nils-herrmann/clean_scirepeval huggingface dataset:
Visual Cultural Symbol Recognition Based on Muti-Feature Extracting

Visual cultural symbol (VCS) is common around us, and it's very important for cultural study. Especially, it's useful and efficient if we can study VCS through CS. In the Internet, Mostly VCS display as an image. Machine learning is emerging, but image recognition is focused on face or man detective, it's lack of VCS recognition study. Content based image classification techniques are gaining increasing popularity in the visual contents of the images for classifying images to their categories of interest which has been accomplished using various techniques. Feature extraction is an important part of the classification process. In this paper, we mainly using HOG (Histogram of Oriented Gradient), LBP (Local Binary Pattern), RGB, to extract the VCS's contour, texture, color features, respectively, and also comprehend them. The efficiency of feature extraction techniques to implement according to above methodologies are tested using the Support Vector Machines (SVM) Classifier. In all these techniques different degrees of image classification precision and recall has been calculated. There are some impressive conclusions which are made from our experiments.
Geometric dilution of precision for bearing-only passive location in three-dimensional space

Geometric dilution of precision (GDOP) is a measurement of localisation accuracy in bearing-only passive location. However, the current GDOP expression is available only for two dimensions; while GDOP is widely adopted in spatial application, consequently, the explicit GDOP expression in three-dimensional (3D) space using the Cauchy-Binet formula is derived. The derived GDOP expression is used in two examples, which shows that the localisation accuracy is affected by both the number of sensors and the observation geometry.
No-reference blur index using blur comparisons

Presented is a new no-reference blur index for still images that is based on the observation that it can be difficult to perceive between versions of an image blurred to different degrees. A `re-blurred` image is produced by intentionally blurring the test image. Local sample statistics are computed in the vicinity of detected edges of the original and re-blurred images, respectively. These are differenced and normalised to construct a new blur index. Experimental results on four simulated blur databases and on the Real Blur Image Database show that the proposed method obtains high correlations with test subjective quality evaluations.
Study of specific absorption rate (SAR) induced in human endocrine glands for using mobile phones

With the quick development and widespread use of mobile phones has led to arising concern about the possible adverse health effects of radio frequency electromagnetic field exposure. This study aims to present the dosimetry analysis of the electromagnetic fields induced by mobile phone on human endocrine glands. A finite-difference time-domain (FDTD) method was employed to calculate the specific absorption rate (SAR) in a realistic human head-neck model from exposure to a generic handset at 1750 MHz. The results show that the locally induced SAR in thyroid gland is much larger than that in both hypophysis and hypothalamus glands. The induced SAR in thyroid for the mobile in short message service (SMS) position is much larger than that in the voice position. However, in all of the examined cases, the SAR values in endocrine glands are all below the IEEE safety standard.
A Capacitor Current Based Adaptive Hysteresis Controlled Fast Transient Response DC-DC Converter

This paper presents a capacitor current based adaptive hysteresis controlled DC-DC converter. This controller avoids wide range frequency band filter or complicated compensation. Based on that capacitor current reflects the load current directly and fast, the proposed system uses a simple analog differentiator to sense the voltage capacitor current. Meanwhile, a PI compensation loop is added to improve loop accuracy. The adaptive hysteresis control is implemented by a frequency regulator. The adaptive hysteresis controller ensures the hysteresis comparator work at a fixed frequency. Also, the system is optimized by introducing a ramp generator. The ramp generator is the combination of the PI compensation and the differentiator. This optimization simplifies and minimizes the controller. The system is designed in TSMC 0.35 um standard CMOS process. Simulation results show that when load current changes from 1 A to 10 A (10% to 100% of full load) at 1A/ns, the restore time is 8.93 us.
Antagonist muscle co-activation of limbs in human infant crawling: A pilot study

Muscle Co-activation (MCo) is the simultaneous muscular activation of agonist and antagonist muscle groups, which provides adequate joint stability, movement accuracy during movement. Infant crawling is an important stage of motor function development that manifests non-synchronization growth and development of upper and lower limbs due to the well-known gross motor development principle of head to toe. However, the effect of MCo level for agonist and antagonist muscle groups on motor function development of limbs has not been previously reported. In this paper, sEMG signals were collected from triceps brachii (TB) and biceps brachii (BB), quadriceps femoris (QF) and hamstrings (HS) of limbs when fourteen infants were crawling at their self-selected speed. Antagonist muscle co-activation was evaluated by measuring two common indexes (co-activation index and Pearson's correlation coefficient).A significant difference was observed between upper limbs and lower limbs, but the relationship between MCo and speed of crawling was poor. This study is an opening for further investigation including a longitudinal study and compare against infant with CNS disorders.
Dual FET active patch elements for spatial power combiners

