Customized bus services are conducive to improving urban traffic and environment, and have attracted widespread attention. However, the problems encountered in the new customized bus mode include the large difference between the basis of customized bus passenger flow data analysis and the basis of the traditional bus passenger flow data analysis, and the difficulty in different vehicle scheduling caused by the combination of traditional and customized bus modes. We propose a customized bus passenger flow analysis algorithm and multi-destination customized bus (...) line capacity scheduling algorithm, and display them in an intuitive way. The experimental results show that the algorithm model established in this paper can basically meet the data requirements of operation and management, and can provide decision support for customized bus line planning. (shrink)

For unmanned aerial vehicle, object detection at different scales is an important component for the visual recognition. Recent advances in convolutional neural networks have demonstrated that attention mechanism remarkably enhances multiscale representation of CNNs. However, most existing multiscale feature representation methods simply employ several attention blocks in the attention mechanism to adaptively recalibrate the feature response, which overlooks the context information at a multiscale level. To solve this problem, a multiscale feature filtering network is proposed in this paper for image (...) recognition system in the UAV. A novel building block, namely, multiscale feature filtering module, is proposed for ResNet-like backbones and it allows feature-selective learning for multiscale context information across multiparallel branches. These branches employ multiple atrous convolutions at different scales, respectively, and further adaptively generate channel-wise feature responses by emphasizing channel-wise dependencies. Experimental results on CIFAR100 and Tiny ImageNet datasets reflect that the MFFNet achieves very competitive results in comparison with previous baseline models. Further ablation experiments verify that the MFFNet can achieve consistent performance gains in image classification and object detection tasks. (shrink)

This field study investigated the relationship between strategic human resource management, internal environmental concern, organizational citizenship behavior for the environment, and environmental performance. The originality of the present research was to link human resource management and environmental management in the Chinese context. Data consisted of 151 matched questionnaires from top management team members, chief executive officers, and frontline workers. The main results indicate that organizational citizenship behavior for the environment fully mediates the relationship between strategic human resource management and environmental (...) performance, and that internal environmental concern moderates the effect of strategic human resource management on organizational citizenship behavior for the environment. (shrink)

Children's utterances from late infancy to 3 years of age were examined to infer their conception of knowledge. In Study 1, the utterances of two English-speaking children were analysed and in Study 2, the utterances of a Mandarin-speaking child were analysed – in both studies, for their use of the verb know. Both studies confirmed that know and not know were used to affirm, query or deny knowledge, especially concerning an ongoing topic of conversation. References to a third party were (...) rare. By implication, 2-year-olds have a conception of knowledge that underpins their exchange of information in conversation. Implications for the child's developing theory of mind are discussed. (shrink)

Research on knowledge hiding has largely focused on its antecedents while overlooking its consequences. Drawing on moral cleansing theory, we adopt a “perpetrator-centric view” and posit that employees who engage in playing dumb and evasive hiding–two specific knowledge hiding behaviors that involve deception–will subsequently perform more organizational citizenship behavior directed toward individuals (OCB-I) because they perceive a loss of moral credits following their moral transgression. Further, we propose that the indirect effects are contingent on perpetrators’ moral identity internalization. We tested (...) our hypotheses using a time-lagged research design with a sample of 362 respondents from a large pharmaceutical group company. Consistent with our hypotheses, we found that employees who engaged in playing dumb and evasive hiding subsequently exhibited more OCB-I as they perceived a loss of moral credits, whereas employees who engaged in rationalized hiding did not. In addition, the positive relationships between playing dumb and evasive hiding with perceived loss of moral credits were stronger when perpetrators had high moral identity internalization, as were the indirect effects of playing dumb and evasive hiding on OCB-I via perceived loss of moral credits. Our research contributes to the understanding of when and how engaging in knowledge hiding affects perpetrators and their compensatory behaviors toward coworkers. (shrink)

Yang returns to the problem of referential ambiguity, addressed in the opening paper by Gleitman and Trueswell. Using a computational approach, he argues that “big data” approaches to resolving referential ambiguity are destined to fail, because of the inevitable computational explosion needed to keep track of contextual associations present when a word is uttered. Yang tests several computational models, two of which depend on one‐trial learning, as described in Gleitman and Trueswell’s paper. He concludes that such models outperform (...) cross‐situational learning models, thereby formalizing, reinforcing, and advancing the conclusions offered by Gleitman and Trueswell. (shrink)

The target article by David Alfandre et al. offers a new ethical framework to guide COVID-19 contingency surge planning and response, and applies this ethical framework to three case example...

