This paper proposes to use spatio-temporal patterns that the concentration of propagating information molecules form in the molecular communication environment and develops a new modulation technique for molecular communication between bio-nanomachines. In molecular communication considered in this paper, information molecules transmitted from a group of sender bio- nanomachines propagate in the environment, chemically react with the molecules in the environment, change their concentration, and form an oscillating and propagating pattern. The rates at which sender bio-nanomachines transmit information molecules determines the frequency, amplitude and phase characteristics of the pattern, and the sender bio-nanomachines modify the transmission rates in order to modulate information on to frequency, amplitude and phase characteristics of the pattern. A group of receiver bio-nanomachines detects these characteristics to collectively decode information. This paper develops a new model of molecular communication through pattern formation. Using the model developed in this paper and numerical examples, this paper demonstrates the advantages of the proposed modulation technique, namely, higher information capacity and longer communication distances.

Systems of distributed nanomachines are an anticipated paradigm for future interaction with biological systems. Future applications for systems of distributed nanomachines require nanomachines to coordinate among themselves as well as interact with larger-scale systems such as medical or environment devices. One potential technique to communicate with distributed nanomachines is through molecular communication. For example, a nanomachine transmits pulses of a type of molecule to represent bits of information and a device (i.e. may be either a nano-scale or larger-scale device) decodes information from the concentration characteristics of the type of molecule. In this paper, we consider multiple transmitters multiplexing bits of information to a micro-scale receiver using the same type of molecule. Concentration of the type of molecule depends on the bits transmitted and the distances to the transmitters. We model the concentration detected by the receiver to measure the expected number of bits per transmission interval.

This paper investigates, through computer simulations, statistical behavior of molecular motors transporting cargos on a network of protein filaments in an engineered environment. This paper also examines how molecular motors' statistical behavior is applied to building. a molecular communication system. A molecular motor, such as kinesin, is a protein complex. It exists in eukaryotic cells and functions as a nano-scale autonomous nanomachine that carries nano-scale to micro-scale signaling molecules on a network of protein filaments (i.e., cytoskeletal network) in eukaryotic cells. At an intersection of protein filaments on a cytoskeletal network, a molecular motor shows stochastic movement and may stay on the current protein filament or may switch onto an intersecting protein filament, resulting in stochastic delivery of signaling molecules from the nucleus to organelles over a cytoskeletal network. Molecular communication is an engineered system to transmit information by modulating information on molecules and by transporting modulated molecules from senders to receivers. One of promising approaches to building a molecular communication system is to use molecular motors to transport information-modulated molecules on an engineered protein filament network connecting senders and receivers. In order to examine the feasibility of this approach, this paper simulated statistical behavior of molecular motors carrying cargo molecules through multiple protein filament intersections on a protein filament network. Simulations model stochastic movement of a molecular motor at a single intersection of protein filaments using the measurement data obtained through in vitro experiments (using kinesins and microtubules) conducted by the authors of this paper and evaluates the stochastic delivery of molecules from the senders to the receivers over multiple intersections of protein filaments arranged in an array topology. Simulation results show that molecular motors stochastically deliver cargo molecules to a specific receiver (or to a specific set of receivers) with a given probability over an array of protein filament intersections.

The ability to design systems of nanomachines may lead to new techniques for future applications. Systems of nanomachines may provide novel mechanisms to interact with cells for medicine, to detect and process waste molecules for environmental applications, or to self-organize nanomachines to manufacture objects. A nanomachine may require information about other nanomachines, such as distance to the other nanomachines, to achieve some applications. Molecular communication is one suitable communication technique for communicating among autonomous nanomachines which are limited in size and capability. In this paper, we consider how a nanomachine can estimate distance information from signal characteristics of a molecular communication. One transceiver nanomachine, T, requests another transceiver nanomachine, R, to transmit a feedback signal. T then estimates distance between T and R from the signal. Several design choices are considered for distance measurement. For transmission, options include releasing a spike of molecules or gradually releasing molecules. For propagation, options include whether or not the environment contains repeaters between T and R. For receiving, options include detecting a threshold concentration of molecules by sampling at a time instant or by capturing molecules over time. The options are compared in terms of range, delay, and accuracy through simulation.

