nils-herrmann/clean_scirepeval huggingface dataset:
Multifunction Electromagnetic Transmitting System for Mineral Exploration

Electrical and electromagnetic methods have long played an important role in mineral exploration. For example, in active source prospecting methods, when measuring the values of many electrical parameters, the signal-to-noise ratio can be improved by increasing the transmitting power. In this paper, we present a multifunction borehole ground electromagnetic transmitting system that transmits rectangular waves at a frequency of 0.01–10 kHz with a frequency error less than 10−8 Hz @ 1 Hz (depending on the high-precision temperature compensation crystal) and the initial synchronization error between the transmitter and receiver is less than $ \pm \text{0.1}\,\mu {\text{s}}$. During operation, either the maximum transmitting voltage output can reach 950 V or the maximum transmitting current can exceed 90 A, but both cannot be achieved simultaneously. We tested the transmitting system at its maximum power output continuously for over 8 h and the power output was more than 48 kW at a current above 60 A. The energy was delivered above ground or underground using existing drill casings to produce the high-power transmissions. The field experiments show that the system meets the demands of the controlled-source audio-frequency magnetotelluric and induced polarization methods used in mineral exploration.
Panorama Painting: With a Bare Digital Camera

This paper presents the design and implementation of an approach to creating a single-viewpoint full view panorama photograph from a set of image sequence. To ensure the simplicity for both shooting and stitching, input images are individual frames extracted from a panning video sequence. The ordered approach also proves to be computationally less expensive than the case where input images are disordered. The video sequence can be recorded with a digital camera. For most digital cameras, the quality of video sequence (typically 640 by 480, 25 frames per second) is good enough to provide acceptable resolution and frame rate. The approach discussed in this paper comes with an implementation, which is least human-involved.
Optimized address assignment with array and loop transformations for minimizing schedule length

Reducing address arithmetic operations by optimization of address offset assignment greatly improves the performance of digital signal processor (DSP) applications. However, minimizing address operations alone may not directly reduce code size and schedule length for DSPs with multiple functional units. Little research work has been conducted on loop optimization with address offset assignment problem for architectures with multiple functional units. In this paper, we combine loop scheduling, array interleaving, and address assignment to minimize the schedule length and the number of address operations for loops on DSP architectures with multiple functional units. Array interleaving is applied to optimize address assignment for arrays in loop scheduling process. An algorithm, address operation reduction rotation scheduling (AORRS), is proposed. The algorithm minimizes both schedule length and the number of address operations. with to list scheduling, AORRS shows an average reduction of 38.4% in schedule length and an average reduction of 31.7% in the number of address operations. Compared with rotation scheduling, AORRS shows an average reduction of 15.9% in schedule length and 33.6% in the number of address operations.
Temperature Dependence of Kerr Constant for Water at 658 nm and for Pulsed Intense Electric Fields

The temperature dependence of the Kerr constant for water has been determined over the range 19 °C-45 °C at a wavelength of 658 nm. This paper presents the experimental arrangement used for this purpose and the data obtained, for which a polynomial fit is provided. A formula is also suggested to help estimate the variation of the Kerr constant for water with both temperature and wavelength.
Movie2Comics: Towards a Lively Video Content Presentation

As a type of artwork, comics is prevalent and popular around the world. However, despite the availability of assistive software and tools, the creation of comics is still a labor-intensive and time-consuming process. This paper proposes a scheme that is able to automatically turn a movie clip to comics. Two principles are followed in the scheme: 1) optimizing the information preservation of the movie; and 2) generating outputs following the rules and the styles of comics. The scheme mainly contains three components: script-face mapping, descriptive picture extraction, and cartoonization. The script-face mapping utilizes face tracking and recognition techniques to accomplish the mapping between characters' faces and their scripts. The descriptive picture extraction then generates a sequence of frames for presentation. Finally, the cartoonization is accomplished via three steps: panel scaling, stylization, and comics layout design. Experiments are conducted on a set of movie clips and the results have demonstrated the usefulness and the effectiveness of the scheme.
Study on crystalline morphology and breakdown property of micro-, nano-, micro-/nano- composites

