Search results for: data representation

Authors: Fatma Abdedayem

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We propose an extension to the famous method called Bag of words (BOW) which proved a successful role in the field of image categorization. Practically, this method based on representing image with visual words. In this work, firstly, we extract features from images using Spatial Pyramid Representation (SPR) and two dissimilar color descriptors which are opponent-SIFT and transformed-color-SIFT. Secondly, we fuse color local features by joining the two histograms coming from these descriptors. Thirdly, after collecting of all features, we generate multi-dictionaries coming from n random feature subsets that obtained by dividing all features into n random groups. Then, by using these dictionaries separately each image can be represented by n histograms which are lately concatenated horizontally and form the final histogram, that allows to combine Multiple Dictionaries (MDBoW). In the final step, in order to classify image we have applied Support Vector Machine (SVM) on the generated histograms. Experimentally, we have used two dissimilar image datasets in order to test our proposition: Caltech 256 and PASCAL VOC 2007.

Keywords: bag of words (BOW), color descriptors, multi-dictionaries, MDBoW

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Authors: Melissa Valle

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This paper draws upon the studies of visual culture and intersectionality to illuminate how visuality can naturalize social hierarchies. Through the use of iconography, it decodes the denotative, connotative and ideological meanings of symbols of ritualistic events in the context of the Colombian Atlantic Coast. An examination of such exceptional moments, i.e. of the spectacle, brings into focus how such performances are imbued with meaning by both the on-looker and the performer. Through an analysis of preexisting visuals (e.g., advertisements, social media) and visual materials produced by the researcher for the purpose of photo-elicitation interviews, this paper provides a contextual analysis of the ways in which three representations, popular during Colombian Atlantic coastal festivals (Negrita Puloy, Las Palenqueras, and El Son de Negro), have been historically, culturally and politically constituted. This work reveals that the visualizations are born out of and reproduce typifications systems heavily based upon race, gender, class, and ethnicity. Understanding the ways these categories are mutually constituted through the cultural practice of visual representation is essential to a more comprehensive understanding of the role such representation plays in the reproduction of social difference.

Keywords: Colombia, festivals, intersectionality, visual culture

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

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High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: change detection, multiindex scene representation, spectral index, QuickBird, WorldView

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

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Reverse Logistics (RL) Process is considered as complex and dynamic network that involves many stakeholders such as: suppliers, manufactures, warehouse, retails, and costumers, this complexity is inherent in such process due to lack of perfect knowledge or conflicting information. Ontologies, on the other hand, can be considered as an approach to overcome the problem of sharing knowledge and communication among the various reverse logistics partners. In this paper, we propose a semantic representation based on hybrid architecture for building the Ontologies in an ascendant way, this method facilitates the semantic reconciliation between the heterogeneous information systems (ICT) that support reverse logistics Processes and product data.

Keywords: Reverse Logistics, information management, heterogeneity, ontologies, semantic web

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Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

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To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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Authors: Mohammed Muzafar, Darshan Ruikar

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BIM, an acronym for Building Information Modelling relates to the practice of creating a computer generated model which is capable of displaying the planning, design, construction and operation of a structure. The resulting simulation is a data-rich, object-oriented, intelligent and parametric digital representation of the facility, from which views and data, appropriate to various users needs can be extracted and analysed to generate information that can be used to make decisions and to improve the process of delivering the facility. BIM also refers to a shift in culture that will influence the way the built environment and infrastructure operates and how it is delivered. One of the main issues of concern in the construction industry at present in the UK is its record on Health & Safety (H&S). It is, therefore, important that new technologies such as BIM are developed to help improve the quality of health and safety. Historically the H&S record of the construction industry in the UK is relatively poor as compared to the manufacturing industries. BIM and the digital environment it operates within now allow us to use design and construction data in a more intelligent way. It allows data generated by the design process to be re-purposed and contribute to improving efficiencies in other areas of a project. This evolutionary step in design is not only creating exciting opportunities for the designers themselves but it is also creating opportunity for every stakeholder in any given project. From designers, engineers, contractors through to H&S managers, BIM is accelerating a cultural change. The paper introduces the concept behind a research project that mitigates the H&S risks associated with the construction, operation and maintenance of assets through the adoption of BIM.

