Search results for: collaborative reading approach

Authors: Ruben Lopez-Rodriguez

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In a microgrid, diverse energy sources (both renewable and non-renewable) are combined with energy storage units to form a localized power system. Microgrids function as independent entities, capable of meeting the energy needs of specific areas or communities. This paper introduces a Model Predictive Control (MPC) approach tailored for grid-connected microgrids, aiming to optimize their operation. The formulation employs Mixed-Integer Programming (MIP) to find optimal trajectories. This entails the fulfillment of continuous and binary constraints, all while accounting for commutations between various operating conditions such as storage unit charge/discharge, import/export from/towards the main grid, as well as asset connection/disconnection. To validate the proposed approach, a microgrid case study is conducted, and the simulation results are compared with those obtained using a rule-based strategy.

Keywords: microgrids, mixed logical dynamical systems, mixed-integer optimization, model predictive control

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Authors: Ehsan Atefi, Michael Grigware

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Respiratory failure secondary to surfactant deficiency resulting from respiratory distress syndrome is considered one major cause of morbidity in preterm infants. Surfactant replacement treatment (SRT) is considered an effective treatment for this disease. Here, we introduce an AI-mediated approach for estimating the distribution of surfactant in the lung airway of a newborn infant during SRT. Our approach implements machine learning to precisely estimate the splitting ratio of a liquid drop during bifurcation at different injection velocities and patient orientations. This technique can be used to calculate the surfactant residue remaining on the airway wall during the surfactant injection process. Our model works by minimizing the pressure drop difference between the two airway branches at each generation, subject to mass and momentum conservation. Our platform can be used to generate feedback for immediately adjusting the velocity of injection and patient orientation during SRT.

Keywords: respiratory failure, surfactant deficiency, surfactant replacement, machine learning

Procedia PDF Downloads 129

Authors: Abdelrahman Taha, Niloofar Malekghaini, Hamed Ebrahimian, Ramin Motamed

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This paper compares the substructure and direct methods for soil-structure interaction (SSI) analysis in the time domain. In the substructure SSI method, the soil domain is replaced by a set of springs and dashpots, also referred to as the impedance function, derived through the study of the behavior of a massless rigid foundation. The impedance function is inherently frequency dependent, i.e., it varies as a function of the frequency content of the structural response. To use the frequency-dependent impedance function for time-domain SSI analysis, the impedance function is approximated at the fundamental frequency of the structure-soil system. To explore the potential limitations of the substructure modeling process, a two-dimensional reinforced concrete frame structure is modeled using substructure and direct methods in this study. The results show discrepancies between the simulated responses of the substructure and the direct approaches. To isolate the effects of higher modal responses, the same study is repeated using a harmonic input motion, in which a similar discrepancy is still observed between the substructure and direct approaches. It is concluded that the main source of discrepancy between the substructure and direct SSI approaches is likely attributed to the way the impedance functions are calculated, i.e., assuming a massless rigid foundation without considering the presence of the superstructure. Hence, a refined impedance function, considering the presence of the superstructure, shall be developed. This refined impedance function is expected to significantly improve the simulation accuracy of the substructure approach for structural systems whose behavior is dominated by the fundamental mode response.

Keywords: direct approach, impedance function, soil-structure interaction, substructure approach

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Authors: Evy Rombaut, Marie-Anne Guerry

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Predicting voluntary turnover of employees is an important topic of study, both in academia and industry. Researchers try to uncover determinants for a broader understanding and possible prevention of turnover. In the current study, we use a data set based approach to reveal determinants for turnover, differing for blue and white collar workers. Our data set based approach made it possible to study actual turnover for more than 500000 employees in 15692 Belgian corporations. We use logistic regression to calculate individual turnover probabilities and test the goodness of our model with the AUC (area under the ROC-curve) method. The results of the study confirm the relationship of known determinants to employee turnover such as age, seniority, pay and work distance. In addition, the study unravels unknown and verifies known differences between blue and white collar workers. It shows opposite relationships to turnover for gender, marital status, the number of children, nationality, and pay.