In order to investigate the effect of adding micro- and nano- inorganic particles in the polymer on the morphology and dielectric properties, the low density polyethylene (LDPE) was used as the matrix, the inorganic micro and nano silicon dioxide (SiO2) were selected as inorganic fillers, origin LDPE and M-SiO2 and N-SiO2 and MN-SiO2 composite materials were respectively prepared by melt blending, and the influence of preparation process of M/N-SiO2 and N/M-SiO2 in different ratio and adding sequence on composites were also discussed. The crystalline morphology and breakdown properties of the composites were investigated. The experimental results show that the crystal grain size of the composites with inorganic fillers obviously reduces and the distribution is more uniform comparing with LDPE. The average crystal grain size of N-SiO2 is 23.1μm which is the smallest among all samples and that of origin LDPE is the biggest about 46.5μm in size. The DC breakdown field strength of the composites with SiO2 in different size and contain was significantly higher than that of LDPE, the breakdown strength of N-SiO2 composites is the highest, which is 338.8 kV/mm and 20.1% higher than LDPE. The results of comparative experiments show that the preparation process of the micro- and nano-composites has obvious influence on their properties.
Using chaos eye method to diagnose power capacitors

This study focused on the measurement and diagnostic analysis of partial discharge in power capacitors operating under prolonged periods of high voltage. An off-line test was conducted on two power capacitors, which were subjected to defect preprocessing before the experiment. The partial discharge test of the terminal to the outer casing was carried out using a 24kV high voltage transformer. The voltage of the power discharge, after which the voltage signals of the test voltage and the partial discharge were extracted. The characteristics of the discharge signal were identified using an oscilloscope. The chaos synchronization detection method was then employed to establish a chaotic error scatter plot for the discharge voltage he gravity (chaos eye) of the error scatter plot was used as the fault diagnosis feature. The advantage of this approach was the drastic reduction of the amount of data for feature extraction, and the effective detection of the slight discharge signal variation in power capacitors, thereby anticipating their operation and enabling the implementation of preemptive contingency measures to avoid major accidents.
Overview of pulsed power researches at CAEP

Pulsed power researches for military and civil applications have been conducted at China Academy of Engineering Physics (CAEP) for more than fifty years. The pulsed power research activities include development of pulsed power components such as different kinds of high voltage switches, series of pulsed power sources and pulsed X-ray machines, high current accelerators for Z-pinch and flash X-ray radiography as well as medical application, electro-magnetic launch and so on. The most recent progress of pulsed power researches at CAEP will be presented.
Image-Based Three-Dimensional Human Pose Recovery by Multiview Locality-Sensitive Sparse Retrieval

Image-based 3-D human pose recovery is usually conducted by retrieving relevant poses with image features. However, it suffers from the high dimensionality of image features and the low efficiency of the retrieving process. Particularly for multiview data, the integration of different types of features is difficult. In this paper, a novel approach is proposed to recover 3-D human poses from silhouettes. This approach improves traditional methods by adopting multiview locality-sensitive sparse coding in the retrieving process. First, it incorporates a local similarity preserving term into the objective of sparse coding, which groups similar silhouettes to alleviate the instability of sparse codes. Second, the objective function of sparse coding is improved by integrating multiview data. The experimental results show that the retrieval error has been reduced by 20% to 50%, which demonstrate the effectiveness of the proposed method.
Dynamic Scratch-Pad Memory Management with Data Pipelining for Embedded Systems

In this paper, we propose an effectivedata pipelining technique, SPDP (scratch-pad datapipelining), for dynamic scratch-pad memory (SPM)management with DMA (Direct Memory Access). InSPDP, we group multiple iterations of a loop intoa block for SPM allocation, and implement a datapipeline by overlapping the execution of CPU instructionsand DMA operations. We have implementedour SPDP technique into the IMPACT compiler,and conduct experiments using a set of benchmarksfrom DSPstone, Mibench and Mediabench on thecycle-accurate VLIW simulator of Trimaran. Theexperimental results show that our technique achievessignificant performance improvement compared withthe previous work.
Using ENN-1 to Inspect the Air Pollution of Automobile Exhaust by Remote Sensing Data

This research uses the extension neural network type-1 (ENN-1) method for air pollution inspected by remote sensing data of automobile's exhaust. The outdated automobiles emit exhaust as part of the moving air pollutants. To lessen the air pollution effectively and improve the efficiency of remote sensing tools, this paper develop a automatic inspected method based on the ENN-1 and using the data of automobile exhausted telemeter, the ENN-1 can embed the salient features of parallel computation and learning capability. The experimental results show that the proposed method has less learning time, high classificatory accuracy rate, and fault-tolerant than the other methods
Development of centering alignment detector for high precision seamless steel tubes

