nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of and Improvement on Ranking Method for Fuzzy AHP

The transformation of fuzzy consistency comparison matrices and the final ranking method of fuzzy analytical hierarchy process (fuzzy AHP) are studied. The shortcoming of prevalent final ranking methods, often not able to fully address the preferences of decision makers, is discussed, and a new transformation method for consistency fuzzy comparison matrices based on the fuzzy comparison vectors is put forward. Further, by applying the comparison scale of the ideal solution to the fuzzy comparison vectors, an improvement on the final ranking method, based on the decision maker's ideal solution, is put forward. These make it easier to obtain the fuzzy consistency comparison matrix and the final ranking more desirable. Numerical illustrations at the end of the paper prove our improvement to be effective
Apply EDTA and NTA to Extract Fe and Al Ions from Sewage Sludges: Batch Study

Heavy metals accumulating in the sludge after active sludge process limit the further use of sludge due to their toxicity. This study was carried out to extract Fe and Al from practical sewage sludge at different pH values and EDTA / NTA doses. The result showed that EDTA and NTA acted significant extraction on Fe and Al from sewage sludge when pH <7, and only a little effect after pH of 7. Fe and Al have similar tendency of being extracted, while Fe is more readily extracted than Al from practical sewage sludge. The most extraction percentage by EDTA reached up to 62.5% and 26.9% for Fe and Al at pH of 2.69, and that by NTA reached up to 36.3% and 26.9% for Fe and Al at pH of 4.57 and 2.78 respectively. Also, Fe and Al were effect by SS apparently when EDTA was applied, and Fe was more, however hardly when NTA. Comparing the NTA with EDTA treatment of sludge, Fe is more easily extracted by EDTA than NTA.
Data sniffing - monitoring of machine learning for online adaptive systems

Adaptive systems are systems whose function evolves while adapting to current environmental conditions, Due to the real-time adaptation, newly learned data have a significant impact on system behavior When online adaptation is included in system control, anomalies could cause abrupt loss of system functionality and possibly result in a failure. In this paper we present a framework for reasoning about the online adaptation problem. We describe a machine learning tool that sniffs data and detects anomalies before they are passed to the adaptive components for learning. Anomaly detection is based on distance computation. An algorithm for framework evaluation as well as sample implementation and empirical results are discussed. The method we propose is simple and reasonably effective, thus it can be easily adopted for testing.
Characterizing Evolutionary Algorithm Using Complex Networks Theory: A Case Study

Evolutionary algorithms (EAs) are a type of complex systems which mimic biological evolution in nature to solve real world problems. In this paper, we propose to use complex networks theory to characterize the topological properties of evolutionary algorithms (EAs). A case study on Guo's algorithm is given as an example to show how to use our method. In our method, we represent the evolutionary process of Guo's algorithm as a directed network, directed evolutionary algorithm network (DEAN). Many aspects of DEAN are analyzed, such as degree distribution, average path length, assortativity coefficient, and clustering coefficient. Our results imply that DEAN is a small-world and scare-free type network. Our results give great insight into the underlining regularities in EAs.
Data-Driven 4D Visualization for Simulating Highway Construction Processes

This paper presents a method which discretizes long and narrow belt-shaped structure into sequence of cross-sections and creates cross-section models automatically based on the real construction data. Then completion and schedule model of construction are obtained by connecting cross-section schedule models. This Method reduces data volumes effectively and improves automation degree and scalability of modeling constructions. The experiment has shown that this system is full-featured, the modeling and visualization of construction processes can meet the requirement of real-time.
A Configurable Event Correlation Architecture for Adaptive J2EE Applications

Distributed applications that adapt as their environment changes are developed from self-managing, self-configuring and self-optimising behaviours. This requires constant monitoring of the state of the environment, and analysing multiple sources of events. Event correlation is the process of correlating monitored events from multiple sources for further analysis. It is essential that event correlation supports reliable event management with minimal delay. This paper describes the design and implementation of an event correlation architecture for adaptive J2EE applications. The architecture supports flexible configuration of event correlation in terms of the reliability and performance. This is especially useful in situations when multiple sources of events have different level of requirements for reliability and performance. We evaluate the performance overhead of this event correlation architecture and demonstrate its practical usage in a case study of an adaptive image server application.
An optrode with built-in self-diagnostic and fracture sensor for cortical brain stimulation

