nils-herrmann/clean_scirepeval huggingface dataset:
High-Performance Mid-Wavelength InAs/GaSb Superlattice Infrared Detectors Grown by Production-Scale Metalorganic Chemical Vapor Deposition

We demonstrate high-performance mid-wavelength <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> infrared detectors based on InAs/GaSb type-II superlattices (SLs) grown by a production-scale metalorganic chemical vapor deposition system. Through a specially-designed gas switching sequence and the use of GaAs-type of interfacial layers, strain-balanced SLs with excellent material quality were obtained, as evidenced by atomic force microscopy, photoluminescence, X-ray diffraction, and transmission electron microscopy. The processed devices, with a cutoff wavelength around 4.8 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>, exhibited a R<sub>0</sub>A of <inline-formula> <tex-math notation="LaTeX">$2.3\times 10^{4}~\Omega $ </tex-math></inline-formula>cm<sup>2</sup> and a peak responsivity of 1.4 A/W at 77 K. A specific detectivity of <inline-formula> <tex-math notation="LaTeX">$7.2\times 10^{12}$ </tex-math></inline-formula> cmHz<inline-formula> <tex-math notation="LaTeX">$^{1/2}$ </tex-math></inline-formula>/W was achieved at <inline-formula> <tex-math notation="LaTeX">$3.7~\mu \text{m}$ </tex-math></inline-formula>. These values are comparable with those reported for InAs/GaSb SL detectors with similar cutoff wavelengths grown by molecular beam epitaxy.
High speed non-contact printing for solar cell front side metallization

This work presents a non-contact high speed printing technology for patterning high aspect ratio fine grid lines for the front side metallization of crystallized silicon solar cells. The approach of achieving fine line printing with high aspect ratio was obtained by combining focused work of both material and process together. A modified silver paste was directly patterned by a one-step process onto the silicon wafers without using a screen mask and the line width was as small as 50µm, while the height was around 30µm after firing. The preliminary study of these printed cells showed up to a 0.5% efficiency increase by effectively reducing the shading area while maintaining high grid line conductivity and low contact resistance.
Hybrid model of absorption refrigeration system components

Absorption refrigeration system is a nonlinear process with strong interactions among each working device. It is of practically significance to develop a accurate and reliable model for real-time optimization and performance monitoring of overall system. The hybrid modeling approach take advantages of both physical and empirical modeling approaches. The model is robust and gives a better match to real performance over the entire operating range. The hybrid model of absorption refrigeration system components (evaporator, condenser, heat exchanger etc.) are analyzed in the paper. The L-M method is used to identify the unknown parameters in the model, and lay the foundation for further optimization performance of system.
Design of a Practical DSSS Communication System Based on TMS320c5416 DSP

Direct sequence spread spectrum technology is very important in wireless telecommunication systems and data communication systems because it has many advantages, such as good concealment, and being able to overcome the multiple access interference. A practical DSSS communication system based on TMS320c5416 Digital Signal Processor is designed in the paper, which consists of baseband modulator, IF modulator/demodulator, local oscillator, antenna, Liquid crystal displays monitor and TMS320c5416 DSP, etc. The experiment result of transmission shows that the direct sequence spread spectrum system designed can realize effective data transmission and anti-interference communication with advantages of high data transmission rate and wide spectrum range.
A novel dynamic ice-structure interaction model for ice-induced vibrations

A dynamic single degree-of-freedom ice-structure interaction (ISI) model is developed based on a novel physical mechanism combination between self-excited vibration (SEV) and forced vibration (FV). Van der Pol (VDP) equation, together with ice stress-strain rate curve and ice-velocity failure length are coupled to model the internal fluctuating nature of ice force in conjunction with the relative velocity and relative displacement caused by the structure as external effect. Resonant condition has been captured during ISI. Moreover, ice force frequency lock-in (FLI) phenomenon during ice-induced vibrations (IIV) is also observed. General results show good agreement with those in full-scale experiments as well as numerical results available in the literature.
A problem-snapshot view of patient history data for cardiac preoperative evaluation

Preoperative risk evaluation is a very important work before a cardiac surgery. Clinicians always have to spend much time reviewing the information about operative risk factors. In this paper, we have made a few tentative attempts to help clinicians improve the efficiency of risk evaluation. First a surgery-problem network for cardiac surgeries is built to extract the associated medical problems from patient history problems. Then a set of data filter rules are defined for each medical problem to retrieve the required data, which is clustered around the problems and forms a set of snapshots. After that, we propose a multi-level-timeline method to visualize the problems and snapshots extracted. Finally, a special problem-snapshot visualization tool for cardiac preoperative evaluation is designed and developed as a result. The tool provides a quick way of reviewing the information which is helpful for cardiac preoperative risk evaluation through information visualization technology. It can save a lot of tedious work.
Improve Accuracy of Fingerprinting Localization with Temporal Correlation of the RSS

