nils-herrmann/clean_scirepeval huggingface dataset:
Dynamic Policy Access Model Based on Formal Concept Analysis

Formal concept analysis was creatively used in policy based network management in this study. It takes much time for a conflict detection routine to search every policy in policy repository with conventional policy access models to see if conflict occurs before a new dynamic policy is added to the policy repository. A novel access model for dynamic policies was proposed based on classification concept lattice to address this problem. Dynamic policies were organized into a concept lattice to be grouped effectively and stably. Then a conflict detection pre-process algorithm based on the concept lattice was proposed after a policy deployment procedure was designed. The algorithm greatly reduces the number of policies necessary for conflict detection, and increases efficiency of conflict detection. Performance analysis and simulation show that the proposed model is effective.
A Digital Parallel Current-Mode Control Algorithm for DC–DC Converters

This paper presents a novel digital current-mode control strategy for dc-dc converters. In the proposed algorithm, the required duty cycle is calculated directly by two parallel terms. With some simple operations in digital implementation, the resultant control system achieves rapid and precise output voltage regulation under the input voltage and output load change. Moreover, the implementation of the proposed algorithm with a digital controller is discussed in detail. Analysis shows that the parallel current-mode control does not exhibit subharmonic oscillation. A 400-kHz switching frequency buck converter based on field-programmable gate array implementation is built to verify the feasibility and advantages of the parallel current-mode control.
ANNIDS: intrusion detection system based on artificial neural network

This paper describes a network intrusion detection system based on artificial neural network (ANNIDS). The advantage of neural network ensures that ANNIDS does not need expert knowledge and it can find unknown or novel intrusions. The key part of ANNIDS is an adaptive resonance theory neural network (ART). ANNIDS can be trained in real-time and in an unsupervised way. A weight hamming distance method is used in detection, which is simple and correct in finding anomalous behavior. A well-trained ANNIDS can monitor the network in real time. The experimental results show that ANNIDS performs best when vigilance parameter is 0.4 to 0.5 and intrusion threshold is 0.4. The false positive error is about 8%, the negative error is about 2%, and the total error is lower 10%.
Comparison of Acoustic Wave Sensors With Different Cut ${\rm LiNbO}_{3}$ Working on Pseudo-LFE Mode

In this paper, two pseudo-LFE devices made up of X-cut and (yxl) 21.82° LiNbO3 are investigated and compared. The coupling factors of both devices are calculated and the impedance characteristics are tested by impedance analyzer. The sensitivity and stability of both devices to the electrical property changes of liquid are also tested in isopropanol-water and NaClwater solution. We find that the X-cut LiNbO3 device has a higher piezoelectric coupling factor and better resonance in the deionized water than (yxl) 21.82° LiNbO3 device. The results also show that X-cut LiNbO3 devices are more sensitive to the change of liquid conductivity and permittivity than (yxl) 21.82° LiNbO3 device even with similar stability.
Data Envelopment Analysis Based Strategy of Assessing Schemes for Power System Black Start

Restoration of a power system after a complete blackout is a very important issue to the safety of the power system. Reasonable black start schemes are necessary to restore the power system as soon as possible. Based on data envelopment analysis, a new strategy for assessing black start schemes is proposed in this paper. Schemes' technical verification is taken into consideration in the process of the assessment. Whether a scheme is effective is defined by employing its input and output indexes' values entirely. The application to a practical power system verifies that the method could provide dispatchers more comprehensive and objective decision references
A Novel Hierarichical Speaker Identification Method

This paper proposes a novel hierarchical speaker identification method to save the speaker identification and training time, viz. First is to get a coarse decision by a fast scan all registered speakers using PCA classifier to found M possible target speakers; then is to get a final decision by the proposed Multi-Reduced Support Vector Machine (MRSVM). And the MRSVM has two reduction steps to reduce training time and the memory size for SVM. Firstly, speech feature dimensions are reduced by using PCA transform, the noise is removed from speech simultaneity; secondly, the training data are selected at boundary of each cluster as Support Vectors (SVs) by using Kernel-based fuzzy clustering technique. The experiment results show that the training data, time and storage size can be reduced remarkably by using the proposed reduction method, and the identification velocity is improved greatly by the hierarchical identification method and the system has better robustness.
An Email Forensics Analysis Method Based on Social Network Analysis

Computer crime investigation and forensics is an important research work to combat criminal activity in cyberspace. But the complexity of computer criminal groups makes the computer crime forensics to be a challenge. Email is an important communication mean in computer crime communication. So the email forensics is needed to organized crime. This paper proposed an email forensics method based on graph clustering method and social network analysis (SNA). We analyze and mine emails data of the suspicious users' accounts using the new method, which can create email communication network graph for suspicious computer criminal organizations. The algorithm developed can analyze computer organization's structure and core members. The effectiveness of the method proposed has been proved by our experimental data and results. The research may help investigators to find more email evidence and case clues and improve investigators' email forensic capability, especially to the investigation for organized crime.
Cascode switching modeling and improvement in flyback converter for LED lighting applications

