Search results for: distributional semantics

Authors: Paule Olivia Akotto

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The recent literature suggests spending between 50%-85% of oil rents. However, there are not yet clear guidelines for allocating this windfall in the public investment system, while most of the resource-rich countries fail to improve their intergenerational mobility. We study a design of the optimal spending system in Senegal, a low-income developing country featuring newly discovered oil fields and low intergenerational mobility. We build a dynamic general equilibrium model in which rural and urban (Dakar and other urban centers henceforth OUC) households face different health, education, and employment opportunities based on their location, affecting their intergenerational mobility. The model captures the relationship between oil rents, public investment, and multidimensional inequality of opportunity. The government invests oil rents in three broad sectors: health and education, road and industries, and agriculture. Through endogenous productivity externality and human capital accumulation, our model generates the predominant position of Dakar and OUC households in terms of access to health, education, and employment in line with Senegal data. Rural households are worse off in all dimensions. We compute the optimal spending policy under two sets of simulation scenarios. Under the current Senegal public investment strategy, which weighs more health and education investments, we find that the reform maximizing the decline in inequality of opportunity between households, frontloads investment during the first eight years of the oil exploitation and spends the perpetual value of oil wealth thereafter. We will then identify the marginal winners and losers associated with this policy and its redistributive implications. Under our second set of scenarios, we will test whether the Senegalese economy can reach better equality of opportunity outcomes under this frontloading reform, by allowing the sectoral shares of investment to vary. The trade-off will be between cutting human capital investment in favor of agricultural and productive infrastructure or increasing the former. We will characterize the optimal policy by specifying where the higher weight should be. We expect that the optimal policy of the second set strictly dominates in terms of equality of opportunity, the optimal policy computed under the current investment strategy. Finally, we will quantify this optimal policy's aggregate and distributional effects on poverty, well-being, and gender earning gaps.

Keywords: developing countries, general equilibrium, inequality of opportunity, oil rents

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Authors: Aseel Zibin, Abdel Rahman Altakhaineh

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This study analyses 30 cartoons depicting THE DEAL OF THE CENTURY as envisaged by two Jordanian cartoonists, namely, EmadHajjaj and Osama Hajjaj. Conceptual Blending Theory (CBT) and Multimodal Metaphor Theory (MMT) are adopted as a theoretical framework to interpret the metaphors and metonymies used in the target cartoons. The results reveal that the target domain THE DEAL OF THE CENTURY was conceptualized mainly through layered metaphors that have metonymic basis and event metaphors\allegories. Specifically, 6 groups were identified: OBJECT or a situation involving OBJECTS, situations involving HUMANS\HYBRIDS of HUMANS and OBJECTS, an ANIMAL OR situation involving an ANIMAL, hybrids of WEAPONS and humans, and event metaphors used to build a story\allegory. The target domain was also depicted via event metaphors used to build a story; some of which are embedded in the Jordanian culture, while others could be perceivable cross-culturally. The results also demonstrate that the most widely used configurations to construe the metaphors was the pictorial source–verbal target in line with Lan and Zuo (2016); the motivation was probably the greater conceptual density and concreteness of visual representation since the target is better captured verbally because of its abstractness. The use of cross-modal mappings of this type was attributed to the abstractness of the target domain, THE DEAL OF THE CENTURY, which makes it more construable via verbal cues rather than visual ones. In contrast, the source domains used were mainly concrete and thus perceivable pictorially rather than verbally.

Keywords: semiotics, cognitive semantics, metaphor, culture, blending, cartoon

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Authors: Jose Marie E. Ocdenaria, Riceli C. Mendoza

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Culturally, languages meet, merge, share, exchange, appropriate, donate, and divide in and to and from each other. Further, this type of recurrence manifests in East Asian cultures, where language influence diffuses across geographical proximities. Historically, China has notable impacts on Japan’s culture. For instance, Japanese borrowed words from China and their way of reading and writing. This qualitative and descriptive employing contrastive analysis study addressed the true and false cognates of Japanese-Philippine languages and Chinese-Philippine languages. It involved a rich collection of data from various sources like textual pieces of evidence or corpora to gain a deeper understanding of true and false cognates between L1 and L2. Cognates of Japanese-Philippine languages and Chinese-Philippine languages were analyzed contrastively according to orthography, phonology, and semantics. The words presented were the roots; however, derivatives, reduplications, and variants of stress were included when they shed emphases on the comparison. The basis of grouping the cognates was its phonetic-semantic resemblance. Based on the analysis, it revealed that there are words which may have several types of lexical relationship. Further, the study revealed that the Japanese language has more false cognates in the Philippine languages, particularly in Tagalog and Cebuano. On the other hand, there are more true cognates of Chinese in Tagalog. It is the hope of this study to provide a significant contribution to a diverse audience. These include the teachers and learners of foreign languages such as Japanese and Chinese, future researchers and investigators, applied linguists, curricular theorists, community, and publishers.

