nils-herrmann/clean_scirepeval huggingface dataset:
An optimization method for single intersection’s signal timing based on SARSA(λ) algorithm

Considering the operating characteristic of intersection signal control system, the reinforcement learning method was introduced to the intersection signal control system due to its powerful adaptability. By defining the state sets, action sets and reward function for a reinforcement learning agent, a new intersection signal control model was established based on reinforcement learning, and an optimization method for single intersectionpsilas signal timing was presented using SARSA(lambda) algorithm. Analyses show that this new signal timing optimization method can make the intersection saturation degree approach to the optimum section as close as possible, improve the efficiency of the crossing, increase utilization rate of green light, and decrease intersection traffic delay and number of stops.
A potential field method for bottom navigation of autonomous underwater vehicles

The potential filed method is proposed to solve the bottom navigation problem of an underactuated autonomous underwater vehicle, including the bottom avoidance problem and the bottom following problem. The desired depth is treated as a stationary goal and the sea bottom is a moving obstacle in the bottom avoidance problem. And the desired altitude above the bottom is a moving goal and the maximum designed depth acts as a stationary obstacle in the bottom following problem. To improve the performance, the slope of sea bottom is added to the conventional potential forces as the relative velocity between the vehicle and the bottom, resulting in the dynamic potential field which is originally addressed for motion planning of mobile robots. A two layered hierarchical architecture is used to solve the motion control problem. The preliminary simulation results are provided to demonstrate that the proposed potential field based controller is easy for implementation with a satisfying performance.
Compact dual-band LTCC filter using folded resonators

This paper presents a dual-band bandpass compact low temperature co-fired ceramic (LTCC) filter using folded resonators. The passband of the proposed filter centred at 2.45 GHz and 5.2 GHz, and three transmission zeroes are generated. It is easy to couple the Π-type resonators of the proposed structure compared with the planar form. The filter is miniaturized by using the LTCC multilayers structure, and the size of the circuit is 5.5× 5.1 × 2.3 mm3.
EEG-based emotion classification using convolutional neural network

Electroencephalograph (EEG) signals can real-time reflect the brain activity. Using EEG signal to analysis human emotional states is a common research. Brain network analysis is a way to study brain emotional activity, it bases on the graph theory and finds the brain connectivity patterns. This way should calculate the matrices of functional connectivity of EEG and extract the characteristics from the matrices. This paper describes a straightforward way to use the matrices of functional connectivity and extract feature by using Convolution Neural Network (CNN). CNN was employed to accomplish several task: 1) 2-classification task, 2) 3-classification task and 3) 4-classification task, and the average accuracy of 2-classification task is about 85%, 3-classification task is about 78% and 4-classification is about 75%. The study demonstrations that the matrices of functional connectivity carries important informations about the emotional states, and the CNN model can extract the distinguishing featurse to differentiate the emotional states.
Performance optimization for steam generator level control based on a revised simultaneous perturbation stochastic approximation algorithm

With the development of intelligent technology, the nuclear power plant(NPP) is getting more and more smarter. For the traditional nuclear power plant, the performance of the steam generator level control was greatly determined by a group of preset control parameters. Usually, these parameter settings were not optimal because the tuning process was experience-based, cumbersome and time-consuming. To improve the control performance and make the NPP more smarter, in this paper, a revised Simultaneous Perturbation Stochastic Approximation algorithm(SPSA) was proposed to optimize the control parameters of the steam generator level control system. The effectiveness of this method has been demonstrated through simulation experiments.
LFT uncertain model validation with time and frequency domain measurements

We study a model validation problem pertaining to linear fractional transform (LFT) uncertainty models. We extend previous validation approaches, based upon either time or frequency measurements, to one using simultaneously time and frequency domain data. We show that this problem can be reduced to two independent convex feasibility tests, each of which corresponds to the time or frequency domain data alone, and each can be verified numerically using available algorithms and software programs. The merit of such a mixed time and frequency domain approach, therefore, lies in that not only can it accommodate the two distinctively different types of measurement data simultaneously, but also from a computational standpoint it will not suffer from a complexity growth beyond that associated with the existing time domain tests.
The AmphiHex: A novel amphibious robot with transformable leg-flipper composite propulsion mechanism

The amphibious robot is so attractive and challenging for its broad application and its complex working environment. It should walk on rough ground, maneuver underwater and pass through transitional terrain such as sand and mud, simultaneously. To tackle with such a complex task, a novel amphibious robot (AmphiHex-I) with transformable leg-flipper composite propulsion is proposed and developed. This paper presents the detailed structure design of the transformable leg-flipper propulsion mechanism and its drive module, which enables the amphibious robot passing through the terrain, water and transitional zone between them. A preliminary theoretical analysis is conducted to study the interaction between the elliptic leg and transitional environment such as granular medium. An orthogonal experiment is designed to study the leg locomotion in the sandy and muddy terrain with different water content. Finally, basic propulsion experiments of AmphiHex-I are launched, which verified the locomotion capability on land and underwater is achieved by the transformable leg-flipper mechanism.
Frequency-selective rasorber based on equivalent circuit analysis