Keywords: building information modeling, BIM levels, health, safety, integration

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Authors: Wegig Muwonugroho

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Subjectivity in advertisement is a ‘power’ possessed by advertisements to construct trend, concept, truth, and ideology through subconscious mind. Advertisements, in performing their functions as message conveyors, use such visual representation to inspire what’s ideal to the people. Ambient media is advertising medium making the best use of the environment where the advertisement is located. Miracle Aesthetic Clinic (Miracle) popularizes the visual representation of its ambient media advertisement through the omission of face-image of both female mannequins that function as its ambient media models. Usually, the face of a model in advertisement is an image commodity having selling values; however, the faces of ambient media models in Miracle advertisement campaign are suppressed over the table and wall. This face concealing aspect creates not only a paradox of subjectivity but also plurality of meaning. This research applies critical discourse analysis method to analyze subjectivity in obtaining the insight of ambient media’s meaning. First, in the stage of textual analysis, the embedding attributes upon female mannequins imply that the models are denoted as the representation of modern women, which are identical with the identities of their social milieus. The communication signs aimed to be constructed are the women who lose their subjectivities and ‘feel embarrassed’ to flaunt their faces to the public because of pimples on their faces. Second, in the stage of analysis of discourse practice, it points out that ambient media as communication media has been comprehensively responded by the targeted audiences. Ambient media has a role as an actor because of its eyes-catching setting, and taking space over the area where the public are wandering around. Indeed, when the public realize that the ambient media models are motionless -unlike human- stronger relation then appears, marked by several responses from targeted audiences. Third, in the stage of analysis of social practice, soap operas and celebrity gossip shows on the television become a dominant discourse influencing advertisement meaning. The subjectivity of Miracle Advertisement corners women by the absence of women participation in public space, the representation of women in isolation, and the portrayal of women as an anxious person in the social rank when their faces suffered from pimples. The Ambient media as the advertisement campaign of Miracle is quite success in constructing a new trend discourse of face beauty that is not limited on benchmarks of common beauty virtues, but the idea of beauty can be presented by ‘when woman doesn’t look good’ visualization.

Keywords: ambient media, advertisement, subjectivity, power

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Authors: Nadezhda Kvatashidze

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The conceptual framework of International Financial Reporting Standards determines the basic principles of accounting. The said principles have multiple applications, with professional judgments being one of those. Recognition and assessment of the information contained in financial reporting, especially so the somewhat uncertain events and transactions and/or the ones regarding which there is no standard or interpretation are based on professional judgments. Professional judgments aim at the formulation of expert assumptions regarding the specifics of the circumstances and events to be entered into the report based on the conceptual framework terms and principles. Experts have to make a choice in favor of one of the aforesaid and simulate the situations applying multi-variant accounting estimates and judgment. In making the choice, one should consider all the factors, which may help represent the information in the best way possible. Professional judgment determines the relevance and faithful representation of the presented information, which makes it more useful for the existing and potential investors. In order to assess the prospected net cash flows, the information must be predictable and reliable. The publication contains critical analysis of the aforementioned problems. The fact that the International Financial Reporting Standards are developed continuously makes the issue all the more important and that is another point discussed in the study.

Keywords: conceptual framework, faithful representation, professional judgement, relevance

