Search results for: parallel corpus

Authors: C. F. Ocoleanu, A. I. Dolan, G. Cividjian, S. Teodorescu

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In this paper we make a temperature investigations in two type of superposed crimped connections using experimental determinations. All the samples use 8 copper wire 7.1 x 3 mm2 crimped by two methods: the first method uses one crimp indents and the second is a proposed method with two crimp indents. The ferrule is a parallel one. We study the influence of number and position of crimp indents. The samples are heated in A.C. current at different current values until steady state heating regime. After obtaining of temperature values, we compare them and present the conclusion.

Keywords: crimped connections, experimental determinations, temperature, heat transfer

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Authors: Nurul Jamilah Binti Rosly

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The typology of motion must be understood as a change from one location to another. But from a conceptual point of view, motion can also occur in non-spatial contexts associated with human and social factors. Therefore, from the conceptual point of view, the concept of non-spatial motion involves the movement of time, ownership, identity, state, and existence. Accordingly, this study will focus on the lexical as shared, accept, be, store, and exist as the study material. The data in this study were extracted from the Database of Languages and Literature Corpus Database, Malaysia, which was analyzed using semantics and syntax concepts using Conceptual Structure Theory - Ray Jackendoff (2002). Semantic representations are represented in the form of conceptual structures in argument functions that include functions [events], [situations], [objects], [paths] and [places]. The findings show that the mapping of these arguments comprises three main stages, namely mapping the argument structure, mapping the tree, and mapping the role of thematic items. Accordingly, this study will show the representation of non- spatial Malay language areas.

Keywords: arguments, concepts, constituencies, events, situations, thematics

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Authors: Adeline Stals

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The transformation of architectural design practices has been underway for almost forty years due to the development and democratization of computer technology. New and more efficient tools are constantly being proposed to architects, amplifying a technological wave that sometimes stimulates them, sometimes overwhelms them, depending essentially on their digital culture and the context (socio-economic, structural, organizational) in which they work on a daily basis. Our focus is on VR, AR, and MR technologies dedicated to architecture. The commercialization of affordable headsets like the Oculus Rift, the HTC Vive or more low-tech like the Google CardBoard, makes it more accessible to benefit from these technologies. In that regard, researchers report the growing interest of these tools for architects, given the new perspectives they open up in terms of workflow, representation, collaboration, and client’s involvement. However, studies rarely mention the consequences of the sample studied on results. Our research provides an overview of VR, AR, and MR researches among a corpus of papers selected from conferences and journals. A closer look at the sample of these research projects highlights the necessity to take into consideration the context of studies in order to develop tools truly dedicated to the real practices of specific architect profiles. This literature review formalizes milestones for future challenges to address. The methodology applied is based on a systematic review of two sources of publications. The first one is the Cumincad database, which regroups publications from conferences exclusively about digital in architecture. Additionally, the second part of the corpus is based on journal publications. Journals have been selected considering their ranking on Scimago. Among the journals in the predefined category ‘architecture’ and in Quartile 1 for 2018 (last update when consulted), we have retained the ones related to the architectural design process: Design Studies, CoDesign, Architectural Science Review, Frontiers of Architectural Research and Archnet-IJAR. Beside those journals, IJAC, not classified in the ‘architecture’ category, is selected by the author for its adequacy with architecture and computing. For all requests, the search terms were ‘virtual reality’, ‘augmented reality’, and ‘mixed reality’ in title and/or keywords for papers published between 2015 and 2019 (included). This frame time is defined considering the fast evolution of these technologies in the past few years. Accordingly, the systematic review covers 202 publications. The literature review on studies about XR technologies establishes the state of the art of the current situation. It highlights that studies are mostly based on experimental contexts with controlled conditions (pedagogical, e.g.) or on practices established in large architectural offices of international renown. However, few studies focus on the strategies and practices developed by offices of smaller size, which represent the largest part of the market. Indeed, a European survey studying the architectural profession in Europe in 2018 reveals that 99% of offices are composed of less than ten people, and 71% of only one person. The study also showed that the number of medium-sized offices is continuously decreasing in favour of smaller structures. In doing so, a frontier seems to remain between the worlds of research and practice, especially for the majority of small architectural practices having a modest use of technology. This paper constitutes a reference for the next step of the research and for further worldwide researches by facilitating their contextualization.

