7,110 research outputs found
Technical Dimensions of Programming Systems
Programming requires much more than just writing code in a programming language. It is usually done in the context of a stateful environment, by interacting with a system through a graphical user interface. Yet, this wide space of possibilities lacks a common structure for navigation. Work on programming systems fails to form a coherent body of research, making it hard to improve on past work and advance the state of the art.
In computer science, much has been said and done to allow comparison of programming languages, yet no similar theory exists for programming systems; we believe that programming systems deserve a theory too.
We present a framework of technical dimensions which capture the underlying characteristics of programming systems and provide a means for conceptualizing and comparing them.
We identify technical dimensions by examining past influential programming systems and reviewing their design principles, technical capabilities, and styles of user interaction. Technical dimensions capture characteristics that may be studied, compared and advanced independently. This makes it possible to talk about programming systems in a way that can be shared and constructively debated rather than relying solely on personal impressions.
Our framework is derived using a qualitative analysis of past programming systems. We outline two concrete ways of using our framework. First, we show how it can analyze a recently developed novel programming system. Then, we use it to identify an interesting unexplored point in the design space of programming systems.
Much research effort focuses on building programming systems that are easier to use, accessible to non-experts, moldable and/or powerful, but such efforts are disconnected. They are informal, guided by the personal vision of their authors and thus are only evaluable and comparable on the basis of individual experience using them. By providing foundations for more systematic research, we can help programming systems researchers to stand, at last, on the shoulders of giants
TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH
Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on people’s lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)
Consolidation of Urban Freight Transport – Models and Algorithms
Urban freight transport is an indispensable component of economic and social life in cities. Compared to other types of transport, however, it contributes disproportionately to the negative impacts of traffic. As a result, urban freight transport is closely linked to social, environmental, and economic challenges. Managing urban freight transport and addressing these issues poses challenges not only for local city administrations but also for companies, such as logistics service providers (LSPs). Numerous policy measures and company-driven initiatives exist in the area of urban freight transport to overcome these challenges. One central approach is the consolidation of urban freight transport. This dissertation focuses on urban consolidation centers (UCCs) which are a widely studied and applied measure in urban freight transport. The fundamental idea of UCCs is to consolidate freight transport across companies in logistics facilities close to an urban area in order to increase the efficiency of vehicles delivering goods within the urban area. Although the concept has been researched and tested for several decades and it was shown that it can reduce the negative externalities of freight transport in cities, in practice many UCCs struggle with a lack of business participation and financial difficulties. This dissertation is primarily focused on the costs and savings associated with the use of UCCs from the perspective of LSPs. The cost-effectiveness of UCC use, which is also referred to as cost attractiveness, can be seen as a crucial condition for LSPs to be interested in using UCC systems. The overall objective of this dissertation is two-fold. First, it aims to develop models to provide decision support for evaluating the cost-effectiveness of using UCCs. Second, it aims to analyze the impacts of urban freight transport regulations and operational characteristics on the cost attractiveness of using UCCs from the perspective of LSPs. In this context, a distinction is made between UCCs that are jointly operated by a group of LSPs and UCCs that are operated by third parties who offer their urban transport service for a fee. The main body of this dissertation is based on three research papers. The first paper focuses on jointly-operated UCCs that are operated by a group of cooperating LSPs. It presents a simulation model to analyze the financial impacts on LSPs participating in such a scheme. In doing so, a particular focus is placed on urban freight transport regulations. A case study is used to analyze the operation of a jointly-operated UCC for scenarios involving three freight transport regulations. The second and third papers take on a different perspective on UCCs by focusing on third-party operated UCCs. In contrast to the first paper, the second and third papers present an evaluation approach in which the decision to use UCCs is integrated with the vehicle route planning of LSPs. In addition to addressing the basic version of this integrated routing problem, known as the vehicle routing problem with transshipment facilities (VRPTF), the second paper presents problem extensions that incorporate time windows, fleet size and mix decisions, and refined objective functions. To heuristically solve the basic problem and the new problem variants, an adaptive large neighborhood search (ALNS) heuristic with embedded local search heuristic and set partitioning problem (SPP) is presented. Furthermore, various factors influencing the cost attractiveness of UCCs, including time windows and usage fees, are analyzed using a real-world case study. The third paper extends the work of the second paper and incorporates daily and entrance-based city toll schemes and enables multi-trip routing. A mixed-integer linear programming (MILP) formulation of the resulting problem is proposed, as well as an ALNS solution heuristic. Moreover, a real-world case study with three European cities is used to analyze the impact of the two city toll systems in different operational contexts
