Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter-Free Audio Motif Discovery in Large Data Archives

The discovery of repeated structure, i.e. motifs/near-duplicates, is often the first step in exploratory data mining. As such, the last decade has seen extensive research efforts in motif discovery algorithms for text, DNA, time series, protein sequences, graphs, images, and video. Surprisingly, there has been less attention devoted to finding repeated patterns in audio sequences, in spite of their ubiquity in science and entertainment. While there is significant work for the special case of motifs in music, virtually all this work makes many assumptions about data (often to the point of being genre specific) and thus these algorithms do not generalize to audio sequences containing animal vocalizations, industrial processes, or a host of other domains that we may wish to explore. In this work we introduce a novel technique for finding audio motifs. Our method does not require any domain-specific tuning and is essentially parameter-free. We demonstrate our algorithm on very diverse domains, finding audio motifs in laboratory mice vocalizations, wild animal sounds, music, and human speech. Our experiments demonstrate that our ideas are effective in discovering objectively correct or subjectively plausible motifs. Moreover, we show our novel probabilistic early abandoning approach is efficient, being two to three orders of magnitude faster than brute-force search, and thus faster than real-time for most problems.
Cognitive Spectrum Sharing: An Enabling Wireless Communication Technology for a Wide Use of Smart Systems

A smart city is an environment where a pervasive, multi-service network is employed to provide citizens improved living conditions as well as better public safety and security. Advanced communication technologies are essential to achieve this goal. In particular, an efficient and reliable communication network plays a crucial role in providing continue, ubiquitous, and reliable interconnections among users, smart devices, and applications. As a consequence, wireless networking appears as the principal enabling communication technology despite the necessity to face severe challenges to satisfy the needs arising from a smart environment, such as explosive data volume, heterogeneous data traffic, and support of quality of service constraints. An interesting approach for meeting the growing data demand due to smart city applications is to adopt suitable methodologies to improve the usage of all potential spectrum resources. Towards this goal, a very promising solution is represented by the Cognitive Radio technology that enables context-aware capability in order to pursue an efficient use of the available communication resources according to the surrounding environment conditions. In this paper we provide a review of the characteristics, challenges, and solutions of a smart city communication architecture, based on the Cognitive Radio technology, by focusing on two new network paradigms—namely, Heterogeneous Network and Machines-to-Machines communications—that are of special interest to efficiently support smart city applications and services.
Almost sure convergence to consensus in Markovian random graphs

In this paper we discuss the consensus problem for a network of dynamic agents with undirected information flow and random switching topologies. The switching is determined by a Markov chain, each topology corresponding to a state of the Markov chain. We show that in order to achieve consensus almost surely and from any initial state the sets of graphs corresponding to the closed positive recurrent sets of the Markov chain must be jointly connected. The analysis relies on tools from matrix theory, Markovian jump linear systems theory and random processes theory. The distinctive feature of this work is addressing the consensus problem with ¿Markovian switching¿ topologies.
The Chronological Factor in Understanding the Middle and Upper Paleolithic of Eurasia

For more than half a century, prehistorians have grappled with radiocarbon-based chronologies that are often contradictory and imprecise. Several key debates in the Paleolithic have their roots, at least partially, in basic issues of chronology. When did Neanderthals disappear? When did Homo sapiens disperse across Eurasia? How long was the overlap among several hominin groups? Without reliable time control, these questions are unanswerable, and unravelling the Paleolithic remains a distant and virtually unachievable goal. It is only recently that the extent of the problems with the application of radiocarbon dating near the limit of the method has become understood. Major challenges have arisen, ranging from inadvisable and poor selection of samples, on the one hand, to the analytical, chemical, and instrumental challenges of dating the low amounts of residual radiocarbon in these samples, on the other. Recent work has led to significant developments in the field. In this paper, we briefly review some of these developments, drawing on recent work undertaken at two sites, Bondi Cave (Georgia) and Kostenki 14 (Russia). By comparing new radiocarbon determinations against previous results, it is possible to begin to quantify quite how erroneous some of the previous chronometric models were.
Classification of Hyperspectral Image with Feature Selection and Parameter Estimation

This paper presents a new method for hyperspectral image classification. It combines support vector machine (SVM), particle swarm optimization (PSO), and genetic algorithm (GA) together. Its aim is to improve the classification accuracy and reduce the computation consumption based on heuristic algorithms. Because the classification accuracy is impacted by the parameters of the SVM model and feature space in the training and testing steps. In order to optimize the parameters and feature subset, our proposed technique integrates the GA operators into PSO. The effectiveness of the proposed system is carried out on a real hyperspectral data set. Comparison for the classification performance with other reference classifiers is also reported. The obtained results clearly confirm the superiority of the proposed hybrid algorithm
Mobility Assisted Routing Strategy (MARS) for Hybrid Ad Hoc Networks

