Workload control in job shops with re-entrant flows: an assessment by simulation

One of the key functions of Workload Control is order release. Jobs are not released immediately onto the shop floor – they are withheld and selectively released to create a mix of jobs that keeps work-in-process within limits and meet due dates. A recent implementation of Workload Control’s release method highlighted an important issue thus far overlooked by research: How to accommodate re-entrant flows, whereby a station is visited multiple times by the same job? We present the first study to compare the performance of Workload Control both with and without re-entrant flows. Simulation results from a job shop model highlight two important aspects: (i) re-entrant flows increase variability in the work arriving at a station, leading to a direct detrimental effect on performance; (ii) re-entrant flows affect the release decision-making process since the load contribution of all visits by a job to a station has to fit within the norm. Both aspects have implications for practice and our interpretation of previous research since: (i) parameters given for work arriving may significantly differ from those realised; (ii) increased workload contributions at release mean that prior simulations may have been unstable, leading to some jobs never being released.     

Magnetic Properties of Thermal Sprayed Tungsten Carbide–Cobalt Coatings

In the information age, the storage and accessibility of data is of vital importance. There are several possibilities to fulfill this task. Magnetic storage of data is a well‐established method and the range of materials used is continuously extended. In this study, the magnetic remanence of thermally sprayed tungsten carbide–cobalt (WCCo)‐coatings in dependence of their thickness is examined. Two magnetic fields differing in value and geometry are imprinted into the coatings and the resulting remanence field is measured. It is found that there are two effects, which in combination determine the effective value of the magnetic remanence usable for magnetic data storage.

     

Electrochemical Behavior of Single CuO Nanoparticles: Implications for the Assessment of their Environmental Fate

The electrochemical behavior of copper oxide nanoparticles is investigated at both the single particle and at the ensemble level in neutral aqueous solutions through the electrode‐particle collision method and cyclic voltammetry, respectively. The influence of Cl^? and NO₃^? anions on the electrochemical processes occurring at the nanoparticles is further evaluated. The electroactivity of CuO nanoparticles is found to differ between the two types of experiments. At the single‐particle scale, the reduction of the CuO nanoparticles proceeds to a higher extent in the presence of chloride ion than of nitrate ion containing solutions. However, at the multiparticle scale the CuO reduction proceeds to the same extent regardless of the type of anions present in solution. The implications for assessing realistically the environmental fate and therefore the toxicity of metal‐based nanoparticles in general, and copper‐based nanoparticles in particular, are discussed.     

Expression of NHE1 and NHE4 in rat pancreatic zymogen granule membranes

We previously characterized a Na+/H+ exchange activity in rat pancreatic zymogen granules [Anderie, I., and Thévenod, F. (1996) J. Membrane Biol, 152, 195-205]. Here we have identified the Na+/H+ exchanger (NHE) isoforms present in zymogen granules by functional studies with NHE inhibitors. The NHE1 specific blocker HOE 694 [3-(methylsulfonyl-4-piperidino-benzoyl)-guanidine methanesulfonate] inhibited zymogen granule Na+/H+ exchange in a concentration dependent manner, maximally to 53 +/- 5% of controls at 100nM. The remaining Na+/H+ exchange activity was inhibitable by EIPA [5-(N-ethyl-N-isopropyl)amiloride] (EC50 approximately 25 microM) or benzamil (EC50 approximately 100 microM). Amiloride inhibited weakly suggesting that "amiloride-resistant" and "amiloride-sensitive" NHE are expressed in zymogen granules. cDNA sequences encoding NHE1- and NHE4-specific transmembrane domains were detected by RT-PCR in rat pancreatic tissue and in the rat pancreatic acinar cell line AR4-2J. The presence of NHE1 and NHE4 in zymogen granule membranes was confirmed by immunoblots of zymogen granule membranes and by pre-embedding immunogold labeling of purified rat pancreatic zymogen granules with polyclonal NHE1 and NHE4 antibodies. Therefore, we propose that NHE1 and NHE4 are expressed in zymogen granule membranes of rat exocrine pancreas.     

An Adaptive Neuro-fuzzy Inference System for Robot Handling Fabrics with Curved Edges towards Sewing

This paper presents the design of a neuro-fuzzy visual servoing controller for robot guiding fabrics with curved edges towards sewing. Fabrics comprising real cloths consist of curved edges of arbitrary curvatures that can not be standardized. To overcome this difficulty, the idea is to train the robot sewing system and to apply this methodology in a real-time operation environment. The proposed approach for robot sewing is based on visual servoing and a learning technique that combines neural networks and fuzzy logic. A novel genetic-oriented clustering method is used to construct the initial FIS models and then, adaptive neuro-fuzzy inference systems allow tuning them so that it is possible to obtain better estimates. Extensive experiments were carried out in order to build data sets using fabrics with curved edges of various curvatures. The proposed model is validated using fabrics that had not been included in the training process and the results demonstrate that the proposed approach is efficient and effective for robot guiding fabrics with arbitrary curved edges towards sewing.     

