Miracle-dz/UniFAR-FTUs huggingface dataset:
From Relative to Absolute Teleseismic Travel Times: The Absolute Arrival‐Time Recovery Method (AARM)

Dense, short-term deployments of seismograph networks are frequently used to study upper-mantle structure. However, recordings of variably emergent teleseismic waveforms are often of lower signal-to-noise ratio (SNR) than those recorded at permanent observatory sites. Therefore, waveform coherency across a network is frequently utilized to calculate relative arrival times between recorded traces, but these measurements cannot easily be combined or reported directly to global absolute arrival-time databases. These datasets are thus a valuable but untapped resource with which to fill spatial gaps in global absolute-wavespeed tomographic models. We developed an absolute arrival-time recovery method (AARM) to retrieve absolute time picks from relative-arrival-time datasets, working synchronously with filtered and unfiltered data. We also include a relative estimate of uncertainty for potential use in data weighting during subsequent tomographic inversion. Filtered waveforms are first aligned via multichannel cross correlation. These time shifts are applied to unfiltered waveforms to generate a phase-weighted stack. Cross correlation with the primary stack or the SNR of each trace is used to weight a secondhigher SNR stack. The first arrival on the final stack is picked manually to recover absolute arrival times for the aligned waveforms. We test AARM on a recently published dataset from southeast Canada (∼10;000 picks). When compared with the available equivalent earthquake–station pairs on the International Seismological Centre (ISC) database,∼83% ofAARMpicks agree towithin 0:5 s. Tests using syntheticP-wave data indicate that AARMproduces absolute arrivaltime picks to accuracies of better than 0.25 s, akin to uncertainties in ISC bulletins. Electronic Supplement: Graphical output from testing of the absolute arrivaltime recovery method (AARM) on observed dataset and an archive containing a copy of the AARM code, plotting scripts, and user guide.
Direct marketing modeling with CART and CHAID

In a recent article in the Journal of Direct Marketing, R. Thrasher gave an introduction to the Classification and Regression Trees (CART) methodology from the point of view of direct marketing. Following up on this work, with the help of a case study, this article investigates further technical aspects of response modeling with CART and Chi-Square Automatic Interaction Detector (CHAID) of practical relevance to direct marketing professionals and researchers and compares the performance of CART and CHAID models built on the same analysis file, finding that the response lifts are very close for both types of models.
Rubidium-strontium isotopic studies in the Kalgoorlie-Norseman area, Western Australia

The reported age of 1100 ± 50 m.y. for the Albany Granite is taken as marking the waning stages of the main orogeny in the south coast of Western Australia. The high initial °'Sr/ Sr for this granite, 0.7118 ± 0.0064, suggests an anatectic or rheomorphic origin which is con­ sistent with petrographic evidence for the absence of a later metamorphism. Shales from the Stirling Range Beds indicate a metamorphic event at 1150 ± 40 m.y. which is considered to be the time of upthrusting of rocks of higher metamorphic grade to their present position ad­ jacent to the Stirling Range Beds. The minimum age of deposition for the Stirling Range Beds is postulated as 1340 m.y.
WHO’S WHO IN NETWORKS. WANTED: THE KEY PLAYER

Who’s Who in Networks. Wanted: The Key Player* Finite population non-cooperative games with linear-quadratic utilities, where each player decides how much action she exerts, can be interpreted as a network game with local payoff complementarities, together with a globally uniform payoff substitutability component and an own concavity effect. For these games, the Nash equilibrium action of each player is proportional to her Bonacich centrality in the network of local complementarities, thus establishing a bridge with the sociology literature on social networks. This Bonacich-Nash linkage implies that aggregate equilibrium increases with network size and density. We then analyze a policy that consists in targeting the key player, that is, the player who, once removed, leads to the optimal change in aggregate activity. We provide a geometric characterization of the key player identified with an inter-centrality measure, which takes into account both a player’s centrality and her contribution to the centrality of the others. JEL Classification: A14, C72 and L14
Continuous integration in GITHUB : experiences with TRAVIS-CI

