Showing papers by "Aalto University published in 2022"
TL;DR: Interpolation Consistency Training (ICT) as mentioned in this paper encourages the prediction at an interpolation of unlabeled points to be consistent with the interpolations of the predictions at those points.
354 citations
TL;DR: This paper proposed a bidirectional emotional recurrent unit for conversational sentiment analysis, where a generalized neural tensor block followed by a two-channel classifier is designed to perform context compositionality and sentiment classification, respectively.
97 citations
TL;DR: A hybrid teaching-learning-based optimization (TLBO) and crow search algorithm (CSA) is used to obtain a reliable optimal solution with a low standard deviation for flexible EH in the presence of renewable energy sources and active loads.
54 citations
TL;DR: In this paper, the authors discuss the learning ability of buildings with a system-level perspective and present an overview of autonomous machine learning applications that make independent decisions for building energy management, and conclude that the buildings' adaptability to unpredicted changes can be enhanced at the system level through AI-initiated learning processes and by using digital twins as training environments.
54 citations
TL;DR: A novel encoder-decoder architecture, called contextual ensemble network (CENet), for semantic segmentation, where the contextual cues are aggregated via densely usampling the convolutional features of deep layer to the shallow deconvolutional layers.
51 citations
TL;DR: In this article, the authors proposed a novel deep learning method, i.e. variational mode decomposition long short-term memory (VMD-LSTM), for bus travel speed prediction in urban traffic networks using a forecast of bus arrival information on variable time horizons.
42 citations
TL;DR: In this article, a review of the DL methods for automatic detection of depression to extract a representation of depression from audio and video is presented. And the challenges and promising directions related to the automatic diagnoses of depression using DL are discussed.
39 citations
TL;DR: In this article , a novel encoder-decoder architecture, called contextual ensemble network (CENet), is proposed for semantic segmentation, where the contextual cues are aggregated via densely usampling the convolutional features of deep layer to the shallow deconvolutional layers.
34 citations
TL;DR: In this article , the authors present an introduction to how quantum geometry governs superfluidity in platforms including, and beyond, graphene, and explain how a new type of topology discovered in TBG could affect superconductivity, pinpoint the geometric contribution in its Beretzinskii-Kosterlitz-Thouless (BKT) critical temperature, and mention moir\'e materials beyond TBG.
Abstract: Designer 2D materials where the constituent layers are not aligned may result in band structures with dispersionless, "flat" bands. Twisted bilayer graphene has been found to show correlated phases as well as superconductivity related to such flat bands. In parallel, theory work has discovered that superconductivity and superfluidity is determined by the quantum geometry and topology of the band structure. These recent key developments are merging to a flourishing research topic: understanding the possible connection and ramifications of quantum geometry on the induced superconductivity and superfluidity in moir\'e multilayer and other flat band systems. This article presents an introduction to how quantum geometry governs superfluidity in platforms including, and beyond, graphene. We explain how a new type of topology discovered in TBG could affect superconductivity, pinpoint the geometric contribution in its Beretzinskii-Kosterlitz-Thouless (BKT) critical temperature, and mention moir\'e materials beyond TBG. Ultracold gases are introduced as a complementary platform for quantum geometric effects and a comparison is made to moir\'e materials. An outlook sketches the prospects of twisted multilayer systems in providing the route to room temperature superconductivity.
27 citations
TL;DR: In this article, a flexible coordinated power system expansion planning (CPSEP) framework is proposed to minimize the summation of the expansion planning, operation and reliability costs while taking the network model based on AC optimal power flow constraints, and the reliability and flexibility considerations into account.
26 citations
TL;DR: A novel optimization framework based on a hybrid information gap decision theory (IGDT) and robust optimization (RO) to handle the optimal self-scheduling of the EH within a medium-term horizon for large consumers is developed.
Gulf University for Science and Technology1, American Museum of Natural History2, Sewanee: The University of the South3, Queen's University Belfast4, Leibniz Institute of Marine Sciences5, Free University of Berlin6, Leibniz Association7, University of Southern Denmark8, Woods Hole Oceanographic Institution9, Université Paris-Saclay10, University of South Florida11, Aalto University12, University of Helsinki13
TL;DR: In this article, the authors collected and reviewed reported data on the economic impacts of invasive alien fishes using InvaCost, the most comprehensive global database of invasion costs, and assessed which socioeconomic sectors are most affected.
01 Jan 2022
TL;DR: In this article, a continuous-time algorithm that incorporates network topology changes in discrete jumps is proposed to remove chattering that arises because of the discretization of the underlying CT process, which converges to the SVM classifier over time-varying weight balanced directed graphs by using arguments from matrix perturbation theory.
Abstract: In this letter, we consider the binary classification problem via distributed Support Vector Machines (SVMs), where the idea is to train a network of agents, with limited share of data, to cooperatively learn the SVM classifier for the global database. Agents only share processed information regarding the classifier parameters and the gradient of the local loss functions instead of their raw data. In contrast to the existing work, we propose a continuous-time algorithm that incorporates network topology changes in discrete jumps. This hybrid nature allows us to remove chattering that arises because of the discretization of the underlying CT process. We show that the proposed algorithm converges to the SVM classifier over time-varying weight balanced directed graphs by using arguments from the matrix perturbation theory.