Modeling of the cascode switching structure used in Flyback converter for achieving fast startup in the deeply dimmed phase-cut LED driver is presented in this paper. The cascode structure's inherent instability and oscillation issue is modeled and analyzed quantitatively. Three solutions are proposed to stabilize the structure and suppress the unstable voltage oscillation. Solutions are studied using the proposed model for design robustness. And this model can be further applied to the popular new high voltage (for example 650V) cascode GaN FET technology. Experimental results of a 20W phase-cut dimmable LED driver are demonstrated to verify the proposed modeling method and solutions.
Combined adaptive fuzzy control for uncertain MIMO nonlinear systems

A combined adaptive fuzzy control method of a class of uncertain MIMO nonlinear systems is studied in this paper. In this method, the proposed controllers consist of two parts: the direct and indirect adaptive control terms. Compared with existing methods for controlling MIMO systems, this novel method can trade off fuzzy descriptions for control rules at the same time to achieve better adaptation properties and improve control effect. In addition, most methods need to assume that the minimum approximation error is required to satisfy the square-integrable condition. The method proposed in this paper doesn't need this assumption, and the effect of minimum approximation error could be removed by the adaptive compensation term. Based on Lyapunov stability theory, it can be ensured that all signals of closed-loop system are bounded, and the tracking errors converge to a small neighborhood around zero. Simulation results indicate the validity of the proposed method.
An accurate loss model for current-source gate driver with interleaving BUCK converter

Using traditional voltage source driver, switching losses will be increased with increasing of switching frequency. A new circuit of interleaving BUCK converter using the current source driver is presented in this paper. Based on the current source driver, a new analytical loss model of the power MOSFET is developed. A non-linear parameter called Incremental Conductance is introduced to the model for analyzing switching loss more accurately. Finally, experimental results are presented for the CSD operating in an interleaving BUCK converter at 1 MHz, 12 V input, 1.3 V /25A output. The validity of the loss model is verified by experimental results.
A study on the sync guidance of the multi-lasers with the micro-vision

In the application of the multi-beam laser accumulation for high energy, it is a key technology to guide the lasers into a micro area precisely and quickly. This paper proposes a laser spot identify and laser track sync control method, with the micro-vision feedback, parameterizing the laser spot based on the spot's counter characteristics. At the same time, the method is optimized in identifying the mass center and distinguishing the overlapped areas for the laser spots. The distributed method is verified by simulation and experiments. Compared with existing method, the sync control one guides lasers as the same precision but is 4 time higher efficiency under a 4 beam lasers experimental result.
Digital Charge Balance Controller With an Auxiliary Circuit for Improved Unloading Transient Performance of Buck Converters

In this paper, a digital charge balance controller is presented which is capable of controlling a buck converter and an auxiliary circuit to achieve an excellent unloading transient response. The auxiliary circuit significantly reduces the voltage overshoot caused by an unloading transient, while the digital charge balance controller reduces the settling time of the converter. The controller is capable of implementing load-line regulation and yields a smooth transition from one loading condition to another. Simulation and experimental verification is performed and demonstrates significant transient improvement over previously proposed solutions.
A novel design of dual ladder resistor D/A converter

This paper presents a novel dual ladder resistor D/A converter architecture. A 10 bits D/A converter is implemented which is based on this architecture. The present architecture provides a novel decoding scheme for dual ladder resistor D/A converter that reduces the size of the decoding logic, reduces the number of switches in coarse resistor stage and fine resistor stage. Experience of the 10 bits D/A converter design was shared. The design achieves INL and DNL of +0.3/−0.4LSB, +0.5/−0.4 LSB. This 10 bits D/A converter was used in reference voltage source chip which was taped out by Chartered 0.35μm CMOS 2P4M Mixed-mode process.
Designing the Cloud-Based DOE Systems Biology Knowledgebase

Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and their complexity, but increasingly such databases are providing the basis for new scientific discoveries. To engage effectively with these community resources, integrated analyses, synthesis and simulation software is needed, supported by scientific workflows. In order to provide a more collaborative, community driven research environment for this heterogeneous setting, the Department of Energy (DOE) has decided to develop a federated, cloud based cyber infrastructure -- the Systems Biology Knowledgebase (Kbase). In this context the Pacific Northwest National Laboratory (PNNL) has been defining and testing the basic federated cloud-based system architecture and developed a prototype implementation. Community wide accessibility of biological data and the capability to integrate and analyze this data within its changing research context were seen as key technical functionalities the Kbase needs to enable. In this paper we describe the results of our investigations into the design of this cloud based federated infrastructure for: $bullet$ Semantics driven data discovery, access and integration $bullet$ Data annotation, publication and sharing $bullet$ Workflow enabled data analysis $bullet$ Project based collaborative working We describe our approach, exemplary use cases and our prototype implementation that demonstrates the feasibility of this approach.
A 1-MHz High-Efficiency 12-V Buck Voltage Regulator With a New Current-Source Gate Driver

