Context: The European Union has recently introduced a suite of foundational digital regulations—the Cyber Resilience Act, the Artificial Intelligence Act, the Radio Equipment Directive, the NIS 2 Directive, and the Cybersecurity Act—that directly affect the engineering of software-intensive systems. While these instruments aim to enhance trust and security, their overlapping scopes generate a complex compliance landscape that software development must address at the design, implementation, and deployment stages. Objectives: This paper examines the cross-regulatory impact of such EU cybersecurity legislation from a software engineering perspective, aiming to provide a set of guidelines and recommendations for implementing a compliance-by-design approach. Method: We analyse and compare the five legal instruments, focusing on how their obligations intersect with each other. We then translate their regulatory requirements into actionable artefacts, ranging from architectural constraints and security controls to organisational processes, using a legal engineering approach. Finally, we propose a compliance-by-design lifecycle pattern that integrates regulatory alignment into requirements engineering, system design, and testing. Results: To demonstrate applicability, we evaluate three representative use cases: an AI-enabled power plant, an autonomous drone delivery platform, and an AI-powered clinical decision support system. These examples demonstrate that multiple regulatory regimes often govern software-based systems. We conclude with practical recommendations for suppliers, deployers, and policymakers towards an integrated compliance framework to promote compliance-aware software engineering. Conclusion: Our findings indicate that the European digital landscape is shifting compliance from a post-hoc audit exercise to a design-time engineering principle. Embedding compliance early into the software development lifecycle not only supports regulatory alignment but also improves system resilience and trustworthiness.

We present the Di2Win Document Intelligence Platform (DIP). This modular AI-driven pipeline transforms raw document images --- captured by scanners or mobile phones --- into structured data and business actions in a single pass. The system comprises five loosely-coupled micro-services: (1) image-quality verification using a contrast-invariant model that flags blur, skew, and illumination issues above 100 ms per page; (2) document classification via a Transformer-base model with layout embeddings, delivering top-k types with calibrated confidence; (3) information extraction through i) Dilbert, a multimodal Token-Layout-Language model fine-tuned on weakly-labeled forms or ii) Delfos, a Large Language Model Mixture of Experts fine-tuned with well-defined prompts; (4) DataDrift, a powerful rules engine to avoid inconsistent outputs concerning the business process; and (5) process automation orchestrated by a Business Process Model Notation (BPMN) plus a Robot Process Automation (RPA) engine that routes results to databases, APIs, or human-review queues. All AI components are orchestrated through a messaging service to control the information flow, and the application exposes REST/gRPC endpoints to communicate with outside consumers. This enables the hot-swapping of models without downstream code changes by plugging a new message consumer into the messaging system. This also provides horizontal scalability since to increase the application throughput, we only need to add new AI engine consumers to the messaging system. Deployed in banking, insurance, and healthcare, the Di2Win DIP has processed more than 30 million pages, reducing average handling time by 79% and re-keying errors by 86 %, speeding up the workflows up to ten times. Our DocEng demonstration allows attendees to upload documents, observe live quality and confidence dashboards, and edit extracted fields with immediate feedback to the active-learning loop.

This article presents a novel approach that automates part of the work of network security architects, enabling them to design fine-grained secure network architectures. We have developed a methodology that, starting from high-level security requirements, called intents, and an initial unprotected network architecture, computes the optimal security zones and integrates security functions to protect both inter- and intra-zone communications. We implemented this methodology as a proof-of-concept framework, leveraging the flexibility and expressivity of Answer Set Programming, a form of declarative logic programming.

Metaverse brings a new era in educational settings, providing a wide range of services, such as VR-and XR-based skill training and AI-driven individualised learning experiences. While educational metaverses unlock unique opportunities for enriched learning experiences, they concurrently raise security and privacy concerns due to their heterogeneous nature. In this work, we provide a concise overview of the potentials of metaverse technologies within education and how their vulnerabilities could hinder them, formulating critical research questions encompassing a wide spectrum of concerns. In addition, we provide an overview of research works promising a trustworthy metaverse environment and propose potential remedies to address the identified challenges. By exploring these issues, this work aims to contribute to the development of trustworthy educational metaverse environments.

Data quality plays a crucial role in the data governance of organizations, as it is essential to ensure that data are fit for the purpose for which they are intended, whether for operational activities, decision-making processes, or strategic planning. As data silos begin to be integrated to form data spaces, guaranteeing data quality becomes a necessity to achieve a reliable collaborative ecosystem. Nevertheless, the concept of data quality remains ambiguous, with various definitions and interpretations offered in the literature, despite its importance. This lack of consensus has led to the need for a thorough review of the different data quality criteria used in scientific work. Therefore, this paper serves as a systematic survey aimed at exploring and consolidating diverse perspectives on data quality. By thoroughly analyzing existing literature, this study compiles a comprehensive set of 30 agreed-upon data quality criteria, with their respective names and definitions. These criteria act as a valuable resource for organizations seeking to establish effective data quality monitoring practices. Then, we expose challenges raised by collaborative data processing and highlight possible research directions where data quality plays a major role.

