Search results for: multi granular linguistic contexts

Authors: Austin Vander Wel, Katherin Vargas Henao

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Washington, DC, is a city in which Spanish, along with several other minority languages, is prevalent not only among tourists but also those living within city limits. In response to this linguistic diversity and DC’s adoption of the Language Access Act in 2004, the Washington Metropolitan Area Transit Authority (WMATA) committed to addressing the need for equal linguistic representation and established a five-step plan to provide the best multilingual information possible for public transportation users. The current study, however, strongly suggests that this de jure policy does not align with the reality of Spanish’s representation on DC public transportation–although perhaps doing so in an unexpected way. In order to investigate Spanish’s de facto representation and how it contrasts with de jure policy, this study implements a linguistic landscapes methodology that takes critical language-policy as its theoretical framework (Tollefson, 2005). Specifically concerning de facto representation, it focuses on the discrepancies between digital spaces and the actual physical spaces through which users travel. These digital vs. in situ conditions are further analyzed by separately addressing aural and visual modalities. In digital spaces, data was collected from WMATA’s website (visual) and their bilingual hotline (aural). For in situ spaces, both bus and metro areas of DC public transportation were explored, with signs comprising the visual modality and recordings, driver announcements, and interactions with metro kiosk workers comprising the aural modality. While digital spaces were considered to successfully fulfill WMATA’s commitment to representing Spanish as outlined in the de jure policy, physical spaces show a large discrepancy between what is said and what is done, particularly regarding the bus system, in addition to the aural modality overall. These discrepancies in situ spaces place Spanish speakers at a clear disadvantage, demanding additional resources and knowledge on the part of residents with limited or no English proficiency in order to have equal access to this public good. Based on our critical language-policy analysis, while Spanish is represented as a right in the de jure policy, its implementation in situ clearly portrays Spanish as a problem since those seeking bilingual information can not expect it to be present when and where they need it most (Ruíz, 1984; Tollefson, 2005). This study concludes with practical, data-based steps to improve the current situation facing DC’s public transportation context and serves as a model for responding to inadequate enactment of de jure policy in other language policy settings.

Keywords: Urban landscape, language access, critical-language policy, spanish, public transportation

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multi-criteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development shows PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: gis, site suitability analysis, tidal current energy resource assessment, webgis

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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Authors: Pietro P. Falciglia, Erica Gagliano, Vincenza Brancato, Alfio Catalfo, Guglielmo Finocchiaro, Guido De Guidi, Stefano Romano, Paolo Roccaro, Federico G. A. Vagliasindi

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Cesium-137 (¹³⁷Cs) is a major radionuclide in spent nuclear fuel processing, and it represents the most important cause of contamination related to nuclear accidents. Cesium-137 has long-term radiological effects representing a major concern for the human health. Several physico-chemical methods have been proposed for ¹³⁷Cs removal from impacted water: ion-exchange, adsorption, chemical precipitation, membrane process, coagulation, and electrochemical. However, these methods can be limited by ionic selectivity and efficiency, or they present very restricted full-scale application due to equipment and chemical high costs. On the other hand, adsorption is considered a more cost-effective solution, and activated carbons (ACs) are known as a low-cost and effective adsorbent for a wide range of pollutants among which radionuclides. However, adsorption of Cs onto ACs has been investigated in very few and not exhaustive studies. In addition, exhausted activated carbons are generally discarded in landfill, that is not an eco-friendly and economic solution. Consequently, the regeneration of exhausted ACs must be considered a preferable choice. Several alternatives, including conventional thermal-, solvent-, biological- and electrochemical-regeneration, are available but are affected by several economic or environmental concerns. Microwave (MW) irradiation has been widely used in industrial and environmental applications and it has attracted many attentions to regenerating activated carbons. The growing interest in MW irradiation is based on the passive ability of the irradiated medium to convert a low power irradiation energy into a rapid and large temperature increase if the media presents good dielectric features. ACs are excellent MW-absorbers, with a high mechanical strength and a good resistance towards heating process. This work investigates the feasibility of MW irradiation for the regeneration of Cs-exhausted ACs. Adsorption batch experiments were carried out using commercially available granular activated carbon (GAC), then Cs-saturated AC samples were treated using a controllable bench-scale 2.45-GHz MW oven and investigating different adsorption-regeneration cycles. The regeneration efficiency (RE), weight loss percentage, and textural properties of the AC samples during the adsorption-regeneration cycles were also assessed. Main results demonstrated a relatively low adsorption capacity for Cs, although the feasibility of ACs was strictly linked to their dielectric nature, which allows a very efficient thermal regeneration by MW irradiation. The weight loss percentage was found less than 2%, and an increase in RE after three cycles was also observed. Furthermore, MW regeneration preserved the pore structure of the regenerated ACs. For a deeper exploration of the full-scale applicability of MW regeneration, further investigations on more adsorption-regeneration cycles or using fixed-bed columns are required.

