How Entropic Regression Beats the Outliers Problem in Nonlinear System Identification

In this work, we developed a nonlinear System Identification (SID) method that we called Entropic Regression. Our method adopts an information-theoretic measure for the data-driven discovery of the underlying dynamics. Our method shows robustness toward noise and outliers and it outperforms many of the current state-of-the-art methods. Moreover, the method of Entropic Regression overcomes many of the major limitations of the current methods such as sloppy parameters, diverse scale, and SID in high dimensional systems such as complex networks. The use of information-theoretic measures in entropic regression poses unique advantages, due to the Asymptotic Equipartition Property (AEP) of probability distributions, that outliers and other low-occurrence events are conveniently and intrinsically de-emphasized as not-typical, by definition. We provide a numerical comparison with the current state-of-the-art methods in sparse regression, and we apply the methods to different chaotic systems such as the Lorenz System, the Kuramoto-Sivashinsky equations, and the Double Well Potential

The Prospective Researches as Approach in Planning for Development in New Urban Communities

The purpose of this study is to identify the relationship between Prospective Researches and planning for social, economic, environmental and health development in new urban communities. The study used a comprehensive social survey for the employees of the new city of Assiut Governorate, which has 300 employees. The researcher used 100 members of the study community to verify the validity and consistency of the tool used in the study. The study was conducted in the hope of studying the relationship between uses of prospective researches and planning for the development of new urban communities in Assiut Governorate. The study included the employees of the new city of Assiut, which has 300 employees. The selection of participants was based on comprehensive Social survey techniques. The data were collected in 2018. The researcher created a model with an introduction letter. He then asked all participants to fill out this letter with the title of study, nature, purpose and name of the participant. The data collection period lasted about 25 days. The results of the study indicate that a strong positive relationship expected between Prospective Researches and planning for social, economic, environmental and health

Programming the Interactions of Collective Adaptive Systems by Relying on Attribute-based Communication

Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and interdependent, and are operating in dynamic and possibly unpredictable environments. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavour. In this article we propose a language-based approach for programming the interactions of collective-adaptive systems by relying on attribute-based communication; a paradigm that permits a group of partners to communicate by considering their run-time properties and capabilities. We introduce AbC, a foundational calculus for attribute-based communication and show how its linguistic primitives can be used to program a complex and sophisticated variant of the well-known problem of Stable Allocation in Content Delivery Networks. Also other interesting case studies, from the realm of collective-adaptive systems, are considered. We also illustrate the expressive power of attribute-based communication by showing the natural encoding of other existing communication paradigms into AbC

A Behavioural Theory for Interactions in Collective-Adaptive Systems

We propose a process calculus, named AbC, to study the behavioural theory of interactions in collective-adaptive systems by relying on attribute-based communication. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interaction among components is dynamically established by taking into account "connections" as determined by predicates over their attributes. The structural operational semantics of AbC is based on Labeled Transition Systems that are also used to define bisimilarity between components. Labeled bisimilarity is in full agreement with a barbed congruence, defined by simple basic observables and context closure. The introduced equivalence is used to study the expressiveness of AbC in terms of encoding broadcast channel-based interactions and to establish formal relationships between system descriptions at different levels of abstraction

On Expressiveness and Behavioural Theory of Attribute-based Communication

Attribute-based communication is an interesting alternative to broadcast and binary communication when providing abstract models for the so called Collective Adaptive Systems which consist of a large number of interacting components that dynamically adjust and combine their behavior to achieve specifc goals. A basic process calculus, named AbC, is introduced whose primary primitive for interaction is attribute-based communication. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interactions among components are dynamically established by taking into account\connections" as determined by predicates over the attributes exposed by components. First, the syntax and the semantics of AbC are presented, then expressiveness and effectiveness of the calculus are demonstrated both in terms of the ability to model scenarios featuring collaboration, reconfiguration, and adaptation and of the possibility of encoding a process calculus for broadcasting channel-based communication and other communication paradigms. Behavioral equivalences for AbC are introduced for establishing formal relationships between different descriptions of the same system

A calculus for attribute-based communication

The notion of attribute-based communication seems promising to model and analyse systems with huge numbers of interacting components that dynamically adjust and combine their behaviour to achieve specific goals. A basic process calculus, named AbC, is introduced that has as primitive construct exactly attribute-based communication and its impact on the above mentioned kind of systems is considered. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in a broadcast fashion and communication links among components are dynamically established by taking into account interdependences determined by predicates over attributes. First, the syntax and the reduction semantics of AbC are presented, then its expressiveness and effectiveness is demonstrated by modelling two scenarios from the realm of TV streaming channels. An example of how well-established process calculi could be encoded into AbC is given by considering the translation into AbC of a prototypical π-calculus process

Finance, Financial Services, and Economics Growth How Does the Size of the Financial Sector and Different Types of Financial Services Impact Economic Growth?

This paper studies the relationship between finance, financial services, and economic growth. More particularly, this study attempts to answer the following two questions: What is the relationship between the size of the financial sector and economic growth? And how do different types of financial services impact economic growth? Understanding the dynamics between the financial sector and economic growth is extremely important from an intellectual as well as practical perspective. Intellectually speaking, it is safe to say that finance as a sector and financial services in general do not have a very good reputation in popular culture, especially in the post 2008 world. Hence, understanding the how finance impact economic growth will put the public opinion of finance to test. Practically speaking, understanding the relationship between finance and growth is extremely important from a public policy and regulatory perspective since finance has proven itself to be impactful and relevant after it sent the global economy into a the deepest recession in a century. If policy makers have insights on the relationship between finance and social wellbeing, they will be able to assess whether (1) this relationship is linearly positive or whether it diminishes at some point. If finance impacts society positively up to a point, policy makers will be able to create regulation that disincentives the size of the financial sector to grow beyond healthy levels. At the same time, if policy makers had insight on (B) which financial activities/services are more harmful to social welling than others, then they will be able to create an incentive system or a legal framework that encourages certain type of activities while limiting others

A distributed API for coordinating AbC programs

Collective adaptive systems exhibit a particular notion of interaction where environmental conditions largely influence interactions. Previously, we proposed a calculus, named AbC, to model and reason about CAS. The calculus proved to be effective by naturally modelling essential CAS features. However, the question on the tradeoff between its expressiveness and its efficiency, when implemented to program CAS applications, is to be answered. In this article, we propose an efficient and distributed coordination infrastructure for AbC. We prove its correctness, and we evaluate its performance. The main novelty of our approach is that AbC components are infrastructure agnostic. Thus the code of a component does not specify how messages are routed in the infrastructure but rather what properties a target component must satisfy. We also developed a Go API, named GoAt, and an Eclipse plugin to program in a high-level syntax which can be automatically used to generate matching Go code. We showcase our development through a non-trivial case study