Search results for: semantic impairments

Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Sadeq Alyaari, Muhammad Alkhunayn, Montaha Al Yaari, Ayman Al Yaari, Ayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction. The purpose of this Systematic Literature Review and Meta-analysis ((SLR & Meta-analysis) was to examine the differences between Asperger syndrome (AS) individuals and typically developing and achieving individuals (TD) regarding language competence and how these differences related to AS individuals’ age and the significance such differences add to our knowledge of understanding their language performance as issues that are still underdiagnosed and ill-treated entities. Methods. The study followed SLR & Meta-analysis protocol and was armed with data of 456 AS subjects and controls (231 and 225, respectively) abstracted from 14 studies that have been collected from different electronic bibliographic databases including web of science, Scopus, EMBASE, Cochrane library, PubMed, PsycInfo and google scholar along with unpublished literature. Results. Outlined results show deterioration in language competence of AS subjects in comparison to TD controls. Such deterioration impairs conversational implicature more than it does conventional maxims of AS individuals’ pragmatic language and has no relationship with their age. Results also show that the difference in intelligence features of the mental reality in the language competence becomes smaller with increasing age and that the difference in representational content features becomes larger. Conclusions. These findings help experts in the field not only predict pragmatic language impairments in AS individuals but also enable AS individuals themselves to decode and/or interpret speech inputs; therefore, perceive the world around them and interact with their community members. Outcomes should be considered to lay out a path for further exploration of genetics, etiology, and response to treatment of all these premises that are currently unsearched in AS individuals.

Keywords: pragmatic language characteristics, language competence, mental faculty, mental reality, features, language performance, pragmatics, conventional maxims

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Amina Ottozbeer, Nazanin Derakhshan

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Emotion regulation, a transdiagnostic process, is often impaired in individuals with high trait anxiety due to compromised executive functioning and attentional control. Recent research underscores the importance of studying individual differences and contextual factors in understanding the adaptability of emotion regulation processes, particularly in those with high trait anxiety. Prior studies have emphasized the role of self-efficacy in promoting positive cognitive flexibility outcomes and mitigating executive function impairments in highly anxious individuals. Accordingly, the objective of this study was to examine the moderating influence of attentional control, cognitive flexibility, and self-efficacy on the relationship between trait anxiety and emotion regulation. Using a correlational design, an online study was conducted with a sample of 82 participants (mean age: 22 years). Self-report questionnaires measured individual difference variables. The Classic Stroop Task assessed attentional control as an objective measure of cognitive flexibility . The findings revealed three significant interactions. Firstly, high cognitive flexibility and self-efficacy were linked to reduced expressive suppression in individuals with low trait anxiety. Secondly, elevations in cognitive flexibility and self-efficacy were associated with increased suppression in those with high trait anxiety. Thirdly, high trait anxiety was associated with reduced attentional control. The results suggest that typically adaptive processes can yield different outcomes in highly anxious populations, highlighting the need to explore additional variables that could alter the impact of cognitive flexibility and self-efficacy on emotion regulation in individuals with high anxiety. These findings have significant clinical implications, emphasizing the need to consider individual differences in emotion regulation and trait anxiety to inform more effective psychological treatments.

Keywords: attentional control, trait anxiety, emotional dysregulation, transdiagnostic, individual differences

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Authors: O. F. Elkommos

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“Humour studies” is an interdisciplinary research area that is relatively recent. It interests researchers from the disciplines of psychology, sociology, medicine, nursing, in the work place, gender studies, among others, and certainly teaching, language learning, linguistics, and literature. Linguistic theories of humour research are numerous; some of which are of interest to the present study. In spite of the fact that humour courses are now taught in universities around the world in the Egyptian context it is not included. The purpose of the present study is two-fold: to review the state of arts and to show how linguistic theories of humour can be possibly used as an art and craft of teaching and of learning in EFL literature classes. In the present study linguistic theories of humour were applied to selected literary texts to interpret humour as an intrinsic artistic communicative competence challenge. Humour in the area of linguistics was seen as a fifth component of communicative competence of the second language leaner. In literature it was studied as satire, irony, wit, or comedy. Linguistic theories of humour now describe its linguistic structure, mechanism, function, and linguistic deviance. Semantic Script Theory of Verbal Humor (SSTH), General Theory of Verbal Humor (GTVH), Audience Based Theory of Humor (ABTH), and their extensions and subcategories as well as the pragmatic perspective were employed in the analyses. This research analysed the linguistic semantic structure of humour, its mechanism, and how the audience reader (teacher or learner) becomes an interactive interpreter of the humour. This promotes humour competence together with the linguistic, social, cultural, and discourse communicative competence. Studying humour as part of the literary texts and the perception of its function in the work also brings its positive association in class for educational purposes. Humour is by default a provoking/laughter-generated device. Incongruity recognition, perception and resolving it, is a cognitive mastery. This cognitive process involves a humour experience that lightens up the classroom and the mind. It establishes connections necessary for the learning process. In this context the study examined selected narratives to exemplify the application of the theories. It is, therefore, recommended that the theories would be taught and applied to literary texts for a better understanding of the language. Students will then develop their language competence. Teachers in EFL/ESL classes will teach the theories, assist students apply them and interpret text and in the process will also use humour. This is thus easing students' acquisition of the second language, making the classroom an enjoyable, cheerful, self-assuring, and self-illuminating experience for both themselves and their students. It is further recommended that courses of humour research studies should become an integral part of higher education curricula in Egypt.

