Miracle-dz/UniFAR-FTUs huggingface dataset:
ASM + + charts : an intuitive circuit representation ranging from low level RTL to SoC design

This article presents a methodology to describe digital circuits from register transfer level to system level. When designing systems it encapsulates the functionality of several modules and also encapsulates the connections between those modules. To achieve these results, the possibilities of Algorithmic State Machines (ASM charts) have been extended to develop a compiler. Using this approach, a System-on-a-Chip (SoC) design becomes a set of linked boxes where several special boxes encapsulate the connections between modules. The compiler processes all required boxes and files, and then generates the corresponding HDL code, valid for simulation and synthesis. A small SoC example is shown.
An Optimal Algorithm for Large Frequency Moments Using O(n^(1-2/k)) Bits

In this paper, we provide the first optimal algorithm for the remaining open question from the seminal paper of Alon, Matias, and Szegedy: approximating large frequency moments. We give an upper bound on the space required to find a k-th frequency moment of O(n^(1-2/k)) bits that matches, up to a constant factor, the lower bound of Woodruff et. al for constant epsilon and constant k. Our algorithm makes a single pass over the stream and works for any constant k > 3. It is based upon two major technical accomplishments: first, we provide an optimal algorithm for finding the heavy elements in a stream; and second, we provide a technique using Martingale Sketches which gives an optimal reduction of the large frequency moment problem to the all heavy elements problem. We also provide a polylogarithmic improvement for frequency moments, frequency based functions, spatial data streams, and measuring independence of data sets.
Achieving elasticity for cloud MapReduce jobs

These days, both the cloud computing paradigm and MapReduce programming framework have become key enablers for running big data analytics and large-scale compute- and data-intensive applications. Achieving proper elasticity for cloud MapReduce jobs is a critical research problem that has been overlooked. In this paper, we focus on how to achieve proper elasticity for MapReduce jobs when executed on cloud clusters. In particular, we present an analytical queueing model that can be used to determine at any given time and under different workload conditions the minimal number of mappers and reducers needed to satisfy the Service Level Objective (SLO) response time.
A Survey of Image to Text Detection Methodology

The automatic detection of text within a natural image is an important problem in many applications. Text detection in natural images has gained much attention in the last years as it is a primary step towards fully autonomous text recognition. It needs to be fast, efficient and robust in order to feed an OCR classifier with the correct input. In other words, segmented regions must correspond to the actual text. A lot of work has been done for detecting text in images and a lot has to be done. This paper gives detailed survey on image to text detection mechanism. This paper gives the description of work done for automatically detection of text from images, localize and extract horizontally aligned text in images (and digital videos) with complex backgrounds.
Association among Complement Factor H Autoantibodies, Deletions of CFHR, and the Risk of Atypical Hemolytic Uremic Syndrome

To evaluate the association among complement factor H-related (CFHRs) gene deficiency, complement factor H (CFH) autoantibodies, and atypical hemolytic uremic syndrome (aHUS) susceptibility. EMBASE, PubMed, and the ISI Web of Science databases were searched for all eligible studies on the relationship among CFHRs deficiency, anti-FH autoantibodies, and aHUS risk. Eight case-control studies with 927 cases and 1182 controls were included in this study. CFHR1 deficiency was significantly associated with an increased risk of aHUS (odds ratio (OR) = 3.61, 95% confidence interval (95% CI), 1.96, 6.63, p < 0.001), while no association was demonstrated in individuals with only CFHR1/R3 deficiency (OR = 1.32, 95% CI, 0.50, 3.50, p = 0.56). Moreover, a more significant correlation was observed in people with both FH-anti autoantibodies and CFHR1 deficiency (OR = 11.75, 95% CI, 4.53, 30.44, p < 0.001) in contrast to those with only CFHR1 deficiency. In addition, the results were essentially consistent among subgroups stratified by study quality, ethnicity, and gene detection methods. The present meta-analysis indicated that CFHR1 deletion was significantly associated with the risk of aHUS, particularly when combined with anti-FH autoantibodies, indicating that potential interactions among CFHR1 deficiency and anti-FH autoantibodies might impact the risk of aHUS.
A threshold model for time varying copulas

We develop threshold models that allow copula functions or their association parameters changing across time. The number and location of thresholds is assumed unknown. We use a Markov chain Monte Carlo strategy combined with Laplace estimates that evaluate the required marginal densities for a given model. We apply our methodology to financial time series emphasizing the ability to improve estimates of risk characteristics, as well as measuring financial contagion by inspecting changing dependence structures.
Soy Consumption and Colorectal Cancer Risk in Humans: A Meta-Analysis

