nils-herrmann/clean_scirepeval huggingface dataset:
Tight Lower Bounds for Channel Hopping Schemes in Cognitive Radio Networks

In this paper, we consider the two-user multichannel rendezvous problem in a cognitive radio network (CRN) and derive tight lower bounds for maximum time-to-rendezvous (MTTR) and maximum conditional time-to-rendezvous (MCTTR) of various channel hopping (CH) schemes under a channel loading constraint. In the symmetric and synchronous setting, we propose a novel Cycle-Adjustable Channel Hopping (CACH) scheme to achieve the MTTR lower bound (when the channel loading is bounded above by 1/u with u being a prime power). Thus, the MTTR lower bound is tight and the CACH scheme is optimal in minimizing MTTR among all the symmetric and synchronous CH schemes under the same channel loading constraint. In the asymmetric setting, we show that the classical wait-for-mommy strategy can be used to achieve the MCTTR lower bound, and thus it is optimal. In the symmetric and asynchronous setting, we also show a hierarchical construction of an asynchronous CH sequence by using two smaller asynchronous CH sequences. To further understand the effect of channel loading to the other performance metrics in a CRN, we perform various computer simulations for various CH schemes. Our simulation results show that the average time-to-rendezvous of CACH is independent of the total number of channels, and it is also robust to the disturbance of primary users.
Accelerator physics challenges of the fs-slicing upgrade at the ALS

The goal of the Femtoslicing project at the ALS is to provide 100-200 fs long pulses of soft and hard x-rays with moderate flux and with a repetition rate of 10-40 kHz for experiments concerning ultrafast dynamics in solid state physics, chemistry and biology. The femtoslicing principle employs a femtosecond laser beam to interact resonantly (inverse FEL interaction) with the electron beam in the ALS. The induced energy spread over the femtosecond duration is converted to a transverse displacement by exploiting the dispersion of the storage ring. The displaced femtosecond electron pulse then radiates and produces femtosecond synchrotron radiation. To achieve the necessary spatial separation of the energy modulated slice from the rest of the bunch, a sizeable local vertical dispersion bump in the undulator used as radiator is required. This presents challenges in terms of the nonlinear dynamics and control of the vertical emittance.
Mode-dependent robust stability and stabilisation of uncertain networked control systems via an average dwell time switching approach

The stability analysis and synthesis problem of networked control systems (NCSs) with communication limits and system uncertainties is investigated via an average dwell time switching control method. Active time-varying sampling strategy and hybrid node driven mode are proposed to generate a series of one-step time delay subsystems of closed-loop NCS. Gridding approach is introduced to transform the continuous time axis into discrete time sequences which limits the switching rules in a finite set. By constructing multiple parameter-dependent quadratic Lyapunov-like functions with norm bounded uncertainties, sufficient stability conditions are derived and the robust mode-dependent network controller is designed to guarantee the proposed uncertain switched NCS globally asymptotically stable for any switching signal with admissible ADT. A for-loop algorithm is integrated into the formulated LMI optimisation problem to avoid predefining the switching sequence and the occurring times of network induced factors. Finally, simulation results illustrate the effectiveness of the proposed methods.
A Knowledge-Based Evolutionary Multiobjective Approach for Stochastic Extended Resource Investment Project Scheduling Problems

