Basic Ranking Research Articles

A Driftwood‐Based Record of Arctic Sea Ice During the Last 500 Years From Northern Svalbard Reveals Sea Ice Dynamics in the Arctic Ocean and Arctic Peripheral Seas

AbstractWe present a 500‐year history of naturally felled driftwood incursion to northern Svalbard, directly reflecting regional sea ice conditions and Arctic Ocean circulation. Provenance and age determinations by dendrochronology and wood anatomy provide insights into Arctic Ocean currents and climatic conditions at a fine spatial resolution, as crossdating with reference chronologies from the circum‐Arctic boreal forests enables determination of the watershed the driftwood originated from. Sample crossdating may result in a wide range of matches across the pan‐boreal region, which may be biased toward regions covered by the reference chronologies. Our study considers alternate approaches to selecting probable origin sites, by weighting scores via reference chronology span and visualizing results through spatiotemporal density plots, as opposed to more basic ranking systems. As our samples come from naturally felled trees (not logged or both), the relative proportions of different provenances are used to infer past ocean current dominance. Our record indicates centennial‐to decadal‐scale shifts in source regions for driftwood incursion to Svalbard, aligning with Late Holocene high variability and high frequency shifts in the Transpolar Drift and Beaufort Gyre strengths and associated fluctuating climate conditions. Driftwood occurrence and provenance also track the northward ice formation shift in peripheral Arctic seas in the past century. A distinct decrease in driftwood incursion during the last 30 years matches the observed decline in pan‐Arctic sea ice extent in recent decades. Our new approach successfully employs driftwood as a proxy for Arctic Ocean surface circulation and sea ice dynamics.

Ranking Conjunctions for Partial Delete Relaxation Heuristics in Planning

Heuristic search is one of the most successful approaches to classical planning, finding solution paths in large state spaces. A major focus has been the development of domain-independent heuristic functions. One recent method are partial delete relaxation heuristics, improving over the standard delete relaxation heuristic through imposing a set C of conjunctions to be treated as atomic. Practical methods for selecting C are based on counter-example guided abstraction refinement, where iteratively a relaxed plan is checked for conflicts and new atomic conjunctions are introduced to address these. However, in each refinement step, the choice of possible new conjunctions is huge. The literature so far offers merely one simple strategy to make that choice. Here we fill that gap, considering a sizable space of basic ranking strategies as well as combinations thereof. We furthermore devise ranking strategies for conjunction-forgetting, where the ranking pertains to the current conjunctions and thus statistics over their usefulness can be maintained. Our experiments show that ranking strategies do make a large difference in performance, and that our new strategies can be useful.

Ranking Multi-Metric Scientific Achievements Using a Concept of Pareto Optimality

The ranking of multi-metric scientific achievements is a challenging task. For example, the scientific ranking of researchers utilizes two major types of indicators; namely, number of publications and citations. In fact, they focus on how to select proper indicators, considering only one indicator or combination of them. The majority of ranking methods combine several indicators, but these methods are faced with a challenging concern—the assignment of suitable/optimal weights to the targeted indicators. Pareto optimality is defined as a measure of efficiency in the multi-objective optimization which seeks the optimal solutions by considering multiple criteria/objectives simultaneously. The performance of the basic Pareto dominance depth ranking strategy decreases by increasing the number of criteria (generally speaking, when it is more than three criteria). In this paper, a new, modified Pareto dominance depth ranking strategy is proposed which uses some dominance metrics obtained from the basic Pareto dominance depth ranking and some sorted statistical metrics to rank the scientific achievements. It attempts to find the clusters of compared data by using all of indicators simultaneously. Furthermore, we apply the proposed method to address the multi-source ranking resolution problem which is very common these days; for example, there are several world-wide institutions which rank the world’s universities every year, but their rankings are not consistent. As our case studies, the proposed method was used to rank several scientific datasets (i.e., researchers, universities, and countries) for proof of concept.