Keywords: adsorption mechanisms, cesium, granular activated carbons, microwave regeneration

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Authors: Merih Welay Welesilassie, Marianne Nikolov

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Research into second and foreign language (L2) acquisitions has demonstrated that L2 anxiety, perceived proficiency, and L2 willingness to communicate (L2WTC) profoundly impact language learning outcomes. However, the complex interplay between these variables has yet to be fully explored, as these factors are dynamic and context-specific and can vary across different learners and learning environments. This study, therefore, utilized a cross-sectional quantitative survey research design to scrutinise the causal relationships between L2 anxiety, English proficiency, and L2WTC of 609 Ethiopian preparatory school students. The model for the L2WTC, both inside and outside the classroom, has been expanded to include an additional sub-scale known as the L2WTC in a digital setting. Moreover, in contrast to the commonly recognised debilitative-focused L2 anxiety, the construct of L2 anxiety has been divided into facilitative and debilitative anxiety. This method allows to measure not only the presence or absence of anxiety but also evaluate if anxiety helps or hinders the L2 learning experience. A self-assessment proficiency measure was also developed specifically for Ethiopian high school students. The study treated facilitative and debilitative anxiety as independent variables while considering self-assessed English proficiency and L2WTC in the classroom, outside the classroom, and in digital settings as dependent variables. Additionally, self-assessed English proficiency was used as an independent variable to predict L2WTC in these three settings. The proposed model, including these variables, was tested using structural equation modelling (SEM). According to the descriptive analysis, the mean scores of L2WTC in the three settings were generally low, ranging from 2.30 to 2.84. Debilitative anxiety casts a shadow on the positive aspects of anxiety. Self-assessed English proficiency was also too low. According to SEM, debilitative anxiety displayed a statistically significant negative impact on L2WTC inside the classroom, outside the classroom, in digital settings, and in self-assessed levels of English proficiency. In contrast, facilitative anxiety was found to positively contribute to L2WTC outside the classroom, in digital settings, and in self-assessed English proficiency. Self-assessed English proficiency made a statistically significant and positive contribution to L2WTC within the classroom, outside the classroom, and in digital contexts. L2WTC inside the classroom was found to positively contribute to L2WTC outside the classrooms and in digital contexts. The findings were systematically compared with existing studies, and the pedagogical implications, limitations, and potential avenues for future research were elucidated. The outcomes of the study have the potential to significantly contribute to the advancement of theoretical and empirical knowledge about improving English education, learning, and communication not only in Ethiopia but also in similar EFL contexts, thereby providing valuable insights for educators, researchers, and policymakers.

Keywords: debilitative anxiety, facilitative anxiety, L2 willingness to communicate, self-assessed English proficiency

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Authors: Kishor Bhagwat, Gayatri Vyas

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Construction industry is earmarked with complex processes depending on the nature and scope of the project. In recent years, developments in this sector are remarkable and have resulted in both positive and negative impacts on the environment and human being. Sustainable construction can be looked upon as one of the solution to overcome the negative impacts since sustainable construction is a vast concept, which includes many parameters, and sometimes the use of multi-criteria decision making [MCDM] tools becomes necessary. The main objective of this study is to determine the weightage of sustainable building parameters with the help of MCDM tools. Questionnaire survey was conducted to examine the perspective of respondents on the importance of weights of the criterion, and the respondents were architects, green building consultants, and civil engineers. This paper presents an overview of research related to Indian and international green building rating systems and MCDM. The results depict that economy, environmental health, and safety, site selection, climatic condition, etc., are important parameters in sustainable construction.

