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In this article we establish a bridge between dynamical systems, including topological and measurable dynamical systems as well as continuous skew product flows and nonautonomous dynamical systems; and coalgebras in categories having all finite products. We introduce a straightforward unifying definition of abstract dynamical system on finite product categories. Furthermore, we prove that such systems are in a unique correspondence with monadic algebras whose signature functor takes products with the time space. We substantiate that the categories of topological spaces, metrisable and uniformisable spaces have exponential objects w.r.t. locally compact Hausdorff, σ-compact or arbitrary time spaces as exponents, respectively. Exploiting the adjunction between taking products and exponential objects, we demonstrate a one-to-one correspondence between monadic algebras (given by dynamical systems) for the left-adjoint functor and comonadic coalgebras for the other. This, finally, provides a new, alternative perspective on dynamical systems.

Dans cette thèse, nous démontrons de nouvelles propriétés algébriques et homotpiques des opérades : probème du scindage des opérations et dualité de Koszul sur une algbre de Hopf. Dans une première partie, nous fournissons une construction opéradique qui donne un cadre général répondant au problème du scindage des opérations définissant des structures algébriques. Nous montrons que cette construction est équivalente au produit noir de Manin et qu'elle est reliée aux opérateurs de Rota-Baxter. Nous obtenons ainsi une méthode plus efficace pour calculer des produits noirs de Manin, illustrée par plusieurs exemples. Ceci nous permet de décrire une structure algébrique canonique sur l'espace des matrices carrées à coefficients dans une algèbre sur un certain type d'opérades. Dans une seconde partie, nous étendons la dualité de Koszul classique de opérades aux catégories de modules sur une algèbre de Hopf. Ceci nous permet d'obtenir une nouvelle version optimale du théorème de transfert homotopique. Dans ce cas, nous pouvons décrire la structure d'algèbre de Batalin-Vilkovisky, par exemple, transférée à travers une équivalence d'homotopie lorsqu'il y a compatibilité entre les données homotopique et algébrique.

Nous développons une version homotopique de la théorie de Morita classique en utilisant la notion de monade forte. C'était Anders Kock qui a montré qu'une monade T dans une catégorie monoidale E est forte si et seulement si la monade T est enrichie. Nous montrons que cette correspondance entre force et enrichissement se traduit par un 2-isomorphisme de 2-catégories. Sous certaines conditions sur la monade T, nous montrons que la catégorie homotopique des T-algèbre est équivalente au sens de Quillen à la catégorie homotopique des modules sur le monoïde d'endomorphismes de la T-algèbre T (I) librement engendré par l'unité I de E . Dans le cas particulier où E est la catégorie des Γ-espaces de Segal munie de la structure de modèle stable de Bousfi eld-Friedlander et T est la monade forte associée à une Γ-théorie bien pointée, nous retrouvons un théorème de Stefan Schwede, comme corollaire du théorème homotopique de Morita.

Security and privacy are among the growing concerns of a Vehicular Ad hoc Network (VANET) which requires a high degree of liability from its participants. In this dissertation, We address security, anonymity and privacy challenges of VANETs in the light of the IEEE standards for vehicular communications. VANET provides a variety of road-safety and other applications through wireless devices installed in vehicles and roadside infrastructure. A roadside infrastructure in VANET is generally public, and is prone to several different malicious attacks including node compromise, impersonation, and false message delivery attacks. Therefore, a user of a VANET must verify the integrity of a message that is delivered from a roadside infrastructure. On the other hand, a vehicle-originated message should be anonymous in order to ensure user-privacy in a VANET. However, a vehicle must not be able to take advantage of its anonymity for any misbehavior like sending false messages or malicious updates to other vehicles or a roadside infrastructure. We use proxy signature, identity-based signature, and elliptic curve cryptosystems to provide authentication for infrastructure generated messages, and anonymous authentication for vehicle originated messages. Authentication in a dense traffic condition is a challenge for a receiving entity as it incurs a processing delay at the receiving end. We address this issue with a dynamic approach that selectively verifies received messages based on a message's MAC-layer priority and a sender's information relevance. This approach makes a trade-off between priority and fairness in vehicular message authentication. We develop a network simulator to measure the impact of our authentication schemes over a WAVE protocol stack. Also, we investigate how some of the MAC-layer weaknesses may impair the security of a VANET. Our solutions are lightweight, bandwidth friendly and compatible to the current standards of vehicular communications.

