Optimizing one-shot learning with binary synapses

A network of excitatory synapses trained with a conservative version of Hebbian learning is used as a model for recognizing the familiarity of thousands of once-seen stimuli from those never seen before. Such networks were initially proposed for modeling memory retrieval (selective delay activity). We show that the same framework allows the incorporation of both familiarity recognition and memory retrieval, and estimate the network's capacity. In the case of binary neurons, we extend the analysis of Amit and Fusi (1994) to obtain capacity limits based on computations of signal-to-noise ratio of the field difference between selective and non-selective neurons of learned signals. We show that with fast learning (potentiation probability approximately 1), the most recently learned patterns can be retrieved in working memory (selective delay activity). A much higher number of once-seen learned patterns elicit a realistic familiarity signal in the presence of an external field. With potentiation probability much less than 1 (slow learning), memory retrieval disappears, whereas familiarity recognition capacity is maintained at a similarly high level. This analysis is corroborated in simulations. For analog neurons, where such analysis is more difficult, we simplify the capacity analysis by studying the excess number of potentiated synapses above the steady-state distribution. In this framework, we derive the optimal constraint between potentiation and depression probabilities that maximizes the capacity.     

A methodology to incorporate product mix variations in cellular manufacturing

The identification of part families and machine groups that form the cells is a major step in the development of a cellular manufacturing system and, consequently, a large number of concepts, theories and algorithms have been proposed. One common assumption for most of these cell formation algorithms is that the product mix remains stable over a period of time. In today’s world, the market demand is being shaped by consumers resulting in a highly volatile market. This has given rise to a new class of products characterized by low volume and high variety. To incorporate product mix changes into an existing cellular manufacturing system many important issues have to be tackled. In this paper, a methodology to incorporate new parts and machines into an existing cellular manufacturing system has been presented. The objective is to fit the new parts and machines into an existing cellular manufacturing system thereby increasing machine utilization and reducing investment in new equipment.     

Investigations on mode-division multiplexed free-space optical transmission for inter-satellite communication link

Wireless Networks - Inter-satellite data transmission links are very crucial for providing global inter-connectivity. We report designing and investigations on high date rate inter-satellite...     

Modulated Triple‐Material Nano‐Heterostructures: Where Gold Influenced the Chemical Activity of Silver in Nanocrystals

For efficient charge separations, multimaterial hetero‐nanostructures are being extensively studied as photocatalysts. While materials with one heterojunction are widely established, the chemistry of formation of multijunction heterostructures is not explored. This needs a more sophisticated approach and modulations. To achieve these, a generic multistep seed mediated growth following controlled ion diffusion and ion exchange is reported which successfully leads to triple‐material hetero‐nanostructures with bimetallic‐binary alloy‐binary/ternary semiconductors arrangements. Ag₂S nanocrystals are used as primary seeds for obtaining AuAg‐AuAgS bimetallic‐binary alloyed metal–semiconductor heterostructures via partial reduction of Ag(I) using Au(III) ions. These are again explored as secondary seeds for obtaining a series of triple‐materials heterostructures, AuAg‐AuAgS‐CdS (or ZnS or AgInS₂), with introduction of different divalent and trivalent ions. Chemistry of each step of the gold ion–induced changes in the rate of diffusion and/or ion exchanges are investigated and the formation mechanism for these nearly monodisperse triple material heterostructures are proposed. Reactions without gold are also performed, and the change in the reaction chemistry and growth mechanism in presence of Au is also discussed.     