Recent study presents a fundamental limit of the RSS fingerprinting based indoor localization. In this paper, we theoretically show that the temporal correlation of the RSS can further improve accuracy of the fingerprinting localization. In particular, we construct a theoretical framework to evaluate how the temporal correlation of the RSS can influence reliability of location estimation, which is based on a newly proposed radio propagation model considering the time-varying property of signals from Wi-Fi APs. The framework is then applied to analyze localization in the one-dimensional physical space, which reveals the fundamental reason why localization performance can be improved by leveraging temporal correlation of the RSS. We extend our analysis to high-dimensional scenarios and mathematically depict the boundaries in the RSS sample space, which distinguish one physical location from another. Moreover, we develop an algorithm to utilize temporal correlation of the RSS to improve the location estimation accuracy, where the process for choosing key design parameters are provided through experiments. Experiment results show that the localization reliability and accuracy can be improved by up to 13 and 30 percent with appropriate leveraging the RSS temporal correlation information.
Control of an Active Suspension Based on Fuzzy Logic

In this paper, a control strategy of active suspension based on the fuzzy logic control has been investigated. Using incorporating feedback from force sensor at front and rear active suspension system, the control system shows the improvement of the dynamic responses of the vehicle. A multi degree-of-freedom nonlinear model is co-simulated by MATLAB/Simulink and ADAMS/car. The simulation results indicate that the proposed active suspension is very effective in the vibration isolation.
A general-purpose representation of biosignal data based on MFER and CDA

Electric mechanical or chemical signals of biological origin delivered by human bodies can always be of interest for diagnosis, patient monitoring, and biomedical research. Such biomedical signals, namely biosignals, are usually presented by flat file format or proprietary format when digitized for acquisition, storage, transfer and analysis. Recent advances in the ubiquitous computing technology make it possible to measure biosignal data anywhere and anytime. But a big challenge resides in the realm of ubiquitous computing, which is the uniform integration and communication of data. This problem also exists in the development of the electronic health record and telemedicine. Standardizing the data presentation is the best solution to resolve these problems. But a general-purpose, effective, user-friendly, and universally accepted data format for biosignal is not available at this moment. This paper proposes a simple and complete representation of biosignal data based on MFER and CDA. It adopts frame structure of MFER to encode the waveform data of biosignal and uses hierarchical structure of CDA to describe its non-waveform data. This composite format not only inherits the advantages of MFER and CDA, but also facilitates the implementation of interpretation of biosignal.
A New Two-Stage Hierarchical Framework for Mammogram Retrieval

In this work, we described a new two-stage hierarchical framework for mammogram retrieval. We tested the proposed approach on the reference library from USF-DDSM. For each query ROI (region of interest), the proposed scheme first computes its 14 texture and shape features, then the voting method based on five classifiers is used to classify the ROIs in the reference library, this phase eliminates ROIs that are very semantic different from the query ROI. Next, the scheme uses the k-nearest neighbor K-NN algorithm to select the 40 most ldquosimilarrdquo regions with the same computational level from a large reference library, and computes the mutual information (MI) between the query ROI and each of the selected ROIs from the database. Finally, 15 regions with the highest MI values, which seem to be the most visual similar to the query ROI, are selected and displayed to the observers. We tested the proposed method involving 80 queries, on average the 73.8% of the displayed ROIs are considered semantic and visual similar to the query region. Preliminary experimental results showed that the proposed scheme can achieve better accuracy than the single-classifier based method and the vector distance based similarity metric.
An 0.03 μm gate-length enhancement-mode InAlAs/InGaAs/InP MODFET's with 300 GHz f/sub T/ and 2 S/mm extrinsic transconductance

We have developed high-performance enhancement-mode InP-based modulation-doped field-effect transistors with 0.03 /spl mu/m gate-length. A record high current gain cutoff frequency exceeding 300 GHz has been achieved, and the maximum extrinsic transconductance is as high as 2 S/mm with an associated drain current of 0.5 A/mm at a drain bias of 1 V. This high performance is a result of the reduction or gate length, the use of the high barrier metal Pt as gate electrodes, and most importantly the employment of the well-developed wet-etching technology that allows the formation of a very deep gate groove while retaining small side etching. The excellent E-MODFET performance opens up the possibility of implementing ever faster high-speed circuits based on direct-coupled FET logic.
Design and Fabrication of Dual-Trench Epitaxial Diode Array for High-Density Phase-Change Memory

