nils-herrmann/clean_scirepeval huggingface dataset:
Decision Support for Maintenance Management Using Bayesian Networks

The maintenance process has undergone several major developments that have led to proactive considerations and the transformation of the traditional "fail and fix" practice into the "predict and prevent" proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy, is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing pars and diagnoses the faults in machinery. But diagnosis application relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference, however, in the area of oil monitoring, it is a new field. This paper develops an integrated Bayesian network based decision support system for maintenance of diesel.
Design and development of trees' spatial distribution charting tool

The paper was to generate trees' spatial distribution map through using VBA programming language in Excel. Scatter diagram of “chart type” in Excel was served as basic framework. Graphics was generated through invoking the object of ChartObject and Chart. Trees' spatial distribution map of circular plot was imported through polar coordinates. Graphical information was added to trees'spatial distribution map through the idea of “numerous points composing of a circle”. The tool operates very quickly and easily and is practicable. It not only could analyze trees'spatial distribution and competition among trees, but also provide reference for decision-making of forest management practice.
Diatomological Distribution of Pearl River in Guangzhou and Yangtze River in Hubei Province and Its Application to the Diagnosis of Drowning Cases

Diatoms have received much popularity as forensic evidence for diagnosing death by drowning. Distribution of diatoms in any water body, and its correlation with the diatom genus recovered from the drowned body can be a method of choice to resolve questions related to drowning sites. In this study, we collected 24 water samples from sites across the Pearl River in Guangzhou and 16 water samples from Yangtze River flowing through Hubei Province, China to do an analysis of diatoms' distribution and to analyze the relationship between diatom assemblages and drowning sites. The diatoms in the lungs and organs of the circulatory system from 5 postmortem cases died by drowning, which could be observed from the macroscopic autopsy findings and police reports, were compared with diatomological distribution mapping choosing diagnosis parameters including diatom genus, size, concentration, etc. The analysis was undertaken in order to record the significant variation in diatom diversity in the 6 (selected) different types of water bodies in Guangzhou (China) during different seasons (summer, winter), Yangtze river in Hubei Province in summer. Data of Pearl Rive in Guangzhou obtained have been utilized to create diatomological distribution maps, which can diagnosis the suspected drowning cases occurring in a particular area and characterization of different water bodies.
A neutral point clamped multilevel topology flow graph and space NPC multilevel topology

Neutral-Point Clamped (NPC), such as diode-clamped, multilevel inverter technology has emerged recently as a very important alternative in the area of high-power medium-voltage energy control. However, the NPC Multilevel topology also has variable type of structure which cannot be found due to lack of systematic derivation methodology. A new system method, called NPC Flow Graph (NPC-FG), is proposed to derive all the possible topologies in this paper, which sets the basic criteria and special steps to construct topologies. Thirty-two NPC five-level topologies have been derived. Among them, a new family of Space NPC (S-NPC) multilevel topologies is also proposed by NPC-FG. Additional topologies can be derived based on different criteria to meet special requirement, such as Photovoltaic (PV) application. The proposed method can find all the existing multi-level NPC topologies, as well as new ones, with better performance.
A novel isolated two-phase full bridge topology for VRM applications

In this paper a new isolated full bridge is proposed. Compared with conventional full bridge the new topology can double the output power since its primary side and secondary side operate like two conventional full bridges in parallel and phase shift from each other. But it saves two switches at primary side and it achieves better efficiency. To demonstrate the advantages of the new topology two 48 V input, 1V/70 A output, 1 MHz, power module were built on a 12 layers, 2 oz copper PCB, one with four output inductors, the other with three output inductors. 81.3% &80.8% efficiency are achieved respectively at full load (1 V/70 A) compared with two paralleled FB 80.4% at full load (1 V/70 A) around 1% improvement is achieved. At light load (1 V/20 A), 4% improvement is achieved.
Adaptive control software: can we guarantee safety?

