nils-herrmann/clean_scirepeval huggingface dataset:
Diagnosis and Synthesis for Defective Reconfigurable Single-Electron Transistor Arrays

Single-electron transistor (SET) at room temperature has been demonstrated as a promising device for extending Moore's law due to its ultralow power consumption. However, early realizations of SET array lacked variability and reliability due to their fixed architectures and high defect rates of nanowire segments. Therefore, a reconfigurable version of SET was proposed to deal with these issues. Recently, several automated mapping approaches have been proposed for area minimization of reconfigurable SET arrays. However, to the best of our knowledge, seldom mapping algorithms that consider the existence of defective nanowire segments were proposed. Furthermore, before the defect-aware mapping, we have to know the locations of defects in SET arrays. Thus, this paper presents the first diagnosis approach to identify the locations of defects in SET arrays followed by two defect-aware algorithms for mapping SET arrays in different scenarios. The experimental results show that the proposed diagnosis method can detect 100% of defects under a defect rate and distribution in SET arrays. As for the mapping algorithms, the results show that our approach can successfully map the SET arrays with 11.13% and 7.69% width overhead on average in the baseline detour mapping algorithm and defect-reuse mapping algorithm, respectively, in the presence of 5000-ppm defects.
Research on the simulation system of nc milling

Based on the features of NC milling process, the 3D geometric model of virtual machine tool and the fixture are established by the virtual reality technology and OpenGL graphics library with the method of construction of solid geometry (CSG) and boundary representation (B-Rep), and some realistic effects treatments (including material, light, texture mapping, etc.) are applied. The established virtual machine tool can be zoomed, rotated and translated in the view area. And a workpiece decomposition expression model based on the Z-MAP structure is put forward, and Boolean subtraction is performed by using this model and a tool solid model to simulate the real time process of cutting and test the simulation result. Simulation example proves that this system runs reliably and improves NC machining efficiency. (4 pages)
Comparison and fusion of multiresolution features for texture classification

We investigate the texture classification problem with individual and combined multiresolution features, i.e., dyadic wavelet frame, Gabor wavelet, and steerable pyramid. The support vector machines are used as classifiers. The experimental results show that the steerable pyramid and Gabor wavelet classify texture images with the highest accuracy, the wavelet frame follows them, and the dyadic wavelet significantly lags them. Experimental results on fused features demonstrate the combination of two feature sets always outperform each method individually. And the fused feature sets of multi-orientation decompositions and stationary wavelet achieve the highest accuracy.
A game-theoretic mode for EV discharging price and its application

With a large number of EV (Electric Vehicle) accessing to distribution network, this paper put to use game theory to balance grid company's gains and the consumers' costs. Reasonable subsidy and discharging price are the fundamental driving force for consumers to participate in V2G (Vehicle-to-grid). Based on different strategic decisions of grid company and consumers, the paper analyzes the their profits and the losses explains the relasionship between dischanging price and the numbers of EV paticipating to V2G. This research provides a reference for companies to formulate the subsidy and the discharging price.
Application of a Capture Technique to the 3D Harbor Construction

The main purpose of this paper is to design an innovative ship handling simulation program by combining the development of Quest3D software and the Google earth harbor terrain software. The paper describes the usage of the Google earth program to retrieve the latitude and longitude elevation, through GIS conversion and 3D graphical model to generate the Quest 3D harbor construction blueprint. Projectors display the image with build-in formula calculated angle settings to achieve a better perspective for the projectors installation. A 3D virtual reality scene was built by using the Maya Model, and then we overlap with the harbor module to complete the famous world ports. The results will be tested in the ship handling simulator machine at the 3D virtual reality software development laboratory.
An improved social spider algorithm for the Flexible Job-Shop Scheduling Problem

In this paper, we propose a novel swarm algorithm, called social spider algorithm (SSA), to solve the Flexible Job-Shop Scheduling Problem (FJSP). The SSA algorithm stresses the difference between the two different search agents (spiders): males and females . Some strategies are utilized to generate the initial individual in order to ensure certain quality and diversity, such as global search (GS) and local search (LS) and so on. Moreover, instead of the original SSA algorithm, the improved SSA is combined with the selection, crossover and mutation operation to enhance the performance. The computational result shows that the proposed algorithm produces better results than other authors' algorithms [23].
Development of a piezoelectric polyvinylidene fluoride polymer-based sensor patch for simultaneous heartbeat and respiration monitoring

