Search results for: Learning materials

Authors: Joelle Thng, Li Fang

Abstract:

Objective: As programming becomes a highly valued and sought-after skill in the economy, many universities have started offering Python courses to help students keep up with the demands of employers. This study focuses on designing a university module that effectively educates undergraduate students on financial analysis using Python programming. Methodology: To better satisfy the specific demands for each sector, this study adopted a qualitative research modus operandi to craft a module that would complement students’ existing financial skills. The lessons were structured using research-backed educational learning tools, and important Python concepts were prudently screened before being included in the syllabus. The course contents were streamlined based on criteria such as ease of learning and versatility. In particular, the skills taught were modelled in a way to ensure they were beneficial for financial data processing and analysis. Results: Through this study, a 6-week course containing the chosen topics and programming applications was carefully constructed for finance students. Conclusion: The findings in this paper will provide valuable insights as to how teaching programming could be customised for students hailing from various academic backgrounds.

Keywords: curriculum development, designing effective instruction, higher education strategy, python for finance students

Procedia PDF Downloads 65

Authors: F. Ben Abdelghani, W. Maherezi

Abstract:

Dredging operations generate, each year, a great quantity of marine sediments. These raw materials can not be used in road construction without a specific treatment process. Sediments suitability tests has shown that most of studied sediments are not suitable to be used in road construction. In order to improve their compacity and their mechanical performance, addition of a granular material is recommended. The use of a dredged sand, to improve the granular mixture containing sediments, allows a better management of the two types of dredge materials (sand and sediment). In this study, a new road material containing dredged marine sediments and dredged sand is formulated and treated by adding various binders. Mechanical performance investigation of different mixtures by measuring Proctor-IPI values and simple compressive strengths is realized.

Keywords: dredged sediments, suitability tests, road construction, hydraulic binder, mechanical performance

Procedia PDF Downloads 349

Authors: Yixiu Liu, Yunzhou Zhang, Jianning Chi, Hao Chu, Rui Zheng, Libo Sun, Guanghao Chen, Fangtong Zhou

Abstract:

In the last few years, large-scale person re-identification has attracted a lot of attention from video surveillance since it has a potential application prospect in public safety management. However, it is still a challenging job considering the variation in human pose, the changing illumination conditions and the lack of paired samples. Although the accuracy has been significantly improved, the data dependence of the sample training is serious. To tackle this problem, a new strategy is proposed based on bag of visual words (BoVW) model of designing the feature representation which has been widely used in the field of image retrieval. The local features are extracted, and more discriminative feature representation is obtained by cross-view dictionary learning (CDL), then the assignment map is obtained through k-means clustering. Finally, the BoVW histograms are formed which encodes the images with the statistics of the feature classes in the assignment map. Experiments conducted on the CUHK03, Market1501 and MARS datasets show that the proposed method performs favorably against existing approaches.

Keywords: bag of visual words, cross-view dictionary learning, person re-identification, reranking

Procedia PDF Downloads 178

Authors: Nynne Nørup, Julie Helles Eriksen, Rikke M. Moalem, Else Skjold

Abstract:

Despite a growing focus on the high environmental impact of textiles, textile waste is only recently considered as part of the waste field. Consequently, there is a general lack of knowledge and data within this field. Particularly the lack of a common perception of textiles generates several problems e.g., to recognize the full material potential the fraction contains, which is cruel if the textile must enter the circular economy. This study aims to qualify a method to make the resources in textile waste visible in a way that makes it possible to move them as high up in the waste hierarchy as possible. Textiles are complex and cover many different types of products, fibers and combinations of fibers and production methods. In garments alone, there is a great variety, even when narrowing it to only undergarments. However, textile waste is often reduced to one fraction, assessed solely by quantity, and compared to quantities of other waste fractions. Disregarding the complexity and reducing textiles to a single fraction that covers everything made of textiles increase the risk of neglecting the value of the materials, both with regards to their properties and economical. Instead of trying to fit textile waste into the current primarily linear waste system where volume is a key part of the business models, this study focused on integrating textile waste as a resource in the design and production phase. The study combined interdisciplinary methods for determining replacement rates used in Life Cycle Assessments and Mass Flow Analysis methods with the designer’s toolbox to hereby activate the properties of textile waste in a way that can unleash its potential optimally. It was hypothesized that by activating Denmark's tradition for design and high level of craftsmanship, it is possible to find solutions that can be used today and create circular resource models that reduce the use of virgin fibers. Through waste samples, case studies, and testing of various design approaches, this study explored how to functionalize the method so that the product after the end-use is kept as a material and only then processed at fiber level to obtain the best environmental utilization. The study showed that the designers' ability to decode the properties of the materials and understanding of craftsmanship were decisive for how well the materials could be utilized today. The later in the life cycle the textiles appeared as waste, the more demanding the description of the materials to be sufficient, especially if to achieve the best possible use of the resources and thus a higher replacement rate. In addition, it also required adaptation in relation to the current production because the materials often varied more. The study found good indications that part of the solution is to use geodata i.e., where in the life cycle the materials were discarded. An important conclusion is that a fully developed method can help support better utilization of textile resources. However, it stills requires a better understanding of materials by the designers, as well as structural changes in business and society.

Keywords: circular economy, development of sustainable processes, environmental impacts, environmental management of textiles, environmental sustainability through textile recycling, interdisciplinary method development, resource optimization, recycled textile materials and the evaluation of recycling, sustainability and recycling opportunities in the textile and apparel sector

Procedia PDF Downloads 76

Authors: Amir Nourbakhsh Habibabadi, Alireza Ashori

Abstract:

Context: The growing concern over the management of plastic waste and the high demand for wood-based products have led to the development of wood-plastic composites. Agricultural residues, which are abundantly available, can be used as a source of lignocellulosic fibers in the production of these composites. The use of recycled polymers and nanomaterials is also a promising approach to enhance the mechanical and physical properties of the composites. Research Aim: The aim of this study was to investigate the feasibility of using recycled high-density polyethylene (rHDPE), polypropylene (rPP), and agricultural residues fibers for manufacturing wood-plastic nano-composites. The effects of these materials on the mechanical properties of the composites, specifically tensile and flexural strength, were studied. Methodology: The study utilized an experimental approach where extruders and hot presses were used to fabricate the composites. Five types of cellulosic residues fibers (bagasse, corn stalk, rice straw, sunflower, and canola stem), three levels of nanomaterials (carbon nanotubes, nano silica, and nanoclay), and coupling agent were used to chemically bind the wood/polymer fibers, chemicals, and reinforcement. The mechanical properties of the composites were then analyzed. Findings: The study found that composites made with rHDPE provided moderately superior tensile and flexural properties compared to rPP samples. The addition of agricultural residues in several types of wood-plastic nano-composites significantly improved their bending and tensile properties, with bagasse having the most significant advantage over other lignocellulosic materials. The use of recycled polymers, agricultural residues, and nano-silica resulted in composites with the best strength properties. Theoretical Importance: The study's findings suggest that using agricultural fiber residues as reinforcement in wood/plastic nanocomposites is a viable approach to improve the mechanical properties of the composites. Additionally, the study highlights the potential of using recycled polymers in the development of value-added products without compromising the product's properties. Data Collection and Analysis Procedures: The study collected data on the mechanical properties of the composites using tensile and flexural tests. Statistical analyses were performed to determine the significant effects of the various materials used. Question addressed: Can agricultural residues and recycled polymers be used to manufacture wood-plastic nano-composites with enhanced mechanical properties? Conclusion: The study demonstrates the feasibility of using agricultural residues and recycled polymers in the production of wood-plastic nano-composites. The addition of these materials significantly improved the mechanical properties of the composites, with bagasse being the most effective agricultural residue. The study's findings suggest that composites made from recycled materials can offer value-added products without sacrificing performance.

