In this paper, we propose an E-voting procedure which, by utilizing the multi-part ballot mode, provides voters an enhanced way to cast and audit their own votes with great anonymity. The proposed scheme, the Multi-part ballot based Name and vOte separaTed E-voting system (M-NOTE), is partially based on our previous works, which have achieved the goal of keeping candidates confidential and voters anonymous, as well as reducing the risk of leaking both candidates' and voters' identities during the ballot distribution phase. In addition, M-NOTE can prevent the possible clash attack in which either malicious authority or hackers could partially manipulate voting results by tampering voters' original ballots. Meanwhile, our performance analysis shows that M-NOTE provides an outstanding secured level, as the possibility of ballot reconstruction and voting result manipulation has been reduced to closer to zero. This E-voting system also illustrates to readers an applicable framework of designing a fair election in the future.

The integration of information and communication technologies with renewable energy sources will upgrade the conventional power distribution network to a Smart Grid, a smart and economic network, which can reduce power loss and carbon footprints. The power distribution network in the Smart Grid can be regarded as composing of multiple microgrids that include the customers, micro-sources and controllers. We propose the Adaptive-Economic Power Distribution Algorithm (AEPDA), which adaptively changes the topology of the distribution network in order to reduce the power transmission distance and maximize the utilization of renewable energy sources. The algorithm works in two operation states: the "online" mode when the microgrids are connected to the main power transmission grids and the "off-line" mode when the microgrids are disconnected from the main grid and are islanded. In the "on-line" mode, the On-Line Economic Microgrids Coalition Algorithm (OLEMCA) can form optimal coalitions among the mirco-grids; in the "off-line" mode, the Off-Line Micro-sources Coalition Algorithm (OLMCA) optimizes the coalitions among the micro-generators in each microgrid. The simulation results demonstrate that the proposed algorithms can reduce the power loss in the "on-line" mode and reduce costs for the customers in the "off-line" mode.

ABSTRACT In this paper, we propose an improved electronic voting (E‐voting) system based on our previous work Name and vOte separaTed E‐voting system. The proposed E‐voting system, referred to as Enhanced Name and vOte separaTed E‐voting system, is improved with a new protocol design and a watchdog hardware device added to ensure voter confidentiality and voting accuracy. In our improved scheme, rather than Election Committee and Vote Counting Committee, an impartial third party, Ballot Distribution Center, is proposed to take the responsibility of distributing ballots. The votes and the candidates' names are separated into two parts while voters cast their votes. The watchdog device records all voting transactions during the election to prevent voting disputes and other malicious behaviors from voter frauds. Our proposed procedure addresses issues related to voter confidentiality and candidate privacy, voting frauds and voting accuracy, and will thus help to create a fair election. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, we will discuss an E-voting procedure by utilizing ring signature. The proposed scheme, RE-NOTE, is based on our previous work E-NOTE and has the benefit of reducing the risk of leaking voters' identities during the ballot distribution procedure. In addition, we will consider the “Clash Attack” which is a simple attack on the verification procedure during an election. Either authority or hackers may use the receipt to manipulate the voting results. We will show how our proposed scheme can mitigate such an attack. Our proposed scheme addresses issues related to both voter's and candidate's confidentiality and verification, and thus provides a framework for fair elections.

This work proposes an automated steering control system for passenger cars. Feasibility of a control strategy based on a front sensor and a Global Positioning System (GPS) has been evaluated using computer simulations. First, the steering angles can be estimated by using the driving data provided by the front sensor and GPS. Second, the road curvature estimator for real-time situation is designed based on its relationship with the steering angle. Third, accurate and real-time estimation of the vehicle's lateral displacements with respect to the road is accomplished. Finally, a closed-loop controller is used to control the lateral dynamics of the vehicle. The proposed estimation and control algorithms are validated by computer simulation results. They show that this lateral steering control system achieves good and robust performance for vehicles to follow a reference path.

In this paper, we propose an E-voting system based on and improved from our previous work (Name and vOte separaTed E-voting system, NOTE). The proposed E-voting system, referred to as Enhanced NOTE (E-NOTE), is enhanced with a new protocol design and watchdog hardware device to ensure voter confidentiality and voting accuracy. In our improved scheme, other than the Election Committee (EC) and Vote Counting Committee (VCC), an impartial third party, Ballot Distribution Center (BDC), is proposed to take the responsibility of distributing ballots. The votes and the candidates' names are separated into two parts when the voters cast their votes. The watchdog device records all voting transactions to prevent voter frauds. Our proposed procedure addresses issues related to voter confidentiality, voter frauds, and voting accuracy, thus providing a framework for fair elections.

The increasing use of intrusion detection system gives rise to a huge volume of alert logs, making it hard for security administrators to uncover hidden attack scenarios. In this paper, we propose a four-layer semantic scheme designed to allow inferring attack scenarios and enabling attack semantic queries. The modified case grammar, PCTCG, is used to convert the raw alerts into machine-understandable uniform alert streams. The 2-atom alert semantic network, 2-AASN are used to generate attack scenario classes. Afterwards, based on the alert context, attack scenario instances are extracted and attack semantic query results on attack scenario instances using spreading activation technique are forwarded to the security administrator.