Keywords: Contrastive Analysis, Japanese, Chinese and Philippine languages, Qualitative and descriptive study, True and False Cognates

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Authors: Harshan Tee Pee

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Climate elements include surface temperatures, rainfall patterns, humidity, type and amount of cloudiness, air pressure and wind speed and direction. Change in one element can have an impact on the regional climate. The scientific predictions indicate that global climate change will increase the number of extreme events, leading to more frequent natural hazards. Global warming is likely to intensify the risk of drought in certain parts and also leading to increased rainfall in some other parts. Drought is a slow advancing disaster and creeping phenomenon– which accumulate slowly over a long period of time. Droughts are naturally linked with aridity. But droughts occur over most parts of the world (both wet and humid regions) and create severe impacts on agriculture, basic household welfare and ecosystems. Drought condition occurs at least every three years in India. India is one among the most vulnerable drought prone countries in the world. The economic impacts resulting from extreme environmental events and disasters are huge as a result of disruption in many economic activities. The focus of this paper is to develop a comprehensive understanding about the distributional impacts of disaster, especially impact of drought on agricultural production and income through a panel study (drought year and one year after the drought) in Raikhel village, Maharashtra, India. The major findings of the study indicate that cultivating area as well as the number of cultivating households reduced after the drought, indicating a shift in the livelihood- households moved from agriculture to non-agriculture. Decline in the gross cropped area and production of various crops depended on the negative income from these crops in the previous agriculture season. All the landholding categories of households except landlords had negative income in the drought year and also the income disparities between the households were higher in that year. In the drought year, the cost of cultivation was higher for all the landholding categories due to the increased cost for irrigation and input cost. In the drought year, agriculture products (50 per cent of the total products) were used for household consumption rather than selling in the market. It is evident from the study that livelihood which was based on natural resources became less attractive to the people to due to the risk involved in it and people were moving to less risk livelihood for their sustenance.

Keywords: climate change, drought, agriculture economics, disaster impact

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Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Marilei Amadeu Sabino

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Idiomatic expressions are linguistic phraseologisms present in natural languages. Known to be metaphorical linguistic combinations, a good majority of them provide elements that reveal important cultural aspects of their linguistic community through their metaphors. With the advent of Cognitive Linguistics (more specifically of Cognitive Semantics), the metaphor ceased to be related to poetic language and rhetorical embellishment and came to be seen as part of simple everyday language, reflecting the way human beings think, act and conceive reality, i. e., a fundamental mechanism of human conceptualizations of the world. In this sense, it came to be conceived as an inevitable mechanism for representing the nature of thought and language. The speakers, in conceptualizing reality, often use metaphorically parts of the body in expressions known as somatic. Several conceptual metaphors appear to be potentially universal or near-universal, because people across the world share certain bodily experiences. In these terms, many linguistic metaphors may be identical or very similar in several languages. These similarities, according to the Theory of Conceptual Metaphor, derive from universal aspects of the human body. Thus, this research aims to investigate the nature of some metaphors underlying somatic idiomatic expressions of Portuguese, Italian and English languages, establishing a pattern of similarities and differences among them from a trilingual perspective. The analysis shows that much of the studied expressions are really structurally, semantically and metaphorically identical or similar in the three languages. These findings incite relevant discussions concerning mother and foreign language learning and aim to contribute to the teaching of phraseological Lexicon as well as to materials development in mono and multilingual perspectives.

Keywords: idiomatic expressions, materials development, metaphors, phraseological lexicon, teaching and learning

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Authors: Tuba Sari

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One of the major transformations caused by the industrial revolution, technological developments and globalization is undoubtedly acceleration of urbanization process. Globalization, in particular, is one of the major factors that trigger this transformation. In this context, as a result of the global metropolitan city system, multifunctional rising structure forms are becoming undeniable fact of the world’s leading metropolises as the manifestation of prestige and power with different life choices, easy accessibility to services related to the era of technology. The scope of research deals with five different urban centers in İstanbul where high-rise housing is increasing dramatically after 2000’s. Therefore, the research regards multi-centered urban residential pattern being created by high-rise housing structures in the city. The methodology of the research is based on two main issue, one of them is related to sampling method of high-rise housing projects in İstanbul, while the other method of the research is based on the model of Semantics. In the framework of research hypothesis, it is aimed to prove that the character of vertical intensive structuring in Istanbul is based on seeking of different forms and images in the expressive quality, considering the production of existing high-rise buildings in residential areas in recent years. In respect to rising discourse of 'World City' in the globalizing world, it is very important to state the place of Istanbul in other developing world metropolises. In the perspective of 'World City' discourse, Istanbul has different projects concerning with globalization, international finance companies, cultural activities, mega projects, etc. In brief, the aim of this research is examining transformation forms of high-rise housing development in Istanbul within the frame of developing world cities, searching and analyzing discourse and image related to these projects.

