Active artefact management for distributed software engineering

We describe a software artefact repository that provides its contents with some awareness of their own creation. "Active" artefacts are distinguished from their passive counterparts by their enriched meta-data model which reflects the work-flow process that created them, the actors responsible, the actions taken to change the artefact, and various other pieces of organisational knowledge. This enriched view of an artefact is intended to support re-use of both software and the expertise gained when creating the software. Unlike other organisational knowledge systems, the meta-data is intrinsically part of the artefact and may be populated automatically from sources including existing data-format specific information, user supplied data and records of communication. Such a system is of increased importance in the world of "virtual teams" where transmission of vital organisational knowledge, at best difficult, is further constrained by the lack of direct contact between engineers and differing development cultures

FLaMAS: Federated Learning Based on a SPADE MAS

[EN] In recent years federated learning has emerged as a new paradigm for training machine learning models oriented to distributed systems. The main idea is that each node of a distributed system independently trains a model and shares only model parameters, such as weights, and does not share the training data set, which favors aspects such as security and privacy. Subsequently, and in a centralized way, a collective model is built that gathers all the information provided by all of the participating nodes. Several federated learning framework proposals have been developed that seek to optimize any aspect of the learning process. However, a lack of flexibility and dynamism is evident in many cases. In this regard, this study aims to provide flexibility and dynamism to the federated learning process. The methodology used consists of designing a multi-agent system that can form a federated learning framework where the agents act as nodes that can be easily added to the system dynamically. The proposal has been evaluated with different experiments on the SPADE platform; the results obtained demonstrate the benefits of the federated system while facilitating flexibility and scalability.This research was partially supported by the MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government.Rincón-Arango, JA.; Julian, V.; Carrascosa Casamayor, C. (2022). FLaMAS: Federated Learning Based on a SPADE MAS. Applied Sciences. 12(7):1-14. https://doi.org/10.3390/app1207370111412

SPADE 3: Supporting the New Generation of Multi-Agent Systems

[EN] Although intelligent agent-based systems have existed for several years, the progression in terms of real applications or their integration in the industry have not yet reached the expected levels. During the last two decades, many agent platforms have appeared with the aim of simplifying the development of multi-agent systems. Some of these platforms have been designed for general purposes, while others have been oriented towards specific domains. However, the lack of standards and the complexity associated with supporting such systems, among other difficulties, have hampered their generalised use. This article looks in depth at the current situation of existing agent platforms, trying to analyse their current shortcomings and their expected needs in the near future. The goal of the paper is to identify possible lines of work and some of the most crucial aspects to be considered in order to popularize the application of agent technology as a dynamic and flexible solution to current problems. Moreover, the paper presents SPADE 3, a new version of the SPADE middleware, which has been totally redesigned in order to conform to the identified challenges. Finally, a case study is proposed to illustrate how SPADE 3 is able to fulfill these challenges.This work was supported in part by the Spanish Government, under Project RTI2018-095390-B-C31-AR.Palanca Cámara, J.; Terrasa Barrena, AM.; Julian Inglada, VJ.; Carrascosa Casamayor, C. (2020). SPADE 3: Supporting the New Generation of Multi-Agent Systems. IEEE Access. 8:182537-182549. https://doi.org/10.1109/ACCESS.2020.3027357S182537182549

Are You a Boy or a Girl? Show Me Your REAL ID

Although many official documents and forms of identification contain a sex or gender identifier, gender, as a category on these documents, is not very helpful in confirming a person\u27s identity. If the purpose of the inclusion of gender on official documents is to accurately identify an individual, technological advances have given us more accurate methods of ensuring a person\u27s identity. Technologies such as fingerprinting, facial recognition and retinal scans are far superior methods of determining whether a person is who they claim to be. The use of gender or sex on identification cards does little to positively identify individuals, and instead, creates problems for people who do not fall neatly into either of the two currently accepted categories of sex or gender. As a weak identifier, gender should not appear as a category on a state issued driver\u27s license or official identification card, yet states no longer have the authority to decide whether to require its inclusion. The REAL ID Act of 2005 recently went into effect, establishing requirements for state issued identification cards and driver\u27s licenses. The REAL ID Act requires states to issue driver\u27s licenses and identification cards that meet certain requirements to ensure more accurate identification in the post 9/11 world. The nine minimum requirements for information that states must provide on these cards include a person\u27s gender. Although critics have attacked the REAL ID Act on many grounds as an affront to civil liberties, as an unwelcome federal intrusion to a state\u27s police powers, or as the dreaded creation of a national identification card, I argue that the government should remove gender as a required identifier for two additional reasons. First, by barring any state from removing gender or sex from identification cards, the REAL ID Act prevents any state from removing these categories in an effort to reduce the complications of inclusion that a gender identifier inflicts on its gender variant citizens. Second, including a description of gender or sex is not an accurate method of identification, in no small part because gender and sex are not fixed and may later change, so should not be required under a federal law that ostensibly seeks to improve the accuracy of identity cards. This Article first examines the limits of legal classifications that view human traits as dichotomous. Next, it reviews the medical, scientific, and legal problems created by imposing a binary of sex or gender and the resulting problems this creates for many sexual minorities. Finally, this Article examines the REAL ID Act\u27s requirement to include gender, critiquing its inclusion as a poor identifier in light of current identification technology, and a problematic or discriminatory identifier for certain sexual minorities

