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1 – 10 of 100Xiaoyu Li, Osamu Yoshie and Daoping Huang
The purpose of this paper is to detect the existence of unknown wireless devices which could result negative means to the privacy. The perceptual layer of internet of things…
Abstract
Purpose
The purpose of this paper is to detect the existence of unknown wireless devices which could result negative means to the privacy. The perceptual layer of internet of things (IoTs) suffers the most significant privacy disclosing because of limited hardware resources, huge quantity and wide varieties of sensing equipment. Determining whether there are unknown wireless devices in the communicating environment is an effective method to implement the privacy protection for the perceptual layer of IoTs.
Design/methodology/approach
The authors use horizontal hierarchy slicing (HHS) algorithm to extract the morphology feature of signals. Meanwhile, partitioning around medoids algorithm is used to cluster the HHS curves and agglomerative hierarchical clustering algorithm is utilized to distinguish final results. Link quality indicator (LQI) data are chosen as the network parameters in this research.
Findings
Nowadays data encryption and anonymization are the most common methods to protect private information for the perceptual layer of IoTs. However, these efforts are ineffective to avoid privacy disclosure if the communication environment exists unknown wireless nodes which could be malicious devices. How to detect these unknown wireless devices in the communication environment is a valuable topic in the further research.
Originality/value
The authors derive an innovative and passive unknown wireless devices detection method based on the mathematical morphology and machine learning algorithms to detect the existence of unknown wireless devices which could result negative means to the privacy. The simulation results show their effectiveness in privacy protection.
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Xiaoyu Yu, Bang Nguyen and Yi Chen
The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic…
Abstract
Purpose
The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic orientations (entrepreneurial and market foci) with product and process innovations. In addition, it investigates the direct relationship between IoT capability and alliance. Improving these relationships assist in ensuring that new knowledge from the IoT can be translated into tangible business innovations that contribute to economic development.
Design/methodology/approach
Data from 207 new high-technology IoT ventures in China were obtained after three-wave mailing (i.e. two reminders). Following a rigorous process to purify and validate the measurement scale items, the study used structural equation modeling to test the conceptual model.
Findings
Findings demonstrate that an IoT capability only enhances product innovation, however, with the addition and support from IoT alliance, both product and process innovation can be achieved in new high-tech IoT ventures. This nuanced insight suggests that new high-tech IoT ventures should focus on building their IoT capability, and at the same time, develop IoT alliances with value chain partners in order to fully take advantage of IoT and gain a better position to formulate more novel offerings.
Originality/value
The study is first to contribute with a much needed framework of IoT and entrepreneurship by examining the role of IoT capability further in the relationships between: entrepreneurial orientation and market orientation with product and process innovations arising from IoT; and the role of IoT alliance (interfirm relations, partnerships, etc.) on the relationship above.
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Jingjun Liu, Yuzhen Lin and Xiaoyu Li
To study flow‐induced corrosion mechanisms for carbon steel in high velocity flowing seawater and explain corrosive phenomena.
Abstract
Purpose
To study flow‐induced corrosion mechanisms for carbon steel in high velocity flowing seawater and explain corrosive phenomena.
Design/methodology/approach
An overall mathematical model for flow‐induced corrosion of carbon steel in high velocity flow seawater was established in rotating disk apparatus using both numerical simulation and test methods. By studying the impact of turbulent flow using the kinetic energy of turbulent approach and the effects of the computational near‐wall hydrodynamic parameters on corrosion rates, corrosion behaviour and mechanism are discussed here. It is applicable to deeply understand the synergistic effect mechanism of flow‐induced corrosion.
Findings
It is scientific and reasonable to investigate carbon steel corrosion through correlation of the near‐wall hydrodynamic parameters, which can accurately describe the influence of fluid flow on corrosion. The computational corrosion rates obtained by this model are in agreement with measured corrosion data. It is shown that serious flow‐induced corrosion is caused by the synergistic effect between corrosion electrochemical factor and hydrodynamic factor. While corrosion electrochemical factor plays a dominant role in flow‐induced corrosion.
Originality/value
The corrosion kinetics and mechanism of metals in high velocity flowing medium is discussed in this paper. These results will help someone who is interested in flow‐induced corrosion to understand in depth the type of issue.
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Liu Jingjun, Lin Yuzhen and Li Xiaoyu
This paper aims to study flow‐induced corrosion mechanisms for carbon steel in high‐velocity flowing seawater and to explain corrosive phenomena.
Abstract
Purpose
This paper aims to study flow‐induced corrosion mechanisms for carbon steel in high‐velocity flowing seawater and to explain corrosive phenomena.
Design/methodology/approach
An overall mathematical model for flow‐induced corrosion of carbon steel in high‐velocity flow seawater was established in a rotating disk apparatus using both numerical simulation and test methods. By studying the impact of turbulent flow using the kinetic energy of a turbulent approach and the effects of the computational near‐wall hydrodynamic parameters on corrosion rates, corrosion behavior and mechanism are discussed here. It is applicable in order to understand in depth the synergistic effect mechanism of flow‐induced corrosion.
