Simulating the Effect of Pay Table Standard Deviation on Pulls Per Losing Player at the Single-visit Level

While holding par constant, changes in the standard deviation of the pay table produced an inverse effect on pulls per losing player (PPLP), across six different virtual slot machines. This result establishes the standard deviation of a game as a crucial determinant of a slot player\u27s experience. Three different single-trip scenarios were examined via computer simulation, with 50,000 players engaging each game. For example, virtual players began with 100 units, terminating play at bankruptcy or 200 units. As players focus on the outcome of single visits, understanding the determinants of PPLP (or time on device) will help management engineer desirable customer experiences at the trip level. In part, this can be achieved by altering the product mix to better match the expectations of the clientele. Given the remarkable bankruptcy rate of the trip simulations, proxies for value such as PPLP serve as crucial evaluation standards in the satisfaction process

A Fast and Simple Algorithm for Computing M Shortest Paths in Stage Graph

We consider the problem of computing m shortest paths between a source node s and a target node t in a stage graph. Polynomial time algorithms known to solve this problem use complicated data structures. This paper proposes a very simple algorithm for computing all m shortest paths in a stage graph efficiently. The proposed algorithm does not use any complicated data structure and can be implemented in a straightforward way by using only array data structure. This problem appears as a sub-problem for planning risk reduced multiple k-legged trajectories for aerial vehicles

Free Regions of Sensor Nodes

We introduce the notion of free region of a node in a sensor network. Intuitively, a free region of a node is the connected set of points R in its neighborhood such that the connectivity of the network remains the same when the node is moved to any point in R. We characterize several properties of free regions and develop an efficient algorithm for computing them. We capture free region in terms of related notions called in-free region and out-free region. We present an O(n2) algorithm for constructing the free region of a node, where n is the number of nodes in the network

A Fast and Simple Algorithm for Computing M-shortest Paths in State Graph

We consider the problem of computing m shortest paths between a source node s and a target node t in a stage graph. Polynomial time algorithms known to solve this problem use complicated data structures. This paper proposes a very simple algorithm for computing all m shortest paths in a stage graph efficiently. The proposed algorithm does not use any complicated data structure and can be implemented in a straightforward way by using only array data structure. This problem appears as a sub-problem for planning risk reduced multiple k-legged trajectories for aerial vehicles

Tracker-node Model for Energy Consumption in Reconfigurable Processing Systems

In this paper, we present an energy dissipation model for reconfigurable systems in which FPGAs have the property of online reprogramming. The proposed system contains regular nodes and one control node. Each regular node contains both CPU - capable of software processing, and FPGA unit which after being programmed with bitstream serves as the hardware processing parts. Nodes are connected in some structure and the connections form the transport layer. The system is capable of processing tasks in a distributed manner and communication, control and processing parts are taken into consideration in the energy equations. The model has also been used for algorithms that formed the complete system that is used for experimentation

Characterizing Free-regions of Sensor nodes

This paper considers the problem of relocating a sensor node for increasing the quality of coverage. We present the notion of free-region of nodes in a sensor network. We investigate properties of free-regions and their characterizations in term of in-free region and out-free region. A centralized algorithm for constructing the free region of sensor node in presented. The algorithm runs in O(n^2) time, where n is the number of sensor nodes in the network