Cogeneration design problem Computational complexity analysis and solution through an expert system

Purpose - The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.Design/methodology/approach - The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.Findings - The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.Originality/value - The expert system approach is not a "blind" method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.

Novel expert system for defining power quality compensators

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

This paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.

The Seville Expert Workshop for Progress in Posttransplant Lymphoproliferative Disorders

Posttransplant lymphoproliferative disorders (PTLDs) are associated with significant morbidity and mortality among solid-organ transplant patients, but approaches to diagnosis and management vary considerably. An international multidisciplinary panel evaluated current understanding of risk factors and classification systems and developed recommendations to aid in PTLD prevention. We considered evidence on PTLD risk factors including Epstein- Barr virus serostatus and immunosuppression and identified knowledge gaps for future research. Recommendations address prophylactic and preemptive strategies to minimize PTLD development, including modulation of immunosuppression and antiviral drug regimens. Finally, new classification criteria were outlined that may help facilitate standardized reporting and improve our understanding of PTLD.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Niemann-Pick disease type C symptomatology: an expert-based clinical description

Niemann-Pick disease type C (NP-C) is a rare, progressive, irreversible disease leading to disabling neurological manifestations and premature death. The estimated disease incidence is 1:120,000 live births, but this likely represents an underestimate, as the disease may be under-diagnosed due to its highly heterogeneous presentation. NP-C is characterised by visceral, neurological and psychiatric manifestations that are not specific to the disease and that can be found in other conditions. The aim of this review is to provide non-specialists with an expert-based, detailed description of NP-C signs and symptoms, including how they present in patients and how they can be assessed. Early disease detection should rely on seeking a combination of signs and symptoms, rather than isolated findings. Examples of combinations which are strongly suggestive of NP-C include: splenomegaly and vertical supranuclear gaze palsy (VSGP); splenomegaly and clumsiness; splenomegaly and schizophrenia-like psychosis; psychotic symptoms and cognitive decline; and ataxia with dystonia, dysarthria/dysphagia and cognitive decline. VSGP is a hallmark of NP-C and becomes highly specific of the disease when it occurs in combination with other manifestations (e.g. splenomegaly, ataxia). In young infants (<2 years), abnormal saccades may first manifest as slowing and shortening of upward saccades, long before gaze palsy onset. While visceral manifestations tend to predominate during the perinatal and infantile period (2 months–6 years of age), neurological and psychiatric involvement is more prominent during the juvenile/adult period (>6 years of age). Psychosis in NP-C is atypical and variably responsive to treatment. Progressive cognitive decline, which always occurs in patients with NP-C, manifests as memory and executive impairment in juvenile/adult patients. Disease prognosis mainly correlates with the age at onset of the neurological signs, with early-onset forms progressing faster. Therefore, a detailed and descriptive picture of NP-C signs and symptoms may help improve disease detection and early diagnosis, so that therapy with miglustat (Zavesca®), the only available treatment approved to date, can be started as soon as neurological symptoms appear, in order to slow disease progression.

Pedagogização do pedagógico: sobre o jogo do expert no governamento docente

O artigo objetiva colocar em causa a razão imanente entre as práticas educacionais atuais e o âmbito da governamentalidade, por meio da problematização dos processos de pedagogização aí levados a cabo. Mais especificamente, visa analisar o jogo do expert como modalidade privilegiada do governamento docente na atualidade. Para tanto, toma como objeto empírico entrevistas concedidas por especialistas à revista Nova Escola entre 2005 e 2009. A discussão indica uma espécie de saturação pedagogizante do campo escolar, sempre com vistas a um (auto)governamento flexível, porém obstinado, das condutas docentes, operando a reboque da autoridade indefectível do expert, da lógica da desqualificação/requalificação profissional e da apologia da formação permanente, as quais, somadas, redundarão numa acirrada pedagogização do pedagógico

