Miracle-dz/UniFAR-FTUs huggingface dataset:
Dithering Skip Modulation, Width and Dead Time Controllers in Highly Efficient DC-DC Converters for System-On-Chip Applications

This paper proposes temperature-independent load sensor (LS), optimum width controller (OWC), optimum dead-time controller (ODC), and tri-mode operation to achieve high efficiency over an ultra-wide-load range. Higher power efficiency and wider loading current range require rethinking the control method for DC-DC converters. Therefore, a highly efficient tri-mode DC-DC converter is invented in this paper for system-on-chip (SoC) applications, which is switched to sleeping mode at very light load condition or to high-speed mode at heavy load condition. The efficiency improvement is upgraded by inserting new proposed dithering skip modulation (DSM) between conventional pulse-width modulation (PWM) and pulse-frequency modulation (PFM). In other words, an efficiency-improving DSM operation raises the efficiency drop because of transition from PWM to PFM. Importantly, DSM mode can dynamically skip the number of gate driving pulses, which is inverse proportional to load current. Simplistically and qualitatively stated, the novel load sensor automatically selects optimum modulation method and power MOSFET width to achieve high efficiency over a wide load range. Moreover, optimum power MOSFET turn-on and turn-off delays in synchronous rectifiers and reduced ground bounce can save much switching loss by current-mode dead-time controller. Experimental results show the tri-mode operation can have high efficiency about 90% over a wide load current range from 3 to 500 mA. Owing to the effective mitigation of the switching loss contributed by optimum power MOSFET width and reduction of conduction loss contributed by optimum dead-times, the novel width and dead-time controllers achieve high efficiency about 95% at heavy load condition and maintain the highly efficient performance to very light load current about 0.1 mA.
Parallel Simulation of Multi-agent Systems Using Terracotta

This paper describes a novel approach to parallel simulation of complex multi-agent systems which is based on actors and the Java middleware Terracotta. The approach aims to an exploitation of the computing power of modern multicore machines. Terracotta was chosen because it transparently allows to cluster the JVM. The paper discusses design and implementation aspects of the approach, and demonstrates the achievable execution performance through the parallel simulation of a scalable multi-agent system based on the predator/prey model.
RTOS-based software architecture for multisensor fusion system

In this paper, software architecture for multisensor fusion system (MFS) in dynamic environment is described. The architecture has the characteristics of robustness, dynamically reconfigurable framework, "plug-in-play" for sensor, and predictability of sensor action. According to requirements of MFS, the real-time operating system (RTOS) is applied in this software architecture. The result is an RTOS-based software architecture, which consists of five kinds of tasks: sensor sampling task (SST), sensor data processing task (SDPT), fusion task (FT), management task (MT) and man/machine interface task (MMIT). A calligraphic robot has been designed and developed in our lab based on the software architecture proposed. The application of the architecture makes the sensor management of the calligraphic robot system easy.
A possible artifact in electroencephalography.

Although it is now well established that the brain does produce a great variety of electrical patterns, the oscillating potentials/ such as the alpha rhythm, have been given particular prominence as examples of some special kind of electrical activity of neurons. The proposal has been entertained, for example, that brain waves may be produced by summation of action potential spikes. In 1948, Jasper suggested that these "waves" indicate spontaneous rhythmic fluctuations in the local excitability of groups of neurons in the cerebral cortex. He further suspected that there may be certain specialized cells in the cortex that produce these rhythmic oscillations in potential. In a later paper (Li, McLennan, & Jasper, 1952) it was clearly demonstrated by simultaneous recording that the action potential spikes of neuronal activity and the slower oscillations of "brain waves" were quite uncorrelated. The authors conclude, "Brain waves do seem to be phenom-
Initiation of voluntary movements at free will and ongoing 0.1-Hz BOLD oscillations in the insula—a pilot study

Recently we hypothesized that the intention to initiate a voluntary movement at free will may be related to the dynamics of hemodynamic variables, which may be supported by the intertwining of networks for the timing of voluntary movements and the control of cardiovascular variables in the insula. In the present study voluntary movements of 3 healthy subjects were analyzed using fMRI scans at 1.83-s intervals along with the time course of slow hemodynamic changes in sensorimotor networks. For the analyses of BOLD time courses the Wavelet transform coherence (WTC) and calculation of phase-locking values were used. Analyzed was the frequency band between 0.07 and 0.13 Hz in the supplementary motor area (SMA) and insula, two widely separated regions co-active in motor behavior. BOLD signals displayed slow fluctuations, concentrated around 0.1 Hz whereby the intrinsic oscillations in the insula preceded those in the SMA by 0.5–1 s. These preliminary results suggest that slow hemodynamic changes in SMA and insula may condition the initiation of a voluntary movement at free will.
Simultaneously estimating DOA and phase error of a partly calibrated ULA by data reconstruction