In this paper, node mobility is used to enhance the performance of route discovery in hybrid ad hoc networks. Some fast moving nodes (FNs) collect last encounter information while they are moving within the network. Whenever they encounter static nodes (SNs), they diffuse their last encounter information to SNs. According to the temporal-spatial correlation, both FNs and SNs can compute the distance with other nodes, therefore the last encounter information can guide route search. Inspired by such consideration, mobility assisted routing strategy (MARS) is developed for hybrid ad hoc networks. Plentiful simulations demonstrate that the route search cost is decreased significantly, and is linear with the distance between source and destination nodes. An analytical model for warm-up period of this protocol is proposed, which is coincident well with simulation results. Both simulation results and the analytical model show that the warm-up period is shortened greatly.
Bulk loading large collections of hyperlinked resources

The problem of loading large collections of hyperlinked resources into a relational database is complicated with inter-node references when these references cannot be indexed. We show that this scenario can arise in many real life hyperlinked resources and propose several solutions to address the problem. We run some experiments over a graph of the Web with 178 million nodes and around 1 billion edges and report our results.
Sprouty2-Mediated Inhibition of Fibroblast Growth Factor Signaling Is Modulated by the Protein Kinase DYRK1A

ABSTRACT Raf-MEK-extracellular signal-regulated kinase (Erk) signaling initiated by growth factor-engaged receptor tyrosine kinases (RTKs) is modulated by an intricate network of positive and negative feedback loops which determine the specificity and spatiotemporal characteristics of the intracellular signal. Well-known antagonists of RTK signaling are the Sprouty proteins. The activity of Sprouty proteins is modulated by phosphorylation. However, little is known about the kinases responsible for these posttranslational modifications. We identify DYRK1A as one of the protein kinases of Sprouty2. We show that DYRK1A interacts with and regulates the phosphorylation status of Sprouty2. Moreover, we identify Thr75 on Sprouty2 as a DYRK1A phosphorylation site in vitro and in vivo. This site is functional, since its mutation enhanced the repressive function of Sprouty2 on fibroblast growth factor (FGF)-induced Erk signaling. Further supporting the idea of a functional interaction, DYRK1A and Sprouty2 are present in protein complexes in mouse brain, where their expression overlaps in several structures. Moreover, both proteins copurify with the synaptic plasma membrane fraction of a crude synaptosomal preparation and colocalize in growth cones, pointing to a role in nerve terminals. Our results suggest, therefore, that DYRK1A positively regulates FGF-mitogen-activated protein kinase signaling by phosphorylation-dependent impairment of the inhibitory activity of Sprouty2.
Offshore wind power planning in Korea

Wind power generation is globally recognized as the most universal and reliable form of renewable energy. Korea is currently depending mostly on coal and petroleum to generate electrical power and is now trying to replace them with renewable energy such as offshore wind power generation. To make this possible, Korea has announced the National offshore power roadmap and is now in pursuit. However, large scale offshore wind farms can incur many problems, such as power quality problems, when connecting to a power system. [1][2] Thus, KEPCO is on the process of a research study to evaluate the effects that connecting offshore wind power generation to a power system has on the power system. This paper looks over offshore wind power planning in Korea and describes the development of impact assessment technology of offshore wind farms.
Gene Dosage–limiting Role of Aire in Thymic Expression, Clonal Deletion, and Organ-specific Autoimmunity

Inactivation of the autoimmune regulator (Aire) gene causes a rare recessive disorder, autoimmune polyendocrine syndrome 1 (APS1), but it is not known if Aire-dependent tolerance mechanisms are susceptible to the quantitative genetic changes thought to underlie more common autoimmune diseases. In mice with a targeted mutation, complete loss of Aire abolished expression of an insulin promoter transgene in thymic epithelium, but had no effect in pancreatic islets or the testes. Loss of one copy of Aire diminished thymic expression of the endogenous insulin gene and the transgene, resulting in a 300% increase in islet-reactive CD4 T cells escaping thymic deletion in T cell receptor transgenic mice, and dramatically increased progression to diabetes. Thymic deletion induced by antigen under control of the thyroglobulin promoter was abolished in Aire homozygotes and less efficient in heterozygotes, providing an explanation for thyroid autoimmunity in APS1. In contrast, Aire deficiency had no effect on thymic deletion to antigen controlled by a systemic H-2K promoter. The sensitivity of Aire-dependent thymic deletion to small reductions in function makes this pathway a prime candidate for more subtle autoimmune quantitative trait loci, and suggests that methods to increase Aire activity would be a potent strategy to lower the incidence of organ-specific autoimmunity.
Informed Omnivore : Visualizing Organic Food Production in Canada

