Search results for: European Standard Classification

Authors: H. Ozbasaran

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IPN and IPE sections, which are commonly used European I shapes, are widely used in steel structures as cantilever beams to support overhangs. A considerable number of studies exist on calculating lateral torsional buckling load of I sections. However, most of them provide series solutions or complex closed-form equations. In this paper, a simple equation is presented to calculate lateral torsional buckling load of IPN and IPE section cantilever beams. First, differential equation of lateral torsional buckling is solved numerically for various loading cases. Then a parametric study is conducted on results to present an equation for lateral torsional buckling load of European IPN and IPE beams. Finally, results obtained by presented equation are compared to differential equation solutions and finite element model results. ABAQUS software is utilized to generate finite element models of beams. It is seen that the results obtained from presented equation coincide with differential equation solutions and ABAQUS software results. It can be suggested that presented formula can be safely used to calculate critical lateral torsional buckling load of European IPN and IPE section cantilevers.

Keywords: cantilever, IPN, IPE, lateral torsional buckling

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

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The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature.

Keywords: job-shop scheduling, classification, constraints, objective functions

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Authors: Yi-De Liu

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For many European cities, a key motivation in developing event strategies is to use event as a catalyst for urban regeneration. One type of event that is particularly used as a means of urban development is the European Capital of Culture (ECOC) initiative. Based on a case study of the 2008 ECOC Liverpool, this paper aims at conceptualising the significance of major event for a city’s economic, cultural and social regenerations. In terms of economic regeneration, the role of the ECOC is central in creating Liverpool’s visitor economy and reshaping city image. Liverpool planned different themes for eight consecutive years as a way to ensure economic sustainability. As far as cultural regeneration is concerned, the ECOC contributed to the cultural regeneration of Liverpool by stimulating cultural participation and interest from the demand side, as well as improving cultural provision and collaboration within the cultural sector from the supply side. So as to social regeneration, Liverpool treated access development as a policy guideline and considered the ECOC as an opportunity to enhance the sense of place. The most significant lesson learned from Liverpool is its long-term planning and efforts made to integrate the ECOC into the overall urban development strategy. As a result, a more balanced and long-term effect on urban regeneration could be achieved.

Keywords: cultural event, urban regeneration, european capital of culture, Liverpool

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Authors: L. Gómez-Limia, I. Franco, T. Blanco, S. Martínez

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European eels (Anguilla anguilla) belong to Anguilliformes order and Anguillidae family. They are generally classified as warm-water fish. Eels have a great commercial value in Europe and Asian countries. Eels can reach high weights, although their commercial size is relatively low in some countries. The capture of larger eels would facilitate the recovery of the species, as well as having a greater number of either glass eels or elvers for aquaculture. In the last years, the demand and the price of eels have increased significantly. However, European eel is considered critically endangered by the International Union for the Conservation of Nature (IUCN) Red List. The biochemical composition of fishes is an important aspect of quality and affects the nutritional value and consumption quality of fish. In addition, knowing this composition can help predict an individual’s condition for their recovery. Fish is known to be important source of protein rich in essential amino acids. However, there is very little information about changes in amino acids composition of European eels with increase in size. The aim of this study was to evaluate the effect of two different weight categories on the amino acids content in muscle tissue of wild European eels. European eels were caught in River Ulla (Galicia, NW Spain), during winter. The eels were slaughtered in ice water immersion. Then, they were purchased and transferred to the laboratory. The eels were subdivided into two groups, according to the weight. The samples were kept frozen (-20 °C) until their analysis. Frozen eels were defrosted and the white muscle between the head and the anal hole. was extracted, in order to obtain amino acids composition. Thirty eels for each group were used. Liquid chromatography was used for separation and quantification of amino a cids. The results conclude that the eels are rich in glutamic acid, leucine, lysine, threonine, valine, isoleucine and phenylalanine. The analysis showed that there are significant differences (p < 0.05) among the eels with different sizes. Histidine, threonine, lysine, hydroxyproline, serine, glycine, arginine, alanine and proline were higher in small eels. European eels muscle presents between 45 and 46% of essential amino acids in the total amino acids. European eels have a well-balanced and high quality protein source in the respect of E/NE ratio. However, eels with higher weight showed a better ratio of essential and non-essential amino acid.

