nils-herrmann/clean_scirepeval huggingface dataset:
Off-centre load-insensitive digital quartz resonator force sensor

A digital output force sensor has been developed utilising a unique elastic structure and an AT-cut quartz crystal resonator (QXR) based on an energy trapping effect as sensing element. The force-sensitive QXR is preloaded into the elastic structure, through which a force proportional to the applied force is exerted on the QXR, and the force measurement is accomplished by measuring frequency changes. The elastic structure consists of several flexible hinges and has the advantages of no mechanical friction and no clearance, and therefore nonelastic effects of the digital force sensor are minimised. The elastic structure is specially configured to avoid measurement error induced by off-centre loads. To compensate the temperature coefficient of sensitivity, a dual-harmonic-mode self-temperature-sensing method is employed to measure the applied force and the in situ temperature simultaneously with the same QXR. A practical design is developed and the dependence of the measurement range on the elastic structure dimensions as well as the changes of the quality factor of QXR before and after preloading are discussed. FEM simulation and experimental results show that the force sensor has good performance and is insensitive to off-centre load. Detailed specifications of the force sensor are given.
Hierarchical and adaptive volume-growing methods for the PET based biologic target volume delineation for radiotherapy treatment planning

To more accurately and precisely delineate a biologic target volume (BTV) for PET-guided radiotherapy treatment planning, we proposed a novel tumor segmentation method by hierarchically utilizing an adaptive volume-growing algorithm (AVGA). First, a rough volume of interest (VOI) is manually cut by a radiation oncologist that encloses a tumor volume. The voxel having the highest standard uptake values (SUV) in the manual VOI is chosen as a seed of the first AVGA. One of all 6-neighboring voxels (N6) of the current tumor volume (CTV) is successively appended to the CTV. The growing criterion of the AVAG is that the SUV of the appended voxel is higher than the mean SUV of the CTV multiplied by a threshold value, and its SUV subtracted from the mean SUV of the CTV is a minimum in the N6. We have always observed a sharp volume growth at a certain threshold value T1 between 0.3 and 0.7, in which case many voxels outside of the delineated tumor volume are appended to the CTV. So, the first AVGA is stopped just before the sharp volume growth and the second AVGA is launched to refine the BTV delineation. The resulting CTV by the first AVGA is chosen as a seed volume of the second AVGA, and the threshold varies from T1 to 0.30 with an adding growing criterion which the SUV of the current appended voxel is not higher than one of the last appended voxel. The idea behind is high-noise characteristics, partial volume effects due to the low spatial resolution, the tumor extension with lower SUV, and the spillover effects of some PET images. Patient studies were tested and evaluated by an experienced radiation oncologist. The results demonstrated that the proposed method can more accurately and precisely delineate a BTV due to the second AVGA. This method can automatically process PET images with different sizes of tumor volume and different signal to background ratios (SBR). The resulting BTV is reproducible and also independent of the initial VOI.
On-line detection of foreign substances in glass bottles filled with transfusion solution through computer vision

In this paper, a real time computer vision system was developed to detect a glass bottle filled with transfusion solution on a packing line. The theory, the mechanical structure, and the detection algorithm are described. Foreign substances mixed in transfusion solution are distinguished from bottle side wall defects by a relative movement between a resting bottle and the inside moving solution. Foreign objects moving down in the bottle are first detected with background subtracting, where a normalized cross correlation is employed to identify two frames between which no moving objects overlap and the static back-ground is obtained through an inter-frame difference. In the second stage, falling objects are recognized through an adapted mean-shift tracker, in which an adaptive searching window is used to only find falling objects. The system was tested on 250-ml transfusion bottles. The result shows that it can effectively detect the small visible foreign substances fulfilling the requirements of the application..
A probabilistic approach for rate-distortion modeling of multiscale binary shape

The purpose of this paper it to explore the relationship between the rate-distortion (R-D) characteristics of multi scale binary shape and Markov Random Field (MRF) parameters. In our experiments, we consider two prior models. The first MRF model takes into account pair-wise interaction between pels, and for the binary case, is typically referred to as the auto-logistic model; the second MRF model accounts for higher order spatial interactions and is referred to as the Chien model. Experimental results indicate that the auto-logistic model is not sufficient to characterize the R-D characteristics of multi scale binary shape data. However, higher order models, such as the Chien model, do seem feasible. We propose to use the statistical moments of the Chien model as input to a neural network to accurately predict the rate and distortion of the binary shape when coded at various scales.
Empty bottle inspector based on machine vision