This project report documents a design study in the domain of organic agriculture, and presents Informed Omnivore, an exploratory analysis tool for visualizing the Canadian organic food industry. A goal of this application is to provide consumers with the information necessary to make informed choices when buying local or organic food. I provide an overview of the domain, task, and data addressed by the application, followed by a description of the information visualization solution. This is followed by an analysis of the solution's strengths and weaknesses. This report concludes with a discussion of potential areas for future work. The contribution of Informed Omnivore is a demonstration of information visualization techniques applied to domain of organic agriculture, motivating casual users to make sustainable and healthy food choices.
Role of stop instruction in a human-robot interactive directional guidance task

Some nonverbal information such as prosody are reported to be able to play a role of penalty signal in human-human and human-agent communication. In order to investigate whether other nonverbal information such as gesture can play similar role in human-robot interactive task, a pilot experiment using a directional guidance task was conducted. The results suggested that a part of ldquostoprdquo instructions might play a role of a penalty signal, and changes of usage frequency of these ldquostoprdquo instructions could possibly infer the learning stage of human instructorspsila adaptation to robots.
Combining Domain Adaptation Approaches for Medical Text Translation

This paper explores a number of simple and effective techniques to adapt statistical machine translation (SMT) systems in the medical domain. Comparative experiments are conducted on large corpora for six language pairs. We not only compare each adapted system with the baseline, but also combine them to further improve the domain-specific systems. Finally, we attend the WMT2014 medical summary sentence translation constrained task and our systems achieve the best BLEU scores for Czech-English, EnglishGerman, French-English language pairs and the second best BLEU scores for reminding pairs.
Color-dielectric gauge theory on a transverse lattice

We investigate consequences of the effective colour-dielectric formulation of lattice gauge theory using the light-cone Hamiltonian formalism with a transverse lattice [1]. As a quantitative test of this approach, we have performed extensive analytic and numerical calculations for 2 + 1-dimensional pure gauge theory in the large N limit. We study the structure of coupling constant space for our effective potential by comparing with results available from conventional Euclidean lattice Monte Carlo simulations of this system. In particular, we calculate and measure the scaling behaviour of the entire low-lying glueball spectrum, glueball wavefunctions, string tension, asymptotic density of states, and deconfining temperature.
SAM: A Multithreaded Pipeline Architecture for Data ow Computing

SAM is a multithreaded pipeline architecture which supports multiple instruction threads running on a single shared high speed pipeline. It supports a data ow-style of programming in which the parallelism in the program is represented as a directed acyclic graph. Because the SAM architecture is basically an extension of the von Neumann architecture, conventional sequential programming is also supported. The SAM architecture resembles a RISC machine with a few additional features. Both experimental data and mathematical analysis show that the SAM architecture can achieve a pipeline e ciency of nearly 100% with minimal overhead.
USE OF SAR PRODUCTS FOR HYDROLOGICAL END-TO-END APPLICATION

It is an undeniable fact that decision-aid tools now provide the means for making environmental appraisals. But sometimes their imprecision jeopardises their credibility. The authors used the indicator method to evaluate the Vulnerability of Surface Water to Phytosanitary Products (VESPP in French). This method of comparison was refined by applying fuzzy arithmetic, making it more reliable.
Cortical Microinfarcts Detected In Vivo on 3 Tesla MRI: Clinical and Radiological Correlates

Background and Purpose— Cortical microinfarcts (CMIs) are a common postmortem finding associated with vascular risk factors, cognitive decline, and dementia. Recently, CMIs identified in vivo on 7 Tesla MRI also proved retraceable on 3 Tesla MRI. Methods— We evaluated CMIs on 3 Tesla MRI in a population-based cohort of 194 nondemented older people (72–80 years) with systolic hypertension. Using a case–control design, participants with and without CMIs were compared on age, sex, cardiovascular risk factors, and white matter hyperintensity volume. Results— We identified 23 CMIs in 12 participants (6%). CMIs were associated with older age, higher diastolic blood pressure, and a history of recent stroke. There was a trend for a higher white matter hyperintensity volume in participants with CMIs. Conclusions— We found an association of CMIs with clinical parameters, including age and cardiovascular risk factors. Although the prevalence of CMIs is relatively low, our results suggest that the study of CMIs in larger clinical studies is possible using 3 Tesla MRI. This opens the possibility of large-scale prospective investigation of the clinical relevance of CMIs in older people.
Mobile Phones as 3-DOF Controllers: A Comparative Study

Conventional input devices such as the mouse and keyboard lack in intuitiveness when it comes to 3D manipulation tasks. In this paper, we explore the use of accelerometer and digital compass equipped mobile phones as 3-DOF controllers in a 3D object rotation task. We put the mobile phone up against the established standards, a mouse and a touch pen and compare their performance in a rotation task. Our preliminary evaluation indicates that for this type of task, with only 5 minutes of practice the mobile phone is significantly faster than both the mouse and the touch pen.
Entrepreneurship and Household Saving

