Search results for: text processing

Authors: Surabhi Pandey, Pavuluri Srinivasa Rao

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Extrusion processing is a high-temperature short time (HTST) treatment which can improve protein quality and digestibility together with retaining active nutrients. In-vitro protein digestibility of plant protein-based foods is generally enhanced by extrusion. The current study aimed to investigate the effect of extrusion cooking on in-vitro protein digestibility (IVPD) and conformational modification of protein in green banana flour extrudates. Green banana flour was extruded through a co-rotating twin-screw extruder varying the moisture content, barrel temperature, screw speed in the range of 10-20 %, 60-80 °C, 200-300 rpm, respectively, at constant feed rate. Response surface methodology was used to optimise the result for IVPD. Fourier-transform infrared spectroscopy (FTIR) analysis provided a convenient and powerful means to monitor interactions and changes in functional and conformational properties of extrudates. Results showed that protein digestibility was highest in extrudate produced at 80°C, 250 rpm and 15% feed moisture. FTIR analysis was done for the optimised sample having highest IVPD. FTIR analysis showed that there were no changes in primary structure of protein while the secondary protein structure changed. In order to explain this behaviour, infrared spectroscopy analysis was carried out, mainly in the amide I and II regions. Moreover, curve fitting analysis showed the conformational changes produced in the flour due to protein denaturation. The quantitative analysis of the changes in the amide I and II regions provided information about the modifications produced in banana flour extrudates.

Keywords: extrusion, FTIR, protein conformation, raw banana flour, SDS-PAGE method

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: S. Bouameur, S. Chirani

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The aim of this study was to evaluate the potential use of EthylCellulose in the preparation of microspheres as a Drug Delivery System for sustained release of phenobarbital. The microspheres were prepared by solvent evaporation technique using ethylcellulose as polymer matrix with a ratio 1:2, dichloromethane as solvent and Polyvinyl alcohol 1% as processing medium to solidify the microspheres. Size, shape, drug loading capacity and entrapement efficiency were studied.

Keywords: phenobarbital, microspheres, ethylcellulose, polyvinylacohol

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Songyun Chen

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Recent scholarly attention to sentiment analysis has provided researchers with a deeper understanding of how emotions are conveyed in writing and leveraged by academic authors as a persuasive tool. Using the National Research Council (NRC) Sentiment Lexicons (version 1.0) created by the National Research Council Canada, this study examined specific emotions in research articles (RAs) across four disciplines, including literature, education, biology, and computer & information science based on four datasets totaling over three million tokens, aiming to reveal how the emotions are conveyed by authors in academic writing. The results showed that four emotions—trust, anticipation, joy, and surprise—were observed in all four disciplines, while sadness emotion was spotted solely in literature. With the emotion of trust being overwhelmingly prominent, the rest emotions varied significantly across disciplines. The findings contribute to our understanding of emotion strategy applied in academic writing and genre characteristics of RAs.

Keywords: sentiment analysis, specific emotions, emotional landscape, research articles, academic writing

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Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue

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With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.

Keywords: historic districts, color planning, semantic segmentation, natural language processing

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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: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

