Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

Songlin Lyu, Francesco Amodio, Giovanni De Gregorio et al.

We present the results of the application of a nuclear potential consisting of two- and three-nucleon contact interactions in nuclear structure investigations. The nuclear Hamiltonian has been derived for a very low-energy regime within the framework of the effective field theory, its low-energy constants have been fitted to a few low-energy nucleon-nucleon experimental observables and the deuteron and 3H binding energies. Our goal is to validate the ability of this Hamiltonian to reproduce some important features of open-shell nuclei, and to this end we derive effective shell-model Hamiltonians for nuclei in the p- and sd-shell mass regions. The results of shell-model calculations with these effective Hamiltonians are then compared with experiment, and also with those obtained with a nuclear Hamiltonian derived within chiral perturbation theory, that includes also terms with one- and two-pion exchanges.

Marcos Vinicius Cruz, Pragya Verma, Grischa Liebel

Dyslexia is a common learning disorder that primarily impairs an individual's reading and writing abilities. In adults, dyslexia can affect both professional and personal lives, often leading to mental challenges and difficulties acquiring and keeping work. In Software Engineering (SE), reading and writing difficulties appear to pose substantial challenges for core tasks such as programming. However, initial studies indicate that these challenges may not significantly affect their performance compared to non-dyslexic colleagues. Conversely, strengths associated with dyslexia could be particularly valuable in areas like programming and design. However, there is currently no work that explores the experiences of dyslexic software engineers, and puts their strengths into relation with their difficulties. To address this, we present a qualitative study of the experiences of dyslexic individuals in SE. We followed the basic stage of the Socio-Technical Grounded Theory method and base our findings on data collected through 10 interviews with dyslexic software engineers, 3 blog posts and 153 posts on the social media platform Reddit. We find that dyslexic software engineers especially struggle at the programming learning stage, but can succeed and indeed excel at many SE tasks once they master this step. Common SE-specific support tools, such as code completion and linters are especially useful to these individuals and mitigate many of the experienced difficulties. Finally, dyslexic software engineers exhibit strengths in areas such as visual thinking and creativity. Our findings have implications to SE practice and motivate several areas of future research in SE, such as investigating what makes code less/more understandable to dyslexic individuals.

Hassan Sartaj, Shaukat Ali, Ana Cavalcanti et al.

Self-adaptive robotic systems operate autonomously in dynamic and uncertain environments, requiring robust real-time monitoring and adaptive behaviour. Unlike traditional robotic software with predefined logic, self-adaptive robots exploit artificial intelligence (AI), machine learning, and model-driven engineering to adapt continuously to changing conditions, thereby ensuring reliability, safety, and optimal performance. This paper presents a research agenda for software engineering in self-adaptive robotics, structured along two dimensions. The first concerns the software engineering lifecycle, requirements, design, development, testing, and operations, tailored to the challenges of self-adaptive robotics. The second focuses on enabling technologies such as digital twins, AI-driven adaptation, and quantum computing, which support runtime monitoring, fault detection, and automated decision-making. We identify open challenges, including verifying adaptive behaviours under uncertainty, balancing trade-offs between adaptability, performance, and safety, and integrating self-adaptation frameworks like MAPE-K/MAPLE-K. By consolidating these challenges into a roadmap toward 2030, this work contributes to the foundations of trustworthy and efficient self-adaptive robotic systems capable of meeting the complexities of real-world deployment.

T. Chuprina, D. Méndez, V. Nigam et al.

Requirements specification patterns have received much attention as they promise to guide the structured specification of natural language requirements. By using them, the intention is to reduce quality problems related to requirements artifacts. Patterns may need to vary in their syntax (e.g. domain details/ parameter incorporation) and semantics according to the particularities of the application domain. However, pattern-based approaches, such as EARS, are designed domain-independently to facilitate their wide adoption across several domains. Little is yet known about how to adopt the principle idea of pattern-based requirements engineering to cover domain-specificity in requirements engineering and, ideally, integrate requirements engineering activities into quality assurance tasks. In this paper, we propose the Pattern-based Domain-specific Requirements Engineering Approach for the specification of functional and performance requirements in a holistic manner. This approach emerges from an academia-industry collaboration and is our first attempt to frame an approach which allows for analyzing domain knowledge and incorporating it into the requirements engineering process enabling automated checks for requirements quality assurance and computer-aided support for system verification. Our contribution is two-fold: First, we present a solution to pattern-based domain-specific requirements engineering and its exemplary integration into quality assurance techniques. Second, we showcase a proof of concept using a tool implementation for the domain of flight controllers for Unmanned Aerial Vehicles. Both shall allow us to outline next steps in our research agenda and foster discussions in this direction.

Filipe Fernandes, Cláudia Werner

Blockchain technologies for rewards in education are gaining attraction as a promising approach to motivate student learning and promote academic achievement. By providing tangible rewards for educational attainment and engagement, such as digital tokens, educators can motivate learners to take a more active role in their learning and increase their sense of ownership and responsibility for their academic outcomes. In this context, this work proposes the Software Engineering Skill (SES) token as a way of rewarding students in order to improve their experiences in Software Engineering Education (SEE). We performed a proof of concept and conclude that SES token can be deployed in a platform to support SEE.

