Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic manipulation considerations for the articulated body mobile robot

Some methods of mobile manipulator control for the articulated body mobile robot "KORYU (KR)" are analyzed. KR is a class of mobile robot composed of serially connected "unit segments", configuring a long articulated body which resembles a train or a snake in shape. This configuration has an intrinsic advantage of making possible the use of the body's degrees of freedom (DOF) not only for "locomotion", but also for "manipulation". In order to demonstrate this characteristic we built a real mechanical model called KR-II, equipped with a 2 DOF manipulator in its foremost part. In the paper, two configurations for augmenting the number of this manipulator DOF are considered. The first method "fixed manipulator" considers the robot fixed to the ground, so that the manipulation control issue can be studied using well-known standard manipulator control theories. In the second method "mobile manipulator" special attention is paid to integrating manipulation tasks with body locomotion (steering) freedom. We verify that mobile manipulation can be smoothly integrated with a steering control method already developed in earlier works. Experimental results are shown to demonstrate the validity of the proposed augmented manipulation configurations and respective control methods.
Evolutive HMM for multi-speaker tracking system

Seeking within a speech sequence the speaker utterances is one of the main tasks of indexing. In this paper, the proposed speaker tracking system is defined in the case where all speaker identities are known beforehand. The conversation is modeled as an evolutive HMM-like model, in which speaker models computed are added one by one. A temporary indexing is proposed after each speaker adding and then challenged at the next step. This process is iterated until all the speakers are detected. The system has been assessed using multi-speaker messages generated by concatenation of Switchboard mono-speaker segments. The obtained results show the potentiality of the proposed solution.
Incidence of Aeromonas species isolated from different food sources and water

A total number of 350 random samples of raw milk, pasteurized milk, dairy products, tap water and water of udder wash were collected from markets in portSaid Province and examined for prevalence of Aeromonas species using starch ampicillin medium, The incidence of Aeromonas species isolated from raw milk, pasteurized milk, kariesh cheese, dmietta cheese, refrigerated white cheese, tap water and water of udder wash were 58%, 26%, 70%, 48%, 40%, 16% and 68%, respectively. The total number of mesophilic Aeromonas isolates from 350 examined samples was 202 isolates of which 104 (51.5%) isolates were A. hydrophila, 60 (29.7%) isolates were A. caviae, 25 (12.4%) isolates were A. sobria and 11 (5.4%) isolates were A. schubertii. The highest number of isolates (42) were recovered from water of udder wash samples, while the lowest number of isolates were recovered from pasteurized milk and tap water samples. Result of antibiotic sensitivity test revealed high degree of sensitivity towards chloramphenicol, amikacin, ceftriaxone and ciprofloxacin, resistant to ampicillin and colistin sulphate. Result of agarose gel electrophoresis revealed that A. hydrophila , A. caviae and A. schubertii have only one plasmid DNA with molecular weight 2.8 kbp While A. sobria was negative for plasmid. INTRODUCTION Motile Aeromonades have been included in the list of bacterial pathogens (Janda et al, 1983 and Holmberg et al, 1986). Buchanan (1984) indicated that the Aeromonades form a group of pathogens, which are emerging as food borne organisms of increasing importance. Aeromonades are gram-negative rod shape, motile by single polar flagellum , can be isolated from a variety of food, including meat, poultry, milk, milk products, fish, shell fish and vegetables (Melas et al, 1999). And widely distributed in the aquatic environment, including raw and processed drinking water (Holmes et al, 1996). The presence of food borne pathogens in milk is due to direct contact with
Extending automatic transcripts in a unified data representation towards a prosodic-based metadata annotation and evaluation