Keywords: ABTH, deviance, disjuncture, episodic, GTVH, humour competence, humour comprehension, humour in the classroom, humour in the literary texts, humour research linguistic theories, incongruity-resolution, isotopy-disjunction, jab line, longer text joke, narrative story line (macro-micro), punch line, six knowledge resource, SSTH, stacks, strands, teaching linguistics, teaching literature, TEFL, TESL

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Authors: Javier De La Torre Costa, Belen Rubio Ballester, Martina Maier, Paul F. M. J. Verschure

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After a stroke, a great number of patients experience persistent motor impairments such as hemiparesis or weakness in one entire side of the body. As a result, the lack of use of the paretic limb might be one of the main contributors to functional loss after clinical discharge. We aim to reverse this cycle by promoting the use of the paretic limb during activities of daily living (ADLs). To do so, we describe the key components of a system that is composed of a wearable bracelet (i.e., a smartwatch) and a mobile phone, designed to bring a set of neurorehabilitation principles that promote acquisition, retention and generalization of skills to the home of the patient. A fundamental question is whether the loss in motor function derived from learned–non–use may emerge as a consequence of decision–making processes for motor optimization. Our system is based on well-established rehabilitation strategies that aim to reverse this behaviour by increasing the reward associated with action execution as well as implicitly reducing the expected cost associated with the use of the paretic limb, following the notion of the reinforcement–induced movement therapy (RIMT). Here we validate an accelerometer–based measure of arm use, and its capacity to discriminate different activities that require increasing movement of the arm. We also show how the system can act as a personalized assistant by providing specific goals and adjusting them depending on the performance of the patients. The usability and acceptance of the device as a rehabilitation tool is tested using a battery of self–reported and objective measurements obtained from acute/subacute patients and healthy controls. We believe that an extension of these technologies will allow for the deployment of unsupervised rehabilitation paradigms during and beyond the hospitalization time.

Keywords: stroke, wearables, learned non use, hemiparesis, ADLs

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Authors: Olufemi Olupe

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Within linguistics, various approaches have been adopted to the study of language. One of such approaches is the syntax. The syntax is an aspect of the grammar of the language which deals with how words are put together to form phrases and sentences and how such structures are interpreted in language. Ambiguity, which is also germane in this discourse is about the uncertainty of meaning as a result of the possibility of a phrase or sentence being understood and interpreted in more than one way. In the light of the above, this paper attempts a syntactic study of syntactic ambiguities in The English Language, using the Transformational Generative Grammar (TGG) Approach. In doing this, phrases and sentences were raised with each description followed by relevant analysis. Finding in the work reveals that ambiguity cannot always be disambiguated by the means of syntactic analysis alone without recourse to semantic interpretation. The further finding shows that some syntactical ambiguities structures cannot be analysed on two surface structures in spite of the fact that there are more than one deep structures. The paper concludes that in as much as ambiguity remains in language; it will continue to pose a problem of understanding to a second language learner. Users of English as a second language, must, however, make a conscious effort to avoid its usage to achieve effective communication.

