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Strategic Reasoning for Enterprise Architectures: The SIENA Modeling Framework
Get PDFThis thesis contributes to the area of Enterprise Modeling by proposing the SIENA modeling framework for the representation of strategic enterprise architectures and automated reasoning with such models. In this work, we provide the SIENA language that provides abstractions for capturing enterprise’s motivational elements (i.e. goals of different shades like mission, vision, strategic, tactical and operational goals) and their connections with behavioral elements (i.e., operations, business processes, commitments and activities) through which they are operationalized. The SIENA language also introduces the distinguishing feature of dimensional refinement operators, a new operator that can be used for the refinement of strategic goals in terms of time, location and products/services dimensions. SIENA language is also accompanied by modeling guidelines for the construction of its models. Besides the SIENA language, we also propose a business process language called Azzurra which is founded on the primitives of commitments and protocols for the representation of business processes. The representation of business processes in terms of commitments is a distinguishing feature of our approach. Further, our framework also supports the design of business processes specified using the Azzurra language from SIENA operational goals. As one of the greatest advantages of conducting enterprise modeling is to gain the ability to perform automated analysis using enterprise models, we also propose a formal reasoning technique for the automated generation of strategic plans subject to constraints to satisfy enterprise’s strategic goals. The overall approach is validated by means of a number of different activities, including self-evaluation, experimentation and in-depth case studies with novices
Structural Kernels and Neural Network Models for Question Answering Systems
Get PDFTree kernels and neural networks are powerful machine learning models for extracting patterns from data. Tree kernels compute the similarity between two tree-structured text representations that may incorporate syntactic and semantic information. Neural networks map words into informative embeddings, and learn complex non-linear decision functions by applying a number of transformations to the input. Joining the two approaches is an exciting research direction. In this work, which is set in a Question Answering (QA) context, we apply the individual models to classification and ranking tasks. More importantly, we explore the intersection of tree kernels and neural networks, with the goal of developing more accurate models.
Initially, we focus on a challenging QA task, the resolution of Crossword Puzzles (CPs), and improve an automatic CP solver by tackling two problems: (i) answering crossword clues by reranking snippets from a search engine, and (ii) clue paraphrasing, which is extremely useful for finding clues with the same answers. We apply reranking models based on syntactic structures, and therefore tree kernels, to increase the accuracy and speed of the solver. In addition, we design and evaluate a composite kernel that combines a kernel over structures, and a kernel on neural network induced representations.
Going beyond the neural feature vector approach, we develop a structural kernel that exploits a deep siamese network for evaluating the similarity between words. We assess the resulting model on two classification tasks: question classification and sentiment analysis.
To conclude, we study QA models that establish links between question and candidate answer passages using semantic information. First, we present our tree kernel model for answer sentence selection, which captures relations between important question words and entities in the answer. Then, we build a neural network model that can be trained to extract semantic features from text, and eventually establish links between text pairs. We show that such network is able to better model the notion of question-answer relatedness on several QA datasets, compared to the tree kernel model
Spatial representation from birth to old age: Insights from comparative neurobiology and behavioral genomics.
Get PDFFinding one’s way back to a safe refuge or recalling the best place to find food is essential to all animals including human beings. We engage in future actions based on past events. So how does our brain compute such important cognitive tasks? Is it an innate ability we have from birth that is hardwired into the blueprint of our brains? And what happens if for some reason we realize that we are unable to perform these cognitive abilities in old age or due to a neurological disorder?
The hippocampus is the main area of the brain involved in memory and learning. Animal studies show evidence of its role in spatial navigation and memory. The complex network of spatial cells in the hippocampus, all participate in constructing a cognitive map in the brain, where an animal stores information about the external environment and uses it to engage in future actions. However, despite the importance in its function, the hippocampus is also one of the first areas of the brain to be affected by aging and other neurological disorders.
The present thesis used the help of various animal models to answer three questions: first whether hippocampal function is present immediately at birth, second whether genes can regulate hippocampal activity and third whether a sensitive task such as reorientation can highlight hippocampal alteration caused by age. To answer the first question, we used the domestic chick that has the advantage of being tested after hatching. We show evidence that a change in environmental shape can alter hippocampal activity in naïve chicks, suggesting that hippocampal function is present already in early stages of life. Furthermore, we investigated if genes regulate hippocampal activity. We used a mouse model that carried one half of the Williams syndrome deletion, a disorder known for its hippocampal deficit. We show evidence that genes on the proximal deletion of Williams syndrome deletion, can alter reorientation and episodic memory, two hippocampal related functions. Finally, we aimed to find an appropriate task to highlight the allocentric difficulty that arises in age. We used aged animals of two species (mice and rats) and tested them in the reorientation paradigm. We show that this simple task has potential to be a better suited assay to evaluate hippocampal behavior
Bifurcations and instability in non-linear elastic solids with interfaces
Get PDFThe study of local and global instability and bifurcation phenomena is crucial for many engineering applications in the field of solid mechanics.
