Trajectory Tracking Control of an Underactuated Underwater Vehicle Redundant Manipulator System

The purpose of this study is to control the position of an underactuated underwater vehicle manipulator system (U‐UVMS). It is possible to control the end‐effector using a regular 6‐DOF manipulator despite the undesired displacements of the underactuated vehicle within a certain range. However, in this study an 8‐DOF redundant manipulator is used in order to increase the positioning accuracy of the end‐effector. The redundancy is resolved according to the criterion of minimal vehicle and joint motions. The underactuated underwater vehicle redundant manipulator system is modeled including the hydrodynamic forces for the manipulator in addition to those for the autonomous underwater vehicle (AUV). The shadowing effects of the bodies on each other are also taken into account when computing the hydrodynamic forces. The Newton‐Euler formulation is used to derive the system equations of motion including the thruster dynamics. In order to establish the end‐effector trajectory tracking control of the system, an inverse dynamics control law is formulated. The effectiveness of the control law even in the presence of parameter uncertainties and disturbing ocean currents is illustrated by simulations.     

The relation between preset distinguishing sequences and synchronizing sequences

We study the relation between synchronizing sequences and preset distinguishing sequences which are some special sequences used in finite state machine based testing. We show that the problems related to preset distinguishing sequences can be converted into related problems of synchronizing sequences. Using the results existing in the literature for synchronizing sequences, we offer several reflections of these results for preset distinguishing sequences. Although computing a preset distinguishing sequence is PSPACE-hard , we do identify a class of machines for which computing a preset distinguishing sequence can be performed in polynomial time and argue that this class is practically relevant. We also present an experimental study to compare the performance of exponential brute-force and polynomial heuristic algorithms to compute a preset distinguishing sequence.     

Handling large-scale node failures in mobile sensor/robot networks

In Wireless Sensor Networks (WSNs), maintaining connectivity with the sink node is a crucial issue to collect data from sensors without any interruption. While sensors are typically deployed in abundance to tolerate possible node failures, a large number of simultaneous node failures within the same region may result in partitioning the network which may disrupt the network operation significantly. Given that WSNs are deployed in inhospitable environments, such node failures are very likely due to storms, fires, floods, etc. The self-recovery of the network from these large-scale node failures is challenging since the nodes will not have any information about the location and span of the damage. In this paper, we first present a distributed partition detection algorithm which quickly makes the sensors aware of the partitioning in the network. This process is led by the sensors whose upstream nodes fail due to damages. Upon partition detection, sensors federate the partitions and restore data communication by utilizing the former routing information stored at each sensor to the sink node and exploiting sensor mobility. Specifically, the locations of failed sensors on former routes are used to assess the span of the damage and some of the sensors are relocated to such locations to re-establish the routes with the sink node. Relocation on such former routes is performed in such a way that the movement overhead on sensors is also minimized. Our proposed approach solely depends on the local information to ensure autonomicity, timeliness and scalability. The effectiveness of the proposed federation approach is validated through realistic simulation experiments and has been shown to provide the mentioned features.     

Cost and benefit analysis of authentication systems

This study investigates the key elements an online service or product provider needs to consider when adopting another single-factor or two-factor authentication system. We also uncover the conditions that make the new one-factor or two-factor authentication system more preferable. By using the probability of system failure, this study generalizes all possible combination of authentication systems into four different cases. This generalization allows us to compare different systems and to determine the key factors managers need to consider when adopting a new authentication system. The key factors are (1) additional implementation costs, (2) customer switching which is determined by the market share and customers' preferences, and (3) expected losses when the new system fails. This study also suggests that if the provider chooses an expensive new system, the provider needs to have a larger market share to justify the spending. Also, regulators can encourage the adoption of a more secure authentication system by changing the penalty a firm faces when the system fails. Finally, it could also be preferable to have both one-factor and two-factor authentication systems depending on the customers' characteristics.     

Using the continuous price as control variate for discretely monitored options

Variance reduction is of highest importance in financial simulation. In this study, we present a new and simple variance reduction technique for pricing discretely monitored lookback and barrier options. It is based on using the corresponding continuously monitored option as external control variate. To obtain the value of the continuously monitored price both, conditional simulation and conditional expectation can be utilized. From numerical experiments we can conclude that the efficiency gains obtained by our new method are significant.     

Maximizing lifetime of event-unobservable wireless sensor networks

In wireless sensor networks (WSNs) contextual information such as the information regarding whether, when, and where the data is collected cannot be protected using only traditional measures (e.g., encryption). Contextual information can be protected against global eavesdroppers by periodic packet transmission combined with dummy traffic filtering at proxy nodes. In this paper, through a Linear Programming (LP) framework, we analyze lifetime limits of WSNs preserving event-unobservability with different proxy assignment methodologies. We show that to maximize the network lifetime data flow should pass through multiple proxies that are organized as a general directed graph rather than as a tree.     

Embedding complete binary trees in product graphs

This paper shows how to embed complete binary trees in products of complete binary trees, products of shuffle‐exchange graphs, and products of de Bruijn graphs with small dilation and congestion. In the embedding results presented here the size of the host graph can be fixed to an arbitrary size, while we define no bound on the size of the guest graph. This is motivated by the fact that the host architecture has a fixed number of processors due to its physical design, while the guest graph can grow arbitrarily large depending on the application. The results of this paper widen the class of computations that can be performed on these product graphs which are often cited as being low‐cost alternatives for hypercubes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Modeling and prediction of Turkey’s electricity consumption using Artificial Neural Networks

Artificial Neural Networks are proposed to model and predict electricity consumption of Turkey. Multi layer perceptron with backpropagation training algorithm is used as the neural network topology. Tangent-sigmoid and pure-linear transfer functions are selected in the hidden and output layer processing elements, respectively. These input–output network models are a result of relationships that exist among electricity consumption and several other socioeconomic variables. Electricity consumption is modeled as a function of economic indicators such as population, gross national product, imports and exports. It is also modeled using export–import ratio and time input only. Performance comparison among different models is made based on absolute and percentage mean square error. Electricity consumption of Turkey is predicted until 2027 using data from 1975 to 2006 along with other economic indicators. The results show that electricity consumption can be modeled using Artificial Neural Networks, and the models can be used to predict future electricity consumption.     

Effects of instantaneous power-supply failure on the operation of slip-energy recovery drives

Performance analyses of slip energy recovery drives during and at recovery after instantaneous power-supply failure in one or more supply phases have been carried out. Transient slip energy recovery drive currents and voltages under such fault conditions have been obtained theoretically using mathematical models which take into account the three-phase, single-phase, and disconnected power-supply conditions. A detailed set of theoretical and experimental results is given to clarify the expected behavior of the drive under instantaneous power-supply failure of a few cycles duration and at recovery. Insertion of an external bypass resistor into the dc link by the use of a static switch has been discussed to suppress the induced overvoltages and, hence, overcurrents in the rotor windings and converters, after recovery of the supply.     

The use of mixture experiments in tolerance allocation problems

The response surface methodology (RSM) approach can be used to determine the optimal component tolerances in an assembly. Frequently, response surface designs such as Box-Behnken design and central composite design are used in tolerance allocation problems. In this article, mixture experiments, which are essentially constructed for designing a blend composition, are proposed instead of response surface designs in order to observe the cost values. Also some advantages and disadvantages of mixture designs are discussed.