A novel dual-FET active patch antenna element and arrays for quasi-optical power combining are described. The circuit uses two FET's that symmetrically load a split patch antenna. The configuration of the devices decreases H-plane cross-polarization dramatically. The power combining was achieved by injection locking through mutual coupling. An equivalent isotropic radiation power of 0.88 W for a 2-element dual-FET patch antenna array has been obtained. For a 2/spl times/2 array, an equivalent isotropic radiated power of 2.99 W was achieved. The circuit is planar and amenable to monolithic circuits.
Kernel-based Fuzzy K-nearest-neighbor Algorithm

In this paper, the fuzzy k-nearest-neighbor is extended to a kernel-based model which performs a nonlinear classification by kernel methods. This generalized model is called kernel-based fuzzy k-nearest-neighbor model. Through a nonlinear mapping the input data are mapped into a high-dimensional feature space where fuzzy k-nearest-neighbor is performed. The computation of the nonlinear mapping is finished implicitly by kernel methods. The kernel methods are used as a chief means of computing fuzzy k-nearest-neighbor efficiently in high-dimensional feature space where the nonlinear pattern now appears linear. The effectiveness of the proposed algorithm is shown for classification in application to the real world data sets. The proposed model compares favorably with fuzzy k-nearest-neighbor
Automatic Segmentation and Quantitative Diagnosis of Pulmonary Parenchyma in Thoracic CT

An adaptive threshold segmenting and contour tracing method was applied to extract the pulmonary parenchyma automatically from thoracic CT images. The density distribution of high resolution CT was used to determine the region and severity of emphysema.. Experimental results showed that the novel method can be adopted to segment the pulmonary parenchyma automatically and the accurate and effective results were presented as expected. This method can also be applied on analyzing the pathological change regions, performing quantitative analysis and helping on diagnosis of emphysema.
Frequency response measurements of DC-DC buck converter

The key design objective for switched mode power supplies is to achieve stability. The uncompensated system is affected by disturbances appearing at the input voltage as well as in the load current. To mitigate the effect of these disturbances some sort of control scheme is necessary to be added to the system for stable operation and robustness of the system. The introduction of control scheme into the feedback path of the converter system enables it to cope with the issue of disturbances. The frequency domain performance measure parameters i.e. gain margin, phase margin and crossover frequency give fair idea about the stability and overall performance of the system. But the analysis of the system only via simulation is not sufficient for most applications. In many cases the actual circuit is affected by parasitic elements and electromagnetic interference. Therefore measurement of the loop gain of the system is necessary to ensure the system's stable operation. In this work modeling of DC-DC buck converter system is done in Matlab. The results for uncompensated system, controller and compensated system are obtained. Before the implementation of prototype Saber is used for schematic simulation of the system. The simulation in Saber gives a fair idea about the performance of the actual system. Finally based on the system modeled, a prototype is implemented and frequency response measurements are done using network analyzer. The measurement results agree with simulation results and system is able to achieve the targeted values of phase margin and crossover frequency.
Key technology in embedded control system of jacquard knitting

Key technology in design of embedded jacquard knitting control system was introduced in this paper, including technology requirements, real-time requirements, mechanical delays and embedded control system structure. The control system is of compact structure, reasonable design, high performance-price ratio, and can fully meet the jacquard knitting control requirements of the current computerized circular knitting machines. The research of this project provides some theory and practical effect for the product development of electronic jacquard control system.
Sensitive body image detection technology based on skin color and texture cues

This paper researches the features of pornographic videos sensitive body videos, and presents a method to recognize and shield the sensitive content automatically. Skin color is one of important cues for pornographic video's detection. Firstly, transform the color space, calculate Gaussian probability distribution, definite threshold value, analyze texture and noise to extract skin message from a frame image, and then build a skin color mask. Secondly, study the differences between sensitive body image and normal image in skin color distribution to extract some effective factors for judging and determine threshold values of the judgment factors. Finally, judge whether there is sensitive content in a frame image using the values of the factors and make the appropriate process for current frame according to the judgment result. Our algorithm achieves the satisfactory experimental results of shielding the sensitive content automatically when people watch video.
The authentication and identity delegation about mobile agent system based on trusted computing platform

