Quentin Grossetti, Cedric du Mouza, Nicolas Travers and Camelia Constantin
Social network platforms are considered today as a major communication mean. Their success leads to an unprecedented growth of user-generated content; therefore, finding…
Abstract
Purpose
Social network platforms are considered today as a major communication mean. Their success leads to an unprecedented growth of user-generated content; therefore, finding interesting content for a given user has become a major issue. Recommender systems allow these platforms to personalize individual experience and increase user engagement by filtering messages according to user interest and/or neighborhood. Recent research results show, however, that this content personalization might increase the echo chamber effect and create filter bubbles that restrain the diversity of opinions regarding the recommended content.
Design/methodology/approach
The purpose of this paper is to present a thorough study of communities on a large Twitter data set that quantifies the effect of recommender systems on users’ behavior by creating filter bubbles. The authors further propose their community-aware model (CAM) that counters the impact of different recommender systems on information consumption.
Findings
The authors propose their CAM that counters the impact of different recommender systems on information consumption. The study results show that filter bubbles effects concern up to 10% of users and the proposed model based on the similarities between communities enhance recommendations.
Originality/value
The authors proposed the CAM approach, which relies on similarities between communities to re-rank lists of recommendations to weaken the filter bubble effect for these users.
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Cedric Lab and Philippe Caussignac
A stationary 3D energy‐transport model valid for semiconductor heterostructure devices is derived from a semiclassical Boltznmann equation by the moment method. In addition to the…
Abstract
A stationary 3D energy‐transport model valid for semiconductor heterostructure devices is derived from a semiclassical Boltznmann equation by the moment method. In addition to the well‐known conservation equations, we obtain original interface conditions, which are essential to have a mathematically well‐posed problem. An appropriate modelling of the physical parameters appearing in the system of equations is proposed for gallium arsenide. The model being written and its particularities mentioned, we present a novel numerical algorithm to solve it. The discretization of the equations is achieved by means of standard and mixed finite element methods. We apply the model and numerical algorithm to simulate a 2D AlGaAs/GaAs MODFET. Comparisons between expenrimental measurements and calculations are carried out. The influence of the modelling of the physical parameters, especially the electron mobility and the energy relaxation time, is noted. The results show the satisfactory behaviour of our model and numerical algorithm when applied to GaAs heterostructure devices.
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C. David Remy, Oliver Baur, Martin Latta, Andi Lauber, Marco Hutter, Mark A. Hoepflinger, Cédric Pradalier and Roland Siegwart
The purpose of this paper is to introduce the robotic quadrupedal platform ALoF that is designed to aid research on perception in legged locomotion.
Abstract
Purpose
The purpose of this paper is to introduce the robotic quadrupedal platform ALoF that is designed to aid research on perception in legged locomotion.
Design/methodology/approach
A well‐balanced size and complexity of the robot results in a robust platform that is easy to handle, yet able to perform complex maneuvers as well as to carry sophisticated 3D sensors. A very large range of motion allows the robot to actively explore its surroundings through haptic interaction, and to choose between a wide range of planning options.
Findings
This robot was employed and tested in the lunar robotics challenge organized by the European Space Agency, for which the authors also developed a novel crawling gait, in which the weight of the robot is alternately supported by scaled plates under the main body and the four shank segments. This allowed for stable locomotion in steep terrain with very loose soil.
Originality/value
The paper describes how a very large range of motion allows the robot to actively explore its surroundings through haptic interaction, and to choose between a wide range of planning options. The paper describes how the authors developed a novel crawling gait, in which the weight of the robot is alternately supported by scaled plates under the main body and the four shank segments.
Cédric Plessis and Emin Altintas
The Great Resignation has led to a significant increase in the number of people quitting their jobs due to reasons such as stagnant wages, rising cost of living, job…
Abstract
Purpose
The Great Resignation has led to a significant increase in the number of people quitting their jobs due to reasons such as stagnant wages, rising cost of living, job dissatisfaction and safety concerns. Therefore, the aim of this study is that it is important to help people develop better cognitive resources to face adversity.
Design/methodology/approach
The Great Resignation has led to a significant increase in the number of people quitting their jobs due to reasons such as stagnant wages, rising cost of living, job dissatisfaction and safety concerns. Therefore, it is important to help people develop better cognitive resources to face adversity. In this study, we administered a questionnaire to 250 employees to determine the variables that could help them build cognitive resources. These variables included the satisfaction of basic psychological needs (autonomy, competence and affiliation), psychological capital, motivation regulation (within the self-determination theory) and well-being (assessed by self-esteem, positive emotions, positive automatic thoughts and vitality). The results revealed that satisfaction of basic needs is associated with better psychological capital and more self-autonomous behavior, which leads to higher psychological well-being. These findings are discussed in the paper, emphasizing the importance of management and work context that satisfy the basic needs and help to build resources with psychological capital.
Findings
The results revealed that satisfaction of basic needs is associated with better psychological capital and more self-autonomous behavior, which leads to higher psychological well-being. These findings are discussed in the paper, emphasizing the importance of management and work context that satisfy the basic needs and help to build resources with psychological capital.
Originality/value
Highlight the importance of consequences of the Great Resignation and the need to internationalize this concept.