This paper proposes a new current-source gate drive circuit for a synchronous buck converter. The proposed driver can drive two MOSFETs independently with different drive currents for optimal design. For the control MOSFET, the optimal design involves a tradeoff between switching loss reduction and drive circuit loss; while for the synchronous-rectifier MOSFET, the optimal design involves a tradeoff between body diode conduction loss and drive circuit loss. Furthermore, the new drive circuit can achieve: 1) significant switching loss reduction; 2) gate energy recovery and high gate drive voltage to reduce R DS(ON) conduction losses; 3) reduced conduction loss and reverse recovery loss of the body diode; and 4) zero-voltage switching of all the drive switches. The improved driver using integrated inductors is presented with multiphase buck voltage regulators (VRs) to reduce the number of magnetic cores and the core loss. The experimental results prove that a significant efficiency improvement has been achieved. At 1.5-V output, the new driver improves the efficiency from 84% using a conventional driver to 87.3% at 20 A, and at 30 A, from 79.4% to 82.8%. Overall, the new driver approach is attractive from the standpoints of both performance and cost-effectiveness.
An optimized water detection algorithm for SAR images utilizing SOPC technologies

This paper investigates a water detection algorithm of region-of-interest extraction based on the combination of sobel edge detection and contrast stretching transformation. The implementation of the proposed method is utilized for SAR (Synthetic Aperture Radar) imaging with SOPC (Systems on a Programmable Chip) embedded technology. It also puts forward an effective and realizable approach for the parallel processing data. The water detection algorithm is first optimized for SOPC system and is implemented on Xilinx Zynq-7020 chip with dual cortex-A9 ARM processors. As a result, the average consumption time of water detection algorithm reduces over 38 percent, which ensures the real-time requirement in the real-time object detection system.
A new model for designing multi-hole multi-permeability nonlinear LTCC inductors

Nonlinear inductors have wide applications in DC/DC converters. The multi-hole multi-permeability nonlinear inductors have been proved to have gradually changing wide-range inductance curve while requiring no extra DC bias, which makes them suitable in various high efficiency DC/DC converters. This paper focuses on the design of such a multi-hole multi-permeability inductor. In the conventional design, complicated simulation needs to be executed when the coupling matrix among all the holes are taken into consideration. A dedicated model for calculating the inductance value is proposed in this paper to reduce the complexity. In the proposed model, the inductance simulation is simplified to calculating inductance of three basic units which are included in a nine-hole inductor. By simulating the nine-hole inductor, inductance of any rectangle shape multi-permeability nonlinear inductor with any number of evenly distributed holes on it can be calculated. Based on the proposed model, design guideline of the nonlinear inductor is also summarized. A sixteen-hole, two-permeability prototype is presented to demonstrate the design process according to the new model. The complete simulation and the test results are also provided to verify the model. The proposed model correlate with the simulation results very well.
An Improved Random Early Detection Algorithm Based on Flow Prediction

Random Early Detection(RED) is a network congestion control algorithm which calculates the packet-lossratio according to current length of average queue. This paper describes an improved RED algorithm: Firstly, predicts network flows with RBF neural Network in order to forecast queue length much earlier, and then, fits the Packet-loss-ratio of RED algorithm according to some special points using curve fitting method, therefore, controls nonlinear network congestion. From our simulation, it can be concluded that the algorithm avoids congestion more efficiently.
Area optimization in deep sub-micron VLSI design

Area is an important factor in deep sub-micron VLSI design. In order to save die size during back-end design for our DSP microprocessor - SuperV, double metal power rings were designed, and some standard cells were also put under the horizontal power straps. In this way, more than 12% die size saved. Other optimization methods were also introduced to save area during placement and routing. Finally, the core area is shrank to 4mm times 4mm, and the chip's area is decreased to 5mm times 5mm including the bonding pads
Development and Research of Measuring Capacitance and Inductance Based in Experiment Teaching

A measurement method of capacitance and inductance based on 16Bit MCU is introduced in this paper, it uses LC oscillatory circuit, signal processing circuit and MCU resource to produce the signal and measure the frequency of it, and convert the frequency to the value of LCR. The measure result is showed in the way of liquid display and voice broadcast. Finally, the error of result is analyzed and solve problems. The Instrument make things convenient for the students.
Device and Circuit Interaction Analysis of Stochastic Behaviors in Cross-Point RRAM Arrays

