Quantum cellular neural networks

We have previously proposed a way of using coupled quantum dots to construct digital computing elements—quantum-dot cellular automata. Here we consider a different approach to using coupled quantum-dot cells in an architecture which, rather than reproducing Boolean logic, uses a physical near-neighbor connectivity to construct an analog cellular neural network.     

On the optically transparent WDM ATM multicast (3M) switches

We describe an architecture design and implementation of the optically transparent wavelength-division-multiplexed (WDM) asynchronous-transfer-mode (ATM) multicast (3M) switch for all optical high-speed networks. By using the WDM techniques, the wire complexity in both the switch fabric and the concentrator can be reduced from O(N²) to O(N). By using integrated photonic devices and highly parallel processing and pipeline control electronic circuits the switch is handling signals at the cell level (53 bytes) instead of at the bit level and can achieve very high speed and high throughput operation. Several key components, including a cell synchronizer, a photonic VCI over-writting unit, a wavelength converter, an optical concentrator, and a WDM memory, have also been proposed to realize this 3M switch. All of the photonic devices are highly integratable and are very suitable for building future large-scale, low-cost photonic ATM switches. A combination of both the ATM and WDM techniques will provide an ultimate version for optical networking with almost unlimited capacity.     

A cellular automata model with probability infection and spatial dispersion

In this article, we have proposed an epidemic model based on the probability cellular automata theory. The essential mathematical features are analysed with the help of stability theory. We have given an alternative modelling approach for the spatiotemporal system which is more realistic from the practical point of view. A discrete and spatiotemporal approach is shown by using cellular automata theory. It is interesting to note that both the size of the endemic equilibrium and the density of the individuals increase with the increase of the neighbourhood size and infection rate, but the infections decrease with the increase of the recovery rate. The stability of the system around the positive interior equilibrium has been shown by using a suitable Lyapunov function. Finally, experimental data simulation for SARS disease in China in 2003 and a brief discussion are given.     

宏微观耦合模拟熔池不同区域中枝晶竞争生长过程

针对熔化焊过程建立了宏微观耦合模型,模拟了熔池内不同区域凝固过程中随机取向枝晶的竞争生长过程. 通过宏观三维有限元模型计算熔池中瞬态的传热传质过程,利用双线性插值算法将凝固参数传递给微观组织模型. 采用元胞自动机法模拟随机取向的枝晶在熔池凝固条件下的竞争生长过程. 模拟结果表明,所建立的微观模型能够精确模拟任意生长取向的枝晶. 凝固条件中最大温度梯度方向对枝晶竞争过程有明显选择作用,生长方向与最大温度梯度方向相同或接近的枝晶在竞争中具有更大优势. 焊缝中的晶粒组织由枝晶簇发展形成,晶粒组织的形貌演变取决于相邻枝晶簇之间的竞争过程,具有择优取向的枝晶簇会逐渐排挤非择优取向的枝晶簇并最终将其阻挡在凝固组织内部,宏观晶粒的取向与其内部枝晶簇的生长方向并不一定相同. 熔池中心线附近区域在焊接过程中具有更小的温度梯度、更大的凝固速率以及更大的局部冷却速率,凝固后可以获得更加细小的焊缝枝晶组织. 枝晶间距的模拟结果与相应凝固条件下的试验数据符合较好. 关键词： 焊接熔池 枝晶形貌 竞争生长 元胞自动机     

From quantum cellular automata to quantum lattice gases

A natural architecture for nanoscale quantum computation is that of a quantum cellular automaton. Motivated by this observation, we begin an investigation of exactly unitary cellular automata. After proving that there can be no nontrivial, homogeneous, local, unitary, scalar cellular automaton in one dimension, we weaken the homogeneity condition and show that there are nontrivial, exactly unitary, partitioning cellular automata. We find a one-parameter family of evolution rules which are best interpreted as those for a one-particle quantum automaton. This model is naturally reformulated as a two component cellular automaton which we demonstrate to limit to the Dirac equation. We describe two generalizations of this automaton, the second, of which, to multiple interacting particles, is the correct definition of a quantum lattice gas.     

Biophysical model for high-throughput tumor and epithelial cell co-culture in complex biochemical microenvironments

The in vivo tumor microenvironment is a complex niche that includes heterogeneous physical structures,unique biochemical gradients and multiple cell interactions.Its high-fidelity in vitro reconstruction is of fundamental importance to improve current understandings of cell behavior,efficacy predictions and drug safety.In this study,we have developed a high-throughput biochip with hundreds of composite extracellular matrix(ECM)microchambers to co-culture invasive breast cancer cells(MDA-MB-231-RFP)and normal breast epithelial cells(MCF-10 A-GFP).The composite ECM is composed of type I collagen and Matrigel which provides a heterogeneous microenvironment that is similar to that of in vivo cell growth.Additionally,the growth factors and drug gradients that involve human epidermal growth factor(EGF),discoidin domain receptor 1(DDR1)inhibitor 7 rh and matrix metalloproteinase inhibitor batimastat allow for the mimicking of the complex in vivo biochemical microenvironment to investigate their effect on the spatial-temporal dynamics of cell growth.Our results demonstrate that the MDA-MB-231-RFP cells and MCF-10 A-GFP cells exhibit different spatial proliferation behaviors under the combination of growth factors and drugs.Basing on the experimental data,we have also developed a cellular automata(CA)model that incorporated drug diffusion to describe the experimental phenomenon,as well as employed Shannon entropy(SE)to explore the effect of the drug diffusion coefficient on the spatial-temporal dynamics of cell growth.The results indicate that the uniform cell growth is related to the drug diffusion coefficient,which reveals that the pore size of the ECM plays a key role in the formation of complex biochemical gradients.Therefore,our integrated,biomimetic and high-throughput co-culture platforms,as well as the computational model can be used as an effective tool for investigating cancer pathogenesis and drug development.     

