nils-herrmann/clean_scirepeval huggingface dataset:
Face recognition based on the uncorrelated discriminant transformation

The extraction of discriminant features is the most fundamental and important problem in face recognition. This paper presents a method to extract optimal discriminant features for face images by using the uncorrelated discriminant transformation and KL expansion. Experiments on the ORL database and the NUST603 database have been performed. Experimental results show that the uncorrelated discriminant transformation is superior to the Foley}Sammon discriminant transformation and the new method to extract uncorrelated discriminant features for face images is very e!ective. An error rate of 2.5% is obtained with the experiments on the ORL database. An average error rate of 1.2% is obtained with the experiments on the NUST603 database. Experiments show that by extracting uncorrelated discriminant features, face recognition could be performed with higher accuracy on lower than 16 16 resolution mosaic images. It is suggested that for the uncorrelated discriminant transformation, the optimal face image resolution can be regarded as the resolution m n which makes the dimensionality N"mn of the original image vector space be larger and closer to the number of known-face classes. 2001 Pattern Recognition Society.
Predictive information processing in music cognition. A critical review.

Expectation and prediction constitute central mechanisms in the perception and cognition of music, which have been explored in theoretical and empirical accounts. We review the scope and limits of theoretical accounts of musical prediction with respect to feature-based and temporal prediction. While the concept of prediction is unproblematic for basic single-stream features such as melody, it is not straight-forward for polyphonic structures or higher-order features such as formal predictions. Behavioural results based on explicit and implicit (priming) paradigms provide evidence of priming in various domains that may reflect predictive behaviour. Computational learning models, including symbolic (fragment-based), probabilistic/graphical, or connectionist approaches, provide well-specified predictive models of specific features and feature combinations. While models match some experimental results, full-fledged music prediction cannot yet be modelled. Neuroscientific results regarding the early right-anterior negativity (ERAN) and mismatch negativity (MMN) reflect expectancy violations on different levels of processing complexity, and provide some neural evidence for different predictive mechanisms. At present, the combinations of neural and computational modelling methodologies are at early stages and require further research.
Classification of occupational therapy intervention for inpatient stroke rehabilitation.

We investigated the specific type of occupational therapy intervention used by occupational therapists during inpatient stroke rehabilitation in one midwestern U.S. hospital to determine the frequency of prefunctional versus functional activity use.



A retrospective chart analysis was conducted of clients who received inpatient stroke rehabilitation between January 2003 and June 2004. Type of intervention, intervention strategies, and adaptive equipment use were recorded for each session provided.



The majority of sessions (65.77%, n = 1,022) consisted of activities that were prefunctional in nature compared with 48.26% (n = 750) that focused on activities of daily living. Musculoskeletal intervention strategies were used in more than half (52.25%) of the sessions.



More sessions were spent on prefunctional than on functional activities, and musculoskeletal intervention strategies were most common. Future research studies are warranted to determine the most effective intervention for this client population.
Resource-Efficient Neural Architect

Neural Architecture Search (NAS) is a laborious process. Prior work on automated NAS targets mainly on improving accuracy, but lacks consideration of computational resource use. We propose the Resource-Efficient Neural Architect (RENA), an efficient resource-constrained NAS using reinforcement learning with network embedding. RENA uses a policy network to process the network embeddings to generate new configurations. We demonstrate RENA on image recognition and keyword spotting (KWS) problems. RENA can find novel architectures that achieve high performance even with tight resource constraints. For CIFAR10, it achieves 2.95% test error when compute intensity is greater than 100 FLOPs/byte, and 3.87% test error when model size is less than 3M parameters. For Google Speech Commands Dataset, RENA achieves the state-of-the-art accuracy without resource constraints, and it outperforms the optimized architectures with tight resource constraints.
Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks

The positioning methods based on received signal strength (RSS) measurements, link the RSS values to the position of the mobile station(MS) to be located. Their accuracy depends on the suitability of the propagation models used for the actual propagation conditions. In indoor wireless networks, these propagation conditions are very difficult to predict due to the unwieldy and dynamic nature of the RSS. In this paper, we present a novel method which dynamically estimates the propagation models that best fit the propagation environments, by using only RSS measurements obtained in real time. This method is based on maximizing compatibility of the MS to access points (AP) distance estimates. Once the propagation models are estimated in real time, it is possible to accurately determine the distance between the MS and each AP. By means of these distance estimates, the location of the MS can be obtained by trilateration. The method proposed coupled with simulations and measurements in a real indoor environment, demonstrates its feasibility and suitability, since it outperforms conventional RSS-based indoor location methods without using any radio map information nor a calibration stage.
Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection

fMRI and EEG are complimentary methods for the analysis of brain activity since each method has its strength where the other one has limits: The spatial resolution is thus in the range of millimeters with fMRI and the time resolution is in the range of milliseconds with EEG. For a comprehensive understanding of brain activity in target detection, nine healthy subjects (age 24.2 +/- 2.9) were investigated with simultaneous EEG (27 electrodes) and fMRI using an auditory oddball paradigm. As a first step, event-related potentials, measured inside the scanner, have been compared with the potentials recorded in a directly preceding session in front of the scanner. Attenuated amplitudes were found inside the scanner for the earlier N1/P2 component but not for the late P300 component. Second, an independent analysis of the localizations of the fMRI activations and the current source density as revealed by low resolution electromagnetic tomography (LORETA) has been done. Concordant activations were found in most regions, including the temporoparietal junction (TPJ), the supplementary motor area (SMA)/anterior cingulate cortex (ACC), the insula, and the middle frontal gyrus, with a mean Euclidean distance of 16.0 +/- 6.6 mm between the BOLD centers of gravity and the LORETA-maxima. Finally, a time-course analysis based on the current source density maxima was done. It revealed different time-course patterns in the left and right hemisphere with earlier activations in frontal and parietal regions in the right hemisphere. The results suggest that the combination of EEG and fMRI permits an improved understanding of the spatiotemporal dynamics of brain activity.
An Efficient HOS-Based Gait Authentication of Accelerometer Data

We propose a novel efficient and reliable gait authentication approach. It is based on the analysis of accelerometer signals using higher order statistics. Gait patterns are obtained by transformation of acceleration data in feature space represented with higher order cumulants. The proposed approach is able to operate on multichannel and multisensor data by combining feature-level and sensor-level fusion. Evaluation of the proposed approach was performed using the largest currently available data set OU-ISIR containing inertial data of 744 subjects. Authentication was performed by cross-comparison of gallery and probe gait patterns transformed in feature space. In addition, the proposed approach was evaluated using data set collected by McGill University, containing long-sequence acceleration signals of 20 subjects acquired by smartphone during casual walking. The results have shown an average equal error rate of 6% to 12%, depending on the selected experimental parameters and setup. When compared with the latest state of the art, evaluated performance reveal the proposed approach as one of the most efficient and reliable of the currently available accelerometer-based gait authentication approaches.
A three-phase flyback current-fed push-pull bidirectional dc-dc converter for dc microgrid application

This paper proposes a new three-phase flyback current-fed push-pull bidirectional dc-dc converter, which in both senses operation of the proposed converter is analyzed and explained even as the DC transfer function in continuous, discontinuous and critical conduction mode has been presented. The proposed converter is suitable for the dc microgrids bus, such as those having fuel cells, PV array and wind turbine as the DC source power supply. Where bidirectional power flow related with battery or supercapacitor bank charge and discharge is necessary.
A high-accuracy method for fine registration of overlapping point clouds

This paper presents a high-accuracy method for fine registration of two partially overlapping point clouds that have been coarsely registered. The proposed algorithm, which is named dual interpolating point-tosurface method, is principally a modified variant of point-to-surface Iterative Closest Point (ICP) algorithm. The original correspondences are established by adopting a dual surface fitting approach using B-spline interpolation. A novel auxiliary pair constraint based on the surface fitting approach, together with surface curvature information, is employed to remove unreliable point matches. The combined constraint directly utilizes global rigid motion consistency in conjunction with local geometric invariant to reject false correspondences precisely and efficiently. The experimental results involving a number of realistic point clouds demonstrate that the new method can obtain accurate and robust fine registration for pairwise 3D point clouds. This method addresses highest accuracy alignment with less focus on recovery from poor coarse registrations.
Time-frequency Analysis 3.1 Time-frequency Analysis