This paper proposes a self-diagnostic subsystem for a new generation of brain implants with active electronics. The primary objective of such probes is to deliver optical pulses to optogenetic tissue and record the subsequent activity, but lifetime is currently unknown. Our proposed circuits aim to increase the safety of implanting active electronic probes into human brain tissue. Therefore, prolonging the lifetime of the implant and reducing the risks to the patient. The self-diagnostic circuit will examine the optical emitter against any abnormality or malfunctioning. The fracture sensor examines the optrode against any rapture or insertion breakage. The optrode including our diagnostic subsystem and fracture sensor has been designed and successfully simulated at 350nm AMS technology node and sent for manufacture.
Differential wide-slot UWB antenna with band-notched applications

A novel differential wide-slot ultrawideband(UWB) antenna with band-notched selectivity is proposed and investigated in this paper. The antenna consists of a rectangle ground with a wide slot and a stepped differential feeding line. In order to realize controllable notched bands characteristics, a pair of half-wave-length slits are utilized in ground and feeding structure. Moreover, the notched bands can be adjusted by the length of slits. The wide slot on the top layer is fed by the differential feeding structure by proximity coupling. Simulated results show that the -10dB impedance bandwidth is 136% (from 2.12 to 11.2 GHz), with a notch band from 5.05 to 5.9 GHz, respectively. Due to the adopting the differential feeding, the proposed antenna has low cross polarization. The radiation performance and gain is also simulated.
Dynamic NBTI characteristics of p-MOSFET with N-plasma SiON Gate Dielectric

In this paper, the dynamic negative bias temperature instability (DNBTI) characteristics of p-MOSFET with N-plasma SiON dielectric are studied. Under dynamic stress, the nearly consistent frequency dependent characteristics of threshold voltage shift (DeltaVth) and interface trap density (DeltaNit) were observed. The results show that the degradation and recovery of DNBTI are still dominated by the generation and passivation of the interfacial traps associated with Si-H bond breaking and released H species diffusion during stress phase and back diffusion of H and repassivation of broken equivSi bonds during passivation phase, which could be depicted by the so-called reaction-diffusion (R-D) model. Meanwhile, the reduced passivation effect with increased stress time was observed, which suggests that the generation and passivation of Nit seems to present a fatigue effect. These observed DNBTI characteristics may relate to the nitrogen trapping effect on the diffusion of H species in SiON dielectric layer
A Fuzzy Multicriteria Group Decision Making Method With Probability For Construction Safety Evaluation

In order to appraise more accurately the safety conditions of construction sites, evaluation indexes for construction site safety conditions are given. By introducing probability theory and fuzzy group decision methods into construction evaluation, a comprehensive evaluation method based on fuzzy group decision making is put forward. This method applies AHP in determining weight of each expert and uses fuzzy comprehensive evaluation with probability to evaluate the safety conditions of construction sites. Weights and evaluation values of indexes could be reasonably determined when group decision making method is applied. Further, evaluation by means of connecting probability theory and fuzzy evaluation method together is an improvement over the prevalent method of scoring by experts, since safe production conditions could be reflected more objectively and completely
A robust RST invariant image watermarking method based on locally detected features

This paper presents a robust rotation, scaling and translation (RST) invariant image watermarking method based on locally detected features. First, the feature points are detected in the original image by using the Harris corner detection. Then, the Delaunay tessellation is created on these feature points. Watermark data are embedded and detected in each of the Delaunay triangles. The Harris corner detection is the key point in this scheme. Traditionally, the global threshold is used for the Harris corner detection. As a result, the points are concentrated on areas with rich texture information and the contrast change within the image. In this way, the locations of points are seriously affected by attacks, such as, geometrical attacks. It makes the watermark detection difficult or even impossible. In order to generate more robust feature points, we use a local threshold feature detection method, in which local thresholds are used for different parts of the target image. The feature points are almost uniformly distributed on the image. The experimental results show that this method makes feature points very robust after geometrical attacks, JPEG compression and noise addition.
Comparative Study of Negative Capacitance Ge pFETs With HfZrOx Partially and Fully Covering Gate Region

We report a comparative study of the negative capacitance (NC) Ge pFETs with HfZrO<sub><italic>x</italic></sub> (HZO) partially and fully covering gate region. Utilizing the layout with HZO partially covering the gate, the internal voltage gain <italic>dV</italic><inline-formula> <tex-math notation="LaTeX">$_{{\textsf {int}}}$ </tex-math></inline-formula>/<italic>dV</italic><inline-formula> <tex-math notation="LaTeX">$_{{\textsf {GS}}} > \textsf {10}$ </tex-math></inline-formula> is demonstrated in NC Ge pFETs, which is attributed to the NC effect induced by HZO film. NC transistor demonstrates the hysteresis above 2 V, the sub-60 mV/decade subthreshold swing, and the improved drive current over internal-gated MOSFET. As the area of HZO is increased to fully cover the gate, the increased ferroelectric capacitance <inline-formula> <tex-math notation="LaTeX">${C} _{{\textsf {FE}}}$ </tex-math></inline-formula> produces the much better capacitance matching between <inline-formula> <tex-math notation="LaTeX">${C} _{\textsf {FE}}$ </tex-math></inline-formula> and the MOS capacitance of TaN/HfO<sub>2</sub>/Ge channel, contributing to the elimination of hysteresis of the NC Ge pFET. NC Ge pFETs with the gate fully covered by HZO achieve a much higher gate capacitance peak and a 36% enhancement in drive current compared to the devices with HZO partially covering gate.
An improved zero voltage switching flyback converter topology