Planning problems, such as mission capability planning in defense, can traditionally be modeled as a resource investment project scheduling problem (RIPSP) with unconstrained resources and cost. This formulation is too abstract in some real-world applications. In these applications, the durations of tasks depend on the allocated resources. In this paper, we first propose a new version of RIPSPs, namely extended RIPSPs (ERIPSPs), in which the durations of tasks are a function of allocated resources. Moreover, we introduce a resource proportion coefficient to manifest the contribution degree of various resources to activities. Since the more realistic nature of projects in practice implies that the circumstances under which the plan will be executed are stochastic in nature, we present a stochastic version of ERIPSPs, namely stochastic extended RIPSPs (SERIPSPs). To solve SERIPSPs, we first use scenarios to capture the space of possibilities (i.e., stochastic elements of the problem). We focus on three sources of uncertainty: duration perturbation, resource breakdown, and precedence alteration. We propose a robustness measure for the solutions of SEPIPSPs when uncertainties interact. We then formulate an SERIPSP as a multiobjective optimization model with three optimization objectives: makespan, cost, and robustness. A knowledge-based multiobjective evolutionary algorithm (K-MOEA) is proposed to solve the problem. The mechanism of K-MOEA is simple and time efficient. The algorithm has two main characteristics. The first is that useful information (knowledge) contained in the obtained approximated nondominated solutions is extracted during the evolutionary process. The second is that extracted knowledge is utilized by updating the population periodically to guide subsequent search. The approach is illustrated using a synthetic case study. Randomly generated benchmark instances are used to analyze the performance of the proposed K-MOEA. The experimental results illustrate the effectiveness of the proposed algorithm and its potential for solving SERIPSPs.
Multibody Grouping by Inference of Multiple Subspaces from High-Dimensional Data Using Oriented-Frames

Recently, subspace constraints have been widely exploited in many computer vision problems such as multibody grouping. Under linear projection models, feature points associated with multiple bodies reside in multiple subspaces. Most existing factorization-based algorithms can segment objects undergoing independent motions. However, intersections among the correlated motion subspaces will lead most previous factorization-based algorithms to erroneous segmentation. To overcome this limitation, in this paper, we formulate the problem of multibody grouping as inference of multiple subspaces from a high-dimensional data space. A novel and robust algorithm is proposed to capture the configuration of the multiple subspace structure and to find the segmentation of objects by clustering the feature points into these inferred subspaces, no matter whether they are independent or correlated. In the proposed method, an Oriented-Frame (OF), which is a multidimensional coordinate frame, is associated with each data point indicating the point's preferred subspace configuration. Based on the similarity between the subspaces, novel mechanisms of subspace evolution and voting are developed. By filtering the outliers due to their structural incompatibility, the subspace configurations will emerge. Compared with most existing factorization-based algorithms that cannot correctly segment correlated motions, such as motions of articulated objects, the proposed method has a robust performance in both independent and correlated motion segmentation. A number of controlled and real experiments show the effectiveness of the proposed method. However, the current approach does not deal with transparent motions and motion subspaces of different dimensions.
Performance of University students on English reading and writing when using a Web 2.0 tool

Instructional technology has been integrated into teaching activities for a long time. The purpose of the study was to compare University students' performance in using a wiki as an effective pedagogical tool versus traditional English instruction in an English reading and writing course. The researchers employed a true experimental and questionnaire methodology design. The study participants were 100 students between 20 and 35 years of age who were enrolled in a four-year college in Taiwan. The result showed that students obtained higher performance in using a wiki tool than in traditional English instruction. The study also investigated the impacts of student learning attitudes by integrating Web 2.0 tools. The result indicated that females had higher positive attitudes toward utilization of a wiki for their projects than males. The result also showed that younger participants had more of an interest in their projects through a wiki.
A direct electron beam energy spread measurement system for beam instability and FEL research

One of critical beam parameters for the storage ring based light sources is the energy spread of the electron beam. An accurate measurement of the energy spread remains a challenge. It is well known that the energy spread of the electron beam can degrade the spontaneous radiation spectrum of an optical-klystron (OK) which consists of two wigglers separated by a buncher magnet. The reduced modulation in the spectrum can be used to determine the energy spread of the beam. This paper describes our newly developed energy spread measurement system employing a compact and versatile spectrometer. This system is used in the beam instability research and free-electron laser (FEL) research. In particular, by measuring the increase of electron beam energy spread we have studied the onset of microwave instability.
MBE growth of InP-HBT structures on Ge-on-insulator/Si substrates by MBE

