nils-herrmann/clean_scirepeval huggingface dataset:
Detecting Unsafe Driving Patterns using Discriminative Learning

We propose a discriminative learning approach for fusing multichannel sequential data with application to detect unsafe driving patterns from multi-channel driving recording data. The fusion is performed using a discriminatively trained graphical model -conditional random field (CRF). The proposed approach offers several advantage over existing information fusing approaches. First, it derives its classification power by directly modelling and maximizing the conditional probability. Second, it represents the variable dependency in an undirected graph, which is very efficient in inference. Third, it does not require to label all the training data and utilizes both labelled and unlabelled data efficiently by semi-supervised learning algorithms. The proposed approach is evaluated on driving recording data collected from driving simulator -STISIM. Experiments show it outperforms the simple discriminative classifier (SVM) and generative model (HMM).
Applying decision-oriented accounting principles for the simulation-based design of logistics systems in production

In this contribution, we focus on the configuration of logistics systems embedded into production processes. To evaluate the dynamic behavior of alternative configurations, Discrete-Event Simulation (DES) proofs helpful. Emphasis is typically put on physical performance measures. However, as configuration decisions have significant financial impact to the firm, an additional monetary impact assessment is usually performed. This requires cost accounting techniques that appropriately incorporate system complexity into the financial model. To this end, we propose a novel approach to extend the applicability of DES for configuration problems. The basic idea is to incorporate technical consumption or engineering production functions into Riebel's Generic Direct Cost Accounting and to add both methods to a standard DES modeling. Consequently, the informational value of DES is significantly improved. Misleading decision support can be avoided and insights into the relationship between processes and the value structure are achieved. Both of which contribute towards improved configuration decisions.
A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data

In open abdominal image-guided liver surgery, sparse measurements of the organ surface can be taken intraoperatively via a laser-range scanning device or a tracked stylus with relatively little impact on surgical workflow. We propose a novel nonrigid registration method which uses sparse surface data to reconstruct a mapping between the preoperative CT volume and the intraoperative patient space. The mapping is generated using a tissue mechanics model subject to boundary conditions consistent with surgical supportive packing during liver resection therapy. Our approach iteratively chooses parameters which define these boundary conditions such that the deformed tissue model best fits the intraoperative surface data. Using two liver phantoms, we gathered a total of five deformation datasets with conditions comparable to open surgery. The proposed nonrigid method achieved a mean target registration error (TRE) of 3.3 mm for targets dispersed throughout the phantom volume, using a limited region of surface data to drive the nonrigid registration algorithm, while rigid registration resulted in a mean TRE of 9.5 mm. In addition, we studied the effect of surface data extent, the inclusion of subsurface data, the trade-offs of using a nonlinear tissue model, robustness to rigid misalignments, and the feasibility in five clinical datasets.
Configuration control of 7 DOF arms

Applications of the configuration control approach to motion control of redundant 7 DOF (degree-of-freedom) arms are described. This approach provides a unified framework for resolution of redundancy to accomplish a broad range of objectives. The configuration control approach is briefly described, and a graphics simulation environment for control of 7 DOF Robotics Research arms is discussed. Computer simulation results are presented to demonstrate elbow control, obstacle avoidance, and optimal joint motion as redundancy resolution goals for the 7 DOF arm.<<ETX>>
An evaluation of optimization techniques for estimation of muscle forces based on EMGS during static isometric tasks

The purpose of this study was to critically evaluate ,the modeling potential of. optimization techniques for predicting muscle forces during isometric loading. Models of both the elbow a n d wrist joints were constructed, including all major active muscles. Several different protocols were implemented, incIuding models which balance one, two, three, and mixed degrees of freedom, and modulated co-contraction. Theoretical predictions were compared with EMG data. Results indicate a strong dependence of muscle coordination predictions on the number of degrees of freedom balanced, and a relative insensitivity to the particular objective function which is optimized. No particular optimization protocol was found to adequately represent actual muscle activity at the elbow, although predictions at the wrist were more favorable due to differences in the degrees of freedom at the joints.
A packaged high-performance decision IC up to 45-Gb/s