The paper considers the problem of how to simultaneously estimate the direction-of-arrival (DOA) of a source signal and the phase error of a uniform linear array (ULA). We introduce a new method to estimate those parameters for a partly calibrated ULA. As its name suggests, partly calibrated ULA means a array with some of its sensor elements have been calibrated. In particular, our method can be well executed when there is only one calibrated sensor. Firstly, the proposed method reconstructs some sets of data from the array snapshots. According to the subspace theory, a set of linear combination associated with DOA and array phase errors can be extracted with the help of eigenvalue decomposition (EVD). The unknown DOA and sensor phase erros can thus be described by a set of linear equation and its solution can be obtained by least squares (LS) approach. Different from other partily calibrated array based methods, this method can even work well under the condition that the calibrated element is not consecutively located round the reference one. The proposed method is both simple and effective, and simulation comparisons with other algorithms validate its effectiveness.
Modelling heatwaves in viticultural regions of southeastern Australia

The production of quality wine grapes is sensitive to heatwaves, especially at key phenostages such as flowering and ripening. Climatological models of heatwaves with application in viticulture need to account for (a) a range of meteorological variables, (b) intensity, (c) duration and (d) timing of events. The meteorological variable most commonly associated with heatwaves is maximum temperature; however, high minimum temperatures associated with heatwaves are also relevant for viticulture. Intensity should be expressible as either exceeding a categorical threshold such as 35°C or a relative threshold such as the 90th percentile. In addition to the chance of heatwaves of a given intensity and duration for the growing season (September to April), viticulturists are interested in monthly and fortnightly windows to account for the timing of critical phenostages. The model presented here is an attempt to meet these four requirements. The model is stochastic and incorporates seasonality and daily persistence of temperature through a Markov process and implies that frequency (or the return period) of heatwaves decreases (increases) geometrically with each additional day of duration. The final model is expressed as a simple equation involving a single location-specific parameter, M, which relates to the maritime influence. The model was tested over the viticultural regions of southeastern Australia by comparison with observed data, and by assessing the physical and climatological meaning of parameter M. Cross-validated model estimates of annual frequency of heatwaves were in good agreement with observations. The parameter M proved robust and physically meaningful: it is location-specific, its isopleths have the qualitative impression of sea-breeze or maritime influence and it is quantitatively related to the skewness of the summertime maximum temperature distribution.
Compression-based ray casting of very large volume data in distributed environments

The paper proposes a novel parallel/distributed ray casting scheme for very large volume data that can be effectively used in distributed environments. Our method, based on data compression, attempts to enhance the rendering speedups by quickly reconstructing voxel data from local memory rather than expensively fetching them from remote memory spaces. Our compression based volume rendering scheme minimizes communications between processing elements during rendering computation, hence it is very appropriate for both distributed memory multiprocessors and PC/workstation clusters, where the relatively high communication costs often hinder efficient parallel/distributed processing. We report experimental results on both a Cray T3E and a PC/workstation cluster for the Visible Man dataset.
A functional angle on some after-effects in cortical vision

The question of how our brains and those of other animals code sensory information is of fundamental importance to neuroscience research. Visual illusions offer valuable insight into the mechanisms of perceptual coding. One such illusion, the tilt after–effect (TAE), has been studied extensively since the 1930s, yet a full explanation of the effect has remained elusive. Here, we put forward an explanation of the TAE in terms of a functional role for adaptation in the visual cortex. The proposed model accounts not only for the phenomenology of the TAE, but also for spatial interactions in perceived tilt and the effects of adaptation on the perception of direction of motion and colour. We discuss the implications of the model for understanding the effects of adaptation and surround stimulation on the response properties of cortical neurons.
Non-solvable base change for Hilbert modular representations and zeta functions of twisted quaternionic Shimura varieties

In this paper we prove some non-solvable base change for Hilbert modular representations, and we use this result to show the meromorphic continuation to the entire complex plane of the zeta functions of some twisted quaternionic Shimura varieties. The zeta functions of the twisted quaternionic Shimura varieties are computed at all places.
Clause-iteration with MapReduce to scalably query datagraphs in the SHARD graph-store

