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A matrix is a
Abstract
A matrix is a
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This article examines the history, development, and application of the sandwich estimate of variance. In describing this estimator, we pay attention to applications that…
Abstract
This article examines the history, development, and application of the sandwich estimate of variance. In describing this estimator, we pay attention to applications that have appeared in the literature and examine the nature of the problems for which this estimator is used. We describe various adjustments to the estimate for use with small samples, and illustrate the estimator’s construction for a variety of models. Finally, we discuss interpretation of results.
Satya R. Chakravarty, Nachiketa Chattopadhyay, Nora Lustig and Rodrigo Aranda
This paper attempts to interpret the Bartholomew (1973) index of mobility in terms of a directional mobility index based on the one-step expected states of movement…
Abstract
This paper attempts to interpret the Bartholomew (1973) index of mobility in terms of a directional mobility index based on the one-step expected states of movement corresponding to a specific state of transition matrix. A partial ordering of directional mobility of a general state of transition matrices, referred to as “upward mobility favoring sequential averaging (UMFSA),” is proposed using the algebraic equivalent of the generalized Lorenz ordering of expected states. When the underlying mobility depends on the initial distribution of the states, using a Bayesian approach, the indices are reexamined for a general class of matrices. This enables us to interpret the Prais (1955) and Bibby (1975) mobility index in this framework.
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Matrix structures are complex and conflict prone, so multinational enterprises (MNEs) would utilize them only if they conferred some advantage over less complex…
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Matrix structures are complex and conflict prone, so multinational enterprises (MNEs) would utilize them only if they conferred some advantage over less complex organizational structures. Based upon the information-processing view, a theory of matrix advantage is proposed. It is supported by a secondary analysis of data from a major study of German MNEs. Matrix structures are shown to have an advantage over the elementary structural types. Specifically, the matrix structures fit higher levels of transnational strategy than elementary structures. Transnational strategy is assessed by two concepts: firm internationalization (involvement in foreign sales, manufacturing, and research and development (R&D)) and corporate integration (intracompany transfers). Moreover, three-dimensional matrices are associated with higher levels of transnational strategy than are two-dimensional matrices, confirming the gains from having additional structural dimensions. Matrix structures arise because of the need to simultaneously fit high levels of both firm internationalization and corporate integration. Matrices fit the transnational strategy type of Bartlett and Ghoshal. Implications are drawn for the relationship between the head office and the subsidiary. The matrix often subjects the subsidiary to conflicting expectations from the head office, which it can attempt to manage. Similarly, the head office is challenged by the task of integrating the information that comes from different dimensions of the matrix.
James P. LeSage and R. Kelley Pace
For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely…
Abstract
For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.
Wei Yu and Junpeng Chen
The purpose of this paper is to explore the potential of enriching the library subject headings with folksonomy for enhancing the visibility and usability of the library…
Abstract
Purpose
The purpose of this paper is to explore the potential of enriching the library subject headings with folksonomy for enhancing the visibility and usability of the library subject headings.
Design/methodology/approach
The WorldCat-million data set and SocialBM0311 are preprocessing and over 210,000 library catalog records and 124,482 non-repeating tags were adopted to construct the matrix to observe the semantic relation between library subject headings and folksonomy. The proposed system is compared with the state-of-the-art methods and the parameters are fixed to obtain effective performance.
Findings
The results demonstrate that by integrating different semantic relations from library subject headings and folksonomy, the system’s performance can be improved compared to the benchmark methods. The evaluation results also show that the folksonomy can enrich library subject headings through the semantic relationship.
Originality/value
The proposed method simultaneous weighted matrix factorization can integrate the semantic relation from the library subject headings and folksonomy into one semantic space. The observation of the semantic relation between library subject headings and social tags from folksonomy can help enriching the library subject headings and improving the visibility of the library subject headings.
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Gokcin Cinar, Elena Garcia and Dimitri N. Mavris
The purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The…
Abstract
Purpose
The purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The intent for these evaluations was to account for varying operation strategies and to support architectural design space decisions, at the conceptual design stages, rather than single-point design solutions.
