Search results for: features matching

Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

Procedia PDF Downloads 237

Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

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Authors: Liang Wang, Wei Zhang

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There have been some existing researches on design-based engineering learning (DBEL) and project-based or problem-based engineering learning (PBEL). Those findings have greatly promoted the reform of engineering education in China. However, the engineering with a big E means that more and more engineering activities are designed and operated by communities of practice (CoPs), namely community-based engineering learning. However, whether community-based engineering learning can promote students' innovation has not been verified in published articles. This study fills this gap by investigating the relationship between community-based learning approach and students’ creativity, using engineering identity as an intermediary variable. The goal of this study is to discover the core features of community-based engineering learning, and make the features more beneficial for students’ creativity. The study created and adapted open survey items from previously published studies and a scale on learning community, students’ creativity and engineering identity. Firstly, qualitative content analysis methods by MAXQDA were used to analyze 32 open-ended questionnaires. Then the authors collected data (n=322) from undergraduate students in engineering competition teams and engineering laboratories in Zhejiang University, and structural equation modelling (SEM) was used to understand the relationship between different factors. The study finds: (a) community-based engineering learning has four main elements like real-task context, self-inquiry learning, deeply-consulted cooperation and circularly-iterated design, (b) community-based engineering learning can significantly enhance the engineering undergraduate students’ creativity, and (c) engineering identity partially moderated the relationship between community-based engineering learning and undergraduate students' creativity. The findings further illustrate the value of community-based engineering learning for undergraduate students. In the future research, the authors should further clarify the core mechanism of community-based engineering learning, and pay attention to the cultivation of undergraduate students’ engineer identity in learning community.

Keywords: community-based engineering learning, students' creativity, engineering identity, moderate effect

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Authors: Brighton Chamunorwa

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The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Jean-François Caron

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The current attempts to develop what we can call 'super soldiers' are problematic in many regards. This is what this text will try to explore by concentrating primarily on the repercussions of this technology and medical research on the physical and psychological integrity of soldiers. It argues that medicines or technologies may affect soldiers’ psychological and mental features and deprive them of their capacity to reflect upon their actions as autonomous subjects and that such a possibility entails serious moral as well as judicial consequences.

Keywords: military research, super soldiers, involuntary intoxication, criminal responsibility

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Authors: Wafeek Mohamed Ibrahim Mohamed

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In the era of globalization and openness informational. Anyone who thinks about innovation in the earth population in Islam in our contemporary reality, he will find that it is not destined to its civilized extension to last. The purpose of the research is a trial to reach a realistic vision for creative, innovative and intellectual thought for the earth population in Islam as an instrument to Confrontation and observe the changes that have affected in the architecture of the land during different eras. Through knowing the controls of the ruling legitimacy(that served as definitions and laws which formulate its features) and using customs, traditions, and conventions as a telescope for the earth population in Islam, It explained the impact of them on features of creative formation for the architecture of the land in our contemporary reality. The study shows a modern vision to identify innovation in the earth population in Islam. As well as reformulating its mental image and monitoring its changes in Islamic heritage cities. This will be done through a two main branches: firstly, set forth a theory represented in studying creative concepts which formulate the population of the earth in Islam. Such as initiative and responsibility for reviving the dead land, the lane [alley] as formation unit and social solidarity,… Etc.. The second branch is preparing a practical, critical vision for innovative conceptual thought for the architecture of the land of Islam, through studying the development of a traditional Islamic city., The conceptual thought of making the birth festival ["Al-Refaee"] and its emulation for governing roles in the traditional city building. The research concludes The necessity of forming the suggested a creative vision for identifying how to re-form the conceptual for our contemporary population of the earth. It poses an important question which is how to return to creativity in the architecture of the land of Islam in our built environments.