Keywords: polymer, composites, wood, nano

Procedia PDF Downloads 59

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 57

Authors: J. K. Adedeji, M. O. Oyekanmi

Abstract:

This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

Procedia PDF Downloads 239

Authors: Jagannath Prasad Tegar, Zeeshan Ahmad

Abstract:

The Ordinary Portland Cement (OPC) is a major constituent of concrete, which is being used extensively since last half century. The production of cement is impacting not only environment alone, but depleting natural materials. During the past 3 decades, the scholars have carried out studies and researches to explore the supplementary cementatious materials such as Ground granulated Blast furnace slag (GGBFS), silica fumes (SF), metakaolin or fly ash (FA). This has contributed towards improved cementatious materials which are being used in construction, but not the way it is supposed to be. The alkali activated slag concrete is another innovation which has constituents of cementatious materials like Ground Granuled Blast Furnace Slag (GGBFS), Fly Ash (FA), Silica Fumes (SF) or Metakaolin. Alkaline activators like Sodium Silicate (Na₂SiO₃) and Sodium Hydroxide (NaOH) is utilized. In view of evaluating properties of alkali activated slag concrete blended with polypropylene shredding and accelerator, research study is being carried out. This research study is proposed to evaluate the effect of polypropylene shredding and accelerating admixture on mechanical properties of alkali-activated slag concrete. The mechanical properties include the compressive strength, splitting tensile strength and workability. The outcomes of this research are matched with the hypothesis and it is found that 27% of cement can be replaced with the ground granulated blast furnace slag (GGBFS) and for split tensile strength 20% replacement is achieved. Overall it is found that 20% of cement can be replaced with ground granulated blast furnace slag. The tests conducted in the laboratory for evaluating properties such as compressive strength test, split tensile strength test, and slump cone test. On the aspect of cost, it is substantially benefitted.

Keywords: ordinary Portland cement, activated slag concrete, ground granule blast furnace slag, fly ash, silica fumes

Procedia PDF Downloads 166

Authors: Madhavi Godavarthy

Abstract:

The globalized world has been witnessing the ubiquity of the English language and has made it mandatory that students be equipped with the required Communication and soft skills. For students and especially for students studying in technical streams, gaining command over the English language is only a part of the bigger challenges they will face in the future. Linguistic capabilities if blended with the right attitude and a positive personality would deliver better results in the present environment of the digitalized world. An English classroom has that ‘space’; a space if utilized well by the teacher can pay rich dividends. The prescribed syllabus for English in the process of adapting itself to the challenges of a more and more technical world has meted out an indifferent treatment in including ‘literary’ material in their curriculum. A debate has always existed regarding the same and diversified opinions have been given. When the student is motivated to reach Literature through intrinsic motivation, it may contribute to his/her personality-development. In the present paper, the element of focus is on the scope and space to motivate students by creating a specific space for herself/himself amidst the schedules of the teaching-learning processes by taking into consideration a few literary excerpts for the purpose.

Keywords: English language, teaching and learning process, reader response theory, intrinsic motivation, literary texts

Procedia PDF Downloads 598

Authors: Argyro-Maria Skourmalla

Abstract:

Today’s reality is characterized by diversity in different levels and aspects of everyday life. Focusing on the aspect of language and communication in Higher Education (HE), the present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, adopted its new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. In addition, with around 10.000 students and staff coming from various countries around the world, linguistic diversity in this university is seen as both a resource and a challenge that calls for an inclusive and multilingual approach. The present paper includes data derived from semi-structured interviews with lecturing staff from different disciplines and an online survey with undergraduate students at the University of Luxembourg. Participants shared their experiences and point of view regarding linguistic diversity in this context. Findings show that linguistic diversity in this university is seen as an asset but comes with challenges, and even though there is progress in the use of multilingual practices, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: linguistic diversity, higher education, Luxembourg, multilingual practices, teaching, learning

Procedia PDF Downloads 53

Authors: Sun Zhe, Ruggero Micheletto

Abstract:

The research of neural network is very important for the development of advanced next generation intelligent devices and the medical treatment. The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. For this reason, we made a model with only two coupled neurons and studied the influence of connection strength between them. To emulate the neuronal activity of realistic neurons, we prefer to use the Izhikevich neuron model. This model can simulate the neuron variables accurately and it’s simplicity is very suitable to implement on computers. In this research, the parameter ρ is used to estimate the correlation coefficient between spike train of two coupling neurons.We think the results is very important for figuring out the mechanism between synchronization of coupling neurons and synaptic plasticity. The result also presented the importance of the spike frequency adaptation in complex systems.