Continuous integration (CI) is a software engineering practice of frequently merging all developer working copies with a shared main branch [1], e.g., several times a day, or with every commit. This continuous application of quality control checks aims to speed up the development process and to ultimately improve software quality, by reducing the integration problems occurring between team members that develop software collaboratively [1]. With the advent of social media in (OSS) software development, recent years have witnessed many changes to how software is developed, and how developers collaborate, communicate, and learn [2]. One such prominent change is the emergence of the pull-based development model [3], made popular by the “social coding” platform GITHUB. In this model one can distinguish between direct contributions to a project, coming from a typically small group of developers with write access to the main project repository, and indirect ones, coming from developers who fork the main repository, update their copies locally, and submit pull requests for review and merger. GITHUB’s implementation of the pull-based development model enables anyone with an account to submit changes to any repository with only a few clicks. This represents an unprecedented low barrier to entry for potential contributors, but it also impacts testing behavior [4]: GITHUB project owners reported scalability challenges when integrating outside contributions, driving them towards automated tests. Automated CI services, such as TRAVIS-CI1—integrated with GITHUB itself—or JENKINS2, facilitate this process: whenever a commit is recorded or a pull request is received, the contribution is merged automatically into a testing branch, the existing test suite is run, and the contribution author and project owner are notified of the results. This extended abstract summarizes the finding of our study of TRAVIS-CI, arguably the most popular CI service on GITHUB [5]. 3 We quantitatively explore to what extent GITHUB developers use the TRAVIS-CI, and whether the contribution type (direct or indirect) or project characteristics are associated with the success of the automatic builds.
Robust extraction of eyes from face

In this paper we propose a new algorithm to detect the irises of both eyes from a human face in an intensity image. Using the separability filter proposed by Fukui et al. (1997), the algorithm first extracts intensity valleys, which we call blobs in this paper, as the candidates for the irises. Next, for each pair of blobs, the algorithm computes a cost using Hough transform and separability filter to measure the fit of the pair of blobs to the image. And then, the algorithm selects a pair of blobs with the smallest cost as the irises of both eyes. As the result of the experiment using all faces without spectacles in the face database of the University of Bern, the success rate of the proposed algorithm was 96.5% on average.
Bayesian Population Decoding of Spiking Neurons

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a ‘spike-by-spike’ online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.
Development of Volcanic Ash Plume Tracking Model PUFF and Estimation of the Airborne Ash Density

Airborne volcanic ash is a danger object for the aviation safety. Once the jet aircraft encounters the ash cloud and engine failure occurs, the damage is estimated to reach to a billion of US dollar. Hence the real-time monitoring and estimation of the airborne ash density is an important research subject. According to ICAO report, the ash density above 2 mg/m3 is a threshold for the danger zone of the aircraft. A system to predict the airborne ash density is desired based on the real-time observation of the emission rate and plume height. In this study, we conducted numerical simulations of volcanic ash dispersal from Sakurajima volcano using the real-time volcanic ash plume dispersion model PUFF, combined with the real-time estimation of emission rate and plume height based on seismicity record. The PUFF model is applied to the eruption of Kuchinoerabu-jima in May 2015, and the airborne ash density was estimated based on the fallout data at Yakushima. According to the simulation, the ash plume movement agrees well with the satellite imagery by Himawari-8. The plume is located at 200 km from the volcano 8 hours after the eruption, and has the density more than 100 mg/m3. The simulated result offers important information of airborne ash density which is useful to the aviation safety.
City Research Online

—We explore the effects of selecting alternative layouts in hierarchical displays that show multiple aspects of large multivariate datasets, including spatial and temporal characteristics. Hierarchical displays of this type condition a dataset by multiple discrete variable values, creating nested graphical summaries of the resulting subsets in which size, shape and colour can be used to show subset properties. These ‘small multiples’ are ordered by the conditioning variable values and are laid out hierarchically using dimensional stacking. Crucially, we consider the use of different layouts at different hierarchical levels , so that the coordinates of the plane can be used more effectively to draw attention to trends and anomalies in the data. We argue that these layouts should be informed by the type of conditioning variable and by the research question being explored. We focus on space-ﬁlling rectangular layouts that provide data-dense and rich overviews of data to address research questions posed in our exploratory analysis of spatial and temporal aspects of property sales in London. We develop a notation (‘HiVE’) that describes visualisation and layout states and provides reconﬁguration operators, demonstrate its use for reconﬁguring layouts to pursue research questions and provide guidelines for this process. We demonstrate how layouts can be related through animated transitions to reduce the cognitive load associated with their reconﬁguration whilst supporting the exploratory process.
Phoneme Recognition Using Time-Delay Neural Networks

