Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling performance of a parallel streaming engine: bridging theory and costs

While data are growing at a speed never seen before, parallel computing is becoming more and more essential to process this massive volume of data in a timely manner. Therefore, recently, concurrent computations have been receiving increasing attention due to the widespread adoption of multi-core processors and the emerging advancements of cloud computing technology. The ubiquity of mobile devices, location services, and sensor pervasiveness are examples of new scenarios that have created the crucial need for building scalable computing platforms and parallel architectures to process vast amounts of generated streaming data. In practice, efficiently operating these systems is hard due to the intrinsic complexity of these architectures and the lack of a formal and in-depth knowledge of the performance models and the consequent system costs. The Actor Model theory has been presented as a mathematical model of con- current computation that had enormous success in practice and inspired a number of contemporary work in this area. Recently, the Storm system has been presented as a realization of the principles of the Actor Model theory in the context of the large scale processing of streaming data. In this paper, we present, to the best of our knowledge, the first set of models that formalize the performance characteristics of a practical distributed, parallel and fault-tolerant stream processing system that follows the Actor Model theory. In particular, we model the characteristics of the data flow, the data processing and the system management costs at a fine granularity within the different steps of executing a distributed stream processing job. Finally, we present an experimental validation of the described performance models using the Storm system.
Relations Between Time and Tape Complexities

It is shown that if a language <italic>L</italic> is recognized by a (nondeterministic) single-tape Turing machine of time complexity <italic>T</italic>(<italic>n</italic>), then <italic>L</italic> is recognized by a (nondeterministic) offline Turing machine of tape complexity <italic>T</italic><supscrpt>1/2</supscrpt>(<italic>n</italic>). If <italic>T</italic>(<italic>n</italic>) ≥ <italic>n</italic><supscrpt>2</supscrpt>;, <italic>L</italic> is recognized by a (nondeterministic) single-tape Turing machine of tape complexity <italic>T</italic><supscrpt>1/2</supscrpt>(<italic>n</italic>). If a language <italic>L</italic> is recognized by a (nondeterministic) offline Turing machine of time complexity (<italic>T</italic>(<italic>n</italic>), then <italic>L</italic> is recognized by a (nondeterministic) offline Turing machine of tape complexity (<italic>T</italic>(<italic>n</italic>) log <italic>n</italic>)<supscrpt>1/2</supscrpt> and by a (nondeterministic) single-tape Turing machine of that tape complexity if <italic>T</italic> (<italic>n</italic>) ≥ <italic>n</italic><supscrpt>2</supscrpt>/log <italic>n</italic>.
Coincidence based Mapping Extraction with Genetic Algorithms

Ontology Aligning is an answer to the problem of handling heterogenous information on different domains. After application of some measures, one reaches a set of similarity values. The final goal is to extract mappings. Our contribution is to introduce a new genetic algorithm (GA) based extraction method. The GA, employs a structured based weighting model, named “coincidence based model”, as its fitness function. In the first part of the paper, some preliminaries and notations are given and then we introduce the coincidence based weighting. In the second part the paper discusses the details of the devised GA with the evaluation results for
Per block pre-distortion of a multi-carrier non-linear satellite communication channel

In this paper, we propose a pre-distortion algorithm for a two carriers non-linear satellite communication channel. In the considered scenario, two linearly modulated carriers are amplified by the same non-linear power amplifier aboard the satellite. Due to the presence of the shaping filter at the transmitter side and the receiver filter (and possibly interference with filters aboard the satellite), the received signal is affected by non-linear intersymbol interference (ISI) but also non-linear adjacent channel interference (ACI). We consider the case where the two signals are transmitted from the same gateway, so that joint pre-distortion of the two signals is possible. Simulations for the 8PSK modulation show that the algorithm is able to greatly reduce the impact of the non-linear interference.
Link Completion using Prediction by Partial Matching

Prediction by partial matching (PPM) is typically used as a powerful method for data compression. Recently, PPM was applied to solve link prediction problem, e. g. , predictive prefetching on the Web. Link completion is a link analysis problem and is almost identical to link prediction but harder and more general. This research applies PPM to impute the missing links in single (directed) graph-structured data model with node and link labels. The experiments use the co-authorship dataset for case-study. Our proposed algorithm not only uses original PPM forward method but also PPM backward and hybrid methods. The algorithm can predict any missing position at any position of a given query link. The experimental results show the prediction accuracy in several dimensions depending on the testing data.
Transfer entropy between cortical and basal ganglia electrophysiology

