Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Visual data mining using principled projection algorithms and information visualization techniques

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.

Incorporating social role theory into topic models for social media content analysis

In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.

Visualisation of bioinformatics datasets

Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental importance in biology. Predicting functions of polymorphic molecules is important in order to design more effective medicines. Analysing major histocompatibility complex (MHC) polymorphism is important for mate choice, epitope-based vaccine design and transplantation rejection etc. Most of the existing exploratory approaches cannot analyse these datasets because of the large number of molecules with a high number of descriptors per molecule. This thesis develops novel methods for data projection in order to explore high dimensional biological dataset by visualising them in a low-dimensional space. With increasing dimensionality, some existing data visualisation methods such as generative topographic mapping (GTM) become computationally intractable. We propose variants of these methods, where we use log-transformations at certain steps of expectation maximisation (EM) based parameter learning process, to make them tractable for high-dimensional datasets. We demonstrate these proposed variants both for synthetic and electrostatic potential dataset of MHC class-I. We also propose to extend a latent trait model (LTM), suitable for visualising high dimensional discrete data, to simultaneously estimate feature saliency as an integrated part of the parameter learning process of a visualisation model. This LTM variant not only gives better visualisation by modifying the project map based on feature relevance, but also helps users to assess the significance of each feature. Another problem which is not addressed much in the literature is the visualisation of mixed-type data. We propose to combine GTM and LTM in a principled way where appropriate noise models are used for each type of data in order to visualise mixed-type data in a single plot. We call this model a generalised GTM (GGTM). We also propose to extend GGTM model to estimate feature saliencies while training a visualisation model and this is called GGTM with feature saliency (GGTM-FS). We demonstrate effectiveness of these proposed models both for synthetic and real datasets. We evaluate visualisation quality using quality metrics such as distance distortion measure and rank based measures: trustworthiness, continuity, mean relative rank errors with respect to data space and latent space. In cases where the labels are known we also use quality metrics of KL divergence and nearest neighbour classifications error in order to determine the separation between classes. We demonstrate the efficacy of these proposed models both for synthetic and real biological datasets with a main focus on the MHC class-I dataset.

Shared cognitive processes underlying past and future thinking:the impact of imagery and concurrent task demands on event specificity

Recent literature has argued that whereas remembering the past and imagining the future make use of shared cognitive substrates, simulating future events places heavier demands on executive resources. These propositions were explored in 3 experiments comparing the impact of imagery and concurrent task demands on speed and accuracy of past event retrieval and future event simulation. Results provide support for the suggestion that both past and future episodes can be constructed through 2 mechanisms: a noneffortful "direct" pathway and a controlled, effortful "generative" pathway. However, limited evidence emerged for the suggestion that simulating of future, compared with retrieving past, episodes places heavier demands on executive resources; only under certain conditions did it emerge as a more error prone and lengthier process. The findings are discussed in terms of how retrieval and simulation make use of the same cognitive substrates in subtly different ways. © 2011 American Psychological Association.

Are school-of-thought words characterizable?

School of thought analysis is an important yet not-well-elaborated scientific knowledge discovery task. This paper makes the first attempt at this problem. We focus on one aspect of the problem: do characteristic school-of-thought words exist and whether they are characterizable? To answer these questions, we propose a probabilistic generative School-Of-Thought (SOT) model to simulate the scientific authoring process based on several assumptions. SOT defines a school of thought as a distribution of topics and assumes that authors determine the school of thought for each sentence before choosing words to deliver scientific ideas. SOT distinguishes between two types of school-of-thought words for either the general background of a school of thought or the original ideas each paper contributes to its school of thought. Narrative and quantitative experiments show positive and promising results to the questions raised above © 2013 Association for Computational Linguistics. © 2013 Association for Computational Linguistics.

The non-violence of love:a Hildebrand-Girard encounter

If love is a social as well as a personal reality, it could be fruitful to compare Von Hildebrand’s understanding of love and desire with that of cultural anthropologist René Girard. Girard depicts love and desire as a triangular process which arises from imitation, rather than the result of auto-generative affection. In this sense, Girardian theory would seem to convict Von Hildebrand of what is called the romantic lie wherein desire is thought to arise through the mutual appreciation of two subjects. However, in The Nature of Love Von Hildebrand shows his awareness of the possibility that love can be awakened by imitation. Moreover, the lack of a sufficient reason in Girardian theory for avoiding violence can be answered by turning to Von Hildebrand’s appreciation of the ontological basis for desire.

