This study aims to formulate a relationship between total perceived discomfort (TPD) and six joint moments { shoulder, elbow, L5/S1, hip, knee, and ankle. We conducted a manual material handling experiment with varying holding points and load amplitudes and measured joint angles and subjective TPD. Furthermore,joint moments were calculated from the measured joint angles. Three approximation models { sum, maximum,and square sum { were compared in terms of TPD prediction accuracy, and the sum model was selected as the TPD function because its average error was lowest. Individually approximated TPD functions for males and females did not show improved accuracy compared with the TPD function for both genders. Therefore,a single TPD function was applied irrespective of gender. The correlation coefficient between measured and predicted TPD functions was compared to those of four observational methods { OWAS, RULA, REBA, and NIOSH lifting equation; that of the proposed TPD function was the highest.

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Japanese companies offering plant maintenance services often employ workers from Asian neighbors. Those workers receive practical skill training at training centers before being dispatched to the various plants where they actually work. This paper proposes a method and a system for providing those workers with the practical skill training. The system judges progress in the work from the images of the facilities to be maintained and gives step-by-step instructions to the workers in accordance with the progress in the work. The system employs the client-server architecture of processing. A client displays operation manuals to the workers nearest to the facilities. The server judges the progress in the maintenance work and combines all the data for the practical skill training. In this paper the validity of the method is verified by a trial operation and discussed from the standpoint of the processing time and the determination of the progress in the work.

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The traditional da-industrial salt supply chains in China cannot match supply and demand very well because of demand uncertainty, which causes huge losses to salt making enterprises and also inŽuences the performance of the whole supply chain. How to deal with the demand uncertainty to improve the performance of the supply chain is an important subject for the da-industrial salt supply chain. In this paper, we introduce the traditional da-industrial salt supply chains in China and analyse the main problems in the operation mode as follows. One problem is that the traditional operations mode in da-industrial salt supply chains impacts the performance of the whole supply chain. The other one is that the high demand uncertainty brings damage and huge losses to the supply chain. To solve these problems, we propose supply contracts with options in da-industrial salt supply chains in China. Purchasing options enables the salt using enterprise to gain Žexibility in the order decision-making, and to reduce forecasting error by further collecting demand information. For the salt making enterprise, she can be compensated from the revenue obtained from the options.

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Mathematical approaches for solving product designs problem can be used by not only elder designers who have implicit/ambiguous knowledge of design experienced, but also younger designers even they have not so much experience, because such mathematical methods lead designers to obtain an optimal design automatically. However, there is a very serious lake to use such optimal methods in practice where the optimal solution has been obtained by a set of given coefficient parameters, which are so hard to be fixed accurately by even those most-experienced designers. In this paper,a set of simultaneous equations is built to represent the relations between product designs and correlative category labels. Parameter estimation is to fix the parameters that making all of relations to be feasible. A Boltzmann machine algorithm with belief propagation is used to perform the parameter estimation, where the number of simultaneous equations may be less than the number of parameters, to be solved possibly. Numerical experiments are provided to show the efficiency and utility of the algorithm. As a result, the value of training error is approaching to 0 slowly and stably, so it can be foresaw that parameters are estimated.

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Many network systems have been applied extensively in the real world, for example, a route guiding system and an optimal path of a network connection to Internet services. Many papers have dealt with networks with two specific nodes. Each edge has criteria, for example distances, costs, and the time required. The optimal path problem aims to obtain the particular path that has a minimum value of criteria. In this paper, we consider the optimal path problem for a three-objective network. In a multi-objective network, edges have two or more criteria. Few cases exist where multi-criteria are optimized at the same time. Thus, it is worth obtaining Pareto solutions as optimal paths in multi-objective networks. An extended Dijkstra's algorithm was proposed to obtain Pareto solutions of two- and threeobjective networks. Even if we use this existing algorithm, obtaining optimal paths is difficult in large networks that have many nodes. Therefore, more efficient algorithms than the extended Dijkstra's algorithm were proposed. However, these algorithms cannot obtain all Pareto solutions. Thus, an efficient and exact algorithm that can obtain all Pareto solutions is required. We describe an essential and effective idea in reducing search space. Using this idea, our algorithms can set bounds to search within less space than the extended Dijkstra's algorithm and obtain all Pareto solutions. For evaluating the algorithms, we conducted numerical experiments. As a result, we show our algorithms are more efficient than the extended Dijkstra's algorithm.

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