nils-herrmann/clean_scirepeval huggingface dataset:
An efficient method to compute three fingered planar object grasps using active contour models

This paper presents an efficient method to grasp an unknown planar object (disk-like object) using a three-fingered Barrett band. First, active contour models are extracted from the images taken by Biclops, a dual camera directed vision system. The centroid of each active contour model is computed, employed in triangulation, and used as an estimate of a 3-D centroid point of the object. To compute precisely where the gripper will go and how to configure the gripper to grasp the object, the active contour models are also used in a polar coordinate frame to extract concave and convex sections of the model. The proposed algorithm attempts to place the thumb in concave sections of the object, with the remaining two fingers place such that a grasp quality metric is maximized. As a consequence, the geometric properties of the object itself can improve the quality of grasp. In this work, the gripper contact is modeled as a surface rather than a point. This makes the interaction between the object and the gripper more realistic. Only a small set of inflection points are chosen as potential grasping locations. Thus the complexity of the proposed algorithm is linear as opposed to cubic if all the points on the object boundary are chosen as potential grasping locations.
Theory and Algorithms for Constructing Discrete Morse Complexes from Grayscale Digital Images

We present an algorithm for determining the Morse complex of a two or three-dimensional grayscale digital image. Each cell in the Morse complex corresponds to a topological change in the level sets (i.e., a critical point) of the grayscale image. Since more than one critical point may be associated with a single image voxel, we model digital images by cubical complexes. A new homotopic algorithm is used to construct a discrete Morse function on the cubical complex that agrees with the digital image and has exactly the number and type of critical cells necessary to characterize the topological changes in the level sets. We make use of discrete Morse theory and simple homotopy theory to prove correctness of this algorithm. The resulting Morse complex is considerably simpler than the cubical complex originally used to represent the image and may be used to compute persistent homology.
Directional spatial I-blocks for the MC-EZBC video coder

In subband/wavelet interframe video compression, motion-compensated coders make use of estimated motion paths to compress the data. When these motion paths are not valid, due to either occlusion or difficulty in their estimation, artifacts can sometimes be created in the embedded lower frame rate video. Since these coders are intended for scalable application, it is important that the lower frame rate video be as free of artifacts as possible. The incorporation of I-blocks in the context of hierarchical variable size block matching (HVSBM) allows for inevitable occasional poorly connected motion blocks. Directional spatial interpolation/prediction can then be employed to minimize such a block's energy in a temporal high frame. Results are provided for the MC-EZBC (motion compensated embedded zeroblock coding) coder that has been recently under investigation at MPEG.
Automatically Controlled Coverage of the Voltage Plane of Quasi-Unilateral Devices

We developed a systematic procedure to efficiently cover the (V1, V2) voltage plane of two-port microwave devices. The method is restricted to (quasi-)unilateral devices, because we assume that the V1(t) does not change when applying an additional a2 travelling voltage wave. By choosing the adequate magnitude and phase of this a2 signal, the V2 of interest can be constructed. We illustrate this method on a HEMT and show that, for the used experimental conditions, only 27 vectorial large-signal measurements are sufficient to cover the (V1, V2) operating region of the device. This is a significant reduction in the number of required measurements for non-linear model generation, in comparison to the classical approach based on multi-bias broadband S-parameter measurements.
Embedded image coding using zeroblocks of subband/wavelet coefficients and context modeling

With fast computation and excellent compression efficiency, two embedded coding techniques, zero-tree/-block coding and context modeling of the subband/wavelet coefficients, have been widely utilized for image coding applications. In this research, we present a new embedded wavelet image coding algorithm with an attempt to combine advantages of these two successful coding schemes. The experimental results show that the proposed algorithm outperforms the respected zero-tree/-block coders, SPIHT and SPECK, in compression efficiency. It is also comparable to the state-of-art JPEG 2000 test coder in PSNR performance while retaining the attractive low-complexity feature of the zeroblock coders.
Swing-free trajectory generation for dual cooperative manipulators using dynamic programming

In the high speed transport of freely suspended objects, traditional methods of suppressing residual oscillations may not produce satisfactory results. Nonlinearities may exist to the point that the linearizing assumptions required by these methods may no longer be valid. The optimization algorithm of dynamic programming (DP) is advantageous for such intrinsically nonlinear applications. This paper will outline the development of the DP algorithm for discrete time systems. It also describe the application of the algorithm to a rapid maneuver of a long slender payload suspended by a cable at each end. The cables are each held by one of two independent robot manipulators. The DP algorithm will be used to generate optimal swing-free motion trajectories for the robots. Simulation and experimental results show that residual oscillations are virtually nonexistent
Prioritized sensor detection via dynamic Voronoi-based navigation