Central to human intelligence, visual categorization is a skill that is both remarkably fast and accurate. Although there have been numerous studies in primates regarding how information flows in inferiortemporal (ITC) and prefrontal (PFC) cortices during online discrimination of visual categories, there has been little comparable research on the human cortex. To bridge this gap, this thesis explores how visual categories emerge in prefrontal cortex and the ventral stream, which is the human homologue of ITC. In particular, cortical spatiotemporal plasticity in visual category learning was investigated using behavioral experiments, magnetoencephalographic (MEG) imaging, and statistical machine learning methods. From a theoretical perspective, scientists from work on non-human primates have posited that PFC plays a primary role in the encoding of visual categories. Much of the extant research in the cognitive neuroscience literature, however, emphasizes the role of the ventral stream. Despite their apparent incompatibility, no study has evaluated these theories in the human cortex by examining the roles of the ventral stream and PFC in online discrimination and acquisition of visual categories. To address this question, I conducted two learning experiments using visually-similar categories as stimuli and recorded cortical response using MEG—a neuroimaging technique that offers a millisecond temporal resolution. Across both experiments, categorical information was found to be available during the period of cortical activity. Moreover, late in the learning process, this information is supplied increasingly in the ventral stream but less so in prefrontal cortex. These findings extend previous theories by suggesting that the ventral stream is crucial to long-term encoding of visual categories when categorical perception is proficient, but that PFC jointly encodes visual categories early on during learning. From a methodological perspective, MEG is limited as a technique because it can lead to false discoveries in a large number of spatiotemporal regions of interest (ROIs) and, typically, can only coarsely reconstruct the spatial locations of cortical responses. To address the first problem, I developed an excursion algorithm that identified ROIs contiguous in time and space. I then used a permutation test to measure the global statistical significance of the ROIs. To address the second problem, I developed a method that incorporates domainspecific and experimental knowledge in the modeling process. Utilizing faces as a model category, I used a predefined “face” network to constrain the estimation of cortical activities by applying differential shrinkages to regions within and outside this network. I proposed and implemented a trial-partitioning approach which uses trials in the midst of learning for model estimation. Importantly, this renders localizing trials more precise in both the initial and final phases of learning. In summary, this thesis makes two significant contributions. First, it methodologically improves the way we can characterize the spatiotemporal properties of the human cortex using MEG. Second, it provides a combined theory of visual category learning by incorporating the large time scales that encompass the course of the learning.

Security and privacy are among the growing concerns of a Vehicular Ad hoc Network (VANET) which requires a high degree of liability from its participants. In this dissertation, We address security, anonymity and privacy challenges of VANETs in the light of the IEEE standards for vehicular communications. VANET provides a variety of road-safety and other applications through wireless devices installed in vehicles and roadside infrastructure. A roadside infrastructure in VANET is generally public, and is prone to several different malicious attacks including node compromise, impersonation, and false message delivery attacks. Therefore, a user of a VANET must verify the integrity of a message that is delivered from a roadside infrastructure. On the other hand, a vehicle-originated message should be anonymous in order to ensure user-privacy in a VANET. However, a vehicle must not be able to take advantage of its anonymity for any misbehavior like sending false messages or malicious updates to other vehicles or a roadside infrastructure. We use proxy signature, identity-based signature, and elliptic curve cryptosystems to provide authentication for infrastructure generated messages, and anonymous authentication for vehicle originated messages. Authentication in a dense traffic condition is a challenge for a receiving entity as it incurs a processing delay at the receiving end. We address this issue with a dynamic approach that selectively verifies received messages based on a message's MAC-layer priority and a sender's information relevance. This approach makes a trade-off between priority and fairness in vehicular message authentication. We develop a network simulator to measure the impact of our authentication schemes over a WAVE protocol stack. Also, we investigate how some of the MAC-layer weaknesses may impair the security of a VANET. Our solutions are lightweight, bandwidth friendly and compatible to the current standards of vehicular communications.

