Doina Bucur

University of Twente | UT · Department of Computer Science

We aim to learn the functional co-response group: a group of taxa whose co-response effect (the representative characteristic of the group) associates well statistically with a functional variable. Different from the state-of-the-art method, we model the soil microbial community as an ecological co-occurrence network with the taxa as nodes (weighte...

We propose a novel model-selection method for dynamic networks. Our approach involves training a classifier on a large body of synthetic network data. The data is generated by simulating nine state-of-the-art random graph models for dynamic networks, with parameter range chosen to ensure exponential growth of the network size in time. We design a c...

Pruning-at-Initialization (PaI) algorithms provide Sparse Neural Networks (SNNs) which are computationally more efficient than their dense counterparts, and try to avoid performance degradation. While much emphasis has been directed towards how to prune, we still do not know what topological metrics of the SNNs characterize good performance. From p...

Soil ecological networks enable us to better understand the complex interactions among a great number of organisms in soil. Soil communities are biotic groups with similar environmental and resource preferences. Community detection thus provides insights into the mechanisms of the soil ecosystem. Therefore, inferring ecological networks with clear...

We answer the question whether, when forming constellations on the night sky, people in astronomical cultures around the world consistently imagine and assign the same symbolism to the same (type of) star cluster. Evidence of such semantic universality has so far been anecdotal. We use two complementary definitions for a star cluster: defined eithe...

In this work, we propose a novel unrolled input- aware bipartite Graph Encoding (GE) that is able to generate, for each layer in a Neural Network, its cor- responding unrolled graph representation based on its relation with the input data. We also extend it into a multipartite GE, to capture the relation between non-consecutive layers.

Small and medium enterprises rely on detailed Web analytics to be informed about their market and competition. Focused crawlers meet this demand by crawling and indexing specific parts of the Web. Critically, a focused crawler must quickly find new pages that have not yet been indexed. Since a new page can be discovered only by following a new outl...

Finding the most influential nodes in a network is a computationally hard problem with several possible applications in various kinds of network-based problems. While several methods have been proposed for tackling the influence maximisation (IM) problem, their runtime typically scales poorly when the network size increases. Here, we propose an ori...

Many industrial sectors have been collecting big sensor data. With recent technologies for processing big data, companies can exploit this for automatic failure detection and prevention. We propose the first completely automated method for failure analysis, machine-learning fault trees from raw observational data with continuous variables. Our meth...

In traditional astronomies across the world, groups of stars in the night sky were linked into constellations—symbolic representations rich in meaning and with practical roles. In some sky cultures, constellations are represented as line (or connect-the-dot) figures, which are spatial networks drawn over the fixed background of stars. We analyse 18...

Finding the most influential nodes in a network is a computationally hard problem with several possible applications in various kinds of network-based problems. While several methods have been proposed for tackling the influence maximisation (IM) problem, their runtime typically scales poorly when the network size increases. Here, we propose an ori...

Many industrial sectors have been collecting big sensor data. With recent technologies for processing big data, companies can exploit this for automatic failure detection and prevention. We propose the first completely automated method for failure analysis, machine-learning fault trees from raw observational data with continuous variables. Our meth...

We measure the color shifts present in colorized images from the ADE20K dataset, when colorized by the automatic GAN-based DeOldify model. We introduce fine-grained local and regional bias measurements between the original and the colorized images, and observe many colorization effects. We confirm a general desaturation effect, and also provide nov...

Discovering new hyperlinks enables Web crawlers to find new pages that have not yet been indexed. This is especially important for focused crawlers because they strive to provide a comprehensive analysis of specific parts of the Web, thus prioritizing discovery of new pages over discovery of changes in content. In the literature, changes in hyperli...

In traditional astronomies across the world, groups of stars in the night sky were linked into constellations -- symbolic representations on the celestial sphere, rich in meaning and with practical roles. In cultures where line or connect-the-dot figures were documented, these visual representations are constrained to the fixed background of stars,...

Mobile malware are malicious programs that target mobile devices. They are an increasing problem, as seen with the rise of detected mobile malware samples per year. The number of active smartphone users is expected to grow, stressing the importance of research on the detection of mobile malware. Detection methods for mobile malware exist but are st...

Mobile malware are malicious programs that target mobile devices. They are an increasing problem, as seen in the rise of detected mobile malware samples per year. The number of active smartphone users is expected to grow, stressing the importance of research on the detection of mobile malware. Detection methods for mobile malware exist but are stil...

Social networks are one the main sources of information transmission nowadays. However, not all nodes in social networks are equal: in fact, some nodes are more influential than others, i.e., their information tends to spread more. Finding the most influential nodes in a network—the so-called Influence Maximization problem—is an NP-hard problem wit...

Humans are good at compositional zero-shot reasoning; someone who has never seen a zebra before could nevertheless recognize one when we tell them it looks like a horse with black and white stripes. Machine learning systems, on the other hand, usually leverage spurious correlations in the training data, and while such correlations can help recogniz...

Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers or spreaders in a large network, no single centrality has consistently good predictive power across a set of 60 finite, diverse, static real-world topologies from six cat...