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Authors: Mohua Dutta

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The primary aim of this research paper is to investigate the forced urban migration of Dalits in India who are fleeing caste persecution in rural areas. This paper examines the relationship between caste and rural-to-urban internal migration in India using a literary text, Rohinton Mistry’s A Fine Balance, highlighting the challenges faced by Dalits in rural areas that force them to migrate to urban areas. Despite the prevalence of such discussions in Dalit autobiographies written in vernacular languages, there is a lack of discussion regarding caste migration in Indian English Literature, including this present text, as evidenced by the existing critical interpretations of the novel, which this paper seeks to rectify. The primary research question is how urban migration affects caste system in India and why rural-to-urban caste migration occurs. The purpose of this paper is to better understand the reasons for Dalit migration, the challenges they face in rural and urban areas, and the lingering influence of caste in both rural and urban areas. The study reveals that the promise of mobility and emancipation provided by class operations drives rural-to-urban caste migration in India, but it also reveals that caste marginalization in rural areas is closely linked to class marginalization and other forms of subalternity in urban areas. Moreover, the caste system persists in urban areas as well, making Dalit migrants more vulnerable to social, political, and economic discrimination. The reason for this is that, despite changes in profession and urban migration, the trapped structure of caste capital and family networks exposes migrants to caste and class oppressions. To reach its conclusion, this study employs a variety of methodologies. Discourse analysis is used to investigate the current debates and narratives surrounding caste migration. Critical race theory, specifically intersectional theory and social constructivism, aids in comprehending the complexities of caste, class, and migration. Mistry's novel is subjected to textual analysis in order to identify and interpret references to caste migration. Secondary data, such as theoretical understanding of the caste system in operation and scholarly works on caste migration, are also used to support and strengthen the findings and arguments presented in the paper. The study concludes that rural-to-urban caste migration in India is primarily motivated by the promise of socioeconomic mobility and emancipation offered by urban spaces. However, the caste system persists in urban areas, resulting in the continued marginalisation and discrimination of Dalit migrants. The study also highlights the limitations of urban migration in providing true emancipation for Dalit migrants, as they remain trapped within caste and family network structures. Overall, the study raises awareness of the complexities surrounding caste migration and its impact on the lives of India's marginalised communities. This study contributes to the field of Migration Studies by shedding light on an often-overlooked issue: Dalit migration. It challenges existing literary critical interpretations by emphasising the significance of caste migration in Indian English Literature. The study also emphasises the interconnectedness of caste and class, broadening understanding of how these systems function in both rural and urban areas.

Keywords: rural-to-urban caste migration in india, internal migration in india, caste system in india, dalit movement in india, rooster coop of caste and class, urban poor as subalterns

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Md. Nuru Miah, A. F. M. Akhter Uddin

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Medicinal plants are grown naturally in a tropical environment in Bangladesh and used as drug and therapeutic agents in the health care system. According to Bangladesh Agricultural Research Institute (BARI), there are 722 species of medicinal plants in the country. Of them, 255 plants are utilized by the manufacturers of Ayurvedic and Unani medicines. Medicinal plants like Aloevera, Ashwagonda, shotomul,Tulsi, Vuikumra, Misridana are extensively cultivated in some selected areas as well; where Aloevera scored the highest position in production. In the early 1980, Ayurvedic and Unani companies procured 80 percent of medicinal plants from natural forests, and the rest 20 percent was imported. Now the scenario has changed; 80 percent is imported, and the rest 20 percent is collected from local products(Source: Astudy on sectorbased need assessment of Business promotion council-Herbal products and medicinal plants, page-4). Uttara Development Program Society, a leading Non- Government development organization in Bangladesh, has been implementing a value chain development project under promoting Agricultural commercialization and Enterprises of Pally Karma Sahayak Foundation (PKSF) funded by the International Fund for Agricultural Development (IFAD) in Natore Sadar Upazila from April 2017 to sustainably develop the technological interventions for products and market development. The ultimate goal of the project is to increase income, generate employment and develop this sector as a sustainable business enterprise. Altogether 10,000 farmers (Nursery owners, growers, input supplier, processors, whole sellers, and retailers) are engaged in different activities of the project. The entrepreneurs engaged in medicinal plant cultivation did not know and follow environmental and good agricultural practices. They used to adopt traditional methodology in production and processing. Locally the farmers didn’t have any positive initiative to expand their business as well as developvalue added products. A lot of diversified products could be possible to develop and marketed with the introduction of post-harvest processing technology and market linkage with the local and global buyer. Training is imparted to the nursery owners and herbal growers on production technologies, sowing method, use of organic fertilizers/compost/pesticides, harvesting procedures, and storage facilities. Different types of herbal tea like Rosella, Moringa, Tulshi, and Basak are being produced and packed locally with a good scope of its marketing in different cities of the country. The project has been able to achieve a significant impact in the development of production technologies, but still, there is room for further improvement in processing, packaging, and marketing level. The core intervention of the current project to develop some entrepreneurs for branding, packaging, promotion, and marketing while considering environment friendly practices. The present strategies will strengthen the knowledge and skills of the entrepreneurs for the production and marketing of their products, maintaining worldwide accepted compliance system for easy access to the global market.