An improved zero voltage switching flyback converter topology is presented in this paper. This converter employs an auxiliary circuit that provides ZVS for both the main and auxiliary and it permits the operation of the converter at very high frequencies. Operating principle, steady state analysis, and design procedure for the auxiliary circuit of the proposed converter, are given. A 50 W, 260 kHz prototype converter is built to verify the performance. Experiments of the proposed converter show an improvement of about 2% in the overall efficiency as compared to the previous ZVS flyback converter.
Design of the intelligent heat meter based on MSP430FW425

This paper describes an optimized hardware and software design for the heat meter. It is equipped with the international popular low-power consumption single-chip microcontroller MSP430FW425, temperature sensor Pt1000, impeller flow meter and zero energy-consuming magnetic sensor. They improve the precision and sensitivity of heat measurement. It also concludes the RFID module which has realized the function of advance payment.
A simple analytical switching loss model for buck voltage regulators

In this paper, a simple and accurate analytical switching loss model is proposed for high frequency synchronous buck voltage regulators. The proposed model uses simple equations to calculate the rise and fall times and uses piecewise linear approximations of the high side MOSFET voltage and current waveforms to allow quick and accurate calculation of switching loss in a synchronous buck voltage regulator. Effects of the common source inductance and other circuit parasitic inductances are included. Spice simulations are used to demonstrate the accuracy of the voltage source driver model operating in a 1 MHz synchronous buck voltage regulator at 12 V input, 1.3 V output. Switching loss was estimated with the proposed model and measured with Spice for load current ranging from 10-30 A, common source inductance ranging from 250-1000 pH, voltage driver supply ranging from 6-12 V.
EATA: Effectiveness based Aggregation Time Allocation algorithm for Wireless Sensor Networks

Aiming at the periodical data gathering application of wireless sensor network, the transmission delay and the network traffic loads are analyzed for the route-based data aggregation algorithm. It is then investigated how to minimize the network traffic within the data delay bound. An optimization problem is deduced based on the traffic aggregation model. Inspired by the hill-climbing algorithm, a centralized algorithm named as ldquoEffectiveness based Aggregation Time Allocation (EATA)rdquo is introduced and evaluated. In our simulation experiments, EATA can lead the network to a maximal traffic aggregation performance and good adaptability compared with other existing algorithms.
A New Multi-attribute Decision Making Method Based on Fuzzy Neural Network

Application of neural networks in fuzzy multi-attribute decision making is studied. A new fuzzy RBF neural network model, which uses triangular fuzzy numbers as inputs, is set up. Another important feature of the model is that the weights of the inputs fully reflect the effect of the decision-maker's preferences for uncertainty on decision results. Further, attribute weights determined by neural networks have the advantages of both subjective and objective weights. Due to the fact that ideal solution samples are introduced into the training samples, the decision results tends to be more in agreement with the decision-maker's intensions and, therefore, more scientific. Numerical illustrations prove the new model to be effective
A general multi-phase coupled-resonant-tank resonant converter

A general multi-phase Coupled-Resonant-Tank (CRT) converter is proposed to achieve automatic current sharing. There are Y-style or Δ-style structures. The series inductor (or capacitor) of each phase are connected by a Coupled impedance which is inductor, capacitor or short-circuit. For easy understanding, a two-phase CRT LLC resonant converter is made as an example to analyze the current sharing performance. There are three types including eight topologies derived from CRT LLC converter. The coupled impedance of each phase can be instead of open-circuit, short-circuit and other inductor or capacitor. The Fundamental Harmonic Analysis (FHA) is utility to estimate the current sharing performance. A 600W, 12V two-phase LLC converter with short-circuit coupled impedance prototype is built. The prototype verified the feasibility and demonstrated advantages of the proposed concept.
A poly-silicon TFT model for circuit simulation

This paper presents a polysilicon thin film transistor (TFT) model for circuit simulation. In this model, the effects of grain boundaries on the turn-on behavior of polysilicon TFT is considered. The potential barrier height is expressed in terms of channel doping, gate oxide thickness, grain size and external gate biases. Based on this, the analytical I-V characteristics are obtained for circuit simulation. Comparisons between the model and the experimental data have been made.
A self core reset and zero voltage switching forward converter topology