MBE growth of InP-based HBTs on GeOI/Si substrates is described. A GaAs buffer is nucleated on the GeOI; then a graded InAlAs metamorphic buffer transitions the lattice constant to InP. TEM shows minimal anti-phase boundaries and limited dislocations propagating into the device layers. Large area DC parameters are similar to LM HBTs grown on InP. Small area devices exhibit peak current gain cutoff frequency (ft) of 170 GHz at 2 mA/mum2 nominal collector current density. Initial work involving selective epitaxial growth on patterned Ge substrates for future integration is also discussed.
InGaAs/InP DHBTs with a 75nm Collector, 20nm base Demonstrating 544 GHz ft, BVCEO = 3.2V, and BVCBO = 3.4V

We report InP/InGaAs/InP double heterojunction bipolar transistors (DHBT) fabricated using a conventional mesa structure. The devices employ a 20 nm highly doped InGaAs base and a 75 nm InP collector containing an InGaAs/InAlAs superlattice grade. These devices exhibit a maximum fτ = 544 GHz with a 347 GHz fmax, which is the highest fτ for an InP DHBT, and highest fτ at a 75 nm collector thickness for any HBT. The devices have been scaled vertically for reduced base and collector electron transit times, and the base-collector mesa has been kept narrow to minimize the capacitance Ccb associated with thinner collectors. The current gain β ≈ 50, BVCEO = 3.2 V, BVCBO = 3.4 V, and the devices operate up to 24 mW/μm (failing at Je = 12 mA/μm , Vce = 2.0 V, ∆Tfailure ≈ 348 K).
Study on the Decontamination Function of Two Kinds of Aquatic Plants Towards Pb²+

This is a study on the decontamination function of two kinds of aquatic plants towards Pb2+, cress and acorus. The results show: both cress and acorus have the ability of removing heavy metal Pb2+, while acorus shows higher decontamination ability, up to 91%. Acorus shows higher accumulation rate of Pb2+ compared to cress and its underground((root) accumulation rate is significantly higher than that on the ground(Stems and leaves); with the Pb2+ concentration of 250mg/L, the underground accumulation rate is up to 1542.97mg/kg and that on the ground was 943.61mg/kg.
Electrically tunable room-temperature 2/spl pi/ liquid crystal terahertz phase shifter

Tunable phase shift up to 360/spl deg/ at 1 THz is demonstrated using electrically controlled birefringence in a vertically aligned nematic liquid crystal (E7) cell, 1.83 mm in thickness. The driving voltage and corresponding field required for a phase shift of 360/spl deg/ at 1 THz are 100 V and 90.5 V/cm, respectively.
Dual-band microstrip bandpass filter with independently-tunable passbands using patch resonator

A novel dual-band bandpass filter using patch resonator combined with microstrip resonant stubs is proposed. Two crossed slots are introduced to disturb the TE200 mode and TE002 mode of patch resonator, forming the first passband (low frequency). Two orthogonal microstrip stubs bring the source–load coupling while they also work as resonators, providing the second passband (high frequency). Each passband can be tuned independently due to the independent-resonant paths and non-crossed couplings between working modes. The proposed filter shares a simple layout, and three transmission zeros are obtained and it results in good selectivity and good out-band rejection. The measured results agree with simulated results well.
Defect Classification by Pulsed Eddy-Current Technique Based on Power Spectral Density Analysis Combined With Wavelet Transform

The main objective of this paper is to precisely classify surface and subsurface cracks and cavities using a feature-based giant magnetoresistive pulsed eddy-current (PEC) sensor. Based on the author's previous work involving amplitude spectral analysis combined with wavelet decomposition, the power spectral density analysis of the direct differential PEC response, and the reconstructed approximate and detail components of wavelet transform are performed to extract the defect feature. Principal component analysis (PCA) is designed to eliminate the dimensional method, which is identified with the ability to supply the low-dimensional feature. PCA confused linear discriminant analysis and the Bayesian classifier are both applied for defect classification. The experimental results reveal that cracks and cavities on the surface and subsurface can be classified satisfactorily by the proposed methods that have the potential for gauging automatic in situ inspection for PEC.
A Blog Clustering Approach Based on Queried Keywords

