Search results for: community- based approach

Authors: Edvard P. G. Bruun

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One of the best ways of improving our understanding of reinforced concrete is through large-scale experimental testing. The gathered information is critical in making inferences about structural mechanics and deriving the mathematical models that are the basis for finite element analysis programs and design codes. An effective way of measuring the strains across a region of a specimen is by using a system of surface mounted Linear Variable Differential Transformers (LVDTs). While a single LVDT can only measure the linear strain in one direction, by combining several measurements at known angles a Mohr’s circle of strain can be derived for the whole region under investigation. This paper presents a method that can be used by researchers, which improves the accuracy and removes experimental bias in the calculation of the Mohr’s circle, using four rather than three independent strain measurements. Obtaining high quality strain data is essential, since knowing the angular deviation (shear strain) and the angle of principal strain in the region are important properties in characterizing the governing structural mechanics. For example, the Modified Compression Field Theory (MCFT) developed at the University of Toronto, is a rotating crack model that requires knowing the direction of the principal stress and strain, and then calculates the average secant stiffness in this direction. But since LVDTs can only measure average strains across a plane (i.e., between discrete points), localized cracking and spalling that typically occur in reinforced concrete, can lead to unrealistic results. To build in redundancy and improve the quality of the data gathered, the typical experimental setup for a large-scale shell specimen has four independent directions (X, Y, H, and V) that are instrumented. The question now becomes, which three should be used? The most common approach is to simply discard one of the measurements. The problem is that this can produce drastically different answers, depending on the three strain values that are chosen. To overcome this experimental bias, and to avoid simply discarding valuable data, a more rigorous approach would be to somehow make use of all four measurements. This paper presents the derivation of a method to draw what is effectively a Mohr’s circle of 'best-fit', which optimizes the circle by using all four independent strain values. The four-strain optimized Mohr’s circle approach has been utilized to process data from recent large-scale shell tests at the University of Toronto (Ruggiero, Proestos, and Bruun), where analysis of the test data has shown that the traditional three-strain method can lead to widely different results. This paper presents the derivation of the method and shows its application in the context of two reinforced concrete shells tested in pure torsion. In general, the constitutive models and relationships that characterize reinforced concrete are only as good as the experimental data that is gathered – ensuring that a rigorous and unbiased approach exists for calculating the Mohr’s circle of strain during an experiment, is of utmost importance to the structural research community.

Keywords: reinforced concrete, shell tests, Mohr’s circle, experimental research

Procedia PDF Downloads 235

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 122

Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

Procedia PDF Downloads 58

Authors: Tiwi Kamidin

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After years of effort trying to integrate environmental education, studies keep revealing that Malaysian still not reached the certain level of desired commitment toward the environment. Some researchers mentioned that our planet healthy is depending on our mentally health especially our psychological and spiritual is split from the natural. Therefore, this study discussed on ecopcyhological approach in order to enhance space consciousness toward the environment. Space consciousness represents not only freedom from ego but also from dependency on the things of this world, from materialism and materiality. It is the spiritual dimension which alone can give transcendent and true meaning to this world. If pupils can balance this internal awareness will put an individual to respect the environment as part of yourself and your family against only as contributors to the continuance of human’s life. Qualitative findings showed that the informants considered their consciousness toward environment has been changed.

Keywords: ecopsychological approach, space consciousness, environmental education, environment

