Search results for: learning pattern

Authors: Md. Shoffikul Islam, Hongqing Hu

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Immobilizing trace elements by reducing their mobility and bioavailability through amendment application, especially biochar (BC), is a cost-effective and efficient method to address their toxicity in the soil environment. However, the low molecular weight organic acids (LMWOAs) in the rhizosphere could affect BC's efficiency to immobilize trace metals as the LMWOAs could either mobilize or fix metals in the soils. Therefore, understanding the BC's and LMWOAs' interaction mechanisms on metals stabilization in the rhizosphere is crucial. The present study examined the impact of BC derived from rice husk, tartaric acid (TA), and oxalic acid (OA), and the combination of BC and TA/OA on the changes of cadmium (Cd), lead (Pb), and zinc (Zn) among their geochemical forms through incubation experiment. The changes of zeta potential and X-ray diffraction (XRD) pattern of BC and BC-amended soils to investigate the probable mechanisms of trace elements' immobilization by BC under the attacks of TA and OA were also examined. The rice husk BC at 5% (w/w) was mixed with the air-dry soil (an Anthrosols) contaminated with Cd, Pb, and Zn in the plastic pot. The TA and OA each at 2, 5, 10, and 20 mM kg-1 (w/v) were added separately into the pot. All the ingredients were mixed thoroughly with the soil. A control (CK) treatment was also prepared without BC, TA, and OA addition. After 7, 15, and 60 days of incubation with 60% (w/v) moisture level at 25 °C, the incubated soils were determined for pH and EC and were sequentially extracted to assess the metals' transformation in soil. The electronegative charges and XRD peaks of BC and BC-amended soils were also measured. The BC, low level of TA (2 mM kg-1 soil), and BC plus the low concentration of TA (BC-TA2) addition considerably declined the acid-soluble Cd, Pb, and Zn in which BC-TA2 was found to be the most effective treatment. The trends were reversed concerning the high levels of TA (>5-20 mM kg-1 soil), all levels of OA (2-20 mM kg-1 soil), and the BC plus high levels of TA/OA treatments. BC-TA2 changed the highest amounts of acid-soluble and reducible metals to the oxidizable and residual fractions with time. The most increased electronegative charges of BC-TA2 indicate its (BC-TA2) highest metals' immobilizing efficiency, probably through metals adsorption and fixation with the negative charge sites. The XRD study revealed the presence of P, O, CO32-, and Cl1- in BC, which might be responsible for the precipitation of CdCO3, pyromorphite, and hopeite concerning Cd, Pb, and Zn immobilization, respectively. The findings demonstrated that the low level of TA increased metals immobilization, while the high levels of TA and all levels of OA enhanced their mobilization. The BC-TA2 was the best treatment in stabilizing metals in soil.

Keywords: biochar, immobilization, low molecular weight organic acids, trace elements contaminated soil

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Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

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Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

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Authors: Aparna Soni

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The much-celebrated foretold story of Indian city engines driving the growth of India has been scrutinized to have serious consequences. A wide spectrum of scholarship has brought to light the un-equalizing effects and the need to adopt a rights-based approach to development planning in India. Notably, these concepts and discourses ubiquitously entail the study of land struggles in the making of Urban. In fact, the very progression of the primitive accumulation theory to accumulation by dispossession, followed by ‘dispossession without development,’ thereafter Development without dispossession and now as Dispossession by financialization noticeably the last three developing in a span of mere three decades, is evidence enough to trace the centrality and evolving role of land in the making of urban India. India, in the last decade, has seen its regional governments actively experimenting with alternative models of land assembly (Amaravati and Delhi land pooling models, the loudly advertised ones). These are publicized as a replacement to the presumably cost and time antagonistic, prone to litigation land acquisition act of 2013. It has been observed that most of the literature treats these models as a generic large bracket of land expropriation and do not, in particular, try to differentially analyse to granularly find a pattern in these alternatives. To cater to this gap, this research comparatively studies these alternative land, assembly models. It categorises them based on their basic architecture, spatial and sectoral application, and governance frameworks. It is found that these alternatives are ad-hoc and fragmented pieces of legislation. These are fit for profit models commodifying land to ease its access by the private sector for real estate led growth. The research augments the literature on the privatization of land use planning in India. Further, it attempts to discuss the increasing role a landowner is expected to play in the future and suggests a way forward to safeguard them from market risks. The study involves a thematic analysis of the policy elements contained in legislative/policy documents, notifications, office orders. The study also derives from the various widely circulated print media information. With the present field-visit limitations, the study relies on documents accessed open-source in the public domain.

