Search results for: text presentation

Authors: Chandan Kundu, Sankar Bhattacharya

Abstract:

A significant disadvantage of fossil fuel energy production is the considerable amount of carbon dioxide (CO₂) released, which is one of the contributors to climate change. Apart from environmental concerns, changing fossil fuel prices have pushed society gradually towards renewable energy sources in recent years. Biomass is a plentiful and renewable resource and a source of carbon. Recent years have seen increased research interest in generating fuels and chemicals from biomass. Unlike fossil-based resources, biomass is composed of lignocellulosic material, which does not contribute to the increase in atmospheric CO₂ over a longer term. These considerations contribute to the current move of the chemical industry from non-renewable feedstock to renewable biomass. This presentation focuses on generating bio-oil and two major platform chemicals that can potentially improve the environment. Thermochemical processes such as pyrolysis are considered viable methods for producing bio-oil and biomass-based platform chemicals. Fluidized bed reactors, on the other hand, are known to boost bio-oil yields during pyrolysis due to their superior mixing and heat transfer features, as well as their scalability. This review and the associated experimental work are focused on the thermochemical conversion of biomass to bio-oil and two high-value platform chemicals, Levoglucosenone (LGO) and 5-Chloromethyl furfural (5-CMF), in a fluidized bed reactor. These two active molecules with distinct features can potentially be useful monomers in the chemical and pharmaceutical industries since they are well adapted to the manufacture of biologically active products. This process took several meticulous steps. To begin, the biomass was delignified using a peracetic acid pretreatment to remove lignin. Because of its complicated structure, biomass must be pretreated to remove the lignin, increasing access to the carbohydrate components and converting them to platform chemicals. The biomass was then characterized by Thermogravimetric analysis, Synchrotron-based THz spectroscopy, and in-situ DRIFTS in the laboratory. Based on the results, a continuous-feeding fluidized bed reactor system was constructed to generate platform chemicals from pretreated biomass using hydrogen chloride acid-gas as a catalyst. The procedure also yields biochar, which has a number of potential applications, including soil remediation, wastewater treatment, electrode production, and energy resource utilization. Consequently, this research also includes a preliminary experimental evaluation of the biochar's prospective applications. The biochar obtained was evaluated for its CO₂ and steam reactivity. The outline of the presentation will comprise the following: Biomass pretreatment for effective delignification Mechanistic study of the thermal and thermochemical conversion of biomass Thermochemical conversion of untreated and pretreated biomass in the presence of an acid catalyst to produce LGO and CMF A thermo-catalytic process for the production of LGO and 5-CMF in a continuously-fed fluidized bed reactor and efficient separation of chemicals Use of biochar generated from the platform chemicals production through gasification

Keywords: biomass, pretreatment, pyrolysis, levoglucosenone

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Authors: Lin Xie, Yang Wang

Abstract:

An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: education, communication, psychology, student learning, language teaching

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Authors: Lee Artz

Abstract:

This presentation outlines US media frames of recent interventions in Iraq, Afghanistan, and Syria and their impact on global media and public discourse. A content analysis of sources, descriptors, and contexts of leading US media (AP, New York Times, Fox News) finds that news coverage highlights terrorism, justifies military action, and downplays the human costs. These media frames that normalize intervention also omit coverage of the environmental consequences of war, with scant or no reporting on pollution, destruction and contamination of agricultural infrastructures and the difficulty of any environmentally sustainable recovery. A content analysis of leading European and Middle East media (Daily Mail, Le Monde, Deutsch Welle, Al Jazeera) indicates that they have adopted the same reporting practices, frames, and techniques resulting in a hybrid, yet homogeneous, increasingly global news environment that does a disservice to the public interest and democracy.

Keywords: conflict, environment, media framing, public interest

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

Abstract:

In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Carla Van De Sande, Jana Vandenberg

Abstract:

Just like physical skills, cognitive skills grow rusty over time unless they are regularly used and practiced, so academic breaks can have negative consequences on student learning and success. The Keeping in School Shape (KiSS) program is an engaging, accessible, and cost-effective intervention that harnesses the benefits of retrieval practice by using technology to help students maintain proficiency over breaks from school by delivering a daily review problem via text message or email. A growth mindset is promoted through feedback messages encouraging students to try again if they get a problem wrong and to take on a challenging problem if they get a problem correct. This paper reports on the relationship between confidence, accuracy, and decision-making during the implementation of the KiSS Program at a large university during winter break for students enrolled in an engineering introductory Calculus course sequence.

