nils-herrmann/clean_scirepeval huggingface dataset:
A New Method on the Segmentation and Recognition of Chinese Characters for Automatic Chinese Seal Imprint Retrieval

In this paper, we propose a new method on the segmentation and recognition of Chinese characters in both circular and elliptical seals for automatic Chinese seal imprint retrieval. The seal identification system compares an input seal image with its model seal. However, the model seal is usually found manually, which costs quite a lot of time and this manual stage has become the bottleneck of automatic seal identification. In addition, traditional automatic methods which were designed for circular seal imprint retrieval cannot work well for elliptical seal images. In order to overcome these shortcomings, our method first fits the contour of seal images and then automatically classifies them into either circular seal shape or elliptical seal shape. After that, we apply different methods for Chinese character segmentation and skew correction with circular and elliptical seal shape images respectively. Finally, we use our classifier combination strategy to recognize the Chinese characters on Chinese seal images. Once optical character recognition (OCR) is done, a model seal imprint corresponding to its input sample seal image is retrieved for verification from the seal imprint database. Experimental results show that our method has better performance than traditional ones.
Research on variable camber wing driven by ultrasonic motors

Taking the Advantages of ultrasonic motors such as high torque, small size, light weight, self-lock and rapid response, a kind of variable camber wing driven by ultrasonic motors is designed in this paper. The morphing wing is suitable for small UAV of low Mach number because it is able to obtain a good aerodynamic efficiency. Parallelogram linkage driven by ultrasonic motor is designed and applied to the variable camber wing to drive the trailing edge. Distributed layout of the mechanism is adopted and continuous deformations can be produced, so various aerodynamic profiles suitable for different flying states can be obtained. The motors are arranged independently in the wing panel, and individually drive the wing sections to morph separately. The whole morphing mechanism is placed in the interior of the wing and the wing surface is covered with smooth flexible skin in order to decrease the aerodynamic drag.
A method of urine detection based on front vision and image recognition

This paper presents a method of urine detection based on front vision and image recognition. Urine detection apparatus is composed of a conveyor belt, a urine detection card, an automatic detection needle and an automatic detection camera, a mobile device and so on. In order to realize the rapid and accurate identification of the circular hole in urine, the model of the front vision of the urine detection instrument was modeled. Firstly, the forward monocular vision imaging model is presented, including the design of software and hardware, and the coordinates of the target center in the image are obtained by combining the characteristic of the target. Then, through the visual calibration model, the target location of monocular vision is achieved, and the coordinates of the center of the circular hole in the camera coordinate system are obtained. The center coordinates of each circle center coordinate of the urine detecting card are consistent with the coordinate of the automatic dripping needle, and the automatic dripping needle can drop down the test liquid to the center of the circular hole of the urine detection card. The experimental results show that this method can detect the urine of different patients in large scale. This method has high sensitivity, shorter detection time, more rapid and efficient, simple and convenient operation. This method has accurate and reliable detection results.
The Design of the Intelligent Window Control System Based on Wireless

As we all know, the role of windows is to adjust the indoor environment and to achieve the comfort of residents. Most of the windows currently used are simply push-pull or translational, and are controlled by humans. However, when you forget to close the window and encounter rainy weather, you will be inconvenienced. Therefore, this paper developed a control system that can automatically control the window switch according to the indoor and outdoor environment changes. The system uses MQ-2 sensor to detect combustible gas indoors, infrared probe to probe the outside case of the window, temperature and humidity sensors to detect the indoor temperature and humidity, photo-resistor to measure the light intensity. The controller collects sensor information to control the stepper motor to change the state of the window open or close. At the same time there are functions, such as regular switch windows, key switch windows and wireless remote control switch window. After testing, the system has realized the remote control and automatic controlled function of the window, reached the goal of smart home, and has good application prospect.
Efficient Scheduling Mechanism for Performance-Heterogeneous Multi-core Processor

Multi-core processor architectures are increasingly being used in high-performance computing environment because heterogeneous characteristics of the processor cores can play an important role in the performance of multicore processors. In the paper, we analyze the architecture and tasks' parallel features of performance-heterogeneous multicore processor based on DHCMP (Dynamic Heterogeneous Chip Multiprocessor). Grouping all of the basic cores into several logic cores and establish a mapping rule from basic cores to logic cores, and apply classification data mining to scheduling process of logic cores, establishing a performance-heterogeneous multicore processor scheduling model and algorithm. Experiments show that the scheduling strategies and algorithm in this paper can improve the utilization of logic cores than other algorithm.
On the theoretical limit of the lightweight of passenger cars based upon the core of Industrial Engineering on eliminating clean ineffective work

