Power systems worldwide are complex and challenging environments. The increasing necessity for an adequate integration of renewable energy sources is resulting in a rising complexity in power systems operation. Multi-agent based simulation platforms have proven to be a good option to study the several issues related to these systems, including the involved players that act in this domain. To take better advantage of these systems, their integration is mandatory. The main contribution of this paper is the development of the Electricity Markets Ontology, which integrates the essential concepts necessary to interpret all the available information related to electricity markets, while enabling an easier cooperation and adequate communication between related systems. Additionally, the concepts and rules defined by this ontology can be extended and complemented according to the needs of other simulation and real systems in this area. Each system’s particular ontology must import the proposed ontology, thus enabling the effective interoperability between independent systems.

The intelligent management systems of the end consumers are endowed with advanced functions being one of them the interaction with external entities through the automatic participation in demand response programs. The development of the intelligent management systems is to reduce the energy consumption based on internal information and on the interaction with an external entity. Moreover, the management approaches results in an active participation of the consumers in the operation of the smart grids and microgrids concepts. The paper developed presents the application of a dynamic priority method in SCADA Office Intelligent Context Awareness Management system to manage the energy resources installed in an office building. The intelligent management method allows the dynamic active participation of the office building in the DR events considering the real data of consumption and generation of one building in Polytechnic of Porto. The main goal of the methodology is to obtain a dynamic scheduling for all energy resources with little interference in the comfort of users. The results of dynamic management model in office building are discussed for the participation in 8 hours demand response event. The power limit of the scenario depends on the consumption and micro- generation power of an October day.

This paper presents the demonstration of an energy resources management approach using a physical smart city model environment. Several factors from the industry, governments and society are creating the demand for smart cities. In this scope, smart grids focus on the intelligent management of energy resources in a way that the use of energy from renewable sources can be maximized, and that the final consumers can feel the positive effects of less expensive (and pollutant) energy sources, namely in their energy bills. A large amount of work is being developed in the energy resources management domain, but an effective and realistic experimentation are still missing. This work thus presents an innovative means to enable a realistic, physical, experimentation of the impacts of novel energy resource management models, without affecting consumers. This is done by using a physical smart city model, which includes several consumers, generation units, and electric vehicles.

—The reduction of the greenhouse gas emissions is a priority all around the globe. The investment on renewable energy sources is contributing for new opportunities in the context of the smart grids and microgrids. Recent advances are transforming the consumer into a prosumer, being able to adapt the consumption depending on its own generated power, and selling the surplus or buying the missing power. In this context, home management systems are emerging as an effective means to support the management of energy resources in the context of communication between functions/devices of a smart home. This paper presents a new agent-based home energy management approach, using ontologies to enable semantic communications between heterogeneous multi-agent entities. The main goal is to support an efficient energy management of end consumers in the context of microgrids, obtaining a scheduling for both real and virtual resources. A case study is presented, which simulates a 25-bus microgrid that includes a laboratorial controlled house (with real and simulated resources), which is managed by the proposed energy management system. Keywords-Demand Response, Distributed Energy Resources, Energy Efficiency, House Management, Ontologies. I.

—Titania slag is a high quality raw material containing titanium in the subsequent process of titanium pigment. The effects of cooling approaches of granulating, water cooling, and air cooling on chemical, phases, and acidolysis of Panzhihua titania slag were investigated. Compared to the original slag which was prepared by the conventional processing route, the results show that the titania slag undergoes oxidation of Ti3+during different cooling ways. The Ti2O3 content is 17.50% in the original slag, but it is 16.55% and 16.84% in water cooled and air-cooled slag, respectively. Especially, the Ti2O3 content in granulated slag is decreased about 27.6%. The content of Fe2O3 in granulated slag is approximately 2.86% also obviously higher than water (<0.5%) or air-cooled slag (<0.5%). Rutile in cooled titania slag was formed because of the oxidation of Ti3+. The rutile phase without a noticeable change in water cooled and air-cooled slag after the titania slag was cooled, but increased significantly in the granulated slag. The rate of sulfuric acid acidolysis of cooled slag is less than the original slag. The rate of acidolysis is 90.61% and 92.46% to the water-cooled slag and air- cooled slag, respectively. However, the rate of acidolysis of the granulated slag is less than that of industry slag about 20%, only 74.72%. Keywords—Cooling approaches, titania slag, granulating, sulfuric acid acidolysis, I.

Context: The analysis of requirements for business-related software systems is often supported by using business process models. However, the final requirements are typically still specified in natural language. This means that the knowledge captured in process models must be consistently transferred to the specified requirements. Possible inconsistencies between process models and requirements represent a serious threat for the successful development of the software system and may require the repetition of process analysis activities. Objective: The objective of this paper is to address the problem of inconsistency between process models and natural language requirements in the context of software development. Method: We define a semi-automated approach that consists of a process model-based procedure for capturing execution-related data in requirements models and an algorithm that takes these models as input for generating natural language requirements. We evaluated our approach in the context of a multiple case study with three organizations and a total of 13 software development projects. Results: We found that our approach can successfully generate well-readable requirements, which do not only positively contribute to consistency, but also to the completeness and maintainability of requirements. The practical use of our approach to identify a suitable subcontractor on the market in 11 of the 13 projects further highlights the practical value of our approach. Conclusion: Our approach provides a structured way to obtain high-quality requirements documents from process models and to maintain textual and visual representations of requirements in a consistent way.

