Task Decomposition Based on Cloud Manufacturing Platform

As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten product development time, reduce costs for resource service providers, and provide technical support for the application of CMfg. However, a cloud manufacturing system has to manage the allocation the correct amount of manufacturing resources, complex production processes, and highly dynamic production environments. At the same time, the tasks issued by service demanders are usually asymmetric and tightly coupled. We solve the complex task decomposition problem by using the traditional methods, that are hard to complete in CMfg. To overcome the shortcomings of CMfg, this paper proposed a task decomposition method based on the cloud platform. For achieving modular production, this approach creatively divides the product production process into four stages: design, manufacturing, transportation, and maintenance. Then a hybrid method, which combines with depth-first search algorithm, fast modular optimization algorithm, and artificial bee colony algorithm, is introduced. The method can obtain a multi-stage task optimization decomposition plan in CMfg. Simulation results demonstrate the proposed method can achieve complex task optimization decomposition in a CMfg environment.

The impact of digital health interventions on the psychological outcomes of patients and families receiving paediatric palliative care: A systematic review and narrative synthesis

Background: Digital health interventions are becoming increasingly important and may be particularly relevant for paediatric palliative care. In line with the aims of palliative care, digital health interventions should aim to maintain, if not improve, psychological wellbeing. However, the extent to which the psychological outcomes of digital health interventions are assessed is currently unknown. Aim: To identify and synthesise the literature exploring the impact of all digital health interventions on the psychological outcomes of patients and families receiving paediatric palliative care. Design: Systematic review and narrative synthesis. Data sources: MEDLINE, EMBASE, Health Management Information Consortium, PsycINFO, Cumulative Index to Nursing and Allied Health Literature and the Midwives Information & Resource Service were searched on the 27th July 2020, in addition to the first five pages of Google Scholar. To be included in the review, papers must have contained: quantitative or qualitative data on psychosocial outcomes, data from patients aged 0–18 receiving palliative care or their families, a digital health intervention, and been written in English. Results: Three studies were included in the review. All looked at the psychological impact of telehealth interventions. Papers demonstrated fair or good quality reporting but had small sample sizes and varied designs. Conclusions: Despite the design and development of digital health interventions that span the technological landscape, little research has assessed their psychosocial impact in the paediatric palliative care community. Whilst the evidence base around the role of these interventions continues to grow, their impact on children and their families must not be overlooked.

Applied Research of Knowledge in the Field of Artificial Intelligence in the Intelligent Retrieval of Teaching Resources

In the development process of education informatization, digital teaching resources continue to grow, and how to manage and organize massive teaching resources has become a key issue for teaching staff. An efficient and accurate search system is an important part of the teaching resource service system. The use of intelligent search engines can search teaching resources comprehensively and efficiently, and the artificial intelligence search engine provides a reliable and convenient solution for the design and development of intelligent search systems. The article analyzes the design principles and technical standards of the intelligent search system, expounds the system’s functional architecture and database design, and introduces the realization process and principles of the search system. By analyzing the characteristics of basic education resources and existing automatic abstracting methods, this paper proposes to integrate the calculated feature word weights in the field of basic education into the algorithm for calculating the weights of abstract sentences and simultaneously examine the sentence position, sentence length, and other texts. There is an automatic summarization algorithm for surface statistics. This article also introduces the search design ideas and implementation steps based on artificial intelligence, makes a scientific evaluation and summary of the actual situation of the automatic abstract system running in the basic education resource search engine, and looks forward to the next improvement work.