Two Fundamental Building Blocks to Provide Quick Reaction Capabilities for the Department of Defense

The Department of Defense (DoD) has a need for long-term development efforts in conjunction with short-term development efforts. Ideally, Quick Reaction Capabilities (QRC) would be able to make use of the same processes that are used for Acquisition Programs (AP) with a few modifications to accommodate the accelerated schedule. Unfortunately, APs have a more fundamental problem with both the development process and the development framework. In August of 2007, the agile development process and modular, open source framework discussed in this thesis were two key factors that enabled the Air Force Research Laboratory (AFRL) to successfully deploy AngelFire in support of Operation Iraqi Freedom (OIF). AngelFire was a QRC and the first Wide Field of View (WFOV) sensor to collect Wide Area Motion Imagery (WAMI) that was not only saved onboard for forensic analysis, but was also disseminated to the users on the ground in near real time. Until APs can adapt and respond more quickly to the demands of irregular warfare, the two fundamental building blocks discussed in this thesis are what will enable QRCs to continue providing the 75% solutions that are needed today

LatentKeypointGAN: Controlling GANs via Latent Keypoints

Generative adversarial networks (GANs) have attained photo-realistic quality in image generation. However, how to best control the image content remains an open challenge. We introduce LatentKeypointGAN, a two-stage GAN which is trained end-to-end on the classical GAN objective with internal conditioning on a set of space keypoints. These keypoints have associated appearance embeddings that respectively control the position and style of the generated objects and their parts. A major difficulty that we address with suitable network architectures and training schemes is disentangling the image into spatial and appearance factors without domain knowledge and supervision signals. We demonstrate that LatentKeypointGAN provides an interpretable latent space that can be used to re-arrange the generated images by re-positioning and exchanging keypoint embeddings, such as generating portraits by combining the eyes, nose, and mouth from different images. In addition, the explicit generation of keypoints and matching images enables a new, GAN-based method for unsupervised keypoint detection

A Configurable Event-Driven Convolutional Node with Rate Saturation Mechanism for Modular ConvNet Systems Implementation

Convolutional Neural Networks (ConvNets) are a particular type of neural network often used for many applications like image recognition, video analysis or natural language processing. They are inspired by the human brain, following a specific organization of the connectivity pattern between layers of neurons known as receptive field. These networks have been traditionally implemented in software, but they are becoming more computationally expensive as they scale up, having limitations for real-time processing of high-speed stimuli. On the other hand, hardware implementations show difficulties to be used for different applications, due to their reduced flexibility. In this paper, we propose a fully configurable event-driven convolutional node with rate saturation mechanism that can be used to implement arbitrary ConvNets on FPGAs. This node includes a convolutional processing unit and a routing element which allows to build large 2D arrays where any multilayer structure can be implemented. The rate saturation mechanism emulates the refractory behavior in biological neurons, guaranteeing a minimum separation in time between consecutive events. A 4-layer ConvNet with 22 convolutional nodes trained for poker card symbol recognition has been implemented in a Spartan6 FPGA. This network has been tested with a stimulus where 40 poker cards were observed by a Dynamic Vision Sensor (DVS) in 1 s time. Different slow-down factors were applied to characterize the behavior of the system for high speed processing. For slow stimulus play-back, a 96% recognition rate is obtained with a power consumption of 0.85mW. At maximum play-back speed, a traffic control mechanism downsamples the input stimulus, obtaining a recognition rate above 63% when less than 20% of the input events are processed, demonstrating the robustness of the networkEuropean Union 644096, 687299Gobierno de España TEC2016-77785- P, TEC2015-63884-C2-1-PJunta de Andalucía TIC-6091, TICP120