Search results for: sparse representation

Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Diksha Kadam

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The study of images of women in literature and women writers has been a significant area of concern for the last four decades because it is as ‘the study of signification and meaning production’ play a vital role in shaping the perceptions and consciousness of various segment of society in relation to the lives, roles, problems and experiences of different categories of women as women and as autonomous citizen of society. In the history of worlds English literature the status of women and representation of her in the writings is an issue of discussion always. The essence of her existence in the literature is felt; the ecstasy of her feelings is always seen. The literature is full of facts and figures. She is one of them. Her contribution to the literature is undoubtedly a beginning of a new era. Multiple challenges and multiple identities as represented in majority of the literary texts and in real provide much hope and assurance to the new generation of mothers and daughters in the direction of transformation of the individual and collective consciousness of society paving way for the emergence of an actually empowered new woman. This paper will focus on some of the prominent Indian and American women writers in English literature and the various dimensions of her image through some of the prominent works. This attempt of mine will be merely a salute to those women who have struggled to prove their identity as one of the members of society.

Keywords: role of women’s writing, new era, contribution to the literature, consciousness, existence

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Hernani Brinati, Mardel de Conti, Moyses Szajnbok, Valentina Domiciano

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This study brings a mathematical model and examples for the numerical prediction of submersible maneuvers in the horizontal and in the vertical planes. The geometry of the submarine is here taken as a body of revolution plus a sail, two horizontal and two vertical rudders. The model includes the representation of the hull resistance and of the propeller thrust and torque, what enables to consider the variation of the longitudinal component of the velocity of the ship when maneuvering. The hydrodynamic forces are represented through power series expansions of the acceleration and velocity components. The hydrodynamic derivatives for the body of revolution are mostly estimated based on fundamental principles applicable to the flow around airplane fuselages in the subsonic regime. The hydrodynamic forces for the sail and rudders are estimated based on a finite aspect ratio wing theory. The objective of this study is to build an expedite model for submarine maneuvers prediction, based on fundamental principles, which may be convenient in the early stages of the ship design. This model is tested against available numerical and experimental data.

Keywords: submarine maneuvers, submarine, maneuvering, dynamics

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Authors: Jesse D. Cano, Marlon J. Remedios

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Cuban tourism has developed so much in the last 30 years to the point of becoming one of the engines of the Cuban economy. With such a development, Cuban companies opting for e-tourism as a way to publicize their products and attract customers has also grown. Despite this fact, the majority of Cuban tourism-themed websites simply provide information on the different products and services they offer which results in many cases, in the user getting overwhelmed with the amount of information available which results in the user abandoning the search before he can find a product that fits his needs. Customization has been recognized as a critical factor for successful electronic tourism business and the use of recommender systems is the best approach to address the problem of personalization. This paper aims to outline a preliminary technique to obtain predictions about which products a particular user would give a better evaluation; these products would be those which the website would show in the first place. To achieve this, the theoretical elements of the Cuban tourism environment are discussed; recommendation systems and geographic information systems as tools for information representation are also discussed. Finally, for each structural component identified, we define a set of rules that allows obtaining an electronic tourism system that handles the personalization of the service provided effectively.

Keywords: geographic information system, technique, tourism products, recommendation

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Authors: Djamal Hamadi, Sifeddine Abderrahmani, Toufik Maalem, Oussama Temami

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In recent years many finite elements have been developed for plate bending analysis. The formulated elements are based on the strain based approach. This approach leads to the representation of the displacements by higher order polynomial terms without the need for the introduction of additional internal and unnecessary degrees of freedom. Good convergence can also be obtained when the results are compared with those obtained from the corresponding displacement based elements, having the same total number of degrees of freedom. Furthermore, the plate bending elements are free from any shear locking since they converge to the Kirchhoff solution for thin plates contrarily for the corresponding displacement based elements. In this paper the efficiency of the strain based approach compared to well known displacement formulation is presented. The results obtained by a new formulated plate bending element based on the strain approach and Kirchhoff theory are compared with some others elements. The good convergence of the new formulated element is confirmed.