A machine-vision-based empty bottle inspector is presented in this paper. The mechanical structure and electric control system are illustrated in detail. A method based on the histogram of edge points is applied for real-time determination of inspection area. For defect detection of bottle wall and bottle bottom, a derivative algorithm from Canny edge detector is proposed. In bottle finish inspection, two artificial neural networks are used for low-level inspection and high-level judgment respectively. A prototype is developed and experimental results demonstrate the feasibility of the inspector. Inspections performed by the prototype have proved the effectiveness and value of the proposed algorithms in automatic real-time inspection.
AMS: a new associated memory based ATM switch

Shared memory based switch is an important model of ATM switches. It can provide optimal switching performance for different traffic patterns. In this paper, a new model of shared memory based switch-associated memory based switch (AMS)-has been presented. AMS has more characteristics, such as simple switching principle, simple system architecture, suitability for different traffic patterns and different service classes, optimal switching performance and memory space utilization. It can also provide multicasting and broadcasting capabilities.
Image Coding Using Dual-Tree Discrete Wavelet Transform

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. Three methods for sparsifying DDWT coefficients, i.e., matching pursuit, basis pursuit, and noise shaping, are compared. We found that noise shaping achieves the best nonlinear approximation efficiency with the lowest computational complexity. The interscale, intersubband, and intrasubband dependency among the DDWT coefficients are analyzed. Three subband coding methods, i.e., SPIHT, EBCOT, and TCE, are evaluated for coding DDWT coefficients. Experimental results show that TCE has the best performance. In spite of the redundancy of the transform, our DDWT TCE scheme outperforms JPEG2000 up to 0.70 dB at low bit rates and is comparable to JPEG2000 at high bit rates. The DDWT TCE scheme also outperforms two other image coders that are based on directional filter banks. To further improve coding efficiency, we extend the DDWT to an anisotropic dual-tree discrete wavelet packets (ADDWP), which incorporates adaptive and anisotropic decomposition into DDWT. The ADDWP subbands are coded with TCE coder. Experimental results show that ADDWP TCE provides up to 1.47 dB improvement over the DDWT TCE scheme, outperforming JPEG2000 up to 2.00 dB. Reconstructed images of our coding schemes are visually more appealing compared with DWT-based coding schemes thanks to the directionality of wavelets.
The adaptive research of data layout in large-scale meteorological data storage system

In the existing large-scale meteorological data storage systems, the real-time of meteorological data applications is poor; transmission of data process is opaque; meteorological data sharing is complex and self-adaptability is bad; the capability of data quality assurance is not good. For these problems, this paper presents a solution of large-scale meteorological data storage system. This paper also presents a consistent hierarchical Hash data layout algorithm. It used to solve transmission and re-layout problem in the system among meteorological data, storage devices, content transmission network and key data buffer devices. And we test this algorithm's fairness, efficiency and adaptability by experiment.
Develop a Low-Temperature In-Line Sputtering System for Flexible and Thinned-Glass Substrates

Flexible and thinned glass substrates are two kinds of important substrates but are difficult to handle by conventional in-line sputtering system for mass production. Here, we designed and developed an in-line sputtering system for mass production that can handle these two kinds of substrates. The key of this success is the well heat management of this system. With the method of multiple cycles of deposition and cooling, this system demonstrated the deposition of thick copper film on flexible substrates at substrate temperature less than 120 °C. The thickness and cooling rate for one cycle are ~800 nm and 0.5 °C/s, respectively. Additionally, the processes of deposition and cooling are parallel in our system. By redesigning the mechanical structure of substrate carrier, the effect of the thermal stress change of substrate carrier on thinned glass substrates is minimized; therefore, our system can uniformly deposited ITO film on large-size thinned glass substrates. The values of sheet resistance, transmittance, and their uniformity are acceptable for industry. Moreover, all the processes of this system are automatic which is ready for mass production.
Edge detection based on orientation distribution of gradient images