Keywords: architectural design, literature review, SME, XR technologies

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Authors: David Tresner-Kirsch

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Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

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Authors: Nirmal Yadav, Tanuja Srivastava

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Shannon theory is an exact method to recover a band limited signals from its sampled values in discrete implementation, using sinc interpolators. But sinc based results are not much satisfactory for band-limited calculations so that convolution with window function, having compact support, has been introduced. Convolution Backprojection algorithm with window function is an approximation algorithm. In this paper, the error has been calculated, arises due to this approximation nature of reconstruction algorithm. This result will be defined for fan beam projection data which is more faster than parallel beam projection.

Keywords: computed tomography, convolution backprojection, radon transform, fan beam

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Kari Bjorn

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Team learning has been studied and modeled as double loop model and its variations. Also, metacognition has been suggested as a concept to describe the nature of team learning to be more than a simple sum of individual learning of the team members. Team learning has a positive correlation with both individual motivation of its members, as well as the collective factors within the team. Team learning of previously very independent members of two teaching teams is analyzed. Applied Science Universities are training future professionals with ever more diversified and multidisciplinary skills. The size of the units of teaching and learning are increasingly larger for several reasons. First, multi-disciplinary skill development requires more active learning and richer learning environments and learning experiences. This occurs on students teams. Secondly, teaching of multidisciplinary skills requires a multidisciplinary and team-based teaching from the teachers as well. Team formation phases have been identifies and widely accepted. Team role stress has been analyzed in project teams. Projects typically have a well-defined goal and organization. This paper explores team stress of two teacher teams in a parallel running two course units in engineering education. The first is an Industrial Automation Technology and the second is Development of Medical Devices. The courses have a separate student group, and they are in different campuses. Both are run in parallel within 8 week time. Both of them are taught by a group of four teachers with several years of teaching experience, but individually. The team role stress scale items - the survey is done to both teaching groups at the beginning of the course and at the end of the course. The inventory of questions covers the factors of ambiguity, conflict, quantitative role overload and qualitative role overload. Some comparison to the study on project teams can be drawn. Team development stage of the two teaching groups is different. Relating the team role stress factors to the development stage of the group can reveal the potential of management actions to promote team building and to understand the maturity of functional and well-established teams. Mature teams indicate higher job satisfaction and deliver higher performance. Especially, teaching teams who deliver highly intangible results of learning outcome are sensitive to issues in the job satisfaction and team conflicts. Because team teaching is increasing, the paper provides a review of the relevant theories and initial comparative and longitudinal results of the team role stress factors applied to teaching teams.

Keywords: engineering education, stress, team role, team teaching

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Authors: Ahmed Elaksher, Islam Omar

