Named Entity Recognition (NER) is a key building block of any Natural Language Processing (NLP) system, making possible the detection and classification entities (e.g., Person, Location) in given text. While large number NER software exist today, it remains difficult for NLP practitioners to clearly objectively identify what perform(s) best. One reasons difference results across literature lack information needed be able fully reproduce experiment. To overcome this problem, paper presents...

In the context of Industry 4.0, companies understand advantages performing Predictive Maintenance (PdM). However, when moving towards PdM, several considerations must be carefully examined. First, they need to have a sufficient number production machines and relative fault data generate maintenance predictions. Second, adopt right approach, which, ideally, should self-adapt machinery, priorities organization, technician skills, but also able deal with uncertainty. Reinforcement learning (RL)...

Maintenance planning and scheduling are an essential part of manufacturing companies to prevent machine breakdowns increase uptime, along with production efficiency. One the biggest challenges is effectively address uncertainty (e.g., unexpected failures, variable time repair). Multiple approaches have been used solve maintenance problem, including dispatching rules (DR), metaheuristics simheuristics, or most recently reinforcement learning (RL). However, best our knowledge, no study has...

According to our original vision of the Internet Things (IoT), it should be possible create ad hoc and loosely coupled information flows between any kinds products, devices, computers, users, systems in general when as needed. However, this is still challenging achieve practice due lack sufficiently generic standardized interfaces for creating needed all devices that IoT composed of. The paper presents necessary requirements such interfaces, well proposed interface standards fulfill those...

By connecting devices, people, vehicles, and infrastructures everywhere in a city, governments their partners can improve community well-being other economic financial aspects (e.g., cost energy savings). Nonetheless, smart cities are complex ecosystems that comprise many different stakeholders (network operators, managed service providers, logistic centers, so on), who must work together to provide the best services unlock commercial potential of so-called Internet Things (IoT). This is one...

This paper proposes a decentralized scheduling framework for peer-to-peer (P2P) transactive energy trading between prosumers and the local electricity market (LEM). In this approach, are modeled in form of networked microgrids (NMG) smart parking lots (SPL), which can exchange P2P framework. At same time, each exchanges information with LEM approach based on distribution locational marginal price (DLMP). The is by an active radial network (EDN), considering high penetration renewable sources...

The Internet of Things (IoT) has promised a future where everything gets connected. Unfortunately, building single global ecosystem that communicate with each other seamlessly is virtually impossible today. reason the IoT essentially collection isolated “Intranets Things”, also referred to as “vertical silos”, which cannot easily and efficiently interact other. Smart cities are perhaps most striking examples this problem since they comprise wide range stakeholders service providers who must...

By connecting devices, people, vehicles and infrastructures everywhere in a city, governments their partners can improve community wellbeing other economic financial aspects (e.g., cost energy savings). Nonetheless, smart cities are complex ecosystems that comprise many different stakeholders (network operators, managed service providers, logistic centers...) who must work together to provide the best services unlock commercial potential of IoT. This is one major challenges faces today's...

The Internet of Things (IoT) has led towards a digital world in which everything becomes connected. Unfortunately, most the currently marketed connected devices feed vertically-oriented closed systems (commonly referred to as vertical silos) prevent development unified global IoT. This issue is all more valid complex environments, such smart cities, exceedingly large amounts heterogeneous sensor data are collected, and platforms stakeholders should also be able interact cooperate. Therefore,...

In many contexts, one is confronted with the problem of extract ing information from large amounts different types soft data (e.g., text) and hard (from e.g., physics-based sensing systems). handling data, signal processing offers a wealth methods related to modeling, estimation, tracking, inference tasks. However, present several challenges that necessitate development new methods. For example, suitable statistical natural language (NLP) methods, text can be converted into logic statements...

During recent years, more and Open Data becomes available used as part of the movement. However, there are reported issues with quality metadata in data portals itself. This is a serious risk that could disrupt project, well e-government initiatives since needs to be managed guarantee reliability public. First assessment frameworks emerge evaluate for given dataset or portal along various dimensions (e.g., information completeness). Nonetheless, common problem such provide meaningful ranking...