The Cascade Neo-Fuzzy Architecture and its Online Learning Algorithm

In the paper learning algorithm for adjusting weight coefficients of the Cascade Neo-Fuzzy Neural Network (CNFNN) in sequential mode is introduced. Concerned architecture has the similar structure with the Cascade-Correlation Learning Architecture proposed by S.E. Fahlman and C. Lebiere, but differs from it in type of artificial neurons. CNFNN consists of neo-fuzzy neurons, which can be adjusted using high-speed linear learning procedures. Proposed CNFNN is characterized by high learning rate, low size of learning sample and its operations can be described by fuzzy linguistic “if-then” rules providing “transparency” of received results, as compared with conventional neural networks. Using of online learning algorithm allows to process input data sequentially in real time mode.

Elder malnutrition: A meta analysis of studies using the nutrition screening initiative determine checklist

To demonstrate the extent of elder malnutrition risk in this country, a meta analysis of 30 studies that used the Nutrition Screening Initiative's "DETERMINE Your Nutritional Health Checklist" was conducted. The studies were divided into three categories: Elder Populations in Healthcare Related Systems (HS), Elder Meal Program Participants (MP), and General Community Residing Elder Population (GC). HS was sub-divided into Hospital Inpatient/Clinic Outpatient and Long Term Care/Home Care. The MP population were identified as Congregate or Home Delivered meal participants. Overall, results indicate that 63% of elders are at moderate (32%) or high (31 %) risk of malnutrition. Home Delivered Meal Participants and Hospital Inpatient/Clinic Outpatients are most likely to be at high risk of malnutrition (49.5% and 49.1%, respectively). Individuals least likely to be at high malnutrition risk are the General Community Residing Elder Population (17.5%) and Congregate Meal Participants (22.5%).

Micropartículas de quitosana estruturadas com aerosil®: estabilidade, adsorção, encapsulação e liberação de substâncias ativas

Biodegradable microspheres used as controlled release systems are important in pharmaceutics. Chitosan biopolymer represents an attractive biomaterial alternative because of its physicochemical and biological characteristics. Chitosan microspheres are expected to become promising carrier systems for drug and vaccine delivery, especially for non-invasive ways oral, mucosal and transdermal routes. Controlling the swelling rate and swelling capacity of the hydrogel and improving the fragile nature of microspheres under acidic conditions are the key challenges that need to be overcomed in order to enable the exploration of the full pharmaceutical potential use of these microparticles. Many studies have focused on the modification of chitosan microsphere structures with cross-linkers, various polymers blends and new organic-inorganic hybrid systems in order to obtain improved properties. In this work, microspheres made of chitosan and nanosized hydrophobic silica (Aerosil R972) were produced by a method consisting of two steps. First, a preparation of a macroscopically homogeneous chitosan-hydrophobic silica dispersion was prepared followed by spray drying. FTIR spectroscopy, X-ray powder diffraction, differential scanning calorimetry, thermal gravimetric analysis, scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (TEM) were used to characterize the microspheres. Also, the were conducted acid stability, moisture sorption capacity, release properties and biological assays. The chitosan-hydrophobic silica composite microspheres showed improved thermal degradation, lower water affinity, better acid stability and ability to retard rifampicin and propranolol hydrochloride (drug models) release under simulated physiological conditions. In vitro biocompatibility studies indicated low cytotoxicity and low capacity to activate cell production of the pro-inflammatory mediator nitric oxide. The results show here encourage further studies on the use of the new chitosan-hydrophobic silica composite microspheres as drug carrier systems via oral or nasal routes.

Joint Optimization for Social Content Delivery in Wireless Networks

Over the last decade, success of social networks has significantly reshaped how people consume information. Recommendation of contents based on user profiles is well-received. However, as users become dominantly mobile, little is done to consider the impacts of the wireless environment, especially the capacity constraints and changing channel. In this dissertation, we investigate a centralized wireless content delivery system, aiming to optimize overall user experience given the capacity constraints of the wireless networks, by deciding what contents to deliver, when and how. We propose a scheduling framework that incorporates content-based reward and deliverability. Our approach utilizes the broadcast nature of wireless communication and social nature of content, by multicasting and precaching. Results indicate this novel joint optimization approach outperforms existing layered systems that separate recommendation and delivery, especially when the wireless network is operating at maximum capacity. Utilizing limited number of transmission modes, we significantly reduce the complexity of the optimization. We also introduce the design of a hybrid system to handle transmissions for both system recommended contents ('push') and active user requests ('pull'). Further, we extend the joint optimization framework to the wireless infrastructure with multiple base stations. The problem becomes much harder in that there are many more system configurations, including but not limited to power allocation and how resources are shared among the base stations ('out-of-band' in which base stations transmit with dedicated spectrum resources, thus no interference; and 'in-band' in which they share the spectrum and need to mitigate interference). We propose a scalable two-phase scheduling framework: 1) each base station obtains delivery decisions and resource allocation individually; 2) the system consolidates the decisions and allocations, reducing redundant transmissions. Additionally, if the social network applications could provide the predictions of how the social contents disseminate, the wireless networks could schedule the transmissions accordingly and significantly improve the dissemination performance by reducing the delivery delay. We propose a novel method utilizing: 1) hybrid systems to handle active disseminating requests; and 2) predictions of dissemination dynamics from the social network applications. This method could mitigate the performance degradation for content dissemination due to wireless delivery delay. Results indicate that our proposed system design is both efficient and easy to implement.