Dualities for a Class of Finite Range Probabilistic Cellular Automata in One Dimension

In this paper we study dualities for a class of one-dimensional probabilistic cellular automata with finite range interactions by using a sequence of extended cellular automata.     

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.     

Optical pulsation mechanism based on optical near-field interactions

We theoretically demonstrate optical pulsation based on optical near-field interactions between quantum nanostructures. It is composed of two quantum dot systems, each of which consists of a combination of smaller and larger quantum dots, so that optical excitation transfer occurs. With an architecture in which the two systems take the role of a timing delay and frequency up-conversion, we observe pulsation in populations pumped by continuous-wave light irradiation. The pulsation is induced with suitable setting of parameters associated with the optical near-field interactions. This will provide critical insights toward the design and implementation of experimental nanophotonic pulse generating devices.     

Optical implementation of the stream cipher based on the irreversible cellular automata algorithm

A hybrid optical scheme for efficient hardware implementation of the one-dimensional, three-neighborhood binary cellular automata rule a(i)(?) =a(i-1)XOR(a(i)OR a(i+1)) -based stream cipher is proposed. The system makes full use of the parallel, space-invariant, cascadable, and modular structure of the algorithm and is simple, robust, and compact. The number of cellular automata arrays can be as large as the number of pixels on the spatial light modulator, which results in an increase in speed (number of bits operated in parallel) and security (key length). The system can be made fully optical with the use of an optically addressable spatial light modulator for the input plane and for the nonlinear threshold element.     

三维空间行人疏散的元胞自动机模型

为了有效刻画行人在三维空间中的疏散状况,结合阶梯因素提出了一种新的三维元胞自动机模型,该模型首先基于位置吸引力和碰撞可能性给出了行人移动概率的计算公式,并通过定义元胞演化过程阐述其疏散策略,同时,利用建立的仿真平台进行实验,深入分析了疏散时间、出口流率、出口宽度、初始行人密度以及系统平均速度之间的关系,以此获得更加符合实际情况的行人流特征,结果表明,疏散时间、出口流率与初始行人密度呈现正相关,而与出口宽度呈现负相关,并且系统平均速度和出口宽度对于最优疏散时间存在一个理想阈值。     

Station Model for Rail Transit System Using Cellular Automata

In this paper, we propose a new cellular automata model to simulate the railway traffic at station. Based on NaSch model, the proposed station model is composed of the main track and the siding track. Two different schemes for trains passing through station are considered. One is the scheme of ＂pass by the main track, start and stop by the siding track＂. The other is the scheme of ＂two tracks play the same role＂. We simulate the train movement using the proposed model and analyze the traffic flow at station. The simulation results demonstrate that the proposed cellular automata model can be successfully used for the simulations of railway traffic. Some characteristic behaviors of railway traffic flow can be reproduced. Moreover, the simulation values of the minimum headway are close to the theoretical values. This result demonstrates the dependability and availability of the proposed model.     

Emergence of self-replicating structures in a cellular automata space

Past cellular automata models of self-replication have always been initialized with an original copy of the structure that will replicate, and have been based on a transition function that only works for a single, specific structure. This article demonstrates for the first time that it is possible to create cellular automata models in which a self-replicating structure emerges from an initial state having a random density and distribution of individual components. These emergent self-replicating structures employ a fairly general rule set that can support the replication of structures of different sizes and their growth from smaller to larger ones. This rule set also allows “random” interactions of self-replicating structures with each other and with other structures within the cellular automata space. Systematic simulations show that emergence and growth of replicants occurs often and is essentially independent of the cellular space size, initial random pattern of components, and initial density of components, over a broad range of these parameters. The number of replicants and the total number of components they incorporate generally approach quasi-stable values with time.     

A Transfer Learning Approach on the Optimization of Edge Detectors for Medical Images Using Particle Swarm Optimization

Edge detection is a fundamental image analysis task, as it provides insight on the content of an image. There are weaknesses in some of the edge detectors developed until now, such as disconnected edges, the impossibility to detect branching edges, or the need for a ground truth that is not always accessible. Therefore, a specialized detector that is optimized for the image particularities can help improve edge detection performance. In this paper, we apply transfer learning to optimize cellular automata (CA) rules for edge detection using particle swarm optimization (PSO). Cellular automata provide fast computation, while rule optimization provides adaptability to the properties of the target images. We use transfer learning from synthetic to medical images because expert-annotated medical data is typically difficult to obtain. We show that our method is tunable for medical images with different properties, and we show that, for more difficult edge detection tasks, batch optimization can be used to boost the quality of the edges. Our method is suitable for the identification of structures, such as cardiac cavities on medical images, and could be used as a component of an automatic radiology decision support tool.     