In the mobile agent system, the authentication and identity delegation of mobile agents are the important security problem. This paper focuses on the issues faced by a relying party when deciding to trust a CA and the certificates that it issues. The scope of this paper is limited to examining the basis for trusting a relying party places in an identity certificate signed by a CA. Some of the working group's discussion of the authentication and delegation of identity of mobile agent are also presented. This paper also gives a way to protect private keys and identity certificates in the mobile agent environment. The mobile agent and agent platform can use these certificates to build trust relationships between the CA and its registration authorities, or trust relationships between the end entities and the service providers.
A Unified Voltage Harmonic Control Strategy for Coordinated Compensation With VCM and CCM Converters

Harmonics have been considered as one of the major issues in modern power grids. Considering the high penetration level of power electronic converter interfaced distributed generation (DG) units, it is of interest to provide ancillary services through DG interfacing converters, such as harmonic compensation. In that case, multiple DG interfacing converters are utilized to compensate harmonics, and the compensation effort should be properly shared among these converters. However, it is rarely considered in existing literatures that converters operating in different modes, such as voltage-controlled mode (VCM) and current-controlled mode (CCM), need to cooperatively provide the compensation function. Aiming at this objective, this paper proposes a unified voltage harmonic mitigation strategy for VCM and CCM converters with high harmonic current sharing accuracy. Another advantage of the proposal is that the grid-side and load-side current measurements are avoided, which reduces the implementation cost. Experimental results are presented to demonstrate the effectiveness of the method.
A novel zonotope-based set-membership identification approach for uncertain system

As a Minkowski summation of several linear segments in the real space, zonotopes have been widely used in set-membership identification (SMI) for uncertain system because of its advantages, such as higher accuracy, compactness of representation and less complexity. A new SMI approach is proposed in this paper to develop a control oriented model based on zonotope, with which complex mathematical calculation of feasible system set (FSS) can be avoided. The main contributions of this work are that we obtain a zonotope-based uncertainty model in an iterative form, via minimizing a new criterion representing the accuracy of the nominal model and the size of uncertainty. To circumvent the problem that the order of identified zonotope increases persistently during iteration and to reduce the computational effort, a novel approach is proposed to keep the order of zonotope constant without losing optimality, which is a contrast to the conventional approach that reduces the order after performing the optimization. The proposed zonotope-based SMI approach can be directly extended for multi-input multi-output (MIMO) system identification using decomposition-composition rule. The effectiveness of the proposed approach is demonstrated by two illustrative examples.
Technologies for Risk Evaluation and Decision-making of the Failure in Municipal Water Distribution System

This paper focuses on a minimum cut-set methodology for reliability evaluation of municipal water distribution systems. Based on the application of minimum cut-set methodology in complex municipal water distribution networks, a calculation model for risk evaluation and decision-making of hydraulic accident in water distribution systems is presented in this paper. A case is conducted to demonstrate the methodology with a program compiled by author. The result obtained shows that minimum cut-set methodology for risk evaluation and decisionmaking of hydraulic accident is scientific, reasonable, effective and valuable for application.
Component analysis of GPRS traffic based on user-level from a live network

Characterizing aggregated GPRS traffic and user traffic is important for performance evaluation and optimization of the networks. In this paper, we investigated these characteristics and their relationship. Our analysis are based upon user-level flow traces from passive monitoring of more than 1000 GPRS/EGPRS cell sites connected to the same SGSN at Gb interface. The traffic traces are from a major China ISP in one urban area of Northern Province during an ongoing 24 h period in August 2012. We found that user traffic volume in a 5-minute period at a given cell is consistent with a heavy-tailed distribution. A small portion of large volume users accounted for more than 70% of downlink resource of cell. Furthermore, with the increase of arriving users in a 5-minute period at a cell, the large-volume users contribute more traffic proportion of total cell traffic. These findings are useful for constructing a practical and predictable mobile internet traffic model.
Model predictive control of post-combustion CO2 capture system for coal-fired power plants

