Mitigating the impact of occupational noise exposure for elderly workers: Setting the functional requirements for an ANC system

Noise affects people in very different aspects and in almost every aspect of our daily life. The most prominent impact of noise exposure is hearing loss. However, it can also impair people at their work settings due to other effects rather than hearing loss. Older works tend to be more susceptible to noise exposure effects at work, firstly because most of them already have some ‘natural’ hearing loss, as a results of the ageing process, and secondly because they also tend to be more susceptible at an psychological level. The current study is an attempt to describe the potential problem and to make a survey to identify the available active noise cancelation systems, as well as to specific the main requirements of this type of systems to be applied in such contexts. Several aspects of characteristics of the ANC systems were identified and are presented in this study. From the obtained results it was possible to have a clearer idea about the potential of this technology, and to confirm that this type of solution can be extremely important as a component of an active ageing program, as the preservation of hearing will also impact on the social life of the exposed workers.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Accuracy comparison of implant impression techniques: A systematic review

Background Several studies link the seamless fit of implant-supported prosthesis with the accuracy of the dental impression technique obtained during acquisition. In addition, factors such as implant angulation and coping shape contribute to implant misfit. Purpose To identify the most accurate impression technique and factors affecting the impression accuracy. Material and Methods A systematic review of peer-reviewed literature was conducted analyzing articles published between 2009 and 2013. The following search terms were used: implant impression, impression accuracy, and implant misfit. A total of 417 articles was identified, 32 were selected for review. Results All 32 selected studies refer to in vitro studies. Fourteen articles compare open and closed impression technique, 8 advocate the open technique and 6 report similar results. Other 14 articles evaluate splinted and non-splinted techniques; all advocating the splinted technique. Polyether material usage was reported in 9; 6 studies tested vinyl polysiloane and 1 study used irreversible hydrocolloid. Eight studies evaluated different copings designs. Intra-oral optical devices were compared in 4 studies. Conclusions The most accurate results were achieved with two configurations: (1) the optical intra-oral system with powder; and (2) the open technique with splinted squared transfer copings, using polyether as impression material.

Optimal behavior of responsive residential demand considering hybrid phase change materials

Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customerâ s cost in different DRPs but also to guaranty the habitantsâ  satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customerâ s electricity cost can be reduced up to 48% by utilizing the proposed model.

From software extensions to product lines of dataflow programs

Abstract Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE-speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the ReFlO tool and present two non-trivial case studies as evidence of our work’s generality

Alterações da hemostasia em crianças submetidas a cirurgia cardíaca com circulação extracorpórea

OBJETIVO: Avaliar as alterações de hemostasia encontradas em crianças submetidas a cirurgia cardíaca com circulação extracorpórea (CEC). MÉTODOS: Estudamos 17 crianças no pré e pós-operatório (PO) imediato, no 1° PO e entre o 4º e 7º PO, analisando o hematócrito, tempo de protrombina (TP), tempo de tromboplastina parcial ativado, fibrinogênio, contagem de plaquetas, fator V e tempo de lise de euglobulina (TLE). Os pacientes foram divididos em grupos com e sem sangramento excessivo no PO. RESULTADOS: Houve alterações significantes no intra-operatório com aumento do TP e tempo de tromboplastina parcial ativado e redução do fibrinogênio, fator V e do TLE. Seis (35%) crianças sangraram excessivamente. A contagem de plaquetas foi significantemente menor no intra-operatório; neste grupo o tempo de CEC foi maior. CONCLUSÃO: Alterações de hemostasia no intra e PO ocorrem como conseqüência da ativação da cascata de coagulação e fibrinólise. A incidência de sangramento excessivo é alta nesta faixa etária. Os grupos com e sem sangramento excessivo diferenciaram-se pelo maior tempo de CEC e contagem reduzida de plaquetas.

Cirurgia valvar em gestantes. Experiência em oito casos

OBJETIVO: Analisar, em gestantes, os resultados da cirurgia cardíaca e as conseqüências da circulação extracorpórea (CEC) nas gestantes e fetos. MÉTODOS: Estudo de 8 gestantes submetidas à cirurgia cardíaca valvar entre janeiro/86 e dezembro/96. Idade média de 31,4±8,9 anos, e idade gestacional entre 12 a 31 (média de 26,6±7,1) semanas. Em todas as pacientes foi realizada monitorização fetal. Durante a CEC manteve-se sempre o fluxo elevado e a temperatura acima de 34°C. Foram realizadas 4 cirurgias da valva aórtica e 4 da valva mitral, sendo duas reoperações. RESULTADOS: Não houve mortalidade materna. Ocorreram dois partos prematuros e em uma criança houve comprometimento neurológico. As demais crianças não apresentaram nenhum comprometimento em seu desenvolvimento. CONCLUSÃO: Os cuidados com o fluxo durante a CEC e a monitorização fetal no intra-operatório foram fundamentais para a obtenção de resultados bastante satisfatórios.

Cirurgia de revascularização do miocárdio através de minitoracotomia esquerda

OBJETIVO: Atualmente existe uma tendência mundial para a realização de cirurgias através de incisões mínimas, denominadas minimamente invasivas, tornando o ato operatório cada vez menos agressivo. A introdução desta nova técnica possibilita a dissecção da artéria torácica interna esquerda (ATIE) e sua anastomose com a artéria interventricular anterior (AIA), através de uma minitoracotomia esquerda. MÉTODOS: De maio/96 a outubro/97, 11 portadores de insuficiência coronária, com lesão única e proximal da AIA, foram submetidos a revascularização do miocárdio (RM). A abordagem cirúrgica consistiu de uma toracotomia ântero-lateral esquerda, de aproximadamente 10cm, através do 4º espaço intercostal esquerdo, e nos últimos 6 casos com ressecção de parte da cartilagem da 4ª e 5ª costelas, dissecção da ATIE, abertura e reparo do pericárdio adjacente à AIA. Todos pacientes receberam ponte única para AIA com enxerto da ATIE, sem auxílio de circulação extracorpórea (CEC). RESULTADOS: A idade variou de 46 a 76 (média = 58,55) anos, sendo 10 (90,90%) pacientes do sexo masculino e 1 (9,09%) feminino. O tempo de permanência hospitalar variou de 4 a 8 (média de 5,2) dias. Nenhum paciente apresentou alteração eletrocardiográfica no pós-operatório imediato. Um paciente apresentou no controle, trombose no 1/3 distal da ATIE com comprometimento importante de fluxo e, outro, estenose ao nível da anastomose, sendo ambos submetidos a angioplastia com sucesso. Não houve mortalidade no grupo estudado. CONCLUSÃO: A ausência de mortalidade, sugere que a cirurgia de RM através de cirurgia minimamente invasiva, em grupos selecionados, é uma excelente alternativa de revascularização da AIA.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Critical events in mechanically ventilated patients

Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.