Search results for: semantic impairments

Authors: Bianca Suárez Puerta

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Multimodal discourse refers to a method of study the media continuum between reality, screens as a device, audience, author, and media as a production from the audience. For this study we used semantic differential, a method proposed in the sixties by Osgood, Suci and Tannenbaum, starts from the assumption that under each particular way of perceiving the world, in each singular idea, there is a common cultural meaning that organizes experiences. In relation to these shared symbolic dimension, this method has had significant results, as it focuses on breaking down the meaning of certain significant acts into series of statements that place the subjects in front of some concepts. In Colombia, in 2016, a tool was designed to measure the meaning of a multimodal production, specially the acts of sense of transmedia productions that managed to receive funds from the Ministry of ICT of Colombia, and also, to analyze predictable patterns that can be found in calls and funds aimed at the production of culture in Colombia, in the context of the peace agreement, as a request for expressions from a hegemonic place, seeking to impose a worldview.

Keywords: semantic differential, semiotics, transmedia, critical analysis of discourse

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Authors: Gabriel Sepulveda Navarro

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Traditional interventions for young offenders are necessary but not sufficient to tackle the multiple causes of juvenile crime. For instance, interventions offered to young offenders often are verbally mediated and dialogue based, requiring important metacognitive abilities as well as abstract thinking, assuming average performance in a wide variety of skills. It seems necessary to assess a broader set of abilities and functions in order to increase the efficiency of interventions while addressing offending. In order to clarify these assumptions, Stroop Test, as well as Rey-Osterrieth Complex Figure Test were applied to juvenile offenders tried and sentenced for violent crimes in Santiago de Chile. A random sample was drawn from La Cisterna Half-Open Program, consisting of 50 young males between 18 and 24 years old, residing in different districts of Santiago de Chile. The analysis of results suggests a disproportionately elevated incidence of impairments in executive functions and visuospatial skills. As an outcome, over 40% of the sample shows a significant low performance in both assessments, exceeding four times the same prevalence rates among young people in the general population. While executive functions entail working memory (being able to keep information and use it in some way), cognitive flexibility (to think about something in more than one way) and inhibitory control (being able to self-control, ignore distractions and delay immediate gratification), visuospatial skills permit to orientate and organize a planned conduct. All of these abilities are fundamental to the skill of avoiding violent behaviour and abiding by social rules. Understanding the relevance of neurodevelopmental impairments in the onset of violent and criminal behaviour, as well as recidivism, eventually may guide the deployment of a more comprehensive assessment and treatment for juvenile offenders.

Keywords: executive functions, half-open program, juvenile offenders, neurodisabilities, visuospatial skills

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Authors: M. Regina Carreira-Lopez

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Lightweight ontologies seek to concrete union relationships between a parent node, and a secondary node, also called "child node". This logic relation (L) can be formally defined as a triple ontological relation (LO) equivalent to LO in ⟨LN, LE, LC⟩, and where LN represents a finite set of nodes (N); LE is a set of entities (E), each of which represents a relationship between nodes to form a rooted tree of ⟨LN, LE⟩; and LC is a finite set of concepts (C), encoded in a formal language (FL). Mondoc enables more refined searches on semantic and classified facets for retrieving specialized knowledge about Atlantic migrations, from the Declaration of Independence of the United States of America (1776) and to the end of the Spanish Civil War (1939). The model looks forward to increasing documentary relevance by applying an inverse frequency of co-ocurrent hypernymy phenomena for a concrete dataset of textual corpora, with RMySQL package. Mondoc profiles archival utilities implementing SQL programming code, and allows data export to XML schemas, for achieving semantic and faceted analysis of speech by analyzing keywords in context (KWIC). The methodology applies random and unrestricted sampling techniques with RMySQL to verify the resonance phenomena of inverse documentary relevance between the number of co-occurrences of the same term (t) in more than two documents of a set of texts (D). Secondly, the research also evidences co-associations between (t) and their corresponding synonyms and antonyms (synsets) are also inverse. The results from grouping facets or polysemic words with synsets in more than two textual corpora within their syntagmatic context (nouns, verbs, adjectives, etc.) state how to proceed with semantic indexing of hypernymy phenomena for subject-heading lists and for authority lists for documentary and archival purposes. Mondoc contributes to the development of web directories and seems to achieve a proper and more selective search of e-documents (classification ontology). It can also foster on-line catalogs production for semantic authorities, or concepts, through XML schemas, because its applications could be used for implementing data models, by a prior adaptation of the based-ontology to structured meta-languages, such as OWL, RDF (descriptive ontology). Mondoc serves to the classification of concepts and applies a semantic indexing approach of facets. It enables information retrieval, as well as quantitative and qualitative data interpretation. The model reproduces a triple tuple ⟨LN, LE, LT, LCF L, BKF⟩ where LN is a set of entities that connect with other nodes to concrete a rooted tree in ⟨LN, LE⟩. LT specifies a set of terms, and LCF acts as a finite set of concepts, encoded in a formal language, L. Mondoc only resolves partial problems of linguistic ambiguity (in case of synonymy and antonymy), but neither the pragmatic dimension of natural language nor the cognitive perspective is addressed. To achieve this goal, forthcoming programming developments should target at oriented meta-languages with structured documents in XML.