In this paper, a frequency-selective rasorber (FSR) with a high efficiency transmission window is proposed for stealth and security applications. By utilizing a new equivalent circuit model to generate the transmission window, there is no lumped and distributed inductor/capacitor (LC) element is used in this structure. Moreover, communication security and stealth performance are promised on the account of the low reflection at operation band. The reflection power is lower than 10 percent from 2.8 GHz to 5.7 GHz, while the transmission window locates at 5.6 GHz with 0.17 dB insertion loss. Finally, simulated results are consistent with circuit computed results, and the rasorber is endurable with the oblique incidence.
Inactivation Effect of Low-Temperature Plasma on Pseudomonas aeruginosa for Nosocomial Anti-Infection

Disinfection and sterilization in hospitals and other public places have always been the focus of attention. In our studies, dielectric barrier corona discharge (DBCD) was used to generate low-temperature plasma (LTP) to treat Pseudomonas aeruginosa (P. aeruginosa, one kind of bacteria responsible for nosocomial infections). The survival colonies of P. aeruginosa were counted with the standard plate-counting method after 30-, , and 120-s exposures to DBCD. We discovered that LTP could lead to more than 5-log reduction of P. aeruginosa after 120-s treatment. Further experiments indicated that OH and excited N2 in LTP and lower pH value in bacterial suspension might synergistically inactivate P. aeruginosa by destroying its outer structure.
An Approach for Anomaly Diagnosis Based on Hybrid Graph Model with Logs for Distributed Services

Detecting runtime anomalies is very important to monitoring and maintenance of distributed services. People often use execution logs for troubleshooting and problem diagnosis manually, which is time consuming and error-prone. In this paper, we propose an approach for automatic anomaly detection based on logs. We first mine a hybrid graph model that captures normal execution flows inter and intra services, and then raise anomaly alerts on observing deviations from the hybrid model. We evaluate the effectiveness of our approach by leveraging logs from an IBM public cloud production platform and two simulated systems in the lab environment. Evaluation results show that our hybrid graph model mining performs over 80% precision and 70% recall and anomaly detection performs nearly 90% precision and 80% recall on average.
Bus signal priority method assessment based on multiple attribute group decision

This thesis puts forward a bus signal priority assessment index system, which including bus traffic efficiency, intersection traffic efficiency, implementation difficulty factors of methods and so on. Because there are some missing, uncertain or fuzzy indices, and relevance between indices. And decision-makers would have their subjective preferences. The thesis then puts forward a bus signal priority assessment method based on uncertain multiple attribute group decision. At the last part, the thesis takes Guangzhou Tianhe Road and Tiyudong Road intersection as an example to assess bus signal priority method, including no priority, all priority and general fuzzy control priority, and verify the effectiveness of the method.
A study on Business Process Reengineering and organization models based on CAS theory

Understanding and perceiving of BPR (Business Process Reengineering) is the bases and the linchpins of successful BRP implementation. Understanding BRP from a CAS (Complexity Adaptive System) point of view will be helpful to our perception to BPR in focus. In this paper, commencing with CAS theory, we analyze, thoroughly and comprehensively, the properties of the Complexity Adaptive System, which are possessed by the Business Process Reengineering, and on the basis of which, an enterprise organization administration model, supported by CAS theory, is proposed.
NFC Loop Antenna in Conjunction With the Lower Section of a Metal Cover

This letter proposes a near-field communication (NFC) antenna for smartphones with a metal cover that includes an embedded narrow slot, therein splitting the metal cover into upper and lower sections. The proposed NFC antenna is a simple loop structure that is formed by incorporating a three-dimensional coupling strip with the upper edge of the metal cover in the lower section. Because this antenna structure can substantially reduce the eddy current, excellent inductive coupling can be achieved through the clearance zone of the narrow slot. The proposed NFC antenna is relatively thin and achieves excellent performance in the read/write mode. Furthermore, in the card emulation mode verified by Europay, MasterCard, and Visa test, it even surpasses the performance of certain other NFC antennas in smartphones with non-metal covers.
Sequence Unscented Kalman Filtering algorithm