Keywords: employee turnover, blue collar, white collar, dataset analysis

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Soyele Esther Kelechi

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The study examined assessing student level of utilization of library books and electronic resources: a case study of Gani Belo library, Federal College of Education, Osiele, Abeokuta, Ogun State, Nigeria. A mixed research method was adopted for the study, a purposive sampling method was used in selecting 1,000 students, with 200 students from each of the five schools in the college. Data were collected through a survey questionnaire designed by the researcher, which assessed library book usage, satisfaction with electronic services, and the extent of library automation. Additionally, face-to-face interviews were conducted with 10 library staff and 10 faculty members. The data collected were analyzed using the descriptive statistics of frequency distributions and percentages, and content analysis was used for the interviews. The findings reveal that more than half of the library clientele visit the library once a month, and this is because they see the library primarily for reading and assignments. Respondents expressed satisfaction with the library collections and general services, not with electronic services. The study also identified that the library's automation is only partially complete, primarily due to the lack of a Local Area Network (LAN) connection. However, measures are underway to achieve full automation. The study concluded that rapid adaptation to technological advancements is crucial for maximizing the use of librariess ICT facilities and electronic services, and the study recommends libraries should prioritize the implementation of electronic services and ICT facilities to ensure uninterrupted access to e-library and automated services, thereby attracting and retaining more users.

Keywords: academic libraries, changing needs of user's electronic services, library collections, library services

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Authors: Omaima N. Ahmad AL-Allaf

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Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Haruo Okabayashi

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The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon

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Authors: Mohammad Sadeghi, Mahdieh Saniee

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Nowadays, development laws have become a major branch of engineering science, laws help humankind achieve his/her basic needs, and it is attracted to the attention of the nations. Therefore, lawyers have been invited to contemplate legislator's approaches respecting legislating countries' economic, social and cultural development plans and to observe the reliance of approaches on two elements of distributive justice and transitional justice in light of legal rationality. Legal rationality in development planning has encountered us with this question that whether a rational approach and existing models in the Iran development planning system approximate us to the goal of development laws respecting the rationalist approach and also regarding wisely decision-making model. The present study will investigate processes, approaches, and damages of development planning in the legislation of country development plans to answer this question.

Keywords: rationality, decision-making process, policymaking, development

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Authors: Marija Mihajlovic Pereira

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Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

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Authors: Ganetsou Evanthia, Koutsikos Emmanouil, Austin Anna Maria

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Information technology has long served the needs of individuals for learning and entertainment, but much less for children in sickness. The aim of the proposed online video game is to provide immersive learning opportunities as well as essential social and emotional scenarios for hospital-bound children with long-term illness. Online self-paced courses on chosen school subjects, including specialised software and multisensory assessments, aim at enhancing children’s academic achievement and sense of inclusion, while doctor minigames familiarise and educate young patients on their medical conditions. Online ethical dilemmas will offer children opportunities to contemplate on the importance of medical procedures and following assigned medication, often challenging for young patients; they will therefore reflect on their condition, reevaluate their perceptions about hospitalisation, and assume greater personal responsibility for their progress. Children’s emotional and psychosocial needs are addressed by engaging in social conventions, such as interactive, daily, collaborative mini games with other hospitalised peers, like virtual competitive sports games, weekly group psychodrama sessions, and online birthday parties or sleepovers. Social bonding is also fostered by having a virtual pet to interact with and take care of, as well as a virtual nurse to discuss and reflect on the mood of the day, engage in constructive dialogue and perspective taking, and offer reminders. Access to the platform will be available throughout the day depending on the patient’s health status. The program is designed to minimise escapism and feelings of exclusion, and can flexibly be adapted to offer post-treatment and a support online system at home.

Keywords: long-term illness, children, hospital, interactive games, cognitive, socioemotional development