Keywords: hypernymy, information retrieval, lightweight ontology, resonance

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Authors: Kirolos Gerges Yakoub Gerges

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Self-sustaining agricultural machines act in stochastic surroundings and therefore, should be capable of perceive the surroundings in real time. This notion can be done using image sensors blended with superior device learning, mainly Deep mastering. Deep convolutional neural networks excel in labeling and perceiving colour pix and since the fee of RGB-cameras is low, the hardware cost of accurate notion relies upon heavily on memory and computation power. This paper investigates the opportunity of designing lightweight convolutional neural networks for semantic segmentation (pixel clever class) with reduced hardware requirements, to allow for embedded usage in self-reliant agricultural machines. The usage of compression techniques, a lightweight convolutional neural community is designed to carry out actual-time semantic segmentation on an embedded platform. The community is skilled on two big datasets, ImageNet and Pascal Context, to apprehend as much as four hundred man or woman instructions. The 400 training are remapped into agricultural superclasses (e.g. human, animal, sky, road, area, shelterbelt and impediment) and the capacity to provide correct actual-time perception of agricultural environment is studied. The network is carried out to the case of self-sufficient grass mowing the usage of the NVIDIA Tegra X1 embedded platform. Feeding case-unique pics to the community consequences in a fully segmented map of the superclasses within the picture. As the network remains being designed and optimized, handiest a qualitative analysis of the technique is entire on the abstract submission deadline. intending this cut-off date, the finalized layout is quantitatively evaluated on 20 annotated grass mowing pictures. Light-weight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show aggressive performance on the subject of accuracy and speed. It’s miles viable to offer value-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigationaxial flux machines, axial flux applications, coreless machines, PM machinesautonomous agricultural machines, deep learning, safety, visual perception

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Authors: Zou Yihui

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The integration of the traditional landscape of the ancient city and the poet's emotions and symbolization into ancient poetry is the unique cultural gene and spiritual core of the historical city, and re-understanding the historical landscape pattern from the poetry is conducive to continuing the historical city context and improving the current situation of the gradual decline of the poetry of the modern historical urban landscape. Starting from Tang poetry uses semantic analysis methods、combined with text mining technology, entry mining, word frequency analysis, and cluster analysis of the landscape information of Tang Chang'an City were carried out, and the method framework for analyzing the urban landscape form based on poetry text was constructed. Nearly 160 poems describing the landscape of Tang Chang'an City were screened, and the poetic landscape characteristics of Tang Chang'an City were sorted out locally in order to combine with modern urban spatial development to continue the urban spatial context.

Keywords: Tang Chang'an City, poetic texts, semantic analysis, historical landscape

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Hamideh Marefat, Eskandar Samadi

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This study examined the effect of semantics on processing ambiguous sentences containing Relative Clauses (RCs) preceded by a complex Determiner Phrase (DP) by Persian-speaking learners of L2 English with different proficiency and Working Memory Capacities (WMCs). The semantic relationship studied was one between the subject of the main clause and one of the DPs in the complex DP to see if, as predicted by Spreading Activation Model, priming one of the DPs through this semantic manipulation affects the L2ers’ preference. The results of a task using Rapid Serial Visual Processing (time-controlled paradigm) showed that manipulation of the relationship between the subject of the main clause and one of the DPs in the complex DP preceding RC has no effect on the choice of the antecedent; rather, the L2ers' processing is guided by the phrase structure information. Moreover, while proficiency did not have any effect on the participants’ preferences, WMC brought about a difference in their preferences, with a DP1 preference by those with a low WMC. This finding supports the chunking hypothesis and the predicate proximity principle, which is the strategy also used by monolingual Persian speakers.