Jorge Melegati, Eduardo Guerra

Software engineering researchers and practitioners have pursued manners to reduce the amount of time and effort required to develop code and increase productivity since the emergence of the discipline. Generative language models are just another step in this journey, but it will probably not be the last one. In this chapter, we propose DAnTE, a Degree of Automation Taxonomy for software Engineering, describing several levels of automation based on the idiosyncrasies of the field. Based on the taxonomy, we evaluated several tools used in the past and in the present for software engineering practices. Then, we give particular attention to AI-based tools, including generative language models, discussing how they are located within the proposed taxonomy, and reasoning about possible limitations they currently have. Based on this analysis, we discuss what novel tools could emerge in the middle and long term.

Daniel Russo

In this paper, the adoption patterns of Generative Artificial Intelligence (AI) tools within software engineering are investigated. Influencing factors at the individual, technological, and societal levels are analyzed using a mixed-methods approach for an extensive comprehension of AI adoption. An initial structured interview was conducted with 100 software engineers, employing the Technology Acceptance Model (TAM), the Diffusion of Innovations theory (DOI), and the Social Cognitive Theory (SCT) as guiding theories. A theoretical model named the Human-AI Collaboration and Adaptation Framework (HACAF) was deduced using the Gioia Methodology, characterizing AI adoption in software engineering. This model's validity was subsequently tested through Partial Least Squares - Structural Equation Modeling (PLS-SEM), using data collected from 183 software professionals. The results indicate that the adoption of AI tools in these early integration stages is primarily driven by their compatibility with existing development workflows. This finding counters the traditional theories of technology acceptance. Contrary to expectations, the influence of perceived usefulness, social aspects, and personal innovativeness on adoption appeared to be less significant. This paper yields significant insights for the design of future AI tools and supplies a structure for devising effective strategies for organizational implementation.

Oluwatosin Ogundare, Gustavo Quiros Araya, Yassine Qamsane

Industrial process engineering and PLC program development have traditionally favored Function Block Diagram (FBD) programming over classical imperative style programming like the object oriented and functional programming paradigms. The increasing momentum in the adoption and trial of ideas now classified as 'No Code' or 'Low Code' alongside the mainstream success of statistical learning theory or the so-called machine learning is redefining the way in which we structure programs for the digital machine to execute. A principal focus of 'No Code' is deriving executable programs directly from a set of requirement documents or any other documentation that defines consumer or customer expectation. We present a method for generating Function Block Diagram (FBD) programs as either the intermediate or final artifact that can be executed by a target system from a set of requirement documents using a constrained selection algorithm that draws from the top line of an associated recommender system. The results presented demonstrate that this type of No-code generative model is a viable option for industrial process design.

G. Chaudhuri, S. Mallik, P. Das et al.

The study of liquid-gas phase transition in heavy ion collisions has generated a lot of interest amongst the nuclear physicists in the recent years. In heavy ion collisions, there is no direct way of measuring the state variables like entropy, pressure, energy and hence unambiguous characterization of phase transition becomes difficult. This work proposes new signatures of phase transition that can be extracted from the observables which are easily accessible in experiments. It is observed that the temperature dependence of the first order derivative of the order parameters in nuclear liquid gas phase transition exhibit similar behavior as that of the variation of specific heat at constant volume Cv which is an established signature of first order phase transition. This motivates us to propose these derivatives as confirmatory signals of liquid-gas phase transition. The measurement of these signals in easily feasible in most experiments as compared to the other signatures like specific heat, caloric curve or bimodality. Total multiplicity, size of largest cluster are some of the order parameters which have been studied. Statistical Models based on canonical ensemble and lattice gas model has been used for the study. This temperature where the peak appears is designated to be the transition temperature and the effect of certain parameters on this has also been examined. The multiplicity derivative signature proposed in this work has been further confirmed by other theoretical models as well as in experimental study.

Yolanda D Austria, Luisito L. Lacatan, John Gregory D Funtera et al.

In this current world where technology is growing up day by day and scientific researchers are presenting new era of discoveries, the need for security is also increasing in all areas. At present, the vehicle usage is basic necessity for everyone. Simultaneously, protecting the vehicle against theft is also very important. Traditional vehicle security system depends on many sensors and cost is also high. When the vehicle is stolen, no more response or alternative could be available to help the owner of the vehicle to find it back. The main goal of this paper is to protect the vehicle from any unauthorized access, using fast, easy-to-use, clear, reliable and economical face recognition technique. An efficient automotive security system is implemented for anti-theft using an embedded system for starting the engine by the use of face recognition and integrated with Global Positioning System (GPS) and Global System for Mobile Communication (GSM). This proposed work is an attempt to design and develop a smart anti-theft system that uses Face recognition, GPS and GSM system to prevent theft and to determine the exact location of vehicle.

Shihang Shen, Haozhao Liang, Wen Hui Long et al.

