4,145 research outputs found
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Pro-Environmental Behaviour Change for Nature: Empirical and Theoretical Evidence from a Field Experiment in Aotearoa New Zealand
Individual behaviour change is a crucial component of our response to current environmental challenges and over recent years, a growing body of literature has focussed on the drivers and levers of pro-environmental behaviours. However, scholars have noted there is a considerable shortage of behavioural science research that focuses on behaviours that directly impact nature and biodiversity. This is concerning, given the enormous value populations place on nature, the fundamental role nature plays in society and because nature is declining rapidly.
In this thesis, we focus on understanding volunteering for nature restoration groups, which we show is an under-researched behaviour in the literature. It also has relatively high potential to deliver positive impacts for biodiversity and nature. We start by developing a simple generalisable theoretical model that suggests three main factors may be inhibiting the uptake of volunteering for nature – uncertainty, inaccuracy and high behavioural adjustment costs. We use this model to inform the design and hypotheses for a large field experiment in Aotearoa New Zealand where we aim to answer the following questions:
How can we increase volunteering for nature restoration groups? What are the effects of volunteering for the first-time on future volunteering behaviour? How does volunteering affect other important outcomes of interest, like environmental identity, locus of control beliefs and wellbeing?
Our field experiment has two stages. In stage one, we randomly assign first-time volunteers (those who are not already engaged in nature volunteering) to treatment groups to assess the impact of a nudge, a supermarket voucher incentive and a nudge and incentive combined on volunteering behaviour. We find that a $50 NZD supermarket incentive increases attendance rates at volunteering events and commitment rates to attend volunteering events. On the other hand, an environmentally and socially motivated nudge in isolation has no effect on volunteering behaviour. However, combining the nudge with the voucher incentive enhances the efficacy of either treatment alone, demonstrating that significant positive synergies exist between nudges and incentives in this context.
In stage two, we show volunteering for the first-time is plausibly randomly assigned, conditional on availability and being offered an incentive. We use this feature to estimate the causal impact of volunteering for the first time on future volunteering behaviour and other outcomes of interest. We find that volunteering for the first time crowds in future volunteering behaviour, generates positive spillovers to other pro-environmental behaviours and strengthens environmental self-identity and locus of control beliefs, which are important pre-cursors to pro-environmental behaviour. Our results show two mechanisms are likely driving these effects. Firstly, volunteering for the first-time provides important information about the benefits of volunteering that are used in future decision-making. Secondly, it strengthens environmental attitudes and identity, which in-turn affect preferences for pro-environmental behaviour. Taken together, our results show that using a financial incentive to help people experiment with volunteering can lead to large positive spillovers and crowding-in effects for future pro-environmental behaviour
Cache-timing attack against HQC
In this paper, we present the first chosen-ciphertext (CC) cache-timing attacks on the reference implementation of HQC.
We build a cache-timing based distinguisher for implementing a plaintext-checking (PC) oracle. The PC oracle uses side-channel information to check if a given ciphertext decrypts to a given message.
This is done by identifying a vulnerability during the generating process of two vectors in the reference implementation of HQC.
We also propose a new method of using PC oracles for chosen-ciphertext side-channel attacks against HQC, which may have independent interest.
We show a general proof-of-concept attack, where we use the Flush&Reload technique and also derive, in more detail, a practical attack on an HQC execution on Intel SGX, where the Prime&Probe technique is used.
We show the exact path to do key recovery by explaining the detailed steps, using the PC oracle. In both scenarios, the new attack requires traces on average with much fewer PC oracle calls than the timing attack of Guo et al. CHES 2022 on an HQC implementation
Digital writing technologies in higher education : theory, research, and practice
This open access book serves as a comprehensive guide to digital writing technology, featuring contributions from over 20 renowned researchers from various disciplines around the world. The book is designed to provide a state-of-the-art synthesis of the developments in digital writing in higher education, making it an essential resource for anyone interested in this rapidly evolving field.