Identifying important nodes for disease spreading is a central topic in network epidemiology. We investigate how well the position of a node, characterized by standard network measures, can predict its epidemiological importance in any graph of a given number of nodes. This is in contrast to other studies that deal with the easier prediction proble...

Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers or spreaders in a large network, no single centrality has consistently good ranking power. We show that statistical classifiers using two or more centralities as input ar...

Cyber-physical systems come with increasingly complex architectures and failure modes, which complicates the task of obtaining accurate system reliability models. At the same time, with the emergence of the (industrial) Internet-of-Things, systems are more and more often being monitored via advanced sensor systems. These sensors produce large amoun...

Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to an explosion of their complexity, size, and failure criticality. While expert knowledge of individual components exists, their interaction is complex. For these reasons, obtaining accurate system reliability models is a hard task. At the same time, s...

Identifying important nodes for disease spreading is a central topic in network epidemiology. We investigate how well the position of a node, characterized by standard network measures, can predict its epidemiological importance in any graph of a given number of nodes. This is in contrast to other studies that deal with the easier prediction proble...

Cyber-physical systems come with increasingly complex architectures and failure modes, which complicates the task of obtaining accurate system reliability models. At the same time, with the emergence of the (industrial) Internet-of-Things, systems are more and more often being monitored via advanced sensor systems. These sensors produce large amoun...

Organizations increasingly depend on Building Automation and Control Systems (BACSs) to support their daily tasks and to comply with laws and regulations. However, BACSs are prone to disruptions caused by failures or active attacks. Given the role BACSs play in critical locations such as airports and hospitals, a comprehensive impact assessment met...

We measure the gender homophily (and other network statistics) on large-scale online book markets: amazon.com and amazon.co.uk, using datasets describing millions of books sold to readers. Large book networks are created by sales (two books are connected if many readers have bought both books) and can recommend new books to buy. The networks are an...

Having insight into the causal associations in a complex system facilitates decision making, e.g., for medical treatments, urban infrastructure improvements or financial investments. The amount of observational data grows, which enables the discovery of causal relationships between variables from observation of their behaviour in time. Existing met...

Using a book co-buying network from amazon.com of over 1 million books, we find empirically that readers who have purchased male first authors before are substantially less likely than expected to buy books by female first authors, when aggregated across the entire book market. Conversely, past buyers of female authors are slightly more likely than...

In novel forms of the Social Internet of Things, any mobile user within communication range may help routing messages for another user in the network. The resulting message delivery rate depends both on the users' mobility patterns and the message load in the network. This new type of configuration, however, poses new challenges to security, amongs...

One of the most relevant problems in social networks is influence maximization, that is the problem of finding the set of the most influential nodes in a network, for a given influence propagation model. As the problem is NP-hard, recent works have attempted to solve it by means of computational intelligence approaches, for instance Evolutionary Al...

In the context of social networks, maximizing influence means contacting the largest possible number of nodes starting from a set of seed nodes, and assuming a model for influence propagation. The real-world applications of influence maximization are of uttermost importance, and range from social studies to marketing campaigns. Building on a previo...

A genetic algorithm with stochastic macro mutation operators which merge, split, move, reverse and align DNA contigs on a scaffold is shown to accurately and consistently assemble raw DNA reads from an accurately sequenced single-read library into a contiguous genome. A candidate solution is a permutation of DNA reads, segmented into contigs. An in...

As the pervasiveness of social networks increases, new NP-hard related problems become interesting for the optimization community. The objective of influence maximization is to contact the largest possible number of nodes in a network, starting from a small set of seed nodes, and assuming a model for information propagation. This problem is of utmo...

We design an evolutionary heuristic for the combinatorial problem of de-novo DNA assembly with short, overlapping, accurately sequenced single DNA reads of uniform length, from both strands of a genome without long repeated sequences. The representation of a candidate solution is a novel segmented permutation: an ordering of DNA reads into contigs,...

Increasingly more digital communication is routed among wireless, mobile computers over ad-hoc, unsecured communication channels. In this paper, we design two stochastic search algorithms (a greedy heuristic, and an evolutionary algorithm) which automatically search for strong insider attack methods against a given ad-hoc, delay-tolerant communicat...

We live in a world of social networks. Our everyday choices are often influenced by social interactions. Word of mouth, meme diffusion on the Internet, and viral marketing are all examples of how social networks can affect our behaviour. In many practical applications, it is of great interest to determine which nodes have the highest influence over...

In novel forms of the Social Internet of Things, any mobile user within communication range may help routing messages for another user in the network. The resulting message delivery rate depends both on the users’ mobility patterns and the message load in the network. This new type of configuration, however, poses new challenges to security, amongs...

Find the dataset at the link: https://www.dropbox.com/s/l98aln9g87caatk/datasets-release-v3.zip?dl=0

A challenging aspect in open ad hoc networks is their resilience against malicious agents. This is especially true in complex, urban-scale scenarios where numerous moving agents carry mobile devices that create a peer-to-peer network without authentication. A requirement for the proper functioning of such networks is that all the peers act legitima...

