Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Credibility theory-based available transfer capability assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

Encouraging the intellectual craft of living research:tattoos, theory and time

This chapter contributes to the anthology on learning to research - researching to learn because it emphases a need to design curricula that enables living research, and on-going researcher development, rather than one that restricts student and staff activities, within a marketised approach towards time. In recent decades higher education (HE) has come to be valued for its contribution to the global economy. Referred to as the neo-liberal university, a strong prioritisation has been placed on meeting the needs of industry by providing a better workforce. This perspective emphasises the role of a degree in HE to secure future material affluence, rather than to study as an on-going investment in the self (Molesworth , Nixon & Scullion, 2009: 280). Students are treated primarily as consumers in this model, where through their tuition fees they purchase a product, rather than benefit from the transformative potential university education offers for the whole of life.Given that HE is now measured by the numbers of students it attracts, and later places into well-paid jobs, there is an intense pressure on time, which has led to a method where the learning experiences of students are broken down into discrete modules. Whilst this provides consistency, students can come to view research processes in a fragmented way within the modular system. Topics are presented chronologically, week-by-week and students simply complete a set of tasks to ‘have a degree’, rather than to ‘be learners’ (Molesworth , Nixon & Scullion, 2009: 277) who are living their research, in relation to their own past, present and future. The idea of living research in this context is my own adaptation of an approach suggested by C. Wright Mills (1959) in The Sociological Imagination. Mills advises that successful scholars do not split their work from the rest of their lives, but treat scholarship as a choice of how to live, as well as a choice of career. The marketised slant in HE thus creates a tension firstly, for students who are learning to research. Mills would encourage them to be creative, not instrumental, in their use of time, yet they are journeying through a system that is structured for a swift progression towards a high paid job, rather than crafted for reflexive inquiry, that transforms their understanding throughout life. Many universities are placing a strong focus on discrete skills for student employability, but I suggest that embedding the transformative skills emphasised by Mills empowers students and builds their confidence to help them make connections that aid their employability. Secondly, the marketised approach creates a problem for staff designing the curriculum, if students do not easily make links across time over their years of study and whole programmes. By researching to learn, staff can discover new methods to apply in their design of the curriculum, to help students make important and creative connections across their programmes of study.

Műszaki és gazdasági hatékonyság Koopmans termeléselméletében (Technical and economic efficiency in Koopmans' theory of production)

Koopmans gyakorlati problémák megoldása során szerzett tapasztalatait általánosítva fogott hozzá a lineáris tevékenységelemzési modell kidolgozásához. Meglepődve tapasztalta, hogy a korabeli közgazdaságtan nem rendelkezett egységes, kellően egzakt termeléselmélettel és fogalomrendszerrel. Úttörő dolgozatában ezért - mintegy a lineáris tevékenységelemzési modell elméleti kereteként - lerakta a technológiai halmazok fogalmán nyugvó axiomatikus termeléselmélet alapjait is. Nevéhez fűződik a termelési hatékonyság és a hatékonysági árak fogalmának egzakt definíciója, s az egymást kölcsönösen feltételező viszonyuk igazolása a lineáris tevékenységelemzési modell keretében. A hatékonyság manapság használatos, pusztán műszaki szempontból értelmezett definícióját Koopmans csak sajátos esetként tárgyalta, célja a gazdasági hatékonyság fogalmának a bevezetése és elemzése volt. Dolgozatunkban a lineáris programozás dualitási tételei segítségével rekonstruáljuk ez utóbbira vonatkozó eredményeit. Megmutatjuk, hogy egyrészt bizonyításai egyenértékűek a lineáris programozás dualitási tételeinek igazolásával, másrészt a gazdasági hatékonysági árak voltaképpen a mai értelemben vett árnyékárak. Rámutatunk arra is, hogy a gazdasági hatékonyság értelmezéséhez megfogalmazott modellje az Arrow-Debreu-McKenzie-féle általános egyensúlyelméleti modellek közvetlen előzményének tekinthető, tartalmazta azok szinte minden lényeges elemét és fogalmát - az egyensúlyi árak nem mások, mint a Koopmans-féle hatékonysági árak. Végezetül újraértelmezzük Koopmans modelljét a vállalati technológiai mikroökonómiai leírásának lehetséges eszközeként. Journal of Economic Literature (JEL) kód: B23, B41, C61, D20, D50. /===/ Generalizing from his experience in solving practical problems, Koopmans set about devising a linear model for analysing activity. Surprisingly, he found that economics at that time possessed no uniform, sufficiently exact theory of production or system of concepts for it. He set out in a pioneering study to provide a theoretical framework for a linear model for analysing activity by expressing first the axiomatic bases of production theory, which rest on the concept of technological sets. He is associated with exact definition of the concept of production efficiency and efficiency prices, and confirmation of their relation as mutual postulates within the linear model of activity analysis. Koopmans saw the present, purely technical definition of efficiency as a special case; he aimed to introduce and analyse the concept of economic efficiency. The study uses the duality precepts of linear programming to reconstruct the results for the latter. It is shown first that evidence confirming the duality precepts of linear programming is equal in value, and secondly that efficiency prices are really shadow prices in today's sense. Furthermore, the model for the interpretation of economic efficiency can be seen as a direct predecessor of the Arrow–Debreu–McKenzie models of general equilibrium theory, as it contained almost every essential element and concept of them—equilibrium prices are nothing other than Koopmans' efficiency prices. Finally Koopmans' model is reinterpreted as a necessary tool for microeconomic description of enterprise technology.

