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The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the IoT-enabled Context-aware BPM (IoT-CaBPM) framework to bridge from the IoT infrastructure to context-aware business processes.

Motivated by the “Three Waves” of BPM research, IoT-enabled context-awareness is, therefore, expected to be achieved for enhancing the business process design, which pilots a new wave of BPR (Business Process Redesign/Reengineering) to enable the business process coevolve with IoT and analytics. This paper reports an illustrative case study of BPR in a Chinese bulk port, one of the hub seaports that widely adopted IoT technologies over the last few years.

The IoT implementation and data analytics has increased the efficiency and improve the monitoring effectively. The proposed IoT-CaBPM framework availably helps to identify and match nodes of IoT devices, business decisions and analytic models in order to redesign a business process towards context-aware variability. As IoT is rapidly becoming the new dominant IT paradigm is moving towards mature implementation in various industries, the corresponding BPR must be planned and executed strategically for achieving better benefits.

Despite some research extend BPM standard by integrating IoT devices as a sort of resources or report generically that the ports operations are affected by IoT, there is still a lack of layers from the IoT infrastructure to context-aware business processes. An industrial BPR case with business models in detail is also a lack for presenting the specific implications and effectiveness of the adoption of such technologies. This paper fills in this gap.

This paper aims to elucidate the systemic processes underlying the enhanced information-control measures taken by the Chinese Communist Party (CCP) under the leadership of President Xi Jinping. The tightening of state information control has stimulated increasingly sophisticated methods of disseminating information on the part of professional and citizen journalists. Drawing on social systems theory as articulated by Niklas Luhmann and others, the authors frame the CCP’s enhanced information-control efforts as a response to the increasing systemic complexity of Chinese journalism, which is part of a self-reproducing, self-regulating (autopoietic) global journalism system. The authors use both subtle and overt protests over Chinese censorship as evidence for the journalism system’s increasing complexity and autonomy. The authors observe that levels of complexity ratchet up as the CCP and Chinese journalism counter each other’s moves. Finally, the authors suggest that the increasing complexity of the CCP’s information-control apparatus may be unsustainable.

The authors ground their argument in Luhmannian social systems theory.

The CCP's effort to control journalism leads to increased internal complexity in the form of huge bureaucracies that themselves must be overseen in an almost endless proliferation of surveillance.

This paper contributes to theoretical work in post-humanism.

To the authors’ knowledge, no studies have examined the tension between CCP censors and Chinese journalism from a Luhmannian systems theory perspective.

Food recalls are more potentially harmful than other product recalls. This research aimed to investigate the effect of the recall strategies of food corporations on their brand image and consumers’ purchase intention.

This study adopts a between-subjects experiment of 2 (corporate recall strategy: voluntary recall, mandatory recall) *3 (food recall level (severity): high, medium, low), and recruits 224 consumers involved in cereal product recall in China. The authors inductively examine the effects of voluntary and mandatory recall on consumer perception and behavior intentions in the recall process.

Voluntary recall (vs. mandatory recall) will improve corporate brand responsibility image (vs. brand ability image) and consumers’ purchase intention to focal brand (vs. competitive brand and organic brand). Perceived corporate legitimacy and food safety play a mediating role. The former has a greater positive impact on brand image, and the latter has a more significant favorable influence on purchase intention. Furthermore, recall level has a moderating effect on the association between corporate recall strategy and perceived food safety, but is not significant in the effect of corporate recall strategy on perceived corporate legitimacy.

Previous inconsistent conclusions cannot effectively guide food corporations to manage recall strategies. This paper demonstrates the response mechanism of the recall strategy from the perspective of corporate social responsibility, which is beneficial to food safety crisis management and research.

This paper examines diverging views on the Chongqing model, the policy experiment led by Bo Xilai from 2007 to 2012 that was famous for its “red songs” and the campaign against organized crime. It has impressed both the supporters of socialist identity of China and the supporters of liberal identity and led to an intense debate concerning China’s path of development. This paper attempts to discuss and clarify to what extent the Chongqing model represented a genuine socialist experiment and the implications of the model for China’s future.

The purpose of this paper is to investigate relationships of urban seismic resilience assessment indicators.

To achieve this aim, construction of the urban seismic resilience assessment indicators system was conducted and 20 indicators covering five dimensions, namely building and lifeline infrastructure, environment, society, economy and institution were identified. Following this, this study used evidence fusion theory and intuitionistic fuzzy sets to process the information from experts then developed the fuzzy total interpretive structure model.

