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LSTM vs. GRU for Arabic Machine Translation 1

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12th International Conference on Soft computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020

作者： Bensalah, Nouhaila Ayad, Habib Adib, Abdellah Ibn El Farouk, Abdelhamid Team Networks Telecoms and Multimedia University of Hassan II Casablanca Casablanca20000 Morocco Teaching Languages and Cultures Laboratory Mohammedia Casablanca Morocco

ISBN: (数字)9783030736897

ISBN: (纸本)9783030736880

The same Machine Translation (MT) approach may not work for European languages as for Arabic, because of its structure. MT based on Neural Networks methods has recently become an alternative approach to the statistical MT. In this paper, a case study is presented on how different sequence to sequence Deep Learning (DL) models perform in the task of Arabic MT. A comprehensive comparison between these models based mainly on: Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional LSTM (BiLSTM) and Bidirectional GRU (BiGRU) is presented. Specifically, each input sequence will be translated into English one using an Encoder-Decoder model based on the four architectures with an attention mechanism. Furthermore, we study the impact of different preprocessing techniques on Arabic MT. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Educational Technological Game for Children's Education

Educational Technological Game for Children's Education

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4th International Conference on intelligent Human systems Integration (IHSI) - Integrating People and intelligent systems

作者： Condor-Herrera, Dmar Ramos-Galarza, Carlos Univ Tecnol Indoamer Ctr Invest Mecatron & Sistemas Interact MIST Carrera Psicol Educ Menc Innovac & Liderazgo Educ Av Machala & Sabanilla Quito Ecuador Pontificia Univ Catolica Ecuador Fac Psicol Av 12 Octubre & Roca Quito Ecuador

ISBN: (纸本)9783030680176;9783030680169

The teaching process in the infant stage is a challenge for the current educational process since children need the use of resources that are consistent with the reality in which they live today. In this context, the ways of teaching have evolved thanks to technological progress, which has led to the emergence of new teaching methodologies, including gamification, which uses the structure of the game for an educational purpose supported by the use of technology for the creation of didactic resources, which due to their structure and design are of great interest to students. Therefore, in this article, the conceptual development of a serious game for teaching natural sciences based on gamification based on the use of technology is presented.

关键词： Gamification Student-centered learning Teaching strategies Serious games

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Human Centered Design in One New Hospital in Canada: A Lived Experience of Healthcare Professionals

Human Centered Design in One New Hospital in Canada: A Lived...

引用

4th International Conference on intelligent Human systems Integration (IHSI) - Integrating People and intelligent systems

作者： Hammouni, Zakia Poldma, Tiiu Univ Montreal Succursale Ctr Ville Montreal PQ 6128 Canada Ctr Interdisciplinary Rehabil Res Greater Montrea Montreal PQ Canada

ISBN: (纸本)9783030680176;9783030680169

Using a constructivist approach, this study focuses on how the design and the physical environment of one contemporary hospital in Canada are perceived by the healthcare professionals and how these factors affect their work and their well-being. Data was collected by observing the physical setting and healthcare professionals' behavior and included semi-structured interviews of 44 healthcare professionals of two care units during 3 months in 2018. The analysis is based on both comparative and interpretive approaches. Results showed that this physical environment is supportive of the work of healthcare professionals and, keeping in mind the linear spatial organization and decentralized layout, this study highlights the importance of adapting the organizational and management system to the spatial configuration of care units in order to achieve the performance and the well-being of these healthcare professionals.

关键词： Human centred design Technology Physical environment Healthcare professionals Lived experience

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Classification of Metabolic Pathways Using Machine Learning Techniques 1

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11th International Conference on Innovations in Bio-Inspired computing and Applications, IBICA 2020 and 10th World Congress on Information and Communication Technologies, WICT 2020

作者： Dongardive, Jyotshna Jamkhedkar, Suruchi University Department of Computer Science University of Mumbai Mumbai400098 India University Department of Life Sciences University of Mumbai Mumbai400098 India

