Introduction to the special issue on teaching and learning in information retrieval

We present an overview of the special issue in this paper. The main objective is to provide information for lecturers on how to improve the student experience, using current knowledge in the field. To this end we present an overview of six papers covering areas as diverse as tools and methods used to support teaching and learning, pedagogical challenges in teaching mathematics for search, etc

Information retrieval and machine learning methods for academic expert finding

In the context of academic expert finding, this paper investigates and compares the performance of information retrieval (IR) and machine learning (ML) methods, including deep learning, to approach the problem of identifying academic figures who are experts in different domains when a potential user requests their expertise. IR-based methods construct multifaceted textual profiles for each expert by clustering information from their scientific publications. Several methods fully tailored for this problem are presented in this paper. In contrast, ML-based methods treat expert finding as a classification task, training automatic text classifiers using publications authored by experts. By comparing these approaches, we contribute to a deeper understanding of academic-expert-finding techniques and their applicability in knowledge discovery. These methods are tested with two large datasets from the biomedical field: PMSC-UGR and CORD-19. The results show how IR techniques were, in general, more robust with both datasets and more suitable than the ML-based ones, with some exceptions showing good performance.Agencia Estatal de Investigación | Ref. PID2019-106758GB-C31Agencia Estatal de Investigación | Ref. PID2020-113230RB-C22FEDER/Junta de Andalucía | Ref. A-TIC-146-UGR2

Lucene4IR: Developing information retrieval evaluation resources using Lucene

The workshop and hackathon on developing Information Retrieval Evaluation Resources using Lucene (L4IR) was held on the 8th and 9th of September, 2016 at the University of Strathclyde in Glasgow, UK and funded by the ESF Elias Network. The event featured three main elements: (i) a series of keynote and invited talks on industry, teaching and evaluation; (ii) planning, coding and hacking where a number of groups created modules and infrastructure to use Lucene to undertake TREC based evaluations; and (iii) a number of breakout groups discussing challenges, opportunities and problems in bridging the divide between academia and industry, and how we can use Lucene for teaching and learning Information Retrieval (IR). The event was composed of a mix and blend of academics, experts and students wanting to learn, share and create evaluation resources for the community. The hacking was intense and the discussions lively creating the basis of many useful tools but also raising numerous issues. It was clear that by adopting and contributing to most widely used and supported Open Source IR toolkit, there were many benefits for academics, students, researchers, developers and practitioners - providing a basis for stronger evaluation practices, increased reproducibility, more efficient knowledge transfer, greater collaboration between academia and industry, and shared teaching and training resources

Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning

Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relies on speech and facial information. For the speech-based modality, we evaluated several transfer-learning techniques, more specifically, embedding extraction and Fine-Tuning. The best accuracy results were achieved when we fine-tuned the CNN-14 of the PANNs framework, confirming that the training was more robust when it did not start from scratch and the tasks were similar. Regarding the facial emotion recognizers, we propose a framework that consists of a pre-trained Spatial Transformer Network on saliency maps and facial images followed by a bi-LSTM with an attention mechanism. The error analysis reported that the frame-based systems could present some problems when they were used directly to solve a videobased task despite the domain adaptation, which opens a new line of research to discover new ways to correct this mismatch and take advantage of the embedded knowledge of these pre-trained models. Finally, from the combination of these two modalities with a late fusion strategy, we achieved 80.08% accuracy on the RAVDESS dataset on a subject-wise 5-CV evaluation, classifying eight emotions. The results revealed that these modalities carry relevant information to detect users’ emotional state and their combination enables improvement of system performance

Frictional power losses on spur gears with tip reliefs. The load sharing role

The load sharing impact on the efficiency of spur gears with modified profile was assessed in this work. The aim was to analyse the influence of the profile modifications on the load sharing, which also considers the effect of the torque level on the system deflections, and how these load sharing variations affected the system efficiency. Due to the frictional effect importance on power losses, in the operating conditions considered, sliding friction between teeth in presence of lubricant was studied in this proposal. The results established that tip relief improves the efficiency of the system due to the reduction of effective contact ratio. Moreover, there is a tip relief which makes optimal the efficiency in specific operating conditions, corresponding to the unit value of the effective contact ratio. Thus, the main conclusion of this work is that the tip relief which makes optimal the efficiency coincides with the theoretical dynamic optimum of the transmission.The authors would like to acknowledge Project DPI 2013-44860 funded by the Spanish Ministry of Science and Technology and the COST ACTION TU 1105 for supporting this research

Analysis of human-induced vibrations in a lightweight framework

This article analyzes the vibratory behavior of a Material-Composed Sandwich (MCS) framework for residential buildings. It has been observed qualitatively that the use of this kind of framework leads to poor comfort levels. The goal of this study is to find out the sources of this lack of comfort, in order to suggest guidelines that can enhance the performance of the MCS framework, without jeopardizing its advantages with respect to the traditional frameworks. To achieve this objective, an Experimental Modal Analysis (EMA) of a sample MCS framework has been carried out in order to determine the dynamic parameters. Then, a numerical Finite Element (FE) model of said sample MCS framework has been developed and adjusted with the results obtained in the experimental test. Based on this, a real-dimension MCS framework FE model has been built and the resultant behavior compared with that of a commonly used framework made of reinforced concrete. This comparison is finally used to assess the uncomfortable dynamic response of the MCS framework and to draw conclusions on the design guidelines in order to enhance the MCS framework vibratory behaviorThe authors would like to acknowledge Project DPI2013-44860 funded by the Spanish Ministry of Science and Technology and COST ACTION TU 1105 for supporting this research