Keywords: aloe vera, herbs and shrubs, market, interventions

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Authors: Nicolás Clavijo Buriticá, Laura Viviana Triana Sanchez

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This research develops a productive context associated with the aquaculture industry in northern Tolima-Colombia, specifically in the town of Lerida. Strategic aspects of chain of fish Production-Distribution, especially those related to supply network design of an association devoted to cultivating, farming, processing and marketing of fish are addressed. This research is addressed from a special approach of Supply Chain Management (SCM) which guides management objectives to the system sustainability; this approach is called Sustainable Supply Chain Management (SSCM). The network design of fish production-distribution system is obtained for the case study by two mathematical programming models that aims to maximize the economic benefits of the chain and minimize total supply chain costs, taking into account restrictions to protect the environment and its implications on system productivity. The results of the mathematical models validated in the productive situation of the partnership under study, called Asopiscinorte shows the variation in the number of open or closed locations in the supply network that determines the final network configuration. This proposed result generates for the case study an increase of 31.5% in the partial productivity of storage and processing, in addition to possible favorable long-term implications, such as attending an agile or not a consumer area, increase or not the level of sales in several areas, to meet in quantity, time and cost of work in progress and finished goods to various actors in the chain.

Keywords: Sustainable Supply Chain, mathematical programming, aquaculture industry, Supply Chain Design, Supply Chain Configuration

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Authors: Adil Basuki Ahza, Michael Liong, Subarna Suryatman

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Healthy chips now dominating the snack market shelves. More than 80% processed snack foods in the market are chips. This research takes the advantages of twin extrusion technology to produce two types of product, i.e. directly expanded and intermediate ready-to-fry or microwavable chips. To improve the functional quality, the cereal-tuber based mix was enriched with antioxidant rich mix of temurui, celery, carrot and isolated soy protein (ISP) powder. Objectives of this research were to find best composite cassava-sorghum ratio, i.e. 60:40, 70:30 and 80:20, to optimize processing conditions of extrusion and study the microstructural, physical and sensorial characteristics of the final products. Optimization was firstly done by applying metering section of extruder barrel temperatures of 120, 130 and 140 °C with screw speeds of 150, 160 and 170 rpm to produce direct expanded product. The intermediate product was extruded in 100 °C and 100 rpm screw speed with feed moisture content of 35, 40 and 45%. The directly expanded products were analyzed for color, hardness, density, microstructure, and organoleptic properties. The results showed that interaction of ratio of cassava-sorghum and cooking methods affected the product's color, hardness, and bulk density (p<0.05). Extrusion processing conditions also significantly affected product's microstructure (p<0.05). The direct expanded snacks of 80:20 cassava-sorghum ratio and fried expanded one 70:30 and 80:20 ratio shown the best organoleptic score (slightly liked) while baking the intermediate product with microwave were resulted sensorial not acceptable quality chips.

Keywords: cassava-sorghum composite, extrusion, microstructure, physical characteristics

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Authors: Sijia Guo

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The development of new technologies and the falling cost of high-speed Internet access have made it easier for institutes and language teachers to opt different ways to communicate with students at distance. The emergence of web-conferencing applications, which integrate text, chat, audio / video and graphic facilities, offers great opportunities for language learning to through the multimodal environment. This paper reports on data elicited from a Ph.D. study of using web-conferencing in the teaching of first-year Chinese class in order to promote learners’ collaborative learning. Firstly, a comparison of four desktop videoconferencing (DVC) tools was conducted to determine the pedagogical value of the videoconferencing tool-Blackboard Collaborate. Secondly, the evaluation of 14 campus-based Chinese learners who conducted five one-hour online sessions via the multimodal environment reveals the users’ choice of modes and their learning preference. The findings show that the tasks designed for the web-conferencing environment contributed to the learners’ collaborative learning and second language acquisition.

