10,000 publications from this institution
The system and network architecture for stationary sensornets is largely solved today with many commercial solutions now available and standardization efforts underway at the IEEE, IETF, ISA, and within many industry groups. However, the existing techniques for reliable, low-power communications in stationary sensornets fail on both counts when confronted with mobility. In this dissertation, we argue that awareness of real or potential mobility enables a solution that handles the mobile case well, and supports stationary networks as a special case. This dissertation addresses micropower mobiscopes, a nascent class of mobile sensornets – small, embedded, and battery-powered systems – that experience unpredictable but structured mobility and are severely energy-constrained. We show how awareness of mobility can simplify their communication challenges, enable low-power operation, and enhance the reliability of data delivery. We introduce the MOV metric, a measure of mobility, and present techniques to gather it on a near nano-power budget. We also present iCount, a regulator-integrated energy meter design that allows nodes to introspect their own energy usage, and adapt their behavior to the actual energy availability and consumption. Integrating the pieces, we present three concrete hardware platforms that support our mobile sensing architecture. We develop a novel asynchronous neighbor discovery algorithm called Disco that allows nodes to operate their radios at very low duty cycles and yet still discover neighbors without any external synchronization information. Recognizing the necessity of beaconing in mobile networks, and the need for mobile-stationary node interactions, we design a link layer synchronization primitive, Backcast, and a receiver-initiated link layer, HotMac, that are suitable for mobile sensing, but also work for stationary networks across a range of conventional data collection workloads and a broad range of duty cycles. We evaluate our thesis with three mobile sensing applications that embody our proposed architecture. The three applications – AutoWitness, SleepTrack, and CommonSense – are representative of asset tracking, health and fitness, and participatory urban sensing, and they each stress different aspects of the architecture, including motion detection, neighbor discovery, communications, interaction patterns, energy management, and data transport. These design points illustrate that our architecture is general enough to enable a range of applications but specific enough to support them well.
Ultra-thin dendrimer films are effective resists for high-resolution lithography using a scanning probe. The authors describe dendritic monolayer formation via covalent attachment to a silicon wafer surface and the field-enhanced oxidation of the dendrimer monolayers using scanning probe lithography to create features with dimensions less than 60 nm. Poly-(benzyl ether) dendrimers, terminated with either benzyl or tert-butyldiphenylsilyl ether groups, were used because of their relative ease of preparation and derivatization.
An autoassociative memory is a device which accepts an input pattern and generates an output as the stored pattern which is most closely associated with the input. In this paper, we propose an autoassociative memory cellular neural network, which consists of one-dimensional cells with spatial derivative inputs, thresholds and memories. Computer simulations show that it exhibits good performance in face recognition: The network can retrieve the whole from a part of a face image, and can reproduce a clear version of a face image from a noisy one. For human memory, research on "visual illusions" and on "brain damaged visual perception", such as the Thatcher illusion, the hemispatial neglect syndrome, the split-brain, and the hemispheric differences in recognition of faces, has fundamental importance. We simulate them in this paper using an autoassociative memory cellular neural network. Furthermore, we generate many composite face images with spurious patterns by applying genetic algorithms to this network. We also simulate a morphing between two faces using autoassociative memory.
Thermolysis of the structurally characterized hafnium phosphide complex, CpCp*HfMe(PHPh) (2), resulted in formation of the triphosphanato compound CpCp*Hf(P3Ph3) (3). Trapping reactions with PMe3 gave evidence for an intermediate phosphinidene complex, which was corroborated by synthesis of the related 2,6-dimesitylphenyl derivative CpCp*(Me3P)HfP(dmp) (8). The hafnocene phenylphosphinidene intermediate can also be intercepted by a [2 + 2]-cycloaddition reaction with 2-butyne. However, reaction of 2 with either xylyl isocyanide or benzophenone gives insertion into the hafnium methyl bond. Under thermolytic conditions, metal dichloro complexes can efficiently intercept a phosphinidene fragment from 2 in a unique phosphinidene ligand exchange reaction. Thus, complex 2 reacts with (dippe)PtCl2 (11, dippe = 1,2-bis(diisopropylphosphino)ethane) and [N(Np)Ar]3TaCl2 (14, Np = neopentyl, Ar = 3,5-Me2C6H3) to afford phosphinidene complexes [(dippe)Pt(μ-PPh)]2 (12) and [N(Np)Ar]3TaPPh (15), respectively, in good isolated yields. A derivative of 12, [(dippe)Pt]2(μ-PPh) (13), was structurally characterized.
