Application of Waste Elimination Theory in Production Processes at Balikpapan Shipyard

The shipbuilding industry also supports the economic sector in Balikpapan. Shipbuilding industry business generally consists of new building and ship repair. There is a shipyard in Balikpapan that already has experience in making landing craft tanks, tugboats and barges. But according to the head of production, this shipyard often experiences delays in the production process. Based on temporary assumptions, this happens due to correction and re-works waste. This study aims to find the initial causes of waste that occur, and try to prevent it. Prevention from the initial cause, is a meaningful innovation. This study uses the fault tree analysis (FTA) method as a modeling of the root causes; and waste management theory is used as the basis for the science of innovation application. The research objective is to increase shipyard productivity. Based on research there are five top events that cause delays in the production process at Balikpapan shipyard, they are work not done; incorrect raw material specifications; incorrect product specifications; changes by surveyor owner; and not yet approved by the class.

AMulet 2.0 for Verifying Multiplier Circuits

AMulet 2.0 is a fully automatic tool for the verification of integer multipliers using computer algebra. Our tool models multiplier circuits given as and-inverter graphs as a set of polynomials and applies preprocessing techniques based on elimination theory of Gröbner bases. Finally it uses a polynomial reduction algorithm to verify the correctness of the given circuit. AMulet 2.0 is a re-factorization and improved re-implementation of our previous multiplier verification tool AMulet 1.0.

On maps which preserve semipositivity and quantifier elimination theory for real numbers

Assume that [Formula: see text] is a superoperator which preserves hermiticity. We give an algorithm determining whether [Formula: see text] preserves semipositivity (we call [Formula: see text] positive in this case). Our approach to the problem has a model-theoretic nature, namely, we apply techniques of quantifier elimination theory for real numbers. An approach based on these techniques seems to be the only one that allows to decide whether an arbitrary hermiticity-preserving [Formula: see text] is positive. Before we go to detailed analysis of the problem, we argue that quantifier elimination for real numbers (and also for complex numbers) can play a significant role in quantum information theory and other areas as well.

Terminal Position and Orientation Coupling in Lower Mobility Robots

The kinematics has attracted continuous interests in the field of robotics. Terminal position and orientation coupling phenomenon is the key problem and the first consideration in the kinematics of lower mobility robots. However, this property was usually neglected or has not been well solved. This paper discusses the terminal position and orientation coupling issues in lower mobility robots, especially for the lower mobility hybrid robots. First, this paper reveals the terminal position and orientation coupling in serial and parallel robots. Then, based on elimination theory, an approach for establishing the terminal position and orientation coupling equations for hybrid robots is proposed, which is illustrated in detail by the (3-RPS) + (RR) and (3-RPS) + (3-RCR) hybrid robots. The results show that the hybrid robots have highly nonlinear terminal position and orientation coupling relations, which are more complicated than serial and parallel robots. The research of this paper is valuable in kinematics modeling of robots.

Bounded, Multidimensional, Integrated Memetic Evolution for Character Recognition Based on Predictive Elimination Theory and Optimization Techniques

This article describes how inspired by the natural process of evolution in genetic algorithms, memetic algorithms (MAs) are a category of cultural evolution phenomenon. The very concept of MA has been discussed in the last few years and is adding newer dimensions to MA and computational skills of algorithms. There are many optimization algorithms which fully exploit the problem under consideration. This article presents a heuristic approach for an improvised algorithm which takes into consideration various optimization parameters in isolation and tries to integrate the self-learning technique of MA. A general structure of MA according to this article should be perfectly in-line with brain activities which are neurotically tested and given maximum emphasis on local search and context-based predictive approaches rather than mathematically computing every event and taking or picking solutions based on results of certain formula. This article goes one step beyond the conventional set of the variety of problem domains, ranging from discrete optimization, continuous optimization, constrained optimization and multi objective optimization in which MAs have been successfully implemented. These optimization techniques must be processed using outcomes of predictive optimization and using a method of elimination to make the search set smaller and smaller as we progress deeper into the search. There is a scarcity of literature and also lack of availability of comprehensive reviews on MAs. The proposed technique is a better approach for solving combinatorial optimization problems. This article gives an overview of various domains and problem types in which MA can be used. Apart from this, the problem of character recognition using predictive optimization and implementation of elimination theory MA is discussed.