Keywords: growth mindset, learning loss, on-the-go learning, retrieval practice

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Authors: Henry Nicholas Lee, George Thomas, Juliana Johari, Carmilla Freddie, Caroline Val Madin

Abstract:

Research in comparative and international education often provides value-laden views of an education system within and in between other countries. These views are frequently used by policy makers or educators to explore similarities and differences for, among others, benchmarking purposes. In this study, a comparison is made between Malaysia and England, focusing on the process of writing children went through to create a text, using a multimodal theoretical framework to analyse this comparison. The main purpose is political in nature as it served as an answer to Malaysia’s call for benchmarking of best practices for language learning. Furthermore, the focus on writing in this study adds into more empirical findings about early writers’ writing development and writing improvement, especially for children at the ages of 5-9. In research, comparative studies in English as a Second Language (ESL) writing pedagogy – particularly in Malaysia since the introduction of the Standard- based English Language Curriculum (KSSR) in 2011 as a draft and its full implementation in 2017; reviewed 2018 KSSR-CEFR aligned – has not been done comparatively. In theory, a multimodal theoretical framework somehow allows a logical comparison between first language and ESL which would provide useful insights to illuminate the writing process between Malaysia and England. The comparisons are not representative because of the different school systems in both countries. So far, the literature informs us that the curriculum for language learning is very much emphasised on children’s linguistic abilities, which include their proficiency and mastery of the language, its conventions, and technicalities. However, recent empirical findings suggested that literacy in its concepts and characters need change. In view of this suggestion, the comparison will look at how the process of writing is implemented through the five modes of communication: linguistic, visual, aural, spatial, and gestural. This project draws on data from Malaysia and England, involving 10 teachers, 26 classroom observations, 20 lesson plans, 20 interviews, and 20 brief conversations with teachers. The research focused upon 20 primary children of different genders aged 5-9, and in addition to primary data descriptions, 40 children’s works, 40 brief classroom conversations, 30 classroom photographs, and 30 school compound photographs were undertaken to investigate teachers and children’s use of modes and semiotic resources to design a text. The data were analysed by means of within-case analysis, cross-case analysis, and constant comparative analysis, with an initial stage of data categorisation, followed by general and specific coding, which clustered the data into thematic groups. The study highlights the importance of teachers’ and children’s engagement and interaction with various modes of communication, an adaptation from the English approaches to teaching writing within the KSSR framework and providing ‘voice’ to ESL writers to ensure that both have access to the knowledge and skills required to make decisions in developing multimodal texts and artefacts.

Keywords: comparative education, early writers, KSSR, multimodal theoretical framework, writing development

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Authors: Martina Maria Keitsch

Abstract:

Critical Design (CD) confronts traditional design practice. Instead of reproducing and reinforcing contemporary perceptions of products and services, CD seeks to challenge them with the goal to stimulate debates and visions on societal innovation. CD methods comprise, among other narratives and design of critical objects. The oral presentation is based on a study that discusses concepts, methods, and applications of CD links CD to traditional design, and identifies CD benefits and challenges for design research and practice. The objective of the study is to introduce CD as an alternative for design researchers and practitioners supplementing commercially oriented design approaches. The study utilizes a literature review on CD concepts and methods based on current publications and online documents and illustrates CD practice with help of selected case studies. Findings of the study indicate that CD contribute, among others, to create new societal roles for designers, foster innovative relationships between designers and users, and encourage creativity through imaginative aesthetics.

Keywords: critical design, postmodern design theories, narratives, rhizome

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

Abstract:

Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

Abstract:

Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer

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Authors: H. E. Amolo

Abstract:

The concepts of pollution or contamination and purification or ritual cleansing are very important concepts among traditional Africans. This is because in relation to human behaviors and attitudes, they constitute on the one hand what could be referred to as moral demands and on the other, what results in the default of such demands. The many taboos which a man has to observe are not to be regarded as things mechanical which do not touch the heart, but that the avoidance is a sacred law respected by the community. In breaking it, you offend the divine power’. Researches have shown that, Africans tenaciously hold the belief that, moral values are based upon the recognition of the divine will and that sin in the community must be expelled if perfect peace is to be enjoyed. Sadly enough, these moral values are gradually eroding in contemporary times. Thus, this study proposal calls for a survey of the passage from an African cultural context; how it can enhance the understanding of the text, as well as how it can complement its scholarly interpretation with the view of institutionalizing the concept of holiness as a means of bringing the people closer to God, and also instilling ethical purity and righteousness.