Unscented Kalman Filter (UKF) has been proved to be a superior alternative to the extended Kalman filter (EKF) when solving the nonlinear system in recent years. In order to improve the real-time of the UKF, A new kind of UKF called Sequence UKF is proposed in this paper. Like Rao-Blackwellised Unscented Kalman Filter (RBUKF) , it also deals with nonlinear stochastic discrete-time system with linear measurement equation, however it can decrease the computational complexity with the same filtering accuracy. This algorithm reduces the measurement vector to scalars in measurement-update of UKF by sequence method, so it can avoid inversing the covariance of measurement and reduce a great mount of computation bound. Special algorithm is deduced in this paper. The high performance of sequence UKF is verified by using Monte Carlo simulations.
Vision-based Density Detection of Traffic Flow in Urban Intersection in the Daytime

In urban intersection of intelligent control system, detection of rows of vehicles is essential to the control algorithm, and density estimation method and vision-based detection algorithm are presented in this paper for sake of the limitation of using loop detectors method. Firstly, background segmentation and rebuilding is introduced and algorithm for vehicles segmentation in HSV color space is discussed. Then length and density of traffic flow are calculated. Finally, experimental results and analysis are included
Study on Interior Design Based on Building Information Modeling

The major computer aided software for traditional interior design is AutoCAD. The auxiliary software normally can only perform two-dimensional plane, vertical, and profiles design, and the design effect is not very good. By use of Building Information Modeling software, the technical problems of indoor 3D design can be solved. Building Information Modeling aided design has the advantages of visualization, simulation, optimization, and coordination. Information visualization design of BIM technology is more comprehensive, more intuitive and more efficient, which can provide new design thinking and design methods for interior designers, greatly improving the work efficiency of interior design.
An adaptive meshless method for spectrally resolved bioluminescence tomography

As a novel optical molecular imaging technology, bioluminescence tomography (BLT) has become a research focus which can localize and quantify an internal light source with the bioluminescent signal on the external surface of a small animal. However, BLT is ill-posed because of complex photon propagation in the biological tissue and noisy boundary measured data. Moreover, the disadvantage of the finite element method (FEM) commonly used in BLT is emerged gradually due to the troublesome mesh discretization. Therefore, an adaptive meshless method is presented to perform a quantitative reconstruction of the bioluminescent source for spectrally resolved BLT in this contribution, which not only can reduce the ill-posedness of BLT effectively through the application of multi-spectral information but also can avoid the time-consuming mesh generation. In addition, the reconstruction can be largely improved using adaptive technology based on a posteriori error estimation. Finally, the performance of this method is evaluated by numerical simulation experiments.
Adaptive control of an isolated intersection based on the complete phase group

In reality, traffic demands are quite random, which usually deviate from the application conditions of a certain kind of signal control method and compromise the efficiency of traffic control. To solve such a problem, taking a typical isolated intersection as the research object, the adaptive control of an isolated intersection based on a complete phase group is proposed, which can automatically optimize phase sequence, phase time and cycle by responding to the strongly random traffic demands in real time. Considering the limited signal phases in a complete phase group, the enumeration method is utilized to determine the signal phase and its allowed maximum phase time in the next signal stage. In order to verify the superiority of the proposed adaptive control, extensive simulations have been implemented on Vissim 5.4, compared with fixed timing control, segment timing control and full-actuated control, simulation results fully demonstrate the superiority of this proposed adaptive control in terms of reducing the average vehicle delays while barely affecting the average vehicle stops and total throughputs.
A Novel Hybrid Fuel Cell Power System

A hybrid fuel cell power system is proposed in this paper It consists of a fuel cell, an isolated uni-directional converter, a bi-directional converter, an inverter and a battery. A novel uni-directional converter, hybrid full bridge LLC resonant converter, is proposed and acts as a uni-directional converter in the system. It has several advantages such as: ZVS capability from nearly zero to full load; the rectifier diodes sustain only the output voltage, and realize ZCS; the input current ripple and output filter can reduced; and; high efficiency can be achieved over a wide input voltage range. A new three-level bi-directional converter is employed in the system as the core of the energy management control. Compared with the traditional bidirectional converter, it has some advantages as follow: The structure is simple, and easy to control; the voltage stress on the switches is just half of the V H ; the inductor can be reduced significantly, which lead to fast dynamic response. In order to ensure the system operates with high efficiency, energy management is introduced into the system. The energy management method is proposed in the paper Experimental results are shown to verify the theoretical analysis.
Unsteady Aerodynamic Force Modeling via S-BT Method

