32150042
Exploring Protein's Optimal Hp Configurations by Self-organizing Mapping
Self-organizing map (SOM) has been used in protein folding prediction when the HP model is employed. The existing work uses a square-like shape lattice with l = m x n points to represent the optimal compact structure of a sequence of l amino acids. In this paper, a general l'-size sequence of amino acids is self-organized in a two dimensional lattice with l (> l') points. The obtained minimum configuration then has a flexible shape, in contrast to the compact structure limited in the lattice. To fulfil this extension, a new self-organizing map (SOM) technique is proposed to deal with the difficulty of the unsymmetric input and output spaces. New competition rules in the training phase are introduced and a local search method is applied to overcome the multi-mapping phenomena. Several HP benchmark examples with up to 36 amino acids are tested to verify the effectiveness of the proposed approach in this paper.
7815226
Peak Load Forecasting Using the Self-organizing Map
This paper aims to study the short-term load forecasting of electricity by using an extended self-organizing map. We first adopt a traditional Kohonen self-organizing map (SOM) to learn time-series load data with weather information as parameters. Then, in order to improve the accuracy of the prediction, an extension of SOM algorithm based on error-correction learning rule is used, and the estimation of the peak load is achieved by averaging the output of all the neurons. Finally, as an implementation example, data of electricity demand from New York Independent System Operator (ISO) are used to verify the effectiveness of the learning and prediction for the proposed methods.
8972258
Designing oscillators in synthetic gene networks based on multi-scale dynamics
Multistability, oscillations, and switching exist at various levels of biological processes and organizations and have been investigated on the basis of many theoretical models, such as circadian oscillations with the period protein (PER) and the timeless protein (TIM) in Drosophila, and multistable dynamics regulated by transcriptional factors. Considerable experimental evidence suggests that cellular processes are intrinsically rhythmic or periodic. Various periodic oscillations with different time scales ranging from less than a second to more than a year, which may allow for living organisms to adapt their behaviors to a periodically varying environment, have also been observed experimentally. On the other hand, in synthetic gene networks, both toggle switch and repressilator have been theoretically proposed and further confirmed by experiments. All of these works stress the importance of feedback regulation of transcriptional factors, which is a key in giving rise to oscillatory or multistable dynamical behaviors exhibited by biological genetic systems. In addition, it should be noted that many periodic behaviors do not simply oscillate smoothly; rather, they change rapidly or jump at certain states. In gene expression systems, many different time scales characterize the gene regulatory processes. For instance, the transcription and translation processes generally evolve on a time scale that is much slower than that of phosphorylation, dimerization or binding reactions of transcription factors. In genetic networks, the time scale for expression of some genes is much slower than that of others, depending on the length of the genes. We aim to design robust periodic oscillators in synthetic gene-protein systems by simple nonlinear models and to analyze the basic mechanism of limit cycles with jumping behaviors or relaxation oscillations by exploiting multiple time-scale properties [1, 2]. We show that periodic oscillations are mainly generated by nonlinear feedback loops in gene regulatory systems and the jumping dynamics caused by time scale differences among biochemical reactions. Moreover, effects of time delay are also examined. We show that time delay generally enlarges the stability region of oscillations, thereby making the oscillations more sustainable despite parameter changes or noise [1, 2]. The dynamics of the proposed models is robust in terms of stability and period length to the parameter perturbations or environment variations. Although we mainly analyze some specific models, the mechanisms identified in this work are likely to apply to a variety of genetic regulatory systems. These simple models may actually act as basic building block in synthetic gene-protein networks, such as genetic oscillators or switches because the dynamics is robust for parameter perturbations or environment variations. Several examples are also provided to demonstrate implementation of synthetic oscillators by using genes of the /spl lambda/ phage bacteria.
