Human resource optimisation through semantically enriched data

The industrial domain is experiencing a so-called fourth industrial revolution in which the evergrowing complexity of manufacturing information, the increasing amount of knowledge and the use of web-oriented techniques, represent three crucial factors that are accelerating the growth of complexity of industrial systems. On the other hand, continuous-evolving requirements in industrial environments, due to technology outbreaks and a new global marketplace, have led to an on-going evolution of human resource management through the creation and adoption of alternative business models. In the past decade, semantic models such as ontologies have been proven to be effective for many knowledge-intensive applications, since they provide formal models of domain knowledge that can be exploited in different ways. For all these reasons, an innovative human resource optimisation (HRO) engine is introduced, which employs semantically enhanced information and conditional random field (CRFs) probabilistic models with knowledge derived from industrial shop floor level, and proposes the right person for the right job in real-time shop floor operations towards optimising decisions on how to implement and schedule either repeatedly or non-occurring tasks. Industrial information data flow and semantic enrichment were ensured through the combined use of a common interface data exchange model (CIDEM) and ontologies, after which a feasibility study at a chemical plant presented interesting preliminary results.     

A service based approach for medical image distribution in healthcare Intranets

The Digital Imaging and Communications in Medicine (DICOM) protocol is currently the ubiquitous standard for the communication of medical images and related data within the radiology department. However, seamless image distribution within the healthcare enterprise and especially with research and educational information systems is still hard to achieve, as software developers of such third-party applications have to go through the rather cumbersome task of adapting the DICOM communication model and implementing the DICOM protocol. This paper gives a brief outline of current trends in medical image distribution in the healthcare enterprise, and proposes a new technological approach for distributing DICOM images and related data through commonplace Internet technologies, based on the emerging web services software paradigm. In particular, the paper describes the DICOM Image Management (DIM) web service which acts as a fa?ade for conventional DICOM sources allowing DICOM image data and related information, to be transformed into XML documents encapsulated in SOAP messages, enabling integration at the application level through general purpose standardized web technologies. Implementation issues are discussed and a demonstration of engaging the DIM web service is included.     

Generation of synthetic documents for performance evaluation of symbol recognition & spotting systems

This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.     

Web Service Composition Using a Deductive XML Rule Language

This paper describes a knowledge-based Web Service composition system, called SWIM, which is based on the Service Domain model. Service Domains are communities of related Web Services that are mediated by a single Web Service, called the Mediator Service, which functions as a proxy for them. When a requestor sends a message to the Mediator Service one or more of the related Web Services are selected to dispatch the message and the results returned are aggregated to a single answer to the requestor. Mediator Services can be further composed to more complex Mediator Services that combine several selection and aggregation algorithms among many heterogeneous web services. The system utilizes the X-DEVICE deductive XML rule language for defining complex algorithms for selecting registered web services, combining the results, and synchronizing the workflow of information among the combined web services in a declarative way. In the paper, we demonstrate the flexibility and expressibility of our approach for composing Web Services using several e-business examples, covering most of the workflow patterns found in a comprehensive workflow management system (van der Aalst et al., Distributed and Parallel Databases, vol. 14, no, 1, pp. 5–15, 2003).     

Synthesis and characterization of silica core/nano-ferrite shell particles

Core/shell particles were synthesized by assembling oppositely charged ferrite (Fe₃O₄ or NiFe₂O₄) nanoparticles on the surface of monodispersed silica core particles (having size ～0.4 μm) prepared by hydrolysis and condensation of tetraethylortosilicate. Optimal conditions for synthesis of silica core/nano-Fe₃O₄ shell particles were found at pH ～ 5.4. The obtained particles have superparamagnetic behavior above a blocking temperature of ≈25 K, which make them very attractive for a broad range of biomedical and bioengineering applications. Incorporation of nickel into ferrite structure could not be achieved at lower pH value, so functionalization of core particles was required. Incorporation of nickel into ferrite structure was successful at pH above 7, however at higher pH the formation rate of nickel–ferrite particles becomes very fast and the self-aggregation dominates the competing formation of the nickel–ferrite shell. Because of that the self-aggregation was prevented by surface modification of nickel–ferrite nanoparticles with citric acid before their deposition on the functionalized silica core and homogenous and continuous NiFe₂O₄ shell was finally obtained.     

Development of a wireless radioactive material sensor network

Our team at the United States Army Research Laboratory (ARL) has designed and developed a low-power, compact, wireless-networked gamma sensor (WGS) array. The WGS system provides high sensitivity gamma photon detection and remote warning for a broad range of radioactive materials. This sensor identifies the presence of a 1 μCi Cs137 source at a distance of 1.5 m. The networked array of sensors presently operates as a facility and laboratory sensor for the movement of radioactive check sources. Our goal has been to apply this architecture for field security applications by incorporating low-power design with compact packaging. The performance of this radiation measurement network is demonstrated for both detection and location of radioactive material.     

Rotation invariant hand-drawn symbol recognition based on a dynamic time warping model

One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.     

Multivariate chemometric discrimination of cigarette tobacco blends based on the UV–Vis spectrum of their hydrophilic extracts

The application of UV–Vis spectrophotometry as an alternative or complementary approach to the classification of tobacco products is presented in this work for the first time. Two hundred fifty samples from five different cigarette brands composed of single and mixed tobacco blends were examined for that purpose on the basis of the UV–Vis spectrum of their aqueous extracts. Data transformation based on the normalization of absorbance intensities as a function of sample weight was employed in order to account for differences in the relative intensities of each sample. Principal components analysis (PCA) was used to extract outlier cases and sample classification was then pursued with the aid of discriminant analysis (DA) suggesting that a reduced number of variables (thirteen out of seven hundred initially available) could provide perfect classification (100% correct assignations) of samples containing single tobacco species or different blends and a fair classification of samples with similar composition (80% correct assignations) yielding an overall 95.7% correct classification. To this pursue, classification and regression trees were found to afford perfect classification of all samples using only a few logic rules based on appropriate split conditions at the expense of inserting 15 variables in the model.