493776
Evolutionary Ensemble for Stock Prediction
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ensemble makes the decision of buying or selling more conservative. It showed notable improvement on the average over not only the buy-and-hold strategy but also other traditional ensemble approaches.
3218907
Assignment Copy Detection Using Neuro-genetic Hybrids
It is difficult for teachers to find out copies in their program assignments. We propose a method which detects the similarity of assignments. We first transform a program into a sequence of tokens and provide it to an artificial neural network. The neural network is optimized by a hybrid genetic algorithm. Experimental results showed considerable improvement on artificial neural networks.
18194762
Daily Stock Prediction Using Neuro-genetic Hybrids
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic algorithm optimizes the neural networks under a 2D encoding and crossover. To reduce the time in processing mass data, a parallel genetic algorithm was used on a Linux cluster system. It showed notable improvement on the average over the buy-and-hold strategy. We also observed that some companies were more predictable than others.
9128432
An Efficient Method for Version Control of a Tree Data Structure
61822837
Resilient Localization for Sensor Networks in Outdoor Environments
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold (20-30m) while maintaining a distance-invariant median measurement error of about 1% of maximum range (33cm). The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments
15346879
A 3-D FPGA wire resource prediction model validated using a 3-D placement and routing tool
The interconnection architecture of FPGAs such as switches dominates performance of FPGAs. Three-dimensional integration of FPGAs overcomes interconnect limitations by allowing instances to be located and signals to be routed in 3-D space. Wire resource prediction is important for fast and accurate interconnection planning in 3-D FPGA. In this paper, we extend the existing analytic model shown in [13] with a new parameter for our 3-D FPGA which has cluster-based logic blocks. The proposed wire resource prediction model is applied to our 3-D FPGA using a Xilinx Virtex2 slice [18] and our 3-D routing architecture. We validate the effectiveness of the extended model by comparing the required number of channel wires predicted by the extended analytic equation with that of the placed and routed results using 3-D placement and routing algorithm designed for our 3-D FPGA for a number of benchmark circuits. The extended 3-D wire resource prediction model predicts the required channel capacity with an average of 11.1% error for 17 large circuits from LGSynth93 and ISPD2001 Verilog benchmarks.
13194172
ActorNet: an actor platform for wireless sensor networks
We present actorNet, a mobile agent platform for wireless sensor networks (WSNs). WSNs are well-suited to multiagent systems: agent autonomy reduces the need for communication, saving precious energy. Mobile agents are also an intuitive technique for remotely reprogramming sensors deployed in the field. However, implementing agent programs directly on a WSN is complicated by the many limitations of sensor nodes, including limited memory, slow processors, low bandwidth and finite energy. ActorNet eases development by providing an abstract environment for lightweight concurrent object-oriented mobile code on WSNs. As such, it enables a wide range of new dynamic applications, including fully customizable queries and aggregation functions, in-network interactive debugging and high-level concurrent programming on the inherently parallel sensor network platform. Moreover, actorNet cleanly integrates all of these features into a fine-tuned, multi-threaded embedded Scheme interpreter that supports compact, maintainable programs---a significant advantage over primitive stack-based virtual machines.
21969752
The design and implementation of automata-based testing environment for Java multi-thread programs
Deterministic execution testing has been considered a promising method for concurrent program testing because of its reproducibility. However, since deterministic execution requires that a synchronization sequence to be replayed is feasible and valid, it is not directly applicable to a situation in which synchronization sequences, being valid but infeasible, are taken into account. To resolve this problem, we proposed automata-based testing in previous work, where a concurrent program is executed according to one sequence accepted by the automaton recognizing all sequences semantically equivalent to a given sequence. In this paper, we present the automata-based testing environment for Java multi-thread programs, and design and implement key components-automata generator, program transformer and replay controller. Algorithms for generating the equivalence automaton of a given sequence are presented and a program transformation method is suggested in order to guide a program to be executed according to the sequence accepted by the automaton. The replay controller is also redesigned and implemented to adopt the automaton. By illustrating automata-based testing procedures with the gas station example, we show how the proposed approach works in Java multi-threaded programs.