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For many years, Mars surface has been a mystery for scientists. Lately with the help of geospatial data and photogrammetric procedures researchers were able to capture some insights about this planet. Two of the most imperative data sources to explore Mars are the The High Resolution Imaging Science Experiment (HiRISE) and the Mars Orbiter Laser Altimeter (MOLA). HiRISE is one of six science instruments carried by the Mars Reconnaissance Orbiter, launched August 12, 2005, and managed by NASA. The MOLA sensor is a laser altimeter carried by the Mars Global Surveyor (MGS) and launched on November 7, 1996. In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images for generating a more accurate and trustful surface of Mars. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. In this project, we employed three different 3D to 2D transformation models. These are the parallel projection (3D affine) transformation model; the extended parallel projection transformation model; the Direct Linear Transformation (DLT) model. A set of tie-points was digitized from both datasets. These points were split into two sets: Ground Control Points (GCPs), used to evaluate the transformation parameters using least squares adjustment techniques, and check points (ChkPs) to evaluate the computed transformation parameters. Results were evaluated using the RMSEs between the precise horizontal coordinates of the digitized check points and those estimated through the transformation models using the computed transformation parameters. For each set of GCPs, three different configurations of GCPs and check points were tested, and average RMSEs are reported. It was found that for the 2D transformation models, average RMSEs were in the range of five meters. Increasing the number of GCPs from six to ten points improve the accuracy of the results with about two and half meters. Further increasing the number of GCPs didn’t improve the results significantly. Using the 3D to 2D transformation parameters provided three to two meters accuracy. Best results were reported using the DLT transformation model. However, increasing the number of GCPS didn’t have substantial effect. The results support the use of the DLT model as it provides the required accuracy for ASPRS large scale mapping standards. However, well distributed sets of GCPs is a key to provide such accuracy. The model is simple to apply and doesn’t need substantial computations.

Keywords: mars, photogrammetry, MOLA, HiRISE

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Authors: Sakhon Woothipatanapan, Surasit Prakobkit

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This paper presents a model for analysis the induced voltage of transmission lines (energized) acting on neighboring distribution lines (de-energized). From environmental restrictions, 22 kV distribution lines need to be installed under 115 kV transmission lines. With the installation of the two parallel circuits like this, they make the induced voltage which can cause harm to operators. This work was performed with the ATP-EMTP modeling to analyze such phenomenon before field testing. Simulation results are used to find solutions to prevent danger to operators who are on the pole.

Keywords: transmission system, distribution system, induced voltage, off-line operation

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Authors: Lily Chimuanya, Esther Ajiboye, Emmanuel Uba

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One of the consequences of online communication is the birth of new orthography genres characterised by novel conventions of abbreviation and acronyms usually referred to as Netspeak. Netspeak, also known as internet slang, is a style of writing mainly used in online communication to limit the length of text characters and to save time. The aim of this study is to evaluate how second language users of the English language have internalised this new convention of writing; identify the recurrent patterns of Netspeak; and assess the consistency of the use of the identified patterns in relation to their meanings. The study is corpus-based, and data drawn from WhatsApp chart pages of selected groups of Nigerian English speakers show a large occurrence of inconsistencies in the patterns of Netspeak and their meanings. The study argues that rather than emphasise the negative impact of Netspeak on the communicative competence of second language users, studies should focus on suggesting models as yardsticks for standardising the usage of Netspeak and indeed all other emerging language conventions resulting from online communication. This stance stems from the inevitable global language transformation that is eminent with the coming of age of information technology.

Keywords: abbreviation, acronyms, Netspeak, online communication, standardisation

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Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

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Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

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Authors: Tahar Alimi, Rahma Boujelbane, Wiem Derouich, Lamia Hadrich Belguith

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Machine translation task of low-resourced languages such as Arabic is a challenging task. Despite the appearance of sophisticated models based on the latest deep learning techniques, namely the transfer learning and transformers, all models prove incapable of carrying out an acceptable translation which includes Arabic dialects because they not official status. In this paper, a machine translation model designed to translate Arabic multidialectal content into Modern Standard Arabic (MSA), leveraging both new and existing parallel resources. The latter achieved the best results for both Levantine and Maghrebi dialects with BLEU score of 64.99.

Keywords: Arabic translation, dialect translation, fine-tune, msa translation, transformer, translation

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Authors: A. M. Sagir

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This paper derived four newly schemes which are combined in order to form an accurate and efficient block method for parallel or sequential solution of third order ordinary differential equations of the form y^'''= f(x,y,y^',y^'' ), y(α)=y_0,〖y〗^' (α)=β,y^('' ) (α)=μ with associated initial or boundary conditions. The implementation strategies of the derived method have shown that the block method is found to be consistent, zero stable and hence convergent. The derived schemes were tested on stiff and non-stiff ordinary differential equations, and the numerical results obtained compared favorably with the exact solution.