Keywords: computer-mediated communication (CMC), CALL evaluation, TBLT, web-conferencing, online Chinese teaching

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Authors: E. P. Bhowmik, R. Singh

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Certain materials casually thrown away as by-product household waste, such as used tea leaves, used coffee remnants, eggshells, peanut husks, coconut coir, unwanted paper, and pencil shavings- have scope in the hidden properties that they offer as recyclable raw ingredients. This paper aims to explore and experiment with the sustainable potential of such disposed wastes, obtained from domestic and commercial backgrounds, that could otherwise contribute to the field of interior design if mass-collected and repurposed. Research has been conducted on available recorded methods of mass-collection, storage, and processing of such materials by certain brands, designers, and researchers, as well as the various application and angles possible with regards to re-usage. A questionnaire survey was carried out to understand the willingness of the demographics for efforts of the mass collection and their openness to such unconventional materials for interiors. An experiment was also conducted where the selected waste ingredients were used to create small samples that could be used as decorative panels. Comparisons were made for properties like color, smell, texture, relative durability, and weight- and accordingly, applications were suggested. The experiment, therefore, helped to propose to recycle of the common household as a potential surface finish for floors, walls, and ceilings, and even founding material for furniture and decor accessories such as pottery and lamp shades; for non-structural application in both residential and commercial interiors. Common by-product wastes often see their ends at landfills- laymen unaware of their sustainable possibilities dispose of them. However, processing these waste materials and repurposing them by incorporating them into interiors would serve as a sustainable alternative to ethical dilemmas in the construction of interior design/architecture elements.

Keywords: interior materials, mass-collection, sustainable, waste recycle

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Authors: Theng Theng Ong

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This study adopts a multidisciplinary method by combining the corpus-based discourse analysis study and language attitude study to explore the construction of Malaysia airline tragedies: MH370, MH17 and QZ8501 in the selected Malaysian and United Kingdom (UK) online news. The study aims to determine the ways in which Malaysian Airline tragedies MH370, MH17 and QZ8501 are linguistically defined and constructed in terms of keyword and collocation. The study also seeks to identify the types of discourse that are presented in the new articles. The differences or similarities in terms of keywords, topics or issues covered by the selected Malaysian and UK news media will also be examined. Finally, the language attitude study will be carried out to examine the Malaysia and UK university students’ attitudes toward the keywords, topics or issues covered by the selected Malaysian and UK news media pertaining to Malaysian Airline tragedies MH370, MH17 and QZ8501. The analysis is divided into two parts with the first part focusing on corpus-based discourse analysis on the media text. The second part of the study is to investigate Malaysians and UK news readers’ attitudes towards the online news being reported by the Malaysian and UK news media pertaining to the Airline tragedies. The main findings of corpus-based discourse analysis are essential in designing the questions in the questionnaires and interview and therefore led to the identification of the attitudes among Malaysian and UK news. This study adopts a multidisciplinary method by combining the corpus-based discourse analysis study and language attitude study to explore the construction of Malaysia airline tragedies: MH370, MH17 and QZ8501 in the selected Malaysian and United Kingdom (UK) online news. The study aims to determine the ways in which Malaysian Airline tragedies MH370, MH17 and QZ8501 are linguistically defined and constructed in terms of keyword and collocation. The study also seeks to identify the types of discourse that are presented in the new articles. The differences or similarities in terms of keywords, topics or issues covered by the selected Malaysian and UK news media will also be examined. Finally, the language attitude study will be carried out to examine the Malaysia and UK university students’ attitudes toward the keywords, topics or issues covered by the selected Malaysian and UK news media pertaining to Malaysian Airline tragedies MH370, MH17 and QZ8501. The analysis is divided into two parts with the first part focusing on corpus-based discourse analysis on the media text. The second part of the study is to investigate Malaysians and UK news readers’ attitudes towards the online news being reported by the Malaysian and UK news media pertaining to the Airline tragedies. The main findings of corpus-based discourse analysis are essential in designing the questions in the questionnaires and interview and therefore led to the identification of the attitudes among Malaysian and UK news.