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Pauline Blanchet

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In a world where images are a prominent part of our daily lives and a way of absorbing information, the analysis of the representation of migration narratives is vital. This thesis raises questions concerning the power of illustrations, drawings and visual culture in order to represent the migration narratives in the age of Instagram. The rise of graphic novels and comics has come about in the last fifteen years, specifically regarding contemporary authors engaging with complex social issues such as migration and refugeehood. Due to this, refugee subjects are often in these narratives, whether they are autobiographical stories or whether the subject is included in the creative process. Growth in discourse around migration has been present in other art forms; in 2018, there has been dedicated exhibitions around migration such as Tania Bruguera at the TATE (2018-2019), ‘Journeys Drawn’ at the House of Illustration (2018-2019) and dedicated film festivals (2018; the Migration Film Festival), which have shown the recent considerations of using the arts as a medium of expression regarding themes of refugeehood and migration. Graphic visuals are fast becoming a key instrument when representing migration, and the central thesis of this paper is to show the strength and limitations of this form as well the methodology used by the actors in the production process. Recent works which have been released in the last ten years have not being analysed in the same context as previous graphic novels such as Palestine and Persepolis. While a lot of research has been done on the mass media portrayals of refugees in photography and journalism, there is a lack of literature on the representation with illustrations. There is little research about the accessibility of graphic novels such as where they can be found and what the intentions are when writing the novels. It is interesting to see why these authors, NGOs, and curators have decided to highlight these migrant narratives in a time when the mainstream media has done extensive coverage on the ‘refugee crisis’. Using primary data by doing one on one interviews with artists, curators, and NGOs, this paper investigates the efficiency of graphic novels for depicting refugee stories as a viable alternative to other mass medium forms. The paper has been divided into two distinct sections. The first part is concerned with the form of the comic itself and how it either limits or strengthens the representation of migrant narratives. This will involve analysing the layered and complex forms that comics allow such as multimedia pieces, use of photography and forms of symbolism. It will also show how the illustration allows for anonymity of refugees, the empathetic aspect of the form and how the history of the graphic novel form has allowed space for positive representations of women in the last decade. The second section will analyse the creative and methodological process which takes place by the actors and their involvement with the production of the works.

Keywords: graphic novel, refugee, communication, media, migration

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Noury Bakrim

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When dealing with motivation/arbitrariness, forming form (Forma Formans) and morphodynamics are to be grasped as relevant implications of enunciation/enactment, schematization within the specificity of language as sound/meaning articulation. Thus, the fact that a language is a form does not contradict stasis/dynamic enunciation (reflexivity vs double articulation). Moreover, some languages exemplify the role of the forming form, uttering, and schematization (roots in Semitic languages, the Chinese case). Beyond the evolutionary biosemiotic process (form/substance bifurcation, the split between realization/representation), non-isomorphism/asymmetry between linguistic form/norm and linguistic realization (phonetics for instance) opens up a new horizon problematizing the role of Brain – sensorimotor contribution in the continuous forming form. Therefore, we hypothesize biotization as both process/trace co-constructing motivation/forming form. Henceforth, referring to our findings concerning distribution and motivation patterns within Berber written texts (pulse based obstruents and nasal-lateral levels in poetry) and oral storytelling (consonant intensity clustering in quantitative and semantic/prosodic motivation), we understand consonant clustering, motivation and schematization as a complex phenomenon partaking in patterns of oral/written iconic prosody and reflexive metalinguistic representation opening the stable form. We focus our inquiry on both Amazigh and English clusters (/spl/, /spr/) and iconic consonant iteration in [gnunnuy] (to roll/tumble), [smummuy] (to moan sadly or crankily). For instance, the syllabic structures of /splaeʃ/ and /splaet/ imply an anamorphic representation of the state of the world: splash, impact on aquatic surfaces/splat impact on the ground. The pair has stridency and distribution as distinctive features which specify its phonetic realization (and a part of its meaning) /ʃ/ is [+ strident] and /t/ is [+ distributed] on the vocal tract. Schematization is then a process relating both physiology/code as an arthron vocal/bodily, vocal/practical shaping of the motor-articulatory system, leading to syntactic/semantic thematization (agent/patient roles in /spl/, /sm/ and other clusters or the tense uvular /qq/ at the initial position in Berber). Furthermore, the productivity of serial syllable sequencing in Berber points out different expressivity forms. We postulate two Components of motivated formalization: i) the process of memory paradigmatization relating to sequence modeling under sensorimotor/verbal specific categories (production/perception), ii) the process of phonotactic selection - prosodic unconscious/subconscious distribution by virtue of iconicity. Basing on multiple tests including a questionnaire, phonotactic/visual recognition and oral/written reproduction, we aim at patterning/conceptualizing consonant schematization and motivation among EFL and Amazigh (Berber) learners and speakers integrating biolinguistic hypotheses.