Keywords: block method, hybrid, linear multistep, self-starting, third order ordinary differential equations

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Authors: Suzi M. S. Cavalari, Tim Lewis

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Teletandem is a bilingual model of virtual exchange in which two partners from different countries( and speak different languages) meet synchronously and regularly over a period of 8 weeks to learn each other’s mother tongue (or the language of proficiency). At São Paulo State University (UNESP), participants should answer a questionnaire before starting the exchanges in which one of the questions refers to setting a goal to be accomplished with the help of the teletandem partner. In this context, the present presentation aims to examine the goal-setting activity of 79 Brazilians who participated in Portuguese-English teletandem exchanges over a period of four years (2012-2015). The theoretical background is based on goal setting and self-regulated learning theories that propose that appropriate efficient goals are focused on the learning process (not on the product) and are specific, proximal (short-term) and moderately difficult. The data set used was 79 initial questionnaires retrieved from the MulTeC (Multimodal Teletandem Corpus). Results show that only approximately 10% of goals can be considered appropriate. Features of these goals are described in relation to specificities of the teletandem context. Based on the results, three mechanisms that can help learners to set attainable goals are discussed.

Keywords: foreign language learning, goal setting, teletandem, virtual exchange

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Authors: Bineet Kumar

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Many civil engineering infrastructures frequently encounter repetitive loading during their service life. Due to the inherent complexity observed in concrete, like quasi-brittle materials, understanding the fatigue behavior in concrete still posesa challenge. Moreover, the fracture process zone characteristics ahead of the crack tip have been observed to be different in fatigue loading than in the monotonic cases. Therefore, it is crucial to comprehend the energy dissipation associated with the fracture process zone (FPZ) due to repetitive loading. It is well known that stiffness degradation due to cyclic loadingprovides a better understanding of the fracture behavior of concrete. Under repetitive load cycles, concrete members exhibit a two-stage stiffness degradation process. Experimentally it has been observed that the stiffness decreases initially with an increase in crack length and subsequently increases. In this work, an attempt has been made to propose an analytical expression to predict energy dissipation and later the stiffness degradation as a function of crack length. Three-point bend specimens have been considered in the present work to derive the formulations. In this approach, the expression for the resultant stress distribution below the neutral axis has been derived by correlating the bending stress with the cohesive stresses developed ahead of the crack tip due to the existence of the fracture process zone. This resultant stress expression is utilized to estimate the dissipated energydue to crack propagation as a function of crack length. Further, the formulation for the stiffness degradation has been developed by relating the dissipated energy with the work done. It can be used to predict the critical crack length and fatigue life. An attempt has been made to understand the influence of stress amplitude on the damage pattern by using the information on the rate of stiffness degradation. It has been demonstrated that with the increase in the stress amplitude, the damage/FPZ proceeds more in the direction of crack propagation compared to the damage in the direction parallel to the span of the beam, which causes a lesser rate of stiffness degradation for the incremental crack length. Further, the effect of loading frequency has been investigated in terms of stiffness degradation. Under low-frequency loading cases, the damage/FPZ has been found to spread more in the direction parallel to the span, in turn reducing the critical crack length and fatigue life. In such a case, a higher rate of stiffness degradation has been observed in comparison to the high-frequency loading case.

