Abstract The large-scale multi-attribute group decision-making (LSMAGDM) problem has become a hot research topic in the field of decision science. An R-numbers large-scale multi-attribute group ...decision-making (R-LSMAGDM) model is proposed to be constructed in this paper based on the advantages of R-numbers in capturing risks. First, the most commonly used clustering method, k -means, is introduced to determine the sub-groups. Then, a new sub-group weighting determination model is constructed by considering sub-group size and sub-group entropy. Next, we also build an optimized consensus-reaching model by improving the calculation method of the mean value. Then, the R-numbers weighted Hamy mean (RNWHM) operator is proposed to aggregate the sub-group information. In addition, the logarithmic percentage change-driven objective weighting (LOPCOW) method and the compromise ranking of alternatives from distance to ideal solution (CRADIS) method are used for attribute weighting calculation and alternative ranking, respectively. Finally, the effectiveness of the model is verified by an application example of hydrogen fuel cell logistics path selection.
In this article, we argue that folding back is successful when the learners engage in exploratory talk. To support our argument, we sourced data from a Grade 10 mathematics classroom of 54 learners ...who participated in a four-week teaching experiment conducted by the second author. We mainly focused on talks in two groups of learners to address the silence of literature on folding back that alludes to the kind of talk that learners engage in. Data were captured through video recording of learners' interactions as they worked on the tasks in different sessions. We present these data as transcribed extracts of talks that the learners held and synthesise them into stories through Polkinghorne's narrative mode of data analysis, also using a process that Kim referred to as narrative smoothing. Pirie and Kieren's conception of folding back and Wegerif and Mercer's three ways of talking and thinking among learners were used as a heuristic device for synthesising the stories. The narratives illustrate that exploratory talk promotes folding back, where learners build on each other's ideas to develop geometry understanding. Therefore, the significance of this article is that for classrooms that wish to promote growth in understanding through folding back, the type of talk that should be normative is exploratory talk.
Sociologists have long been interested in the meaning workers derive from their jobs. The issue has garnered increasing academic and policy attention in recent years with the concept of “meaningful ...work,” yet little is known about how social stratification relates to access to it. This paper addresses this issue by exploring how the meaningfulness of jobs—as rated by their incumbents—is stratified across classes and occupations in a national survey of 14,000 working adults in the United Kingdom. It finds modest differentials between classes, with those in routine and manual occupations reporting the lowest levels of meaningfulness and those in managerial and professional occupations and small employers and own account workers reporting the highest levels. Detailed job attributes (e.g., job complexity and development opportunities) explain much of the differences in meaningfulness between classes and occupations, and much of the overall variance in meaningfulness. The main exception is the specific case of how useful workers perceive their jobs to be for society: A handful of occupations relating to health, social care, and protective services which cut across classes stand out from all other occupations. The paper concludes that the modest stratification between classes and occupations in meaningful work is largely due to disparities in underlying job complexity and development opportunities. The extent to which these aspects of work can be improved, and so meaningfulness, especially in routine and manual occupations, is an open, yet urgent, question.
With the increasing amounts of UAVs usage, the supervision of unmanned aerial vehicles (UAV) has become particularly important, and the demand for detecting and following UAVs has grown rapidly. ...Compared with ground targets, UAVs are more difficult to track because of the high speed of the target and the interference caused by the shadow of either a target or a tracker. In addition, the problem of how to research the target when the target leaves the camera’s field of view has not received sufficient attention. In this paper, a shadow recognition algorithm and the detection network of a target based on deep learning are combined to eliminate the interference caused by shadows. Fuzzy control is applied in the process of following and the dynamic characteristics of UAV are considered in obstacle avoidance, which ensures the stability of the UAV for tracking. Finally, a spatial probability distribution algorithm based on Bayesian prediction is proposed for re-searching a lost target, which can rediscover a target after that target is lost. For this work, a UAV experimental platform has been built and the algorithm feasibility is verified through both simulation and a physical experiment.
Who you know: The classed structure of social capital Alecu, Andreea; Helland, Håvard; Hjellbrekke, Johs ...