The purpose of this study is to extend prior research on this topic by investigating whether the impact of ownership concentration moderates the link between corporate social performance and financial performance. This study uses a set of unique, hand-collected pollution control data to measure CSP, based on a sample of Taiwanese listed companies during the period from 1996 to 2006. The results of the empirical analysis provide firm support for the idea that the divergence between control rights and the cash (...) flow rights of controlling owners negatively moderates the link between social and short- and long-run FP. (shrink)

This paper investigates the moderating role of industry regulation on the effectiveness of audit committees in restricting earnings management. Using comprehensive panel data of S&P 1500 firms between 2003 and 2007, we find that the proportion of CEO directors on an audit committee is positively associated with earnings management in unregulated industries, while this association is significantly weaker in regulated industries. Further, the proportion of financial experts on an audit committee is negatively associated with earnings management. Our results also indicate (...) that the average board tenure of audit committee members is negatively related to earnings management in regulated industries, but positively affects earnings management in unregulated industries. Finally, audit committee members’ average directorship increases earnings management in regulated industries, but reduces earnings management in unregulated industries. Overall, our results suggest that the effectiveness of audit committees in reducing earnings management and improving financial reporting quality is influenced by industry regulation. (shrink)

The concept of digital twinning has become a hot topic in the manufacturing industry in recent years. The emerging digital twin technology is an intelligent technology that makes full use of multimodels, big data, and interdisciplinary knowledge, which provides some new approaches for the field of the intelligent manufacturing industry. The job shop scheduling problem has been an important research field in the discrete manufacturing industry. Digital twin technology is adopted to solve the problem of job shop scheduling, which provides (...) the possibility for the intelligent development of workshops. Based on digital twin technology and combined with the actual problem of production line scheduling, we propose a new intelligent scheduling platform to solve the shop scheduling problems above. Meanwhile, based on the prediction and diagnosis of multisource dynamic interference in the workshop production process by big data analysis technology, the corresponding interference strategy is formulated in advance by the scheduling cloud platform. The model simulation experiment of intelligent dispatching cloud platform was carried out, and some enterprises in intelligent manufacturing workshop were taken as examples to verify the superiority of the dispatching cloud platform. Finally, we look forward to the future research direction of intelligent manufacturing based on digital twin technology. (shrink)

The initial online publication contained a typesetting mistake in the author information. The original article has been corrected.

In this paper, we track the motion of multiple targets in sports videos by a machine learning algorithm and study its tracking technique in depth. In terms of moving target detection, the traditional detection algorithms are analysed theoretically as well as implemented algorithmically, based on which a fusion algorithm of four interframe difference method and background averaging method is proposed for the shortcomings of interframe difference method and background difference method. The fusion algorithm uses the learning rate to update the (...) background in real time and combines morphological processing to correct the foreground, which can effectively cope with the slow change of the background. According to the requirements of real time, accuracy, and occupying less video memory space in intelligent video surveillance systems, this paper improves the streamlined version of the algorithm. The experimental results show that the improved multitarget tracking algorithm effectively improves the Kalman filter-based algorithm to meet the real-time and accuracy requirements in intelligent video surveillance scenarios. (shrink)

This study examined the effect of emotional context on the semantic memory of subsequent emotional words during discourse comprehension in two eye-tracking experiments. Four-sentence discourses were used as experimental materials. The first three sentences established an emotional or neutral context, while the fourth contained an emotional target word consistent with the preceding emotional context's valence. The discourses were presented twice using the text change paradigm, where the target words were replaced with strongly - or weakly-related words during the second presentation. (...) Thus, four conditions were included in the present study: Emotional-strongly-related, Emotional-weakly-related, Neutral-strongly-related and Neutral-weakly-related. In Experiment 1, negative contexts and negative target words were used, whereas in Experiment 2, positive contexts and positive target words were used. The results revealed a semantic relatedness effect, whereby the strongly-related words have lower change detection accuracy, longer reading times and more fixations in both Experiments 1 and 2. Furthermore, across both experiments, the magnitude of the semantic relatedness effect was greater in the emotionally congruent contexts than in the neutral contexts. These results suggest that emotional context could increase efforts to change the discrimination of subsequent words and demonstrate an important role of emotional context on semantic memory during discourse processing. (shrink)