ISBN: (数字)9783030736033

ISBN: (纸本)9783030736026

The metabolic network consists of several metabolic pathways. Classifying metabolic pathways is a subtask of the larger task of reconstructing the whole metabolic network from a genome. In present study an attempt has been made to detect various pathways in cancer and viral infections using machine learning techniques. The data was collected from metabolic networks of six different types of cancer pathways and viral infections pathways known to cause cancer in humans listed in KEGG PATHWAY database. Five different machine learning classifier techniques were applied to determine the accuracy of the classification in these two datasets. The overall results suggest that these classifiers could be able to give a range of accuracy of 71%–72% in both the dataset with a range between 50% to 100% accuracy. The results reveal that Random forest gives the highest accuracy in six out of twelve datasets followed by Decision tree. Therefore, this indicates that Random forest technique and the proposed method might be efficient in classifying the cancer and viral metabolic pathways in the present study. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Subspace Guided Collaborative Clustering Based on Optimal Transport 1

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12th International Conference on Soft computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020

作者： Ben-Bouazza, Fatima-Ezzahraa Bennani, Younès Touzani, Abdelfettah Cabanes, Guénaël LIPN UMR 7030 CNRS Université Sorbonne Paris Nord Villetaneuse France LaMSN La Maison des Sciences Numériques Saint Denis France LAMA-FSDM Université Sidi Mohamed Ben Abdellah Fes Morocco

ISBN: (数字)9783030736897

ISBN: (纸本)9783030736880

Collaborative clustering is a promising approach in the learning from other learners research area. Although extensive research have been done to improve the collaborative approaches, they still suffer from several issues, including the mechanism of exchanging the information and how to measure the quality of this information. In this paper we introduce a new model of collaboration guided by feature selection, where the main idea is to choose the features that give the best representation for each collaborator and guarantee the communication between them, while preserving the privacy of each collaborator. Collaborative clustering will be developed within the framework of the theory of optimal transport. Indeed, this theory offers a formalism that is highly adapted to collaboration between members of a set of collaborators. Extensive experiments were conducted on multiple data-sets to evaluate the proposed approach and demonstrate its utility. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Clustering algorithms

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Mining Time-Stamped Electronic Health Records with Referenced Sequences 1

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Future of Information and Communication Conference, FICC 2021

作者： Woods, Anne Meyer, Craig Sauer, Brian Cohen, Beth Northern California Institute for Research and Education San FranciscoCA94121 United States Department of Medicine University of California San Francisco San FranciscoCA United States Department of Internal Medicine Division of Epidemiology University of Utah Salt Lake CityUT United States

ISBN: (数字)9783030731038

ISBN: (纸本)9783030731021

Electronic Health Records (EHRs) are typically stored as time-stamped encounter records. Judicious interpretation of temporal relationship between medical records is an integral part of assessing clinical information. Analogously, data analyzed by statistical or data mining methods need to contain time-interdependent analysis variables (TIAVs), whose values represent the clinical embodiment to be investigated. Unlike directly measured data, TIAV formulation is an iterative collaboration between programmer and investigator. This is because clinical TIAVs are context specific and often not absolute, and a custom program is needed to create and assess TIAVs. With rapidly growing interest in mining EHRs, there is a need for scalable solutions to optimize TIAV generation. We describe a framework of using sequences of time-referenced entities as building blocks. Scripts of simple functions are used with these entities to create TIAVs that incorporates multiple interdependencies, hence reducing the need for custom programs. We provide three examples to illustrate the principles of this method using the Veterans Health Administration’s EHR data. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Iterative methods

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A Memetic Random Key Algorithm for the Balanced Travelling Salesman Problem 1

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Metaheuristics Summer School, MESS 2018

作者： Aslan, Ayse University of Groningen Groningen9747 Netherlands

ISBN: (数字)9783030685201

ISBN: (纸本)9783030685195

This paper considers a variant of the well-known travelling salesman problem. In this variant, the cost of travelling from a vertex to another is an arbitrary value on the real line and the objective is finding a tour with minimum absolute value cost. We propose a memetic random key algorithm for this problem and experiment with different settings of the algorithm. The experiments explore the use of a flexible decoding mechanism and also the frequency of applying local search within the random key algorithm. © Springer Nature Switzerland AG 2021.