Let f (t) be a mathematical idealization of some physical signal depending on time t. Perhaps f can be considered as a superposition of oscillating components but these oscillations have to be limited to some finite extension in time. This is a fundamental problem of the Fourier inversion formula which states that, for a well-behaved signal f one has f (t) = ∞ −∞ˆf (ξ)e 2πitξ dξ expressing a complex signal f as a superposition of exponentials e 2πitξ. If f vanishes outside some finite set then the exponentials, which extend over all time, must cancel each other in some fantastic way that makes it virtually impossible to quantify in any intuitive way which frequencies play a dominant role at any particular time t. 3.1.2 Frequency Local in time Consider a physical signal to be a square integrable real-valued function of time, x(t). One can define a complex extension z(t) = x(t) + iy(t) bey letting y(t) be the inverse Fourier transform of −isgn (t)ˆ x(ξ) where sgn denotes the signum function ξ/|ξ|. In this casê z = ˆ x + iˆy has only positive frequencies. Exercise 3.1.1. Explain why z(t) has an extension to a complex argument t + is, s > 0 that is analytic in the upper half plane {t + is : s > 0}. You may assume that x(t) is a continuous, bounded, absolutely integrable function. The analytic signal z has the polar form r(t)e iθ(t) where r = x 2 + y 2 and θ = arctan y/x. The instantaneous frequency can be defined as dθ/dt. This point of view however is a little too simple because x(t) can be a superposition of multiple oscillating components and the instantaneous frequency cannot resolve multiple oscillating contributions. We will return to this point later in this chapter. First we want to consider some fundamental issues governing the impossibility of joint time-frequency localization and, in view of these limitations, mathematical tools that aim to characterize compositions of signals in terms of time localized oscillations in view of such limitations. One typically refers to such tools as time-frequency representations. As with the case of Fourier transforms we will encounter both continuous and discrete parameter time-frequency representations. 3.1.3 The Heisenberg-Wiener inequality Variance inequalities Theorem 3.1.2. (Heisenberg uncertainty principle) If f ∈ L 2 (R) with f 2 = 1 then xf (x) 2 ξ ˆ f (ξ) 2 ≥ …
Classifying eye and head movement artifacts in EEG signals

Brain Computer Interfaces has some exciting prospects such as controlling devices at the speed of thought. However BCI technology is far from attaining this goal. A significant challenge the EEG-based system has is the interference of artifacts in the EEG generated by eye and head movement. This paper presents the use of machine learning techniques to classify artifacts in the EEG. Successful artifact classification was then be applied to improve existing artifact removal techniques. The experiment used a state-of-the-art EEG system to gather the classifier input. An eye tracker and motion sensor were also used to measure and provide the ground truth for the classification experiments. The data from these devices were captured using custom built software developed for this research. The classifiers tested showed potential to classify artifacts in the EEG when trained on a per-person basis. This research paves the way for further work to be carried out to explore subject-independent artifact classification.
Game design as marketing : How game mechanics create demand for virtual goods

Selling virtual goods for real money is an increasingly popular revenue model for massivelymultiplayer online games (MMOs), social networking sites (SNSs) and other online hangouts. In this paper, we argue that the marketing of virtual goods currently falls short of what it could be. Game developers have long created compelling game designs, but having to market virtual goods to players is a relatively new situation to them. Professional marketers, on the other hand, tend to overlook the internal design of games and hangouts and focus on marketing the services as a whole. To begin bridging the gap, we propose that the design patterns and game mechanics commonly used in games and online hangouts should be viewed as a set of marketing techniques designed to sell virtual goods. Based on a review of a number of MMOs, we describe some of the most common patterns and game mechanics and show how their effects can be explained in terms of analogous techniques from marketing science. The results provide a new perspective to game design with interesting implications to developers. Moreover, they also suggest a radically new perspective to marketers of ordinary goods and services: viewing marketing as a form of game design.
Development of a full bridge GaN HEMT converter for inductive power transfer application

This paper presents the results of the development and use of a full bridge GaN high electron mobility transistor (HEMT) converter used in an inductive power transfer (IPT) application. Experimental results using a Si MOSFETs converter in an IPT setup has previously been reported. By using GaN HEMTs instead of Si MOSFETs, the converter efficiency can be increased over a broad range of operating points. Component selection regarding the gate isolation and low parasitics are discussed. The efficiency comparison between the Si and GaN converters shows that a GaN converter can outperform the Si in both soft and hard switching operation points if correctly designed.
Are mmWave Low-Complexity Beamforming Structures Energy-Efficient? Analysis of the Downlink MU-MIMO

Future cellular systems based on the use of above-6 GHz frequencies, the so-called millimeter wave (mmWave) bandwidths, will heavily rely on the use of antenna arrays both at the transmitter and at the receiver, possibly with a large number of elements. For complexity reasons, fully digital precoding and postcoding structures may turn out to be unfeasible, and thus suboptimal structures, making use of simplified hardware and a limited number of RF chains, have been investigated. This paper considers and makes a comparative assessment, both from a spectral efficiency and energy efficiency point of view, of several suboptimal precoding and postcoding beamforming structures for the downlink of a cellular multiuser MIMO (MU-MIMO) system. Based on the most recently available data for the energy consumption of phase shifters and switches, we show that there are cases where fully-digital beamformers may achieve a larger energy efficiency than lower-complexity solutions, as well as that structures based on the exclusive use of switches achieve quite unsatisfactory performance in realistic scenarios.
Mitigation of Solar Irradiance Intermittency in Photovoltaic Power Systems With Integrated Electric-Vehicle Charging Functionality