For the first time, the design and fabrication of dual-trench epitaxial p/n junction diodes in a commercially standard 0.13-μm complementary metal-oxide-semiconductor process are introduced in this letter. The 16 × 16 diode arrays with 0.196-μm2 (5F2) cell size have been successfully fabricated, showing the excellent electrical properties of its sufficient current drive ability in excess of 12.5 mA/μm2, large on-/off-current ratio greater than nine orders of magnitude, and its excellent crosstalk immunity. A dual-trench epitaxial diode could be used as the access device for high-density phase-change memory and could also produce highly scalable embedded applications for 45-nm node and beyond, due to its unique process integration scheme.
Effective Load-Balancing Framework for Distributed WebGIS

The inquiry of vector data and transmission of massive data between the client and the server end has become the critical key of the problem because of the contradiction between Distributed WebGIS massive data and the limited bandwidth of network resources. Based on analysis of the two frameworks of WebGIS and the properties of intelligent Agent in the field of Distributed WebGIS, this paper attempts to present a hybrid model WebGIS framework. The performance of this hybrid model has been verified though the experiment for cable monitoring system conducted in State Grid in Beijing. It has been proved that this framework is effective on improving the inquiry speed and maintaining a good network-load performance.
A Semantic Match Algorithm for Web Services Based on Improved Semantic Distance

The remarkable increase of web services raises the challenge of service discovery. In UDDI, the description of the services is based on syntax and the search does not effectively make use of the IO properties of the services. In order to overcome these limitations, some semantic match algorithms have been proposed. This paper analyzed the defects of the semantic match algorithm proposed by M. Paolucci et ], introduced the semantic match method based on semantic distance and indicated the defects of current semantic match algorithm based on semantic distance. Then this paper proposed a semantic match algorithm based on improved semantic distance. By concrete examples, we show that our improved algorithm eliminated the defects of the algorithm proposed in  and the defects of the current semantic match algorithm based on semantic distance. So our improved algorithm does improve the precision ratio and the recall ratio of service discovery.
Design of a cross-shaped piezoelectric motor with single driving foot

A cross-shaped piezoelectric motor with length of 43mm and diameter of 11 mm was proposed in this paper. Two third bending modes were used to generate ellipse trajectory at the driving foot located at the vibrator's center. Sixteen pieces of piezoelectric ceramic plates with sizes of 5mm×3mm×1mm were used to excite two third bending modes. Sine and cosine voltages with effective value of 100V at the frequency of 54.696 kHz were applied to the piezoelectric ceramic plates in right and left sides of the vibrator. Symmetrical structure of the motor solved the problem of mode frequency degeneracy. Two excitation methods were put forward to excite two third bending vibrations. And effectiveness of the two excitation methods was compared by the transient analysis with finite element method. Transient analysis results showed that motion trajectories of nodes on the driving feet were three-dimensional and that ellipse motion in the XOY plane was fit to drive the motor, and the new excitation method improves the vibration amplitude in the OX and OY by 2 times and 4 times, respectively compared with the vibration amplitude excited by the traditional excitation method.
FOTP: Face-Based Object Tracking Protocol in Wireless Sensor Network

Object tracking is an important application in Wireless Sensor Network (WSN). High-accuracy and energy-efficiency are key requirements. In this paper, we propose a novel face-based object tracking protocol (FOTP), which is used to track the object with low energy consumption and high quality. FOTP combines a hexagon algorithm with face-architecture system model, which can provide precise detection and efficient tracking. Firstly, soldier nodes observe the object and elect a near node (NN) which is the nearest node to the object. And then, the NN tracks the tracked object (TO) and predicts its next position by hexagon algorithm. Furthermore, candidate faces will be woken up by the NN and responsible for continuously tracking the coming TO. Being compared with previous works, FOTP tracks object with limited sensor participants. Simulations show our protocol can not only support efficient tracking but also conserver more energy.
Improved Dynamic RON of GaN Vertical Trench MOSFETs (OG-FETs) Using TMAH Wet Etch

This letter reports on the dynamic <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> performance of large-area GaN vertical trench MOSFETs (OG-FETs) fabricated on bulk GaN substrates. OG-FETs demonstrated excellent DC performance with a breakdown voltage of 900 V and a <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> of 4.1 <inline-formula> <tex-math notation="LaTeX">$\Omega$ </tex-math></inline-formula> (8.2 <inline-formula> <tex-math notation="LaTeX">$\text{m}\Omega \cdot \text {cm}^{2}$ </tex-math></inline-formula>). However, damage to the trench sidewalls caused by RIE dry etching led to poor dynamic <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> performance. An improved dynamic <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> performance was achieved by following the RIE dry etch with a TMAH wet etch. With this process combination, the dynamic <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> was reduced by more than 10 times compared with the dynamic <inline-formula> <tex-math notation="LaTeX">$R_{\text{ON}}$ </tex-math></inline-formula> in devices fabricated by dry etch only.
Iterative learning control of linear continuous systems with variable initial states based on 2-D system theory

