Ranking Of Sites Research Articles

Quality Ranking of the Best CO2 Storage Aquifers in the Nordic Countries

Ranking of CO2 storage sites in the Nordic countries has previously been reported from the NORDICCS project. The ranking was based on geological characteristics of reservoir and seal, data coverage and safety evaluation of the storage complex. Estimated storage capacity were included but not taken into account in the ranking except if two storage sites were equally ranked. This paper presents a method for evaluating knowledge gaps for a storage site based on characterisation and assessment criteria presented in the EU CCS Directive, and a new updated ranking is presented where knowledge gaps are taken into account.

Актуальные проблемы использования объектов культурного наследия исторических городов в туристских целях (на примере города Калининграда)

The article presents an overview of the theoretical and practical approaches of domestic and foreign authors to the using historical and cultural heritage sites for tourist purposes for the development of regional tourism. Most scientists define cultural heritage sites as one of the most important conditions for the development of cultural and educational tourism. Further development of this territory is provided by strategic planning, state policy, the creation of a regulatory and legal framework, the development of specialized state programs, attraction of investments, creation of a specialized infrastructure, and implementation of a competent marketing policy. The article also presents the limiting factors of the using cultural heritage sites in the Russian Federation on the example of Kaliningrad region. Within the study the authors examine institutional capacities and state instruments for the restoration of cultural heritage objects with the aim of including in a regional tourism product. The authors develop authorial methodology of systematizing cultural heritage sites used for tourist purposes. The criterion for ranking cultural heritage sites is the degree of their preservation, accessibility and functional purpose. This methodology has been tested on cultural heritage sites in the city of Kaliningrad functionally related to fortifications. But it can be used in scientific research and in practice for ranking and other categories of cultural heritage sites of the regions of the Russian Federation.

Connect the dots: Accessibility, readability and site ranking – An investigation with reference to top ranked websites of Government of India

With the emergence of World Wide Web (WWW) as the primary reference channel of information, the need for making it barrier-free for all categories of users has evolved into a critical factor. Making the web resources barrier-free for users requires action across various dimensions such as accessibility and readability. This paper presents an analysis of accessibility, readability, and site-ranking of top ranked (N=20) government websites of India. The accessibility analysis has been carried out using aChecker and WAVE tools. The readability of the contents of the website is measured with six different indices such as Flesch-Kincaid reading ease, Flesch-Kincaid grade level, Gunning fog, SMOG, Coleman-Liau index and Automated Readability Index. The ranking of sites by National Informatics Centre (NIC) has been utilized to select the top ranked websites and their corresponding rankings are compared with global site ranking services such as Alexa. The correlation among these three factors of accessibility, readability, and site-ranking has been carried out with Spearman’s rank correlation method and the inferences derived from the results are presented.

Evaluation of the impact of traffic volume on site ranking

ABSTRACTThis study aims to compare and quantify the impact of traffic volume on hotspot identification. The data consist of geometric and traffic features of freeways of California for the six-year period (2005–2010). Five functional roadway classifications were used for analyzing the role of traffic volume in different environments. Four hotspot identification (HSID) methods were selected for this study, namely, Empirical Bayesian count with volume (EBWT), Empirical Bayesian count without volume (EBWOT), crash rate (CR), and crash number (CF). To determine the superiority of the above methods, four evaluation tests were conducted which include Site Consistency Test (SCT), Method Consistency Test (MCT), Total Rank Difference Test (TRDT), and Total Performance Difference Test (TPDT). The safety performance functions (SPF) that include the traffic volume show a better fit to crash count than do the ones without traffic volume. The results also show that EBWT mostly comes out to be the superior method as indicated by the four tests, followed by EBWOT, CF, and the worst performer CR. The advantages associated with the inclusion of traffic volume in SPFs are also transferred to the HSID with EBWT showing the best performance in most cases.