42859429
Hardware verification using symbolic state transition graphs
A new approach for hardware verification using symbolic state transition graphs (implemented in BDDs) is presented. We propose a novel idea, a symbolic state transition graph (STG), which can represent finite state machines FSM in terms of the relations between symbolic input variables, state variables, and output results, rather than the exact input-output bit patterns. Compared to conventional STG methods, the symbolic STG is more concise, higher-level, has fewer states and is easier to specify. Based on the transition relation method and an event-driven scheduling technique to compute the symbolic states, we propose two algorithms to verify the circuit implementation with respect to its symbolic STGs. The algorithms can be used to find out a necessary condition for the implementation to satisfy the specification, which can be used for the allocation of design errors.<<ETX>>
25000873
Design, analysis, and implementation of an agent driven pull-based distributed video-on-demand system
The problem of employing multiple servers to serve a pool of clients on a network based multimedia service is addressed. We have designed and practically implemented a prototype system employing multiple servers to render a long duration movie to the customers. We have employed a multiple server retrieval strategy proposed in the literature [39] to realize this system. In the system, server coordination, client behavior and service facilities are completely controlled by an Agent based approach in which we have used the recent Jini technology. Several issues, ranging from data retrieval from individual server, behavior of the underlying network infrastructure, to client management and resource (client buffers) management, are considered in this implementation. We describe in detail our experiences in this complete design process of every module in the software architecture, its purpose, and working style. Further, the system is shown to be robust amidst unpredictable failures, i.e., in the event of server crashes. The load balancing capability is built-in as a safe guard measure to assure a continuous presentation. We present a comprehensive discussion on the software architecture to realize this working system and present our experiences. A system comprising a series of Pentium III PCs on a fast Ethernet network is built as a test-bed. Through this prototype, a wider scope of research challenges ahead are highlighted as possible extensions.
8213932
End-to-End Asymmetric Link Capacity Estimation
Knowledge of link capacity is important for network design, management, and utilization. With the increasing popularity of asymmetric link technologies (such as DSL, 1xRTT, and satellite links), it is desirable to have a capacity estimation technique, which can simultaneously measure forward and backward direction link capacities on an Internet path. Moreover, this estimation must often be “sender only”, because of receiver limitations or lack of standards. In this study, we propose a simple, fast and accurate technique, called AsymProbe, to estimate asymmetric link capacities. AsymProbe is a “sender only”, round trip procedure. It achieves asymmetric link capacity estimation by strategically altering the ratio of probe and acknowledgement packet sizes. Using simulation and testbed experiments, we validate AsymProbe with a variety of network configurations. The results show that AsymProbe can correctly estimate the asymmetric link capacities as long as an appropriate packet size ratio can be employed.
6316461
Partitioned optimization algorithms for multiple sequence alignment
Multiple sequence alignment is an important and difficult problem in molecular biology and bioinformatics. In this paper, we propose a partitioning approach that significantly improves the solution time and quality by utilizing the locality structure of the problem. The algorithm solves the multiple sequence alignment in three stages. First, an automated and suboptimal partitioning strategy is used to divide the set of sequences into several subsections. Then a multiple sequence alignment algorithm based on ant colony optimization is used to align the sequences of each subsection. Finally, the alignment of original sequences can be obtained by assembling the result of each subsection. The ant colony algorithm is highly optimized in order to avoid local optimal traps and converge to global optimal efficiently. Experimental results show that the algorithm can significantly reduce the running time and improve the solution quality on large-scale multiple sequence alignment benchmarks.
62256007
CapProbe: a simple and accurate capacity estimation technique
We present a new capacity estimation technique, called CapProbe. CapProbe combines delay as well as dispersion measurements of packet pairs to filter out samples distorted by cross-traffic. CapProbe algorithms include convergence tests and convergence speed-up techniques by varying probing parameters. Our study of CapProbe includes a probability analysis to determine the time it takes CapProbe to converge on the average. Through simulations and measurements, we found CapProbe to be quick and accurate across a wide range of traffic scenarios. We also compared CapProbe with two previous well-known techniques, pathchar and pathrate. We found CapProbe to be much more accurate than pathchar and similar in accuracy to pathrate, while providing faster estimation than both. Another advantage of CapProbe is its lower computation cost, since no statistical post processing of probing data is required.