This paper presents a decentralized coordination algorithm that allows a team of sensor-enabled robots to navigate a region containing non-convex obstacles and take measurements within the region that contain the highest probability of having “good” information first. This approach is motivated by scenarios where prior knowledge of the search space is known or when time constraints are present that limit the amount of area that can be searched by a robot team. Practical applications include search and rescue, target detection, and hazardous contaminations. Our cooperative control algorithm combines Voronoi partitioning, a global optimization technique, and a modified navigation function to prioritize sensor detection. The issues we address such as non-convex obstacles as well as global search are not extensively addressed in the current literature. Simulation results of the control algorithm are given and validate the prioritized sensing behavior as well as the collision avoidance property.
Personalized wearable systems for real-time ECG classification and healthcare interoperability: Real-time ECG classification and FHIR interoperability

Continuous monitoring of an individual's health using wearable biomedical devices is becoming a norm these days with a large number of wearable kits becoming easily available. Modern wearable health monitoring devices have become easily available in the consumer market, however, real-time analyses and prediction along with alerts and alarms about a health hazard are not adequately addressed in such devices. Taking ECG monitoring as a case study the research paper focusses on signal processing, arrhythmia detection and classification and at the same time focusses on updating the electronic health records database in realtime such that the concerned medical practitioners become aware of an emergent situation the patient being monitored might face. Also, heart rate variability (HRV) analysis is usually considered as a basis for arrhythmia classification which largely depends on the morphology of the ECG waveforms and the sensitivity of the biopotential measurements of the ECG kits, so it may not yield accurate results. Initially, the ECG readings from the 3-Lead ECG analog front-end were de-noised, zero-offset corrected, filtered using recursive least square adaptive filter and smoothed using Savitzky-Golay filter and subsequently passed to the data analysis component with a unique feature extraction method to increase the accuracy of classification. The machine learning models trained on MITDB arrhythmia database (MIT-BIH Physionet) showed more than 97% accuracy using kNN classifiers. Neuralnet fitting models showed mean-squared error of as low as 0.0085 and regression value as high as 0.99. ECG abnormalities based on annotations in MITDB could be classified and these ECG observations could be logged to a server implementation based on FHIR standards. The instruments were networked using IoT (Internet of Things) devices and ECG event observations were coded according to SNOMED coding system and could be accessed in Electronic Health Record by the concerned medic to take appropriate and timely decisions. The system emphasizes on ‘preventive care rather than remedial cure’ as the next generation personalized health-care monitoring devices become available.
Fast physical models for Si LDMOS power transistor characterization

A new quasi-two-dimensional (Q2D) model is described for microwave laterally diffused MOS (LDMOS) power transistors. A set of one-dimensional energy transport equations are solved across a two-dimensional cross-section in a “current-driven” form. This process-oriented nonlinear model accounts for thermal effects, avalanche breakdown and gate conduction. It accurately predicts DC and microwave characteristics as demonstrated by comparison with measured DC characteristics, transconductance, forward gain, S21, and large-signal gate and drain charges for a LDMOS transistor. The model is fast, taking less than 30 ms to extract a 50 point DC IDS-VDS characteristic and less than 5 ms to produce S-parameters at a single frequency.
Impact of connection type on the efficiency of wireless power transfer systems

Analysing a wireless power transfer system is necessary to understand its performance and how different parameters can affect it. The associated analysis can be used as a reference to choose the suitable parameters given the constraints in any required design.  The topologies studied are series-series SS, series-parallel SP, parallel-series PS and parallel-parallel PP connections. Each topology has a different performance for the same combination. This gives a variety from which to choose suitable designs for specific systems with different loads, where the impact of the load on the efficiency also needs to be considered.
BPT Using Multi-dimensional Information for Semi-Automatic Content Retrieval

This paper presents a semi-automatic tool for content management systems for use in visual media production which is based on a Binary Partition Tree (BPT). In contrast to traditional content based image retrieval systems that work with entire images, the proposed tool analyses individual objects. Defined objects are produced by performing the segmentation inside a multi-dimensional BPT. The tree structure is colour based with the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. The BPTs can be intuitively browsed and stored within XML documents. To perform retrieval when post processing, a node of the query image is matched against the nodes of the BPT in the database representation. These are matched according to a combination of MPEG-7 descriptors, including colour, texture and edge histograms. The paper illustrates how the use of multi-dimensional information stored within BPTs, can significantly enhance content retrieval results for natural images. Performance evaluation results show how influential the quality segmentations are within retrieval results.
Event-Driven Configuration of a Neural Network CMP System over a Homogeneous Interconnect Fabric