Graph data processing is an emerging application area for cloud computing because there are few other information infrastructures that cost-effectively permit scalable graph data processing. We present a scalable cloud-based approach to process queries on graph data utilizing the MapReduce model. We call this approach the Clause-Iteration approach. We present algorithms that, when used in conjunction with a MapReduce framework, respond to SPARQL queries over RDF data. Our innovation in the Clause-Iteration approach comes from 1) the iterative construction of query responses by incrementally growing the number of query clauses considered in a response, and 2) our use of flagged keys to join the results of these incremental responses. The Clause-Iteration algorithms form the basis of our scalable, SHARD graph-store built on the Hadoop implementation of MapReduce. SHARD performs favorably when compared to existing "industrial" graph-stores on a standard benchmark graph with 800 million edges. We discuss design considerations and alternatives associated with constructing scalable graph processing technologies.
A distributed intrusion detection system for industrial automation networks

Modern automation is measured in terms of interoperability and easy administration. Introducing technology focussing on these criteria, however, induce new security risks to existing and future automation installations. Current security approaches in automation do not keep pace with the rising security challenges. Prevalent in automation is the use of access control to protect the system from malicious activity, such as extern attacks. Means to inspect the automation traffic to identify attacks that already have overcome access control or are initiated from inside the automation system are not available, yet. For filling this gap, we investigate in the application of intrusion detection techniques on industrial automation. In this paper, we present the current state of an intrusion detection system tailored to the analysis of operation down to traffic between automation devices on field layer.
Parents’ experiences in a home-based dialogic reading programme

ABSTRACT Research conducted over the past 30 years has demonstrated the effectiveness of dialogic reading in facilitating young children’s language development. The present study examined parents’ experiences in a dialogic reading programme with their preschooler aged 2–5 years. The study sample of 52 parent–child dyads was divided into two groups: a low-income/Head Start sample and a middle-income sample. The shared reading programme was associated with significant gains in children’s vocabulary. Main themes identified in parent interviews post-intervention included Positive Impressions of Programme, Liking Programme Structure, Liking When Child Showed Learning or Ability, Enjoying Time with Child, Finding Appropriate Time to Read, and within the low-income/Head Start sample, Challenges with Programme Execution. Parents in the middle-income sample were significantly more likely to indicate Positive Impressions of Programme compared to parents in the low-income/Head Start sample. Recommendations for bolstering interventions using dialogic reading are discussed.
Modelling Turkey's Energy Consumption Based on Artificial Neural Network

Energy plays a fundamental role in an economy. Turkey has the world's 15th largest GDP-Purchasing power parity and 17th largest Nominal GDP. Economists and political scientists classify Turkey as a newly industrialized country. In this study, an alternative model for Turkey’s energy consumption is proposed for the time between 1980 and 2004. Artificial neural network based model (ANN) is preferred as a forecasting tool. Gross domestic product (GDP), which is based on purchasing power parity, industrial production index and total population are utilized in the model. It is found that the energy consumption has direct relations with the Industrial Production Index. Moreover, population and GDP has causality effects.
Strategic Decisions in the Transition to Deregulated Markets

Liberalisation of markets is supposed to be an adequate procedure to satisfy the worldwide demand for innovations. However, the transition from regulated markets to competition is a disequilibrium phenomenon and requires specific consideration of the appearing dynamics. We present in this paper a simple, yet general, model which is instrumental in understanding the likely market evolution during a liberalisation process. Furthermore, the developed System Dynamics-based model provides the possibility to simulate strategic decision-making in out-of-equilibrium markets caused by deregulation. The impacts on firm and market performance of a price-maker strategy, enabled through process innovation, on the one hand and a differentiation strategy on the other hand are discussed in details. The model is adapted to a goods market, albeit the presented implications have much wider use.
Estimating At-Sea Mortality of Marine Turtles from Stranding Frequencies and Drifter Experiments

Strandings of marine megafauna can provide valuable information on cause of death at sea. However, as stranding probabilities are usually very low and highly variable in space and time, interpreting the results can be challenging. We evaluated the magnitude and distribution of at-sea mortality of marine turtles along the Pacific coast of Baja California Sur, México during 2010–11, using a combination of counting stranded animals and drifter experiments. A total of 594 carcasses were found during the study period, with loggerhead (62%) and green turtles (31%) being the most common species. 87% of the strandings occurred in the southern Gulf of Ulloa, a known hotspot of loggerhead distribution in the Eastern Pacific. While only 1.8% of the deaths could be definitively attributed to bycatch (net marks, hooks), seasonal variation in stranding frequencies closely corresponded to the main fishing seasons. Estimated stranding probabilities from drifter experiments varied among sites and trials (0.05–0.8), implying that only a fraction of dead sea turtles can be observed at beaches. Total mortality estimates for 15-day periods around the floater trials were highest for PSL, a beach in the southern Gulf of Ulloa, ranging between 11 sea turtles in October 2011 to 107 in August 2010. Loggerhead turtles were the most numerous, followed by green and olive ridley turtles. Our study showed that drifter trials combined with beach monitoring can provide estimates for death at sea to measure the impact of small-scale fisheries that are notoriously difficult to monitor for by-catch. We also provided recommendations to improve the precision of the mortality estimates for future studies and highlight the importance of estimating impacts of small–scale fisheries on marine megafauna.
Insights from Network Structure for Text Mining