The purpose of this study is to examine the role of imagination in Immanuel Kant&amp / #8217 / s Critique of Pure Reason by means of a detailed textual analysis and interpretation. In my systematic reading of the Kantian text, I analyse how the power of imagination comes to the foreground of Kant&amp / #8217 / s investigation into the transcendental conditions of knowledge. This is to explain the mediating function of imagination between the two distinct faculties of the subject / between sensibility and understanding. Imagination achieves its mediating function between sensibility and understanding through its activity of synthesis. By means of exploring the features of the activity of synthesis I attempt to display that imagination provides the ground of the unification of sensibility and understanding. The argument of this study resides in the claim that the power of imagination, through its transcendental synthesis, provides the ground of the possibility of all knowledge and experience. This is to announce imagination as the building block of Kant&amp / #8217 / s Copernican Revolution that grounds the objectivity of knowledge in its subjective conditions. Therefore, the goal of this study is to display imagination as a distinctive human capacity that provides the relation of our knowledge to the objects.

The present study investigated the differential effects of test-induced priming on false memories evoked by Converging Associates Procedure (DRM lists) and Category Associates Procedures (Category lists). The experimental settings involved the manipulation of test order of the critical items, in relation to the list items from their corresponding lists. The significance of the study comes from the fact that it directly compares the false memories elicited by Converging Associates Procedure and Category Associates Procedures within the same experimental settings. The results demonstrated that associative processes at test affected the proportion of false recollections elicited by DRM lists more than that elicited by Category lists. The results are discussed in relation to gist based theories of false memory and activation/monitoring account.

Sloutsky (2010; Kloos與Sloutsky, 2008) 操弄不同的類別結構亂度 (categorical entropy) 進行類別學習作業，藉此提出了雙系統理論，認為人們會啟動不同的系統，濃縮式系統 (compression-based system)或選擇式系統 (selection-based system)，以適應不同的類別結構組成之刺激材料。本研究回顧了Sloutsky的研究證據與過去類別學習領域的相關文獻，認為此雙系統理論可能只適用在向度數目較多的情境之下，因此設計了三個實驗，使用和Kloos與Sloutsky (2008) 相同的實驗派典，欲說明刺激材料的向度個數確實會影響到人們的類別學習行為。實驗一發現，Sloutsky所預測的類別結構與學習方式之交互作用只出現在向度個數較多的情境，向度個數少時則無此交互作用。實驗二得到與實驗一相同的結果，並排除了刺激材料本身特性（幾何圖形或類自然類別材料）此一混淆變項。實驗三採用特別設計的依變項，直接觀察受試者採用相似性(similarity)或規則(rule)的方式進行分類判斷，集群分析的結果顯示在向度數目少的情境時，不管何種類別結構受試者均傾向使用以規則為基礎的選擇式系統學習。因此，綜合以上發現，本研究認為Sloutsky的雙系統理論必須考慮到向度數目此一變項，才能更廣泛的應用於各種類別學習情境之中。 / The goal of this research is to point out that the dimensions of experimental materials can influence human category learning, which is neglected by traditional models of category learning. Three experiments in this research examined the effect of stimuli complexity by following the paradigms of Kloos and Sloutsky (2008). In Experiment 1, the prediction of Sloutsky’s theory (2010) on the interaction effect between category structures and learning conditions succeeds only at high complexity of materials, but fails in the low complexity condition. Experiment 2 was conducted by the same experimental setting as Experiment 1, but the natural-like stimuli were replaced by well-defined artificial geometrics. The result of Experiment 2 is the same as Experiment 1, suggesting that the complexity of materials plays a critical role in category learning no matter what kind of stimuli are used. Experiment 3 found that various materials complexity had distinct effects on human category representations. Namely, when experimental stimuli are relatively complex, people would use the corresponding category learning system to represent stimuli to learn dense categories or sparse ones. In contrast, when the stimuli are relatively simple, participants would represent the stimuli in a rule-based manner both in dense and sparse category structures.