Keywords: globalization, high-rise, housing, image

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

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Authors: Hongyun Li, Zhibin Jiang

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The travel of passengers in the urban rail transit network is influenced by changes in network structure and operational status, and the response of individual travel preferences to these changes also varies. Firstly, the influence of the suspension of urban rail transit line sections on passenger travel along the line is analyzed. Secondly, passenger travel trajectories containing multi-dimensional semantics are described based on network UD data. Next, passenger panel data based on spatio-temporal sequences is constructed to achieve frequent passenger clustering. Then, the Graph Convolutional Network (GCN) is used to model and identify the changes in travel modes of different types of frequent passengers. Finally, taking Shanghai Metro Line 11 as an example, the travel behavior patterns of frequent passengers after the Huaqiao section shutdown during the COVID-19 epidemic are analyzed. The results showed that after the section shutdown, most passengers would transfer to the nearest Anting station for boarding, while some passengers would transfer to other stations for boarding or cancel their travels directly. Among the passengers who transferred to Anting station for boarding, most of passengers maintained the original normalized travel mode, a small number of passengers waited for a few days before transferring to Anting station for boarding, and only a few number of passengers stopped traveling at Anting station or transferred to other stations after a few days of boarding on Anting station. The results can provide a basis for understanding urban rail transit passenger travel patterns and improving the accuracy of passenger flow prediction in abnormal operation scenarios.

Keywords: urban rail transit, section shutdown, frequent passenger, travel behavior pattern

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Authors: Alexander K. Guo

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PM2.5 poses a large threat to people’s health and the environment and is an issue of large concern in Beijing, brought to the attention of the government by the media. In addition, both the United States Embassy in Beijing and the government of China have increased monitoring of PM2.5 in recent years, and have made real-time data available to the public. This report utilizes hourly historical data (2008-2016) from the U.S. Embassy in Beijing for the first time. The first objective was to attempt to fit probability distributions to the data to better predict a number of days exceeding the standard, and the second was to uncover any yearly, seasonal, monthly, daily, and hourly patterns and trends that may arise to better understand of air control policy. In these data, 66,650 hours and 2687 days provided valid data. Lognormal, gamma, and Weibull distributions were fit to the data through an estimation of parameters. The Chi-squared test was employed to compare the actual data with the fitted distributions. The data were used to uncover trends, patterns, and improvements in PM2.5 concentration over the period of time with valid data in addition to specific periods of time that received large amounts of media attention, analyzed to gain a better understanding of causes of air pollution. The data show a clear indication that Beijing’s air quality is unhealthy, with an average of 94.07µg/m3 across all 66,650 hours with valid data. It was found that no distribution fit the entire dataset of all 2687 days well, but each of the three above distribution types was optimal in at least one of the yearly data sets, with the lognormal distribution found to fit recent years better. An improvement in air quality beginning in 2014 was discovered, with the first five months of 2016 reporting an average PM2.5 concentration that is 23.8% lower than the average of the same period in all years, perhaps the result of various new pollution-control policies. It was also found that the winter and fall months contained more days in both good and extremely polluted categories, leading to a higher average but a comparable median in these months. Additionally, the evening hours, especially in the winter, reported much higher PM2.5 concentrations than the afternoon hours, possibly due to the prohibition of trucks in the city in the daytime and the increased use of coal for heating in the colder months when residents are home in the evening. Lastly, through analysis of special intervals that attracted media attention for either unnaturally good or bad air quality, the government’s temporary pollution control measures, such as more intensive road-space rationing and factory closures, are shown to be effective. In summary, air quality in Beijing is improving steadily and do follow standard probability distributions to an extent, but still needs improvement. Analysis will be updated when new data become available.

Keywords: Beijing, distribution, patterns, pm2.5, trends

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

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Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

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Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

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Authors: Hanan Eltayeb, Reem Al Refaie

