Evaluation of glass samples for forensic purposes — An application of likelihood ratios and an information-theoretical approach

This article presents an experimental study about the influence of the selection of an adequate database for evidence evaluation using chemical profiles. Evidence evaluation in the forensic sense can be seen as the comparison of two glass objects, one of known origin, denoted as control glass, and typically would be from the scene of a crime, and the other one of unknown origin, termed recovered glass, which might be found in association with a suspect. The aim is to obtain some estimate of the weight of evidence for the degree of support to any of the hypothesis in the case, typically these might be that the control and recovered glass come from the same source (θ_p), and control and recovered glass come from different sources (θ_d). A likelihood ratio is considered a suitable measure of the evidential weight for the competing propositions. The observations are of the elemental composition of glass, measured using a Scanning Electron Microscopy, coupled with an Energy Dispersive X-ray spectrometer technique. A number of glass objects have been analyzed and their chemical profiles form a database which represents several sources of variation. In this paper questions surrounding the choice of observations to make are addressed empirically by assessing the impact of building each model using a database different from the one using for comparison. The performance of each evidence evaluation method is assessed by classical methods such as Tippett plots, or more recent information-theoretical approaches such as empirical cross-entropy (ECE) plots.The results show that several of the compositional elements are very robust to the selection of the background database, namely; calcium, silicon and sodium observed in their oxide forms. We also show that the likelihood ratio computed with the combination of these variables show a remarkable discriminating power, and good calibration, allowing them to be employed for the calculation of the strength of evidence in forensic case work.     

A variable-size local domain approach for increased design confidence in simulation-based optimization

Simulation-based design optimization utilizes computational models that rely on assumptions and approximations. There is a need therefore, to ensure that the obtained designs will exhibit the desired behavior as anticipated given the model predictions. The common approach to accomplish that is to validate the utilized computational models prior to the design optimization process. However, this is practically an impossible task especially for design problems with high-dimensional design and parameter spaces. We have recently proposed a different approach for maximizing confidence in the designs generated during a sequential simulation-based optimization process based on calibrating the computational models when necessary and within local subdomains of the design space. In that work, the size of the local domains was held fixed and not linked to uncertainty, and the confidence in designs was quantified using Bayesian hypothesis testing. In this article, we present an improved methodology. Specifically, we use a statistical methodology to account for uncertainty and to determine the size of the local domains at each stage of the sequential design optimization process using parametric bootstrapping that involves maximum likelihood estimators of model parameters. The sequential process continues until the local domain does not change from stage to stage during the design optimization process, ensuring convergence to an optimal design. The proposed methodology is illustrated with the design of a thermal insulator using one-dimensional, linear heat conduction in a solid slab with heat flux boundary conditions.     

Modeling computational limitations in H-Phy and Overlay-NoC architectures

High performance computing demands constant growth in computational power and services that can be offered by modern supercomputers. It requires technological and designing advances in the multiprocessor internal structures as well as novel computing models considering the very high computing demands. One of the increasingly important requirements of computing platforms is a functionality that allows efficient managing computational resources, i.e., monitor them, restrict an access to some part of the resources, account for computational service, or ensure reliability and quality of service when some resources are broken or disabled. In this paper, we present a new model describing computational limitations for processing tasks on multiprocessor systems. The model is implemented in Hardware-Physical (H-Phy) and Overlay-Network-on-Chip (Overlay-NoC) architectures. Both architectures and the model are described and analyzed. Experimentation system is also presented, together with simulation assumptions, results of research and their study. The paper provides complete models of H-Phy and Overlay-NoC structures with an ability to restrict processing resources.     

Algebraic Constructions: A Simple Framework for Complex Dependencies and Parameterisation

We propose a simple framework of algebraic constructions for software specification, modular design and development. Algebraic constructions generalise (parameterised) modules by allowing on one hand a rather arbitrary collection of elements to form the parameter and on the other hand dependencies between the module elements to be spelled out explicitly. Algebraic constructions are specified in a very natural way by means of ordinary algebraic specifications. They are combined using a sum operation which captures as special cases various operations on (parameterised) modules offered by standard specification and development frameworks. We show the expected composability result for the sum of algebraic constructions and of their specifications.     

