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In recent years, there has been an increasing interest in music generation using machine learning techniques typically used for classification or regression tasks. This is a field still in its infancy, and most attempts are still characterized by the imposition of many restrictions to the music composition process in order to favor the creation of “interesting” outputs. Furthermore, and most importantly,...
Modelers face multiple challenges in their work. In this paper, we focus on two of them. First, multiple modeling methods and tools are currently available. Modelers are sometimes limited by their tools or paradigms. Second, when multiple models are proposed for the same case, a decision maker needs criteria to decide which model to choose for his/her objective.
With the immense growth of online social applications, trust plays a more and more important role in connecting users to each other, sharing their personal information and attracting him to receive recommendations. Therefore, how to obtain trust relationships through mining online social networks became a critical issue. To calculate the level of trust between two users, many computational trust models...
The synthesis of controllers enforcing safety properties is a well understood problem for which we have practical algorithms as well as a deep theoretical understanding. This problem is typically formulated as game between the controller seeking to enforce the safety property and the environment seeking to violate it. The solution of these games is given by a winning set: inside the winning set the...
Traditional affective lexicons are mainly based on discrete classes, such as positive, happiness, sadness, which may limit its expressive power compared to the dimensional representation in which affective meanings are expressed through continuous numerical values on multiple dimensions, such as valence-arousal. Traditional methods for acquiring dimensional lexicons are mainly based on time-consuming...
Code smells are symptoms of poor design and implementation choices. Previous studies empirically assessed the impact of smells on code quality and clearly indicate their negative impact on maintainability, including a higher bug-proneness of components affected by code smells. In this paper we capture previous findings on bug-proneness to build a specialized bug prediction model for smelly classes...
Some open systems must address a standard resourceallocation problem: how to collectivise and distribute aset of common-pool resources, with respect to multiple criteriasuch as fairness, inclusivity and sustainability. Previous work inself-organising multi-agent systems formalised Nicholas Rescher'stheory of distributive justice so that agents could self-organise theallocation according to contextualised...
Social Internet of Things (SIoT) is an evolutionary idea which combines traditional IoT models with social network paradigms. "Objects" in SIoT formulate social relationships with other "trusted objects" according to the relationships of their owners which deliver trustworthy services on request. From our trust platform concept to identify vital trust metrics, attributes, we propose...
Deep Convolutional Neural Networks(DCNNs) have recently shown great performance in many high-level vision tasks, such as image classification, object detection and more recently outdoor semantic segmentation. However, the convolutional layer only process the local regions in the image, ignoring the global context information. To overcome this poor localization property of Convolutional Neural Networks(CNNs),...
Network function visualization and software-defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We present a YANG model for describing...
Security issues of cloud computing environments are considered a major challenge for its full adoption. A Service Level Agreement (SLA) corroborates the shared management vision provided by the cloud computing paradigm, which can assist with related security issues. The necessity to address security requirements in cloud computing SLAs is considered important for both providers and consumers, along...
Trust and reputation are commonly considered critical concepts in open dynamic multi-agent systems, where agents must rely on their peers to achieve their goals. Several computational trust models have been proposed to manage trust in such situation. The diversity of those models makes user confused about which one to choose. Different testbeds were proposed to evaluate trust and reputation systems...
The nearest neighbor classification rule is a memory-based technique, in that its standard learning phase consists in storing the entire set of examples, or training set. During classification, the nearest neighbors of the incoming test object are retrieved in the store and their labels are combined to determine the answer. In order to alleviate both the spatial and temporal cost of this strategy,...
Trust is becoming an increasingly important issue in large-scale distributed systems. Especially self-managed systems from the Autonomic and Organic Computing domains consisting of several cooperating entities have to rely on an automated estimation how reliable and trustworthy potential cooperation partners are. In this paper, we introduce a novel concept to represent trust among those entities....
Monitoring the performances of a business process is a key issue in many organizations, especially when predefined constraints exist on them, due to contracts or internal requirements. Several approaches were defined recently in the literature for predicting the performances of a single process instance. However, in many real situations, process-oriented performance metrics and associated constraints...
Threshold-based sampling schemes such send-on-delta, level-crossing with hysteresis and integrate-and-fire are studied as non-linear input-output systems that map Lipschitz continuous signals to event sequences with −1 and 1 entries. By arguing that stability requires an event sequence of alternating −1 and 1 entries to be close to the zero-sequence w.r.t. the given event metric, it is shown that...
This work combines model-based local shape analysis and data-driven local contextual feature learning for improved detection of pulmonary nodules in low dose computed tomography (LDCT) chest scans. We reduce orientation-induced appearance variability by performing intensity-weighted principal component analysis (PCA) to estimate the local orientation at each candidate location. Random comparison primitives...
This study highlights the importance of considering gender and offline cultural context when working in virtual teams. To this end, we examine gender differences in performance and participation within virtual teams in a popular online game, drawing from behavioral game data from game servers in nine countries, each representing a distinct region of the world. Results are compared to metrics from...
Touching components are connection zones occurring between text-lines or words of the same line and are one of the problems that make unconstrained handwritten text segmentation greatly hard. In this paper, we propose a recognition based method to separate these components once localized in Arabic manuscript images. It first identifies, for a given touching component, a similar model stored in a dictionary...
This study describes and evaluates a novel trust model for a range of collaborative applications. The model assumes that humans routinely choose to trust their peers by relying on few recurrent presumptions, which are domain independent and which form a recognisable trust expertise. We refer to these presumptions as trust schemes, a specialised version of Walton's argumentation schemes. Evidence is...
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