In the first part of the book, the authors offer an overview of the impact that digitalization has had on writing, covering more than 25 key technological innovations and their implications for writing practices and pedagogical uses. Drawing on these chapters, the second part of the book explores the theoretical underpinnings of digital writing technology such as writing and learning, writing quality, formulation support, writing and thinking, and writing processes. The authors provide insightful analysis on the impact of these developments and offer valuable insights into the future of writing. Overall, this book provides a cohesive and consistent theoretical view of the new realities of digital writing, complementing existing literature on the digitalization of writing. It is an essential resource for scholars, educators, and practitioners interested in the intersection of technology and writing
Novel Architectures for Offloading and Accelerating Computations in Artificial Intelligence and Big Data
Due to the end of Moore's Law and Dennard Scaling, performance gains in general-purpose architectures have significantly slowed in recent years. While raising the number of cores has been a viable approach for further performance increases, Amdahl's Law and its implications on parallelization also limit further performance gains. Consequently, research has shifted towards different approaches, including domain-specific custom architectures tailored to specific workloads.
This has led to a new golden age for computer architecture, as noted in the Turing Award Lecture by Hennessy and Patterson, which has spawned several new architectures and architectural advances specifically targeted at highly current workloads, including Machine Learning. This thesis introduces a hierarchy of architectural improvements ranging from minor incremental changes, such as High-Bandwidth Memory, to more complex architectural extensions that offload workloads from the general-purpose CPU towards more specialized accelerators. Finally, we introduce novel architectural paradigms, namely Near-Data or In-Network Processing, as the most complex architectural improvements.
This cumulative dissertation then investigates several architectural improvements to accelerate Sum-Product Networks, a novel Machine Learning approach from the class of Probabilistic Graphical Models. Furthermore, we use these improvements as case studies to discuss the impact of novel architectures, showing that minor and major architectural changes can significantly increase performance in Machine Learning applications.
In addition, this thesis presents recent works on Near-Data Processing, which introduces Smart Storage Devices as a novel architectural paradigm that is especially interesting in the context of Big Data. We discuss how Near-Data Processing can be applied to improve performance in different database settings by offloading database operations to smart storage devices. Offloading data-reductive operations, such as selections, reduces the amount of data transferred, thus improving performance and alleviating bandwidth-related bottlenecks.
Using Near-Data Processing as a use-case, we also discuss how Machine Learning approaches, like Sum-Product Networks, can improve novel architectures. Specifically, we introduce an approach for offloading Cardinality Estimation using Sum-Product Networks that could enable more intelligent decision-making in smart storage devices. Overall, we show that Machine Learning can benefit from developing novel architectures while also showing that Machine Learning can be applied to improve the applications of novel architectures
Optimization of 5G Second Phase Heterogeneous Radio Access Networks with Small Cells
Due to the exponential increase in high data-demanding applications and their services per
coverage area, it is becoming challenging for the existing cellular network to handle the massive
sum of users with their demands. It is conceded to network operators that the current
wireless network may not be capable to shelter future traffic demands. To overcome the challenges
the operators are taking interest in efficiently deploying the heterogeneous network.
Currently, 5G is in the commercialization phase. Network evolution with addition of small
cells will develop the existing wireless network with its enriched capabilities and innovative
features. Presently, the 5G global standardization has introduced the 5G New Radio (NR) under
the 3rd Generation Partnership Project (3GPP). It can support a wide range of frequency
bands (<6 GHz to 100 GHz).
For different trends and verticals, 5G NR encounters, functional splitting and its cost evaluation
are well-thought-out. The aspects of network slicing to the assessment of the business
opportunities and allied standardization endeavours are illustrated. The study explores the
carrier aggregation (Pico cellular) technique for 4G to bring high spectral efficiency with the
support of small cell massification while benefiting from statistical multiplexing gain. One
has been able to obtain values for the goodput considering CA in LTE-Sim (4G), of 40 Mbps
for a cell radius of 500 m and of 29 Mbps for a cell radius of 50 m, which is 3 times higher
than without CA scenario (2.6 GHz plus 3.5 GHz frequency bands).
Heterogeneous networks have been under investigation for many years. Heterogeneous network
can improve users service quality and resource utilization compared to homogeneous
networks. Quality of service can be enhanced by putting the small cells (Femtocells or Picocells)
inside the Microcells or Macrocells coverage area. Deploying indoor Femtocells for 5G
inside the Macro cellular network can reduce the network cost. Some service providers have
started their solutions for indoor users but there are still many challenges to be addressed.
The 5G air-simulator is updated to deploy indoor Femto-cell with proposed assumptions with
uniform distribution. For all the possible combinations of apartments side length and transmitter
power, the maximum number of supported numbers surpassed the number of users
by more than two times compared to papers mentioned in the literature. Within outdoor environments,
this study also proposed small cells optimization by putting the Pico cells within
a Macro cell to obtain low latency and high data rate with the statistical multiplexing gain of
the associated users.