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To be able to connect and relate to shows spoken in a foreign language, advanced learners must understand not only linguistics inferences but also cultural, metacognitive, and pragmatic connotations in colloquial Egyptian TV series. These connotations are needed to both understand the different facets of the dramas put before them, and they’re also consistently grown and formulated through watching these shows. The inferences have become a staple in the Egyptian colloquial culture over the years, making their way into day-to-day conversations as Egyptians use them to speak, relate, joke, and connect with each other, without having known one another from previous times. As for advanced learners, they need to understand these inferences not only to watch these shows, but also to be able to converse with Egyptians on a level that surpasses the formal, or standard. When faced with some of the somewhat recent shows on the Egyptian screens, learners faced challenges in understanding pragmatics, cultural, and religious background of the target language and consequently not able to interact effectively with a native speaker in real-life situations. This study aims to enhance the linguistic and cultural proficiency of learners through studying two genres of TV Colloquial Egyptian series. Study samples derived from two recent comedian and social Egyptian series ('The Seventh Neighbor' سابع جار, and 'Nelly and Sherihan' نيللي و شريهان). When learners watch such series, they are usually faced with a problem understanding inferences that have to do with social, religious, and political events that are addressed in the series. Using discourse analysis of the sematic, semantic, pragmatic, cultural, and linguistic characteristics of the target language, some major deductions were highlighted and repeated, showing a pattern in both. The research paper concludes that there are many sets of lingual and para-lingual phrases, idioms, and proverbs to be acquired and used effectively by teaching these series. The strategies adopted in the study can be applied to different types of media, like movies, TV shows, and even cartoons, to enhance student proficiency.

Keywords: Egyptian series, culture, linguistic competence, pragmatics, semantics, social

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Authors: Geanderson Eduardo Ambrósio, Dênis Antônio Da Cunha, Marcel Viana Pires

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Historically, human development has been based on economic gains associated with intensive energy activities, which often are exhaustive in the emission of Greenhouse Gases (GHGs). It requires the establishment of targets for mitigation of GHGs in order to disassociate the human development from emissions and prevent further climate change. Brazil presents itself as one of the most GHGs emitters and it is of critical importance to discuss such reductions in intra-national framework with the objective of distributional equity to explore its full mitigation potential without compromising the development of less developed societies. This research displays some incipient considerations about which Brazil’s micro-regions should reduce, when the reductions should be initiated and what its magnitude should be. We started with the methodological assumption that human development and GHGs emissions arise in the future as their behavior was observed in the past. Furthermore, we assume that once a micro-region became developed, it is able to maintain gains in human development without the need of keep growing GHGs emissions rates. The human development index and the carbon dioxide equivalent emissions (CO2e) were extrapolated to the year 2050, which allowed us to calculate when the micro-regions will become developed and the mass of GHG’s emitted. The results indicate that Brazil must throw 300 GT CO2e in the atmosphere between 2011 and 2050, of which only 50 GT will be issued by micro-regions before it’s develop and 250 GT will be released after development. We also determined national mitigation targets and structured reduction schemes where only the developed micro-regions would be required to reduce. The micro-region of São Paulo, the most developed of the country, should be also the one that reduces emissions at most, emitting, in 2050, 90% less than the value observed in 2010. On the other hand, less developed micro-regions will be responsible for less impactful reductions, i.e. Vale do Ipanema will issue in 2050 only 10% below the value observed in 2010. Such methodological assumption would lead the country to issue, in 2050, 56.5% lower than that observed in 2010, so that the cumulative emissions between 2011 and 2050 would reduce by 130 GT CO2e over the initial projection. The fact of associating the magnitude of the reductions to the level of human development of the micro-regions encourages the adoption of policies that favor both variables as the governmental planner will have to deal with both the increasing demand for higher standards of living and with the increasing magnitude of reducing emissions. However, if economic agents do not act proactively in local and national level, the country is closer to the scenario in which emits more than the one in which mitigates emissions. The research highlighted the importance of considering the heterogeneity in determining individual mitigation targets and also ratified the theoretical and methodological feasibility to allocate larger share of contribution for those who historically emitted more. It is understood that the proposals and discussions presented should be considered in mitigation policy formulation in Brazil regardless of the adopted reduction target.

Keywords: greenhouse gases, human development, mitigation, intensive energy activities

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: D. W. M. S. Samarathunga, Isuru Dharmarathne

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In aphasia, various levels of symbolic language processing (semantics) are affected. It is shown that Persons with Aphasia (PWA) often experience more problems comprehending some categories of words than others. The study aimed to determine lexical semantic deficits seen in Auditory Comprehension (AC) and to describe lexical-semantic deficits across six selected word categories. Thirteen (n =13) persons diagnosed with post-stroke aphasia (PSA) were recruited to perform an AC task. Foods, objects, clothes, vehicles, body parts and animals were selected as the six categories. As the test stimuli, black and white line drawings were adapted from a picture set developed for semantic studies by Snodgrass and Vanderwart. A pilot study was conducted with five (n=5) healthy nonbrain damaged Sinhala speaking adults to decide familiarity and applicability of the test material. In the main study, participants were scored based on the accuracy and number of errors shown. The results indicate similar trends of lexical semantic deficits identified in the literature confirming ‘animals’ to be the easiest category to comprehend. Mann-Whitney U test was performed to determine the association between the selected variables and the participants’ performance on AC task. No statistical significance was found between the errors and the type of aphasia reflecting similar patterns described in aphasia literature in other languages. The current study indicates the presence of selectivity of lexical semantic deficits in AC and a hierarchy was developed based on the complexity of the categories to comprehend by Sinhala speaking PWA, which might be clinically beneficial when improving language skills of Sinhala speaking persons with post-stroke aphasia. However, further studies on aphasia should be conducted with larger samples for a longer period to study deficits in Sinhala and other Sri Lankan languages (Tamil and Malay).

