nils-herrmann/clean_scirepeval huggingface dataset:
Z Source Inverter: Topology Improvements Review
Venue: IEEE Industrial Electronics Magazine

One of the most promising power electronics converter topologies is the Z source inverter (ZSI) The ZSI is an emerging topology for power electronics dc ac converters with interesting properties such as buck boost characteristics and single stage conversion. A two port network, composed of two capacitors and two inductors connected in an X shape, is employed to provide an impedance source (Z source) network, coupling the inverter main circuit to the dc input source. The ZSI advantageously uses the shoot through (ST) state to boost the input voltage, which improves the inverter reliability and enlarges its application fields. In comparison with other power electronics converters, it provides an attractive single stage dc ac conversion with buck boost capability with reduced cost, reduced volume, and higher efficiency due to a lower component number. For emerging power generation technologies, such as fuel cells, photovoltaic (PV) arrays, and wind turbines, and new power electronic applications such as electric and hybrid vehicles, the ZSI is a very promising and competitive topology
Toward Automatic Rhodopsin Modeling as a Tool for High Throughput Computational Photobiology.
Venue: Journal of chemical theory and computation

We report on a prototype protocol for the automatic and fast construction of congruous sets of QM/MM models of rhodopsin like photoreceptors and of their mutants. In the present implementation the information required for the construction of each model is essentially a crystallographic structure or a comparative model complemented with information on the protonation state of ionizable side chains and distributions of external counterions. Starting with such information, a model formed by a fixed environment system, a flexible cavity system, and a chromophore system is automatically generated. The results of the predicted vertical excitation energy for 27 different rhodopsins including vertebrate, invertebrate, and microbial pigments indicate that such basic models could be employed for predicting trends in spectral changes and/or correlate the spectral changes with structural variations in large sets of proteins.
The Magnetic, Mechanical, Thermal Properties and Uv Resistance of CoFe2O4/SiO2 Coated Film on Wood

Magnetic wood has potential for electromagnetic shielding, as an indoor electromagnetic wave absorber, and for heavy metal adsorption. In this article, magnetic wood materials were prepared by precipitating magnetic CoFe2O4 nanoparticles and SiO2 on a wood surface via a hydrothermal process. The morphology, crystalline phase, and chemical structure of the magnetic wood composites were characterized by scanning electron microscope (SEM) transmission electron microscope (TEM) X ray diffraction (XRD) Raman spectroscopy, and Fourier transform infrared spectroscopy (FTIR) The as fabricated wood composites exhibited excellent magnetic and anti ultraviolet properties. Thermal analysis showed that the incorporation of SiO2 gel retarded the thermal decomposition of magnetic wood matrix and improved the thermal stability of wood. Moreover, the mechanical performance of the modified wood materials was also evaluated.
Efficient whole body trajectory optimization using contact constraint relaxation
Venue: 2016 IEEE RAS 16th International Conference on Humanoid Robots (Humanoids)

In this work we present a Trajectory Optimization framework for whole body motion planning for floating base robots. We demonstrate how the proposed approach can optimize whole body trajectories for most common gaits found in bipeds and quadrupeds. The underlying optimal control problem is solved efficiently using Sequential Linear Quadratic control. In contrast to most previous methods, the proposed approach is fast while still using a full dynamic model. Additionally, the approach is contact model free. Instead contact forces are added to the Optimal Control formulation as additional control inputs and contact constraints are handled using a relaxation approach. In our experiments we demonstrate that, despite this relaxation, our solver resolves constraint violations in only a few iterations. Hardware experiments underline the transferability from simulation to hardware.
Collective strategy for obstacle navigation during cooperative transport by ants
Venue: Journal of Experimental Biology

Group cohesion and consensus have primarily been studied in the context of discrete decisions, but some group tasks require making serial decisions that build on one another. We examine such collective problem solving by studying obstacle navigation during cooperative transport in ants. In cooperative transport, ants work together to move a large object back to their nest. We blocked cooperative transport groups of Paratrechina longicornis with obstacles of varying complexity, analyzing groups' trajectories to infer what kind of strategy the ants employed. Simple strategies require little information, but more challenging, robust strategies succeed with a wider range of obstacles. We found that transport groups use a stochastic strategy that leads to efficient navigation around simple obstacles, and still succeeds at difficult obstacles. While groups navigating obstacles preferentially move directly toward the nest, they change their behavior over time; the longer the ants are obstructed, the more likely they are to move away from the nest. This increases the chance of finding a path around the obstacle. Groups rapidly changed directions and rarely stalled during navigation, indicating that these ants maintain consensus even when the nest direction is blocked. Although some decisions were aided by the arrival of new ants, at many key points, direction changes were initiated within the group, with no apparent external cause. This ant species is highly effective at navigating complex environments, and implements a flexible strategy that works for both simple and more complex obstacles.  Ant groups navigate obstacles with a collective strategy that adapts to obstacle difficulty. Groups begin with simple behaviors; if unsuccessful, they switch to robust behaviors that work for more difficult obstacles.
Collective strategy for obstacle navigation during cooperative transport by ants