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Authors: Rohan Bhasin

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Agrammatism in non-fluent Aphasia Cases can be defined as a language disorder wherein a patient can only use content words ( nouns, verbs and adjectives ) for communication and their speech is devoid of functional word types like conjunctions and articles, generating speech of with extremely rudimentary grammar . Past approaches involve Speech Therapy of some order with conversation analysis used to analyse pre-therapy speech patterns and qualitative changes in conversational behaviour after therapy. We describe this approach as a novel method to generate functional words (prepositions, articles, ) around content words ( nouns, verbs and adjectives ) using a combination of Natural Language Processing and Deep Learning algorithms. The applications of this approach can be used to assist communication. The approach the paper investigates is : LSTMs or Seq2Seq: A sequence2sequence approach (seq2seq) or LSTM would take in a sequence of inputs and output sequence. This approach needs a significant amount of training data, with each training data containing pairs such as (content words, complete sentence). We generate such data by starting with complete sentences from a text source, removing functional words to get just the content words. However, this approach would require a lot of training data to get a coherent input. The assumptions of this approach is that the content words received in the inputs of both text models are to be preserved, i.e, won't alter after the functional grammar is slotted in. This is a potential limit to cases of severe Agrammatism where such order might not be inherently correct. The applications of this approach can be used to assist communication mild Agrammatism in non-fluent Aphasia Cases. Thus by generating these function words around the content words, we can provide meaningful sentence options to the patient for articulate conversations. Thus our project translates the use case of generating sentences from content-specific words into an assistive technology for non-Fluent Aphasia Patients.

Keywords: aphasia, expressive aphasia, assistive algorithms, neurology, machine learning, natural language processing, language disorder, behaviour disorder, sequence to sequence, LSTM

Procedia PDF Downloads 164

Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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Authors: Mostafa Shahriari, Theophile Chaumont-Frelet, David Pardo

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Resistivity measurements are used to characterize the Earth’s subsurface. They are categorized into two different groups: (a) those acquired on the Earth’s surface, for instance, controlled source electromagnetic (CSEM) and Magnetotellurics (MT), and (b) those recorded with borehole logging instruments such as Logging-While-Drilling (LWD) devices. LWD instruments are mostly used for geo-steering purposes, i.e., to adjust dip and azimuthal angles of a well trajectory to drill along a particular geological target. Modern LWD tools measure all nine components of the magnetic field corresponding to three orthogonal transmitter and receiver orientations. In order to map the Earth’s subsurface and perform geo-steering, we invert measurements using a gradient-based method that utilizes the derivatives of the recorded measurements with respect to the inversion variables. For resistivity measurements, these inversion variables are usually the constant resistivity value of each layer and the bed boundary positions. It is well-known how to compute derivatives with respect to the constant resistivity value of each layer using semi-analytic or numerical methods. However, similar formulas for computing the derivatives with respect to bed boundary positions are unavailable. The main contribution of this work is to provide an adjoint-based formulation for computing derivatives with respect to the bed boundary positions. The key idea to obtain the aforementioned adjoint state formulations for the derivatives is to separate the tangential and normal components of the field and treat them differently. This formulation allows us to compute the derivatives faster and more accurately than with traditional finite differences approximations. In the presentation, we shall first derive a formula for computing the derivatives with respect to the bed boundary positions for the potential equation. Then, we shall extend our formulation to 3D Maxwell’s equations. Finally, by considering a 1D domain and reducing the dimensionality of the problem, which is a common practice in the inversion of resistivity measurements, we shall derive a formulation to compute the derivatives of the measurements with respect to the bed boundary positions using a 1.5D variational formulation. Then, we shall illustrate the accuracy and convergence properties of our formulations by comparing numerical results with the analytical derivatives for the potential equation. For the 1.5D Maxwell’s system, we shall compare our numerical results based on the proposed adjoint-based formulation vs those obtained with a traditional finite difference approach. Numerical results shall show that our proposed adjoint-based technique produces enhanced accuracy solutions while its cost is negligible, as opposed to the finite difference approach that requires the solution of one additional problem per derivative.

Keywords: inverse problem, bed boundary positions, electromagnetism, potential equation

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Authors: Mohamed Sarrab, Hadj Bourdoucen

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Mobile applications are verified to check the correctness or evaluated to check the performance with respect to specific security properties such as availability, integrity, and confidentiality. Where they are made available to the end users of the mobile application is achievable only to a limited degree using software engineering static verification techniques. The more sensitive the information, such as credit card data, personal medical information or personal emails being processed by mobile application, the more important it is to ensure the confidentiality of this information. Monitoring non-trusted mobile application during execution in an environment where sensitive information is present is difficult and unnerving. The paper addresses the issue of monitoring and controlling the flow of confidential information during non-trusted mobile application execution. The approach concentrates on providing a dynamic and usable information security solution by interacting with the mobile users during the run-time of mobile application in response to information flow events.