Keywords: displacement fields, finite elements, plate bending, Kirchhoff theory, strain based approach

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Authors: Joe Amalraj, M. Arunkumar

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Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Yessica Martinez Soto, Cesar E. Jimenez Yanez, Margarita Barak Velasquez, Yaralin Aceves Villanueva

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The presence of violent behavior in society is growing rapidly, which causes people to live in an environment of constant tension due to fear of becoming victims of violent acts. It is up to social scientists to be able to carry out analyzes in this regard to identify the different ways in which violence is normalized among people. The interest of this research work focuses on investigating the perception of violence in Mexican University students through the technique of drawing. To carry out this research, we worked with 67 university students from the Autonomous University of Baja California in Mexico, who drew an image of how they understood the concept of violence. His works showed us a variety of emotions, actions, and elements that relate and link with violence. One of the methodological tools to recognize and establish the link between the knowledge of a concept between discourse and practice is through graphic representations, that is, drawings. Although the drawing gives us a personal interpretation of the reality of each artist, the repetition of elements and the representation of similar situations allowed us to identify the degrees of incidence of the different types of violence and the areas in which it manifests itself.

Keywords: college students, Mexico, social representations, violence

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Authors: Unity Nkateng

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New forms of academic writing such as apprenticeship genres are developing in the field of applied linguistics. However, these perspectives have not adequately addressed the issue of social work students in Botswana. The paper addresses the issue of academic writing with special attention to the types of documents written by University of Botswana (UB) social work students on their fieldwork placement. The research method for this study combines two major research tools in the qualitative inquiry which are text analysis and interviews in order to investigate the context in which the texts are produced. 12 students were consulted and gave their consent for the study. 26 case reports were collected from the Department of Social work at the University of Botswana. The findings show that the case reports students write during their fieldwork placements have 6 moves, which focus on the clients’ story and describe what the students have done and achieved. The significance is that the discrepancy between professional writing and students writing raise questions about the extent to which students are being prepared for professional writing. Students have indicated that their academic writing varies according to the preferences of individual lecturers rather than the requirement of the work situation.

Keywords: apprenticeship genres, client's voice, material processes, relational possesive processes

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Daniel James Pitchforth, Timothy James Rogers, Ulf Tyge Tygesen, Elizabeth Jane Cross

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Wave loading is a primary cause of fatigue within offshore structures and its quantification presents a challenging and important subtask within the SHM framework. The accurate representation of physics in such environments is difficult, however, driving the development of data-driven techniques in recent years. Within many industrial applications, empirical laws remain the preferred method of wave loading prediction due to their low computational cost and ease of implementation. This paper aims to develop an approach that combines data-driven Gaussian process models with physical empirical solutions for wave loading, including Morison’s Equation. The aim here is to incorporate physics directly into the covariance function (kernel) of the Gaussian process, enforcing derived behaviors whilst still allowing enough flexibility to account for phenomena such as vortex shedding, which may not be represented within the empirical laws. The combined approach has a number of advantages, including improved performance over either component used independently and interpretable hyperparameters.

Keywords: offshore structures, Gaussian processes, Physics informed machine learning, Kernel design

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Rubab Z. Kahlon, Ibtisam Butt, Isma Younis, Aamer G. Mufti

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Worldwide lung cancer 1.61 million cases were seen in both genders. Lung carcinoma is the major cause of both morbidity and mortality in the world. Purpose of the present study was to describe the spatio- temporal trends of lung cancer in both genders. A retrospective study was conducted. Total 1498 patients of lung carcinoma were examined. Only lung cancer patients from all over the Punjab were included in the present study. MS Excel 2010 was used for data tabulation and calculation while the Arc GIS version 9.3 was used for geographical representation of the data. 1498 cases of Lung cancer were found from 2008-2012. The number of male patients was 1236 and female was 262. Majority of the patients were from Lahore districts with 807 patients. Lung cancer was more prevalent in male as compared to female in our region. Increase in the prevalence of lung cancer was prominently seen in the most populated and industrial areas of the Punjab province. Time trend of five years showed fluctuation in the lung cancer incidence during the study period.