TL;DR: In this paper, a solar and geothermal energy assisted integrated energy system (IES) is proposed employing a gas turbine, absorption and ground heat pump cycles, and electric and thermal storage units.
TL;DR: In this paper , the authors investigate the vdW semiconductor/metal heterostructure built with 2D semiconducting InSe and metallic 1T-phase NbTe2, whose electron affinity χInSe and work function ΦNbTe 2 almost exactly align.
Abstract: van der Waals (vdW) heterostructures based on two-dimensional (2D) semiconducting materials have been extensively studied for functional applications, and most of the reported devices work with sole mechanism. The emerging metallic 2D materials provide us new options for building functional vdW heterostructures via rational band engineering design. Here, we investigate the vdW semiconductor/metal heterostructure built with 2D semiconducting InSe and metallic 1T-phase NbTe2, whose electron affinity χInSe and work function ΦNbTe2 almost exactly align. Electrical characterization verifies exceptional diode-like rectification ratio of >103 for the InSe/NbTe2 heterostructure device. Further photocurrent mappings reveal the switchable photoresponse mechanisms of this heterostructure or, in other words, the alternative roles that metallic NbTe2 plays. Specifically, this heterostructure device works in a photovoltaic manner under reverse bias, whereas it turns to phototransistor with InSe channel and NbTe2 electrode under high forward bias. The switchable photoresponse mechanisms originate from the band alignment at the interface, where the band bending could be readily adjusted by the bias voltage. In addition, a conceptual optoelectronic logic gate is proposed based on the exclusive working mechanisms. Finally, the photodetection performance of this heterostructure is represented by an ultrahigh responsivity of ∼84 A/W to 532 nm laser. Our results demonstrate the valuable application of 2D metals in functional devices, as well as the potential of implementing photovoltaic device and phototransistor with single vdW heterostructure.
01 Apr 2022
TL;DR: In this paper , the Bow Crossing Range (BCR) was investigated during routine operations of merchant ships, and the results indicated that BCR is strongly related to the type of navigational area (open sea or restricted waters) but not with the dimensions or speed of ships.
Abstract: Even in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is Bow Crossing Range (BCR). Therefore, this paper aims to investigate, what are typical, empirical values of BCR during routine operations of merchant ships, as well as investigate what factors impact this indicator and to what extent. To this end, a ten-year big dataset of real maritime traffic obtained from the Automatic Identification System (AIS) was used to provide statistical and spatiotemporal analyses. The results indicate that BCR is strongly related to the type of navigational area (open sea or restricted waters) but not with the dimensions or speed of ships. Among analyzed vessel types, passenger ships were noted as vessels that cross other bows at the closes ranges. Results of this study may be found interesting by fleet managers and developers of Maritime Autonomous Surface Ships (MASS). The former could utilize the results to provide revised operational guidelines for deck officers while the latter - propose an early-detection warning system based on empirical data for prospective MASS.
TL;DR: In this article , the structural and mechanical properties of nanoporous (NP) carbon materials by extensive atomistic machine-learning (ML) driven molecular dynamics (MD) simulations are studied.
Abstract: We study the structural and mechanical properties of nanoporous (NP) carbon materials by extensive atomistic machine-learning (ML) driven molecular dynamics (MD) simulations. To this end, we retrain a ML Gaussian approximation potential (GAP) for carbon by recalculating the a-C structural database of Deringer and Csányi adding van der Waals interactions. Our GAP enables a notable speedup and improves the accuracy of energy and force predictions. We use the GAP to thoroughly study the atomistic structure and pore-size distribution in computational NP carbon samples. These samples are generated by a melt-graphitization-quench MD procedure over a wide range of densities (from 0.5 to 1.7 g/cm3) with structures containing 131 072 atoms. Our results are in good agreement with experimental data for the available observables and provide a comprehensive account of structural (radial and angular distribution functions, motif and ring counts, X-ray diffraction patterns, pore characterization) and mechanical (elastic moduli and their evolution with density) properties. Our results show relatively narrow pore-size distributions, where the peak position and width of the distributions are dictated by the mass density of the materials. Our data allow further work on computational characterization of NP carbon materials, in particular for energy-storage applications, as well as suggest future experimental characterization of NP carbon-based materials.
TL;DR: In this article, a planar 5-coil mTMS transducer was designed and manufactured to allow controlling the maximum of the induced electric field (E-field) within a cortical region approximately 30mm in diameter.
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TL;DR: In this paper , the authors explore the dynamics of 30 rankings in natural, social, economic, and infrastructural systems, comprising millions of elements and timescales from minutes to centuries.