Keywords: semantics, relative clause processing, ambiguity resolution, proficiency, working memory capacity

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: Samanta Kietytė

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The object of this study is the verbal derivatives stemming from the Lithuanian prefix per-. The prefix under examination can be classified as prepositional, having descended from the preposition per, thereby sharing the same prototypical meaning – denoting movement OVER. These frequently co-occur within sentences (1). The aim of this paper is to conduct a semantic analysis of the prefix per- and to propose a possible radial network of its meanings. In essence, the aim is to identify the interrelationships existing between its meanings. 1) Jis peršoko per tvorą/ 3SG.NOM.M jump.PST.3 over fence.ACC.SG. /ʻHe jumped over the fenceʼ. The foundation of this work lies in the methodological and theoretical framework of cognitive linguistics. The prototypical meaning of prefixes consistently embodies spatial dimensions that can be described through image schemas. This entails the identification of the trajectory, the landmark, and the relation between them in the situation described by the prefixed verb. The meanings of linguistic units are not perceived as arbitrary, but rather, they are interconnected through semantic motivation. According to this perspective, a singular meaning within linguistic units is considered as prototypical, while additional meanings are descended (not necessarily directly) from it. For example, one of the per- meanings TRANSFER (2) is derived from the prototypical meaning OVER. 2) Prašau persiųsti vadovo laišką man./ Ask.PRS.1 forward.INF manager.GEN.SG email.ACC.SG 1.SG.DAT/ ʻPlease forward the manager‘s email to meʼ. Certain semantic relations are explained by the conceptual metaphor and metonymy theory. For instances, when prefixed verb has a meaning WIN (3) it is related to the prototypical meaning. In this case, the prefixed verb describes situations of winning in various ways. In the prototypical meaning, the trajector moves higher than the landmark, and winning is metaphorically perceived as being higher. 3) Sūnus peraugo tėvą./ Son.NOM.SG outgrow.PST.3 father.ACC.SG/ ʻThe son has outgrown the fatherʼ. The data utilized for this study was collected from the 2014 grammatically annotated text "Lithuanian Web (LithuanianWaC v2)", consisting of 63,645,700 words. Given that the corpus is grammatically lemmatized, the list of the 793 items was obtained using the wordlist function and specifying that verbs starting with per were searched. The list included not only prefixed verbs but also other verbs whose roots have the same letter sequences as prefixes. Also, words with misspellings, without diacritical marks, and words listed for lemmatization errors were rejected, and a total of 475 derivatives were left for further analysis. The semantic analysis revealed that there are 12 distinct meanings of the prefix per-. The spatial meanings were extracted by determining what a trajector is, what a landmark is, and what the relation between them is. The connection between non-spatial meanings and spatial ones occurs through semantic motivation established by identifying elements that correspond to the trajector and landmark. The analysis reveals that there are no strict boundaries among these meanings, instead showing a continuum that encompasses a central core and a peripheral association with their internal structure, i.e., some derivatives are more prototypical of a particular meaning than others.

Keywords: word-formation, cognitive semantics, metaphor, radial networks, prototype theory, prefix

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Lai Gwen Chan, Yining Ong, Audrey Yoke Poh Wong

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Background. The efficacy of electroconvulsive therapy (ECT) as a form of treatment to a range of mental disorders is well-established. However, ECT is often associated with either temporary or persistent cognitive side-effects, resulting in the failure of wider prescription. Of which, retrograde amnesia is the most commonly reported cognitive side-effect. Most studies found a recalling deficit in autobiographical memories to be short-term, although a few have reported more persistent amnesic effects. Little is known about ECT-related amnesic effects in Asian population. Hence, this study aims to resolve conflicting findings, as well as to better elucidate the effects of ECT on cognitive functioning in a local sample. Method: 12 patients underwent bilateral ECT under the care of Psychological Medicine Department, Tan Tock Seng Hospital, Singapore. Participants’ cognition and level of functioning were assessed at four time-points: before ECT, between the third and fourth induced seizure, at the end of the whole course of ECT, and two months after the index course of ECT. Results: It was found that Global Assessment of Functioning scores increased significantly at the completion of ECT. Case-by-case analyses also revealed an overall improvement in Personal Semantic and Autobiographical memory two months after the index course of ECT. A transient dip in both personal semantic and autobiographical memory scores was observed in one participant between the third and fourth induced seizure, but subsequently resolved and showed better performance than at baseline. Conclusions: The findings of this study suggest that ECT is an effective form of treatment to alleviate the severity of symptoms of the diagnosis. ECT does not affect attention, language, executive functioning, personal semantic and autobiographical memory adversely. The findings suggest that Asian patients may respond to bilateral ECT differently from Western samples.