Keywords: innovation and creation, architecture, the land in Islam, criticism of design

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Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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Authors: Yilin Ma, Zhaomiao Liu, Xiang Wang, Yan Pang

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Microscale droplets play an increasingly important role in various applications, including medical diagnostics, material synthesis, chemical engineering, and cell research due to features of high surface-to-volume ratio and tiny scale, which can significantly improve reaction rates, enhance heat transfer efficiency, enable high-throughput parallel studies as well as reduce reagent usage. As a mature technique to manipulate small amounts of liquids, droplet microfluidics could achieve the precise control of droplet parameters such as size, uniformity, structure, and thus has been widely adopted in the engineering and scientific research of multiple fields. Necking processes of the droplet in the cross junction microchannels are experimentally and theoretically investigated and dynamic mechanisms of the neck thinning in two different regimes are revealed. According to evolutions of the minimum neck width and the thinning rate, the necking process is further divided into different stages and the main driving force during each stage is confirmed. Effects of the flow rates and the cross-sectional aspect ratio on the necking process as well as the neck profile at different stages are provided in detail. The distinct features of the two regimes in the squeezing stage are well captured by the theoretical estimations of the effective flow rate and the variations of the actual flow rates in different channels are reasonably reflected by the channel width ratio. In the collapsing stage, the quantitative relation between the minimum neck width and the remaining time is constructed to identify the physical mechanism.

Keywords: cross junction, neck thinning, force analysis, inertial mechanism

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Authors: Ali A. Karakhan

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Stakeholders in the architecture, engineering, and construction (AEC) industry have been always searching for strategies to develop, design, and construct healthy and smart building projects. Healthy and smart building projects require that the building process including design and construction be altered and carefully implemented in order to bring about sustainable outcomes throughout the facility lifecycle. Healthy and smart building projects are expected to positively influence organizational success and facility performance across the project lifecycle leading to superior outcomes in terms of people, economy, and the environment. The present study aims to identify potential strategies that AEC organizations can implement to achieve healthy and smart building projects. Drivers and barriers for healthy and smart building features are also examined. The study findings indicate that there are three strategies to advance the development of healthy and smart building projects: (1) the incorporation of high-quality products and low chemical-emitting materials, (2) the integration of innovative designs, methods, and practices, and (3) the adoption of smart technology throughout the facility lifecycle. Satisfying external demands, achievement of a third-party certification, obtaining financial incentives, and a desire to fulfill professional duty are identified as the key drivers for developing healthy and smart building features; whereas, lack of knowledge and training, time/cost constrains, preference for/adherence to customary practices, and unclear business case for why healthy buildings are advantageous are recognized as the primary barriers toward a wider diffusion of healthy and smart building projects. The present study grounded in previous engineering, medical, and public health research provides valuable technical and practical recommendations for facility owners and industry professionals interested in pursuing sustainable, yet healthy and smart building projects.

Keywords: healthy buildings, smart construction, innovative designs, sustainable projects

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Authors: Shima Soleimani, Steven Eckels

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One area of special importance for the surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fine height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling the inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fine height has a greater impact on performance factors than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer, and pressure drops up to 21% and 56% compared to a 2D one, respectfully.

Keywords: three-dimensional micro-fin tube, heat transfer, friction factor, heat exchanger

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Authors: Sung Un Kim, Ivana Martinović, Snježana Stanarević Katavić

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As more and more youth use mobile devices, such as tablets and smartphones, for information seeking in their everyday lives, the purpose of this study is to understand the behaviors of youth seeking health information on mobile devices. The specific objective of this study is to examine 1) for what health issues youth use mobile devices, 2) for what reasons youth use mobile devices to obtain health information, 3) in what ways youth use mobile devices for health information, and 4) the features of health applications that youth find useful. The researchers devised a questionnaire for this study. Four hundred eight students from two high schools, located in Osijek, Croatia, participated by answering the questionnaire (281 girls and 127 boys). The collected data were analyzed using descriptive statistics and content analysis. The results show that among all participants, about 85 percent (n = 344) reported having used mobile devices for health information. The most frequent health topic for which they had been using mobile devices is physical activity (n = 273), followed by eating issues and nutrition (n = 224), mental health (n = 160), sexual health (n = 157), alcohol, drugs, and tobacco (n = 125), safety (n = 96) and particular diseases (n = 62). They use mobile devices to obtain health information due to the ease of use (n = 342), the ease of sharing health information (n = 281), portability (n = 215), timeliness (n = 162), and the ease of tracking/recording/monitoring health status (n = 147). Of those who have used mobile devices for health information, three-quarters (n = 261) use mobile devices to search health information, while 32.8% (n =113) use applications and 31.7% (n =109) browse information. Those who have used applications for health information (n = 113) consider the alert feature (n=107) as the most useful, followed by the tracking/recording/monitoring feature (n =92), the customized information feature (n = 86), the video feature (n = 58), and the sharing feature (n =39). It is notable that although health applications have been actively developed and studied, a majority of the participants search for or browse information on mobile devices, instead of using applications. The researchers will discuss reasons that some of them did not use mobile devices to obtain health information, students’ concerns about using health applications, and features that they wish to have in health applications.