This article presents an overview and analysis of the key cybersecurity problems, challenges and requirements to be addressed in the future, which we derived through 63 interviews with European stakeholders from security-critical sectors including Open Banking, Supply Chain, Privacy-preserving Identity Management, Security Incident Reporting, Maritime Transport, Medical Data Exchange, and Smart Cities. We show that common problems, challenges and requirements across these sectors exist in relation to building trust, implementing privacy and identity management including secure and useable authentication, building resilient systems, standardisation and certification, achieving security and privacy by design, secure and privacy-compliant data and information sharing, and government regulations. Our results also indicate cybersecurity trends and allow to derive directions for future research and innovation activities that will be of high importance for Europe.

It is well-known that Massive MIMO systems (Multiple-input multiple-output) have high potential for future wireless broadband systems. Massive MIMO (m-MIMO) relies on spatial multiplexing, and for that reason the base station needs a precise channel knowledge at uplink and downlink. Pilots can be used for channel state information (CSI) estimation, but common estimation processes imply a matrix inversion which can be a heavy computational process for m-MIMO system where the number of antennas used in the communication is very high. To alleviate computational requirements, reduce latency and to improve battery life capacity of mobile devices matrix inversion operations should be avoided. Having in mind these constrains, a new channel estimation method based on Zadoff-Chu (ZC) sequences is presented here, that achieves similar or better performance than least squares (LS) or minimum mean-Square Error (MMSE) channel estimators. It is also presented a set of performance results that sustain our assumption.

Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. All these requirements should be met while assuring energy efficiency for mobile devices and base stations. Most likely, the future 5G systems will include massive MIMO (Multiple Input Multiple Output) schemes with dozen or hundreds of antennas enabling beamforming while operating in the millimeter wave spectrum. As soon as the millimetric wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped. This paper presents a transmission system with bi-dimensional antenna arrays, based on a double layer structure combining beamforming with a multi-branch power amplification that achieves simultaneously power efficiency in amplification of multilevel constellations without penalties on system performance when compared with common schemes using only beamforming.

This paper presents a new algorithm for filtering images of Brazilian bank checks. These images were generated by ATM machines and they present several kind of noise imposed by the digitization process. A new wavelet-based filtering algorithm is proposed for these images allowing a more efficient binarization process using percentage of black thresholding method.

The assessment of routing protocols for wireless networks is a difficult task, because of the networks' highly dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and low earth orbit (LEO) satellites systems, have more predictable dynamics, as the temporal variations in the network topology are somehow deterministic, which may make them easier to study. The graph theoretic model - the evolving graphs - was proposed to help capture the dynamic behavior of these networks, in view of the construction of least cost routing and other algorithms. Our recent experiments showed that evolving graphs have all the potentials to be an effective and powerful tool in the development of routing protocols for dynamic networks. In this paper, we evaluated the shortest journey evolving graph algorithm when used in a routing protocol for MANETs. We use the NS2 network simulator to compare this first implementation to the four well known protocols, namely AODV, DSR, DSDV, and OLSR. In this paper we present simulation results on the energy consumption of the nodes. We also included other EG protocol, namely EGForemost, in the experiments.

In the broadcasting problem, one node needs to broadcast a message to all other nodes in a network. If nodes can only communicate with one neighbor at a time, broadcasting takes at least $\lceil \log_2 N \rceil$ rounds in a network of N nodes. In the neighborhood broadcasting problem, the node that is broadcasting needs to inform only its neighbors. In a binary hypercube with N nodes, each node has $\log_2 N$ neighbors, so neighborhood broadcasting takes at least $\lceil \log_2 \log_2 (N+1) \rceil$ rounds. In this paper, we present asymptotically optimal neighborhood broadcast protocols for binary hypercubes.

The highly dynamic behavior of wireless networks make them very difficult to evaluate, e.g. as far as the performance of routing algorithms is concerned. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and low Earth orbit (LEO) satellites systems have more predictable dynamics, as the temporal variations in the network topology are somehow deterministic. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of these networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study on the uses of these theoretical results into practical situations. Therefore, the objective of this work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we used the NS2 network simulator to first implement an evolving graph based routing protocol, and then to evaluate such protocol compared to three major ad-hoc protocols (DSDV, DSR, AODV). Interestingly, our experiments showed that evolving graphs have all the potentials to be an effective and powerful tool in the development of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like stochastically predictable behavior. We also discuss such issues in this paper, as a result of our experience

Abstract This paper describes efficient coarse‐grained parallel algorithms and implementations for a suite of interval graph problems. Included are algorithms requiring only a constant number of communication rounds for connected components, maximum weighted clique, and breadth‐first‐search and depth‐first‐search trees, as well as $O(log p)$ communication rounds algorithms for optimization problems such as minimum interval covering, maximum independent set and minimum dominating set, where $p$ is the number of processors in the parallel system. This implies that the number of communication rounds is independent of the problem size. Implementations of these algorithms are evaluated on parallel clusters, using both Fast Ethernet and Myrinet interconnection networks, and on a CRAY T3E parallel multicomputer, with extensive experimental results being presented and analyzed. Copyright © 2002 John Wiley & Sons, Ltd.