Based upon the core of Industrial Engineering (IE) on eliminating clean ineffective work (ECIW) together with Automobile operational equation (AOE), the theoretical limit of the effective curb mass of passenger car (TLECMPC), two ways for solving TLECMPC, the ratio of the effective curb mass of passenger car (RECMPC) and the ratio of the ineffective curb mass of passenger cars (RICMPC) have been advanced for the first time in this paper. And then the theoretical lightweight limit of passenger cars (TLLPC) and the theoretical limit of fuel saving of passenger cars (TLFSPC) relative to TLLPC have been presented in this paper. The case in this paper indicates that as to H original passenger car with 1300 (Kg) curb mass, its RICMPC is 62.15% high, its TLLPC is 808 (Kg) high and its TLFSPC is 3(L/100 Km).
Can Activities of Human Daily Life be Recognized and Predicted?

Understanding Activities of Human Daily Life is a fundamental and essential AI problem for Ubiquitous Computing and Human-Computer Interaction. Activity inference has attracted enormous research on activity recognition from mobile sensor data. However, it is not clear how different signals can influence activity inference. To this end, we investigated the problem of activity recognition and prediction. Experiments showed that contextual signals like time, location, previous activity and related person are much more useful than demographical signals for activity recognition and prediction. We improved the accuracy of activity recognition by more than 15% comparing to existing work on the same dataset. What's more, we revealed that we can predict what will you do next with high accuracy.
Corrosion Behavior of Cu-Al Intermetallic Compounds in Copper Wire Bonding in Chloride-Containing Accelerated Humidity Testing

Accelerated reliability testing is widely used in the microelectronic packaging to evaluate the long-term reliability of electronic devices. Although a lower intermetallic growth rates in Cu-Al joint improved its performance in thermal aging comparing with Au wirebonds, it is a great challenge to pass through accelerated humidity tests for Cu wirebonds, because Cu-Al intermetallics are easily subjected to chloride-induced corrosion. Unfortuniately, no literature has ever given direct evidences on IMC corrosion process, thus fundamental corrosion mechanism is still obscured. In this paper, we systematically investigated the corrosion behavior of Cu-Al intermetallic compounds (IMCs) under accelerated humidity environment. A high resolution transmission electron microscopy (HRTEM) was used to identify interfacial intermetallics in thermal aged Cu-Al ball bonds, in which Cu<sub>3</sub>Al<sub>2</sub> was confirmed between Al<sub>2</sub>Cu and Cu<sub>9</sub>Al<sub>4</sub>. Selective Cu-Al IMC corrosion occurs when chloride was present in the accelerated humidity environment: Cu<sub>3</sub>Al<sub>2</sub> and Cu<sub>9</sub>Al<sub>4</sub> were continuously corroded while the Al<sub>2</sub>Cu remained immune. Microstructure analysis using HRTEM revealed the corrosion process of corroded IMCs (Al<sub>2</sub>Cu and Cu<sub>9</sub>Al<sub>4</sub>) and the root cause of corrosion immunity for Al<sub>2</sub>Cu layer.
A Prototype System of Courtesy Amount Recognition for Chinese Bank Checks

In this paper, we present a prototype system of courtesy amount recognition (CAR) for Chinese bank checks. The system deals with color check images and consists of five modules: skew correction, binarization, string extraction, segmentation and recognition. The whole system is designed under three principles: information fusion, complementary method combination and multi-hypotheses generation then evaluation. Information from color, gray and binary images is fused and complementary algorithms are applied for binarization and string extraction. Multi-hypotheses are made by keeping all possible candidates when ambiguous solutions exist in extraction and segmentation. Then the most suitable one is selected as the final result by evaluating the probabilities from recognition. Experiments show that our system is very promising based on a large number of real checks collected from different banks.
EEG-Based Lower-Limb Movement Onset Decoding: Continuous Classification and Asynchronous Detection

Brain–machine interfaces have been used to incorporate the user intention to trigger robotic devices by decoding movement onset from electroencephalography. Active neural participation is crucial to promote brain plasticity thus to enhance the opportunity of motor recovery. This paper presents the decoding of lower-limb movement-related cortical potentials with continuous classification and asynchronous detection. We executed experiments in a customized gait trainer, where 10 healthy subjects performed self-initiated ankle plantar flexion. We further analyzed the features, evaluated the impact of the limb side, and compared the proposed framework with other typical decoding methods. No significant differences were observed between the left and right legs in terms of neural signatures of movement and classification performance. We obtained a higher true positive rate, lower false positives, and comparable latencies with respect to the existing online detection methods. This paper demonstrates the feasibility of the proposed framework to build a closed-loop gait trainer. Potential applications include gait training neurorehabilitation in clinical trials.
Notice of Retraction The attitudes of Chinese and South African managers to corporate social responsibility