Keywords: language, syntax, semantics, morphology, ambiguity

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Authors: Sara Sahraoui

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This research studied the effect of Alzheimer's disease (AD) on language information processing in subjects with Alzheimer’s disease (AD) who were bilingual (French and dialectical Arabic). The results show a disorder of certain semantic aspects of their mother tongue (L1). On the other hand, grammatical levels appeared to be relatively unaffected in oral speech in L1 but were disturbed in the second language (L2). In consequence, we constructed a cognitive-language stimulation protocol for bilingual patients (PSCLAB) to respond to this disorder. The efficacy of this protocol in terms of rehabilitation was assessed in 30 such patients through discourse analysis carried out before and after initiating the protocol. The results show that cognitive/language training using the PSCLAB appears to improve the language behaviour of bilingual patients with AD. However, this survey study aims to verify the satisfaction of patients’ relatives with the results of cognitive language training by PSCLAB. We developed a brief instrument to measure the satisfaction of family members. The results report that the patient's relatives are satisfied with the results of cognitive training by PSCLAB.

Keywords: satisfaction, Alzheimer's disease, rehabilitation, levels language

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Authors: Athicha Cherdpunt, Patompong Satapornpong

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The medical cannabis is made up of components also known as cannabinoids, which consists of two ingredients which are Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Interestingly, the Cannabinoid can be used for many treatments such as chemotherapy, including nausea and vomiting, cachexia, anorexia nervosa, spinal cord injury and disease, epilepsy, pain, and many others. However, the adverse drug reactions (ADRs) of THC can cause sedation, anxiety, dizziness, appetite stimulation and impairments in driving and cognitive function. Furthermore, genetic polymorphisms of CYP2C9, CYP2C19 and CYP3A4 influenced the THC metabolism and might be a cause of ADRs. Particularly, CYP2C19*17 allele increases gene transcription and therefore results in ultra-rapid metabolizer phenotype (UM). The aim of this study, is to investigate the frequency of CYP2C19*17 alleles in Thai patients who have been treated with medical cannabis. We prospectively enrolled 60 Thai patients who were treated with medical cannabis and clinical data from College of Pharmacy, Rangsit University. DNA of each patient was isolated from EDTA blood, using the Genomic DNA Mini Kit. CYP2C19*17 genotyping was conducted using the real time-PCR ViiA7 (ABI, Foster City, CA, USA). 30 patients with medical cannabis-induced ADRs group, 20 (67%) were female, and 10 (33%) were male, with an age range of 30-69 years. On the other hand, 30 patients without medical cannabis-induced ADRs (control group) consist of 17 (57%) female and 13 (43%) male. The most ADRs for medical cannabis treatment in the case group were dry mouth and dry throat (77%), tachycardia (70%), nausea (30%) and arrhythmia(10%). Accordingly, the case group carried CYP2C19*1/*1 (normal metabolizer) approximately 93%, while 7% patients carrying CYP2C19*1/*17 (ultra rapid metabolizers) exhibited in this group. Meanwhile, we found 90% of CYP2C19*1/*1 and 10% of CYP2C19*1/*17 in control group. In this study, we identified the frequency of CYP2C19*17 allele in Thai population which will support the pharmacogenetics biomarkers for screening and avoid ADRs of medical cannabis treatment.

Keywords: CYP2C19, allele frequency, ultra rapid metabolizer, medical cannabis

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: Maria Joseph Israel, Ahmed Amer

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Our work aims to broaden the application of provenance technology beyond its traditional domains of scientific workflow management and database systems by offering a general provenance framework to capture richer and extensible metadata in unstructured textual data sources such as literary texts, commentaries, translations, and digital humanities. Specifically, we demonstrate the feasibility of capturing and representing expressive provenance metadata, including more of the context for citing scholarly works (e.g., the authors’ explicit or inferred intentions at the time of developing his/her research content for publication), while also supporting subsequent augmentation with similar additional metadata (by third parties, be they human or automated). To better capture the nature and types of possible citations, in our proposed provenance scheme metaScribe, we extend standard provenance conceptual models to form our proposed provCite ontology. This provides a conceptual framework which can accurately capture and describe more of the functional and rhetorical properties of a citation than can be achieved with any current models.