Keywords: green building, sustainability, multi-criteria decision making method [MCDM], analytical hierarchy process [AHP], technique for order preference by similarity to an ideal solution [TOPSIS], entropy

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Authors: Samuel Ntsanwisi

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This study investigates the transformative role of Artificial Intelligence (AI) and Virtual Reality (VR) in the preservation of endangered African languages. The study is contextualized within the film and television industry, highlighting disparities in screen representation for certain languages in South Africa, underscoring the need for increased visibility and preservation efforts; with globalization and cultural shifts posing significant threats to linguistic diversity, this research explores approaches to language preservation. By leveraging AI technologies, such as speech recognition, translation, and adaptive learning applications, and integrating VR for immersive and interactive experiences, the study aims to create a framework for teaching and passing on endangered African languages. Through digital documentation, interactive language learning applications, storytelling, and community engagement, the research demonstrates how these technologies can empower communities to revitalize their linguistic heritage. This study employs a dual-method approach, combining a rigorous literature review to analyse existing research on the convergence of AI, VR, and language preservation with primary data collection through interviews and surveys with ten filmmakers. The literature review establishes a solid foundation for understanding the current landscape, while interviews with filmmakers provide crucial real-world insights, enriching the study's depth. This balanced methodology ensures a comprehensive exploration of the intersection between AI, VR, and language preservation, offering both theoretical insights and practical perspectives from industry professionals.

Keywords: language preservation, endangered languages, artificial intelligence, virtual reality, interactive learning

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Authors: Srushti Bhatt, M. B. Kiran

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Two-sided assembly line balancing problem is yet to be addressed simply to compete for the global market for manufacturers. The task assigned in an ordered sequence to get optimum performance of the system is known as assembly line balancing problem mainly classified as single and two sided. It is very challenging in manufacturing industries to balance two-sided assembly line, wherein the set of sequential workstations the task operations are performed in two sides of the line. The conflicting major objective in two-sided assembly line balancing problem is either to maximize /minimize the performance parameters. The present study emphases on combining different evolutionary algorithm; ant colony, Tabu search and petri net method; and compares their results of an algorithm for solving two-sided assembly line balancing problem. The concept of multi objective optimization of performance parameters is now a day adopted to make a decision involving more than one objective function to be simultaneously optimized. The optimum result can be expected among the selected methods using multi-objective optimization. The performance parameters considered in the present study are a number of workstation, slickness and smoothness index. The simulation of the assembly line balancing problem provides optimal results of classical and practical problems.

Keywords: Ant colony, petri net, tabu search, two sided ALBP

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Authors: Eleni C. Mazarakioti, Anastasios Zotos, Anna-Akrivi Thomatou, Efthimios Kokkotos, Achilleas Kontogeorgos, Athanasios Ladavos, Angelos Patakas

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“Gigantes Elefantes” is a particularly dynamic crop of giant beans cultivated in western Macedonia (Greece). This variety of large beans growing in this area and specifically in the regions of Prespes and Kastoria is a protected designation of origin (PDO) species with high nutritional quality. Mislabeling of geographical origin and blending with unidentified samples are common fraudulent practices in Greek food market with financial and possible health consequences. In the last decades, multi-elemental composition analysis has been used in identifying the geographical origin of foods and agricultural products. In an attempt to discriminate the authenticity of Greek beans, multi-elemental analysis (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Ge, K, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, Se, Sr, Ta, Ti, Tl, U, V, W, Zn, Zr) was performed by inductively coupled plasma mass spectrometry (ICP-MS) on 320 samples of beans, originated from Greece (Prespes and Kastoria), China and Poland. All samples were collected during the autumn of 2021. The obtained data were analysed by principal component analysis (PCA), an unsupervised statistical method, which allows for to reduce of the dimensionality of the enormous datasets. Statistical analysis revealed a clear separation of beans that had been cultivated in Greece compared with those from China and Poland. An adequate discrimination of geographical origin between bean samples originating from the two Greece regions, Prespes and Kastoria, was also evident. Our results suggest that multi-elemental analysis combined with the appropriate multivariate statistical method could be a useful tool for bean’s geographical authentication. Acknowledgment: This research has been financed by the Public Investment Programme/General Secretariat for Research and Innovation, under the call “YPOERGO 3, code 2018SE01300000: project title: ‘Elaboration and implementation of methodology for authenticity and geographical origin assessment of agricultural products.