An edge detection scheme which exploits both the magnitude and orientation information of a gradient image is presented. A pixel with a large gradient is considered as an edge element only if the samples in its neighborhood have a unique orientation (straight edge) or a few strong directions (mixed edge). By making use of the orientation information, the proposed scheme can effectively distinguish between the edge points defining object boundaries and those constituting texture patterns. It is also insensitive to noise since the detection is based on the orientation assumed by the majority of the pixels in a neighborhood instead of the individual orientation or intensity variation.<<ETX>>
Research on Computer-Assisted DEM-Based Flight Plan of Aerial Photography

For aerial photography, the forward overlap and side overlap of any point in the photographic image are dependent on its height difference to fiducial altitude of the flight block. The hypsography should be taken as the primary factor into consideration in the flight plan of aerial photography, especially in the process of auto-planning by computer. However, many softwares used for flight planning donpsilat take the hypsography into consideration, so the result of the flight planning may not satisfy the demand of photogrammetry. Therefore the authors have a sort of software developed, which can support importing of the DEM data stored in various file formats including database. In order to verify the validity of the design result, we have finished a pilot project and made a comparison between the design data and real flying data. Through the comparison we infer the software can satisfy the demand of flight planning completely.
Online multiscale entropy estimation using distribution statistics

Multiscale entropy (MSE) is a measurement for quantifying the randomness of a sequence of data. Recently, it has been proven to be the most effective way to analyze the complexity of physiological signals in biomedicine and other fields. The implementation of MSE is computationally expensive because it considers multiple complexities of several data sequences with multiple scales and the computation of entropy for each data sequence is time consuming. A large number of original observed data for computing MSE is necessary because the number of data reduces when the scale increases. We must confirm that the data for each scale is enough to robustly obtain entropy. The large data problem makes MSE difficult for online application of processing sequential data. This paper provides a new online MSE computation method to improve computation efficiency of MSE. Furthermore, we apply distribution statistics in online MSE computation procedure to reduce the storage space of a system. In addition to segmenting the original data sequence into several non-overlapped sliding windows to reduce the data amount of each computation, different kinds of metadata are defined for metadata updating algorithm to accelerate computation time and save storage space. Experiments analyses with electrocardiogram (ECG) revealed that the proposed MSE estimation methods achieved significant improvement of more than 15 times faster than the conventional method for N= 60,000. Moreover, the proposed method only uses about 1/500,000 storage space compared to the conventional method.
Heat-Depolymerizable Polypropylene Carbonate as a Temporary Bonding Adhesive for Fabrication of Flexible Silicon Sensor Chips

This paper presents a method for fabrication of flexible silicon sensor chips using temporary bonding, backside thinning, debonding, and flexible packaging. Flexibility of silicon chips requires ultrathin thickness, which imposes a challenge to debonding of thinned silicon chips from carrier wafers because of the fragility of silicon. To address this problem, temporary bonding using polypropylene carbonate (PPC), a heat-depolymerizable polymer material, as bonding adhesive is developed. PPC allows damage-free detachment of ultrathin silicon chips from carrier wafers by heating after backside thinning. The method is demonstrated and applied to the fabrication of silicon stress sensor chips with thickness down to  $30~\mu \text{m}$ . The measurement results show that the ultrathin silicon chips have good flexibility and function well. The processes are optimized, and the detailed parameters are reported. The preliminary results demonstrate the feasibility of the method, and show its potential application in the fabrication of flexible ultrathin silicon sensors.
Security of Mobile Agent-Based Web Applications

Mobile agents are considered to be an alternative to client-server systems. Security issues are discussed for generic agent-based systems, i.e. intelligent agents migrate to agent platforms. Public key infrastructure (PKI) is a major cryptographic systems deployed for agent-based systems. Cryptographic techniques such as digital signatures, hash function, proxy certificate and attribute certificate, are utilized for protecting both intelligent agents and agent platforms. Countermeasures to agent protections and agent platform protection are given, which are based on information security mechanisms such as authentication, authorization, access control and confidentiality. Other major security concern such as the identity binding and delegation between intelligent agent and its host are discussed with solutions based on proxy certificates and attribute certificates.
Adaptive coherent-signal subspace algorithm for direction estimation and tracking

A new adaptive algorithm is proposed for adjusting the coherent noise subspace of the coherently averaged covariance matrix (CACM) by a constrained least-squares search. The proposed estimator possesses a superior rate of convergence and good tracking properties. All simulations confirm this prediction. The algorithm incurs greater computational cost at each iteration and has a tendency to become numerically unstable. Fortunately, the use of double-precision arithmetic can eliminate the instability problem. also the systolic array implementation developed in recent years may achieve real-time processing.<<ETX>>
A Front-Side Released Single Crystalline Silicon Piezoresistive Microcantilever Sensor