Keywords: commodification, dispossession, land acquisition, landowner

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Daijun Chen

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Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

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Authors: Mirain Rhys, Kevin Smith

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In 2017, the Welsh Government introduced an ambitious, new strategy to increase the number of Welsh speakers in Wales to 1 million by 2050. The Welsh education system is a vitally important feature of this strategy. All children attending state schools in Wales learn Welsh as a second language until the age of 16 and are assessed at General Certificate of Secondary Education (GCSE) level. In 2013, a review of Welsh second language instruction in Key Stages 3 and 4 was completed. The report identified considerable gaps in teachers’ preparation and training for teaching Welsh; poor Welsh language ethos at many schools; and a general lack of resources to support the instruction of Welsh. Recommendations were made across a number of dimensions including curriculum content, pedagogical practice, and teacher assessment, training, and resources. With a new national curriculum currently in development, this study builds on this review and provides unprecedented detail into pupils’ and teachers’ perceptions of Welsh language instruction. The current research built on data taken from an existing capacity building research project on Welsh education, the Wales multi-cohort study (WMS). Quantitative data taken from WMS surveys with over 1200 pupils in schools in Wales indicated that Welsh language lessons were the least enjoyable subject among pupils. The current research aimed to unpick pupil experiences in order to add to the policy development context. To achieve this, forty-four pupils and four teachers in three schools from the larger WMS sample participated in focus groups. Participants from years 9, 11 and 13 who had indicated positive, negative and neutral attitudes towards the Welsh language in a previous WMS survey were selected. Questions were based on previous research exploring issues including, but not limited to pedagogy, policy, assessment, engagement and (teacher) training. A thematic analysis of the focus group recordings revealed that the majority of participants held positive views around keeping the language alive but did not want to take on responsibility for its maintenance. These views were almost entirely based on their experiences of learning Welsh at school, especially in relation to their perceived lack of choice and opinions around particular lesson strategies and assessment. Analysis of teacher interviews highlighted a distinct lack of resources (materials and staff alike) compared to modern foreign languages, which had a negative impact on student motivation and attitudes. Both staff and students indicated a need for more practical, oral language instruction which could lead to Welsh being used outside the classroom. The data corroborate many of the review’s previous findings, but what makes this research distinctive is the way in which pupils poignantly address generally misguided aims for Welsh language instruction, poor pedagogical practice and a general disconnect between Welsh instruction and its daily use in their lives. These findings emphasize the complexity of incorporating the educational sector in strategies for Welsh language maintenance and the complications arising from pedagogical training, support, and resources, as well as teacher and pupil perceptions of, and attitudes towards, teaching and learning Welsh.

Keywords: bilingual education, language maintenance, language revitalisation, minority languages, Wales

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Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: sound detection, impulsive signal, background noise, neural network

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Authors: Hande Barkan-Ozturk, Angelika Menner, Alexander Bismarck