Keywords: electroconvulsive therapy (ECT), autobiographical memory, cognitive impairment, psychiatric disorder

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Authors: Sameh Baccari, Mahmoud Neji

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In recent years, the rapid developments on mobile devices and wireless technologies enable new dimension capabilities for the learning domain. This dimension facilitates people daily activities and shortens the distances between individuals. When these technologies have been used in learning, a new paradigm has been emerged giving birth to mobile learning. Because of the mobility feature, m-learning courses have to be adapted dynamically to the learner’s context. The main challenge in context-aware mobile learning is to develop an approach building the best learning resources according to dynamic learning situations. In this paper, we propose a context-aware mobile learning system called Collaborative and Context-aware Mobile Learning System (CCMLS). It takes into account the requirements of Mobility, Collaboration and Context-Awareness. This system is based on the semantic modeling of the learning context and the learning content. The adaptation part of this approach is made up of adaptation rules to propose and select relevant resources, learning partners and learning activities based not only on the user’s needs, but also on its current context.

Keywords: mobile learning, mobile technologies, context-awareness, collaboration, semantic web, adaptation engine, adaptation strategy, learning object, learning context

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Authors: Vassilis Argyropoulos, Magda Nikolaraizi, Maria Papazafiri

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This study describes a series of learning workshops, which took place within CUIDAR project. The workshops aimed to empower children to share their experiences and views in relation to natural hazards and disasters. The participants in the workshops were ten primary school students who had severe visual impairments or multiple disabilities and visual impairments (MDVI). The main objectives of the workshops were: a) to promote access of the children through the use of appropriate educational material such as texts in braille, enlarged text, tactile maps and the implementation of differentiated instruction, b) to make children aware regarding their rights to have access to information and to participate in planning and decision-making especially in relation to disaster education programs, and c) to encourage children to have an active role during the workshops through child-led and experiential learning activities. The children expressed their views regarding the meaning of hazards and disasters. Following, they discussed their experiences and emotions regarding natural hazards and disasters, and they chose to place the emphasis on a hazard, which was more pertinent to them, their community and their region, namely fires. Therefore, they recalled fires that have caused major disasters, and they discussed about the impact that these fires had on their community or on their country. Furthermore, they were encouraged to become aware regarding their own role and responsibility to prevent a fire or get prepared and know how to behave if a fire occurs. They realized that prevention and preparation are a matter of personal responsibility. They also felt the responsibility to inform their own families. Finally, they met important people involved in fire protection such as rescuers and firefighters and had the opportunity to carry dialogues. In conclusion, through child led workshops, experiential and accessible activities, the students had the opportunity to share their own experiences, to express their views and their questions, to broaden their knowledge and to realize their personal responsibility in disaster risk reduction, specifically in relation to fires.

Keywords: accessibility, children, disasters, visual impairment

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to collect information in unknown environments to realize simultaneous localization and environment map construction, which has a wide range of applications in autonomous driving, virtual reality and other related fields. At present, the related research achievements about VSLAM can maintain high accuracy in static environment. But in dynamic environment, due to the presence of moving objects in the scene, the movement of these objects will reduce the stability of VSLAM system, resulting in inaccurate localization and mapping, or even failure. In this paper, a robust VSLAM method was proposed to effectively deal with the problem in dynamic environment. We proposed a dynamic region removal scheme based on semantic segmentation neural networks and geometric constraints. Firstly, semantic extraction neural network is used to extract prior active motion region, prior static region and prior passive motion region in the environment. Then, the light weight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static region and dynamic region. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under high dynamic environment.