This study reports a piezoelectric polyvinylidene fluoride (PVDF) polymer-based sensor patch for simultaneous heartbeat and respiration detections. The principle is based on the piezoelectric sensing mechanism to detect the pulsatile vibrations, and periodical deformations on the chest wall of human body during heartbeats and respirations, respectively. In this study, the sensor patch with a structurally curved PVDF film was designed, and fabricated. The role of the curved structure designed to enhance detection signals, and the capability of the sensor to faithfully detect the heartbeats and respirations were experimentally evaluated. Results revealed that the sensor was proved to be able to generate the heartbeat and respiration signals which were in concordance with those based on a commercial electrocardiogram (ECG), and respiratory effort transducer, respectively. As a whole, this study has developed a PVDF-based sensor patch which was capable of monitoring the heartbeats and respirations with high fidelity. Other distinctive features include its small size, light weight, ease of use, low cost, and portability. All these make it a promising sensing device to monitor heartbeats and respirations either in medical centers, or home care units.
A novel screen content fast transcoding framework based on statistical study and machine learning

In this paper, a novel screen content transcoding framework is presented to efficiently bridge the state-of-art High Efficiency Video Coding (HEVC) standard and its incoming screen content coding (SCC) extension currently pending finalization. The proposed scheme is implemented as an Intra-coding “pre-processing” module on top of official SCC test model software (SCM). Both Coding Unit (CU) statistical features (such as CU color quantity, CU pixel variance, CU edge directionality distribution, etc.) and decoded video side information (such as CU partitions, modes, residual, etc.) are jointly analyzed. Accordingly, fast CU mode decisions and CU partitions bypass / termination heuristics are designed. Compared with SCM-4.0 official release, the proposed fast transcoding scheme can achieve an average of 48% re-encoding complexity reduction over JCT-VC screen content testing sequences with less than 2.14% marginal BD-Rate increase under SCC common testing conditions for All-Intra (AI) configuration.
High-performance of geometric primitives detection usinig genetic algorithm

In this paper, we present some new methods for high performance of geometric primitives detection using a genetic algorithm (GA). At first, we describe the detection algorithm based on minimal subset and improvement of fitness function of geometric primitives. Secondly, we analyze the structure of minimal subsets and its probability properties in a digital image, and we improved the probability of primitive detection by reducing the invalid parts. Thirdly, we mention the subpixel measurement technique that makes edge location highly accurate, thereby increasing the accuracy of primitives by replacing the minimal subset with their subpixels. Finally, we present a method to simultaneously detect several primitives using the equivalence genes which are regarded as the set of points on a primitive; it has some excellent functions such as observation of convergence, promotion of convergence, confirmation of convergence and maintenance of multiple subpopulations.
A Region Based Image Matching Method with Spatial Constraints

In this paper, a new region-based image matching method was proposed to find the user defined regions in other images. Not only local features and overall features are used, but spatial constraints are also employed. Experimental data were composed of 1000 images from Corel and 1000 I frames extracted from CCTV and MPEG-7 videos. Three matching strategies were compared in experiments. They were overall feature only, color and spatial constraints, and color/texture with constraints. As well, lots of noise was introduced to test the robustness of the proposed method. Experimental results showed that the method was feasible and effective.
Coded EXcitation with spectrum inversion (CEXSI) for ultrasound array imaging

In this paper, a scheme called coded excitation with spectrum inversion (CEXSI) is presented. An established optimal binary code whose spectrum has no nulls and possesses the least variation is encoded as a burst for transmission. Using this optimal code, the decoding filter can be derived directly from its inverse spectrum. Various transmission techniques can be used to improve energy coupling within the system pass-band. We demonstrate its potential to achieve excellent decoding with very low (<80 dB) side-lobes. For a 2.6 /spl mu/s code, an array element with a center frequency of 10 MHz and fractional bandwidth of 38%, range side-lobes of about 40 dB have been achieved experimentally with little compromise in range resolution. The signal-to-noise ratio (SNR) improvement also has been characterized at about 14 dB. Along with simulations and experimental data, we present a formulation of the scheme, according to which CEXSI can be extended to improve SNR in sparse array imaging in general.
$L_{1/2}$  Regularization: Convergence of Iterative Half Thresholding Algorithm

In recent studies on sparse modeling, the nonconvex regularization approaches (particularly, Lq regularization with q ∈ (0,1)) have been demonstrated to possess capability of gaining much benefit in sparsity-inducing and efficiency. As compared with the convex regularization approaches (say, L1 regularization), however, the convergence issue of the corresponding algorithms are more difficult to tackle. In this paper, we deal with this difficult issue for a specific but typical nonconvex regularization scheme, the L1/2 regularization, which has been successfully used to many applications. More specifically, we study the convergence of the iterative half thresholding algorithm (the half algorithm for short), one of the most efficient and important algorithms for solution to the L1/2 regularization. As the main result, we show that under certain conditions, the half algorithm converges to a local minimizer of the L1/2 regularization, with an eventually linear convergence rate. The established result provides a theoretical guarantee for a wide range of applications of the half algorithm. We provide also a set of simulations to support the correctness of theoretical assertions and compare the time efficiency of the half algorithm with other known typical algorithms forL1/2 regularization like the iteratively reweighted least squares (IRLS) algorithm and the iteratively reweighted l1 minimization (IRL1) algorithm.
Research on real-time vibration-insensitive inspection and classification algorithms for automatic online vision-based inspector