A packaged D-type flip-flop (DFF) decision circuit for optical OC-768 systems and testing equipment is reported. The circuit uses 1 /spl mu/m InP SHBT technology featuring f/sub T//f/sub max/=150 GHz and has been operated up to 45 Gb/s with a clock phase margin about 180/spl deg/. Measured output eye diagrams from packaged devices exhibit 9/8 ps rise/fall with only 3ps peak-peak jitter. A single-ended AC-coupled clock input makes the application of this circuit very convenient. The IC dissipates 440 mW from a -4V supply voltage.
Design, construction, and demonstration of a prototype mobile Global Broadcast Service (GBS) joint in-theater injection (JITI) terminal

To provide proof of concept of the Global Broadcast Service (GBS) in-theater injection capability during the testbed phase (Phase I) of the GBS acquisition, a prototype theater injection point (TIP) was designed, constructed and demonstrated by the US Army Space Command. The prototype TIP was designated the joint in-theater injection (JITI) terminal. This paper describes the design and construction of the JITI terminal. Demonstration of the terminal during the Joint Warrior Interoperability Demonstration (JWID) 96 and during its operation as the uplink facility for the CONUS GBS testbed are discussed. Some specific experiments conducted during the demonstrations are described.
Constraint handling in agent-based optimization by independent sub-swarms

Agent-based optimization algorithms are an effective means of solving global optimization problems with design spaces containing multiple local minima, however, modifications have to be made to such algorithms to be able to solve constrained optimization problems. The gravitational search algorithm (GSA) is an efficient and effective agent-based method, however, the idea of global transfer of data that is key to the algorithm's success prohibits coupling of many state-of-the-art methods for handling constraints. Hence, a robust method, called separation-sub-swarm (3S) has been developed specifically for use with GSA by exploiting but also accommodating the global transfer of data that occurs in GSA, however it can also act as an entirely black-box module so is generally applicable. This newly developed 3S method has been shown to be efficient and effective at optimizing a suite of constrained analytical test functions using GSA.
Detecting Anomaly in Videos from Trajectory Similarity Analysis

Trajectories of moving objects provide crucial clues for video event analysis especially in surveillance applications. In this paper, we study the problem of detecting anomalous events by analyzing the motion trajectories in videos. Different trajectories of the same category may have varying relative velocities, in addition to the variations and noises in location samples; hence the core of the problem is to provide a robust and accurate function for measuring the similarities of trajectory pairs. We propose a novel learning based algorithm for estimating the similarities of the multi-dimensional sequence pairs, and then an anomaly detection framework is presented to detect anomalous motion trajectories in surveillance videos. Our proposed algorithm offers several advantages over the traditional algorithms for dealing with the trajectories of moving objects. First, the similarity measurement is robust against data imperfections such as noise, algorithmic error and etc. Second, we introduce a learning algorithm which allows the similarity function to be adapted to the particular problems being solved. Third, the proposed anomaly detection framework is fully automatic and without parametric distribution assumption on the data. The experiments on both outdoor and indoor surveillance videos validate the effectiveness of our proposed framework in detecting anomalous trajectories.
Detecting semantic concepts using context and audiovisual features

Detection of high-level semantics from audio-visual data is a challenging multimedia understanding problem. The difficulty mainly lies in the gap that exists between low level media features and high level semantic concepts. In an attempt to bridge this gap, Naphade et al. ) proposed a probabilistic framework for semantic understanding. The components of this framework are probabilistic multimedia objects and a graphical network of such objects. We show how the framework supports detection of multiple high-level concepts, which enjoy spatial and temporal-support. More importantly, we show why context matters and how it can be modeled. Using a factor graph framework, we model context and use it to improve detection of sites, objects and events. Using concepts outdoor and flying-helicopter we demonstrate how the factor graph multinet models context and uses it for late integration of multimodal features. Using ROC curves and probability of error curves we support the intuition that context should help.
Band-limited signal extrapolation in the presence of noise

Recently, two-step procedures for band-limited signal extrapolation have received a great deal of attention in the engineering community ([1],[2]). In this paper, we show that several two-step procedures with different underlying models can be unified by means of non-iterative algorithms for solving optimization problems in Hilbert spaces. In particular, some modifications of these procedures for noisy data are shown to be particular cases of regularization techniques for integral equations of the first kind. We present a result which gives insight into the meaning of the regularizing parameter. Some numerical examples of applying this result to signal extrapolation are shown. This unification together with those presented for iterative least-squares algorithms (), and the prolate spheroidal expansion (), demonstrate that most of the well-known procedures for band-limited extrapolation can be considered as special cases of standard techniques in integral equations and operator theory.
Design and development of a high performance gyro-TWT-amplifier operating at a cyclotron harmonic frequency

A 35 GHz gyro-TWT (traveling wave tube) amplifier designed for operation at the second harmonic of the cyclotron frequency is presented. It is expected that 200 kW peak output, 15% bandwidth, 40 dB saturated gain and efficiency of 25% can be obtained. The design may be extended to 94 GHz operation at the fourth cyclotron harmonic. These harmonic gyrotron amplifiers will operate at a magnetic field strength which is compatible with modern permanent-magnet technology.<<ETX>>
Development of a sampling-based global sensitivity analysis workflow for multiscale computational cancer models.