Explicit analytical formulae of ranking indices without the requirement of multiplicative compatibility

The ranking of fuzzy numbers is often given by a special class of utility functions, better known as ranking indices of the first kind. Recently, we have proved that the effective ranking of fuzzy numbers from a set containing all real numbers can be done by involving a very particular class of ranking indices. In this way, the searching of effective ranking methods is essentially simplified. In this paper, firstly we extend this result in a sense which allows us to find explicit formulae for ranking indices defined on other important subsets of fuzzy numbers, as for example the set of positive trapezoidal fuzzy numbers or the set of positive triangular fuzzy numbers. Another novelty is that, reducing all those ranking indices that generate the same ordering to a special member of their class, under some reasonable regularity assumptions, we find all the orderings on trapezoidal fuzzy numbers, or positive trapezoidal fuzzy numbers, respectively, which satisfy all the basic requirements of Wang and Kerre, except for the compatibility with scalar multiplication. This special member of the class is what we call a basic ranking index, that is, a ranking index which assigns to a fuzzy number a real number that belongs to its support. Actually, these basic ranking indices can be extended to linear functionals, so their form is very simple and ready to be used in applications. Similar results are obtained for the set of triangular fuzzy numbers and positive triangular fuzzy numbers, respectively. The key element in all these theoretical results, is that under some reasonable regularity properties, we can reduce a ranking index to this so called basic ranking index, which has a simpler form but generates the same order, that is, a binary relation with the same graph. As a first application, we review several ranking approaches got from ranking indices which are additive functions with respect to addition of fuzzy numbers and check their properties from the list of Wang and Kerre. Then, we do the same for a group of ranking indices none of them being additive functions with respect to the addition of fuzzy numbers. We can always do that, as long as we reduce a nonadditive ranking index to a basic ranking index, with both ranking indices generating the same ordering. For the newly obtained ranking index, we will just need to study additivity or scale invariance, depending on which type of property from the list of Wang and Kerre are we interested in. An interesting special case of nonadditive ranking index that cannot be reduced to a basic ranking index is the so called signed distance. We slightly modify this ranking index, so that it can be reduced to a basic ranking index. In this way, we never get contradictory results for fuzzy numbers with disjoint supports. Lastly, we propose a method to extend the ordering of positive trapezoidal fuzzy numbers to the ordering of arbitrary positive fuzzy numbers.

Application of Fuzzy Decision Making with Multiple Criteria in Ranking Natural Radioactivity Levels of Beach Sediments

Objectives: Fuzzy set theory is a marvelous tool to handle uncertainty associated with vagueness, imprecision and lack of information. The objective of this paper is to solve a Multiple Criteria Decision Making problem (MCDM) in fuzzy environment using LR Fuzzy number with a numerical example. Methods/Statistical Analysis: Decision making is a process of selecting a possible course of action from all available alternatives. The scope of the problem is to rank the natural radioactivity levels of various sites of Kerala beaches from the pre-investigated radioactivity supporting parameters of the beach sites. This can be achieved by using vertex method. The parameters are categorized in to cost and benefit criteria and the basic ranking is based on the performance index which is close to 1. Findings: The data for the current study is collected from a researcher, in which the radioactivity levels are calculated using experimental studies. In this paper, just by considering radioactivity supporting parameters of the beach sites, the sites are ranked. As the samples are collected from first three feet of the sites, the data are taken as LR fuzzy numbers. Using vertex method, performance index is calculated and the sites are ranked. The sites which are mentioned as most hazardous and least hazardous in the pre- investigated study is found to take first and last few ranks in the present study. Finally, the result is analyzed for various risk attitudes and several levels of confidence. Application/Improvements: Any real life problem with multiple criteria can be modeled as fuzzy multi criteria decision making problem using any type of fuzzy number and can be solved by vertex method. The type of fuzzy number is decided depending upon the data.

