A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

ProjectION: Investigation Operative Networks

Corporations and enterprises have embraced the notion of shared experiences and collective workplaces by incorporating coworking places. A great deal of the methodology carries from the studio culture that architecture schools foster as well as think tank culture. Maker spaces and incubator spaces are prime examples of places that engender creative thought and products. This thesis seeks to explore the impact that architecture has on collaborative spaces with a focus on augmenting to their generated learning and design activities. The investigation explores the collaborative design process as a series of interactions between groups of individuals. This involves the impact of technology and its implications on those interactions. The goal of this thesis is not to further the use of a tool or systematic procedure, but to use architecture as a framing device to form places for collaborative processes.

Forms of Collaboration in Collaborative Enterprises: An Ontological Model

Part 19: Knowledge Management in Networks

Reasoning on the Risks of Dynamic Manufacturing Networks through Cognitive Mapping

Part 17: Risk Analysis

Strategic Context, Organizational Features and Network Performances: A Survey on Collaborative Networked Organizations of Italian SMEs

Part 15: Performance Management Frameworks

Towards Automated Business Process Deduction through a Social and Collaborative Platform

Part 12: Collaboration Platforms

Pillars and Elements to Develop an Open Business Model for Innovation Networks

Part 9: Innovation Networks

Business-IT Alignment in PSS Value Networks: A Capability-Based Framework

Part 8: Business Strategies Alignment

Methodological and Technological Support for the Coordination of Smart Networks of SMEs

Part 2: Behaviour and Coordination

Collaborative Systems of Systems Need Collaborative Design

Part 1: Introduction

The Evolution of Norms in Trade and Financial Networks in the First Global Age: the case of Simon Ruiz's network

In the 16th century, merchants and bankers gained a social influence and political relevance, due to their capacity of ‘faire travailler l’argent des autres’ (Benassar 1972:50). For the success of their activity, they built evolving networks with cooperative partners. These networks were much more than the sum of all partners. In the case study of the Castilian merchant Simon Ruiz, the network functioned in an unique way and independent from any formal institutional control. Its functioning varied in how different partners were associated and the particular characteristics and contents of these social ties. Being a self-organized network, since the formal institutions of trade regulation and the Crown control didn’t influence the network functioning, the Simon Ruiz network was deeply embedded in the economic and financial performance of the Hispanic Empires, in two different ways. The first, purely commercial. The monopolistic regime which was applied by the two crowns in the trade of certain colonial goods was insufficient to the costs of imperial maintenance. In such manner, particulars tried to rent a contract of exploration of trade, paying an annual sum to the crown, as in the Portuguese trade. Some of these agents also moved along Simon Ruiz’s network. But others were involved in relations with the imperial crowns on a second way, the finance. Maintaining Empires implied a lot of human, technical but also financial means, and most of the times Kings were forced to recur to these merchants, as we will demonstrate. What were the implications of these collaborative relations in both parts? The main goal of this paper is to comprehend the evolution of informal norms within Simon Ruiz’s network and how they influenced cooperative behavior of the agents, particularly analyzing mechanisms of sanctioning, control, punishment and reward, as well as their consequences in different dimensions: future interactions, social repercussions and in agent’s economic health and activity. The research is based in the bills of exchange and commercial correspondence of the private archive of Simon Ruiz, located in the Provincial Archive of Valladollid, Spain.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

Stromal Myofibroblasts In Squamous Cell Carcinoma Of The Tongue In Young Patients - A Multicenter Collaborative Study.

The purpose of this study was to evaluate the presence of myofibroblasts, frequently associated with a more aggressive neoplastic behavior, in oral tongue squamous cell carcinoma (TSCC) of young patients and to compare with the distribution observed in older patients. Tumor samples from 29 patients younger than 40 years old affected by TSCC were retrieved and investigated for the presence of stromal myofibroblasts by immunohistochemical reactions against α smooth muscle actin, and the results obtained were compared to TSCC cases affecting older patients. No positive reaction could be found in the stromal areas devoid of neoplastic tissue, whereas myofibroblasts were present in 58.6% of the lesions in young patients and in 75.9% of the older ones. No significant difference was found when comparing the invasive front and the overall stroma of both groups, and no correlation could be obtained with stromal α smooth muscle actin expression, higher tumor grades or clinical stage (P > .05). There was no significant difference between the presence of stromal myofibroblasts of TSCC affecting young and old individuals.