This paper empirically explores Chinese and South African managers' attitudes toward corporate social responsibility in Chinese state-owned mining enterprises in South Africa. The results find that South African managers hold significantly more favourable attitudes towards corporate social responsibility than their Chinese counterparts. More Chinese than South African managers consider corporate social responsibility to be a business case which can be useful to the business. This study reveals the reasons for implementing corporate social responsibility and the different cultural aspects of Chinese `collectivism' and South African `individualism'.
Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance

This paper deals with the issue of data-driven adaptive sliding mode control for a family of discrete-time nonlinear processes with tracking error constraint. More specifically, a novel transformed error algorithm together with a new sliding mode control framework is investigated to ensure the tracking error converges to a predefined zone all the time. Moreover, the proposed controller can guarantee a convergence rate and steady-state behavior for the tracking error depending only on the input/output measurement data, which is more effective in the complex industrial processes. Simulations are given to validate the theoretical results.
A Low Power Grid-Based Cluster Routing Algorithm of Wireless Sensor Networks

In wireless sensor networks, the energy of nodes is limited. so designing efficient routing for reducing energy consumption is important. In this paper we proposed A Low Power Grid-based Cluster Routing Algorithm of Wireless Sensor Networks (LPGCRA). The characteristic of this algorithm is that the WSN is divided into different grids according to information of the node location, and then the nodes are organized within the grid by the clustering way. The clustering head is chose dynamiclly according to energy dissipation of the cluster nodes, then communicates with BS node through a relaying node. This algorithm is useful to reduce node energy consumption and prolonged life of the system, also enhanced the balance of network load. The simulation results shows that this algorithm balanced the energy consumption of the nodes effectively and improved the network lifetime.
On the method-independent lower bound (MILB) to the variance of attenuation estimation in random reflection.

Based on the Cramer-Rao inequality, the MILB is calculated for the problem of estimating the frequency slope of the attenuation coefficient of tissue from random reflections of ultrasonic waves. Under typical signal conditions, this bound for a 1-cm x 1-cm region was found to be about 0.08 db/(MHz-cm), rather close to the clinical requirement of 0.1 dB/(MHz-cm). Comparison to existing methods (including an autoregressive deconvolution method) shows room for further improvement.
Amplitude Modulation Strain Noise Reduction by Displacement Field Correction

In ultrasound strain imaging, random fluctuations of the signal amplitude result in a match only occurred at certain regions from pre- and post-compression window pairs. This produces amplitude modulation (AM) strain noise. In this paper a new suppressing amplitude modulation method called displacement filed correction (DFC) is presented. Both simulation and phantom experiment demonstrate that the presented method can efficiently reduce amplitude modulated strain noise and achieve the considerable improvement in the strain image quality and performance.
An Improved Side Information Refinement Method in Distributed Video Coding

Distributed video coding (DVC) is a new kind of video codec scheme that exploits the statistical characteristics of source at the decoder part. The estimated side information is modeled with the original Wyner-Ziv frame and an additive noise. Side information plays an important role in determining the performance of the codec. In Turbo-or-LDPC-based DVC decoding, the log-likelihood ratio (LLR) for every source bit is calculated using side information and dependent channel model. In this paper, we propose a side information refinement method, which uses previously decoded bit-planes to update the side information for current bit-plane decoding. With the refined side information, more accurate channel model and bit LLRs are achieved, which results in a lower bit rate in video coding Rate-Distortion (RD) performance.
Parallel Matrix Multiplication Algorithm Based on Vector Linear Combination Using MapReduce

Matrix multiplication is used in a variety of applications. It requires a lot of computation time especially for large-scale matrices. Parallel processing is a good choice for matrix multiplication operation. To overcome the efficiencies of existing algorithms for parallel matrix multiplication, a matrix multiplication processing scheme based on vector linear combination (VLC) was presented. The VLC scheme splits the matrix multiplication procedure into two steps. The first step obtains the weighted vectors by scalar multiplication. The second step gets the final result through a linear combination of the weighted vectors with identical row numbers. We present parallel matrix multiplication implementations using MapReduce (MR) based on VLC scheme and explain in detail the MR job. The map method receives the matrix input and generates intermediate (key, value) pairs according to the VLC scheme requirement. The reduce method conducts the scalar multiplication and vectors summation. In the end, the reduce method outputs the result in the way of row vector. Then performance theoretical analysis and experiment result comparing with other algorithms are proposed. Algorithm presented in this paper needs less computation time than other algorithms. Finally, we conclude the paper and propose future works.
A fast and robust vision system for autonomous mobile robots