Linear measures such as cross-correlation, coherence, and directed transfer functions have previously been applied to investigate the functional connectivity between brain regions. However, such methods do not account for nonlinear interactions between the signals. Separately, dopaminergic cell transplants have been shown to provide symptomatic amelioration and partial electrophysiological normalization of aberrant basal ganglia firing patterns in Parkinson's Disease. However, the precise extent and mechanisms of basal ganglia electrophysiological normalization have remained unclear. In this experiment we computed the transfer entropy between electroencephalograms (EEGs) and basal ganglia local field potentials (LFPs) from urethane-anesthetized rats, in order to investigate both linear and nonlinear interactions. We used the 6-hydroxy-dopamine lesioned medial forebrain bundle hemiparkinsonian (HP) rat model, and recorded from the substantia nigra and subthalamic nucleus of normal rats, HP rats, and HP rats with murine fetal ventral mesencephalic cell transplants, looking separately at slow wave EEG epochs versus global activation epochs. We found that both the crosscorrelation and the transfer entropy between the motor cortical EEG and basal ganglia LFPs was increased in the HP group (p<;0.05) and returned to normal levels in the grafted group, in most nuclei and conditions. However, the transfer entropy more robustly showed the difference between the groups. Our findings indicate that transfer entropy is a sensitive tool for nonlinear inter-nucleic functional connectivity analyses, and demonstrate the novel restorative ability of dopaminergic grafts for the parkinsonian basal ganglia electrophysiology.
Fp6-027026, K-space Id4.4.1: State of the Art Report on Multimedia Mining State of the Art Report on Multimedia Mining History Version Date Reason Revised By

Workpackage: WP4.4 Estimated Staff Months: Dissemination Level: CO Nature: R Approval Status: Pending Version: 13 Total Number of Pages: 61 Distribution List: Filename: KS_ID42_GU_2006-11-02_State-of-the-Art-Multimedia-Mining.doc Keyword list: Multimedia Mining, Multimedia Indexing, Machine Learning, Semantic Analysis, Clustering and Classification, Relevance Feedback, Latent. Abstract Multimedia mining is a nascent area of research. Due to accumulation of large amounts of data, methods for the analysis and exploration of data are needed. Compared to textual or other structured domain, the application of multimedia data mining is limited. In this document, we review prominent techniques used in multimedia mining.
Predicted Residual Error Sum of Squares of Mixed Models: An Application for Genomic Prediction

Genomic prediction is a statistical method to predict phenotypes of polygenic traits using high-throughput genomic data. Most diseases and behaviors in humans and animals are polygenic traits. The majority of agronomic traits in crops are also polygenic. Accurate prediction of these traits can help medical professionals diagnose acute diseases and breeders to increase food products, and therefore significantly contribute to human health and global food security. The best linear unbiased prediction (BLUP) is an important tool to analyze high-throughput genomic data for prediction. However, to judge the efficacy of the BLUP model with a particular set of predictors for a given trait, one has to provide an unbiased mechanism to evaluate the predictability. Cross-validation (CV) is an essential tool to achieve this goal, where a sample is partitioned into K parts of roughly equal size, one part is predicted using parameters estimated from the remaining K – 1 parts, and eventually every part is predicted using a sample excluding that part. Such a CV is called the K-fold CV. Unfortunately, CV presents a substantial increase in computational burden. We developed an alternative method, the HAT method, to replace CV. The new method corrects the estimated residual errors from the whole sample analysis using the leverage values of a hat matrix of the random effects to achieve the predicted residual errors. Properties of the HAT method were investigated using seven agronomic and 1000 metabolomic traits of an inbred rice population. Results showed that the HAT method is a very good approximation of the CV method. The method was also applied to 10 traits in 1495 hybrid rice with 1.6 million SNPs, and to human height of 6161 subjects with roughly 0.5 million SNPs of the Framingham heart study data. Predictabilities of the HAT and CV methods were all similar. The HAT method allows us to easily evaluate the predictabilities of genomic prediction for large numbers of traits in very large populations.
Journal of Theoretical and Applied Information Technology a Comparative Study of Distance Metrics Used in Face Recognition

Face recognition(FR) has become a specialized application area within the field of computer, among which the appearance-based approaches are popular. The appearance-based FR can be induced into the subspace projection step and a nearest neighbor classifier. Because face image data have the property of high dimension, the subspace projection methods should be employed for dimensionality reduction. They include Principal component analysis (PCA), Linear discriminant analysis (LDA), Independent component analysis (ICA) and Non-negative matrix factorization (NMF). In this paper, all the subspace projection algorithms are explored and face recognition system based on the four techniques presented. The simulation experiments are implemented with ORL face dataset, the results presented and analyzed. Also the four techniques are compared in recognition performance for FR.
Frames of Mind

