nils-herrmann/clean_scirepeval huggingface dataset:
On reducing both shift and capture power for scan-based testing

Power consumption in scan-based testing is a major concern nowadays. In this paper, we present a new X-fllling technique to reduce both shift power and capture power during scan tests, namely LSC-filling. The basic idea is to use as few as possible X-bits to keep the capture power under the peak power limit of the circuit under test (CUT), while using the remaining X-bits to reduce the shift power to cut down the CUT's average power consumption during scan tests as much as possible. In addition, by carefully selecting the X-filling order, our X-filling technique is able to achieve lower capture power when compared to existing methods. Experimental results on ISCAS'89 benchmark circuits show the effectiveness of the proposed methodology.
Design of compact dual-mode dual-band filtering power divider with high selectivity

A new design method for a compact dual-mode dual-band filtering power divider is proposed. To achieve two transmission poles in both of the two passbands, the odd- and even-mode resonant properties of the dual-mode resonator are employed in the design. By symmetrically locating four dual-mode resonators at both sides of the main transmission line and choosing the proper output topology, the introduced circuit can successfully realise the dual-band power division and filtering selectivity property. Two resistors are utilised to achieve good in-band isolation performance of the filtering power divider. For demonstration, a dual-band filtering power divider with two passbands centred at 2.2 and 2.7 GHz was designed and measured. Simulated and measured results are provided which show a good agreement.
Hardware Design of Fall Detection System Based on ADXL345 Sensor

In order to meet the demand for nursing care of the elderly, this paper introduces fall detection principle, overall composition, design scheme, main control circuit and the control program of a fall detection system based on ADXL345 sensor. The system selects MSP430F149 as the microprocessor to complete the signal analysis and processing functions, and judge whether the individual falls through the fall detection algorithm. The attitude angle which is related to the acceleration of the output of the ADXL345 sensor is considered as the judgment standard. According to the electrical signals change, the system can make accurate judgments, send out the alarm and start up the protective device. It has the characteristics of compact structure, simple and reasonable design, flexible control.
Preparation of the Bragg reflectors of tuneable thin film bulk acoustic wave resonators by RF sputtering

Electrically tuneable thin film bulk acoustic wave resonators have drawn much attention for their advantages of high Q factors, integrable feature and small sizes. Accurate controlling of the thickness of the Bragg reflectors directly affects the Q-factor of the resonators with solidly mounted structure. In this paper, the preparation method to precisely control the thickness of the Bragg reflectors by RF sputtering has been studied. The structure of W/SiO2 alternated layers with different thicknesses was successfully prepared by RF sputtering method. The film thicknesses showed good linearity over time. The deposition rates of two layers under different annealing conditions were derived.
A Web-App Auto-Testing System Based on Test-Flow and Control Constraints

Because of the fast growth of Web application and relative technology, the automatic testing for Web has become more and more complexity. This paper proposed an automatic system for Web-app functional testing which based on a XML description and also integrated the web pagespsila structure analysis. It improved the traditional way of record, and it can auto-generate test data and test cases by the constraints and the rules we defined in this paper. This system can record the path that user operated on a Web with all the pages passed by. Referring the definition of workflow, it defines a test-flow and described in XML. It can do test work as a user when flowing the test-flow with using the data which was been generated, so it has implemented a more automatic testing.
Adaptive Template for Parsing Object of Indoor Scene Image

In this paper, we propose an adaptive template for semantic labeling of indoor scene objects and estimating their oriented bounding facets (OBFs). The proposed adaptive template encodes prior geometric information of objects based on statistics of the training images. Given an input image, we utilize the adaptive template on the detected bounding boxes to initialize the raw labeling and OBF estimation of objects. To refine the initial results, multiple cubes/faces that follows geometric principles of adaptive template are generated to make up OBFs hypotheses. Each of the OBFs hypotheses is scored by the consistency matched with its corresponding semantic labeling result. The OBFs hypothesis that has the highest matching score with the corresponding labeling result is selected as the final parsing result. We evaluate our method on the bed, sofa and tea table categories, on both real and rendered indoor scenes. The experimental results show that our method has improved performance compared with the state-of-the-art detectors, and can give reasonable 3D interpretations of objects.
GFSK Demodulation Using Sequential Monte Carlo Technique