Abstract: Abstract Virtually anything can be and is ranked; people, institutions, countries, words, genes. Rankings reduce complex systems to ordered lists, reflecting the ability of their elements to perform relevant functions, and are being used from socioeconomic policy to knowledge extraction. A century of research has found regularities when temporal rank data is aggregated. Far less is known, however, about how rankings change in time. Here we explore the dynamics of 30 rankings in natural, social, economic, and infrastructural systems, comprising millions of elements and timescales from minutes to centuries. We find that the flux of new elements determines the stability of a ranking: for high flux only the top of the list is stable, otherwise top and bottom are equally stable. We show that two basic mechanisms — displacement and replacement of elements — capture empirical ranking dynamics. The model uncovers two regimes of behavior; fast and large rank changes, or slow diffusion. Our results indicate that the balance between robustness and adaptability in ranked systems might be governed by simple random processes irrespective of system details.
TL;DR: In this article , the authors demonstrate that a moiré pattern between a van der Waals superconductor and a monolayer ferromagnet creates a periodic potential modulation that enables the realization of a topological superconducting state that would not be accessible in the absence of the Moiré.
Abstract: The search for artificial topological superconductivity has been limited by the stringent conditions required for its emergence. As exemplified by the recent discoveries of various correlated electronic states in twisted van der Waals materials, moiré patterns can act as a powerful knob to create artificial electronic structures. Here, we demonstrate that a moiré pattern between a van der Waals superconductor and a monolayer ferromagnet creates a periodic potential modulation that enables the realization of a topological superconducting state that would not be accessible in the absence of the moiré. The magnetic moiré pattern gives rise to Yu-Shiba-Rusinov minibands and periodic modulation of the Majorana edge modes that we detect using low-temperature scanning tunneling microscopy (STM) and spectroscopy (STS). Moiré patterns and, more broadly, periodic potential modulations are powerful tools to overcome the conventional constraints for realizing and controlling topological superconductivity.
TL;DR: Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research as mentioned in this paper, and several methodological articles address these practices in detail.
Abstract: Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressi...
TL;DR: In this paper, the authors proposed a framework for assessing the accident susceptibility of a ship in operation involved in open-sea and coastal navigation, based on observable and relevant factors, known to affect the navigator's performance, and as a consequence accident probability.
TL;DR: In this paper , an effective strategy to enhance the OER activity of a perovskite electrocatalyst through improving the electrical conductivity introduced by the structural transition was proposed.
TL;DR: In this paper , a pyrolyzed black mass obtained from an industrial recycling plant was improved by adding a pre-treatment step consisting of mechanical attrition with and without kerosene addition.
Abstract: The comminution of spent lithium-ion batteries (LIBs) produces a powder containing the active cell components, commonly referred to as “black mass.” Recently, froth flotation has been proposed to treat the fine fraction of black mass (<100 µm) as a method to separate anodic graphite particles from cathodic lithium metal oxides (LMOs). So far, pyrolysis has been considered as an effective treatment to remove organic binders in the black mass in preparation for flotation separation. In this work, the flotation performance of a pyrolyzed black mass obtained from an industrial recycling plant was improved by adding a pre-treatment step consisting of mechanical attrition with and without kerosene addition. The LMO recovery in the underflow product increased from 70% to 85% and the graphite recovery remained similar, around 86% recovery in the overflow product. To understand the flotation behavior, the spent black mass from pyrolyzed LIBs was compared to a model black mass, comprising fully liberated LMOs and graphite particles. In addition, ultrafine hydrophilic particles were added to the flotation feed as an entrainment tracer, showing that the LMO recovery in overflow products is a combination of entrainment and true flotation mechanisms. This study highlights that adding kerosene during attrition enhances the emulsification of kerosene, simultaneously increasing its (partial) spread on the LMOs, graphite, and residual binder, with a subsequent reduction in selectivity.
TL;DR: In vitro permeability studies showed that Fc-functionalized NPs induced an increase in the amount of insulin that permeated across a Caco-2/HT29-MTX co-culture model, showing apparent permeability coefficients (Papp) of 2.37 × 10−6 cm/s, over the 1.66 × 10–10−6cm/s observed for their non- functionalized counterparts.
TL;DR: An extended LMI is proposed which, in conjunction with the rest of LMIs, results in a solution with a larger upper bound on delays than what would be feasible without it.
TL;DR: In this paper, an internal combustion engine for cooling, heating and power production is proposed by feeding the exhaust gas to an absorption heat pump to satisfy the heating and cooling demands and to an organic Rankine Cycle-unit to produce power and hot water.
TL;DR: In this article , the authors provide a meta-theoretical analysis of the B2B research domain by analyzing its major research communities and their paradigmatic ways of producing knowledge, highlighting the fragmented knowledge base, identifying neglected issues and unanswered questions, and suggest how to advance theory construction in the field.
TL;DR: It is shown that a phase-locked loop—which is normally grid following—can be designed so as to emulate a generic power controller, thus, becoming grid-forming.
Abstract: In grid-forming control, the swing equation of a synchronous machine is emulated by a power controller. Thereby, frequency droop, power-oscillation damping, and/or virtual inertia can be obtained. In this letter, it is shown that a phase-locked loop—which is normally grid following—can be designed so as to, in turn, emulate a generic power controller, thus, becoming grid-forming.
TL;DR: In this article, the ternary elements incorporated in the titanium oxide (TiO2) layer were used to improve the surface homogeneity, roughness, hydrophobicity, and growth rate.