nils-herrmann/clean_scirepeval huggingface dataset:
Application of cloud computing in physical activity research

Accelerometers-based devices provide a convenient and efficient way to measure the physical activity, but they are not convenient enough for general users. To improve the ease of use, we developed a novel accelerometer-based cloud-computing system that can automatically upload the recorded acceleration data by telemetry to a cloud end server for further analysis. This automatic cloud computing actimeter system is composed of a miniature wireless actimeter (KY9), a router and a cloud server. The KY9, taped on the body of the users, senses the bodily tri-axis acceleration signals. The acquired acceleration signals are automatically and wirelessly transmitted to the router, which in turn are automatically uploaded to the cloud server. Finally the data are stored and analyzed in the cloud server. The cloud server contains several linear and non-linear analyses for the acceleration signals and further provides quantitative information for exercise and sleep. The users or the investigators can view the analysis results through a standard web browser without installing additional application programs. The system is characteristic of miniature terminal, automatic wireless transmission, long-term recording and on-line analysis. The cloud platform enables accelerometers to be applied in the field of healthcare, and the automatic wireless transmission greatly improves convenience for both the users and the investigators.
Avoidance Response of Young Rock Carp (Procypris rabaudi Tchang) to Gas Supersaturation as an Environmental Toxicity

Avoidance response can be measured as starting for sublethal toxicity, and serve as a tool for environmental risk assessment and analysis of toxicological impact. In order to investigate behavioral alterations of young rock carp (Procypris rabaudi Tchang) induced by gas supersaturation, a two-choice laboratory apparatus and generated gas supersaturated water system was designed by our laboratory. With these laboratory systems, experiments were conducted to examine the avoidance behavior of rock carp exposed to gas supersaturation. Avoidance behavior was measured under different supersaturated water (105,115,125,135, &145%) and equilibrated water at 25°C water-temperature and 0.08m waterlevel. The different avoidance percentage about the supersaturated water (105,115,125,135, &145%) were highly significant difference by a simple factor experiment of ANOVA. The avoidance percentage was bigger than 90% when gas supersaturation exceeded 135%, while the avoidance percentage was declining extremely with the gas supersaturation reducing. When gas supersaturation was below 115% the avoidance percentage was lower than 15%, and showed a preference for supersaturated water. Data from this experiment were presented to exemplify alterations in behavior of young rock carp under gas supersaturation conditions. The movement analyses can be used to identify characteristic behavioral responses to the supersaturated water, and assist in risk assessment the effects of high dams on aquatic ecosystem.
Improved method based on NMF for face recognition

A method of dealing with NMF (non-negative matrix factorization) basis to enhance face recognition rate is introduced in this paper. Firstly, we use discrete wavelet transformation to produce a representation in the low frequency domain, and get basic matrix according to the NMF method. Secondly, parts of face features which possess outstanding performance are extracted by threshold value judgments, and they are used to form optimized facial subspace feature. The training and testing images are projected to the optimized subspace feature. Finally, support vector machine is used for classification. Experiments show that the improved method is workable, especially under the circumstance of partial occlusion, it achieves remarkable effects.
A parallel architecture for feature extraction in content-based image retrieval system

Although it is possible to retrieve images from database using a unique identification defined by a human operator as an index to images, it is more convenient and natural to search images based on their contents. The principle of content-based image retrieval (CBIR) system is to retrieve images based on the content of the images. One of the important components in CBIR system is to extract the visual features of the images for performing more abstract analysis. However, some of these features are computationally expensive. To solve this issue, a flexible parallel architecture has been proposed to improve the extraction time for the system. This architecture provides the software system with the flexibility of adding and removing any visual features from the system. Thus, a system becomes more intelligent and so it is able to adapt changes caused by the replacement of more appropriate visual features for representing the images.
Intrusion Detection Using Isomap and Support Vector Machine

Intrusion detection is still a crucial issue for network security. Support vector machine (SVM) has been successfully applied in intrusion detection systems. However, for further improvement in performance, data dimension reduction should have drawn special attention. This paper proposes a scheme using popular non-linear dimension reduction tool Isomap and one-class support vector machine to detect U2R (user to root) and R2L (remote to local) intrusions. Experiment results on KDDCUP 99 datasets show that our scheme achieves high detection rate for R2L or U2R intrusions and significantly low false positive rate compared with one class SVM alone. It is justified that data dimension reduction is a worthwhile preprocessing stage for achieving high performance in the intrusion detection system.
Establishment of Early Warning System for Accidental Water Pollution Incidents in China

