425 research outputs found
An Anthropological Study of Risk Management of Medical Care at Elementary and Junior High Schools
An Anthropological Study of Risk Management of Disaster Response at Elementary and Junior High Schools
Video ads dissemination through WiFi-cellular hybrid networks
PerCom2009 : The Seventh Annual IEEE International Conference on Pervasive Computing and Communications , Mar 16-20, 2009 , Dallas, TX, USAIn this paper, we propose a method for video ads dissemination through a hybrid network consisting of WiFi and cellular networks, in order to provide timely delivery of video ads with preferred content to users according to the users' contexts. In recent years, video download/streaming services for cellular phones have already become popular. Among various video delivery services, a service for disseminating video ads according to the users' contexts is expected to achieve high advertising effects. However, context-aware video ads dissemination will consume large bandwidth since the size of video ad is rather large and the same ad is required at different time from various users. We propose a new video ads dissemination method for mobile terminals which utilizes both WiFi and cellular networks. In the proposed method, a file of video ad is divided into pieces and each node exchanges the pieces with neighbor nodes using WiFi ad hoc communication so that the usage of cellular network is reduced. In order to make the method works effectively for a large number of nodes, we propose an algorithm where mobile nodes autonomously and probabilistically decide their actions without a central control. Through simulations, we confirmed that our method reduces cellular network usage by about 93% compared with a case that all nodes download video ads via cellular network, and works effectively in cases with a large number of nodes and high mobility
A Method to Plan Group Tours with Joining and Forking
SEAL2006 : Asia-Pacific Conference on Simulated Evolution and Learning , Oct 15-18, 2006 , Hefei, ChinaGroup sightseeing has some advantages in terms of required budget and so on. Some travel agents provide package tours of group sightseeing, but participants have to follow a predetermined schedule in tour, and thus there may be no plan which perfectly satisfies the tourist's expectation. In this paper, we formalize a problem to find group sightseeing schedules for each user from given users’ preferences and time restrictions corresponding to each destination. We also propose a Genetic Algorithm-based algorithm to solve the problem. We implemented and evaluated the method, and confirmed that our algorithm finds efficient routes for group sightseeing
Flexible implementation of genetic algorithms on FPGAs
FPGA '06 : ACM/SIGDA 14th international symposium on Field programmable gate arrays , Feb 22-24, 2006 , Monterey, CA, USAGenetic algorithms (GAs) are useful since they can find near optimal solutions for combinatorial optimization problems quickly. Although there are many mobile/home applications of GAs such as navigation systems, QoS routing and video encoding systems, it was difficult to apply GAs to those applications due to low computational power of mobile/home appliances. In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture which consists of several modules for GA operations to compose a GA pipeline, and a parallel architecture consisting of multiple concurrent pipelines. The proposed architectures are simple enough to be implemented on FPGAs, applicable to various problems, and easy to estimate the size of the resulting circuit. We also propose a model for predicting the size of resulting circuit from given parameters consisting of the problem size, the number of concurrent pipelines and the number of candidate solutions for GA. Based on the proposed method, we have implemented a tool to facilitate GA circuit design and development. This tool allows designers to find appropriate parameter values so that the resulting circuit can be accommodated in the target FPGA device, and to automatically obtain RTL VHDL description. Through experiments using Knapsack Problem and TSP, we show that the FPGA circuits synthesized based on the proposed method run much faster and consume much lower power than software implementation on a PC and that our model can predict the size of the resulting circuit accurately enough
General Architecture for Hardware Implementation of Genetic Algorithm
FCCM 2006 : 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines , Apr 24-26, 2006 , Napa, CA, USAIn this paper, the authors propose a technique to flexibly implement genetic algorithms (GAs) for various problems on FPGAs. For the purpose, the authors propose a common architecture for GA. The proposed architecture allows designers to easily implement a GA as a hardware circuit consisting of parallel pipelines which execute GA operations. The proposed architecture is scalable to increase the number of parallel pipelines. The architecture is applicable to various problems and allows designers to estimate the size of resulting circuits. The authors give a model for predicting the size of resulting circuits from given parameters. Based on the proposed method, the authors have implemented a tool to facilitate GA circuit design and development. Through experiments using knapsack problem and traveling salesman problem (TSP), the authors show that the FPGA circuits synthesized based on the proposed method run much faster and consume much lower power than software implementation on a PC and the model can predict the size of the resulting circuit accurately enough
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