2,555 research outputs found

    Alterungsverhalten von Li-Ionen-Zellen mit siliziumhaltigen Anoden - chemische und physikalische Untersuchungen

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    Silizium gewinnt als Anoden-Aktivmaterial für Lithium-Ionen Zellen kontinuierlich an Bedeutung. Vor allem als Teilsubstituent des standardmäßig verwendeten Anoden-Aktivmaterials Graphit wird Silizium bzw. Siliziumoxid bereits heute kommerziell eingesetzt. Der Zusammenhang von Silizium bzw. Siliziumanteil und dessen Einfluss auf das Alterungsverhalten der Zellen wurde für viele Einzelaspekte in der Fachliteratur ausführlich untersucht, allerdings bedingen und beeinflussen sich die einzelnen Alterungseffekte gegenseitig, sodass eine ganzheitliche Untersuchung von Partikel- über Elektroden- bis hin zur Zellebene notwendig ist. Durch ebendiese ganzheitliche Betrachtung konnten in der vorliegenden Arbeit zuvor unbeachtete Wirkzusammenhänge identifiziert und untersucht werden. Es wurde der Zusammenhang unterschiedlicher Alterungseinflüsse mit dem in den Zellen enthaltenen Silizium und der Lebensdauer ebendieser betrachtet. Dazu wurden unterschiedlichste elektrochemische, chemisch-physikalische und mechanische Untersuchungsmethoden an unterschiedlichen Zellformaten und Zelltypen durchgeführt. Zunächst wurde der Einfluss des Siliziumgehalts auf Lade- und Entladekurven, irreversiblen Kapazitätsverlust, Innenwiderstand, Dickenänderung und Alterungsverhalten untersucht. Die betrachteten Zellen wurden mit gleichen Zellparametern (d. h. Aktivmaterialien, Elektrolyten, Separatoren, Flächenkapazitäten, Binderanteilen, Porositäten, etc.) hergestellt. Einzig der SiOx-Anteil in den Anoden wurde variiert. Zunächst fanden systematische Messungen der o. g. Zellparameter an Laborzellen im Halb- und Vollzellformat statt. Mit Hilfe ausführlicher differentieller Spannungsanalysen an Anoden und Kathoden konnte so der Einfluss auf die jeweiligen Aktivmaterialien und deren Alterungsverhalten untersucht werden. Auch unterschiedliche Spannungsfenster und der Einfluss des zur Reaktion verfügbaren Lithiums wurden betrachtet. Im weiteren Verlauf wurden aus den zuvor ausführlich charakterisierten Elektroden mehrlagige Laborpouchzellen hergestellt und unter unterschiedlichen äußeren Drücken über einen ausgedehnten Zeitraum (d. h. viele Vollzyklen) untersucht. Im Verlauf der Langzeitzyklisierung wurden regelmäßig differentielle Spannungsanalysen und Innenwiderstandsbestimmungen durchgeführt, um so den detaillierten Alterungsverlauf abbilden zu können. Am Ende der Langzeituntersuchungen wurden die Zellen geöffnet und ausführliche Post-mortem-Analysen mit Hilfe unterschiedlichster chemisch-physikalischer Analysemethoden durchgeführt. Zuletzt wurden die in den vorherigen Kapiteln erarbeiteten Erkenntnisse auf kommerziell erhältliche, siliziumhaltige Rundzellen angewendet. Nach ausführlicher Charakterisierung der verwendeten Zellen und ihrer Bestandteile, wurden diese in unterschiedlichen Spannungsfenstern gezykelt und untersucht und dabei der Einfluss auf die Zellalterung, d. h. den Kapazitätsverlust und Innenwiderstandsanstieg, aber vor allem auch das Zelldickenwachstum, die Wickelverformung und Materialalterung genau analysiert. So konnten direkte Zusammenhänge der Alterungseinflüsse, hervorgerufen u. a. durch das enthaltene Silizium, gefunden werden, die zu einem Kapazitätsverlust und schließlich zum Zelltod führen

    Authentication enhancement in command and control networks: (a study in Vehicular Ad-Hoc Networks)