In recent years a high number of accidental water pollution incidents in China bring a serious threat to people’s livelihoods and health, the aquatic ecological system, economic development, and social stability. The traditional practice in water emergency management has been mainly focusing on mitigation after an incident. In fact prevention before an incident is more important than mitigation after an incident. Early warning is one of the most cost-effective, practical and comprehensive measures for prevention. There are many weaknesses and gaps in early warning system in China. Based on analysis of these deficiencies, a series of policy recommendations for establishing early warning system for water contamination incidents can be put forward.
Distributed port recall (DPR) attacks and its detection

Based on the analysis of DDos attacks in communication and the study of the popular port recall techniques, we found that the harm is more serious when combining them to form a new kind of attacks. A model called distributed port recall attacks is presented in this paper to describe this combination, and some misuse intrusion detection methods based on the records of connections (sessions) and anomaly intrusion detection methods based on the behaviors of users are also proposed. The detection schemes can detect DPR attacks effectively.
Comments on “Radial Uniform Circular Antenna Array for Dual-Mode OAM Communication”

In this letter, we comment on the statement that nonzero-orbital angular momentum (OAM)-mode wave with a major lobe at the beam center can be generated using radial uniform circular arrays. We perform the full-wave electromagnetic simulations and analyses, and results show that the claimed nonzero OAM in the commented letter is, actually, the angular momentum.
Optimal Power Flow in Stand-Alone DC Microgrids

Direct-current microgrids (DC-MGs) can operate in either grid-connected or stand-alone mode. In particular, stand-alone DC-MG has many distinct applications. However, the optimal power flow problem (OPF) of a stand-alone DC-MG is inherently non-convex. In this paper, the OPF of DC-MG is investigated considering convex relaxation based on second-order cone programming. Mild assumptions are proposed to guarantee the exactness of relaxation, which only require uniform nodal voltage upper bounds and positive network loss. It is revealed that the exactness of second-order conic (SOC) relaxation of DC networks does not rely on topology or operating mode of DC networks, and an optimal solution must be unique if it exists. If line constraints are considered, the exactness of SOC relaxation may not hold. In this regard, two heuristic methods are proposed to give approximate solutions. Numerical experiments confirm the theoretic results.
Look, Perceive and Segment: Finding the Salient Objects in Images via Two-stream Fixation-Semantic CNNs

Recently, CNN-based models have achieved remarkable success in image-based salient object detection (SOD). In these models, a key issue is to find a proper network architecture that best fits for the task of SOD. Toward this end, this paper proposes two-stream fixation-semantic CNNs, whose architecture is inspired by the fact that salient objects in complex images can be unambiguously annotated by selecting the pre-segmented semantic objects that receive the highest fixation density in eye-tracking experiments. In the two-stream CNNs, a fixation stream is pre-trained on eye-tracking data whose architecture well fits for the task of fixation prediction, and a semantic stream is pre-trained on images with semantic tags that has a proper architecture for semantic perception. By fusing these two streams into an inception-segmentation module and jointly fine-tuning them on images with manually annotated salient objects, the proposed networks show impressive performance in segmenting salient objects. Experimental results show that our approach outperforms 10 state-of-the-art models (5 deep, 5 non-deep) on 4 datasets.
A Fast Quasi-Dense Matching Method

The paper presents a fast quasi-dense matching algorithm using an adaptive window. The algorithm starts from a set of sparse seed matches, then propagates to the neighboring pixels, finally the most points in the images are matched. This algorithm adopts an additional level of incremental calculation to enhance the speed of computing the sum of squared difference (SSD). The confidence coefficient is introduced and the search window is varied in inverse proportion to it, namely realizing the adaptive search window. The algorithm has been tested with three stereo images and the results demonstrate its accuracy and efficiency.
Control of Bidirectional Current Source SVPWM Converter in the Power Accumulator Battery Testing System

The battery test requests its system converter to output excellent charging/discharging current. According to the special request, this paper designed the main circuit of current mode PWM converter, and put forward a loop-locked control method based on dq coordinate conversion to SVPWM converters in the power accumulator battery testing system. The set can output low ripple and fast response testing current in a wide adjustable range and operates in high power factor. It delivers the power accumulator's energy to the power grid without harmonic solutions and increases the transform efficiency by SVPWM and get high power factor and high dynamic response quality by dq coordinate conversion.
Design and Implementation of Portable Multifunctional Data Acquisition Terminal