Middle school teachers perspectives on inclusion: A qualitative study

Historically, research has placed considerable emphasis on developing a systematic body of knowledge about education in which little voice has been given to teachers themselves. The critical role that teachers play in this generative process such as reflecting, acting and theorizing upon practices that shape life in the classroom has largely been ignored in favor of technical innovation and organizational procedure. As schools struggle to reform and restructure, an understanding of how teachers interpret their practices in context and how the culture of schools influence, constrain, or encourage these practices become critical aspects of school success or failure. ^ This study examined the perspectives on inclusion of seven middle school teachers as they attempted to include exceptional students in regular classes. The study utilized three forms of data collection: observations were made of participant interactions as they led their everyday school lives; document analysis was used as a means to gain an understanding of programs affecting exceptional students, and interviews were used to give voice to teacher's perceptions regarding inclusion, allowing description in their own words rather than those imposed by an outside inquirer. Data collection and analysis sought to identify emerging themes, categories and patterns, allowing for the creation of substantive theory grounded in empirical data. ^ The key issues that emerged in the study were considered in terms of three general categories. The first, teaching and learning, revealed stark contrasts in opinions regarding the type of human support thought necessary for successful inclusion. Regular educators clung to the traditional notion of solitary teachers directing all class activity, while exceptional educators preferred a more team-oriented approach. The second, school structure, revealed that highly collaborative structures were only partially successful in creating additional conversation between regular and exceptional educators. Collegiality was affected by lack of staff experience with the process as well as its implementation in a top-down fashion. The third, school culture and climate, revealed that regular educators believed the school was prepared for a limited amount of inclusion. Although exceptional educators acknowledged school readiness, they did not believe that inclusion was an important item on the school's reform agenda. ^

Enabling adaptability in service aggregates using transparent shaping techniques

Distributed applications are exposed as reusable components that are dynamically discovered and integrated to create new applications. These new applications, in the form of aggregate services, are vulnerable to failure due to the autonomous and distributed nature of their integrated components. This vulnerability creates the need for adaptability in aggregate services. The need for adaptation is accentuated for complex long-running applications as is found in scientific Grid computing, where distributed computing nodes may participate to solve computation and data-intensive problems. Such applications integrate services for coordinated problem solving in areas such as Bioinformatics. For such applications, when a constituent service fails, the application fails, even though there are other nodes that can substitute for the failed service. This concern is not addressed in the specification of high-level composition languages such as that of the Business Process Execution Language (BPEL). We propose an approach to transparently autonomizing existing BPEL processes in order to make them modifiable at runtime and more resilient to the failures in their execution environment. By transparent introduction of adaptive behavior, adaptation preserves the original business logic of the aggregate service and does not tangle the code for adaptive behavior with that of the aggregate service. The major contributions of this dissertation are: first, we assessed the effectiveness of BPEL language support in developing adaptive mechanisms. As a result, we identified the strengths and limitations of BPEL and came up with strategies to address those limitations. Second, we developed a technique to enhance existing BPEL processes transparently in order to support dynamic adaptation. We proposed a framework which uses transparent shaping and generative programming to make BPEL processes adaptive. Third, we developed a technique to dynamically discover and bind to substitute services. Our technique was evaluated and the result showed that dynamic utilization of components improves the flexibility of adaptive BPEL processes. Fourth, we developed an extensible policy-based technique to specify how to handle exceptional behavior. We developed a generic component that introduces adaptive behavior for multiple BPEL processes. Fifth, we identify ways to apply our work to facilitate adaptability in composite Grid services.

Toward an understanding of how individuals overcome challenges to development: A phenomenological study of an inner -city student's attitude toward academic orientation and life

The purpose of this qualitative case study was to gain an understanding of the phenomenon of academic orientation by seeking the insights into an inner-city Haitian-American middle school student's attitudes and world view toward education and life. A phenomenological approach was used in order to explore the way in which Cindy, a minority student, gives meaning to her lived-experiences in terms of her desire to meet academic expectations and her ability to overcome social adversity and/or other risk factors.^ The study attempted to answer the following two research questions: (1) What provides the focus for Cindy's (the subject's) approach to her school work and/or life? (2) What are the processes that give meaning and direction to academic orientation and life for Cindy? In-depth interviewing was the primary method of data collection. In addition, journal and sketchbook entries and school district records were used and classroom observations made.^ The nature of the study to understand lived-experience facilitated the use of the case study method and a phenomenological method of description. Data analysis was conducted by means of an adapted form of the constant comparative approach. Patterns in the data which emerged were coded and categorized according to underlying generative themes. Phenomenological reflection and analysis were used to grasp the experiential structures of Cindy's experience. The following textural themes were identified and confirmed to be essential themes to Cindy's experience: personal challenge to do her best, personal challenge to want to learn, having a sense of determination, being able to think for self, having a disposition to like self, achieving self-respect through performance, seeing a need to help others, being intrinsically motivated, being an independent learner, attending more to academic pressure and less to peer pressure, having motivational catalysts in her life, learning and support opportunities, and having a self-culture. Using Mahrer's humanistic theory of experiencing, Cindy's development was interpreted in terms of her progression through a sequence of developmental plateaus: externalized self, internalized self, and integrating and actualizing self.^ The findings of this study were that Cindy's desire to meet academic expectations is guided by a meaning construction internal frame of reference. High expectations of self in conjunction with other protective factors found in Cindy's home and school environments were also found to be linked to her educational resilience and success. Cindy's lived-experiences were also found to be related to Mahrer's theory of human development. In addition, it was concluded that "minority" students do not all fit into social categories and labels. ^