Viability Theory and Economic Modeling

A brief introduction into the theory of differential inclusions, viability theory and selections of set valued mappings is presented. As an application the implicit scheme of the Leontief dynamic input-output model is considered.

Kornai’s DRSE Theory Versus General Equilibrium Theory

János Kornai’s DRSE theory (Kornai, 2014) follows the ex post model philosophy which radically rejects the ex ante set of conditions laid down by the dominant neoclassical school and the stringent limits of equilibrium, and defines its own premises for the functioning of capitalist economy. In other words, the DRSE theory represents an extremely novel trend among the various schools of economics. The theory is still only a verbal model with the following supporting pillars as the immanent features of the capitalist system: dynamism, rivalry and the surplus economy. (The English name of the theory uses the initial letters of the terms Dynamism, Rivalry, Surplus Economy). The dominance of the surplus economy, that is, oversupply is replaced by monopolistic competition, uncertainty over the volume of demand, Schumpeterian innovation, dynamism, technological progress, creative destruction and increasing return to scale with rivalry between producers and service providers for markets. This paper aims to examine whether the DRSE theory can be formulated as a formal mathematical model. We have chosen a special route to do this: first we explore the unreal ex ante assumptions of general equilibrium theory (Walras, 1874; Neumann, 1945), and then we establish some of the possible connections between the premises of DRSE, which include the crucial condition that just like in biological evolution, there is no fixed steady state in the evolutionary processes of market economy, not even as a point of reference. General equilibrium theory and DRSE theory are compared in the focus of Schumpeterian evolutionary economics.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Segmentação fuzzy de objetos tridimensionais com propriedades texturais

Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

A Theory and Test of How Speakers with Nonnative Accents are Evaluated in Entrepreneurial Settings

An abundance of research in the social sciences has demonstrated a persistent bias against nonnative English speakers (Giles & Billings, 2004; Gluszek & Dovidio, 2010). Yet, organizational scholars have only begun to investigate the underlying mechanisms that drive the bias against nonnative speakers and subsequently design interventions to mitigate these biases. In this dissertation, I offer an integrative model to organize past explanations for accent-based bias into a coherent framework, and posit that nonnative accents elicit social perceptions that have implications at the personal, relational, and group level. I also seek to complement the existing emphasis on main effects of accents, which focuses on the general tendency to discriminate against those with accents, by examining moderators that shed light on the conditions under which accent-based bias is most likely to occur. Specifically, I explore the idea that people’s beliefs about the controllability of accents can moderate their evaluations toward nonnative speakers, such that those who believe that accents can be controlled are more likely to demonstrate a bias against nonnative speakers. I empirically test my theoretical model in three studies in the context of entrepreneurial funding decisions. Results generally supported the proposed model. By examining the micro foundations of accent-based bias, the ideas explored in this dissertation set the stage for future research in an increasingly multilingual world.

Technology is Set to Change Real Estate Forever

Major developments in the technological environment can become commonplace very quickly. They are now impacting upon a broad range of information-based service sectors, as high growth Internet-based firms, such as Google, Amazon, Facebook and Airbnb, and financial technology (Fintech) start-ups expand their product portfolios into new markets. Real estate is one of the information-based service sectors that is currently being impacted by this new type of competitor and the broad range of disruptive digital technologies that have emerged. Due to the vast troves of data that these Internet firms have at their disposal and their asset-light (cloud-based) structures, they are able to offer highly-targeted products at much lower costs than conventional brick-and-mortar companies.

