A forefront to machine translation technology: deployment on the cloud as a service to enhance QoS parameters

Singh, Muskaan; Kumar, Ravinder; Chana, Inderveer

doi:10.1007/s00500-020-04923-7

Cited by 9 publications

(3 citation statements)

References 47 publications

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“…However, the matching process of this method is complicated and it is difficult to match highquality services. Literature [10] analysed the QoS attributes of the service, combined the representative attributes in the service into a matrix form, and obtained high-quality services through a local optimal selection algorithm. is algorithm has a faster matching speed, but the shortcomings are obtained.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Mobile Internet of Things Dynamic Grid QoS Service Matching Mechanism and Simulation Analysis

Fan

2021

Complexity

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With the development of the mobile Internet of Things, people have higher and higher requirements for services, and how to provide high-quality services that meet the needs of users has also become a hot issue of current research. This article is also in the context of the mobile Internet of Things, researching the solution to the service matching problem. In order to provide high-quality grid services, the grid system needs the support of quality of service (QoS). Based on the existing QoS matching strategy, a service matching strategy based on dynamic grid QoS is proposed. This paper combines semantic information, considers service quality QoS and user preferences, and improves the success rate of service matching through hierarchical matching, so as to provide users with high-quality services. At the same time, the classic Max-Min algorithm in grid task scheduling is analysed, and on this basis, the impact of QoS on task scheduling is fully considered, and combined with the concept of execution cost, a grid task based on QoS constraints (MOS) is proposed. Through simulation verification and analysis, the strategy in this paper not only achieved higher matching performance, but also improved the success rate of task execution, and the effect of system load balancing was also significantly improved.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Mobile Internet of Things Dynamic Grid QoS Service Matching Mechanism and Simulation Analysis

Fan

2021

Complexity

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“…The literature combined with the interactive Chinese English translation model system, analyzed and discussed the overall architecture and network topology of mobile computing applications under the mobile cloud computing mode, analyzed and discussed the dynamic application segmentation under the mobile cloud computing environment, integrated the Chinese English interactive translation model system, and explained the operating and development environments of the client and server [10]. Then, according to the actual needs, the main working modules of the server and client and the main functions of each module are introduced in detail [11]. Based on the research of natural language processing, the literature designed a new method for translating English poetry into Chinese, and selected target poetry for experimental verification [12].…”

Section: Related Workmentioning

confidence: 99%

Research on interactive system of Chinese-English translation model in cloud computing environment based on deep learning

Mai¹,

Yuan²

2023

Preprint

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At present, human translation is characterized by low efficiency, high cost, high consumption of resources and time, so it is urgent to study automatic translation technology to meet the needs of information interaction and language communication in various countries under the background of economic globalization. This topic has also become a hot issue in the field of translation. After a long period of development, machine translation technology has gradually become popular and widely used, replacing human translation technology as the mainstream technology. Therefore, this paper implements the construction of an interactive system of English Chinese bilingual translation model based on cloud computing environment by introducing deep learning algorithm. The system can learn by itself on the basis of analyzing source documents, and predict target translation output by extracting features. The system is equipped with a translation engine based on the data source, which can realize interactive translation, and the final output can be achieved by processing the predicted translation output and based on the translator's understanding. Through the design of simulation experiments for system detection, the results show that the Chinese English translation model system has a high translation quality. By comparing it with the baseline system, it can be seen that both of them can translate sentences normally in 8 PR cycles (PR * 8, about 18% KSMR), and the data set improvement rate is about + 35 BLEU, that is, 76 BLEU is finally achieved. This proves that users can maintain the translation accuracy while reducing the number of effective interactions by using the optimized translation model to translate the target text, showing the effectiveness. In this paper, an interactive Chinese English translation system is designed by combining deep learning with cloud computing.

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“…In the data-driven academic era, the IoT empowers educational institutions to gather and oversee data derived from interconnected devices, such as smartphones, tablets, RFID sensors, barcoding systems, cameras, EEG devices and handheld gadgets (Kumar and Al-Besher, 2022). IoT provides a smart learning environment and offers ubiquitous access to required information resources for improving professional competencies (Sarwar et al , 2019; Setiawan et al , 2022; Singh et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

Effects of e-learning technologies on university librarians and libraries: a systematic literature review

Shahzad

Khan

2023

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Purpose The purpose of this study was to identify the effects of emerging technologies in e-learning on university librarians and libraries. The study also intended to identify emerging technologies in e-learning and challenges being faced to implement e-learning technologies. Design/methodology/approach The preferred reporting items for the systematic review and meta-analysis method was applied as the research methodology for conducting the study. A total of 25 core studies published in peer-reviewed journals were selected to conduct a systematic literature review. The data were analysed through a thematic approach. Findings The results of the study revealed that e-learning technologies assist library professionals to strengthen their expertise and support them in initiating smart library services to deliver customer-focused services. A shortage of skilled manpower, the unavailability of adequate IT infrastructure, a lack of technical support, copyright issues, poor planning and ineffective library leadership are major challenges to implementing emerging technologies in e-learning. Originality/value The study offers theoretical implications by adding valuable literature to the existing body of knowledge. It has a societal impact as it has offered recommendations and practical solutions for the successful adoption of emerging technologies in e-learning. The study also offers managerial implications to develop fruitful policies for implementing e-learning technologies for the innovative sustainable competence development of library manpower and implementation of smart library services.

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A forefront to machine translation technology: deployment on the cloud as a service to enhance QoS parameters

Cited by 9 publications

References 47 publications

[Retracted] Mobile Internet of Things Dynamic Grid QoS Service Matching Mechanism and Simulation Analysis

[Retracted] Mobile Internet of Things Dynamic Grid QoS Service Matching Mechanism and Simulation Analysis

Research on interactive system of Chinese-English translation model in cloud computing environment based on deep learning

Effects of e-learning technologies on university librarians and libraries: a systematic literature review

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