The appeal of including adaptive components in complex computational systems, such as flight control, is in their ability to cope with a changing environment. Continual changes induce uncertainty that limits the applicability of conventional verification and validation (V&V) techniques. In safety-critical applications, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. We present a nonconventional V&V approach suitable for online adaptive systems. We applied this approach to an adaptive flight control system that employs neural network learning for online adaptation. Presented methodology consists of a Novelty Detection technique and Online Stability Monitoring tools. The Novelty Detection technique is based on support vector data description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's stability theory detect unstable learning behavior in neural networks.
Content filtering research based on web community structure

The web contents are massive, diverse and semantics-missing, which bring significant challenges to the content-filtering. This paper proposes a new method of web content-filtering, which takes full advantage of the web structure feature that the similar topic webpages integrate into the web community, and uses the web community detection algorithm to get more content-similar webpages after filtering one webpage. In addition, by constructing and analyzing the associated mathematical model, it proves that this method significantly raised the efficiency, compared with the other third-party content-filtering technology.
A precisely regulated multiple output forward converter topology

A precisely regulated multiple output forward converter topology is presented in this paper. In this topology, each output voltage is directly and independently regulated by its own feedback control circuit that controls the appropriate synchronous rectifiers in the pertinent output stage, while the main switch is feedforward controlled. Thus, there is no cross regulation between the outputs, and design of each output becomes straightforward. Steady state analysis is performed to understand the topology and to provide design guidance. A prototype circuit with two outputs is built, and experiment are carried out on this prototype and the results verify the concepts and design.
A study on the teleoperation of robot systems via WWW

We describe a study on a teleoperated robot control system developed in the ART (Advanced Robotics and Teleoperation) Lab. at the University of Alberta. When using the system, a remote operator just needs a general-purpose computer with Internet connection and a World Wide Web (WWW) browser to remotely operate the robot through the Internet. A control architecture that combines computer and robot is constructed. This system is divided into two primary parts, the client part, which is executed on the remote operator's computer, and the server part, which resides on the server workstation in the ART Lab. The two parts are connected via the Internet. A graphical interface on the remote computer screen, showing the robot and its environment, enables the remote operator to send control commands to the robot. Communication coordination between the client and the server is developed using Java language. Since the real-time control through the Internet typically suffers from random time-delay and bandwidth constraints, many traditional control methods will suffer from stability and obstacle avoidance related issues. One approach to deal with the mentioned problems is to use event-based control methods for planning and control which have been successful in reducing the effects of the constraints by adopting a nontime based reference system in the control algorithm. We will apply this method in our Internet-based telerobotic systems. The nontime referenced action control scheme is used to deal with the unpredictable time-delays.
An electrolytic capacitor-free single stage Buck-Boost LED driver and its integrated solution

For a conventional offline Buck-Boost LED driver, significant low frequency ripple current is produced when a high power factor has been achieved. In this paper, an innovative LED driver technology based on the Buck-Boost topology has been proposed. The featured configuration has greatly reduced the low frequency ripple current without compromising power factor performance. High efficiency and low component cost features have also been retained from conventional Buck-Boost LED driver. A 10W, 50V-0.2A experimental prototype has been constructed to verify the performance of the proposed technology.
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data

With the development of Internet, the increasing volume of information posted on micro-blogging sites like Twitter necessitates the need for efficient information filtering. In conventional text classification problems, it is assumed that the feature vectors extracted from the available documents are sufficient to learn good classifiers. However, this conventional approach is not likely to work for Twitter due to the limited number of characters on each tweet. From a higher level, each tweet can be viewed as an abbreviated abstraction of a long document, and we only have a partial observation of this document. To solve the problem caused by the partial observations, we introduce a novel domain adaption/transfer learning approach called Assisted Learning for Partial Observation (ALPOS). The basic idea is to use a large number of multi-labeled examples (source domain) to improve the learning on the partial observations (target domain). In particular, we learn a hidden, higher-level abstraction space, which is meaningful for the multi-labeled examples in the source domain. This is done by simultaneously minimizing the document reconstruction error and the error in a classification model learned in the hidden space by using known labels from the source domain. The partial observations in the target space are then mapped to the same hidden space for recovery and classification. We compare the performance of this method with existing approaches on synthetic data and the well-known Reuters-21578 dataset. We also present experimental results on twitter classification.
A gain-enhanced rectangular patch antenna with artificial magnetic conductor ground

A kind of composite antenna with an artificial magnetic conductor ground is designed in this paper. This antenna consists of a 3×3 hexagonal annular gap artificial magnetic conductor unit cells and a rectangular patch antenna fed by coplanar waveguide. The in-phase reflection is suitable for the composite antenna. The distance between the patch antenna and the ground is 0.1λ at zero-phase reflection frequency for gain enhancement and low profile. The experimental results show that the relative operating bandwidth of the composite antenna is 23.3%, and the gain is more than 9dB.
An initial evaluation of requirements dependency types in change propagation analysis