In particular, interfaces within solid bodies are of great importance in the bifurcation analysis, as they constitute localized zones in which discontinuities or jumps in displacement, strain or stress may occur. Different instability phenomena, heavily conditioned by the presence of interfaces, were analyzed in the present thesis.
The first phenomenon that has been considered is the propagation of a shear band, which is a localized shear deformation developing in a ductile material. This shear band, assumed to be already present inside of a ductile
matrix material (obeying von Mises plasticity with linear hardening), is modelled as a discontinuity interface following two different approaches.
In the first approach, the conditions describing the behavior of a layer of material in which localized strain develop are introduced and implemented in a finite element computer code. A shear deformation is simulated by imposing appropriate displacement conditions on the boundaries of the matrix material, in which the shear band is present and modelled through an imperfect interface, having null thickness.
The second approach is based on a perturbative technique, developed for a J2-deformation theory material, in which the shear band is modeled as the emergence of a discontinuity surface for displacements at a certain stage of a uniform deformation process, restricted to plane strain conditions.
Both the approaches concur in showing that shear bands (differently from cracks) propagate rectilinearly under shear loading and that a strong stress concentration is expected to be present at the tip of the shear band, two key features in the understanding of failure mechanisms of ductile materials [results of this study have been reported in (Bordignon et al. 2015)].
The second type of interface analyzed in the present thesis is a perfectly frictionless sliding interface, subject to large deformations and assumed to be present within a uniformly strained nonlinear elastic solid. This type of interface may model lubricated sliding contact between soft solids, a topic of interest in biomechanics and for the design of small-scale engineering devices.
The analyzed problem is posed as follows. Two elastic nonlinear solids are considered jointed through a frictionless and bilateral surface, so that continuity of the normal component of the Cauchy traction holds across the surface, but the tangential component is null. Moreover, the displacement can develop only in a way that the bodies in contact do neither detach, nor overlap. Surprisingly, this finite strain problem has not been correctly formulated until now, so that this formulation has been developed in the thesis. The incremental equations are shown to be non-trivial and different from previously (and erroneously) employed conditions. In particular, an exclusion condition for bifurcation is derived to show that previous formulations based on frictionless contact or ‘spring-type’ interfacial conditions are not able to predict bifurcations in tension, while experiments (one of which, ad hoc designed, is reported) show that these bifurcations are a reality and can be predicted when the correct sliding interface model is used. Therefore, the presented approach introduces a methodology for the determination of bifurcations and instabilities occurring during lubricated sliding between soft bodies in contact [results of this study have been reported in (Bigoni et al. 2018)]
Model Order Reduction and its Application to an Inverse Electroencephalography Problem
Get PDFModel order reduction is a technique to reduce computational times of parameterized PDEs while maintaining good accuracy of the approximated solution. Reduced basis methods (RB) are the most common algorithms for reducing the complexity of parameterized PDEs and nowadays they are widely applied and very actively researched in numerous fields. We propose two ideas to further enhance model reduction: the Fundamental Order Reduction Method (FOR) and offline error estimators for RB methods. The FOR method uses nonlinear combinations of the solutions to build the reduced model and use simple affine evaluations to execute the online stage. On the other hand, offline estimators are a class of estimators that move a-posteriori operations to the offline stage, reducing in this way the load of computations in the online stage. We apply these two ideas to an EEG equation which is useful for detecting the position where an epilepsy seizure begins inside the brain. We present two known ways to solve this equation: direct approach and subtraction approach, and show theoretical and numerical results of the application of the RB and FOR methods. We prove that is not feasible to apply model reduction in the direct approach but show that it is possible in the subtraction approach. Afterwards we solve the inverse problem associated with the EEG equation using a combination of the FOR method and neural networks
Enabling Novel Interactions between Applications and Software-Defined Networks
Get PDFOver the last few decades the pervasive diffusion of software has greatly simplified the introduction of new functionalities: updates that used to require complex and expensive re-engineering of physical devices can now be
accomplished almost at the push of a button.
