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Healing through design; a trauma informed design approach to permanent refugee housing
No full textSince September 2023, more than 120,000 Armenians have been forcefully
displaced from their homes in Artsakh (Nagorno-Karabagh) as a result of ethnic
cleansing. While this is a specific example, it happens frequently across
the globe, resulting in forced displacement and displacement trauma. That is
why crisis architecture and sustainable housing solutions that foster mental and
physical well-being are needed.
In this thesis, the aim is to design a permanent housing project in Dilijan, Tavush
province, Armenia, that incorporates trauma-informed design principles,
accessibility, sustainable building methods, and Armenian vernacular housing
architecture to find answers and a design solution to the following research
question:
How can permanent refugee housing be designed to promote
recovery from trauma?
How can vernacular housing architecture contribute to designing
a sense of safety, familiarity, and cultural identity in refugee
housing?
How can vernacular construction techniques and materials be
used to enhance sustainability and durability?
The research methods include a combination of literature research on
trauma-informed design principles, Armenian vernacular housing architecture,
traditional building methods and materials, reviews on existing refugee
settlements, and interviews with displaced individuals from Artsakh.
As a result, the project offers a site-specific permanent housing solution that
addresses the physical and emotional needs of displaced individuals, creating
a model for future refugee housing initiatives that can be constructed sustainabl
Čoarvemátta - Terrain model
No full textČoarvemátta comes from the Sámi words for horn and root, after the innermost and strongest part of the reindeer antlers. This symbolizes different qualities and strengths and represents elements that unite, as Čoarvemátta will be a unifying force for the institutions that share the building: the Sami National Theatre Beaivváš and the Sami High School and Reindeer Herding School.
The landscape model’s purpose is to show the placement of the building, both in relation to the built-up area of Kautokeino and to the vast plateau, which is reindeer herding lands. The small sliver format was chosen to highlight this relationship. The placement of the building is interesting, as the idea of a monumental, cultural building placed in such a non-urban way is unusual
Privacy Risks in Time Series Models: Membership Inference in Deep Learning-Based Time Series Forecasting Models
No full textAs machine learning models become increasingly prevalent in time series forecasting applications—such as healthcare or energy systems—their potential to leak sensitive data, for example through membership inference attacks (MIAs), raises serious privacy concerns. While MIAs are well-studied in domains like image classification, their implications for time series models remain underexplored. This thesis investigates the vulnerability of deep learning-based time series forecasting models to MIAs, focusing on univariate and multivariate prediction tasks using LSTM and N-HiTS architectures. We conduct systematic experiments on two real-world datasets—EEG signals and electricity load usage—from distinct domains, characterized by varying temporal granularity and privacy sensitivity.
Several MIA techniques are evaluated, including LiRA and RMIA—originally stateof-the-art in other data modalities and adapted here for time series—as well as an ensemble-based attack previously shown to be effective for time series models. In addition, we introduce two new attacks: (i) Multi-Signal LiRA, a multi-signal variant of LiRA that can leverage a diverse set of time series-specific signals such as trend, seasonality, and TS2Vec embeddings; and (ii) Deep Time Series (DTS) attack, a novel deep learning-based MIA tailored specifically for time series forecasting. Performance is assessed across both sample-level and user-level inference scenarios.
Our findings reveal key patterns in MIA performance relative to model type, dataset characteristics, and attack signals, providing insight into how various attack settings affect privacy leakage in time series domains. These discoveries underscore the need for robust privacy auditing tools and the integration of privacy-preserving techniques when working with sensitive temporal data, while also providing guidance for future research on privacy risks in time series machine learning models
Development of a Sustainability Maturity Framework for Industrial Operations
No full textWhat does it take for sustainability to move beyond strategy and become part of dayto-
day decisions in industrial operations? This thesis dives into the space between intent
and execution, where companies set ambitious climate goals but struggle to embed them
in their operations. To address this challenge, the study designs a sustainability maturity
assessment framework tailored to the realities of industrial contexts. Through an in
depth single-case study at a global manufacturing firm, the framework is informed by an
investigation into the organizational enablers and challenges that influence sustainability
integration in practice.
The study is structured around two research questions:
(1) What organizational enablers and challenges influence the integration of sustainability
into operational decision-making in a large industrial firm?
(2) How can sustainability maturity assessment principles be leveraged to design a contextually
tailored framework for assessing operational integration in industrial firms?
Empirical findings highlight several challenges such as data accessibility issues, misaligned
KPIs, and limited decision authority at operational levels. At the same time, strategic
leadership, employee engagement, local initiatives, and internal tools such as the R framework
and Lean based systems provide leverage points for integration. Building on these
insights, the study proposes a tailored maturity assessment framework that reflects operational
conditions and offers a diagnostic tool for identifying integration gaps and guiding
improvement efforts. By examining how sustainability can be embedded in real-world industrial
operations, the study contributes both empirical understanding and a practical
tool for bridging the gap between strategy and execution
Copenhagen Women's building - Detail model
No full textThe women's building in Copenhagen was commissioned by the danish women's organisation (Kvindernes samfund) and built in 1936. Its original purpose was to serve as a meeting place for women and other women's organisations. When it was built it had amenities such as a restaurant, meeting rooms and halls as well as rooms for hotel use
Homomorphic vs Functional Encryption in Intrusion Detection Systems for OT Networks
No full textAs the number and complexity of cybersecurity threats against Operational Technology (OT) systems rise, the need for effective countermeasures becomes increasingly critical. One such countermeasure is the deployment of Intrusion Detection Systems (IDS) that monitor for signs of malicious activity. However, the implementation of IDSs can present several challenges. OT devices can be resource-constrained, and personnel with expertise in IDS can be difficult to find. For these reasons, IDS functionality is frequently outsourced to external parties. While effective, this solution raises concerns due to the large amount of potentially sensitive data that is shared with the external party. To address the privacy risks of data sharing, a surge in research has focused on cryptographic techniques that enable privacy-preserving external IDSs. While many interesting techniques have been presented, few studies include rigorous performance evaluations and technical comparisons between different approaches. This thesis aims to fill this gap by comparing two cryptographic
techniques in an OT setting.
