Search results for: language as technology
8936 Using Geopolymer Technology on Stabilization and Reutilization the Expansion Behavior Slag
Authors: W. H. Lee, T. W. Cheng, K. Y. Lin, S. W. Huang, Y. C. Ding
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Basic Oxygen Furnace (BOF) Slag and electric arc furnace (EAF) slag is the by-product of iron making and steel making. Each of slag with produced over 100 million tons annually in Taiwan. The type of slag has great engineering properties, such as, high hardness and density, high compressive strength, low abrasion ratio, and can replace natural aggregate for building materials. However, no matter BOF or EAF slag, both have the expansion problem, due to it contains free lime. The purpose of this study was to stabilize the BOF and EAF slag by using geopolymer technology, hoping can prevent and solve the expansion problem. The experimental results showed that using geopolymer technology can successfully solve and prevent the expansion problem. Their main properties are analyzed with regard to their use as building materials. Autoclave is used to study the volume stability of these specimens. Finally, the compressive strength of geopolymer mortar with BOF/FAF slag can be reached over 21MPa after curing for 28 days. After autoclave testing, the volume expansion does not exceed 0.2%. Even after the autoclave test, the compressive strength can be grown to over 35MPa. In this study have success using these results on ready-mixed concrete plant, and have the same experimental results as laboratory scale. These results gave encouragement that the stabilized and reutilized BOF/EAF slag could be replaced as a feasible natural fine aggregate by using geopolymer technology.Keywords: BOF slag, EAF slag, autoclave test, geopolymer
Procedia PDF Downloads 1338935 A Comparative Analysis of (De)legitimation Strategies in Selected African Inaugural Speeches
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
Procedia PDF Downloads 698934 Low Temperature Biological Treatment of Chemical Oxygen Demand for Agricultural Water Reuse Application Using Robust Biocatalysts
Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi
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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts
Procedia PDF Downloads 1298933 Enhancing Code Security with AI-Powered Vulnerability Detection
Authors: Zzibu Mark Brian
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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.Keywords: AI, machine language, cord security, machine leaning
Procedia PDF Downloads 368932 Artificial Intelligence for Traffic Signal Control and Data Collection
Authors: Reggie Chandra
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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal
Procedia PDF Downloads 1698931 An Empirical Investigation of Mobile Banking Services Adoption in Pakistan
Authors: Aijaz A. Shaikh, Richard Glavee-Geo, Heikki Karjaluoto
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Adoption of Information Systems (IS) is receiving increasing attention such that its implications have been closely monitored and studied by the IS management community, industry and professional gatekeepers. Building on previous research regarding the adoption of technology, this paper develops and validates an integrated model of the adoption of mobile banking. The model originates from the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB). This paper intends to offer a preliminary scrutiny of the antecedents of the adoption of mobile banking services in the context of a developing country. Data was collected from Pakistan. The findings showed that an integrated TAM and TPB model greatly explains the adoption intention of mobile banking; and perceived behavioural control and its antecedents play a significant role in predicting adoption Theoretical and managerial implications of findings are presented and discussed.Keywords: developing country, mobile banking service adoption, technology acceptance model, theory of planned behavior
Procedia PDF Downloads 4198930 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment
Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee
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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation
Procedia PDF Downloads 3488929 How Manufacturing Firm Manages Information Security: Need Pull and Technology Push Perspective
Authors: Geuna Kim, Sanghyun Kim
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This study investigates various factors that may influence the ISM process, including the organization’s internal needs and external pressure, and examines the role of regulatory pressure in ISM development and performance. The 105 sets of data collected in a survey were tested against the research model using SEM. The results indicate that NP and TP had positive effects on the ISM process, except for perceived benefits. Regulatory pressure had a positive effect on the relationship between ISM awareness and ISM development and performance.Keywords: information security management, need pull, technology push, regulatory pressure
Procedia PDF Downloads 2988928 The Effect of Supercritical Carbon Dioxide Process Variables on The Recovery of Extracts from Bentong Ginger: Study on Process Variables