Findings
It was found that it is scientific and reasonable to investigate carbon steel corrosion through correlation of the near‐wall hydrodynamic parameters, which can accurately describe the influence of fluid flow on corrosion. The computational corrosion rates obtained by this model are in good agreement with measured corrosion data. It is shown that serious flow‐induced corrosion is caused by the synergistic effect between the corrosion electrochemical factor and the hydrodynamic factor, while the corrosion electrochemical factor plays a dominant role in flow‐induced corrosion.
Originality/value
The corrosion kinetics and mechanism of metals in a high‐velocity flowing medium is discussed here. These results will help those interested in flow‐induced corrosion to understand in depth the type of issue.
This paper analyses the escalating Sino-Western race to develop a safe, efficacious and durable vaccine (i.e. “Goldilocks COVID-19 vaccine”). It argues that such efforts would be…
Abstract
Purpose
This paper analyses the escalating Sino-Western race to develop a safe, efficacious and durable vaccine (i.e. “Goldilocks COVID-19 vaccine”). It argues that such efforts would be considerably more effective if there is greater international cooperation instead of the corrosive rivalry driven by misplaced nationalism.
Design/methodology/approach
This study deploys a case-study approach, supported by literature on existing coronavirus disease 2019 (COVID-19) vaccine development efforts.
Findings
Despite the seeming success of recent COVID-19 vaccines, their actual efficacy is far from certain. Moreover, access to these vaccines would not be equitable internationally. This problem is exacerbated by the fact that their unique properties make storage and distribution prohibitively expensive, and international mechanisms to provide distribution to economically depressed regions are non-existent. Given the significant difficulties, it would be incumbent upon the great powers (i.e. China and America) to work together not only in vaccine development but also in the establishment of a distribution platform to ensure equitable access worldwide.
Originality/value
This study is one of the few social science research papers on COVID-19 vaccine development and its implications for society at large.
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Sai Liang, Xiaoxia Zhang, Chunxiao Li, Hui Li and Xiaoyu Yu
Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to…
Abstract
Purpose
Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to investigate the determinants of the responding behavior of hosts on peer-to-peer property rental platforms.
Design/methodology/approach
This study applied a comprehensive framework based on the theory of planned behavior. Empirical models are constructed based on 89,967 guest reviews with their associated responses to reveal the responding pattern of property hosts.
Findings
Unlike hotel managers, property hosts are more likely to reply to positive than to negative reviews; moreover, when they do choose to respond to negative reviews, they are likely to do so negatively, in a “tit-for-tat” way. This study also finds that one reason for the difference of responding patterns between property hosts and hotel managers is the hosts’ lack of experience of consumer relationship management and service recovery.
Research limitations/implications
This study provides a good start point for future theoretical development regarding effective responding strategy on peer-to-peer property rental platforms, as well as some useful implications for practitioners.
Originality/value
This study is an early attempt to analyze the impact of the particularity of emerging platforms on the responding behavior of service providers based on a comprehensive conceptual framework and empirical model thus provides a good starting point for the further investigation of effective response strategies on these emerging platforms.
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Yonghong Zhang, Shouwei Li, Jingwei Li and Xiaoyu Tang
This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of…
Abstract
Purpose
This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of memory dependence period, ultimately enhancing the model's predictive accuracy.
Design/methodology/approach
This paper enhances the traditional grey Bernoulli model by introducing memory-dependent derivatives, resulting in a novel memory-dependent derivative grey model. Additionally, fractional-order accumulation is employed for preprocessing the original data. The length of the memory dependence period for memory-dependent derivatives is determined through grey correlation analysis. Furthermore, the whale optimization algorithm is utilized to optimize the cumulative order, power index and memory kernel function index of the model, enabling adaptability to diverse scenarios.
Findings
The selection of appropriate memory kernel functions and memory dependency lengths will improve model prediction performance. The model can adaptively select the memory kernel function and memory dependence length, and the performance of the model is better than other comparison models.
Research limitations/implications
The model presented in this article has some limitations. The grey model is itself suitable for small sample data, and memory-dependent derivatives mainly consider the memory effect on a fixed length. Therefore, this model is mainly applicable to data prediction with short-term memory effect and has certain limitations on time series of long-term memory.
Practical implications
In practical systems, memory effects typically exhibit a decaying pattern, which is effectively characterized by the memory kernel function. The model in this study skillfully determines the appropriate kernel functions and memory dependency lengths to capture these memory effects, enhancing its alignment with real-world scenarios.
Originality/value
Based on the memory-dependent derivative method, a memory-dependent derivative grey Bernoulli model that more accurately reflects the actual memory effect is constructed and applied to power generation forecasting in China, South Korea and India.
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Nao Li, Xiaoyu Yang, IpKin Anthony Wong, Rob Law, Jing Yang Xu and Binru Zhang
This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a…
Abstract
Purpose
This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a neural network model.
