nils-herrmann/clean_scirepeval huggingface dataset:
A Power-Aware Cloud Architecture with Smart Metering

With the growing interest of cloud computing and carbon emission reduction, how to build energy efficient cloud architecture becomes a crisis issue for service providers. In this paper, we propose a power-aware cloud architecture based on DRBL (Diskless Remote Boot in Linux), cpufreqd and xenpm. We also introduce a low-cost smart metering system based on open hardware Arduino board. Composing with existing technique, such as Dynamic Voltage Frequency Scaling (DVFS), ACPI, diskless design and RAM disk storage, our experiment results show that this architecture will reduce energy consumption from 4 to 11% when running CPU-intensive applications. In conclusion, this paper reveals that service providers could benefit from diskless design and RAM disk storage if their applications are CPU-intensive.
A Duplication Software for Cloud-Based Web Site: An Example of Google Sites

The cloud technologies are popular and enhanced by most vendors. Cloud services can share resources ubiquitously even some of them are free of charge. Most users meet normal operating flows in the cloud environment and must face the derived problems after one of the potential problems is occurred. One of the potential problems for cloud services is data lose. However, it is difficult for vendors to guarantee no data missing anytime. The research team proposes an intelligent cloud-based backup service (CBS) to duplicate the specific web site that is generated by the Google Sites environment and to decrease the data lose possibility. This service is designed by Java programing language and some Java libraries, such as HtmlUnit and jsoup parser, as well as can be executed on most operating systems. The downloadable web pages are shown by tree structure and the original cloud-based web addresses are replaced by local file folder locations, respectively. Some specific eXtensible Hypertext Markup Language (XHTML) tags that are created by Google Sites are extra processed by the CBS. The Google might not release enough white documents for Google Sites during our development period. However, the proposed service can still efficiently backup specific web site that is constructed by Google Sites and let users save their cloud web site in their local storages. Hence, it is necessary for cloud vendors to harmonize a series of commercial standards for further engineering utilization.
Improved bwmorph Function in the MATLAB Image Processing Toolbox for Fast Computation of Repeated Morphological Dilations and Erosions

In applications, morphological operations such as dilation and erosion are executed consecutively for a number of times. Direct use of the existing MATLAB functions for this task is time consuming. To accelerate such repeated dilations and erosions, improving measures are proposed. Binary image pixels are categorized into open feature pixels, closed feature pixels, and background pixels. By introducing a status matrix storing the category of each pixel and manipulating an open pixel list, each single operation of the repeated dilations or erosions is restricted on those pixels where the operation has real effects, and thus eliminate redundant and unnecessary computations. Experimental results show that the proposed approach is effective, and the repeated operations are significantly accelerated.
High-speed disturbance-free nonvolatile flip-flop based on complementary polarizers

This paper presents a hybrid CMOS/magnetic nonvolatile flip-flop (NVFF) for standby-power-critical and quick-startup applications. Different from conventional magnetic NVFFs, which are based on the two-terminal magnetic tunnel junction (MTJ), the proposed NVFF employs the complementary-polarizer magnetic tunnel junction (CPMTJ) to introduce the non-volatility. The writing and sensing circuits of CPMTJ are separately merged into the master stage of the NVFF to perform store and restore operations when the power turns on/off. In addition, the proposed NVFF is designed to operate as fast as the conventional CMOS flip-flop in the active mode. For performance evaluation of the proposed structure, SPICE model of CPMTJ is developed based on the theories of spin-transfer-torque (STT) switching and tunneling magnetoresistance effect, and then simulations are conducted in comparison of the conventional magnetic NVFF. Simulation results show that the proposed NVFF achieves 59% faster storing speed under iso-writing transistor width condition and 57% reduced storing energy for the same storing speed. By utilizing the cancellation of opposite spin-transfer torques, the proposed structure is expected to achieve a fully disturbance-free restore operation. Moreover, a 4GHz toggling speed in the active mode is demonstrated in SPICE pre-layout simulations using 45nm CMOS technology.
Parameter estimation of disk drive servo system using a hybrid simplex differential evolution algorithm

To accurately maintain the head position along the center of the track, determining the optimal parameters of the disk drive servo control system is one of most important works. In this paper, a hybrid optimization algorithm incorporated Nelder & Mead (NM) simplex method into the differential evolution (DE) algorithm was presented to the optimum parameter estimation of a disk drive servo system. This hybrid procedure performed the exploration with DE and the exploitation with the NM simplex method. Three experiments under the different conditions of command signal, sampling period and measuring noises were used to test the effectiveness of the proposed approach. The experiment results demonstrate that the hybrid optimization algorithm is superior to the two original search techniques (i.e. NM and DE) in terms of solution quality and convergence rate, and is an effective method for the parameter estimation of a control system.
Data Management at Kenting's Underwater Ecological Observatory