Keywords: corpus linguistics, critical discourse analysis, news media, tragedies study

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Authors: O. F. Elkommos

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

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

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Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: Lixin Zhao, Genmao Zhou

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Traditional acid in-situ leaching (ISL) is not suitable for the sandstone uranium deposit with low permeability and high content of carbonate minerals, because of the blocking of calcium sulfate precipitates. Another factor influences the uranium acid in-situ leaching is that the pyrite in ore rocks will react with oxidation reagent and produce lots of sulfate ions which may speed up the precipitation process of calcium sulphate and consume lots of oxidation reagent. Due to the advantages such as less chemical reagent consumption and groundwater pollution, CO₂+O₂ in-situ leaching method has become one of the important research areas in uranium mining. China is the second country where CO₂+O₂ ISL has been adopted in industrial uranium production of the world. It is shown that the CO₂+O₂ ISL in China has been successfully developed. The reaction principle, technical process, well field design and drilling engineering, uranium-bearing solution processing, etc. have been fully studied. At current stage, several uranium mines use CO₂+O₂ ISL method to extract uranium from the ore-bearing aquifers. The industrial application and development potential of CO₂+O₂ ISL method in China are summarized. By using CO₂+O₂ neutral leaching technology, the problem of calcium carbonate and calcium sulfate precipitation have been solved during uranium mining. By reasonably regulating the amount of CO₂ and O₂, related ions and hydro-chemical conditions can be controlled within the limited extent for avoiding the occurrence of calcium sulfate and calcium carbonate precipitation. Based on this premise, the demand of CO₂+O₂ uranium leaching has been met to the maximum extent, which not only realizes the effective leaching of uranium, but also avoids the occurrence and precipitation of calcium carbonate and calcium sulfate, realizing the industrial development of the sandstone type uranium deposit.

Keywords: CO₂+O₂ ISL, industrial production, well field layout, uranium processing

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Authors: Pratikno Hidayat, Khamdan Cahyari

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Hydrogen is the ultimate choice of energy carriers in future. It contents high energy density (42 kJ/g), emits only water vapor during combustion and has high energy conversion up to 50% in fuel cell application. One of the promising methods to produce hydrogen is from organic waste through dark fermentation method. It utilizes sugar-rich organic waste as substrate and hydrogen-producing microorganisms to generate the hydrogen. Solid waste of sago processing industries in Indonesia is one of the promising raw materials for both producing biofuel hydrogen and mitigating the environmental impact due to the waste disposal. This research was meant to investigate the effect of chemical and biological pretreatment i.e. acid treatment and mushroom cultivation toward lignocellulosic waste of these sago industries. Chemical pretreatment was conducted through exposing the waste into acid condition using sulfuric acid (H2SO4) (various molar i.e. 0.2, 0.3, and 0.4 M and various duration of exposure i.e. 30, 60 and 90 minutes). Meanwhile, biological treatment was conducted through utilization of the solid waste as growth media of mushroom (Oyster and Ling-zhi) for 3 months. Dark fermentation was conducted at pH 5.0, temperature 27℃ and atmospheric pressure. It was noticed that chemical and biological pretreatment could improve hydrogen yield with the highest yield at 3.8 ml/g VS (31%v H2). The hydrogen production was successfully performed to generate high percentage of hydrogen, although the yield was still low. This result indicated that the explosion of acid chemical and biological method might need to be extended to improve degradability of the solid waste. However, high percentage of hydrogen was resulted from proper pretreatment of residual sludge of biogas plant to generate hydrogen-producing inoculum.

