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And Now What (Part 1)? Language Teaching: How We Met the ERT Challenge? 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Guerra, Joaquim CIAC Algarve Univ Campus Gambelas P-8005139 Faro Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Foreign language teaching in general has been thought of from a dynamic perspective, in face-to-face context learning, where learners and teachers interact immediately and simultaneously in the classroom. COVID-19 and the successive lockdowns were a complex test for teaching and learning in general. The pandemic forced a discourse and methodological change with an urgent integration of ICT in the teaching and learning process. These allowed the incorporation of applications that ensure immediate contact and at the same time are within the reach of all teachers and learners. Based on a survey that led to the development of a questionnaire addressed to teachers, this study seeks to take stock of the teaching of foreign languages, in particular, post-lockdowns. The questionnaire had both closed and open-ended questions, and the data were analyzed statistically and through content analysis. This paper presents the social, demographic, and academic background of the participants and what they considered their difficulties. In short, they revealed that they faced similar pedagogical and technological difficulties as other university teachers, leading one to believe that the Emergency Remote Teaching highlighted the general lack of preparation of university teachers to deal with emergency situations, such as the one experienced during the COVID-19 lockdowns, regardless of the country and teaching context.

关键词： Foreign Language Teaching COVID-19 Emergency Remote Teaching Consequences Technology in Education Teaching Methodology Digital Literacy Higher Education

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Prioritisation of Software Demands Using the Analytic Hierarchy Process Method: A Case Study in a Public Organisation 13th

Prioritisation of Software Demands Using the Analytic Hierar...

引用

13th Computer Science Online Conference

作者： de Farias, Maria Adalgiza Pinheiro, Placido Rogerio Forte, Dilthey Pontes Univ Fortaleza Fortaleza Ceara Brazil

ISBN: (纸本)9783031702990;9783031703003

This research aimed to establish priorities for addressing demands by executing WorkOrders (WO) in the systems development sector of a public agency in the state of Ceara. Throughout the process, the sequence of execution of WOs registered between 2021 and 2023 was prioritised, considering weights and values defined by decision-makers through the application of the Analytic Hierarchy Process (AHP), combining techniques of relative and absolute measurement. The research was conducted through a single case study using semi-structured interviews and documentary analysis based on registered demands. Four professionals from the agency participated, working with the researcher to develop the AHP method. The results indicate that the opening date and the time for the execution of each WO were irrelevant, given the weight assigned to each activity/task to be performed. New priorities were defined, and a ranking of twenty-seven WOs to be executed sequentially was structured. The commitment of those involved made it possible to organise the execution of these WOs concurrently with the daily incoming demands.

关键词： Multicriteria Decision Analysis Analytic Hierarchy Process (AHP) method Demands Prioritisation Work Orders Management systems

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Identifying Valid User Stories Using BERT Pre-trained Natural Language Models 11th

Identifying Valid User Stories Using BERT Pre-trained Natura...

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Scoggin, Sandor Borges Marques-Neto, Humberto Torres Pontifical Catholic Univ Minas Gerais PUC Minas Dept Comp Sci Belo Horizonte MG Brazil

ISBN: (纸本)9783031456473;9783031456480

Currently, in the software industry, agile methodologies are vastly adopted. These methods use natural language for Requirement Engineering (RE) and are mostly done through the usage of User Stories (UST). This translates into a high cost to elicit and map the software requirements. Pre-trained language models have been shown to be able to verify the validity of requirements in UST format. Aiming to further understand their effectiveness, this paper presents a comparison between different BERT models to validate UST and discusses which model is the most efficient for RE. The main contributions contemplate an enhancement of the available datasets and validation models with up to 98% accuracy. We understand that further analyses should consider which aspect is more important in real-world applications: recall or precision.

关键词： User Stories BERT NLP

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Modeling, Identification and Analysis of Twin Rotor MIMO systems 13th

Modeling, Identification and Analysis of Twin Rotor MIMO Sys...

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13th Computer Science Online Conference

作者： Wendimu, Abebe Alemu Shaikh, Ibrahim Zerdazi, El Wardi Matusu, Radek Tomas Bata Univ Zlin Fac Appl Informat Dept Automat & Control Engn Nam TG Masaryka 5555 Zlin 76001 Czech Republic

ISBN: (纸本)9783031702846;9783031702853

This paper focuses on the modeling and identification of a Twin Rotor Multi-Input-Multi-Output systems (TRMS). It begins with an overview of TRMS, followed by the formulation and analysis of a comprehensive nonlinear model based on first principles. The static characteristics of main-elevation and tail-azimuth are explored, considering the influence of rotors on each other. Factors affecting real-time model measurements are investigated. The paper then proceeds to identify TRMS parameters using the "fminsearch" algorithm, the Autoregressive Exogenous Input (ARX) model and Auto-Regressive Moving Average with Exogenous Input (ARMAX) models. Comparative analyses of results from each method are presented. Finally, a comprehensive comparison is made between the nonlinear model, linear models, and real-time experimental data for elevation /pitch and azimuth /yaw angles. This work significantly contributes to understanding TRMS systems, providing insights into nonlinear modeling, identification, and analysis. The findings establish a foundation for advancing comprehension of plant behavior and designing requisite control systems.