The management of real-time streaming data in large-scale collaborative applications presents major processing, communication and administrative challenges. To that end, an open-source RBNB DataTurbine provides an excellent basis for developing robust streaming data middleware. The current RBNB DataTurbine streaming data middleware system satisfies a core set of critical infrastructure requirements including reliable data transport, the promotion of sensors and sensor streams to first-class objects, a framework for the integration of heterogeneous instruments, and a comprehensive suite of services for data management, routing, synchronization, monitoring, and visualization. As a part of PRAGMA telescience group, in collaboration with the National Center for High- Performance Computing (NCHC) Taiwan, researchers at the San Diego Supercomputer Center (SDSC) deployed RBNB DataTurbine-based system to acquire data from underwater cameras (in the ocean) at Renting. More specifically, we describe a system that integrates sensors (underwater video cameras) with computing and storage Grids to create a complete fabric for conducting e-Science. The system is currently used for observation by marine research scientists at the Research Center for Biodiversity, Academia Sinica in Taiwan. The described system increased performance and availability of the captured videos and we are, so far, pleased with its results.
A peer-to-peer video-on-demand system using multiple description coding and server diversity

We propose a video streaming system that uses many ordinary computers (peers) as servers, which is less costly and more scalable than using a single or a few dedicated servers. To circumvent frequent peer disconnects and limited peer up-link bandwidth, each video is coded into multiple descriptions, which are distributed over multiple peers. The system serves a client request by streaming multiple descriptions of the requested video from separate peers. Using the MD-FEC coding scheme, and simple models for peer disconnects, reconnects and for searching replacement serving peers after a peer disconnect, we simulated video streaming in such a system. Our results show significant benefits in using a large number of descriptions and serving peers.
Cvus: A Computer Vision-understanding System

This paper presents a Lisp-based system for understanding the computer vision (CVUS). The system is basicly composed of four parts: Knowledge Base (KB), Image-Under- standing Modules (IUM), Image Data Base (IDB) and a Master Control Program (MCP). There are two kinds of knowledge in the KB, rules and frames. The rule includes the declarative rule and the image rule. The frame is an object knowledge code. There are two kinds of frames in the system: the concept frame and the rule frame. The concept frame is used for representing a basic vision concept. The rule frame is used for representing the relative rules. The IUM is mainly composed of two parts: image precessing and reasoning. The main purpose of the image processing is to identify the sense elements and set up their relationship. The inference mechanism uses backward chaining control strategy and the inference model adopts the inexactly reasoning model. There are four kinds of image data in the IDB. They are original vision image data, labeled image data, basic elements data and logical relationship data. The relation model is adopted to organize the data. The MCP coordinates the different parts in the system,,establishes the synchronization and chooses at appropriate processing model to perform the suitable computer vision- understanding procedure.
New Method of Character Relations Auto-Extraction

A new method of character relations auto-extraction from Chinese text set is proposed in this paper. In this method, characters and their relations are extracted from sentences and documents by computing the relative strength and attributive weight of relative properties. Each dispersed relation is organized and represented by the relative coefficient. For the purpose of exhibiting relations visually, the relations map, which describes characters and relative properties between them, could be constructed based on the coefficients. The experiment of relation extraction shows that the precision and recall of this method are 85.56% and 61.94%; the experiment of relations map shows that the precision and recall are 94.74% and 52.94% of level-1, 96.88% and 59.62% of level-2, respectively. In this paper, we propose a new method of character relations extraction from Chinese text set automatically. The method extracts and organizes the character relations which are dispersed in the text set. Moreover, we extract the characters which are nearby the center character in relation, and construct a visual character relations map to describe the relations and the relative properties between them.
An integrated boost converter with maximum power point tracking for solar photovoltaic energy harvesting

An integrated boost converter with maximum power point tracking for solar photovoltaic (PV) energy harvesting has been proposed. The maximum power point tracking (MPPT) function is realized with analog circuits, instead of using a microprocessor. In the proposed chip, the output power of the PV modules is controlled by modulating the on-time of the boost converter. The chip was designed and fabricated by using TSMC 0.18 μm 1P6M mixed-signal CMOS process. The total chip area is 1.08×1.25 mm2, which is much smaller than that with a microprocessor. The measured maximum tracking efficiency is 90%.
Dual-Wavelength 2- $\mu \text{m}$  Fiber Laser With Coupled Fiber Bragg Grating Cavities