Keywords: hydrogen, sago waste, chemical, biological, dark fermentation, Indonesia

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Authors: Attahir Shehu Mainiyo, Ahmad Ibrahim Karfe

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The Glorious Qur’an, as the central religious text of Islam, addresses various aspects of human life and provides guidance for personal and societal development. It also outlines the moral excellence of individuals and communities, focusing on spiritual, moral, and social dimensions. Da’wah is the act of inviting others to Islam, emphasizing the significance of conveying the message with kindness, patience, and understanding. Qur’anic moral excellence, as evinced in the Qur’an encompasses virtues such as compassion, honesty, humility, patience, and generosity. The Glorious Qur’an, therefore, harps on the importance of embodying these values in daily life, serving as a guide for individuals engaged in Da’wah activities to exemplify moral excellence through their actions and characters. It is in line with this backdrop that this article intends to assess the Da’wah and Qur’anic Moral Excellence. However, to achieve the objectives of the research, the article attempts to answer some basic questions. Emphasizes were laid in the Glorious on the need to invite others to the true path of Islam and the qualities of Da’i necessary for his Da’wah activities. The paper also discussed the impact of Qur’anic moral excellence on the Da’i and those invited to Islam. The paper adopts an analytical methodology and utilizes secondary data for the research.

Keywords: Da'wah, Qur'an, moral, excellence

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Authors: Mustafa Ekici, Sacide Güzin Mazman

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Programming is the one of ability in computer science fields which is generally perceived difficult by students and various individual differences have been implicated in that ability success. Although several factors that affect programming ability have been identified over the years, there is not still a full understanding of why some students learn to program easily and quickly while others find it complex and difficult. Programming self-efficacy and mathematic success are two of those essential individual differences which are handled as having important effect on the programming success. This study aimed to identify the relationship between programming performance, programming self efficacy and mathematics success. The study group is consisted of 96 undergraduates from Department of Econometrics of Uşak University. 38 (39,58%) of the participants are female while 58 (60,41%) of them are male. Study was conducted in the programming-I course during 2014-2015 fall term. Data collection tools are comprised of programming course final grades, programming self efficacy scale and a mathematics achievement test. Data was analyzed through correlation analysis. The result of study will be reported in the full text of the study.

Keywords: programming performance, self efficacy, mathematic success, computer science

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Authors: Adegoke Yinka Adebayo

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An understanding of the critical product attributes that impact on in vivo performance is key to the production of safe and effective medicines. Thus, a key driver for our research is the development of new basic science and technology underpinning the development of new pharmaceutical products. Research includes the structure and properties of drugs and excipients, biopharmaceutical characterisation, pharmaceutical processing and technology and formulation and analysis.

Keywords: drug discovery, drug development, drug delivery

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Authors: Bujar Ismaili, Bahti Ismajli, Venhar Ismaili, Skender Ramadani

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In Kosovo, the problem with the electricity supply is huge and does not meet the demands of consumers. Older thermal power plants, which are regarded as big environmental polluters, produce most of the energy. Our experiment is based on the production of electricity using the closed method that does not affect environmental pollution by using waste as fuel that is considered to pollute the environment. The experiment was carried out in the village of Godanc, municipality of Shtime - Kosovo. In the experiment, a production line based on the production of electricity and central heating was designed at the same time. The results are the benefits of electricity as well as the release of temperature for heating with minimal expenses and with the release of 0% gases into the atmosphere. During this experiment, coal, plastic, waste from wood processing, and agricultural wastes were used as raw materials. The method utilized in the experiment allows for the release of gas through pipes and filters during the top-to-bottom combustion of the raw material in the boiler, followed by the method of gas filtration from waste wood processing (sawdust). During this process, the final product is obtained - gas, which passes through the carburetor, which enables the gas combustion process and puts into operation the internal combustion machine and the generator and produces electricity that does not release gases into the atmosphere. The obtained results show that the system provides energy stability without environmental pollution from toxic substances and waste, as well as with low production costs. From the final results, it follows that: in the case of using coal fuel, we have benefited from more electricity and higher temperature release, followed by plastic waste, which also gave good results. The results obtained during these experiments prove that the current problems of lack of electricity and heating can be met at a lower cost and have a clean environment and waste management.

