Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adopting intelligent manufacturing practices in view of Industry 4.0 requirements. Intelligent is the process enhancing production through use cutting-edge technologies, sensor integration, analytics, and Internet Things (IoT). The proposed paper mainly focuses on study scope evolution quality control t...

this paper aims to investigate the presence of quantifier phrase and classifier phrase in the dp of sarhadi dialect of the baluchi language. to reach this goal, pseudo partitive constructions and their characteristics in different languages are introduced and then it is shown that determiner phrases containing a classifier in baluchi are examples of juxtaposed pseudo partitive constructions in ...

The study is dictated by the need to make reasonable decisions in classification of observations, for example, problems medical prediction and diagnostics. Today, as part digitalization healthcare, decision-making a doctor carried out using intelligent information systems. introduction such systems contributes implementation policies aimed at ensuring sustainable development health sector. pape...

objective(s): this study addresses feature selection for breast cancer diagnosis. the present process uses a wrapper approach using ga-based on feature selection and ps-classifier. the results of experiment show that the proposed model is comparable to the other models on wisconsin breast cancer datasets. materials and methods: to evaluate effectiveness of proposed feature selection method, we ...

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on synergistic combinations of multiple approaches to develop the next generation of intelligent systems. A fundamental stimulus to the investigations of Hybrid Intelligent Systems (HIS) is the awareness that combined approaches will be necessary to solve challenging problems in complex rea...

The use of Machine Learning (ML) techniques is already widespread in Medicine Diagnosis. The use of these techniques helps increasing the efficiency of human diagnostic, which is significantly affected by the human conditions such as stress as well as the lack of experience. In this paper, integration between two ML techniques casebased reasoning (CBR) and artificial neural network (ANN) is use...

Meta-learning allows an intelligent agent to leverage prior learning episodes as a basis for quickly improving performance on a novel task. Bayesian hierarchical modeling provides a theoretical framework for formalizing meta-learning as inference for a set of parameters that are shared across tasks. Here, we reformulate the model-agnostic meta-learning algorithm (MAML) of Finn et al. (2017) as ...

A current trend in modern HCI is represented by Embodied Conversational Agents (ECAs), even designed to run on the Web. They are virtual 3D human-like front ends coupled with software agents that are able to engage in a conversation with a user and execute complex tasks, such as, for example, searching for some specific information or ordering some items from the catalogue of an online shop. Th...

In this paper we describe a simple model of adaptive agents of different types, represented by Learning Classifier Systems (LCS), which make investment decisions about a risk free bond and a risky asset under a well defined stock market environment. Our main aim is to explore the degree of reliability that artificially intelligent agents can have when applied to real life economic problems. We ...

The FP7 EU project ISi-PADAS aims at conceiving an intelligent system, called PADAS, to support drivers, which intervenes continuously from warning up to automatic braking in the whole longitudinal control of the vehicle. However, such supporting systems can have some unwanted sideeffect: due to the presence of automation in the driving task, less attention and reaction are needed by the driver...