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Urban parks play a key role in recreational activities, public health, and ecosystem services in urban areas. Using GIS and Fragstats, this study investigated the spatiotemporal dynamics of urban parks in Xi'an, China from 1949 to 2015 and the corresponding driving forces. The results show that the number and area of parks in Xi'an increased constantly during this period, especially from 2000 to 2015. Up to 2015, small green spaces, usually adjacent to streets, occupied the largest proportion among all types of parks. Archaeological parks were the largest in total area, but wetland parks were leading in average size of a single park. The density of parks was negatively correlated with their distance to the Clock Tower at the center of Xi'an. The dynamics of urban parks in highly urbanized areas were significantly different from that of their counterparts in suburban areas. Driving forces such as urban planning, urbanization and green space policies, and milestone events in the city's development jointly had a great effect on the distribution of parks in Xi'an. The research outcomes will support the upcoming Green Space Planning of Xi'an and benefit the pursuit of sustainability and human wellbeing.

The purpose of this paper is to explore the influence of PRINCE2 (PRoject IN Controlled Environments 2) standard on customer satisfaction jointly with vendor relationship management capability in the information technology outsourcing (ITO) context. This paper further tries to explore the above underlying mechanism by studying the mediating effect of deliverable quality.

This paper develops a mediated moderation model to explain the underlying influence processes of PRINCE2 standard, vendor relationship management capability and deliverable quality on ITO customer satisfaction. By conducting a pair-wise survey of 260 project managers in seven Iranian firms, the model and hypotheses are empirically tested with the partial least squares method.

Our results suggest that firms benefit more in terms of IT costs reduction when they have a higher level of complementary investment in an external standard, especially through an interplay effect of the external standard and internal relational aspect. Firms can make business processes more amenable to outsourcing and facilitate monitoring of vendor performance and effective coordination with vendors. More interestingly, we find that this interactive effect is fully mediated by deliverable quality, which, in turn, directly increases ITO customer satisfaction.

This study adds some new knowledge and provides new views to study ITO customer satisfaction by addressing the importance of PRINCE2 standard. This study further enhances our understanding in terms of the underlying pathway through which the PRINCE2 standard jointly affects customer satisfaction with vendor relationship management capability and deliverable quality. With the effort of explicitly explaining the complex mechanisms, this study helps ITO managers proactively escort outsourcing activities and projects.

The purpose of this paper is to probe the recursive identification of piecewise affine Hammerstein models directly by using input-output data. To explain the identification process of a parametric piecewise affine nonlinear function, the authors prove that the inverse function corresponding to the given piecewise affine nonlinear function is also an equivalent piecewise affine form. Based on this equivalent property, during the detailed identification process with respect to piecewise affine function and linear dynamical system, three recursive least squares methods are proposed to identify those unknown parameters under the probabilistic description or bounded property of noise.

First, the basic recursive least squares method is used to identify those unknown parameters under the probabilistic description of noise. Second, multi-innovation recursive least squares method is proposed to improve the efficiency lacked in basic recursive least squares method. Third, to relax the strict probabilistic description on noise, the authors provide a projection algorithm with a dead zone in the presence of bounded noise and analyze its two properties.

Based on complex mathematical derivation, the inverse function of a given piecewise affine nonlinear function is also an equivalent piecewise affine form. As the least squares method is suited under one condition that the considered noise may be a zero mean random signal, a projection algorithm with a dead zone in the presence of bounded noise can enhance the robustness in the parameter update equation.

To the best knowledge of the authors, this is the first attempt at identifying piecewise affine Hammerstein models, which combine a piecewise affine function and a linear dynamical system. In the presence of bounded noise, the modified recursive least squares methods are efficient in identifying two kinds of unknown parameters, so that the common set membership method can be replaced by the proposed methods.

This research proposes an innovative fault-tolerant media content list management technology applied to the smart robot domain.