This paper is concerned with the variable initial states problem in iterative learning control (ILC) for linear continuous systems. Firstly, the properties of the trajectory of 2-D continuous-discrete Roesser model are analyzed by using Lyapunov's method. Then, for any variable initial states which absolutely converge to the desired initial state, some sufficient conditions in the form of linear matrix inequalities (LMI) are given to ensure the convergence of the PD-type ILC rules. It implies that the ILC rules can be used to achieve the perfect tacking for variable initial states, even if the system dynamic is unknown. Finally, two numerical examples are given to illustrate the perfect tracking performance with exponentially convergent initial states.
1H NMR-Based Metabonomics Study of Urine and Serum Samples from Diabetic db/db Mice

A metabonomics approach based on high resolution 1 H NMR spectroscopy was applied to investigate the metabolite fingerprints in urine and serum samples from db/db mice of 8 weeks old, an animal model of type 2 diabetes mellitus (T2DM). Both NMR spectra and metabonomics results were discussed and the variations on related metabolic pathway were analyzed. The urinary excretions of diabetic mice have elevated levels of citrate, alanine, acetate, TMAO, hippurate, taurine, creatinine, succinate, pyruvate, glycine in addition to evident increase of glucose compared to the control ones. The metabolic variation in serum samples of db/db mice is marked by the increases of lactate, 3-hydroxybutyrate, glutamine, glutamate and choline and the decreases of leucine and valine. These results indicate that NMR-based metabonomics is an efficient approach for investigating the subtle metabolic alterations in urine and serum from diabetic mice and the findings of the characteristic metabolites would be helpful for early diagnosis and prevention of T2DM and its related complications.
A novel clustering method based on K-MEANS with region growing for micro-calcifications in mammographic images

Breast cancer is one of the most dangerous malignant tumors of women in the world. A particularly important clue of such disease is the presence of clusters of micro-calcifications. However, it is difficult for radiologists to provide both accurate and uniform evaluation for benign or malignant pathologic modifications of micro-calcifications. The radiologists are usually obtained by using human expertise in recognizing the presence of given patterns and types of micro-calcifications. In order to automatically detect such clusters and improve the accuracy, in this paper, K-MEANS-based region growing clustering algorithm is proposed to automatically finding clusters of micro-calcifications in the phase of clustering in mammography. The approach has been successfully tested on a standard database of 30 mammographic images, publicly available.
A stochastic combinatorial optimization model for test sequence optimization

Traditional test sequence optimization methods for path testing have three problems: 1) fake test results may occur; 2) unnecessary repetitive tests may exist; 2) actual test coverage rate could be low. These problems are because the effects of the faults on the test sequence execution are not considered by traditional methods. To solve these problems, we defined a stochastic combinatorial optimization model in this paper. At the same time, we constructed a multistage dynamic combinatorial optimization model to solve it. In each stage, the stochastic optimization is transferred into a deterministic optimization and the faults are taken as the stage changing factors. Simulation results show that the effective test efficiency and test coverage rate are evidently increased by this stochastic combinatorial optimization model.
Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation.

In this paper, we study the heterogeneous domain adaptation (HDA) problem, in which the data from the source domain and the target domain are represented by heterogeneous features with different dimensions. By introducing two different projection matrices, we first transform the data from two domains into a common subspace such that the similarity between samples across different domains can be measured. We then propose a new feature mapping function for each domain, which augments the transformed samples with their original features and zeros. Existing supervised learning methods (e.g., SVM and SVR) can be readily employed by incorporating our newly proposed augmented feature representations for supervised HDA. As a showcase, we propose a novel method called Heterogeneous Feature Augmentation (HFA) based on SVM. We show that the proposed formulation can be equivalently derived as a standard Multiple Kernel Learning (MKL) problem, which is convex and thus the global solution can be guaranteed. To additionally utilize the unlabeled data in the target domain, we further propose the semi-supervised HFA (SHFA) which can simultaneously learn the target classifier as well as infer the labels of unlabeled target samples. Comprehensive experiments on three different applications clearly demonstrate that our SHFA and HFA outperform the existing HDA methods.
Effect of Registration Error on Infrared Image and Visible Image Fusion Quality

In this research, the effect of registration error on infrared image and visible image fusion quality was discussed. The registration errors from different directions were adopted to simulate the real registration error. Meanwhile, the infrared and visible images under different registration error were analyzed. The result showed that among the Laplacian Pyramid fusion, Gradient Pyramid fusion, Contrast Pyramid fusion and SIDWT with Haar fusion, the Laplacian Pyramid fusion can better maintain the infrared and visible image fusion quality under a certain registration error. Moreover, when dealing with different registration errors, single integration indicator was not sufficient in describing the infrared and visible image fusion quality. Instead, the multi integration indicators shall be taken into consideration.