Configuring a million-core parallel system at boot time is a difficult process when the system has neither specialised hardware support for the configuration process nor a preconfigured default state that puts it in operating condition. SpiNNaker is a parallel Chip Multiprocessor (CMP) system for neural network (NN) simulation. Where most large CMP systems feature a sideband network to complete the boot process, SpiNNaker has a single homogeneous network interconnect for both application inter-processor communications and system control functions such as boot load and run-time user-system interaction. This network improves fault tolerance and makes it easier to support dynamic run-time reconfiguration, however, it requires a boot process that is transaction-level compatible with the application’s communications model. Since SpiNNaker uses event-driven asynchronous communications throughout, theloader operates with purely local control: there is no global synchronisation, state information, or transition sequence. A novel two-stage “unfolding” boot-up process efficiently configures the SpiNNaker hardware and loads the application using a high-speed flood-fill technique with support for run-time re-configuration. SystemC simulation of a multi-CMP SpiNNaker system indicates an error-free CMP configuration time of 1.3ms, while a high-level simulation of a full-scale system (64K CMPs) indicates a mean application-loading time of ∼20ms (for a 100KB application), which is virtually independent of the sizeof the system. We verified the CMP configuration process with hardware-level Verilog simulation.
Expanding the twin pulse swing free profile

The twin-pulse motion profile is still perhaps the simplest profile in existence for reducing residual vibration. Its primary drawback is that of narrow bandwidth, i.e., it is effective for attenuating only a very narrow range of frequencies about its design frequency. This has led to the inclusion of more pulses to improve robustness to frequency variation. However, one cost of adding pulses is extending the duration of the resulting motion. This paper presents several techniques whereby the basic twin-pulse motion profile can be expanded to reduce its frequency sensitivity while still preserving its advantages. These techniques include intentionally mis-aligning the null points of ideal twin pulses and a convolved boxcar function, then adding a trapezoidal profile component, finally culminating in what we term a misaligned boxcar/trapezoidal/twin pulse (M- BC:TZ:TP) motion profile. This expanded profile and a basic twin-pulse profile were both evaluated on a ten-pendula system with natural frequencies varying over a range of nearly 10%. Simulation results showed an overall reduction of 97% with the expanded twin-pulse profile, and notably all ten frequencies were attenuated; only one frequency was attenuated with the standard twin-pulse profile. Experiments using a linear rail transport system and the ten pendula device validated the simulation. These expanded profiles retain the simplicity and short duration of the twin-pulse with increased robustness to frequency variations.
Object-based semi-automatic tool for content retrieval

The essence of a content-based retrieval system is to find images that are semantically related to the user's query from a database. Humans are much better than computers at extracting semantic information from images, being able to segment individual objects subconsciously. The availability of a pool of pre-segmented objects found using region analysis allows the human behaviour to be replicated. A semi-automatic tool for a region-based image retrieval system is presented.
Arbitration by selective removal of temporally dependent redundancies

This paper examines the transmission of real-time video and still images over the same medium, and presents an arbitration mechanism for efficient transfer of bulky data in the presence of scarce resources, by intelligently compromising the video stream. The arbitration selectively removes video packets based on the observation that if an intra-coded packet is lost, its dependants will not enhance the video but actually degrade it. The identification of this event permits them to be discarded thus freeing up resources at the expense of reduced temporal rate. This principle is also true for packets exceeding the end-to-end delay requirement and it can also be applied towards the end of scenes where information content is low. The freeing of resources improves the mean buffer occupancy; therefore losses and delay are reduced. A series of simulations are conducted to illustrate these points.
A multi-input multi-output recursive least squares algorithm with applications to LORAN-C transmitter

A MIMO RLS control algorithm is developed to automatically shape and control a signal produced by an AN/FPN44A Loran-C transmitter in simulation using digital signal processing techniques. The input signal to the transmitter amplifying tubes is formed to produce a desired output signal. A MATLAB computer program that simulates the Loran-C 44A tube transmitter is used to test and analyze the control algorithm. The successful results can be used in the US Coast Guard efforts to redesign various portions of the Loran-C tube-transmitter equipment to enhance and expand automation with new technology.<<ETX>>
A behavioral model for a wideband RF analog-to-digital converter

We describe a behavioral model of an interleaving RF-to-digital ADC. The ADC has an input bandwidth of over 3 GHz, and is a 16-bit interleaved digitizer. The model includes both analog and digital parts, describing the analog nonlinearity and frequency response, and digital impairments such as jitter, thermal noise, and interleaving errors. The model is implemented in a commercial simulator. The model is built from simulated data to enable the design of RF system architecture prior to the availability of first silicon.
A new technology for epitaxial II-VI compound semiconductor devices