Computer vision system is an important sensor for autonomous mobile robot. However, the design of a vision system that can satisfy the needs of both robustness and efficiency is still difficult. In this paper, a fast and robust vision system is described which increases its speed and robustness through choosing suitable color space, algorithms of mathematical morphology and active adjustment in parameters. All of the algorithms are employed in a pan-tilt vision system of an autonomous mobile robot.
Study on topic tracking system based on KNN

Text classification is the key technology for topic tracking, and vector space model (VSM) is one of the most simple and effective topics representation model. Feature selection algorithm in VSM is an important means of data pre-processing, and it can reduce vector space dimension and improve the generalization ability of the algorithm. Therefore, it is necessary for feature selection algorithms to be in-depth and extensive research. So we develop a topic tracking system to study how feature dimension and the value of K-neighbors affect topic tracking. Then we get the variation law that they affect topic tracking, and add up their optimal values in topic tracking. Finally, TDT evaluation methods prove that optimal topic tracking performance based on adjusting the value of K-neighbors for text increases by 7.246% more than feature dimension.
A Multilevel Thresholding Method Based on Improved Chaos Optimization for Image Segmentation

Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. So a novel optimal multilevel thresholding method based on the improved chaos optimization algorithm (COA) for image segmentation is presented in this paper. Firstly, an improved COA is described; Instead of the traditional chaos optimization algorithm which employs two search stages: rough search and precise one, this improved COA uses one chaos search process directly and selects quite a few initial values to overcome the bad starting value problems of the traditional COA and to get better optimal results. Then the improved COA and maximum entropy are combined to get multilevel thresholds. Segmentation experimental results show the proposed approach is effective and gets competitive visual effects.
Automatic path and trajectory planning for laser cladding robot based on CAD

The robot path planning for forming complex parts is one of the key techniques in coaxial laser cladding powder. In this paper, a method of automatic robot path generation from CAD (computer aided design) is proposed. The size information and topological information of the CAD model are extracted. The redundant vertexes are removed. The new vertexes are ordered and traversed by binary tree algorithm model. The topological relations between vertexes, edges and faces are established. The CAD model and the robot path are displayed with OpenGL. The comparison and analysis between contour planning and hyperbolic curve planning are completed. The simulation shows the feasibility and validity of the path generation based on CAD. A new way of automatic robot path generation from CAD model is given and the efficiency of the robot cladding is improved.
Image Reconstruction of High-Quality Photoacoustic Tomography Using Wavelet-Analysis-Based Algorithm

A modified method of high-quality photoacoustic tomography reconstruction incorporates wavelet-analysis-based algorithm into filtered back-projection algorithm is proposed. According to the method, each photoacoustic signal captured by ultra-wideband transducer is decomposed into a combination of multiple wavelets to realize wide band-pass antinoise processing. The modified algorithm is successfully applied to image simulated breast tumor phantom and brain structure of a rat brain in vivo, respectively. In the reconstructed images, the extra- and intra-annulus structure of the simulated breast tumor phantom is clearly identified with effective noise suppression. The vascular network and other detailed brain structures of rat brain organization are clearly identified with the skull and scalp intact. The image spatial resolution can reach 204 microns approximately. The experimental results demonstrate that the modified method based on the wavelet-analysis-based algorithm has much higher antinoise capacity, and can greatly improve the reconstruction image quality for deeply penetrating photoacoustic tomography.
Experimental research on the triggering characteristic of TVS under AC condition

Triggered vacuum switches (TVS), have found fast growing applications in the field of power system and pulse power. A closing switch is the necessary controlling device of power supply of an ElectroMagnetic Launcher (EML) system and synthetic making test of high-voltage circuit breakers for short-circuit current introduce, which should have the ability to quick connect the circuit and precisely controlling the moment of connection. It also should isolate the high power storage, then close the circuit at a set time. TVS gets fast development in recent years, which attributes to its many advantages. High insulation level of vacuum medium and the fast diffusion of post-arc plasma make TVS have the ability to turn on and off high voltage and high current with higher frequency. Electrodes and trigger are sealed in the vacuum chamber and free from outside disturbance, that ensures the reliability of TVS. Arcs running in vacuum have very low arc voltage that leads to much lower energy input to the arc and thus result in a lower electrode erosion rate. In our research, a series experiments have been carried out on the sample TVS especially with AC load between the main electrodes. The triggering and delay characteristics were emphatically expounded. An elaborated circuit for controlling the TVS is proposed herein. The triggering energy of the controller can be adjusted conveniently. By means of changing the triggering energy, the experimental results show that the delay and jitter times decrease with increasing trigger energy. The delay and jitter times decreases magnificently with the increasing voltage in the main gap. By increasing the main-gap voltage, the triggered probability increases.