Precision agriculture, a modern agriculture system, is a good solution for the implementation of pollution-free agricultural program. The start point of precision agriculture is the collection of agricultural growth data, but it is not an easy job as the APB (Agricultural Production Base) is always far away from city center and located remotely. As a result, the APB is hard to be covered by network, and an online data collection method takes no effects. Besides, acquisition work may last for a long time in field, so the terminal must be long duration without direct power supply. Aiming at these requests, this paper presents a PMDAT (Portable Multifunction Data Acquisition Terminal) based on ARM, which supports not only online data collection, but also supports offline data collection. When network is not available, PMDAT launches an embedded application to support working offline and stores the offline collected data in terminal temporary, when network is available, PMDAT first uploads the offline collected data automatically and updates itself to maintain consistent basic information of APB with Data Center, then launches an embedded browser to support collecting data online. In addition, in order to support working in field for long time, we integrate a powerful rechargeable battery into PMDAT, and pay attention to low power consumption design. This is a new approach to meet practical needs very well.
Prediction of mode and static stability of negative buoyancy vehicle

This article concerned modelling the dynamics of a novel type of autonomous underwater vehicle, which looked like a plane and worked in the condition of negative buoyancy. Linear system theory was applied to study the hydrodynamics of the negative buoyancy vehicle (NBV). The motions in the lognitudinal plane and the lateral plane were divided into a few modes, and the influence of buoyancy and metacentric height on the modes of motion were predicted based on the analysis of eigenvalue and eigenvector, as well as the criterion of static stability under constant load on the two planes was proved, which could be applied on NBV design.
Research and implementation based on SIP technique of web

SIP is one of the standards for Voice Communications System based on IP. It is also the kernel technique of soft-switch and next generation network (NGN). In this paper, a method using Java SIP Servlet to realize SIP protocol on the explorer of the terminal on the Web is put forward through research on SIP protocol, the relationship between SIP and HTTP is introduced, the key code to achieve SIP by SIP Servlet based on web and key support to build call center based on web were provided.
A comparative study of constraint-handling techniques in evolutionary constrained multiobjective optimization

Solving constrained multiobjective optimization problems is one of the most challenging areas in the evolutionary computation research community. To solve a constrained multiobjective optimization problem, an algorithm should tackle the objective functions and the constraints simultaneously. As a result, many constraint-handling techniques have been proposed. However, most of the existing constraint-handling techniques are developed to solve test instances (e.g., CTPs) with low dimension and large feasible region. On the other hand, experimental comparisons on different constraint-handling techniques remain scarce. In view of these two issues, in this paper we first construct 18 test instances, each of which exhibits different properties. Afterward, we choose three representative constraint-handling techniques and combine them with nondominated sorting genetic algorithm II to study the performance difference on various conditions. By the experimental studies, we point out the advantages and disadvantages of different constraint-handling techniques.
A visi-coil fiducial markers detection method on kV projection images during prostate radiation therapy

Here an accurate automated method based on fast marching approach for detecting visi-coil fiducial markers by using kV imaging is presented. Visi-coil segmentation in each kV image is performed on one marker at a time via fast marching method which requires user input of the endpoints. Initially, a 3D model was extracted by thresholding CT images and is used here as reference. The reference 3D model is re-projected onto the kV images. The new 2D re-projection points provide information about the direction of the markers and zones within which each marker endpoint may lie. This information is employed to detect the start and end point of each visi-coil and remove user input in the fast marching method. A 3D reconstruction of the markers is computed from the segmentation results. The proposed automated visi-coil detection algorithm can increase accuracy of marker location on noisy images and when obscured by boney tissue.
Construction of two-dimensional complementary orthogonal sequences with ZCZ and their lower bound

For various applications in image, communications, signal processing, 2-D complementary orthogonal (CO) sequences with zero correlation zone (ZCZ) are widely investigated. In this paper, new lower bounds for 2-D CO sequences with ZCZ, based on matrix theory on rank, are derived and presented. As a direct application to our results, upper bounds on family size of 2-D mutually complementary orthogonal (MCO) codes defined by Luke (1985) are proposed. In Addition, a method for constructing 2-D ternary CO sequences with ZCZ is proposed
A novel neuro-fuzzy model-based run-to-run control for batch processes with uncertainties