Keywords: fatigue life, fatigue, fracture, concrete

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Mingshu Liu, Laura Santamaria, Xavier Carmaniu Mainadé

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As one of the sectors most affected by the COVID-19 pandemic, tourism is facing challenges in revitalizing the industry. But at the same time, it would be a good opportunity to take advantage of digital communication as an effective tool for tourism promotion. Our proposal aims to verify the linguistic operations on online platforms in China. The research is carried out based on the theory of Eco-traductology put forward by Gengshen Hu, whose contribution focuses on the translator's adaptation to the ecosystem environment and the three elaborated parameters (linguistic, cultural and communicative). We also relate it to Even-Zohar's and Toury's theoretical postulates on the Polysystem to elaborate on interdisciplinary methodology. Such a methodology allows us to analyze personal treatments and phraseology in the target text. As for the corpus, we adopt the official Spanish-language website of Turismo de España as the source text and the postings on the two major social networks in China, Weibo and Wechat, in 2019. Through qualitative analysis, we conclude that, in the tourism advertising campaign on Chinese social networks, chengyu (Chinese phraseology) and honorific titles are used very frequently.

Keywords: digital communication, eco-traductology, polysystem theory, tourism advertising

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Authors: Mauricio Plaza, Willian Aperador

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Hip disarticulation is an amputation through the hip joint capsule, removing the entire lower extremity, with a closure of the remaining musculature over the exposed acetabulum. Tumors of the distal and proximal femur were treated by total femur resection; a hip disarticulation sometimes is a performance for massive trauma with crush injuries to the lower extremity. This article discusses the design a system for rehabilitation of a patient with bilateral hip disarticulations. The prosthetics designed allowed the patient to do natural gait suspended between parallel articulate crutches with the body weight support between the crutches. The care of this patient was a challenge due to bilateral amputations at such a high level and the special needs of a patient mobility.

Keywords: amputation, prosthesis, mobility, hemipelvectomy

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Behnoush Sabayan, Ali Alidadi, Saeid Ebarhimi, N. M. Bakhshani

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Hemodialysis (HD) patients are at a high risk of atherosclerotic and vascular disease; also little information is available for the HD impact on brain structure of these patients. We studied the brain abnormalities in HD patients. The aim of this study was to investigate the effect of long term HD on brain structure of HD patients. Non-contrast MRI was used to evaluate imaging findings. Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% were female. According to study, HD patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had small vessel ischemia than the HD patients who underwent HD for a shorter term, which the median time was 3 to 5 months. Most of the small vessel ischemia was located in pre-ventricular, subcortical and white matter (1.33± .471, 1.23± .420 and 1.39±.490). However, the other brain damages like: central pons abnormality, global brain atrophy, thinning of corpus callosum and frontal lobe atrophy were found (P<0.01). The present study demonstrated that HD patients who were under HD for a longer time had small vessel ischemia and we conclude that this small vessel ischemia might be a causative mechanism of brain atrophy in chronic hemodialysis patients. However, additional researches are needed in this area.

Keywords: Hemodialysis Patients, Duration of Hemodialysis, MRI, Zahedan

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Authors: Ferhat Yilmaz

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Defense sector is one of the most important areas where logistics is used extensively. Nations give importance to their defense spending in order to survive in their geography. Parallel to the rising crises around the world, governments increase their defense spending; however, resources are limited while the needs are infinite. Therefore, countries try to develop a more effective use of their defense budget. In order to make logistics more effective and efficient, performance- based logistical system was developed. This article tries to explain the Performance-based Logistical System, its employment process, employment areas, and how it will be used along with other main systems in the Turkey.

Keywords: performance, performance based logistics applications, logistical system, Turkey

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Authors: Cristian Sirbu-Dragomir, Stefan-Mihai Sofian, Adrian Predescu