Group cohesion and consensus have primarily been studied in the context of discrete decisions, but some group tasks require making serial decisions that build on one another. We examine such collective problem solving by studying obstacle navigation during cooperative transport in ants. In cooperative transport, a group of ants works together to move a large object back to their nest. We blocked cooperative transport groups of Paratrechinal longicornis with obstacles of varying complexity, analyzing groups trajectories to infer what kind of strategy the ants employed. Simple strategies require little information, but more challenging, robust strategies succeed with a wider range of obstacles. We found that transport groups use a stochastic strategy that leads to efficient navigation around simple obstacles, and still succeeds at difficult ones. While groups navigating obstacles preferentially move directly toward the nest, they change their behavior over time; the longer the ants are obstructed, the more likely they are to move away from the nest. This increases the chance of finding a path around the obstacle. Groups rapidly changed directions and rarely stalled during navigation, indicating that these ants maintain consensus even when the nest direction is blocked. While some decisions were aided by the arrival of new ants, at many key points direction changes were initiated within the group, with no apparent external cause. This ant species is highly effective at navigating complex environments, and implements a flexible strategy that works quickly for simple obstacles and still succeeds with complex obstacles.
Consensus on consensus: a synthesis of consensus estimates on human caused global warming

The consensus that humans are causing recent global warming is shared by 90% 100% of publishing climate scientists according to six independent studies by co authors of this paper. Those results are consistent with the 97% consensus reported by Cook et al () based on 11 944 abstracts of research papers, of which 4014 took a position on the cause of recent global warming. A survey of authors of those papers (N 2412 papers) also supported a 97% consensus. Tol (2016 ) comes to a different conclusion using results from surveys of non experts such as economic geologists and a self selected group of those who reject the consensus. We demonstrate that this outcome is not unexpected because the level of consensus correlates with expertise in climate science. At one point, Tol also reduces the apparent consensus by assuming that abstracts that do not explicitly state the cause of global warming 'no position' represent non endorsement, an approach that if applied elsewhere would reject consensus on well established theories such as plate tectonics. We examine the available studies and conclude that the finding of 97% consensus in published climate research is robust and consistent with other surveys of climate scientists and peer reviewed studies.
Multi layer neural network for received signal strength based indoor localisation
Venue: IET Commun.

In received signal strength (RSS) based indoor wireless localisation system, radio pathloss model or radio map must be readily obtainable. However, the unpredictability of wireless channel makes it difficult to achieve high accuracy localisation in practice. In this study, the authors employed a multi layer neural network (MLNN) for RSS based indoor localisation without using the radio pathloss model or comparing the radio map. The proposed MLNN localisation system integrate the RSS signals transforming section, the raw data denoising section and the node locating section into a deep architecture. Furthermore, a boosting method is designed to promote location accuracy of the MLNN effectively. Experiment results demonstrate the feasibility and suitability of the proposed algorithm.
CNN Based Subject Independent Driver Emotion Recognition System Involving Physiological Signals for ADAS

Supporting drivers by Advanced Driver Assistance Systems (ADAS) significantly increases road safety. Driver's emotions recognition is a building block of advanced systems for monitoring the driver's comfort and driving ergonomics additionally to driver's fatigue and drowsiness forecasting. This paper presents an approach for driver emotions recognition involving a set of three physiological signals (Electrodermal Activity, Skin Temperature and the Electrocardiogram) Additionally, we propose a CNN (cellular neural network) based classifier to classify each signal into four emotional states. Moreover, the subject independent classification results of all signals are fused using Dempster Shafer evidence theory in order to obtain a more robust detection of the true emotional state. The new system is tested using the benchmarked MAHNOB HCI dataset and the results show a relatively high performance compared to existing competing algorithms from the recent relevant literature.
Hand eye calibration for robotic assisted minimally invasive surgery without a calibration object
Venue: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

In a robot mounted camera arrangement, hand eye calibration estimates the rigid relationship between the robot and camera coordinate frames. Most hand eye calibration techniques use a calibration object to estimate the relative transformation of the camera in several views of the calibration object and link these to the forward kinematics of the robot to compute the hand eye transformation. Such approaches achieve good accuracy for general use but for applications such as robotic assisted minimally invasive surgery, acquiring a calibration sequence multiple times during a procedure is not practical. In this paper, we present a new approach to tackle the problem by using the robotic surgical instruments as the calibration object with well known geometry from CAD models used for manufacturing. Our approach removes the requirement of a custom sterile calibration object to be used in the operating room and it simplifies the process of acquiring calibration data when the laparoscope is constrained to move around a remote centre of motion. This is the first demonstration of the feasibility to perform hand eye calibration using components of the robotic system itself and we show promising validation results on synthetic data as well as data acquired with the da Vinci Research Kit.
Investigation of speaker embeddings for cross show speaker diarization
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