The paper described the automatic alignment detector system composition of centering machine for high-precision seamless steel tubes, including hardware configuration and software structure. The core technology of the system is one new sub-pixel solution technique for circle parameters. Detailed calculation diagram of circle parameters solution and centerline adjustment approach are presented. The efficiency of circle parameter solution technique is validated by comparison with classic circle detection method. It is proved to have fast processing speed without decreasing its accuracy. The contribution of this study is to build up measurement system and realize high precision and rapid centering alignment detection.
Graphical modelling of pinched hysteresis loops of memristors

In this study, a graphical modelling approach of the pinched hysteresis loops exhibited by memristors is presented. This method provides a tool to emulate the hysteresis loop pinched at the origin, with the lobe area varying with the excitation frequency. The direction of the pinched hysteresis loop can be controlled. This graphical modelling method provides an alternative to describe the behaviour of memristors without deriving the coupled non-linear differential equations typically required for physical memristors. The method has been successfully applied to model the Hewlett–Packard memristor device.
AWEDF: An Architecture-Aware Execution and Debugging Workflow for a Highly Reliable Chip

As the technology node of the semiconductor chip enters the nano region, which can help very large scale integration (VLSI) circuits achieve better integration of production density which are companied with faster system operation speed, the embedded industry has been significantly boosted up. Despite the embedded industry trend to embrace the nano region technology, research is lacking on combining the architecture of the chip with the specific workflow to enhance the performance. This paper illustrates a system, focusing on a specific chip, that provides an execution and debugging workflow with a visibility interface to allow user access and operate. Since the existing workflow is primarily applied to common system-on-chip (SoC), and for chips requiring high reliability and execution and energy efficiency that make it difficult to execute programs with good performance, a workflow designed for the unique hardware architecture of the chip is proposed to make good use of hardware. Apart from the high performance of the system, the user-friendly condition is taken into consideration to reduce the developing difficulties. When assessing systems, while correctness,execution and energy efficiency are guaranteed, and, due to the design of workflow, users can conveniently operate the chip even for a beginner, while consuming roughly the same time as or even slightly less time than programming directly on the chip.
OFDMA Uplink PAR Reduction via Tone Reservation

Orthogonal frequency division multiple access (OFDMA) has been widely recognized as a promising solution for broadband wireless networks. Unfortunately, in OFDMA uplink scenarios, high peak-to-average power ratios (PARs) dramatically degrade the power efficiency of the mobile users. This turns out to be one of the most critical problems when implementing OFDMA systems. In this paper, we propose efficient PAR reduction schemes based upon tone reservation. We show by simulation that the PAR can be significantly reduced without incurring multiple- access interference and with a very small loss in bandwidth.
3-D Object Retrieval With Hausdorff Distance Learning

In view-based 3-D object retrieval, each object is described by a set of views. Group matching thus plays an important role. Previous research efforts have shown the effectiveness of Hausdorff distance in group matching. In this paper, we propose a 3-D object retrieval scheme with Hausdorff distance learning. In our approach, relevance feedback information is employed to select positive and negative view pairs with a probabilistic strategy, and a view-level Mahalanobis distance metric is learned. This Mahalanobis distance metric is adopted in estimating the Hausdorff distances between objects, based on which the objects in the 3-D database are ranked. We conduct experiments on three testing data sets, and the results demonstrate that the proposed Hausdorff learning approach can improve 3-D object retrieval performance.
Compact modeling solution of layout dependent effect for FinFET technology

We successfully developed and verified a complete compact model solution for layout dependent effect (LDE) of FinFET technology. LDE has significant impact on the device performances mainly due to the application of stressors and aggressive device scaling. With LDE, performance degradation may be up to 10% or more. In this work, compact model solution for Length of Oxidation (LOD), Well Proximity Effect (WPE), Neighboring Diffusion Effect (NDE), Metal Boundary Effect (MBE), and Gate Line End Effect (GLE) were delivered. This solution was implemented successfully in BSIM-CMG for efficient circuit simulation.
Single-instruction based programmable memory BIST for testing embedded DRAM

With the increasing functionalities in modern SoC design, the need for dense embedded memory is growing. The test issue for this high density embedded DRAM (eDRAM) macro in a complex integration environment is becoming an important issue. In this work, we propose a single-instruction based programmable memory BIST for testing an eDRAM macro. Based on our BIST design, the supported memory testing algorithms are classified into five groups. Moreover, a compact instruction is proposed to encode the operation of each group and a two-level address generator is adopted to produce all the required addressing indexes. The proposed architecture provides a better design tradeoff in terms of the area overhead and the programmability compared with the existing work.
Synchronous Flux Weakening Control With Flux Linkage Prediction for Doubly-Fed Wind Power Generation Systems