Gráficos de controle: aspectos teóricos e práticos a partir da ótica da lógica formal e da lógica fuzzy

O presente trabalho faz um enlace de teorias propostas por dois trabalhos: Transformação de valores crisp em valores fuzzy e construção de gráfico de controle fuzzy. O resultado desse enlace é um gráfico de controle fuzzy que foi aplicado em um processo de produção de iogurte, onde as variáveis analisadas foram: Cor, Aroma, Consistência, Sabor e Acidez. São características que dependem da percepção dos indivíduos, então a forma utilizada para coletar informações a respeito de tais característica foi a análise sensorial. Nas analises um grupo denominado de juízes, atribuía individualmente notas para cada amostra de iogurte em uma escala de 0 a 10. Esses valores crisp, notas atribuídas pelos juízes, foram então, transformados em valores fuzzy, na forma de número fuzzy triangular. Com os números fuzzy, foram construídos os gráficos de controle fuzzy de média e amplitude. Com os valores crisp foram construídos gráficos de controle de Shewhart para média e amplitude, já consolidados pela literatura. Por fim, os resultados encontrados nos gráficos tradicionais foram comparados aos encontrados nos gráficos de controle fuzzy. O que pode-se observar é que o gráfico de controle fuzzy, parece satisfazer de forma significativa a realidade do processo, pois na construção do número fuzzy é considerada a variabilidade do processo. Além disso, caracteriza o processo de produção em alguns níveis, onde nem sempre o processo estará totalmente em controle ou totalmente fora de controle. O que vai ao encontro da teoria fuzzy: se não é possível prever com exatidão determinados resultados é melhor ter uma margem de aceitação, o que implicará na redução de erros.

Modelagem em programação linear para resolução de jogos fuzzy intervalares

A teoria de jogos modela estratégias entre agentes (jogadores), os quais possuem recompensas ao fim do jogo conforme suas ações. O melhor par de estratégias para os jogadores constitui uma solução de equilíbrio. Porém, nem sempre se consegue estimar os dados do problema. Diante disso, os parâmetros incertos presentes em modelos de jogos são formalizados pela teoria fuzzy. Assim, a teoria fuzzy auxilia a teoria de jogos, formando jogos fuzzy. Dessa forma, parâmetros, como as recompensas, tornam-se números fuzzy. Mais ainda, quando há incerteza na representação desses números fuzzy utilizam-se os números fuzzy intervalares. Então, neste trabalho modelos de jogos fuzzy intervalares são analisados e métodos computacionais são desenvolvidos para a resolução desses jogos. Por fim, realizam-se simulações de programação linear para observar melhor a aplicação das teorias estudadas e avaliar a proposta.

What Does Value Matter? The Interest-Relational Theory of the Semantics and Metaphysics of Value

Value and reasons for action are often cited by rationalists and moral realists as providing a desire-independent foundation for normativity. Those maintaining instead that normativity is dependent upon motivation often deny that anything called '"value" or "reasons" exists. According to the interest-relational theory, something has value relative to some perspective of desire just in case it satisfies those desires, and a consideration is a reason for some action just in case it indicates that something of value will be accomplished by that action. Value judgements therefore describe real properties of objects and actions, but have no normative significance independent of desires. It is argued that only the interest-relational theory can account for the practical significance of value and reasons for action. Against the Kantian hypothesis of prescriptive rational norms, I attack the alleged instrumental norm or hypothetical imperative, showing that the normative force for taking the means to our ends is explicable in terms of our desire for the end, and not as a command of reason. This analysis also provides a solution to the puzzle concerning the connection between value judgement and motivation. While it is possible to hold value judgements without motivation, the connection is more than accidental. This is because value judgements are usually but not always made from the perspective of desires that actually motivate the speaker. In the normal case judgement entails motivation. But often we conversationally borrow external perspectives of desire, and subsequent judgements do not entail motivation. This analysis drives a critique of a common practice as a misuse of normative language. The "absolutist" attempts to use and, as philosopher, analyze normative language in such a way as to justify the imposition of certain interests over others. But these uses and analyses are incoherent - in denying relativity to particular desires they conflict with the actual meaning of these utterances, which is always indexed to some particular set of desires.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.