The United States Air Force Research Laboratory (AFRL) has been exploring the implementation of neurophysiological and psychological constructs to develop a hyper-parallel computing platform. This approach is termed neuromorphic computing. As part of that effort, the primary visual cortex (V1) has been modeled in high performance computing facility. The current columnar V1 model is being expanded to include binocular disparity and motion perception. Additionally, V2 thick and pale stripes are being added to produce a V1/V2 stereomotion and form perception system. Both the V1 and V2 models are based upon structures approximating neocortical minicolumns and functional columns. The neuromorphic strategies employed include columnar organization, integrate-and-fire neurons, temporal coding, point attraction recurrent networks, Reichardt detectors and “confabulation” networks. The interest is driven by the value of applications which can make use of highly parallel architectures we expect to see surpassing one thousand cores per die in the next few years. A central question we seek to answer is what the architecture of hyper-parallel machines should be. We also seek to understand computational methods akin to how a brain deals with sensation, perception, memory, attention decision-making.

We are pursuing an investigation of neuromorphic computational models and architectures in order to leverage present understanding of how the estimated 1011neurons and 1015neuron connections in the mammalian brain are able to do some of the things a human does, and as quickly as it does it, using slow base components, while consuming very little power on affordable synthetic non-biological computing hardware. Understanding and harvesting neurologically based methods is a promising approach with great potential that may help us achieve massively parallel computation far beyond the scope of traditional computing.

A model of portions of the cerebral cortex is being developed to explore neuromorphic computing strategies in the context of highly parallel platforms. The interest is driven by the value of applications which can make use of highly parallel architectures we expect to see surpassing one thousand cores per die in the next few years. A central question we seek to answer is what the architecture of hyper-parallel machines should be. We also seek to understand computational methods akin to how a brain deals with sensing, perception, memory, and cognition. The model is being developed incrementally, starting with the primary visual cortex (V1) field. It is based upon structures roughly corresponding to neocortical minicolumn and functional column structures. Gaps in neuroscience, such as inter-cell connectivity, are filled using estimates of functionality that are plausible given current understanding of the micro-anatomy. The success we encountered with achieving real-time performance is evidence validating the use of Cell-Be architecture in some classes of neuromorphic emulation. In this study we identified a particular gap-fill algorithm for lateral connections within V1 that is suggestive of a learning strategy whereby the lateral network subsumes expectation affect, reducing perception time and improving perception affect.

In this paper, we present our work in the implementation and performance optimization of the recall operation of the Brain-State-in-a-Box (BSB) model on the Cell Broadband Engine processor. We have applied optimization techniques on different parts of the algorithm to improve the overall computing and communication performance of the BSB recall algorithm. Runtime measurements show that, we have been able to achieve about 70% of the theoretical peak performance of the processor.

Cogent confabulation is a computation model that mimics the Hebbian learning, information storage, inter-relation of symbolic concepts, and the recall operations of the brain. The model has been applied to cognitive processing of language, audio and visual signals. In this project, we focus on how to accelerate the computation which underlie confabulation based sentence completion through software and hardware optimization. On the software implementation side, appropriate data structures can improve the performance of the software by more than 5,000X. On the hardware implementation side, the cogent confabulation algorithm is an ideal candidate for parallel processing and its performance can be significantly improved with the help of application specific, massively parallel computing platforms. However, as the complexity and parallelism of the hardware increases, cost also increases. Architectures with different performance-cost tradeoffs are analyzed and compared. Our analysis shows that although increasing the number of processors or the size of memories per processor can increase performance, the hardware cost and performance improvements do not always exhibit a linear relation. Hardware configuration options must be carefully evaluated in order to achieve good cost performance tradeoffs.