Golden Reference-Free Hardware Trojan Localization using Graph Convolutional Network
The globalization of the Integrated Circuit (IC) supply chain has moved most
of the design, fabrication, and testing process from a single trusted entity to
various untrusted third-party entities worldwide. The risk of using untrusted
third-Party Intellectual Property (3PIP) is the possibility for adversaries to
insert malicious modifications known as Hardware Trojans (HTs). These HTs can
compromise the integrity, deteriorate the performance, deny the service, and
alter the functionality of the design. While numerous HT detection methods have
been proposed in the literature, the crucial task of HT localization is
overlooked. Moreover, a few existing HT localization methods have several
weaknesses: reliance on a golden reference, inability to generalize for all
types of HT, lack of scalability, low localization resolution, and manual
feature engineering/property definition. To overcome their shortcomings, we
propose a novel, golden reference-free HT localization method at the
pre-silicon stage by leveraging Graph Convolutional Network (GCN). In this
work, we convert the circuit design to its intrinsic data structure, graph and
extract the node attributes. Afterward, the graph convolution performs
automatic feature extraction for nodes to classify the nodes as Trojan or
benign. Our automated approach does not burden the designer with manual code
review. It locates the Trojan signals with 99.6% accuracy, 93.1% F1-score, and
a false-positive rate below 0.009%.Comment: IEEE Transactions on Very Large Scale Integration Systems (TVLSI),
202
Working in ministries or public organizations in Saudi Arabia : A study of career development and job satisfaction of the Saudi Arabian middle managers
Career development and job satisfaction studies carried out in developing countries are very limited in number. Saudi Arabia is one of those developing countries which appeared on the political scene quite recently, but striving hard to develop its human resources due to its heavy dependence on expatriate labour to initiate and execute its development plans. The genesis of the study began when General Civil Service Bureau officials noticed a large movement of employees from ministries to other sectors (i.e. public organizations and the private sector). The purpose of this dissertation is to examine and analyze the factors behind this movement and relate this to the studies of career development and job satisfaction. The position of government organizations in Saudi Arabia is rather unique. Most of their employees are drawn from Universities due to the regulations of the GCSB of compelling them to work in ministries for a period equivalent to that spent in their University education until graduation. This situation has prevented such graduates from choosing their own occupations and seem to hinder their career development. As a consequence, this study, not only analyzes career development and job satisfaction in Saudi Arabia, but (v) job satisfaction in Saudi Arabia, but also makes a comprehensive evaluation of economic, social and organisational environments which seem to have an effect of the occupational choice of the Saudis. We take the assumption that the ideology of free occupational choice is not properly applied in Saudi Arabia due to some cultural variables (e.g. nepotism and strong family ties). Hence, this thesis will develop a definition of the concept of occupational choice and career development and the process of personnel flow and the ways in which such movement can be influenced within the Saudi context. The study will be primarily concerned with middle managers in two types of organization - government ministries and public organizations. This will hopefully give a profile of the Saudi situation as far as occupational choice, career development and job satisfaction are concerned
Towards thinking classrooms: foundation stage possibilities in Northern Ireland
The integration of thinking skills programmes into primary and secondary school curricula has gained increasing prominence in global educational policy over the past two decades. This research investigated the factors that influence how a particular approach to the development of thinking skills adopted in the Northern Ireland (NI) context is interpreted and implemented by teachers in early years classrooms. The Thinking Skills and Personal Capabilities Framework (TSPC) was introduced as a statutory component of the revised NI curriculum in 2007 and this study explores its enactment through the perceptions of key groups that interface with the policy from a range of different contexts: teachers and Head Teachers, Curriculum Advisory and Support staff, university academics and Initial Teacher Education staff. The study adopted an interpretive approach, utilising interviews with members of these key groups to explore their perceptions of the factors that influence the effective and consistent implementation of the TSPC and to explain possible reasons why it has embedded effectively in some NI primary schools and not in others. In addition to interviews, policy analysis of key texts that shape teachers’ approaches to the TSPC was undertaken using a framework based on Fairclough’s three-dimensional approach to critical discourse analysis. The purpose of this analysis was to explore the connection between the discourses used in these texts, and the extent to which the ideological cues that underpin them exert an influence on how teachers interpret and implement thinking skills in their practice. The study also explored how human capital theory, and an ecological approach to the enactment of the TSPC based on Bronfenbrenner’s Ecological Systems Model (1979), provide different frameworks for understanding how the TSPC is interpreted and implemented in practice, with particular reference to Northern Ireland.