Addressing schemes of self-monitoring of blood glucose in type 2 diabetes: a European perspective and expert recommendation

Self-monitoring of blood glucose (SMBG) in type 2 diabetes has increasingly been shown to display beneficial effects on glycemic control. SMBG is not only associated with a reduction of hemoglobin A1c but has also been demonstrated to increase patients' awareness of the disease. SMBG has also the potential to visualize and predict hypoglycemic episodes. International guidelines by the International Diabetes Federation, the European Society of Cardiology, and the European Association for the Study of Diabetes and also the International Society for Pediatric and Adolescent Diabetes emphasize that SMBG is an integral part of self-management. More recently, two European consensus documents have been published to give recommendations for frequency and timing of SMBG also for various clinical scenarios. Recently, a European expert panel was held to further facilitate and enhance standardized approaches to SMBG. The aim was to present simple, clinically meaningful, and standardized SMBG strategies for type 2 diabetes. The panel recommended a less intensive and an intensive scheme for SMBG across the type 2 diabetes continuum. The length and frequency of SMBG performance depend on the clinical circumstances and the quality of glycemic control. The expert panel also recommended further evaluation of various schemes for SMBG in type 2 diabetes in clinical studies.

The role of self-monitoring of blood glucose in glucagon-like Peptide-1-based treatment approaches: a European expert recommendation

The role of glucagon-like peptide (GLP)-1-based treatment approaches for type 2 diabetes mellitus (T2DM) is increasing. Although self-monitoring of blood glucose (SMBG) has been performed in numerous studies on GLP-1 analogs and dipeptidyl peptidase-4 inhibitors, the potential role of SMBG in GLP-1-based treatment strategies has not been elaborated. The expert recommendation suggests individualized SMBG strategies in GLP-1-based treatment approaches and suggests simple and clinically applicable SMBG schemes. Potential benefits of SMBG in GLP-1-based treatment approaches are early assessment of treatment success or failure, timely modification of treatment, detection of hypoglycemic episodes, assessment of glucose excursions, and support of diabetes management and diabetes education. Its length and frequency should depend on the clinical setting and the quality of metabolic control. It is considered to play an important role for the optimization of diabetes management in T2DM patients treated with GLP-1-based approaches.

Interdisciplinary expert consensus document on management of type B aortic dissection

An expert multidisciplinary panel in the treatment of type B aortic dissection reviewed available literature to develop treatment algorithms using a consensus method. Data from 63 studies published from 2006 to 2012 were retrieved for a total of 1,548 patients treated medically, 1,706 patients who underwent open surgery, and 3,457 patients who underwent thoracic endovascular repair (TEVAR). For acute (first 2 weeks) type B aortic dissection, the pooled early mortality rate was 6.4% with medical treatment and increased to 10.2% with TEVAR and 17.5% with open surgery, mostly for complicated cases. Limited data for treatment of subacute (2 to 6 weeks after onset) type B aortic dissection showed an early mortality rate of 2.8% with TEVAR. In chronic (after 6 weeks) type B aortic dissection, 5-year survival of 60% to 80% was expected with medical therapy because complications were likely. If interventional treatment was applied, the pooled early mortality rate was 6.6% with TEVAR and 8.0% with open surgery. Medical treatment of uncomplicated acute, subacute, and chronic type B aortic dissection is managed with close image monitoring. Hemodynamic instability, organ malperfusion, increasing periaortic hematoma, and hemorrhagic pleural effusion on imaging identify patients with complicated acute type B aortic dissection requiring urgent aortic repair. Recurrence of symptoms, aortic aneurysmal dilation (>55 mm), or a yearly increase of >4 mm after the acute phase are predictors of adverse outcome and need for delayed aortic repair ("complicated chronic aortic dissections"). The expert panel is aware that this consensus document provides proposal for strategies based on nonrobust evidence for management of type B aortic dissection, and that literature results were largely heterogeneous and should be interpreted cautiously.