Keywords: dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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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: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: R. Güçlü, E. Küçüksakarya

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Word association (WA) gives the broadest information on how knowledge is structured in the human mind. Cognitive linguistics, psycholinguistics, and applied linguistics are the disciplines that consider WA tests as substantial in gaining insights into the very nature of the human cognitive system and semantic knowledge. In this study, Berlin and Kay’s basic 11 color terms (1969) are presented as the stimuli words to a total number of 300 Turkish university students. The responses are analyzed according to Fitzpatrick’s model (2007), including four categories, namely meaning-based responses, position-based responses, form-based responses, and erratic responses. In line with the findings, the responses to free association tests are expected to give much information about Turkish university students’ psychological structuring of vocabulary, especially morpho-syntactic and semantic relationships among words. To conclude, theoretical and practical implications are discussed to make an in-depth evaluation of how associations of basic color terms are represented in the mental lexicon of Turkish university students.

Keywords: color term, gender, mental lexicon, word association task

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Authors: Liu Jia’nan

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The default accounts hold the view that there exists a kind of scalar implicature which can be processed without context and own a psychological privilege over other scalar implicatures which depend on context. In contrast, the Relevance Theorist regards context as a must because all the scalar implicatures have to meet the need of relevance in discourse. However, in Katsos, the experimental results showed: Although quantitatively the adults rejected under-informative utterance with lexical scales (context-independent) and the ad hoc scales (context-dependent) at almost the same rate, adults still regarded the violation of utterance with lexical scales much more severe than with ad hoc scales. Neither default account nor Relevance Theory can fully explain this result. Thus, there are two questionable points to this result: (1) Is it possible that the strange discrepancy is due to other factors instead of the generation of scalar implicature? (2) Are the ad hoc scales truly formed under the possible influence from mental context? Do the participants generate scalar implicatures with ad hoc scales instead of just comparing semantic difference among target objects in the under- informative utterance? In my Experiment 1, the question (1) will be answered by repetition of Experiment 1 by Katsos. Test materials will be showed by PowerPoint in the form of pictures, and each procedure will be done under the guidance of a tester in a quiet room. Our Experiment 2 is intended to answer question (2). The test material of picture will be transformed into the literal words in DMDX and the target sentence will be showed word-by-word to participants in the soundproof room in our lab. Reading time of target parts, i.e. words containing scalar implicatures, will be recorded. We presume that in the group with lexical scale, standardized pragmatically mental context would help generate scalar implicature once the scalar word occurs, which will make the participants hope the upcoming words to be informative. Thus if the new input after scalar word is under-informative, more time will be cost for the extra semantic processing. However, in the group with ad hoc scale, scalar implicature may hardly be generated without the support from fixed mental context of scale. Thus, whether the new input is informative or not does not matter at all, and the reading time of target parts will be the same in informative and under-informative utterances. People’s mind may be a dynamic system, in which lots of factors would co-occur. If Katsos’ experimental result is reliable, will it shed light on the interplay of default accounts and context factors in scalar implicature processing? We might be able to assume, based on our experiments, that one single dominant processing paradigm may not be plausible. Furthermore, in the processing of scalar implicature, the semantic interpretation and the pragmatic interpretation may be made in a dynamic interplay in the mind. As to the lexical scale, the pragmatic reading may prevail over the semantic reading because of its greater exposure in daily language use, which may also lead the possible default or standardized paradigm override the role of context. However, those objects in ad hoc scale are not usually treated as scalar membership in mental context, and thus lexical-semantic association of the objects may prevent their pragmatic reading from generating scalar implicature. Only when the sufficient contextual factors are highlighted, can the pragmatic reading get privilege and generate scalar implicature.

Keywords: scalar implicature, ad hoc scale, dynamic interplay, default account, Mandarin Chinese processing

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Authors: Joanna Wielochowska, Aneta Wielochowska