Reproducible psychoacoustic experiments and computational perception models in a modular software framework

Psychoacoustic experiments and auditory models are fundamental elements of hearing research helping to understand human auditory perception. One successful way to apply models has been to use the model as artificial observer, performing exactly the same psychoacoustic experiment as human subjects [e.g., Jepsen et al., J. Acoust. Soc. Am. 124, 422 (2008)]. While the signal processing parts of this and other models are publicly available, reproducible research requires availability of the complete framework including stimulus generation, experimental procedure, and interface to the model. For this, AFC for Matlab/Octave [www.aforcedchoice.com] provides a free and highly flexible framework to design and run psychoacoustic measurements with subjects and computer models. Previous versions of AFC have been used for nearly two decades in several highly ranked psychoacoustic research sites. To foster reproducible research, AFC offers full downward compatibility to the very first version, and the ability to easily overload or add measurement procedures, audio drivers, and models/model interfaces. Here a new version is presented with the above model as a use case. A database of psychoacoustic experiments from numerous publications is established, to provide the stimulus generation of the experiments, methods, and models for exact reproduction of the original work for teaching and research.

Cultural landscapes and attributes of “culturalness” in protected areas: An exploratory assessment in Greece

Cultural landscapes are poorly inventoried and evaluated in protected natural areas. This study presents a novel procedure to assess cultural landscape features and their cultural values in the major protected areas of Greece. After identifying a set of culturally modified land cover types and habitat types the GIS-based survey of the entire Natura 2000 protected area network in Greece (419 sites) shows that roughly 67% of protected area land cover consists of cultural landscape features. This was corroborated by the distribution of culturally modified habitat types which take up approximately 50% of the areal cover in a subset of the nation's Natura 2000 network (241 Special Areas for Conservation). Moreover, a set of 12 cultural attributes involving cultural heritage values, traditional land uses and aesthetic quality indicators were scored to assess these “cultural values” in each site. Gradient maps were produced to express an initial nation-wide site ranking profile. Heatmaps help link instead of solely rank culturally valuable sites that are in proximity to each other, showcasing site clusters of outstanding value. These analyses help define the level of “culturalness” of each site based on human-modified landscape and habitat types and provide a baseline review of cultural values in protected natural areas. This screening-level survey identifies the protected areas that may require special attention for managing cultural elements-of-diversity. Difficulties with data availability and uncertainties are reviewed. This procedure supports a paradigm shift that promotes a more holistic evaluation and management of biodiversity-centered protected areas, where until recently cultural landscapes were rarely appreciated.

Methods for Harmonic Analysis and Reporting in Future Grid Applications

The rollout of advanced metering infrastructure, advanced distribution automation schemes, and integration of generation into distribution networks, along with a raising of awareness of power quality (PQ), means that there is an increase in the availability of power system monitoring data. In particular, the data for harmonics, whether it is voltage or current harmonics, is now available from a large number of sites and from a diverse range of PQ instruments. The traditional analysis and reporting of power quality examines harmonic orders to the 50th. This means that the harmonic data available for analysis are significantly larger than, for example, steady-state voltage variations where only a few parameters are examined (e.g., the voltage on each phase). Higher frequency components, sometimes called high-frequency harmonics, in the 10–250 kHz range arising primarily due to power-electronic interfaced generation are also becoming significant. Given the vast amount of harmonic data that will be captured through grid instrumentation, a significant challenge lies in developing methods of analysis and reporting that reduces the data to a form that is easily understood and clearly identifies issues but does not omit important details. This paper introduces a number of novel methods of analysis and reporting which can be used to reduce vast amounts of harmonic data for individual harmonic orders down to a small number of indices or graphical representations which can be used to describe harmonic behavior at an individual site as well as at many sites across an electricity network. The methods presented can be used to rank site performance in order for mitigation strategies. The application of each method described is investigated using real-world data.

The bases of seismic microzoning of the territories with difficult engineering-geological conditions (on the example of the Black Sea coast of North-West Caucasus)

The paper considers the territory of the Black Sea coast of North-West Caucasus, to determine the complexity and the degree of variability of the engineering-geological conditions as factors of the degree of a local seismic hazard changing. A complex studying of the territory has been executed, the major engineering-geological factors defining the specifics of microseismic zoning, have been defined. The engineering-geological and seismic properties of the main stratigraphic-genetic complexes and engineering-geological elements have been analyzed. An influence of the soil conditions on seismic intensity has been specified, a calculation of the sizes of an increment of the seismic intensity for the typical conditions by means of a method of seismic rigidities has been executed. An assessment of the spatial variability of the possible sizes of an increment of seismic intensity at the sites with standard geological sections by geostatistical methods has been made. A model of a total size of the increment of the seismic intensity in the explored territory has been developed. It has been established that elements of a rank of engineering-geological subdistricts and sites, which are an analog of seismic microdistricts, are the most uniform in engineering-geological and seismic properties.

