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This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

In the shaft and end windings of large turbogenerators, unacceptably high mechanical stresses can occur as a result of subsynchronous resonances (SSRs) in the system network-generator-shaft. These stresses can cause severe damages. Subsynchronous resonances are characterized by the occurrence of currents and electromagnetic torques in the air gap of the generator with frequencies that are significantly below the synchronous frequency. When simulating the balancing processes in multi-machine networks, the generators are represented by Canay’s equivalent circuit diagrams. The parameters used here are determined from geometric dimensions of the generator, taking into account material properties, and verified by means of surge short-circuit tests in which the 50 and 100 Hz components are dominant. This paper aims to examine whether the parameters of the equivalent circuit diagram determined in this way reproduce correctly the dynamic behavior of a synchronous machine, even if the SSR occur.

The simulation program NETOMAC is used to simulate the SSRs for different parameters. The results of these simulations are then compared with those obtained by the finite difference (FD) method calculations.

The comparison of the waveforms calculated with NETOMAC and FELMEC for an SSR shows that the original equivalent circuit diagram parameters provide satisfactory results. An extension of Canay’s equivalent circuit diagram is not necessary. Optimization of the discussed parameters leads to a significant improvement in comparison to the calculation with the parameters from the generator data sheet.

The unresolved doubt has been proven, that the Parka generator model with the manufacturer’s parameters can also be used for subsynchronous studies of electromechanical resonances of systems. However, it was advisable to improve the simulation results by optimizing the generator parameters used in the calculations. By optimizing the parameters for the SSRs, the calculation of the occurring torques has been significantly improved.

The design phase is generally characterized with two-way multiple information exchanges/overlaps between the interdependent entities. In this paper, entity is a generic term to represent teams, components, activities or parameters. Existing approaches can either capture a single overlap or lack practical application in representing multiple overlaps. The beeline diagraming method (BDM) network is efficient in representing multiple overlaps for construction projects. However, it considers any entity as indivisible and cannot distinguish partial criticality of entities. In reality, the design phase in any construction project is driven by need basis and often has numerous interruptions. Hence, there is a need to develop an alternate network analysis for BDM for interruptible execution. The paper aims to discuss these issues.

A pilot study is conducted to formulate the hypothetical examples. Subsequently, these hypothetical BDM examples are analyzed to trace a pattern for criticality. This pattern study along with the existing precedence diagramming method network analysis enabled to derive new equations for forward pass, backward pass and float. Finally, the proposed concepts are applied to two design cases and reviewed with the design experts.

The proposed network analysis for BDM is efficient for interruptible entity execution.

The proposed BDM network is an information-intensive network that enables the design participants to view the project holistically. Application to two distinct cases emphasizes that the concept is generic and can be applied to any project that is characterized with beelines.

An alternate network analysis for BDM is investigated for interruptible entity execution. This study also clarifies the related concepts – interdependency, iteration, overlaps and multiple information exchanges/linkages.

The purpose of this paper is to discuss the identification of the model parameters for constitutive model capable of representing the failure of massive structures, from two kinds of experiments: a uniaxial tensile test and a three‐point bending test.

A detailed development of the ingredients for constitutive model for failure of massive structures are presented in Part I of this paper. The salient feature of the model is in its ability to correctly represent two different failure mechanisms for massive structures, the diffuse damage in so‐called fracture process zone with microcracks and localized damage in a macrocrack. The identification of such model parameters is best performed from the tests under heterogeneous stress field. Two kinds of tests are used: the simple tension test and the three‐point bending test. The former allows us illustrate the non‐homogeneity of the strain field at failure even under homogeneous stress, whereas the latter provides a very good illustration for the proposed inverse optimization problem for which the specimen is subjected to a heterogeneous stress field.

Several numerical examples are presented in order to illustrate a very satisfying performance of the proposed methodology for identifying the corresponding material parameters of the constitutive model for failure of massive structures.

The paper confirms that one can make a very good use of the proposed identification procedure for estimating the corresponding parameters of damage model for localized failure of massive structure, and the advantages to using the experimental results obtained by testing under heterogeneous stress field.

The purpose of this research is to propose a new model for the integration of concurrent function deployment (CFD) and parameter (P) diagram in order to prioritize innovation factors.

Each of the approaches of CFD and P diagram and their features has been demonstrated and according to their common features, an integrated model has been designed in two phases. It has been examined in Sepahan Industrial Group, of which the major product is API gas pipeline network demanded by Isfahan Province Gas Organization. A questionnaire has been designed and delivered to four major units of Isfahan Province Gas Organization.

“Hydrostatic test” and “number of close end branch pipes” with the average values of 4.78 and 3.31 have been found as the first and last priorities of importance to customers, respectively. The output of the first phase includes “equipments” as the first priority of control factors, and “changing market or customers wants” as the first priority of noise factors. The results of the second phase show that “fault‐free product” and “successful innovation outcomes” are, respectively, recognized as first priorities of response factors. Finally, “successful innovation outcomes” has been determined as the first priority of response factors.

