Design of a Drivetrain for Sae Baja Racing Off-Road Vehicle

With growing time, the participation of the students in SAE BAJA is increasing year by year. The vehicle\u27s performance is highly dependent on the installation and appropriate use of Drivetrain components. Drivetrain includes powertrain (prime mover i.e. engine/motor) and transmission components (gearbox, shafts etc). Therefore, Drivetrain is also called as the driving force of any vehicle. The proper design of Drivetrain is thus a part and parcel for any vehicle. The lack of literature available for a optimize design of Drivetrain makes it a hard nut to crack for the students who don\u27t have any past experience. Thus there is a need for some source by which the students can learn to design the Drivetrain for SAE BAJA. The engine vibration is another aspect which is needed to be considered. NVH consideration is another deciding parameter in BAJA vehicle\u27s performance which if neglected could leads to lethal results. Therefore proper installation of engine mounts is required according to the need. Thus, this segment aims at developing the Drivetrain for BAJA vehicles which can boost up the performance of the vehicle. Properly use of a powertrain and transmission components for a vehicle along with the calculations according to the need will be discussed in detail. This segment also aims at developing the conceptual understanding of the performance parameters of a BAJA vehicle among the student which will be helpful in their academic curriculum as wel

Automatic Concept Embedding Model (ACEM): No train-time concepts, No issue!

Interpretability and explainability of neural networks is continuously increasing in importance, especially within safety-critical domains and to provide the social right to explanation. Concept based explanations align well with how humans reason, proving to be a good way to explain models. Concept Embedding Models (CEMs) are one such concept based explanation architectures. These have shown to overcome the trade-off between explainability and performance. However, they have a key limitation -- they require concept annotations for all their training data. For large datasets, this can be expensive and infeasible. Motivated by this, we propose Automatic Concept Embedding Models (ACEMs), which learn the concept annotations automatically.Comment: Appeared in IJCAI 2023 Workshop on Explainable Artificial Intelligence (XAI

Geographic location based search application

LAUREA MAGISTRALEGli algoritmi di ricerca per i siti web sono in evoluzione dal momento in cui sono stati creati siti web dinamici che raccolgono e memorizzano i dati. È ormai diventata una procedura fondamentale nello sviluppo di un sito web, l'implementazione di un buon algoritmo di ricerca che aiuta gli utenti a trovare risultati rilevanti. Per i siti web con contenuti che si occupano di posizioni geografiche, un algoritmo di ricerca che utilizza il sistema di coordinate geografiche per recuperare i dati è vantaggioso in quanto invece che restituire "cosa" l'utente sta cercando, l'interrogazione restituisce "dove" l'utente sta cercando. La ricerca basata sulla localizzazione geografica svolge un ruolo fondamentale per aiutare gli utenti a trovare risultati rilevanti, considerando che la posizione della ricerca sarà molto specifica per l'area interessata. A sua volta, questo approccio richiede che i dati siano memorizzati in modo che ogni singola informazione sia composta da una coppia di coordinate come valori predefiniti. In questa tesi, discutiamo il modo in cui il concetto di algoritmo di ricerca basata sulla localizzazione può essere utilizzato per le applicazioni Web. Sono anche discussi i componenti e le strutture utilizzate per la sua implementazione con l'aiuto di 'foody experience', una piattaforma che collega persone di varie città a viaggiatori provenienti da tutto il mondo.Search Algorithms for websites have been evolving since the time when dynamic websites came into existence, which collect and store data. It has now become a fundamental procedure in the development of a website, to implement a good search algorithm which helps the users to find relevant results. For websites with content dealing with geographic locations, a search algorithm which uses the geographic coordinate system to retrieve data is advantageous, as it requires the query to be ‘where’ the user is searching, rather than ‘what’ the user is searching for. Geographic Location based search now plays a key role in helping the users find results which are relevant to them, as considering the location for querying will make the search very specific to the area the user is searching in. In turn, this approach also requires the data to be stored in way that every piece of information is having a pair of coordinates as default property. In this thesis, we discuss how the concept of location based search algorithm can be used for Web Applications, and describe the components and frameworks used for its implementation with the help of the work ‘foody experience’, which is a platform that connects hosts from various cities to travelers from all over the world

On Model Stability as a Function of Random Seed

In this paper, we focus on quantifying model stability as a function of random seed by investigating the effects of the induced randomness on model performance and the robustness of the model in general. We specifically perform a controlled study on the effect of random seeds on the behaviour of attention, gradient-based and surrogate model based (LIME) interpretations. Our analysis suggests that random seeds can adversely affect the consistency of models resulting in counterfactual interpretations. We propose a technique called Aggressive Stochastic Weight Averaging (ASWA)and an extension called Norm-filtered Aggressive Stochastic Weight Averaging (NASWA) which improves the stability of models over random seeds. With our ASWA and NASWA based optimization, we are able to improve the robustness of the original model, on average reducing the standard deviation of the model's performance by 72%.Comment: v1; Accepted for publication at CoNLL 201

Relaxation dynamics of carbon nanotubes of enriched chiralities

In our work we combined experimental and theoretical investigations of the relaxation dynamics of the single wall carbon nanotubes (SW-CNTs) in solution samples with enriched chiralities of (7,5) and (7,6) species. In two-color pump-probe studies we observe three-exponential decay in the differential transmission spectra in the range of few picoseconds, tens of picoseconds, and hundreds of picoseconds. Decay curves are very similar for both SW-CNT chiralities under resonant excitation and probing of excited and ground state transition energies, respectively. Both types of tubes exhibit no changes in decay for the different excitation energies in the range ±50meV around the excited state. By tuning the probe pulse towards energies higher then ground state (up to +350meV) we observe acceleration of the first decay component from 5.8ps down to 1.6ps. Our experimental results are supported by time resolved microscopic calculations based on carbon nanotube Bloch equations proving the fast decay component behavior being dominated through scattering with acoustic phonons