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Microfluidic mixing technology grew rapidly in the past few years due to its many advantages over the macro-scale mixing, especially the ability to use small amounts of internal volume and also very high surface-to-volume ratio. The Reynold number identify whether the mixing is operated by the laminar or turbulence flow. Therefore, mixing with very fast kinetic can be achieved by diminishing the channel dimensions to decrease Reynold number and the laminar flow can be accomplished. Moreover, by using obstacles in the micromixer, the mixing length and the contact area between the species have been increased. Therefore, the channel geometry and its surface property have great importance to reach satisfactory mixing results. Since poly(-merised) High Internal Phase Emulsions (polyHIPEs) have more than 74% porosity and their pores are connected each other with pore throats, which cause high permeability, they are ideal candidate to build a micromixer. The HIPE precursor is commonly produced by using an overhead stirrer to obtain relatively large amount of emulsion in batch process. However, we will demonstrate that a desired amount of emulsion can be prepared continuously with micromixer build from polyHIPE, and such HIPE can subsequently be employed as ink in 3D printing process. In order to produce the micromixer a poly-Pickering(St-co-DVB)HIPE with 80% porosity was prepared with modified silica particles as stabilizer and surfactant Hypermer 2296 to obtain open porous structure and after coating of the surface, the three 1/16' ' PTFE tubes to transfer continuous (CP) and internal phases (IP) and the other is to collect the emulsion were placed. Afterwards, the two phases were injected in the ratio 1:3 CP:IP with syringe dispensers, respectively, and highly viscoelastic H(M)IPE, which can be used as an ink in 3D printing process, was gathered continuously. After the polymerisation of the resultant emulsion, polyH(M)IPE has interconnected porous structure identical to the monolithic polyH(M)IPE indicating that the emulsion can be prepared constantly with poly-Pickering-HIPE as micromixer and it can be used to prepare desired pattern with a 3D printer. Moreover, the morphological properties of the emulsion can be adjustable by changing flow ratio, flow speed and structure of the micromixer.

Keywords: 3D-Printing, emulsification, macroporous polymer, micromixer, polyHIPE

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Authors: Iman Dwi Almunandar, Nellawaty A. Tewu, Anshari Al Ghaniyy

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The emergence of academic procrastination behavior among students in Indonesian, especially the students of Faculty of Psychology at YARSI University becomes a habit to be underestimated, so often interfere with the effectiveness of learning process. The lecturers at the Faculty of Psychology YARSI University have very often warned students to be able to do and collect assignments accordance to predetermined deadline. However, they are still violated it. According to researchers, this problem needs to do a proper training for the solution to minimize academic procrastination behavior on students. In this study, researchers conducted analyze needs for deciding whether need the training or not. Number of sample is 30 respondents which being choose with a simple random sampling. Measurement of academic procrastination behavior is using the theory by McCloskey (2011), there are six dimensions: Psychological Belief about Abilities, Distractions, Social Factor of Procrastination, Time Management, Personal Initiative, Laziness. Methods of analyze needs are using Questioner, Interview, Observations, Focus Group Discussion (FGD), Intelligence Tests. The result of analyze needs shows that psychology students generation of 2015 at the Faculty of Psychology YARSI University need for training on Time Management.

Keywords: procrastination, psychology, analyze needs, behavior

Procedia PDF Downloads 357

Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

Procedia PDF Downloads 337

Authors: Laura Brennan, Ram Balakumar

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ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology.

Keywords: artificial intelligence, otolaryngology, surgical training, medical education