Keywords: aphasia, auditory comprehension, selective lexical-semantic deficits, semantic categories

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Authors: Ayon Mukherjee

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Covariate-adjusted response-adaptive (CARA) designs use the available responses to skew the treatment allocation in a clinical trial in towards treatment found at an interim stage to be best for a given patient's covariate profile. Extensive research has been done on various aspects of CARA designs with the patient responses assumed to follow a parametric model. However, ranges of application for such designs are limited in real-life clinical trials where the responses infrequently fit a certain parametric form. On the other hand, robust estimates for the covariate-adjusted treatment effects are obtained from the parametric assumption. To balance these two requirements, designs are developed which are free from distributional assumptions about the survival responses, relying only on the assumption of proportional hazards for the two treatment arms. The proposed designs are developed by deriving two types of optimum allocation designs, and also by using a distribution function to link the past allocation, covariate and response histories to the present allocation. The optimal designs are based on biased coin procedures, with a bias towards the better treatment arm. These are the doubly-adaptive biased coin design (DBCD) and the efficient randomized adaptive design (ERADE). The treatment allocation proportions for these designs converge to the expected target values, which are functions of the Cox regression coefficients that are estimated sequentially. These expected target values are derived based on constrained optimization problems and are updated as information accrues with sequential arrival of patients. The design based on the link function is derived using the distribution function of a probit model whose parameters are adjusted based on the covariate profile of the incoming patient. To apply such designs, the treatment allocation probabilities are sequentially modified based on the treatment allocation history, response history, previous patients’ covariates and also the covariates of the incoming patient. Given these information, an expression is obtained for the conditional probability of a patient allocation to a treatment arm. Based on simulation studies, it is found that the ERADE is preferable to the DBCD when the main aim is to minimize the variance of the observed allocation proportion and to maximize the power of the Wald test for a treatment difference. However, the former procedure being discrete tends to be slower in converging towards the expected target allocation proportion. The link function based design achieves the highest skewness of patient allocation to the best treatment arm and thus ethically is the best design. Other comparative merits of the proposed designs have been highlighted and their preferred areas of application are discussed. It is concluded that the proposed CARA designs can be considered as suitable alternatives to the traditional balanced randomization designs in survival trials in terms of the power of the Wald test, provided that response data are available during the recruitment phase of the trial to enable adaptations to the designs. Moreover, the proposed designs enable more patients to get treated with the better treatment during the trial thus making the designs more ethically attractive to the patients. An existing clinical trial has been redesigned using these methods.

Keywords: censored response, Cox regression, efficiency, ethics, optimal allocation, power, variability

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Authors: Bahareh Yousefian, Laurel Smith Stvan

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Linguistic structures have two facades: form and meaning. These structures could have either literal meaning or figurative meaning (although it could also depend on the context in which that structure appears). The literal meaning is understandable more easily, but for the figurative meaning, a word or concept is understood from a different word or concept. In linguistic structures with a figurative meaning, it’s more difficult to relate their forms to the meanings than structures with literal meaning. In these cases, the relationship between form and figurative meaning could be studied from different perspectives. Various linguists have been curious about what happens in someone’s mind to understand figurative meaning through the forms; they have used different perspectives and theories to explain this process. It has been studied through cognitive linguistics as well, in which mind and mental activities are really important. In this viewpoint, meaning (in other words, conceptualization) is considered a mental process. In this descriptive-analytic study, 20 Persian compound nouns with figurative meanings have been collected from the Persian-language Moeen Encyclopedic Dictionary and other sources. Examples include [“Sofreh Xaneh”] (traditional restaurant) and [“Dast Yar”] (Assistant). These were studied in a cognitive semantics framework using “Conceptual Blending Theory” which hasn’t been tested on Persian compound nouns before. It was noted that “Conceptual Blending Theory” could lead to the process of understanding the figurative meanings of Persian compound nouns. Many cognitive linguists believe that “Conceptual Blending” is not only a linguistic theory but it’s also a basic human cognitive ability that plays important roles in thought, imagination, and even everyday life as well (though unconsciously). The ability to use mental spaces and conceptual blending (which is exclusive to humankind) is such a basic but unconscious ability that we are unaware of its existence and importance. What differentiates Conceptual Blending Theory from other ways of understanding figurative meaning, are arising new semantic aspects (emergent structure) that lead to a more comprehensive and precise meaning. In this study, it was found that Conceptual Blending Theory could explain reaching the figurative meanings of Persian compound nouns from their forms, such as [talkative for compound word of “Bolbol + Zabani” (nightingale + tongue)] and [wage for compound word of “Dast + Ranj” (hand + suffering)].