Keywords: consonant motivation and prosody, language and order of life, anamorphic representation, represented representation, biotization, sensori-motor and brain representation, form, formalization and schematization

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Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

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Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: digital twin, distributed energy resources, remote terminal units, supervisory control and data acquisition system, smart recursive load flow

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Authors: Tamas Madl

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Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

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Authors: Laila Vivas

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Fossil Health is proposed as a value-concept to describe the hegemonic health paradigms that underpin health enactment. Such representation is justified by Foucaldian and related ideas on biopower and biosocialities, calling for the politicization of health and signalling the importance of narratives. This approach, hence, enables contemplating health paradigms as reflexive or co-constitutive of health itself or, in other words, conceiving health as a verb. Fossil health is a symbolic representation, influenced by Andreas Malm’s concept of fossil capitalism, that integrates environment and health as non-dichotomic areas. Fossil Health sustains that current notions of human and non-human health revolve around fossil fuel dependencies. Moreover, addressing disequilibria from established health ideals involves fossil-fixes. Fossil Health, therefore, represents causes and consequences of a health conception that has the agency to contribute to the functioning of a particular structural eco-social model. Moreover, within current capitalist relations, Fossil Health expands its meaning to cover not only fossil implications but also other dominant paradigms of the capitalist system that are (re)produced through health paradigms, such as the burgeoning of technoscience and biomedicalization, privatization of health, expertization of health, or the imposing of standards of uniformity. Overall, Fossil Health is a comprehensive approach to environment and health, where understanding hegemonic health paradigms means understanding our (human-non-human) nature paradigms and the structuring effect these narratives convey.

Keywords: fossil health, environment, paradigm, capitalism

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Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

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This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

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Authors: Ryo Sato

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The United States and many other countries witness alarmingly low voting rates among youths, skewing democratic representation. Many scholars and pundits have ascribed to this trend young voters' laziness, indifference, and self-centeredness and placed blame on them. However, a growing body of research is focusing on structural barriers to voting, which are defined as built-in obstacles lying in electoral laws and procedures. Drawing on national survey data from 891 young adults in 2020 and extant literature on structural barriers to voting, the project aims to develop a framework for analyzing systematic obstacles to voting experienced by young people and offer tangible policy recommendations. The preliminary findings presented at this conference include an intersectional analysis of the survey data, focusing on how different social categories — race, gender, socioeconomic status, immigration status, and others — in combination create unique voting experiences and barriers. This project offers a critical framework to combat the individualized understanding of low voting rates among youths and inform pathways to functional democracy.

Keywords: youth voting behavior, structural barriers, intersectionality, democratic participation, S

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Authors: Eman Alatawi

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The world is currently experiencing an upsurge in the number of international migrants, which has reached 281 million worldwide; in particular, both the UK and Saudi Arabia have recently been faced with an unprecedented number of immigrants. As a result, the media in these two countries is constantly posting news about the issue, and newspapers, in particular, play a vital role in shaping the public’s view of immigration issues. Because the media is an influential tool in society, it has the ability to construct a specific image of migrants and influence public opinion concerning immigrant groups. However, most of the existing studies have addressed the plight of migrants in the UK, Europe, and the US, and few have considered the Middle East; specifically, there is a pressing need for studies that focus on the press in Saudi Arabia, which is one of the main countries that is experiencing immigration at a tremendous rate. This paper employs critical discourse analysis (CDA) to examine the depiction of migrants in the British and Saudi Arabian media in order to explore the involvement of three linguistic features in the media’s representation of migrant-related topics. These linguistic features are the names, metaphors, and collocations that the press in the UK and in Saudi Arabia uses to describe migrants; the impact of these depictions is also considered. This comparative study could create a better understanding of how the Saudi Arabian press presents the topic of migrants and immigration, which will assist in extending the understanding of migration discourses beyond an Anglo-centric viewpoint. The main finding of this study was that both British and Saudi Arabian newspapers tended to represent migrants’ issues by painting migrants in a negative light through the use of negative references or names, metaphors, and collocations; furthermore, the media’s negative stereotyping of migrants was found to be consistent, which could have an influence on the public’s opinion of these minority groups. Such observations show that the issue is not as simple as individuals, press systems, or political affiliations.