关键词： Linear identification Linear model Nonlinear model Twin Rotor MIMO systems

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Development of Autonomous Vehicle Motion Planning and Control Algorithms with D* Planner and Model Predictive Control

Development of Autonomous Vehicle Motion Planning and Contro...

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Intelligent systems Conference (IntelliSys)

作者： Mondal, Somnath Chen, Bo Michigan Technol Univ Houghton MI 49931 USA

ISBN: (纸本)9783031477171;9783031477188

This paper presents the development of motion planning and control algorithms for autonomous vehicles in a dynamic environment. Path planning are implemented using the D Star (Dynamic A Star) path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm are tested using Model-In-the-Loop (MIL) method with the help of MATLAB((R)) Driving Scenario Designer and Unreal Engine((R)) Simulator by Epic Games((R)). Test scenario is built, and a camera sensor is configured to simulate the sensory data and feed it to the controller for further processing and vehicle motion planning. Simulation results of vehicle motion control with path planning for dynamic obstacle avoidance are presented. The simulation results show that an autonomous vehicle (ego vehicle) follows a commanded velocity when the relative distance between the ego vehicle and an obstacle is greater than a calculated safe distance. When the relative distance is close to the safe distance, the ego vehicle maintains the headway. When an obstacle is detected by the ego vehicle and the ego vehicle wants to pass the obstacle, the ego vehicle performs obstacle avoidance maneuver by tracking desired lateral positions.

关键词： Autonomous vehicle motion planning D star algorithm Model predictive control

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An Evaluation of Gender Bias in 167K Movie Posters

An Evaluation of Gender Bias in 167K Movie Posters

引用

Intelligent systems Conference

作者： Song, Yusen Pocol, Andreea Istead, Lesley Carleton Univ Ottawa ON K1S 5B6 Canada Univ Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9783031663284;9783031663291

Movie posters, as the front-line marketing tools, significantly shape audience expectations and perceptions, making their analysis crucial for understanding broader industry trends. This study uses the DeepFace facial recognition library to identify 'gender bias' in movie posters, which we define by the disproportionate prominence of male characters in terms of visibility, spatial position, and size, as compared to female characters. Employing novel analytical techniques, we examined a dataset of 167,322 movie posters and observed a prevalent male bias. This bias is consistent across genres, geographical regions, and decades, though variations exist: action and adventure genres display pronounced male bias, while romance genres show more balanced representations. Additionally, movies exhibiting male bias tend to achieve higher box office revenues and ratings. Our findings underscore the need for addressing gender representations in movie marketing materials and suggest avenues for future research in this domain. We conclude with a poster analysis of the 50 highest-grossing movies of all time, which shows that gender - and racial - representation is improving over time.

关键词： Big data Film Face detection

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Ocean Wind Speed Retrieval Method with a Relative Wind Direction Using Microwave Radiometer Data

Ocean Wind Speed Retrieval Method with a Relative Wind Direc...

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Intelligent systems Conference (IntelliSys)

作者： Arai, Kohei Azuma, Kenta Saga Univ Saga 8408502 Japan

ISBN: (纸本)9783031477171;9783031477188

An ocean wind speed retrieval method with microwave radiometer data is proposed considering relative wind directions on observed brightness temperature. The conventional method is based on regressive analysis between in-situ ocean wind and brightness temperature observed with microwave radiometer without consideration of relative wind direction. Although geophysical parameters are also taken into account for the conventional method based on regression analysis based on least square method such as steepest descent method, conjugate gradient method, etc., global optimum solution cannot be expected. The proposed method is based on the geophysical models and uses a modified simulated annealing. In the experiment, Advanced Microwave Scanning Radiometer (AMSR-E) data and the corresponding NCEP Global Data Assimilation System (GDAS) data are used. It is found the discrepancy between the wind speed derived from AMSR-E and GDAS depending on Relative Wind Direction (RWD). Also, it is found that the estimation accuracy is improved by up to 61.2% which depends on location and seasons in concern. In the worst case, ocean speed estimation accuracy was degraded by 0.94% though.