This paper describes a framework that extends automatic speech transcripts in order to accommodate relevant information coming from manual transcripts, the speech signal itself, and other resources, like lexica. The proposed framework automatically collects, relates, computes, and stores all relevant information together in a self-contained data source, making it possible to easily provide a wide range of interconnected information suitable for speech analysis, training, and evaluating a number of automatic speech processing tasks. The main goal of this framework is to integrate different linguistic and paralinguistic layers of knowledge for a more complete view of their representation and interactions in several domains and languages. The processing chain is composed of two main stages, where the first consists of integrating the relevant manual annotations in the speech recognition data, and the second consists of further enriching the previous output in order to accommodate prosodic information. The described framework has been used for the identification and analysis of structural metadata in automatic speech transcripts. Initially put to use for automatic detection of punctuation marks and for capitalization recovery from speech data, it has also been recently used for studying the characterization of disfluencies in speech. It was already applied to several domains of Portuguese corpora, and also to English and Spanish Broadcast News corpora.
Study and design of antennas for WLAN MIMO applications

Recently, the use of wireless communications and especially WLAN networks has been growing. WLAN networks that use the IEEE 802.11n standard have a greater capacity for data transport as well as a higher communication speed. To achieve these requirements, MIMO systems present an adequate solution. Due to their reduced cost and straightforward manufacturing, printed antennas are in high demand for use in short range communications. In this work, various printed double band MIMO antennas are presented, exploring spatial and polarization diversity, using the Rogers © rt/duroid 5880 substrate, fed by a coplanar waveguide, tuned to the frequencies of 2.45 and 5.6 GHz, from the Industrial, Scientific and Medical band (ISM). The structures were simulated in free space (S-parameter, radiation diagrams, correlation coefficient and diversity gain). Subsequently, the two element antenna that presented the best performance was chosen, and it was manufactured along with the four element antenna. The performance of both antennas was analysed using the reflection and transmission coefficient measured in the laboratory. The obtained results were expected to be better in terms of the resonance of the antennas, however they were satisfactory in terms of the uncoupling. The manufactured antennas are suitable to use on WLAN in an indoor environment.
Small-scale ice-ocean-wave processes and their impact on coupled environmental polar prediction

Here we present an overview of small-scale ice-ocean-wave processes relevant for coupled environmental prediction. Particular examples are taken from global and regional Canadian coupled atmosphere-ice-ocean forecasting systems. These cases demonstrate the importance of coupling for ice infested seas even for short lead times. Key challenges and lessons learnt thus far are discussed.
Auto-tuning stencil codes for cache-based multicore platforms

As clock frequencies have tapered off and the number of cores on a chip has taken off, the challenge of effectively utilizing these multicore systems has become increasingly important. However, the diversity of multicore machines in today's market compels us to individually tune for each platform. This is especially true for problems with low computational intensity, since the improvements in memory latency and bandwidth are much slower than those of computational rates. One such kernel is a stencil, a regular nearest neighbor operation over the points in a structured grid. Stencils often arise from solving partial differential equations, which are found in almost every scientific discipline. In this thesis, we analyze three common three-dimensional stencils: the 7-point stencil, the 27-point stencil, and the Gauss-Seidel Red-Black Helmholtz kernel. We examine the performance of these stencil codes over a spectrum of multicore architectures, including the Intel Clovertown, Intel Nehalem, AMD Barcelona, the highly-multithreaded Sun Victoria Falls, and the low power IBM Blue Gene/P. These platforms not only have significant variations in their core architectures, but also exhibit a 32× range in available hardware threads, a 4.5× range in attained DRAM bandwidth, and a 6.3× range in peak flop rates. Clearly, designing optimal code for such a diverse set of platforms represents a serious challenge. Unfortunately, compilers alone do not achieve satisfactory stencil code performance on this varied set of platforms. Instead, we have created an automatic stencil code tuner, or auto-tuner, that incorporates several optimizations into a single software framework. These optimizations hide memory latency, account for non-uniform memory access times, reduce the volume of data transferred, and take advantage of special instructions. The auto-tuner then searches over the space of optimizations, thereby allowing for much greater productivity than hand-tuning. The fully auto-tuned code runs up to 5.4× faster than a straightforward implementation and is more scalable across cores. By using performance models to identify performance limits, we determined that our auto-tuner can achieve over 95% of the attainable performance for all three stencils in our study. This demonstrates that auto-tuning is an important technique for fully exploiting available multicore resources.
Tidal Analysis Using Time-Frequency Signal Processing and Information Clustering