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Lorenzo Buti

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This paper investigates the nature of democratic action through a critical reading of Claude Lefort’s notion of the democratic ‘regime’. Lefort provides one of the most innovative accounts of the essential features of a democratic regime. According to him, democracy is a political regime that acknowledges the indeterminacy of a society and stages it as a contestation between competing political actors. As such, democracy provides the symbolic markers of society’s openness towards the future. However, despite their democratic features, the recent decades in late capitalist societies attest to a sense of the future becoming fixed and predetermined. This suggests that Lefort’s conception of democracy harbours a misunderstanding of the character and experience of democratic action. This paper examines this underlying tension in Lefort’s work. It claims that Lefort underestimates how a democratic regime, next to its symbolic function, also takes a materially constituted form with its particular dynamics of power relations. Lefort’s systematic dismissal of this material dimension for democratic action can lead to the contemporary paradoxical situation where democracy’s symbolic markers are upheld (free elections, public debate, dynamic between government and opposition in parliament,…) but the room for political decision-making is constrained due to a myriad of material constraints (e.g., market pressures, institutional inertias). The paper draws out the implications for the notion of democratic action. Contra Lefort, it argues that democratic action necessarily targets the material conditions that impede the capacity for decision-making on the basis of equality and liberty. This analysis shapes our understanding of democratic action in two ways. First, democratic action takes an asymmetrical, insurgent form, as a contestation of material power relations from below. Second, it reveals an ambivalent position vis-à-vis the political regime: democratic action is symbolically made possible by the democratic dispositive, but it contests the constituted form that the democratic regime takes.

Keywords: Claude Lefort, democratic action, material constitution, political regime

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Authors: Mihai Rebenciuc, Simona Mihaela Bibic

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Branch of modern mathematics, graphs represent instruments for optimization and solving practical applications in various fields such as economic networks, engineering, network optimization, the geometry of social action, generally, complex systems including contemporary urban problems (path or transport efficiencies, biourbanism, & c.). In this paper is studied the interconnection of some urban network, which can lead to a simulation problem of a digraph through another digraph. The simulation is made univoc or more general multivoc. The concepts of fragment and atom are very useful in the study of connectivity in the digraph that is simulation - including an alternative evaluation of k- connectivity. Rough set approach in (bi)digraph which is proposed in premier in this paper contribute to improved significantly the evaluation of k-connectivity. This rough set approach is based on generalized rough sets - basic facts are presented in this paper.

Keywords: (bi)digraphs, rough set theory, systems of interacting agents, complex systems

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Authors: Pradyumna R., Sridhar S., A. Satyanarayana, Alok S. Chauhan, Baig M. A. H.

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Modern turbine engines for aerospace applications need precision investment cast components such as integrally cast rotors and stators, for their hot end turbine stages. Traditionally, these turbines are used as starter engines. In recent times, such engines are also used for strategic missile applications. The rotor/stator castings consist of a central hub (shrouded in some designs) over which a number of aerofoil shaped blades are located. Since these components cannot be machined, investment casting is the only available route for manufacture and hence stringent dimensional aerospace quality has to be in-built in the casting process itself. In the process of investment casting, pattern generation by injection of wax into dedicated dies/moulds is the first critical step. Traditional approach deals in producing individual blades with hub/shroud features through wax injection and assembly of a set of such injected patterns onto a dedicated and precisely manufactured fixture to wax-weld and generate an integral wax pattern, a process known as the ‘segmental approach’. It is possible to design a single-injection die with retractable metallic inserts in the case of untwisted blades of stator patterns without the shroud. Such an approach is also possible for twisted blades of rotors with highly complex design of inter-blade inserts and retraction mechanisms. DMRL has for long established methods and procedures for the above to successfully supply precision castings for various defence related projects. In recent times, urea based soluble insert approach has also been successfully applied to overcome the need to design and manufacture a precision assembly fixture, leading to substantial reduction in component development times. Present paper deals in length various approaches tried and established at DMRL to generate precision wax patterns for aerospace quality turbine rotors and stators. In addition to this, the importance of simulation in solving issues related to wax injection is also touched upon.

Keywords: die/mold and fixtures, integral rotor/stator, investment casting, wax patterns, simulation

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Authors: Tanwi Priya, Brijesh Kumar Mishra

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Occurrence of aromatic fractions of Natural Organic Matter (NOM) led to formation of carcinogenic disinfection by products such as trihalomethanes in chlorinated water. In the present study, the efficiency of aluminium based electrocoagulation on the removal of prominent aromatic groups such as phenol, hydrophobic auxochromes, and carboxyl groups from NOM enriched synthetic water has been evaluated using various spectral indices. The effect of electrocoagulation on turbidity has also been discussed. The variation in coagulation performance as a function of pH has been studied. Our result suggests that electrocoagulation can be considered as appropriate remediation approach to reduce trihalomethanes formation in water. It has effectively reduced hydrophobic fractions from NOM enriched low turbid water. The charge neutralization and enmeshment of dispersed colloidal particles inside metallic hydroxides is the possible mechanistic approach in electrocoagulation.