Keywords: cognitive linguistics, conceptual blending, figurative meaning, Persian compound nouns

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Noury Bakrim

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Formalization is indeed a foundational Mathematical Linguistics as demonstrated by the pioneering works. While dialoguing with this frame, we nonetheless propone, in our approach of language as a real object, a mathematical linguistics/biosemiotics defined as a dialectical synthesis between induction and computational deduction. Therefore, relying on the parametric interaction of cycles, rules, and features giving way to a sub-hypothetic biological point of view, we first hypothesize a factorial equation as an explanatory principle within Category Mathematics of the Ergobrain: our computation proposal of Universal Grammar rules per cycle or a scalar determination (multiplying right/left columns of the determinant matrix and right/left columns of the logarithmic matrix) of the transformable matrix for rule addition/deletion and cycles within representational mapping/cycle heredity basing on the factorial example, being the logarithmic exponent or power of rule deletion/addition. It enables us to propone an extension of minimalist merge/label notions to a Language Merge (as a computing principle) within cycle recursion relying on combinatorial mapping of rules hierarchies on external Entax of the Event Sequence. Therefore, to define combinatorial maps as language merge of features and combinatorial hierarchical restrictions (governing, commanding, and other rules), we secondly hypothesize from our results feature/hierarchy exponentiation on graph representation deriving from Gromov's Symbolic Dynamics where combinatorial vertices from Fe are set to combinatorial vertices of Hie and edges from Fe to Hie such as for all combinatorial group, there are restriction maps representing different derivational levels that are subgraphs: the intersection on I defines pullbacks and deletion rules (under restriction maps) then under disjunction edges H such that for the combinatorial map P belonging to Hie exponentiation by intersection there are pullbacks and projections that are equal to restriction maps RM₁ and RM₂. The model will draw on experimental biomathematics as well as structural frames with focus on Amazigh and English (cases from phonology/micro-semantics, Syntax) shift from Structure to event (especially Amazigh formant principle resolving its morphological heterogeneity).

Keywords: rule/cycle addition/deletion, bio-mathematical methodology, general merge calculation, feature exponentiation, combinatorial maps, event sequence

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Authors: Taghrid Asfar, Olusanya J. Oluwole, Michael Schmidt, Alejandra Casas, Zoran Bursac, Wasim Maziak.

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Waterpipe (WP) smoking (a.k.a. hookah) has increased dramatically in the US mainly due to the misperception that it is safer than cigarette smoking. Mounting evidence show that WP smoking is addictive and harmful. Health warning labels (HWLs) are effective in communicating smoking-related risks. Currently, the FDA requires that WP tobacco packages have a textual HWL about nicotine. While this represents a good step, it is inadequate given the established harm of WP smoking beyond addiction and the superior performance of pictorial HWLs over text-only ones. We developed 24 WP pictorial HWLs in a Delphi study among international expert panel. HWLs were grouped into 6 themes: addiction, harm compared to cigarettes, harm to others, health effects, quitting, and specific harms. This study aims to compare the effect of the pictorial HWLs compared to the FDA HWL, and 2) the effect of pictorial HWLs between the 6 themes. A 2x7 between/within subject online factorial experimental study was conducted among a national convenience sample of 300 (50% current WP smokers; 50% nonsmokers) US adults (females 71.1%; mean age of 31.1±3.41 years) in March 2022. The first factor varied WP smoking status (smokers, nonsmokers). The second factor varied the HWL theme and type (text, pictorial). Participants were randomized to view and rate 7 HWLs: 1 FDA text HWL (control) and 6 HWLs, one from each of the 6 themes, all presented in random order. HWLs were rated based on the message impact framework into five categories: attention, reaction (believability, relevance, fear), perceived effectiveness, intentions to quit WP among current smokers, and intention to not initiate WP among nonsmokers. measures were assessed on a 5-point Likert scale (1=not at all to 5=very much) for attention and reaction and on a 7-point Likert scale (1=not at all to 7=very much) for the perceived effectiveness and intentions to quit or not initiate WP smoking. Means and SDs of outcome measures for each HWL type and theme were calculated. Planned comparisons using Friedman test followed by pairwise Wilcoxon signed-rank test for multiple comparisons were used to examine distributional differences of outcomes between the HWL type and themes. Approximately 74.4 % of participants were non-Hispanic Whites, 68.4% had college degrees, and 41.5% were under the poverty level. Participants reported starting WTS on average at 20.3±8.19 years. Compared with the FDA text HWL, pictorial HWLs elicited higher attention (p<0.0001), fear (p<0.0001), harm perception (p<0.0003), perceived effectiveness (p<0.0001), and intentions to quit (p=0.0014) and not initiate WP smoking (p<0.0003). HWLs in theme 3 (harm to others) achieved the highest rating in attention (4.14±1), believability (4.15±0.95), overall perceived effectiveness (7.60±2.35), harm perception (7.53±2.43), and intentions to quit (7.35±2.57). HWLs in theme 2 (WP harm compared to cigarettes) achieved the highest rating in discouraging WP smoking initiation (7.32±2.54). Pictorial HWLs were superior to the FDA text-only for several communication outcomes. Pictorial HWLs related to WP harm to others and WP harm compared to cigarette are promising. These findings provide strong evidence for the potential implementation of WP-specific pictorial HWLs.