Geophysical time series have a complex nature that poses challenges to reaching assertive conclusions, and require advanced mathematical and computational tools to unravel embedded information. In this paper, time–frequency methods and hierarchical clustering (HC) techniques are combined for processing and visualizing tidal information. In a first phase, the raw data are pre-processed for estimating missing values and obtaining dimensionless reliable time series. In a second phase, the Jensen–Shannon divergence is adopted for measuring dissimilarities between data collected at several stations. The signals are compared in the frequency and time–frequency domains, and the HC is applied to visualize hidden relationships. In a third phase, the long-range behavior of tides is studied by means of power law functions. Numerical examples demonstrate the effectiveness of the approach when dealing with a large volume of real-world data.
DISPLACEMENT ESTIMATES AND COLLAPSE PREDICTION OF DEGRADING STRUCTURAL SYSTEMS

Seismic code provisions in several countries have recently adopted the new concept of performance-based design. New analysis procedures have been developed to estimate seismic demands for performance evaluation. Most of these procedures are based on simple models, and do not take into account degradation effects, a major factor influencing structural behavior under earthquake excitations. More importantly, most of these models can not predict collapse of structures under seismic loads. This study presents a newly developed model that incorporates degradation effects into seismic analysis of structures. The newly developed model was added to the material library of commercial software for seismic analysis of structural systems. A new energy-based approach is used to define several types of degradation effects. The model also permits collapse prediction of structures under seismic excitations. The model was used to conduct extensive statistical dynamic analysis of different structural systems subjected to a large ensemble of recent earthquake records. Strength levels that subject structures to collapse were identified from the study, for collapse-prevention limit state design purposes. Results were also used to propose approximate methods for estimating maximum inelastic displacements of degrading systems, in case collapse does not occur, for use in performance-based seismic code provisions. The findings provide necessary information for the design evaluation phase of a general performance-based earthquake design process, and could be used for evaluation and modification of existing seismic codes of practice.
Characterisation and Stability of Pigments Extracted from Sargassum binderi Obtained from Semporna, Sabah (Pencirian dan Kestabilan Pigmen yang Diekstrak daripada Sargassum binderi dari Semporna, Sabah)

This study was carried out to identify the pigment extracted from Malaysian brown seaweed, Sargassum binderi and its stability in various conditions. Pigments were extracted using methanol:chloroform:water (4:2:1, v/v/v), which is part of fucoidan extraction process, where the pigments were waste. Carotenoid and chlorophyll were found in the extract using UV-vis spectrophotometer (420 and 672 nm, respectively). Fucoxanthin was identified as the carotenoid present using HPLC, while its functional groups and structure were determined using FTIR and 1 H NMR, respectively. The fucoxanthinrich extract stability was tested on different pH (pH1-13), light exposure (dark and light) and storage temperature (4oC, 25oC and 50oC). The stability tests showed that it was most stable at pH5-7, stored in dark condition and at the storage temperature of 4oC and 25oC. The fucoxanthin-rich extract from Sargassum binderi has potential to be applied as bioingredient and functional food as it is stable in normal storage conditions.
Exploring L2 structural convergence in peer task-based interaction

This study explored the occurrence and characteristics of structural convergence, defined as speakers’ propensity to reuse an underlying syntactic structure to which they have been exposed in recent discourse, and its link to production accuracy in L2 unscripted task-based interactions. Twenty-two English university learners (eleven dyads) with diverse language backgrounds completed two versions of a problem-solving discussion task in two separate sessions. Their video-recorded interactions were transcribed and coded for structural convergence (occurrence, structure types and accuracy). The results showed that participants demonstrated structural convergence in unscripted L2 task-based interactions. They also converged on different structures to varying degrees across the two interaction sessions. In addition, the results also showed an association between structural convergence and production accuracy, with participants producing more correct and incorrect targets when exposed to correct and incorrect primes respectively. These results are discussed in terms of impact of the nature of task interaction on occurrence and characteristics of structural convergence, and the role of structural convergence in L2 production accuracy.
Sorting Nexin 5 Controls Head and Neck Squamous Cell Carcinoma Progression by Modulating FBW7

