Search results for: semantic dementia

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad

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As a result of the growth of the web, people are able to express their views and opinions. They can now post reviews of products at merchant sites and express their views on almost anything in internet forums, discussion groups, and blogs. Therefore, the number of product reviews has grown rapidly. The large numbers of reviews make it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). For sentiment classification, most existing methods utilize a list of opinion words whereas this paper proposes a fuzzy approach for evaluating sentiments expressed in customer product reviews, to predict the strength levels (e.g. very weak, weak, moderate, strong and very strong) of customer product reviews by combinations of adjective, adverb and verb. The proposed fuzzy approach has been tested on eight benchmark datasets and obtained 74% accuracy, which leads to help the organization with a more clear understanding of customer's behavior in support of business planning process.

Keywords: fuzzy logic, customer product review, sentiment analysis

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Authors: Rasha M. Hussein, Reem M. Hashem, Laila A. Rashed

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Alzheimer’s disease is the most common dementia disease in the elderly. It is characterized by the accumulation of extracellular amyloid β (Aβ) peptides and intracellular hyper-phosphorylated tau protein. In addition, recent evidence indicates that accumulation of intracellular amyloid β peptides may play a role in Alzheimer’s disease pathogenesis. This suggests that intracellular Heat Shock Proteins (HSP) that maintain the protein quality control in the cell might be potential candidates for disease amelioration. DNAJB6, a member of DNAJ family of HSP, effectively prevented the aggregation of poly glutamines stretches associated with Huntington’s disease both in vitro and in cells. In addition, DNAJB6 was found recently to delay the aggregation of Aβ42 peptides in vitro. In the present study, we investigated the ability of DNAJB6 to prevent the aggregation of both intracellular and extracellular Aβ peptides using transfection of HEK293 cells with Aβ-GFP and recombinant Aβ42 peptides respectively. We performed western blotting and immunofluorescence techniques. We found that DNAJB6 can prevent Aβ-GFP aggregation, but not the seeded aggregation initiated by extracellular Aβ peptides. Moreover, DNAJB6 required interaction with HSP70 to prevent the aggregation of Aβ-GFP protein and its J-domain was essential for this anti-aggregation activity. Interestingly, overexpression of other DNAJ proteins as well as HSPB1 suppressed Aβ-GFP aggregation efficiently. Our findings suggest that DNAJB6 is a promising candidate for the inhibition of Aβ-GFP mediated aggregation through a canonical HSP70 dependent mechanism.

Keywords: Aβ, Alzheimer’s disease, chaperone, DNAJB6, aggregation

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Authors: Anam Bhatti, Sumbal Arif, Mariam Mehar, Sohail Younas

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CSR has become one of the imperative implements in satisfying customers. The impartial of this research is to calculate CSR, relationship marketing, and customer satisfaction. In Pakistan, there is not enough research work on the effect of CSR and relationship marketing on relationship maintainer and customer loyalty. To find out deductive approach and survey method is used as research approach and research strategy respectively. This research design is descriptive and quantitative study. For data, collection questionnaire method with semantic differential scale and seven point scales are adopted. Data has been collected by adopting the non-probability convenience technique as sampling technique and the sample size is 400. For factor confirmatory factor analysis, structure equation modeling and medication analysis, regression analysis Amos software were used. Strong empirical evidence supports that the customer’s perception of CSR performance is highly influenced by the values.

Keywords: CSR, Relationship marketing, Relationship maintainer, Customer loyalty, Customer satisfaction