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TagCaptcha: annotating images with CAPTCHAs

Image retrieval has long been plagued by limitations on automatic methods because they cannot reliably extract semantic data from low-level features. The result is that users must formulate awkward and inefficient queries in terms these systems can understand. Humans, on the other hand, have the ability to quickly and accurately summarise visual data. This dichotomy, named the semantic gap, is a fundamental problem in image retrieval. We aim to narrow the semantic gap in a typical retrieval scenario by motivating users to provide semantic image annotations. We propose a system of collecting image annotations based on the need for human verification on the web. Similar in principle to work by von Ahn et al. [2, 3], the idea is to exploit the requirement of users to pass tests in order to incrementally annotate images.
A Combinatorial Auction mechanism for multiple resource procurement in cloud computing

Multiple resource procurement from several cloud vendors participating in bidding is addressed in this paper. This is done by assigning dynamic pricing for these resources. Since we consider multiple resources to be procured from several cloud vendors bidding in an auction, the problem turns out to be one of a combinatorial auction. We pre-process the user requests, analyze the auction and declare a set of vendors bidding for the auction as winners based on the Combinatorial Auction Branch on Bids (CABOB) model. Simulations using our approach with prices procured from several cloud vendors' datasets show its effectiveness in multiple resource procurement in the realm of cloud computing.
Maximum‐Likelihood Analysis Using TREE‐PUZZLE

TREE‐PUZZLE provides means to analyze and reconstruct evolutionary relationships and trees based on quartets, i.e. groups of 4 sequences. explains how to reconstruct trees based on the maximum‐likelihood principle and quartet puzzling. discusses likelihood mapping, a method to visualize phylogenetic content in a multiple sequence alignment. explains how to compare tree topologies using different tests.
Lungs Nodule Detection Using Semantic Segmentation and Classification with Optimal Features

Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of its nodules. Radiologists need support from automated tools for precise opinion. Automated detection of the affected lungs nodule is difficult because of the shape similarity among healthy tissues. Over the years, several expert systems have been developed that help radiologists to diagnose lung cancer. In this article, we propose a framework to precisely detect lungs cancer by classifying it between benign and malignant nodules. The framework is tested using the subset of the publicly available at the Lung Image Database Consortium image collection (LIDC-IDRI). Multiple techniques including filtering and noise removing are applied for pre-processing. Subsequently, the OTSU and the semantic segmentation are used to accurately detect the unhealthy lungs nodules. In total, 13 nodules features were extracted using Principal Components Analysis (PCA) algorithm. Four optimal features are selected based on the classification performance. In the classification phase, 9 different classifiers are used along with two types of validation schemes i.e. train test holdout validation with 70-30 data split and 10 fold cross-validation. Our experiments show that the proposed system provides 99.23\% accuracy using logic boost classifier.
International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

Test driven design (TDD) and design driven testing (DDT) are used for test case generation. TDD generates so many duplicated test cases at the end of the project. DDT is novel approach to generate test cases based on design model of application. Comparative study indicates batter result using DDT. White-box traditional regression testing depends on analysis of impact of changes in source code. This practice minimizes the amount of testing required to validate code changes but they do not influence on requirement specification. Black-box testing supports ability to test from higher level design and requirement. Test optimal is a tool to generate test cases based on model driven environment using UML activity diagrams. Traditional approach generates many numbers of large and duplicate test cases. This paper focuses on test case generation techniques and describes proposed approach for improvement in test case minimization and prioritization. Proposed approach will minimize and prioritize generated test cases and generate optimal test cases using model driven testing. Changes in modified activity diagram element will identify Reusable and retestable test case. Filtering and prioritization will lead to better available resource utilization and will improve software project management.
Multi-Connection Mechanism of Mobile Agent in Grid

Grid is a research hot point in computer industry. In this paper, mobile agents are used as carriers of distributed tasks in grid, which can migrate between grid services autonomously and intelligently. Some mobile agents transmit a great deal of data in high-bandwidth and high-delay grid environment. According to features of grid and mobile agents, a new multiple connection mechanism is proposed. Experiments have proved that this mechanism, in which both transmission delay and package loss is thought as indicator of congestion, have higher transmission speed than the mechanism in which only package loss is thought as indicator of congestion.
A DISTRIBUTED GARBAGE COLLECTOR FOR ACTIVE OBJECTS

