A measure of standing of journals in stratified networks

The concept of a stratified journal network is advanced where the nodes are journals and the relation is citation aggregated over the articles in these journals. The standing of the journals in the network can be measured through tools based on input-output models. These measures can be used to chart the changing status of journals at different time points.     

An efficient similarity measure technique for medical image registration

In this paper, an efficient similarity measure technique is proposed for medical image registration. The proposed approach is based on the Gerschgorin circles theorem. In this approach, image registration is carried out by considering Gerschgorin bounds of a covariance matrix of two compared images with normalized energy. The beauty of this approach is that there is no need to calculate image features like eigenvalues and eigenvectors. This technique is superior to other well-known techniques such as normalized cross-correlation method and eigenvalue-based similarity measures since it avoids the false registration and requires less computation. The proposed approach is sensitive to small defects and robust to change in illuminations and noise. Experimental results on various synthetic medical images have shown the effectiveness of the proposed technique for detecting and locating the disease in the complicated medical images.     

A revised measure of standing of journals in stratified networks

A modified index of journal standing in a stratified journal to journal citation network is proposed. The original index, generated through an application of input-output analysis, is used as the first step of an iterative procedure that converges on the new index. This index, an eiginvector of the inverted matrix used in the input-output analysis, has improved validity and better distributional properties than the original index.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

Relative measure index: a metric to measure the quality of journals

Journal impact factors (JIF) have been an accepted indicator of ranking journals. However, there has been increasing arguments against the fairness of using the JIF as the sole ranking criteria. This resulted in the creation of many other quality metric indices such as the h-index, g-index, immediacy index, Citation Half-Life, as well as SCIMago journal rank (SJR) to name a few. All these metrics have their merits, but none include any great degree of normalization in their computations. Every citation and every publication is taken as having the same importance and therefore weight. The wealth of available data results in multiple different rankings and indexes existing. This paper proposes the use of statistical standard scores or z-scores. The calculation of the z-scores can be performed to normalize the impact factors given to different journals, the average of z-scores can be used across various criteria to create a unified relative measurement (RM) index score. We use the 2008 JCR provided by Thompson Reuters to demonstrate the differences in rankings that would be affected if the RM-index was adopted discuss the fairness that this index would provide to the journal quality ranking.     

Using mutual information as a cocitation similarity measure

Scientometrics - The debate regarding to which similarity measure can be used in co-citation analysis lasted for many years. The mostly debated measure is Pearson’s correlation coefficient r....     

A multiple-link,mutually reinforced journal-ranking model to measure the prestige of journals

Scientometrics - This paper presents a novel model of science funding that exploits the wisdom of the scientific crowd. Each researcher receives an equal, unconditional part of all available...     

A novel similarity measure towards effective recommendation using Matusita coefficient for Collaborative Filtering in a sparse dataset

Collaborative Filtering (CF) is a prominent approach to ensure personalized recommendations to active online users. An efficient CF is the memory-based strategy that finds nearest neighbours to an active user using conventional similarity measures. Most such measures deal with a co-rated item rated by a pair of users and hence they are not appropriate to provide an effective recommendation to a sparse dataset having less co-rated items. This study proposes a novel similarity measure, Matusita coefficient in CF (MCF), which considers all ratings given by a user to estimate nearest neighbours. MCF considers local and global rating information provided by users on different rating scales. The performance of the proposed measure is examined and checked by comparing it to conventional measures using popular benchmark datasets like MovieLens and Netflix. The recommendation results demonstrate that the proposed measure outperforms conventional similarity measures on various performance metrics like Mean Absolute Error, Root Mean Squared Error, accuracy, precision, recall and coverage.     

Measuring the similarity between the reference and citation distributions of journals

The “Jaccardized Czekanowski index”, JCz, an indicator measuring the similarity between the cited and citing journal list of a given journal is proposed in the paper. It is shown that the indicator characterizes the network properties of individual journals and, in aggregated form, also that of subject categories or countries. For subject categories, JCz appears to be related to the multidisciplinarity of the category. For countries, the multinational or local character of the publishers seems to have determining role.     