Keywords: Croatia, health information, information seeking behaviors, mobile devices, youth

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

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Authors: Zsuzsanna Fejes

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The aim of this paper is to provide an overview of the legal history of constitutionalism in Hungary, in focus of the democratic transitions in 1989-1990, describing the historical and political background of the changes and presenting the main and most important features of the new democracy, and institutional and legal orders. In Hungary the evolved political, economic and moral crisis prior to the constitutional years 2010-11 had been such a constitutional moment, which led to an opportune and unavoidable change at the same time. The Hungarian constitutional power intended to adopt a new constitution, which was competent to create a common constitutional identity and to express a national unity. The Hungarian Parliament on 18th April 2011 passed the New Fundamental Law. The new Fundamental Law rich in national values meant a new challenge for the academics, lawyers, and political scientists. Not only the classical political science, but also the constitutional law and theory have to struggle with the interpretation of the new declarations about national constitutional values in the Fundamental Law. The main features and structure of the new Fundamental Law will be analysed, and given a detailed interpretation of the Preamble as a declaration of constitutional values. During the examination of the Preamble shall be cleared up the components of Hungarian statehood and national unity, individual and common human rights, the practical and theoretical demand on national sovereignty, and the content and possibilities for the interpretation of the achievements of the historical Constitution. These scopes of problems will be presented during the examination of the text of National Avowal, as a preamble of the Fundamental Law. It is examined whether the Fundamental Law itself could be suitable and sufficient means to citizens of Hungary to express the ideas therein as their own, it will be analysed how could the national and European common traditions, values and principles stated in the Fundamental Law mean maintenance in Hungary’s participation in the European integration.

Keywords: common constitutional values, constitutionalism, national identity, national sovereignty, national unity, statehood

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Authors: Arezoo Assarian, Reza Javaherdashti

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Microbiologically influenced corrosion (MIC) is an electrochemical process that can affect both metals and non-metals. The cost of MIC can amount to 40% of the cost of corrosion. MIC is enhanced via factors such as but not limited to the presence of certain bacteria and archaea as well as mechanisms such as external electron transfer. There are five methods by which electrochemical corrosion, including MIC, can be prevented, of which coatings are an effective method due to blinding anode, cathode and, electrolyte from each other. Conventional ordinary coatings may themselves become nutrient sources for the bacteria and therefore show low efficiency in dealing with MIC. Recently our works on polyaspartic coating (DTM) have shown promising results, therefore nominating DTM as the most appropriate coating material to manage both MIC and general electrochemical corrosion very efficiently. Nanosilver particles are known for their antimicrobial properties that make them of desirable distractive impacts on any germs. This coating will be formulated based on Nanosilver phosphate and copper II oxide in the resin network and co-reactant. The nanoparticles are light and heat-sensitive agents. The method which is used to keep nanoparticles in the film coating is the encapsulation of active ingredients. By this method, it will prevent incompatibility between different particles. For producing microcapsules, the interfacial cross-linking method will be used. This is achieved by adding an active ingredient to an aqueous solution of the cross-linkable polymer. In this paper, we will first explain the role of coating materials in controlling and preventing electrochemical corrosion. We will explain MIC and some of its fundamental principles, such as bacteria establishment (biofilm) and the role they play in enhancing corrosion via mechanisms such as the establishment of differential aeration cells. Later we will explain features of DTM coatings that highly contribute to preventing biofilm formation and thus microbial corrosion.

