nils-herrmann/clean_scirepeval huggingface dataset:
Improved discrete particle swarm optimization based on edge coding and multilevel reduction strategy for larger scale TSP

In order to improve particle swarm optimization (PSO) to solve complex and large scale discrete optimization problems, the paper introduces an improved discrete particle swarm optimization (IDPSO) based on edge coding and multilevel reduction strategy. First, redefine the velocity and position of the particle based on edge-coding, and adopted converted insertion of the edge to update the information of the particle. Next, introduce multilevel reduction strategy to improve the global convergence ability of the algorithm. The improved algorithm is applied to solve representative cases of traveling salesman problem (TSP), The results show that the improved DPSO is efficient and valid on the complex TSP, and the multilevel reduction strategy can contribute to develop the ability of PSO when facing up to the complex and large scale problems greatly.
Fabrication of 40 kHz receiving piezoelectric micro-machined ultrasonic transducers

This paper presents the fabrication of piezoelectric micro-machined ultrasonic transducers (PMUT) used in acoustic location field in the air. The transducer consists of piezoelectric ZnO thin film and the membrane made of Si3N4. The calculation of the vibration mode of PMUT has been made by the FEM method. Experiment results indicate the resonant frequency of the PMUT is 43.7 kHz. The initial results on receiving experiment using the PMUT as the receiver with the matching circuit are also presented.
A soft measurement method of conductance on the SOFC electrode

For the requirements of the SOFC electrode conductance measurement process, a system model with a three-tiered structure and a soft measurement model of SOFC electrode conductance are established. In view of measurement model being vulnerable to the change of temperature, the measurement experiment adopts programming calefactive control by setting temperature segments of different lengths. The nominal temperature segment range provided by the temperature control instrument is limited on the spot. Under this condition, this paper presents a soft measurement method by introducing pre-dislocation loop technology which is used to position the temperature programming operation range, so the measurement system can freely define the length of the temperature programming segment, and the heating process achieves the seamless extension. In the application of this method, the system makes a real-time measurement on the SOFC electrode conductance continuously with 8∼10 hours as a period. The experiment results show that, the SOFC measurement process is stable, with high accuracy, efficiency, and accessibility.
Topology Aware Task Allocation and Scheduling for Real-Time Data Fusion Applications in Networked Embedded Sensor Systems

In networked embedded sensor systems, data fusion is a viable solution to significantly reduce energy consumption while achieving real-time guarantee. Emerging data fusion applications demand efficient task allocation and scheduling techniques. However, existing approaches can not be effectively applied concerning both network topology and wireless communications. In this paper, we formally model TATAS, the topology-aware task allocation and scheduling problem for real-time data fusion applications, and show it is NP-complete. We also propose an efficient three-phase heuristic to solve the TATAS problem. We implement our technique and conduct experiments based on a simulation environment. Experimental results show that, as compared with traditional approaches, our technique can achieve significant energy saving and effectively meet the real-time requirements as well.
Towards improving performance of galvanic coupling Intra-Body Communication

This paper investigates how to improve the communication performance of galvanic coupling Intra-Body Communication (IBC). Towards this objective, an in vivo measurement is firstly carried out to obtain the channel characteristics of human body in the frequency range from 100 Hz to 1 MHz. Severe gain variation and phase non-linearity are observed in the frequency response lower than frequency of 200 kHz. Then pulse shaping and channel equalization are introduced for QPSK and 16QAM modulation systems to eliminate the channel impairments in both simulations and experiments. The results show that root raised cosine pulses can significantly reduce Bit Error Rate (BER). Furthermore, the channel equalization improves BER 1-10% for QPSK, and more than 20% for 16QAM. The results indicate pulse shaping and channel equalization are effective ways for BER reduction, which are very important for the design of IBC system.
World population projections using metabolic GM (1,1) model

Forecasts of population size allow city planners, economists, public agencies, environmentalists, and social scientists to prepare for what is to come, so the research on population projections has become a focus of demographers' research. In the study, population system is regarded as a grey system and a method based on GM (1,1) model from Grey system theory is introduced to population projections. Two key aspects of the method are crucial for obtaining best accuracy of prediction. They are the choice of the length for the original data to be used in the model and the adoption of the metabolic GM (1,1) model in prediction. The former determines what initial data to be used while the latter describes an iteration process on how to proceed to predict. The method is then applied to the projections of world population. The results show that in 2012 world population will surpass 7 billion; in 2029 it will grow beyond 8 billion and in 2050 it will be between 8.9 and 9.4 billion, which is in accordance with the latest projections from the UN. The findings show the metabolic GM (1,1) model is an effective mathematical means in population projections.
Effects of Oxygen Plasma and Dopamine Coating on Poly(Vinylidene Fluoride) Microfiltration Membrane for the Resistance to Protein Fouling

