentation is one of the methods that can be used to assess the mechanical properties of the soft tissues. It uses a flat-ended ultrasound transducer to directly contact the tissue to sense tissue deformation under an applied load. This paper introduced a novel noncontact ultrasound indentation system using water jet compression. The key idea was to utilize a water jet as the indenter as well as the coupling medium for propagation of the ultrasound beam. High frequency focused ultrasound (20 MHz) was used to measure the indentation deformation at a microscopic level. It has been demonstrated that the system could effectively assess the tissue-mimic phantoms with different stiffness. Water jet coupling allows the system to conduct C-scan on soft tissues rapidly and conveniently. By applying different pressures while taking C-scan sequences, the modulus images of the phantoms could be obtained based on the applied pressure and the phantom deformation and thickness. This paper presented the preliminary results on gel phantoms. The spatial resolution, the contrast resolution of the measurements and the reproducibility of the results were also discussed
Modeling the relation between muscle thickness and wrist angle based on bone-muscle lever model

Muscle modeling is a powerful tool to study the skeletal muscle, and can give a better perception of the mechanisms of muscular functions. In this study, a mathematical model was proposed based on the bone-muscle lever model to illuminate the non-linear relation between the thickness of extensor carpi radialis muscle and wrist angle. The ultrasound image, SEMG signals were synchronously sampled from the extensor carpi radialis muscle together with the wrist angle during the whole process of wrist extension and flexion to validate the model. The wrist angle was then calculated using the measured muscle thickness by this model. The overall mean correlation coefficient value was 0.96 ± 0.02, and the overall mean standard root mean square error was 5.82 ± 1.95, which were much better than the results of other regression methods. The results show that the wrist angle is well predicted by our model, and it suggests that this model is helpful to study the relationship between internal muscle structural changes and external limb behaviors.
Study on the generation mechanism of coseismic electric signals

An electromagnetic fault model, which considers the compensation of the piezoelectric effect and the dislocation theory of faults, is presented to deal with reported coseismic electric signals. Charges are assumed to be induced by the stress changes associated with an earthquake. The stress-induced charges are quantified by the charge density as a function of the polarization, which can be calculated using a piezoelectric model and an analytical solution of seismic stress. The theoretical charge distribution around the Nojima fault, which moved at the 1995 Kobe earthquake (M=7.2), was obtained. The coseismic electric field, consistent with that observed at the Kobe earthquake, was estimated as the field due to the charges which compensate the piezoelectric charges.
Effect of Sequence Discharge on Components in a 600-kJ PPS Used for Electromagnetic Launch System

Pulsed power supply (PPS) applied in the electromagnetic launch system must have a compact design and high reliability. In this paper, a PPS for electromagnetic launch system is built up. The main parts in a pulse forming unit (PFU) of a PPS are energy storage capacitors (8 kV/75 kJ), pulse-shaping inductor (10 <formula formulatype="inline"><tex Notation="TeX">$\mu{\rm H}$</tex></formula>), pulse thyristor, crowbar diode, and a Rogowski coil for current measuring. The energy storage density of the PFU is 0.74 <formula formulatype="inline"><tex Notation="TeX">${\rm MJ}/{\rm m}^{3}$</tex></formula>. Eight PFUs form a pulse forming network (PFN) of 600 kJ. In many cases, the discharge current waveform of the PFN must be adjusted for lower peak value and lower electromagnetic force. On the basis of this PFN, in this paper, we analyze the effect of sequence discharge on the semiconductors. To prevent diode from overvoltage during the recovery process, different parameters of snubber circuit have been researched in the experiments. Finally, we set up a model of the serial augment rail gun in a personal simulation program with integrated circuit emphasis, and the safety of PFU can be affirmed by simulation if the voltage of the rail gun keeps positive during the course of the discharge.
A real-valued approach for wideband DOA estimation using spherical arrays

Direction of arrival (DOA) estimation of wideband signals is considered of great importance in array signal processing. In order to estimate both azimuth and elevation angles with good performance, a spherical array is used to capture the space signal information. Considering the property of spherical harmonic function, we propose a unitary transformation and two-step smoothing to turn the complex-valued direction matrix into a real-valued one. Compared with other algorithms, the proposed approach can achieve better performance especially when the number of snapshot is small. Simulations can certify the robustness and effectiveness of the proposed method.