In economic researches, much effort was devoted to the problem of how to increase the economics of countries. However, the development of a country may fluctuate a lot due to international and domestic problems. Thus, we should also evaluate the robustness of countries against unexpected economic recessions. In this paper, we use perturbation to quantify the robustness of countries using two renowned algorithms: method of reflections and fitness-complexity method. The robustness characterizes the stability of countries’ competitiveness against economic recessions. The (...) experiments in the international trade networks show that FCM could characterize the robustness better than MR. High fitness countries of FCM have strong robustness against economic crises, which enlarges the application fields of FCM. Additionally, we simulate the trade conflict between USA and China. The simulation results show that China suffers much in the trade conflict, while USA loses very little and has strong robustness in this conflict. (shrink)

This paper uses panel OLS, IV, and system GMM methods to empirically study the effects of manufacturing and producer service corporate co-agglomeration on green economy efficiency in China. Chinese panel data from 2000 to 2019 are collected to assess the GEE and co-agglomeration degrees. The regression results show that there is an “inverted U-shaped” relationship between co-agglomeration and GEE. However, regional heterogeneity is found in the effects of corporate co-agglomeration on GEE. The mediating analysis indicates that corporate co-agglomeration could increase (...) GEE through business entrepreneurship and innovation entrepreneurship. Variables such as transportation infrastructure, human capital, foreign direct investment, and environmental regulations are also found to have an elevating effect on GEE, whereas local fiscal expenditure on environmental protection has little effect. The findings in this paper indicate that entrepreneurship plays an important role in the process of co-agglomeration impacting GEE which differs in different regions and thus provide references for corporate and regional sustainable development. (shrink)

This paper investigates a composite learning prescribed performance control scheme for uncertain strict-feedback system. Firstly, a prescribed performance boundary condition is developed for the tracking error, and the original system is transformed into an equivalent one by using a transformation function. In order to ensure that the tracking error satisfies the PPB, a sufficient condition is given. Then, a control scheme of PPC combined with neural network and backstepping technique is proposed. However, the unknown functions cannot be guaranteed to estimate (...) accurately by this method. To solve this problem, predictive errors are defined by applying online recorded date and instantaneous date. Furthermore, novel composite learning laws are proposed to update NN weights based on a partial persistent excitation condition. Subsequently, the stability of the closed-loop system is guaranteed and all signals are kept bounded by using composite learning PPC method. Finally, simulation results verify the effectiveness of the proposed methods. (shrink)

Four experiments examined the strategies that individuals develop in sentential reasoning. They led to the discovery of five different strategies. According to the theory proposed in the paper, each of the strategies depends on component tactics, which all normal adults possess, and which are based on mental models. Reasoners vary their use of tactics in ways that have no deterministic account. This variation leads different individuals to assemble different strategies, which include the construction of incremental diagrams corresponding to mental models, (...) and the pursuit of the consequences of a single model step by step. Moreover, the difficulty of a problem (i.e., the number of mental models required by the premises) predisposes reasoners towards certain strategies. Likewise, the sentential connectives in the premises also bias reasoners towards certain strategies, e.g., conditional premises tend to elicit reasoning step by step whereas disjunctive premises tend to elicit incremental diagrams. (shrink)

Business Ethics, the Environment &Responsibility, Volume 31, Issue 3, Page 620-633, July 2022.

In this paper, we mainly investigate the existence of states based on the Glivenko theorem in bounded semihoops, which are building blocks for the algebraic semantics for relevant fuzzy logics. First, we extend algebraic formulations of the Glivenko theorem to bounded semihoops and give some characterizations of Glivenko semihoops and regular semihoops. The category of regular semihoops is a reflective subcategory of the category of Glivenko semihoops. Moreover, by means of the negative translation term, we characterize the Glivenko variety. Then (...) we show that the regular semihoop of regular elements of a free algebra in the variety of Glivenko semihoops is free in the corresponding variety of regular semihoops. Similar results are derived for the semihoop of dense elements of free Glivenko semihoops. Finally, we give a purely algebraic method to check the existence of states on Glivenko semihoops. In particular, we prove that a bounded semihoop has Bosbach states if and only if it has a divisible filter, and a bounded semihoop has Riečan states if and only if it has a semi-divisible filter. (shrink)

Business Ethics: A European Review, EarlyView.