This paper presents the design, fabrication, and characterization of a piezoresistive microcantilever sensor fabricated on silicon-on-insulator (SOI) wafers. The microcantilever consists of two silicon dioxide supporting layers and a single crystalline SOI layer in-between. The piezoresistors are implanted in the surface of the SOI layer to exploit its large piezoresistive coefficients. Laminated beam theory is employed to design the microcantilevers and the piezoresistors. A front-side releasing method is developed to suspend the microcantilevers by isotropically etching the substrate beneath the microcantilevers from the front-side of the wafers using SF6 plasma. The features of SOI wafers and the front-side releasing enable high uniformity and high yield for the fabrication of piezoresistive microcantilever sensors. The sensors are validated using specific binding reaction of antigen and antibody of immunoglobulin G on the sensor surface, and the experimental results show that they are promising for portable and integrated sensing applications.
Robust Exponential Stability for Time-Delays Neural Networks with Discontinuous Activation Functions

In this paper, we considers the global robust exponential stability of uncertain neural networks with discontinuous activation functions and time-varying delays. Based on the Lyapunov-Krasovskii stability theory, we originally analyze the global robust exponential stability of discontinuous neural networks with time-varying delays using the linear matrix inequalities(LMIs). Thus, our results are brand new compared to previous literature. A numerical example is given to validate the effectiveness of our results.
Prediction of weather impacted airport capacity using ensemble learning

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.
Block-sparse compressed sensing with partially known signal support via non-convex minimisation

The mixed l
 2
/
 l
 p
 (0 <; p
 ≤ 1) norm minimisation method with partially known support for recovering block-sparse signals is studied. The authors mainly extend this work on block-sparse compressed sensing by incorporating some known part of the block support information as a priori and establish sufficient restricted p
-isometry property (
 p
-RIP) conditions for exact and robust recovery. The authors' theoretical results show it is possible to recover the block-sparse signals via l
 2
/
 l
 p
 minimisation from reduced number of measurements by applying the partially known support. The authors also derive a lower bound on necessary random Gaussian measurements for the p
-RIP conditions to hold with high possibility. Finally, a series of numerical experiments are carried out to illustrate that fewer measurements with smaller p
 are needed to reconstruct the signal.
Improving BER Performance by Using V-Shaped Read Head Array in Heat-Assisted Magnetic Recording

Heat-assisted magnetic recording (HAMR) is the leading candidate for the next generation of magnetic recording. In HAMR, the thermal profile (with circular contours produced by the near-field transducer) combined with the current writer structures results in recording transitions with noticeable curvature, which causes edge erasure at high linear density and increased transition noise. This transition curvature affects the bit error rate (BER) and is thus important to the model. As the micromagnetic simulations are computationally demanding, in this paper we investigate a fast and simplified write model to capture the transition curvature of HAMR. As the transition curvature causes signal degradation in normally oriented read head array (NHA) having straight gaps, we propose a V-shaped read head array (VHA) by rotating the side readers at appropriate angles to follow the curvature shapes and improve the readback signal. Simulations indicate that, with 2-D signal processing, VHA can provide improved BER performance compared to the NHA in the presence of readback transition curvature on HAMR media. Also this paper indicates that the Curie temperature variance affects BER performance more severely than the anisotropy field variance.
Study on wind-EV complementation in transmission grid side

Electrical vehicles (EVs) have drawn much attention recently. The appropriate energy resource to charge EVs is one of the key factors in EVs' development. On the other hand, how to reduce abandoned wind energy is one of the main problems in wind power application. The conception and the benefits of “wind-EV complementation” are presented in this paper from the viewpoint of transmission grid. A mathematical model of EVs charging/discharging in aggregator mode is presented, based on which the problem of how to reduce abandoned wind energy is researched. The simulation results of the coordinated and uncoordinated charging, different EVs penetration and different charging modes (unidirectional and bidirectional mode) are compared in reducing abandoned wind energy. It can be concluded that with more EVs' total charging capacity and higher wind energy proportion to the charging energy, the abandoned wind energy will be less and the “wind-EV complementation” effect will be better. Finally, the benefits of “wind-EV complementation” are concluded and the future research prospects are pointed out.