Authors: Muhamad Syafiq Hakimi Kamaruddin, Norhidayah Suleiman
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Ginger extracts (Zingiber officinale Rosc.) have been attributed therapeutic properties primarily as antioxidant, anticancer, and anti-inflammatory properties. Conventional extractions including Soxhlet and maceration are commonly used to extract the bioactive compounds from plant material. Nevertheless, high energy consumption and being non-environmentally friendly are the predominant limitations of the conventional extractions method. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. A pressure (10-30 MPa), temperature (40-60 °C), and median particle size (300-600 µm) were conducted at a CO2 flow rate of 0.9 ± 0.2 g/min for 120 mins. The highest overall yield was 4.58% obtained by the scCO2 extraction conditions of 300 bar and 60 °C with 300µm of ginger powder for 120 mins. In comparison, the yield of the extract was increased considerably within a short extraction time. The results show that scCO2 has a remarkable ability over ginger extract and is a promising technology for extracting bioactive compounds from plant material.Keywords: conventional, ginger, non-environmentally, supercritical carbon dioxide, technology
Procedia PDF Downloads 1168927 Dual Role of Microalgae: Carbon Dioxide Capture Nutrients Removal
Authors: Mohamad Shurair, Fares Almomani, Simon Judd, Rahul Bhosale, Anand Kumar, Ujjal Gosh
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This study evaluated the use of mixed indigenous microalgae (MIMA) as a treatment process for wastewaters and CO2 capturing technology at different temperatures. The study follows the growth rate of MIMA, removals of organic matter, removal of nutrients from synthetic wastewater and its effectiveness as CO2 capturing technology from flue gas. A noticeable difference between the growth patterns of MIMA was observed at different CO2 and different operational temperatures. MIMA showed the highest growth grate when injected with CO2 dosage of 10% and limited growth was observed for the systems injected with 5% and 15 % of CO2 at 30 ◦C. Ammonia and phosphorus removals for Spirulina were 69%, 75%, and 83%, and 20%, 45%, and 75% for the media injected with 0, 5 and 10% CO2. The results of this study show that simple and cost-effective microalgae-based wastewater treatment systems can be successfully employed at different temperatures as a successful CO2 capturing technology even with the small probability of inhibition at high temperaturesKeywords: greenhouse, climate change, CO2 capturing, green algae
Procedia PDF Downloads 3338926 Advances in the Design of Wireless Sensor Networks for Environmental Monitoring
Authors: Shathya Duobiene, Gediminas Račiukaitis
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Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.Keywords: IoT, network formation, sensor nodes, SSAIL technology
Procedia PDF Downloads 888925 Requests and Responses to Requests in Jordanian Arabic
Authors: Raghad Abu Salma, Beatrice Szczepek Reed
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Politeness is one of the most researched areas in pragmatics as it is key to interpersonal interactional phenomena. Many studies, particularly in linguistics, have focused on developing politeness theories and exploring linguistic devices used in communication to construct and establish social norms. However, the question of what constitutes polite language remains a point of ongoing debate. Prior research primarily examined politeness in English and its native speaking communities, oversimplifying the notion of politeness and associating it with surface-level language use. There is also a dearth of literature on politeness in Arabic, particularly in the context of Jordanian Arabic. Prior research investigating politeness in Arabic make generalized claims about politeness in Arabic without taking the linguistic variations into account or providing empirical evidence. This proposed research aims to explore how Jordanian Arabic influences its first language users in making and responding to requests, exploring participants' perceptions of politeness and the linguistic choices they make in their interactions. The study focuses on Jordanian expats living in London, UK providing an intercultural perspective that prior research does not consider. This study employs a mixed-methods approach combining discourse completion tasks (DCTs) with semi-structured interviews. While DCTs provide insight into participants’ linguistic choices, semi-structured interviews glean insight into participants' perceptions of politeness and their linguistic choices impacted by cultural norms and diverse experiences. This paper discusses previous research on politeness in Arabic, identifies research gaps, and discusses different methods for data collection. This paper also presents preliminary findings from the ongoing study.Keywords: politeness, pragmatics, jordanian arabic, intercultural politeness
Procedia PDF Downloads 798924 Potential and Development of Children with Atypical Rett Syndrome (CDKL5 Gene Mutation) and Augmentative and Alternative Communication
Authors: Anna Amato
