Search results for: computer assisted language learning

Authors: Thais Cavalheri Santos, Pedro Jose Gabriel Ferreira, Alexandre Daliberto Frugoli, Lucio Leonardo, Pedro Americo Frugoli

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This paper presents a low cost education proposal to be used in engineering courses. The engineering education in universities of a developing country that is in need of an increasing number of engineers carried out with quality and affordably, pose a difficult problem to solve. In Brazil, the political and economic scenario requires academic managers able to reduce costs without compromising the quality of education. Within this context, the elaboration of a physics principles teaching method with the construction of an electronic balance is proposed. First, a method to develop and construct a load cell through which the students can understand the physical principle of strain gauges and bridge circuit will be proposed. The load cell structure was made with aluminum 6351T6, in dimensions of 80 mm x 13 mm x 13 mm and for its instrumentation, a complete Wheatstone Bridge was assembled with strain gauges of 350 ohms. Additionally, the process involves the use of a software tool to document the prototypes (design circuits), the conditioning of the signal, a microcontroller, C language programming as well as the development of the prototype. The project also intends to use an open-source I/O board (Arduino Microcontroller). To design the circuit, the Fritizing software will be used and, to program the controller, an open-source software named IDE®. A load cell was chosen because strain gauges have accuracy and their use has several applications in the industry. A prototype was developed for this study, and it confirmed the affordability of this educational idea. Furthermore, the goal of this proposal is to motivate the students to understand the several possible applications in high technology of the use of load cells and microcontroller.

Keywords: Arduino, load cell, low-cost education, strain gauge

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Authors: Maryam Khalili, Fateme Ghanei

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As one of the most significant phenomena of industrialized societies, tourism plays a key role in encouraging regional developments and enhancing higher standards of living for local communities in particular. Traveling is a formative experience endowed with lessons on various aspects of life. It allows us learning how to enhance the social position as well as the social relationships. However, people forget the need to travel and gain first-hand experiences as they have to cope with the ever-increasing rate of stress created by the disorders and routines of the urban dwelling style. In this paper, various spaces of such experiences were explored through a virtual tour with two underlying aims: 1) encouraging, informing, and educating the community in terms of tourism development, and 2) introducing a temporary release from the routines. This study enjoyed a practical-qualitative research methodology, and the required data were collected through observation and using a multiple-response questionnaire. The participants (19-48 years old) included 41 citizens of both genders (63.4% male and 36.6% female) from two regions in Tehran, selected by cluster-probability sampling. The results led to development of a spatial design for a virtual tour experience in Tehran where different areas are explored to both raise people’s awareness and educate them on their cultural heritage.

Keywords: ecotourism, education, gamification, social interaction, urban design, virtual tour

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Julio Kauss, Miguel Cadillo, David Mauricio

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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: e-commerce, retail, SMEs, reference model

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Authors: Devinder Singh, Rajneesh Kumar, Arvind Kumar

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The present investigation deals with the deformation of micropolar generalized thermoelastic solid subjected to thermo-mechanical loading due to a thermal laser pulse. Laplace transform and Fourier transform techniques are used to solve the problem. Thermo-mechanical laser interactions are taken as distributed sources to describe the application of the approach. The closed form expressions of normal stress, tangential stress, coupled stress and temperature are obtained in the domain. Numerical inversion technique of Laplace transform and Fourier transform has been implied to obtain the resulting quantities in the physical domain after developing a computer program. The normal stress, tangential stress, coupled stress and temperature are depicted graphically to show the effect of relaxation times. Some particular cases of interest are deduced from the present investigation.