Keywords: neural networks, noise, stochastic processes, coupled neurons, correlation coefficient, synchronization, pacemaker, synaptic plasticity

Procedia PDF Downloads 266

Authors: Ganiyu I. Lawal, Olatunde I. Sekunowo, Stephen I. Durowaye

Abstract:

Composites depending on the nature of their constituents and mode of production are regarded as one of the advanced materials that drive today’s technology. This paper attempts a short review of the subject matter with a general aim of pushing to the next level the frontier of knowledge as it impacts the technology of nano-particles manufacturing. The objectives entail an effort to; aggregate recent research efforts in this field, analyse research findings and observations, streamline research efforts and support industry in taking decision on areas of fund deployment. It is envisaged that this work will serve as a quick hand-on compendium material for researchers in this field and a guide to relevant government departments wishing to fund a research whose outcomes have the potential of improving the nation’s GDP.

Keywords: advanced materials, composites, mechanical properties, nano-particles

Procedia PDF Downloads 262

Authors: Sneha Thakur, Sanjeev Karmakar

Abstract:

This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

Procedia PDF Downloads 59

Authors: Reza Zakerinejad

Abstract:

Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

Procedia PDF Downloads 517

Authors: Yenni Anggrayni

Abstract:

The lack of awareness of the significant prevalence of school absenteeism in Indonesia, which ultimately results in high rates of school dropouts, is an unresolved issue. Therefore, this study aims to investigate the root causes of chronic absenteeism qualitatively and quantitatively using the bioecological systems paradigm in secondary schools for any reason. This study used an open-ended questionnaire to collect data from 1,148 students in six West Java Province districts/cities. Univariate and stepwise multiple logistic regression analyses produced a prediction model for the components. Analysis results show that poor teacher-student relationships, bullying by peers or teachers, negative perception of education, and lack of parental involvement in learning activities are the leading causes of chronic absenteeism. Another finding is to promote home-school partnerships to improve school climate and parental involvement in learning to address chronic absenteeism.

Keywords: bullying, chronic absenteeism, dropout of school, home-school partnerships, parental involvement

Procedia PDF Downloads 54

Authors: Mohammed Abu Shquier

Abstract:

This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

Procedia PDF Downloads 23

Authors: Kazeem Oluwatoyin Ajape

Abstract:

The study is concerned with the problem of how to improve the teaching of Arabic as a foreign language in Nigerian Higher Education System. The paper traces the historical background of Arabic education in Nigeria and also outlines the problems facing the language in Nigerian Institutions. It lays down some of the essential foundation work necessary for bringing about systematic and constructive improvements in the Teaching of Arabic as a Foreign Language (TAFL) by giving answers to the following research questions: what is the appropriate medium of instruction in teaching a foreign or second language? What is the position of English language in the teaching and learning of Arabic/Islamic education? What is the relevance of the present curriculum of Arabic /Islamic education in Nigerian institutions to the contemporary society? A survey of the literature indicates that a revolution is currently taking place in FL teaching and that a new approach known as the Communicative Approach (CA), has begun to emerge and influence the teaching of FLs in general, over the last decade or so. Since the CA is currently being adapted to the teaching of most major FLs and since this revolution has not yet had much impact on TAPL, the study explores the possibility of the application of the CA to the teaching of Arabic as a living language and also makes recommendations towards the development of the language in Nigerian Institutions of Higher Learning.