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Every child needs communication. If spoken language is not or not fully available due to congenital or acquired limitations, those affected need appropriate ways. These can be found in many possibilities of Augmentative and Alternative Communications (AAC). In the communication promotion of severely impaired children, who can use their own body communication forms only to a limited extent for the differentiated understanding, computers with eye control play an essential role. It takes some time to understand the individual forms of communication of the child. Children who depend on the AAC need competent support to learn to communicate in a motivated way in their everyday life. The aim of the present parents' survey (n = 4), which was evaluated descriptively, is to demonstrate the development of communicative abilities as well as the motivation to use complex communication aids with eye control by patients with atypical Rett Syndrome. An increase in communication skills, well-being, self-reliance, and self-esteem, an improvement in social participation, as well as a reduction in anger and screaming events, were noted. The complex visual communication tools were available daily for 3 out of 4 patients with atypical Rett Syndrome. It raises research questions regarding speech understanding and the ability to drive eye control technology in a larger group of atypical Rett Syndrome patients.Keywords: augmentative and alternative communications, AAC, atypical Rett-syndrome, children, development
Procedia PDF Downloads 1178923 Assessment of E-Portfolio on Teacher Reflections on English Language Education
Authors: Hsiaoping Wu
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With the wide use of Internet, learners are exposed to the wider world. This exposure permits learners to discover new information and combine a variety of media in order to reach in-depth and broader understanding of their literacy and the world. Many paper-based teaching, learning and assessment modalities can be transferred to a digital platform. This study examines the use of e-portfolios for ESL (English as a second language) pre-service teacher. The data were collected by reviewing 100 E-portfolio from 2013 to 2015 in order to synthesize meaningful information about e-portfolios for ESL pre-service teachers. Participants were generalists, bilingual and ESL pre-service teachers. The studies were coded into two main categories: learning gains, including assessment, and technical skills. The findings showed that using e-portfolios enhanced and developed ESL pre-service teachers’ teaching and assessment skills. Also, the E-portfolio also developed the pre-service teachers’ technical stills to prepare a comprehensible portfolio to present who they are. Finally, the study and presentation suggested e-portfolios for ecological issues and educational purposes.Keywords: assessment, e-portfolio, pre-service teacher, reflection
Procedia PDF Downloads 3178922 Hierarchical Tree Long Short-Term Memory for Sentence Representations
Authors: Xiuying Wang, Changliang Li, Bo Xu
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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis
Procedia PDF Downloads 3498921 Analyzing Apposition and the Typology of Specific Reference in Newspaper Discourse in Nigeria
Authors: Monday Agbonica Bello Eje
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The language of the print media is characterized by the use of apposition. This linguistic element function strategically in journalistic discourse where it is communicatively necessary to name individuals and provide information about them. Linguistic studies on the language of the print media with bias for apposition have largely dwelt on other areas but the examination of the typology of appositive reference in newspaper discourse. Yet, it is capable of revealing ways writers communicate and provide information necessary for readers to follow and understand the message. The study, therefore, analyses the patterns of appositional occurrences and the typology of reference in newspaper articles. The data were obtained from The Punch and Daily Trust Newspapers. A total of six editions of these newspapers were collected randomly spread over three months. News and feature articles were used in the analysis. Guided by the referential theory of meaning in discourse, the appositions identified were subjected to analysis. The findings show that the semantic relation of coreference and speaker coreference have the highest percentage and frequency of occurrence in the data. This is because the subject matter of news reports and feature articles focuses on humans and the events around them; as a result, readers need to be provided with some form of detail and background information in order to identify as well as follow the discourse. Also, the non-referential relation of absolute synonymy and speaker synonymy no doubt have fewer occurrences and percentages in the analysis. This is tied to a major feature of the language of the media: simplicity. The paper concludes that appositions is mainly used for the purpose of providing the reader with much detail. In this way, the writer transmits information which helps him not only to give detailed yet concise descriptions but also in some way help the reader to follow the discourse.Keywords: apposition, discourse, newspaper, Nigeria, reference