Abstract The de Bruijn digraph B(d, D) has degree d, diameter D, dD vertices, and dD+1 arcs. It is usually defined by words of size D on an alphabet of cardinality d, through a cyclic left‐shift permutation on the words, after which the rightmost symbol is changed. In this paper, we show that any digraph defined on words of a given size, through an arbitrary permutation on the alphabet and an arbitrary permutation on the word indices, is isomorphic to the de Bruijn digraph, provided that this latter permutation is cyclic. We use this result to improve from O(dD+1) to $\Theta(\sqrt{d^{D+1}})$ the number of lenses required for the implementation of B(d, D) by the Optical Transpose Interconnection System proposed by Marsden et al. [Opt Lett 18 (1993), 1083–1085]. © 2002 Wiley Periodicals, Inc.

The de Bruijn digraph B(d, D) is usually defined by words of size D on an alphabet of cardinality d, through a cyclic left shift permutation on the words, after which the rightmost symbol is changed. In this paper we show that any digraph defined on words and alphabets of the same size, through an arbitrary permutation on the alphabet and an arbitrary permutation on the word indices, is isomorphic to the de Bruijn, provided that this latter permutation is cyclic. This work is motivated by the next application. It is known that the optical transpose interconnection system from UCSD can implement the de Bruijn interconnections for n nodes, for a fixed d, with O(n) lenses. We show here how to improve this hardware requirement to /spl Theta/(/spl radic/n).

The main result of this paper shows that the block-based digital medial axis transform can be computed in parallel by a constant number of calls to scan (parallel prefix) operations. This gives time- and/or work-optimal parallel implementations for the distance-based and the block-based medial axis transform in a wide variety of parallel architectures. Since only eight scan operations plus a dozen local operations are performed, the algorithm is very easy to program and use. The originality of our approach is the use of the notion of a derived grid and the oversampling of the image in order to reduce the computation of the block-based medial axis transform in the original grid to the much easier task of computing the distance based medial axis transform of the oversampling of the image on the derived grid.

In the multiprocessor scheduling problem, a given program is to be scheduled in a given multiprocessor system such that the program's execution time is minimized. This problem being very hard to solve exactly, many heuristic methods for finding a suboptimal schedule exist. We propose a new combined approach, where a genetic algorithm is improved with the introduction of some knowledge about the scheduling problem represented by the use of a list heuristic in the crossover and mutation genetic operations. This knowledge-augmented genetic approach is empirically compared with a "pure" genetic algorithm and with a "pure" list heuristic, both from the literature. Results of the experiments carried out with synthetic instances of the scheduling problem show that our knowledge-augmented algorithm produces much better results in terms of quality of solutions, although being slower in terms of execution time.

This paper presents a new decomposition technique for hierarchical Cayley graphs. This technique yields a very easy implementation of the divide and conquer paradigm for some problems on very complex architectures as the star graph or the pancake. As applications, we introduce algorithms for broadcasting and prefix-like operations that improve the best known bounds for these problems. We also give the first nontrivial optimal gossiping algorithms for these networks. In star-graphs and pancakes with N=n! processors, our algorithms take less than [log N]+1.5n steps.

The main result of this paper shows that the block-based digital medial axis transform can be computed in parallel by a constant number of calls to scan (parallel prefix) operations. This gives time- and/or work-optimal parallel algorithms for the distance-based and the block-based medial axis transform in a wide variety of parallel architectures. In order to design such an algorithm, we first demonstrate that computing a block-based medial axis transform of a binary image reduces to computing the distance based medial axis transform of an oversampling of the image, by proving that their labelings are equivalent.

A parallel algorithm for solving the knapsack problem on a single-instruction, multiple-data machine with shared memory is presented. The shared memory allows concurrent reading while concurrent writing is forbidden. The knapsack problem is of size n, which the algorithm solves in time T=O(n*(2/sup n/2/)/sup epsilon /) when P=O((2/sup n/2/)/sup (1- epsilon )/), 0>

A parallel algorithm for generating all the k! permutations of kPk for every (1 ≤k ≤ n) is presented. The architecture consists of a linear processor array with n elements. The kth processor receives a permutation p of k–1Pk–1 from the (k — 1 )th processor and intercalates k at all the k possible positions of the sequence p, one at a time. After each intercalation it sends the permutation obtained to the (k + l)th processor and also outputs it. In this way the nth processor outputs all the n! permutations of nPn in (n + n!) units of time and our profit are all the kPk(1 ≤k < N) which output is included in that time. The network is VLSI implementable and fault tolerant. It is shown how to find the position of a given permutation and how to obtain the permutation of a given position, where position refers to the generation order of the permutations by each processor. With a simple modification in the algorithm performed by the processors, the network is able to generate combinations.