Keywords: districts, gender, lung cancer trends, Punjab province of Pakistan

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Authors: Carlos Marden Cabral Coutinho, Jose Luis Bolzan de Morais

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The article proposed intends to analyze the possibility (and conditions) of a media regulation law in a democratic rule of law in the twenty-first century. To do so, will be presented initially the idea of the public sphere (by Jürgen Habermas), showing how it is presented as an interface between the citizen and the state (or the private and public) and how important is it in a deliberative democracy. Based on this paradigm, the traditional perception of the role of public information (such as system functional element) and on the possibility of media regulation will be exposed, due to the public nature of their activity. A critical argument will then be displayed from two different perspectives: a) the formal function of the current media information, considering that the digital age has fragmented the information access; b) the concept of a constructive democracy, which reduces the need for representation, changing the strategic importance of the public sphere. The question to be addressed (based on the comparative law) is if the regulation is justified in a polycentric democracy, especially when it operates under the digital age (with immediate and virtual communication). The proposal is to be presented in the sense that even in a twenty-first century the media in a democratic rule of law still has an extremely important role and may be subject to regulation, but this should be on terms very different (and narrower) from those usually defended.

Keywords: constructive democracy, media, digital age, public sphere

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Authors: Debananda Mohapatra, Subramanya Badrayyana, Smrutiranjan Parida

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Carbon nano-onions (CNOs) are the spherical graphitic nanostructures composed of concentric shells of graphitic carbon can be hypothesized as the intermediate state between fullerenes and graphite. These are very important members in fullerene family also known as the multi-shelled fullerenes can be envisioned as promising supercapacitor electrode with high energy & power density as they provide easy access to ions at electrode-electrolyte interface due to their curvature. There is still very sparse report concerning on CNOs as electrode despite having an excellent electrodechemical performance record due to their unavailability and lack of convenient methods for their high yield preparation and purification. Keeping all these current pressing issues in mind, we present a facile scalable and straightforward flame synthesis method of pure and highly dispersible CNOs without contaminated by any other forms of carbon; hence, a post processing purification procedure is not necessary. To the best of our knowledge, this is the very first time; we developed an extremely simple, light weight, novel inexpensive, flexible free standing pristine CNOs electrode without using any binder element. Locally available daily used cotton wipe has been used for fabrication of such an ideal electrode by ‘dipping and drying’ process providing outstanding stretchability and mechanical flexibility with strong adhesion between CNOs and porous wipe. The specific capacitance 102 F/g, energy density 3.5 Wh/kg and power density 1224 W/kg at 20 mV/s scan rate are the highest values that ever recorded and reported so far in symmetrical two electrode cell configuration with 1M Na2SO4 electrolyte; indicating a very good synthesis conditions employed with optimum pore size in agreement with electrolyte ion size. This free standing CNOs electrode also showed an excellent cyclic performance and stability retaining 95% original capacity after 5000 charge –discharge cycles. Furthermore, this unique method not only affords binder free - freestanding electrode but also provide a general way of fabricating such multifunctional promising CNOs based nanocomposites for their potential device applications in flexible solar cells and lithium-ion batteries.

Keywords: binder-free, flame synthesis, flexible, carbon nano onion

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Authors: Alison Wilde, Stephen Millett

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The cultural value of disabled people has largely been overlooked within forms of media and cultural analysis until the 1980s, when disabled people and disability studies highlighted the cultural misrecognition of disabled people and called for improved forms of cultural recognition and representation. Despite an increase in cultural analysis of representations of disabled people, much has been assumed about how images are read, and little work has been done on the value attributed to disabled people by media audiences and the viewing interests and encounters of film audiences. In particular, there has been little work on film reception, or on the way that young people interpret images of disability. We set out to understand some of the ways that young people read disability imagery, by showing small groups of young people different types of film featuring impairments, chosen from three different eras in film. These were Freaks, Rear Window (remake), and Finding Nemo. The discussions after these films allowed them to explore their own experiences of disability alongside the evolution of cultural representations; in so doing they discussed significant themes of cultural value and reflected on their own identities, e.g. in/dependency, autonomy, and competency and the ways these intersected with self-identity, and attitudes to disabled people.

Keywords: film, audience, identity, disability

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Authors: Prathmesh Vikas Patil, Yashaswini Lomte Patil

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Laminated composite materials have considerable attention in various engineering applications due to their exceptional strength-to-weight ratio and mechanical properties. The analysis of laminated composite plates in three-dimensional (3D) elasticity is a complex problem, as it requires accounting for the orthotropic anisotropic nature of the material and the interactions between multiple layers. Conventional approaches, such as the classical plate theory, provide simplified solutions but are limited in performing exact analysis of the plate. To address such a challenge, the state space method emerges as a powerful numerical technique for modeling the behavior of laminated composites in 3D. The state-space method involves transforming the governing equations of elasticity into a state-space representation, enabling the analysis of complex structural systems in a systematic manner. Here, an effort is made to perform a 3D elasticity analysis of plates with cross-ply and angle-ply laminates using the state space approach. The state space approach is used in this study as it is a mixed formulation technique that gives the displacements and stresses simultaneously with the same level of accuracy.