Keywords: aromatic fractions, electrocoagulation, natural organic matter, spectral indices

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Authors: M. Caporale

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French Curricula across the US have recently suffered low enrollment and have experienced difficulties with retention, thus resulting in fewer students minoring and majoring in French and enrolling in upper-level classes. Successful undergraduate programs offer French courses with a strong cultural and interdisciplinary or multidisciplinary component. The World Language Curriculum in liberal arts colleges in America needs to take into account the cultural aspects of the language and encourage students to think critically about the country or countries they are studying. Limiting the critical inquiry to language or literature narrowly defined provides and incomplete and stagnant picture of France and the Francophone world in today's global community. This essay discusses the creation and implementation of a hybrid interdisciplinary L1/L2 course titled "Topics in Francophone Cinema" (subtitle "Francophone Women on Screen and Behind the Camera"). Content-based interdisciplinary courses undoubtedly increase the profile of French and Francophone cultural Studies by introducing students of other disciplines to fundamental questions relating to the French and Francophone cultures (in this case, women's rights in the Francophone world). At the same time, this study determines that through targeted reading and writing assignments, sustained aural exposure to L2 through film,and student participation in a one-credit supplementary weekly practicum (creative film writing workshop), significant advances in L2 competence are achieved with students' oral and written production levels evolving from Advanced Low to Advanced-mid, as defined by the ACFL guidelines. Use of differentiated assessment methods for L1/L2 and student learning outcomes for both groups will also be addressed.

Keywords: interdisciplinary, Francophone cultural studies, language competency, content-based

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Authors: Mohammed Belalia Douma

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Interactive learning is considered as the most effective strategy of learning, it is an educational philosophy based on the learner's contribution and involvement mainly in classroom and how he interacts toward his small society “classroom”, and the level of his collaboration into challenge, discovering, games, participation, all these can be provided through the interactive learning, which aims to activate the learner's role in the operation of learning, which focuses on research and experimentation, and the learner's self-reliance in obtaining information, acquiring skills, and forming values and attitudes. Whereas not based on memorization only, but rather on developing thinking and the ability to solve problems, on teamwork and collaborative learning. With the exchange or roles - teacher to student- , when the student will be more active and performing operations more than the student under the interactive learning method; we might face a several issues dealing with class controlling management, noise, and stability of learning… etc. This research paper is observing the application of the interactive learning on reality “classroom” and answers several assumptions and analyzes the issues coming up of these strategies mainly: noise, class control…etc The research sample was about 150 student of the 3rd year primary school in “Chlef” district, Algeria, level: beginners in the range of age 08 to 10 years old . We provided a questionnaire of confidential fifteen questions and also analyzing the attitudes of learners during three months. it have witnessed as teachers a variety of strategies dealing with applying the interactive learning but with a different issues; time management, noise, uncontrolled classes, overcrowded classes. Finally, it summed up that although the active education is an inevitably effective method of teaching, however, there are drawbacks to this, in addition to the fact that not all theoretical strategies can be applied and we conclude with solutions of this case study.

Keywords: interactive learning, student, learners, strategies.

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Authors: Abbas Moradi, Mohsen Safajoy, Reza Yazdanparast

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Analysis of blade-disc dovetail joints is one of the biggest challenges facing designers of aero-engines. To avoid comparatively expensive experimental full-scale tests, numerical methods can be used to simulate loaded disc-blades assembly. Mortar method provides a powerful and flexible tool for solving frictional contact problems. In this study, 2D frictional contact in dovetail has been analysed based on the mortar algorithm. In order to model the friction, the classical law of coulomb and moving friction cone algorithm is applied. The solution is then obtained by solving the resulting set of non-linear equations using an efficient numerical algorithm based on Newton–Raphson Method. The numerical results show that this approach has better convergence rate and accuracy than other proposed numerical methods.