Results are presented 5G NR functional split six and split seven, for three frequency bands
(2.6 GHz, 3.5GHz and 5.62 GHz). Based on the analysis for shorter radius values, the best
is to select the 2.6 GHz to achieve lower PLR and to support a higher number of users, with
better goodput, and higher profit (for cell radius u to 400 m). In 4G, with CA, from the
analysis of the economic trade-off with Picocell, the Enhanced multi-band scheduler EMBS
provide higher revenue, compared to those without CA. It is clearly shown that the profit of
CA is more than 4 times than in the without CA scenario. This means that the slight increase
in the cost of CA gives back more than 4-time profit relatively to the ”without” CA scenario.Devido ao aumento exponencial de aplicações/serviços de elevado débito por unidade de
área, torna-se bastante exigente, para a rede celular existente, lidar com a enormes quantidades
de utilizadores e seus requisitos. É reconhecido que as redes móveis e sem fios atuais
podem não conseguir suportar a procura de tráfego junto dos operadores. Para responder
a estes desafios, os operadores estão-se a interessar pelo desenvolvimento de redes heterogéneas
eficientes. Atualmente, a 5G está na fase de comercialização. A evolução destas
redes concretizar-se-á com a introdução de pequenas células com aptidões melhoradas e
características inovadoras. No presente, os organismos de normalização da 5G globais introduziram
os Novos Rádios (NR) 5G no contexto do 3rd Generation Partnership Project
(3GPP). A 5G pode suportar uma gama alargada de bandas de frequência (<6 a 100 GHz).
Abordam-se as divisões funcionais e avaliam-se os seus custos para as diferentes tendências
e verticais dos NR 5G. Ilustram-se desde os aspetos de particionamento funcional da rede à
avaliação das oportunidades de negócio, aliadas aos esforços de normalização. Exploram-se
as técnicas de agregação de espetro (do inglês, CA) para pico células, em 4G, a disponibilização
de eficiência espetral, com o suporte da massificação de pequenas células, e o ganho
de multiplexagem estatística associado. Obtiveram-se valores do débito binário útil, considerando
CA no LTE-Sim (4G), de 40 e 29 Mb/s para células de raios 500 e 50 m, respetivamente,
três vezes superiores em relação ao caso sem CA (bandas de 2.6 mais 3.5 GHz).
Nas redes heterogéneas, alvo de investigação há vários anos, a qualidade de serviço e a utilização
de recursos podem ser melhoradas colocando pequenas células (femto- ou pico-células)
dentro da área de cobertura de micro- ou macro-células). O desenvolvimento de pequenas
células 5G dentro da rede com macro-células pode reduzir os custos da rede. Alguns prestadores
de serviços iniciaram as suas soluções para ambientes de interior, mas ainda existem
muitos desafios a ser ultrapassados. Atualizou-se o 5G air simulator para representar a
implantação de femto-células de interior com os pressupostos propostos e distribuição espacial
uniforme. Para todas as combinações possíveis do comprimento lado do apartamento, o
número máximo de utilizadores suportado ultrapassou o número de utilizadores suportado
(na literatura) em mais de duas vezes. Em ambientes de exterior, propuseram-se pico-células
no interior de macro-células, de forma a obter atraso extremo-a-extremo reduzido e taxa de
transmissão dados elevada, resultante do ganho de multiplexagem estatística associado.
Apresentam-se resultados para as divisões funcionais seis e sete dos NR 5G, para 2.6 GHz,
3.5GHz e 5.62 GHz. Para raios das células curtos, a melhor solução será selecionar a banda
dos 2.6 GHz para alcançar PLR (do inglês, PLR) reduzido e suportar um maior número de
utilizadores, com débito binário útil e lucro mais elevados (para raios das células até 400 m).
Em 4G, com CA, da análise do equilíbrio custos-proveitos com pico-células, o escalonamento
multi-banda EMBS (do inglês, Enhanced Multi-band Scheduler) disponibiliza proveitos superiores
em comparação com o caso sem CA. Mostra-se claramente que lucro com CA é mais
de quatro vezes superior do que no cenário sem CA, o que significa que um aumento ligeiro
no custo com CA resulta num aumento de 4-vezes no lucro relativamente ao cenário sem CA
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