Can fuzzy logic bring complex issues in risk based optimal ranking of hazardous plant sites into focus? A case study

Selection of sites for the installation of hazardous plants in general and thermal power plants in particular, has assumed significant importance due to excessive air pollution load. Coal-fired power based thermal plants which generate 41% of the world’s electricity are a major source of local pollution and health hazard. It is therefore, important to decide suitable sites for these plants with low risk levels based on formalised mathematical techniques. In this paper, realizing uncertainty in parametric data, authors used fuzzy logic based formalisms, wherein goal in combination with constraints is considered as fuzzy multi constraint optimization problem. The study concludes with identifying optimal ranking of nine thermal power plants in India with ‘low risk’ potential. The limitations of this study have also been outlined.

Forecasting the ranks of sites suitable for power plant installations

An increase in the number of decision parameters used for ranking of sites for a power plant installation using the soft computing techniques leads to complex formulations that are computationally expensive[41]. Amongst a large number of decision parameters, if some of the parameters do not significantly contribute towards the ranking process, then we need not consider these for decision making. Moreover, it is very tedious to form fuzzy sets for all the 87 decision parameters from several environmental experts, which serve as inputs to certain soft computing techniques used for ranking. The decision parameters comprise of some parameters used to describe air quality, water quality, land suitability, socioeconomic and ecological suitability. We have made an attempt to reduce the number of input decision parameters so that the processing is computationally fast without significantly degrading the accuracy of the end results. We have also attempted to predict futuristic values of some of the relevant parameters to infer site suitability and/or ranking, futuristically (subsequent five years) which can act as a planning tool.

Evaluating Influence of Neighboring Structures on Spatial Crash Frequency Modeling and Site-Ranking Performance

Many neighborhood weight matrices have been adopted for modeling crash spatial heterogeneity. However, there has been little evaluation of their influence on crash prediction modeling performance. This study investigated 17 spatial-proximity matrices for development of spatial crash prediction models and site ranking with county-level data in California. Of the group of matrices being evaluated, traffic exposure–weighted and population-weighted distance-based matrices were first proposed in the traffic safety field. Bayesian spatial analysis was conducted with a combination of a first-order autoregressive error process and time trend for crashes to address the serial correlation of crashes in successive years. Two diagnostic measures were used for assessment of goodness of fit and complexity of models, and seven evaluation criteria were employed to assess the benefits associated with better-fitting models in site ranking. The results showed that modeling performance improved with an increase in number of neighbors considered in the weight matrix. However, a larger number of neighbors also led to greater variability of modeling performance. Specifically, Queen-2 and Decay-50 models proved to be superior among the adjacency- and distance-based models, respectively. The significance of incorporating spatial correlations was highlighted by the consistently poor performance of the base model, which included only the heterogeneity random effect. Finally, model-fitting performance seems to be strongly correlated with site-ranking performance. The models with closer goodness of fit tend to yield more consistent ranking results.

Observations on the Use of Crash Modification Factor-Corrected Crash Prediction Models to Identify Sites with Promise

The Highway Safety Manual (HSM) provides guidance on the application of crash prediction models for network screening, evaluation of alternative designs, and evaluation of implemented safety improvements. A variety of models are available. They may be classified as network screening level (or simple models), project level [or crash modification factor (CMF)–corrected models], and evaluation-level models. The use of crash prediction models to identify sites with promise of safety improvement is often based on assessing the difference between the expected number of crashes ( Ne) at a site and the predicted number of crashes ( Np) for similar sites within the population. A large difference between Ne and Np may denote a safety problem and be used to identify and rank sites with promise. The HSM indicates that CMF-corrected models may be used for network screening purposes. However, issues arise in the analysis regarding the definition of similar sites. When CMF-corrected models are used, the definition of similar sites changes with changes in the CMF adjustments particular to each site. Use of ( Ne − Np) for identifying and ranking sites with promise does not work well when the analysis uses a CMF-corrected estimate of Np. A large combined CMF will increase Np and thereby decrease the value ( Ne − Np). But a large combined CMF may point to a site with promise. This paper examines this phenomenon in detail, reviews a case study, and suggests that simple models may be preferable for identifying sites with promise.

