A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

The Changing Relationship between Supervisors and Subordinates: How Managing This Relationship Evolves over Time

Understanding how the relationship between a subordinate and manager develops over time has been a critical matter both for academics and for business. In both academic journals and industry publications, some writers have argued that the relationship is driven by perceptions of fairness and treatment, and that developing the relationship can lead to better performance. Others have argued that higher performers get better treatment and resources, which results in superior relationships with their managers. There is really no clear answer of what comes first—perceptions of fairness, satisfaction with the supervisor, or job performance—and which leads to which.

On the Use of Regression and Verbal Protocol Analysis in Modeling Analysts’ Behavior in an Unstructured Task Environment: A Methodological Note

This paper discusses areas for future research opportunities by addressing accounting issues faced by management accountants practicing in hospitality organizations. Specifically, the article focuses on the use of the uniform system of accounts by operating properties, the usefulness of allocating support costs to operated departments, extending our understanding of operating costs and performance measurement systems and the certification of practicing accountants.

Digital nonlinear equalization for optical transmission systems

This thesis focuses on digital equalization of nonlinear fiber impairments for coherent optical transmission systems. Building from well-known physical models of signal propagation in single-mode optical fibers, novel nonlinear equalization techniques are proposed, numerically assessed and experimentally demonstrated. The structure of the proposed algorithms is strongly driven by the optimization of the performance versus complexity tradeoff, envisioning the near-future practical application in commercial real-time transceivers. The work is initially focused on the mitigation of intra-channel nonlinear impairments relying on the concept of digital backpropagation (DBP) associated with Volterra-based filtering. After a comprehensive analysis of the third-order Volterra kernel, a set of critical simplifications are identified, culminating in the development of reduced complexity nonlinear equalization algorithms formulated both in time and frequency domains. The implementation complexity of the proposed techniques is analytically described in terms of computational effort and processing latency, by determining the number of real multiplications per processed sample and the number of serial multiplications, respectively. The equalization performance is numerically and experimentally assessed through bit error rate (BER) measurements. Finally, the problem of inter-channel nonlinear compensation is addressed within the context of 400 Gb/s (400G) superchannels for long-haul and ultra-long-haul transmission. Different superchannel configurations and nonlinear equalization strategies are experimentally assessed, demonstrating that inter-subcarrier nonlinear equalization can provide an enhanced signal reach while requiring only marginal added complexity.

On the fly type specialization without type analysis

Les langages de programmation typés dynamiquement tels que JavaScript et Python repoussent la vérification de typage jusqu’au moment de l’exécution. Afin d’optimiser la performance de ces langages, les implémentations de machines virtuelles pour langages dynamiques doivent tenter d’éliminer les tests de typage dynamiques redondants. Cela se fait habituellement en utilisant une analyse d’inférence de types. Cependant, les analyses de ce genre sont souvent coûteuses et impliquent des compromis entre le temps de compilation et la précision des résultats obtenus. Ceci a conduit à la conception d’architectures de VM de plus en plus complexes. Nous proposons le versionnement paresseux de blocs de base, une technique de compilation à la volée simple qui élimine efficacement les tests de typage dynamiques redondants sur les chemins d’exécution critiques. Cette nouvelle approche génère paresseusement des versions spécialisées des blocs de base tout en propageant de l’information de typage contextualisée. Notre technique ne nécessite pas l’utilisation d’analyses de programme coûteuses, n’est pas contrainte par les limitations de précision des analyses d’inférence de types traditionnelles et évite la complexité des techniques d’optimisation spéculatives. Trois extensions sont apportées au versionnement de blocs de base afin de lui donner des capacités d’optimisation interprocédurale. Une première extension lui donne la possibilité de joindre des informations de typage aux propriétés des objets et aux variables globales. Puis, la spécialisation de points d’entrée lui permet de passer de l’information de typage des fonctions appellantes aux fonctions appellées. Finalement, la spécialisation des continuations d’appels permet de transmettre le type des valeurs de retour des fonctions appellées aux appellants sans coût dynamique. Nous démontrons empiriquement que ces extensions permettent au versionnement de blocs de base d’éliminer plus de tests de typage dynamiques que toute analyse d’inférence de typage statique.

How to optimize operational shipping processes of non-production materials? The Volkswagen Autoeuropa case study

Field lab: Entrepreneurial and innovative ventures

Healthcare Network Modeling and Analysis

Part 20: Health and Care Networks

A Risk Analysis Method to Support Virtual Organization Partners’ Selection

Part 17: Risk Analysis

Avaliação de desempenho no Instituto Português de Oncologia, Francisco Gentil de Lisboa

Mestrado em Gestão de Recursos Humanos

Muito além da tecnologia : o impacto dos mecanismos não operacionais na efetividade da governança de TI na administração pública

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Administração, 2016.