Design/methodology/approach
To this end, main propulsion subsystems were categorized into energy, power and thrust sources. Two types of matrices, namely, the property and interdependency matrices, were created to describe the relationships and power flows among these sources. These matrices were used to define various electrified propulsion architectures, including, but not limited to, turboelectric, series-parallel and distributed electric propulsion configurations.
Findings
As a case study, the matrices were used to generate and operate the distributed electric propulsion architecture of NASA’s X-57 Mod IV aircraft concept. The mission performance results were acceptably close to the data obtained from the literature. Finally, the matrices were used to simulate the changes in the operation strategy under two motor failure scenarios to demonstrate the ease of use, rapidness and automation.
Originality/value
It was seen that this new framework enables rapid and analysis-based comparisons among unconventional propulsion architectures where solutions are driven by requirements.
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Yanhui Liu, Lingjie Zhu, Lei Zhou and Yongjiu Li
This paper aims to explore the influence of the reinforcement included either glass beads (GBs) or carbon fiber (CF) on the reinforced polyamide 12 (PA12) composite…
Abstract
Purpose
This paper aims to explore the influence of the reinforcement included either glass beads (GBs) or carbon fiber (CF) on the reinforced polyamide 12 (PA12) composite samples prepared by selective laser sintering (SLS).
Design/methodology/approach
In this paper, the microstructure and mechanical properties are investigated, and the results are compared with those obtained for non-reinforced pure PA12 samples prepared by SLS.
Findings
The tensile fracture surface of the non-reinforced pure PA12 sample presents strong micro-deformation within the crack origination zone between the melted PA12 matrix and the un-melted PA12 particle cores. As a result, the pure PA12 sample exhibits the greatest maximum elongation. The maximum tensile strength is obtained for the CF reinforced sample because of the strengthening effect of CF and the relatively good bonding between CFs and the PA12 matrix. The minimum tensile strength is obtained for the GB reinforced PA12 sample because of the relatively weak bonding between GBs and the PA12 matrix.
Originality/value
These results demonstrate that the characteristics of the interfaces between the reinforcement and the PA12 matrix have an important influence on the fracture mechanisms and mechanical properties of PA12 composites fabricated by SLS.
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Chemmalar Selvi G. and Lakshmi Priya G.G.
In today’s world, the recommender systems are very valuable systems for the online users, as the World Wide Web is loaded with plenty of available information causing the…
Abstract
Purpose
In today’s world, the recommender systems are very valuable systems for the online users, as the World Wide Web is loaded with plenty of available information causing the online users to spend more time and money. The recommender systems suggest some possible and relevant recommendation to the online users by applying the recommendation filtering techniques to the available source of information. The recommendation filtering techniques take the input data denoted as the matrix representation which is generally very sparse and high dimensional data in nature. Hence, the sparse data matrix is completed by filling the unknown or missing entries by using many matrix completion techniques. One of the most popular techniques used is the matrix factorization (MF) which aims to decompose the sparse data matrix into two new and small dimensional data matrix and whose dot product completes the matrix by filling the logical values. However, the MF technique failed to retain the loss of original information when it tried to decompose the matrix, and the error rate is relatively high which clearly shows the loss of such valuable information.
Design/methodology/approach
To alleviate the problem of data loss and data sparsity, the new algorithm from formal concept analysis (FCA), a mathematical model, is proposed for matrix completion which aims at filling the unknown or missing entries without loss of valuable information to a greater extent. The proposed matrix completion algorithm uses the clustering technique where the users who have commonly rated the items and have not commonly rated the items are captured into two classes. The matrix completion algorithm fills the mean cluster value of the unknown entries which well completes the matrix without actually decomposing the matrix.
Findings
The experiment was conducted on the available public data set, MovieLens, whose result shows the prediction error rate is minimal, and the comparison with the existing algorithms is also studied. Thus, the application of FCA in recommender systems proves minimum or no data loss and improvement in the prediction accuracy of rating score.
Social implications
The proposed matrix completion algorithm using FCA performs good recommendation which will be more useful for today’s online users in making decision with regard to the online purchasing of products.
Originality/value
This paper presents the new technique of matrix completion adopting the vital properties from FCA which is applied in the recommender systems. Hence, the proposed algorithm performs well when compared to other existing algorithms in terms of prediction accuracy.
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