Keywords: health communication, waterpipe smoking, factorial experiment, reaction, harm perception, tobacco regulations

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Authors: Helena Maragou

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Introducing Toni Morrison’s fiction to a classroom overseas entails a significant pedagogical investment, from monitoring students’ uncertain journey through Morrison’s shifty semantics to filling in the gaps of cultural knowledge and understanding for the students to be able to relate text to context. A rewarding process, as Morrison’s works present a tremendous opportunity for transnational dialogue, an opportunity that hinges upon Toni Morrison’s bringing to the fore the untold and unspeakable lives of racial ‘Others’, but also, crucially, upon her broader critique of Western ideological hegemony. This critique is a fundamental aspect of Toni Morrison’s politics and one that appeals to young readers of Toni Morrison in Greece at a time when the questioning of institutions and ideological traditions is precipitated by regional and global change. It is more or less self-evident that to help a class of international students get aboard a Morrison novel, an instructor should begin by providing them with cultural context. These days, students’ exposure to Hollywood representations of the African American past and present, as well as the use of documentaries, photography, music videos, etc., as supplementary class material, provide a starting point, a workable historical and cultural framework for textual comprehension. The true challenge, however, lies ahead: it is one thing for students to intellectually grasp the historical hardships and traumas of Morrison’s characters and to even engage in aesthetic appreciation of Morrison’s writing; quite another to relate to her works as articulations of experiences akin to their own. The great challenge, then, is in facilitating students’ discovery of the universal Morrison, the author who speaks across cultures while voicing the untold tales of her own people; this process of discovery entails, on a pedagogical level, that students be guided through the works’ historical context, to plunge into the intricacies of Morrison’s discourse, itself an elaborate linguistic booby trap, so as to be finally brought to reconsider their own historical experiences using the lens of Morrison’s fiction. The paper will be based on experience of teaching a Toni Morrison seminar to a class of Greek students at the American College of Greece and will draw from students’ exposure and responses to Toni Morrison’s “Nobel Prize Lecture,” as well as her novels Song of Solomon and Home.

Keywords: toni morrison, international classroom, pedagogy, African American literature

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Authors: Yaqing Hu

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This paper puts forward a syntactic analysis involving multidominance and rightward movement in Chinese bi-comparatives, as in 'Yuehan bi Mali gao (John is taller than Mary).' It is argued here that the predicate of comparison is a shared constituent in two small clauses, namely one for the target and one for the standard; and then it moves rightward to form a degree phrase with the comparative morpheme. This proposal comes from four aspects. First, the example above can also be expressed in this way, 'A: Yuehan he Mali, shui gao? (John and Mary, who is taller?) B: Yuehan gao./Yuehan geng gao. (John is taller).' This shows that the gradable adjective is predicated of the target. In addition, according to a constraint on Chinese bi-comparatives, namely the target and the standard must be arguments of the predicate simultaneously, it is not unreasonable to assume that the gradable adjective may also be predicated of the standard. Second, subcomparatives are totally disallowed in Chinese, as in '*zhe-zhang zhuozi bi zhe-zhang yizi kuan chang. (This table is longer than this chair is wide.)' In order to save it from ungrammaticality, the target and the standard should be compared along the same dimension denoted by the gradable adjective. It may follow that in Chinese comparatives, having equal roles in the same eventuality, the target and the standard bear the same thematic relationship with the predicate of comparison. Third, verb-copy can appear in Chinese bi-comparatives, as in 'Yuehan qi ma bi Mali qi ma qi de kuai. (John rides horses faster than Mary does.)' The predicate qi seems to form a small clause with both the target and the standard. This might be supporting evidence that both the target and the standard share the predicate of comparison. Fourth, Chinese comparatives do have comparative morphemes, as in 'Yuehan bi Mali geng gao. (John is taller than Mary)', which is semantically equivalent to the first example above. Thus, it follows that one feature of Chinese comparative morphemes is that they can remain overt or covert in the syntax, which will not affect semantics. This further shows that comparative morphemes in bi-comparatives may not be able to saturate the degree argument denoted by the predicate of comparison due to its optionality in the structure. These four aspects present a challenge to the Direct Analysis used in Chinese comparatives since this approach would presume that the target and the standard somehow show independency with the predicate in the syntax. Meanwhile, this study also rejects the previous analysis of multidomiance in bi-comparatives in which the degree phrase comprised of the comparative morpheme and the gradable adjective may be shared by the standard when the comparative morpheme is covert. This syntactic analysis proposed in this study will therefore offer a different perspective of how to treat degree phrase in Chinese comparatives and may offer evidence to argue whether there is degree phrase movement in bi-comparatives as in its English counterparts.

