Using pliers in assembly work: short and long task duration effects of gloves on hand performance capabilities and subjective assessments of discomfort and ease of tool manipulation

The present study investigated the effects of wearing typical industrial gloves on hand performance capabilities (muscle activity, wrist posture, touch sensitivity, hand grip and forearm torque strength) and subjective assessments for an extended duration of performing a common assembly task, wire tying with pliers, which requires a combination of manipulation and force exertion. Three commercially available gloves (cotton, nylon and nitrile gloves) were tested and compared with a bare hand condition while participants performed the simulated assembly task for 2 h. The results showed that wearing gloves significantly increased the muscle activity, wrist deviation, and discomfort whilst reducing hand grip strength, forearm torque strength and touch sensitivity. The combined results showed that the length of time for which gloves are worn does affect hand performance capability and that gloves need to be evaluated in a realistic working context. The results are discussed in terms of selection of gloves for industrial assembly tasks involving pliers.     

Municipal wastewater treatment by biofiltration: comparisons of various treatment layouts. Part 1: assessment of carbon and nitrogen removal

One of the largest wastewater treatment plants in the Paris conurbation (240,000 m(3)/d) has been studied over several years in order to provide technical and economical information about biological treatment by biofiltration. Biofiltration systems are processes in which carbon and nitrogen pollution of wastewater are treated by ascendant flow through immersed fixed cultures. This paper, focused on technical information, aims: (1) to compare performances of the three biological treatment layouts currently used in biofiltration systems: upstream denitrification (UD), downstream denitrification (DD) and combined upstream-downstream denitrification (U-DD) layouts; and (2) to describe in detail each treatment step. Our study has shown that more than 90% of the carbon and ammoniacal pollution is removed during biological treatment, whatever the layout used. Nitrate, produced during nitrification, is then reduced to atmospheric nitrogen. This reduction is more extensive when the denitrification stage occurs downstream from the treatment (DD layout with methanol addition), whereas it is only partial when it is inserted upstream from the treatment (UD layout - use of endogenous carbonaceous substrate). So, the UD layout leads to a nitrate concentration that exceeds the regulatory threshold in the effluent, and the treatment must be supplemented with a post-denitrification step (U-DD layout). Our work has also shown that the optimal ammonium-loading rate is about 1.1-1.2 kg N-NH(4)(+) per m(3) media (polystyrene) and day. For denitrification, the optimal nitrate-loading rate is about 2.5 kg N per m(3) media (expanded clay) and day in the case of DD with methanol, and is about 0.25 kg N-NO(3)(-) per m(3) media and day in the case of UD with exogenous carbonaceous substrate.     

A framework for improving e-commerce websites usability using a hybrid genetic algorithm and neural network system

An ever-increasing use of Internet has greatly been affecting the importance of e-commerce websites. As such, analyzing those websites and discovering customers’ purchasing power, the present study tends to propose a framework and an appropriate structure to make the websites more flexible and highly functional. Such an efficient and effective framework facilitates customers’ purchasing capacities. In this framework, different techniques and methods including the genetic algorithm, neural networks, and collaborative filtering are utilized. The pre- and post-execution data show that the proposed framework changes the website structure based on the two criteria, i.e., sales conversion rate and average pre-purchase page views and finally leading to improved website usability.     

Distortion in diffraction tomography caused by multiple scattering

In this paper, we have first presented a new computational procedure for the calculation of the "true" forward scattered fields of a multicomponent object. By "true" we mean fields that are not limited by the first-order approximations, such as those used in the first-order Born and Rytov calculations. Although the results shown will only include the second-order fields for a multicomponent object, the computational procedure can easily be generalized for higher order scattering effects. Using this procedure we have shown by computer simulation that even when each component of a two-component object is weakly scattering, the multiple scattering effects become important when the components are blocking each other. We have further shown that when strongly scattering components that are large compared to a wavelength are not blocking each other, the scattering effects can be ignored. Both these conclusions agree with intuitive reasoning. Since all the currently available diffraction tomography algorithms are based on the assumption that the object satisfies the first-order scattering assumption, it is interesting to test them under conditions when this assumption is violated. We have used the scattered fields obtained with the new computational procedure to test these algorithms, and shown the resulting artifacts. Our main conclusion drawn from this computer simulation study is that even when object inhomogeneities are as small as 5 percent of the background, multiple scattering can introduce severe distortions in multicomponent objects.     

Distributed fault detection for interconnected second-order systems

In this paper, the existence of unknown input observers for networks of interconnected second-order linear time invariant systems is studied. Two classes of distributed control systems of large practical relevance are considered. It is proved that for these systems, one can construct a bank of unknown input observers, and use them to detect and isolate faults in the network. The result presents a distributed implementation. In particular, by exploiting the system structure, this work provides further insight into the design of UIO for networked systems. Moreover, the importance of certain network measurements is shown. Infeasibility results with respect to available measurements and faults are also provided, as well as methods to remove faulty agents from the network. Applications to power networks and robotic formations are presented. It is shown how the developed methodology apply to a power network described by the swing equation with a faulty bus. For a multi-robot system, it is illustrated how a faulty robot can be detected and removed.     