On the discovery of subsumption relations for the alignment of ontologies

For the effective alignment of ontologies, the subsumption mappings between the elements of the source and target ontologies play a crucial role, as much as equivalence mappings do. This paper presents the “Classification-Based Learning of Subsumption Relations” (CSR) method for the alignment of ontologies. Given a pair of two ontologies, the objective of CSR is to learn patterns of features that provide evidence for the subsumption relation among concepts, and thus, decide whether a pair of concepts from these ontologies is related via a subsumption relation. This is achieved by means of a classification task, using state of the art supervised machine learning methods. The paper describes thoroughly the method, provides experimental results over an extended version of benchmarking series of both artificially created and real world cases, and discusses the potential of the method.     

Filling of very deep, wide trenches by BenzoCycloButene polymer

A process for deep trench filling by BenzoCycloButene (BCB) polymer is explored. Deep trenches with 100-μm depth and different aspect ratios from 1.4 to 20 have been successfully filled by BCB. Besides, chemical mechanical polishing (CMP) of BCB is studied with the main goals of smoothing surface topography of substrate after BCB filling and removing excess BCB coating which may be necessary in some applications. Removal rate for BCB, V _RR, of about 0.24 μm/min has been achieved for hard cured BCB films using acid slurry. After CMP, the BCB layer showed a roughness of about 1.36 nm (Rq, measured by atomic force microscopy, AFM).     

2D/3D image registration on the GPU

We present a method that performs a rigid 2D/3D image registration efficiently on the Graphical Processing Unit (GPU). As one main contribution of this paper, we propose an efficient method for generating realistic DRRs that are visually similar to x-ray images. Therefore, we model some of the electronic post-processes of current x-ray C-arm-systems. As another main contribution, the GPU is used to compute eight intensity-based similarity measures between the DRR and the x-ray image in parallel. A combination of these eight similarity measures is used as a new similarity measure for the optimization. We evaluated the performance and the precision of our 2D/3D image registration algorithm using two phantom models. Compared to a CPU + GPU algorithm, which calculates the similarity measures on the CPU, our GPU algorithm is between three and six times faster. In contrast to single similarity measures, our new similarity measure achieved precise and robust registration results for both phantom models.     

Evaluation of six night vision enhancement systems: qualitative and quantitative support for intelligent image processing

OBJECTIVE: An evaluation study was conducted to answer the question of which system properties of night vision enhancement systems (NVESs) provide a benefit for drivers without increasing their workload. BACKGROUND: Different infrared sensor, image processing, and display technologies can be integrated into an NVES to support nighttime driving. Because each of these components has its specific strengths and weaknesses, careful testing is required to determine their best combination. METHOD: Six prototypical systems were assessed in two steps. First, a heuristic evaluation with experts from ergonomics, perception, and traffic psychology was conducted. It produced a broad overview of possible effects of system properties on driving. Based on these results, an experimental field study with 15 experienced drivers was performed. Criteria used to evaluate the development potential of the six prototypes were the usability dimensions of effectiveness, efficiency, and user satisfaction (International Organization for Standardization, 1998). RESULTS: Results showed that the intelligibility of information, the easiness with which obstacles could be located in the environment, and the position of the display presenting the output of the system were of crucial importance for the usability of the NVES and its acceptance. Conclusion: All relevant requirements are met best by NVESs that are positioned at an unobtrusive location and are equipped with functions for the automatic identification of objects and for event-based warnings. APPLICATION: These design recommendations and the presented approach to evaluate the systems can be directly incorporated into the development process of future NVESs.     

Integrated A.I. systems

The broad range of capabilities exhibited by humans and animals is achieved through a large set of heterogeneous, tightly integrated cognitive mechanisms. To move artificial systems closer to such general-purpose intelligence we cannot avoid replicating some subset—quite possibly a substantial portion—of this large set. Progress in this direction requires that systems integration be taken more seriously as a fundamental research problem. In this paper I make the argument that intelligence must be studied holistically. I present key issues that must be addressed in the area of integration and propose solutions for speeding up rate of progress towards more powerful, integrated A.I. systems, including (a) tools for building large, complex architectures, (b) a design methodology for building realtime A.I. systems and (c) methods for facilitating code sharing at the community level.