In this paper, a run-to-run control with neuro-fuzzy model updating mechanism is developed. This strategy features the ability to learn from previous batches to obtain iteratively the optimal control profile and adjust the neuro-fuzzy model parameters. In addition, an updating algorithm guaranteeing the global convergence of the weights of the model is developed based on the Lyapunov approach. As a result, model uncertainties can be handled. Simulation results show that by updating the model from batch to batch, the control profile converges to the corresponding suboptimal one in the subsequent batches.
Distributed Interference-Aware Cooperative Random Access in Multi-Hop Wireless Networks

Cooperative communication has emerged as a promising technique to improve transmission reliability and spectral efficiency by utilizing virtual antenna arrays formed by multiple nodes in wireless networks. In this paper, we study distributed interference-aware random access strategies based on cooperative link selection scheduling for multi-hop wireless networks. In order to fully exploit the broadcast feature of wireless channels, improve spatial reuse, and achieve diversity gains, the cooperative random access is formulated as a network utility optimization problem with probabilistic model and interference avoidance. In the multi-hop wireless networks, the nodes near the destination node in the current hop that can decode the data packets from the source node are able to serve as candidate relays to take part in the cooperative transmission in the next hop. Simulation results show that our proposed spectrum access strategy significantly improves the system average throughput and spectrum efficiency compared with the existing solutions.
Kansei engineering in automotive body-side styling design

This study focused on the relationship between automotive body-side modeling and Kansei image. It is divided into four phases. The first stage: the sample and image words collection; the second stage: the representative sample and representative image semantic choice; the third stage: the establishment of the corresponding relationship between automobile styling elements of image semantics and form features; the fourth stage: the analysis and testing. It established a body side of the segmentation model form factors. Through multivariate analysis, the paper had studied the segments within the study area with correlation analysis, cluster analysis and multiple regression analysis, and got the correspondence of emotional feelings and values of data.
Performance of UWB PSK systems using fully saturated power amplifiers

This paper studies the performance of ultra-wideband (UWB) radio communications systems employing phase shift keying (PSK) modulation and fully saturated power amplifiers through additive white Gaussian noise (AWGN) channel or Rayleigh fading channel. An impulse response method is provided to analyze the signal-to-noise ratio (SNR) degradation. Both convolutional code and turbo code are employed with the Viterbi decoding and the iterative decoding, respectively. The decoding algorithms are modified for the Rayleigh fading channel. Near optimal bit error rate (BER) performance is achieved when employing either convolutional code or turbo code. The simulation results match the derivation. Therefore, fully saturated power amplifiers can be employed in UWB PSK systems to significantly reduce radio cost, simplify radio circuit, and increase battery life for portable terminals.
A SISO neuro-fuzzy wiener model identification by correlation analysis method

A novel identification algorithm is presented in this paper for neuro-fuzzy based single-input-single-output (SISO) Wiener model with colored noises. The independent identical distribution (iid) Gaussian random signals are adopted to identify the Wiener system, leading to the separation of linear part from nonlinear counterpart in the identification problem. Therefore, correlation analysis method can be used for the identification of the linear part. Moreover, least-squares-based parameter identification algorithm that can avoid the impact of colored noise is proposed to identify the static nonlinear part. Lastly, an example is used to verify the effectiveness of the proposed method.
Automatic Design of High-Sensitivity Color Filter Arrays With Panchromatic Pixels

In most of existing digital cameras, color images have to be reconstructed from raw images, which only have one color sensed at each pixel, as their imaging sensors are covered by color filter arrays (CFAs). At each pixel, a CFA usually allows only a portion of the light spectrum to pass through, and thereby reduces the light sensitivity of pixels. To address this issue, previous works have explored adding panchromatic pixels into CFAs. However, almost all existing methods assign panchromatic pixels empirically, making the designed CFAs prone to aliasing artifacts. In this paper, based on a mathematical model, we propose a fully automatic approach to designing high-sensitivity CFAs using panchromatic pixels. By the frequency structure representation of CFAs, we formulate high-sensitivity CFA design as a continuous multi-objective optimization problem, where robustness to aliasing artifacts and percentage of panchromatic pixels are simultaneously maximized. We analyze the characteristics of our new formulation. According to the analysis, we develop a new method to propose frequency structure candidates, which can produce CFAs that reach a desired percentage of panchromatic pixels. Then for each candidate, we optimize parameters to obtain the final CFA, which is an appropriately balanced solution to the multi-objective optimization problem. We formulate the two design procedures as constrained optimization problems and solve them using the alternating direction method. Extensive experiments confirm the advantage of the proposed method in both low-light and normal-light conditions.