Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows:

Use of competition detection in TCP for simple topology networks

The fairness (or TCP-friendliness) of recent high-speed TCP proposals for high bandwidth-delay product networks is generally poor. We believe that the lack of TCP-friendliness of high-speed TCP proposals stems from their ineffectiveness in detecting competing TCP flows. We suggest a competition detection mechanism for a single TCP flow to detect the presence of competing TCP flows. We propose a new TCP, called Adaptive TCP (A-TCP) to demonstrate the usefulness of the competition detection mechanism. A-TCP uses the competition detection mechanism to control its aggressiveness: If it does not detect competing flows, a single A-TCP flow increases its sending rate aggressively in order to highly utilize the network. Otherwise, it behaves like a standard TCP flow to fairly share network resources with competing flows. We implemented A-TCP as part of Linux as well as in ns-2. Experimental results show that A-TCP achieves better fairness than existing high-speed TCP proposals when they compete against standard TCP in simple topology networks.     

Laser pyrolysis in papers and patents

Journal of Intelligent Manufacturing - This paper presents a critical review of laser pyrolysis. Although this technology is almost 60 years old, in literature many researchers, both from...     

Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.     

Two is better than one: A diploid genotype for neural networks

In nature the genotype of many organisms exhibits diploidy, i.e., it includes two copies of every gene. In this paper we describe the results of simulations comparing the behavior of haploid and diploid populations of ecological neural networks living in both fixed and changing environments. We show that diploid genotypes create more variability in fitness in the population than haploid genotypes and buffer better environmental change; as a consequence, if one wants to obtain good results for both average and peak fitness in a single population one should choose a diploid population with an appropriate mutation rate. Some results of our simulations parallel biological findings.     

Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis

This paper presents a heuristic algorithm for solving a job-shop scheduling problem with sequence dependent setup times and min/max separation constraints among the activities (SDST-JSSP/max). The algorithm relies on a core constraint-based search procedure, which generates consistent orderings of activities that require the same resource by incrementally imposing precedence constraints on a temporally feasible solution. Key to the effectiveness of the search procedure is a conflict sampling method biased toward selection of most critical conflicts and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically both on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times and by introducing a new benchmark with setups and generalized precedence constraints.     

Model-based cold-start speed control scheme for spark ignition engines

This paper presents a model-based control scheme to the cold-start speed control in spark ignition (SI) engines. The multi-variable control algorithm is developed with the purpose of improving the transient performance of the starting engine speed: the control inputs are the fuel injection, the throttle and the spark advance (SA), while the engine speed and the air mass flow rate are the measured signals. The fuel injection is performed with a dual sampling rate system: the cycle-based fuel injection command is individually adjusted for each cylinder by using a TDC (top dead center)-based air charge estimation. The desired performance for speed regulation is achieved by using a coordinated control of SA and throttle operation. The speed error convergence of the closed loop system is proved for simplified, second-order model with a time-delay, and the robustness with respect to parameter uncertainties is investigated. The performance and the robustness with respect to modeling uncertainties of the proposed control scheme are tested using an industrial engine simulator with six cylinders.     

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.