Search results

The purpose of this paper is to conduct a comprehensive review on the implementation and the effect of Japan's Stress Check Program, a national program to monitor and control workplace psychosocial factors that was initiated in December 2015.

We comprehensively reviewed articles published in Japanese and English, assessed the performance of the Stress Check Program and summarized future challenges. We also discussed the implications for practice.

The available literature presented a scientific basis for the efficiency and validity of predictions using the Brief Job Stress Questionnaire, which is the instrument recommended to screen workers with high stress in the program. No study has verified the effect of the program on workers' mental health by using group analysis of stress check results. There is room for improvement in tools that contribute to identifying workers with high stress and in measures for improving the work environment. The Stress Check Program contrasts with risk management of psychosocial factors at work, widely adopted in European countries as a strategy for improving workers' mental health by focussing on the psychosocial work environment.

Although the effectiveness of the Japanese program needs further evaluation, future developments of the program would provide insight for national policies on psychosocial risks/psychosocial stress at work.

This paper is the first systematic review on the implementation and effects of Japan's Stress Check Program.

This paper deals with the discrimination problem of the states which involve two types of uncertainty: “randomness” and “fuzziness.” This problem is very important in the fields of soft science such as management science, sociology, eta, since the object of discrimination involves these types of uncertainty. In this paper, we propose a discrimination system of fuzzy states on a probability space and derive the decision rule which minimizes the average of error probability of discrimination. In our formulation of the discrimination system there exists the case that a large number of observations does not necessarily make the average of error probability small, so that an index for decision of an upper limit of number of observations is also derived.

The aim of this paper is to implement direct teaching of industrial manipulators using current sensors. The traditional way to implement teaching is either to use a teaching pedant, which is time consuming, or use force sensors, which increases system cost. To overcome these disadvantages, a novel method is explored in the paper by using current sensors installed at joints as torque observers.

The method uses current sensors installed at each joint of a manipulator as torque observers and estimates external forces from differences between joint-driven torque computed based on the values of current sensors and commanded values of motor-driven torque. The joint-driven torque is computed by cancelling out both pre-calibrated gravity and friction resistance (compensation). Also, to make the method robust, the paper presents a strategy to detect unexpected slowly drifts and zero external forces and stop the robot in those situations.

Experimental results demonstrated that compensating the joint torques using both pre-calibrated gravity and friction resistance has performance comparable to a force sensor installed on the end effector of a manipulator. It is possible to implement satisfying direct teaching without using force sensors on 7 degree of freedom manipulators with large mass and friction resistance.

The main contribution of the paper is that the authors cancel out both pre-calibrated gravity and friction resistance to improve the direct teaching using only current sensors; they develop methods to avoid unsafe situations like slow drifts. The method will benefit industrial manipulators, especially those with large mass and friction resistance, to realize flexible and reliable direct teaching.

Although the decision‐making problem at the lower level is generally well‐defined, the decision‐making problem at the higher level would not contain the detail. Much of decision‐making at the higher level might take place in a fuzzy environment, so that it is only necessary to decide roughly what actions, what states and what parameters should be considered. This paper deals with the higher level problem in which we can regard the elements‐states of nature, feasible actions and available information‐as fuzzy objects. Since the uncertainty of meaning of objects is represented by the fuzzy sets and the uncertainty of occurrence of objects is defined by the probability, a specific formulation of the higher level decision problem can be defined by the probability of fuzzy events. From the same aspect, the definitions of worth, entropy and quantity concerning fuzzy information are given in this paper, and we have tried to extend some of the statistical decision theory to the fuzzy decision problem. To explain our formulation, an investment problem is presented as an example.

A wire matrix has been developed for mounting LED dot matrix displays whereby insulated wires are ‘woven’ to produce a matrix that is fixed on an aluminium board with epoxy adhesive. This monolayer woven wire board simplifies the fabrication process of the display board while at the same time showing more than double the heat dissipation of conventional insulated aluminium printed circuit boards and five times that of conventional glass epoxy printed circuit boards when mounted with bare LED chips. In addition, it is suitable for high‐density and high‐brightness LED dot matrix displays.

The decision rule which minimizes the probability of error, in the discrimination problem, is the Bayes decision rule which assigns x to the class with the highest a posteriori probability. This rule leads to a partial probability of error which is given by Pe(x) = 1−max p(C2lx) for each x e X. Prior to observing X, the probability of error associated with X is defined as Pe = EX [Pe(x)]. Tanaka, Okuda and Asai formulated the discrimination problem with fuzzy classes and fuzzy information using the probability of fuzzy events and derived a bound for the average error probability, when the decision in the classifier is made according to the fuzzified Bayes method. The aim is to obtain bounds for the average error probability in terms of (αβ)‐information energy, when the decision in the classifier is made according to the fuzzified Bayes method.

This paper aims to deal with the design of new hybrid approach for the assistance of the flexion extension movement of the knee joint.

The control approach combines the use of a knee joint orthosis along with functional electrical stimulation (FES) within an assist-as-needed paradigm. An active impedance controller is used to assist the generation of muscular stimulation patterns during the extension sub-phase of the knee joint movement. The generated FES patterns are appropriately tailored to achieve flexion/extension movement of the knee joint, which allows providing the required assistance by the subject through muscular stimulation. The generated torque through stimulation is tracked by a non-linear disturbance observer and fed to the impedance controller to generate the desired trajectory that will be tracked using a standard proportional derivative controller.

The approach was tested in experiments with two healthy subjects. Results show satisfactory performances in terms of estimating the knee joint torque, as well as in terms of cooperation between the FES and the orthosis actuator during the execution of the knee joint flexion/extension movements.

The authors designed a new hybrid approach for the assistance of the flexion extension movement of the knee joint, which has not been studied yet. The control approach combines the use of a knee joint orthosis along with FES within an assist-as-needed paradigm.

This study aims to evaluate the melting process of the phase-change RT-35 material in a shell and tube heat exchanger saturated with a porous medium. Titanium porous media with isotropic and inhomogeneous structures are studied. The considered tubes in the shell and tube exchanger are made of copper with specific thicknesses. The phase-change material has a non-Newtonian behavior and follows the endorsed Carreau–Yasuda Model.

The enthalpy–porosity method is used for modeling of the melting process. The governing equations were transferred to their dimensionless forms. Finally, the equations are solved by applying the Galerkin finite element method.

The findings for different values of the relative permeability (K*) and permeability deviation angle (λ) are represented in the forms of charts, streamlines and constant temperature contours. The considerable effects of the relative permeability (K*) and deviation angle (λ) on the flow line patterns of the melting phase-change material are some of the significant achievements of this works.

This study was conducted using data from relevant research articles provided by reputable academic sources. The data included in this manuscript have not been published previously and are not under consideration by any other journal.