Keywords: biofilm, corrosion, microbiologically influenced corrosion(MIC), nanosilver particles, polyaspartic coating (DTM)

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Authors: Elena E. Lyakso, Olga V. Frolova, Yuri N. Matveev, Aleksey S. Grigorev, Alexander S. Nikolaev, Viktor A. Gorodnyi

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The study of the children’s emotional sphere depending on age and psychoneurological state is of great importance for the design of educational programs for children and their social adaptation. Atypical development may be accompanied by violations or specificities of the emotional sphere. To study characteristics of the emotional state reflection in the voice and speech features of children, the perceptual study with the participation of adults and the automatic recognition of speech were conducted. Speech of children with typical development (TD), with Down syndrome (DS), and with autism spectrum disorders (ASD) aged 6-12 years was recorded. To obtain emotional speech in children, model situations were created, including a dialogue between the child and the experimenter containing questions that can cause various emotional states in the child and playing with a standard set of toys. The questions and toys were selected, taking into account the child’s age, developmental characteristics, and speech skills. For the perceptual experiment by adults, test sequences containing speech material of 30 children: TD, DS, and ASD were created. The listeners were 100 adults (age 19.3 ± 2.3 years). The listeners were tasked with determining the children’s emotional state as “comfort – neutral – discomfort” while listening to the test material. Spectrographic analysis of speech signals was conducted. For automatic recognition of the emotional state, 6594 speech files containing speech material of children were prepared. Automatic recognition of three states, “comfort – neutral – discomfort,” was performed using automatically extracted from the set of acoustic features - the Geneva Minimalistic Acoustic Parameter Set (GeMAPS) and the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS). The results showed that the emotional state is worse determined by the speech of TD children (comfort – 58% of correct answers, discomfort – 56%). Listeners better recognized discomfort in children with ASD and DS (78% of answers) than comfort (70% and 67%, respectively, for children with DS and ASD). The neutral state is better recognized by the speech of children with ASD (67%) than by the speech of children with DS (52%) and TD children (54%). According to the automatic recognition data using the acoustic feature set GeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.687; children with DS – 0.725; TD children – 0.641. When using the acoustic feature set eGeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.671; children with DS – 0.717; TD children – 0.631. The use of different models showed similar results, with better recognition of emotional states by the speech of children with DS than by the speech of children with ASD. The state of comfort is automatically determined better by the speech of TD children (precision – 0.546) and children with ASD (0.523), discomfort – children with DS (0.504). The data on the specificities of recognition by adults of the children’s emotional state by their speech may be used in recruitment for working with children with atypical development. Automatic recognition data can be used to create alternative communication systems and automatic human-computer interfaces for social-emotional learning. Acknowledgment: This work was financially supported by the Russian Science Foundation (project 18-18-00063).

Keywords: autism spectrum disorders, automatic recognition of speech, child’s emotional speech, Down syndrome, perceptual experiment

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Authors: Theresa Zagers, Rita Guerra

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Most research investigating how receiving communities perceive, and experience migration has overlooked the potential role of subjective social class and social class identity in positive intergroup relations and social cohesion of migrants and host societies. The present study aimed to provide insights to understand this relationship and focused on three important features: prosocial behaviour, attitudes and emotions towards Muslim immigrants in Flanders, Belgium. Building on relative deprivation-gratification theory we examined the indirect relationships of subjective social class on prosocial behaviour/intentions, attitudes and emotions via relative deprivation (RD), as well as the moderator role of the importance of social class identity. 431 Belgian participants participated in an online survey study. Overall, our results supported the predicted indirect effect of subjective social class: the lower the subjective social class, the higher the perceptions of relative deprivation, which in turn is related to less prosocial behaviour intentions, and more negative attitudes and emotions towards immigrants. This indirect effect was, however, not moderated by the importance of social class identity. Interestingly, the direct effects of subjective social class showed a different pattern: when bypassing deprivation our results showed higher subjective social class was detrimental for intergroup relations (more negative attitudes and emotions), and that lower subjective social class was positively related to prosocial intentions for those identifying highly with their class identity. Overall, we gained valuable insights in the relationship of subjective social class and the three features of intergroup relations.

Keywords: social class, relative deprivation-gratification, prosocial behavior, attitudes, emotions, Muslim immigrants

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Adijat Olubukola Olateju

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Women empowerment is an essential developmental tool in every economy especially in less developed countries; as it helps to enhance women's socio-economic well-being. Some empirical evidence has shown that microcredit has been an effective tool in enhancing women empowerment, especially in developing countries. This paper therefore, investigates the impact of microcredit programme on women empowerment in Lagos State, Nigeria. The study used Cowries Microfinance Bank (CMB) as a case study bank, and a total of 359 women entrepreneurs were selected by simple random sampling technique from the list of Cowries Microfinance Bank. Selection bias which could arise from non-random selection of participants or non-random placement of programme, was adjusted for by dividing the data into participant women entrepreneurs and non-participant women entrepreneurs. The data were analyzed with a Propensity Score Matching (PSM) technique. The result of the Average Treatment Effect on the Treated (ATT) obtained from the PSM indicates that the credit programme has a significant effect on the empowerment of women in the study area. It is therefore, recommended that microfinance banks should be encouraged to give loan to women and for more impact of the loan to be felt by the beneficiaries the loan programme should be complemented with other programmes such as training, grant, and periodic monitoring of programme should be encouraged.