Abnormal condition detection in a cement rotary kiln with system identification methods

In this paper, we use system identification methods for abnormal condition detection in a cement rotary kiln. After selecting proper inputs and output, an input–output model is identified for the plant’s normal conditions. A novel approach is used in order to estimate the delays of the input channels of the kiln before identification part. This method eases the identification since with determining the input channels delays, the dimension of search space in the identification part reduces. Afterward, to identify the kiln’s model, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOcally LInear MOdel Tree (LOLIMOT) algorithm which is an incremental tree-structure algorithm. Finally, with the model for normal condition of the kiln, the incident of abnormalities in output are detected based on the length of duration and magnitude of difference between the real output and model’s output. We distinguished three abnormal conditions in the kiln, two of which are known as common abnormal conditions and another one which was not characteristically known for cement experts either.     

An experimental search-based approach to cohesion metric evaluation

In spite of several decades of software metrics research and practice, there is little understanding of how software metrics relate to one another, nor is there any established methodology for comparing them. We propose a novel experimental technique, based on search-based refactoring, to ‘animate’ metrics and observe their behaviour in a practical setting. Our aim is to promote metrics to the level of active, opinionated objects that can be compared experimentally to uncover where they conflict, and to understand better the underlying cause of the conflict. Our experimental approaches include semi-random refactoring, refactoring for increased metric agreement/disagreement, refactoring to increase/decrease the gap between a pair of metrics, and targeted hypothesis testing. We apply our approach to five popular cohesion metrics using ten real-world Java systems, involving 330,000 lines of code and the application of over 78,000 refactorings. Our results demonstrate that cohesion metrics disagree with each other in a remarkable 55 % of cases, that Low-level Similarity-based Class Cohesion (LSCC) is the best representative of the set of metrics we investigate while Sensitive Class Cohesion (SCOM) is the least representative, and we discover several hitherto unknown differences between the examined metrics. We also use our approach to investigate the impact of including inheritance in a cohesion metric definition and find that doing so dramatically changes the metric.     

Developing a New Integrated Bi-Objective Model for Buffer and Process Time Optimization Problem using Optimization via Simulation Approach

The cost of semi-finished products storage and processing time are two issues affecting the rate of manufacturing in all production systems. The acceleration in production time is usually associated with the increase of costs and lack of appropriate allocation of the production line buffers imposing production costs and increase in delivery time and decrease in productivity. Many previous studies have focused on deterministic production systems using mathematical programming models. Moreover, the optimization of buffers and processing times with stochastic events has not been considered simultaneously. In this study, a new simulation-based optimization model has been proposed to address the modeling and solving of buffer and processing time optimization problem in a stochastic environment. The real world problem has been modeled by using the simulation technique and the model replicated by a design of experiment method. The results were used to build a meta-model of regression for the objective functions and finally, a new mathematical model was solved by a multiobjective Genetic Algorithm. The results of this research show that the proposed approach has efficient solutions and could be easily applied to real world problems.     

Study of generalized delay-timers in alarm configuration

In process plants, alarms are configured to notify operators of any abnormalities or faults. However, in practice a majority of raised alarms are false or nuisance and create problems for operators as they face an increasing number of alarms to handle. Adding delay-timers is a simple technique that can reduce this problem and is widely exercised in industry. In this work we propose a generalized delay-timer framework where instead of consecutive n samples in the conventional case, n₁ out of n consecutive samples (n₁ ≤ n) are considered to raise an alarm. For the generalized delay-timer, three important performance indices, namely, the false alarm rate (FAR), the missed alarm rate (MAR) and the expected detection delay (EDD), are calculated using Markov processes. Moreover, the performance and sensitivity of generalized delay-timers are compared with conventional delay-timers.     

Solid-state supercapacitor based on breath figured polymethyl methacrylate deposited by graphene: the effect of electrode surface

Solid-state supercapacitors are fabricated using transparent polymethyl methacrylate (PMMA) films decorated by breath figures BF, as an electrode and polyvinyl alcohol (PVA)-H₂SO₄ as an electrolyte. The holes on the surface of the transparent PMMA created by BF method have diameters of 0.5–10 μm. Graphene is deposited by spray coating using a dispersion mixture of graphene layers. The fabricated electrodes were characterized by cyclic voltammetry (CV), galvanostatic charge–discharge, electrochemical impedance spectroscopy, charge stability and life time for evaluating their supercapacitance performance. From CV data at 5 mV/s scan rate, high specific capacitance equal to 344 for BFPMMA/G F/g and, 45 F/g for PMMA/G has been measured. By the same way, energy densities have been measured as 430 and 56.25 Wh/kg for the mentioned electrodes, respectively.