Keywords: European eels, amino acids, HPLC, body size

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Geetika Barman, B. S. Daya Sagar

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In this article, we proposed a pixel-wise classification of hyperspectral images using a mathematical morphology operator-based distance metric called “dilation distance” and “erosion distance”. This method involves measuring the spatial distance between the spectral features of a hyperspectral image across the bands. The key concept of the proposed approach is that the “dilation distance” is the maximum distance a pixel can be moved without changing its classification, whereas the “erosion distance” is the maximum distance that a pixel can be moved before changing its classification. The spectral signature of the hyperspectral image carries unique class information and shape for each class. This article demonstrates how easily the dilation and erosion distance can measure spatial distance compared to other approaches. This property is used to calculate the spatial distance between hyperspectral image feature vectors across the bands. The dissimilarity matrix is then constructed using both measures extracted from the feature spaces. The measured distance metric is used to distinguish between the spectral features of various classes and precisely distinguish between each class. This is illustrated using both toy data and real datasets. Furthermore, we investigated the role of flat vs. non-flat structuring elements in capturing the spatial features of each class in the hyperspectral image. In order to validate, we compared the proposed approach to other existing methods and demonstrated empirically that mathematical operator-based distance metric classification provided competitive results and outperformed some of them.

Keywords: dilation distance, erosion distance, hyperspectral image classification, mathematical morphology

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Authors: Olgun Akbulut

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Turkey has entered in the European human rights monitoring in the early 1990s. Since then many improvements have been observed in domestic law. However, one area stays the least developed one: gender discrimination. Although the country is proud of the fact that electoral rights for women were recognized in Turkey even before many developed countries in the west, interestingly the first Turkish case where the European Court of Human Rights (ECrtHR) found discrimination concerned gender discrimination. With the proposed paper, the author is willing to determine and analyze the findings of the ECrtHR in cases decided against Turkey concerning gender discrimination, identify whether Turkish public institutions display coordination in engagement or disengagement in implementing the judgments where the ECrtHR found discrimination on the basis of gender and evaluate the effectiveness of the Court's jurisprudence on Turkish gender policy.

Keywords: equality, gender discrimination, human rights, Turkey

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Authors: Zahid Ahmad, Nauman Ali

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This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: B. Tiseo, V. Quaranta, G. Bruno, G. Sisinni

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There is an increasing demand of nano-satellite development among universities, small companies, and emerging countries. Low-cost and fast-delivery are the main advantages of such class of satellites achieved by the extensive use of commercial-off-the-shelf components. On the other side, the loss of reliability and the poor success rate are limiting the use of nano-satellite to educational and technology demonstration and not to the commercial purpose. Standardization of nano-satellite environmental testing by tailoring the existing test standard for medium/large satellites is then a crucial step for their market growth. Thus, it is fundamental to find the right trade-off between the improvement of reliability and the need to keep their low-cost/fast-delivery advantages. This is particularly even more essential for satellites of CubeSat family. Such miniaturized and standardized satellites have 10 cm cubic form and mass no more than 1.33 kilograms per 1 unit (1U). For this class of nano-satellites, the qualification process is mandatory to reduce the risk of failure during a space mission. This paper reports the description and results of the space qualification test campaign performed on Endurosat’s CubeSat nano-satellite and modules. Mechanical and environmental tests have been carried out step by step: from the testing of the single subsystem up to the assembled CubeSat nano-satellite. Functional tests have been performed during all the test campaign to verify the functionalities of the systems. The test duration and levels have been selected by tailoring the European Space Agency standard ECSS-E-ST-10-03C and GEVS: GSFC-STD-7000A.