Keywords: cultural practices, Igbo ideology, purification, rituals

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Etsuo Morishita

Abstract:

This paper presents the project and experiment-based fluid dynamics education in Meisei University, a private institution in Tokyo, Japan. We pay attention not only to the basic engineering courses but also to the practical aspect of engineering experience. So, we prepare courses called the Projects from I to VI. The Projects I and II are designed for the first year, III and IV are designated for the second year, V and VI are prepared for the third year, respectively. Each supervisor is responsible for two of these projects every year. When students take the Project V and VI at the third year, we automatically assume that these students will join the lab of the project for the graduation thesis. We would like to show our experience in the Project I in the summer term, 2016. In this project, we introduce a traction flight vehicle called Cat Flyer. This is a kind of a kite towed by a car for example. This is very similar to parasailing, but flight is possible even on the roads. Experiments in mechanical engineering education are also very important, and we would like to explain our course on centrifugal pump, venture, and orifice. Although these are described in detail in the text books of fluid dynamics, it is still crucial to have practical experiments as a student.

Keywords: aerodynamics, experiment, fluid dynamics, project

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Authors: Subodh Chandra Shakya, Rajendra Sapkota, Aakash Tamang, Shushant Pudasaini, Sujan Adhikari, Sajjan Adhikari

Abstract:

Lots of efforts have been made in order to measure the semantic similarity between the text corpora in the documents. Techniques have been evolved to measure the similarity of two documents. One such state-of-art technique in the field of Natural Language Processing (NLP) is word to vector models, which converts the words into their word-embedding and measures the similarity between the vectors. We found this to be quite useful for the task of resume ranking. So, this research paper is the implementation of the word2vec model along with other Natural Language Processing techniques in order to rank the resumes for the particular job description so as to automate the process of hiring. The research paper proposes the system and the findings that were made during the process of building the system.

Keywords: chunking, document similarity, information extraction, natural language processing, word2vec, word embedding

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Authors: Rick Evans

Abstract:

Despite over 40 years of research into why women choose not to enroll or leave undergraduate engineering programs, along with the subsequent and serious efforts to attract more women, women receiving bachelor's degrees in engineering in the US have remained disappointingly low. We know that even despite their struggles to become more welcoming and inclusive, engineering programs remain gendered, raced and classed. However, our research team has found that women who participate and indeed thrive in undergraduate engineering project teams do so in numbers that far exceed their participation in undergraduate programs. We believe part of the answer lies in the ways that project teams facilitate experiential learning, specifically providing opportunities for members to play, practice and perform. We employ a multi-case study method and assume a feminist, activist and interpretive perspective. We seek to generate concrete and context-dependent knowledge in order to explore potentially new variables and hypotheses. Our focus is to learn from those select women who are thriving. For this oral or e-poster presentation, we will focus on the results of the second of our semi-structured interviews – the learning journey interview. During this interview, we ask participants to tell us the story/ies of their participation in project teams. Our results suggest these women find joy in their experience of developing and applying engineering expertise. They experience this joy and develop their expertise in the highly patterned progression of play, practice and performance. Play is a purposeful activity in which someone enters an imaginary world, a world not yet real to them. However, this imaginary world is still very much connected to the real world, in this case, a particular kind of engineering, in that the ways of engaging are already established, codified and rule-governed. As such, these women are novices motivated to join a community of actors. Practice, better understood as practices, a count noun, is an embodied, materially interconnected collection of actions organized around the shared understandings of that community of actors. Those shared understandings reveal a social order – a particular field of engineering. No longer novices, these women begin to develop and display their emergent identities as engineers. Perform is activity meant either to demonstrate competence and/or to enable, even teach play and practice to others. As performers, these women participants become models for others. They direct play and practice, contextualizing both within a field of engineering and the specific aims of the project team community. By playing, practicing and performing engineering, women claim their identities as engineers and, equally important, have those identities acknowledged by team members. If we hope to transform our gendered, raced, classed institutions, we need to learn more about women who thrive within those institutions. We need to learn more about their processes of becoming and belonging as engineers. Our research presentation begins with a description of project teams and our multi-case study method. We then offer detailed descriptions of play, practice, and performance using the voices of women in project teams.

