Determination of optimal part delivery dates in a stochastic assembly line

We consider the problem of determining the optimal part delivery dates of a low volume, small lot assembly line which manufactures large and costly products. Parts are assembled at each stage to a subassembly. The arrival time of an assembly part from a vendor is assumed to be a normally distributed random variable. A dynamic programming algorithm is developed to minimize work-in-process inventory of parts and subassemblies. It is implemented on the single job problem. Its further extensions to the multi-job case and to incorporate the cost of setting delivery dates are also discussed.     

Automating the refinement of specifications for distributed systems via syntactic transformations

The idea of successively refining an abstract specification until it contains enough detail to suggest an implementation has been investigated by numerous researchers. The emphasis to date has been on techniques that, unfortunately, lead to a large amount of manual formal labour for each refinement step. With such techniques, both the cost and the possibility of errors arising informal manipulation are high. Using a theorem prover can reduce the number of manipulation errors, but, given current technology, the amount of labour is still daunting. This research explores an alternative solution to the refinement problem, namely the use of syntactic transformations to realize each refinement step. We reduce formal labour by employing automatic transformations that guarantee the preservation of desirable properties—e.g., deadlock-freedom. Automatic transformations are particularly appealing for the development of large, complex distributed systems, where a manual approach to refinement would be prohibitively expensive. Distributed computations are, by nature, reactive and concurrent, so their correctness cannot be specified as a simple functional relationship between inputs and outputs. Instead, specifications must describe the time-varying behaviour of the system. Further difficulty is caused by the fact that such important characteristics of distributed systems as deadlock-freedom are global properties that cannot be achieved through considering local structures only. Transformations generally must encompass the entire system. This paper presents two syntactic transformations—the left-sequence introduction and the right-sequence introduction—and demonstrates that they preserve deadlock-freedom.     

Study of Leaching of Multimetal Sulphides Through an Interdisciplinary Approach

The leaching of a real multimetal bulk concentrate cannot often be adequately understood on the basis of published literature on simpler and often ideal systems because the process is far too complex, Moreover, the data can become ambiguous in the absence of adequate information on raw materials. Thus any process development work requires a thorough knowledge of the raw material characteristics. This paper describes the use of an interdisciplinary study for a better understanding of ammonia leaching of multimetal sulphides. The techniques employed comprise of X-ray diffraction, thermal analysis, chemical analysis and microscopy.     

Simultaneous pole-placement/stabilization of pairs of linear time-invariant plants using a continuous-time periodic controller

Given a pair of single input single output (SISO), linear time-invariant (LTI), and strictly proper plants of relative order r, this paper employs a continuous-time periodic controller to achieve 1) simultaneous pole-placement for r = 1 and 2) guaranteed simultaneous stabilization for r = 2; 3, and 4, which jobs LTI controllers cannot, in general, do. The controller also ensures insignificant output ripples. The analysis is based on averaging principle. The computational steps for controller synthesis are linear algebraic in nature. An example illustrates the design procedure.     

Textural pattern classification for oral squamous cell carcinoma

Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer‐aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey‐level co‐occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy.     

Automated system for characterization and classification of malaria‐infected stages using light microscopic images of thin blood smears

In this paper, we propose a comprehensive image characterization cum classification framework for malaria‐infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three‐image segmentation algorithms (namely, rule‐based, Chan–Vese‐based and marker‐controlled watershed methods), marker‐controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F‐statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features’ subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria‐infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F‐statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria‐infected stage classification.     

Analysis of foundation sliding of an arch dam considering the hydromechanical behavior

This paper presents the application of a methodology which can be used to assess arch dam foundation stability,using the discrete element method (DEM) and the code 3DEC.A global three-dimensional model...     

Droplet Size and Coalescence Stability of Whey Protein Stabilized Milkfat Peanut Oil Emulsions

Droplet diameter and the polydispersity of droplet size tended to decrease with increased proportion of peanut oil. Macromolecular additives affected droplet size. Xanthan gum or sodium carboxymethyl-cellulose (Na-CMC) produced smaller droplets than the controls, but the average diameter was independent of the composition of the dispersed phase. At 50°C the coalescence stability of these emulsions qualitatively correlated with the initial droplet diameter. Xanthan gum and Na-CMC, despite increasing continuous phase viscosity, gave lower stability than controls, primarily the result of flocculation of droplets due to depletion of the highly hydrophilic macromolecule from the intervening region between approaching droplets. At 25°C, stability increased as solid butter oil content of the dispersed phase increased.