A complex network approach to urban growth

The economic geography can be viewed as a large and growing network of interacting activities. This fundamental network structure and the large size of such systems makes complex networks an attractive model for its analysis. In this paper we propose the use of complex networks for geographical modeling and demonstrate how such an application can be combined with a cellular model to produce output that is consistent with large scale regularities such as power laws and fractality. Complex networks can provide a stringent framework for growth dynamic modeling where concepts from e.g. spatial interaction models and multiplicative growth models can be combined with the flexible representation of land and behavior found in cellular automata and agent-based models. In addition, there exists a large body of theory for the analysis of complex networks that have direct applications for urban geographic problems. The intended use of such models is twofold: i) to address the problem of how the empirically observed hierarchical structure of settlements can be explained as a stationary property of a stochastic evolutionary process rather than as equilibrium points in a dynamics, and, ii) to improve the prediction quality of applied urban modeling.evolutionary economics, complex networks, urban growth

An Observational Framework to the Zipfian Analysis among Different Languages: Studies to Indonesian Ethnic Biblical Texts

The paper introduces the used of Zipfian statistics to observe the human languages by using the same (meaning) corpus/corpora but different in grammatical and structural utterances. We used biblical texts since they contain corpuses that have been most widely and carefully translated into many languages. The idea is to reduce the possibility of noise came from the meaning of the texts in distinctive language. The result is that the robustness of the Zipfian law is observable and some statistical differences are discovered between English and widely used national and several ethnic languages in Indonesia. The paper ends by modestly propose further possible framework in interdisciplinary approaches to human language evolution

Optimization models of natural communication

A family of information theoretic models of communication was introduced more than a decade ago to explain the origins of Zipf’s law for word frequencies. The family is a based on a combination of two information theoretic principles: maximization of mutual information between forms and meanings and minimization of form entropy. The family also sheds light on the origins of three other patterns: the principle of contrast; a related vocabulary learning bias; and the meaning-frequency law. Here two important components of the family, namely the information theoretic principles and the energy function that combines them linearly, are reviewed from the perspective of psycholinguistics, language learning, information theory and synergetic linguistics. The minimization of this linear function is linked to the problem of compression of standard information theory and might be tuned by self-organization.Peer ReviewedPostprint (author's final draft

Stochastic models and graph theory for Zipf's law

In questo elaborato ci siamo occupati della legge di Zipf sia da un punto di vista applicativo che teorico. Tale legge empirica afferma che il rango in frequenza (RF) delle parole di un testo seguono una legge a potenza con esponente -1. Per quanto riguarda l'approccio teorico abbiamo trattato due classi di modelli in grado di ricreare leggi a potenza nella loro distribuzione di probabilità. In particolare, abbiamo considerato delle generalizzazioni delle urne di Polya e i processi SSR (Sample Space Reducing). Di questi ultimi abbiamo dato una formalizzazione in termini di catene di Markov. Infine abbiamo proposto un modello di dinamica delle popolazioni capace di unificare e riprodurre i risultati dei tre SSR presenti in letteratura. Successivamente siamo passati all'analisi quantitativa dell'andamento del RF sulle parole di un corpus di testi. Infatti in questo caso si osserva che la RF non segue una pura legge a potenza ma ha un duplice andamento che può essere rappresentato da una legge a potenza che cambia esponente. Abbiamo cercato di capire se fosse possibile legare l'analisi dell'andamento del RF con le proprietà topologiche di un grafo. In particolare, a partire da un corpus di testi abbiamo costruito una rete di adiacenza dove ogni parola era collegata tramite un link alla parola successiva. Svolgendo un'analisi topologica della struttura del grafo abbiamo trovato alcuni risultati che sembrano confermare l'ipotesi che la sua struttura sia legata al cambiamento di pendenza della RF. Questo risultato può portare ad alcuni sviluppi nell'ambito dello studio del linguaggio e della mente umana. Inoltre, siccome la struttura del grafo presenterebbe alcune componenti che raggruppano parole in base al loro significato, un approfondimento di questo studio potrebbe condurre ad alcuni sviluppi nell'ambito della comprensione automatica del testo (text mining)

An Analysis of Major Acquisition Reforms through Text Mining and Grounded Theory Design

Cost growth is an established phenomenon within Defense Acquisition that the US Government has attempted to abolish for decades through seemingly endless cycles of reform. Dozens of experts and senior leaders within the acquisition community have published their notions on the reasons for cost growth, nevertheless, legislation has yet to eradicate this presumed conundrum. For this reason, this research is aimed at identifying existing trends within past major Defense Acquisition Reform legislation, as well as in a compendium of views from leaders within the Defense Acquisition community on the efficacy of acquisition reform, to determine the possible disconnect. To accomplish this goal, this research takes a qualitative approach, utilizing various Text Mining methodologies (word frequency, word relationships, term frequency-inverse document frequency, sentiment analysis, and topic modeling), along with Grounded Theory Design, to analyze the major reforms and expert views. The results of this research corroborate the current literature’s claim that past Defense Acquisition reforms have not been able to sufficiently address the root causes of cost growth, and identifies six potential root causes of cost growth: Strategy, the Industrial Base, Risk Management, the Requirements and Research, Development, Test, and Evaluation (RDT&E) Processes, the Workforce, and Cost Estimates and the Planning, Programming, Budget, and Execution (PPBE) Process