Keywords: pulse laser, integral transform, thermoelastic, boundary value problem

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Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Turkyh Alotibi, Ghadah Obeid Alrasheed, Afaf Saad Alshaibani, Moneerah Obeid Alrasheed

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This study explores factors that influence MBA enrolment and investigates strategic prerequisites for developing a viable online MBA program at Alfaisal University in the Kingdom of Saudi Arabia. It compares students’ perspectives about online MBA against the face-to-face on-site MBA program. With the self-administered online survey tool, we collected data from 52 first- and second-year MBA students enrolled at Alfaisal University for the 2021 Fall Semester. The data from the survey questionnaire, distributed at the university’s College of Business, reports that approximately 60% of MBA students prefer face-to-face, in-person courses. Their preference for considering an online MBA, primarily rests on two factors, the university’s ranking (68% would enroll for an online MBA program offered by Harvard Business School) and 34.07% for the program timing (timetable). Alfaisal University’s outstanding ranking makes it viable to offer an online MBA either independently or in collaboration with other internationally reputed business schools. The paper contains useful insights to set “the strategic agenda for Online MBA program” in no accredited University but with a good reputation. The information from the case study could be useful for supporting the strategic intent to start an Online MBA program in Saudi Arabia.

Keywords: online MBA, online education demand, university management, course evaluation, blended learning

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Jay-R. Hosana Leonidas, Jayson A. Lucilo

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The K-12 Curriculum in the Philippines shed light to mathematics education as it recognizes the use of smartphones/mobile phones as appropriate tools necessary in teaching mathematics. However, there were limited pieces of evidence on the use of these devices in teaching and learning process. This descriptive study developed lessons integrating the use of mobile phone applications with basis on low-level competencies of students in Precalculus and determined its effects on students’ conceptual understanding, procedural skills, and attitudes towards Precalculus. Employing Bring Your Own Device (BYOD) scheme in the study, lessons developed were conducted among Grade 11 Science, Technology, Engineering, and Mathematics (STEM) students at Central Bicol State University of Agriculture for the academic year 2018-2019. This study found that there is a significant difference between the competency levels of students along conceptual understanding and procedural skills prior to and after the conduct of lessons developed. Also, it disclosed that the use of mobile phone applications had positive effects on students’ attitudes towards Precalculus. Thus, the use of mobile phone applications in teaching Precalculus can enrich students’ understanding of concepts and procedural skills (solving and graphing skills) and can increase students’ motivation, self-confidence, and enjoyment in dealing with Precalculus.

Keywords: bring your own device, mathematics education, mobile phone applications, senior high school

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Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Nkereke M. Essien

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The intention of this paper is to examine stress in the Educated Nigerian Accent of English (ENAE) with the aim of analyzing stress and rhythmic patterns of Nigerian English. Our aim also is to isolate differences and similarities in the stress patterns studied and also know what forms the accent of these Educated Nigerian English (ENE) which marks them off from other groups or English’s of the world, to ascertain and characterize it and to provide documented evidence for its existence. Nigerian stress and rhythmic patterns are significantly different from the British English stress and rhythmic patterns consequently, the educated Nigerian English (ENE) features more stressed syllables than the native speakers’ varieties. The excessive stressed of syllables causes a contiguous “Ss” in the rhythmic flow of ENE, and this brings about a “jerky rhythm’ which distorts communication. To ascertain this claim, ten (10) Nigerian speakers who are educated in the English Language were selected by a stratified Random Sampling technique from two Federal Universities in Nigeria. This classification belongs to the education to the educated class or standard variety. Their performance was compared to that of a Briton (control). The Metrical system of analysis was used. The respondents were made to read some words and utterance which was recorded and analyzed perceptually, statistically and acoustically using the one-way Analysis of Variance (ANOVA). The Turky-Kramer Post Hoc test, the Wilcoxon Matched Pairs Signed Ranks test, and the Praat analysis software were used in the analysis. It was revealed from our findings that the Educated Nigerian English speakers feature more stressed syllables in their productions by spending more time in pronouncing stressed syllables and sometimes lesser time in pronouncing the unstressed syllables. Their overall tempo was faster. The ENE speakers used tone to mark prominence while the native speaker used stress to mark pronounce, typified by the control. We concluded that the stress pattern of the ENE speakers was significantly different from the native speaker’s variety represented by the control’s performance.