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Luciana Salomon

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The Andes hold one of the highest plant species diversity in the world. How such diversity originated is one of the most intriguing questions in studies addressing the pattern of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as major triggers of this spectacular diversity. The Andes are one of the most species-rich area for the largest genus from the Asteraceae family, Senecio. There, the genus presents an incredible variation in growth form and ecological niche space. If this diversity of Andean Senecio can be explained by a monophyletic origin and subsequent radiation has not been tested up to now. Previous studies trying to disentangle the evolutionary history of some Andean Senecio struggled with the relatively low resolution and support of the phylogenies, which is indicative of recently radiated groups. Using Hyb-Seq, a powerful approach is available to address phylogenetic questions in groups whose evolutionary histories are recent and rapid. This approach was used for Senecio to build a phylogenetic backbone on which to study the mechanisms shaping its hyper-diversity in the Andes, focusing on Senecio ser. Culcitium, an exclusively Andean and well circumscribed group presenting large morphological variation and which is widely distributed across the Andes. Hyb-Seq data for about 130 accessions of Seneciowas generated. Using standard data analysis work flows and a newly developed tool to utilize paralogs for phylogenetic reconstruction, robustness of the species treewas investigated. Fully resolved and moderately supported species trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within this group, some species formed well-supported clades congruent with morphology, while some species would not have exclusive ancestry, in concordance with previous studies showing a geographic differentiation. Additionally, paralogs were detected for a high number of loci, indicating duplication events and hybridization, known to be common in Senecio ser. Culcitium might have lead to hybrid speciation. The rapid diversification of the group seems to have followed a south-north distribution throughout the Andes, having accelerated in the conquest of new habitats more recently available: i.e., Montane forest, Paramo, and Superparamo.

Keywords: evolutionary radiations, andes, paralogy, hybridization, senecio

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

Procedia PDF Downloads 139

Authors: Max Neu

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A large variety of studies on the utilization of games in classroom settings promote positive effects on students motivation for learning. Still, most of those studies rarely can give any specifics about the factors that might lead to changes in students motivation. The undertaken study has been conducted in tandem with the development of a highly classroom-optimized serious game, with the intent of providing a subjectively positive initial contact with the subject of political participation and to enable the development of personal motivation towards further engagement with the topic. The goal of this explorative study was to Identify the factors that influence students motivation towards the subject when serious games are being used in classroom education. Therefor, students that have been exposed to a set of classes in which a classroom optimized serious game has been used. Afterwards, a selection of those have been questioned in guided interviews that have been evaluated through Qualitative Content Analysis. The study indicates that at least 23 factors in the categories, mechanics, content and context potentially influence students motivation to engage with the classes subject. The conclusions are of great value for the further production of classroom games as well as curricula involving digital games in general.

Keywords: formal education, games in classroom, motivation, political education

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Sally A. Brown

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Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

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Authors: Mohammad Anwar, Shah Waliullah

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The development of science and technology in the present era has an urgent demand for the training of thinking of undergraduates. This requirement actively promotes research and teaching of basic theories, beneficial to the career development of students. This study clarified the dialectical relation between the thermodynamic equilibrium constant and reaction rate constant through the contrast thinking method. Findings reveal that both the isobaric Van't Hoff equation and the Arrhenius equation had four similar forms, and the change in the trend of both constants showed a similar law. By the derivation of the formation rate constant of the product (KY) and the consumption rate constant of the reactant (KA), the ratio of both constants at the end state indicated the nature of the equilibrium state in agreement with that of the thermodynamic equilibrium constant (K^θ (T)). This study has thus presented that the thermodynamic equilibrium constant contained the characteristics of microscopic dynamics based on the analysis of the reaction mechanism, and both constants are organically connected and unified. The reaction enthalpy and activation energy are closely related to each other with the same connotation.

Keywords: thermodynamic equilibrium constant, reaction rate constant, PBL teaching, dialectical relation, innovative thinking

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Authors: Hassan Attahiru Gwandu

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This study aims at surveying and analyzing the contribution of Sokoto scholars or Sokoto Caliphate in the development of science and technology in West Africa. Today, it is generally accepted that the 19^th century Islamic revivalism in Hausaland was a very important revolution in the history of Hausa society and beyond. It is therefore, as a result of this movement or Jihad; the Hausaland (West Africa in general) witnessed several changes and transformations. These changes were in different sectors of life from politics, economy to social and religious aspect. It is these changes especially on religion that will be given considerations in this paper. The jihad resulted is the establishment of an Islamic state of Sokoto Caliphate, the revival Islam and development of learning and scholarship. During the existence of this Caliphate, a great deal of scholarship on Islamic laws were revived, written and documented by mostly, the three Jihad leaders; Usmanu Danfodiyo, his brother Abdullahi Fodiyo and his son Muhammad Bello. The trio had written more than one thousand books and made several verdicts on Islamic medicine. This study therefore, seeks to find out the contributions of these scholars or the Sokoto caliphate in the development of science in West Africa.