Keywords: engineering education, gender, identity, project teams

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Authors: Mohammad Saeed Bahramy

Abstract:

Transition metal dichalcogenides have experienced a resurgence of interest in the past few years owing to their rich properties, ranging from metals and superconductors to strongly spin-orbit-coupled semiconductors and charge-density-wave systems. In all these cases, the transition metal d-electrons mainly determine the ground state properties. This presentation focuses on the chalcogen-derived states. Combining density-functional theory calculations with spin- and angle-resolved photoemission, it is shown that these states generically host a coexistence of type I and type II three-dimensional bulk Dirac fermions as well as ladders of topological surface states and surface resonances. It will be discussed how these naturally arise within a single p-orbital manifold as a general consequence of a trigonal crystal field, and as such can be expected across many compounds. Our finding opens a new route to design topological materials with advanced functionalities.

Keywords: topology, electronic structure, Dirac semimetals, transition metal dichalcogenides

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Authors: Hilde Heim

Abstract:

The textile industry is known for its swift adoption of innovations in fashion technology (Fash-Tech). The industry is also known for its harmful effects on the environment. Opportunely, Fash-Tech is expected to facilitate the turn towards more sustainable practice. However, although several technologies have the potential for advancing sustainable practice, many industry players, whether large or small, are confused and misinformed about Fash-Tech adoption, application, and impact. Through a visual poster presentation, this project aims to map global fashion innovations along the supply chain from fibre production to waste management, thus providing a clearer picture of numbers, scale, and adoption. While the project aims to identify Fash-Tech effectiveness in reaching sustainability goals, it also identifies areas of congestion as well as insufficiency in the accessibility of Fash-Tech. This project intends to help inform future decisions in business, investment, and policy for the advancement of sustainable practice.

Keywords: fashion technology, sustainability, supply chain, enterprise management

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Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

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The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Thassanant Unnanantn, Suttipong Boonphadung

Abstract:

This research study aimed to survey and analyze the attitudes of pre-service teachers’ the analytical thinking development based on Miller’s Model. The informants of this study were 22 third year teacher students majoring in Thai. The course where the instruction was conducted was English for Academic Purposes in Thai Language 2. The instrument of this research was an open-ended questionnaire with two dimensions of questions: academic and satisfaction dimensions. The investigation revealed the positive attitudes. In the academic dimension, the majority of 12 (54.54%), the highest percentage, reflected that the method of teaching analytical thinking and language simultaneously was their new knowledge and the similar percentage also belonged to text cohesion in writing. For the satisfaction, the highest frequency count was from 17 of them (77.27%) and this majority favored the openness or friendliness of the teacher.

Keywords: analytical thinking development, Miller’s Model, attitudes, pre-service teachers

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Authors: Wilaiwan Jongwilaikasaem, Phatteera Sarakornborrirak

Abstract:

While Thai television producers feel anxious about digital disruption, Love Destiny, Thai television period drama became smash hit in Thailand in 2018. Audience throughout the country not only watched the drama both offline and online but also spread the content of the drama on social media and followed cultural trends from the protagonist. Thus, the main purpose of this article is to examine the secret behind the success of Love Destiny. Data were collected from content analysis and in-depth interview. The result shows that the key success of the drama is from earned media phenomenon from the audience and marketers’ engagement. As Love Destiny has full-flavored content with traditional challenged plot, delicate production, and presentation of Thainess in a positive and tangible way; audience and marketers are enthusiastic about building up the popular trend of Love Destiny on social media and also coming back home to watch televisions when the drama was on the air.

Keywords: Thai drama, earned media, Love Destiny, television

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Bharti Gupta, V. K. Kukreja

Abstract:

A comprehensive numerical study is presented for the solution of time-dependent advection diffusion problems by using cubic B-spline collocation method. The linear combination of cubic B-spline basis, taken as approximating function, is evaluated using the zeros of shifted Chebyshev polynomials as collocation points in each element to obtain the best approximation. A comparison, on the basis of efficiency and accuracy, with the previous techniques is made which confirms the superiority of the proposed method. An asymptotic convergence analysis of technique is also discussed, and the method is found to be of order two. The theoretical analysis is supported with suitable examples to show second order convergence of technique. Different numerical examples are simulated using MATLAB in which the 3-D graphical presentation has taken at different time steps as well as different domain of interest.