Abstract Using data from the 1983 and 1989 Federal Reserve Board Surveys of Consumer Finances, we quantify three findings about entrepreneurial saving decisions and their role in household wealth accumulation. First, entrepreneurial households own a substantial share of household wealth and income, and this share increases throughout the wealth distribution and the income distribution. Second, the portfolios of entrepreneurial households, even wealthy ones, are very undiversified, with the bulk of assets held within active businesses. Third, wealth-income ratios and saving rates are higher for entrepreneurial households even after controlling for age and other demographic variables. Taken together, these findings suggest that studies of household saving decisions in general and of the savings decisions of wealthy or high-income households in particular have paid insufficient attention to the role of entrepreneurial decisions and their role in wealth accumulation.
Magic Quadrant for Customer Data Mining , 2 Q 07

Most enterprises rely on a combination of vendors to enable customer data mining. SAS and SPSS offer broad solutions that will serve the requirements of many CRM initiatives. Angoss Software has broad data mining capabilities, but limited drill-down CRM expertise. KXEN and Portrait Software (the former Quadstone) offer solutions focused on increasing analyst productivity, while ThinkAnalytics focuses on embedding predictive analytics into multichannel deployments. Fair Isaac and Unica offer data mining solutions that are valuable complements to other applications in their portfolios.
Information criteria performance for feature selection

This paper shows the information criteria (IC) performances in feature selection framework. Feature selection aims to select a representative subset among a wide set of features. We apply this approach to classify an hand segmented image. The performance is tested using various feature selection schemes (SFS, SBS, SFFS and SBFS) to select the candidate subsets. The accuracy of the approach is based on a good quality of the joint probability density approximation of the combined features. They are obtained using histogram optimized thanks to the adaptive arithmetic coding principles. Our approach is tested on different reference data. The subsets quality is evaluated using correct classification rate computed on multiple classifiers. Results show stability and convergence properties of this tool and its ability to select representative subsets (in the sense that the subset of feature is a good characterization of the classes in which the data belong). Information Criteria could be used for feature selection as a good alternative to other criteria.
Generalized Feasibility Analysis on Uniform Multiprocessors

This paper presents feasibility tests for scheduling instances of real-time jobs on uniform multiprocessor platforms. In a uniform multiprocessor, each processor has an associated speed – a job executing on a processor of speed s for t time units performs s × t units of work. Two feasibility tests are presented. First, a sufficient condition is presented – whenever this condition holds the jobs are known to be feasible on the multiprocessor. Then, a necessary condition is presented – whenever the jobs are feasible on the multiprocessor, this condition must hold.
Long Term Comprehension of Software Systems: A Methodology for Study

Studies of software comprehension often use short-term recall as a way to study comprehension. Experiments range from broad descriptions of program purpose to tests that require subject to ‘fill in the gaps’. There is little doubt that human memory is a very important issue when it comes to understanding how software systems work. This paper addresses the topic of ‘long term’ comprehension, namely, the retention of programming knowledge over a period of months, years or even decades. Long-term retention of programming knowledge is thought to be an area within the psychology of programming literature that has received surprisingly little attention. To stimulate debate, methodological issues that may affect the study of long-term comprehension are detailed. Finally, a planned experiment based upon related psychology of programming studies is outlined.
Towards evaluating type of service related Quality-of-Experience on mobile networks

Quality of Service (QoS) metrics have been traditionally used to evaluate the perceived quality of services delivered by network operators. However, these metrics are not suitable for evaluating the experience of an end-user. The experience of a user is quantified based upon activities such as speed of web page loading, quality of video streaming, or voice quality of Internet-telephony. Due to the temporal and geographical nature of mobile networks, the perceived experience of a user may change based on location and time. Mobile operators may prioritize certain services over others, leading to a service type dependent Quality of Experience (QoE). In this paper we present a mobile application developed to gather metrics necessary to evaluate QoE in a mobile environment. Our approach towards obtain not just a general, but service specific mean opinion score (MOS) to quantify QoE is also discussed. Initial experiments and measurement tests show that it is possible for the same operator to deliver different QoE based on service and even time-of-day.
Human tracking in crowded environment with stereo cameras

In this paper, a human detection and tracking system in a crowded environment is presented. The biggest challenge of the system is to detect occluded people from the captured video where visible information of the occluded people in a camera is reduced. Many researchers proposed to reconstruct the occluded information from other cameras which are installed in the same place with different viewing angles, but, hardware cost and computation cost will be increased. In this paper, a stereo camera system is used with a novel occlusion model to solve the occlusion problem. Result shows that it significantly reduces the hardware cost and computation cost of the system while maintaining a good tracking result under severe occlusions.