The findings suggest that there are a number of significant factors that both enable and constrain the effective implementation of the TSPC across schools. The region’s political, social and historical context was viewed by participants as playing a key role in how policy reforms are interpreted and implemented. School leaders can play a central role in mediating the impact of these reforms to ensure that they are implemented in ways that take account of diverse and specific school contexts. From the perspective of participants, Head Teachers and school leaders also play a pivotal role in nurturing teachers’ professional learning, skill, and motivation in the teaching of thinking skills. Consistent opportunities for professional development, including collaborative working, and sharing of practice, both in and beyond the school, was viewed as the primary means of ensuring the development of a shared vision and language about thinking skills, and participants agreed that this is central to its consistent implementation across all schools.
Analysis of the participants’ understandings of the purpose of teaching thinking skills, and the aims of education more broadly, highlighted a tension between approaches to education that focus on children’s holistic development, and policy discourses, especially those related to Human Capital Theory that view education as a mechanism for achieving economic goals. The influence of these discourses across a range of public policy areas, as well as the disconnect between what participants and policy-makers viewed as the purpose of thinking, was highlighted in the analysis. For participants, the integration of thinking skills into the curriculum was about developing autonomy, criticality, and independence in children’s thinking, whereas policy-makers viewed it from a human capital perspective and strongly linked it to discourses of ‘lifelong learning’, ‘employability’ and ‘skill’.
From the perspective of participants, the findings indicate that for policy makers in Northern Ireland to better understand how to embed the TSPC as a core component of the curriculum in all schools a number of cross-system actions need to be undertaken. These include a baseline review of the impact of the TSPC in the ten years since its inception as part of the comprehensive review of education announced by the Minister for Education in January 2021. The data suggests that this review should ensure that teachers and school leaders are central to its design and approach and that it is fully inclusive of all schools in Northern Ireland that sit within its scope. A return to more localised support and advice services with a coordinated approach to the development of the TSPC in all schools was also viewed by participants as essential to its development and embedding in all schools.
A more coordinated, multi-disciplinary approach to implementation would, it was argued, ensure that ongoing professional learning in thinking skills was accessible, including the establishment of more strategic, collaborative partnerships with higher education, ITE and Inspection Services. This changed focus, I conclude, requires a move away from human capital and sector specific approaches to the consistent development of thinking skills programmes in all Northern Ireland schools. Recommendations also centre on future policy reforms that are inclusive and that give teachers their professional place as the primary implementers for the development of thinking skills programmes in schools
Scalable software and models for large-scale extracellular recordings
The brain represents information about the world through the electrical activity of
populations of neurons. By placing an electrode near a neuron that is firing (spiking), it
is possible to detect the resulting extracellular action potential (EAP) that is transmitted
down an axon to other neurons. In this way, it is possible to monitor the communication
of a group of neurons to uncover how they encode and transmit information. As the
number of recorded neurons continues to increase, however, so do the data processing
and analysis challenges. It is crucial that scalable software and analysis tools are developed
and made available to the neuroscience community to keep up with the large
amounts of data that are already being gathered.