A fault tolerant Content List Management Unit (CLMU) for real-time streaming systems focusing on smart robot claw machines is proposed to synchronize and manage the hyperlink stored on media servers. The fault-tolerant mechanism is realized by the self-healing method. A media server allows exchanging the hyperlink within the network through the CLMU mechanism.

Internet users can access the current multimedia information, and the multimedia information list can be rearranged appropriately. Furthermore, the service of the proposed multimedia system should be uninterrupted even when the master media server fails. Therefore, one of the slave media servers enables the Content List Service (CLS) of the proposed CLMU and replaces the defunct master media server.

The recovery time is less than 1.5 seconds. The multimedia transmission is not interrupted while any one of the media servers keeps functioning. The proposed method can serve to stabilize the system of media servers in a smart robot domain.

The purpose of this study is to develop optimal evacuation plan to provide valuable theoretical and practical insight in the fire evacuation work of similar structures, by proposing a systematic simulation-based guided-evacuation agent-based model (GAM) and a three-stage mathematical evacuation model to investigate how to simulate, assess and improve the performance efficiency of the evacuation plan.

The authors first present the self-evacuation and guided-evacuation models to determine the optimal evacuation plan in ship chamber. Three key performance indicators are put forward to quantitatively assess the evacuation performance within the two fire scenarios. The evacuation model in tower is built to obtain the dividing points of the three different fire evacuation plans.

The study shows that the optimal evacuation plan determined by the GAM considering social relationships effectively relieves the congestion or collision of evacuees and improves the evacuation uniformity. The optimal evacuation plan not only solves the crush caused by congestion or collision of evacuees but also can greatly shorten the evacuation time for passenger ship fire.

This study establishes the GAM considering the interactive evacuee characteristics and the proportion of evacuees guided by the crew members to make the optimal evacuation plan more time-efficient. The self-evacuation process is simulated to assess the performance of the guided-evacuation strategies, which are used to verify the effectiveness and feasibility of the optimal evacuation plan in this research.

The purpose of this study is to provide ideas and theoretical guidance for green, environmentally friendly and efficient “bacteriostasis with bacteria” technology.

In this paper, a beneficial strain of bacteria was extracted and purified from marine mud. Weight-loss test, morphological observation and electrochemical test were used to systematically study the effect of sulfate-reducing bacteria (SRB)-induced corrosion inhibition on X65 steel in simulated offshore oil field production water.

The results showed that a beneficial strain was selected and identified as Vibrio alginolyticus. Under the condition of co-culture of SRB, the average corrosion rate of X65 steel was significantly reduced. In the mixed bacterial system, the surface of X65 steel samples was relatively flat, and the structure of biofilm and corrosion product film was dense. The number of corrosion pits, the average diameter and depth of corrosion pits were significantly reduced. The localized corrosion of X65 steel was significantly inhibited.

The complex and changing marine environment makes the corrosion problem of marine steel increasingly severe, and the microbiologically influenced corrosion (MIC) caused by SRB is particularly serious. The research and development of environmentally friendly corrosion protection technology is a long-term and difficult problem. The use of beneficial microorganisms to control MIC is a green and efficient anticorrosion measure. Compared with terrestrial microorganisms, marine microorganisms can adapt to complex environments, and their metabolites exhibit special biological activities. The use of marine beneficial bacteria can inhibit SRB activity to achieve the corrosion inhibition effect.

Online reviews increasingly present the characteristic of bidirectional communication with the advent of Web 2.0 era and tend to be asymmetrical and individualized in linguistic information. The authors aim to develop a new linguistic conversion model that exploits the asymmetric and personalized information from online reviews to express such linguistic information. A new online recommendation approach is provided.

The necessity of new linguistic conversation model is elucidated, and a leverage factor is incorporated into the linguistic label of negative review to handle the asymmetry problems of linguistic scale. A possible value range of the leverage factor is studied. A new linguistic conversation model is accordingly established with an unbalanced linguistic label and a cloud model. The authors develop a new online recommendation approach based on several modules, such as initialization, conversion, user-clustering and recommendation models.