The purpose of the present study was to determine the relationship between soy consumption and colorectal cancer risk in humans by conducting a meta-analysis of available epidemiologic studies. We systematically reviewed publications obtained through a Medline literature search and identified four cohort and seven case-control studies on soy and colorectal cancer risk that met the inclusion criteria. We extracted the risk estimate (hazard ratio, relative risk, or odds ratio) of the highest and the lowest reported categories of intake from each study and conducted this analysis using a random-effects model. Our analysis did not find that soy consumption was associated with colorectal cancer risk [combined risk estimate, 0.90; 95% confidence interval (95% CI), 0.79-1.03] nor did the separate analyses on colon cancer (combined risk estimate, 0.88; 95% CI, 0.74-1.06) and rectal cancer (combined risk estimate, 0.88; 95% CI, 0.67-1.14). However, when separately analyzed on the basis of gender, we found that soy was associated with an approximately 21% reduction in colorectal cancer risk in women (combined risk estimate, 0.79; 95% CI, 0.65-0.97; P = 0.026), but not in men (combined risk estimate, 1.10; 95% CI, 0.90-1.33). Thus, consumption of soy foods may be associated with a reduction in colorectal cancer risk in women, but not in men. Cancer Epidemiol Biomarkers Prev; 19(1); 148–58
Identifying Skype nodes by NetFlow-based graph analysis

In this paper we present an algorithm that is able to progressively discover nodes of a Skype overlay P2P network. Starting from a single, known Skype node, we can easily identify other Skype nodes in the network, through the analysis of widely available and standardized IPFIX (NetFlow) data. Instead of relying on the analysis of content characteristics or packet properties, we monitor connections of known Skype nodes in the network and then progressively discover other nodes through the analysis of their mutual contacts. We show that our results are comparable to the methods using more complex data analytics. The use of standardized input data allows for easy deployment onto real networks. Moreover, because this approach requires only short processing times, it scales very well in larger and higher speed networks.
Interference Alignment at Intermediate SNR with Perfect or Noisy CSI

Interference alignment is a new technique combining transmitter precoding and receiver interference suppression to achieve the optimal multiplexing gain in interference networks by exploiting knowledge of channel state information of all transmission links. So far closed form solutions for the transmit filters have only been found in certain cases. Also the feasibility of interference alignment schemes based on symbol extensions, over a limited number of signalling dimensions, is still an open problem. In this work we investigate the performance in terms of bit error rates, of interference alignment schemes at intermediate signal-to-noise ratios, through Monte Carlo simulations. We focus our attention on the three and four users time-varying interference channel, using both the closed form solutions known at present as well as iterative algorithms. We then investigate the impact of noisy channel state information on the performances of some of the interference alignment systems considered. In the single input single output interference channel the closed form solutions of the interference alignment cause considerably different bit error rates for the different nodes in the network. In the multiple input multiple output interference channel we exhibit that bit error rate saturates at moderate signal-to-noise ratios when interference alignment schemes are infeasible and even when they are feasible, some of the analyzed algorithms show unpredictable behaviors by deteriorating the performance as the signal-to-noise ratio exceeds a threshold. Further re nements are necessary in order to obtain better bit error rates in these cases. We evince that additional improvements are also needed to the original interference alignment schemes in order to mitigate their sensitivity to noisy channel state information
New Methods of Data Clustering and Classification Based on NMF

Nonnegative matrix factorization method is a kind of new matrix decomposition method. It is an effective tool for large data processing and analysis. At the same time, NMF has an important performance on intelligent information processing and pattern recognition. This paper first analyses and discusses the NMF algorithms based on its basic theory. We then propose new methods of data clustering and classification based on NMF separately. NMF method is applied to reduce the dimension of the original matrix. We run clustering algorithms on the encoded matrix after NMF processing instead of on the original matrix. Running clustering algorithms on smaller encoded matrix can save more time and storage space. After that, we bring in a series of improvement methods of classification on the basis of clustering. Finally we have done experiments to test and verify them, and gotten good results.
System level evaluation of optical RAM circuits based on cross coupled SOAs and SOA-MZIs in the time and frequency domain

One of the key issues in Central Processing Unit (CPU) chips is the “Memory Wall” problem, where the clock frequency of RAM circuits cannot keep up in pace with the clock of the multiple cores. The current approach by chip architects to tackle this obstacle is to increase constantly the size of the cache memories on the dye in order to prevent the cores standing in idle state, while expecting data from the RAM circuit. However, this solution is totally inefficient considering that the dye area of the chip is very precious and could be used alternative for the integration of additional cores, transceivers etc. that would radically enhance the performance of current CPUs. A disruptive solution for data storage within the chip is the introduction of optics in the processor layout by embedding photonic RAM circuits operating at multiple tens of GHz frequencies that would unleash the processing performance of CPU cores at high clock rates. In this direction we present a system level tool for the calculation of maximum obtainable speed from optical RAM cell layouts comprising of three cross coupled switches based on Semiconductor Optical Amplifiers (SOAs) or SOA based Mach-Zehnder interferometers. The investigation is based on a qualitative frequency and a quantitative time domain analysis.
Reproductive Biology of a Grassland Songbird Community in Northcentral Montana