A Hirsch-type index for journals

Summary We suggest that a h-type index - equal to h if you have published h papers, each of which has at least h citations - would be a useful supplement to journal impact factors.     

Infrared target tracking with kernel-based performance metric and eigenvalue-based similarity measure

An infrared target tracking framework is presented that consists of three main parts: mean shift tracking, its tracking performance evaluation, and position correction. The mean shift tracking algorithm, which is a widely used kernel-based method, has been developed for the initial tracking for its efficiency and effectiveness. A performance evaluation module is applied for the online evaluation of its tracking performance with a kernel- based metric to unify the tracking and performance metric within a kernel-based tracking framework. Then the tracking performance evaluation result is input into a controller in which a decision is made whether to trigger a position correction process. The position correction module employs a matching method with a new eigenvalue-based similarity measure computed from a local complexity degree weighted covariance matrix. Experimental results on real-life infrared image sequences are presented to demonstrate the efficacy of the proposed method.     

A new systematic formalism for similarity analysis

Summary A new systematic formalism is presented for similarity analysis—i.e., for reducing the number of independent variables in systems consisting of partial differential equations and a set of auxiliary conditions. The formalism is a specialization of previous group theory techniques developed by the authors. Concurrent with its presentation, and to illustrate that it is particularly well suited for practical similarity analyses, the formalism is applied to certain three-dimensional incompressible boundary layer flows; and a variety of results are elicited which exhibit somewhat greater generality than any previously reported for the class of flows.     

A multivariate model for evaluating emergency medicine journals

Scientometrics - This paper proposes a multivariate model for the evaluation of international emergency medicine journals using the most widely used, efficient and representative productivity and...     

基于移动相似度评估的移动自组网多跳成簇算法

针对移动自组网(MANETs)节点间的相互移动,提出了一个移动相似度(MSD)评估模型,利用该模型可以得到量化相对移动程度的参数--MSD,然后提出了一种基于节点间的平均移动相似度(AMSD)的多跳成簇算法,此算法根据节点的AMSD建立稳定的簇结构,并通过设置关联节点、簇首竞争阈值减少簇首改变,采用事件触发的方式实现了...     

A tree-structured crash surrogate measure for freeways

In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicle’s action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The results show that the proposed indicator outperforms the three traditional crash surrogate measures (i.e., Time to Collision, Proportion of Stopping Distance, and Crash Potential Index) in representing rear-end crash risks. The applications of this measure are also discussed.     

A new measure for supplier performance evaluation

Recently the concept of dimensional analysis was used to propose a supplier performance measure and to obtain an index called the VPI (Vendor Performance Index). Usually the performance criteria used in supplier performance evaluation include quantitative and qualitative criteria. Here a new supplier performance measure is proposed as an alternative to the VPI. For qualitative criteria, a two-directional consideration is used instead of a one-directional approach, which results in only a single score. The fuzzy bag method is used to compensate for blindness in human judgement. Then all scores for quantitative and qualitative criteria are combined in an intuitive sum of weighted averages called the SUR. The SUR is illustrated and compared with the VPI by means of two examples.     

A new importance measure for risk-informed decision making

In this paper, we introduce a new importance measure, the differential importance measure (DIM), for probabilistic safety assessment (PSA). DIM responds to the need of the analyst/decision maker to get information about the importance of proposed changes that affect component properties and multiple basic events. DIM is directly applicable to both the basic events and the parameters of the PSA model. Unlike the Fussell–Vesely (FV), risk achievement worth (RAW), Birnbaum, and criticality importance measures, DIM is additive, i.e. the DIM of groups of basic events or parameters is the sum of the individual DIMs. We discuss the difference between DIM and other local sensitivity measures that are based on normalized partial derivatives. An example is used to demonstrate the evaluation of DIM at both the basic event and the parameter level. To compare the results obtained with DIM at the parameter level, an extension of the definitions of FV and RAW is necessary. We discuss possible extensions and compare the results of the three measures for a more realistic example.