Mitigation of the variability in output power of renewable generators such as solar photovoltaic (PV) systems is a growing concern as these generators reach higher penetrations on electric grids. Furthermore, increased penetration of electric vehicle (EV) loads presents a challenge for distribution feeders. This paper presents a system where a bidirectional, highly efficient, dc-dc EV charger is placed between the high-voltage dc bus of a PV inverter and the EV battery. The system partially alleviates feeder overloading by providing fast charging for the EV battery from the PV system. In addition, the charger is capable of diverting fast changes in PV power output to the battery, thereby reducing the rate of change of inverter output power to a level below the ramp rate of existing grid resources. The paper addresses sizing of the charger and energy storage based on the PV system rating, the desired maximum ramp rate, and site solar irradiation characteristics, including geographic dispersion of PV arrays. Analysis suggests that small amounts of energy storage can accomplish large reductions in output power ramp rate. Experimental results are shown for a 10 kW, 98% efficient dc-dc charger based on bidirectional four-phase zero-voltage-switching converter.
The complex dielectric constant of pure and sea water from microwave satellite observations

We provide a new fit for the microwave complex dielectric constant of water in the salinity range between 0-40 ppt using two Debye relaxation wavelengths. For pure water, the fit is based on laboratory measurements in the temperature range between -20/spl deg/C and +40/spl deg/C including supercooled water and for frequencies up to 500 GHz. For sea water, our fit is valid for temperatures between -2/spl deg/C and +29/spl deg/C and for frequencies up to at least 90 GHz. At low frequencies, our new model is a modified version of the Klein-Swift model. We compare the results of the new fit with various other models and provide a validation using an extensive analysis of brightness temperatures from the Special Sensor Microwave Imager.
Template Attacks

We present template attacks, the strongest form of side channel attack possible in an information theoretic sense. These attacks can break implementations and countermeasures whose security is dependent on the assumption that an adversary cannot obtain more than one or a limited number of side channel samples. They require that an adversary has access to an identical experimental device that he can program to his choosing. The success of these attacks in such constraining situations is due manner in which noise within each sample is handled. In contrast to previous approaches which viewed noise as a hindrance that had to be reduced or eliminated, our approach focuses on precisely modeling noise, and using this to fully extract information present in a single sample. We describe in detail how an implementation of RC4, not amenable to techniques such as SPA and DPA, can easily be broken using template attacks with a single sample. Other applications include attacks on certain DES implementations which use DPA–resistant hardware and certain SSL accelerators which can be attacked by monitoring electromagnetic emanations from an RSA operation even from distances of fifteen feet.
Facial soft-tissue spaces and retaining ligaments of the midcheek: defining the premaxillary space.

This anatomical study was undertaken to define the soft-tissue spaces, retaining ligaments, and their relations in the midcheek.



Sixty fresh hemifaces were dissected. The retaining ligaments and facial spaces were defined and their dimensions recorded. The course of the key vessels and branches of the facial and infraorbital nerves were defined and their anatomical relations noted.



The preseptal and prezygomatic spaces underlie the lid-cheek and malar segments of the midcheek. A previously undocumented soft-tissue space, the premaxillary space, was found to underlie the nasolabial segment. The retaining ligaments of the midcheek are the tear trough-orbicularis retaining ligament complex in the upper midcheek and the zygomatic and maxillary ligaments in the lower midcheek. The tear trough-orbicularis retaining ligament complex separates the preseptal space above from the prezygomatic and premaxillary spaces below. Facial nerve branches in the midcheek are closely associated with the zygomatic ligaments located outside the lower boundary of the prezygomatic space and are protected so long as the dissection is kept within this space. The infraorbital nerve is protected by the floor of the premaxillary space, formed by the levator labii superioris and, at the inferior boundary of the space, by the close relation with the maxillary ligaments.



This study completely defined the spaces and retaining ligaments of the midcheek. Knowledge of this anatomy is key to safe and atraumatic suborbicular dissection for effective midcheek lifts.
A Model-Driven Engineering Approach for ROS using Ontological Semantics

This paper presents a novel ontology-driven software engineering approach for the development of industrial robotics control software. It introduces the ReApp architecture that synthesizes model-driven engineering with semantic technologies to facilitate the development and reuse of ROS-based components and applications. In ReApp, we show how different ontological classification systems for hardware, software, and capabilities help developers in discovering suitable software components for their tasks and in applying them correctly. The proposed model-driven tooling enables developers to work at higher abstraction levels and fosters automatic code generation. It is underpinned by ontologies to minimize discontinuities in the development workflow, with an integrated development environment presenting a seamless interface to the user. First results show the viability and synergy of the selected approach when searching for or developing software with reuse in mind.