Search results for: European Standard Classification

Authors: Pedro M. Abreu, Bruno R. Mendes

Abstract:

The management of pharmacotherapy and the process of dispensing medicines is becoming critical in clinical pharmacy due to the increase of incidence and prevalence of chronic diseases, the complexity and customization of therapeutic regimens, the introduction of innovative and more expensive medicines, the unbalanced relation between expenditure and revenue as well as due to the lack of rationalization associated with medication use. For these reasons, co-payments emerged in Europe in the 70s and have been applied over the past few years in healthcare. Co-payments lead to a rationing and rationalization of user’s access under healthcare services and products, and simultaneously, to a qualification and improvement of the services and products for the end-user. This analysis, under hospital practices particularly and co-payment strategies in general, was carried out on all the European regions and identified four reference countries, that apply repeatedly this tool and with different approaches. The structure, content and adaptation of European co-payments were analyzed through 7 qualitative attributes and 19 performance indicators, and the results expressed in a scorecard, allowing to conclude that the German models (total score of 68,2% and 63,6% in both elected co-payments) can collect more compliance and effectiveness, the English models (total score of 50%) can be more accessible, and the French models (total score of 50%) can be more adequate to the socio-economic and legal framework. Other European models did not show the same quality and/or performance, so were not taken as a standard in the future design of co-payments strategies. In this sense, we can see in the co-payments a strategy not only to moderate the consumption of healthcare products and services, but especially to improve them, as well as a strategy to increment the value that the end-user assigns to these services and products, such as medicines.

Keywords: clinical pharmacy, co-payments, healthcare, medicines

Procedia PDF Downloads 221

Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

Abstract:

Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

Procedia PDF Downloads 404

Authors: Javier Alfonso Bonilla-Chávez, Angélica Lozano

Abstract:

In North America, more than 2,000 people annually die in accidents related to railroad tracks. In 2020, collisions at grade crossings were the main cause of deaths related to railway accidents in Mexico. Railway networks have constant interaction with motor transport users, cyclists, and pedestrians, mainly in grade crossings, where is the greatest vulnerability and risk of accidents. Usually, accidents at grade crossings are directly related to risky behavior and non-compliance with regulations by motorists, cyclists, and pedestrians, especially in developing countries. Around the world, countries classify these crossings in different ways. In Mexico, according to their dangerousness (high, medium, or low), types A, B and C have been established, recommending for each one different type of auditive and visual signaling and gates, as well as horizontal and vertical signaling. This classification is based in a weighting, but regrettably, it is not explained how the weight values were obtained. A review of the variables and the current approach for the grade crossing classification is required, since it is inadequate for some crossings. In contrast, North America (USA and Canada) and European countries consider a broader classification so that attention to each crossing is addressed more precisely and equipment costs are adjusted. Lack of a proper classification, could lead to cost overruns in the equipment and a deficient operation. To exemplify the lack of a good classification, six crossings are studied, three located in the rural area of Mexico and three in Mexico City. These cases show the need of: improving the current regulations, improving the existing infrastructure, and implementing technological systems, including informative signals with nomenclature of the involved crossing and direct telephone line for reporting emergencies. This implementation is unaffordable for most municipal governments. Also, an inventory of the most dangerous grade crossings in urban and rural areas must be obtained. Then, an approach for improving the classification of grade crossings is suggested. This approach must be based on criteria design, characteristics of adjacent roads or intersections which can influence traffic flow through the crossing, accidents related to motorized and non-motorized vehicles, land use and land management, type of area, and services and economic activities in the zone where the grade crossings is located. An expanded classification of grade crossing in Mexico could reduce accidents and improve the efficiency of the railroad.

Keywords: accidents, grade crossing, railroad, traffic safety

Procedia PDF Downloads 79

Authors: Ahmed M. Seyam, Rita Nemes, Salem Georges Nehme

Abstract:

Europe and the United States have a worldwide significance in the field of concrete control and construction; according to that, a lot of countries adopted their standards and regulations in the concrete field, as proof of the Europe and US strong standards and due to lack of own regulations. The main controlled property of concrete are the compressive strength, flexure tensile strength, and modulus of elasticity as it relates both to its bearing capacity and to the durability of the elements built with it, so in this paper, ASTM standard and EN standards method of testing those properties were put under the microscope to compare the variations between them.

