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Why and how more and more people get involved and use social networking systems are critical topics in social network analysis (SNA). As a matter of fact, social networking systems bring online a growing number of acquaintances, for many different purposes. Both business interests and personal recreational goals are motivations for using online social networks (OSN) or other social networking systems. The participation in social networks is a phenomenon which has been studied with several theories, and SNA is useful for common business problems, e.g., launching distributed teams, retaining people with vital knowledge for the organization, improving access to knowledge and spreading ideas and innovation. Nevertheless, there are some difficulties, such as anti-social behaviors of participants, lack of incentives, organizational costs and risks. In this article, a survey of the basic features of SNA, participation theories and models are discussed, with emphasis on social capital, information spreading, motivations for participation, and anti-social behaviors of social network users.

Image synthesis is currently one of the most addressed image processing topic in computer vision and deep learning fields of study. Researchers have tackled this problem focusing their efforts on its several challenging problems, e.g. image quality and size, domain and pose changing, architecture of the networks, and so on. Above all, producing images belonging to different domains by using a single architecture is a very relevant goal for image generation. In fact, a single multi-domain network would allow greater flexibility and robustness in the image synthesis task than other approaches. This paper proposes a novel architecture and a training algorithm, which are able to produce multi-domain outputs using a single network. A small portion of a dataset is intentionally used, and there are no hard-coded labels (or classes). This is achieved by combining a conditional Generative Adversarial Network (cGAN) for image generation and a Meta-Learning algorithm for domain switch, and we called our approach MetalGAN. The approach has proved to be appropriate for solving the multi-domain label-less problem and it is validated on facial attribute transfer, using CelebA dataset.

Products sorting is a task of paramount importance for many countries’ agricultural industry. An accurate quality check assures that good products are not wasted, and rotten, broken and bent food are properly discarded, which is extremely important for food production chains. Such products sorting and quality controls are often performed with consolidated instruments, since simple systems are easier to maintain, validate, and they speed up the processing in terms of production line speed and products per second. Moreover, industries often lack advanced formation, required for more sophisticated solutions. As a result, the sorting task for many food products is mainly done by color information only. Sorting machines typically detect the color response of products to specific LEDs with various light wavelengths. Unfortunately, a color check is often not enough to detect some very common defects. The shape of a product, instead, reveals many important defects and is highly reliable in detecting external objects mixed with food. Also, shape can be used to take detailed measurements of a product, such as its area, length, width, anisotropy, etc. This paper proposes a complete treatment of the problem of sorting food by its shape. It treats real-world problems such as accuracy, execution time, latency and it provides an overview of a full system used on state-of-the-art measurement machines.

Why and how more and more people get involved and use social networking systems are critical topics in social network analysis (SNA). As a matter of fact, social networking systems bring online a growing number of acquaintances, for many different purposes. Both business interests and personal recreational goals are motivations for using online social networks (OSN) or other social networking systems. The participation in social networks is a phenomenon which has been studied with several theories, and SNA is useful for common business problems, e.g., launching distributed teams, retaining people with vital knowledge for the organization, improving access to knowledge and spreading ideas and innovation. Nevertheless, there are some difficulties, such as anti-social behaviors of participants, lack of incentives, organizational costs and risks. In this article, a survey of the basic features of SNA, participation theories and models are discussed, with emphasis on social capital, information spreading, motivations for participation, and anti-social behaviors of social network users.

This paper describes, from motivations and main objectives to actual implementation, a novel agent-oriented programming language called JADEL. JADEL is designed to support the effective implementation of JADE agents and multi-agent systems in the scope of real-world model-driven development because it concretely helps developers by natively supporting agent-oriented abstractions, and because it is based on mature industrial-strength technologies. The four core abstractions that JADEL supports, namely agents, behaviours, communication ontologies, and interaction protocols, are presented by gradually introducing the specific syntaxes that the language provides for them. In the last part of the paper, a complete example of a simple JADEL multi-agent system is presented and discussed. Such an example is a well-known example from the official distribution of JADE and many programmers learned the basics of JADE from it. The choice of this example allows comparing JADEL source code with reference Java source code using JADE, and it clearly emphasizes the practical advantages of agent-oriented programming. Section 1 introduces and motivates the presented work. Section 2 surveys major AOP languages and, even if it cannot be considered exhaustive, it highlights the specific features of selected languages that have been relevant for the design of JADEL. Section 3 provides an overview of the features of JADE that are supported by JADEL. Section 4 presents the language in details by discussing main supported abstractions, and by specifying its formal syntax. Section 5 presents the most interesting parts of a complete example of the use of JADEL to develop a simple multi-agent system. Finally, Section 6 concludes the paper with a discussion of the current state of the presented work, and a preliminary assessment of the proposed language.