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer worldwide. Long-term survival rates in patients with HNSCC have not increased significantly in the past 30 years. Therefore, looking for novel molecular targets that control HNSCC progression is urgently required to improve the treatment of HNSCC. Here, we identified Sorting Nexin 5 (SNX5) as a new regulator that plays an oncogenic function in HNSCC progression. Analyzing HNSCC patients' data from the Cancer Genome Atlas (TCGA) indicates that the expression levels of SNX5 in HNSCC are significantly elevated compared to normal tissues. Furthermore, higher SNX5 expression correlates with a worse prognosis for HNSCC patients. These results suggest that SNX5 has an oncogenic role. Consistently, loss of SNX5 in HNSCC cells dramatically reduces colony formation and significantly decreases tumor growth in xenograft mouse models. SNX5 interacts with the tumor suppressor F-box/WD repeat-containing protein 7 (FBW7), an E3 ubiquitin ligase that mediates ubiquitination and degradation of oncoproteins such as c-Myc, NOTCH1, and Cyclin E1. By interacting with FBW7, SNX5 inhibits FBW7-mediated oncoproteins ubiquitination. In this way, SNX5 decreases the FBW7-mediated oncoproteins degradation to promote HNSCC progression.
A FRAMEWORK TO QUANTIFY INDUCED SEISMICITY DUE TO WASTEWATER INJECTION IN OKLAHOMA

A bi-product of hydraulic fracturing is massive quantities of waste fluids, which are routinely injected underground. In regions such as Oklahoma, the injection rates are high enough to alter the poro-elastic stress-field significantly, leading to a sharp increase in seismicity rates. Even though most of the events in Oklahoma are of small size, magnitudes up to 5.8 have been observed. In an attempt to quantify the extent of the problem, we develop a framework for seismic hazard assessment in regions with potentially induced seismicity. The result is a statistical model capable of distinguishing natural/tectonic seismicity from injection-induced seismicity with a certain degree of confidence. It can also be used to forecast seismicity rates, given a scenario for future injection rates. The induced seismicity is assumed to follow a modified version of the GutenbergRichter law, incorporating the Seismogenic Index principles. _________________________________________ PhD student, UME School, School of Advanced Studies IUSS Pavia (email: i.grigoratos@utexas.edu) Research Fellow, University of Texas at Austin Professor, School of Advanced Studies IUSS Pavia Professor, University of Texas at Austin Research Scientist, Bureau of Economic Geology, University of Texas at Austin Grigoratos I, Bazzurro P, Rathje E, Savvaidis A. framework to quantify induced seismicity due to wastewater injection in Oklahoma. Proceedings of the 11 National Conference in Earthquake Engineering, Earthquake Engineering Research Institute, Los Angeles, CA. 2018. Eleventh U.S. National Conference on Earthquake Engineering Integrating Science, Engineering & Policy June 25-29, 2018 Los Angeles, California A framework to quantify induced seismicity due to wastewater injection in Oklahoma Iason Grigoratos, Paolo Bazzurro, Ellen Rathje, Alexandros Savvaidis
Folksonomies as Document Summary Engines A Study of Delicious.com Tagging Behaviour.