Keywords: Arabic Language, foreign language, Nigerian institutions, curriculum, communicative approach

Procedia PDF Downloads 589

Authors: Ruedee Niyomrath

Abstract:

The purposes of this research is aim to build the energy saving stove for stew coconut sugar. The research started from explores ceramic raw materials in local area, create the appropriate mixture of ceramic raw materials for construction material of stove, and make it by ceramic process. It includes design and build the energy saving stove, experiment the efficiency of energy saving stove as to thermal efficiency, energy saving, performance of time, and energy cost efficiency, transfer the knowledge for community, stove manufacturers, and technicians. The findings must be useful to the coconut sugar enterprises producing, to reduce the cost of production, preserve natural resources, and environments.

Keywords: ceramic raw material, energy saving stove, stove design, performance of stove, stove for stew coconut sugar

Procedia PDF Downloads 345

Authors: Meryem Kanzari, Rabah Boukhanouf, Hatem G. Ibrahim

Abstract:

Indirect Evaporative Cooling process has the advantage of supplying cool air at constant moisture content. However, such system can only supply air at temperatures above wet bulb temperature. This paper presents a mathematical model for a sub-wet bulb temperature indirect evaporative cooling arrangement that can overcome this limitation and supply cool air at temperatures approaching dew point and without increasing its moisture content. In addition, the use of porous ceramics as wet media materials offers the advantage of integration into building elements. Results of the computer show that the proposed design is capable of cooling air to temperatures lower than the ambient wet bulb temperature and achieving wet bulb effectiveness of about 1.17.

Keywords: indirect evaporative cooling, porous ceramic, sub-wet bulb temperature, mathematical modeling

Procedia PDF Downloads 278

Authors: Nihar Kanta Patra, Akhtar Hussain

Abstract:

This comprehensive study, through the perspective of librarians, explores the library as a metaphor and its profound significance in representing knowledge and learning. It delves into how librarians perceive the library as a metaphor and the ways in which it symbolizes the acquisition, preservation, and dissemination of knowledge. The research investigates the most common metaphors used to describe libraries, as witnessed by librarians, and analyzes how these metaphors reflect the evolving role of libraries in society. Furthermore, the study examines how the library metaphor influences the perception of librarians regarding academic libraries as physical places and academic library websites as virtual spaces, exploring their potential for learning and exploration. It investigates the evolving nature of the library as a metaphor over time, as seen by librarians, considering the changing landscape of information and technology. The research explores the ways in which the library metaphor has expanded beyond its traditional representation, encompassing digital resources, online connectivity, and virtual realms, and provides insights into its potential evolution in the future. Drawing on the experiences of librarians in their interactions with library users, the study uncovers any specific cultural or generational differences in how people interpret or relate to the library as a metaphor. It sheds light on the diverse perspectives and interpretations of the metaphor based on cultural backgrounds, educational experiences, and technological familiarity. Lastly, the study investigates the evolving roles of libraries as observed by librarians and explores how these changing roles can influence the metaphors we use to represent them. It examines the dynamic nature of libraries as they adapt to societal needs, technological advancements, and new modes of information dissemination. By analyzing these various dimensions, this research provides a comprehensive understanding of the library as a metaphor through the lens of librarians, illuminating its significance, evolution, and its transformative impact on knowledge, learning, and the changing role of libraries in society.

Keywords: library, librarians, metaphor, perception

Procedia PDF Downloads 74

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 124

Authors: S. C. Lin, W. W. Cheng, M. S. Wu

Abstract:

This study attempted to investigate the connection between teacher professional development program and students’ Learning. This study took Readers’ Theater Teaching Program (RTTP) for professional development as an example to inquiry how participants apply their new knowledge and skills learned from RTTP to their teaching practice and how the impact influence students learning. The goals of the RTTP included: 1) to enhance teachers RT content knowledge; 2) to implement RT instruction in teachers’ classrooms in response to their professional development. 2) to improve students’ ability of reading fluency in professional development teachers’ classrooms. This study was a two-year project. The researchers applied mixed methods to conduct this study including qualitative inquiry and one-group pretest-posttest experimental design. In the first year, this study focused on designing and implementing RTTP and evaluating participants’ satisfaction of RTTP, what they learned and how they applied it to design their English reading curriculum. In the second year, the study adopted quasi-experimental design approach and evaluated how participants RT instruction influenced their students’ learning, including English knowledge, skill, and attitudes. The participants in this study composed two junior high school English teachers and their students. Data were collected from a number of different sources including teaching observation, semi-structured interviews, teaching diary, teachers’ professional development portfolio, Pre/post RT content knowledge tests, teacher survey, and students’ reading fluency tests. To analyze the data, both qualitative and quantitative data analysis were used. Qualitative data analysis included three stages: organizing data, coding data, and analyzing and interpreting data. Quantitative data analysis included descriptive analysis. The results indicated that average percentage of correct on pre-tests in RT content knowledge assessment was 40.75% with two teachers ranging in prior knowledge from 35% to 46% in specific RT content. Post-test RT content scores ranged from 70% to 82% correct with an average score of 76.50%. That gives teachers an average gain of 35.75% in overall content knowledge as measured by these pre/post exams. Teachers’ pre-test scores were lowest in script writing and highest in performing. Script writing was also the content area that showed the highest gains in content knowledge. Moreover, participants hold a positive attitude toward RTTP. They recommended that the approach of professional learning community, which was applied in RTTP was benefit to their professional development. Participants also applied the new skills and knowledge which they learned from RTTP to their practices. The evidences from this study indicated that RT English instruction significantly influenced students’ reading fluency and classroom climate. The result indicated that all of the experimental group students had a big progress in reading fluency after RT instruction. The study also found out several obstacles. Suggestions were also made.

Keywords: teacher’s professional development, program evaluation, readers’ theater, english reading instruction, english reading fluency

Procedia PDF Downloads 377

Authors: Nugraheni Widianingtyas, Niko Albert Setiawan

Abstract:

For ELESP Teachers’ College, teaching learning strategies such as presentation and group discussion are classical ones to be implemented in the class. In order to create a breakthrough which can bring about more positive advancements in the learning process, a Focus Group Discussion (FGD) is being offered and implemented in certain classes. Interestingly, FGD is frequently used in the social-business inquiries such as for recruiting employees. It is then interesting to investigate FGD when it is implemented in the educational scope, especially in the Sociolinguistics class which regarded as one of the most arduous subjects in this study program. Thus, this study focused on how FGD enhances students Sociolinguistics mastery. In response to that, a quantitative survey research was conducted in which observation, questionnaire, and interview (triangulation method) became the instruments. The respondents of this study were 29 sixth-semester students who take Sociolinguistics of ELESP, Sanata Dharma University in 2017. The findings indicated that FGD could help students in enhancing Sociolinguistics mastery. In addition, it also revealed that FGD was exploring students’ logical thinking, English communication skill, and decision-making.

Keywords: focus group discussion, material mastery, sociolinguistics, teaching strategy

Procedia PDF Downloads 197

Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

Abstract:

The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

Procedia PDF Downloads 128

Authors: Shahrad Ebrahimzadeh

Abstract:

Nowadays, the main efforts of the researchers aim to constantly evolve new, optimized and efficient construction materials and methods related to reinforced concrete beams. Due to the fewer applied materials and offering a higher structural efficiency compared to solid concrete beams with the same concrete area, hollow reinforced concrete beams (HRCB) internally reinforced with steel rebars have been employed extensively for bridge structural members and high-rise buildings. Many experimental studies have been conducted to investigate the behavior of hollow beams subjected to bending loading and found that the structural performance of HRCBs is critically affected by many design parameters. While the proper design of the HRCBs demonstrated comparable behavior to solid sections, inappropriate design leads beams to be extremely prone to brittle failure. Another potential issue that needs to be further investigated is the replacement of steel bars with suitable materials due to their susceptibility to corrosion. Hence, to develop a reliable construction system, the application of GFRP bars as a non-corroding material has been utilized. Furthermore, this study aims to critically review the different design parameters that affect the flexural performance of the HRCBs and recognize the gaps of knowledge in the better design and more effective use of this construction system.