In recent years, blogs were used between friends and family members. Nowadays, more and more bloggers are willing to share information with others. Therefore, it is desirable that related blogs can be connected. Clustering is often used for establishing connections between blogs. Full-text keywords retrieval process (FKRP) is generally used to obtain the keywords of posts, and the keywords were then used to cluster posts. Another approach is to use tags or categories chosen by bloggers for their posts. However, the overhead of FKRP is relatively high and the use of tagging is associated with synonymy related issues. More recently, there is an emerging concept called social tagging, which is about having web resources tagged by the general public together. Similar to this concept, we developed a blog connect platform that collects queried keywords used by the people for searching for a post. With the queried keywords, formal concept analysis (FCA) associated with agglomerative hierarchical clustering method is used to cluster posts. The experimental results showed that the accuracy of the proposed approach is better than those of other studies.
A bi-subspace model for robust visual tracking

The changes of the target's visual appearance often lead to tracking failure in practice. Hence, trackers need to be adaptive to non-stationary appearances to achieve robust visual tracking. However, the risk of adaptation drift is common in most existing adaptation schemes. This paper describes a bi-subspace model that stipulates the interactions of two different visual cues. The visual appearance of the target is represented by two interactive subspaces, each of which corresponds to a particular cue. The adaption of the subspaces is through the interaction of the two cues, which leads to robust tracking performance. Extensive experiments show that the proposed approach can largely alleviate adaptation drift and obtain better tracking results.
Analysis on Operator Man-Made Risk of Enterprise's Sustainable Innovation Process

The paper firstly defines several concepts about operator man-made risk of enterprise’ s sustainable innovation process, then identifies risk factors, and on this basis, analyzes the risk factors, finally proposes risk-response measures. It can deepen and improve the enterprise’ s sustainable innovation management theoretical framework, enrich and develop innovation theory, and which can provide theoretical basis and reference for the government administration to broaden ideas and emancipate their minds.
Independent Gabor Analysis of Discriminant Features Fusion for Face Recognition

A discriminant feature fusion model is proposed for face recognition with large variations of pose, expression, lighting, etc. Discriminant features are extracted by the wavelet transform-based method from two source images. One source image is a holistic gray value image and the other is an illumination invariant geometric image. Face sample is reconstructed by the adaptive fused discriminant feature. Then a bank of Gabor filters is built to extract Gabor representations of the reconstructed samples. Finally higher-order statistical relationships among variables of samples are extracted for classifier. According to experiments, the model outperforms conventional algorithms under complex conditions (large variations of lighting, expression, accessory, etc.).
Weight Initialization of Feedforward Neural Networks by Means of Partial Least Squares

A method to set the weight initialization and the optimal number of hidden nodes of feedforward neural networks (FNN) based on the partial least squares (PLS) algorithm is developed. The combination of PLS and FNN method ensures that the outputs of neurons are in the active region and increases the rate of convergence. The performance of the FNN, PLS, and PLS-FNN are compared according to an example of customer satisfaction measurement with unknown relationship between the input and output data. The results show that the hybrid PLS-FNN has the smallest root mean square error and the highest imitating precision. It substantially provides the good initial weights, improves the training performance and efficiently achieves an optimal solution
Research on the Wiki & HIS-Based Application Mode of Hospital Knowledge Management

Through the requirement analysis of hospital management, the paper elaborates the necessity and feasibility of hospital informatization from the traditional information management to knowledge management based on the hospital information system (HIS hereafter). With the discussion of knowledge management mechanisms and characteristics of Wiki, a Wiki & HIS-based application mode of hospital knowledge management is put forward with a case of the clinician combined with his practical application. This solution can organically match the e-commerce service mode and the techniques of Web2.0 to the requirement of hospital knowledge management, and is helpful to construct the new dynamic, open, distributed and service-oriented hospital information system.
Analysis on the clean production technology of processing waste edible oils to biodiesel