Keywords: concrete, ASTM, EU standards, compressive strength, flexural strength, modulus of elasticity

Procedia PDF Downloads 61

Authors: Emmanuel Pedler, Elena Raevskikh, Maxime Jaffré

Abstract:

Can the cultural geography of European cities be durably managed by European policies? To answer this question, two hypotheses can be proposed. (1) Either European cultural policies are able to erase cultural inequalities between the territories through the creation of new areas of cultural attractiveness in each beneficiary neighborhood, city or country. Or, (2) each European region historically rooted in a number of endogenous socio-historical, political or demographic factors is not receptive to exogenous political influences. Thus, the cultural attractiveness of a territory is difficult to measure and to impact by top-down policies in the long term. How do these two logics - European and local - interact and contribute to the emergence of a valued, popular sense of a common European cultural identity? Does this constant interaction between historical backgrounds and new political concepts encourage a positive identification with the European project? The European cultural policy programs, such as ECC (European Capital of Culture), seek to develop new forms of civic cohesion through inclusive and participative cultural events. The cultural assets of a city elected ‘ECC’ are mobilized to attract a wide range of new audiences, including populations poorly integrated into local cultural life – and consequently distant from pre-existing cultural offers. In the current context of increasingly heterogeneous individual perceptions of Europe, the ECC program aims to promote cultural forms and institutions that should accelerate both territorial and cross-border European cohesion. The new cultural consumption pattern is conceived to stimulate integration and mobility, but also to create a legitimate and transnational ideal European citizen type. Our comparative research confronts contrasting cases of ‘European Capitals of Culture’ from the south and from the north of Europe, cities recently concerned by the ECC political mechanism and cities that were elected ECC in the past, multi-centered cultural models vs. highly centralized cultural models. We aim to explore the impacts of European policies on the urban cultural geography, but also to understand the current obstacles for its efficient implementation.

Keywords: urbanism, cultural policies, cultural institutions, european cultural capitals, heritage industries, exclusion effects

Procedia PDF Downloads 232

Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

Abstract:

In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

Procedia PDF Downloads 828

Authors: David Martínez Rico, Juan Pablo Farid Cuéllar Martínez

Abstract:

After more than half a century that the first treaty of European cooperation was created, the final result of a difficult and long historical process, which is the current European Union, is facing economical and social challenges. The barriers of policies differences and national sovereignties seem to be being defeated in the last and present decades. However, the last crisis of 2008 brought back problems as xenophobia and nationalism. In this ambit of identity, European Union has made many efforts to reinforce a European identity and leave behind the radical nationalisms which generated World Wars. Nevertheless, these social problems are increasing and becoming more present in the life of many Europeans. Even, in the last Euro Parliamentarian Elections of the present year, 2014, the extreme right parties, in favor of xenophobic and anti European ideals, got more seats and are increasing their presence in Euro Parliament. This essay approaches to this controversial topic of European identity. Taking as start point the nationalist divisions that are causing internal divergences in Europe, the authors of this research study the role and contributions of the Memorials of the fallen soldiers and heroes of World Wars, present in many cities as Amsterdam, Brussels and Paris, to the impossibility to reach an European identity, it means that Europeans feel first part of Europe in place to feel first part of a nation. The objective of this essay is to reaffirm the thesis that establishes that the European Union won´t reach the longed supranational identity with just with the current strategies, because yet there are many cultural elements in its member states societies which exalt the heroes and soldiers of the past wars, increasing nationalism feelings. Besides, in it are promoted some interesting ideas that could change the course in this quest of a European social identity.

Keywords: identity, memorials, European identity, nationalism, proposals

Procedia PDF Downloads 397

Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

Abstract:

It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

Procedia PDF Downloads 48

Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

Abstract:

In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

Procedia PDF Downloads 292

Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

Abstract:

Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

Procedia PDF Downloads 845

Authors: K. Masera, A. K. Hossain

Abstract:

Hardly any neat biodiesel satisfies the European EN14214 standard for compression ignition engine application. To satisfy the EN14214 standard, various additives are doped into biodiesel; however, biodiesel additives might cause other problems such as increase in the particular emission and increased specific fuel consumption. In addition, the additives could be expensive. Considering the increasing level of greenhouse gas GHG emissions and fossil fuel depletion, it is forecasted that the use of biodiesel will be higher in the near future. Hence, the negative aspects of the biodiesel additives will likely to gain much more importance and need to be replaced with better solutions. This study aims to satisfy the European standard EN14214 by blending the biodiesels derived from sustainable feedstocks. Waste Cooking Oil (WCO) and Animal Fat Oil (AFO) are two sustainable feedstocks in the EU (including the UK) for producing biodiesels. In the first stage of the study, these oils were transesterified separately and neat biodiesels (W100 & A100) were produced. Secondly, the biodiesels were blended together in various ratios: 80% WCO biodiesel and 20% AFO biodiesel (W80A20), 60% WCO biodiesel and 40% AFO biodiesel (W60A40), 50% WCO biodiesel and 50% AFO biodiesel (W50A50), 30% WCO biodiesel and 70% AFO biodiesel (W30A70), 10% WCO biodiesel and 90% AFO biodiesel (W10A90). The prepared samples were analysed using Thermo Scientific Trace 1300 Gas Chromatograph and ISQ LT Mass Spectrometer (GC-MS). The GS-MS analysis gave Fatty Acid Methyl Ester (FAME) breakdowns of the fuel samples. It was found that total saturation degree of the samples was linearly increasing (from 15% for W100 to 54% for A100) as the percentage of the AFO biodiesel was increased. Furthermore, it was found that WCO biodiesel was mainly (82%) composed of polyunsaturated FAMEs. Cetane numbers, iodine numbers, calorific values, lower heating values and the densities (at 15 ^oC) of the samples were estimated by using the mass percentages data of the FAMEs. Besides, kinematic viscosities (at 40 °C and 20 °C), densities (at 15 °C), heating values and flash point temperatures of the biomixture samples were measured in the lab. It was found that estimated and measured characterisation results were comparable. The current study concluded that biomixture fuel samples W60A40 and W50A50 were perfectly satisfying the European EN 14214 norms without any need of additives. Investigation on engine performance, exhaust emission and combustion characteristics will be conducted to assess the full feasibility of the proposed biomixture fuels.

Keywords: biodiesel, blending, characterisation, CI engine

Procedia PDF Downloads 142

Authors: Behzad Moeini Sam, Sara Mohammadi Avandi

Abstract:

The rituals of fire among the Iranians go back to the general Proto-Indo-European and Indo-Iranian eras when they lived in regions known as the Pontic-Caspian (Indo-Europeans) and Kazakhstan (the Andronovo culture belonging to the Indo-Iranian tribes), and we can get to know about their vulgar heritage despite their separation from each other during several millennia. The early Aryan settlers of Iran had brought their cults to their new home and were bequeathed to them by their Indo-Iranian ancestors. Tradition speaks of several great sacred Iranian fires consecrated by the pre-Zoroastrian kings. Ātar or fire corresponds to the Vedic Agni Atar's functions are elaborately delineated in the Later Avesta. This paper aims to show the fire cults among the Iranian Lur tribes that originate in the past. Therefore, it will be searched for rituals in equally Indo-European and Indo-Iranian Periods and Old Iranian Texts and their frequency among the Lur tribes. In addition to the library books, we tried to interview the chiefs of Lur tribes. Finally, we concluded that the fire among the Lur Tribes is a sequence of beliefs of the Proto-Indo-European and Indo-Iranian Periods reflected in Old and Middle Iranian texts.

Keywords: Indo-European, ancient Iran, fire, Lur, Zoroastrian

Procedia PDF Downloads 55

Authors: Gehad S. Kaseb, Mona F. Ahmed

Abstract:

Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. Few studies apply SA to Arabic dialects. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-AATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, classification, sentiment analysis, tweets

Procedia PDF Downloads 113

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

Procedia PDF Downloads 100

Authors: T. S. Ijimdiya, K. J. Osinubi

Abstract:

This study examines the influence of compactive efforts on hydraulic conductivity behaviour of compacted black cotton soil treated with bagasse ash which is necessary in assessing the performance of the soil - bagasse ash mixture for use as a suitable barrier material in waste containment application. Black cotton soil treated with up to 12% bagasse ash (obtained from burning the fibrous residue from the extraction of sugar juice from sugarcane) by dry weight of soil for use in waste containment application. The natural soil classifies as A-7-6 or CH in accordance with the AASHTO and the Unified Soil Classification System, respectively. The treated soil samples were prepared at molding water contents of -2, 0, +2, and +4 % of optimum moisture contents and compacted using four compactive efforts of Reduced British Standard Light (RBSL), British Standard light (BSL), West African Standard (WAS) and British Standard Heavy (BSH). The results obtained show that hydraulic conductivity decreased with increase in bagasse ash content, moulding water content and compaction energy.