Extant studies on private regulation have not reached a sufficient understanding about the interplay between private and public regulations, due to underdeveloped theoretical framework and the lack of large-sample empirical investigations. Leveraging ISO 14001 adoption among Chinese firms as the research context, the current research draws on the institutional theory to examine how firm’s adoption of ISO 14001 standard, as a specific form of private regulation, affects the incidence of public environmental inspections. To test our arguments, we conduct two empirical (...) studies. Study 1 uses the first-hand data of a corporate social responsibility survey on Chinese manufacturing firms, whereas Study 2 deploys the second-hand longitudinal archival data of the government environmental inspections on Chinese listed firms. Both of the two studies reveal consistent findings that ISO 14001 adoption decreases the incidence of government environmental inspections, and that the effect of ISO 14001 adoption becomes stronger in state-owned enterprises and firms with top management team’s political ties. Our findings are suggestive of a complementary relationship between private and public regulations, in a sense that private regulations can compensate for the weaknesses of public regulations by offering faster, more flexible and cost-efficient means of enforcement, which allows the public authorities to economize on the deployment of public resources to monitor the rest non-compliant firms. (shrink)

Implicational tonoid logics and their relational semantics have been introduced by Yang and Dunn. This paper extends this investigation to implicational partial Galois logics. For this, we first define some implicational partial gaggle logics as special kinds of implicational tonoid logics called “implicational partial Galois logics.” Next, we provide Routley–Meyer-style relational semantics for finitary those logics.

This paper presents an adaptive neural tracking control approach for a two-joint robotic manipulator with unknown time-varying delays. In order to work out the effect of unknown time-varying delays on the two-joint robotic manipulator, the appropriate Lyapunov–Krasovskii functionals and separation technology are chosen to settle this matter. The neural networks work as an approximator that has the advantage of estimating the unknown function in the system. In this paper, Lyapunov stability analysis can prove that all signals of the closed-loop system (...) are semiglobal uniformly ultimately bounded and the tracking error can converge to a compact neighborhood with respect to zero. The simulation consequences demonstrate the availability of the feedforward control approach. (shrink)

The brain-computer interface based on functional near-infrared spectroscopy has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals’ features based on transfer learning and ensemble learning theory. In detail, we used the Independent Component Analysis algorithm for (...) the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study’s findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface. (shrink)

In the presence of heterogeneity between the randomized controlled trial (RCT) participants and the target population, evaluating the treatment effect solely based on the RCT often leads to biased quantification of the real-world treatment effect. To address the problem of lack of generalizability for the treatment effect estimated by the RCT sample, we leverage observational studies with large samples that are representative of the target population. This article concerns evaluating treatment effects on survival outcomes for a target population and considers (...) a broad class of estimands that are functionals of treatment-specific survival functions, including differences in survival probability and restricted mean survival times. Motivated by two intuitive but distinct approaches, i.e., imputation based on survival outcome regression and weighting based on inverse probability of sampling, censoring, and treatment assignment, we propose a semiparametric estimator through the guidance of the efficient influence function. The proposed estimator is doubly robust in the sense that it is consistent for the target population estimands if either the survival model or the weighting model is correctly specified and is locally efficient when both are correct. In addition, as an alternative to parametric estimation, we employ the nonparametric method of sieves for flexible and robust estimation of the nuisance functions and show that the resulting estimator retains the root- n n consistency and efficiency, the so-called rate-double robustness. Simulation studies confirm the theoretical properties of the proposed estimator and show that it outperforms competitors. We apply the proposed method to estimate the effect of adjuvant chemotherapy on survival in patients with early-stage resected non-small cell lung cancer. (shrink)

Mental representations are more than emulations. Different types of representations, including external representations, various mental models (distorted and abstract), and emulative models, can all play important roles in human cognition. To explain cognitive performance in a specific task, a systematic analysis of the underlying representational structures and their interactions is needed.