Nouhaila Bensalah, Habib Ayad, Abdellah Adib and Abdelhamid Ibn El Farouk
The paper aims to enhance Arabic machine translation (MT) by proposing novel approaches: (1) a dimensionality reduction technique for word embeddings tailored for Arabic text…
Abstract
Purpose
The paper aims to enhance Arabic machine translation (MT) by proposing novel approaches: (1) a dimensionality reduction technique for word embeddings tailored for Arabic text, optimizing efficiency while retaining semantic information; (2) a comprehensive comparison of meta-embedding techniques to improve translation quality; and (3) a method leveraging self-attention and Gated CNNs to capture token dependencies, including temporal and hierarchical features within sentences, and interactions between different embedding types. These approaches collectively aim to enhance translation quality by combining different embedding schemes and leveraging advanced modeling techniques.
Design/methodology/approach
Recent works on MT in general and Arabic MT in particular often pick one type of word embedding model. In this paper, we present a novel approach to enhance Arabic MT by addressing three key aspects. Firstly, we propose a new dimensionality reduction technique for word embeddings, specifically tailored for Arabic text. This technique optimizes the efficiency of embeddings while retaining their semantic information. Secondly, we conduct an extensive comparison of different meta-embedding techniques, exploring the combination of static and contextual embeddings. Through this analysis, we identify the most effective approach to improve translation quality. Lastly, we introduce a novel method that leverages self-attention and Gated convolutional neural networks (CNNs) to capture token dependencies, including temporal and hierarchical features within sentences, as well as interactions between different types of embeddings. Our experimental results demonstrate the effectiveness of our proposed approach in significantly enhancing Arabic MT performance. It outperforms baseline models with a BLEU score increase of 2 points and achieves superior results compared to state-of-the-art approaches, with an average improvement of 4.6 points across all evaluation metrics.
Findings
The proposed approaches significantly enhance Arabic MT performance. The dimensionality reduction technique improves the efficiency of word embeddings while preserving semantic information. Comprehensive comparison identifies effective meta-embedding techniques, with the contextualized dynamic meta-embeddings (CDME) model showcasing competitive results. Integration of Gated CNNs with the transformer model surpasses baseline performance, leveraging both architectures' strengths. Overall, these findings demonstrate substantial improvements in translation quality, with a BLEU score increase of 2 points and an average improvement of 4.6 points across all evaluation metrics, outperforming state-of-the-art approaches.
Originality/value
The paper’s originality lies in its departure from simply fine-tuning the transformer model for a specific task. Instead, it introduces modifications to the internal architecture of the transformer, integrating Gated CNNs to enhance translation performance. This departure from traditional fine-tuning approaches demonstrates a novel perspective on model enhancement, offering unique insights into improving translation quality without solely relying on pre-existing architectures. The originality in dimensionality reduction lies in the tailored approach for Arabic text. While dimensionality reduction techniques are not new, the paper introduces a specific method optimized for Arabic word embeddings. By employing independent component analysis (ICA) and a post-processing method, the paper effectively reduces the dimensionality of word embeddings while preserving semantic information which has not been investigated before especially for MT task.
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Mariam Ben Hassen, Sahbi Zahhaf and Faiez Gargouri
Addressing integrity, flexibility and interoperability challenges in enterprise information systems (EISs) is often hindered by the “three-fit” barrier, which encompasses…
Abstract
Purpose
Addressing integrity, flexibility and interoperability challenges in enterprise information systems (EISs) is often hindered by the “three-fit” barrier, which encompasses vertical, horizontal and transversal fit problems. To overcome these obstacles, we propose solutions aimed at defining the business view of EIS. This study addresses these issues by proposing solutions tailored to the business view of EIS. Specifically, it introduces the core ontology of sensitive business processes (COSBP), a conceptual framework designed to formalize and define the multidimensional dimensions of sensitive business processes (SBPs). By providing a unified structure of central concepts and semantic relationships, COSBP enhances both knowledge management (KM) and business process management (BPM) in organizational contexts.
Design/methodology/approach
This paper adopts the design science research methodology covering the phases of a design-oriented research project that develops new artifacts, such as the COSBP ontology, based on SBP modeling requirements. Following a formal multi-level, multi-component approach, COSBP is structured into sub-ontologies across different abstraction levels. Built upon the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) foundational ontology, COSBP integrates and extends core concepts from core domain ontologies in business processes. The framework specifies six key modeling dimensions of SBPs – functional, organizational, behavioral, informational, intentional and knowledge – each represented as a distinct class of ontological modules (OMs).
Findings
COSBP offers a semantically rich and precise framework for modeling SBPs, addressing complexity and ambiguity in conceptual modeling. It supports the creation of expressive and effective SBP models while enabling consensus-driven representation at a generic level. Additionally, COSBP serves as a foundation for extending modeling notations and developing tools that align with these notations. Its application in enterprise environments improves the integration, adaptability and interoperability of EISs, ultimately enhancing organizational processes and decision-making.
Originality/value
The development of the COSBP ontology holds considerable potential for application in various industries beyond its original focus on business process management and KM. The ontology’s capability to semantically model sensitive, knowledge-intensive and dynamic processes can be extended to other real-life scenarios in other complex domains and sectors – for example, finance and banking, government and public services, insurance, manufacturing and supply chain management, retail, E-commerce, logistics and transportation crisis management, government and public services, higher education and so on. By integrating artificial intelligence (AI) with the COSBP ontology, we aim to enable more intelligent decision-making, process monitoring and improved management of SBPs in knowledge-driven domains.
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Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the…
Abstract
Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.
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Sathiyamoorthy Margabandu and Senthil Kumar Subramaniam
The study aims to investigate the influence of fabric hybridization, stacking sequences and matrix materials on the tensile strength and damping behavior of jute/carbon reinforced…
Abstract
Purpose
The study aims to investigate the influence of fabric hybridization, stacking sequences and matrix materials on the tensile strength and damping behavior of jute/carbon reinforced hybrid composites.
Design/methodology/approach
The hybrid composites were fabricated with different sequences of fabric plies in epoxy and polyester matrix using a hand layup technique. The tensile and vibration characteristics were evaluated on the hybrid laminated composite models using finite element analysis (FEA), and the results were validated experimentally according to ASTM standards. The surface morphology of the fractured specimens was studied using the scanning electron microscope.
Findings
The experimental results revealed that the position of jute layers in the hybrid composites has a significant influence on the tensile strength and damping behavior. The hybrid composite with jute fiber at the surface sides and carbon fibers at the middle exhibited higher tensile strength with superior damping properties. Further, it is found that the experimental results are in good coherence with the FEA results.
Originality/value
The less weight and low-cost hybrid composites were fabricated by incorporating the jute and carbon fabrics in interply configurations. The influences of fabric hybridization, stacking arrangements and matrix materials on the tensile and vibration behavior of jute/carbon hybrid composites have been numerically evaluated and the results were experimentally validated.