The first technique uses Cheon-Kim-Kim-Song (CKKS), an instance of homomorphic
encryption (HE) that allows an IDS server to perform computations on encrypted
data. The resulting values are then decrypted by the client to determine whether
the system has been compromised. The second approach uses function-hiding inner
product encryption (FHIPE), an instance of functional encryption (FE). It enables an
external IDS server to calculate the distance between a client system’s normal state
and current state without revealing either. This distance is then used for intrusion
detection.
The HE and FE techniques are evaluated on the Secure Water Treatment (SWaT)
dataset using a neural network-based IDS. The results show that both methods
achieve threat detection accuracy comparable to their unencrypted counterpart. The
additional detection latency introduced by the systems is found to be less than 125
ms. The client-side memory demands are less than 4 MB for the HE approach and
less than 82 kB for the FE approach. Lastly, while both schemes increase the average
network payload size significantly, the overall bandwidth usage remains manageable
for most modern systems
Managing Code Evolution: Refactoring Challenges in Kattis’ Code Judge
No full textOnline code judges are platforms that offer programming problems and assess submitted solutions based on correctness, efficiency, and other performance metrics. As online code judges evolve to support increasingly complex features, maintaining backward compatibility and secure system design becomes a significant challenge. This thesis investigates the practical implications of refactoring and extending the Kattis code judge to accommodate their new problem package format. By collaborating with Kattis, the project focusses on developing a selected set of key features from their upcoming 2023-07 problem format. Through a combination of architectural design and modular programming, the thesis proposes a solution to handle both the upcoming 2023-07 format and the old legacy format. The work also includes solutions for the integration of static validators, using markdown for problem statements and multi-pass problems. The project resulted in the addition of 5,716 and deletion of 1,070 lines of code, of which 1,967 of the additions and 644 deletions were merged into Kattis’ codebase. The results of the project highlight the nuances of creating maintainable systems, identifying sacrifices in simplicity that are made to accomplish modular designs. The project also gives insight into the special considerations that need to be addressed when developing features from the 2023-07 format
Managing construction cost inflation; a multi-strategy framework for risk mitigation and contract optimization
No full textExpanding the Scope of Football Analytics by Integrating Tracking Data and Utilizing Statistical Learning
No full textThe recent decade has seen a data revolution within football as data analytics and
statistical learning have become established vital tools. The data revolution has also
seen the emergence of a new type of football data called tracking data. This thesis
first explores how information from tracking data can be integrated with established
event data and improve an established statistical learning model providing an expectancy
metric for passes called xP. Secondly, the thesis explores how it can used to
create a new type of statistical expectancy metric for player playability previously
unattainable with only event data.
Using event data and tracking data from 28 real football games, these separate
datasets have been synchronized to extract new information and context for passing
events. This information was used to train and compare a statistical learning model
for the xP metric with a model only trained on the previously known event data.
The results indicate that the added tracking data information provides a significantly
improved xP model especially in terms of understanding passing events and
therefore making more realistic pass probability predictions. Despite clear improvement,
there exist possibilities to further improve the xP model in regards to for
example a more accurate data synchronization process as well as further improved
feature engineering.
Moreover, the synchronized tracking and event data in combination with the improved
xP model were used to develop a metric that describe player playability
expectancy called xPlay. The new metric provides a simple and elegant way of
measuring player playability and results of various implementations indicate that
the metric can serve as a great tool in both player and team evaluation. Although
promising results the metric is in need of more evaluation on a bigger scale
Implementation av externa avbrott i RISC-V-processorn SERV
No full textOlika processordesigner är optimerade för att möta kriterier såsom maximal prestanda,
strömsnålhet eller högt kärnantal. Processorn SERV är designad kring ett enkelt kriterium:
att vara världens minsta RISC-V-processor. Detta har uppnåtts genom att använda en bitseriell
dataväg och genom att göra avkall på all funktionalitet förutom den mest väsentliga.
För att göra SERV till en mer praktiskt användbar processor, har vi implementerat
externa avbrott och sleep-läge samtidigt som vi hållit oss till det övergripande målet om
låg implementationskostnad. Utöver att vara open source, är SERV dessutom mycket
väldokumenterad. För att hålla oss till denna standard har vi gjort all vår kod open
source och skapat blockdiagram för all funktionalitet som implementerats. Vi har också
testat implementationen via testbenches och på FPGA-hårdvara för att verifiera att
allt fungerar som väntat. Vi har utvärderat designen enligt implementationskostnad och
energibesparingar på en Artix-7 FPGA