— This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal participation in multiple electricity markets With the emergence of new requirements for electrical power markets, it has become fundamental to develop tools to aid in decision making, understanding the functioning of markets and forecast iterations that occur between the different entities in the market. Artificial intelligence plays a crucial role in the development of these tools. Using artificial intelligence techniques it is possible to simulate the different existing players in the market, to enable these players to be adaptive to any situation, and to model any type of trading. Artificial intelligence based metaheuristic optimization tools allow solving problems in a short time, and with very close results to those that deterministic techniques are able to achieve, at the cost of a high execution time. The achieved results, using a simulation scenario based on real data from the Iberian electricity market, show that the proposed method is able to reach better results than previous implementations of a Particle Swarm Optimization (PSO) and a Simulated Annealing (SA) methods, while achieving very similar objective function results to those of a deterministic approach, in a much faster execution time. Index Terms— Artificial intelligence, Electricity Markets, Genetic Algorithm, Portfolio Optimization I.

—Corrosion behaviour of hypereutectic Al-19Si automotive alloy in different pH=1, 3, 5, 7, 9, 11, and 13 environments was carried out using conventional gravimetric measurements and was complemented by resistivity, optical micrograph, scanning electron microscopy (SEM) and X-ray analyzer (EDX) investigations. Gravimetric analysis confirmed that the highest corrosion rate is shown at pH 13 followed by pH 1. Minimum corrosion occurs in the pH range of 3.0 to 11 due to establishment of passive layer on the surface. The highest corrosion rate at pH 13 is due to the presence of sodium hydroxide in the solution which dissolves the surface oxide film at a steady rate. At pH 1, it can be attributed that the presence of aggressive chloride ions serves to pick up the damage of the passive films at localized regions. With varying exposure periods by both, the environment complies with the normal corrosion rate profile that is an initial steep rise followed by a nearly constant value of corrosion rate. Resistivity increases in case of pH 1 solution for the higher pit formation and decreases at pH 13 due to formation of thin film. The SEM image of corroded samples immersed in pH 1 solution clearly shows pores on the surface and in pH 13 solution, and the corrosion layer seems more compact and homogenous and not porous. Keywords—Al-Si alloy, corrosion, pH, resistivity, SEM. I.

—The Internet of Things (IoT) interconnects various identifiable devices within Internet for sensing and monitoring processes. In particular, Wireless Sensor Network (WSN) is formed by connecting identifiable devices like smart sensor, embedded CPU (Central Processing Unit), low power radios, to the internet through gateway that interfaces WSN to the internet. To handle the large amount of data generated by devices in IOT environment, cloud infrastructure provides Sensing as a Service(SeaaS) which can make sensor data available in cloud infrastructure for sensing and observing the environment conditions. Today’s cloud models are not designed for the volume, variety, and velocity of data that the IoT generates. Handling the volume, variety, and velocity of IoT data requires a new computing model. In this paper, we surveyed some typical applications of Sensor Network using Cloud computing as backbone spotlighting on fog computing to overcome some of the management issues of cloud computing and to handle time- sensitive data. Since Cloud computing provides plenty of application, platforms and infrastructure over the Internet, it may combined with Sensor network and fog computing in the application areas such as environmental monitoring, weather forecasting, transportation business, healthcare, military application etc which requires to handle within a second. Keywords—WSN,cloud computing, fog computing, CSaaS, Internet of Things

—The ceramic yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) has been used as a dental biomaterial for several decades. The strength and toughness of this material can be accounted for by its toughening mechanisms, which include transformation toughening, crack deflection, zone shielding, contact shielding, and crack bridging. Prevention of crack propagation is of critical importance in high-fatigue situations, such as those encountered in mastication and para-function. However, the poor translucence of Y-TZP in polycrystalline form is such that it may not meet the aesthetic requirements due to its white/grey appearance. To improve the optical properties of Y-TZP, more detailed study of the optical properties is required; in particular, precise evaluation of the refractive index, absorption coefficient, and scattering coefficient are necessary. The measurement of the optical parameters has been based on the assumption that light scattered from biological media is isotropically distributed over all angles. In fact, the optical behavior of real biological materials depends on the angular scattering of light due to the anisotropic nature of the materials. The purpose of the present work is to evaluate the optical properties (including color, opacity/translucence, scattering, and fluorescence) of zirconia dental ceramics and their control through modification of the chemical composition, phase composition, and surface microstructure. Keywords—Optical properties, opacity/translucence, scattering, fluorescence, chemical composition, phase composition, surface microstructure. I.

—The recent changes on the electrical power systems make the role of distributed generation more important. Employing distributed generation in demand side allows the consumers to have active participation in the electricity markets. This paper implements the real-time simulation of a local microgrid that consists of two subsystems: home area network and neighborhood area network. In this system, the home area network is the electrical grid of a house and the neighborhood area network is the low voltage electrical distribution grid of the neighborhood. The main contribution of this paper is to assess scenarios for energy transactions between these two areas using real resources. In the case studies, several real profiles have been employed for simulating the consumption and generation of this local microgrid. Index Terms— Distributed Generation, Hardware-in-the-Loop, Microgrid, Real-Time Simulation, Renewable Energy Transactions. I.

The Internet of Things (IoT) such as the use of robots, sensors, actuators, electronic signalization and a variety of other Internet enabled physical devices may provide for new advanced smart applications to be used in construction in very near future. Such applications require real-time responses and are therefore time-critical. Therefore, in order to support collaboration, control, monitoring, supply management, safety and other construction processes, they have to meet dependability requirements, including requirements for high Quality of Service (QoS). Dependability and high QoS can be achieved by using adequate number and quality of computing resources, such as processing, memory and networking elements, geographically close to the smart environments. The goal of this study is to develop a practical edge computing architecture and design, which can be used in to support smart construction environments with high QoS. This study gives particular attention to the solution design, which relies on latest cloud and software engineering approaches and technologies, and provides elasticity, interoperability and adaptation to companies' specific needs. Two edge computing applications supporting video communications and construction process documentation are developed and demonstrate a viable edge computing design for smart construction.