There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale 'in silico' cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this study, the authors therefore propose a sampling-based GSA workflow consisting of three phases - pre-analysis, analysis and post-analysis - by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance; they then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarised ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that extracellular signal-regulated kinase, a downstream molecule of the epidermal growth factor receptor signalling pathway, has the most important impact on regulating both the tumour volume and expansion rate in the algorithm used.
An unsupervised adaptive strategy for constructing probabilistic roadmaps

Since planning environments are complex and no single planner exists that is best for all problems, much work has been done to explore methods for selecting where and when to apply particular planners. However, these two questions have been difficult to answer, even when adaptive methods meant to facilitate a solution are applied. For example, adaptive solutions such as setting learning rates, hand-classifying spaces, and defining parameters for a library of planners have all been proposed. We demonstrate a strategy based on unsupervised learning methods that makes adaptive planning more practical. The unsupervised strategies require less user intervention, model the topology of the problem in a reasonable and efficient manner, can adapt the sampler depending on characteristics of the problem, and can easily accept new samplers as they become available. Through a series of experiments, we demonstrate that in a wide variety of environments, the regions automatically identified by our technique represent the planning space well both in number and placement.We also show that our technique has little overhead and that it out-performs two existing adaptive methods in all complex cases studied.
8.1: Nonlinear characteristics of transverse interaction in sheet beam amplifiers

We model the interaction between a planar electron beam and the transverse electromagnetic fields in a slow-wave structure. We summarize the linear theory of the coupled equations, including the space charge of the beam, and apply this to obtain the basic characteristics of the transverse interaction mechanism. We present results also using a non-linear theory, based on a number of simplifying assumptions that allow for closed form solutions to be obtained. A number of insights into the characteristics of the interaction close to saturation are presented.
A pocket-size broadband electric field detection and storage device

The radio-frequency (RF) dosimeter developed by the Oak Ridge National Laboratory is described. It is a portable, pocket-sized, cumulative-dose recording device designed to detect and record the strengths and durations of electric fields present in the work areas of naval vessels. The device measures an integrated dose and records the electric fields that exceed the permissible levels set by the American National Standards Institute. Features of the RF dosimeter include a frequency range of 30 MHz to 10 GHz and a three-dimensional sensor. Data obtained with the RF dosimeter will be used to determine the ambient field-strength profile for shipboard personnel over an extended time. Readings are acquired and averaged over a 6-min period corresponding to the rise time of the core body temperature. These values are stored for up to 6 months, after which the data are transferred to a computer by means on the dosimeter's serial port.<<ETX>>
5.3: A large signal model of Extended Interactions Klystrons

Extended Interaction Klystron (EIK) cavities consist of shorted (resonant) sections of a periodic or bi-periodic structure. The response of such cavities to currents induced by the passage of a bunched beam may be represented by an impedance matrix that relates the voltage in each section to the induced currents. We have implemented this representation in the CHRISTINE large signal code. Using a modal expansion for the cavity fields we have computed the impedance matrix for a simple ‘ladder’ circuit. Using this matrix in a CHRISTINE simulation, we have found good agreement for the AC current vs. axial location in a 3-cavity circuit, compared with results from the 3D particle-in-cell code MAGIC.
Benefits of Integrating Meta Data into a Context Model

Meta data - data about data - improves the value of the operational data by giving applications and users additional information on the data's origin, its precision or staleness. We outline the benefits of modeling meta data in context models: it can be used for resource finding, enhanced data selection, trust and data quality issues and sensor fusion. We show how meta data included into an object-based context model influences the data modeling and the selection process in the query language. Finally, we describe our implementation of the presented functionality in the Nexus platform
A secure way of exchanging the secret keys in advanced metering infrastructure