Keywords: mobile application, run-time verification, usable security, direct information flow

Procedia PDF Downloads 381

Authors: Amany A. Ragheb, Ghada Ragheb, Abd ElRahman A.

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Egypt has a countless heritage of mansions, castles, cities, towns, villages, industrial and manufacturing sites. This richness of heritage provides endless and matchless prospects for culture. Despite being famous worldwide, Egypt’s heritage still is in constant need of protection. Political conflicts and religious revolutions form a direct threat to buildings in various areas, historic, archaeological sites, and religious monuments. Egypt has witnessed two revolutions in less than 60 years; both had an impact on its architectural heritage. In this paper, the authors aim to review legal and policy framework to protect the cultural heritage and present the risk management strategy for cultural heritage in conflict. Through a review of selected international models of devastated architectural heritage in conflict zones and highlighting some of their changes, we can learn from the experiences of other countries to assist towards the development of a methodology to halt the plundering of architectural heritage. Finally, the paper makes an effort to enhance the formulation of a risk management strategy for protection and conservation of cultural heritage, through which to end the plundering of Egypt’s architectural legacy in the Egyptian community (revolutions, 1952 and 2011); and by presenting to its surrounding community the benefits derived from maintaining it.

Keywords: cultural heritage, legal regulation, risk management, preservation

Procedia PDF Downloads 400

Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Ying Zhou, Jian-Hua Wang

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Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

Procedia PDF Downloads 274

Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

Procedia PDF Downloads 545

Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

Procedia PDF Downloads 105

Authors: Pietro D'Ambrosio, Roberta D'Ambrosio

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The upgrading of the architectural and urban heritage of the urban historic centers almost always involves the planning for the reuse and refunctionalization of the structures. Such interventions have complexities linked to the need to take into account the urban and social context in which the structure and its intrinsic characteristics such as historical and artistic value are inserted. To these, of course, we have to add the need to make a preliminary estimate of recovery costs and more generally to assess the economic and financial sustainability of the whole project of re-socialization. Particular difficulties are encountered during the pre-assessment of costs since it is often impossible to perform analytical surveys and structural tests for both structural conditions and obvious cost and time constraints. The methodology proposed in this work, based on a multidisciplinary and data-driven approach, is aimed at obtaining, at very low cost, reasonably priced economic evaluations of the interventions to be carried out. In addition, the specific features of the approach used, derived from the predictive analysis techniques typically applied in complex IT domains (big data analytics), allow to obtain as a result indirectly the evaluation process of a shared database that can be used on a generalized basis to estimate such other projects. This makes the methodology particularly indicated in those cases where it is expected to intervene massively across entire areas of historical city centers. The methodology has been partially tested during a study aimed at assessing the feasibility of a project for the reuse of the monumental complex of San Massimo, located in the historic center of Salerno, and is being further investigated.

Keywords: evaluation, methodology, restoration, reuse

Procedia PDF Downloads 187

Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 169

Authors: Sri Wartini

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Based on the sovereignty over natural resources principle, the Indonesian government has an authority to exploit the natural resources within a national jurisdiction of Indonesia. The forest is one of the natural resources which is very valuable for Indonesia. It becomes the source of raw material for many industrial activities, such as pharmaceutical industry, pulp industry, and household furniture industry. Hence, it contributes to the economic development of Indonesia. However, the exploitation of the forest may cause negative impacts, such as environmental pollution and environmental degradation. The implementation of the sovereignty over natural resources principle in Indonesia may jeopardize the forest and affect the sustainability of the forest if there is no appropriate policy of the government to exploit the forest in a sustainable manner. The exploitation of the forest in Indonesia, in some extent, has caused serious impact to environment and biodiversity. Hence, in order to sustain and to maintain the forest as the valuable resources to the future generation, the government of Indonesia has already adopted many programmes and action plans. The aim of the research is to undertake a critical examination of the issues relating to the the implementation of sovereignty over natural resources to the exploitation of the forest in Indonesia. It is a normative research and the methodology employed in this research is library research. While the approaches employed in the research are conceptual approach., statutory approach, and comparative approach. The research finds that the implementation of sovereignty over natural resources principle in the exploitation of the forest in Indonesia is limited by other principles of international environmental law, such as sustainable development principle, intergenerational principle and common concern principle which have been adopted in the government policy and various regulations regarding the exploitation of the forest in Indonesia.