In the automatic online vision-based inspector on pharmaceutical production line, vibration disturbance from electromechanical system mostly leads to failure using traditional inter-frame difference algorithm. In this paper, a real-time vibration-insensitive inter-frame difference inspection algorithm for online impurities detection is proposed to overcome the disturbance. The inspection algorithm employs an efficient subpixel image registration method (based on a mountain-climbing searching strategy) and adaptive local threshold segmentation. Inspection can be finished in no more than 0.93 second. Experimental inspection results of false alarm rate 4.51% and omission rate 0.14% show detection validity even if vibration amplitude increases to five pixels. Then impurity classification based on Relevance Vector Machine (RVM) is carried out as feedback to monitor and improve the manufacture process. Classification accuracy above 97% satisfies the requirements for automatic production line.
Novel system design for readback at 10 terabits per square inch user areal density

A novel system design for sensing very high density magnetic recording data, such as that envisioned for two-dimensional magnetic recording, is proposed. The key idea is a rotated sense head, so that the shields are aligned down-track, combined with oversampled signal processing to regain the lost down-track resolution. Based on a random Voronoi grain model, simulation indicates that for bits with dimension of 8 nm × 6 nm, 5.5 nm grains, and a reader with 4 nm × 18 nm × 18 nm free layer and 11 nm shield-shield spacing, the bit error rate can drop from 20.9% for a normally positioned head array to 4.2% for a single-rotated single head with sampling period of 2 nm, a minimum mean squared error equalizer, and pattern-dependent noise prediction detector. The user density computed using the Shannon capacity limit is greatly increased to 10.1 Tb/in2.
Analysis and optimization of a compliant mechanism-based digital force/weight sensor

Digital force/weight sensors have some advantages over their analog counterparts. This paper describes the optimization and implementation of a novel digital force/weight sensor that uses a thickness-shear quartz crystal resonator (QCR) and a unique compliant mechanism. The compliant mechanism consists of eight flexure hinges and is used to fix the sensitive QCR and transfer the measured force. Advantages of such a sensor include inherent digital output, high resolution, high reliability, and low cost. Due to the complex structure and the multivariables of the compliant mechanism, conventional trial methods are inefficient in determining the dimensions. To solve this problem, an optimization method has been developed by employing rigid-body model, finite element method, and nonlinear programming techniques. Experimental results show that it is more efficient than trial methods in optimizing complex compliant mechanism-based sensors. This method can be used as a generic method for optimizing force sensors using compliant mechanisms, to obtain the desired specifications.
A fuzzy-based dynamic channel borrowing scheme for wireless cellular networks

In this paper, a fuzzy-based dynamic channel-borrowing scheme (FDCBS) is presented to maximize the number of served calls in distributed wireless cellular network. The uneven traffic load may create hot-spot cells and possibly causes a high blocking rate in the hot-spot cells. Most conventional method use load indices with a threshold value to determine the load status of a cell. However, it exists a ping-pong effect as loads are around the threshold value. This result causes an unstable system and unnecessary message passed overhead. In addition, the estimation of traffic load is difficult and time-consuming. Thus, an intelligent prediction mechanism is needed. In this paper, we develop a method to predict the cell load and to solve the channel-borrowing problem based on the fuzzy logic control. The FDCBS exhibits better adaptability, robustness and fault-tolerant capability thus yielding better performance compared with other algorithms. Through simulations, we evaluate the blocking rate, update overhead, and channel acquisition delay time of the proposed method. The results demonstrate that our algorithm has lower blocking rate, less update overhead and shorter channel acquisition delays.
Individual pitch control strategy on alleviating periodic load fluctuations

Considering the periodic load fluctuations of wind turbine caused by wind shear and tower shadow, the individual pitch control strategy is proposed in this paper. According to the wind model of wind shear and tower shadow, the individual pitch control based on azimuth angle and load feedback is discussed, the blade flapwise load feedback is superimposed on the basis of azimuth angle weight coefficient distribution to fine correct the pitch angle of each blade. The strategy is applied on a 1.5 MW wind turbine, the simulation results on Matlab platform show that the proposed strategy can significantly alleviate blade flapwise load fluctuations, which means the strategy holds good potential to reduce rotor unbalance loads and mitigate fatigue loads of wind turbine.
System Design for Readback Above 1 Tbit/${\rm In}^{2}$ From Granular Media