Keywords: cubic B-spline basis, spectral norms, shifted Chebyshev polynomials, collocation points, error estimates

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Authors: Shangerganesh Lingeshwaran

Abstract:

In this presentation, we have performed numerical simulations for a reaction-diffusion equation with various nonlinear density-dependent diffusion operators and proliferation functions. The mathematical model represented by parabolic partial differential equation is considered to study the invasion of gliomas (the most common type of brain tumors) and to describe the growth of cancer cells and response to their treatment. The unknown quantity of the given reaction-diffusion equation is the density of cancer cells and the mathematical model based on the proliferation and migration of glioma cells. A standard Galerkin finite element method is used to perform the numerical simulations of the given model. Finally, important observations on the each of nonlinear diffusion functions and proliferation functions are presented with the help of computational results.

Keywords: glioma invasion, nonlinear diffusion, reaction-diffusion, finite eleament method

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Authors: Lin Xie, Yang Wang

Abstract:

An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

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Authors: Shahin Zanbaghi, Saeed Samet

Abstract:

The internet has transformed the way we shop. Previously, most of our purchases came in the form of shopping trips to a nearby store. Now, it’s as easy as clicking a mouse. But with great convenience comes great responsibility. We have to be constantly vigilant about our personal information. In this work, our proposed approach is to encrypt the information printed on the physical packages, which include personal information in plain text, using a symmetric encryption algorithm; then, we store that encrypted information into a Blockchain network rather than storing them in companies or corporations centralized databases. We present, implement and assess a blockchain-based system using Ethereum smart contracts. We present detailed algorithms that explain the details of our smart contract. We present the security, cost, and performance analysis of the proposed method. Our work indicates that the proposed solution is economically attainable and provides data integrity, security, transparency, and data traceability.

Keywords: blockchain, Ethereum, smart contract, commit-reveal scheme

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Authors: Joshua Chew, Vesa Cheng, David Thomson

Abstract:

Background: Hereditary angioedema (HAE) or C1 esterase deficiency is a relatively rare entity that has a potential for significant anesthetic complications. Methods: A literature review was performed of published cases of surgery in patients with HAE. Results were limited to English language only and cases were examined for management strategies and successful prevention of acute attacks. Results: The literature revealed the successful use of C1 esterase inhibitors as the most common agent in surgical prophylaxis therapy. Other therapeutic targets described included kallikrein inhibitors and bradykinin B2 receptor antagonists. Conclusions: Therapeutic targets that exist for the management of acute attacks in HAE have been successfully employed in the setting of surgery. The data is currently limited and could not be used as a firm evidence base, but the limited outcomes seen are positive and reassuring for the prospective anesthetic management of this potentially fatal condition.

Keywords: anesthesia, C1 esterase deficiency, hereditary angioedema, surgical prophylaxis

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Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

Abstract:

Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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Authors: Brynn Patrice Fader

Abstract:

The objective of this research project is to assess the ways in which Jean-Francois Menards French translation Harry Potter a l'ecole des sorciers translates the cultural references from the original text JK Rowlings' Harry Potter and the Philosophers Stone. The method of this analysis is to focus on analyzing the reasons for and the ways in which Menard translates the spells and catchphrases throughout the novel and the effects that these choices have on the reader. While at times Menard resorts to the omission or manipulation and borrowing he also contrasts these techniques by transferring the cultural references using the direct translational approach. It appears that the translator resorts to techniques other than direct translation when it is necessary to ensure that the target audience will understand the events and conversations taking place.

Keywords: cultural elements, direct translation, manipulation, omission

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Authors: Yousef Rostami Gharainy

Abstract:

This paper presents resource consumption accounting as an imaginative way to deal with management accounting which concentrates on administrators as the essential clients of the data and gives the best information of conventional management accounting. This system underscores that association's asset reasons costs, accordingly in costing frameworks the emphasis ought to be on assets and utilization of them. Resource consumption accounting consolidates two costing methodologies, action based and German cost accounting method known as GPK. This methodology notwithstanding giving a chance to managers to decide, makes task management accounting as operational. The reason for this article is to clarify the idea of resource consumption accounting, its parts and highlights and use of this strategy in associations. In the first place we deliver to presentation of resource consumption accounting, foundation, reasons for its development and the issues that past costing frameworks confronted it. At that point we give standards and presumptions of this technique; at last we depict the execution of this strategy in associations and its preferences over other costing strategies.

Keywords: resource consumption accounting, management accounting, action based method, German cost accounting method

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Authors: Swarnadip Ghosh

Abstract:

Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

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