Keywords: geographical origin, authenticity, multi-elemental analysis, beans, ICP-MS, PCA

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Authors: Ashkan Nazari, Saied Taheri

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Knowledge of tire-pavement interaction plays a crucial role in designing safer and more reliable tires. Characterizing the tire-pavement frictional interaction leads to a better understanding of vehicle performance in braking and acceleration. In this work, we devise a multi-scale simulation approach to incorporate the effect of pavement surface asperities in different length-scales. We construct two- and three-dimensional Finite Element (FE) models to simulate the interaction between a rubber block and a rough pavement surface with asperities in different scales. To achieve this, the road profile is scanned via a laser profilometer and the obtained asperities are implemented in an FE software (ABAQUS) in micro and macro length-scales. The hysteresis friction, which is due to the dissipative nature of rubber, is the main component of the friction force and therefore is the subject of study in this work. Using different scales not only will assist in characterizing the pavement asperities with sufficient details but also, it is highly effective in preventing extreme local deformations and stress gradients which results in divergence in FE simulations. The simulation results will be validated with experimental results as well as the results reported in the literature.

Keywords: friction, finite element, multi-scale modeling, rubber

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Authors: Rubia Gaur, Surindra Suthar

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The present study investigates the anaerobic co-digestion of duckweed (Lemna gibba) and waste activated sludge (WAS) of different proportions with acclimatized anaerobic granular sludge (AAGS) as inoculum in mesophilic conditions. Batch experiments were performed in 500 mL capacity reagent bottles at 300C temperature. Varied combinations of pre-treated duckweed biomass with constant volume of anaerobic inoculum (AAGS - 100 mL) and waste activated sludge (WAS - 22.5 mL) were devised into five batch tests. The highest methane generation was observed with batch study, T4. The Gompertz model fits well on the experimental data of the batch study, T4. The values of correlation coefficient were achieved relatively higher (R2 ≥ 0.99). The co-digestion without pre-treatment of both duckweed and WAS shows poor generation of methane gas.

Keywords: aquatic weed, biogas, biomass, Gompertz equation, waste activated sludge

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Dariusz Jemielniak

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The near future will bring significant changes to contemporary organizations and management, because of the rapidly increasing role of immaterial goods and knowledge workers. The area of copyright, IP, as well as digital (non-material) goods and media redistribution seems to be one of the major challenges for the economy and society in general, and management and organization studies in particular. The proposed paper shows the views and perceptions of fairness of digital media sharing among Harvard Law School LL.M. students, basing on 50 qualitative interviews and 100 questionnaires. The researcher took an ethnographic approach to the study and joined the 2016 Harvard LL.M. Facebook group, which allowed natural socializing and joining for in-person events and private parties more easily. After making acquaintance with many of the students, the researcher conducted a quantitative questionnaire with 100 respondents, allowing to better understand the respondents perception of fairness in digital files sharing in different contexts (depending on the price of the media, its availability, regional licensing, status of the copyright holder, etc.). Basing on the results of the questionnaire, the researcher followed up with long-term, open ended, loosely structured ethnographic interviews (50 interviews were conducted) to further deepen the understanding of the results. The major finding of the study is that Harvard lawyers, in spite of the highest possible understanding of law, as well as professional standards, generally approve of digital piracy in certain contexts. Interestingly, they are also more likely to approve of it if they work for the government rather than the private sector. The conclusions from this study allow a better understanding of how ‘fairness’ is perceived by the younger generation of law professionals, and also open grounds for a more rational licensing policing.