The performance of a rotated sense head is examined for densities of 2-7 Tbits/ in2 recorded on granular media, such as that envisioned for 2-D magnetic recording. The key idea is that tightly placed shields are used to guarantee the resolution in the cross-track direction, and oversampled signal processing regains the lost resolution in the down-track direction. It also avoids the necessity for a complex 2-D detector and head array, or latency issues if a single head were employed in the normal orientation. Simulation shows that the new design achieves a density gain of 1.7X (single head) and 2.1X (head array) over a normally oriented single head at a target bit error rate (BER) of 10-3 with sampling period of 2 nm, minimum mean square error equalizer, and Viterbi detector. The new design shows greatly reduced BER relative to a normally oriented single head for all densities, including a very few grains per channel bit .
Noise figure in UWB systems

Noise figure (NF) is a commonly used system parameter that quantifies the degradation in the signal-to-noise ratio (SNR) as the signal passes through a system. Different from the narrow band systems, the energy of the transmitted signal spread on wide band in the UWB (Ultra Wide Band) systems. The NF is varying in the signal band if a narrow band system NF is used in UWB systems, a more precise NF is needed for UWB systems. Conventional narrow band systems noise analysis methods and their shortcomings are discussed, then an NF that suit for digital UWB systems is described. Take a UWB LNA design for example, the advantage of the UWB NF is demonstrated as a conclusion.
An object based graph representation for video comparison

This paper develops a novel object based graph model for semantic video comparison. The model describes a video with detected objects as nodes, and relationship between the objects as edges in a graph. We investigated several spatial and temporal features as the graph node attributes, and different ways to describe the spatial-temporal relationship between objects as the edge attributes. To tackle the problem of erratic camera motion on the detected object, a global motion estimation and correction approach is proposed to reveal the true object trajectory. We further propose to evaluate the similarity between two videos by establishing the object correspondence between two object graphs through graph matching. The model is verified on a challenging user generated video dataset. Experiments show that our method outperforms other video representation frameworks in matching videos with the same semantic content. The proposed object graph provides a compact and robust semantic descriptor for a video, which can be used for applications such as video retrieval, clustering and summarization. The graph representation is also flexible to incorporate other features as node and edge attributes.
The investigation of the formaldehyde gas sensor based on organic thin-film-transistors

The organic thin film transistor (OTFT) with the ratio of channel width (W) to length (L) as 8000/25 was fabricated for the application of formaldehyde gas sensors. The copper phthalocyanine (CuPc) and silicon dioxide was used as the active layer and the insulating layer, respectively, and the titanium/aurum thin films were made as the source/drain electrodes for the prepared OTFT. The voltage-current characteristic curve of the OTFT was measured. The source-drain current in the saturation region changed when the prepared OTFT device was exposed to formaldehyde vapour compared to that under the circumstance of nitrogen at room temperature. It was observed that the OTFT sensor based on CuPc has high sensitivity for formaldehyde vapour. The source-drain current can be considered as a key parameter to monitor chemical species. Such OTFT devices are promising to operate as a novel chemical sensors.
Identification of ball and plate system using multiple neural network models

Based on the dynamic characteristics of the ball and plate system, the mathematic description of system is usually derived by using Lagrange equations, but the controller of the system is very difficult to design according to this kind of model. For the convenience of controller design, NARMA and NARMA-L2 model are always used to describe the nonlinear system. Two kinds of nonlinear models (NARMA and NARMA-L2 model) are set up for the ball and plate system, and BP neural network will be trained to approximate the nonlinear function of these two models. The comparison of different models is made by simulations, and the advantage and shortcoming of different models are analyzed in details. The results of this paper will be very useful for the study of modeling and controller design of complex nonlinear system.
Image Compression using 2D Dual-tree Discrete Wavelet Transform (DDWT)

In this paper, we investigate image compression using 2D dual-tree discrete wavelet transform (DDWT), which is an overcomplete transform with direction-selective basis functions. To further sparsify DDWT coefficients, an iterative projection-based noise shaping method is employed. We analyze the statistics of DDWT coefficients as well as the inter-scale, inter-subband, and intra-subband dependency among the DDWT coefficients. We further evaluate the application of SPIHT and EBCOT for coding DDWT coefficients. Experimental results show that SPIHT is more effective than EBCOT for DDWT, and the DDWT-SPIHT coder outperforms JPEG2000 at low bit rates and is comparable to JPEG2000 at high bit rates.