Search results

This study aims to provide a solution of the power flow calculation for the low-voltage ditrect current power grid. The direct current (DC) power grid is becoming a reliable and economic alternative to millions of residential loads. The power flow (PF) in the DC network has some similarities with the alternative current case, but there are important differences that deserve to be further concerned. Moreover, the dispatchable distributed generators (DGs) in DC network can realize the flexible voltage control based on droop-control or virtual impedance-based methods. Thus, DC PF problems are still required to further study, such as hosting all load types and different DGs.

The DC power analysis was explored in this paper, and an improved Newton–Raphson based linear PF method has been proposed. Considering that constant impedance (CR), constant current (CI) and constant power (CP) (ZIP) loads can get close to the practical load level, ZIP load has been merged into the linear PF method. Moreover, DGs are much common and can be easily connected to the DC grid, so V nodes and the dispatchable DG units with droop control have been further taken into account in the proposed method.

The performance and advantages of the proposed method are investigated based on the results of the various test systems. The two existing linear models were used to compare with the proposed linear method. The numerical results demonstrate enough accuracy, strong robustness and high computational efficiency of the proposed linear method even in the heavily-loaded conditions and with 10 times the line resistances.

The conductance corresponding to each constant resistance load and the equivalent conductance for the dispatchable unit can be directly merged into the self-conductance (diagonal component) of the conductance matrix. The constant current loads and the injection powers from dispatchable DG units can be treated as the current sources in the proposed method. All of those make the PF model much clear and simple. It is capable of offering enough accuracy level, and it is suitable for applications in DC networks that require a large number of repeated PF calculations to optimize the energy flows under different scenarios.

Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.

Interaction content is created during online learning interaction for the exchanged information to convey experience and share knowledge. Prior studies have mainly focused on the quantity of online learning interaction content (OLIC) from the perspective of types or frequency, resulting in a limited analysis of the quality of OLIC. Domain concepts as the highest form of interaction are shown as entities or things that are particularly relevant to the educational domain of an online course. The purpose of this paper is to explore a new method to evaluate the quality of OLIC using domain concepts.

This paper proposes a novel approach to automatically evaluate the quality of OLIC regarding relevance, completeness and usefulness. A sample of OLIC corpus is classified and evaluated based on domain concepts and textual features.

Experimental results show that random forest classifiers not only outperform logistic regression and support vector machines but also their performance is improved by considering the quality dimensions of relevance and completeness. In addition, domain concepts contribute to improving the performance of evaluating OLIC.

This paper adopts a limited sample to train the classification models. It has great benefits in monitoring students’ knowledge performance, supporting teachers’ decision-making and even enhancing the efficiency of school management.

This study extends the research of domain concepts in quality evaluation, especially in the online learning domain. It also has great potential for other domains.

As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform.

First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced.

Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO.

The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.

Bat algorithm (BA) is a global optimization method, but has a worse performance on engineering optimization problems. The purpose of this study is to propose a novel chaotic bat algorithm based on catfish effect (CE-CBA), which can effectively deal with optimization problems in real-world applications.

Incorporating chaos strategy and catfish effect, the proposed algorithm can not only enhance the ability for local search but also improve the ability to escape from local optima traps. On the one hand, the performance of CE-CBA has been evaluated by a set of numerical experiment based on classical benchmark functions. On the other hand, five benchmark engineering design problems have been also used to test CE-CBA.

The statistical results of the numerical experiment show the significant improvement of CE-CBA compared with the standard algorithms and improved bat algorithms. Moreover, the feasibility and effectiveness of CE-CBA in solving engineering optimization problems are demonstrated.

This paper proposed a novel BA with two improvement strategies including chaos strategy and catfish effect for the first time. Meanwhile, the proposed algorithm can be used to solve many real-world engineering optimization problems with several decision variables and constraints.

A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

Because of relatively short product life cycles, radical product innovation has more significant influences on firms' competitive advantages in dynamic environments. Past studies identified various cultural characteristics of a firm, which are key drivers of developing radical product innovation on an ongoing basis. However, few studies have investigated the interaction between organizational culture and external market feedback in developing radical product innovation.