Technology Innovation and Global Competition-evidence from Global 500 Strong Construction Enterprise

Technology innovation plays a key role in strengthening the competitiveness of the enterprises. It is a good method for the company to win the market within background of global economy and fierce competition. Based on the literature review of the enterprise innovation and technology development status, choosing the construction enterprise listed in top 500 companies of 2015 as an example, this paper firstly analyzed the enterprises’ basic ranking status and overall competitiveness. From the perspective of technology innovation management, then explored the differences among the construction enterprises from five aspects of technology innovation: (1) R and D human resources, (2) capital investment, (3) organization management, (4) incentives mechanism, and (5) innovation cooperative mechanism. The comparison between Chinese construction companies and international construction companies are presented as well with the root cause analysis of the difference on innovation management. Research found that Chinese construction enterprises are dominated the global leading position, but the technology innovation management mode and internationality is not strong. Finally, the paper put forward corresponding countermeasures and suggestions on how to improve the innovation performance for Chinese construction enterprises. It pointed out that the Chinese construction enterprises should strengthen technological innovation management, establish a professional technological innovation system and incentives mechanism to maintain international competitiveness and achieve sustainable development goals.

Network-based method for ranking of efficient units in two-stage DEA models

This study presents a methodology that is able to further discriminate the efficient decision-making units (DMUs) in a two-stage data envelopment analysis (DEA) context. The methodology is an extension of the single-stage network-based ranking method, which utilizes the eigenvector centrality concept in social network analysis to determine the rank of efficient DMUs. The mathematical formulation for the method to work under the two-stage DEA context is laid out and then applied to a real-world problem. In addition to its basic ranking function, the exercise highlights two particular features of the method that are not available in standard DEA: suggesting a benchmark unit for each input/intermediate/output factor, and identifying the strengths of each efficient unit. With the methodology, the value of DEA greatly increases.

Ranking Plays and Playwrights in Traditional Chinese Drama Criticism

A striking feature of traditional Chinese drama criticism is the desire by some critics to produce comprehensive systems that evaluate and comparatively rank large numbers of plays and their playwrights. Two basic ranking systems were used. One, which had its origins in the evaluation of historical figures, candidates for office, and officials in the Later Han and Six Dynasties period (25–588), was used to divide people into nine ranks (pin 品), produced by doubling up the categories of “higher“ (shang 上), “middle” (zhong 中), and “lower” (xia 下): “higher of the higher” (shangshang 上上), “middle of the higher” (shangzhong 上中), “lower of the higher” (shangxia 上下), “higher of the middle” (zhongshang 中上), etc. The way the categories are labeled and distinguished from each other pays attention primarily to hierarchy. The other system, first developed in calligraphy and painting criticism, used a smaller number of categories (pin 品) that could vary in their number and hierarchical sequence from critic to critic, although the general hierarchy was pretty consistent. Each of these categories had a name that stressed particular aesthetic qualities or goals such as shenpin 神品 (divine class),

Interpreting TF-IDF term weights as making relevance decisions

A novel probabilistic retrieval model is presented. It forms a basis to interpret the TF-IDF term weights as making relevance decisions. It simulates the local relevance decision-making for every location of a document, and combines all of these “local” relevance decisions as the “document-wide” relevance decision for the document. The significance of interpreting TF-IDF in this way is the potential to: (1) establish a unifying perspective about information retrieval as relevance decision-making; and (2) develop advanced TF-IDF-related term weights for future elaborate retrieval models. Our novel retrieval model is simplified to a basic ranking formula that directly corresponds to the TF-IDF term weights. In general, we show that the term-frequency factor of the ranking formula can be rendered into different term-frequency factors of existing retrieval systems. In the basic ranking formula, the remaining quantity - log p (r¯| t ∈ d ) is interpreted as the probability of randomly picking a nonrelevant usage (denoted by r¯) of term t . Mathematically, we show that this quantity can be approximated by the inverse document-frequency (IDF). Empirically, we show that this quantity is related to IDF, using four reference TREC ad hoc retrieval data collections.

Charting taxonomic knowledge through ontologies and ranking algorithms

Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research. The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria. The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute to the preservation our scientific heritage.

On ranking techniques for desktop search

Users tend to store huge amounts of files, of various formats, on their personal computers. As a result, finding a specific, desired file within the file system is a challenging task. This article addresses the desktop search problem by considering various techniques for ranking results of a search query over the file system. First, basic ranking techniques, which are based on various file features (e.g., file name, access date, file size, etc.), are considered and their effectiveness is empirically analyzed. Next, two learning-based ranking schemes are presented, and are shown to be significantly more effective than the basic ranking methods. Finally, a novel ranking technique, based on query selectiveness, is considered for use during the cold-start period of the system. This method is also shown to be empirically effective, even though it does not involve any learning.