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Whilst the relationship between scientific areas such as cognitive psychology, neurobiology and philosophy of mind has been emphasized in recent decades of scientific research, concepts and discoveries made in both fields overlap and complement each other in their quest for answers to similar questions. The object of the following case study is to describe, analyze and illustrate the nature and characteristics of a certain cognitive experience which appears to display features of synaesthesia, or rather high-level synaesthesia (ideasthesia). The following research has been conducted on the subject of two authors, monozygotic twins (both polysynaesthetes) experiencing involuntary associations of identical nature. Authors made attempts to identify which cognitive and conceptual dependencies may guide this experience. Operating on self-introduced nomenclature, the described phenomenon- multi-dimensional processing of textual and visual information- aims to define a relationship that involuntarily and immediately couples the content introduced by means of text or image a sensation of appearing in a certain place in the mind’s eye. More precisely: (I) defining a concept introduced by means of textual content during activity of reading or writing, or (II) defining a concept introduced by means of visual content during activity of looking at image(s) with simultaneous sensation of being allocated to a given place in the mind’s eye. A place can be then defined as a cognitive representation of a certain concept. During the activity of processing information, a person has an immediate and involuntary feel of appearing in a certain place themselves, just like a character of a story, ‘observing’ a venue or a scenery from one or more perspectives and angles. That forms a unique and unified experience, constituting a background mental landscape of text or image being looked at. We came to a conclusion that semantic allocations to a given place could be divided and classified into the categories and subcategories and are naturally linked with an individual’s semantic knowledge-base. A place can be defined as a representation one’s unique idea of a given concept that has been established in their semantic knowledge base. A multi-level structure of selectivity of places in the mind’s eye, as a reaction to a given information (one stimuli), draws comparisons to structures and patterns found in botany. Double-flowered varieties of flowers and a whorl system (arrangement) which is characteristic to components of some flower species were given as an illustrative example. A composition of petals that fan out from one single point and wrap around a stem inspired an idea that, just like in nature, in philosophy of mind there are patterns driven by the logic specific to a given phenomenon. The study intertwines terms perceived through the philosophical lens, such as definition of meaning, subjectivity of meaning, mental atmosphere of places, and others. Analysis of this rare experience aims to contribute to constantly developing theoretical framework of the philosophy of mind and influence the way human semantic knowledge base and processing given content in terms of distinguishing between information and meaning is researched.

Keywords: information and meaning, information processing, mental atmosphere of places, patterns in nature, philosophy of mind, selectivity, semantic knowledge base, senses, synaesthesia

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from McRae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-worls, resilience to damage

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Authors: Sandra Baez, Mariana Pino, Mildred Berrio, Hernando Santamaria-Garcia, Lucas Sedeno, Adolfo Garcia, Sol Fittipaldi, Agustin Ibanez

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Schadenfreude refers to the perceiver’s experience of pleasure at another’s misfortune. This is a multidetermined emotion which can be evoked by hostile feelings and envy. The experience of Schadenfreude engages mechanisms implicated in diverse social cognitive processes. For instance, Schadenfreude involves heightened reward processing, accompanied by increased striatal engagement and it interacts with mentalizing and perspective-taking abilities. Patients with Huntington's disease (HD) exhibit reductions of Schadenfreude experience, suggesting a role of striatal degeneration in such an impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced Schadenfreude. This study investigated whether gray matter (GM) atrophy in HD patients correlates with ratings of Schadenfreude. First, we compared the performance of 20 HD patients and 23 controls on an experimental task designed to trigger Schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. Results showed that while both groups showed similar ratings of envy, HD patients reported lower Schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalizing network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in Schadenfreude, while offering novel evidence about their neural correlates. In addition, our results open the door to future studies investigating social emotion processing in other clinical populations characterized by striatal or mentalizing network impairments (e.g., Parkinson’s disease, schizophrenia, autism spectrum disorders).

Keywords: envy, Gray matter atrophy, Huntigton's disease, Schadenfreude, social emotions

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Authors: Raquel Rossini, Edelvais Caldeira

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The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: Luísa Pedro, José Pais-Ribeiro, João Páscoa Pinheiro

Abstract:

Multiple Sclerosis (MS) is a chronic disease of the central nervous system that affects more often young adults in the prime of his career and personal development, with no cure and unknown causes. The most common signs and symptoms are fatigue, muscle weakness, changes in sensation, ataxia, changes in balance, gait difficulties, memory difficulties, cognitive impairment and difficulties in problem solving. MS is a relatively common neurological disorder in which various impairments and disabilities impact strongly on function and daily life activities. The aim of this study is to examine the implications of the program of self-regulation in the perception of illness and mental health (psychological well-being domain) in MS patients. MS is a relatively common neurological disorder in which various impairments and disabilities impact strongly on function and daily life activities. The aim of this study is to examine the implications of the program of self-regulation in the perception of illness and mental health (psychological well-being domain) in MS patients. After this, a set of exercises was implemented to be used in daily life activities, according to studies developed with MS patients. We asked the subjects the question “Please classify the severity of your disease?” and used the domain of psychological well-being, the Mental Health Inventory (MHI-38) at the beginning (time A) and end (time B) of the program of self-regulation. We used the Statistical Package for the Social Sciences (SPSS) version 20. A non-parametric statistical hypothesis test (Wilcoxon test) was used for the variable analysis. The intervention followed the recommendations of the Helsinki Declaration. The age range of the subjects was between 20 and 58 years with a mean age of 44 years. 58.3 % were women, 37.5 % were currently married, 67% were retired and the mean level of education was 12.5 years. In the correlation between the severity of the disease perception and psychological well before the self-regulation program, an obtained result (r = 0.26, p <0.05), then the self-regulation program, was (r = 0.37, p <0.01), from a low to moderate correlation. We conclude that the program of self-regulation for physical activity in patients with MS can improve the relationship between the perception of disease severity and psychological well-being.

Keywords: psychological well-being, multiple sclerosis, self-regulation, physical activity

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Authors: Muhammed Muvaffak Alhasan, Ali Alriyami, Ali Almanei

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Despite the extreme importance of etymological studies in documenting the linguistic heritage, and showing its roots and connections in the classical language; However, etymological dictionaries are still rare in the Arab library in general. Etymology is the science of etymology that investigates how vocabulary is reproduced and reproduced, by exploring the origin of words and the phonetic and semantic changes that occurred in them over time, trying to reconfigure an identity card for the word showing its origin and the path it took through time until it reached its current state. This research seeks to make an etymological study on the terminology used in the traditional dagger making in the Sultanate of Oman through the following steps: 1. Collecting the terms relating to traditional dagger making and recording them in order to document and preserve them. 2. Arranging them alphabetically in order to facilitate searching and dealing with them. 3. Setting up a historical identification card for each word by applying an etymological study that shows its source from which they descended its links with standard and the phonological and semantic changes it underwent until it reached its current form.

Keywords: cultural heritage, etymology, Omani dagger, Oman

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Authors: Dean Raiyasmi, Elvi Citraresmana, Sutiono Mahdi

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Language shapes the human mind and its concept toward things. Using image schemas, in nowadays technology, even AI (artificial intelligence) can concept things in response to their creator negativity or positivity. This is reflected inside one of the most selling game around the world in 2012 called Dragon Age Origins. The AI in form of NPC (Non-Playable Character) inside the game reflects on the creator of the game on negativity or positivity toward the lexical concept of mage. Through image schemas, shaping the lexical concept of mage deemed possible and proved the negativity or positivity creator of the game toward mage. This research analyses the cognitive-semantic process of image schema and shaping the concept of ‘mage’ by describing kinds of image schemas exist in the Dragon Age Origin Game. This research is also aimed to analyse kinds of image schemas and describing the image schemas which shaping the concept of ‘mage’ itself. The methodology used in this research is qualitative where participative observation is employed with five stages and documentation. The results shows that there are four image schemas exist in the game and those image schemas shaping the lexical concept of ‘mage’.

Keywords: cognitive semantic, image-schema, conceptual metaphor, video game

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Authors: Sufia Maroof

Abstract:

This empirical study investigated the web-translations of five Pakistani public offices (FPSC, FIA, HEC, USB, and Ministry of Finance) offering Urdu tab as an option to access information on their official websites. Triangulation of quantitative and qualitative research design informed the researcher of the semantic, lexical and syntactic caveats in these translations. The study hypothesized that majority of the Pakistani population is oblivious of the Supreme Court’s amendments in language policy concerning national and official language; hence, Urdu web-translations of the public departments have not been accessed effectively. Firstly, the researcher conducted an online survey, comprising of two sections, close ended and short answer based questions. Secondly, the researcher compiled corpus of the five selected websites in a tabular form to compare the data. Thirdly, the administrators of the departments had been contacted regarding the methods of translation and the expertise of the personnel involved. The corpus was assessed for TQA after examining the lexical, semantic, syntactical and technical alignment inaccuracies and imperfections. The study suggests the public offices to invest in their Urdu webs by either hiring expert translators or engaging expertise of a translation agency for this project to offer quality translation to public.

Keywords: machine translations, public offices, Urdu translations, websites

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm

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