FSE–Ag complex NS: preparation and evaluation of antibacterial activity

Silver (Ag) complexes of drugs and their nanosystems have great potential as antibacterials. Recently, an Ag complex of furosemide (Ag–FSE) has shown to be a promising antimicrobial. However, poor solubility of Ag–FSE could hamper its introduction into clinics. Therefore, the authors developed a nanosuspension of Ag–FSE (Ag–FSE_NS) for its solubility and antibacterial activity enhancement. The aim of this study was to introduce a novel nanoantibiotic with enhanced antibacterial efficacy. Ag–FSE_NS was prepared by precipitation–ultrasonication technique. Size, polydispersity index (PI) and zeta potential (ZP) of prepared Ag–FSE_NS were measured by dynamic light scattering, whereas surface morphology was determined using scanning electron microscopy (SEM). In vitro antibacterial activity was evaluated against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa using broth microdilution method. Size, PI and ZP of optimised Ag–FSE_NS1 were 191.2 ± 19.34 nm, 0.465 ± 0.059 and −55.7 ± 8.18 mV, respectively. SEM revealed that Ag–FSE_NS1 particles were rod or needle‐like with smooth surfaces. Saturation solubility of Ag–FSE in NS increased eight‐fold than pure Ag–FSE. Ag–FSE_NS1 exhibited two‐fold and eight‐fold enhancements in activity against E. coli and S. aureus, respectively. The results obtained showed that developed Ag–FSE_NS1 holds a promise as a topical antibacterial.Inspec keywords: nanomedicine, nanofabrication, light scattering, surface morphology, silver, particle size, solubility, suspensions, scanning electron microscopy, electrokinetic effects, drugs, biomedical materials, antibacterial activity, microorganisms, nanoparticles, drug delivery systems, transmission electron microscopyOther keywords: saturation solubility, topical antibacterial, size 171.86 nm to 210.54 nm, voltage ‐47.52 mV to ‐63.88 mV, Ag, broth microdilution method, Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus, SEM, scanning electron microscopy, surface morphology, dynamic light scattering, particle size, polydispersity index, precipitation–ultrasonication technique, nanoantibiotic, nanosuspension, furosemide, nanosystems, drugs, Ag–FSE_NS preparation, in vitro antibacterial activity, pure Ag–FSE, Ag–FSE_NS1 particles, optimised Ag–FSE_NS1, zeta potential, enhanced antibacterial efficacy, antibacterials     

Roadmap for the next generation of dynamic function allocation theories and strategies

Dynamic function allocation theories have matured, but not to the extent that they can be implemented in actual environments. The authors identify a roadmap to help to get to that stage, after a brief review of relevant function allocation theories and the gaps in knowledge in adaptive allocation theories. Past research has focused on short‐term implementations of dynamic function allocation, which last for minutes (but never more than a few hours). Stable and enduring implementations of dynamic function allocation, lasting over days or possibly years, require a better and scientific understanding of the interaction among trigger mechanisms, adaptation strategies, and interruption strategies. The possibility of an unintentional consequence of this adaptive allocation, that the automated agent becomes confined to limited levels of automation, has to be ruled out after experimental evidence. © 2010 Wiley Periodicals, Inc.     

Reinterpretable Imager: Towards Variable Post‐Capture Space,Angle and Time Resolution in Photography

We describe a novel multiplexing approach to achieve tradeoffs in space, angle and time resolution in photography. We explore the problem of mapping useful subsets of time‐varying 4D lightfields in a single snapshot. Our design is based on using a dynamic mask in the aperture and a static mask close to the sensor. The key idea is to exploit scene‐specific redundancy along spatial, angular and temporal dimensions and to provide a programmable or variable resolution tradeoff among these dimensions. This allows a user to reinterpret the single captured photo as either a high spatial resolution image, a refocusable image stack or a video for different parts of the scene in post‐processing. A lightfield camera or a video camera forces a‐priori choice in space‐angle‐time resolution. We demonstrate a single prototype which provides flexible post‐capture abilities not possible using either a single‐shot lightfield camera or a multi‐frame video camera. We show several novel results including digital refocusing on objects moving in depth and capturing multiple facial expressions in a single photo.     

Polynomial based scheme (PBS) for establishing Authentic Associations in Wireless Mesh Networks

The varying degree of mobility of Mesh Clients has provided much more flexibility in Wireless Mesh Networks, and establishing an Authentic Association among entities is a non-trivial problem. In this paper, we introduce a Polynomial Based scheme which provides pair-wise connectivity, low communication, marginal storage overhead and high scalability while making on the fly Authentic Association feasible. The proposed scheme is also observed to be resilient against both traffic analysis and node capture attacks.     

Fairness of Transitions in Diagnosability of Discrete Event Systems

Failure diagnosability has been widely studied for discrete event system (DES) models because of modeling simplicity and computational efficiency due to abstraction. In the literature it is often held that for diagnosability, such models can be used not only for systems that fall naturally in the class of DES but also for the ones traditionally treated as continuous variable dynamic systems. A class of algorithms for failure diagnosability of DES models has been successfully developed for systems where fairness is not a part of the model. These algorithms are based on detecting cycles in the normal and the failure model that look identical. However, there exist systems with all transitions fair where the diagnosability condition that hinges upon this feature renders many failures non-diagnosable although they may actually be diagnosable by transitions out of a cycle. Hence, the diagnosability conditions based on cycle detection need to be modified to hold for many real-world systems where all transitions are fair. In this work, however, it is shown by means of an example that a system may have some transitions fair and some unfair. A new failure diagnosability mechanism is proposed for DES models with both fair and unfair transitions. Time complexity for deciding diagnosability of DES models with fair and unfair transitions is analyzed and compared with the time complexities of other DES diagnosability analysis methods reported in the literature.