Procedia PDF Downloads 1748920 Research and Application of the Three-Dimensional Visualization Geological Modeling of Mine
Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao
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Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.Keywords: three-dimensional geological modeling, geological database, geostatistics, block model
Procedia PDF Downloads 708919 The Role of Access Control Techniques in Creating a Safe Cyberspace for Children
Authors: Sara Muslat Alsahali, Nout Mohammed Alqahtani
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Digital technology has changed the world, and with the increasing number of children accessing the Internet, it has now become an integral part of children's lives from their early years. With the rapid development of digital technology, the risks children face on the internet also evolve from cyberbullying to misuse, sexual exploitation, and abuse of their private information over the Internet. Digital technology, with its advantages and disadvantages, is now a fact of our life. Therefore, knowledge of how to reduce its risks and maximize its benefits will help shape the growth and future of a new generation of digital citizens. This paper will discuss access control techniques that help to create secure cyberspace where children can be safe without depriving them of their rights and freedom to use the internet and preventing them from its benefits. Also, it sheds light on its challenges and problems by classifying the methods of parental controlling into two possibilities asynchronous and synchronous techniques and choosing YouTube as a case study of access control techniques.Keywords: access control, cyber security, kids, parental monitoring
Procedia PDF Downloads 1378918 Exploring the Use of Discourse Markers by American Male and Female Politicians: A Corpus Based Study
Authors: Gohar Rahman, Rabia Saad Ullah
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This research aims to examine the use of discourse markers within the dominion of political speeches, differentiating between genders. The analysis centers on twelve speakers, comprising six males and six females. Speeches selected include commencement, victory, state union addresses, campaigns, and presidential speeches. Halliday and Hasan's cohesion framework, specifically discourse markers, is utilized as a theoretical framework. Data is quantitatively analyzed using AntConc to identify marker frequency. The findings are presented through Excel's tables and graphs, suggesting differences in discourse marker preferences between genders. The findings suggest a divergence in the preferences for discourse markers between males and females. However, asserting that females utilize discourse markers more frequently due to the increased use of filler words, face threat mitigation, and polite speech would be an exaggeration. The disparity in frequency is not substantial, suggesting that males and females exhibit varying language inclinations to some degree.Keywords: discourse markers, political discourse, gender, speeches, language
Procedia PDF Downloads 588917 The Design of Information Technology System for Traceability of Thailand’s Tubtimjun Roseapple
Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Sawanath Treesathon
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As there are several countries which import agriculture product from Thailand, those countries demand Thailand to establish the traceability system. The traceability system is the tool to reduce the risk in the supply chain in a very effective way as it will help the stakeholder in the supply chain to identify the defect point which will reduce the cost of operation in the supply chain. This research is aimed to design the traceability system for Tubtimjun roseapple for exporting to China, and it is the qualitative research. The data was collected from the expert in the tuntimjun roseapple and fruit exporting industry, and the data was used to design the traceability system. The design of the tubtimjun roseapple traceability system was followed the theory of supply chain which starts from the upstream of the supply chain to the downstream of the supply chain to support the process and condition of the exporting which included the database designing, system architecture, user interface design and information technology of the traceability system.Keywords: design information, technology system, traceability, tubtimjun roseapple
Procedia PDF Downloads 1708916 Ecosystems: An Analysis of Generation Z News Consumption, Its Impact on Evolving Concepts and Applications in Journalism
Authors: Bethany Wood
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The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.Keywords: journalism, generation z, digital, social media
Procedia PDF Downloads 868915 Empowering Certificate Management with Blockchain Technology
Authors: Yash Ambekar, Kapil Vhatkar, Prathamesh Swami, Kartikey Singh, Yashovardhan Kaware