ZnS and ZnSe are grown by metalorganic chemical-vapor deposition over GaAs and GaAlAs chemi-stop layers on a GaAs substrate. The III-V layers allow selective chemical removal of the substrate in order to expose the ZnS. The device allows investigation of the electrical and optical properties of epitaxial wide-gap II-VI compounds in the absence of any influence from the substrate material.
Motion-compensated 3-D subband coding of video

This paper describes a video coding system based on motion-compensated three-dimensional (3-D) subband/wavelet coding (MC-3DSBC), which can overcome the limits of both 3-D SBC and MC prediction-based coding. In this new system, spatio-temporal subbands are generated by MC temporal analysis and a spatial wavelet transform, and then encoded by 3-D subband-finite state scalar quantization (3DSB-FSSQ). The rate allocation from the GOP level to each class of subbands is optimized by utilizing the structural property of MC-3DSBC that additive superposition approximately holds for both rate and distortion. The proposed video coding system is applied to several test video clips. Its performance exceeds that of both a known MPEG-1 implementation and a similar subband MC predictive coder while maintaining modest computational complexity and memory size.
Network design and interconnection pricing in a heterogeneous terrain

In the design of a telecom network, the selection of link technology in a heterogeneous terrain is a challenging task as cost varies according to distance and total bandwidth. Traditionally research effort considers only distance and bandwidth for modelling of financial cost and ignores the effects terrain may have. We show quantitatively how geographical terrain and associated link technology influence the total cost. Our approach has implications for regulators who need to govern interconnection prices of services (voice, message or data) which may be provided by networks of different operators. We have modelled the link cost based on distance, bandwidth, terrain and technology simultaneously using a general error regression technique applied to real data obtained from the Indian Telecom Company, BSNL. We show that the error between the actual and modelled cost is less than 5% for all cases. Using our model, the financial cost to the operator is reduced and regulators can ensure a balanced development for the country.
Spatial Variation Of First Heart Sound Frequency Dynamics Across The Canine Leff Ventricle: A Comparison Of Intracardiac And Epicardial Recordings

Cardiac compressional and shear wave contribution to the first heart sound was investigated by comparing the frequency and phase of epicardial and intraventricular recordings. We hypothesized that the impulse-like closure of the mitral valve would dominate intraventricular recordings in contrast to the rising frequencies observed in epicardial recordings. However, intraventricular and epicardial recordings often exhibited very similar time-frequency spectra with a powerful rising frequency component beginning prior to mitral valve closure. Time-frequency spectra varied little across the left ventricle but no simple phase relationships were observed among the recording sites. While mitral valve closure produced a prominent high frequency component, it did not profoundly alter the underlying signal dynamics. These findings suggest that myocardial contraction plays a significant role in first heart sound initiation and frequency modulation.
Player identification in interactive sport scenes using region space analysis prior information and number recognition

This paper proposes using a novel region space technique to track sport persons for the purpose of extracting their shirt numbers and use this to provide augmented information to the viewer. The region adjacency graph and picture trees are used to perform a search for an object using prior knowledge from a scene description. Once the candidate object has been extracted the sub-space is examined for alphanumeric characters, which are then characterized by optical character recognition. Rogue candidates may be removed based on the recognition histograms with improved robustness using temporal analysis. The recognized sport person is accentuated using graphical overlays from a database.
Segmentation and tracking using region adjacency graphs, picture trees and prior information

Tracking of video objects in pixel space using block based methods or template matching suffers from boundary alignment problems, assumes knowledge of object location, and is severely effected by rotation and shear. This paper suggests a region domain based object tracking algorithm. Using region adjacency graphs it is proposed to perform the search in region space, using relational information rather than absolute value. Interframe inconsistencies in region space are overcome using a picture tree search technique.
Frame interpolation and bidirectional prediction of video using compactly encoded optical-flow fields and label fields

We consider the problems of motion-compensated frame interpolation (MCFI) and bidirectional prediction in a video coding environment. These applications generally require good motion estimates at the decoder. We use a multiscale optical-flow-based motion estimator that provides smooth, natural motion fields under bit-rate constraints. These motion estimates scale well with change in temporal resolution and provide considerable flexibility in the design and operation of coders and decoders. In the MCFI application, this estimator provides excellent interpolated frames that are superior to those of conventional motion estimators, both visually and in terms of peak signal-to-noise ratio (PSNR). We also consider the effect of occlusions in the bidirectional prediction application and introduce a dense label field that complements our motion estimator. This label field enables us to adaptively weight the forward and backward predictions and gives us substantial visual and PSNR improvements in the covered/uncovered regions of the sequence.