A total of 20 urban seismic resilience assessment indicators are reconstructed into a hierarchical and visual system structure including five levels. Indicators in the bottom level including debris flow risk, landslide risk, earthquake experience and demographic characteristics are fundamental indicators that significantly impact other indicators. Indicators in the top level including open space, gas system and public security are direct indicators influenced more by other indicators. Other indicators are in middle levels. Results of MICMAC analysis visually categorize these indicators into independent indicators, linkage indicators, autonomous indicators and dependent indicators according to driving power and dependence.

This paper attempts to explore relationships of urban seismic resilience assessment indicators with the interpretive structural model method. Additionally, Fuzzy total interpretive structure model is developed combined with evidence fusion theory and intuitionistic fuzzy sets, which is the extension of total interpretive structure model. Research results can assist the analytic network process method in assessing urban seismic resilience in future research.

The purpose of this paper is to investigate the corrosion behaviors of 2A12 aluminum alloy in NaCl and EXCO solution, and establish the relationship between the corrosion depth and the time.

Alternate immersion corrosion test chamber was used to perform the corrosion test. The corrosion mediums were 3.5 percent NaCl solution and EXCO solution (NaCl 234 g/L, KNO3 50 g/L, 68 percent HNO3 6.8 mL/L). The surface morphology was studied using the digital microscope.

The average corrosion rate of aluminum alloy in NaCl solution decreased gradually at the initial stage and then went to a plateau value. The average corrosion rate of aluminum alloy in EXCO solution increased first, then showed a downward trend. The empirical function D=At B was verified.

The results could provide a reference for the establishment of accelerated environmental spectrum in the laboratory and give instructions on the application of aluminum alloy in alternated dry and wet environment.

The purpose of this research paper is to design a disturbance observer-based control based on the robust model reference adaptive backstepping sliding-mode control for attitude quadrotor model subject to uncertainties and disturbances.

To estimate and reject the disturbance, a disturbance observer is designed for the exogenous disturbances with perturbation while a control criterion is developed for the tracking of desired output. To achieve the control performance, backstepping and sliding-mode control techniques are patched together to obtain robust chattering-free controller. Furthermore, a model reference adaptive control criterion is also combined with the design of robust control for the estimation and rejection of uncertainties and unmodeled dynamics of the attitude quadrotor.

The findings of this research work includes the design of a disturbance observer-based control for uncertain attitude quadrotor system with the ability of achieving tracking control objective in the presence of nonlinear exogenous disturbance with and without perturbation.

In practice, the quadrotor flight is opposed by different kinds of the disturbances. In addition, being an underactuated system, it is difficult to obtain an accurate mathematical model of quadrotor for the control design. Thus, a quadrotor model with uncertainties and disturbances is inevitable. Hence, it is necessary to design a control system with the ability to achieve the control objectives in the presence of uncertainties and disturbances.

Designing the control methods for quadrotor control without uncertainties and disturbances is a common practice. However, investigating the uncertain quadrotor plant in the presence of nonlinear disturbances is rarely taken into consideration for the control design. Hence, this paper presents a control algorithm to address the issues of the uncertainties and disturbances as well as investigate a control algorithm to achieve tracking performance.

The purpose of this paper is to survey the technical performance of the cement industry including those related to procedures; groundwork of raw materials, fuels and semi-finished products for processing; accessibility of machinery, plant and equipment for various operations; arrangement and process control management.

A broad range of survey and research was reviewed, and all revealed the methods to recognize the key influences for development of green technology. The study explores the present scenario of green manufacturing (GM) strategies of Indian cement companies and provides the industrial ecology, ways of reducing energy consumption, environmental impact data collection, design and control of manufacturing systems and integration of product and manufacturing system. It also reveals the problems in decision-making systems owing to the impact of the green product design. Here, in this paper, all information is obtained by the medium of internet, journals, articles, and magazines.

This paper describes a problem of global warming, gas, water and other wastages emissions at the time of cement manufacturing and put forward a path that enables decision makers to assess the perception of GM in their organization and in prioritizing GM efforts.

This perspective survey is to provide an integrative outlook of performance methods for GM practices in the Indian cement industries. It gives important information, which expectantly will help in cement industry to adopt GM practices. This paper fills the gap in the literature on identification, establishment, and validation of performance measures of GM for Indian cement industries.

Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.

Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.

Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.

This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.