A self core reset and zero voltage switching (ZVS) forward converter topology is presented in this paper. By employing a simple auxiliary circuit, the proposed topology is able to achieve self reset of the power transformer without the use of the conventional tertiary reset winding, and its main switch can be turned on and turned off under ZVS independent of line and load conditions. This simplifies the power transformer, and the switching losses are substantially removed to improve the overall efficiency. Steady state analysis of the circuit is performed. Based on the analysis, a design procedure is presented, and the effects of the circuit parameters on the flux excursion of the power transformer are investigated to make sure self reset can be achieved without increasing the core losses. Simulation and experiment on a 5 V, 100 W prototype circuit operated at 200 kHz are carried out to verify the design, about 5% higher overall efficiency is obtained in the prototype converter than in its conventional counterpart.
A kalman filtering for linear discrete-time system with unknown inputs

This paper focuses on the joint input and state estimation for linear stochastic discrete-time systems. To obtain unique estimators that are optimal in the sense of being both least-squares and minimum-variance unbiased (MVU) and their recursive solution, an objective function of the sum of squared errors of outputs is first minimized with respect to an extended state vector including states and unknown inputs. A recursive solution of the extended state vector is then derived with the aid of matrix manipulations. Finally, appropriate matrix decomposition and transformation are used to extract the recursive solutions only involving the current states and unknown inputs from the recursive solution obtained in the previous step. This approach avoids excessive computation due to the dimensions of the matrices that increase with time. As a result, the resulting recursive solution is referred to as a general Kalman filter with unknown inputs (GKF-UI), which covers the most general case of unknown inputs so far in the literature without resorting to transforming the outputs and/or unknown inputs. The unknown inputs to be estimated by the proposed GKF-UI could be arbitrary signals without any prior information and the properties of the proposed GKF-UI are also examined. A numerical example with partial feedthrough from three unknown inputs is used to demonstrate the effectiveness and accuracy of the proposed algorithm.
A novel track-to-track association algorithm based on DWT

A novel track-to-track association algorithm based on multiple 1-D discrete wavelet transform (DWT) has been proposed. Since the signal and noise exhibit different features in wavelet domain, the ratio of energy in high resolution wavelet space to energy in low resolution scale space is introduced to establish hypothesis test model based on F-distribution. Two test methods have been presented to resolve the multi-dimension problem. Computer simulation results show that the algorithm is effective and has a good performance to distinguish two closely cross tracks or two closely parallel tracks as well.
A unified physical model of switching behavior in oxide-based RRAM

Excellent bipolar resistive switching (RS) behavior was achieved in TiN/ZnO/Pt resistive random access memory (RRAM) devices. A unified physical model based on electrons hopping transport among oxygen vacancies along the conductive filaments (CFs) is proposed to elucidate the RS behavior in the RRAM devices. In the unified physical model, a new reset mechanism due to the depletion of electrons in oxygen vacancies and the recovery of electron-depleted oxygen vacancies (VO +) with non-lattice oxygen ions (O2-) is proposed and identified.
Clustering algorithm of power load curves in distribution network based on analysis of matrix characteristic roots

In order to solve the problem of determining the clustering number of power load curves, this paper presented a clustering method based on the analysis of matrix characteristic roots. The clustering number is determined by the analysis result and the method is applied to the power load curves clustering. Firstly, the unified mathematical expression of the same type of load curves is established based on the changing pattern of load curves. Then, the equivalent relation between the clustering number of load curves and the number of larger characteristic roots is demonstrated. Besides, two criterions are presented to calculate the number of larger characteristic roots; and the number is the clustering number. After that, the load matrix is standardized and clustered by K-means algorithm. At last, the clustering result is evaluated by two indexes, the distance within classes and the distance between classes; and case simulation is given to prove the effectiveness and reasonability of the method proposed.
A novel analog implementation of capacitor charge balance controller with a practical extreme voltage detector

In this paper, a practical analog implementation of capacitor charge balance controller is presented, which is capable of achieving the optimal response for dc-dc Buck converters without relying on the knowledge of the nominal passive component (output inductor and capacitor) value. This ready-for-integration analog controller applies the output voltage curve analysis for deriving the formulas to optimize the response under the load transients. A simple extension is also offered for adaptive voltage positioning (AVP) application to power the modern processors. Furthermore, an operational amplifier (OPAMP) based peak/valley voltage detector is presented in place of using a fast or asynchronous ADC, as a result, lower cost, lower operating power consumption and fully analog implementation can be expected. Finally, simulation and experimental results are provided to validate the proposed schemes.