It is not unusual that a photographer must whittle down a large set of hundreds (or more! ) of photographs to a more concise and interesting subset before publishing or sharing the set. Such a selection process can be repetitive and boring within a photographer's workflow, since it might devolve into a decision process that feels arbitrary in the case of distinguishing between two relatively similar photos.
An R package to analyse LC/MS metabolomic data: MAIT (Metabolite Automatic Identification Toolkit)

Summary: Current tools for liquid chromatography and mass spectrometry for metabolomic data cover a limited number of processing steps, whereas online tools are hard to use in a programmable fashion. This article introduces the Metabolite Automatic Identification Toolkit (MAIT) package, which makes it possible for users to perform metabolomic end-to-end liquid chromatography and mass spectrometry data analysis. MAIT is focused on improving the peak annotation stage and provides essential tools to validate statistical analysis results. MAIT generates output files with the statistical results, peak annotation and metabolite identification. Availability and implementation: http://b2slab.upc.edu/software-and-downloads/metabolite-automatic-identification-toolkit/. Contact: francesc.fernandez. albert@upc.edu Supplementary information: Supplementary data are available at Bioinformatics online
The hypocretin/orexin system in sleep disorders: preclinical insights and clinical progress

Much of the understanding of the hypocretin/orexin (HCRT/OX) system in sleep–wake regulation came from narcolepsy–cataplexy research. The neuropeptides hypocretin-1 and -2/orexin-A and -B (HCRT-1 and -2/OX-A and -B, respectively), as we know, are intimately involved in the regulation wakefulness. The HCRT/OX system regulates sleep–wake control through complex interactions between monoaminergic/cholinergic (wake-promoting) and gamma-aminobutyric acid-ergic (sleep-promoting) neuronal systems. Deficiency of HCRT/OX results in loss of sleep–wake control or stability with consequent unstable transitions between wakefulness to nonrapid eye movement and rapid eye movement sleep. This manifests clinically as abnormal daytime sleepiness with sleep attacks and cataplexy. Research on the development of HCRT/OX agonists and antagonists for the treatment of sleep disorders has dramatically increased with the US Food and Drug Administration approval of the first-in-class dual HCRT/OX receptor antagonist for the treatment of insomnia. This review focuses on the origin, mechanisms of HCRT/OX receptors, clinical progress, and applications for the treatment of sleep disorders.
Proceedings of ICSP ’ 96

FO contours tend to decline over the course of a major intonation phrase’ (MaIP). These FO downtrends form an envelope decomposed of a baseline and a top-line ( Pierrhumbert 1980, Maeda 1976,Cohen and t’Hart 1967). The baseline declination is a non -uniform function. That is, the slope of its angle is greater at the lower level constituents boundaries of the prosodic structure, e.g. at the edge of Noun Phrase that forms a prosodic boundary, i.e. at the edge of a minor intonation phrase(Mi1P); while its gradient is smaller for the rest of the utterance. The top-line, on the other hand, has a steplike reduction per peak. This compresses the pitch range much greater than the baseline. Application of the downstep rules can result in high quality synthetic speech.
Algorithms for Node Clustering in Wireless Sensor Networks: A Survey

The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) have led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes and organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. In this paper we provide a comprehensive analysis of clustering algorithms available for WSN and classify them based on the cluster formation parameters and cluster head (CH) election criteria. We further study the key design challenges and discuss the performance issues related clustering algorithms.
Functional Analysis of Genes Differentially Expressed in the Drosophila Wing Disc: Role of Transcripts Enriched in the Wing Region

Differential gene expression is the major mechanism underlying the development of specific body regions. Here we assessed the role of genes differentially expressed in the Drosophila wing imaginal disc, which gives rise to two distinct adult structures: the body wall and the wing. Reverse genetics was used to test the function of uncharacterized genes first identified in a microarray screen as having high levels of expression in the presumptive wing. Such genes could participate in elaborating the specific morphological characteristics of the wing. The activity of the genes was modulated using misexpression and RNAi-mediated silencing. Misexpression of eight of nine genes tested caused phenotypes. Of 12 genes tested, 10 showed effective silencing with RNAi transgenes, but only 3 of these had resulting phenotypes. The wing phenotypes resulting from RNAi suggest that CG8780 is involved in patterning the veins in the proximal region of the wing blade and that CG17278 and CG30069 are required for adhesion of wing surfaces. Venation and apposition of the wing surfaces are processes specific to wing development providing a correlation between the expression and function of these genes. The results show that a combination of expression profiling and tissue-specific gene silencing has the potential to identify new genes involved in wing development and hence to contribute to our understanding of this process. However, there are both technical and biological limitations to this approach, including the efficacy of RNAi and the role that gene redundancy may play in masking phenotypes.
Useful Dimensions of Haptic Perception: 50 Years After The Senses Considered as Perceptual Systems