The British journal of sociology,
June 2022, 2022-Jun-01, 2022-06-00, 20220601, Letnik:
73, Številka:
3
Journal Article
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This article focuses on the social structuring of social capital, understood as resources embedded in social networks. The analysis integrates key theoretical–methodological insights from two ...distinct approaches concerned with social capital and inequality: the position‐generator approach associated with Nan Lin and the spatial approach associated with Pierre Bourdieu. Empirically, we exploit the possibilities of survey data containing detailed information about the social ties of a representative sample of the Norwegian adult population (N = 4007). By means of Multiple Correspondence Analysis (MCA), we construct a space of social ties, a spatial representation of systematic similarities and differences between individuals' social ties to a set of 33 occupational positions. In this space, social capital is structured according to two primary dimensions: (i) the level of social ties, in terms of individuals' number of contacts; and (ii), the quality of social ties, in terms of a division between being connected to others in high‐status positions and others in low‐status positions. By means of Ascending Hierarchical Cluster analysis, five clusters are identified within the space of social ties: a homogenous working‐class cluster, a well‐connected working‐class cluster, a cluster of high‐status ties, a homogenous high‐status cluster and a low‐volume cluster. Moreover, the analysis clearly indicates that the structure of social capital is connected to respondents' class positions, their volumes of cultural and economic capital and their class origin. The analysis thus draws attention to the role of social capital in processes of social closure, regarding both resource monopolization and class formation.
A gravity matching algorithm is a crucial component of a vehicle's underwater navigation system. This article studies the improvement in the out-of-domain matching reliability and positioning ...accuracy of underwater navigation. To achieve these goals, a novel cyclic boundary semisquare-domain researching (CBSR) method is proposed. Two times the inertial error is first employed to span an initial small-square domain and find an initial optimal matching position, which results in controlling the matching efficiency. If this optimal position is located on the domain boundary, the cyclic boundary semisquare-domain rematching mechanism is triggered. The cyclic boundary semisquare domain is iteratively generated to perform repositioning and obtain a better matching position until it falls into the interior of the matching domain. The final optimal matching position is used to calibrate the sensor's parameters and aid the navigation of the underwater vehicle. Experimental results prove that the proposed CBSR method has outstanding positioning capacity for underwater gravity matching navigation and higher matching reliability and lower mismatching probability of the vehicle's out-of-domain positioning. For excellent and good suitable tracks, the number of out-of-domain mismatches of the CBSR method, compared with terrain contour matching (TERCOM), are reduced by 97.73% and 86.05%, respectively, while the out-of-domain average matching accuracies are all less than one grid resolution and are improved by 85.23% and 81.07%, indicating the effectiveness and feasibility of the proposed CBSR model for improving the matching reliability and positioning accuracy of out-of-domain underwater navigation.
This article focuses on historical elite dynamics and investigates elites' integration over time. We describe the changing relations and composition of the central circles in Swiss elite networks at ...seven benchmark years between 1910 and 2015 by relying on 22,262 elite individuals tied to 2587 organizations among eight key sectors, and identify for each year the most connected core of individuals. We explore network cohesion and sectoral bridging of the elite core and find that it moved from being a unitary corporate elite, before 1945, to an integrated corporatist elite, between the 1950s and 1980s, before fragmenting into a loose group, with an increased importance of corporate elites, in the 1990s onwards. The core was always dominated by business and their forms of legitimacy but, at times of crisis to the hegemony of corporate elites, after the Second World War and (only) shortly after the 2008 financial crisis, elite circles expanded and included individuals with delegated forms of power, such as politicians and unionists. In the most recent cohort (2015), the share of corporate elites in the core is similar to the one before the First World War and during the interwar period. This return to the past echoes findings on wealth inequality and economic capital accumulation by a small group of individuals organized around the most powerful companies.
There has been increased focus within the human dimensions of climate change on understanding the complex and multiple ways of 'knowing' climate. While these discussions are important in recognising ...different ways of knowing the climate and climate change processes already underway, we argue that this epistemological approach is limited and challenging. It begins with an assumption that there is one world (climate) out there that can just be known differently, and that knowledge can be isolated from ways of being and acting in the world. This often results in a distilling of complex knowledge practices into information for the purposes of integration. Drawing from a material-semiotic approach from Science and Technology Studies (STS), we propose a shift of focus to ontology, with an emphasis on the enactment of knowledge and reality (climate) simultaneously. We present ethnographic data from two drought events (2008/2009 and 2010/2011) among Maasai pastoralists in Northern Tanzania in East Africa to illustrate the value of such an approach, using multiple topologies (regional, network, fluid) for thinking through and following multiple enactments of drought in practice.
Efficient design of new processes and products requires not only an effective problem solving, but reliable forecasts of coming and distant changes. Decision making about investments into emerging ...technologies and strategic planning activities also rely upon consistent forecasts of technological substitution. There is a long record of applying different extrapolation techniques and, in particular, the logistic growth curves (S-curves) for studies about future changes. However, inappropriate use of S-shaped curves often leads to strange and inadequate results. Thus, among others, it is important to well define the system to forecast and provide an interpretable model from data.
The paper illustrates the use of single logistic curve and logistic component analysis focusing on the coherence between model, data and interpretation. Directions for improving these techniques are discussed and a process for unambiguous definition of system is introduced.
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