Poly(vinylidene fluoride) (PVDF) membrane was widely employed for filtration owing to its good mechanical property, thermal stability, and solvent resistance. However, the hydrophobic surface of PVDF might result in protein adsorption and the reduction of permeate flux. This paper proposed two approaches, O2 plasma treatment and dopamine coating, to study the protein fouling behavior on PVDF membranes. Both O2 plasma modified and dopamine coated PVDF membranes showed reduced water contact angles. Moreover, O2 plasma resulted in higher surface area and higher surface electronegativity, while dopamine coating caused the reduction of total surface area of membrane and imparted positive charges. electron spectroscopy for chemical analysis characterizations confirmed the presence of oxygen functionalities that validated the functionalities accounted for the negative charges. The fouling resistance to bovine serum albumin (BSA) was promoted by O2 plasma treatment, where the time to reach fouling was delayed by more than 10 min and the flux was higher on the modified PVDF than that on the pristine membrane. Further reduction of membrane fouling was achieved by prolonging the plasma treatment time, which resulted in more negatively charged PVDF surface. On the other hand, rapid flux reduction was observed on the dopamine coated PVDF membrane, whereas the resistance to protein was limited. The results of dynamic BSA adsorption indicated that the membrane fouling was affected by the overall resulted surface properties including surface electrical charge, surface wettability, and surface area. Moreover, oxygen plasma treatment proved to promote the filtration performance effectively, which is presumably due to the surface charge effects. On the other hand, the adhesive dopamine coating resulted in stronger protein adhesion and therefore fast flux loss. The obtained results provide alternative surface modification methods for microfiltration membranes with higher efficiency and better fouling resistance.
On Improving Real-Time Interrupt Latencies of Hybrid Operating Systems with Two-Level Hardware Interrupts

In this paper, we propose to implement hybrid operating systems based on two-level hardware interrupts. We analyze and model the worst-case real-time interrupt latency for RTAI and identify the key component for its optimization. Then, we propose our methodology to implement hybrid operating systems with two-level hardware interrupts by combining the real-time kernel and the time sharing OS (Operating System) kernel. Based on the methodology, we discuss the important issues for the implementation. Finally, we implement a hybrid system called RTLinux-THIN (Real-Time LINUX with Two-level Hardware INterrupts) on the ARM architecture by combining ARM Linux kernel 2.6.9 and μC/OS-II. We conduct experiments on a set of real application programs including mplayer, Bonnie, and iperf, and compare the interrupt latency and interrupt task distributions for RTLinux-THIN (with and without cache locking), RTAI, Linux, and Linux with RT patch on a hardware platform based on Intel PXA270 processor. The results show that our scheme not only provides an easy method for implementing hybrid systems but also achieves the performance improvement for both the time sharing and real-time subsystems.
Stochastic Multiview Hashing for Large-Scale Near-Duplicate Video Retrieval

Near-duplicate video retrieval (NDVR) has been a significant research task in multimedia given its high impact in applications, such as video search, recommendation, and copyright protection. In addition to accurate retrieval performance, the exponential growth of online videos has imposed heavy demands on the efficiency and scalability of the existing systems. Aiming at improving both the retrieval accuracy and speed, we propose a novel stochastic multiview hashing algorithm to facilitate the construction of a large-scale NDVR system. Reliable mapping functions, which convert multiple types of keyframe features, enhanced by auxiliary information such as video-keyframe association and ground truth relevance to binary hash code strings, are learned by maximizing a mixture of the generalized retrieval precision and recall scores. A composite Kullback-Leibler divergence measure is used to approximate the retrieval scores, which aligns stochastically the neighborhood structures between the original feature and the relaxed hash code spaces. The efficiency and effectiveness of the proposed method are examined using two public near-duplicate video collections and are compared against various classical and state-of-the-art NDVR systems.
Multichannel Hankel Matrix Completion Through Nonconvex Optimization