Keywords: knowledge representation, provenance architecture, ontology, metadata, bibliographic citation, semantic web annotation

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Authors: Shakhawath Hossain, Tazkia Tahsin

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Introduction/Background: Intellectual disability is a disability characterized by significant limitations both in intellectual functioning and in adaptive behavior, which covers many everyday social and practical skills. Vocational education is a multi-professional approach that is provided to individuals of working age with health-related impairments, limitations, or restrictions with work functioning and whose primary aim is to optimize work participation. Instrumental Activities of Daily Living activities to support daily life within the home and community. Like as community mobility, financial management, meal preparation, and clean-up, shopping. Material and Method: Electronic searches of Medline, PubMed, Google scholar, OT Seeker literature using the key terms of intellectual disability, vocational rehabilitation, instrumental activities of daily living and Occupational Therapy, as well as a thorough manual search for relevant literature. Results: There were 13 articles, all qualitative and quantitative, which are included in this review. All studies were mixed methods in design. To take the Occupational Therapy services, there is a significant improvement in their children's various areas like as sensory issues, cognitive abilities, perceptual skills, visual, motor planning, and group therapy. After taking the vocational and instrumental activities of daily living training children with intellectual disabilities to participate in their daily activities and work as an employee different company or organizations. Conclusion: The persons with intellectual disability are an integral part of our society who deserves social support and opportunities like other human beings. From the result section of the project papers, it is found that the significant benefits of Occupational Therapy services in the aspects of vocational and instrumental activities of daily living.

Keywords: occupational therapy, daily living activities, intellectual disabilities, instrumental ADL

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Yu Hung Chiang, Hei Chia Wang

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Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Wei-Chen Chang, Yu-Cheng Pei

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This research examines wearable interaction design to mediate the design anthropology and participatory design found in technology and fashion. We will discuss the principles of design anthropology and participatory design using a wearable and fashion product process to transmit the ‘people-situation-reason-object’ method and analyze five sense applied examples that provide new thinking for designers engaged in future industry. Design anthropology and Participatory Design attempt to engage physiological and psychological design through technology-function, meaning-form and fashion aesthetics to achieve cognition between user and environment. The wearable interaction provides technological characteristics and semantic ideas transmitted to craft-cultural, collective, cheerful and creative performance. It is more confident and innovative attempt, that is able to achieve a joyful, fundamental interface. This study takes two directions for cultural thinking as the basis to establish a set of life-craft designs with interactive experience objects by users that assist designers in examining the sensual feelings to initiate a new lifestyle value.

Keywords: design anthropology, wearable design, design communication, participatory design

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Authors: Alalddin Al-Tarawneh

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In its literal translation, the Qur’an is frequently subject to misinterpretation as a result of failures to deliver its meaning into any language. This paper relies on the genuine aspect that the Qur’an is an oral performance in its nature; and the objective of any Qur’an translation is to deliver its meaning in English. Therefore, it approaches the translation of the Qur’an beyond the usual formal linguistic approach in order to include an extra-textual factor. This factor is the recitation or oral performance of the Qur’an, that is, tajweed as it is termed in Arabic. The translations used in this paper to apply the suggested approach were carefully chosen to be representative of the problems that exist in many Qur’an translations. These translations are The Meaning of the Holy Quran: Translation and Commentary by Ali (1989), The Meaning of the Glorious Koran by Pickthall (1997/1930), and The Quran: Arabic Text with Corresponding English Meanings by Sahih (2010). Through the examples cited in this paper, it is suggested that the agents involved in producing a ‘translation’ of the Holy Qur’an have to take into account its oral aspect which yields additional senses and meanings that are not being captured by adhering to the words of the ‘written’ discourse. This paper attempts in its translation into English.

Keywords: oral performance, tajweed, Qur'an translation, recitation

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Authors: Zhuo Jing-Schmidt, Jun Lang

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Numeral classifiers are common in Asian languages. Research on numeral classifiers primarily focuses on noun classifiers that quantify and individuate nominal referents. There is a scarcity of research on event quantification using verb classifiers. This study aims to understand the semantic and conceptual basis of event quantification in Chinese. From a usage-based Construction Grammar perspective, this study presents a corpus analysis of event quantification in Chinese. Drawing on a large balanced corpus of contemporary Chinese, we analyze 667 NOUN col-lexemes totaling 31136 tokens of a productive numeral classifier construction in Chinese. Using collostructional analysis of the collexemes, the results show that the construction quantifies and classifies dramatic events using a theater-based conceptual metaphor. We argue that the usage patterns reflect the cultural entrenchment of theater as in Chinese conceptualization and the construal of theatricality in linguistic expression. The study has implications for cognitive semantics and construction grammar.