Keywords: accent, Nigerian English, rhythm, stress

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Authors: Carmela Perta

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Among the studies flourished in the field of historical sociolinguistics, mainly in the strand devoted to English history, during its Medieval and early modern phases, multilingual texts had been analysed using theories and models coming from contact linguistics, thus applying synchronic models and approaches to the past. This is true also in the case of contact phenomena which would transcend the writing level involving the language systems implicated in contact processes to the point of perceiving a new variety. This is the case for medieval administrative-commercial texts in which, according to some Scholars, the degree of fusion of Anglo-Norman, Latin and middle English is so high a mixed code emerges, and there are recurrent patterns of mixed forms. Interesting is a collection of multilingual business writings by John Balmayn, an Englishman overseeing a large shipment in Tuscany, namely the Cantelowe accounts. These documents display various analogies with multilingual texts written in England in the same period; in fact, the writer seems to make use of the above-mentioned patterns, with Middle English, Latin, Anglo-Norman, and the newly added Italian. Applying an atomistic yet dynamic approach to the study of contact phenomena, we will investigate these documents, trying to explore the nature of the switching forms they contain from an intra-writer variation perspective. After analysing the accounts and the type of multilingualism in them, we will take stock of the assumed mixed code nature, comparing the characteristics found in this genre with modern assumptions. The aim is to evaluate the possibility to consider the switching forms as core elements of a mixed code, used as professional variety among merchant communities, or whether such texts should be analysed from a switching perspective.

Keywords: historical sociolinguistics, historical code switching, letters, medieval england

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Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

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Authors: Somoshree Datta, Chithra A. V., Sandeep Nithyanandan, Smitha K. K.

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Space exploration has always been at the forefront of technological innovation, pushing the boundaries of human knowledge and capabilities. In recent years, the integration of Artificial Intelligence (AI) has revolutionized the field, offering unprecedented opportunities to enhance the efficiency, autonomy and intelligence of space missions. This survey paper aims to provide a comprehensive overview of the multifaceted applications of AI in space exploration, exploring the evolution of this synergy and its impact on mission success, scientific discovery, and the future of space endeavors. Indian Space Research Organization (ISRO) has achieved great feats in the recent moon mission (Chandrayaan-3) and sun mission (Aditya L1) by using artificial intelligence to enhance moon navigation as well as help young scientists to study the Sun even before the launch by creating AI-generated image visualizations. Throughout this survey, we will review key advancements, challenges and prospects in the intersection of AI and space exploration. As humanity continues its quest to explore the cosmos, the integration of AI promises to unlock new frontiers, reshape mission architectures, and redefine our understanding of the universe. This survey aims to serve as a comprehensive resource for researchers, engineers and enthusiasts interested in the dynamic and evolving landscape of AI applications in space exploration.

Keywords: artificial intelligence, space exploration, space missions, deep learning

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Authors: Shangdong Zhu, Yunzhou Zhang, Jie Zhang, Hang Hu, Yazhou Zhang

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Image stitching is a very important branch in the field of computer vision, especially for panoramic map. In order to eliminate shape distortion, a novel stitching method is proposed based on gradually changing matrix when images are horizontal. For images captured horizontally, this paper assumes that there is only translational operation in image stitching. By analyzing each parameter of the homography matrix, the global homography matrix is gradually transferred to translation matrix so as to eliminate the effects of scaling, rotation, etc. in the image transformation. This paper adopts matrix approximation to get the minimum value of the energy function so that the shape distortion at those regions corresponding to the homography can be minimized. The proposed method can avoid multiple horizontal images stitching failure caused by accumulated shape distortion. At the same time, it can be combined with As-Projective-As-Possible algorithm to ensure precise alignment of overlapping area.