Keywords: empowerment, microcredit, socio-economic wellbeing, development

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Authors: Jonathan Matyenyika

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In recent years, automobile manufacturers have increasingly produced vehicles equipped with cutting-edge automotive electronic technology to match the fast-paced digital world of today; this has brought about various benefits in different business sectors that make use of these vehicles as a means of turning over a profit. In the logistics industry, vehicles equipped with this technology have proved to be very utilitarian; this paper focuses on the benefits automobile electronic equipped vehicles have in the logistics industry. Automotive vehicle manufacturers have introduced new technological electronic features to their vehicles to enhance and improve the overall performance, efficiency, safety and driver comfort. Some of these features have proved to be beneficial to logistics operators. To start with the introduction of adaptive cruise control in long-distance haulage vehicles, to see how this system benefits the drivers, we carried out research in the form of interviews with long-distance truck drivers with the main question being, what major difference have they experienced since they started to operate vehicles equipped with this technology to which most stated they had noticed that they are less tired and are able to drive longer distances as compared to when they used vehicles not equipped with this system. As a result, they can deliver faster and take on the next assignment, thus improving efficiency and bringing in more monetary return for the logistics company. Secondly, the introduction of electric hybrid technology, this system allows the vehicle to be propelled by electric power stored in batteries located in the vehicle instead of fossil fuel. Consequently, this benefits the logistic company as vehicles become cheaper to run as electricity is more affordable as compared to fossil fuel. The merging of electronic systems in vehicles has proved to be of great benefit, as my research proves that this can benefit the logistics industry in plenty of ways.

Keywords: logistics, manufacturing, hybrid technology, haulage vehicles

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Takatoshi Ishii, Koji Kimita, Keiichi Muramatsu, Yoshiki Shimomura

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To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.

Keywords: co-creational education, e-portfolios, ICT integration, latent dirichlet allocation

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Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad

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Distress refers to an unpleasant metal state or emotional suffering marked by negative affect such as depression (e.g., lost interest; sadness; hopelessness), anxiety (e.g., restlessness; feeling tense). These negative affect have been mostly suggested to be concomitant of metal disorders such as positive psychosis symptoms and also of proneness to psychotic features in non-clinical population. Psychotic features proneness including hallucination, delusion and schizotypal traits, have been found to be associated with metacognitive beliefs. Metacognition has been conceptualized as ‘thinking about thoughts, monitoring and controlling of cognitive processes’. The aim of the current study was to investigate the role of psychosis proneness in the association of metacognitions and distress. We predicted psychosis proneness would mediate the association of metacognitive beliefs and the distress. A sample of 420 university students was randomly recruited to endorse questionnaires of the study that consisted of DASS-21questionnaire for assessing levels of distress, Cartwright–Hatton & Wells, Meta-cognitions Questionnaire (MCQ-30) for assessing metacognitive beliefs, Launay-Slade Hallucination Scale-revised (LSHS-R), Peters et al. Delusions Inventory, Schizotypal Personality Questionnaire-Brief. Conducting a bootstrapping approach in order to investigate our hypothesis, the result showed that there was no a direct association between metacognitive dimensions and psychological distress and psychosis proneness significantly mediated the association. Finding suggested that individuals with dysfunctional metacognitive beliefs experience high levels of distress if they are prone to psychosis symptoms. In other words, psychosis proneness is a path through which individuals with dysfunctional metacognitions experience high levels of psychological distress.