Advanced metering infrastructure (AMI) security has become a challenging issue now days because of its integration with the external networks, remote system, and internet world. Today's metering infrastructure employs computer based monitoring and control operations to enable application of one network to exchange data with other application of different network. Communication protocol, network topologies, and computerization plays crucial roles to make the metering infrastructure advanced and further make a grid smarter. On the other hand, cyber attacks already associated with such computer networks and communication protocol can easily affect the communication of AMI applications. Therefore, from trespasser point of view, in this paper, we explore the various possible types of undesirable security threats followed by desirable security attributes required for the AMI. The paper further describes and implements a signature based station-to-station protocol for exchanging the secret shared keys among the AMI applications to get rid from undesirable security threats.
Cluster-based mobile-to-mobile channel characterization for realistic modelling of multipath-components

In this paper, we present a new channel model for mobile-to-mobile (M2M) channels based on extensive measurements conducted at 30MHz-400MHz in various environments. We use the tapped-delay-line model and determine the discrete tabs by distributing scatterers on ellipses in the environment. For a distinctive characterization of the M2M channel we extract channel parameters from the measurements using the high-resolution parameter estimation algorithm RIMAX and perform a cluster algorithm for statistical analysis. In order to make the measurement results accessible for simulations we derive a cluster-based statistical parametrization of the model. We perform simulations to compare the results with measurements and show that the model is well-suited for simulating M2M channels.
Energy efficient sleep/wake scheduling of stations in wireless networks

A wireless ad hoc network is typically Constrained by battery power, and hence, it is important to conserve battery power in order to keep the network alive for a long time. We consider a wireless network consisting of an access point (AP) and a wireless node, which is limited by energy, and we seek scheduling algorithms that conserve battery power at the wireless node. Since the packet arrivals are stochastic, communication happens only during the time slots when packets are available. Hence, keeping the receiver ON at all times is wasteful of resources. However, when the receiver is turned OFF, a packet, on arrival, is stored in a buffer (at the AP) which incurs a holding cost. We propose sleep/wake scheduling at the wireless node with an objective of minimizing the power spent (at the receive node) and the queuing delay at the AP, while maintaining the stability of the queue. We note here that this energy optimum scheduling is a distributed problem in which the queue-length information at the transmitter is not known at the receiver. We show that the optimum wake process at the receiver follows closely as that of the arrival process of the packets at the AP. We numerically evaluate the optimum scheduler, and discuss the energy and queuing delay performance of our proposed optimum scheduler.
Estimating three-dimensional motion parameters of a rigid planar patch

We present a new direct method of estimating the three-dimensional motion parameters of a rigid planar patch from two time-sequential perspective views (image frames). First, a set of eight pure parameters are defined. These parameters can be determined uniquely from the two given image frames by solving a set of linear equations. Then, the actual motion parameters are determined from these pure parameters by a method which requires the solution of a sixth-order polynomial of one variable only, and there exists a certain efficient algorithm for solving a sixth-order polynomial. Aside from a scale factor for the translation parameters, the number of real solutions never exceeds two. In the special case of three-dimensional translation, the motion parameters can be expressed directly as some simple functions of the eight pure parameters. Thus, only a few arithmetic operations are needed.
Application of a phase-conjugate Brillouin mirror to generation of high-quality variable-duration KrF pulses

Phase conjugation by Brillouin scattering in SF/sub 6/ gas has been implemented on a two-pass KrF amplifier to provide near-diffraction-limited output pulses having a very low background level of amplified spontaneous emission. The pulse duration is variable between 1 and 10 ns by simply attenuating the input pulse. These pulses have also been used for the generation of much shorter duration pulses by truncated Brillouin scattering at the surface of cyclohexane.
An Approach to Integration Testing of Object-Oriented Programs

Object-oriented programming has some unique features which facilitate software reuse and component-based development. However, testing object-oriented programs using only traditional techniques is unlikely to find the faults caused by these features. The problem is that few integration testing techniques have been systematically studied or defined. We present a novel approach to generate and execute test cases for object-oriented programs from UML diagrams. We have designed an approach to implement test cases using the concept of coordination contract. A coordination contract, related to the idea of the active association class in UML, defines connections among a group of objects without interfering with their implementations. By using the contract, test case generation and execution can be completed automatically. A prototype tool has been developed to automatically derive the contracts based on the mechanism of test case generation mentioned above.