Keywords: energy, heating, atmosphere, waste, gasification

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Syed Tahir Shah, Fazal Muhammad, Syed Kashif Shah, Maleeha Gul

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In recent days, natural gas has become a relatively clean and quality source of energy, which is recovered from deep wells by expensive drilling activities. The recovered substance is purified by processing in multiple stages to remove the unwanted/containments like dust, dirt, crude oil and other particles. Mostly, gas utilities are concerned with essential objectives of quantity/quality of natural gas delivery, financial outcome and safe natural gas volumetric inventory in the transmission gas pipeline. Gas quantity and quality are primarily related to standards / advanced metering procedures in processing units/transmission systems, and the financial outcome is defined by purchasing and selling gas also the operational cost of the transmission pipeline. SNGPL (Sui Northern Gas Pipelines Limited) Pakistan has a wide range of diameters of natural gas transmission pipelines network of over 9125 km. This research results in answer a few of the issues in accuracy/metering procedures via multiple advanced gadgets for gas flow attributes after being utilized in the transmission system and research. The effects of good pressure management in transmission gas pipeline network in contemplation to boost the gas volume deposited in the existing network and finally curbing gas losses UFG (Unaccounted for gas) for financial benefits. Furthermore, depending on the results and their observation, it is directed to enhance the maximum allowable working/operating pressure (MAOP) of the system to 1235 PSIG from the current round about 900 PSIG, such that the capacity of the network could be entirely utilized. In gross, the results depict that the current model is very efficient and provides excellent results in the minimum possible time.

Keywords: natural gas, pipeline network, UFG, transmission pack, AGA

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Authors: Fatima Muhammad Shitu

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This paper focuses on the variation of sentence types in English academic writing. The major focus is on whether variation in sentence types can be attributable to the linguistic and most of all the gender of the writers. The objective of this paper is to analyze the sentence types produced by Male and Female ESL writers and to determine whether writers vary the frequency and use of sentence types across the text depending on the rhetorical choices of the writers to construct identity. This study is hinged on the functionalist approach to analyzing academic writing in use. For the purpose of this study, a corpus of 20 academic papers was created and the use of sentences types was analyzed. The data for the study was collated using percentages. In this case, the number of occurrences of the different sentence types were analyzed, calculated and then converted to percentages for each group i.e., male and female ESL writers. The results from these analyses were compared and contrasted in order to determine whether Male and Female ESL writer vary their sentence types, and, or employed the same or different sentence types in their texts. The conclusion is that Male and Female ESL writers not only vary in their use of sentence types in academic writings but also differ.

Keywords: sentence variation, ESL, gender, academic writing

Procedia PDF Downloads 328

Authors: Yi-Ling Chen, Dung-Ying Lin

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In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

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Authors: Dandeswar Bisoyi, Preeti Yadav, Utpal Barua

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This study address particular way that verbal information can affect the processing of positive and interesting qualities which help in making the brand attractive to the consumer. Also, it address the development of a communication strategy which is a very important part of the marketing plan we have to take into account many factors. Out of all the product strengths, the strategy has to outline one marked differential which will drive our brand. This is the fundamental base on which the entire creative strategy will be big idea-based.

Keywords: copy writing, advertisement, marketing, branding, recall

Procedia PDF Downloads 579

Authors: Gizem Kodak

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The Strait of Çanakkale, together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: maritime accidents, EDA, Strait of Çanakkale, navigational safety

Procedia PDF Downloads 95