The technique of post-combustion CO2 capture is one of the most direct and effective means of reducing CO2 emissions from coal-fired power plants. However, owing to the complex behavior of CO2 capture system, such as large inertia, strong coupling among multi-variables, and strict constraints, the conventional PID controllers cannot meet the flexible operation requirement. For this reason, this paper proposes the use of model predictive control to improve the control performance of the CO2 capture system. Subspace identification is firstly utilized to identify a model from input-output data of the CO2 capture system. The power plant flue gas is considered in the modeling as measured disturbance, so that its influence can be quickly removed by the predictive control system. The model predictive controller is then developed on the identified model to regulate the CO2 capture level and re-boiler temperature. To alleviate the effect of unknown disturbances and modeling mismatches, and achieve an offset-free tracking of the capture system, integral action is added by using an augmented state-space model in the controller design. Simulation results on an amine solvent-based post-combustion CO2 capture system demonstrates the effectiveness of the proposed controller.
A new distributed localization algorithm for ZigBee wireless networks

Node localization becomes an exciting research area for recently large emergence of ZigBee based wireless applications, where received signal strength indication is adopted as a coarse but simple method on range measurement. Compared with the centralized approach, distributed algorithm that nodes locally calculate their own position coordinates can significantly reduce location-related network traffic; however, this is an intensive process. Unlike commercial digital-hardware-block based method used in CC2431, we propose a novel distributed algorithm that can be implemented based on common 8-bit MCU. In this algorithm, instead of ‘log-normal’, ‘piecewise linear’ path loss model was established, which let only linear operation when estimating range from RSSI. Besides, min-max method, other than maximum likelihood estimation method, was used to simplify coordinate calculation. Furthermore, ZigBee compatible sensor node modules were developed to carry out the contrast experiments, and results demonstrate the new method has close or even better precision compared with basic algorithm, but with lower cost.
A hierarchical topological planner for multi-storey building navigation

In this paper, we present a hierarchical path planner for autonomous navigation of a tracked robot in buildings that have multiple storeys. The planner utilizes a multiple layered topological map that integrates both topological and metrical information to represent the multi-storey environment, which allows the robot to navigate between different storeys of the building efficiently while avoiding dynamic obstacles on the way. The high semantic levels of the map represent semantic places or areas while the low level metric graph is created on top of an occupancy grid, where the topological nodes serve as waypoints that assist the robot in the path planning. Based on the graph, the mission planner plans tasks hierarchically and each of the executing tasks is implemented as an active state in a Finite State Machine (FSM) to control the robot to complete the tasks. Simulations and realistic experiments have demonstrated the effectiveness of the proposed planner for multi-storey building navigation.
Research on quotation system of auto's stamping die

The traditional quotation of auto's stamping mold is carried on according to the accumulated experiences of professionals or applying traditional weighting method or computer-aided method of working-hours, because of various types of molds, complex structure, multi-factors of price impact, and big difficulty of quotation. In this study, in order to achieving more accurate quotation, the quotation system is designed based on parameter's optimization of weighting and working-hours method, meanwhile, quotation system based on fuzzy method of similarity comparison is designed by adopting fuzzy mathematics theory and prediction technology. In this work, the mathematic model, system architecture, and business logic of system implementation of mold pricing method of combining weighting, working-hours, with fuzzy similarity comparison methods are given. The computer-aided quotation system of auto's stamping mold is constructed by combining C/S model with B/S model. The system fully considers the features such as complex manufacturing technology and high accuracy in demand. The demand of stamping quotation of different users and different stamping mold types is satisfied based on main manufacturing crafts means.
System matching and simulation of dual-motor drive coupling for electric vehicles

The dual-motor drive system for electric vehicles is researched, which comprises two drive motors and coupling device. The dual-motor together provide power for the vehicle while the vehicle travels at a cruising speed or high constant speed. The main drive motor provides power to the vehicle during periods of peak torque demand such as vehicle acceleration or climbing. Taking 18t electric bus as example, do the parameters matching for dual-motor drive system. At last, the dynamic of the electric bus is simulated in Matlab/Simulink and the result demonstrates the effectiveness of the dual-motor drive system. The dynamic performance of the electric bus perfectly meets the need of the design target.
Principal object detection towards product image search

Online shopping is an attractive, convenient, and efficient shopping way for billions of web users. A disappointing fact is that it is usually difficult for users to find the products fitting their needs purely based on text search. Content-based product image search becomes a promising way to solve this problem. However, the presence of natural backgrounds and fashion models significantly affect the feature matching, which makes product image search a challenging task. To clean the background and minimize the influence of noises, in this paper, a graph-based principal object detection algorithm is proposed to extract the product items while removing backgrounds and noises. A product image retrieval system is then constructed to verify the effectiveness of the proposed approach. Experiments on a large scale dataset with 1.36 million product images crawled from Taobao demonstrate the proposed approach significantly improves the retrieval performance.