Enhancement of Mechanical Engineering Degree through student design competition as added value. Considerations and viability

This paper proposes using a student design competition as a learning tool in the Mechanical Engineering Degree for enhancing the general competences and motivation of the students, transferring theoretical knowledge to practical situations and bringing together all courses involved under a common framework. This constitutes an added value that the in-person universities should offer to their students as a consequence of the Bologna process and the raising of open online resources for self-learning. In order to assess the viability of this proposal, a pilot competition design activity (CDA) is presented using project-based learning methods during a Mechanism Theory course for sophomore students. Meanwhile, 27 participants of a 45-student course from a European university took part in the pilot CDA, which consisted of redesigning the motorbike rear suspension used in a student design competition. Participants also completed mid-term and final exams as well as a survey to get their perception of this activity. Based on the success of the pilot CDA, the authors are planning to implement the proposal, including similar CDAs in other Mechanical Engineering courses to use the competition as a link between them and to encourage students to participate on the competition.This work [Project DPI2013-44860] was supported by the Spanish Ministry of Science and Technology and Vicerrector Primero y de Profesorado of the University of Cantabria

Planetary transmission load sharing: Manufacturing errors and system configuration study

This paper addresses the effect of manufacturing errors such as eccentricity and planet pin positioning errors on the quasi-static behavior of a 3 planet planetary transmission, taking into account different configurations regarding the bearing condition of the sun gear shaft. The aim of the paper is to shed light on some untouched aspects of the load sharing behavior of planetary transmissions, such as the effect of radial positioning errors of the planets when different pressure angles are used, and the impact of the different loadings per planet on the actual load per tooth. A modeling approach is employed, and physical explanations and simplified graphs are provided to help understand the behavior of the transmission when the sun is allowed to float and errors are introduced. The model used, developed by the authors and presented and validated in previous works, hybridizes analytical solutions with finite element models in order to compute the contact forces. The results obtained show that the teeth loads are much lower than expected compared to the planet uneven loads, both in the non-defected and defected transmission, and that radial positioning errors have non-negligible effect on the load sharing ratio under certain operating conditions.The authors would like to acknowledge Project DPI2013-44860 funded by the Spanish Ministry of Science and Technology for supporting this research

Frictional power losses on spur gears with tip reliefs. The friction coefficient role

In this proposal, the effect of the friction coefficient on the efficiency of spur gears with tip reliefs was analysed. For this purpose, the efficiency values using an average friction coefficient along the mesh cycle were compared with those obtained implementing an enhanced friction coefficient formulation, which is based on elastohydrodynamic lubrication fundamentals. In this manner, it can be established the differences between both formulations in the efficiency and friction coefficient values, as well as the advantages of using this enhanced friction coefficient with respect to formulations implemented in traditional approaches of efficiency calculation. In addition to studying the impact of the friction coefficient choice on efficiency, the profile modifications influence on the friction coefficient and efficiency was also assessed. In this regard, three tip relief case studies were set out; pinion tip reliefs, driven wheel tip reliefs and profile modifications in both gears. From the results, it was inferred that the choice of friction coefficient formulation clearly influences the efficiency in gear transmissions with tip reliefs, obtaining discrepancies between both formulations with regard to which tip relief case study provides the lowest efficiency values.The authors would like to acknowledge Project DPI 2013-44860 funded by the Spanish Ministry of Science and Technology

Gear transmission dynamics: Effects of index and run out errors

This work describes a non-linear dynamic model for the study of the vibration signals generated by gear transmissions. The developed model considers both the parametric excitations due to the variable compliance of bearings and gears, can handle changes in the transmitted torque and allows the integration of the dynamic equations quickly and accurately. This model has been developed previously by the authors to assess the profile deviations on the dynamic behavior of gear transmissions and its influence on the transmitted torque. It also includes the presence of gear defects as cracks and pitting during the calculation of meshing forces. In this paper, the model has been enhanced in order to include two common defects such as index errors and run out or eccentricity errors. Index errors occur as a result of a non-uniform angular distribution of the tooth profiles along the pitch circle. Run out appears due to the displacement of the geometric center of the gear with respect to the center of rotation of the shaft on which it is mounted. Although both errors are caused by different reasons, sometimes they have been confused because of their similitudes. The procedure for including both kinds of errors in the model is described and simulations under several transmitted torques are presented. The results are assessed and compared focusing the attention on certain transmission parameters and magnitudes as transmission error, load forces in the tooth flanks and demodulation techniques on the resulting vibratory signals.The authors would like to acknowledge Project DPI2013-44860 funded by the Spanish Ministry of Science and Technology and COST ACTION TU 1105 for supporting this research