A survey of the correlation between trust and reputation in electronic commerce B2C using Alexa rank

In general approaches of electronic trust in B2C e-commerce, to facilitate purchase decision process, the customers select valid brands based on the authenticity of web and regulatory mechanisms. This approach is not suitable for purchase from small companies without active brands in e-commerce. To purchase from these companies, we should follow other e-trust approaches. One of the approaches applied by information literate people is referring to valid ranking sites like Alexa rank. This study evaluates the correlation between Alexa rank and formal measures of trust in electronic space and extracts a new method for e-trust based on electronic reputation extracted from the results of existing ranking in ranking sites. To do this, 100 store websites are selected based on regulatory lists and the formal criteria of trust is measured and the correlation of these criteria with Alexa rank is compared.

Investigation of the Correlation Between Trust and Reputation in B2C e-Commerce Using Alexa Ranking

As a general approach to gain electronic trust in business-to-consumer e-commerce, the customers select valid brands based on the authenticity of the Web and regulatory mechanisms in order to facilitate purchase decision process. This approach is not suitable for purchase from small companies without brands active in e-commerce. To purchase from these companies, we should follow other e-trust approaches. One of the approaches applied in information literate is to refer to valid ranking sites like Alexa rank. Here, we have evaluated the correlation between Alexa rank and the formal measures of trust in electronic space, and have suggested a new method for the e-trust that is based on an electronic reputation built on the existing ranking results given by the ranking sites. To this end, we selected 100 store Websites based on regulatory lists, and the formal criteria of trust for them were measured along with the correlation of these criteria with Alexa rank.

Using entropy and AHP-TOPSIS for comprehensive evaluation of internet shopping malls and solution optimality

Consumers are switching from offline to online to buy everything due to this reason nowadays internet shopping malls (ISMs) are setting up a very crucial role in the economy. For assessment and ranking are basically a critical work which could be exploitation of internet shopping malls information resources when consider in a scientific way, there are many methods for the evaluation and ranking of e-commerce sites. Taking into consideration traffic rank, inbound links, competition, speed, and keyword statistics, in literature multi criteria decision making (MCDM) methods are rarely used by the researchers to find the rank of internet shopping malls (ISMs) on the basis of primary/secondary data of these influencing factors. This study, therefore, is unique to narrow down the gap in literature by employing MCDM methods i.e. entropy and analytic hierarchy process (AHP) to collect the weight of influencing factors and technique for order preference by similarity to ideal (TOPSIS) to find the rank of internet shopping malls (ISMs). After finding out the rank of selected criteria, solution optimality needs to be done to find the average ideal solution matrix. Conclusion and managerial implications of the study are also discussed.

Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India.

Cyclist deceleration rate as surrogate safety measure in Montreal using smartphone GPS data

Urban areas in North American cities with positive trends in bicycle usage also witness a high number of cyclist injuries every year. Previous cyclist safety studies based on the traditional approach, which relies on historical crash data, are known to have some limitations such as the fact that crashes need to happen (a reactive approach). This paper explores the use of GPS deceleration events as a surrogate-proactive measure and investigates the relationship between reported cyclist road injuries and deceleration events. The surrogate safety measure is defined based on deceleration values representing hard breaking situations. This work uses a large sample of GPS cyclist trip data from a smartphone application to extract deceleration rates at intersections and along segments and to explore its relationship with the number of observed injuries and validate deceleration rate (DR) as a surrogate safety measure. Using Spearman’s rank correlation coefficient, we compared the ranking of sites based on the expected number of injuries and based on DR. The ranks of expected injuries and dangerous decelerations were found to have a correlation of 0.60 at signalized intersections, 0.53 at non-signalized intersections and 0.57 at segments. Despite the promising results of this study, more granular data and validation work needs to be done to improve the reliability of the measures. The technological limitations and future work are discussed at the end of the paper.