Keywords: CubeSat, nano-satellite, shock, testing, vibration

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Authors: M. Marín-Ferrer, M. A. Hernández, T. Tollefsen, S. Vanzo, E. Nweke, P. V. Tognoli, M. De Cort

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Under the terms of Article 36 of the Euratom Treaty, European Union Member States (MSs) shall periodically communicate to the European Commission (EC) information on environmental radioactivity levels. Compilations of the information received have been published by the EC as a series of reports beginning in the early 1960s. The environmental radioactivity results received from the MSs have been introduced into the Radioactivity Environmental Monitoring database (REMdb) of the Institute for Transuranium Elements of the EC Joint Research Centre (JRC) sited in Ispra (Italy) as part of its Directorate General for Energy (DG ENER) support programme. The REMdb brings to the scientific community dealing with environmental radioactivity topics endless of research opportunities to exploit the near 200 millions of records received from MSs containing information of radioactivity levels in milk, water, air and mixed diet. The REM action was created shortly after Chernobyl crisis to support the EC in its responsibilities in providing qualified information to the European Parliament and the MSs on the levels of radioactive contamination of the various compartments of the environment (air, water, soil). Hence, the main line of REM’s activities concerns the improvement of procedures for the collection of environmental radioactivity concentrations for routine and emergency conditions, as well as making this information available to the general public. In this way, REM ensures the availability of tools for the inter-communication and access of users from the Member States and the other European countries to this information. Specific attention is given to further integrate the new MSs with the existing information exchange systems and to assist Candidate Countries in fulfilling these obligations in view of their membership of the EU. Article 36 of the EURATOM treaty requires the competent authorities of each MS to provide regularly the environmental radioactivity monitoring data resulting from their Article 35 obligations to the EC in order to keep EC informed on the levels of radioactivity in the environment (air, water, milk and mixed diet) which could affect population. The REMdb has mainly two objectives: to keep a historical record of the radiological accidents for further scientific study, and to collect the environmental radioactivity data gathered through the national environmental monitoring programs of the MSs to prepare the comprehensive annual monitoring reports (MR). The JRC continues his activity of collecting, assembling, analyzing and providing this information to public and MSs even during emergency situations. In addition, there is a growing concern with the general public about the radioactivity levels in the terrestrial and marine environment, as well about the potential risk of future nuclear accidents. To this context, a clear and transparent communication with the public is needed. EURDEP (European Radiological Data Exchange Platform) is both a standard format for radiological data and a network for the exchange of automatic monitoring data. The latest release of the format is version 2.0, which is in use since the beginning of 2002.

Keywords: environmental radioactivity, Euratom, monitoring report, REMdb

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Authors: G. Cinelli, T. Tollefsen, P. Bossew, V. Gruber, R. Braga, M. A. Hernández-Ceballos, M. De Cort

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In 2006, the Joint Research Centre (JRC) of the European Commission started the project of the 'European Atlas of Natural Radiation'. The Atlas aims at preparing a collection of maps of Europe displaying the levels of natural radioactivity caused by different sources (indoor and outdoor radon, cosmic radiation, terrestrial radionuclides, terrestrial gamma radiation, etc). The overall goal of the project is to estimate, in geographical resolution, the annual dose that the public may receive from natural radioactivity, combining all the information from the different radiation components. The first map which has been developed is the European map of indoor radon (Rn) since in most cases Rn is the most important contribution to exposure. New versions of the map are realised when new countries join the project or when already participating countries send new data. We show the latest status of this map which currently includes 25 European countries. Second, the JRC has undertaken to map a variable which measures 'what earth delivers' in terms of Rn. The corresponding quantity is called geogenic radon potential (RP). Due to the heterogeneity of data sources across the Europe there is need to develop a harmonized quantity which at the one hand adequately measures or classifies the RP, and on the other hand is suited to accommodate the variety of input data used to estimate this target quantity. Candidates for input quantities which may serve as predictors of the RP, and for which data are available across Europe, to different extent, are Uranium (U) concentration in rocks and soils, soil gas radon and soil permeability, terrestrial gamma dose rate, geological information and indoor data from ground floor. The European Geogenic Radon Map gives the possibility to characterize areas, on European geographical scale, for radon hazard where indoor radon measurements are not available. Parallel to ongoing work on the European Indoor Radon, Geogenic Radon and Cosmic Radiation Maps, we made progress in the development of maps of terrestrial gamma radiation and U, Th and K concentrations in soil and bedrock. We show the first, preliminary map of the terrestrial gamma dose rate, estimated using the data of ambient dose equivalent rate available from the EURDEP system (about 5000 fixed monitoring stations across Europe). Also, the first maps of U, Th, and K concentrations in soil and bedrock are shown in the present work.