Keywords: cross ply laminates, angle ply laminates, state space method, three-dimensional elasticity analysis

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Authors: Marta Bas-Szymaszek

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This research examines the intricate relationship between language practices and beliefs within international environmental non-governmental organizations (ENGOs), with a particular focus on the Climate Action Network Europe (CAN Europe). While acknowledging that ENGOs often employ multilingual staff, this study aims to analyze the dual role of English within this sector. While English facilitates practical communication among individuals from diverse backgrounds, it also perpetuates inequalities and marginalization within CAN Europe. Instances of linguistic dominance impede participation and representation, reinforcing language hierarchies. Furthermore, the symbolic power of English risks overshadowing the multilingual skills of NGO employees. Through fourteen in-depth interviews, focus group discussions, and observations, this research uncovers the lived experiences of individuals navigating Europe’s largest environmental NGO network. By analyzing CAN Europe’s implicit language policy and the hegemony of English, this study illuminates the challenges within multilingual settings. The organization advocates for the implementation of more inclusive language policies and practices, with the objective of recognizing and embracing linguistic diversity within international environmental NGOs.

Keywords: language policy, English, NGOs, linguistic inclusion, multilingualism

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Heba M. Wagih, Hoda M. O. Mokhtar

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Social Network has recently played a significant role in both scientific and social communities. The growing adoption of social network applications has been a relevant source of information nowadays. Due to its popularity, several research trends are emerged to service the huge volume of users including, Location-Based Social Networks (LBSN), Recommendation Systems, Sentiment Analysis Applications, and many others. LBSNs applications are among the highly demanded applications that do not focus only on analyzing the spatiotemporal positions in a given raw trajectory but also on understanding the semantics behind the dynamics of the moving object. LBSNs are possible means of predicting human mobility based on users social ties as well as their spatial preferences. LBSNs rely on the efficient representation of users’ trajectories. Hence, traditional raw trajectory information is no longer convenient. In our research, we focus on studying human behavior trajectory which is the major pillar in location recommendation systems. In this paper, we propose an ontology design patterns with their underlying description logics to efficiently annotate human behavior trajectories.

Keywords: human behavior trajectory, location-based social network, ontology, social network

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Ihsan Burak Cam, Ferhan Balci-Torun, Ayhan Topuz, Esin Ari, Ismail Gokhan Deniz, Ilker Genc

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The seeds of Vaccaria hispanica have been used in food and pharmaceutical industry. It is an important product due to its superior starch granules, triterpenic saponins, and cyclopeptides suitable for drug delivery. V. hispanica naturally grows in different climatic regions and has genotypes that differ in terms of seed content and composition. Sixty-six V. hispanica seed specimens were collected based on the representation of the distribution in all regions of Turkey and the determination of possible genotypic differences between regions. The seeds, collected from each of the 66 locations, were grown in greenhouse conditions in Akdeniz University, Antalya. Saponin and cyclopeptide contents of the V. hispanica seeds were determined after harvest. Accelerated solvent extraction (ASE) was applied for the extraction of saponins and cyclopeptides. Cyclopeptide (segetalin A) and saponin content of V. hispanica seeds were found in the range of 0.165-0.654 g/100 g and 0.15-1.14 g/100 g, respectively. The results were found to be promising for the seeds from Turkey in terms of saponin content and quality. Acknowledgment: This study was supported by the Scientific and Research Council of Turkey (TUBITAK) (project no 112 O 136).

Keywords: Vaccaria hispanica, saponin, cyclopeptid, cow cockle seeds

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Authors: Diana Codat

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Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

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Authors: Jonix Owino, Heather Fuller