Keywords: Environmental damage, negative impacts, pollution, the sovereignty over natural resources

Procedia PDF Downloads 386

Authors: Shaila Rana, Wasim Alhamdani

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Effective cybersecurity learning relies on an engaging, interactive, and entertaining activity that fosters positive learning outcomes. VR cybersecurity training may promote these aforementioned variables. However, a methodological approach and framework have not yet been created to allow trainers and educators to employ VR cybersecurity training methods to promote positive learning outcomes to the author’s best knowledge. Thus, this paper aims to create an approach that cybersecurity trainers can follow to create a VR cybersecurity training module. This methodology utilizes concepts from other cybersecurity training frameworks, such as NICE and CyTrONE. Other cybersecurity training frameworks do not incorporate the use of VR. VR training proposes unique challenges that cannot be addressed in current cybersecurity training frameworks. Subsequently, this ontology utilizes concepts unique to developing VR training to create a relevant methodology for creating VR cybersecurity training modules. The outcome of this research is to create a methodology that is relevant and useful for designing VR cybersecurity training modules.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training, ontology

Procedia PDF Downloads 289

Authors: Maryam Savari, Mohamad Nizam Ayub, Ainuddin Wahid Abdul Wahab

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Game-based Learning (GBL) is an alternative that provides learners with an opportunity to experience a volatile environment in a safe and secure place. A volatile environment requires a different technique to facilitate learning and prevent injury and other hazards. Subjects involving elasticity are always considered hazardous and can cause injuries,for instance a bouncing ball. Elasticity is a topic that necessitates hands-on practicality for learners to experience the effects of elastic objects. In this paper the scope is to investigate the natural interaction between learners and elastic objects in a safe environment using GBL. During interaction, the potentials of natural contact in the process of learning were explored and gestures exhibited during the learning process were identified. GBL was developed using Kinect technology to teach elasticity to primary school children aged 7 to 12. The system detects body gestures and defines the meanings of motions exhibited during the learning process. The qualitative approach was deployed to constantly monitor the interaction between the student and the system. Based on the results, it was found that Natural Interaction GBL (Ni-GBL) is engaging for students to learn, making their learning experience more active and joyful.

Keywords: elasticity, Game-Based Learning (GBL), kinect technology, natural interaction

Procedia PDF Downloads 484

Authors: Mohammed Abu Shquier

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

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

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Authors: Ararat Khachatryan, Davit Mirzoyan

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In sub micrometer technology, the aging phenomenon starts to have a significant impact on the reliability of integrated circuits by bringing performance degradation. For that reason, it is important to have a capability to evaluate the aging effects accurately. This paper presents an accurate aging measurement approach based on phase-locked loop (PLL) and voltage-controlled oscillator (VCO) circuit. The architecture is rejecting the circuit self-aging effect from the characteristics of PLL, which is generating the frequency without any aging phenomena affects. The aging monitor is implemented in low power 32 nm CMOS technology, and occupies a pretty small area. Aging simulation results show that the proposed aging measurement circuit improves accuracy by about 2.8% at high temperature and 19.6% at high voltage.

Keywords: aging effect, HCI, NBTI, nanoscale

Procedia PDF Downloads 359

Authors: Takashi Kaminagayoshi, Shigeyuki Haruyama

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To improve the manufacturing efficiency of biologics, such as antibody drugs, a quality engineering framework was designed. Within this framework, critical steps and parameters in the manufacturing process were studied. Identification of these critical steps and critical parameters allows a deeper understanding of manufacturing capabilities, and suggests to process development department process control standards based on actual manufacturing capabilities as part of a PDCA (plan-do-check-act) cycle. This cycle can be applied to each manufacturing process so that it can be standardized, reducing the time needed to establish each new process.

