Near Infrared Light Heating of Soft Tissue Phantoms Containing Nanoparticles

International audienceThe objective of this paper is to investigate the effect of the addition of nanoparticles to soft tissue phantoms, aiming at the enhancement of photothermal therapy for cancer. The phantoms were made of Polyvinyl chloride-plastisol (PVC-P), with two different nanoparticles, namely, titanium dioxide nanoparticles (TiO2) and silica nanoparticles (SiO2). A phantom without nanoparticles and a phantom containing a thermal paste were also manufactured for comparison purposes. The PVC-P phantom is transparent to the near infrared laser light, whereas the addition of titanium dioxide nanoparticles modified the optical properties enhancing the local heating, as demonstrated through experiments with a laser-diode and an infrared camera

Approach for preventive maintenance planning of machine tools

This paper addresses a common problem to manufacturing companies: the maintenance of machine tools and their components. Preventive maintenance has always been a great challenge for companies, due to the need of predicting failures or production shutdowns, which requires knowledge and resources. However, the planning of machine tools maintenance presents itself as an even more complex problem due to the distinct lifetimes of their components. Age-based preventive replacement and Block replacement models define optimal replacement intervals for one item based on associated maintenance costs. A machine tool can be seen as a serial system of components or items. The concepts of group technology and clustering can be used to group components together in order to define common preventive maintenance intervals and reduce the number of production stops. In the literature, some contributions are found. However, the defined groups are static as well as the preventive maintenance intervals. This paper presents a conceptual model for the definition of dynamic clusters and intervals. It also presents an application to record the inputs, data collected in real time, needed to group components and set up preventive maintenance intervals. The developed application is being implemented in a metalworking company.We would like to thank the companies that are involved in the project and express our appreciation for the commitment of the employees involved. This work has been supported by Norte 010247 FEDER 017833 – TechParts I&D

Price modeling of IaaS providers - An approach focused on enterprise application integration

One of the main advances in information technology today is cloud computing. It is a great alternative for users to reduce costs related to the need to acquire and maintain computational infrastructure to develop, implement and execute software applications. Cloud computing services are offered by providers and can be classified into three main modalities: Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS) and Infrastructureas-a-Service (IaaS). In IaaS, the user has a virtual machine at their disposal with the desired computational resources at a given cost. Generally, the providers offer infrastructure services divided into instances, with preestablished configurations. The main challenge faced by companies is to choose the instance that best fits their needs among the many options offered by providers. Frequently, these companies need a large computational infrastructure to manage and improve their business processes and, due to the high cost of maintaining local infrastructure, they have begun to migrate applications to the cloud in order to reduce these costs. In this paper, we introduce a proposal for price modeling of instances of virtual machines using linear regression. This approach analyzes a set of simplified hypotheses considering the following providers: Amazon EC2, Google Compute Engine and Microsoft Windows Azure.info:eu-repo/semantics/acceptedVersio

Agrio et Emulsio – development of new products with vinegar and sweetpotatoes

Agrio et Emulsio project (POCI-01-0145-FEDER-023583) develops in vinegar and food emulsions areas. In line Agrio, vinegar technological ability enables the development of multiple products, by fermentative and non-fermentative prototyping. Articulating technological, laboratory and sensory tests and inspired both by the marinades in wine or vinegar of the Mediterranean gastronomy and in the traditional Portuguese recipe of “drunk” pear in red wine, two prototypes are undergoing final development, using sweet potato cultivars (Ipomoea batatas) as main ingredient. A sweet and sour “drunk” pickle has been developed by fresh pack pickling technology (without fermentation), using a spicy red wine vinegar with cinnamon and black pepper, sweetened with brown sugar and added Gin. The marinade was designed to be a ready-to-eat vegan product, with tofu and sweet potato previously salted in brine and then submerged in the marinade liquid. The marinade matrix is a diluted blend of red wine vinegar and regional liqueur wine from Ribatejo, flavored with red pepper, herbs and spices. Pre-salting in brine, maturation and the final heat treatment are fundamental for the quality and safety of both prototypes that were designed to provide innovation and convenience: new products with long shelf life, aims the preservation of seasonal/surplus raw materials.info:eu-repo/semantics/publishedVersio

Forum participation plugin for Moodle: development and discussion

At present, a large amount of software has been created to analyze social networks, such as libraries to access online social networking APIs, software to draw graphs and tools to use and analyze networks. In fact, and because of the use of Moodle as standard Learning Management System at the University of Las Palmas de Gran Canaria, in 2009 was born the idea of creating a plugin for Moodle capable of analyzing forums in which students participate and of identifying the major players within the student network. This work is about the present state of such plugin, which provides useful information to teachers so that, through the use of social network analysis, allows them to make decisions to improve and promote participatory education. Here, we show the application of the plugin to three case studies, in two different universities, which allowed to evaluate its usefulness and to compare the information according to the variables that influenced each case study

Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

This paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found in the literature, and its advantages for decision support and flexible/adaptive anti-spam filtering configuration is demonstrated. A study is performed using the Wirebrush4SPAM framework anti-spam filtering and the SpamAssassin email dataset. The NSGA-II evolutionary multi-objective optimization algorithm was applied for the purpose of validating and demonstrating the adoption of this novel approach to the anti-spam filtering optimization problem, formulated from the multi-objective optimization perspective. The results obtained from the experiments demonstrated that this optimization strategy allows the decision maker (anti-spam filtering system administrator) to select among a set of optimal and flexible filter configuration alternatives with respect to classification quality and classification efficiency

Task scheduling characterisation in enterprise application integration

Cloud computing allows enterprises to incorporate applications and computational resources as services, and thus, enterprises can concentrate on their business processes, without concerning the development, configuration and maintenance of these applications and resources. Integration platforms are one of these services that allow enterprises to integrate applications in order to reduce the maintenance costs and operations of the integration of on-premises platforms. However, high performance on resources offered by the cloud, demands improvement in task scheduling of integration platforms. Our literature review has identified a lack of studies in the field of enterprise application integration, focusing on specificities and vulnerabilities of the task scheduling of integration processes. This is a pioneer work regarding the characterisation of the scheduling of tasks of integration processes. We propose a ranking according to their conceptual models and apply this ranking to five integration processes. Then, we have statistically analysed the influence of each component of their conceptual models on the performance of the execution of these integration processes. We characterise the task scheduling of integration processes and presented a mathematical equation for the makespan as a function of the components of this characterisation. This study can guide software engineers in the optimal task scheduling for integration processes, which can improve the performance runtime systems regarding using the computational resources and result in minimisation of costs of companies.info:eu-repo/semantics/acceptedVersio

Queue-priority optimized algorithm: a novel task scheduling for runtime systems of application integration platforms

The need for integration of applications and services in business processes from enterprises has increased with the advancement of cloud and mobile applications. Enterprises started dealing with high volumes of data from the cloud and from mobile applications, besides their own. This is the reason why integration tools must adapt themselves to handle with high volumes of data, and to exploit the scalability of cloud computational resources without increasing enterprise operations costs. Integration platforms are tools that integrate enterprises’ applications through integration processes, which are nothing but workflows composed of a set of atomic tasks connected through communication channels. Many integration platforms schedule tasks to be executed by computational resources through the First-in-first-out heuristic. This article proposes a Queue-priority algorithm that uses a novel heuristic and tackles high volumes of data in the task scheduling of integration processes. This heuristic is optimized by the Particle Swarm Optimization computational method. The results of our experiments were confirmed by statistical tests, and validated the proposal as a feasible alternative to improve integration platforms in the execution of integration processes under a high volume of data.info:eu-repo/semantics/acceptedVersio

An ontology knowledge inspection methodology for quality assessment and continuous improvement

Ontology-learning methods were introduced in the knowledge engineering area to automatically build ontologies from natural language texts related to a domain. Despite the initial appeal of these methods, automatically generated ontologies may have errors, inconsistencies, and a poor design quality, all of which must be manually fixed, in order to maintain the validity and usefulness of automated output. In this work, we propose a methodology to assess ontologies quality (quantitatively and graphically) and to fix ontology inconsistencies minimising design defects. The proposed methodology is based on the Deming cycle and is grounded on quality standards that proved effective in the software engineering domain and present high potential to be extended to knowledge engineering quality management. This paper demonstrates that software engineering quality assessment approaches and techniques can be successfully extended and applied to the ontology-fixing and quality improvement problem. The proposed methodology was validated in a testing ontology, by ontology design quality comparison between a manually created and automatically generated ontology.info:eu-repo/semantics/publishedVersio

Production of Natural Pigments by Penicillium brevicompactum Using Agro-Industrial Byproducts

The demand for natural pigments for industrial applications has significantly increased. Penicillium brevicompactum was recently reported as a promising pigments producer using submerged fermentation and a synthetic culture medium containing lactose. In this work, pigment production by P. brevicompactum was studied under different fermentation conditions, namely, submerged fermentation with free (SmF) and immobilized mycelium (SmFi), and solid-state fermentation (SSF). The potential of culture media composed of agro-industrial byproducts (cheese-whey (CW) and corn steep liquor (CSL)) was investigated for the first time as low-cost alternatives to pigment production by P. brevicompactum. The fungus showed great adaptability to the different culture media and types of fermentation, being able to synthesize pigments under all the tested conditions. A culture medium composed of 34.6 g/L of CW and 8 g/L of CSL proved to be the most suitable alternative to the synthetic medium, especially under SmF and SmFi. Our data also show that different mixtures of pigments (yellow, orange, and red) can be produced depending on the medium composition and the type of fermentation. Additionally, the immobilization and reuse of biomass to produce pigments by P. brevicompactum were demonstrated for the first time, suggesting the possibility of operating under repeated batch mode at an industrial scale