Keywords: Chinese comparatives, degree phrase, movement, multidominance, syntactic analysis

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Authors: Antonio Piga

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The study of language strategies in financial and corporate discourse has always been vital for understanding how companies manage to communicate effectively with a wider customer base and offers new perspectives on how companies interact with key stakeholders, not only to convey transparency and an image of trustworthiness, but also to create affiliation and attract investment. In the light of Systemic Functional Linguistics, the purpose of this study is to examine and analyse the annual reports of Asian and Western joint-stock companies involved in oil refining and power generation from the point of view of the functions and frequency of grammatical metaphors. More specifically, grammatical metaphor - through the lens of Critical Discourse Analysis (CDA) - is used as a theoretical tool for analysing a synchronic cross-cultural study of the communicative strategies adopted by Asian and Western companies to communicate social and environmental sustainability and showcase their ethical values, performance and competitiveness to local and global communities and key stakeholders. According to Systemic Functional Linguistics, grammatical metaphor can be divided into two broad areas: ideational and interpersonal. This study focuses on the first type, ideational grammatical metaphor (IGM), which includes de-adjectival and de-verbal nominalisation. The dominant and more effective grammatical tropes used by Asian and Western corporations in their annual reports were examined from both a qualitative and quantitative perspective. The aim was to categorise and explain how ideational grammatical metaphor is constructed cross-culturally and presented through structural language patterns involving re-mapping between semantics and lexico-grammatical features. The results show that although there seem to be more differences than similarities in terms of the categorisation of the ideational grammatical metaphors conceptualised in the two case studies analysed, there are more similarities than differences in terms of the occurrence, the congruence of process types and the role and function of IGM. Through the immediacy and essentialism of compacting and condensing information, IGM seems to be an important linguistic strategy adopted in the rhetoric of corporate annual reports, contributing to the ideologies and actions of companies to report and promote efficiency, profit and social and environmental sustainability, thus advocating the engagement and investment of key stakeholders.

Keywords: corporate annual reports, cross-cultural perspective, ideational grammatical metaphor, rhetoric, systemic functional linguistics

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Authors: Nataliya L. Ogurechnikova

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The paper aims to clarify the function of articles in the English speech and specify their place and role in the English language, taking into account the use of articles for delimitation of speech. A focus of the paper is the use of the definite and the indefinite articles with different types of noun phrases which comprise either one noun with or without attributes, such as the King, the Queen, the Lion, the Unicorn, a dimple, a smile, a new language, an unknown dialect, or several nouns with or without attributes, such as the King and Queen of Hearts, the Lion and Unicorn, a dimple or smile, a completely isolated language or dialect. It is stated that the function of delimitation is related to perception: the number of speech units in a text correlates with the way the speaker perceives and segments the denotation. The two following combinations of words the house and garden and the house and the garden contain different numbers of speech units, one and two respectively, and reveal two different perception modes which correspond to the use of the definite article in the examples given. Thus, the function of delimitation is twofold, it is related to perception and cognition, on the one hand, and, on the other hand, to grammar, if the subject of grammar is the structure of speech. Analysis of speech units in the paper is not limited by noun phrases and is amplified by discussion of peripheral phenomena which are nevertheless important because they enable to qualify articles as a syntactic phenomenon whereas they are not infrequently described in terms of noun morphology. With this regard attention is given to the history of linguistic studies, specifically to the description of English articles by Niels Haislund, a disciple of Otto Jespersen. A discrepancy is noted between the initial plan of Jespersen who intended to describe articles as a syntactic phenomenon in ‘A Modern English Grammar on Historical Principles’ and the interpretation of articles in terms of noun morphology, finally given by Haislund. Another issue of the paper is correlation between description and denotation, being a traditional aspect of linguistic studies focused on articles. An overview of relevant studies, given in the paper, goes back to the works of G. Frege, which gave rise to a series of scientific works where the meaning of articles was described within the scope of logical semantics. Correlation between denotation and description is treated in the paper as the meaning of article, i.e. a component in its semantic structure, which differs from the function of delimitation and is similar to the meaning of other quantifiers. The paper further explains why the relation between description and denotation, i.e. the meaning of English article, is irrelevant for noun morphology and has nothing to do with nominal categories of the English language.

Keywords: delimitation of speech, denotation, description, perception, speech units, syntax

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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