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    Intelligent transportation systems contribute to improved traffic safety by facilitating real time communication between vehicles. By using wireless channels for communication, vehicular networks are susceptible to a wide range of attacks, such as impersonation, modification, and replay. In this context, securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything (V2X) communication, constitutes a technological challenge that needs to be addressed. Hence, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. In this challenging scenario, physical (PHY)-layer authentication has gained popularity, which involves leveraging the inherent characteristics of wireless channels and the hardware imperfections to discriminate between wireless devices. However, PHY-layerbased authentication cannot be an alternative to crypto-based methods as the initial legitimacy detection must be conducted using cryptographic methods to extract the communicating terminal secret features. Nevertheless, it can be a promising complementary solution for the reauthentication problem in VANETs, introducing what is known as “cross-layer authentication.” This thesis focuses on designing efficient cross-layer authentication schemes for VANETs, reducing the communication and computation overheads associated with transmitting and verifying a crypto-based signature for each transmission. The following provides an overview of the proposed methodologies employed in various contributions presented in this thesis. 1. The first cross-layer authentication scheme: A four-step process represents this approach: initial crypto-based authentication, shared key extraction, re-authentication via a PHY challenge-response algorithm, and adaptive adjustments based on channel conditions. Simulation results validate its efficacy, especially in low signal-to-noise ratio (SNR) scenarios while proving its resilience against active and passive attacks. 2. The second cross-layer authentication scheme: Leveraging the spatially and temporally correlated wireless channel features, this scheme extracts high entropy shared keys that can be used to create dynamic PHY-layer signatures for authentication. A 3-Dimensional (3D) scattering Doppler emulator is designed to investigate the scheme’s performance at different speeds of a moving vehicle and SNRs. Theoretical and hardware implementation analyses prove the scheme’s capability to support high detection probability for an acceptable false alarm value ≤ 0.1 at SNR ≥ 0 dB and speed ≤ 45 m/s. 3. The third proposal: Reconfigurable intelligent surfaces (RIS) integration for improved authentication: Focusing on enhancing PHY-layer re-authentication, this proposal explores integrating RIS technology to improve SNR directed at designated vehicles. Theoretical analysis and practical implementation of the proposed scheme are conducted using a 1-bit RIS, consisting of 64 × 64 reflective units. Experimental results show a significant improvement in the Pd, increasing from 0.82 to 0.96 at SNR = − 6 dB for multicarrier communications. 4. The fourth proposal: RIS-enhanced vehicular communication security: Tailored for challenging SNR in non-line-of-sight (NLoS) scenarios, this proposal optimises key extraction and defends against denial-of-service (DoS) attacks through selective signal strengthening. Hardware implementation studies prove its effectiveness, showcasing improved key extraction performance and resilience against potential threats. 5. The fifth cross-layer authentication scheme: Integrating PKI-based initial legitimacy detection and blockchain-based reconciliation techniques, this scheme ensures secure data exchange. Rigorous security analyses and performance evaluations using network simulators and computation metrics showcase its effectiveness, ensuring its resistance against common attacks and time efficiency in message verification. 6. The final proposal: Group key distribution: Employing smart contract-based blockchain technology alongside PKI-based authentication, this proposal distributes group session keys securely. Its lightweight symmetric key cryptography-based method maintains privacy in VANETs, validated via Ethereum’s main network (MainNet) and comprehensive computation and communication evaluations. The analysis shows that the proposed methods yield a noteworthy reduction, approximately ranging from 70% to 99%, in both computation and communication overheads, as compared to the conventional approaches. This reduction pertains to the verification and transmission of 1000 messages in total

    Development of variable and robust brain wiring patterns in the fly visual system

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    Precise generation of synapse-specific neuronal connections are crucial for establishing a robust and functional brain. Neuronal wiring patterns emerge from proper spatiotemporal regulation of axon branching and synapse formation during development. Several neuropsychiatric and neurodevelopmental disorders exhibit defects in neuronal wiring owing to synapse loss and/or dys-regulated axon branching. Despite decades of research, how the two inter-dependent cellular processes: axon branching and synaptogenesis are coupled locally in the presynaptic arborizations is still unclear. In my doctoral work, I investigated the possible role of EGF receptor (EGFR) activity in coregulating axon branching and synapse formation in a spatiotemporally restricted fashion, locally in the medulla innervating Dorsal Cluster Neuron (M- DCN)/LC14 axon terminals. In this work I have explored how genetically encoded EGFR randomly recycles in the axon branch terminals, thus creating an asymmetric, non-deterministic distribution pattern. Asymmetric EGFR activity in the branches acts as a permissive signal for axon branch pruning. I observed that the M-DCN branches which stochastically becomes EGFR ‘+’ during development are synaptogenic, which means they can recruit synaptic machineries like Syd1 and Bruchpilot (Brp). My work showed that EGFR activity has a dual role in establishing proper M-DCN wiring; first in regulating primary branch consolidation possibly via actin regulation prior to synaptogenesis. Later in maintaining/protecting the levels of late Active Zone (AZ) protein Brp in the presynaptic branches by suppressing basal autophagy level during synaptogenesis. When M-DCNs lack optimal EGFR activity, the basal autophagy level increases resulting in loss of Brp marked synapses which is causal to increased exploratory branches and post-synaptic target loss. Lack of EGFR activity affects the M-DCN wiring pattern that makes adult flies more active and behave like obsessive compulsive in object fixation assay. In the second part of my doctoral work, I have asked how non-genetic factors like developmental temperature affects adult brain wiring. To test that, I increased or decreased rearing temperature which is known to inversely affect pupal developmental rate. We asked if all the noisy cellular processes of neuronal assembly: filopodial dynamics, axon branching, synapse formation and postsynaptic connections scale up or down accordingly. I observed that indeed all the cellular processes slow down at lower developmental temperature and vice versa, which changes the DCN wiring pattern accordingly. Interestingly, behavior of flies adapts to their developmental temperature, performing best at the temperature they have been raised at. This shows that optimal brain function is an adaptation of robust brain wiring patterns which are specified by noisy developmental processes. In conclusion, my doctoral work helps us better understand the developmental regulation of axon branching and synapse formation for establishing precise brain wiring pattern. We need all the cell intrinsic developmental processes to be highly regulated in space and time. It is infact a combinatorial effect of such stochastic processes and external factors that contribute to the final outcome, a functional and robust adult brain

    Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR

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    This paper advances the fine-grained sketch-based image retrieval (FG-SBIR) literature by putting forward a strong baseline that overshoots prior state-of-the-arts by ~11%. This is not via complicated design though, but by addressing two critical issues facing the community (i) the gold standard triplet loss does not enforce holistic latent space geometry, and (ii) there are never enough sketches to train a high accuracy model. For the former, we propose a simple modification to the standard triplet loss, that explicitly enforces separation amongst photos/sketch instances. For the latter, we put forward a novel knowledge distillation module can leverage photo data for model training. Both modules are then plugged into a novel plug-n-playable training paradigm that allows for more stable training. More specifically, for (i) we employ an intra-modal triplet loss amongst sketches to bring sketches of the same instance closer from others, and one more amongst photos to push away different photo instances while bringing closer a structurally augmented version of the same photo (offering a gain of ~4-6%). To tackle (ii), we first pre-train a teacher on the large set of unlabelled photos over the aforementioned intra-modal photo triplet loss. Then we distill the contextual similarity present amongst the instances in the teacher's embedding space to that in the student's embedding space, by matching the distribution over inter-feature distances of respective samples in both embedding spaces (delivering a further gain of ~4-5%). Apart from outperforming prior arts significantly, our model also yields satisfactory results on generalising to new classes. Project page: https://aneeshan95.github.io/Sketch_PVT/Comment: Accepted in CVPR 2023. Project page available at https://aneeshan95.github.io/Sketch_PVT

    Use of the first-acquired language modulates pupil size in the processing of island constraint violations

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    IntroductionTraditional studies of the population called “heritage speakers” (HS) have treated this group as distinct from other bilingual populations, e.g., simultaneous or late bilinguals (LB), focusing on group differences in the competencies of the first-acquired language or “heritage language”. While several explanations have been proposed for such differences (e.g., incomplete acquisition, attrition, differential processing mechanisms), few have taken into consideration the individual variation that must occur, due to the fluctuation of factors such as exposure and use that characterize all bilinguals. In addition, few studies have used implicit measures, e.g., psychophysiological methods (ERPs; Eye-tracking), that can circumvent confounding variables such as resorting to conscious metalinguistic knowledge.MethodologyThis study uses pupillometry, a method that has only recently been used in psycholinguistic studies of bilingualism, to investigate pupillary responses to three syntactic island constructions in two groups of Spanish/English bilinguals: heritage speakers and late bilinguals. Data were analyzed using generalized additive mixed effects models (GAMMs) and two models were created and compared to one another: one with group (LB/HS) and the other with groups collapsed and current and historical use of Spanish as continuous variables.ResultsResults show that group-based models generally yield conflicting results while models collapsing groups and having usage as a predictor yield consistent ones. In particular, current use predicts sensitivity to L1 ungrammaticality across both HS and LB populations. We conclude that individual variation, as measured by use, is a critical factor tha must be taken into account in the description of the language competencies and processing of heritage and late bilinguals alike

    Multi-Level Data-Driven Battery Management: From Internal Sensing to Big Data Utilization

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    Battery management system (BMS) is essential for the safety and longevity of lithium-ion battery (LIB) utilization. With the rapid development of new sensing techniques, artificial intelligence and the availability of huge amounts of battery operational data, data-driven battery management has attracted ever-widening attention as a promising solution. This review article overviews the recent progress and future trend of data-driven battery management from a multi-level perspective. The widely-explored data-driven methods relying on routine measurements of current, voltage, and surface temperature are reviewed first. Within a deeper understanding and at the microscopic level, emerging management strategies with multi-dimensional battery data assisted by new sensing techniques have been reviewed. Enabled by the fast growth of big data technologies and platforms, the efficient use of battery big data for enhanced battery management is further overviewed. This belongs to the upper and the macroscopic level of the data-driven BMS framework. With this endeavor, we aim to motivate new insights into the future development of next-generation data-driven battery management

    The Appropriation of Value from Knowledge: Three Essays on Technological Discontinuities, Market Entry, and Patent Strategy

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    Knowledge accumulation and protection are critical considerations of the firm. How does the capability to appropriate value from knowledge affect firm strategies in the industries? To answer this question, I develop a new theory and evidence to argue that appropriate value from knowledge is a central consideration in firms’ capabilities and decisions to deal with technological changes and intellectual property issues. In particular, I examine the relatedness of products and markets, the strategic uses of patents, and how firms can successfully adapt to concerns regarding technological changes and intellectual property leakage. Throughout my three dissertation chapters, I find evidence that the capability to appropriate value from knowledge can affect how firms behave in consistent and essential ways. These findings provide important implications for knowledge-based views of the firm and strategy-based recommendations in terms of the management of knowledge assets

    AI: Limits and Prospects of Artificial Intelligence

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    The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence
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