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The rise of online courses and certifications has created new opportunities for individuals to enhance their skills. However, this digital transformation has also given rise to coun- terfeit certificates. To address this multifaceted issue, we present a comprehensive certificate management system founded on blockchain technology and strengthened by smart contracts. Our system comprises three pivotal components: certificate generation, authenticity verification, and a user-centric digital locker for certificate storage. Blockchain technology underpins the entire system, ensuring the immutability and integrity of each certificate. The inclusion of a cryptographic hash for each certificate is a fundamental aspect of our design. Any alteration in the certificate’s data will yield a distinct hash, a powerful indicator of potential tampering. Furthermore, our system includes a secure digital locker based on cloud storage that empowers users to efficiently manage and access all their certificates in one place. Moreover, our project is committed to providing features for certificate revocation and updating, thereby enhancing the system’s flexibility and security. Hence, the blockchain and smart contract-based certificate management system offers a robust and one-stop solution to the escalating problem of counterfeit certificates in the digital era.Keywords: blockchain technology, smart contracts, counterfeit certificates, authenticity verification, cryptographic hash, digital locker
Procedia PDF Downloads 468914 A Critical Discourse Analysis of President Muhammad Buhari's Speeches
Authors: Joy Aworo-Okoroh
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Politics is about trust and trust is challenged by the speaker’s ability to manipulate language before the electorate. Critical discourse analysis investigates the role of language in constructing social relationships between a political speaker and his audience. This paper explores the linguistic choices made by President Muhammad Buhari that enshrines his ideologies as well as the socio-political relations of power between him and Nigerians in his speeches. Two speeches of President Buhari –inaugural and Independence Day speeches are analyzed using Norman Fairclough’s perspective on Halliday’s Systemic functional grammar. The analysis is at two levels. The first level of analysis is the identification of transitivity and modality choices in the speeches and how they reveal the covert ideologies. The second analysis is premised on Normal Fairclough’s model, the clauses are analyzed to identify elements of power, hesistation, persuasion, threat and religious statement. It was discovered that Buhari is a dominant character who manipulates the material processes a lot.Keywords: politics, critical discourse analysis, Norman Fairclough, systemic functional grammar
Procedia PDF Downloads 5518913 Exploring Transitions between Communal- and Market-Based Knowledge Sharing
Authors: Benbya Hind, Belbaly Nassim
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Markets and communities are often cast as alternative forms of knowledge sharing, but an open question is how and why people dynamically transition between them. To study these transitions, we design a technology that allows geographically distributed participants to either buy knowledge (using virtual points) or request it for free. We use a data-driven, inductive approach, studying 550 members in over 5000 interactions, during nine months. Because the technology offered participants choices between market or community forms, we can document both individual and collective transitions that emerge as people cycle between these forms. Our inductive analysis revealed that uncertainties endemic to knowledge sharing were the impetus for these transitions. Communities evoke uncertainties about knowledge sharing’s costs and benefits, which markets resolve by quantifying explicit prices. However, if people manipulate markets, they create uncertainties about the validity of those prices, allowing communities to reemerge to establish certainty via identity-based validation.Keywords: knowledge sharing, communities, information technology design, transitions, markets
Procedia PDF Downloads 1808912 The Effect of Unconscious Exposure to Religious Concepts on Mutual Stereotypes of Jews and Muslims in Israel
Authors: Lipaz Shamoa-Nir, Irene Razpurker-Apfeld
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This research examined the impact of subliminal exposure to religious content on the mutual attitudes of majority group members (Jews) and minority group members (Muslims). Participants were subliminally exposed to religious concepts (e.g., Mezuzah, yarmulke or veil) and then they filled questionnaires assessing their stereotypes towards the out-group members. Each participant was primed with either in-group religious concepts, out-group concepts or neutral ones. The findings show that the Muslim participants were not influenced by the religious content to which they were exposed while the Jewish participants perceived the Muslims as less 'hostile' when subliminally exposed to religious concepts, regardless of concept type (out-group/in-group). This research highlights the influence of evoked religious content on out-group attitudes even when the perceiver is unaware of prime content. The power that exposure to content in a non-native language has in activating attitudes towards the out-group is also discussed.Keywords: intergroup attitudes, stereotypes, majority-minority, religious out-group, implicit content, native language
