Miracle-dz/UniFAR-FTUs huggingface dataset:
DETECTION OF LOCAL SITE CONDITIONS INFLUENCING EARTHQUAKE SHOCK AND SECONDARY EFFECTS IN THE VALPARAISO AREA IN CENTRAL-CHILE USING REMOTE SENSING AND GIS METHODS

The potential contribution of remote sensing and GIS techniques to earthquake hazard analysis was investigated in Valparaiso in Chile in order to improve the systematic, standardized inventory of those areas that are more susceptible to earthquake ground motions or to earthquake related secondary effects such as landslides, liquefaction, soil amplifications, compaction or even tsunami-waves. Geophysical, topographical, geological data and satellite images were collected, processed, and integrated into a spatial database using Geoinformation Systems (GIS) and image processing techniques. The GIS integrated evaluation of satellite imageries, of digital topographic data and of various open-source geodata can contribute to the acquisition of those specific tectonic, geomorphologic/ topographic settings influencing local site conditions in Valparaiso, Chile. Using the weighted overlay techniques in GIS, susceptibility maps were produced indicating areas, where causal factors influencing nearsurface earthquake shock occur aggregated. Causal factors (such as unconsolidated sedimentary layers within a basin’s topography, higher groundwater tables, etc.) summarizing and interfering each other, rise the susceptibility of soil amplification and of earthquake related secondary effects. This approach was used as well to create a tsunami flooding susceptibility map. LANDSAT Thermal Band 6-imageries were analysed to get information of surface water currents in this area.
Continuous and intermittent exposure of neonatal rat calvarial cells to PTHrP (1-36) inhibits bone nodule mineralization in vitro by downregulating bone sialoprotein expression via the cAMP signaling pathway [version 2; peer review: 2 approved]

The development and growth of the skeleton in the absence of parathyroid-hormone-related protein (PTHrP) is abnormal. The shortening of appendicular bones in PTHrP gene null mice is explained by an effect of PTHrP on endochondral bone growth. Whether or not PTHrP influences intramembranous ossification is less clear. The purpose of this study was to determine the effect of exogenous PTHrP on intramembranous ossification in vitro . Neonatal rat calvarial cells maintained in primary cell culture conditions that permit spontaneous formation of woven bone nodules by intramembranous ossification were studied. The expression of PTHrP, parathyroid hormone 1 receptor (PTH1R), and alkaline phosphatase (AP) by osteogenic cells in developing nodules and the effects of PTHrP (1-36) on nodule development was determined over 3-18 days. PTHrP and PTH1R were detected colonies of osteogenic cells on culture day three, and AP was detected on day six. PTHrP and its receptor were localized in pre-osteoblasts, osteoblasts, and osteocytes, and AP activity was detected in pre-osteoblasts and osteoblasts but
SBArt4 as Automatic Art and Live Performance Tool

References: [1] Tatsuo Unemi, “A Breeding Tool for Abstract Animations and Its Applications”, 13 Generative Art Conference, 451-458, Milan, Italy, 2010 [2] www.intlab. soka.ac. jp/ ~unemi/sbart/4/ Abstract: SBArt4 is originally a breeding tool to produce abstract images and animations [1]. This paper describes a newly implemented functionality of automated evolution using some types of computational aesthetic measures as fitness criteria. Measures include information complexity, global contrast factor, histogram of color distribution, and so on. In addition to these measures for a still image, a method to evaluate the motion was introduced. They are useful to discard boring pieces but do not always fit with human user’s preference. I introduced graphical user interface to allow the user to adjust the balance among different measures, and provided methods to let individuals migrate between a field for breeding and a population for evolution. It realized a wide range of intermediate production style between pure breeding and fully automated evolution. Utilizing parallel processing, efficient algorithms, and synchronized sound effects, a new generative style of both live performance and fully automatic art became possible to be realized.
Adaptive Hierarchical Key Structure Generation for Key Management in Wireless Sensor Networks using A *

civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.
3 ImageCLEFlifelog 2019 LMRT Task : LIFER 2 . 0-Baseline Interactive Retrieval Search Engine