This paper studies the multichannel missing data recovery problem when the measurements are generated by a dynamical system. A new model, termed multichannel low-rank Hankel matrices, is proposed to characterize the intrinsic low-dimensional structures in multichannel time series. The data recovery problem is formulated as a nonconvex optimization problem, and two fast algorithms (AM-FIHT and RAM-FIHT), both with linear convergence rates, are developed to recover the missing points with provable performance guarantees. The required number of observations is significantly reduced, compared with conventional low-rank completion methods. Our methods are verified through numerical experiments on synthetic data and recorded synchrophasor data in power systems.
Analyses and judgment methods of single-phase broken-line fault for loaded distribution line

The frequency of broken-line fault occurred in distribution network is increasing over the past years. Broken-line fault will create negative sequence and zero sequence voltages, which will seriously affect the normal work of loads. However, distribution network has not equipped with special protection against broken-line fault yet. In this paper, single-phase broken-line fault in distribution network is studied, features of the voltages at both ends of the fault line and the current flowing through the fault line are analyzed by using symmetrical component method combined with phasor diagrams when various single-phase broken-line fault occurs, and it proposes the main criterion and the additional criterions based on the theoretical analyses, as well as a method to judge the section that the broken-line fault located. Finally, simulation analysis is carried out through PSCAD/EMTDC, which ensures the correctness of the theoretical analysis and the protection criterions.
Single sideband radio over fiber transmission with an integrated polymeric waveguide ring resonator

Besides the general advantages of microwave photonic filters for signal processing, the integrated waveguide ones have their potential to bring down volume and weight of systems. An integrated polymeric waveguide ring resonator was designed and fabricated by a simple UV-based soft-lithography technology, with which the single sideband filtering response was realized and 20 Mbps QPSK signal carried by 14.35 GHz microwave was transmitted successfully over 25 km single mode fiber.
Simulation and verification of the virtual memory management system with MSVL

The paging mechanism is widely used in most modern systems to handle the virtual memory. Many page replacement algorithms have been proposed. Therefore, the cor-rectness and reliability of virtual memory management systems become very important. It is essential to formalize and verify the system in a formal way. In this paper, we model the virtual memory management system with MSVL, which is a parallel programming language used for the modeling, simulation and verification of software and hardware systems. Then we employ the model checking approach based on MSVL to verify the interval related properties and periodic repeated properties of the system.
A bidirectional vector associative memory architecture with application to neural networks

A bidirectional architecture for associative memory (AM) capable of vector arithmetic operations is proposed. Conventional bit-operation and word-operation are generalized to row and column operations, respectively. By introducing a pair of masking and tagging mechanisms, the proposed architecture demonstrates a symmetric functionality such that associative memory can be performed in both column and row directions. A set of built-in vector arithmetic and logic units (VALU) are designed to perform the basic vector operations, which offers O(max{n,m}) speed-up for vector operations than conventional AM at a linear (O(n+m)) cost for realizing an n/spl times/m AM array. As an applicational example, an associative processing implementation of artificial neural networks is considered.
Incremental least squares policy iteration in reinforcement learning for control

We propose a novel algorithm of reinforcement learning for control problems which combines value-function approximation with linear architectures and approximate policy iteration. This algorithm improves least-squares policy iteration (LSPI) methods by using incremental least-squares temporal-difference learning algorithm (iLSTD) for prediction problems. We show that the novel algorithm has less computing complexities than LSPI, and has the same performance as LSPI in learning optimal policies.
In-Image Accessibility Indication

There are about 8% of men and 0.8% of women suffering from colorblindness. Due to the loss of certain color information, regions or objects in several images cannot be recognized by these viewers and this may degrade their perception and understanding of the images. This paper introduces an in-image accessibility indication scheme, which aims to automatically point out regions in which the content can hardly be recognized by colorblind viewers in a manually designed image. The proposed method first establishes a set of points around which the patches are not prominent enough for colorblind viewers due to the loss of color information. The inaccessible regions are then detected based on these points via a regularization framework. This scheme can be applied to check the accessibility of designed images, and consequently it can be used to help designers improve the images, such as modifying the colors of several objects or components. To our best knowledge, this is the first work that attempts to detect regions with accessibility problems in images for colorblindness. Experiments are conducted on 1994 poster images and empirical results have demonstrated the effectiveness of our approach.
OTH passive location based on the troposcatter signal group delay and beamspace MUSIC