Sustainable exploitation of offshore renewable energy sources

Energy transition is the response of humankind to the concerning effects of fossil fuels depletion, climate change and energy insecurity, and calls for a deep penetration of renewable energy sources (RESs) in power systems and industrial processes. Despite the high potentials, low impacts and long-term availability, RESs present some limits which need to be overcome, such as the strong variability and difficult predictability, which result in scarce reliability and difficult applicability in steady-state processes. Some technological solutions relate to energy storage systems, equipment electrification and hybrid systems deployment, thus accomplishing distributed generation even in remote sites as offshore. However, all of these actions cannot disregard sustainability, which represents a founding principle for any project, bringing together economics, reliability and environmental protection. To entail sustainability in RESs-based innovative projects, previous knowledge and tools are often not tailored or miss the novel objectives. This research proposes three methodological approaches, bridging the gaps. The first contribute adapts literature-based indicators of inherent safety and energy efficiency to capture the specificities of novel process plants and hybrid systems. Minor case studies dealing with novel P2X processes exemplify the application of these novel indicators. The second method guides the conceptual design of hybrid systems for the valorisation of a RES in a site, by considering the sustainability performances of alternative design options. Its application is demonstrated through the comparison of two offshore sites where wave energy can be valorised. Finally, “OHRES”, a comprehensive tool for the sustainable optimisation of hybrid renewable energy systems is proposed. “OHRES” hinges on the exploitation of multiple RESs, by converting ex-post sustainability indicators into discrimination markers screening a large number of possible system configurations, according to the location features. Five case studies demonstrate “OHRES” versatility in the sustainable valorisation of multiple RESs.

Extending the 2P-Kt ecosystem: CLP and Labelled LP

The ability to create hybrid systems that blend different paradigms has now become a requirement for complex AI systems usually made of more than a component. In this way, it is possible to exploit the advantages of each paradigm and exploit the potential of different approaches such as symbolic and non-symbolic approaches. In particular, symbolic approaches are often exploited for their efficiency, effectiveness and ability to manage large amounts of data, while symbolic approaches are exploited to ensure aspects related to explainability, fairness, and trustworthiness in general. The thesis lies in this context, in particular in the design and development of symbolic technologies that can be easily integrated and interoperable with other AI technologies. 2P-Kt is a symbolic ecosystem developed for this purpose, it provides a logic-programming (LP) engine which can be easily extended and customized to deal with specific needs. The aim of this thesis is to extend 2P-Kt to support constraint logic programming (CLP) as one of the main paradigms for solving highly combinatorial problems given a declarative problem description and a general constraint-propagation engine. A real case study concerning school timetabling is described to show a practical usage of the CLP(FD) library implemented. Since CLP represents only a particular scenario for extending LP to domain-specific scenarios, in this thesis we present also a more general framework: Labelled Prolog, extending LP with labelled terms and in particular labelled variables. The designed framework shows how it is possible to frame all variations and extensions of LP under a single language reducing the huge amount of existing languages and libraries and focusing more on how to manage different domain needs using labels which can be associated with every kind of term. Mapping of CLP into Labeled Prolog is also discussed as well as the benefits of the provided approach.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Toward Optimal Design of Piezoelectric Transducers Based on Multifunctional and Smoothly Graded Hybrid Material Systems

This work explores the design of piezoelectric transducers based on functional material gradation, here named functionally graded piezoelectric transducer (FGPT). Depending on the applications, FGPTs must achieve several goals, which are essentially related to the transducer resonance frequency, vibration modes, and excitation strength at specific resonance frequencies. Several approaches can be used to achieve these goals; however, this work focuses on finding the optimal material gradation of FGPTs by means of topology optimization. Three objective functions are proposed: (i) to obtain the FGPT optimal material gradation for maximizing specified resonance frequencies; (ii) to design piezoelectric resonators, thus, the optimal material gradation is found for achieving desirable eigenvalues and eigenmodes; and (iii) to find the optimal material distribution of FGPTs, which maximizes specified excitation strength. To track the desirable vibration mode, a mode-tracking method utilizing the `modal assurance criterion` is applied. The continuous change of piezoelectric, dielectric, and elastic properties is achieved by using the graded finite element concept. The optimization algorithm is constructed based on sequential linear programming, and the concept of continuum approximation of material distribution. To illustrate the method, 2D FGPTs are designed for each objective function. In addition, the FGPT performance is compared with the non-FGPT one.