Keywords: piracy, digital sharing, perception of fairness, legal profession

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Authors: Y. Long, L. Liu, K. V. Branin

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One challenge faced by procurement decision-maker during the acquisition process is how to compare similar products from different suppliers and allocate orders among different products or services. This work focuses on allocating orders among multiple suppliers considering rebate. The objective function is to minimize the total acquisition cost including purchasing cost and rebate benefit. Rebate benefit is complex and difficult to estimate at the ordering step. Rebate rules vary for different suppliers and usually change over time. In this work, we developed a system to collect the rebate policies, standardized the rebate policies and developed two-stage optimization models for ordering allocation. Rebate policy with multi-tiers is considered in modeling. The discontinuous cost function of rebate benefit is formulated for different scenarios. A piecewise linear function is used to approximate the discontinuous cost function of rebate benefit. And a Mixed Integer Programing (MIP) model is built for order allocation problem with multi-tier rebate. A case study is presented and it shows that our optimization model can reduce the total acquisition cost by considering rebate rules.

Keywords: discontinuous cost function, mixed integer programming, optimization, procurement, rebate

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Authors: Lawrence Mzukisi Madikizela, Luke Chimuka

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Removal of organics from wastewater offers a better water quality, therefore, the purpose of this work was to investigate the use of molecularly imprinted polymer (MIP) for the elimination of selected organics from water. A multi-template MIP for the adsorption of naproxen, ibuprofen and diclofenac was synthesized using a bulk polymerization method. A MIP was synthesized at 70°C by employing 2-vinylpyridine, ethylene glycol dimethacrylate, toluene and 1,1’-azobis-(cyclohexanecarbonitrile) as functional monomer, cross-linker, porogen and initiator, respectively. Thermogravimetric characterization indicated that the polymer backbone collapses at 250°C and scanning electron microscopy revealed the porous and roughness nature of the MIP after elution of templates. The performance of the MIP in aqueous solutions was evaluated by optimizing several adsorption parameters. The optimized adsorption conditions were 50 mg of MIP, extraction time of 10 min, a sample pH of 4.6 and the initial concentration of 30 mg/L. The imprinting factors obtained for naproxen, ibuprofen and diclofenac were 1.25, 1.42, and 2.01, respectively. The order of selectivity for the MIP was; diclofenac > ibuprofen > naproxen. MIP showed great swelling in water with an initial swelling rate of 2.62 g/(g min). The synthesized MIP proved to be able to adsorb naproxen, ibuprofen and diclofenac from contaminated deionized water, wastewater influent and effluent.

Keywords: adsorption, molecularly imprinted polymer, multi template, pharmaceuticals

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Authors: Nisar Alungal Chungath

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“No human being is illegal" has become a dictum strongly upheld in the context of global immigration and migration, highlighting the ethical and moral dimensions of how societies and governments treat individuals and communities who have crossed political borders or are living in a country without legal authorization. It seeks to shift the focus from categorizing human beings as illegal immigrants to recognizing their inherent human rights and the complexities of their circumstances. As a complex social phenomenon, law has been a crucial instrument in shaping, regulating and governing human societies and vice versa. The law has now become a humongous political project of the modern majoritarian regimes to democratically illegitimize and illegalize the unpopular sections and minorities. Drawing from the theoretical frameworks of dialectics, the paper explores the philosophical underpinnings of the historical evolution and dynamic nature of modern law. The paper employs a phenomenological approach to analyze the dialectical relations between individuals, societies, and legal systems, aiming to shed light on the ethical and political implications of these interactions. By examining the historical essence of law, its relationship with social and cultural norms, and the role of power dynamics, this article argues for constantly maintaining the dialectics of law—the dynamic interplay between legal norms, social practices, cultural values, and historical contexts through a philosophical and phenomenological lens, in order to bridge the gap between universal principles and particular contexts. The paper will shed light to the dialectics of the law in the context of instances of the legal persecutions of the modern secular democracies such as Citizenship Amendment Act-2019, India.