Keywords: antibody drugs, biologics, manufacturing efficiency, PDCA cycle, quality engineering

Procedia PDF Downloads 345

Authors: Olumide Yusuf Jimoh

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Reading comprehension is an interactive and purposeful process of getting meaning from and bringing meaning to a text. Over the years, teachers of the English Language (in Nigeria) have been glued to the monotonous method of making students read comprehension passages silently and then answer the questions that follow such passages without making the reading session interactive. Hence, students often find such exercises monotonous and boring. Consequently, students'’ interest in language learning continues to dwindle, and this often affects their overall academic performance. Relying on Communicative Accommodation Theory therefore, the study employed the qualitative research design method to x-ray Communicative Language Teaching Approach (CLTA) in reading comprehension. Moreover, techniques such as the Genuinely Collaborative Reading Approach (GCRA), Jigsaw reading, Pre-reading, and Post-reading tasks were examined. The researcher submitted that effective reading comprehension could not be done passively. Students must respond to what they read; they must interact not only with the materials being read but also with one another and with the teacher; this can be achieved by developing communicative and interactive reading programs.

Keywords: collaborative reading approach, communicative teaching, interactive reading program, pre-reading task, reading comprehension

Procedia PDF Downloads 106

Authors: Jitka Molnarova

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Based on De Soto’s idea that a formal land title can provide a secure home and access to credit to poor urban families, a large number of developing countries accepted the formalization of informal settlements as the ultimate solution for their housing crises and struggles with poverty. After two decades of implementation, very little is known about the effects this policy has on the quality of the neighborhoods it produces and on the development of cities in general. Using the capital of Peru -where the solution originated- as a case study, this paper illustrates the negative outcomes this policy has on urban development arguing that land titling encourages 1) expansion of the city often to areas of high physical risk, 2) production of precarious housing on unserviced land, and 3) practices of illegal land trafficking. The evidence is based on interviews with community leaders and officials working at the Cooperation for Formalization of Informal Property (COFOPRI), comparison of satellite images documenting the expansion of Lima in the past twenty years, and a technical evaluation of dozens of houses that have been or are in the process of being granted a land title.

Keywords: COFOPRI, De Soto, housing policies, land titling, land trafficking, Lima, Peru, precarious housing, urban expansion

Procedia PDF Downloads 187

Authors: Eleni Stefania Kalapoda

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The current fossil-fuel based urbanization pattern and the estimated human population growth are increasing the environmental footprint on our planet’s precious resources. To mitigate the estimated skyrocketing in greenhouse gas emissions associated with the construction of new cities and infrastructure over the next 50 years, we need a radical rethink in our approach to construction to deliver a net zero built environment. This paper assesses the carbon footprint of a mass-timber, a steel, and a concrete structural alternative for peri-urban densification in the Hudson Valley's urban fringe, along with examining the updated policy and the building code adjustments that support synergies between timber construction in city making and sustainable management of timber forests. By quantifying the carbon footprint of a structural prototype for four different material assemblies—a concrete (post-tensioned), a mass timber, a steel (composite), and a hybrid (timber/steel/concrete) assembly applicable to the three updated building typologies of the IBC 2021 (Type IV-A, Type IV-B, Type IV-C) that range between a nine to eighteen-story structure alternative—and scaling-up that structural prototype to the size of a neighborhood district, the paper presents a quantitative and a qualitative approach for a forest-based construction economy as well as a resilient and a more just supply chain framework that ensures the wellbeing of both the forest and its inhabitants.

Keywords: mass-timber innovation, concrete structure, carbon footprint, densification