Comunidades energéticas sustentáveis: estudo de Implementação de uma comunidade eólica no Algarve

Tese de Doutoramento, Gestão da Inovação e do Território, Faculdade de Economia, Universidade do Algarve, 2016

Lições Aprendidas (Lessons Learned) no Exército Português

As Lições Aprendidas em contexto militar permite reduzir o risco operacional e, simultaneamente, aumentar o grau de sucesso das operações. Desde a década de cinquenta, o Exército português demostrou querer aprender com a experiência, nomeadamente com os Franceses na Argélia e Indochina e com os Ingleses no Quénia e Malásia. Na década de sessenta e início dos anos setenta, durante a denominada Guerra de África, acentuou-se esta necessidade. O Exército Português, desde 2012, dispõe de uma capacidade de Lições Aprendidas, constituída por um processo, estrutura e ferramentas, que tem como principal objetivo, precisamente, facilitar o desiderato de se tornar uma organização aprendente. Neste sentido, é pertinente estudar e comparar estes dois sistema, para melhor perceber o fenómeno no passado e evidenciar a capacidade de hoje em dia. Para isso é necessário descreve-los segundo certos parâmetros ou indicadores. Estes indicadores estão evidentes no modelo criado pela Organização Tratado Atlântico Norte para uma capacidade de Lições Aprendidas. Na Investigação foi utilizado uma abordagem Dedutiva, como procedimentos podemos já depreender que foram utilizados o Histórico e Comparativo, as técnicas de recolha de dados foram as Entrevistas e Análise Documental. O estudo proporcionou a materialização do processo, a perceção da estrutura dedicada, das ferramentas, a influência da mentalidade, liderança, e difusão de informação feitas na guerra de África. Na atualidade, muitos dos indicadores de análise estão descritos em diretivas e doutrina de referência, no entanto é pertinente perceber como é que funcionam e criam melhorias hoje em dia. Conclui-se que o modelo criado pela Organização Tratado Atlântico Norte, que valida uma capacidade de Lições Aprendidas nas organizações militares é intemporal, pois depreende-se, que a lógica que a sustenta em tudo se aplica à guerra de África Portuguesa e à atualidade, o que demostra que esta capacidade é fundamental para tornar o Exército Português mais eficaz e eficiente nas suas atividades e missões futuras.

Optimización financiera de portafolios de inversión en la Bolsa de Valores de Colombia mediante el uso de RGOP

La Bolsa de Valores de Colombia (BVC) ha tenido un impacto reducido en la población colombiana sobre todo debido a la falta de educación financiera y a múltiples casos de corrupción que han opacado su rol en la sociedad -- En general, los colombianos ven con incertidumbre, desconfianza y escepticismo las ventajas de invertir en la bolsa tales como obtener rendimientos superiores que las de las inversiones tradicionales, seguridad en las transacciones y disponibilidad del dinero cuando se requiera, lo que desencadena inversiones en métodos más tradicionales, como los CDT (certificado de depósito a término), con muy bajas tasas de rendimiento, o en negocios que representan altos riesgos -- Dicho comportamiento ha generado que muchas de las inversiones que realiza una persona promedio en Colombia no vayan más allá de productos financieros conocidos, negocios familiares o tradicionales, pirámides o multiniveles que entorpecen el sistema financiero -- Una de las principales barreras encontradas al momento de invertir en la Bolsa de Valores de Colombia son creencias populares tales como: a) es obligatorio tener grandes capitales de dinero, o b) es necesario un conocimiento financiero especializado para invertir -- También resulta incierto para muchos usuarios en cuáles acciones convendría invertir una vez desmitificadas las anteriores creencias -- Para mitigar algunos de dichos inconvenientes, el estudio de portafolios de inversión propone como estrategia principal la diversificación de la inversión y la limitación del riesgo con el fin de crear portafolios altamente eficientes en términos financieros -- Si bien existen múltiples técnicas para la creación y la optimización de portafolios de inversión (por ejemplo: growth optimal portfolio), su uso en Colombia es limitado debido en lo primordial a que es una metodología reciente y a que su implementación no suele ser trivial, puesto que requiere el uso de múltiples herramientas computacionales para ser puesto en práctica -- El presente trabajo de grado presenta la implementación de un algoritmo de optimización robusto, en el sentido de las distribuciones de probabilidad requeridas, llamado portafolio óptimo de crecimiento robusto (robust growth optimal portfolio o RGOP) para acciones de la Bolsa de Valores de Colombia -- Se escogieron varios portafolios al tener en cuenta tres criterios de inclusión para las acciones y se simularon tres escenarios y una suposición con el fin de demostrar la eficacia del algoritmo para minimizar el riesgo de inversión y maximizar la tasa de crecimiento en unos horizontes de tiempo predefinidos -- En último lugar se compararon las rentabilidades de los diferentes portafolios propuestos con las tasas de captación de CDT y CDA (certificados de depósito de ahorro) de bancos populares en Colombia -- La implementación del algoritmo se realizó en la plataforma Matlab y se acudió a varias bibliotecas de modelamiento matemático -- Sin tener en cuentas los costos de transacciones por compra y venta de acciones, los resultados muestran que mientras el sector financiero ofrecía a través de los CDT inferiores de 180 días un promedio de 4.80% de rentabilidad, en un período similar el RGOP arrojaba en promedio 11.83% en los portafolios de inversión de los tres escenarios, es decir, la metodología propuesta ofreció rendimientos superiores a las ofertas de los bancos en 147% para los períodos simulados -- En conclusión, todos los escenarios analizados presentaron mejores rendimientos en la simulación que los rendimientos ofrecidos por los bancos durante el mismo período; se les dio mayor ponderación a las acciones que presentaron tasas de crecimiento mayores de tal forma que se minimizaran los riesgos implícitos de invertir en bolsa -- El RGOP mostró ser una técnica robusta para su uso con acciones de la Bolsa de Valores de Colombia porque ofreció una sólida combinación entre retorno y riesgo para futuros inversionistas