Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing k-Inflated Poisson-Binomial Distributed Longitudinal Data in Consumer Behavior

The first step in process mining of a business is to collect data on the process that is being analyzed. Sometimes the response variable in a longitudinal study of customers is a count variable. It may seem that the effect of some covariates related to the consumer can be modeled on the desired success probability via a binomial regression. However, the count variable may have inflation at the value k, and may also arise as the sum of consecutive Bernoulli variables with different success probabilities. In this paper, we will account for these features using a longitudinal (mixed effects) k-inflated Poisson-Binomial model. We demonstrate the utility of the introduced model by fitting it to a simulated data set related to the customers of a supermarket.
Smart DCU Digital Twin: Towards Smarter Universities

Although both smart city and digital twin are ambiguous and contested terms, there exists a co-creative link between the two. Theoretically, digital twin seems to be a sustainable digital solution for smart cities to achieve ideal city vision by digitization of physical urban spaces. This study investigates and informs the role, benefits and challenges in developing and deploying digital twin solution for efficient decision-making in infrastructure planning and management. This technology is experimented in a 3D cyberspace of Dublin City University, which is also one of the testbeds under the broader Smart Dublin umbrella. It is an ongoing project and expects to develop effective use-cases for monitoring present situations, multi-stakeholder collaboration and action research towards a responsive and adaptive campus environment.
Optimal Monetary and Fiscal Policies In a Search-theoretic Model of Money and Unemployment ∗

In this paper we study the optimal monetary and fiscal policies of a general equilibrium model of unemployment and money with search frictions both in labor and goods markets as in Berentsen, Menzio and Wright (2010). We abstract from revenue-raising motives to focus on the welfare-enhancing properties of optimal policies. We show that some of the inefficiencies in the Berentsen, Menzio and Wright (2010) framework can be restored with appropriate fiscal policies. In particular, when lump sum monetary transfers are possible, a production subsidy financed by money printing can increase output in the decentralized market and a vacancy subsidy financed by a dividend tax even when the Hosios’ rule does not hold. JEL Classification: E52, E63.
Iris Center Localization Using Energy Map With Image Inpaint Technology and Post-Processing Correction

Iris center localization is the basis of iris biometrics, face recognition and gaze tracking. However, individual differences, changes in facial expression, varying light conditions, occlusion, and so on, all bring great challenges to accurately localize the iris center. In order to improve localization accuracy in low-quality images and meet the need of efficiency in practical applications, a novel method of iris center localization is proposed in this paper using energy map synthesis based on image gradient, image inpaint technology, and post-processing correction. The image inpaint technology is firstly adopted to inhibit the effect of some specular reflection. Then the energy maps based on image gradient and eye ROI (Region Of Interest) midpoint are synthesized to significantly improve the localization accuracy. In the end, post-processing correction is carried out to eliminate influence of the closed eye and other large derivations to further improve the localization accuracy. The algorithm is verified on the challenging BioID database, Talking Face Video database and the MUCT face database. The result shows the localization accuracy has outperformed the state-of-the-art unsupervised methods on the three databases, and it is suitable for real-time applications.
Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design

Bayesian optimization (BO) is a powerful framework to optimize black box expensive-to-evaluate functions via sequential interactions. In several important problems (e.g. drug discovery, circuit design, neural architecture search, etc.), though, such functions are defined over combinatorial and unstructured spaces. This makes existing BO algorithms not feasible due to the intractable maximization of the acquisition function to find informative evaluation points. To address this issue, we propose GameOpt , a novel game-theoretical approach to combinatorial BO. GameOpt establishes a cooperative game between the different optimization variables and computes informative points to be game equilibria of the acquisition function. These are stable configurations from which no variable has an incentive to deviate – analog to local optima in continuous domains. Crucially, this allows us to efficiently break down the complexity of the combinatorial domain into individual decision sets, making GameOpt scalable to large combinatorial spaces. We demonstrate the application of GameOpt to the challenging protein design problem and validate its performance on two real-world protein datasets. Each protein can take up to 20 X possible configurations, where X is the length of a protein, making standard BO methods unusable. Instead, our approach iteratively selects informative protein configurations and very quickly discovers highly active protein variants compared to other baselines.
Spatial variation of CDOM and its influencing factors in tropical East Indian Ocean during summer