Effects of Nd:YAG Laser Irradiation on the Hybrid Layer of Different Adhesive Systems

Purpose: The aim of this in vitro study was to evaluate the microtensile bond strength (mu TBS) and hybrid layer morphology of different adhesive systems, either followed by treatment with Nd:YAG laser irradiation or not. Previous studies have shown the effects of Nd:YAG laser irradiation on the dentin surface at restoration margins, but there are few reports about the significance of the irradiation on the hybrid layer. Materials and Methods: The flattened coronal and root dentin samples of 24 bovine teeth were randomly divided into 8 groups, according to the adhesive system used - Scotchbond Multi Purpose (SBMP) or Clearfil SE Bond (CSEB) - and were either irradiated with Nd:YAG or not, with different parameters: 0.8 W/10 Hz, 0.8 W/20 Hz, 1.2 W/10 Hz, 1.2 W/20 Hz. The left sides of specimens were the control groups, and right sides were irradiated. A composite crown was built over bonded surfaces and stored in water (24 h at 37 degrees C). Specimens were sectioned vertically into slabs that were subjected to mu TBS testing and observed by SEM. Results: Control groups (27.81 +/- 1.38) showed statistically higher values than lased groups (21.37 +/- 0.99), and CSEB control group values (31.26 +/- 15.71) were statistically higher than those of SBMP (24.3 +/- 10.66). There were no significant differences between CSEB (20.34 +/- 10.01) and SBMP (22.43 +/- 9.82) lased groups. Among parameters tested, 0.8 W/10 Hz showed the highest value (25.54 +/- 11.74). Nd:YAG laser irradiation caused dentin to melt under the adhesive layer of both adhesive systems tested. Conclusion: With the parameters used in this study, Nd:YAG laser irradiation of the hybrid layer promoted morphological changes in dentin and negatively influenced the bond strength of both adhesive systems.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Lesion detection performance in an anthropomorphic chest phantom: comparative analysis of low-dose CT data on two hybrid imaging systems

Introduction: multimodality environment; requirement for greater understanding of the imaging technologies used, the limitations of these technologies, and how to best interpret the results; dose optimization; introduction of new techniques; current practice and best practice; incidental findings, in low-dose CT images obtained as part of the hybrid imaging process, are an increasing phenomenon with advancing CT technology; resultant ethical and medico-legal dilemmas; understanding limitations of these procedures important when reporting images and recommending follow-up; free-response observer performance study was used to evaluate lesion detection in low-dose CT images obtained during attenuation correction acquisitions for myocardial perfusion imaging, on two hybrid imaging systems.

Is there space for senior civil servants hybrid management models across political- administrative systems?

Comunicação apresentada na 17.ª conferência anual da NISPACee, realizada de 14 a 16 de Maio de 2009.

How are top officials hybrid management models present across political-administrative systems?

Comunicação apresentada na 4th Annual ICPA - International Conference on Public Administration "Building bridges to the future: leadership and collaboration in public administration", na Universidade de Minnesota nos Estados Unidos, de 24 a 26 de setembro de 2008

Hybrid turbo FEC/ARQ systems and distributed space-time coding for cooperative transmission

Cooperative transmission can be seen as a "virtual" MIMO system, where themultiple transmit antennas are in fact implemented distributed by the antennas both at the source and the relay terminal. Depending on the system design, diversity/multiplexing gainsare achievable. This design involves the definition of the type of retransmission (incrementalredundancy, repetition coding), the design of the distributed space-time codes, the errorcorrecting scheme, the operation of the relay (decode&forward or amplify&forward) and thenumber of antennas at each terminal. Proposed schemes are evaluated in different conditionsin combination with forward error correcting codes (FEC), both for linear and near-optimum(sphere decoder) receivers, for its possible implementation in downlink high speed packetservices of cellular networks. Results show the benefits of coded cooperation over directtransmission in terms of increased throughput. It is shown that multiplexing gains areobserved even if the mobile station features a single antenna, provided that cell wide reuse of the relay radio resource is possible.