Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators

Life histories of people who stutter : on becoming someone.

Thesis (Ph.D.) - University of Durban-Westville, 2003.This study explores participants' experiences of stuttering in their lifeworlds over time through the lens of self-identity formations. The critical questions raised are: How do participants form their self-identities in their lifeworlds over time in relation to stuttering? In the context of their self-identity formations, how do they negotiate stuttering? A narrative life history methodology was used with intention to access personal, temporal and social dimensions of experience. Seven adult participants, two female and five male participants, with histories of living with stuttering since childhood, were invited to share their stories. Their personal experiences are embedded in diverse lifeworlds in KwaZulu-Natal, South Africa, a context making a sociopolitical transition from apartheid to democracy. The data was produced through retrospective accounts of their experiences via a series of dialogical interviews. Issues of empathy, power, and positioning and quality in the research process are problematised. The data was analysed at three levels. The first level of analysis entailed a narrative analysis of interview data, represented as seven individual research stories. The second level of analysis is a cross-case analysis using the seven research stories for the purposes of theorising. The outcomes of the third level of analysis are abstractions and explanatory concepts which respond to the critical questions in a general way. The genesis of two self-identity trajectories, self-identity as DisOther and self-identity as Able/Potential are traced over time. The biographical, contextual and social forces shaping self-identity formations and participants' actions in negotiating stuttering are illuminated. The self-identity trajectories are unique in the context of each biography. However, the relative prominence of self-identity formation as DisOther across cases in school years was evident. In contrast, self-identity as Able/Potential became prominent, during adulthood, for some participants. The experience is rendered as complex and fluid through a set of abstractions and explanatory concepts. These concepts foreground the changing and multiple relationships between self-identity formations, the influence of social forces shaping self-identity, the impact critical catalysts shaping self-identity formations, and strategic manipulation of self-identity in negotiating stuttering. In particular, the strategies to negotiate stuttering successfully are examined. The limitations of the study and potential application of this theoretical offering in the research, educational and clinical domains of Speech-Language Pathology are discussed

Layered Reactive Planning in the IALP Team IALP

Abstract. The main ideas behind the implementation of the IALP RoboCup team are discussed: an agent architecture made of a hierarchy of behaviors, which can be combined to obtain different roles; a memory model which relies of the absolute positions of objects. The team is programmed using ECL, a Common Lisp implementation. The research goal that we are pursuing with IALP is twofold: (1) we want to show the flexibility and effectiveness of our agent architecture in the RoboCup domain and (2) we want to test ECL in a real time application.

Layered Reactive Planning in the IALP Team

The main ideas behind the implementation of the IALP RoboCup team are discussed: an agent architecture made of a hierarchy of behaviors, which can be combined to obtain different roles; a memory model which relies of the absolute positions of objects. The team is programmed using ECL, a Common Lisp implementation designed for being embeddable within C based applications. The research goal that we are Pursuing with IALP is twofold: (1) we want to show the flexibility and effectiveness of our agent architecture in the RoboCup domain and (2) we want to test ECL in a real time application