Keywords: event quantification, classifier, corpus, metaphor

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Authors: Xuri Tang, Ting Pan

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Metaphor institutionalization refers to the propagation of a metaphor that leads to its acceptance in speech community as a norm of the language. Such knowledge is important to both theoretical studies of metaphor and practical disciplines such as lexicography and language generation. This paper reports an empirical study of metaphor institutionalization of 14 Chinese metaphors. It first explores the pattern of metaphor institutionalization by fitting the logistic function (or S-shaped curve) to time series data of conventionality of the metaphors that are automatically obtained from a large-scale diachronic Chinese corpus. Then it reports a questionnaire-based survey on the propagation scale of each metaphor, which is measured by the average number of subjects that can easily understand the metaphorical expressions. The study provides two pieces of evidence supporting the hypothesis that metaphor institutionalization is a phrase transition: (1) the pattern of metaphor institutionalization is an S-shaped curve and (2) institutionalized metaphors generally do not propagate to the whole community but remain in equilibrium state. This conclusion helps distinguish metaphor institutionalization from topicalization and other types of semantic change.

Keywords: metaphor institutionalization, phase transition, propagation scale, s-shaped curve

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Authors: Huan Lin, Liwen Pang

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In order to reduce the ambiguity and uncertainty of product form bionic design, a product form bionic design method based on eye tracking is proposed. The eye-tracking experiment is designed to calculate the average time ranking of the specific parts of the bionic shape that the subjects are looking at. Key bionic shape is explored through the experiment and then applied to a desk lamp bionic design. During the design case, FAHP (Fuzzy Analytic Hierachy Process) and SD (Semantic Differential) method are firstly used to identify consumer emotional perception model toward desk lamp before product design. Through investigating different desk lamp design elements and consumer views, the form design factors on the desk lamp product are reflected and all design schemes are sequenced after caculation. Desk lamp form bionic design method is combined the key bionic shape extracted from eye-tracking experiment and priority of desk lamp design schemes. This study provides an objective and rational method to product form bionic design.

Keywords: Bionic design; Form; Eye tracking; FAHP; Desk lamp

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Authors: Ana Paula Vilas Boas Viveiros Lopes, Marly Monteiro de Carvalho

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The new product development for decades has favored companies that can put their products to market quickly and efficiently, providing sustainable competitive advantage difficult to be achieved by their competitors. This paper presents the outcomes of a systematic review of the literature relating to new product development that was published between 1992 and 2012. A hybrid methodological approach that combines bibliometrics, content analysis and semantic analysis was applied. The review discusses the publication patterns, focusing on aspects related to scientific collaboration. The results show that the main academic journal that discusses this theme is “Journal of Product Innovation Management”. Although the first paper relating to this theme was published in 1992, the number of publications on the subject only began to increase substantially in 1999. Most of the studies reviewed in this paper applied qualitative research methods, indicating that most of the research on the theme is still in an exploratory phase.

Keywords: project type, project typology, new product development, sustainable competitive advantage

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Authors: Dalila Souilem, Salma Boumiza, Abdelkarim Abdelkader

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The Clarifier Dialogue Interface (CDI) is a part of an online teaching system based on human-machine communication in learning situation. This interface used in the system during the learning action specifically in the evaluation step, to clarify ambiguities in the learner's response. The CDI can generate patterns allowing access to an information system, using the selectors associated with lexical units. To instantiate these patterns, the user request (especially learner’s response), must be analyzed and interpreted to deduce the canonical form, the semantic form and the subject of the sentence. For the efficiency of this interface at the interpretation level, a set of substitution operators is carried out in order to extend the possibilities of manipulation with a natural language. A second approach that will be presented in this paper focuses on the object languages with new prospects such as combination of natural language with techniques of handling information system in the area of online education. So all operators, the CDI and other interfaces associated to the domain expertise and teaching strategies will be unified using FRAME representation form.

Keywords: dialogue, e-learning, FRAME, information system, natural language

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Authors: Salma A. El-Marasy, Reham M. Abd-Elsalam, Omar A. Ahmed-Farid