The colored dissolved organic matter, abbreviated as CDOM, is an important ingredient that affects the light absorption characteristics of seawater, and one of the key elements for ocean color research. In the case of only few focus on temporal and spatial variation of CDOM in tropical East Indian Ocean, this paper analyzes the CDOM spectral characteristics of this area based on the optical data of the summer survey in Southeast Indian Ocean in 2016, the variation and the related factors affecting the CDOM absorption characteristics of this area by using MODIS/ VIIRS satellite remote sensing data. The results shows that 1) the CDOM absorption spectrum meets quasi-exponential decay characteristics, and the surface ag(440) changes from 0.002 to 0.098 m-1, which is smaller than that of inshore water is larger than that of Southeast Pacific Ocean; 2) ag(440) in 8°S is significantly greater than 5°S, and the maximum appears in the southwest of the observation area (88°E, 8°S); 3) above the shallow depth of 100m, ag(440) tends to increase with depth; 4) the distribution of surface CDOM absorption coefficient shows significant consistency with chlorophyll concentration (r=0.8495), while not related to sea surface temperature (r=0.0064). CDOM and chlorophyll have similar driving mechanisms in the research area. The spatial distribution of CDOM is influenced by the subaqueous equatorial currents, the low-temperature waters from the Southern Ocean, and short-term small-scale effects, while the profile distribution is related to light field and nutrients. This study provides a further reference for understanding the optical properties of tropical waters in the East Indian Ocean.
Hawksford Learning an Overcomplete Dictionary using a Cauchy Mixture Model for Sparse Decay

An algorithm for learning an overcomplete dictionary using a Cauchy mixture model for sparse decomposition of an underdetermined mixing system is introduced. The mixture density function is derived from a ratio sample of the observed mixture signals where 1) there are at least two but not necessarily more mixture signals observed, 2) the source signals are statistically independent and 3) the sources are sparse. The basis vectors of the dictionary are learned via the optimization of the location parameters of the Cauchy mixture components, which is shown to be more accurate and robust than the conventional data mining methods usually employed for this task. Using a well known sparse decomposition algorithm, we extract three speech signals from two mixtures based on the estimated dictionary. Further tests with additive Gaussian noise are used to demonstrate the proposed algorithm’s robustness to outliers. Keywords—expectation-maximization, Pitman estimator, sparse decomposition
Similitud funcional de genes basada en conocimiento biológico

Over the last few year, our knowledge about biological processes in living organisms has greatly expanded both in quantity and resolution, mostly thanks to the introduction of high-throughput sequencing technology. Making sense of these vast amount of biological data through methods such as automated learning is therefore critical to gain further insights into the molecular mechanisms behind fundamental biological processes. This work aims at establishing the quality of new genetic model based on actual biological data. First, a tool for analyzing the coherence of a group of genes according to their common role in metabolic processes is developed. This tool allows the evaluation and validation of different gene sets obtained through any clustering technique. Additionally, a novel measure of functional similarity of a group of genes has been introduced. This measure, called GFD, is based on the Gene Ontology, and it assigns a numerical value to a gene set for each of the three GO ontologies. Concretely, GFD computes the similarity based only on the most common and specific functionality of the genes. GFD compre favorably against the most relevant measures. Our approach is especially relevant in the study of genes that are involved in several functions.
Seed-Growing Heart Segmentation in Human Angiograms

In this paper an image segmentation scheme that is based on combinations of a non–parametric technique and a seed based clustering algorithm is reported. The method has been applied to clinical unsubtracted angiograms of the human heart. The first step of the method consists in applying a mean shift–based filter in order to improve the left ventricle cavity information in angiographic images. Second, the initial seed is semi– automatically generated from the aortic valve manual localization by a specialist. Third, each angiographic image is segmented using a clustering algorithm that begins with the seed which is grown until image pixels associated to the left ventricle cavity are clustered. A validation is performed by comparing the estimated contours with respect to contours manually traced by a cardiologists. From this validation stage the maximum of the average contour error considering six angiographic sequences (a total of 178 images) is 7.30 %.
Fuzzy Ideas Explain Fechner Law and Help Detect Relation Between Objects in Video

—How to find relation between objects in a video? If two objects are closely related – e.g., a computer and it mouse – then they almost always appear together, and thus, their numbers of occurrences are close. However, simply computing the differences between numbers of occurrences is not a good idea: objects with 100 and 110 occurrences are most probably related, but objects with 1 and 5 occurrences probably not, although 5 − 1 is smaller than 110 − 100 . A natural idea is, instead, to compute the difference between re-scaled numbers of occurrences, for an appropriate nonlinear re-scaling. In this paper, we show that fuzzy ideas lead to the selection of logarithmic re-scaling, which indeed works very well in video analysis – and which also explains Fechner Law in psychology, that our perception of difference between two stimuli is determined by the difference between the logarithms of their intensities.
An Improved Sphere-Packing Bound Targeting Codes of Short to Moderate Block Lengths and Applications