The unbalanced effect between negative and positive reviews is verified with real data and measured using indirect methods. A new online recommendation approach of electronic products is proposed and used as an illustrative example to prove the practicality, effectiveness and feasibility of the proposed approach.

Due to the unavailable transaction information of customers, the limitation of this study is the effectiveness of the authors’ established recommendation system for platform or website cannot be verified.

In most existing studies, the influence of negative review is counterbalanced by positive review, and the unbalanced effect between negative and positive reviews is ignored. The negative review receives much attention from consumers and businesses. This study thus highlights the influence of negative review.

The purpose of this paper is to explore the underlying mechanisms through which interactivity and fairness perception impart influence on solvers’ continuance intention in crowdsourcing contest settings.

On basis of self-determination theory and social exchange theory, this study focuses on the mediating roles of motivation and platform trust to explain the underlying influence processes of interactivity and fairness perception on continuance intention. A sample of 306 solvers was obtained from an online crowdsourcing platform through two separated surveys. The hypotheses were tested using the partial least squares method and bias-corrected bootstrapping method.

The empirical results indicate that motivation and platform trust together fully mediate the effect of interactivity on continuance intention, and the effect of fairness perception on continuance intention is also fully mediated by motivation and platform trust. While motivation is found to have a stronger mediating effect than platform trust does.

This study contributes to the crowdsourcing research by figuring out the pathway through which interactivity and fairness perception influence solvers’ continuance intention.

The purpose of this paper is to explore the underlying mechanisms through which integration capability and learning capability influence IT outsourcing performance from vendor’s perspective.

This paper develops a moderated mediation model to explain the underlying influence processes of integration capability and learning capability on vendor’s performance. A sample of 237 vendor firms was obtained from China through two separated surveys. The hypotheses were tested with the partial least squares method and bias-corrected bootstrapping method.

The empirical results indicate that external integration capability (EIC) mediates the effect of internal integration capability (IIC) on vendor outsourcing performance, and the relationship between EIC and vendor performance is positively moderated by learning capability, while learning capability has a negative moderating effect on the link between IIC and vendor performance. Further, the conditional indirect effect is suggested. The indirect effect of IIC on vendor performance through EIC becomes non-significant when learning capability is low.

This study highlights the counterintuitive notion that learning capability may not always have uniformly positive effects and figure out the mechanism through which integration capability and learning capability can effectively improve IT outsourcing performance.

Quality function deployment (QFD) has been widely applied in new product development, but existing research on QFD has some limitations. Primarily, QFD lacks the capability to provide feedback on the satisfaction degree of customer requirements (CRs) according to the actual values of engineering characteristics (ECs). In addition, QFD does not quantitatively consider the interrelationships among ECs. Reverse QFD (R-QFD) was introduced to implement the feedback process. On this basis, this paper quantitatively considers the interrelationships among ECs in the R-QFD model and extends these relationships to encompass combinations of multiple ECs, aiming to improve the inference accuracy of the model.

A nonlinear regression model was established between CRs and ECs, aiming to infer the satisfaction degree of CRs based on the implementation status of ECs. This model considers the interdependencies among ECs and extends the consideration of pairwise EC correlations from every two to every fifteen. Lingo Software is utilized to seek solutions for this program. To facilitate the implementation of the program, a directive to simplify the solution has been proposed.

The experimental results indicate that the interrelationships among ECs significantly affect the inference accuracy of the R-QFD model, thereby verifying the necessity of considering higher-order interrelationships among ECs within the R-QFD framework. Based on the results from data experiments, this paper also proposes research recommendations pertaining to ECs hierarchy for varying quantities of ECs.

The outcomes of this study have further refined the R-QFD model, addressing its limitations of ignoring the interrelationships among ECs. This transformation elevates the R-QFD model from a relatively simple linear model to a nonlinear model formed through modeling, thereby enhancing its accuracy and applicability. In practical terms, this study provides case support for the application of the R-QFD model in manufacturing industry.