Molecular communication is one method for communication among nano-scale components (artificial or biological) that perform simple computation, sensing, or actuation. Future applications using nano-scale components may require communication mechanisms to coordinate with other components. For example, uni-cast is one primitive communication mechanism for transmission from one sender to one receiver and allows two nano-scale components to coordinate and perform some function. In this paper, we consider designing a molecular communication system that applies a molecular motor transport mechanism existing in biological cells. In molecular motor transport, a sender (nano-scale component) releases information molecules, and molecular motors transport the information molecules along protein filaments to a receiver (nano-scale component) up to hundreds of micrometers away. We consider a plus-centered aster (receiver with multiple protein filaments leading to the receiver) as one possible arrangement for protein filaments. We perform simulations to evaluate the probability of sending an information molecule to the receiver. The simulation results indicate that the proposed uni-cast molecular communication is limited in range (distance between sender and receiver with a reasonable success probability) and that the proposed molecular motor system transports simulated information molecules (100 nm radius spheres) with a greater success probability and than a passive diffusion-only system.

Research and development in modeling and simulation of human cognizance functions requires a high-performance computing platform for manipulating large-scale mathematical models. Traditional computing architectures cannot fulfill the attendant needs in terms of arithmetic computation and communication bandwidth. In this work, we propose a novel hybrid computing architecture for the simulation and evaluation of large-scale associative neural memory models. The proposed architecture achieves very high computing and communication performances by combining the technologies of hardware-accelerated computing, parallel distributed data operation and the publish/subscribe protocol. Analysis has been done on the computation and data bandwidth demands for implementing a large-scale brain-state-in-a-box (BSB) model. Compared to the traditional computing architecture, the proposed architecture can achieve at least 100X speedup.

Molecular communication is a new paradigm for communication between biological nanomachines over a short-range (a nano- and micro-scale range). Biological nanomachines are nano- and micro-scale devices that either exist in the biological world or are artificially created from biological materials and that perform simple functions such as sensing, logic, and actuation. Molecular communication provides a mechanism for biological nanomachines to communicate information by propagating molecules that represent the information. Molecular communication is based on observations of existing biological systems which use molecules as communication carriers. With the advancement of current research in areas such as synthetic biology and bio-nanotechnologies, it may become relatively easy in the near future to develop systems of biological nanomachines communicating through molecules. In this paper, we present a framework for describing molecular communication systems.

This paper describes the development of a model to assess the distribution of response times for mobile volunteers of a Public Access Defibrillation (PAD) scheme in Northern Ireland. Using parameters based on a trial period, the model predicts that a PAD volunteer would arrive before the Emergency Medical Services (EMS) to 18.8% of events to which they are paged in a given year period. This is in agreement with what has actually been observed during the trial period (where volunteers have actually reached 15% of events before the EMS), and thus assisting validation of the model. Results from this model illustrate how ongoing volunteer commitment is key to the success of the scheme.

Error correction can greatly improve the performance and extend the range of broadcast teletext systems. In this paper, the requirements for an error-correcting scheme for broadcast teletext in North America (NABTS) are set down. An error-correction scheme which meets all these requirements is then described. The simplest case employs the one parity bit in each 8 bit byte and no suffix of parity check bits at the end of each data block. The next level also uses a single byte of parity check bits at the end of each data block. Adding a second byte of parity checks at the end of each data block results in a Reed-Solomon code, called theCcode, for each data block. Adding one data block of parity checks afterh - 1data blocks results in a set ofhdata packets being encoded into a bundle, in which verticalCcodes provide powerful interleaving. In a final alternative, two data blocks hold the check bytes for the vertical codewords, and the most powerful coding scheme, the double bundle code, results. The detailed mathematical definitions of the various codes are referred to or described, formulas for performance calculations are referred to, and performance curves are presented for the AWGN channel as well as for measured field data. These performance curves are discussed and compared to the performance of a difference set cyclic code, originally designed for the Japanese teletext system, which corrects any 8 bits in error in a packet.