This paper introduces an algorithm that performs garbage collection in distributed systems of active objects (i.e., objects having their own threads of control). The proposed garbage collector is made of a set of local garbage collectors, one per node, loosely coupled to a global garbage collector. The novelties of the proposed garbage collector come from the fact that local garbage collectors need not be synchronized with each other for detecting garbage objects, and that faulty communication channels are tolerated. The paper describes the proposed garbage collector, together with its implementation and performance for a concurrent object-oriented language running on a local area network of workstations. R esum e : Nous proposons dans ce document un algorithme de d etection des miettes adapt e aux syst emes distribu es d'objets actifs (i.e., poss edant leurs propres ls de contr^ ole). Le ramasse-miettes propos e est constitu e d'un ensemble de ramasse-miettes locaux, un pour chaque nnud de l'architec-ture, et d'un ramasse-miettes global au syst eme. La principale originalit e de l'algorithme propos e r eside dans le fait qu'il n'est pas n ecessaire que les ramasse-miettes locaux se synchronisent pour la d etection des miettes. En outre, les communications non-ables sont support ees. Ce document d ecrit l'algorithme de ramasse-miettes propos e, ainsi que sa mise en uvre et ses performances pour un langage de programmation concurrent a objets s'ex e-cutant au dessus d'un r eseau local de stations de travail. Mots-cl e : Ramasse-miettes, langages de programmation concurrents a objets, syst emes distribu es, objets actifs.
Confronting, Confirming, and Dispelling Myths Surrounding ERP-in-the-Cloud: From Iron Cage to Agility

of our case. [14, p. 36] Accordingly, we see ERPc as freeing organizations from the negative impacts of the iron cage bureaucracy associated with many traditional stand-alone ERP-systems. Cloud based ERP-systems on the other hand, can be implemented faster, cheaper, and with more fl exibility. The result is empowered organizations that embrace agility, and the ben-e fi ts associated therein.
The Emergence of Boundary Spanning Competence in Practice: Implications for Information Systems' Implementation and Use

This paper investigates how an organizational competence in boundary spanning emerges in practice by drawing on the concepts of boundary spanner and boundary object. Using data from two qualitative field studies, we argue that in order for boundary spanning to emerge a new joint field of practice must be produced. Our data illustrate that agents partially transform their practices in local settings so as to accommodate the interests of their counterparts. While negotiating the new joint field, agents become what we call "boundary spanners-in-practice" who produce and use objects which then become locally useful and which acquire a common identity - hence, "boundary objects-in-use. " Moreover, we show how boundary spanners-in-practice use various organizational and professional resources including the influence that comes with being nominated to boundary spanners' roles to create the new joint field. The conditions necessary for boundary spanners-in-practice to emerge are outlined and discussed; as are important implications for IS implementation and use.
A Multi-Layer Non-Newtonian Model of Cardiovascular Inflammation

Cellular functions related to the maintenance of homoeostasis are regulated by shear forces sensed by endothelial cells. The endothelial cells sense local changes in shear stress. The resulting signals are either transduced into chemical responses or transmitted to the surroundings to regulate the cellular activity [1-5]. In the current literature, models of blood flow applied to the characterization of atherosclerotic plaques consider blood as a Newtonian fluid because of the characteristic length of the domain [5]. At predilection sites for plaque deposition, the diameter of the blood particles is much smaller than the normal arterial diameter. However, under disease condition, the proportions can dramatically change due to a reduction greater than 80% in the arterial cross-section, in cases of severe stenosis [6]. Here we show that in diseased arteries, the local particle concentration can peak at locations associated to high inflammation.
Estimating Word Translation Probabilities for Thai – English Machine Translation using EM Algorithm

Selecting the word translation from a set of target language words, one that conveys the correct sense of source word and makes more fluent target language output, is one of core problems in machine translation. In this paper we compare the 3 methods of estimating word translation probabilities for selecting the translation word in Thai – English Machine Translation. The 3 methods are (1) Method based on frequency of word translation, (2) Method based on collocation of word translation, and (3) Method based on Expectation Maximization (EM) algorithm. For evaluation we used Thai – English parallel sentences generated by NECTEC. The method based on EM algorithm is the best method in comparison to the other methods and gives the satisfying results. Keywords—Machine translation, EM algorithm.