Keywords: phenomenology, dialectic, modern law, politics, resistance, margins

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Authors: Amani Hassan Abu Atieh

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This study aims at examining the patterns of ideology reflected in the written discourse of women writers in the media of Jordan; Lana Mamkgh is taken as an example. This study critically analyzes the discursive, linguistic, and cognitive representations that she employs as an agent in the institutionalized discourse of the media. Grounded in van Dijk’s critical discourse analysis approach to Sociocognitive Discourse Studies, the present study builds a multilayer framework that encompasses van Dijk’s triangle: discourse, society, and cognition. Specifically, the study attempts to analyze, at both micro and macro levels, the underlying cognitive processes and structures, mainly ideology and discursive strategies, which are functional in the production of women’s discourse in terms of meaning, forms, and functions. Cognitive processes that social actors adopt are underlined by experience/context and semantic mental models on the one hand and social cognition on the other. This study is based on qualitative research and adopts purposive sampling, taking as an example a sample of an opinion article written by Lana Mamkgh in the Arabic Jordanian Daily, Al Rai. Taking her role as an agent in the public sphere, she stresses the National and feminist ideologies, demonstrating the use of assertive, evaluative, and expressive linguistic and rhetorical devices that appeal to the logic, ethics, and emotions of the addressee. Highlighting the agency of Jordanian writers in the media, the study sought to achieve the macro goal of dispensing political and social justice to the underprivileged. Further, the study seeks to prove that the voice of Jordanian women, viewed as underrepresented and invisible in the public arena, has come through clearly.

Keywords: critical discourse analysis, sociocognitive theory, ideology, women discourse, media

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Authors: Asma Rebaya, Kaouther Gasmi, Imen Amari, Salem Hasnaoui

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Over these last years, applications such as telecommunications, signal processing, digital communication with advanced features (Multi-antenna, equalization..) witness a rapid evaluation accompanied with an increase of user exigencies in terms of latency, the power of computation… To satisfy these requirements, the use of hardware/software systems is a common solution; where hardware is composed of multi-cores and software is represented by models of computation, synchronous data flow (SDF) graph for instance. Otherwise, the most of the embedded system designers utilize Simulink for modeling. The issue is how to simplify the c code generation, for a multi-cores platform, of an application modeled by Simulink. To overcome this problem, we propose a workflow allowing an automatic transformation from the Simulink model to the SDF graph and providing an efficient schedule permitting to optimize the number of cores and to minimize latency. This workflow goes from a Simulink application and a hardware architecture described by IP.XACT language. Based on the synchronous and hierarchical behavior of both models, the Simulink block diagram is automatically transformed into an SDF graph. Once this process is successfully achieved, the scheduler calculates the optimal cores’ number needful by minimizing the maximum density of the whole application. Then, a core is chosen to execute a specific graph task in a specific order and, subsequently, a compatible C code is generated. In order to perform this proposal, we extend Preesm, a rapid prototyping tool, to take the Simulink model as entry input and to support the optimal schedule. Afterward, we compared our results to this tool results, using a simple illustrative application. The comparison shows that our results strictly dominate the Preesm results in terms of number of cores and latency. In fact, if Preesm needs m processors and latency L, our workflow need processors and latency L'< L.

Keywords: hardware/software system, latency, modeling, multi-cores platform, scheduler, SDF graph, Simulink model, workflow