Under grid-voltage dips, there exist dc and negative sequence components in the stator and rotor flux of doubly-fed induction generator (DFIG). As a result, higher transient overcurrent is generated in the rotor. To enhance the low-voltage ride-through (LVRT) ability of the DFIG, a synchronous flux weaken control strategy with flux linkage prediction is proposed to suppress the transient overcurrent. In the proposed control strategy, the deadbeat predictive control is used to realize rapid synchronization and weak interaction between the stator and rotor flux by flux linkage prediction under grid-voltage dips. A series of research is carried out on a typical 1.5-MW DFIG system, and comparisons are made with the LVRT control strategy based on proportional-resonant (PR) controller to validate the proposed control strategy. The results indicate that the proposed control strategy is effective in suppressing overcurrent in the stator and rotor and reducing oscillations in torque, which largely improves the performance of the DFIG during grid-voltage dips.
The research about the influence of urbanization and industrialization on land financial dependence of local government in China

Urbanization and industrialization strongly affect the land finance of local government and the effect varies in different stages of economic development in China. Based on the provincial panel data from 2005 to 2009, this study divides the 31 provinces in China into I, II and III economic development stages and make variance analysis between different regions. After analyzing, the result indicates that the land financial dependence in China is universally inevitable currently and regional differences of the effects exist. In the regions at Stage I, urbanization and industrialization exert little effect on land finance; whilst in regions at Stage II, with the rise of urbanization and industrialization, their effects on land financial dependence ascend gradually. In addition, the degree of effects of industrialization is larger than that of urbanization in regions of Stage II. However, in regions at Stage III, the dependence of urbanization and industrialization on land finance begins to detach. That is, the dependence rises with the rising of urbanization and drops with the rising of industrialization, and this detach is in keeping with the fact that urbanization lags behind industrialization in China. According to above results, different economic regions should adopt differentiated land-use policies in future.
Trust Agent-Based Behavior Induction in Social Networks

The essence of social networks is that they can influence people's public opinions and group behaviors form quickly. Negative group behavior influences societal stability significantly, but existing behavior-induction approaches are too simple and inefficient. To automatically and efficiently induct behavior in social networks, this article introduces trust agents and designs their features according to group behavior features. In addition, a dynamics control mechanism can be generated to coordinate participant behaviors in social networks to avoid a specific restricted negative group behavior.
HLPA: A hybrid label propagation algorithm to find communities in large-scale networks

Fast detecting communities is challenging in large-scale real-world social networks and an important task in many scientific domains, such as Complex Networks and Social Network Analysis. In this paper, we propose a Hybrid Label Propagation Algorithm (HLPA) for finding communities on large-scale real-world social networks. And we conduct our experiments on real-world social networks datasets and get meaningful community results. Our method can get detection results on large-scale networks significantly fast, due to the following two benefits. The first is that our near linear algorithm HLPA is using a novel hybrid updating scheme, label decaying strategy and different initialization methods on different networks to improve the quality and scalability for detecting communities. And the second is that this is the first attempt implementation at community detection on the lightning-fast cluster computing framework Dpark, which is a Python version of Spark. Through experiment, we compare our algorithm with the state-of-art algorithms, and have confirmed our algorithms' superiority and universality for working on unweighted overlapping community detection of large-scale real-world social networks.
Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder

Existing video hash functions are built on three isolated stages: frame pooling, relaxed learning, and binarization, which have not adequately explored the temporal order of video frames in a joint binary optimization model, resulting in severe information loss. In this paper, we propose a novel unsupervised video hashing framework dubbed self-supervised video hashing (SSVH), which is able to capture the temporal nature of videos in an end-to-end learning to hash fashion. We specifically address two central problems: 1) how to design an encoder–decoder architecture to generate binary codes for videos and 2) how to equip the binary codes with the ability of accurate video retrieval. We design a hierarchical binary auto-encoder to model the temporal dependencies in videos with multiple granularities, and embed the videos into binary codes with less computations than the stacked architecture. Then, we encourage the binary codes to simultaneously reconstruct the visual content and neighborhood structure of the videos. Experiments on two real-world data sets show that our SSVH method can significantly outperform the state-of-the-art methods and achieve the current best performance on the task of unsupervised video retrieval.