This paper derives an improved sphere-packing (ISP) bound targeting codes of short to moderate block lengths. We first review classical results, i.e., the 1959 sphere-packing (SP59) bound of Shannon for the Gaussian channel, and the 1967 sphere-packing (SP67) bound for discrete memoryless channels. A recent improvement on the SP67 bound, as suggested by Valembois and Fossorier, is also discussed. These concepts are used for the derivation of a new bound (referred to as the ISP bound) which is uniformly tighter than the SP67 bound and its recent improved version. Under a mild condition, the ISP bound is applicable to general memoryless channels, and some of its applications are exemplified. Its tightness is studied by comparing it with bounds on the ML decoding error probability, and computer simulations of iteratively decoded turbo-like codes. The paper also presents a technique which performs the entire calculation of the SP59 bound in the logarithmic domain, thus facilitating the exact calculation of the SP59 bound for moderate to large block lengths without the need for asymptotic approximations. It is shown that the ISP bound suggests an interesting alternative to the SP59 bound, especially for digital modulations of high spectral efficiency.
Behavioral and Brain Functions Response Variability in Attention-deficit/hyperactivity Disorder: a Neuronal and Glial Energetics Hypothesis

1. Abstract Background: Current concepts of Attention-Deficit/Hyperactivity Disorder (ADHD) emphasize the role of higher-order cognitive functions and reinforcement processes attributed to structural and biochemical anomalies in cortical and limbic neural networks innervated by the monoamines, dopamine, noradrenaline and serotonin. However, these explanations do not account for the ubiquitous findings in ADHD of intra-individual performance variability, particularly on tasks that require continual responses to rapid, externally-paced stimuli. Nor do they consider attention as a temporal process dependent upon a continuous energy supply for efficient and consistent function. A consideration of this feature of intra-individual response variability, which is not unique to ADHD but is also found in other disorders, leads to a new perspective on the causes and potential remedies of specific aspects of ADHD.
Dirlik and Spectral Methods in Vibration Fatigue: A Review with a Historical Perspective

: The frequency domain techniques (also known as “spectral methods”) prove significantly more efficient than the time domain fatigue life calculations, especially when they are used in con ‐ junction with finite element analysis. Frequency domain methods are now well established, and suitable commercial software is commonly available. Among the existing techniques, the methods by Dirlik and by Tovo–Benasciutti (TB) have become the most used. This study presents the histor ‐ ical background and the motivation behind the development of these two spectral methods, by also emphasizing their application and possible limitations. It further presents a brief review of the other spectral methods available for cycle counting directly from the power spectral density of the random loading. Finally, some ideas for future work are suggested.
An Optimal Algorithm for Online Non-Convex Learning

In many online learning paradigms, convexity plays a central role in the derivation and analysis of online learning algorithms. The results, however, fail to be extended to the non-convex settings, which are necessitated by tons of recent applications. The Online Non-Convex Learning problem generalizes the classic Online Convex Optimization framework by relaxing the convexity assumption on the cost function (to a Lipschitz continuous function) and the decision set. The state-of-the-art result for ønco demonstrates that the classic Hedge algorithm attains a sublinear regret of O(√T log T). The regret lower bound for øco, however, is Omega(√T), and to the best of our knowledge, there is no result in the context of the ønco problem achieving the same bound. This paper proposes the Online Recursive Weighting algorithm with regret of O(√T), matching the tight regret lower bound for the øco problem, and fills the regret gap between the state-of-the-art results in the online convex and non-convex optimization problems.
Prediction of human protein function according to Gene Ontology categories

MOTIVATION The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence. RESULTS We have developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors can all be predicted. Although the method relies on protein sequences as the sole input, it does not rely on sequence similarity, but instead on sequence derived protein features such as predicted post translational modifications (PTMs), protein sorting signals and physical/chemical properties calculated from the amino acid composition. This allows for prediction of the function for orphan proteins where no homologs can be found. Using this method we propose two novel receptors in the human genome, and further demonstrate chromosomal clustering of related proteins.
Concept and Design of the BioBiped1 Robot for Human-like Walking and Running