Text mining and data harvesting algorithms have become popular in the computational linguistics community. They employ patterns that specify the kind of information to be harvested, and usually bootstrap either the pattern learning or the term harvesting process (or both) in a recursive cycle, using data learned in one step to generate more seeds for the next. They therefore treat the source text corpus as a network, in which words are the nodes and relations linking them are the edges. The results of computational network analysis, especially from the world wide web, are thus applicable. Surprisingly, these results have not yet been broadly introduced into the computational linguistics community. In this paper we show how various results apply to text mining, how they explain some previously observed phenomena, and how they can be helpful for computational linguistics applications.
Complex fuzzy sets: towards new foundations

Uncertainty of complex-valued physical quantities z=x+y can be described by complex fuzzy sets. Such sets can be described by membership functions /spl mu/(x, y) which map the universe of discourse (complex plane) into the interval [0, 1]. The problem with this description is that it is difficult to directly translate into words from natural language. To make this translation easier, several authors have proposed to use, instead of a single membership function for describing the complex number, several membership functions which describe different real-valued characteristics of this number, such as its real part, its imaginary part, its absolute value, etc. The quality of this new description strongly depends on the choice of these real-valued functions, so it is important to choose them optimally. We formulate the problem of optimal choice of these functions and show that, for all reasonable optimality criteria, the level sets of optimal functions are straight lines and circles. This theoretical result is in good accordance with our numerical experiments, according to which such functions indeed lead to a good description of complex fuzzy sets.
Vitamin D receptor polymorphisms or serum levels as key drivers of breast cancer development? The question of the vitamin D pathway

As total vitamin D levels are often lower in black than in white Americans, the former are frequently classified as vitamin D-deficient. To fully understand African vitamin D (25(OH)D) status, other factors should be considered, e.g. vitamin D blood carrier, vitamin D-binding protein (DBP), vitamin D receptor (VDR) and DBP polymorphisms. A prospective study on an indigenous black Tanzanian and a Caucasian Italian population was performed on 50 healthy donors from both populations and 35 Caucasian and 18 African breast cancer patients. 25(OH)D and DBP serum levels were analyzed by ELISA. A1012G, Cdx2 and Fok1 VDR polymorphisms and DBP polymorphisms rs4588 and rs7041 were genotyped by real-time PCR. Vitamin D and DBP levels were lower in healthy African donors than in Caucasians. Africans had a significantly higher frequency of AA and CC for Cdx2 and Fok1 polymorphisms, respectively. These allelic variants were related to a higher transcription of VDR gene and a higher activity of VDR receptor. With regard to polymorphism distribution, Africans showed innate higher levels and activity of VDR. We conclude that a strengthening of the vitamin D pathway could have a protective role against the development of breast cancer in the African population.
Removable singularities for Yang–Mills connections in higher dimensions

We prove several removable singularity theorems for singular Yang-Mills connections on bundles over Riemannian manifolds of dimensions greater than four. We obtain the local and global removability of singularities for Yang-Mills connections with L∞ or L n/2 bounds on their curvature tensors, with weaker assumptions in the L°° case and stronger assumptions in the L n/2 case. With the global gauge construction methods we developed, we also obtain a 'stability' result which asserts that the existence of a connection with uniformly small curvature tensor implies that the underlying bundle must be isomorphic to a flat bundle.
INTERACTIVE SONIFICATION OF COLLABORATIVE AR-BASED PLANNING TASKS FOR ENHANCING JOINT ATTENTION

This paper introduces a novel sonification-based interaction support for cooperating users in an Augmented Reality setting. When using head-mounted AR displays, the field of view is limited which causes users to miss important activities such as object interactions or deictic references of their interaction partner to (re-)establish joint attention. We introduce an interactive sonification which makes object manipulations of both interaction partners mutually transparent by sounds that convey information about the kind of activity, and can optionally even identify the object itself. In this paper we focus on the sonification method, interaction design and sound design, and we furthermore render the sonification both from sensor data (e.g. object tracking) and manual annotations. As a spin-off of our approach we propose this method further for the enhancement of interaction observation, data analysis, and multimodal annotation in interactional linguistics and conversation analysis.