The influence of zinc ions discharged in a non-aqueous cell on a copper catalyst on the rate of cyclohexanol dehydrogenation reaction

Results of studies on the influence of a copper catalyst modification with zinc ions on the activity in the reaction of cyclohexanol dehydrogenation are presented. The modification has been performed by electrochemical discharging-insertion of zinc ions on a copper electrode in a non-aqueous cell. It has been demonstrated that the catalyst activity depends on the amount of discharged zinc ions as well as on the nature and concentration of the electrolyte. In the case of zinc ions discharged from a solution of ZnCl₂ in propylene carbonate, the yield of cyclohexanone increased up to five times and using Zn(BF₄)₂ in dimethylformamide almost twenty times. The activity of the system in the competing reaction of dehydration was low, hence the selectivity in the dehydrogenation reaction was high.     

Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform

Results of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the article. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high-resolution camera images, maintaining the cost of resources usage at a reasonable level. Two selected algorithms: the Gaussian mixture models and the Codebook, are presented and their computational complexity is discussed. Various approaches to the parallel implementation, including assigning the image pixels to threads, the task scheduling methods and the thread management systems, are presented. The experiments were performed on a supercomputer cluster, using a single machine with 12 physical cores. The accuracy and performance of the implemented algorithms were evaluated for varying image resolutions and numbers of concurrent processing threads. On a basis of the evaluation results, an optimal configuration for the parallel implementation of the system for real-time video content analysis on a supercomputer platform was proposed.     

Multimodal processes optimization subject to fuzzy operation time constraints: declarative modeling approach

We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle (AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network (MTN). The multimodal processes behind the multi-product production flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN’s structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation (CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.     

An integrated model for the transshipment yard scheduling problem

A hub-and-spoke railway system is an efficient way of handling freight transport by land. A modern rail–rail train yard consists of huge gantry cranes that move the containers between the trains. In this context, we consider a rail–rail transshipment yard scheduling problem (TYSP) where the containers arrive to the hub and need to be placed on a train that will deliver them to their destination. In the literature, the problem is decomposed hierarchically into five subproblems, which are solved separately. First, the trains have to be grouped into bundles in which they visit the yard. Next, the trains have to be assigned to tracks within these bundles, namely parking positions. Then the final positions for the containers on trains have to be determined. Next, the container moves that need to be performed are assigned to the cranes. Finally, these moves have to be sequenced for each crane for processing. In this paper, an integrated MILP model is proposed, which aims to solve the TYSP as a single optimization problem. The proposed formulation also enables us to define more robust and complex objective functions that include key characteristics from each of the above-mentioned subproblems. The strength of our proposed formulation is demonstrated via computational experiments using the data from the literature. Indeed, the results show that the TYSP can be solved without the use of decomposition techniques and more insight can be obtained from the same input data used to solve particular single decomposed subproblems.     

A methodology for implementation of mobile robot in adaptive manufacturing environments

With the rapid development of technologies, many production systems and modes has been advanced with respect to manufacturing, management and information fields. The paper deals with the problem of the implementation of an autonomous industrial mobile robot in real-world industrial applications in which all these fields are considered, namely mobile robot technology, planning and scheduling and communication. A methodology for implementation consisting of: a mobile robot system design (Little Helper prototype), an appropriate industrial application (multiple-part feeding), an implementation concept for the industrial application (the Bartender Concept), a mathematical model and a genetic algorithm-based heuristic is proposed. Furthermore, in order for the mobile robot to work properly in a flexible (cloud-based) manufacturing environment, the communications and exchange of data between the mobile robot with other manufacturing systems and shop-floor operators are addressed in the methodology. The proposed methodology provides insight into how mobile robot technology and abilities contribute to cloud manufacturing systems. A real-world demonstration at an impeller production line in a factory and computational experiments are conducted to demonstrate the effectiveness of the proposed methodology.