Keywords: computational contact mechanics, dovetail joints, nonlinear FEM, mortar approach

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Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

Abstract:

In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Jothilakshmy Nagammal

Abstract:

This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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Authors: P. Pramod Kumar, Madhu Salumari, V. V. Subba Rao

Abstract:

Due to their high strength-to-weight ratio, carbon nanotube (CNTs) reinforced polymer composites are being considered as one of the most promising nanocomposites which can improve the performance when used in structural applications. The buckling behavior is one of the most important parameter needs to be considered in the design of structural members like beams and plates. In the present paper, the elastic constants of CNT reinforced polymer composites are evaluated by using Mori-Tanaka micromechanics approach. Knowing the elastic constants, an analytical study is being conducted to investigate the buckling behavior of nanocomposites for different CNT volume fractions at different boundary conditions using first-order shear deformation theory (FSDT). The effect of stacking sequence and CNT radius on the buckling of beam has also been presented. This study is being conducted primarily with an intension to find the stiffening effect of CNTs when used in polymer composites as reinforcement.

Keywords: CNT, buckling, micromechanics, FSDT

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Authors: P. Satish Kumar, V. Ramu, K. Ramakrishna

Abstract:

In this paper, an efficient multilevel wave form synthesis technique is proposed and applied to a 99-level inverter. The basic principle of the proposed scheme is that the continuous output voltage levels can be synthesized by the addition or subtraction of the instantaneous voltages generated from different voltage levels. This synthesis technique can be realized by an array of switching devices composing full-bridge inverter modules and proper mixing of each bi-directional switch modules. The most different aspect, compared to the conventional approach, in the synthesis of the multilevel output waveform is the utilization of a combination of bidirectional switches and full bridge inverter modules with reduced number of components. A 99-level inverter consists of three full-bridge modules and six bi-directional switch modules. The validity of the proposed scheme is verified by the simulation.

Keywords: cascaded connection, multilevel inverter, synthesis, total harmonic distortion

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Authors: Jiao Li

Abstract:

Language teachers have been expected to play diversified new roles in times of educational changes. Considering the critical role that materials play in teaching and learning, language teachers have been increasingly involved in developing materials. Using identity as an analytic lens, this study aims to explore language teachers’ experiences as materials developers in China, focusing on the challenges they face and responses to them. It will adopt a multimethod approach. At the first stage, about 12 language teachers who have developed or are developing materials will be interviewed to have a broad view of their experiences. At the second stage, three language teachers who are developing materials will be studied by collecting interview data, policy documents, and data obtained from online observation of their group meetings so as to gain a deeper understanding of their experiences in materials development. It is expected that this study would have implications for teacher development, materials development, and curriculum development as well.

Keywords: educational changes, teacher development, teacher identity, teacher learning, materials development

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Authors: Brian Kwok

Abstract:

Hong Kong is well-known for its name as "the Pearl of the Orient", due to its spectacular night-view with vast amount of decorative neon lights on the streets. Neon signs are first used as the pervasive media of communication for all kinds of commercial advertising, ranging from movie theatres to nightclubs and department stores, and later appropriated by artists as medium of artwork. As a well-established visual language, it displays texts in bilingual format due to British's colonial influence, which are sometimes arranged in an opposite reading order. Research on neon signs as a visual representation is rare but significant because they are part of people’s collective memories of the unique cityscapes which associate the shifting values of people's daily lives and culture identity. Nevertheless, with the current policy to remove abandoned neon signs, their total number dramatically declines recently. The Buildings Department found an estimation of 120,000 unauthorized signboards (including neon signs) in Hong Kong in 2013, and the removal of such is at a rate of estimated 1,600 per year since 2006. In other words, the vernacular cultural values and historical continuity of neon signs will gradually be vanished if no immediate action is taken in documenting them for the purpose of research and cultural preservation. Therefore, the Hong Kong Neon Signs Archive project was established in June of 2015, and over 100 neon signs are photo-documented so far. By content analysis, this project will explore the two components of neon signs – the use of visual languages and vernacular tacit knowledge of neon makers. It attempts to answer these questions about Hong Kong's neon signs: 'What are the ways in which visual representations are used to produce our cityscapes and streetscapes?'; 'What are the visual languages and conventions of usage in different business types?'; 'What the intact knowledge are applied when producing these visual forms of neon signs?'

Keywords: cityscapes, neon signs, tacit knowledge, visual representation

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Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

Abstract:

In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

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