The matrixes of the two phases could become larger if the number of factors in the P diagram increases, and therefore, filling and analyzing the matrixes might become time consuming and difficult.

The proposed integrated model can be effective for almost all organizations that aim to meet the dynamic needs of markets and customers and intend to incorporate innovation in their products and services. By the new approach, determination and prioritization of innovation factors can be done based on customers' viewpoint, while in the traditional approaches this was done only from the viewpoint of engineers and designers.

Fiber-reinforced armor-grade polymer-matrix composite materials with a superior penetration resistance are traditionally developed using legacy knowledge and trial-and-error empiricism. This approach is generally quite costly and time-consuming and, hence, new (faster and more economical) approaches are needed for the development of high-performance armor-grade composite materials. One of these new approaches is the so-called materials-by-design approach. Within this approach, extensive use is made of the computer-aided engineering (CAE) analyses and of the empirically/theoretically established functional relationships between an armor-grade composite-protected structure, the properties of the composite materials, material microstructure (as characterized at different length-scales) and the material/structure synthesis and fabrication processes. The paper aims to discuss these issues.

In the present work, a first step is made toward applying the materials-by-design approach to the development of the armor-grade composite materials and protective structures with superior ballistic-penetration resistance. Specifically, CAE analyses are utilized to establish functional relationships between the attributes/properties of the composite material and the penetration resistance of the associated protective structure, and to identify the combination of these properties which maximize the penetration resistance. In a follow-up paper, the materials-by-design approach will be extended to answer the questions such as what microstructural features the material must possess in order for the penetration resistance to be maximized and how such materials should be synthesized/processed.

The results obtained show that proper adjustment of the material properties results in significant improvements in the protective structure penetration resistance.

To the authors’ knowledge, the present work is the first reported attempt to apply the materials-by-design approach to armor-grade composite materials in order to help improve their ballistic-penetration resistance.

Road pricing is an efficient strategy for managing urban traffic to relieve congestion. The macroscopic fundamental diagram (MFD), which relates the average network density and flow, is a simple tool for assessing road pricing effects on transportation network performance. However, recent research indicates that it may have complexity (an MFD hysteresis loop), especially for city-scale networks. Although ignoring MFD hysteresis may provide inaccurate results, pricing models that consider this hysteresis are scarce. This paper aims to assess road pricing effects on network performance considering MFD hysteresis characteristics.

This paper evaluated different pricing strategies spatially and temporally and compared network performance based on MFD shape in the presence of MFD hysteresis loops. These strategies were developed on a multimodal (cars and buses) network using a multi-agent transport simulation (MATSim).

This study found that pricing some links for a short duration with an optimum charge calculated based on the MFD provides higher travel time savings than the previous relevant studies.

These findings may facilitate assessing road pricing effects on multimodal network performance considering MFD hysteresis.

This study aims to improve the complexity of chaotic systems and the security accuracy of information encrypted transmission. Applying five-dimensional memristive Hopfield neural network (5D-HNN) to secure communication will greatly improve the confidentiality of signal transmission and greatly enhance the anticracking ability of the system.

Chaos masking: Chaos masking is the process of superimposing a message signal directly into a chaotic signal and masking the signal using the randomness of the chaotic output. Synchronous coupling: The coupled synchronization method first replicates the drive system to get the response system, and then adds the appropriate coupling term between the drive The synchronization error and the coupling term of the system will eventually converge to zero with time. The synchronization error and coupling term of the system will eventually converge to zero over time.

A 5D memristive neural network is obtained based on the original four-dimensional memristive neural network through the feedback control method. The system has five equations and contains infinite balance points. Compared with other systems, the 5D-HNN has rich dynamic behaviors, and the most unique feature is that it has multistable characteristics. First, its dissipation property, equilibrium point stability, bifurcation graph and Lyapunov exponent spectrum are analyzed to verify its chaotic state, and the system characteristics are more complex. Different dynamic characteristics can be obtained by adjusting the parameter k.

A new 5D memristive HNN is proposed and used in the secure communication

Prefabricated construction is often hindered by scheduling delays. This paper aims to propose a schedule delay prediction model system, which can provide the key information for controlling the delay effects of risk-related factors on scheduling in prefabricated construction.

This paper combines SD (System Dynamics) and BP (Back Propagation) neural network to predict risk related delays. The SD-based prediction model focuses on dynamically presenting the interrelated impacts of risk events and activities along with workflow. While BP neural network model is proposed to evaluate the delay effect for a single risk event disrupting a single job, which is the necessary input parameter of SD-based model.

The established model system is validated through a structural test, an extreme condition test, a sensitivity test, and an error test, and shows an excellent performance on aspect of reliability and accuracy. Furthermore, 5 scenarios of case application during 3 different projects located in separate cities prove the prediction model system can be applied in a wide range.

This paper contributes to academic research on combination of SD and BP neural network at the operational level prediction, and a practical prediction tool supporting managers to take decision-making in a timely manner against delays.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.