80 research outputs found
Learning Representations for New Sound Classes With Continual Self-Supervised Learning
In this paper, we work on a sound recognition system that continually
incorporates new sound classes. Our main goal is to develop a framework where
the model can be updated without relying on labeled data. For this purpose, we
propose adopting representation learning, where an encoder is trained using
unlabeled data. This learning framework enables the study and implementation of
a practically relevant use case where only a small amount of the labels is
available in a continual learning context. We also make the empirical
observation that a similarity-based representation learning method within this
framework is robust to forgetting even if no explicit mechanism against
forgetting is employed. We show that this approach obtains similar performance
compared to several distillation-based continual learning methods when employed
on self-supervised representation learning methods.Comment: Accepted to IEEE Signal Processing Letter
Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks
With the growing popularity of electric vehicles (EVs), maintaining power
grid stability has become a significant challenge. To address this issue, EV
charging control strategies have been developed to manage the switch between
vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes for EVs. In this context,
multi-agent deep reinforcement learning (MADRL) has proven its effectiveness in
EV charging control. However, existing MADRL-based approaches fail to consider
the natural power flow of EV charging/discharging in the distribution network
and ignore driver privacy. To deal with these problems, this paper proposes a
novel approach that combines multi-EV charging/discharging with a radial
distribution network (RDN) operating under optimal power flow (OPF) to
distribute power flow in real time. A mathematical model is developed to
describe the RDN load. The EV charging control problem is formulated as a
Markov Decision Process (MDP) to find an optimal charging control strategy that
balances V2G profits, RDN load, and driver anxiety. To effectively learn the
optimal EV charging control strategy, a federated deep reinforcement learning
algorithm named FedSAC is further proposed. Comprehensive simulation results
demonstrate the effectiveness and superiority of our proposed algorithm in
terms of the diversity of the charging control strategy, the power fluctuations
on RDN, the convergence efficiency, and the generalization ability
High-performance infrared photodetectors based on InAs/InAsSb/AlAsSb superlattice for 3.5 µm cutoff wavelength spectra
High-performance infrared p-i-n photodetectors based on InAs/InAsSb/AlAsSb superlattices on GaSb substrate have been demonstrated at 300K. These photodetectors exhibit 50% and 100% cut-off wavelength of ∼3.2 µm and ∼3.5 µm, respectively. Under -130 mV bias voltage, the device exhibits a peak responsivity of 0.56 A/W, corresponding to a quantum efficiency (QE) of 28%. The dark current density at 0 mV and -130 mV bias voltage are 8.17 × 10−2 A/cm2 and 5.02 × 10−1 A/cm2, respectively. The device exhibits a saturated dark current shot noise limited specific detectivity (D*) of 3.43 × 109 cm·Hz1/2/W (at a peak responsivity of 2.5 µm) under -130 mV of applied bias
Uber die Welch-Fraenkelschen Bazillen und ihre Verwandten im Darmkanal
Der Welch-Fraenkelsche Bazillus, der sich als ein Bodenbakterium weit im Boden verbreitet, ist obligater Anaerobier, und bekannt als Erreger des Gasoedems, welches eine chirurgisch und insbesonders kriegschirurgisch wichtige Wundinfektionskrankheit ist. Die Tatsache, dass dieses Stabchen nicht nur aus dem Boden, sondern auch aus menschlichem Darm gezuchtet wird, hat viele Autoren schon bisweilen beschaftigt. Dieser Bazillus ist Gram-positiv, gross und kraftig, abgerundet, unbeweglich und sporuliert nicht im gewohnlichen Nahrboden. Die Milch wurde sturmisch mit Gasbildung vergoren. Schon nach 20 Stunden schwamm das Kasein deutlich geschieden in truber, immer klarer werdender Molke. Die Kaseingerinnsel wurden ferner nicht wieder durch Peptonisierung gelost, noch kam es nach dem leicht sauerlich bleibenden Geruch zu Eiweissfaulniss. Die oben beschriebene Eigenschaft, die sog. Sturmische Gerinnung , ist charakteristisches Merkmal zur Diagnose-stellung des Welch-Fraenkelschen Bazillus. Der Verfasser hat aus 172 Faeces der Menschen 244 Stamme der Welch-Fraenkelschen Bazillen und 39 ahnliche Stamme, die von erstem Bazillus deutlich voneinander in Eigenstumlichkeit abweicht gezuchtet; d. h. dem Letzteren fehlt die sturmische Gerinnung. Diesen Bazillus nennt der Verfasser einen Verwandten der Welch-Fraenkelschen