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Dementia is characterized by impairments in memory and other cognitive abilities. This study aims to elucidate the possible ameliorative effect of silymarin on scopolamine-induced dementia using the object recognition test (ORT). The study was extended to demonstrate the role of cholinergic activity, oxidative stress, neuroinflammation, brain neurotransmitters and histopathological changes in the anti-amnestic effect of silymarin in demented rats. Wistar rats were pretreated with silymarin (200, 400, 800 mg/kg) or donepezil (10 mg/kg) orally for 14 consecutive days. Dementia was induced after the last drug administration by a single intraperitoneal dose of scopolamine (16 mg/kg). Then behavioral, biochemical, histopathological, and immunohistochemical analyses were then performed. Rats pretreated with silymarin counteracted scopolamine-induced non-spatial working memory impairment in the ORT and decreased acetylcholinesterase (AChE) activity, reduced malondialdehyde (MDA), elevated reduced glutathione (GSH), restored gamma-aminobutyric acid (GABA) and dopamine (DA) contents in the cortical and hippocampal brain homogenates. Silymarin dose-dependently reversed scopolamine-induced histopathological changes. Immunohistochemical analysis showed that silymarin dose-dependently mitigated protein expression of a glial fibrillary acidic protein (GFAP) and nuclear factor kappa-B (NF-κB) in the brain cortex and hippocampus. All these effects of silymarin were similar to that of the standard anti-amnestic drug, donepezil. This study reveals that the ameliorative effect of silymarin on scopolamine-induced dementia in rats using the ORT maybe in part mediated by, enhancement of cholinergic activity, anti-oxidant and anti-inflammatory activities as well as mitigation in brain neurotransmitters and histopathological changes.

Keywords: dementia, donepezil, object recognition test, rats, silymarin, scopolamine

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Jiechen Yin, Xiang Hong, Ran Liu

Abstract:

Atrazine (ATR), a widely used triazine herbicide, is an environmental endocrine disruptor that can cause health problems. However, whether there are multi/trans-generational reproductive impacts of ATR have not been studied to our best knowledge. Therefore, in this study, Caenorhabditis elegans was used as a preferable model organism to identify the multi/trans-generational reproductive toxicity of ATR. L1 larvae were exposed to different concentrations (0.0004–40 mg/L) of ATR for 48 h. Successive generations (F1 to F5) were fed without ATR and consecutive exposure. The results showed that ATR exposure during P0 decreased fecundity, including a reduction in fertilized eggs, oocytes, and ovulation rate, delayed gonadal development, and decreased the relative area of the gonad arm and germ cell number. Furthermore, continuous ATR exposure (P0–F5) causes a significant increase in reproductive toxicity in subsequent generations, although no significant toxicity occurred in the P0 generation after exposure to environmental-related concentrations, suggesting that ATR exposure might have cumulative effects. Likewise, parental exposure to ATR caused transgenerational toxicity impairments. Interestingly, reproductive toxicity not development toxicity was transmitted to several generations (F1–F4), and the F2 generation showed the most notable changes. QRT-PCR results showed that genes related to DNA methylation 6mA (damt-1, nmad-1) and histone H3 methylation (mes-4, met-2, set-25, set-2, and utx-1) can also be passed on to offspring. The function of H3K4 and H3K9 methylation were explored by using loss-of-function mutants for set-2, set-25, and met-2. Transmissible reproductive toxicity was absent in met-2(n4256), set-2(ok952), and set-25(n5021) mutants, which suggests that the histone methyltransferases H3K4 and H3K9 activity are indispensable for the transgenerational effect of ATR. Finally, the downstream genes of DNA methylation and histone H3 methylation were determined. ATR upregulated the expression of ZC317.7, hsp-6, and hsp-60. Mitochondrial stress in parental generation dependent transcription 6mA modifiers may establish these epigenetic marks in progeny.

Keywords: ATR, Caenorhabditis elegans, multi-/trans-generation, reproductive toxicity

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Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

Abstract:

This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

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Authors: Hamzeh Mazaherylaghab, Mehrangiz Vahabian, Seyyedeh Zahra Asghari

Abstract:

The present study initially focused on the frequency of phrasal verbs used by Iranian learners of English. The results then needed to be compared to the findings from native speaker corpora. After the extraction of phrasal verbs from learner and native-speaker corpora the findings were analysed. The results showed that Iranian learners avoided using phrasal verbs in many cases. Some of the findings proved to be significant. It was also found that the learners used the single-word counterparts of the avoided phrasal verbs to compensate for their lack of knowledge in many cases. Semantic complexity and Lack of L1 counterpart may have been the main reasons for avoidance, but despite the avoidance phenomenon, the learners displayed a tendency to use many other phrasal verbs which may have been due to the increase in the number of multi-word verbs in Persian. The overall scores confirmed the fact that the language produced by the learners illustrates signs of more formal style in comparison with the native speakers of English by using less phrasal verbs and more formal single word verbs instead.

Keywords: corpus, corpora, LOCNESS, phrasal verbs, single-word verb

Procedia PDF Downloads 201