Folksonomies like Delicious.com’s tagging ecosystem ostensibly offer a ready supply of human-reviewed text and summary information. The manually assigned tags in folksonomies can be seen as the manual counterpart to key words in corpus linguistics that are extracted automatically through tools such as WordSmith (Scott (1996)) and Wmatrix (Rayson (2008)). This paper examines the Delicious.com social bookmarking service to assess the extent to which tag-based folksonomies of documents represent information already accessible using existing information retrieval metrics. The metrics compared include ﬁve different information retrieval measures (Log-Likelihood, TFIDF, RFR, WordNet synonym connectedness and position of ﬁrst occurrence), as well as two measures derived from tags themselves. We perform multiple keyword analyses, comparing the results of each against the manual tag selection through dimensionality reduction using principal component analysis. We then go on to ﬁt classiﬁers to identify tags from keyword selections, and critique the quality of these classiﬁers’ output. We ﬁnd that log-likelihood is the single best indicator of manual tag selection, and that improving the classiﬁcation model by inclusion of other metrics provides only modest improvements in exchange for large increases in complexity.
DYNAMIC BEHAVIOR OF EMBANKMENT DAM ON LIQUEFIABLE FOUNDATION SUBJECT TO MODERATE EARTHQUAKE LOADING

Liquefaction-induced ground displacements resulting from earthquake shaking are a major threat to the stability of earth dams comprising of, or underlain by, loose saturated granular soils. Many liquefaction induced earth dam failures or near-failures have been reported around the world during various earthquakes. Such embankment damages were particularly destructive when the underlying saturated granular soils liquefied, resulting in cracking, settlement, lateral spreading, and slumping of the embankment.
A minimally supervised approach for question generation : what can we learn from a single seed ?

In this paper, we investigate how many quality natural language questions can be generated from a single question/answer pair (a seed). In our approach we learn patterns that relate the various levels of linguistic information in the question/answer seed with the same levels of information in text. These patterns contain lexical, syntactic and semantic information and when matched against a target document, new question/answer pairs can be generated. Here, we focus specifically on the task of generating questions. Several works, for instance in Question Answering, explore the re-writing of questions to create (usually lexical) patterns; instead, we use several levels of linguistic information – lexical, syntactic and semantic (through the use of named entities). Also, the patterns are commonly hand-crafted, as opposed to our strategy where patterns are automatically learned, based on a single seed. Preliminary results show that with the single question/answer seed pair – “When was Leonardo da Vinci Born? ”/1452 – we manage to generate several questions (from documents related with 25 personalities), from which 80% were evaluated as plausible.
Customer interactions on social media and their impact on trust and loyalty: the moderating role of product learning

Article history: Received: April 5, 2019 Received in revised format: April 19 2019 Accepted: May 2, 2019 Available online: May 5, 2019 This research examines the customer engagement on social media platforms in the tourism industry and its effect on customer loyalty through the mediated effect of customer trust. Furthermore, the moderating role of product learning is investigated on the hypothesized relationships. Data was collected from guests in 5 stars hotels in Kyrenia region in Northern Cyprus. In this study, out of the 459 collected surveys, only 419 were analyzed due to missing or incomplete data. The analysis conducted here followed the two step approach for structure equations modelling. Firstly, a confirmatory factor analysis was appraised to prepare data for structural model. Then the structural model helped shape our direct hypothesis testing, before analyzing the mediating and moderating impacts. The data provided evidence to link customer interactions on social media with trust and loyalty (Hypotheses 1-3) while trust revealed a mediating effect between interaction and loyalty. Finally, product learning did have an empowering impact on the relationship between interaction and trust. © 2019 by the authors; licensee Growing Science, Canada
UPDATING AN LU FACTORIZATION AND ITS APPLICATION TO SCALABLE OUT-OF-CORE COMPUTATION

We show how to compute an LU factorization of a matrix when the factors of a leading principle submatrix are already known. The approach incorporates pivoting akin to partial pivoting, a strategy we call incremental pivoting. A practical, scalable out-of-core implementation of the LU factorization that maintains reasonable numerical stability is built upon the result. Here we use the term scalable to mean that performance is maintained as the matrix size grows well beyond available (in-core) memory. By practical we mean that the implementation achieves high performance. The resulting method enables the solution of large-scale problems using limited computational resources and/or reduces the cost of an architecture by reducing the amount of memory that needs to be purchased. An implementation using the Formal Linear Algebra Methods Environment (FLAME) Application Programming Interface (API) is described. Experimental results demonstrate high performance on an Intel Itanium2 based server.