Under the guiding of Industry-University-Institute strategy, cooperating with Changzhou University and Petrochemical Research Institute of Lanzhou Petrochemical Company, Jingzhong Sunlight Petrochemical Co., Ltd. developed a clean production technology of biodiesel. The raw material of this technology is waste edible oils and fats, and the two parts of process of which are solid acid catalyzed continuous esterification and methanol supercritical transesterification. No new “three wastes” created during the whole procedure. Final product fatty acid methyl ester (biodiesel product) fitted the critical requirements of BD100 biodiesel standard (GB/T20828-2007). passed GB/T 7305 (Determination of demulsibility characteristics), which means suitable for storing and using near water body. Based on the summery of laboratory research, PEP (Process Economics Program) report was generated and design drawing was completed. The project to build a demonstration device which owns 20,000 tons capacity biodiesel for marine has started in Beijing, to demonstrate the values of local-resource-local-producing, change-wastes-into-valuables and protecting water recourses. During the developing process, three patents and two knowhows are created.
Detecting contextual anomalies of crowd motion in surveillance video

Many works have been proposed on detecting individual anomalies in crowd scenes, i.e., human behaviors anomalous with respect to the rest of the behaviors. In this paper, we introduce a new concept of contextual anomaly into the field of crowd analysis, i.e., the behaviors themselves are normal but they are anomalous in a specific context. Our system follows an unsupervised approach. It automatically discovers important contextual information from the crowd video and detects the blobs corresponding to contextually anomalous behaviors. Our experiments show that the approach works well in detecting contextual anomalies from crowd video with different motion contexts.
Targeted drug delivery with focus ultrasound-induced blood-brain barrier opening Using acoustically-activated nanodroplets

Focused ultrasound (FUS) in the presence of systemically administered microbubbles has been shown to locally, transiently and reversibly increase the permeability of the blood-brain barrier (BBB), thus allowing targeted delivery of therapeutic agents in the brain for the treatment of central nervous system diseases. Currently, microbubbles are the only agents that have been used to facilitate the FUS-induced BBB opening. However, they are constrained within the intravascular space due to their micron-size diameters, limiting the delivery effect at or near the microvessels. In the present study, acoustically-activated nanodroplets were used as a new class of contrast agents to mediate FUS-induced BBB opening in order to study the feasibility of utilizing these nanoscale phase-shift particles for targeted drug delivery in the brain. Significant dextran delivery was achieved in the mouse hippocampus using nanodroplets at clinically relevant pressures. Conventional microbubbles with the same lipid shell composition and perfluorobutane core as the nanodroplets were also used to compare the efficiency of FUS-induced dextran delivery. It was found that nanodroplets had a higher BBB opening pressure threshold but a lower stable cavitation threshold than microbubbles, indicating that contrast agent-dependent acoustic emission monitoring should be carried out. More homogeneous dextran delivery within the targeted hippocampus was achieved using nanodroplets without inducing inertial cavitation or compromising safety. Our results offered a new means of developing the FU-Sinduced BBB opening technology for potential extravascular targeted drug delivery in the brain, extending the potential drug delivery region beyond the cerebral vasculature.
Hybrid knowledge representation in compositional modeling

Compositional modeling can be used to model dynamic hybrid systems the behavior of which is piecewise continuous. The model is defined by a collection. of continuous scenario models and a switching mechanism to transition from one model to another. The scenario model itself is a collection of modeling knowledge which includes parameters and relations among them, constraints, control information, etc. This paper introduces our research on knowledge representation in compositional modeling. The constituents of the scenario model are described. Semi-quantitative knowledge, such as interval value and fuzzy set formalism, is integrated to ease a flexible modeling environment.