Search results

The current understanding of serendipity is based primarily on studies employing westerners as the participants, and it remains uncertain whether or not this understanding would be pervasive under different cultures, such as in China. In addition, there is not a sufficient systematic investigation of context during the occurrence of serendipity in current studies. The purpose of this paper is to examine the above issues by conducting a follow-up empirical study with a group of Chinese scholars.

The social media application “WeChat” was employed as a research tool. A diary-based study was conducted and 16 participants were required to send to the researchers any cases of serendipity they encountered during a period of two weeks, and this was followed by a post-interview.

Chinese scholars experienced serendipity in line with the three main processes of: encountering unexpectedness, connection-making and recognising the value. An updated context-based serendipity model was constructed, where the role of context during each episode of experiencing serendipity was identified, including the external context (e.g. time, location and status), the social context and the internal context (e.g. precipitating conditions, sagacity/perceptiveness and emotion).

The updated context model provides a further understanding of the role played by context during the different processes of serendipity. The framework for experiencing serendipity has been expanded, and this may be used to classify the categories of serendipity.

With the continuous technological development of automated driving and expansion of its application scope, the types of on-board equipment continue to be enriched and the computing capabilities of on-board equipment continue to increase and corresponding applications become more diverse. As the applications need to run on on-board equipment, the requirements for the computing capabilities of on-board equipment become higher. Mobile edge computing is one of the effective methods to solve practical application problems in automated driving.

In this study, in accordance with practical requirements, this paper proposed an optimal resource management allocation method of autonomous-vehicle-infrastructure cooperation in a mobile edge computing environment and conducted an experiment in practical application.

The design of the road-side unit module and its corresponding real-time operating system task coordination in edge computing are proposed in the study, as well as the method for edge computing load integration and heterogeneous computing. Then, the real-time scheduling of highly concurrent computation tasks, adaptive computation task migration method and edge server collaborative resource allocation method is proposed. Test results indicate that the method proposed in this study can greatly reduce the task computing delay, and the power consumption generally increases with the increase of task size and task complexity.

The results showed that the proposed method can achieve lower power consumption and lower computational overhead while ensuring the quality of service for users, indicating a great application prospect of the method.

Autonomous driving depends on the collection, processing and analysis of environmental information and vehicle information. Environmental perception and processing are important prerequisite for the safety of self-driving of vehicles; it involves road boundary detection, vehicle detection, pedestrian detection using sensors such as laser rangefinder, video camera, vehicle borne radar, etc.

Subjected to various environmental factors, the data clock information is often out of sync because of different data acquisition frequency, which leads to the difficulty in data fusion. In this study, according to practical requirements, a multi-sensor environmental perception collaborative method was first proposed; then, based on the principle of target priority, large-scale priority, moving target priority and difference priority, a multi-sensor data fusion optimization algorithm based on convolutional neural network was proposed.

The average unload scheduling delay of the algorithm for test data before and after optimization under different network transmission rates. It can be seen that with the improvement of network transmission rate and processing capacity, the unload scheduling delay decreased after optimization and the performance of the test results is the closest to the optimal solution indicating the excellent performance of the optimization algorithm and its adaptivity to different environments.

In this paper, the results showed that the proposed method significantly improved the redundancy and fault tolerance of the system thus ensuring fast and correct decision-making during driving.

The purpose of this paper is to show how a quartz crystal microbalance modified with poly (epichlorohydrin) (PECH) is fabricated and used for detection of acetone vapor using a spin‐coating method.

Measurements are based on the frequency shifts due to the adsorption of acetone vapor on the surface of the modified electrodes. A first‐order linear time‐invariant (LTI) system model is used to simulate the sensor response.

It is found that frequency shifts are linear to the concentrations of analyte, and cycle test examination shows good repeatability. The sensitivity to acetone vapor is better than other volatile compounds. A good match result is obtained with the LTI system model.

The device performance opens a potential way for analyzing acetone vapor.

This study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors investigate the moderating role of three categories of visitors – direct, hesitant and hedonic – in the relationship between product information diversity and consumer decision making.

The research utilizes a sample of 1,101,062 product click streams from 4,200 consumers. Visitors are clustered using the k-means algorithm. The diversity of information recommendations for single and multi-category products is characterized using granularity and dispersion, respectively. Empirical analysis is conducted to examine their influence on the two-stage decision-making process of heterogeneous online visitors.

