Energy performance comparison of ventilation-based heating versus water-based heating systems in an efficient residential building

in Fluid Dynamics & Material Processing (in press)

The application of air-based heating systems as a possible approach to reduce the construction costs in highly efficient residential buildings is becoming popular. Air-based heating systems have been well ... [more ▼]

The application of air-based heating systems as a possible approach to reduce the construction costs in highly efficient residential buildings is becoming popular. Air-based heating systems have been well-known for their usage in passive houses during the past three decades. Available studies on such systems tend mostly to focus only on comparing exhaust air heat pump technology with conventional systems in efficient buildings. Moreover, most of the existing studies ignore the usual presence of the electrical heaters as backup. Besides, a comprehensive study and comparison between different air-based heating system concepts is still missing. In this study, four different air-based heating system concepts separated by the type of heat source of heat pump for heating and domestic hot water are defined. These systems are compared to four conventional heating system, including floor heating and direct electrical system employing dynamic annual simulations. According to simulation results, the systems with floor heating have shown the best system efficiencies and the lowest energy demand in comparison to the other systems. The main reason for this was the lower supply temperatures of the floor heating systems. Between the air heating systems, the system equipped with an outdoor air heat pump showed a better energy performance than an exhaust air system. The main reason for this could be attributed to the power limitation of exhaust air heat pump systems. [less ▲]

A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms

in ACM Transactions on Software Engineering and Methodology (in press)

Users frequently interact with software systems through data entry forms. However, form filling is time-consuming and error-prone. Although several techniques have been proposed to auto-complete or pre ... [more ▼]

Users frequently interact with software systems through data entry forms. However, form filling is time-consuming and error-prone. Although several techniques have been proposed to auto-complete or pre-fill fields in the forms, they provide limited support to help users fill categorical fields, i.e., fields that require users to choose the right value among a large set of options. In this paper, we propose LAFF, a learning-based automated approach for filling categorical fields in data entry forms. LAFF first builds Bayesian Network models by learning field dependencies from a set of historical input instances, representing the values of the fields that have been filled in the past. To improve its learning ability, LAFF uses local modeling to effectively mine the local dependencies of fields in a cluster of input instances. During the form filling phase, LAFF uses such models to predict possible values of a target field, based on the values in the already-filled fields of the form and their dependencies; the predicted values (endorsed based on field dependencies and prediction confidence) are then provided to the end-user as a list of suggestions. We evaluated LAFF by assessing its effectiveness and efficiency in form filling on two datasets, one of them proprietary from the banking domain. Experimental results show that LAFF is able to provide accurate suggestions with a Mean Reciprocal Rank value above 0.73. Furthermore, LAFF is efficient, requiring at most 317 ms per suggestion. [less ▲]

An (Un)Necessary Evil - Users’ (Un)Certainty about Smartphone App Permissions and Implications for Privacy Engineering

in 2022 7th IEEE European Symposium on Security and Privacy Workshops (EuroSPW) (in press)

App permission requests are a control mechanism meant to help users oversee and safeguard access to data and resources on their smartphones. To decide whether to accept or deny such requests and make this ... [more ▼]

App permission requests are a control mechanism meant to help users oversee and safeguard access to data and resources on their smartphones. To decide whether to accept or deny such requests and make this consent valid, users need to understand the underlying reasons and judge the relevance of disclosing data in line with their own use of an app. This study investigates people’s certainty about app permission requests via an online survey with 400 representative participants of the UK population. The results demonstrate that users are uncertain about the necessity of granting app permissions for about half of the tested permission requests. This implies substantial privacy risks, which are discussed in the paper, resulting in a call for user-protecting interventions by privacy engineers. [less ▲]

Intelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges

in IEEE Network (in press)

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement ... [more ▼]

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement based on blockchain mining. Yet the existing approaches for these enabling technologies are isolated, providing only tailored solutions for specific services and scenarios. To fill this gap, we propose a novel cooperative task offloading and blockchain mining (TOBM) scheme for a blockchain-based MEC system, where each edge device not only handles computation tasks but also deals with block mining for improving system utility. To address the latency issues caused by the blockchain operation in MEC, we develop a new Proof-of-Reputation consensus mechanism based on a lightweight block verification strategy. To accommodate the highly dynamic environment and high-dimensional system state space, we apply a novel distributed deep reinforcement learning-based approach by using a multi-agent deep deterministic policy gradient algorithm. Experimental results demonstrate the superior performance of the proposed TOBM scheme in terms of enhanced system reward, improved offloading utility with lower blockchain mining latency, and better system utility, compared to the existing cooperative and non-cooperative schemes. The paper concludes with key technical challenges and possible directions for future blockchain-based MEC research. [less ▲]

Maschinelles Lernen in der automatischen Auswertung von Punktwolken: Beispiele der Erfahrungen an der Universität Luxemburg

Scientific Conference (2023, October 07)

I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies

in Proceedings on Privacy Enhancing Technologies (2023)

Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as a disease, in a group of individuals. Unfortunately, careless sharing of GWAS ... [more ▼]

Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as a disease, in a group of individuals. Unfortunately, careless sharing of GWAS statistics might give rise to privacy attacks. Several works attempted to reconcile secure processing with privacy-preserving releases of GWASes. However, we highlight that these approaches remain vulnerable if GWASes utilize overlapping sets of individuals and genomic variations. In such conditions, we show that even when relying on state-of-the-art techniques for protecting releases, an adversary could reconstruct the genomic variations of up to 28.6% of participants, and that the released statistics of up to 92.3% of the genomic variations would enable membership inference attacks. We introduce I-GWAS, a novel framework that securely computes and releases the results of multiple possibly interdependent GWASes. I-GWAS continuously releases privacy-preserving and noise-free GWAS results as new genomes become available. [less ▲]

A review: Suppression of the solidification cracks in the laser welding process by controlling the grain structure and chemical compositions

in Advanced joining processes (2023), 7

Laser beam welding of miscellaneous material combinations is an effective joining technology useful for diverse industrial applications because it can provide high speed, flexibility, and precision ... [more ▼]

Laser beam welding of miscellaneous material combinations is an effective joining technology useful for diverse industrial applications because it can provide high speed, flexibility, and precision. However, welding defects like solidification cracking are some of the challenges in the joining process. The past decade has seen an extended effort to deal with this issue in many studies. However, there remains to be more comprehensive research regarding preventive procedures for solidification cracking by changing the grain structure. Following a thorough understanding of the solidification crack mechanism theories, we reviewed recent research on the critical role of metallurgical factors in the solidification cracks during laser welding. It considers the influence of the grain structure, intermetallic compounds, and laser welding parameters to propose preventive procedures to suppress the solidification cracks. Recent achievements show grain refiners, laser beam oscillation, ultrasonic vibration, and implementation of double laser sources are the main strategies that suppress or minimize solidification cracks. Furthermore, in laser beam welding of dissimilar materials, like steel-hard metal and copper-aluminum, brittle intermetallic compounds are recognized as one of the main reasons for the solidification crack susceptible increment. Recent approaches to overcome the formation or reduce the number of intermetallic compounds through various laser parameters and setups are discussed. [less ▲]

The Digital Archive and the Politics of Digitisation

Presentation (2023, April 28)

This paper will explore a key question for historians today: what are the politics of cultural heritage digitisation and its implications for historical research? What are the benefits and opportunities ... [more ▼]

This paper will explore a key question for historians today: what are the politics of cultural heritage digitisation and its implications for historical research? What are the benefits and opportunities afforded by digitisation and what challenges arise? How do digital resources shape the historical themes, topics, and debates that can be researched, and how might they influence research agendas more broadly? In what ways can they enable us to ask new research questions or open avenues of inquiry that challenge existing master narratives? Can digital resources facilitate research into transnational histories when most digitization projects are still nationally framed? In short, what biases might digital archives introduce in our work and how does that differ from issues of bias and selection in the ‘paper’ archive? To address questions such as these, I will discuss several key parameters of the politics of digitisation set within a broader historical and global context. [less ▲]

Towards Log Slicing

in Dawes, Joshua; Shin, Donghwan; Bianculli, Domenico (Eds.) Towards Log Slicing (2023, April)

This short paper takes initial steps towards developing a novel approach, called log slicing, that aims to answer a practical question in the field of log analysis: Can we automatically identify log ... [more ▼]

This short paper takes initial steps towards developing a novel approach, called log slicing, that aims to answer a practical question in the field of log analysis: Can we automatically identify log messages related to a specific message (e.g., an error message)? The basic idea behind log slicing is that we can consider how different log messages are "computationally related" to each other by looking at the corresponding logging statements in the source code. These logging statements are identified by 1) computing a backwards program slice, using as criterion the logging statement that generated a problematic log message; and 2) extending that slice to include relevant logging statements. The paper presents a problem definition of log slicing, describes an initial approach for log slicing, and discusses a key open issue that can lead towards new research directions. [less ▲]

Personal Informatics at Work

Scientific Conference (2023, April)

An ever-increasing amount of sensor technologies surrounds our work environment, collecting data about workers? activity and wellbeing ? often without them having any say in this. This datafication of the ... [more ▼]

An ever-increasing amount of sensor technologies surrounds our work environment, collecting data about workers? activity and wellbeing ? often without them having any say in this. This datafication of the workplace can help find novel ways to stimulate healthy behaviors or increase productivity. However, the ubiquitous usage of data collectors in the workplace can also put employees in a position of power imbalance, where management is frequently aiming at ?optimizing? employees towards normative and more-than-often problematic standards of productivity and wellbeing. Yet, data-tracking practices might not only seek an optimum but also can be interpreted towards self-enhancement (Meissner, 2016). In this sense, optimization is not per se an improvement on previous goals, but rather allows ?the discovery of new opportunities?. Indeed, data can be a means of giving space for users to be curious about their own subjective work experiences. Personal Informatics research has mostly focused on leisure and health-related topics but it takes on different forms, requirements, and ethical considerations for a work context. To explore how such considerations emerge from material practices, we conducted a field study, deploying a research probe called Habilyzer at a workplace (N=5). Findings show that users explored aspects meaningful to them yet highlight discrepancies between the envisioned self-tracking goals and participants? practices. Regarding sensors? open-endedness, a balance between the burden of data collection and the value derived from it appeared critical. We contribute new insights into how open-ended sensor technologies can be designed to support self-tracking practices in the workplace. [less ▲]