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Authors: Hondozi Jahja

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There is an obvious need to learn Arabic language and teach it to other speakers through the new curricula. The idea is to bridge the gap between theory and practice. To that end, we have sought to offer some means of help to master the Arabic language, in addition to our efforts to apply these means, enriching the culture of the student and develop his vocabulary. There is no doubt that taking care of the practical aspect of the grammar was our constant goal, and this particular aspect is what builds the student’s positive values and refine his taste and develop his language. In addressing these issues, we have adopted a school-based approach based primarily on the active and positive participation of the student. The theoretical linguistic issues - in our opinion - are not a primary goal, but the goal is to be used them by students through speaking and applying them. Among the objectives of this research is to establish the basic language skills of the students using new means that help the student to acquire these skills and apply them in various subjects of interest in his progress and development. Unfortunately, some of our students consider the grammar as ‘difficult’, ‘complex’ and ‘heavy’ in itself. This is one of the obstacles that stand in the way of their desired results. As a consequence, they end up talking – mumbling - about the difficulties they face in applying those rules. Therefore, some of our students finish their university studies and are unable to express what they feel using language correctly. For this purpose, we have sought in this research to follow a new integrated approach, which is to study the grammar of the language through modern means of the consolidation of the principle of functional language, and that the rule implies to control tongues and linguistic expressions properly. This research is a result of a practical experience as a teacher of Arabic language for non-native speakers at the ‘Hassan Pristina’ University, located in Pristina, the capital of Kosovo and at the Qatar Training Center since its establishment in 2012.

Keywords: arabic, applied methods, acquire, learning

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Authors: Amar Khoukhi, Mohamed Shahab

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This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: Lexi Li

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This study aims to contribute to the field of how computer technology can be exploited to enhance EFL textbook design. Specifically, the study demonstrates how computerized native and learner corpora can be used to enhance modal verb treatment in EFL textbooks. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because the pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the “secondary school” section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was compared with the textbook corpus in terms of the use (distributional features, semantic functions, and co-occurring constructions) in order to examine the degree of influence of the textbook on learners’ use of modal verbs. Moreover, the learner corpus was analyzed for the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The results indicate discrepancies between the textbook presentation of modal verbs and authentic modal use in natural discourse in terms of distributions of frequencies, semantic functions, and co-occurring structures. Furthermore, there are consistent patterns of use between the learner corpus and the textbook corpus with respect to the three above-mentioned aspects, except could, will and must, partially confirming the correlation between the frequency effects and L2 grammar acquisition. Further analysis reveals that the exceptions are caused by both positive and negative L1 transfer, indicating that the frequency effects can be intercepted by L1 interference. Besides, error analysis revealed that could, would, should and must are the most difficult for Chinese learners due to both inter-linguistic and intra-linguistic interference. The discrepancies between the textbook corpus and the native corpus point to a need to adjust the presentation of modal verbs in the textbooks in terms of frequencies, different meanings, and verb-phrase structures. Along with the adjustment of modal verb treatment based on authentic use, it is important for textbook writers to take into consideration the L1 interference as well as learners’ difficulties in their use of modal verbs. The present study is a methodological showcase of the combination both native and learner corpora in the enhancement of EFL textbook language authenticity and appropriateness for learners.

Keywords: EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Celine Davis

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The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Lily Chimuanya, Ehioghae Esther

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Language, a versatile and sophisticated tool, is fundamentally sacrosanct to mankind especially within the realm of politics. In this dynamic world, political leaders adroitly use language to engage in a strategic show aimed at manipulating or mechanising the opinion of discerning people. This nuanced synergy is marked by different rhetorical strategies, meticulously synced with contextual factors ranging from cultural, ideological, and political to achieve multifaceted persuasive objectives. This study investigates the (de)legitimation strategies inherent in African presidential inaugural speeches, as African leaders not only state their policy agenda through inaugural speeches but also subtly indulge in a dance of legitimation and delegitimation, performing a twofold objective of strengthening the credibility of their administration and, at times, undermining the performance of the past administration. Drawing insights from two different legitimation models and a dataset of 4 African presidential inaugural speeches obtained from authentic websites, the study describes the roles of authorisation, rationalisation, moral evaluation, altruism, and mythopoesis in unmasking the structure of political discourse. The analysis takes a mixed-method approach to unpack the (de)legitimation strategy embedded in the carefully chosen speeches. The focus extends beyond a superficial exploration and delves into the linguistic elements that form the basis of presidential discourse. In conclusion, this examination goes beyond the nuanced landscape of language as a potent tool in politics, with each strategy contributing to the overall rhetorical impact and shaping the narrative. From this perspective, the study argues that presidential inaugural speeches are not only linguistic exercises but also viable weapons that influence perceptions and legitimise authority.

Keywords: CDA, legitimation, inaugural speeches, delegitmation

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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