Change propagation analysis helps predict the parts of the software that may be affected if a change is made. Existing research on change propagation focuses on design and code level changes. However, as a software evolves, the requirements that drive these changes also have intricate dependencies. Understanding the effect of these requirement dependencies on change prorogation is useful but not trivial. More than twenty requirements dependency types have been identified in the literature, however there still lacks an evaluation of the applicability of these dependency types in requirements and change propagation analysis.  We aim to investigate whether these dependency types are useful for change propagation analysis.  We conducted a case study in a real-world industry project. This case study evaluates two representative dependency models covering twenty five types of dependencies.  Our initial evaluation has found that five dependency types are particularly useful in change propagation analysis and practitioners with different backgrounds have various viewpoints on change propagation. Thus change impact analysis should involve a wide range of stakeholders including project managers, requirements engineers, designers and developers.  Our case study provides insights into requirements dependencies and their effects on change propagation analysis for both research and practice.
Combination of PANA and Diameter in Trusted Vehicle Network

Vehicle network is popular gradually. For more security in vehicle network, a trusted AAA (Authentication, Authorization and Accounting) environment for vehicle network must be established. The paper proposes an approach to establish such an environment using combination of two next generation AAA protocols, PANA (Protocol for carrying Authentication for Network Access) and Diameter. The ability of their combination both in work patterns and in the protocol structure is analyzed, and an AAA network entity communication structure and the architecture of the key device to combine the protocols are put forward. Moreover, the implement method of the software base on Open Diameter on the key device is given in detail. This scheme is proved to be effective through experiment.
Design and implementation of a high resolution DPWM based on a low-cost FPGA

This paper proposes a new implementation method which can achieve DPWM with time resolution under 100ps. Utilizing the carry flag delay time, a high resolution DPWM can be achieved by low cost FPGA. The proposed DPWM method is, in principle, intended for FPGA implementation, but it can achieve high time resolution DPWMS and can be implemented in low cost FPGA. Linearity was manually optimized using the presented technique which reduces the non-linearity error. The proposed DPWM with 15-bit and 70–80ps resolution with a switching frequency of 1 MHz has been successfully implemented on a low-cost Atera Cyclone-II series FPGA.
Adaptive Fuzzy Control for a Class of Nonlinear Discrete-Time Systems With Backlash

An adaptive fuzzy controller design is studied for uncertain nonlinear systems in this paper. The considered systems are of the discrete-time form in a triangular structure and include the backlash and the external disturbance. By using the prediction function of future states, the systems are transformed into an n-step ahead predictor. The fuzzy logic systems (FLSs) are used to approximate the unknown functions, unknown backlash, and backlash inversion, respectively. A discrete-time tuning algorithm is developed to estimate the optimal fuzzy parameters. Compared with the previous works for the discrete-time systems with backlash, the main contributions of the paper are that 1) the rigorous restriction for the functional estimation error is removed, and 2) the external disturbance is bounded, but the bound is not required to be known. A novel controller and the adaptation laws are constructed by using the discrete Taylor series expansion and the difference Lyapunov analysis, and thus, those limitations in the previous works are overcome. It is proven that all the signals in the closed-loop system are bounded and that the system output can be to follow the reference signal to a bounded compact set. A simulation example is provided to illustrate the effectiveness of the proposed approach.
Design of the input-output model toolbox in Matlab

Matlab is a high-performance language for scientific and technical computing. It integrates computation, visualization, and programming in an environment which provides many specific toolboxes. Different toolboxes can be used in corresponding areas, such as math, control theory, economics. We described the design of the Leontief input-output model toolbox which can simulate the trajectories of input and output of economic systems and automatically control the run of economic systems. By means of mathematic methods, the Leontief input-output systems were directly treated without converted to general systems. A sufficient condition under which the Leontief input-output models are stable is investigated. Based on this, the control algorithm is derived. Finally, the code of the input-output toolbox is provided.
A Novel Scheme for Suppressing Velocity Ambiguity in Narrowband Blood Flow Velocity Estimation

Color flow imaging plays a major role in the diagnosis of many vascular diseases, especially cardiovascular disease. A novel scheme is proposed to suppress velocity ambiguity induced by the narrowband estimators based on the two-dimensional correlation function model by incorporating with the wideband velocity estimation techniques. The basic idea is that the velocity is first estimated by narrowband estimator based on the two-dimensional correlation function model, and then a group of velocity candidates are formed. From these candidates, the wideband estimators search the true velocity. This scheme is tested by a two-dimensional correlation estimator incorporating with the butterfly search estimation method. Simulation results have shown that this scheme is an effective tool to suppress velocity ambiguity
Design Research of a Novel High Speed Nanometer Positioning System on Macro/Micro Driven for MEMS