We develop dual-wavelength 2-μm fiber lasers with coupled cavity configurations based on fiber Bragg gratings and study their output performance and emission dynamics. Efficient cavity-coupling management leads to different dual-wavelength operation regimes. Over 3 W of output power is realized at both 1942 and 2020 nm, and a power ratio of the 1942 nm to the 2020 nm laser emissions can be tuned from 24.9% to 237.6%. This first achieved 2-μm fiber laser system with binary-wavelength emission and flexible power ratios can find applications in various areas.
Improved Multitrack Detection With Hybrid 2-D Equalizer and Modified Viterbi Detector

Increasing track density in magnetic recording systems increases inter-track interference (ITI). One way to handle the increased ITI is to apply 2-D equalization to the signals from multiple tracks. Usually the equalizer coefficients and the corresponding partial response (PR) targets are fixed after training using a pseudo-random bit sequence. We denote such an equalizer as a fixed equalizer. In this paper, we propose and investigate a variable 2-D equalizer for bit patterned media recording (BPMR). In the proposed approach, the equalizer coefficients and corresponding PR targets vary with ITI patterns. These variable equalizer coefficients are determined and stored by training with sequences representing different ITI patterns. In the proposed approach for BPMR, during data detection, these variable equalizer coefficients and corresponding PR targets are embedded into the parallel branches of a modified Viterbi (MV) detector in response to estimated ITI patterns. We term this new approach as V2DEMV [i.e., variable 2-D equalizer with 2-D PR target followed by MV detector] algorithm. Furthermore, we propose to simplify the implementation of the V2DEMV algorithm by identifying the survivor branch among the branches corresponding to the dominant erroneous ITI patterns. Then this survivor branch and other branches corresponding to remaining possible ITI patterns are processed by an F2DEMV (i.e., fixed 2-D equalizer with 2-D PR target followed by MV detector) algorithm to estimate the bits. We term this reduced-complexity approach as an H2DEMV (i.e., hybrid 2-D equalizer with 2-D PR target followed by MV detector) algorithm. Our simulations indicate that for both two readers detecting two tracks and three readers detecting three tracks, at target bit error rate of  $10^{-3}$ , the proposed H2DEMV algorithm can provide noticeable signal-to-noise ratio (SNR) gains compared to F2DE1DV algorithm (i.e., fixed 2-D equalizer with 1-D PR target followed by 1-D Viterbi detector) and F2DEMV algorithm.
Power conversion interface for small-capacity wind power generation system

Power conversion interface for small-capacity wind power generation system based on permanent-magnet synchronous generator (PMSG) is proposed in this paper. The proposed power conversion interface will convert the wind power generated from the three-phase PMSG to a high quality power to inject into the single-phase utility. This power conversion interface comprises of a power converter and a zero-sequence transformer set. The power converter is controlled to generate a set of positive-sequence currents to absorb a real power from the three-phase PMSG and a set of zero-sequence currents to pass through the zero-sequence transformer set to the single-phase utility. A feed-forward control is used to control the proposed power conversion interface so as to simplify the control circuit. A simplified maximum power point tracking method is also proposed and incorporated in the control circuit of the power conversion interface to extract the maximum power of the PMSG-based wind power generation system. Hence, the proposed power conversion interface has the advantages of simplifying both the power circuit and the control circuit. A prototype is developed to demonstrate the performance of the proposed power conversion interface. The experimental results show that the proposed power conversion interface can achieve the expected performance.
Impact of Organic Contamination From Partially Fluorinated O-Ring in High-Temperature Nitride Process on DRAM Performance

This paper is concerned with organic contamination from a partially fluorinated o-ring used in a furnace for a high-temperature process. The organic outgas was confirmed by Fourier transform infrared analysis of the furnace exhaust gas. Experiments from practical trench dynamic random access memory disclosed that outgassed organic contaminants from the nitride process would severely worsen the tunneling leakage current performance of the storage dielectric and lead to fatal yield loss even though the cell capacitance was almost uninfluenced. To eliminate this yield detractor requires several test runs prior to real production after installation of the partially fluorinated o-ring; otherwise, a fully fluorinated o-ring is needed. From a cost viewpoint, the latter is highly suggested.
Comparative study between the river of Tianjin airport industrial zone and Wei Jin Road river

On the base of a large numbers of related-references, the paper introduces the development's background of landscape river home and abroad, then starts from the the basic concept of ecological river landscape, investgates the feature and role of ecological river landscape in Tianjin Airport Industial Zone. We take examples of related research and practical experiences abroad, and point out the existing problems and the cause; discuss the design principles of this watercourse on the theoretical basis of ecology and sociology. selected as reference objects, Wei Jin Road landscape was contrasted from several levels such as river appearance, revetment bottom, treatment cost, so as to further demonstrate the development trend of present City's river Landscape. Finally, according to temporary reality, practical measure related to the construction of ecological river are proposed to provide references for future design.
A study of SNR and BER in Heat Assisted Magnetic Recording (HAMR)