Computer vision techniques are powerful tools to support and enhance creative workflows in fashion industries. In many cases, designer sketches and drawings, made with pen or pencil on raw paper, are the starting point of a fashion workflow. Then, such hand-drawn sketches must be imported into a software, to convert the prototype into a real-world product. This leads to a first important problem, namely, the automatic vectorization of sketches. Moreover, the various outcomes of all creative processes consist of a large number of images, which depict a plethora of products, from clothing to footwear. Recognizing product characteristics and classifying them properly is crucial in order to avoid duplicates and support marketing campaigns. Each feature could eventually require a different method, spacing from segmentation, image retrieval, to machine learning techniques, such as deep learning. Some state-of-the-art techniques and a novel proposal for line extraction and thinning, applied to fashion sketches, are described. Newly-developed methods are presented and their effectiveness in the recognition of features is discussed.

This paper presents the key aspects of a proposed formalization of JADE agents and multi-agent systems based on transition systems. Such a formalization is meant to be useful to describe and clarify how JADE multi-agent systems work and to provide a theoretical instrument to validate and analyze the semantics of JADE agents. This is needed to decouple agent-oriented and object-oriented parts of an agent design and to avoid misunderstandings on the semantics of JADE agents. The chosen approach is to define a structural operational semantics for Java programs written using JADE, and the proposed formalization consists in two parts: the first identifies and defines the main entities that together compose a JADE multi-agent system; the second provides the transition system and rewriting rules. The paper terminates with two explanatory examples of the usage of the transition system. A brief recapitulation of the work concludes the paper.

This paper reports a quantitative assessment of JADEL, an agent-oriented programming language designed to implement JADE agents and multi-agent systems. The assessment is structured in two parts. The first part is intended to evaluate the effectiveness of JADEL for the concrete implementation of agent-based algorithms expressed using a pseudocode. The second part examines the functionality of the language regarding concurrency and message passing by comparing the implementation in JADEL of a set of benchmark algorithms with the corresponding implementations in Scala. The metrics introduced for the two parts of the assessment are meant to evaluate the expressiveness and ease of use of JADEL, and reported results are encouraging.

The most important technological trend of the last years has been the rise of social networking systems to social phenomena involving hundreds of millions of people, attracting users from several social groups. Social networking systems blur the distinction between the private and working spheres, and users use such systems both at home and in the workplace, both professionally and with recreational goals. Social networking systems can be equally used to organize a work meeting, a dinner with colleagues or a birthday party with friends. For example, the chat systems that are embedded in social networking platforms are often the most practical way to contact a colleague to ask an urgent question, especially in technologically oriented companies. Moreover, several traditional information systems have been modified in order to include social aspects. Currently, social networking platforms are mostly used without corporate blessing, maintaining their status as feral systems.

ActoDeS is a software framework for the development of large concurrent and distributed systems. This software framework takes advantage of the actor model and of an its implementation that makes easy the development of the actor code by delegating the management of events (i.e., the reception of messages) to the execution environment. Moreover, it allows the development of scalable and efficient applications through the possibility of using different implementations of the components that drive the execution of actors. In particular, the paper introduces the software framework and presents the results of its experimentation.

This paper presents the core features of JADEL, an agent-oriented domain-specific programming language for the construction of JADE agents, behaviours and ontologies. The work on JADEL originates from the need to assist programmers by means of tools that reduce the complexity and speed up the construction of a JADE agents and multi-agent systems. The features of JADEL discussed in this paper include abstractions for the main entities of JADE—agents, behaviours and ontologies—and they also encompass the features needed for the construction of domain-specific tasks, thus enriching JADE APIs with novel and simple notations.