This paper describes the participation of the Organiser Team in the ImageCLEFlifelog 2019 Solve My Life Puzzle (Puzzle) and Lifelog Moment Retrieval (LMRT) tasks. We proposed to use LIFER 2.0, an enhanced version of LIFER, which was an interactive retrieval system for personal lifelog data. We utilised LIFER 2.0 with some additional visual features, obtained by using traditional visual bag-of-words, to solve the Puzzle task, while with the LMRT, we applied LIFER 2.0 only with the provided information. The results on both tasks confirmed that by using faceted filter and context browsing, a user can gain insights from their personal lifelog by employing very simple interactions. These results also serve as baselines for other approaches in the ImageCLEFlifelog 2019 challenge to compare with.
International Journal of Advanced Research in Computer Science and Software Engineering

— For improving Software quality the standard method is testing, conventional testing methods often fail to detect faults. Concolic testing attempts to remedy this by automatically generating test cases to explore execution paths in a program under test, helping testers achieve greater coverage of program behaviour in a more automated fashion. Often, programmers spend more time fixing bugs in existing code than they do writing new one: it is estimated that more than half of the software-development costs of a typical project are spent on identifying and fixing defects. Simulation and testing are the prevailing approaches when it comes to validating behaviours of computer systems in general and software code in particular. Testing is essential for quality assurance of database applications. Achieving high code coverage of the database application is important in testing. In practice there may exist a copy of live databases that can be used for database application testing. Concolic testing generates test cases that can achieve high coverage in an automated fashion. Core idea behind concolic testing is to obtain symbolic path formulas from concrete executions and solve them to generate test cases by using constraint solvers.
AN OVERVIEW OF PREPROCESSING OF WEB LOG FILES FOR WEB USAGE MINING 1

With the Internet usage gaining popularity and the steady growth of users, the World Wide Web has become a huge repository of data and serves as an important platform for the dissemination of information. The users’ accesses to Web sites are stored inWeb server logs.However, the data stored in the log files do not present an accurate picture of the users’ accesses to the Web site. Hence, preprocessing of the Web log data is an essential and pre-requisite phase before it can be used for knowledge-discovery or mining tasks. The preprocessed Web data can then be suitable for thediscovery and analysis of useful information referred to as Web mining. Web usage mining, a classification of Web mining, is the application of data mining techniques to discover usage patterns from clickstream and associated data stored in one or more Web servers.This paper presents an overview of the various steps involved in the preprocessing stage.
Ecological factors associated with rift valley fever during inter-epidemic period in Tanzania

Climate change influences the distribution of suitable habitats for mosquito vectors responsible for transmission of disease vectors. Rift Valley Fever (RVF) is a climaterelated arboviral infection of animals and humans. Culex pipiens complex is the only mosquito vector known to be associated with RVF epidemics in Tanzania. Climate change is thought to represent a threat towards emerging risk areas for RVF epidemics. The influence of future climate projections on variability of habitat suitability and shift for RVF vectors was assessed in relation to disease outbreaks risk area in Tanzania. Ecological niche models (ENM) were used to estimate potential distributions of disease risk areas based on Culex pipiens complex presence only data approach. Current and future projections climatic variables were used as model inputs. Changes in mosquito vectors habitat suitability under future climatic scenarios were estimated. Partial receiver operating characteristic (ROC) and the area under the curves (AUC) approach was used to evaluate model predictive performance and significance. Predicted habitat suitability for Culex pipiens complex indicated broad-scale potential for change and shift in the distribution of the vectors and disease for both 2020 and 2050 climate scenarios. Predicted risk areas indicate more intensification in the areas surrounding Lake Victoria and north-eastern part of the country through 2050 climate scenario. Findings show higher probability of emerging risk areas spreading towards the western parts of Tanzania from north-eastern areas and decrease in the southern part of the country. Results presented here identified future sites for consideration in order to guide surveillance and control interventions to reduce risk of RVF disease epidemics in Tanzania. A collaborative approach is recommended to develop and adapt climate related disease control and prevention strategies.
Audio-Visual Speech Recognition in the Presence of a Competing Speaker

This paper examines the problem of estimating stream weights for a multistream audio-visual speech recogniser in the context of a simultaneous speaker task. The task is challenging because signal-to-noise ratio (SNR) cannot be readily inferred from the acoustics alone. The method proposed employs artiﬁcial neural networks (ANNs) to estimate the SNR from HMM state-likelihoods. SNR is converted to stream weight using a mapping optimised on development data. The method produces an audio-visual recognition performance better than that of both the audio-only and the video-only baselines across a wide range of SNRs. The performance using SNR estimates based on audio state-likelihoods is compared to that obtained using both audio and visual likelihoods. Although the audio-visual SNR estimator outperforms the audio-only SNR estimator, the recognition performance beneﬁt is small. Ideas for making fuller use of the visual information are discussed.
A Dynamic Explanation for the Ruptures of Repeating Earthquakes on the San Andreas Fault at Parkfield