As Perpendicular Magnetic Recording (PMR) technology reaches its areal density limit, Heat-Assisted Magnetic Recording (HAMR) becomes one of the most promising candidates for the next generation recording technology that could allow continued areal density growth up to 4 Tb/in2. However, as the areal density increases, it will bring many challenges to the recording system, such as increased non-linear bit shift and transition noise, and could lower the SNR . In this work, we focused on the factors that could affect the signal-to-noise ratio (SNR) and hence bit error rate (BER) of the HAMR system: we try to determine which one is more important . We then studied SNR vs BER by processing the readback signal with a 1D minimum mean square error (MMSE) equalizer and an improved Viterbi detector.
Image and Video Denoising Using Adaptive Dual-Tree Discrete Wavelet Packets

We investigate image and video denoising using adaptive dual-tree discrete wavelet packets (ADDWP), which is extended from the dual-tree discrete wavelet transform (DDWT). With ADDWP, DDWT subbands are further decomposed into wavelet packets with anisotropic decomposition, so that the resulting wavelets have elongated support regions and more orientations than DDWT wavelets. To determine the decomposition structure, we develop a greedy basis selection algorithm for ADDWP, which has significantly lower computational complexity than a previously developed optimal basis selection algorithm, with only slight performance loss. For denoising the ADDWP coefficients, a statistical model is used to exploit the dependency between the real and imaginary parts of the coefficients. The proposed denoising scheme gives better performance than several state-of-the-art DDWT-based schemes for images with rich directional features. Moreover, our scheme shows promising results without using motion estimation in video denoising. The visual quality of images and videos denoised by the proposed scheme is also superior.
Compressive Sensing of Hyperspectral Images via Joint Tensor Tucker Decomposition and Weighted Total Variation Regularization

In this letter, we consider the problem of compressive sensing of hyperspectral images (HSIs). We propose a novel tensor-based approach by modeling the global spatial–spectral correlation and local smoothness properties hidden in HSIs. Specifically, we use the tensor Tucker decomposition to describe the global spatial–spectral correlation among all HSI bands, and a weighted 3-D total variation to characterize the local smooth structure in both spatial and spectral modes. We then design an efficient algorithm to solve the resulting optimization problem by using the alternating direction method of multipliers. Experimental results on several HSI data sets demonstrate improved reconstruction performance of the proposed approach, as compared with other competing approaches.
Efficient synthesis of approximate threshold logic circuits with an error rate guarantee

Recently, Threshold logic attracts a lot of attention due to the advances of its physical implementation and the strong binding to neural networks. Approximate computing is a new design paradigm that focuses on error-tolerant applications, e.g., machine learning or pattern recognition. In this paper, we integrate threshold logic with approximate computing and propose a synthesis algorithm to obtain cost-efficient approximate threshold logic circuits with an error rate guarantee. We conduct experiments on IWLS 2005 benchmarks. The experimental results show that the proposed algorithm can efficiently explore the approximability of each benchmark. For a 5% error rate constraint, the circuit cost can be reduced by up to 65%, and 22.8% on average. Compared with a naive method, our approach has a speedup of 2.42 under a 5% error rate constraint.
Adaptive wiener filter based on fast lifting wavelet transform for image enhancement

A lifting-based wavelet domain Wiener filter(LBWDMF) in image enhancement is proposed. Lifting schemes have emerged as a powerful method for implementing bi-orthogonal wavelet filters. The method transforms an image into the wavelet domain using lifting-based wavelet filters and then applies a Wiener filter in the wavelet domain and finally transforms the result into the spatial domain. LBWDMF not only helps in reducing the number of computations but also achieves lossy to lossless performance with finite precision. The proposed method utilizes the multi-scale characteristics of the wavelet transform and the local statistics of each sub-band. In order to validate the effectiveness of the proposed method the result obtained using the proposed method show that the method has better performance in terms of PSNR.
Design and analysis of a miniature 4-dimensional force/torque sensor

This paper describes the design of a 4-dimensional fingertip F/T sensor that measures normal force fz, both tangential force terms fx, fy, and the torque about the normal axis Mz simultaneously, which are of vital importance for the gripper to grasp or hold any object. The Elastic Element (EE) structure featured with an annular diagram and flexible beams, and its static and dynamic performances are involved via ANSYS. At last, the arrangement and attachment strategies of strain gauges are planned. The proposed sensor possesses advantages such as simple and miniature configuration, high sensitivity, and isotropy. Finally, the experiment of the proposed sensor was conducted and validated.