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Browsing by Subject "Task analysis"

Now showing items 1-13 of 13

A Conceptual Model-Based Approach to Improve the Representation and Management of Omics Data in Precision Medicine

García-Simón, Alberto; León-Palacio, Ana; REYES ROMÁN, JOSÉ FABIÁN; Casamayor Rodenas, Juan Carlos; Pastor López, Oscar (Institute of Electrical and Electronics Engineers, 2021)

[EN] Precision medicine has emerged as a disrupting medical model to transform a historically reactive medicine into a proactive one that focuses on delivering individualized treatment. A relevant challenge of precision ...
Analysis of threading libraries for high performance computing

Castelló, Adrián; Mayo Gual, Rafael; Seo, Sangmin; Balaji, Pavan; Quintana Ortí, Enrique Salvador; Peña, Antonio J. (Institute of Electrical and Electronics Engineers, 2020-09-01)

[EN] With the appearance of multi-/many core machines, applications and runtime systems have evolved in order to exploit the new on-node concurrency brought by new software paradigms. POSIX threads (Pthreads) was widely-adopted ...
Deadline-Aware Fair Scheduling for Offloaded Tasks in Fog Computing With Inter-Fog Dependency

Mukherjee, Mithun; Guo, Mian; Lloret, Jaime; Iqbal, Razi; Zhang, Qi (Institute of Electrical and Electronics Engineers, 2020-02)

[EN] A fundamental problem in fog computing networks is how to schedule the deadline-aware offloaded tasks that directly arrive from the end-users and via other fog nodes. The computational resource allocation becomes more ...
DRALBA: Dynamic and Resource Aware Load Balanced Scheduling Approach for Cloud Computing

Nabi, Said; Ibrahim, Muhammad; Jimenez, Jose M. (Institute of Electrical and Electronics Engineers, 2021)

[EN] For the last few years, Cloud computing has been considered an attractive high-performance computing platform for individuals as well as organizations. The Cloud service providers (CSPs) are setting up data centers ...
Dual Indicators to Analyse AI Benchmarks: Difficulty, Discrimination, Ability and Generality

Martínez-Plumed, Fernando; Hernández-Orallo, José (Institute of Electrical and Electronics Engineers (IEEE), 2020-06)

[EN] With the purpose of better analyzing the result of artificial intelligence (AI) benchmarks, we present two indicators on the side of the AI problems, difficulty and discrimination, and two indicators on the side of ...
Early Prediction of Students at Risk of Failing a Face-to-Face Course in Power Electronic Systems

Alcaraz, Raúl; Martínez-Rodrigo, Arturo; Zangróniz, Roberto; Rieta, J J (IEEE, 2021-10-01)

[EN] Early warning systems (EWSs) have proven to be useful in identifying students at risk of failing both online and conventional courses. Although some general systems have reported acceptable ability to work in modules ...
Leveraging Intelligent Computation Offloading with Fog/Edge Computing for Tactile Internet: Advantages and Limitations

Mukherjee, Mithun; Guo, Mian; Lloret, Jaime; Zhang, Qi (Institute of Electrical and Electronics Engineers, 2020-10)

[EN] With the recent advancement in wireless communication and networks, we are at the doorstep of the Tactile Internet. The Tactile Internet aims to enable the skill delivery and thereafter democratize the specialized ...
Multi-Queue Request Scheduling for Profit Maximization in IaaS Clouds

Wang, Shuang; Li, Xiaoping; Sheng, Quan Z.; Ruiz García, Rubén; Zhang, Jinquan; Beheshti, Amin (Institute of Electrical and Electronics Engineers, 2021-11-01)

[EN] In cloud computing, service providers rent heterogeneous servers from cloud providers, i.e., Infrastructure as a Service (IaaS), to meet requests of consumers. The heterogeneity of servers and impatience of consumers ...
Multikernel Clustering via Non-Negative Matrix Factorization Tailored Graph Tensor Over Distributed Networks

Ren, Zhenwen; Mukherjee, Mithun; Bennis, Mehdi; Lloret, Jaime (Institute of Electrical and Electronics Engineers, 2021-07)

[EN] Next-generation wireless networks are witnessing an increasing number of clustering applications, and produce a large amount of non-linear and unlabeled data. In some degree, single kernel methods face the challenging ...
Revenue Maximization in Delay-Aware Computation Offloading Among Service Providers With Fog Federation

Mukherjee, Mithun; Kumar, Vikas; Lloret, Jaime; Zhang, Qi (Institute of Electrical and Electronics Engineers, 2020-08)

[EN] In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog ...
Speaker-Adapted Confidence Measures for ASR using Deep Bidirectional Recurrent Neural Networks

Del Agua Teba, Miguel Angel; Giménez Pastor, Adrián; Sanchis Navarro, José Alberto; Civera Saiz, Jorge; Juan, Alfons (Institute of Electrical and Electronics Engineers, 2018)

[EN] In the last years, Deep Bidirectional Recurrent Neural Networks (DBRNN) and DBRNN with Long Short-Term Memory cells (DBLSTM) have outperformed the most accurate classifiers for confidence estimation in automatic speech ...
TaScaaS: A Multi-Tenant Serverless Task Scheduler and Load Balancer as a Service

Giménez-Alventosa, Vicent; Moltó, Germán; Segrelles Quilis, José Damián (Institute of Electrical and Electronics Engineers, 2021)

[EN] A combination of distributed multi-tenant infrastructures, such as public Clouds and on-premises installations belonging to different organisations, are frequently used for scientific research because of the high ...
Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation

Ruiz-Dolz, Ramon; Alemany-Bordera, José; Heras, Stella; García-Fornes, A (Institute of Electrical and Electronics Engineers, 2021-11-01)

[EN] Argument mining is defined as the task of automatically identifying and extracting argumentative components (e.g., premises, claims, etc.) and detecting the existing relations among them (i.e., support, attack, rephrase, ...