Keywords: image stitching, gradually changing matrix, horizontal direction, matrix approximation, homography matrix

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Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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Authors: Nurulnadwan Aziz, Ariffin Abdul Mutalib, Siti Mahfuzah Sarif

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This paper reports an ongoing project regarding the development of Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) learners. Having developed the intended model, it has to be validated prior to producing it as guidance for the developers to develop an AC4LV. This study requires two phases of validation process which are through expert review and prototyping method. This paper presents a part of the validation process which is findings from experts review on Conceptual Design Model of AC4LV which has been carried out through a questionnaire. Results from 12 international and local experts from various respectable fields in Human-Computer Interaction (HCI) were discussed and justified. In a nutshell, reviewed Conceptual Design Model of AC4LV was formed. Future works of this study are to validate the reviewed model through prototyping method prior to testing it to the targeted users.

Keywords: assistive courseware, conceptual design model, expert review, low vision learners

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: (1) The identity of Amphur (District) Mueang, SamutSongkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. (2) The communication of the identity of AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Songyun Chen

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

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

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Authors: Suman

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In the continuous interaction between the past and the present that historiography is, each time when history gets re/written, a new representation emerges. This new representation is a reflection of the earlier archives and their interpretations, fragmented remembrances of the past, as well as the reactions to the present. Memory, or lack thereof, and stereotyping generally play a major role in this representation. William Dalrymple’s Nine Lives: In Search of the Sacred in Modern India (2009) is one such written account that sets out to narrate the representations of religion and culture of India and contemporary reactions to it. Dalrymple’s nine saints belong to different castes, sects, religions, and regions. By dealing with their religions and expressions of those religions, and through the lived mysticism of these nine individuals, the book engages with some important issues like class, caste and gender in the contexts provided by historical as well as present India. The paper studies the development of religion and accompanied feeling of religiosity in modern as well as historical contexts through a study of these elements in the book. Since, the language used in creation of texts and the literary texts thus produced create a new reality that questions the stereotypes of the past, and in turn often end up creating new stereotypes or stereotypical representations at times, the paper seeks to actively engage with the text in order to identify and study such stereotypes, along with their changing representations. Through a detailed examination of the book, the paper seeks to unravel whether some socio-cultural stereotypes existed earlier, and whether there is development of new stereotypes from Dalrymple’s point of view as an outsider writing on issues that are deeply rooted in the cultural milieu of the country. For this analysis, the paper takes help from the psycho-literary theories of stereotyping and representation.

Keywords: stereotyping, representation, William Dalrymple, religion

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Authors: Sigal Barkai

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'Ironic Historiography' is a hybrid notion combining criticism of historical narratives concerning the Israeli state with ironic artistic expression. The paper will deal with questions of identities of native Israeli visual artists who chose to live out of the country, or to move back and forth to and from it. It will examine the ways these wanderings are reflected in their work. The paper discusses the work of 4 contemporary artists who produce artworks in diverse techniques and media, such as video, performance and installation art. Yael Bartana, Erez Israeli and Tamir Zadok are artists who constantly deal with Israeli nationality and history in their artwork, using ironic components. In comparison, the paper will review the works of Mika Rottenberg, who is now a New York based artist. She is concerned with global social issues and neglected specific national identity altogether. All of them use visual irony as a means of reflecting and criticizing society. The analysis was done in awareness of the life stories of the artists, in an attempt to trace the ways they establish their identities through their art. It was pre-supposed that these identities will be shaped in the in-between space of being an Israeli citizen and a citizen of the world. The study asks how ironic expression appears in their work, what kind of irony do they use and in what ways does it serves them. The methodology combined visual analysis, interviews with the artists, and analyzation of secondary discourses in the media. As theoretical background various fields of knowledge were used, such as literature and language studies, Sociology, and Visual Culture studies. The findings point out that visual and artistic irony has many different goals in the use of historiographic fiction. It can bind an artist to his homeland and native society, or it can help her to detach. It helps healing breaches in the in-between space, or it can be used as a means to completely detach from any identification with a native origin.