Nuclear structure models built from phenomenological mean fields, the effective nucleon-nucleon interactions (or Lagrangians), and the realistic bare nucleon-nucleon interactions are reviewed. The success of covariant density functional theory (CDFT) to describe nuclear properties and its influence on Brueckner theory within the relativistic framework are focused upon. The challenges and ambiguities of predictions for unstable nuclei without data or for high-density nuclear matter, arising from relativistic density functionals, are discussed. The basic ideas in building an ab initio relativistic density functional for nuclear structure from ab initio calculations with realistic nucleon-nucleon interactions for both nuclear matter and finite nuclei are presented. The current status of fully self-consistent relativistic Brueckner-Hartree-Fock (RBHF) calculations for finite nuclei or neutron drops (ideal systems composed of a finite number of neutrons and confined within an external field) is reviewed. The guidance and perspectives towards an ab initio covariant density functional theory for nuclear structure derived from the RBHF results are provided.

Franco Zambonelli

As research in the Internet of Thing area progresses, and a multitude of proposals exist to solve a variety of problems, the need for a general principled software engineering approach for the systematic development of IoT systems and applications arises. In this paper, by synthesizing form the state of the art in the area, we attempt at framing the key concepts and abstractions that revolve around the design and development of IoT systems and applications, and draft a software engineering methodology centered on these abstractions.

T. Nakatsukasa, S. Ebata, P. Avogadro et al.

We present background concepts of the nuclear density functional theory (DFT) and applications of the time-dependent DFT with the Skyrme energy functional for nuclear response functions. Practical methods for numerical applications of the time-dependent Hartree-Fock-Bogoliubov theory (TDHFB) are proposed; finite amplitude method and canonical-basis TDHFB. These approaches are briefly reviewed and some numerical applications are shown to demonstrate their feasibility.

R. Machleidt, D. R. Entem

In spite of the great progress we have seen in recent years in the derivation of nuclear forces from chiral effective field theory (EFT), some important issues are still unresolved. In this contribution, we discuss the open problems which have particular relevance for microscopic nuclear structure, namely, the proper renormalization of chiral nuclear potentials and sub-leading many-body forces.

W. G. Newton

The first results of a new three-dimensional, finite temperature Skyrme-Hartree-Fock+BCS study of the properties of inhomogeneous nuclear matter at densities and temperatures leading to the transition to uniform nuclear matter are presented. A constraint is placed on the two independent components of the quadrupole moment in order to self-consistently explore the shape phase space of nuclear configurations. The scheme employed naturally allows effects such as (i) neutron drip, which results in an external neutron gas, (ii) the variety of exotic nuclear shapes expected for extremely neutron heavy nuclei, and (iii) the subsequent dissolution of these nuclei into nuclear matter. In this way, the equation of state can be calculated across phase transitions from lower densities (where one dimensional Hartree-Fock suffices) through to uniform nuclear matter without recourse to interpolation techniques between density regimes described by different physical models.

A. B. Balantekin

A survey of algebraic approaches to various problems in nuclear physics is given. Examples are chosen from pairing of many-nucleon systems, nuclear structure, fusion reactions below the Coulomb barrier, and supernova neutrino physics to illustrate the utility of group-theoretical and related algebraic methods in nuclear physics.

Matthias Lutz

We apply the relativistic chiral Lagrangian to the nuclear equation of state. An effective chiral power expansion scheme, which is constructed to work around nuclear saturation density, is presented. The leading and subleading terms are evaluated and are shown to provide an equation of state with excellent saturation properties. Our saturation mechanism is found to probe details of the nuclear pion dynamics.

A. Belic, D. J. Dean, M. Hjorth-Jensen

We discuss several pairing-related phenomena in nuclear systems, ranging from superfluidity in neutron stars to the gradual breaking of pairs in finite nuclei. We describe recent experimental evidence that points to a relation between pairing and phase transitions (or transformations) in finite nuclear systems. A simple pairing interaction model is used in order to study and classify an eventual pairing phase transition in finite fermionic systems such as nuclei. We show that systems with as few as 10-16 fermions can exhibit clear features reminiscent of a phase transition.

A. Frank, J. Barea, R. Bijker

Extensions of nuclear supersymmetry are discussed, together with a proposal for new, more stringent and precise tests that probe the susy classification and specific two-particle correlations among supersymmetric partners. The combination of these theoretical and experimental studies may play a unifying role in nuclear phenomena.

D. Kiderlen, V. M. Kolomietz, S. Shlomo

Within the nuclear Fermi-liquid drop model, quantum and thermal fluctuations are considered by use of the Landau-Vlasov-Langevin equation. The spectral correlation function of the nuclear surface fluctuations is evaluated in a simple model of an incompressible and irrotational Fermi liquid. The dependence of the spectral correlation function on the dynamical Fermi-surface distortion is established. The temperature at which the eigenvibrations become overdamped is calculated. It is shown that, for realistic values of the relaxation time parameter and in the high temperature regime, there is a particular eigenmode of the Fermi liquid drop where the restoring force is exclusively due to the dynamical Fermi-surface distortion.