Finding a delivery plan for cancer radiation treatment using multileaf collimators operating in “step-and-shoot” mode can be formulated mathematically as a problem of decomposing an integer matrix into a weighted sum of binary matrices having the consecutive-ones property and sometimes other properties related to the collimator technology. The efficiency of the delivery plan is measured by both the sum of the weights in the decomposition, known as the total beam-on time, and the number of different binary matrices appearing in it, referred to as the cardinality, the latter being closely related to the setup time of the treatment. In practice, the total beam-on time is usually restricted to its minimum possible value (which is easy to find), and a decomposition that minimizes cardinality (subject to this restriction) is sought. This decomposition problem is known to be NP-hard, and the best available exact solution methods cannot solve, in reasonable time, problems with dimensions large enough to be of use in actual medical applications. In this paper, we propose a new heuristic. To ensure that the heuristic is computationally efficient, we make use of exact bounds that apply to the decomposition and prove that these bounds can be computed efficiently. We demonstrate that the heuristic performs very well numerically against the best previously published heuristic (that of Kalinowski), reducing the average gap between the cardinality of the solution found and the optimal value by 37% on the largest problems tested (for which optimal solutions could be found). Importantly, this new heuristic performs well on those instances that are problematical for Kalinowski's heuristic. A “best-of” algorithm, combining heuristics, produces a decomposition with cardinality within one of optimal in about 98.7% of instances tested (for which an optimal solution is available). It reduces the cardinality of solutions produced by about 5% on average. On instances for which optimal solutions can be found, it more than halves the optimality gap and finds an optimal solution in about 28% more cases than Kalinowski's heuristic.

Wireless data services are expected to see in the forth generation (4G) network the same growth in demand that Internet services and wireless voice services have seen in recent years. This paper presents twofold purposes. The former, an architecture for heterogeneous networks that relies on mobile stream control transmission protocol to reach mobility value added services. The latter purpose is aiming to probe an investigation of a mathematical optimization of handover decision to ensure a seamless vertical handover over heterogeneous environment. The simulation of the multi-streaming feature of mobile stream control transmission protocol has shown the effect on reducing latency while users are moving through various networks.

An objective methodology for the specification and synthesis of communicating processes is presented. It is demonstrated that algebraic operators can be used to formulate communicating processes in terms of behavioral constraints and that the corresponding state-machine-type process descriptions can be derived automatically or synthesized from these formulations. The behavioral constraints serve as high-level specifications for communicating processes. These constraints indicate the desired behavior of a process, possibly embedded in a system, by defining its range. The proposed approach is shown to be applicable to a common problem which concerns the synthesis of the central module serving a number of clients in a specific distributed system configuration.>

This paper describes the capabilities and design of a new digital video system which permits a user to record and playback sequences, up to 80 s long, of digitized color television signal. In addition, a user may process the stored video via the associated computer and view the results. The above system, which is called the DVS (Digital Video Store), is intended as a simulation tool for investigating the effects of various video coding and processing algorithms.