Keywords: Europe, natural radiation, mapping, indoor radon

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Wendy de Gomez

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Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

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Authors: Carolina B. A. Morais, Antonio Bob Santos

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In order to determine how innovation procurement can strengthen public efficiency and foster the modernization of public services, while at the same time promoting the opening of new private markets, this paper aims to present the two key instruments for the practice of innovation procurement at a European, national, and regional level – Pre-Commercial Procurement (PCP), and Public Procurement of Innovative Solutions (PPI). Thus, it starts with a theoretical framework on the emergence of this topic in the European Innovation Policy (Section 2), then continues with the identification and systematization of the main mechanisms for its effective adoption, both on the demand and supply side of the market (Section 3), as well as to expose and describe methods and tools for positioning innovation at the heart of public entities. The innovative projects best distinguished by the European Commission for their good practices in innovation procurement are identified, and the main methodology for the development and management of innovation procurement – Forward Commitment Procurement (FCP) – is applied to them in a pioneering way (Section 4). The relevance of innovation in public procurement is systematized and reflected upon in Section 5.

Keywords: innovation procurement, innovation policy, innovation, pubic procurement

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Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

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Authors: Garg Ramneesh, Uppal Sanjeev, Mittal Rajinder, Shah Sheerin, Jain Vikas, Singla Bhupinder

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Introduction: Despite advances in trauma care, a classification system for soft tissue injuries of the face still needs to be objectively defined. Aim: To develop a classification system for soft tissue injuries of the face; that is objective, easy to remember, reproducible, universally applicable, aids in surgical management and helps to develop a structured data that can be used for future use. Material and Methods: This classification system includes those patients that need surgical management of facial injuries. Associated underlying bony fractures have been intentionally excluded. Depending upon the severity of soft tissue injury, these can be graded from 0 to IV (O-Abrasions, I-lacerations, II-Avulsion injuries with no skin loss, III-Avulsion injuries with skin loss that would need graft or flap cover, and IV-complex injuries). Anatomically, the face has been divided into three zones (Zone 1/2/3), as per aesthetic subunits. Zone 1e stands for injury of eyebrows; Zones 2 a/b/c stand for nose, upper eyelid and lower eyelid respectively; Zones 3 a/b/c stand for upper lip, lower lip and cheek respectively. Suffices R and L stand for right or left involved side, B for presence of foreign body like glass or pellets, C for extensive contamination and D for depth which can be graded as D 1/2/3 if depth is still fat, muscle or bone respectively. I is for damage to facial nerve or parotid duct. Results and conclusions: This classification system is easy to remember, clinically applicable and would help in standardization of surgical management of soft tissue injuries of face. Certain inherent limitations of this classification system are inability to classify sutured wounds, hematomas and injuries along or against Langer’s lines.

Keywords: soft tissue injuries, face, avulsion, classification

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Authors: Yi-De Liu

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Destination branding is a popular practice adopted by many cities in the context of intensified tourism competition. However, branding for major event is a relatively new domain in the studies of destination marketing. Based on a case study of Liverpool as the 2008 European Capital of Culture, the aim of this paper is to explore the effectiveness of the key branding campaign - the ‘Look of the City’ programme. This study looks at quantitative data collected from on-street face-to-face survey. 611 questionnaires were distributed to and collected from local residents, visitors from the immediate hinterland, domestic tourists and overseas visitors. The analysis is done, first by investigating respondents’ impression on the Liverpool 08 brand and the branding campaign, and then by exploring the effects of campaign. The positioning of Liverpool compared with other similar cities is addressed in the end. The final section extracts lessons from this empirical investigation.