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Refugees flee from their home countries due to civil unrest, war, persecution and migrate to Western countries such as the United States in search of a safe haven. Transitioning into a new society and culture can be challenging, thereby affecting refugee’s quality of life and well-being in the host communities. Moreover, as individuals age, they experience physical, cognitive and socioemotional changes that may impact their quality of life. However, little is known about the predictors of quality of life among aging refugees. It is not clear how quality of life varies by age, that is, between midlife refugees in comparison to their older counterparts. In addition to age, other sociodemographic factors such as gender, socioeconomic status, or country of origin are likely to have differential associations to quality of life, yet research on such variations among older refugees is sparse. Thus the present study seeks to explore factors associated with quality of life by asking the following research questions: 1) Do sociodemographic factors (such as age and gender) predict quality of life among older refugees, 2) Is there an association between social integration and quality of life, and 3) Is there an association between migratory related experiences (such as post migratory adjustments) and quality of life. The present study recruited 90 refugees (primarily originating from Bhutan, Somalia, Burundi, and Sudan) aged 50 or older living in the US. The participants completed a structured questionnaire which assessed factors such as participant’s sociodemographic attributes (e.g., age, gender, length of residence in the US, country of origin, employment, level of education, and marital status), and validated measures of social integration, post-migration living difficulties, and quality of life. Preliminary results suggest sociodemographic variability in quality of life among these refugees. Further analyses will be conducted using hierarchical regression analyses to address the following hypotheses: first, it is hypothesized that quality of life will vary by age and gender such that younger refugees and men will report higher quality of life. Second, it is expected that refugees with greater levels of social integration will also report better quality of life. Finally, post-migration factors such as language barriers and family stress are hypothesized to predict poorer quality of life. Further results will be analyzed, including potential moderating effects of age and gender, and resulting findings will be interpreted and discussed. The findings from this study have potential implications for communities on how they can better support older refugees as well as develop social programs that can effectively cater to their well-being. Conclusions will be drawn and discussed in light of policies related to both aging and refugee migration within the context of the US.

Keywords: aging out of place, migration, older refugees, quality of life, social integration

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Authors: Manuel Iretzberger

Abstract:

This paper aims to uncover the ideological aspects in the political thought of Carl Schmitt, who is enjoying an ever-increasing popularity in various academic fields, following in the wake of rising interest in questions of sovereignty and legitimacy. Given Schmitt’s biography, i.e. his role as the ‘Crown Jurist of the Third Reich’ (Gurian), an extraordinarily thorough examination is necessary; however, instead of merely ‘deconstructing’ his works, certain ontological truths he might have attained, shall be taken seriously. To this end, his notions of politics and the state of exception are scrutinized, which are indeed considered intriguing, yet prove to be enigmatic and impalpable at the core when read closely. In order to explain this conjuncture, both Schmitt’s philosophy of history and his ‘secret discussion’ (Agamben) with Walter Benjamin are depicted. As it turns out – it is argued – his concept of the Political has to be conceived of as embedded in a much broader context: In a post-transcendental, immanent age, he regards traditional modes of representation as no longer feasible and clings to authoritarianism as a surrogate – his Catholicism plays a decisive role here, forcing him to inject normatively biased assumptions into his political writings. Seeing Schmitt perform ‘rearguard action’ not only serves to disarm his work of most of its menacing aura, it also allows drawing conclusions about ways of legitimatizing democratic rule in modern times, as the paper tries to outline in its last section.

Keywords: Benjamin, history, immanence, Schmitt, sovereignty

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Authors: Nader Ghareeb, Rüdiger Schmidt

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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.

Keywords: damping coefficients, finite element analysis, super-element, state-space model

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Authors: Cosmin-Gabriel Porumb-Ghiurco, Dumitrana Fiț-Iordache, Szőke Árpád

Abstract:

The literature incorporating geographical or tourist-geographical themes and explicit references to the Carpathian area is extremely abundant. Through this paper, we attempt to “undermine” the traditional, tourist-geographical approaches of the Carpathian Arch by targeting an aspect often regarded as marginal but which, if examined, even only empirically, takes the form of a vast problem with multidisciplinary vocation. Therefore, we propose a more extravagant yet pro-touristic approach to the Romanian Carpathian geo-space. Consequently, the explicit goal of this approach consists precisely in broadening the multidisciplinary, essentially geographic scope of the research, the vision and mental representation of the Carpathian area by advancing a lever that would symbolize a different kind of unification between geography and tourism on a more intimate, subtle, mythological and archetypal level. The spiritual and mercantile dimensions of the tourism field in general and of the local Carpathian tourism can meld harmoniously together in order to create a common territorial reality of referral and favorable perspectives for the consolidation of their symbiotic relationship.

Keywords: tourist image, mythical geography, collective imaginary, spiritual patrimony, Carpathians

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

Procedia PDF Downloads 130