Keywords: representation, migrants, the UK press, Saudi Arabia press, cross-linguistic, discourse analysis

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Authors: Noraini Idris, Imelda Albert Gisip

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Women’s full and effective participation and equal opportunities for leadership at all level of decisionmaking process are essential in order to achieve sustainable development goals by 2030. This paper discusses how women in Malaysia generally still find themselves under-represented in political institutions. Leaders from various political parties in Malaysia were all on the same page in their commitment to achieve the target of fielding 30 percent women candidates in election which in turn will increase female representation in the country’s legislative bodies. However, despite their pledge on making equal opportunities to women in decision making process, the 30 percent target has yet to be achieved be it in the federal election nor respective state elections in thirteen states conducted throughout the country until now. Sabah’s political landscape with regards to women leaders’ representation in politic mirrors that at the federal level. During the 15th Parliamentary General Election which was conducted in November 2022, despite Sabah Women’s significant numbers as voters in the electoral rolls which recorded 49.36 percent (833,847 women voters); only 17.6 percent or 21 women candidates out of 119 candidates in Sabah were fielded by the political parties contesting in the election. Sabah has 25 parliamentary seats. Out of 31 women members of Parliament who won the 15th General Election, only 3 women members of Parliament are from Sabah. Even in the 2020 Sabah State Election only nine (9) percent of the candidates or 43 women out of the 447 total candidates were fielded. The current Sabah State legislative Assembly saw only eight (8) percent or 7 women Assemblymen out of 79 Assemblymen in the legislative body. The number of female leaders in the legislative body in Malaysia has never exceeded 15 percent with the highest being 14.86 percent in the Lower House (Dewan Rakyat), 14.42 percent in the Upper House (Dewan Senat) and merely 8 percent in the Sabah State legislative Assembly. Thus, this paper will further discuss the strategies to tackle women leaders underrepresentation in politics particularly in Sabah, Malaysia and to provide suggestions to overcome this issue.

Keywords: women, leaders, politic, Sabah, Malaysia

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Authors: Xhaklina Cani, Ilirjan Malollari, Ismet Beqiraj, Lorina Lici

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Oil characterization is an essential step in the design, simulation, and optimization of refining facilities. To achieve optimal crude selection and processing decisions, a refiner must have exact information refer to crude oil quality. This includes crude oil TBP-curve as the main data for correct operation of refinery crude oil atmospheric distillation plants. Crude oil is typically characterized based on a distillation assay. This procedure is reasonably well-defined and is based on the representation of the mixture of actual components that boil within a boiling point interval by hypothetical components that boil at the average boiling temperature of the interval. The crude oil assay typically includes TBP distillation according to ASTM D-2892, which can characterize this part of oil that boils up to 400 C atmospheric equivalent boiling point. To model the yield curves obtained by physical distillation is necessary to compare the differences between the modelling and the experimental data. Most commercial use a different number of components and pseudo-components to represent crude oil. Laboratory tests include distillations, vapor pressures, flash points, pour points, cetane numbers, octane numbers, densities, and viscosities. The aim of the study is the drawing of true boiling curves for different crude oil resources in Albania and to compare the differences between the modeling and the experimental data for optimal characterization of crude oil.

Keywords: TBP distillation curves, crude oil, optimization, simulation

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Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

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Authors: Benmansour Nassima, Benmansour Souheyla

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The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

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Authors: Jayanti De

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Users of any urban road infrastructure may be classified into various categories. The current paper intends to see whether the opinions on different environmental and transportation criteria vary significantly among different types of road users or not. The paper addresses this issue by using a unique survey data that has been collected from Kolkata, a highly populated city in India. Multiple criteria should be taken into account while planning on infrastructure development programs. Given limited resources, a welfare maximizing government typically resorts to public opinion by designing surveys for prioritization of one project over another. Designing such surveys can be challenging and costly. Deciding upon whom to include in a survey and how to represent each group of consumers/road-users depend crucially on how opinion for different criteria vary across consumer groups. A unique dataset has been collected from various parts of Kolkata to statistically test (using Kolmogorov-Smirnov test) whether assigning of weights to rank the transportation criteria like congestion, air pollution, noise pollution, and morning/evening delay vary significantly across the various groups of users of such infrastructure. The different consumer/user groups in the dataset include pedestrian, private car owner, para-transit (taxi /auto rickshaw) user, public transport (bus) user and freight transporter among others. Very little evidence has been found that ranking of different criteria among these groups vary significantly. This also supports the hypothesis that road- users/consumers form their opinion by using their long-run rather than immediate experience. As a policy prescription, this implies that under-representation or over-representation of a specific consumer group in a survey may not necessarily distort the overall opinion, since opinions across different consumer groups are highly correlated as evident from this particular case study.

Keywords: multi criteria analysis, project-prioritization, road- users, survey designing

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