A New Cellular Automata Model Considering Finite Deceleration and Braking Distance

We present a new cellular automata model for one-lane traffic flow. In this model, we consider the driver prejudgment according to the state of the leading car. We also consider that the vehicle deceleration capability is finite and the braking distance of the high-speed running cars cannot be ignored, which is not considered in most models. Furthermore, comfortable driving is considered, too. Using computer simulations we obtain some basic qualitative results and the fundamental diagram of the proposed model. In comparison with the known models, we find that the fundamental diagram of the proposed model is more realistic than that of the known models.     

Memristor-based vector neural network architecture

Vector neural network(VNN) is one of the most important methods to process interval data.However,the VNN,which contains a great number of multiply-accumulate(MAC) operations,often adopts pure numerical calculation method,and thus is difficult to be miniaturized for the embedded applications.In this paper,we propose a memristor based vector-type backpropagation(MVTBP) architecture which utilizes memristive arrays to accelerate the MAC operations of interval data.Owing to the unique brain-like synaptic characteristics of memristive devices,e.g.,small size,low power consumption,and high integration density,the proposed architecture can be implemented with low area and power consumption cost and easily applied to embedded systems.The simulation results indicate that the proposed architecture has better identification performance and noise tolerance.When the device precision is 6 bits and the error deviation level(EDL) is 20%,the proposed architecture can achieve an identification rate,which is about 92% higher than that for interval-value testing sample and 81% higher than that for scalar-value testing sample.     

Asymmetric nonlinear-mode-conversion in an optical waveguide withPT symmetry

Asymmetric mode transformation in waveguide is of great significance for on-chip integrated devices with one-way effect, while it is challenging to achieve asymmetric nonlinear-mode-conversion (NMC) due to the limitations imposed by phase-matching. In this work, we theoretically proposed a new scheme for realizing asymmetric NMC by combining frequency-doubling process and periodic PT symmetric modulation in an optical waveguide. By engineering the one-way momentum from PT symmetric modulation, we have demonstrated the unidirectional conversion from pump to second harmonic with desired guided modes. Our findings offer new opportunities for manipulating nonlinear optical fields with PT symmetry, which could further boost more exploration on on-chip nonlinear devices assisted by non-Hermitian optics.     

Systematics of the models of immune response and autoimmune disease

A dynamical model of normal immune response has been formulated in terms of cellular automata by Kaufmanet al. We generalize this model incorporating the antigens as a dynamical variable. This generalized model not only describes the kinetics of primary and secondary responses of humoral immunity, together with the appropriate memory cells, but also describes the vaccinated state as well as the states of low-dose and high-dose paralysis. Recently models of autoimmune response have also been developed in terms of discrete automata. But the models are underdetermined by the experimental facts, i.e., several models can account for the same set of observed biological facts. With an aim to find out how large this underdeterminacy is and how it can be reduced systematically, we have carried out an exhaustive computer-aided search of all those discrete three-cell and five-cell models of autoimmune response which at present cannot be ruled out by the existing biological informations. Out of the 3²⁵ possible five-cell models, only one fulfilled our criteria. We also carried out simulations of the dynamics of some of these models on a discrete lattice. We discuss the relevance of random interactions in the context of autoimmune disease.     

Stair evacuation simulation based on cellular automata considering evacuees' walk preferences

As a physical model,the cellular automata(CA) model is widely used in many areas,such as stair evacuation.However,existing CA models do not consider evacuees' walk preferences nor psychological status,and the structure of the basic model is unapplicable for the stair structure.This paper is to improve the stair evacuation simulation by addressing these issues,and a new cellular automata model is established.Several evacuees' walk preference and how evacuee's psychology influences their behaviors are introduced into this model.Evacuees' speeds will be influenced by these features.To validate this simulation,two fire drills held in two high-rise buildings are video-recorded.It is found that the simulation results are similar to the fire drill results.The structure of this model is simple,and it is easy to further develop and utilize in different buildings with various kinds of occupants.     

Improvement in electrical properties of high-κ film on Ge substrate by an improved stress relieved pre-oxide method

High-κ /Ge gate stack has recently attracted a great deal of attention as a potential candidate to replace planar silicon transistors for sub-22 generation. However, the desorption and volatilization of GeO hamper the development of Ge-based devices. To cope with this challenge, various techniques have been proposed to improve the high-κ /Ge interface. However,these techniques have not been developed perfectly yet to control the interface. Therefore, in this paper, we propose an improved stress relieved pre-oxide(SRPO) method to improve the thermodynamic stability of the high-κ /Ge interface. The x-ray photoelectron spectroscopy(XPS) and atomic force microscopy(AFM) results indicate that the GeO volatilization of the high-κ /Ge gate stack is efficiently suppressed after 500℃ annealing, and the electrical characteristics are greatly improved.