Toward understanding the study experience of culturally sensitive graduate students in *American distance education programs

The purpose of this research was to gain an understanding of the study experience of non-American graduate students living outside of the United States and formally engaged in graduate studies in an American Distance Education (DE) Program. These students have been labeled “culturally sensitive.” The nature of this study dictated a qualitative case study methodology using in-depth interviews to collect the data and the hermeneutic approach to understanding and description. This study aims at generating questions and hypotheses that will lead to further investigations that explore the need for cultural and contextual sensitivity in order to provide more equitable and accessible higher education for all. ^ The study attempted to answer the question: What is the study experience of “culturally sensitive” graduate students in American DE Programs? The underlying issue in this study is whether education designed and provided by educators of different socio-cultural backgrounds from that of the students could be content relevant and instructionally appropriate, resulting in educational enhancement and/or prepare students to function adequately in their own communities. ^ Participants in this study (n = 12) were engaged in Master's level (n = 2) and Doctoral level (n = 10) DE programs at American Universities, and were interviewed by E-mail, face-to-face, or using a combination of the two. Data analysis compared interviews and highlighted repetitive patterns. Interview data was triangulated with recent related literature and data from document reviews of archived E-mail conversations between students and their professors. The patterns that emerged were coded and categorized according to generative themes. The following themes were identified in order to analyze the data and confirmed through participant check-back: program benefits, communication, technology, culture and methodology, and reflectivity. ^ Major findings in this study indicate that culture plays an important role in cross-cultural encounters for students in American DE programs vis-à-vis student perceptions as to whether their study needs were being met. Most notably, it was found that the coupling of cultural perceptual differences with transactional distance created a potential barrier to communication that could affect short-term success in American DE programs. To overcome this barrier, students cited good communication as essential in meeting student's needs, especially those communications that were supportive and full of detail and context and from a primary source (ex. directly from the professor). Evaluation was a particularly sensitive issue, especially when students were unaware of their professor's cultural and contextual intricacies and therefore were uncertain about expectations and intended meaning. CSGS were aware of their position and the American rather than global context in which they were participating. Students appear to have developed “extended identities”, meaning that they acculturated in varying degrees in order to be successful in their program but that their local cultural identity was not compromised in any way. For participants from Venezuela access to higher DE has been a limiting factor to participation, due to the high cost of technology and telephone lines for communication. ^

Narratividade e estruturas cognitivas: o encontro entre a linguagem, a cognição e a experiência sociocultural

This work is within the framework of Cognitive Linguistics, which, as opposed to generative modular approach posits that language is not autonomous but part of human cognition manifest mental processing, socio-cultural and bodily experiences. Our goal is to describe and analyze cognitive mechanisms of understanding who work in the formal and meaningful organization of the narrative. In order to study and verification of this phenomenon, this project was based in the theoretical framework of Rapaport et al (1994) with the treatment of deictic center, Zwaan (1999) and Zwaan and Radvansky (1998) with situation models, Minsky (1974) with the concept frame, Johnson (1987) and Duke and Costa (2012) with pictorial schemes. To this end, we focused on the deictic perspective (WHERE, WHEN, WHO), social cognitive structures (frames) and body (pictorial diagrams) and the situation of models built by compreendedor from these cognitive structures. Methodologically, it is a qualitative research (BAUER and GASKELL, 2002), of interpretive base (MOITA LOPES, 1994), based on introspection (Talmy, 2005). The corpus selected is a sample of twelve texts written by 8th grade students, whose production consists of fictional narrative, the production of diary pages. The analyses were conducted by cognitive structures known as constructional blocks (BCs)(SANTOS, 2011), which guid the discussion about how we build understanding and creation of meanings in narratives. The result shows that the narrative events are mentally represented by the understander that conceives a deictic center and that, guided by it, has access to understanding and construction of meaning in narrative by means of cognitive domains established by bodily and socio-cultural experiences.