Keywords: Sokoto caliphate, scholarship, science and technology, West Africa

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Authors: Waddah S. Abdullah, Khaled F. Al-Omari

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Electrokinetic remediation is one of the most influential and effective methods to decontaminate contaminated soils. Electroosmosis and electromigration are the processes of electrochemical extraction of contaminants from soils. The driving force that causes removing contaminants from soils (electroosmosis process or electromigration process) is voltage gradient. Therefore, the electric field distribution throughout the soil domain is extremely important to investigate and to determine the factors that help to establish a uniform electric field distribution in order to make the clean-up process work properly and efficiently. In this study, small-sized passive electrodes (made of graphite) were placed at predetermined locations within the soil specimen, and the voltage drop between these passive electrodes was measured in order to observe the electrical distribution throughout the tested soil specimens. The electrokinetic test was conducted on two types of soils; a sandy soil and a clayey soil. The electrical distribution throughout the soil domain was conducted with different tests properties; and the electrical field distribution was observed in three-dimensional pattern in order to establish the electrical distribution within the soil domain. The effects of density, applied voltages, and degree of saturation on the electrical distribution within the remediated soil were investigated. The distribution of the moisture content, concentration of the sodium ions, and the concentration of the calcium ions were determined and established in three-dimensional scheme. The study has shown that the electrical conductivity within soil domain depends on the moisture content and concentration of electrolytes present in the pore fluid. The distribution of the electrical field in the saturated soil was found not be affected by its density. The study has also shown that high voltage gradient leads to non-uniform electric field distribution within the electroremediated soil. Very importantly, it was found that even when the electric field distribution is uniform globally (i.e. between the passive electrodes), local non-uniformity could be established within the remediated soil mass. Cracks or air gaps formed due to temperature rise (because of electric flow in low conductivity regions) promotes electrical tortuosity. Thus, fracturing or cracking formed in the remediated soil mass causes disconnection of electric current and hence, no removal of contaminant occur within these areas.

Keywords: contaminant removal, electrical tortuousity, electromigration, electroosmosis, voltage distribution

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

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Authors: Hamnah Nisar

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As food is something which is particularly important for survival, in fact, it improves the quality of life and promotes health. Quality food is a key to a healthy life. Consumption of food depends on the knowledge we have regarding the nutrients it contains. Moreover, the awareness and knowledge about something is an initial stage for its improvement. We cannot work on anything unless we have knowledge about it. The pros and cons, effects, causes, dos, and don'ts, especially for an important things like food, are a necessity to learn. That is why my research would be all about analyzing what difference awareness makes on people and how making people more aware about a certain thing can help them improve their lifestyles and bring a positive change for them. The research would be done through questionnaires and interviews among two classes, one would be the upper class and the other would-be lower class. Because the upper class can easily access learning facilities and can know about the new things than the lower class. The questions would be related to what kind of food do they consume, what health issues they face, or what health issues are common among their regions. The results of the research would be helpful to know firstly the effects of awareness and education regarding food on health, how a basic thing like knowledge can have a significant effect on health and can be the cause of several diseases.

Keywords: nutrition, awareness, quality food, knowledge

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Authors: Sonay Ödemiş

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Movement Staff Notation System (MSNS) is a movement transcription, analyzing method, and it's been constantly improved since it was first developed in 2005. This method is based on human anatomy, is being used and applied in the lessons at The Department of Turkish Folk Dances in Istanbul Technical University, nowadays. In this research, it is aimed to discover, how MSNS can help to participants about learning the basic movements of lower extremity. This experiment has six volunteers who were randomly selected. Each volunteer has been graded for their dance backgrounds and all the volunteers have been studied for six weeks. Each week has included different topic and examples such as contacts on foot, jumps, timing, directions and basic symbols of MSNS. Examples have changed from easy to hard. On conclusion, 6 volunteer subjects were tested in final test. The tests were recorded with the camera. In this presentation, it will be explained and detailed the results of the reading test on MSNS. Some of important video records will be watched and interpreted after the test. As a conclusion, all the scores will be interpreted and assessed from different perspectives.