Analyzing the relative source time functions (STFs) of repeating earthquakes (REs) at Parkfield and their spectra indicates that there are two groups of REs. One group of REs (G1) displays simple relative STFs and smooth spectra, whereas the other group (G2) displays complex relative STFs and spectra with obvious holes. We use the boundary integral equation method with different configurations of parameters to simulate the spontaneous dynamic ruptures and fit the observed characteristics. Finally, we find that the differences in the observed characteristics are due to the different configurations of the dynamic parameters. Earthquakes in G1 are self‐arresting ruptures, and earthquakes in G2 are runaway ruptures. Moreover, holes in the spectra of G2 are caused by the dynamic rupture propagation, and the frequency of the holes is a function of the radius of the circular fault, the angle between the station azimuth and the rupture propagation, and the rupture velocity.
Connectivity analysis of one-dimensional ad-hoc networks by

Applications and communication protocols in dynamic ad-hoc networks are exposed to physical limitations imposed by the connectivity relations that result from mobility. Motivated by vehicular freeway scenarios, this paper analyzes a number of important connectivity metrics for instantaneous snapshots of stochastic geographic movement patterns under the assumption of a fixed radio range for each node: (1) The node degree, corresponding to the number of singlehop neighbors of a mobile node; (2) The connectivity number, expressing the number of nodes reachable via multi-hop paths of arbitrary hop-count; (3) the connectivity distance, expressing the geographic distance that a message can be propagated in the network on multihop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops analytic expressions for the distributions and moments of these random variables for general stationary MAP processes on a one dimensional space. The numerical results compares bursty vehicular traffic with independent movement scenarios described by a Poisson process.
Design as conversation with digital materials

This paper explores Donald Schön's concept of design as a conversation with materials, in the context of designing digital systems. It proposes material utterance as a central event in designing. A material utterance is a situated communication act that depends on the particularities of speaker, audience, material and genre. The paper argues that, if digital designing differs from other forms of designing, then accounts for such differences must be sought by understanding the material properties of digital systems and the genres of practice that surround their use. Perspectives from human-computer interaction (HCI) and the psychology of programming are used to examine how such an understanding might be constructed.
Digitally synthesized stochastic flash ADC using only standard digital cells

An ADC is synthesized entirely from Verilog code in 90nm digital CMOS using a standard digital cell library. An analog comparator is generated by cross-coupling two 3-input NAND gates. The random comparator offsets are used as the ADC references and are Gaussian. An implicitly aligned three-section piecewise-linear inverse Gaussian CDF function on chip linearizes the output. SNDR of 35.9dB is achieved at 210MSPS.
Transform-Invariant PCA: A Unified Approach to Fully Automatic Face Alignment, Representation, and Recognition.

We develop a Transform-Invariant PCA (TIPCA) technique which aims to accurately characterize the intrinsic structures of the human face that are invariant to the in-plane transformations of the training images. Specially, TIPCA alternately aligns the image ensemble and creates the optimal eigenspace with the objective to minimize the mean square error between the aligned images and their reconstructions. The learning from the FERET facial image ensemble of 1196 subjects validates the mutual promotion between image alignment and eigenspace representation, which eventually leads to the optimized coding and recognition performance that surpasses the manual alignment based approaches. Experimental results also suggest that state-of-the-art invariant descriptors, such as local binary pattern (LBP), histogram of oriented gradient (HOG), and gabor energy filter (GEF), and classification methods, such as sparse representation based classification (SRC) and support vector machine (SVM), can benefit from using the TIPCA-aligned faces, instead of the manually eye-aligned faces that are widely regarded as the ground-truth alignment. Favorable accuracies against the state-of-the-art results on face coding and face recognition are reported.
Towards Practical Evaluation of Android ICC Resolution Techniques