Keywords: destination branding, major event, European capital of culture, Liverpool

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Authors: Kwounghee Choi

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Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

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Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

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Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: share of electricity generation, k-means clustering, discriminant, CO2 emission

Procedia PDF Downloads 393

Authors: Xi Zhang

Abstract:

Much has been written about the promotion of Standard Mandarin and the negative effects it may have had on the development of non-Mandarin dialects. Less discussed, however, is the fate of northern Chinese dialects that are only marginally different from Standard Mandarin and the effect Standard Mandarin promotion may have had on such dialects. In this paper, we seek to bridge this gap by looking at language preferences in the family and the generational differences that they reflect. Specifically, we survey Mandarin dialect speakers from Xinle county in Hebei province, whose local dialect is similar but not identical to Standard Mandarin. We sample more than 160 families with pre-middle school children and ask the parents a series of questions that probe language behavior, language ability, and language attitude within the family with regard to educating the young. Our study shows that although most parents still speak the Xinle dialect, Standard Mandarin has become the language taught to the majority of children. We also show that only one-third of parents choose to preserve elements of Xinle dialect in the language they teach to their children. We analyze the possible factors (e.g., subjective, geographical, social, and external) that influence language choice and show how these factors collectively contribute to the current state of family language choice for educational purposes. Finally, based on our findings, we offer recommendations for coordinating the promotion of Standard Mandarin and dialect preservation in similar Mandarin-speaking regions.

Keywords: Diglossia, language planning, Mandarin, standard-with-dialects

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Authors: Carmela Perta

Abstract:

Following the example of both International and European legislation, on 15 December 1999 the national law 482/99 Regulations regarding the protection of historic language minorities was approved, providing a national framework for the preservation and renaissance of minority languages «The Italian Republic sustains the language and culture of people speaking Albanian, Catalan, German, Greek, Slovene, Croatian, French, Francoprovençal, Friulan, Ladin, Occitan and Sard». The legislation made it possible to use these languages in education, in public offices, in local government, in the judicial system, in mass media, and allowed for the reinstatement of place and personal names. However, several practical problems have emerged, particularly those concerning the variety that should be used in education, in official documents and in other formal domains, i.e. the local variety, the standard of reference (if there is any), or an over regional koinè. In minority settings, it might seem eminently sensible to use the ready made standard of reference, accepting the Ausbausprache, rather than the language as practice, that is the local variety. However, this process seems to be pointless, as is demonstrated by the results of a fieldwork that was carried out in a small town in the South of Italy where members speak Faetar, the local variety of Francoprovençal. Here the language is largely used by the community members in all domains, moreover a deep sense of loyalty towards the variety they use and a manifested minority identity can be observed analysing the speakers’ attitudes. However, these positive attitudes are towards the vehicle for their distinctive history and culture, and not for an “external” standard, a system which local authorities and planners are trying to introduce in the community. In other words, according to the speakers' reactions, there is little point in struggling to maintain a language, if what is conserved is not the group’s language but another.

Keywords: maintenance, minority languages, endangered languages, francoprovençal

Procedia PDF Downloads 406

Authors: Deviana Yuanitasari

Abstract:

The rapid development of world commerce and trade nowadays has created fast-paced demand in every business activities and transactions. That also includes the need for ready to use and practical form of standard contract. For the company or business owner, the use of standard contract is an alternative way to achieve economic goals faster, effectively and efficiently. In the other hand, for the consumer the practice of using standard contract usually unfavorable, because the contract clauses usually have been defined by the company and cannot be individually negotiated. That means consumer cannot influence the substances of the contract clauses. The purpose of this study is to get deeper understanding and analyze the role of Consumer Dispute Settlement Body in the monitoring of standard clause inclusion by businesses and industries within the context of practicing consumer protection law. Furthermore, this study will focus on the procedure of sanction and the effectiveness of the sanction for the business practitioners which disregard the inclusion of the prohibited standard clause. Therefore, this study will depict the law issues and other phenomenon that related with the role of Consumer Dispute Settlement Body in monitoring the inclusion of standard clause and procedure of sanction for the business practitioners that still use exemption clause within Consumer Protection Law System. This study results that BPSK has been assigned to monitor the inclusion of standard clause and settle consumer dispute. At this stage, BPSK role is passive, which means BPSK only takes an action if there are consumer complaints. The procedure of sanction is not part of BPSK tasks, since should there be a violation of standard clause; BPSK can only ask the business practitioners to remove the prohibited clause and not give a sanction. As a result, the procedure of sanction rule for the Standard Clause violation in this context can be considered as ineffective.

Keywords: standard contract, standard clause, consumer protection law, consumer dispute settlement body

Procedia PDF Downloads 300

Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

Abstract:

Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

Procedia PDF Downloads 53

Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

Abstract:

This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

Procedia PDF Downloads 294