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Authors: Huafeng Wei

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Failures of developing new drugs primarily based on the amyloid pathology hypothesis after decades of efforts internationally lead to changes of focus targeting alternative pathways of pathology in Alzheimer’s disease (AD). Disruption of intracellular Ca2+ homeostasis, especially the pathological and excessive Ca2+ release from the endoplasmic reticulum (ER) via ryanodine receptor (RyRs) Ca2+ channels, has been considered an upstream pathology resulting in major AD pathologies, such as amyloid and Tau pathology, mitochondria damage and inflammation, etc. Therefore, dantrolene, an inhibitor of RyRs that reduces the pathological Ca2+ release from ER and a clinically available drug for the treatment of malignant hyperthermia and muscle spasm, is expected to ameliorate AD multiple pathologies synapse and cognitive dysfunction. Our own studies indicated that dantrolene ameliorated impairment of neurogenesis and synaptogenesis in neurons developed from induced pluripotent stem cells (iPSCs) originated from skin fibroblasts of either familiar (FAD) or sporadic (SAD) AD by restoring intracellular Ca2+ homeostasis. Intranasal administration of dantrolene significantly increased its passage across the blood-brain barrier (BBB) and, therefore its brain concentrations and durations. This can render dantrolene a more effective therapeutic drug with fewer side effects for chronic AD treatment. This review summarizes the potential therapeutic and side effects of dantrolene and repurposes intranasal dantrolene as a disease-modifying drug for future AD treatment.

Keywords: Alzheimer's disease, calcium, drug development, dementia, neurodegeneration, neurogenesis

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Authors: Vivek Kumar

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The effects of physical activity on the human body have been well understood. It just not only keeps us healthy and away from many diseases but also helpful in delay ageing. Those who exercise every day are physically as well as mentally strong. As the age advance, we often see that there is a loss of memory in the elderly people and their retention power weaken with time. The association between physical health and mental health of elderly people nowadays is an important topic of research. Many people at their old age who all were suffering from Alzheimer or Parkinson disease or were at the stage of dementia have been benefited significantly on exercise at daily basis. We would conduct a randomized control trial, where we will select a number of old age people (65 years old or above). These selected old age people will have some sorts of mental illness and currently receiving treatment for the same. We will divide them into 3 groups. The first group of people will receive their normal treatment i.e. taking medicines. The second group of people will receive medicine as well as will do exercise for 45 minutes every day in the early morning, the 3rd group of people will do exercise everyday for 45 minutes but will be given placebo instead of medicine. All the member of these groups will be monitored carefully for 6 months of time and making this sure that all the members of the group are taking medicines or doing exercise according to the group they belong to. The mental status of all the participants will be measured; the data will be analyzed accordingly. Expected results- This research will be helpful in establishing the effect of exercise on the mental health of the old age people. Also, it will be examined that whether the medicines along with regular exercise for can months can cure the mental illness significantly.

Keywords: mental health, elderly people, physical activity, randomized control trial

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Authors: Y. Bablu Singh, B. S. Purkayashtha, Chungkham Yashawanta Singh

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Morphological analysis forms the basic foundation in NLP applications including syntax parsing Machine Translation (MT), Information Retrieval (IR) and automatic indexing in all languages. It is the field of the linguistics; it can provide valuable information for computer based linguistics task such as lemmatization and studies of internal structure of the words. Computational Morphology is the application of morphological rules in the field of computational linguistics, and it is the emerging area in AI, which studies the structure of words, which are formed by combining smaller units of linguistics information, called morphemes: the building blocks of words. Morphological analysis provides about semantic and syntactic role in a sentence. It analyzes the Manipuri word forms and produces several grammatical information associated with the words. The Morphological Analyzer for Manipuri has been tested on 3500 Manipuri words in Shakti Standard format (SSF) using Meitei Mayek as source; thereby an accuracy of 80% has been obtained on a manual check.

Keywords: morphological analysis, machine translation, computational morphology, information retrieval, SSF

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Authors: Smail Boussaadi, Hassina Aliane

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With the rapid growth of scientific literature, it is becoming increasingly challenging for researchers to keep up with the latest findings in their fields. Academic, professional networks play an essential role in connecting researchers and disseminating knowledge. To improve the user experience within these networks, we need effective article recommendation systems that provide personalized content.Current recommendation systems often rely on collaborative filtering or content-based techniques. However, these methods have limitations, such as the cold start problem and difficulty in capturing semantic relationships between articles. To overcome these challenges, we propose a new approach that combines BERTopic (Bidirectional Encoder Representations from Transformers), a state-of-the-art topic modeling technique, with community detection algorithms in a academic, professional network. Experiences confirm our performance expectations by showing good relevance and objectivity in the results.