This letter applies the Sequential Monte Carlo (SMC) approach along with a low complex detection algorithm to non-coherently demodulate a Gaussian frequency shift keying (GFSK) signal in Bluetooth receivers. Sequential importance resampling (SIR) is used to estimate the state of the GFSK signal, while a low complex detection algorithm is used to decide on the received bit. SIR is the original and most used particle filtering algorithm, which approximates the filtering distribution by a weighted set of particles. The bit error rate (BER) analysis is used as the performance metrics of the proposed receiver at the physical layer. Applying SMC technique to GFSK demodulator shows significant performance improvement compared to several other existing techniques that are presented in the literature. In addition, it does not require a pre-detection filter, which is usually used to reject out-of-band interference. Simulation results show approximately 6 dB of BER improvement over the commonly used limiter discriminator with an integrator (LDI) receiver.
Qualitative mapping model of humming melody extraction

Some of the humming retrieval system and the qualitative mapping are introduced briefly. Combining with the music theory, a qualitative mapping model for extracting humming melody and its algorithm are given in this paper. The key points of the algorithm are the method to choose the criterion of the note segmentation dynamically and the dynamic measure to determine the pitch of a note. Experiments show that not only a better result of choosing flexibly and reasonably the criterion of the note segmentation can be determined, but also the note pitch can be extracted accurately. Eventually, the contour of humming melody can be achieved too
Fast and Accurate Mining the Community Structure: Integrating Center Locating and Membership Optimization

Mining communities or clusters in networks is valuable in analyzing, designing, and optimizing many natural and engineering complex systems, e.g., protein networks, power grid, and transportation systems. Most of the existing techniques view the community mining problem as an optimization problem based on a given quality function(e.g., modularity), however none of them are grounded with a systematic theory to identify the central nodes in the network. Moreover, how to reconcile the mining efficiency and the community quality still remains an open problem. In this paper, we attempt to address the above challenges by introducing a novel algorithm. First, a kernel function with a tunable influence factor is proposed to measure the leadership of each node, those nodes with highest local leadership can be viewed as the candidate central nodes. Then, we use a discrete-time dynamical system to describe the dynamical assignment of community membership; and formulate the serval conditions to guarantee the convergence of each node's dynamic trajectory, by which the hierarchical community structure of the network can be revealed. The proposed dynamical system is independent of the quality function used, so could also be applied in other community mining models. Our algorithm is highly efficient: the computational complexity analysis shows that the execution time is nearly linearly dependent on the number of nodes in sparse networks. We finally give demonstrative applications of the algorithm to a set of synthetic benchmark networks and also real-world networks to verify the algorithmic performance.
On bias compensation estimation for noisy AR process

This paper focuses on bias compensation estimation of autoregressive (AR) process in the presence of white noise. It is known that bias compensation principle (BCP) based method requires the estimate of unknown noise variance to compensate the bias of least-squares (LS) estimate to provide consistent AR parameter estimate. In this paper, estimation of noise variance in BCP based methods for noisy AR process estimation is discussed from a unified point of view. It is found that some BCP based methods can be explained in a unified form. Computer simulations are also presented to compare these BCP based methods.
Safety Assessment for Urban Mass Transit System Using Analytical Hierarchy Process

Based on the existing issues and status of urban mass transit (UMT) safety at home and abroad, many key influence factors for UMT safety are proposed in this paper. First, we have analyzed all relevant factors and causations of UMT safety under the human-machine-environmental system. Then, a safety assessment approach based on analytical hierarchy process is proposed in this paper for UMT operating security system. The multi-hierarchy valuation structure is established on the basis of key influence factors for UMT safety. The proposed approach can adjust the balance of safety assessment factors, and provide decision-making advices for the department managers for safety management and safety assessment.
Automatic Dangerous Driving Intensity Analysis for Advanced Driver Assistance Systems From Multimodal Driving Signals

Intelligent vehicles use advanced driver assistance systems (ADASs) to mitigate driving risks. There is increasing demand for an ADAS framework that can increase driving safety by detecting dangerous driving behavior from driver, vehicle, and lane attributes. However, because dangerous driving behavior in real-world driving scenarios can be caused by any or a combination of driver, vehicle, and lane attributes, the detection of dangerous driving behavior using conventional approaches that focus on only one type of attribute may not be sufficient to improve driving safety in realistic situations. To facilitate driving safety improvements, the concept of dangerous driving intensity (DDI) is introduced in this paper, and the objective of dangerous driving behavior detection is converted into DDI estimation based on the three attribute types. To this end, we propose a framework, wherein fuzzy sets are optimized using particle swarm optimization for modeling driver, vehicle, and lane attributes and then used to accurately estimate the DDI. The mean opinion scores of experienced drivers are employed to label DDI for a fair comparison with the results of our framework. The experimental results demonstrate that the driver, vehicle, and lane attributes defined in this paper provide useful cues for DDI analysis; furthermore, the results obtained using the framework are in favorable agreement with those obtained in the perception study. The proposed framework can greatly increase driving safety in intelligent vehicles, where most of the driving risk is within the control of the driver.
A light emitting diode’s chip structure with low stress and high light extraction efficiency