The Over-The-Horizon (OTH) locating of radiation source can be realized by the troposcatter propagation of electromagnetic (EM) signals. This paper studies the troposcatter signal group delay for target ranging and proposes a modified beamspace MUSIC to estimate the arrival azimuth angle of the troposcatter signal. Finally, the OTH target can be located by the ranging and azimuth angle estimation results.
The Model of Vehicle Position Estimation and Prediction Based on State-Space Approach

As one part of ITS (Intelligent Transportation System), IRS (Intelligent Road System) focus on improving the road safety and operation efficiency of highway system based on the idea of cooperation between road infrastructure and vehicles. Many IRS applications such as Collision Avoidance, Automatic Lane Changing and others are principally based on the knowledge of the accurate geographical locations of interrelated vehicles nearby. Based on the state-space approach, this paper addresses the distributed position estimation problem. Specially, the state transfer matrix and measure matrix of the vehicle are established. And based on vehicle dynamics and Kalman filtering, the model of the position state estimation and prediction are formulated. Finally, we found that this approach can get more accurate results by the simulation under condition that the cooperative vehicle communication is available.
User Vitality Ranking and Prediction in Social Networking Services: A Dynamic Network Perspective

Social networking services have been prevalent at many online communities such as Twitter.com and Weibo.com, where millions of users keep interacting with each other every day. One interesting and important problem in the social networking services is to rank users based on their vitality in a timely fashion. An accurate ranking list of user vitality could benefit many parties in social network services such as the ads providers and site operators. Although it is very promising to obtain a vitality-based ranking list of users, there are many technical challenges due to the large scale and dynamics of social networking data. In this paper, we propose a unique perspective to achieve this goal, which is quantifying user vitality by analyzing the dynamic interactions among users on social networks. Examples of social network include but are not limited to social networks in microblog sites and academical collaboration networks. Intuitively, if a user has many interactions with his friends within a time period and most of his friends do not have many interactions with their friends simultaneously, it is very likely that this user has high vitality. Based on this idea, we develop quantitative measurements for user vitality and propose our first algorithm for ranking users based vitality. Also, we further consider the mutual influence between users while computing the vitality measurements and propose the second ranking algorithm, which computes user vitality in an iterative way. Other than user vitality ranking, we also introduce a vitality prediction problem, which is also of great importance for many applications in social networking services. Along this line, we develop a customized prediction model to solve the vitality prediction problem. To evaluate the performance of our algorithms, we collect two dynamic social network data sets. The experimental results with both data sets clearly demonstrate the advantage of our ranking and prediction methods.
Application of extension method to selecting of solar power systems

When designing the solar power generation system is in face of the variety of solar cell, the user must consider not only the needs of the load and also the price of the solar cell, weight, annual power generating capacity (APGC) and the maximum power. It is an important task to find the optimal power generation system with many parameters. Therefore, this paper presents an estimation method based on the extension theory. Using the estimation method can be quick to select the optimal solar power system. The paper proposed the method not only to provide a useful estimated tool for the solar system engineers, but also to supply the important reference with the installation of solar systems to the consumer.
One novel remote sensing method for on-board voltage regulator in computing system

Differential remote sensing has been popularly used in voltage regulator to ensure a high regulation accuracy requirement for processor supply voltage. One new remote sensing method by using normal VR controller is proposed in this paper to achieve similar high regulation accuracy as that by using true differential remote sensing method for output voltage. Advantages of it are analyzed in detail and design considerations are also analyzed as well. Finally, test is conducted for normal VR controllers to verify it's one effective way to achieve good output voltage regulation accuracy for VRs.
Variable stiffness estimation of a Series Elastic Actuator

This paper focuses on estimating the variable stiffness of the Series Elastic Actuator(SEA) through torque and relative position between the motor and the payload measurements. Although position and torque sensors are effective in control schemes, the exorbitant price are not convenient for the application of robotics. Through the mathematical modeling, the variable stiffness of the series elastic actuator sometimes is difficult to obtain accurately. It should be noticed that, an accurate estimation of the variable stiffness is important. In this paper, a Kalman filter based on Taylor expansion is designed to estimate the variable stiffness. Specially, in order to improve the accuracy of the model, the process is divided into two steps for solving the problem of hysteresis, and the recursive least squares algorithm is used to estimate the spring stiffness. Then, according to the accurate spring stiffness value, an estimator of the variable stiffness is presented. The effectiveness of the proposed method on variable stiffness identification is proved through experiments.