A novel Bayesian hierarchical model for road safety hotspot prediction

In this paper, we propose a Bayesian hierarchical model for predicting accident counts in future years at sites within a pool of potential road safety hotspots. The aim is to inform road safety practitioners of the location of likely future hotspots to enable a proactive, rather than reactive, approach to road safety scheme implementation. A feature of our model is the ability to rank sites according to their potential to exceed, in some future time period, a threshold accident count which may be used as a criterion for scheme implementation. Our model specification enables the classical empirical Bayes formulation – commonly used in before-and-after studies, wherein accident counts from a single before period are used to estimate counterfactual counts in the after period – to be extended to incorporate counts from multiple time periods. This allows site-specific variations in historical accident counts (e.g. locally-observed trends) to offset estimates of safety generated by a global accident prediction model (APM), which itself is used to help account for the effects of global trend and regression-to-mean (RTM). The Bayesian posterior predictive distribution is exploited to formulate predictions and to properly quantify our uncertainty in these predictions. The main contributions of our model include (i) the ability to allow accident counts from multiple time-points to inform predictions, with counts in more recent years lending more weight to predictions than counts from time-points further in the past; (ii) where appropriate, the ability to offset global estimates of trend by variations in accident counts observed locally, at a site-specific level; and (iii) the ability to account for unknown/unobserved site-specific factors which may affect accident counts. We illustrate our model with an application to accident counts at 734 potential hotspots in the German city of Halle; we also propose some simple diagnostics to validate the predictive capability of our model. We conclude that our model accurately predicts future accident counts, with point estimates from the predictive distribution matching observed counts extremely well.

Russia’s academic institutes as mirrored by webometrics

How adequately and fully do the indicators used in webometric research help assess the quality and size of scientific websites? This question is asked by the authors of this article. They analyze the sites of Russian academic institutes and their indicators. The degree of value stability of webometric indicators is demonstrated; examples of their discrepancy with assumed meanings are given; and alternative interpretations are offered. This research resulted in a monthly replenished free-for-all database of webometric indicators of academic sites, hosted at http://webometrix.ru, which could become a tool for planning measures to improve the representation of scientific organizations on the Internet and a basis for generating webometric site rankings.

Digital Literacy: Web search ecology and some surprising conclusions about finding and promoting educational resources on the internet

An ecology is a system of interacting and or competing organisms or entities. Alternatively, it may also describe the study of such interactions or competition. In this paper I loosely consider the system of educationalists searching for content to use in their teaching practice to form such a system. Having returned from a course on ICT for social and group learning delivered by the company Smart Solutions (Vassallo 2010) in Malta, I decided to use what I had learnt to build a number of websites publicising the computer tools I had learned about. In choosing free websites, I was choosing platforms which would be available at no cost to educators, as I was hoping to promote teachers’ active participation in the online community, which had been a theme of the course. Using free internet sites, I built a wiki (Cuffe 2011a), on Wikispaces (Anon 2010b), a blog (Cuffe 2010a) on the WordPress.com site (Anon 2011g), a Google group (Cuffe 2010c) , on Google groups (Anon 2011c), and a Trailmeme (Cuffe 2011c), on the Trailmeme site (Anon 2011e). I also built a second blog (Cuffe 2010b) on Blogger (Anon 2011a) and shot a number of Videos (Cuffe 2010d) which I placed on the You Tube site (Anon 2011i). Finally, I built a Prezi (Cuffe 2010e), which I placed on the Prezi site. Some of the sites I created initially placed highly in Google search however web traffic did not seem to correspond in any clear way to my sites rank in search. This was surprising, however I noted that traffic would peak whenever I mentioned a specific site on an online forum, or on an email chat group, and this peak could be many times larger than the regular level of traffic coming in, presumably, from general search (see Figure 1). The rest of this paper describes what I did to explore this further.