To address the identified research gaps, this empirical research began by presenting conceptual foundations that lead to the hypothesized model and then analyzed survey data from 201 original equipment manufacturer suppliers in search of evidence supporting the hypotheses.

The results suggested that a supplier's entrepreneurial orientation and long-term orientation significantly and positively affected proactive market orientation, with proactive market orientation significantly and positively correlated with radical product innovation. The study confirmed that a proactive market orientation is essential in order for entrepreneurial orientation and long-term orientation to affect radical product innovation. Additionally, this study found that supplier–customer electronic integration has a moderating effect on proactive market orientation and radical product innovation.

Radical product innovation is a topic of great interest for both academia and industry, yet a comprehensive conceptual framework for its antecedents is still lacking. To fill this theoretical gap, the present study extended the studies on radical product innovation and examined the relationship between different strategic orientation types in terms of supplier–customer strategic behaviors to determine how suppliers enhance radical product innovation.

Previous studies have argued that trust and commitment can create value in cooperative relationships. However, this study observed that, in practice, trust and commitment alone may not ensure value creation in asymmetric relationships. Accordingly, this study aims to investigate the mediating role of specific assets in the effects of trust and commitment on value creation in asymmetric buyer–seller relationships.

Contract manufacturers (CMs) in Asia were sampled to validate the argument proposed by this study. Most Taiwanese CMs are partnered with international brands (original equipment manufacturers [OEMs]) that have stronger bargaining power. This cooperative relationship is characteristically asymmetric. A questionnaire method was applied, and structural equation modeling was performed to verify the proposed hypotheses.

Specific asset investment (SAI) was a crucial mediator that explained the effects of trust and commitment on the relationship value of an asymmetric cooperative relationship. Past studies have claimed that power asymmetry results in an unequal distribution of benefits. Nevertheless, regarding the relationship between CMs and OEMs, the study revealed that relationship value could still be increased once the congruent goals have been achieved by both parties. This finding contradicts past theoretical predictions.

Characteristically asymmetric CMs–OEMs (seller–buyer) relationships cannot be maintained merely through trust and commitment, particularly in the context of power and resource imbalances in which the stronger party often possesses a wider selection of prospective partners. The results of this study suggested that the CM should unilaterally invest in specific assets conducive to a cooperative relationship as an expression of faith in the relationship with the stronger firm, thereby creating opportunities for value cocreation.

The analysis of the relevance of relationship quality in the context of asymmetric cooperative relationships confirmed the mediating influences of SAI on ensuring value creation and the maintenance of the relationships. Relationship value could still be created despite the highly asymmetry power relationship. The CMs’ SAI is the key mechanism for this achievement.

This paper aims to study a high-temperature (up to 200 °C) data acquisition and processing circuit for logging.

With the decrease in thermal resistance by system-in package technology and exquisite power consumption distribution design, the circuit worked well at high temperatures environment from both theoretical analysis and real experiments evaluation.

In thermal simulation, considering on board chips’ power consumption as additional heat source, the highest temperature point reached by all the chips in the circuit is only 211 °C at work temperature of 200 °C. In addition, the proposed circuit was validated by long time high-temperature experiments. The circuit showed good dynamic performance during a 4-h test in a 200-°C oven, and maintained a signal-to-noise ratio of 92.54 dB, a signal-to-noise and distortion ratio of 91.81 dB, a total harmonic distortion of −99.89 dB and a spurious free dynamic range of 100.28 dB.

The proposed circuit and methodology showed great potential for application in deep-well logging systems and other high-temperature situations.

Although adaptation to climate change is a well-researched topic at the individual level and in highly vulnerable industries, its integration into business strategies is poorly researched. In this chapter, we conduct bibliometric analyses on a sample of 368 relevant papers published in business journals to derive descriptive statistics and map the conceptual and intellectual structure of the field. We find an increased interest in adaptation and confirm a strong representation of industry-specific research. We complement the bibliometric analyses with a content analysis focused on emergent themes in the adaptation scholarship. We discuss systemic influences, individual effects, regulations and stakeholders, and exposure as areas likely to attract further scrutiny in future scholarship. For each theme, we derive practical implications for practitioners and policymakers.