关键词： Ocean wind speed Microwave radiometer Brightness temperature Advanced microwave scanning radiometer (AMSR-E) NCEP global data assimilation system (GDAS) Relative wind direction (RWD)

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Modeling of Hybrid Energy systems Based on Renewable Energy Sources to Cover the Electricity Needs of a Higher Education Institution Using Homer Pro Software 10th

Modeling of Hybrid Energy Systems Based on Renewable Energy ...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Hadziahmetovic, Halima Spago, Damir Husika, Azrduin Sehic, Hadide Univ Sarajevo Fac Mech Engn Sarajevo 71000 Bosnia & Herceg Univ Dzemal Bijedic Mostar Fac Mech Engn Mostar 88104 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

The paper presents the optimization of HRES for covering the electricity needs of a higher education institution using Homer Pro software. 6 scenarios with different system costs were modeled (such as sale and purchase prices of electricity as well as the prices of certain technologies) where technologies such as PV panels, small wind turbines, diesel generators, batteries, etc. were taken into account. The optimization results in all scenarios show that the use of batteries is not profitable and that the need for an additional source of energy such as a diesel generator does not exist. The energy and environmental characteristics of the system were analyzed and it was shown that it is possible to achieve the prosumer type for buildings of similar purpose.

关键词： Hybrid renewable energy systems optimization Homer Pro Prosumer

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Expert systems in Information Security: A Comprehensive Exploration of Awareness Strategies Against Social Engineering Attacks 12th

Expert Systems in Information Security: A Comprehensive Expl...

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Cardoso, Waldson Rodrigues Lima Ribeiro, Admilson de Ribamar Cardoso da Silva, Joao Marco Univ Fed Sergipe Comp Dept UFS Sao Cristovao Brazil Univ Minho Dept Informat Braga Portugal

ISBN: (纸本)9783031602177;9783031602184

This article delves into the pivotal role of expert systems in bolstering information security, with a specific emphasis on their effectiveness in awareness and training programs aimed at thwarting social engineering attacks. Employing a snowball methodology, the research expands upon seminal works, highlighting the intersection between expert systems and cybersecurity. The study identifies a gap in current understanding and aims to contribute valuable insights to the field. By analyzing five key articles as seeds, the research explores the landscape of expert systems in information security, emphasizing their potential impact on cultivating robust defenses against evolving cyber threats.

关键词： Expert systems Information Security Cybersecurity Education Social Engineering Snowball Methodology

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Explainable Dynamic Ensemble Framework for Classification Based on the Late Fusion of Heterogeneous Multimodal Data

Explainable Dynamic Ensemble Framework for Classification Ba...

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Intelligent systems Conference (IntelliSys)

作者： Juraev, Firuz El-Sappagh, Shaker Abuhmed, Tamer Sungkyunkwan Univ Coll Comp & Informat Seoul South Korea Galala Univ Fac Comp Sci & Engn Suez Egypt

ISBN: (纸本)9783031477140;9783031477157

Ensuring precise and reliable classification effectiveness holds paramount importance in essential sectors such as medicine, industry, and healthcare. Machine learning (ML) techniques have evolved in recent years to address the performance, efficiency, and robustness of the applied models. Recent advancements inMachine Learning (ML) techniques have aimed to enhance the performance, efficiency, and robustness of applied models. Ensemble learning has been shown to exhibit superior accuracy, robustness, and generalization capability over classical single ML models in most classification problems. Although dynamic ensembles have extended the performance of static ensembles such as random forest and boosting, current literature on dynamic ensembles primarily focuses on the early fusion of multimodal data. In this study, we present a novel framework that combines dynamic ensemble selection (DES) with a late fusion of heterogeneous multimodal data and model explainability. We evaluated our approach on a classification task of hospital mortality prediction, and our approach achieves a testing accuracy of 90.16%, surpassing existing techniques and providing physicians with case-based reasoning and deep-based classifiers contributions explanations to support their decision-making. We compare our proposed framework against nine widely used ML techniques, including static and dynamic ensemble models with early fusion and static ensemble models with late fusion on a dataset of 6,600 patients from MIT's GOSSIS dataset. The dynamic ensemble model with early fusion achieves a testing accuracy of 86.89%, the LightGBM model achieves a test accuracy of 87.72%, and the soft voting model reaches 87.97% and 89.45% using early and late fusion, respectively. Our proposed framework not only improves the accuracy and robustness of in-hospital mortality prediction models but also offers explainability and potential for further optimization to achieve even higher performance.

关键词： Dynamic ensemble classifier Multi-modality Early fusion Late fusion Static ensemble classifier Explainable ai In-hospital mortality prediction

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