Operações linguístico-discursivas em relatos retextualizados por alunos do ensino fundamental

The following paper attempted to investigate and discuss the possible improvements in the writing of students from the public network in the 6th grade of elementary school. This research was run in the professional master degree In Portuguese Language. Also based upon Genetic Criticism, this study attempting to analyze in which way and in which proportions the alterations done in the texts reveal and perspective capacity in the students as they replace, broad, remove or just move terms in their assignments. We tried to develop our analysis in the pragmatic perspective in which Textual Linguistic is included, investigating the texts and appreciating them as a construction process of meaning. Our theoretical discussion will be based on and socio-interactional conception of language (MARCUSCHI, 2008), as well as in the postulates of Analyze of Discursion (ADAM, 2010, 2008). It has also been used the theoretical assumptions taken from Genetic Criticism which regard the relation between text and genesis, due to the fact that it considers the text and a the result of a construction of progressive elaboration and the writing as an activity of constant movement (DE BIASI, [2000] 2010; GRÉSILLON, 1989; [1990] 2008; [1992] 2002; SALLES, 2008a). To assemble the data in this research we took into consideration the social variables related to the students and the sociocultural context. Nonetheless, this investigation point towards a real classroom situation where we tried to analyze the language functioning in application conditions, thus, giving us authority to describe more precisely the reality we lived in, which provided us with a more attentive look to the observed particularities. This description of the reality appreciated built a path that point to a research of qualitative data approach to which meanings deriving from interpretation were attributed. To conduct this research we resourced to the Action-Research process. The data are comprised of ten personal reports that were created from rewriting assignments, which constitutes a range of twenty texts assessed starting from the linguistic operations acknowledged by Generative Grammar and continued by Lebrave and Grésillon (2009). As result of this analysis, we identified the operation of adding more often than the other ones. The replacement and removal operations display a very close offspring. Nevertheless, the moving operation was scarcely used. These results, besides demonstrating linguistic creativity of the students, revealed that for a text to be seen as “concluded”, the writing student articulates new elaborations through these linguistic operators and that these movements of coming and going, of erasures and amendments contribute significantly for the teacher to approach the relationship the student keeps with his textual and discursive expression, and then, with that, to hold information that eventually provides individual and collective directions in school productions.

"Double Rainbow," "Appalachiana," and "'The Invisible Mass': Exploring Compositional Technique in Alfred Schnittke's Second Symphony"

This dissertation consists of three distinct components: (1) “Double Rainbow,” a notated composition for an acoustic ensemble of 10 instruments, ca. 36 minutes. (2) “Appalachiana”, a fixed-media composition for electro-acoustic music and video, ca. 30 minutes, and (3) “'The Invisible Mass': Exploring Compositional Technique in Alfred Schnittke’s Second Symphony”, an analytical article.

(1) Double Rainbow is a ca. 36 minute composition in four movements scored for 10 instruments: flute, Bb clarinet (doubling on bass clarinet), tenor saxophone (doubling on alto saxophone), french horn, percussion (glockenspiel, vibraphone, wood block, 3 toms, snare drum, bass drum, suspended cymbal), piano, violin, viola, cello, and double bass. Each of the four movements of the piece explore their own distinct character and set of compositional goals. The piece is presented as a musical score and as a recording, which was extensively treated in post-production.

(2) Appalachiana, is a ca. 30 minute fixed-media composition for music and video. The musical component was created as a vehicle to showcase several approaches to electro-acoustic music composition –fft re-synthesis for time manipulation effects, the use of a custom-built software instrument which implements generative approaches to creating rhythm and pitch patterns, using a recording of rain to create rhythmic triggers for software instruments, and recording additional components with acoustic instruments. The video component transforms footage of natural landscapes filmed at several locations in North Carolina, Virginia, and West Virginia into a surreal narrative using a variety of color, lighting, distortion, and time-manipulation video effects.

(3) “‘The Invisible Mass:’ Exploring Compositional Technique in Alfred Schnittke’s Second Symphony” is an analytical article that focuses on Alfred Schnittke’s compositional technique as evidenced in the construction of his Second Symphony and discussed by the composer in a number of previously untranslated articles and interviews. Though this symphony is pivotal in the composer’s oeuvre, there are currently no scholarly articles that offer in-depth analyses of the piece. The article combines analyses of the harmony, form, and orchestration in the Second Symphony with relevant quotations from the composer, some from published and translated sources and others newly translated by the author from research at the Russian State Library in St. Petersburg. These offer a perspective on how Schnittke’s compositional technique combines systematic geometric design with keen musical intuition.