The study reveals that the impact of recommended information diversity on consumer decision making differs significantly between single-category and multiple-category products. Specifically, information diversity in single-category products enhances consumers' click and purchase intention, while information diversity in multiple-category products reduces consumers' click and purchase intention. Moreover, based on the analysis of online visiting heterogeneity, hesitant, direct and hedonic features enhance the positive impact of granularity on consumer decision making; while direct features exacerbate the negative impact of dispersion on consumer decision making.

First, the article provides support for studies related to information cocoon. Second, the research contributes evidence to support the information overload theory. Third, the research enriches the field of precision marketing theory.

This paper provides the strategic direction and coordination mechanism selection for the intelligent transformation of manufacturing enterprises.

A theoretical framework is developed through grounded theory and case analysis.

Collaboration value is the building block of the intelligent product ecosystem. The ecosystem is upgraded via a path of product coordination, platform coordination and network coordination.

This paper provides a framework for enterprises to build an intelligent product ecosystem.

The proposed intelligent product ecosystem framework is new to the literature and lays down a fruitful avenue for future research.

Significant numbers of business process management (BPM) projects fail. Their failure is attributed toward many factors. Among them, low quality of BPM is one reason. Some of the tasks in BPM have their roots in business process reengineering (BPR). The literature has cited many different critical success and failure factors for quality BPM and BPR. Lack of software tools is one of the technology-oriented factors that results in poor BPM and BPR. This paper aims to build a generic feature set offered by software tools for process modeling their analysis implementation and management. It presents an objective analysis in identifying weaknesses and strengths of these tools, primarily for BPM.

A method is proposed to evaluate the quality of process reengineering and management delivered by software tools. It consists of four phases: feature extraction, tool selection, data extraction and tool evaluation.

The data gathered is quantified to test research hypotheses, the results are statistically significant and highlight multiple areas for future improvements. Moreover, the cluster visualizations created also help to understand the strengths and weaknesses of BPM/BPR tools.

Despite the research approach used, there is a chance of subjectivity when it comes to evaluating different tools.

The paper includes implications for practitioners and researchers for choosing appropriate software tool for process modeling, analysis, implementation and management, matching their requirements with BPM and BPR. It also identifies features that are missing in these tools.

This paper provides a comprehensive analysis of BPM and supporting tools, relates them to key stages of BPM life cycle and BPR methodologies. It also identifies various areas for further development in these tools.

The effects of the thermo-mechanical treatment on the properties and microstructure of the Al–Cu–Mg–Ag alloy were investigated.

A short-duration preprecipitation process is designed prior to predeformation aging. The novel predeformation aging (solution treatment + holding at 185 °C for 15 min+ rolling deformation + aging at 185 °C, also named T8) was performed on a heat-resistant Al–Cu–Mg–Ag alloy.

The purpose of this study indicate that a short-duration heat treatment before predeformation is beneficial to the precipitation of O during the aging process. The precursors of O during this process might pin the dislocation and cause the grains to orient along some specific direction, which might be advantageous to the precipitation of O while disadvantageous to that of θ′. This novel thermal-mechanical process could result in an increase in the quantity and decrease in the size of the precipitation of O, which leads to a remarkable strength effect. The potential increases while the current density decreases with an increase in the deformation amount, which implies a smaller intergranular corrosion rate. The fine deformed structure leads to an opposite behavior in the exfoliation corrosion test compared with that for intergranular corrosion.

The intergranular corrosion resistance of the Al–Cu–Mg–Ag alloy is enhanced, whereas the exfoliation corrosion resistance is reduced by novel predeformation aging.

The purpose of this paper is to propose an approach to detect Indirect Memory‐Corruption Exploit (IMCE) at runtime on binary code, which is often caused by integer conversion error. Real‐world attacks were evaluated for experimentation.

Current dynamic analysis detects attacks by enforcing low level policy which can only detect control‐flow hijacking attack. The proposed approach detects IMCE with high level policy enforcement using dynamic taint analysis. Unlike low‐level policy enforced on instruction level, the authors' policy is imposed on memory operation routine. The authors implemented a fine‐grained taint analysis system with accurate taint propagation for detection.

Conversion errors are common and most of them are legitimate. Taint analysis with high‐level policy can accurately block IMCE but have false positives. Proper design of data structures to maintain taint tag can greatly improve overhead.

This paper proposes an approach to block IMCE with high‐level policy enforcement using taint analysis. It has very low false negatives, though still causes certain false positives. The authors made several implementation contributions to strengthen accuracy and performance.