With the increasing demand of high speed and precision positioning system for the devices packaging in microelectromechanical system (MEMS), a novel high speed nanometer positioning XY stage system on macro/micro driven is presented in this paper. The stage integrates the advantage of macro stage driven by linear voice coil motor (VCM) such as long stroke and high speed, and the advantage of micro stage driven by piezoelectric actuator (PZT) such as high response and nanometer resolution. Adopting a novel elastic decoupling mechanism used to avoid the moving gap, the stage haves the entire decoupling characteristic in kinematics and control. Based on the analysis and optimization of the mechanism in high dynamic state, the XY stage prototype is manufactured. And based on the model of control system, the macro-micro control strategy with high speed and high accuracy is investigated. The simulation results verify that the system dynamic performance is significantly increased and the steady-state error is reduced to plusmn10 nm
ActiveCrowd: A Framework for Optimized Multitask Allocation in Mobile Crowdsensing Systems

Worker selection is a key issue in mobile crowd sensing (MCS). While the previous worker selection approaches mainly focus on selecting a proper subset of workers for a single MCS task, a multitask-oriented worker selection is essential and useful for the efficiency of large-scale MCS platforms. This paper proposes ActiveCrowd, a worker selection framework for multitask MCS environments. We study the problem of multitask worker selection under two situations: worker selection based on workers’ intentional movement for time-sensitive tasks and unintentional movement for delay-tolerant tasks. For time-sensitive tasks, workers are required to move to the task venue intentionally and the goal is to minimize the total distance moved. For delay-tolerant tasks, we select workers whose route is predicted to pass by the task venues and the goal is to minimize the total number of workers. Two greedy-enhanced genetic algorithms are proposed to solve them. Experiments verify that the proposed algorithms outperform baseline methods under different experiment settings (scale of task sets, available workers, varied task distributions, etc.).
A New Framework for Accessing Trusted Network

Trusted Network Connect (TNC), whose goal is to improve network security from source, now has become hot topic in security domain. We proposed a new access model for the terminals without meeting the requirements in TNC specifications. Also we discussed the work flow and communication process of presented model. Simulations show that the feasibility of the presented model used in the scenario where terminals fall short of network demand can pass the access authentication of network with TNC specifications.
A new hybrid gate drive scheme for high frequency buck voltage regulators

This paper presents a new hybrid drive scheme for a synchronous buck voltage regulator (VR). The proposed current-source driver is used to drive the control MOSFET to achieve fast switching speed and reduce the switching loss significantly due to the parasitic inductance in addition to gate energy recovery. Conventional voltage driver is used for synchronous rectifier (SR) MOSFET for its simplicity and good immunity and alleviation of dv/dt effect. The experimental results prove the advantages of the new drive scheme and a significant efficiency improvement has been achieved. At 1.3 V output, the new driver improves the efficiency from 82.8% using a conventional driver to 85.6% (an improvement of 2.8%) at 20 A, and at 25 A, from 80.5% to 83.0% (an improvement of 2.5%). The new drive can also be integrated into a standard drive integrated circuit (IC) and replace the conventional voltage drive IC directly. Overall, the new driver scheme is very promising from the standpoints of both performance and cost- effectiveness.
A passive-impedance-matching concept for multiphase resonant converter

A passive impedance matching (PIM) concept is proposed for multi-phase resonant converters application. The new concept can achieve load current sharing between every unit automatically. A passive element such as an inductor or a capacitor is connected in the common branch of the two units (or multi-units), such that several sets of equivalent positive resistors and negative resistors are distributed into these units accordingly. The equivalent virtual resistors are of variable value, which automatically adjust the DC gain in each unit to achieve load sharing. Three equivalents LLC resonant converters with virtual variable resistor are analyzed. The theoretical analysis result shows that the first and third types have good load current sharing performance. A 600W, 12V two-phase LLC converter prototype is built based on the first type. The prototype verified the feasibility and demonstrated advantages of PIM multiphase resonant converter.
Detecting Conflict Policy Rules with Concept Lattice

Concept lattice was creatively used in policy based network management in this study. It takes much time for a conflict detection routine to search every rule in a policy rule set with conventional algorithms to see if conflict occurs before a new rule is added to the rule set. A novel conflict detection algorithm was proposed based on concept lattice to address this problem. The algorithm greatly increases efficiency of conflict detection. Performance analysis and simulation show that the proposed algorithm is effective.