Abstract Successful conservation of grassland bird populations requires basic information on their breeding biology; in particular, information from undisturbed native prairie over an extended period of time. We present data collected at Bowdoin National Wildlife Refuge in northcentral Montana on the reproductive biology of six grassland bird species that breed in mixed-grass prairie: Sprague's Pipit (Anthus spragueii), Savannah (Passerculus sandwichensis), Grasshopper (Ammodramus savannarum), and Baird's (A. bairdii) sparrows, Chestnut-collared Longspur (Calcarius ornatus), and Western Meadowlark (Sturnella neglecta). Basic measures of reproductive biology are presented, including estimates of nest density, phenology, fecundity, parasitism rates, and nest success, and how these and other characteristics varied across years. Nests (n = 1,494) of the six focal species accounted for 98% of all passerine nests found during 1997–2007; Chestnut-collared Longspurs (51%) were the dominant breeding species. Total nest density across years ranged from 20 to 41 nests per 40 ha (CV = 26%) on unburned sites. Mean clutch initiation date and clutch size varied little across years; however, clutch size tended to decrease over the course of a season, regardless of bird species. Daily nest survival rates did not differ markedly among bird species, but did vary substantially among years, suggesting that year-dependent factors were affecting nest success among all species similarly.
The Physical Activity and Leisure Motivation Scale: A confirmatory study of the Malay language version

The aim of this study is to validate a Malay language version of the Physical Activity and Leisure Motivation Scale (PALMS) using a confirmatory approach. Data collection was conducted in Kelantan, Malaysia. Participants were 634 university undergraduate students (female 63%, male 37%), mean age of 21 years. Motivation for physical activity was assessed using the 40-item PALMS, which measures eight motives. PALMS was first translated into Malay using standard forward and backward translation procedures. Participants then completed the PALMS-Malay (PALMS-M). Confirmatory factor analysis (CFA) was conducted, using Mplus 7.3 software, on the 8-motive PALMS-M model. The hypothesised model consisted of 40 observed items, and 8 latent variables. Employing CFA, this model did not result in a good fit to the data. Further examination of CFA results suggested modifications to the path model to improve fit indices. This modification included deleting two problematic items (items 10 and 18) and co-varying the error terms for items 19 and 31. This resulted in improved fit indices (RMSEA = .041 (90% CI: .038, .044), CIfitRMSEA = 1.000, CFI = . 911, TLI = . 901, SRMR = . 052). The final measurement model consisted of 38 items. The majority of the items were retained and were considered acceptable for the present sample.
Distributed Estimation and Control of Algebraic Connectivity Over Random Graphs

In this paper, we propose a distributed algorithm for the estimation and control of the connectivity of ad-hoc networks in the presence of a random topology. First, given a generic random graph, we introduce a novel stochastic power iteration method that allows each node to estimate and track the algebraic connectivity of the underlying expected graph. Using results from stochastic approximation theory, we prove that the proposed method converges almost surely (a.s.) to the desired value of connectivity even in the presence of imperfect communication scenarios. The estimation strategy is then used as a basic tool to adapt the power transmitted by each node of a wireless network, in order to maximize the network connectivity in the presence of realistic medium access control (MAC) protocols or simply to drive the connectivity toward a desired target value. Numerical results corroborate our theoretical findings, thus illustrating the main features of the algorithm and its robustness to fluctuations of the network graph due to the presence of random link failures.
AUDITORY-VISUAL INTERACTIONS

Most displays or other devices designed to communicate information focus on a single sensory modality. This is perhaps a consequence of the fact that most research examining human perceptual capabilities has focused on a single sensory system at a time. However, most events in the natural environment generate physical information affecting multiple sensory modalities. This information is typically co-located in both space and time, and our perceptual systems have evolved to create a single coherent representation of our environment. Recent research has increasingly acknowledged the importance of these regularities, and the topic of multisensory integration became critical for understanding global awareness of the environment. This chapter presents an overview of the most recent research into the integration of auditory and visual information and presents considerations for the design of multisensory (i.e., auditory-visual) displays. The initial section of the chapter presents comparison of the basic features of the auditory and visual modalities and examines the effects of interacting visual and auditory stimuli. Included in this section is a discussion of the relative strengths and weaknesses of each modality and the situations in which one modality dominates. This section is followed by a discussion of perceptual effects when information from both modalities is complementary or conflicting and the role of multisensory attention on the perception of auditory-visual information. The final section of the chapter presents a discussion of the applications of auditory-visual integration principles to audio-visual display (e.g., helmet-mounted displays [HMDs]) and signal designs. Research on the interaction of a third modality, tactile or haptic displays, is just beginning and will not be discussed extensively here, although many of the same considerations can be expected to apply (see Chapter 18, Exploring the Tactile Modality for HMDs).
The Role of Mental Imagery in Understanding Unknown Idioms