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Keywords
Jacques Chabin, Cédric Eichler, Mirian Halfeld Ferrari and Nicolas Hiot
Graph rewriting concerns the technique of transforming a graph; it is thus natural to conceive its application in the evolution of graph databases. This paper aims to propose a…
Abstract
Purpose
Graph rewriting concerns the technique of transforming a graph; it is thus natural to conceive its application in the evolution of graph databases. This paper aims to propose a two-step framework where rewriting rules formalize instance or schema changes, ensuring graph’s consistency with respect to constraints, and updates are managed by ensuring rule applicability through the generation of side effects: new updates which guarantee that rule application conditions hold.
Design/methodology/approach
This paper proposes Schema Evolution Through UPdates, optimized version (SetUpOPT), a theoretical and applied framework for the management of resource description framework (RDF)/S database evolution on the basis of graph rewriting rules. The framework is an improvement of SetUp which avoids the computation of superfluous side effects and proposes, via
Findings
This paper shows graph rewriting into a practical and useful application which ensures consistent evolution of RDF databases. It introduces an optimised approach for dealing with side effects and a flexible and customizable way of dealing with non-determinism. Experimental evaluation of
Originality/value
SetUp originality lies in the use of graph rewriting techniques under the closed world assumption to set an updating system which preserves database consistency. Efficiency is ensured by avoiding the generation of superfluous side effects. Flexibility is guaranteed by offering different solutions for non-determinism and allowing the integration of customized choice functions.
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Mathias Vermeulen, Tom Claessens, Benjamin Van Der Smissen, Cedric S. Van Holsbeke, Jan W. De Backer, Peter Van Ransbeeck and Pascal Verdonck
The purpose of this paper is to use rapid prototyping technology, in this case fused deposition modeling (FDM), to manufacture 2D and 3D particle image velocimetry (PIV…
Abstract
Purpose
The purpose of this paper is to use rapid prototyping technology, in this case fused deposition modeling (FDM), to manufacture 2D and 3D particle image velocimetry (PIV) compatible patient‐specific airway models.
Design/methodology/approach
This research has been performed through a case study where patient‐specific airway geometry was used to manufacture a PIV compatible model. The sacrificial kernel of the airways was printed in waterworks™ which is a support material used by Stratasys Maxum FDM devices. Transparent silicone with known refractive index was vacuum casted around the kernel and after curing out, the kernel was removed by washing out in sodium hydroxide.
Findings
The resulting PIV model was tested in an experimental PIV setup to check the PIV compatibility. The results showed that the model performs quite well when the refractive index (RI) of the silicone and the fluid are matched.
Research limitations/implications
Drawbacks such as the surface roughness, due to the size of the printing layers, and the yellowing of the silicone, due to the wash out of the kernel, need to be overcome.
Originality/value
The paper presents the manufacturing process for making complex thick walled patient‐specific PIV models starting from a strong workable sacrificial kernel. This removable kernel is obtained by switching the building and the support materials of the FDM machine. In this way, the kernel was printed in support material while the building material was used to support the kernel during printing. The model was tested in a PIV setup and the results show that the airway model is suitable for performing particle image velocimetry.
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It's been three years since my previous survey in RSR. Superb reference books in pop music have been appearing so frequently that I've been having trouble keeping up. Let's hope…
Abstract
It's been three years since my previous survey in RSR. Superb reference books in pop music have been appearing so frequently that I've been having trouble keeping up. Let's hope “next year's” survey will only be 12 months in the making and not 36.
Zhenni Ni, Yuxing Qian, Shuaipu Chen, Marie-Christine Jaulent and Cedric Bousquet
This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.
Abstract
Purpose
This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.
Design/methodology/approach
Inspired by Dual Process Theory, we introduce two kinds of prompts: Conclusion-first (System 1) and Explanation-first (System 2), and their respective retrieval-augmented variations. We evaluate the performance of these prompts across accuracy, argument elements, common errors and cost-effectiveness. Our study, conducted on two public health fact-checking datasets, categorized 10,212 claims as knowledge, anecdotes and news. To further analyze the reasoning process of LLM, we delve into the argument elements of health fact-checking generated by different prompts, revealing their tendencies in using evidence and contextual qualifiers. We conducted content analysis to identify and compare the common errors across various prompts.
Findings
Results indicate that the Conclusion-first prompt performs well in knowledge (89.70%,66.09%), anecdote (79.49%,79.99%) and news (85.61%,85.95%) claims even without retrieval augmentation, proving to be cost-effective. In contrast, the Explanation-first prompt often classifies claims as unknown. However, it significantly boosts accuracy for news claims (87.53%,88.60%) and anecdote claims (87.28%,90.62%) with retrieval augmentation. The Explanation-first prompt is more focused on context specificity and user intent understanding during health fact-checking, showing high potential with retrieval augmentation. Additionally, retrieval-augmented LLMs concentrate more on evidence and context, highlighting the importance of the relevance and safety of retrieved content.
Originality/value
This study offers insights into how a balanced integration could enhance the overall performance of LLMs in critical applications, paving the way for future research on optimizing LLMs for complex cognitive tasks.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2024-0111
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Muddesar Iqbal, Sohail Sarwar, Muhammad Safyan and Moustafa Nasralla
The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.
Abstract
Purpose
The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.
Design/methodology/approach
Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.
Findings
The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.
Research limitations/implications
The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.
Social implications
E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.
Originality/value
A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.