Keywords: bagasse ash treatment, black cotton soil, hydraulic conductivity, moulding water contents, compactive efforts

Procedia PDF Downloads 396

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

Procedia PDF Downloads 106

Authors: M. G. Dirodi, G. Gugliotta, C. Leonardi

Abstract:

The member states shall establish zones and agglomerations throughout their territory to assess and manage air quality in order to comply with European directives. In Italy decree 155/2010, transposing Directive 2008/50/EC on ambient air quality and cleaner air for Europe, merged into a single act the previous provisions on ambient air quality assessment and management, including those resulting from the implementation of Directive 2004/107/EC relating to arsenic, cadmium, nickel, mercury, and polycyclic aromatic hydrocarbons in ambient air. Decree 155/2010 introduced stricter rules for identifying zones on the basis of the characteristics of the territory in spite of considering pollution levels, as it was in the past. The implementation of such new criteria has reduced the great variability of the previous zoning, leading to a significant reduction of the total number of zones and to a complete and uniform ambient air quality assessment and management throughout the Country. The present document is related to the new zones definition in Italy according to Decree 155/2010. In particular, the paper contains the description and the analysis of the outcome of zoning and classification.

Keywords: zones, agglomerations, air quality assessment, classification

Procedia PDF Downloads 291

Authors: Bruno Trstenjak, Dzenana Donko

Abstract:

Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

Procedia PDF Downloads 340

Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

Abstract:

In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

Procedia PDF Downloads 524

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

Procedia PDF Downloads 352

Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

Abstract:

In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: association rules, rule-based classification, classification quality, validation

Procedia PDF Downloads 402

Authors: Jun-Yong Lee, Hyoung-Gook Kim

Abstract:

In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

Procedia PDF Downloads 396

Authors: Tamar Lazariashvili

Abstract:

The paper examines the market of bioproducts in the world and in Georgia. The experience of European countries in the field of production of bioproducts is shown, the level of interest of the population in these products is presented, and the tendency of the demand for them to grow is evaluated. Objectives. The purpose of the research is to identify modern challenges and develop recommendations for development opportunities based on the analysis of the European and local market of organic products. Methodologies. General and specific methods are used in the research process: comparative analysis, induction, deduction. A desk study has been conducted. Findings. It has been revealed that the production of organic products in Georgia is significantly behind the European requirements, in the market of organic products of Georgia there is a formation of a layer of consumers who are in favor of healthy food and are ready to pay a different price. Conclusions. Based on the analysis of the bioproducts market, appropriate recommendations are proposed, namely, the introduction of innovative technologies; financial and legal support by the state; provision of consulting services on the tax system; Elimination of asymmetric information in the market and others.

Keywords: bioproducts market, European experience, production of bioproducts, layer of consumers.

Procedia PDF Downloads 33

Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

Abstract:

Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

Procedia PDF Downloads 486

Authors: Reinhard Neck, Guido Schäfer

Abstract:

In this paper, we explore the macroeconomic effects of the European Single Market on Austria by simulating the McKibbin-Sachs Global Model. Global interdependence and the impact of long-run effects on short-run adjustments are taken into account. We study the sensitivity of the results with respect to different assumptions concerning monetary and fiscal policies for the countries and regions of the world economy. The consequences of different assumptions about budgetary policies in Austria are also investigated. The simulation results are contrasted with ex-post evaluations of the actual impact of Austria’s membership in the Single Market. As a result, it can be concluded that the Austrian participation in the European Single Market entails considerable long-run gains for the Austrian economy with nearly no adverse side-effects on any macroeconomic target variable.

Keywords: macroeconomics, European Union, simulation, sensitivity analysis

Procedia PDF Downloads 252

Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

Abstract:

This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

Procedia PDF Downloads 7

Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

Abstract:

Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

Procedia PDF Downloads 445

Authors: Zhengkun Yi

Abstract:

Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

Procedia PDF Downloads 280

Authors: M. de Miguel Molina, V. Santamarina Campos, M. V. Segarra Oña, B. de Miguel Molina

Abstract:

Safety and security concerns play a key role during the design of civil UAs (aircraft controlled by a pilot who is not onboard it) by the producers and the offer of different services by the operators. At present, European countries have fragmented regulations about the manufacture and use of civil drones, therefore the European institutions are trying to approach all these regulations into a common one. In this sense, not only law but also ethics can give guidelines to the industry in order to obtain better reports from their clients. With our results, we would like to give advice to the European industry, as well as give new insights to the academia and policymakers.

Keywords: ethics, regulation, safety, security

Procedia PDF Downloads 630

Authors: Kumar Shashvat, Amol P. Bhondekar

Abstract:

In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

Procedia PDF Downloads 353