Keywords: visual art, irony, identities, Israel

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Authors: Oloyede Akinniyi Ojo

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This study investigated the relationship between truancy and academic performance of Colleges of Education students in southwestern, Nigeria. It also examined the relationship between College Physical environment and truancy behavior among students. Furthermore, it examined the relationship between male and female students involvement in truancy behavior. Purposive sampling was used to select four colleges of education in south-western Nigeria and 120 students per college were selected from year 3 while stratified sampling was used to select schools and courses. A total of 480 students participated in the study. Three research instruments were used for this study namely: Lecturers Attendance Record, Students Statement of Result and ‘College Environment Questionnaires’ (CEQ). Four research questions guided the study. Data was analyzed using descriptive, Chi-square and T-Test. CEQ was validated by a team of experts in the field of educational evaluation. Test reliability was established at an r=0-74. The study concluded that truancy exist in colleges of education and that there was a significant relationship between truancy and academic performance of male and female truants, the study also revealed that physical environment has so much effect on the truancy behavior of the students, hence the study recommended that effort should be made to provide attractive college environment for effective learning.

Keywords: academic performance, colleges of education, students, truancy

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Authors: Abdullah Almulhim

Abstract:

The International Accounting Standards Board (IASB) was established in 2001 to develop International Financial Reporting Standards (IFRS) that bring transparency, accountability, and efficiency to financial markets around the world. In addition, the IFRS provide a unified accounting language, which is especially important in the era of globalization. However, the establishment of a single set of high-quality international accounting standards is a matter of growing importance, as participants in the increasingly integrated world capital market demand comparability and transparency of financial reporting worldwide. Saudi Arabia became the 149th member of the World Trade Organization (WTO) on 11 December 2005, which has increased the need to convert to IFRS. Currently, the Saudi Arabian Monetary Authority (SAMA) requires banks and insurance companies in Saudi Arabia to report under IFRS Standards. However, until the end of 2016, SOCPA standards were applied to all other companies, listed and unlisted. From 2017, listed Saudi companies would be required to report under IFRS Standards as adopted by SOCPA effective 2017. This paper is to investigate the expected benefits gained and highlight the challenges faced by adopting IFRS by the listed companies in the Saudi Stock Exchange. Questionnaires were used as the main method of data collection. They were distributed to listed companies in the Saudi Capital Market. Data obtained through the questionnaires have been imported into SPSS statistical software for analysis. The expected results of this study will show the benefits of adopting IFRS by Saudi Listed Companies. However, this study will investigate the challenges faced by adopting IFRS by the listed companies in the Saudi Arabian Stock Market. Findings will be discussed later upon completion of initial analysis.

Keywords: challenges, IAS, IFRS, opportunities, Saudi, SOCPA

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

Procedia PDF Downloads 109

Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

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In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

Procedia PDF Downloads 251

Authors: Beverly Komen

Abstract:

Online crimes have been on the rise in the recent days, especially with the hit of the covid-19 pandemic. The coronavirus pandemic has led to an unprecedented rise in screen time, this means more families are relying on technology and digital solutions to keep children learning, spending more time on the virtual platforms can leave children vulnerable to online abuse and exploitation. With ease access of affordable phones, internet, and increased online activities, all children are at risk of being abused online hence making the digital space unsafe for children. With these increased use of technology and its accessibility, children are at risk of facing challenges such as access to inappropriate content, online grooming, identity theft, cyber bullying, among other risks. The big question is; as we enjoy the benefits brought in by technology, how do we ensure that our children are save in this digital space? With the analysis of the current trends, there is a gap in knowledge on people’s understanding on child online protection and safety measures when using the digital space. A survey conducted among 50 parents in Nairobi in Kenya indicated that there is a gap in knowledge on online protection of children and over 50 % of the participants shared that for sure they have no idea on how to protect children online. This paper seeks to address the concept of child protection in the digital space and come up with viable solutions in protecting children from online vices.

Keywords: child protection, digital space, online risks, online grooming, cyber bulying, online child sexual exploitation, and abuse

Procedia PDF Downloads 180