Stochastic behaviors of resistive random access memory (RRAM) play an important role in the design of cross-point memory arrays. A Monte Carlo (MC) compact model of oxide RRAM is developed and calibrated with experiments on various device stack configurations. With MC SPICE simulations, we show that an increase in array size and interconnect wire resistance will statistically deteriorate write functionality. Write failure probability (WFP) has an exponential dependence on device uniformity and supply voltage <inline-formula> <tex-math notation="LaTeX">$({V}_{\textsf {DD}})$ </tex-math></inline-formula>, and the array bias scheme is a key knob. Lowering array <inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {DD}}$ </tex-math></inline-formula> leads to higher effective energy consumption (EEC) due to the increase in WFP when the variation statistics are included in the analysis. Random access simulations indicate that data sparsity statistically benefit write functionality and energy consumption. Finally, we show that a pseudo-subarray topology with uniformly distributed preforming cells in the pristine high-resistance state is able to reduce both WFP and EEC, enabling higher net capacity for memory circuits due to improved variation tolerance.
A viable self-aligned bottom-gate MOS transistor technology for deep submicron 3-D SRAM

In this paper, the effect of the nonself-aligned process on the performance variation of a bottom-gate metal oxide semiconductor (MOS) transistor is discussed using a device simulator. The simulation results predict that the nonself-aligned bottom-gate MOS transistor cannot be scaled into the deep submicron regions. A simple fully self-aligned bottom-gate (FSABG) metal oxide semiconductor field effect transistor (MOSFET) technology is then proposed and developed. A new technique for forming thermal oxide on poly-Si serving as the bottom-gate dielectric is also investigated. It is found that the quality of the oxide on the poly-Si recrystallized by the metal induced uni-lateral crystallization (MIUC) is much higher than that by the solid phase crystallization (SPC). Deep submicron fully self-aligned bottom-gate pMOS transistors are fabricated successfully using the proposed technology. The experimentally measured results indicate the device performances depend strongly on the channel-width, and get comparable to that of a single crystal MOSFET if the channel width is less than 0.5/spl mu/m. The effects of the channel width on the device performances are discussed. In addition, the experimental results also confirm that the proposed technology has a good control of the channel film thickness.
A simple and effective still image retrieval paradigm

Considering a classic image-retrieval problem, a user submits a set of index images to a system and through repeated interactions, the goals are narrowed to the image(s) that satisfies the user. To this purpose, conventional content-based image retrieval (CBIR) paradigm make uses of image processing and computer-vision techniques, and tries to understand the visual(color, shape, texture etc) image content. We propose a novel paradigm to this problem from a totally different angle. It attempts to use the human's intuition capabilities. Instead of processing images, the system simply accumulates records of user feedback and recycles them in the form of collaborative filtering, just like a purchase recommendation system such as Amazo web. we use paradigm by a term "content-free" image retrieval (CFIR). We discuss many issues of visual retrieval, argue for the idea of CFIR, and present results of experiment. The experiment results show that the performance of CFIR improve image performance.
Effect of the “torso protective strategy” for safe falling of a biped humanoid robot

The falling of a biped humanoid robot is treated as an extremely unstable state. When an unexpected fall happens, it may cause serious damage to both the robot itself. This study focuses on the falling issue and investigates the effect of the “torso protective strategy” for safe landing of a biped humanoid robot. First, the effectiveness of the torso strategies to the safe landing is analyzed from an energy variation perspective of the robot system. The torso strategies are used to do negative work that reduced the energy of the robot system, thereby reducing the impact velocity of the robot. Then, a comparative simulation is made on a model of humanoid robot to validate the influence of the torso strategies on safe landing.
A compact recording array for neural interfaces

This paper presents a 44-channel front-end neural interface for recording both Extracellular Action Potentials (EAPs) and Local Field Potentials (LFPs) with 60 dB dynamic range. With a silicon footprint of only 0.015 mm2 per recording channel this allows an unprecedented order of magnitude area reduction over state-of-the-art implementations in 0.18 μm CMOS. This highly compact configuration is achievable by introducing an in-channel Sigma Delta assisted Successive Approximation Register (ΣΔ-SAR) hybrid data converter integrated into the analogue front-end. A pipelined low complexity FIR filter is distributed across 44-channels to resolve a 10-bit PCM output. The proposed system achieves an input referred noise of 6.41 μVrms with a 6 kHz bandwidth and sampled at 12.5 kS/s, with a power consumption of 2.6 μW per channel.
A Intelligent Prediction Model of Network Traffic

According to the previous experience, the BP neural network have been holding the leading position in the forecast ability and the study precision. However, the running rate and the skilled speed are too slow to solve the smallest region issues, so Simulation Annealing is introduced in the article. It means that Simulation Annealing-BP neural network is used to the intelligent prediction model and predict the network traffic. It can be seen the efficiency and the precise degree of Simulation Annealing-BP neural network have been enhanced than that of basic BP algorithm through simulation