This paper proposes to investigate speaker embeddings, a representation extracted from hidden layers of deep neural networks trained on a speaker identification task, on cross show diarization. The new representation brings an improvement over i vectors, and we show that while shallow hidden layers give best results on the single show condition, deeper layers yield better performance on cross show diarization. This confirms that deep representations model higher level features which help generalizing to different acoustic conditions. Experiments, conducted on the French corpus of REPERE, show that the deep speaker embeddings technique decreases DER by 0.82 points.
Modelling density segregation in flowing bidisperse granular materials
Venue: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

Preventing segregation in flowing granular mixtures is an ongoing challenge for industrial processes that involve the handling of bulk solids. A recent continuum based modelling approach accurately predicts spatial concentration fields in a variety of flow geometries for mixtures varying in particle size. This approach captures the interplay between advection, diffusion and segregation using kinematic information obtained from experiments and/or discrete element method (DEM) simulations combined with an empirically determined relation for the segregation velocity. Here, we extend the model to include density driven segregation, thereby validating the approach for the two important cases of practical interest. DEM simulations of density bidisperse flows of mono sized particles in a quasi two dimensional bounded heap were performed to determine the dependence of the density driven segregation velocity on local shear rate and particle concentration. The model yields theoretical predictions of segregation patterns that quantitatively match the DEM simulations over a range of density ratios and flow rates. Matching experiments reproduce the segregation patterns and quantitative segregation profiles obtained in both the simulations and the model, thereby demonstrating that the modelling approach captures the essential physics of density driven segregation in granular heap flow.
Adapting \text{B} Tree for Emerging Nonvolatile Memory Based Main Memory
Venue: IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems

Among the emerging nonvolatile memory (NVM) technologies, some resistive memories, including phase change memory (PCM) spin transfer torque magnetic random access memory (STT RAM) and metal oxide resistive RAM (ReRAM) have been considered as promising replacements of conventional dynamic RAM (DRAM) to build future main memory systems. Main memory databases can benefit from their nice features, such as their low leakage power and nonvolatility, the high density of PCM, the good read performance and low read energy consumption of STT RAM, and the low cost of ReRAM's crossbar architecture. However, they also have some disadvantages, such as their long write latency, high write energy, and limited lifetime, which bring challenges to database algorithm design for NVM based memory systems. In this paper, we focus on the design of the ubiquitous B+ tree, aiming to make it NVM friendly. We present a basic cost model for NVM based memory systems which distinguishes writes from reads, and propose detailed CPU cost and memory access models for search, insert, and delete operations on a B+ tree. Based on the proposed models, we analyze the CPU costs and memory behaviors of the existing NVM friendly B+ tree schemes, and find that they suffer from three issues. To address these issues we propose three different schemes. Experimental results show that our schemes can efficiently improve the performance, reduce the memory energy consumption, and extend the lifetime for NVM based memory systems.
Optimizing B+ Tree for PCM Based Hybrid Memory
Venue: EDBT

change memory (PCM) as a newly developed storage medium has many attractive properties such as non volatility, byte addressability, high density and low energy consumption. Thus, PCM can be used to build non volatile main memory databases. However, PCM's long write latency and high write energy bring challenges to PCM based memory systems. In this paper, we propose an improvement over the B+ tree for PCM. Particularly, we consider the read/write tendency of leaf nodes. For write intensive leaf nodes, we use an overflow node technique to reduce PCM writes, while for read intensive ones, we adjust the tree structure to remove overflow nodes to improve read performance. Our experimental results suggest that our proposal outperforms the traditional B+ tree and the overflow B+ tree.
INFLUENCE OF LIQUID NITROGEN COOLING ON MICROSTRUCTURE AND MECHANICAL PROPERTIES OF FRICTION STIR WELDED(FSW) DISSIMILAR AA5083 AA6061 ALUMINUM ALLOY JOINTS