Keywords: dance notation, Turkish dances, reading test, Education

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Authors: Norhidayu Muhamad Zain

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Gelatin, a purified protein derived mostly from porcine and bovine sources, is used widely in food manufacturing, pharmaceutical, and cosmetic industries. However, the presence of any porcine-related products are strictly forbidden for Muslim and Jewish consumption. Therefore, analytical methods offering reliable results to differentiate the sources of gelatin are needed. The aim of this study was to differentiate the sources of gelatin (porcine and tilapia fish) using Fourier transform infrared- attenuated total reflection (FTIR-ATR) combined with two dimensional infrared (2DIR) correlation analysis. Porcine gelatin (PG) and tilapia fish gelatin (FG) samples were diluted in distilled water at concentrations ranged from 4-20% (w/v). The samples were then analysed using FTIR-ATR and 2DIR correlation software. The results showed a significant difference in the pattern map of synchronous spectra at the region of 1000 cm⁻¹ to 1100 cm⁻¹ between PG and FG samples. The auto peak at 1080 cm⁻¹ that attributed to C-O functional group was observed at high intensity in PG samples compared to FG samples. Meanwhile, two auto peaks (1080 cm⁻¹ and 1030 cm⁻¹) at lower intensity were identified in FG samples. In addition, using 2D correlation analysis, the original broad water OH bands in 1D IR spectra can be effectively differentiated into six auto peaks located at 3630, 3340, 3230, 3065, 2950 and 2885 cm⁻¹ for PG samples and five auto peaks at 3630, 3330, 3230, 3060 and 2940 cm⁻¹ for FG samples. Based on the rule proposed by Noda, the sequence of the spectral changes in PG samples is as following: NH₃⁺ amino acid > CH₂ and CH₃ aliphatic > OH stretch > carboxylic acid OH stretch > NH in secondary amide > NH in primary amide. In contrast, the sequence was totally in the opposite direction for FG samples and thus both samples provide different 2D correlation spectra ranged from 2800 cm-1 to 3700 cm⁻¹. This method may provide a rapid determination of gelatin source for application in food, pharmaceutical, and cosmetic products.

Keywords: 2 dimensional infrared (2DIR) correlation analysis, Fourier transform infrared- attenuated total reflection (FTIR-ATR), porcine gelatin, tilapia fish gelatin

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Authors: Sireetorn Kuharat, Anwar Beg

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In this study, multi-mode heat transfer characteristics of spacecraft solar collectors are investigated computationally. Two-dimensional steady-state incompressible laminar Newtonian viscous convection-radiative heat transfer in a rectangular solar collector geometry. The ANSYS FLUENT finite volume code (version 17.2) is employed to simulate the thermo-fluid characteristics. Several radiative transfer models are employed which are available in the ANSYS workbench, including the classical Rosseland flux model and the more elegant P1 flux model. Mesh-independence tests are conducted. Validation of the simulations is conducted with a computational Harlow-Welch MAC (Marker and Cell) finite difference method and excellent correlation. The influence of aspect ratio, Prandtl number (Pr), Rayleigh number (Ra) and radiative flux model on temperature, isotherms, velocity, the pressure is evaluated and visualized in color plots. Additionally, the local convective heat flux is computed and solutions are compared with the MAC solver for various buoyancy effects (e.g. Ra = 10,000,000) achieving excellent agreement. The P1 model is shown to better predict the actual influence of solar radiative flux on thermal fluid behavior compared with the limited Rosseland model. With increasing Rayleigh numbers the hot zone emanating from the base of the collector is found to penetrate deeper into the collector and rises symmetrically dividing into two vortex regions with very high buoyancy effect (Ra >100,000). With increasing Prandtl number (three gas cases are examined respectively hydrogen gas mixture, air and ammonia gas) there is also a progressive incursion of the hot zone at the solar collector base higher into the solar collector space and simultaneously a greater asymmetric behavior of the dual isothermal zones. With increasing aspect ratio (wider base relative to the height of the solar collector geometry) there is a greater thermal convection pattern around the whole geometry, higher temperatures and the elimination of the cold upper zone associated with lower aspect ratio.