Undesired residual stress always exists in light emitting diode (LED) after the process of metalorganic chemical vapor deposition (MOCVD) due to difference in thermal expansion coefficient of different layers, doping, and lattice mismatch. Residual stress would mostly induce defects in the process of LED chips, the packaging, accelerated testing and their applications. The influence of strain/stress on the optical properties of GaN based light emitting diode's (LED) chip is studied by molecular dynamic modeling. By simulation with finite element method (FEM), it is found that the stress caused by differences in thermal expansion coefficiency could be decreased by micro groove structures. The light extraction efficiency of LED chip could enhance with suitable micro structures.
Biomimetic modeling approach for cranial microstructure based on micro-CT technology

For the limits of the symmetrical structure and uncontrollability in current cranial microstructure modeling, a biomimetic modeling approach based on micro-CT technology is proposed in this paper. At the beginning, the natural cranial sample is scanned by micro-CT technology and reconstructed using reverse engineering. Then through the study of the reconstructed sample, it is found that the cranial microstructure is configured by three parts of special architecture nets, cavity and connecting pipe. So after the parametric analysis, modeling to the three parts respectively, and assembly them in a certain form, the partial biomimetic model of the cranial microstructure was established. The results indicate that the biomimetic model and the natural cranial microstructure show high similarity.
A Multi-grade evaluation model for traffic level of service

Regional traffic level of service (LOS) evaluation is a sticking point in urban traffic research. The objective of this study is to develop a model for estimating LOS of regional traffic. Firstly, we presented one method applied in the micro-layer traffic. Secondly, one macro-layer method was constructed, it based on the result of micro-layer. We combine these two layers into a single Multi-grade evaluation model for traffic level of service. The multi-grade evaluation model owns two layers including the micro-layer, which is used to distinguish the segment traffic status, the macro-layer, which is to estimate regional traffic status. The proposed model is applied to several city areas, and the results show its validity.
Scalable service differentiation using purely end-to-end mechanisms: features and limitations

We investigate schemes for achieving service differentiation via weighted end-to-end congestion control mechanisms within the framework of the additive increase/multiplicative decrease (AIMD) principle, and study their performance as instantiations of the TCP protocol. Our first approach considers a class of weighted AIMD algorithms. This approach does not scale well in practice because it leads to excessive loss for flows with large weights, thereby causing early timeouts and a reduction in throughput. Our second approach considers a class of loss adaptive weighted AIMD algorithms. This approach scales by an order of magnitude compared to the previous approach, but is more susceptible to short-term unfairness and is sensitive to the accuracy of loss estimates. We conclude that adapting the congestion control parameters to the loss characteristics is critical to scalable service differentiation; on the other hand, estimating loss characteristics using purely end-to-end mechanisms is an inherently difficult problem.
Harmony search resampling particle filter

Although particle filters have been widely applied from various fields, the impoverishment and degeneration of particle are important factors affecting the performance of particle filters. In this paper, harmony search was introduced into the particle resampling to enhance the algorithm. By updating the vector of harmony memory through the weight based multinomial resampling, the impoverishment and degeneration of particle was efficiently reduced. Experimental results showed that the harmony search resampling particle filters had more accurate filtering results than other typical filters such as system resampling filter.
Research of Reverse Logistics Information Management System Based on B/S+C/S

With the development of economic society, people pay more attention to the requirements of environment protection, reverse logistics gradually attract the interest of people. So the effect of MIS toward reverse logistics becomes much obvious. The traditional development model B/S or C/S structure can not satisfy the reverse logistics system information sharing and security requirements. This article describes the system function model design, and logic structure design and safety design is investigated. The design and realization method of reverse logistics management information system was also put forward.
Image retrieval using scene graphs

This paper develops a novel framework for semantic image retrieval based on the notion of a scene graph. Our scene graphs represent objects (“man”, “boat”), attributes of objects (“boat is white”) and relationships between objects (“man standing on boat”). We use these scene graphs as queries to retrieve semantically related images. To this end, we design a conditional random field model that reasons about possible groundings of scene graphs to test images. The likelihoods of these groundings are used as ranking scores for retrieval. We introduce a novel dataset of 5,000 human-generated scene graphs grounded to images and use this dataset to evaluate our method for image retrieval. In particular, we evaluate retrieval using full scene graphs and small scene subgraphs, and show that our method outperforms retrieval methods that use only objects or low-level image features. In addition, we show that our full model can be used to improve object localization compared to baseline methods.
Design and Implementation of a Vision-Based Motion Capture System