In the context of telecommunications networks, recently modernized by the emergence of the Software-Defined Networking (SDN) paradigm, software has manifested in the form of self-contained applications driving the behavior of the control plane of the network. Such SDN controller applications can introduce profound changes and novel functionalities to large deployed networks without requiring downtime or any changes to deployed boxes, a revolutionary approach compared to current best practices, and which greatly simplifies, perhaps even enables, solving the challenges in the provisioning of network resources imposed by modern distributed business applications consuming a network’s services (e.g., bank communication systems, smart cities, remote surgery, etc.). This thesis studies three types of interaction between business applications, SDN controller applications and networks with the aim of optimizing the network response to a consumer’s needs.
First, a novel interaction paradigm between SDN controller applications and networks is proposed in order to solve a potential configuration problem of SDN networks, which is caused by the limited memory capacity of SDN devices. An algorithm that offers a virtual memory to the network devices is designed and implemented in a SDN application. This interaction shows an increase of the amount of traffic that a SDN device can process in the case of memory overflows. Second, an interaction between business applications and SDN networks shows how it is possible to reduce the blocking probability of service requests in application-centric networks. A negotiation scheme based on an Intent paradigm is presented. Business applications can request connectivity service, receive several alternative solutions from the network based on a degradation of requirements and provide a feedback.
Last, an interaction between business applications, SDN controller applications and networks is defined in order to increase the number of ad-hoc connectivity services offered by network operators to customers. Several service providers can implement a connectivity service in the form of SDN applications and offer them via a SDN App Store on top of a SDN network controller. The App Store demonstrates a lower overhead for the introduction of customized connectivity services
Lettere mercantili in volgare parmense: il carteggio dei Garso
Get PDFIl lavoro presenta l’edizione di un corpus di lettere mercantili in volgare, risalenti all’ultimo ventennio del Trecento, inviate da alcuni esponenti della famiglia parmense dei Garso al fondaco di Francesco di Marco Datini a Pisa, oggi conservate presso il fondo Datini dell’Archivio di Stato di Prato. L’edizione dei 64 testi (finora inediti, ad eccezione di uno) è accompagnata da un commento linguistico che si propone di individuare, accanto ai fenomeni genericamente settentrionali da una parte e alle tracce di contaminazione linguistica con il toscano dall’altra, alcuni tratti caratteristici del volgare parmense. Conclude il lavoro un glossario selettivo che raccoglie il materiale lessicale di uso locale, così come gli elementi riconducibili al formulario mercantile medievale
Under Siege: Counter-Terrorism Policy and Civil Society in Hungary
No full textImmediately after the 9/11 attacks the US launched a macro-securitization program to combat terrorism and included government counter-terrorism measures (CTMs) that impeded on human rights and civil liberties globally. Scholarship has recently turned to the study of CTMs and their effects on civil society organizations (CSOs). This study analyzes the relationship between CTMs and CSOs in Hungary from 2010-2018. First, it examines Hungary’s security milieu, including the formation and implementation of Hungary’s CT laws, polices, and institutions, and the terrorism landscape. Second, it analyzes the effects of CTMs on CSOs and state-civil society relations.
The study uses an exploratory and explanatory research design, and mixed methods of data collection and analysis. Using purposive sampling, 240 questionnaires were analyzed across four CSO categories: peacebuilding, development, human rights advocacy, and humanitarianism. Coded data is used from 70 semi-structured, in-depth interviews with CSO officers, security agents, military personnel, legal experts, politicians, and security, civil society, and development scholars. Secondary sources include: books, articles, and grey literature. Using Chi Square and Pearson Product-Moment Correlation at p≤0.05, the former determines if CSOs were pressured to join government CTMs whereas the latter establishes whether CTMs negatively impacted CSOs’ operational capacities. Descriptive statistics is used to analyze demographic data and ascertain CSOs’ level of support or rejection of government CTMs.
The findings reveal that CTMs grant the state exceptional powers that restrict CSO operations. The quantitative findings show that CSOs were pressured into joining government CTMs (X2 = 220.919). Government CTMs have negatively affected CSOs’ operational costs (59.1%). The government denies CSOs access to information regarding CTMs (35.9%), thus preventing their involvement in CTM formulation processes and implementation. 72.1% of program officers indicated they do not support government CTMs. The interviews revealed growing mutual suspicion between the government and CSOs in the context of counter-terrorism
Changing ties, ambivalent connections: mobilities and networks of Filipinos in London and New York metropolitan areas
Get PDFThe role of social networks in creating and sustaining migration flows, as well as in the adjustment and settlement of migrants, has long been recognized in migration studies. However, cross-fertilization between migration research and network approaches is still uncommon. Utilizing a mixed-method network approach, this study contributes in furthering the understanding of how migrant networks operate. Migrant networks are conceptualized as embedded in dynamic and changing systems, and shown as evolving depending on various contexts and situations.