Keywords: design parameters, experimental investigations, hollow reinforced concrete beams, steel, GFRP, flexural strength

Procedia PDF Downloads 177

Authors: Ahmet Yonetken, Ayhan Erol

Abstract:

Intermetallic materials advanced technology materials that have outstanding mechanical and physical properties for high temperature applications. Especially creep resistance, low density and high hardness properties stand out in such intermetallics. The microstructure, mechanical properties of %80Cr-%10Ti and %10WC powders were investigated using specimens produced by tube furnace sintering at 1000-1400°C temperature. A composite consisting of ternary additions, a metallic phase, Ti,Cr and WC have been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), were investigated to characterize the properties of the specimens. Experimental results carried out for composition %80Cr-%10Ti and %10WC at 1400°C suggest that the best properties as 292HV and 5,34g/cm3 density were obtained at 1400°C.

Keywords: ceramic-metal, composites, powder metallurgy, sintering

Procedia PDF Downloads 452

Authors: Richard E. Miller

Abstract:

12.7-mm thick plates of 6061-T6511 aluminum alloy and high hardness steel (528 HV) were successfully joined by a friction stir bonding process using a tungsten-rhenium stir tool. Process parameter variation experiments, which included tool design geometry, plunge and traverse rates, tool offset, spindle tilt, and rotation speed, were conducted to develop a parameter set which yielded a defect free joint. Laboratory tensile tests exhibited yield stresses which exceed the strengths of comparable AA6061-to-AA6061 fusion and friction stir weld joints. Scanning electron microscopy and energy dispersive X-ray spectroscopy analysis also show atomic diffusion at the material interface region.

Keywords: dissimilar materials, friction stir, welding, materials science

Procedia PDF Downloads 249

Authors: Majed A. Alsalem

Abstract:

In our contemporary world, literacy is an essential skill that enables students to increase their efficiency in managing the many assignments they receive that require understanding and knowledge of the world around them. In addition, literacy enhances student participation in society improving their ability to learn about the world and interact with others and facilitating the exchange of ideas and sharing of knowledge. Therefore, literacy needs to be studied and understood in its full range of contexts. It should be seen as social and cultural practices with historical, political, and economic implications. This study aims to rebuild and reorganize the instructional designs that have been used for deaf and hard-of-hearing (DHH) students to improve their literacy level. The most critical part of this process is the teachers; therefore, teachers will be the center focus of this study. Teachers’ main job is to increase students’ performance by fostering strategies through collaborative teamwork, higher-order thinking, and effective use of new information technologies. Teachers, as primary leaders in the learning process, should be aware of new strategies, approaches, methods, and frameworks of teaching in order to apply them to their instruction. Literacy from a wider view means acquisition of adequate and relevant reading skills that enable progression in one’s career and lifestyle while keeping up with current and emerging innovations and trends. Moreover, the nature of literacy is changing rapidly. The notion of new literacy changed the traditional meaning of literacy, which is the ability to read and write. New literacy refers to the ability to effectively and critically navigate, evaluate, and create information using a range of digital technologies. The term new literacy has received a lot of attention in the education field over the last few years. New literacy provides multiple ways of engagement, especially to those with disabilities and other diverse learning needs. For example, using a number of online tools in the classroom provides students with disabilities new ways to engage with the content, take in information, and express their understanding of this content. This study will provide teachers with the highest quality of training sessions to meet the needs of DHH students so as to increase their literacy levels. This study will build a platform between regular instructional designs and digital materials that students can interact with. The intervention that will be applied in this study will be to train teachers of DHH to base their instructional designs on the notion of Technology Acceptance Model (TAM) theory. Based on the power analysis that has been done for this study, 98 teachers are needed to be included in this study. This study will choose teachers randomly to increase internal and external validity and to provide a representative sample from the population that this study aims to measure and provide the base for future and further studies. This study is still in process and the initial results are promising by showing how students have engaged with digital books.

Keywords: deaf and hard of hearing, digital books, literacy, technology

Procedia PDF Downloads 476

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

Procedia PDF Downloads 342

Authors: Aleš Florian, Lenka Ševelová

Abstract:

Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

Procedia PDF Downloads 317