Spectra Routing

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones[EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results

Avances en Informática y Automática. Decimocuarto workshop

[ES]El Máster Oficial en Sistemas Inteligentes de la Universidad de Salamanca tiene como principal objetivo promover la iniciación de los estudiantes en el ámbito de la investigación. El congreso organizado por el Departamento de Informática y Automática que se celebra dentro del Máster en Sistemas Inteligentes de la Universidad de Salamanca proporciona la oportunidad ideal para que sus estudiantes presenten los principales resultados de sus Trabajos de Fin de Máster y obtengan una realimentación del interés de los mismos. La decimocuarta edición del workshop “Avances en Informática y Automática”, correspondiente al curso 2019 - 2020, ha sido un encuentro interdisciplinar donde se han presentado trabajos pertenecientes a un amplio abanico de líneas de investigación, desde los sistemas multiagente y la visualización de la información hasta la minería de datos pasando por otros campos relacionados. Todos los trabajos han sido supervisados por investigadores de reconocido prestigio pertenecientes a la Universidad de Salamanca, proporcionando el marco idóneo para sentar las bases de una futura tesis doctoral. Entre los principales objetivos del congreso se encuentran: - Ofrecer a los estudiantes un marco donde exponer sus primeros trabajos de investigación. - Proporcionar a los participantes un foro donde discutir ideas y encontrar nuevas sugerencias de compañeros, investigadores y otros asistentes a la reunión. - Permitir a cada estudiante una realimentación de los participantes sobre su trabajo y una orientación sobre las futuras direcciones de investigación. - Contribuir al desarrollo del espíritu de colaboración en la investigación

A Hybrid Model for the Measurement of the Similarity between Twitter Profiles

Social media platforms have been an undeniable part of our lifestyle for the past decade. Analyzing the information that is being shared is a crucial step to understanding human behavior. Social media analysis aims to guarantee a better experience for the user and to increase user satisfaction. To draw any further conclusions, first, it is necessary to know how to compare users. In this paper, a hybrid model is proposed to measure the degree of similarity between Twitter profiles by calculating features related to the users’ behavioral habits. For this, first, the timeline of each profile was extracted using the official TwitterAPI. Then, three aspects of a profile were deliberated in parallel. Behavioral ratios are time-series-related information showing the consistency and habits of the user. Dynamic time warping was utilized to compare the behavioral ratios of two profiles. Next, the audience network was extracted for each user, and to estimate the similarity of two sets, the Jaccard similarity was used. Finally, for the content similarity measurement, the tweets were preprocessed using the feature extraction method; TF-IDF and DistilBERT were employed for feature extraction and then compared using the cosine similarity method. The results showed that TF-IDF had slightly better performance; it was therefore selected for use in the model. When measuring the similarity level of different profiles, a Random Forest classification model was used, which was trained on 19,900 users, revealing a 0.97 accuracy in detecting similar profiles from different ones. As a step further, this convoluted similarity measurement can find users with very short distances, which are indicative of duplicate users

Modern Integrated Development Environment (IDEs)

[EN] One of the important objectives of smart cities is to provide electronic services to citizens, however, this requires the building of related software which is a time-consuming process. In this regard, smart city infrastructures require development tools that can help accelerate and facilitate software development (mobile, IoT, and web applications). Integrated Development Environments (IDEs) are well-known tools that have brought together the features of various tools within one package. Modern IDEs include the advantages of Artificial Intelligence (AI) and Cloud Computing. These technologies can help the developer overcome the complexities associated with multi-platform software products. This paper has explored AI techniques that are applied in IDEs. To this end, the Eclipse Theia (cloud-based IDE) and its AI-based extensions are explored as a case study. The findings show that recommender system models, language modeling, deep learning models, code mining, and attention mechanisms are used frequently to facilitate programming Furthermore, some researches have used NLP techniques and AI-based virtual assistance to promote the interaction between developers and projects.Supported by the project "Intelligent and sustainable mobility supported by multi-agent systems and edge computing (InEDGEMobility): Towards Sustainable Intelligent Mobility: Blockchain-based framework for IoT Security", Reference: RTI2018-095390-B-C32, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), the State Research Agency (AEI) and the European Regional Development Fund (FEDER).Alizadehsani, Z.; Goyenechea Gomez, E.; Ghaemi, H.; Rodríguez González, S.; Jordán, J.; Fernández, A.; Pérez-Lancho, B. (2021). Modern Integrated Development Environment (IDEs). Springer. 274-288. https://doi.org/10.1007/978-3-030-78901-5_2427428

Service Classification through Machine Learning: Aiding in the Efficient Identification of Reusable Assets in Cloud Application Development

Developing software based on services is one of the most emerging programming paradigms in software development. Service-based software development relies on the composition of services (i.e., pieces of code already built and deployed in the cloud) through orchestrated API calls. Black-box reuse can play a prominent role when using this programming paradigm, in the sense that identifying and reusing already existing/deployed services can save substantial development effort. According to the literature, identifying reusable assets (i.e., components, classes, or services) is more successful and efficient when the discovery process is domain-specific. To facilitate domain-specific service discovery, we propose a service classification approach that can categorize services to an application domain, given only the service description. To validate the accuracy of our classification approach, we have trained a machine-learning model on thousands of open-source services and tested it on 67 services developed within two companies employing service-based software development. The study results suggest that the classification algorithm can perform adequately in a test set that does not overlap with the training set; thus, being (with some confidence) transferable to other industrial cases. Additionally, we expand the body of knowledge on software categorization by highlighting sets of domains that consist ‘grey-zones’ in service classification