Keywords: thermal convection, radiative heat transfer, solar collector, Rayleigh number

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Authors: Ersumo Tessema, Bogale Girmaye Tamrat, Mohammed Burka

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Background: Hyperthyroidism is a common thyroid disorder especially in women and characterized by increased thyroid hormone synthesis and secretion. The disorder manifests predominantly as Graves’ disease in iodine-sufficient areas and has increasing prevalence in iodine-deficient countries in patients with nodular thyroid disease and following iodine fortification. In Ethiopia, the magnitude of the disorder is unknown and, in Africa, due to scarcity of resources, its management remains suboptimal. Objective: The aim of this study was to analyze the pattern and management of patients with hyperthyroidism at the United Vision Medical Services Center, Addis Ababa between August 30, 2013, and February 1, 2018. Patients and methods: The study was a retrospective analysis of medical records of all patients with hyperthyroidism at the United Vision Private Medical Services Center, Addis Ababa. A questionnaire was filled out; the collected data entered into a computer and statistically analyzed using the SPSS package. The results were tabulated and discussed with literature review. Results: A total of 589 patients were included in this study. The median age was 40 years, and the male to female ratio was 1.0:7.9. Most patients (93%) presented with goiter and the associated features of toxic goiter except weight loss, sweating and tachycardia were uncommon. Majority of patients presented more than two years after the onset of their presenting symptoms. The most common physical finding (91%), as well as diagnosis, was toxic nodular goiter. The most frequent (83%) derangement in the thyroid function tests was a low thyroid-stimulating hormone, and the most commonly (94%) used antithyroid drug was a propylthiouracil. The most common (96%) surgical procedure in 213 patients was a near-total thyroidectomy with a postoperative course without incident in 92% of all the patients. Conclusion: The incidence and prevalence of hyperthyroidism are apparently on the increase in Addis Ababa, which may be related to the existing severe iodine-deficiency and or the salt iodation program (iodine-induced hyperthyroidism). Hyperthyroidism predominantly affects women and, in surgical services, toxic nodular goiter is more common than diffuse goiter, and the treatment of choice in experienced hands is a near-total thyroidectomy.

Keywords: Ethiopia, grave’s disease, hyperthyroidism, toxic nodular goiter

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: Sonal H. Singh, Bhaskar Bhowmick

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The research hypothesis formulated in this paper examines the importance of microfinance provision for entrepreneurship development by engendering a high level of entrepreneurial orientation among the grassroots entrepreneurs. A theoretically well supported empirical framework is proposed to identify the influence of financial services and non-financial services provided by microfinance institutes in strengthening the impact of grassroots innovation on entrepreneurial orientation under resource constraints. In this paper, Grassroots innovation is perceived in three dimensions: new learning practice, localized solution, and network development. The study analyzes the moderating effect of microfinance provision on the relationship between grassroots innovation and entrepreneurial orientation. The paper employed structural equation modelling on 400 data entries from the grassroots entrepreneurs in India. The research intends to help policymakers, entrepreneurs and microfinance providers to promote the innovative design of microfinance services for the well-being of grassroots entrepreneurs and to foster sustainable entrepreneurship development.

Keywords: entrepreneurship development, grassroots innovation, India, structural equation model

Procedia PDF Downloads 246