Keywords: scientific articles, community detection, academic social network, recommender systems, neural topic model

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Authors: Su-Lin Yu

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This paper will explore how gender and care discourse are intersected, reformulated and contested in American daughters’ caregiving memoirs. In particular, it will attempt to show how gender structure has worked to regulate a daughter’s response to her mother’s illness. In other words, how do certain cultural notions and class difference affect the ways in which the daughter enacts her caregiving response to her mother’s illness? What is the interrelation of female subjectivity and care practice? To understand care and gender politics in the memoirs, this paper will engage in close readings of five texts: Sandra Bullock Simith’s Trading Places: Becoming My Mother’s Mother: A Daughter’s Memoir (2015),Martha Stettinius’s Inside the Dementia Epidemic: A Daughter’s Memoir (2012), Patricia Thompson Collamer’s Grace on the Ledge: a Caregiver's Memoir, Judith Henry’s The Dutiful Daughter's Guide to Caregiving: A Practical Memoir (2015), and The Daughter's Dilemma: A Survival Guide to Caring for an Aging, Abusive Parent by Emily Wanderer Cohen (2018). By analyzing these texts, this paper will show why adult daughters become the primary caregivers, how gender norms and care practices influence a daughter’s thoughts and actions, and how it affects her self-understanding. Taken as a whole, then, the paper will provide an important examination not only of care and gender politics, but also a contribution to the intersecting discourses of illness, death, and mother-daughter relationship.

Keywords: care ethics, daughter-mother relationship, gender politics, memoirs

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Authors: Makenzy Lee Gilbert

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This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, reinforcement, retrieval, and forgetting. Key mathematical foundations, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus's role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future exploration areas.

Keywords: attractor neural networks, connectionism, computational modeling, cognitive neuroscience

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Authors: Samia Alblwi, Amani Ayad

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Mutation testing is the art of generating syntactic variations of a base program and checking whether a candidate test suite can identify all the mutants that are not semantically equivalent to the base: this technique is widely used by researchers to select quality test suites. One of the main obstacles to the widespread use of mutation testing is cost: even small pro-grams (a few dozen lines of code) can give rise to a large number of mutants (up to hundreds): this has created an incentive to seek to reduce the number of mutants while preserving their collective effectiveness. Two criteria have been used to reduce the size of mutant sets: equiva-lence, which aims to partition the set of mutants into equivalence classes modulo semantic equivalence, and selecting one representative per class; subsumption, which aims to define a partial ordering among mutants that ranks mutants by effectiveness and seeks to select maximal elements in this ordering. In this paper we analyze these two policies using analytical and em-pirical criteria.

Keywords: mutation testing, mutant sets, mutant equivalence, mutant subsumption, mutant set minimization

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Authors: Yuhong Zhang, Dan Lu, Chenyang Bu, Peipei Li, Kui Yu, Xindong Wu

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The Cross-Lingual Entity Alignment (CLEA) task aims to find the aligned entities that refer to the same identity from two knowledge graphs (KGs) in different languages. It is an effective way to enhance the performance of data mining for KGs with scarce resources. In real-world applications, the neighborhood structures of the same entities in different KGs tend to be non-isomorphic, which makes the representation of entities contain diverse semantic information and then poses a great challenge for CLEA. In this paper, we try to address this challenge from two perspectives. On the one hand, the cross-KG relation completion rules are designed with the alignment constraint of entities and relations to improve the topology isomorphism of two KGs. On the other hand, a representation method combining isomorphic weights is designed to include more isomorphic semantics for counterpart entities, which will benefit the CLEA. Experiments show that our model can improve the isomorphism of two KGs and the alignment performance, especially for two non-isomorphic KGs.

Keywords: knowledge graphs, cross-lingual entity alignment, non-isomorphic, relation completion

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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: Nirupama Dixit, Anyaa Mittal, Neeru Sood