Procedia PDF Downloads 108

Authors: A. Ferasat, S. Rostampour Yasouri

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Seasonal flu is a highly contagious infection caused by influenza viruses. These viruses undergo genetic changes that result in new epidemics across the globe. Medical attention is crucial in severe cases, particularly for the elderly, frail, and those with chronic illnesses, as their immune systems are often weaker. The purpose of this study was to detect new subtypes of the influenza A virus rapidly using a specific RT-PCR method based on the HA gene (hemagglutinin). In the winter and spring of 2022_2023, 120 embryonated egg samples were cultured, suspected of seasonal influenza. RNA synthesis, followed by cDNA synthesis, was performed. Finally, the PCR technique was applied using a pair of specific primers designed based on the HA gene. The PCR product was identified after purification, and the nucleotide sequence of purified PCR products was compared with the sequences in the gene bank. The results showed a high similarity between the sequence of the positive samples isolated from the patients and the sequence of the new strains isolated in recent years. This RT-PCR technique is entirely specific in this study, enabling the detection and multiplication of influenza and its subspecies from clinical samples. The RT-PCR technique based on the HA gene, along with sequencing, is a fast, specific, and sensitive diagnostic method for those infected with influenza viruses and its new subtypes. Rapid molecular diagnosis of influenza is essential for suspected people to control and prevent the spread of the disease to others. It also prevents the occurrence of secondary (sometimes fatal) pneumonia that results from influenza and pathogenic bacteria. The critical role of rapid diagnosis of new strains of influenza is to prepare a drug vaccine against the latest viruses that did not exist in the community last year and are entirely new viruses.

Keywords: influenza, molecular diagnosis, patients, RT-PCR technique

Procedia PDF Downloads 74

Authors: Olga Guseynova

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Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Kenneth N. Ohei, Roelien Brink

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For decades, teaching and learning processes have centered on the traditional approach (Web 1.0) that promoted teacher-directed pedagogical practices. Currently, there is a realization that the traditional approach is not adequate to effectively address and improve all student-learning outcomes. The subsequent incorporation of social software, Information, and Communication Technology (ICT) tools in universities may serve as complementary to support educational goals, offering students the affordability and opportunity to educational choices and learning platforms. Consequently, educators’ inability to incorporate these instructional ICT tools in their teaching and learning practices remains a challenge. This will signify that educators still lack the ICT skills required to administer lectures and bridging learning gaps. This study probes a methodological concept with the aim of developing a framework towards the adoption of social software in HES to help facilitate business processes and can build social presence among students. A mixed method will be appropriate to develop a comprehensive framework needed in Higher Educational System (HES). After research have been conducted, the adoption of social software will be based on the developed comprehensive framework which is supposed to impact positively on education and approach of delivery, improves learning experience, engagement and finally, increases educational opportunities and easy access to educational contents.

Keywords: blended and integrated learning, learning experience and engagement, higher educational system, HES, information and communication technology, ICT, social presence, Web 1.0, Web 2.0, Web 3.0

Procedia PDF Downloads 157

Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

Procedia PDF Downloads 138

Authors: Nawel Mansouri

Abstract:

Weblog as a form of internet-based resources has become popular as an authentic and constructive learning tool, especially in the language classroom. This research explores the use of weblog storytelling as a pedagogical tool to develop Algerian EFL students’ creative writing. This study aims to investigate the effectiveness of weblog- writing and the attitudes of both Algerian EFL students and teachers towards weblog storytelling. It also seeks to explore the potential benefits and problems that may affect the use of weblog and investigate the possible solutions to overcome the problems encountered. The research work relies on a mixed-method approach which combines both qualitative and quantitative methods. A questionnaire will be applied to both EFL teachers and students as a means to obtain preliminary data. Interviews will be integrated in accordance with the primary data that will be gathered from the questionnaire with the aim of validating its accuracy or as a strategy to follow up any unexpected results. An intervention will take place on the integration of weblog- writing among 15 Algerian EFL students for a period of two months where students are required to write five narrative essays about their personal experiences, give feedback through the use of a rubric to two or three of their peers, and edit their work based on the feedback. After completion, questionnaires and interviews will also take place as a medium to obtain both the students’ perspectives towards the use of weblog as an innovative teaching approach. This study is interesting because weblog storytelling has recently been emerged as a new form of digital communication and it is a new concept within Algerian context. Furthermore, the students will not just develop their writing skill through weblog storytelling but it can also serve as a tool to develop students’ critical thinking, creativity, and autonomy.

Keywords: Weblog writing, EFL writing, EFL learners' attitudes, EFL teachers' views

Procedia PDF Downloads 174

Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

Procedia PDF Downloads 515