In recent years, various QoS routing algorithms have been proposed to meet the QoS requirement of today's multimedia applications. These algorithms can be divided into two categories: source routing and distributed routing. In this paper, we propose a novel QoS routing algorithm, which is an integration of source routing and distributed routing. We introduce the concept of "domain" which is a set of neighboring nodes and links. Each node has its own "domain" and has the accurate link-state information within its "domain". When a QoS request probe arrives at a node will use the link-state information within its "domain" to calculate where the probe should be forwarded to and the probe forwarding path. By doing so, the message overhead induced by probe forwarding can be reduced significantly but the overhead induced by link-state information update may increase dramatically. However, if the size of the "domain" is chosen properly according to the network topology, our algorithm can reduce the message overhead while maintaining high request admission ratio.

Reports a new method for optimizing satellite broadcasting schedules based on the Hopfield neural model in combination with the mean field annealing theory. A clamping technique is used with an associative matrix, thus reducing the dimensions of the solution space. A formula for estimating the critical temperature for the mean field annealing procedure is derived, hence enabling the updating of the mean field theory equations to be more economical. Several factors on the numerical implementation of the mean field equations using a straightforward iteration method that may cause divergence are discussed; methods to avoid this kind of divergence are also proposed. Excellent results are consistently found for problems of various sizes.

The problem of multiprocessor scheduling can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. This scheduling problem is known to be NP-hard, and methods based on heuristic search have been proposed to obtain optimal and suboptimal solutions. Genetic algorithms have recently received much attention as a class of robust stochastic search algorithms for various optimization problems. In this paper, an efficient method based on genetic algorithms is developed to solve the multiprocessor scheduling problem. The representation of the search node is based on the order of the tasks being executed in each individual processor. The genetic operator proposed is based on the precedence relations between the tasks in the task graph. Simulation results comparing the proposed genetic algorithm, the list scheduling algorithm, and the optimal schedule using random task graphs, and a robot inverse dynamics computational task graph are presented.>

This article addresses the path-planning problem for a mobile manipulator system that is used to perform a sequence of tasks specified by locations and minimum oriented force capabilities. The problem is to find an optimal sequence of base positions and manipulator configurations for performing a sequence of tasks given a series of task specifications. The formulation of the problem is nonlinear. The feasible regions for the problem are nonconvex and unconnected. Genetic algorithms applied to such problems appear to be very promising while traditional optimization methods cause difficulties. Computer simulations are carried out on a three-degrees-of-freedom manipulator mounted on a two-degrees-of-freedom mobile base to search for the near optimal path-planning solution for performing the sequence of tasks. © 1994 John Wiley & Sons, Inc.

The problem of scheduling an inverse dynamics computation consisting of m computational modules to be executed on a multiprocessor system consisting of p identical homogeneous processors to achieve a minimum-scheduled length is presented. To achieve the minimum computation time, the Newton-Euler equations of motion are expressed in the homogeneous linear recurrence form, which results in achieving maximum parallelism. To speed up the searching for a solution, a heuristic search algorithm called dynamical highest level first/most immediate successors first (DHLF/MISF) is proposed to find a fast but suboptimal schedule. For an optimal schedule, the minimum-scheduled-length problem can be solved by a state-space search method. An objective function is defined in terms of the task execution time, and the optimization of the objective function is based on the minimax of the execution time. The proposed optimization algorithm solves the minimum-scheduled-length problem in pseudopolynomial time and can be used to solve various large-scale problems in a reasonable time.>

An approach that utilizes the geometric information about the mating parts in generating and synthesizing the C-frame and the compliance-selection vector which are needed at every sampling instant for hybrid position/force control scheme in an insertion task, is presented. A geometric modeling system is used to model the mating objects involved in the insertion task. From the geometric model of the objects and the nominal position-trajectory of the task, a set of cut-planes of the mating objects perpendicular to the insertion direction can be obtained. Due to the uncertainties inherent in working with real-world objects, and the limited position accuracy of the manipulator, an uncertainty model is incorporated into the cut-planes to reflect the position and orientation uncertainties of the C-frame. This approach reduces a difficult three-dimensional problem into a set of two-dimensional problems and will successfully complete the task even in the presence of position and orientation uncertainties.>

The problem of scheduling the robot inverse dynamics computation consisting of m computational modules to be executed on a multiprocessor system consisting of p identical homogeneous processors to achieve a minimum-schedule length is examined. This scheduling problem is known to be NP-complete. To achieve the minimum computation time, the Newton-Euler equations of motion are expressed in the homogeneous linear recurrence form that results in achieving maximum parallelism. To speed up the searching for a solution, a heuristic search algorithm called dynamical highest-level-first/most-immediate-successors-first (DHLF/MISF) is proposed to find a fast but suboptimal schedule. For an optimal schedule the minimum-schedule-length problem can be solved by a state-space search method, the A* algorithm coupled with an efficient heuristic function derived from the Fernandez and Bussell bound.>