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Alzheimer’s disease (AD) is a progressive form of dementia, contributing to up to 70% of cases, mostly observed in elderly but is not restricted to old age. The pathophysiology of the disease is characterized by specific pathological changes in brain. The changes (i.e. accumulation of metal ions in brain, formation of extracellular β-amyloid (Aβ) peptide aggregates and tangle of hyper phosphorylated Tau protein inside neurons) damage the neuronal connections irreversibly. The current issues in improvement of life quality of Alzheimer's patient lies in the fact that the diagnosis is made at a late stage of the disease and the medications do not treat the basic causes of Alzheimer's. The targeted delivery of drug through the blood brain barrier (BBB) poses several limitations via traditional approaches for treatment. To overcome these drug delivery limitation, nanoparticles provide a promising solution. This review focuses on current strategies for efficient targeted drug delivery using nanoparticles and improving the quality of therapy provided to the patient. Nanoparticles can be used to encapsulate drug (which is generally hydrophobic) to ensure its passage to brain; they can be conjugated to metal ion chelators to reduce the metal load in neural tissue thus lowering the harmful effects of oxidative damage; can be conjugated with drug and monoclonal antibodies against BBB endogenous receptors. Finally this review covers how the nanoparticles can play a role in diagnosing the disease.

Keywords: Alzheimer's disease, β-amyloid plaques, blood brain barrier, metal chelators, nanoparticles

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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: L. Paulino Ferreira, M. Gomes Neto, M. Duarte, S. Serra

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Objectives: COVID-19 pandemic has caused older adults to experience a degree of social isolation and loneliness that is unprecedented. Our aim is to review state of the art regarding the consequences of social isolation due to COVID-19 in elderly people. Methods: The authors conducted a search on Medscape and PubMed with the keywords mentioned below, and the most relevant articles were selected. Results: Social isolation leads many elderlies to experience loneliness, anxiety, depression, alcohol abuse, and feelings of abandonment with a perception of being a burden on society. Thus, social isolation has increased the risk for suicide in older people. It is also noteworthy that the exacerbation of psychiatric disorders (such as depression, anxiety, and post-traumatic stress disorder) without correct treatment and follow-up also increases suicide risk. Loneliness is also associated with accelerated cognitive deterioration and dementia. Besides that, during social isolation, it could be more difficult for older people to get medication as well as proper health care. It is also noticed an increase in the risk of falls, poor nutrition, and lack of exercise. All this contributes to weakening elderlies’ immune systems leading to a higher risk of developing infections, cardiovascular events, and cancer, increasing hospitalization and morbimortality. Conclusion: Social isolation in the elderly has a significant impact on physical and mental health, as well as morbimortality and hospitalizations due to non-COVID causes. Nevertheless, further studies will be needed to assess the real dimension of the effects of social isolation due to COVID-19.

Keywords: social isolation, COVID-19, elderly, mental health

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Authors: Jun Hong Lee

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Background: Alzheimer`s disease (AD) I: creases with age and is characterized by the premature progressive loss of neuronal cell. In contrast, cancer cells have inappropriate cell proliferation and resistance to cell death. Objective: We evaluated the association between cancer and AD and also examined the specific types of cancer. Patients and Methods/Material and Methods: This retrospective, nationwide, longitudinal study used National Health Insurance Service – Senior cohort (NHIS-Senior) 2002-2013, which was released by the KNHIS in 2016, comprising 550,000 random subjects who were selected from over than 60. The study included a cohort of 4,408 patients who were first diagnoses as AD between 2003 and 2005. To match each dementia patient, 19,150 subjects were selected from the database by Propensity Score Matching. Results: We enrolled 4,790 patients for analysis in this cohort and the prevalence of AD was higher in female (19.29%) than in male (17.71%). A higher prevalence of AD was observed in the 70-84 year age group and in the higher income status group. A total of 540 cancers occurred within the observation interval. Overall cancer was less frequent in those with AD (12.25%) than in the control (18.46%), with HR 0.704 (95% Confidence Intervals (CIs)=0.0.64-0.775, p-Value < 0.0001). Conclusion: Our data showed a decreased incidence of overall cancers in patients with AD similar to previous studies. Patients with AD had a significantly decreased risk of colon & rectum, lung and stomach cancer. This finding lower than but consistent with Western countries. We need further investigation of genetic evidence linking AD to cancer.

Keywords: Alzheimer, cancer, nationwide, longitudinal study

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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: 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: 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: 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

Abstract:

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

Procedia PDF Downloads 171

Authors: Huan Lin, Liwen Pang

Abstract:

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

Procedia PDF Downloads 226

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

Abstract:

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

Procedia PDF Downloads 448