Keywords: metacognition, non-clinical population, psychological distress, psychosis proneness

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Authors: Andrea Hernandez Hurtado

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Research on social networks (SNs) -- the interactions individuals share with others has shed important light in helping to explain differential use of variable linguistic forms, both in L1s and L2s. Nevertheless, the acquisition of nonstandard L2 Spanish in the Region of Murcia, Spain, and how learners interact with other speakers while sojourning there have received little attention. Murcian Spanish (MuSp) was widely influenced by Panocho, a divergent evolution of Hispanic Latin, and differs from the more standard Peninsular Spanish (StSp) in phonology, morphology, and lexicon. For instance, speakers from this area will most likely palatalize diminutive endings, producing animalico [̩a.ni.ma.ˈli.ko] instead of animalito [̩a.ni.ma.ˈli.to] ‘little animal’. Because L1 speakers of the area produce and prefer salient regional lexicon and morphology (particularly the palatalized diminutive -ico) in their speech, the current research focuses on how international residents in the Region of Murcia use Spanish: (1) whether or not they acquire (perceptively and/or productively) any of the salient regional features of MuSp, and (2) how their SNs explain such acquisition. This study triangulates across three tasks -recognition, production, and preference- addressing both lexicon and morphology, with each task specifically created for the investigation of MuSp features. Among other variables, the effects of L1, residence, and identity are considered. As an ongoing dissertation research, data are currently being gathered through an online questionnaire. So far, 7 participants from multiple nationalities have completed the survey, although a minimum of 25 are expected to be included in the coming months. Preliminary results revealed that MuSp lexicon and morphology were successfully recognized by participants (p<.001). In terms of regional lexicon production (10.0%) and preference (47.5%), although participants showed higher percentages of StSp, results showed that international residents become aware of stigmatized lexicon and may incorporate it into their language use. Similarly, palatalized diminutives (production 14.2%, preference 19.0%) were present in their responses. The Social Network Analysis provided information about participants’ relationships with their interactants, as well as among them. Results indicated that, generally, when residents were more immersed in the culture (i.e., had more Murcian alters) they produced and preferred more regional features. This project contributes to the knowledge of language variation acquisition in L2 speakers, focusing on a stigmatized Spanish dialect and exploring how stigmatized varieties may affect L2 development. Results will show how L2 Spanish speakers’ language is affected by their stay in Murcia. This, in turn, will shed light on the role of SNs in language acquisition, the acquisition of understudied and marginalized varieties, and the role of immersion on language acquisition. As the first systematic account on the acquisition of L2 Spanish lexicon and morphology in the Region of Murcia, it lays important groundwork for further research on the connection between SNs and the acquisition of regional variants, applicable to Murcia and beyond.

Keywords: international residents, L2 Spanish, lexicon, morphology, nonstandard language acquisition, social networks

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya

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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay Tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.

Keywords: ETX, opportunistic routing, PSR, throughput

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Authors: Lorenzo Buti

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This paper investigates the nature of democratic action through a critical reading of Claude Lefort’s notion of the democratic ‘regime’. Lefort provides one of the most innovative accounts of the essential features of a democratic regime. According to him, democracy is a political regime that acknowledges the indeterminacy of a society and stages it as a contestation between competing political actors. As such, democracy provides the symbolic markers of society’s openness towards the future. However, despite their democratic features, the recent decades in late capitalist societies attest to a sense of the future becoming fixed and predetermined. This suggests that Lefort’s conception of democracy harbours a misunderstanding of the character and experience of democratic action. This paper examines this underlying tension in Lefort’s work. It claims that Lefort underestimates how a democratic regime, next to its symbolic function, also takes a materially constituted form with its particular dynamics of power relations. Lefort’s systematic dismissal of this material dimension for democratic action can lead to the contemporary paradoxical situation where democracy’s symbolic markers are upheld (free elections, public debate, dynamic between government and opposition in parliament,…) but the room for political decision-making is constrained due to a myriad of material constraints (e.g., market pressures, institutional inertias). The paper draws out the implications for the notion of democratic action. Contra Lefort, it argues that democratic action necessarily targets the material conditions that impede the capacity for decision-making on the basis of equality and liberty. This analysis shapes our understanding of democratic action in two ways. First, democratic action takes an asymmetrical, insurgent form, as a contestation of material power relations from below. Second, it reveals an ambivalent position vis-à-vis the political regime: democratic action is symbolically made possible by the democratic dispositive, but it contests the constituted form that the democratic regime takes.

Keywords: Claude Lefort, democratic action, material constitution, political regime

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

Procedia PDF Downloads 380