This thesis is composed of three pieces of work which I develop in order to better
process and analyze large-scale extracellular recordings. My work spans all stages of extracellular
analysis from the processing of raw electrical recordings to the development
of statistical models to reveal underlying structure in neural population activity.
In the first work, I focus on developing software to improve the comparison and adoption
of different computational approaches for spike sorting. When analyzing neural
recordings, most researchers are interested in the spiking activity of individual neurons,
which must be extracted from the raw electrical traces through a process called
spike sorting. Much development has been directed towards improving the performance
and automation of spike sorting. This continuous development, while essential,
has contributed to an over-saturation of new, incompatible tools that hinders rigorous
benchmarking and complicates reproducible analysis. To address these limitations, I
develop SpikeInterface, an open-source, Python framework designed to unify preexisting
spike sorting technologies into a single toolkit and to facilitate straightforward
benchmarking of different approaches. With this framework, I demonstrate that modern,
automated spike sorters have low agreement when analyzing the same dataset, i.e.
they find different numbers of neurons with different activity profiles; This result holds
true for a variety of simulated and real datasets. Also, I demonstrate that utilizing a
consensus-based approach to spike sorting, where the outputs of multiple spike sorters
are combined, can dramatically reduce the number of falsely detected neurons.
In the second work, I focus on developing an unsupervised machine learning approach
for determining the source location of individually detected spikes that are
recorded by high-density, microelectrode arrays. By localizing the source of individual
spikes, my method is able to determine the approximate position of the recorded neuriii
ons in relation to the microelectrode array. To allow my model to work with large-scale
datasets, I utilize deep neural networks, a family of machine learning algorithms that
can be trained to approximate complicated functions in a scalable fashion. I evaluate
my method on both simulated and real extracellular datasets, demonstrating that it is
more accurate than other commonly used methods. Also, I show that location estimates
for individual spikes can be utilized to improve the efficiency and accuracy of spike
sorting. After training, my method allows for localization of one million spikes in approximately
37 seconds on a TITAN X GPU, enabling real-time analysis of massive
extracellular datasets.
In my third and final presented work, I focus on developing an unsupervised machine
learning model that can uncover patterns of activity from neural populations
associated with a behaviour being performed. Specifically, I introduce Targeted Neural
Dynamical Modelling (TNDM), a statistical model that jointly models the neural activity
and any external behavioural variables. TNDM decomposes neural dynamics (i.e.
temporal activity patterns) into behaviourally relevant and behaviourally irrelevant dynamics;
the behaviourally relevant dynamics constitute all activity patterns required
to generate the behaviour of interest while behaviourally irrelevant dynamics may be
completely unrelated (e.g. other behavioural or brain states), or even related to behaviour
execution (e.g. dynamics that are associated with behaviour generally but are not
task specific). Again, I implement TNDM using a deep neural network to improve its
scalability and expressivity. On synthetic data and on real recordings from the premotor
(PMd) and primary motor cortex (M1) of a monkey performing a center-out reaching
task, I show that TNDM is able to extract low-dimensional neural dynamics that are
highly predictive of behaviour without sacrificing its fit to the neural data
Optimización del rendimiento y la eficiencia energética en sistemas masivamente paralelos
RESUMEN Los sistemas heterogéneos son cada vez más relevantes, debido a sus capacidades de rendimiento y eficiencia energética, estando presentes en todo tipo de plataformas de cómputo, desde dispositivos embebidos y servidores, hasta nodos HPC de grandes centros de datos. Su complejidad hace que sean habitualmente usados bajo el paradigma de tareas y el modelo de programación host-device. Esto penaliza fuertemente el aprovechamiento de los aceleradores y el consumo energético del sistema, además de dificultar la adaptación de las aplicaciones.