Demonstration of Ranking Issues for Students: A Case Study

This article uses a case study of 2001 town and city data that we analyzed for Boston Magazine. We use this case study to demonstrate the challenges of creating a valid ranking structure. The data consist of three composite indices for 147 individual townships in the Boston metropolitan area representing measures of public safety; the environment; and health. We report the data and the basic ranking procedure used in the magazine article, as well as a discussion of alternative ranking procedures. In particular, we demonstrate the impact of additional adjustment for the size of population, even when per capita data are used. This case study presents an opportunity for discussion of fundamental data analysis concepts in all levels of statistics courses.

RESEARCH PRODUCTIVITY OF THE ECONOMICS PROFESSION IN EAST ASIA

I. INTRODUCTION Research productivity is often ranked for economics departments based on page of journal publications (for example, Graves, Marchand, and Thompson [1982]), while others rate the departments by the number of citations attributed to their faculty (for example, Davis and Papanek [1984]). Recently, Scott and Mitias [1996] used and concepts in their departmental rankings. While the flow of research can be counted to give credit to the department where authors are affiliated at the time of publication, the stock ranking a currently affiliated faculty's stock of past and current research. The alternative rankings also use different sets of journals as well as varied weighting schemes to standardize the length of journal pages and to adjust for journal quality. While several different methods have been used to rank economics departments in the United States, no such assessment has been done for East Asian universities. This article aims to fill this gap by ranking economics professions in East Asia based solely on research productivity. For the purpose of comparison with U.S. universities, our methodology closely follows that of Scott and Mitias [1996] with some variations in the sample length. First, the ranking the of past and current research (for example, Hogan [1984], Laband [1985], Conroy and Dusansky [1995], Scott and Mitias [1996], and Dusansky and Vernon [1998]). Fine research scholars move from one university to another, a phenomenon that sometimes leads to dramatic changes in school performance. However, labor mobility depends to some extent on the degree of importance of research to which a university is attached; more open and research-oriented schools often hire researchers (and their accompanying stock of published research) from other institutions in the region or more often from abroad, while others more or less insulate themselves from inflows of new research. A more accurate reflection of current reality is, therefore, to know who is at a particular university today, not who was at it in the past. Thus, economics faculty affiliated with East Asian universities during the autumn 1997 semester are counted for the stock ranking in East Asia. The economics faculty include all economists in business schools as well as all in economics departments.(1) Faculty names were obtained directly from department chairs and each school's home page on the internet. Second, the basic ranking relies on page of articles published in a set of 36 quality journals over the period 1990-96. Page are employed to capture many variations in the length of articles across journals. The EconLit CD-ROM (September 1997) includes all international journals that have appeared in the Journal of Economic Literature. The choice of a set of quality journals is, however, open to question. Graves, Marchand, and Thompson [1982], for example, examined publications in a set of 24 journals, Hogan [1984] looked at a set of 4, Laband [1985] a set of 27, Bairam [1994] a set of 5, and Conroy and Dusansky [1995] and Dusansky and Vernon [1998] each a set of 8 journals. The criterion employed here for top-36 journals relies on the choice in Scott and Mitias [1996] in which the original set of top-24 journals in Graves, Marchand, and Thompson, [1982] was updated.(2) To check the sensitivity of our findings with alternative sets of journals, we ranked these schools based on top-24 and top-42 journals. The list of 42 top journals was provided to us by Dusansky and Vernon [1998].(3) Third, page counts are employed (for example, Graves, Marchand, and Thompson [1982], Hirsch, Austin, Brooks, and Moore [1984], Conroy and Dusansky [1995], Scott and Mitias [1996], and Dusansky and Vernon [1998]). The Scott-Mitias [1996] conversion factors are used for the basic ranking, in which the number of pages published in 36 journals were standardized to the average length of a page in the AER. …