Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Cardiac digital twins provide a physics and physiology informed framework to deliver predictive and personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs and the high number of model evaluations needed for patient-specific personalization. Artificial Intelligence-based methods can make the creation of fast and accurate whole-heart digital twins feasible. In this work, we use Latent Neural Ordinary Differential Equations (LNODEs) to learn the temporal pressure-volume dynamics of a heart failure patient. Our surrogate model based on LNODEs is trained from 400 3D-0D whole-heart closed-loop electromechanical simulations while accounting for 43 model parameters, describing single cell through to whole organ and cardiovascular hemodynamics. The trained LNODEs provides a compact and efficient representation of the 3D-0D model in a latent space by means of a feedforward fully-connected Artificial Neural Network that retains 3 hidden layers with 13 neurons per layer and allows for 300x real-time numerical simulations of the cardiac function on a single processor of a standard laptop. This surrogate model is employed to perform global sensitivity analysis and robust parameter estimation with uncertainty quantification in 3 hours of computations, still on a single processor. We match pressure and volume time traces unseen by the LNODEs during the training phase and we calibrate 4 to 11 model parameters while also providing their posterior distribution. This paper introduces the most advanced surrogate model of cardiac function available in the literature and opens new important venues for parameter calibration in cardiac digital twins

Dry Lab – Laboratorium Virtual Untuk Anlisa Rekayasa Lumpur Pemboran

Abstract Dry Lab is a virtual laboratory design. We called also as a laboratory of the future. Dry Lab was designed because of the increasingly advanced computerized especially Artificial Intelligence for making a simulator that can function to simulate a tool wich is can similiar with the real condition so that it gets the same results as when run in a conventional laboratory. With the existence of this Simulator technology, then I try to make a virtual simulator for drilling mud analysis which is very much needed in the world of oil engineering education especially and also needed in the world of oil and gas industry, especially when conducting drilling activities. Keywords: Dry Lab, Artificial Intelligence, virtual simulator, drilling mud. Abstrak Dry Lab adalah suatu rancangan virtual laboratorium. Dapat juga dikatakan sebagai Laboratorium masa depan. Dry Lab dirancang karena semakin majunya ilmu komputerisasi Artificial intelligence dalam membuat suatu simulator yang dapat berfungsi mensimulasikan suatu alat sesuai dengan cara kerja aslinya sehingga mendapatkan hasil yang sama seperti saat dijalankan di Laboratorium konvensional.Dengan adanya teknologi Simulator ini, maka saya mencoba membuat suatu simulator virtual untuk analisa lumpur pemboran yang sangat dibutuhkan dalam dunia pendidikan Teknik perminyakan khususnya dan juga dibutuhkan di dalam dunia industri Migas terutama saat melakukan kegiatan pemboran. Kata kunci: Dry Lab, Artificial intelligence, simulator virtual, lumpur pemboran. Reference: Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43. Aly Rasyid, A. R. (2021). Seleksi Material Untuk Casing Sumur Migas & Geothermal–Buku Referensi. Composition and Properties of Drilling and Completion Fluids: Seventh Edition, Caenn, RyenDarley, H. C.H. and Gray, George R. (2016) Composion And Properties Of Drilling And Complition Fluids,  H.C.H Darley and George R. Gray J.T. Patton (New Mexico State U.) P.F. Phelan (Los Alamos Natl Laboratory), Well Damage Hazards Associated With Conventional Completion Fluids Khodja, M., Khodja-Saber, M., Canselier, J. P., Cohaut, N. and Bergaya, F. (2010) ‘Drilling fluid technology: performances and environmental considerations’, Product and Services, From R&D to final solutions, pp. 227-232. Available at: http://cdn.intechopen.com/pdfs-wm/12330.pdf Nasution, M. M., Rasyid, A., & Pahrudin, G. (2022). Desain Formulasi Lumpur Untuk Pemboran Panas Bumi Di Sumur GG-01. JURNAL BHARA PETRO ENERGI, 11-18. Rasyid, A., Mardiana, R. Y., Budiono, K., & Noviasta, B. (2021, December). Drilling optimization in geothermal exploration wells using enhanced design of conical diamond element bit. In Asia Pacific Unconventional Resources Technology Conference, Virtual, 16–18 November 2021 (pp. 1795-1808). Unconventional Resources Technology Conference (URTeC). Rasyid, A., Soesanto, E., & Nababan, E. N. (2022). Evaluasi dan Optimasi Desain Casing Sumur Pemboran dengan Metode Maximum Load di Sumur ENN-1 di Lapangan Batuwangi. JURNAL BHARA PETRO ENERGI, 1-10. Rasyid, A. (2019). Pemanfaatan Wellbore Strengthening Agent Selama Pengeboran di Onshore Sumatera Bagian Utara Indonesia. Jurnal Jaring SainTek, 1(2). Rudi Rubiandini R.S, Buku Teknik Pemboran Volume 1, Bandung, 2015 Virtual and Physical Experimentation in Inquiry-Based Science Labs: Attitudes, Performance  and Access.Journal of Science Education and TechnologyPyatt, Kevin.,Sims, Rod, 2012 Virtual laboratories in engineering education: the simulation lab and remote labComputer Applications in Engineering Education.Balamuralithara, B. Woods, P. C. 2009 Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43.  

Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan

Variations on a Theme: A Bibliography on Approaches to Theorem Proving Inspired From Satchmo

This articles is a structured bibliography on theorem provers, approaches to theorem proving, and theorem proving applications inspired from Satchmo, the model generation theorem prover developed in the mid 80es of the 20th century at ECRC, the European Computer- Industry Research Centre. Note that the bibliography given in this article is not exhaustive

Allocation in Practice

How do we allocate scarcere sources? How do we fairly allocate costs? These are two pressing challenges facing society today. I discuss two recent projects at NICTA concerning resource and cost allocation. In the first, we have been working with FoodBank Local, a social startup working in collaboration with food bank charities around the world to optimise the logistics of collecting and distributing donated food. Before we can distribute this food, we must decide how to allocate it to different charities and food kitchens. This gives rise to a fair division problem with several new dimensions, rarely considered in the literature. In the second, we have been looking at cost allocation within the distribution network of a large multinational company. This also has several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on Artificial Intelligence (KI 2014), Springer LNC

Parameterized Algorithmics for Computational Social Choice: Nine Research Challenges

Computational Social Choice is an interdisciplinary research area involving Economics, Political Science, and Social Science on the one side, and Mathematics and Computer Science (including Artificial Intelligence and Multiagent Systems) on the other side. Typical computational problems studied in this field include the vulnerability of voting procedures against attacks, or preference aggregation in multi-agent systems. Parameterized Algorithmics is a subfield of Theoretical Computer Science seeking to exploit meaningful problem-specific parameters in order to identify tractable special cases of in general computationally hard problems. In this paper, we propose nine of our favorite research challenges concerning the parameterized complexity of problems appearing in this context