Inter-component communication (ICC) is a widely used mechanism in mobile apps, which enables message-based control flow transferring and data passing between components. Effective ICC resolution requires precisely identifying entry points, analyzing data values of ICC fields, modeling related framework APIs, etc. Due to various control-flow and data-value tracking related characteristics involved and the lack of oracles for real-world apps, the practical evaluation of ICC resolution techniques is challenging. To fill this gap, we collect multiple-type benchmark suites with 4,104 apps, covering the characteristic-specific, open-source, and commercial ones. Considering the differences of benchmarks, we adopt various evaluation metrics for them, which are based on the number count, graph structure, and reliable oracle. As the oracle for real-world apps is unavailable, we design a dynamic analysis approach to extract the real ICC links triggered during GUI exploration. Overall, we manually confirm 1,680 ICCs and label 42,000 code characteristic tags to form a reliable oracle set. The evaluation performed on six off-the-shelf ICC resolution tools show that tools behave inconsistently on multiple benchmarks and with different metrics. Using reliable oracles, we find that up to 39% 85% ICCs are missed by the six tools, for their inadequate analysis of specific code characteristics. And with the help of graph metrics, we identify many wrongly reported ICCs caused by conservative analysis or the transitivity of imprecision. Finally, we summarize eight FN/FP patterns in ICC resolution for further improvement. CCS CONCEPTS • Software and its engineering → Software testing and debugging. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. Conference’17, July 2017, Washington, DC, USA © 2022 Association for Computing Machinery. ACM ISBN 978-x-xxxx-xxxx-x/YY/MM. $15.00 https://doi.org/10.1145/nnnnnnn.nnnnnnn
1 Prior Work on Interpreting Query Click Logs

The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who assigns a score o f Perfect, Excellent, etc., depending on how well the URL matc hes the query. In this paper, we study whether clicks can be used t o automatically generate good labels. Intuitively, documen ts that are clicked (resp., skipped) in aggregate can indicate relevan ce (resp., lack of relevance). We give a novel way of transforming click s into weighted, directed graphs inspired by eye-tracking studie s and then devise an objective function for finding cuts in these graphs that induce a good labeling. In its full generality, the problem is N P-hard, but we show that, in the case of two labels, an optimum labelin g can be found in linear time. For the more general case, we prop ose heuristic solutions. Experiments on real click logs show th at clickbased labels align with the opinion of a panel of judges, espe cially as the consensus of the panel grows stronger.
AIS Electronic Library (AISeL)

In workflow management, the data flow perspective specifies how data are produced and consumed by activities in a workflow. Data flow analysis can detect data flow anomalies occurring in a workflow while its control flow can be syntactically error-free. Currently, most commercial workflow management systems do not provide the tools for data flow analysis at design time. We have previously proposed a data flow analysis approach and developed the basic concepts and the essential algorithms. As another step forward, this paper examines the issues of data flow anomalies and their verification from a theoretical point of view and validates the correctness of the proposed approach
Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks

— This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.
Sensitivity of AGCM‐simulated regional JJAS precipitation to different convective parameterization schemes

This study examines the effects of convective parameterization schemes (CPSs) on the simulated June–September (JJAS) precipitation climatology, variability and predictability over southwestern Arabian Peninsula and northeast Africa during 1981–2014 within an atmospheric global climate model framework. The three CPSs used are: the simplified Arakawa–Schubert (SAS) scheme; the SAS scheme with Tokioka modification (STOK) and the Emanuel (EMAN) scheme coupled with a probability distribution function‐based cloud parameterization scheme. SAS and STOK overestimate JJAS total precipitation over the selected domain compared to observations, while EMAN underestimates. EMAN provides the most realistic distribution of precipitation and spatial distribution of convective precipitation despite the tendency for underestimating the total precipitation. The principal patterns of precipitation variability (as measured by the leading empirical orthogonal functions) in EMAN and STOK are clearly related to the observed pattern, while the maximum variability in SAS occurs in a completely different location. The El Niño Southern Oscillation‐related JJAS precipitation teleconnection simulated by the SAS scheme is very weak as compared to observations and other two CPSs. The signal‐to‐noise ratio estimated by SAS and STOK is very low as compared to EMAN. Correlation analysis shows that EMAN performs better than the other two CPSs. Low (high) outgoing longwave radiation (OLR) values are indicative of enhanced (suppressed) convection and hence more (less) cloud coverage. The root mean square error estimated for OLR in EMAN is lower than that of the other two CPSs. The vertical structure of specific humidity and temperature shows less error in EMAN than that of the other two CPSs, which could be a reason for better predictability over the region of interest.