Routing protocols for ad-hoc networks, e.g., the Collection Tree Protocol (CTP), are designed with simple node-local behaviour, but are deployed on testbeds with uncontrollable physical topology; exhaustively verifying the protocol on all possible topologies at design time is not tractable. We obtain topological insights on CTP performance, to answ...

Wireless sensor network (WSN) routing protocols, e.g., the Collection Tree Protocol (CTP), are designed to adapt in an ad-hoc fashion to the quality of the environment. WSNs thus have high internal dynamics and complex global behavior. Classical techniques for performance evaluation (such as testing or verification) fail to uncover the cases of ext...

The analysis of worst-case behavior in wireless sensor networks is an extremely difficult task, due to the complex interactions that characterize the dynamics of these systems. In this paper, we present a new methodology for analyzing the performance of routing protocols used in such networks. The approach exploits a stochastic optimization techniq...

In pervasive computing environments, wireless sensor networks play an important infrastructure role, collecting reliable and accurate context information so that applications are able to provide services to users on demand. In such environments, sensors should be self-adaptive by taking correct decisions based on sensed data in real-time in a decen...

In distributed business process support environments, process interference from multiple stakeholders may cause erroneous process outcomes. Existing solutions to detect and correct interference at runtime employ formal verification and the automatic generation of intervention processes at runtime. However, these solutions are limited in their gener...

Accurate human activity recognition (AR) is crucial for intelligent pervasive environments, e.g., energy-saving buildings. In order to gain precise and fine-grained AR results, a system must overcome partial observability of the environment and noisy, imprecise, and corrupted sensor data. In this work, we propose a rule-based AR architecture that e...

Wireless Sensor Networks (WSNs) are widely adopted for applications ranging from surveillance to environmental monitoring. While powerful and relatively inexpensive, they are subject to behavioural faults which make them unreliable. Due to the complex interactions between network nodes, it is difficult to uncover faults in a WSN by resorting to for...

Networked embedded systems generally have extremely low visibility of system faults. In this paper, we report on experimenting with online, node-local temporal monitors for networked embedded nodes running the TinyOS operating system and programmed in the nesC lan-guage. We instrument the original node software to signal asynchronous atomic events...

Formal verification of business process models is of interest to a number of application areas, including checking for basic process correctness, business compliance, and process variability. A large amount of work on these topics exist, while a comprehensive overview of the field and its directions is lacking. We provide an overview and critical r...

We consider software written for networked, wireless sensor nodes, and specialize software verification techniques for standard C programs in order to locate programming errors in sensor applications before the software's deployment on motes. Ensuring the reliability of sensor applications is challenging: low-level, interrupt-driven code runs witho...

As embedded sensing systems are central to developing pervasive, context-aware services, the applications running on these systems should be intelligible to system programmers and to users. Given that sensor systems are programmed in low-level languages, manually writing high-level explanations about their decision model requires knowledge about th...

Ensuring the reliability of the software deployed on net- worked wireless sensors is a difficult problem: unsafe, low-level, interrupt-driven code runs without memory protection in dynamic environments. To aid the mat- ter, we describe a software analysis tool for the debug- ging and verification of TinyOS 2, MSP430 applications at compile-time. Wh...

We provide the first tool for verifying the logic of context- aware applications written for the mainstream sensor network operating system TinyOS; we focus on detecting programming errors related to incorrect adaptation to context.

Introduction Context-aware applications are typically designed with concurrent context handlers. Verification techniques guarantee their behaviour against a specification; to date, contributions include either the verification of models rather than real software, or validation. Of the latter, [3] generates test suites for context-aware Java program...

We introduce the harvesting of natural background radioactivity for positioning. Using a standard Geiger-Müller counter as sensor, we fingerprint the natural levels of gamma radiation with the aim of then roughly pinpointing the position of a client in terms of interfloor, intrafloor, and indoor-versus-outdoor locations. We find that the performanc...

WepresentaMobile-Ambients-based processcalculustode- scribe context-aware computing in an infrastructure-based Ubiquitous Computing setting. In our calculus, computing agents can provide and discover contextual information and are owners of security policies. Sim- pleaccesscontroltocontextualinformationisnotsu-cienttoinsurecon- fldentiality in Glob...

This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in human-centered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in activity-based sensor networks (ABSNs) knowledge about their usage even at the n...

This paper proposes a service discovery protocol for sensor networks that is specifically tailored for human-centered pervasive environments and scales well to large sensor networks, such as those deployed for medical care in major incidents and hospitals. It uses the high-level concept of computational activities (logical bundles of data and resou...

Introduction For the mainstream sensor operating system TinyOS, a pro- grammer writes concurrent, shared-memory software in either nesC or the recent C TosThreads API (3). Elusive concurrency errors arise because of the nonde- terministic thread interleavings, while context-awareness errors are due to the application's inability to deal with unexpe...

We describe the first software tool for the verification of TinyOS 2, MSP430 applications at compile-time. Given as-sertions upon the state of the sensor node, the tool bound-edly explores all program executions and returns to the pro-grammer an error trace leading to any assertion violation. Besides memory-related errors (out-of-bounds arrays, nul...