Motion Capture has been widely used in many fields such as animation and game production. This paper describes the scheme and implementation of a self-designed vision-based motion capture system. This system is set up based on a Client/Server network structure. The client software tracks every marker attached to the actor’s body and sends the results to the server in real-time. The server software recovers every joint’s 3D position and shows the capturing results simultaneously. It can also convert the 3D position data into BVH file data.
Experimental characterization of the diode-type polysilicon loads for CMOS SRAM

Experimental characterization of the diode-type n/sup +/-p-n/sup +/ poly-Si loads for SRAM applications demonstrates that the resistance of the structure and its response to the bit-line voltages are dominated by such properties of the parasitic thin-film transistor associated with this device as fixed positive charge and 'gate' oxide thickness. Topographical effects observed in this study are interpreted in terms of the thickness variation of a dielectric overlaying the poly-Si feature and the fixed positive charges present in this dielectric in the vicinity of the poly-Si surface.
Monte Carlo Simulation of Terahertz Radiation Waveform from SI-GaAs Photoconductive Antennas

A self-consistent Monte Carlo approach is used to simulate the time resolved terahertz radiation from Si-GaAs photoconductive antenna. An adjustable energy and width of fs laser pulse is applied to illuminate Si-GaAs-based photoconductive antennas. The THz wave profile by simulation is similar to THz radiation waveform from experiment. We analyzed carrier dynamics in photoconductive antenna, and interpreted the mechanism that the width of emitted THz pulse was much wider than the pump pulse. And the mechanism that THz bipolar waveform emitted from Si-GaAs-based photoconductor trigged by high energy optical pulse at lower biased voltage was studied.
Analysis and Evaluation of Connectivity Reliability for Dynamic Transportation Network

Facing to the uncertainty problem of dynamic transport network for the big cities, this paper begins from the viewpoint of connectivity reliability, analyses evaluation method for connectivity reliability, and put forward LOS-based connectivity reliability evaluation model (LOS-CRE model), that integrates traffic level-of-service into reliability evaluation, and that is reference to grades of level of service classified in HCM (Highway Capacity Manual). Meanwhile this paper considers both the actual traffic situation and LOS grading strategy. The specific congestion condition of urban traffic decides a certain level(grade E)as a limit, whether the LOS at some time meets this certain level or not determines the road functions or not, and then make use of the road function situation to calculate the connectivity reliability for any two points (Origin and Destination) in the network. Compared with existed methods, the LOS-CRE model reduces calculation complexity, which process is intuitive and reliable, and which evaluation result will ring significance for the traffic management. In this paper, as experiment demonstration, we pick up a region of Beijing for an example to exhibit the calculation of connectivity reliability for the regional dynamic transportation network. Lastly, we draw the conclusions and present our opinions on the future research work.
Effect of Quantum Dot Scattering and Absorption on the Optical Performance of White Light-Emitting Diodes

Quantum dots (QDs) show a great potential for light-emitting diodes (LEDs) packaging, which still face great challenges compared with the matured phosphor downconversion materials. These are probably caused by the unique scattering and absorption properties of QDs, which are extremely different to the traditional phosphor due to their several nanometers size, while their effect on QDs-converted LEDs (QCLEDs) is barely studied. In this paper, we have experimentally and theoretically investigated the effect of scattering and absorption of CdSe/ZnS QDs on the optical performance for QCLEDs by comparing with the traditional yttrium aluminum garnet phosphor. Results indicate that the strong absorption (reabsorption) of QDs causes low radiant efficacy and stability for QCLEDs; their weak scattering also leads to a low color uniformity. It demonstrates that their unique scattering and absorption properties are key factors leading to low optical performance of QCLEDs compared with the traditional phosphor-converted LEDs. For purpose of gaining the white LED with high efficiency and stability, it is highly suggested to use a low QD concentration to reduce the reabsorption loss and the total internal reflection loss. We believe that this paper can provide a better understanding of improving the optical performance for QCLEDs from the prospective of scattering and absorption. In the future, it is important to use low QD concentration to gain high-performance white LEDs with high downconversion efficiency by optimizing packaging structures.
Parameter estimation of multi-dimensional hidden Markov models - a scalable approach

Parameter estimation is a key computational issue in all statistical image modeling techniques. In this paper, we explore a computationally efficient parameter estimation algorithm for multi-dimensional hidden Markov models. 2-D HMM has been applied to supervised aerial image classification and comparisons have been made with the first proposed estimation algorithm. An extensive parametric study has been performed with 3-D HMM and the scalability of the estimation algorithm has been discussed. Results show the great applicability of the explored algorithm to multi-dimensional HMM based image modeling applications.