La co-ejecución permite que todos los dispositivos cooperen para computar el mismo problema, consumiendo menos tiempo y energÃa. No obstante, los programadores deben encargarse de toda la gestión de los dispositivos, la distribución de la carga y la portabilidad del código entre sistemas, complicando notablemente su programación.
Esta tesis ofrece contribuciones para mejorar el rendimiento y la eficiencia energética en estos sistemas masivamente paralelos. Se realizan propuestas que abordan objetivos generalmente contrapuestos: se mejora la usabilidad y la programabilidad, a la vez que se garantiza una mayor abstracción y extensibilidad del sistema, y al mismo tiempo se aumenta el rendimiento, la escalabilidad y la eficiencia energética. Para ello, se proponen dos motores de ejecución con enfoques completamente distintos.
EngineCL, centrado en OpenCL y con una API de alto nivel, favorece la máxima compatibilidad entre todo tipo de dispositivos y proporciona un sistema modular extensible. Su versatilidad permite adaptarlo a entornos para los que no fue concebido, como aplicaciones con ejecuciones restringidas por tiempo o simuladores HPC de dinámica molecular, como el utilizado en un centro de investigación internacional.
Considerando las tendencias industriales y enfatizando la aplicabilidad profesional, CoexecutorRuntime proporciona un sistema flexible centrado en C++/SYCL que dota de soporte a la co-ejecución a la tecnologÃa oneAPI. Este runtime acerca a los programadores al dominio del problema, posibilitando la explotación de estrategias dinámicas adaptativas que mejoran la eficiencia en todo tipo de aplicaciones.ABSTRACT Heterogeneous systems are becoming increasingly relevant, due to their performance and energy efficiency capabilities, being present in all types of computing platforms, from embedded devices and servers to HPC nodes in large data centers. Their complexity implies that they are usually used under the task paradigm and the host-device programming model. This strongly penalizes accelerator utilization and system energy consumption, as well as making it difficult to adapt applications.
Co-execution allows all devices to simultaneously compute the same problem, cooperating to consume less time and energy. However, programmers must handle all device management, workload distribution and code portability between systems, significantly complicating their programming.
This thesis offers contributions to improve performance and energy efficiency in these massively parallel systems. The proposals address the following generally conflicting objectives: usability and programmability are improved, while ensuring enhanced system abstraction and extensibility, and at the same time performance, scalability and energy efficiency are increased. To achieve this, two runtime systems with completely different approaches are proposed.
EngineCL, focused on OpenCL and with a high-level API, provides an extensible modular system and favors maximum compatibility between all types of devices. Its versatility allows it to be adapted to environments for which it was not originally designed, including applications with time-constrained executions or molecular dynamics HPC simulators, such as the one used in an international research center.
Considering industrial trends and emphasizing professional applicability, CoexecutorRuntime provides a flexible C++/SYCL-based system that provides co-execution support for oneAPI technology. This runtime brings programmers closer to the problem domain, enabling the exploitation of dynamic adaptive strategies that improve efficiency in all types of applications.Funding: This PhD has been supported by the Spanish Ministry of Education (FPU16/03299 grant),
the Spanish Science and Technology Commission under contracts TIN2016-76635-C2-2-R
and PID2019-105660RB-C22.
This work has also been partially supported by the Mont-Blanc 3: European Scalable and
Power Efficient HPC Platform based on Low-Power Embedded Technology project (G.A. No.
671697) from the European Union’s Horizon 2020 Research and Innovation Programme
(H2020 Programme). Some activities have also been funded by the Spanish Science and Technology
Commission under contract TIN2016-81840-REDT (CAPAP-H6 network).
The Integration II: Hybrid programming models of Chapter 4 has been partially performed
under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC
Research Innovation Action under the H2020 Programme. In particular, the author gratefully
acknowledges the support of the SPMT Department of the High Performance Computing
Center Stuttgart (HLRS)
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