ABSTRACT In addressing the character of the haptic system, James Gibson (1966) noted, “The study of useful sensitivity, as distinguished from theoretically basic sensitivities, is only just beginning” (p. 116). Whereas the preceding 150 years had gotten mired in an inventory of isolated sensations, the ensuing 50 years have revealed a good deal about the capabilities of a perceptual system that detects information about the self, the environment, and self-environment relations by means of muscular effort. That research is summarized with special attention to the kind of medium that could ground the useful dimensions of haptic sensitivity.
Biological Learning and Control: Shadmehr and Mussa-ivaldi 3. the Space Inside

In the previous two chapters we have considered how the brain forms maps of the environment as the body moves in it. Now and in the following chapters, we will discuss how the brain forms maps of the body in relation to the external world. As we move and act on the environment, our brain is like a crane operator that must act on a myriad of levers for commanding the motions of the limbs. Even the simplest actions, like reaching for a glass of water, require the coordinated control of about 35 arm and hand muscles. These muscles are divided in smaller compartments, each compartment operated by single motor neuron. In the end there are thousands of little levers that our body-crane operator must act upon successfully for conducting the simple gestures. The body-crane operator receives information about the state of motion of each limb, and about the forces applied by the muscles. There are two geometries for this scenario: the geometry of the body (of its motors and sensors), and the geometry of the world outside. We already encountered this duality in the navigation problem, where the geometry of the images projected on the eyes is different from the geometry of the surrounding space. Here, as well as in the navigation, what matters is that the two geometries are mutually connected. Consider the situation depicted in Fig. 3.1A. It describes an experiment carried out by Pietro Morasso (1981) while he was visiting the laboratory of Emilio Bizzi at MIT. The sketch is the top view of a subject holding the handle of a planar mechanism that was designed by Neville Hogan to study the reaching movements of the hand. We can describe the subject's geometry in two alternative ways. We can focus on his hand or we can focus on his arm. In the first case, the position of the hand on the plane is determined by the two coordinates (,) xy, of its center, taken with respect to a Cartesian system. An alternative way (not the only one) is to look at the two joint angles, the shoulder angle,  , and the elbow angle . These different points of view are related to the different perspective that one may have. Traditional motor physiologists, before Morasso's time, focused on the movements of individual body segments. And, most often, of one body segment at a time, for example …
Understanding Participation Behavior and Status Attainment of Open Source Software Developers - a Latent Class Growth Modeling Approach

The success of open source software (OSS) projects heavily depends on voluntary participation by a large number of developers. Developers new to an OSS community must participate by engaging in community interactions before they are qualified by the community as core developers. This exploratory study examines new peripheral developers’ temporal participation behavior and its impacts on the time taken to attain core developer status. Using the novel latent class growth modeling approach on 133 peripheral developers across 40 OSS projects, we found that these peripheral developers differed in the initial levels and growth trajectories of participation, and distinct classes of participation behavior were identified. We also found that different classes of developers differ in their time taken to attain core developer status. Implications to research and practice are discussed.
CoLe and UTAI at BioASQ 2015: Experiments with Similarity Based Descriptor Assignment

In this paper we describe our participation in the third edition of the BioASQ biomedical semantic indexing challenge. Unlike our participation in previous editions, we have chosen to follow an approach based solely on conventional information retrieval tools. We have evaluated various alternatives for creating textual representations of MEDLINE articles to be stored in an Apache Lucene textual index. Those indexed representations are queried using the contents of the article to be annotated and a ranked list of candidate descriptors is created from the retrieved similar articles. Several strategies to post-process those lists of candidate descriptors were evaluated. Performance in the official runs were far from the most competitive systems, but taking into account that our approach in the performed runs did not employ any external knowledge sources, we think that the proposed method could benefit from richer representations for MEDLINE contents.
Disclosure on corporate and NGO cooperation in Poland – coming out or a low profile approach?

The first aim of the paper is to answer the question regarding the scope of the information on philanthropic cooperation revealed by corporations and charitable organizations in a transition country. We explore the findings from the content analysis of disclosures of 41 corporations and 82 foundations. The results showed that the scope of disclosure on corporate and NGO collaborations is small on both sides. The second objective of the paper is to explore the reasons of the small scope of disclosure on corporations' and NGOs' collaborations. In order to achieve the second aim, we extended our analysis through interviews with CSR managers and directors of foundations. Firstly, some managers adopt the stance that when there is no legal requirements or even voluntary guidelines (like GRI Guidelines), no further disclosure on collaboration is necessary. Moreover, the managers of corporations tend to follow the materiality rule in voluntary disclosure and reveal information only in projects with the biggest budgets and/or major social impact. NGOs do not see the benefits for them in publishing detailed information about their collaboration with companies.