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This paper aims to study Tesla pumps for circulating biofluids. It is desired to make a small pump for the circulation of biofluids. This type of pump will be studied because it has the following characteristics: It doesn’t have blades which results in very small frictions; Reduced friction forces; Low production cost; Increased adaptability to different types of fluids; Low cavitation (towards 0); Low shocks due to lack of blades; Rare maintenance due to low cavity; Very small turbulences in the fluid; It has a low number of changes in the direction of the fluid (compared to rotors with blades); Increased efficiency at low powers.; Fast acceleration; The need for a low torque; Lack of shocks in blades at sudden starts and stops. All these elements are necessary to be able to make a small pump that could be inserted into the thoracic cavity. The pump will be designed to combat myocardial infarction. Because the pump must be inserted in the thoracic cavity, elements such as Low friction forces, shocks as low as possible, low cavitation and as little maintenance as possible are very important. The operation should be performed once, without having to change the rotor after a certain time. Given the very small size of the pump, the blades of a classic rotor would be very thin and sudden starts and stops could cause considerable damage or require a very expensive material. At the same time, being a medical procedure, the low cost is important in order to be easily accessible to the population. The lack of turbulence or vortices caused by a classic rotor is again a key element because when it comes to blood circulation, the flow must be laminar and not turbulent. The turbulent flow can even cause a heart attack. Due to these aspects, Tesla's model could be ideal for this work. Usually, the pump is considered to reach an efficiency of 40% being used for very high powers. However, the author of this type of pump claimed that the maximum efficiency that the pump can achieve is 98%. The key element that could help to achieve this efficiency or one as close as possible is the fact that the pump will be used for low volumes and pressures. The key elements to obtain the best efficiency for this model are the number of rotors placed in parallel and the distance between them. The distance between them must be small, which helps to obtain a pump as small as possible. The principle of operation of such a rotor is to place in several parallel discs cut inside. Thus the space between the discs creates the vacuum effect by pulling the liquid through the holes in the rotor and throwing it outwards. Also, a very important element is the viscosity of the liquid. It dictates the distance between the disks to achieve a lossless power flow.

Keywords: lubrication, temperature, tesla-pump, viscosity

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Authors: Deva Kanta Phukan

Abstract:

An attempt is made where an electrically conducting fluid is injected from a fixed outer cylindrical casing onto an inner moving cylindrical rod. A magnetic field is applied parallel to the axis of the cylindrical rod. The basic governing set of partial differential equations for conservation of mass and momentum are reduced to a set of non-linear ordinary differential equation by introducing similarity transformation, which are integrated numerically. A perturbation solution for the case of large magnetic parameter is derived for constant Reynolds number.

Keywords: annular axi-symmetric stagnation flow, conducting fluid, magnetic field, moving cylinder

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Authors: Masoud Hassanzade Novin, Bahloul Salmani

Abstract:

The process of the translation is not merely the linguistic aspects. It is also considered in the cultural framework of both the source and target text cultures. The translation process and translated texts are confronted the new aspect in 20th century which is considered mostly in the patronage framework and ideological grillwork of the target language. To have these factors scrutinized in the process of the translation both micro-element factors and macro-element factors can be taken into consideration. For the purpose of this study through a qualitative type of research based on critical discourse analysis approach, the case study of the novel “1984” written by George Orwell was chosen as the corpus of the study to have the contrastive analysis by its Persian translated texts. Results of the study revealed some distortions embedded in the target texts which were overshadowed by ideological aspect and patronage network. The outcomes of the manipulated terms were different in various categories which revealed the manipulation aspects in the texts translated.

Keywords: critical discourse analysis, ideology, patronage network, translated texts

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Authors: Amira Zouaoui, Hamed Belloumi, Ferid Kourda

Abstract:

This paper presents the analysis and design of a DC–AC resonant converter applied to induction heating. The proposed topology based on the series-parallel half-bridge resonant inverter is described. It can operate with Zero-Voltage Switching (ZVS). At the resonant frequency, the secondary current is amplified over the heating coil with small switching angle, which keeps the reactive power low and permits heating with small current through the resonant inductor and the transformer. The operation and control principle of the proposed high frequency inverter is described and verified through simulated and experimental results.

Keywords: induction heating, inverter, high frequency, resonant

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Authors: Raquel Rossini, Edelvais Caldeira

Abstract:

The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko

Abstract:

The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.

Keywords: sparse matrix, compressed format, Hubbard model, Anderson model

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

Abstract:

We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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