Lichao Zhu, Hangzhou Yang and Zhijun Yan
The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.
Abstract
Purpose
The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.
Design/methodology/approach
The authors trained a conditional random-filed model for the extraction of temporal expressions. The temporal relation identification is considered as a classification task and several support vector machine classifiers are built in the proposed method. For the model training, the authors extracted some high-level semantic features including co-reference relationship of medical concepts and the semantic similarity among words.
Findings
For the extraction of TIMEX, the authors find that well-formatted expressions are easy to recognize, and the main challenge is the relative TIMEX such as “three days after onset”. It also shows the same difficulty for normalization of absolute date or well-formatted duration, whereas frequency is easier to be normalized. For the identification of DocTimeRel, the result is fairly well, and the relation is difficult to identify when it involves a relative TIMEX or a hypothetical concept.
Originality/value
The authors proposed a new method to extract temporal information from the online clinical data and evaluated the usefulness of different level of syntactic features in this task.
Details
Keywords
Lichao Ma, Hao Yao and Manyuan Sun
The study seeks to unpack the effect of distributed leadership on teacher professionalism, and the mediating roles of collaborative learning and relational trust in the Chinese…
Abstract
Purpose
The study seeks to unpack the effect of distributed leadership on teacher professionalism, and the mediating roles of collaborative learning and relational trust in the Chinese cultural context.
Design/methodology/approach
The proposed framework was examined based on the questionnaire data from 522 primary and secondary school teachers in China using structural equation modeling.
Findings
It was found that distributed leadership had a direct positive impact on collaborative learning and relational trust, which also exerted the direct positive impact on teacher professionalism. However, distributed leadership cannot directly affect teacher professionalism in China. Only through the full mediation of collaborative learning and relational trust, could distributed leadership facilitate teacher professionalism in an indirect way. The proportion of sequence mediating effect was the highest, followed by the single mediating role played by relational trust.
Originality/value
We have demonstrated to international scholars the indirect value of distributed leadership in enhancing teacher professionalism in China. The results not only enrich the existing influencing mechanism framework of professionalism, but also provide valuable implications that school leadership does not have a completely positive effect on teacher professionalism. Only when the empowering leadership style is truly perceived by teachers and strengthens their collaborative learning and mutual trust, can a team of capable educators be formed to promote teacher professionalism. It also indicates that teacher professionalism becomes a systematic and structural process requiring support from multiple parties, such as schools, leaders, colleagues and self.
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Sadia Samar Ali, Shahbaz Khan, Nosheen Fatma, Cenap Ozel and Aftab Hussain
Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this…
Abstract
Purpose
Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.
Design/methodology/approach
The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.
Findings
This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.
Research limitations/implications
This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.
Practical implications
By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.
Originality/value
This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.
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Ran Li, Simin Wang, Zhe Sun, Aohai Zhang, Yuxuan Luo, Xingyi Peng and Chao Li
Depression has become one of the most serious and prevalent mental health problems worldwide. The rise and popularity of social networks such as microblogs provides a wealth of…
Abstract
Purpose
Depression has become one of the most serious and prevalent mental health problems worldwide. The rise and popularity of social networks such as microblogs provides a wealth of psychological data for early depression detection. Language use patterns reflect emotional states and psychological traits. Differences in language use between depressed and general users may help predict and diagnose early depression. Existing work focuses on depression detection using users' social textual emotion expressions, with less psychology-related knowledge.
Design/methodology/approach
In this paper, we propose an RNN-capsule-based depression detection method for microblog users that improves depression detection accuracy in social texts by combining textual emotional information with knowledge related to depression pathology. Specifically, we design a multi-classification RNN capsule that enhances emotion expression features in utterances and improves classification performance of depression-related emotional features. Based on user emotion annotations over time, we use integrated learning to detect depression in a user’s social text by combining the analysis results with components such as emotion change vector, emotion causality analysis, depression lexicon and the presence of surprising emotions.
Findings
In our experiments, we test the accuracy of RNN capsules for emotion classification tasks and then validate the effectiveness of different depression detection components. Finally, we achieved 83% depression detection accuracy on real datasets.
Originality/value
The paper overcomes the limitations of social text-based depression detection by incorporating more psychological background knowledge to enhance the early detection success rate of depression.
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Nan Sun, Beibei Tan, Bolun Sun, Jinjie Zhang, Chao Li and Wenge Yang
Sargassum fusiforme is a popular edible seaweed in coastal cities of China that contains diverse nutrients including iodine. Cooking is an effective way to improve food safety…
Abstract
Purpose
Sargassum fusiforme is a popular edible seaweed in coastal cities of China that contains diverse nutrients including iodine. Cooking is an effective way to improve food safety, but it can alter both the contents of elements along with speciation and bioavailability. Three common cooking methods, the soaking, steaming and boiling, were evaluated for their effects on the protein structures, protein digestibility, iodine content and iodine bioavailability of S. fusiforme.
Design/methodology/approach
Fourier transform infrared spectroscopy was used to study the structural changes of protein, and an in vitro digestion/Caco-2 cell culture system was used to evaluate the digestibility of protein, bioaccessibility and bioavailability of iodine.
Findings
Boiling and steaming altered the protein secondary structure demonstrated by increased a-helix and random coil and decreased β-sheet, which improved the in vitro protein digestibility. Iodine content was reduced by cooking, with the highest loss observed after boiling, followed by soaking and steaming, while it was found that both bioaccessibility and cellular uptake of iodine were significantly elevated by boiling and steaming using an in vitro digestion/Caco-2 cell culture system. The presence of ascorbic acid, citric acid or tyrosine was beneficial for the iodine absorption, while oxalic acid and phytic acid hindered the iodine bioavailability.
Originality/value
The present finding suggested that cooking was conducive to the digestion and absorption of iodine in S. fusiforme. In addition, different dietary factors could have a certain impact on the absorption of iodine. Results of the study are essential for improving the application value of S. fusiforme to ensure reasonable consumption of seaweeds.
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Anton Wiberg, Johan Persson and Johan Ölvander
This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM…
Abstract
Purpose
This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.
Design/methodology/approach
The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.
Findings
Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.
Originality/value
The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.