Biomechanics research shows that the ability of the human locomotor system depends on the functionality of a highly compliant motor system that enables a variety of different motions (such as walking and running) and control paradigms (such as flexible combination of feedforward and feedback controls strategies) and reliance on stabilizing properties of compliant gaits. As a new approach of transferring this knowledge into a humanoid robot, the design and implementation of the first of a planned series of biologically inspired, compliant, and musculoskeletal robots is presented in this paper. Its three-segmented legs are actuated by compliant mono- and biarticular structures, which mimic the main nine human leg muscle groups, by applying series elastic actuation consisting of cables and springs in combination with electrical actuators. By means of this platform, we aim to transfer versatile human locomotion abilities, namely running and later on walking, into one humanoid robot design. First experimental results for passive rebound, as well as push-off with active knee and ankle joints, and synchronous and alternate hopping are described and discussed. BioBiped1 will serve for further evaluation of the validity of biomechanical concepts for humanoid locomotion.
Sustainable Energy, Grids and Networks

This article proposes an open-source testbed to simulate interaction models governing the exchange of flexibility services located within a distribution network. The testbed is an agent-based system in which the distribution system operator, the transmission system operator, producers and retailers make their decisionsbasedonmixed-integerlinearprograms.Thistestbedhelpstohighlightthecharacteristicsofan interaction model, the benefits for the agents and eases the detection of unwanted or abusive behaviors which decreases the welfare. The testbed is implemented in Python and the optimization problems are encoded in the modeling language ZIMPL. A web interface is coupled with an instance generator using macroscopic parameters of the system such as the total power production. This testbed is, therefore, well suitedtotesttheimplementedinteractionmodelsonvariousscenariosandtoextendtheimplementation toothermodels.Fiveinteractionmodelsdevelopedwithindustrialpartnersaresimulatedoverayearona 75-bus test system. Simulations show that interaction models relying on active network management, as they have been developed, lead to substantial welfare even though they suffer from a lack of coordination between the DSO and the TSO. A conservative interaction model restricting grid users to an access range that is computed ahead of time to prevent any congestion, avoids shedding distributed generation but considerably restrains the amount of distributed production.
Atmospheric Chemistry and Physics the Role of Volatile Organic Compounds in the Polluted Urban Atmosphere of Bristol, England

The results of a field campaign carried out from early spring through to the late summer of 2000, in Bris-tol, England, are presented. Continuous measurements of over 40 hydrocarbons have been made at an urban background site, located at Bristol University, for approximately nine months using a Gas Chromatography – Flame Ionisation Detection (GC-FID) system and for a selection of halocar-bons for approximately one month using a Gas Chromatography – Electron Capture Detection (GC-ECD) system. In this paper we present the time-series of the nine halocar-bons and selected hydrocarbons. Daytime and night-time hy-droxyl radical concentrations have been estimated based on the diurnal variations of a selection of the measured hydrocarbons. The average summer daytime concentration of OH was found to be 2.5×10 6 molecules cm −3 and the night-time concentration to be in the range 10 4 to 10 5 molecules cm −3. In addition, the role played by certain VOCs in the formation of ozone is assessed using the POCP (Photochemical Ozone Creation Potential) concept.
FAUST Multiplatform toolbox for Body Brain Digital Musical Instruments

This article presents new tools developed in the FAUST language to create musical interactions using electrophysiological signals as input. The tools developed are centered around signal processing and simulation of electrophysiological signals. These techniques are used to clean and process biosignals and subsequently provide real-time interactions to feed the control of sonic processes. The system provides modules that are musically expressive especially in the domain of spatial sound. These tools also allow to set up a testing environment by replacing the need of electrophysiological capture devices. Thefindings of this research provide a better understanding of how the FAUST language can be used in conjunction with physiological signals and brings to light interesting opportunities to explore further possibilities in music creation in an open source environment with the possibility of multitarget compilation, allowing our modules to be used either in such softwares as Max[10] or embedded in microcontrollers.
Aeroacoustics research in Europe : The CEAS-ASC report on 2011 highlights

The Council of European Aerospace Societies (CEAS) Aeroacoustics Specialists Committee (ASC) supports and promotes the interests of the scientific and industrial aeroacoustics year the committee highlights some of the research and development projects in Europe. This paper is a report on highlights of aeroacoustics research in Europe in 2011, compiled from information provided to the ASC of the CEAS. During 2011, a number of research programmes involving aeroacoustics were funded by the European Commission. Some of the highlights from these programmes are summarized in this paper, as well as highlights from other programmes funded by national programmes or by industry. Furthermore, a concise summary of the CEAS-ASC workshop ‘‘Acoustic Liners and Associated Propagation Techniques’’ held in Lausanne in October 2011 is included in this report. Enquiries concerning all contributions should be addressed to the authors who are given at the end of each subsection. & 2012 Elsevier Ltd. All rights reserved.