Design/methodology/approach
This study constructs an aspect-oriented sentiment classification model using an integrated four-layer neural network: the bidirectional encoder representation from transformers (BERT) word vector model, long short-term memory, interactive attention-over-attention (IAOA) mechanism and a linear output layer. The model was trained, tested and validated on an open training data set and 92,905 reviews extrapolated from restaurants in Tokyo.
Findings
The model achieves significantly better performance compared with other neural networks. The findings provide empirical evidence to validate the suitability of this new approach in the tourism-hospitality domain.
Research limitations/implications
More sentiments should be identified to measure more fine-grained tourism-hospitality experience, and new aspects are recommended that can be automatically added into the aspect set to provide dynamic support for new dining experiences.
Originality/value
This study provides an update to the literature with respect to how a neural network could improve the performance of aspect-oriented sentiment classification for tourism-hospitality online reviews.
研究目的
本文旨在从方面级对在线旅游-酒店评论的情感进行分类。提出了一种基于神经网络模型的面向方面的情感分类新方法。
研究设计/方法/途径
本研究使用集成的四层神经网络构建面向方面的情感分类模型:BERT 词向量模型、LSTM、IAOA 机制和线性输出层。该模型在一个开放的训练数据集和从东京餐厅推断的 92,905 条评论上进行了训练、测试和验证。
研究发现
与其他神经网络相比, 该模型实现了显着更好的性能。研究结果提供了经验证据, 以验证这种新方法在旅游酒店领域的适用性。
研究原创性
该研究提供了有关神经网络如何提高旅游酒店在线评论的面向方面的情感分类性能的新文献。
研究研究局限
应该识别更多的情感从而来更加细化衡量旅游酒店体验, 并推荐新的方面/维度可以被自动添加到方面集中, 为新的用餐体验提供动态支持。
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Xiaoyu Yang, Zhigeng Fang, Xiaochuan Li, Yingjie Yang and David Mba
Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing…
Abstract
Purpose
Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing technologies. The purpose of this paper is to construct a more accurate and stable grey model based on similar information fusion to predict the real-time remaining useful life (RUL) of aircraft engines.
Design/methodology/approach
First, a referential database is created by applying multiple linear regressions on historical samples. Then similarity matching is conducted between the monitored engine and historical samples. After that, an information fusion grey model is applied to predict the future degradation trajectory of the monitored engine considering the latest trend of monitored sensory data and long-term trends of several similar referential samples, and the real-time RUL is obtained correspondingly.
Findings
The results of comparative analysis reveal that the proposed model, which is called similarity-based information fusion grey model (SIFGM), could provide better RUL prediction from the early degradation stage. Furthermore, SIFGM is still able to predict system failures relatively accurately when only partial information of the referential samples is available, making the method a viable choice when the historical whole life cycle data are scarce.
Research limitations/implications
The prediction of SIFGM method is based on a single monotonically changing health indicator (HI) synthesized from monitoring sensory signals, which is assumed to be highly relevant to the degradation processes of the engine.
Practical implications
The SIFGM can be used to predict the degradation trajectories and RULs of those online condition monitoring systems with similar irreversible degradation behaviors before failure occurs, such as aircraft engines and centrifugal pumps.
Originality/value
This paper introduces the similarity information into traditional GM(1,1) model to make it more suitable for long-term RUL prediction and also provide a solution of similarity-based RUL prediction with limited historical whole life cycle data.
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Xiaoyu Wang, Hean Tat Keh and Li Yan
Frontline employees (FLEs) play a pivotal role in service delivery. Beyond their expected in-role behaviors, FLEs often have to perform extra-role behaviors such as providing…
Abstract
Purpose
Frontline employees (FLEs) play a pivotal role in service delivery. Beyond their expected in-role behaviors, FLEs often have to perform extra-role behaviors such as providing additional help to customers. The purpose of this study is to investigate how customers’ power distance belief (PDB) influences their perceptions of FLEs’ warmth and competence when FLEs perform extra-role helping behaviors.
Design/methodology/approach
Four experiments were conducted to test the hypotheses. The first three experiments used a one factor two-level (PDB: low vs high) between-participants design. The fourth one used a 2 (PDB: low vs high) × 2 (firm reputation: low vs high) between-participants design.
Findings
The results indicate that, compared to high-PDB customers, low-PDB customers perceive greater warmth in FLEs’ extra-role helping behaviors but no significant difference in FLEs’ perceived competence. Importantly, these effects are mediated by customer gratitude. Moreover, these effects are moderated by firm reputation such that customers’ perceptions of FLEs’ warmth and competence are both enhanced when the firm has a favorable reputation.
Originality/value
To the best of the authors’ knowledge, the study is the first to identify the differential effects of PDB on customer perceptions of FLEs’ warmth and competence in the context of FLEs’ extra-role helping behaviors and to reveal the mediating role of gratitude. These findings contribute to the literatures on FLEs’ extra-role behaviors and social perceptions of both warmth and competence.
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