Examined are ego-centric networks of the 134 respondents (58 in London and 76 in New York) in three migration phases: before coming to London or New York; initial period of adjustment; and the current network as a result of the subsequent process of settlement in the place of destination (in total, 402 network maps). In particular, compared are three different occupational groups – nurses, domestics, and care workers. Conceptually dividing the migration process in three phases provided the opportunity to study network dynamics and networking practices, albeit retrospectively. Eliciting migrant networks was embedded within in-depth interviews using both electronic and paper-based network visualization.
The findings suggest contrasting network composition in two global cities and across the three occupational groups. In New York, familial ties play an almost exclusive role in facilitating and supporting the movement of Filipino migrants. In London, most of the research participants relied on former employers (in the case of domestic workers) or recruitment agencies (in the case of nurses and care workers in institutional facilities) to facilitate their move. These differences in pre-migration networks then shaped subsequent network formations, adjustments, and settlement experiences. Findings also illustrate that although networks have supportive influence on facilitation of the move and post-migration settlement, familial and co-ethnic ties can also be exploitative to the newly-arrived and undocumented migrants.
Situating the particular cases in macro-level context, the study explores how the narratives of attaining the good life through overseas work are interconnected to the need and demand for care labor in the US and the UK as well as the Philippine state-led marketization of high-quality workers as an export commodity
Customer uncertainty: a source of organizational inefficiency in the light of the modularity theory of the firm
Get PDFOver the last century, customers have become increasingly uncertain about how to be satisfied because of the growing complexity of their own needs. On the one hand, most standardized needs have been satisfied, whereas on the other hand, worldwide demand for intrinsically complex needs (such as health care and long-term care) has increased, especially because of population ageing. On the supply side, producing on the basis of an estimated foreseen demand has become increasingly difficult and customer uncertainty has become a cause of organizational inefficiency. Nevertheless, in the theories of the firm so far developed, the customer is still a missing player, confined to the position of 'rational agent'. This research discusses how organizational efficiency is impacted by customer uncertainty in taking consumption decisions when the needs are complex. The central issue is to understand when it is efficient for the organization to involve the uncertain customer in the production process and, accordingly, which organizational form is the most effective in managing such involvement. Today the lack of clarity regarding this theoretical issue has permitted, or even supported, an imprudent adoption of mass-customization in important sectors which gives customers the option of choosing exclusively from among standardized options, without suitable consideration for both the complexity of their needs and the organization required. My dissertation is organized into three chapters. The first chapter proposes a theoretical framework on the basis of the Modularity Theory of the Firm (Langlois and Robertson 1995; Langlois 2002, 2006; Baldwin and Clark, 2003; 2006), which allows for the identification of the most effective organizational types to face customer uncertainty. The second chapter studies the most efficient way to design and manage production processes in the presence of uncertain customer needs, implying the necessity to involve the customers themselves in the production process. The focus here is also on the design and management of long term care (LTC) services. And the third chapter, by adopting case study research methods for theory building (Eisenhardt, 1989, Yin 2003), in order to investigate the relationship between organizational and production efficiency, analyses five LTC organizations that belong to different categories of modularity and are characterized by different governance forms. Summarizing the results, the thesis firstly theorizes that cooperative governance (the internal organization of labour based on inclusion, participation, and horizontal relations) is the most effective to minimize dynamic transaction costs and the related unexpected production costs (damages, errors, waste of time, legal actions) thanks to developing capabilities related to how to satisfy customers' complex needs. Particularly, the accountability of workers supports a learning-by-doing process that allows for life-long learning and the necessary flexibility to adequately meet customers' needs. Secondly, the study proposes a blueprinting approach to service design and management, which allows for the separation of front/back office in order to improve management efficiency. This structure is particularly suited for supporting decision-making processes in a flat organizational structure (such as the cooperative one), as it clarifies the workflow processes and responsibilities. Thirdly, it empirically applies the theoretical results to situations of long-term care with customer uncertainty and shows how services should be designed in order to maintain a low level of unexpected production costs