Procedia PDF Downloads 2468911 Investigating the English Speech Processing System of EFL Japanese Older Children
Authors: Hiromi Kawai
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This study investigates the nature of EFL older children’s L2 perceptive and productive abilities using classroom data, in order to find a pedagogical solution to the teaching of L2 sounds at an early stage of learning in a formal school setting. It is still inconclusive whether older children with only EFL formal school instruction at the initial stage of L2 learning are able to attain native-like perception and production in English within the very limited amount of exposure to the target language available. Based on the notion of the lack of study of EFL Japanese children’s acquisition of English segments, the researcher uses a model of L1 speech processing which was developed for investigating L1 English children’s speech and literacy difficulties using a psycholinguistic framework. The model is composed of input channel, output channel, and lexical representation, and examines how a child receives information from spoken or written language, remembers and stores it within the lexical representations and how the child selects and produces spoken or written words. Concerning language universality and language specificity in the language acquisitional process, the aim of finding any sound errors in L1 English children seemed to conform to the author’s intention to find abilities of English sounds in older Japanese children at the novice level of English in an EFL setting. 104 students in Grade 5 (between the ages of 10 and 11 years old) of an elementary school in Tokyo participated in this study. Four tests to measure their perceptive ability and three oral repetition tests to measure their productive ability were conducted with/without reference to lexical representation. All the test items were analyzed to calculate item facility (IF) indices, and correlational analyses and Structural Equation Modeling (SEM) were conducted to examine the relationship between the receptive ability and the productive ability. IF analysis showed that (1) the participants were better at perceiving a segment than producing a segment, (2) they had difficulty in auditory discrimination of paired consonants when one of them does not exist in the Japanese inventory, (3) they had difficulty in both perceiving and producing English vowels, and (4) their L1 loan word knowledge had an influence on their ability to perceive and produce L2 sounds. The result of the Multiple Regression Modeling showed that the two production tests could predict the participants’ auditory ability of real words in English. The result of SEM showed that the hypothesis that perceptive ability affects productive ability was supported. Based on these findings, the author discusses the possible explicit method of teaching English segments to EFL older children in a formal school setting.Keywords: EFL older children, english segments, perception, production, speech processing system
Procedia PDF Downloads 2438910 The Impact of Gamification on Self-Assessment for English Language Learners in Saudi Arabia
Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy
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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.Keywords: e-learning system, gamification, motivation, social comparison, visualization
Procedia PDF Downloads 1538909 Knowledge, Hierarchy and Decision-Making: Analysis of Documentary Filmmaking Practices in India
Authors: Nivedita Ghosh
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In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.Keywords: documentary filmmaking, India, technology, knowledge, hierarchy
Procedia PDF Downloads 2628908 Named Entity Recognition System for Tigrinya Language
Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager
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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF
Procedia PDF Downloads 1318907 A Picture Naming Study of European Portuguese-English Bilinguals on Cognates Switch Effects
Authors: Minghui Zou
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This study investigates whether and how cognate status influences switching costs in bilingual language production. Two picture naming tasks will be conducted in this proposed study by manipulating the conditions of how cognates and non-cognates are presented, i.e., separately in two testing blocks vs intermixed in one single testing block. Participants of each experiment will be 24 L1-European Portuguese L2-English unbalanced speakers. Stimuli will include 12 pictures of cognate nouns and 12 of non-cognate nouns. It is hypothesized that there will be cognate switch facilitation effects among unbalanced bilinguals in both of their languages when stimuli are presented either in two single testing blocks or one mixed testing block. Shorter reaction times and higher naming accuracy are expected to be found in cognate switch trials than in non-cognate switch trials.Keywords: cognates, language switching costs, picture naming, European Portuguese, cognate facilitation effect
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