In this paper, the effect of cryogenic (liquid nitrogen) cooling on grain size and influence of microstructure on mechanical properties of Friction stir welded (FSW) dissimilar Aluminium 5083 and 6061 alloys were studied due to their range of usage in naval and marine applications. However cryogenic (liquid nitrogen) coolant was employed immediately behind the FSW tool for rapid cooling to reduce the grain size and improve the mechanical properties of AA5083 and AA6061 Aluminum alloy. The welding parameters such as, welding speed, tool rotational speed and tool pin profile plays a major role in deciding the weld quality. The square tool profile generates a fairly localized deformation which results high volume of material was stirred and carried with the pin tool and also better mixing of plasticized metal. It was observed that better mechanical properties are obtained at rotational speed of 900rpm and welding speed of 31.5mm/min the fine microstructure is obtained. It was also observed that mechanical properties are enormously enriched. The experimental grain size and mechanical properties have correlated by microstructures and fracture structures.
Effect of Head and Tongue Posture on the Pharyngeal Airway Dimensions and Morphology in Three Dimensional Imaging: a Systematic Review
Venue: Journal of oral maxillofacial research

Natural head position is recommended to be optimal at cone beam computed tomography acquisition. For standardization purposes in control of treatment outcome, it is clinically relevant to discuss, if a change of posture from natural head position may have an effect on the pharyngeal airway dimensions and morphology, during computed tomography, cone beam computed tomography or magnetic resonance imaging acquisition. This was the aim of the present literature review study for purposes of valid evidence, which was hypothesized, to be present.  This systematic literature review has been registered in PROSPERO database with following number: CRD42015024567. A systematic literature search performed in PubMed, Embase and Cochrane was carried out in order to evaluate if the effect of human head or tongue posture has an effect on upper airway dimensions and morphology in CT, CBCT or MRI. Study quality assessment was performed. Predictor variable was head and tongue posture. Endpoints were numerical values of upper airway dimensions and morphology.  Overall 1344 articles (Embase 1063, PubMed 269, and Cochrane 12) resulted in four included publications. Quality assessments revealed poor quality and low level evidence by 46 67% of the maximum achievable score. Heterogeneous methodology made a meta analysis impossible, consequently a narrative synthesis was performed.  Limited, poor quality and low evidence level literature is available on the effect of head posture on upper airway dimensions and morphology in three dimensional imaging. Valid evidence requires a standardized method of head and tongue posture during image acquisition in future studies.
An Evaluation of Upper and Lower Pharyngeal Airway Width, Tongue Posture and Hyoid Bone Position in Subjects with Different Growth Patterns.
Venue: Journal of clinical and diagnostic research JCDR

It is important to evaluate the position of the hyoid bone in relation to the tongue at the beginning of orthodontic treatment so that during the treatment, its position may be directed hence overall impact on airway could be assessed.  The aim of this study was to evaluate the upper and lower pharyngeal airway dimensions, posture of tongue and hyoid bone position in young adults with different growth patterns.  Sample size of the study included 90 post adolescent subjects, within the age range of 18 32 years. Based on the different growth pattern of the face, subjects were divided into Group I (n=30; average growth pattern) Group II (n=30; horizontal growth pattern) and Group III (n=30; vertical growth pattern) Lateral cephalogram were traced and analysed manually by the same investigator for evaluation of upper and lower pharyngeal airway, tongue posture and hyoid bone position. The intergroup comparison of upper and lower pharyngeal airway dimensions, posture of tongue and hyoid bone was performed with one way ANOVA test.  The results showed that upper oropharyngeal widths were significantly different in different facial skeletal patterns (p=0.00) Subjects with vertical skeletal pattern have significantly narrower upper airways than those with horizontal skeletal pattern (p= 0.025) There was significantly higher difference in position of dorsum of the tongue in vertical growth pattern group (p=0.00) The hyoid bone was positioned farther from the mandibular symphysis in brachyfacial subjects, reflected by the larger H RGN (Hyoid retrognathion) values compared with the dolichofacial and normal subjects (p=0.044)  The upper oropharyngeal width was found to be narrower in subjects with vertical growth pattern. The dorsum of the tongue is seen to be placed higher in subjects with vertical growth pattern. The hyoid bone was more inferiorly and posteriorly positioned in subjects with horizontal growth pattern. Variations are seen in upper and lower oropharyngeal widths, posture of the tongue and hyoid bone position in all the growth patterns.
Morphological comparison of maxilloface, tongue posture, and pharyngeal airway before and after the mandibular setback surgery

In the present study, we reviewed the patients who were diagnosed as skeletal mandibular prognathism who underwent a sagittal split ramus osteotomy (SSRO) comparing the perioperative change of the tongue posture and the pharyngeal airway. Also, we considered it versus a postoperative change by SSRO about maxillofacial morphology of obstructive sleep apnea hypopnea syndrome (OSAS) and the pharyngeal airway. We reviewed 20 patients diagnosed as skeletal mandibular prognathism in our hospital. We compared the lateral cephalogram data of the patients one month before the operation (T1) one month after (T2) and one year after (T3) with 53 students belonging to our university setting as the normal group who displayed nothing abnormal with the maxillofacial, and 21 patients diagnosed as OSAS at the Tsukuba University Hospital.