In studies of the cognitive processing of idioms, the role of mental imagery in understanding idioms remains a controversial issue. Cacciari and Glucksberg (1995) conducted an experimental study to investigate whether generating mental images of idioms can facilitate their comprehension. Their results appeared to reject both the possible connection between the literal mental image of an idiom and the figurative meaning of the idiom, and the facilitatory effect of mental imagery on comprehension. Our study aims at exploring the facilitatory role of mental images in understanding unknown idioms. We used a paraphrase verification task for transparent and opaque unknown idioms translated from foreign languages into Bulgarian. The results demonstrate that literal mental images of transparent unknown idioms can facilitate their comprehension in terms of error scores in a simple paraphrase verification task. No facilitation effect for opaque unknown idioms was obtained. This points towards a link between the literal mental images of transparent idioms and their figurative meanings.
Consequences of Whole-Genome Triplication as Revealed by Comparative Genomic Analyses of the Wild Radish Raphanus raphanistrum and Three Other Brassicaceae Species[W][OPEN]

This work compares the genomes of four Brassicaceae species to examine the patterns of gene gains and losses following whole-genome duplication, finding that retained genes showed substantial divergence in sequence, expression, function, and network connectivity. This information was used to establish a statistical learning model for predicting whether a duplicate would be retained postpolyploidization. Polyploidization events are frequent among flowering plants, and the duplicate genes produced via such events contribute significantly to plant evolution. We sequenced the genome of wild radish (Raphanus raphanistrum), a Brassicaceae species that experienced a whole-genome triplication event prior to diverging from Brassica rapa. Despite substantial gene gains in these two species compared with Arabidopsis thaliana and Arabidopsis lyrata, ∼70% of the orthologous groups experienced gene losses in R. raphanistrum and B. rapa, with most of the losses occurring prior to their divergence. The retained duplicates show substantial divergence in sequence and expression. Based on comparison of A. thaliana and R. raphanistrum ortholog floral expression levels, retained radish duplicates diverged primarily via maintenance of ancestral expression level in one copy and reduction of expression level in others. In addition, retained duplicates differed significantly from genes that reverted to singleton state in function, sequence composition, expression patterns, network connectivity, and rates of evolution. Using these properties, we established a statistical learning model for predicting whether a duplicate would be retained postpolyploidization. Overall, our study provides new insights into the processes of plant duplicate loss, retention, and functional divergence and highlights the need for further understanding factors controlling duplicate gene fate.
Extracting the features of similarity in short texts

Automatic identification of text similarity has found applications in information retrieval, text summarization, assessment of machine translation, assessment of question answering, word sense disambiguation and many more. In this work, the results of discrimant analysis applied to find out the cumulative effect of the attributes used in the literature so far (ratio of common words, text lentgths, common word sequences, synonyms, hypernyms, hyponyms) in detecting word similarity are reported.
Internet Therapy versus Internet Self-help versus No Treatment for Problematic Alcohol Use: a Randomized Controlled Trial

Background : Problematic alcohol use is the number three leading contributor to global burden of disease, partly because the majority of problem drinkers is not receiving treatment. Internet-based alcohol interventions attract an otherwise untreated population, but its effectiveness has to be established yet. Objective The current study examined the effectiveness of internet-based therapy (Therapy Alcohol Online, TAO) and internet-based self-help (Self-help Alcohol Online, SAO) for problematic alcohol users. Method Adult problem drinkers (N = 205; 51% female; mean age = 42 years old; mean Alcohol Use Disorders Identification Test (AUDIT) score = 20) were randomly assigned to either TAO, SAO, or an untreated waiting list (WL). Participants in the TAO condition received 7 individual text-chat counseling sessions. Both TAO and SAO interventions were based on cognitive behavioral therapy (CBT) and motivational interviewing (MI) techniques. Assessments were planned at baseline, three months and six months after randomization. Primary outcome variables were 7-day time line-follow-back alcohol consumption (TLFB) and treatment response. Secondary outcome variables included measures on quality of life (i.e. EQ-5D). Results : Using generalized estimating equations regression models, intention-to-treat analyses demonstrated significant effects of TAO versus WL and SAO versus WL on TLFB drinking counts at three months. Differences between TAO and SAO were not significant at three months, but were after six months, with larger effects for TAO. Similar patterns of results emerged for treatment response and Quality of life outcome analyses. Conclusions : Results support the effectiveness of CBT/MI based internet therapy and internet self-help for problematic alcohol users. After six months, the internet therapy program led to more positive results than the internet self-help program. []