The main goal of present paper is to construct an efficient reduced order model (ROM) for unsteady aerodynamic force modeling. Balanced Truncation (BT) is presented to address the problem. For conventional BT method, it is necessary to compute exact controllability and observability grammians. Although it is relatively straightforward to compute these matrices in a control setting where the system order is moderate, the technique does not extend easily to high order system. In response to the challenges, Snapshots-BT (S-BT) method is introduced for high order system ROM construction. The outline idea of S-BT method is that Snapshots of primary and dual system approximate the controllability and observability matrices in frequency domain. The method has been demonstrated for AGARD 445.6 wing aeroelastic system. All the results indicate S-BT based ROM is efficient and accurate enough to provide a powerful tool for unsteady aerodynamic force modeling. Keywordsbalanced truncation; snapshot; reduced order model; unsteady aerodynamic force
A Scalable Large-Signal Multiharmonic Model of AlGaN/GaN HEMTs and Its Application in C-Band High Power Amplifier MMIC

A scalable electrothermal large-signal AlGaN/GaN HEMTs model for both fundamental and multiharmonics is presented based on the modified Angelov model. To obtain accurate scalability of the electrothermal model, a simple empirical expression is proposed for the geometric and power-dissipation-dependent nonlinear thermal resistance <inline-formula> <tex-math notation="LaTeX">$R_{{\mathrm {th}}}$ </tex-math></inline-formula>. Only one additional parameter with linear scaling rule is needed in the drain-source current (<inline-formula> <tex-math notation="LaTeX">$I_{{\mathrm {ds}}}$ </tex-math></inline-formula>) model for a scalable large-signal multiharmonic model. The proposed model has been validated by different AlGaN/GaN HEMTs characterized by on-wafer measurements. It shows that the presented scalable model can well predict the dc <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>, pulsed <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>, scattering (S) parameters, and large-signal performance up to third harmonic. Furthermore, to further validation, a C-band power amplifier is designed. The amplifier is realized using the second-harmonic tuned approach to enhance the efficiency. Measurement results show that the GaN high power amplifier (HPA) microwave monolithic integrated circuit (MMIC) exhibits more than 40% power-added efficiency and 60-W output power (<inline-formula> <tex-math notation="LaTeX">$P_{{\mathrm {out}}}$ </tex-math></inline-formula>) with associated gain of 25 dB in 5–6 GHz measured at 28-V drain voltage and pulse signal with 100-<inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> pulsewidth and 10% duty cycle. The area of the chip is 3.2 mm <inline-formula> <tex-math notation="LaTeX">$\times5.3$ </tex-math></inline-formula> mm (16.96 mm<sup>2</sup>). These results show that the proposed model will be useful for high-efficiency HPA MMIC design.
EASIER Sampling for Audio Event Identification

An audio event refers to some specific audio sound which plays important role for video content analysis. In our previous work [M. Xu et. al., (2004)], we have established audio event identification as an audio classification task. Due to the large size of audio database, representative samples are necessary for training the classifier. However, the commonly used random selection of training samples is often not adequate in selecting representative samples. In this paper we present EASIER sampling algorithm to select those data which more efficiently represent audio data characters for audio event identifier training. EASIER deterministic ally produces a subsample whose "distance" from the complete database is minimal. Experiments in the context of audio event identification show that EASIER outperforms simple random sampling significantly
LogSed: Anomaly Diagnosis through Mining Time-Weighted Control Flow Graph in Logs

Detecting execution anomalies is very important to monitoring and maintenance of cloud systems. People often use execution logs for troubleshooting and problem diagnosis, which is time consuming and error-prone. There is great demand for automatic anomaly detection based on logs. In this paper, we mine a time-weighted control flow graph (TCFG) that captures healthy execution flows of each component in cloud, and automatically raise anomaly alerts on observing deviations from TCFG. We outlined three challenges that are solved in this paper, including how to deal with the interleaving of multiple threads in logs, how to identify operational logs that do not contain any transactional information, and how to split the border of each transaction flow in the TCFG. We evaluate the effectiveness of our approach by leveraging logs from an IBM public cloud production platform and two simulated systems in the lab environment. The evaluation results show that our TCFG mining and anomaly diagnosis both perform over 80% precision and recall on average.
A dynamic route guidance arithmetic based on reinforcement learning

The links' weights of road networks are important parameters in the past researches on dynamic traffic route guidance. But they are usually unavailable on the complicated traffic conditions. This research is focused on the development of a dynamic route guidance arithmetic based on reinforcement learning. The arithmetic need not links' weights and made used of data provided by the probe vehicles equipped with GPS sensors. The numbers of the intersections and the time segments were taken as the states. The vehicles' running actions between the intersections were considered as the transition actions from one state to another, and the time costs were described by Q-factors. By observing probe vehicles running in road network, Q-factors were iterated so that the optimal route-choice police could be obtained. Finally, the simulation was processed based on the electronic map data of Guangzhou city. The results indicate that the arithmetic is quite effective on the complex traffic conditions.