Bazillen , und vergleicht dieses Stabchen morphologisch und biologisch mit den Welch-Fraenkelschen Bazillen, welche er aus menschlichen Faeces und klassischem Gasoedem isoliert hat. Morphologie: Die Verwandten sind ebenso mit abgerundetem Ende 0.8-1.0μ breit, 4.0-1.0μ, nicht haufig 15μ in der Lange, zuweilen leicht gekrummt, und werden zarter als Welch-Fraenkelche Bazillen beobachtet. Sporen und Kapseln: Nicht nur in gewohnlichen Nahrboden, sondern auch in den alkalischen-, natriumphosphathaltigen Nahrsubstraten und im Hirnbrei nahm der Verfasser keine Sporen oder Kapseln wahr. Aber nur bei aus Gasoedem gezuchtetem Stamm beobachtete er beide im spezifischen antiserumhaltigen Nahrboden. Kolonientypen: Auf d
Ultimate Monolithic-3D Integration With 2D Materials: Rationale, Prospects, and Challenges
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Ultimate Monolithic-3D Integration With 2D Materials: Rationale, Prospects, and Challenges
Microstructure, texture evolution and mechanical properties of a large-scale multidirectionally forged Mg-Gd-Y-Zn-Zr-Ag alloy
A large-scale Mg-6.2Gd-3.7Y-0.9Zn-0.3Zr-0.3Ag (wt.%) magnesium component with the dimension of 480 × 250 × 160 mm3 was fabricated via direct-chill (DC) casting, homogenization and multidirectional forging (MDF). The evolution of the microstructure, texture and uniaxial tensile properties during MDF process were comprehensively investigated. 2.5%, 5.6% and 10.9% anisotropy were obtained in the MDF alloy subjected to 9, 18 and 27 passes, respectively. The MDF alloy subjected to 27 passes tensile along FD exhibits superior comprehensive mechanical properties, with a yield strength (TYS) of 292 MPa, ultimate tensile strength (UTS) of 384 MPa and elongation of 9.0%. Interdendritic Mg5(Gd, Y, Zn) phases dissolved after homogenization, with the precipitation of intragranular lamellar 14H long period stacking ordered (LPSO) phases from α-Mg matrix. During the MDF process, intragranular lamellar LPSO phases were initially kinked, suppressing dynamic recrystallization (DRX) behavior in the first 9 passes, and subsequently partially dissolved. Dynamic precipitation of Mg5(Gd, Y) and ultrafine LPSO phase were also induced by MDF. With the cumulative deformation of MDF, increased volume fraction of Mg5(Gd, Y) phases, enhanced texture and refined α-Mg grains are likely responsible for the improved mechanical properties via MDF. We also found that prismatic slip is activated in the deformed grains with the c-axis around FD and multiple slip is activated in the other deformed grains during the MDF process. This paper provides a superior MDF processing route to manufacture high-performance large-scale Mg-Gd-Y-Zn-Zr-Ag components for industrial production
Augmenting 3D Ultrasound Strain Elastography by combining Bayesian inference with local Polynomial fitting in Region-growing-based Motion Tracking
Accurately tracking large tissue motion over a sequence of ultrasound images is critically important to several clinical applications including, but not limited to, elastography, flow imaging, and ultrasound-guided motion compensation. However, tracking in vivo large tissue deformation in 3D is a challenging problem and requires further developments. In this study, we explore a novel tracking strategy that combines Bayesian inference with local polynomial fitting. Since this strategy is incorporated into a region-growing block-matching motion tracking framework we call this strategy a Bayesian region-growing motion tracking with local polynomial fitting (BRGMT-LPF) algorithm. More specifically, unlike a conventional block-matching algorithm, we use a maximum posterior probability density function to determine the “correct” three-dimensional displacement vector. The proposed BRGMT-LPF algorithm was evaluated using a tissue-mimicking phantom and ultrasound data acquired from a pathologically-confirmed human breast tumor. The in vivo ultrasound data was acquired using a 3D whole breast ultrasound scanner, while the tissue-mimicking phantom was acquired using an experimental CMUT ultrasound transducer. To demonstrate the effectiveness of combining Bayesian inference with local Polynomial fitting, the proposed method was compared to the original region-growing motion tracking algorithm (RGMT), region-growing with Bayesian interference only (BRGMT), and region-growing with local polynomial fitting (RGMT-LPF). Our preliminary data demonstrate that the proposed BRGMT-LPF algorithm can improve the accuracy of motion tracking
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Ultimate Monolithic-3D Integration With 2D Materials: Rationale, Prospects, and Challenges
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