关键词： Traveling salesman problem

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Gender Equality: An Exploratory Qualitative Study of Social Representations on Existing Practices and Dynamics in Four Municipalities of Baixo Alentejo, Portugal 1

引用

5th World Conference on Qualitative Research, WCQR 2021

作者： Ferro, Lisa Saúde, Sandra Sustainable Development and Entrepreneurship Polytechnic Institute of Beja Beja Portugal Beja Portugal

ISBN: (数字)9783030701871

ISBN: (纸本)9783030701864

Portugal assumed gender equality as one of its strategic priorities in the process of implementing the 2030 Agenda – Sustainable Development Goals. Although strategies and actions have increased and diversified over the years, the latest official reports reveal that equality between men and women in several fields does not go beyond a formal status. The qualitative study developed explores and characterizes the social representations of local key actors on the meaning, domains and practices and dynamics to promote gender equality in four municipalities of Baixo Alentejo, taking five local action framework documents and nine in-depth interviews as sources. With the combined use of T-Lab and webQDA software tools (Computer-Assisted Qualitative Data Analysis Software), a thematic content analysis was carried out on the corpus formed by: 1) the textual sections related to gender equality contained in the documents and 2) the transcriptions of responses. The most repeated keywords were identified with T-Lab and a "word association" analysis was performed. With webQDA, the thematic content analysis was organized by categories and subcategories which allowed the structuring elements of the social representations on gender equality that emerged from the analysed corpus to be identified and interpreted. The analysis reveals an incomplete approach to gender equality in terms of local practices and dynamics, as the intervention is mainly focused on domestic violence. Despite the normative framework and policy guidelines, most key actors lack knowledge regarding some gender equality problems and domains and fail to identify evidences of inequality, which negatively influences the implemented action plans. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Dynamics

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A Data-Driven Dynamic Discretization Framework to Solve Combinatorial Problems Using Continuous Metaheuristics 1

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11th International Conference on Innovations in Bio-Inspired computing and Applications, IBICA 2020 and 10th World Congress on Information and Communication Technologies, WICT 2020

作者： Cisternas-Caneo, Felipe Crawford, Broderick Soto, Ricardo de la Fuente-Mella, Hanns Tapia, Diego Lemus-Romani, José Castillo, Mauricio Becerra-Rozas, Marcelo Paredes, Fernando Misra, Sanjay Pontificia Universidad Católica de Valparaíso Valparaíso Chile Universidad Diego Portales Santiago Chile Covenant University Ota Nigeria

ISBN: (数字)9783030736033

ISBN: (纸本)9783030736026

Combinatorial optimization problems are very common in the real world but difficult to solve. Among the promising algorithms that have been successful in solving these problems are metaheuristics. The two basic search behaviors used in metaheuristics are exploration and exploitation, and the success of metaheuristic search largely depends on the balance of these two behaviors. Machine learning techniques have provided considerable support to improve data-driven optimization algorithms. One of the techniques that stands out is Q-Learning, which is a reinforcement learning technique that penalizes or rewards actions according to the consequence it entails. In this work, a general discretization framework is proposed where Q-Learning can adapt a continuous metaheuristic to work in discrete domains. In particular, we use Q-learning so that the algorithm learns an optimal binarization schemEqe selection policy. The policy is dynamically updated based on the performance of the binarization schemes in each iteration. Preliminary experiments using our framework with sine cosine algorithm show that the proposal presents promising results compared to other algorithms. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Combinatorial optimization

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Mobility-Aware Clustering Routing (MACRON) Algorithm for Lifetime Improvement of Extensive Dynamic Wireless Sensor Network 1

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International Conference on intelligent and Smart computing in Data Analytics, ISCDA 2020

作者： Bhandari, Rajiv Ramesh Raja Sekhar, K. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (数字)9789813361768

ISBN: (纸本)9789813361751

Wireless sensor network is growing rapidly in recent era. The scalability and mobility impose remarkable challenges and degrade overall lifetime of network. The versatile topology with evolving parameters such as location and coverage needs to be modified for extensively dynamic network. The flat sensor network degrades the network’s total lifespan, because it absorbs a lot of resources. Clustering with one-hop distance in sensor network is the best way to elongate network lifespan. Clustering along with adaptive sleep scheduling using reinforcement algorithm produces better results by eliminating the issue of idle listening. The proposed mobility-aware clustering routing algorithm (MACRON) along with self-healing scheduling for extensively dynamic network to handle network communication with one-hop distance and probability distribution function will give better results as compared to RI-MAC, A-TDMA, AODV and MEMAC. The experimental analysis shows that MACRON gives better results in terms of throughput, delay, packet delivery, hop and mean deviation. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless sensor networks

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