Abstract
In this paper we describe de application of a modeling framework, the so-called Conceptual Model Decomposing Value for the Customer (CMDVC), in a Footwear Industry case study, to ascertain the usefulness of this approach. The value networks were used to identify the participants, both tangible and intangible deliverables/endogenous and exogenous assets, and the analysis of their interactions as the indication for an adequate value proposition. The quantitative model of benefits and sacrifices, using the Fuzzy AHP method, enables the discussion of how the CMDVC can be applied and used in the enterprise environment and provided new relevant relations between perceived benefits (PBs).

Abstract
Nowadays, it is a high trend to increase the electricity production using Distributed Generation (DG) technology based on renewable energy resources (RERs) such as photovoltaics and wind power. If these systems are not properly controlled, their connection to the power grid can provoke many problems on the grid side. Therefore, considerations about power generation, safe running and grid connection must be done before connecting DG units into the power grid. This paper is mainly dealing with the grid connection of DG units to the power grids and compensation of the unbalanced loads. The proposed technique provides compensation for active, reactive, unbalanced, and harmonic current components of unbalanced loads. High performance of the proposed technique is obtained through Matlab/Simulink, guaranteeing balanced overall grid currents, injection of maximum available power from DG resources, power factor increase of the utility grid, and a reduction of total harmonic distortion (THD) of grid current, under the proposed operating conditions.

Abstract
As a recently increasing trend among different applications of smart grid vision, smart households as a new implementation area of demand response (DR) strategies have drawn more attention both in research and in engineering practice. On the other hand, optimum sizing of renewable energy based small scale hybrid systems is also a topic that is widely covered by the existing literature. In this study, the sizing of additional distributed generation (DG) and energy storage systems (ESSs) to be applied in smart households, that due to DR activities have a different daily demand profile compared with normal household profiles, is investigated. To the best knowledge of the authors this is the first attempt in the literature to investigate this issue, also including step-wise decreasing cost functions for DC and ESS, varying load and DG production profiles seasonally, and weekday-weekend horizons for a long-term analysis period. The study is conducted using a mixed-integer linear programming (MILP) framework for home energy management system (HEM) modeling and techno-economical sizing. Also, different sensitivity analyses considering the impacts of variation of economic inputs on the provided model are realized.

Abstract
This paper describes and evaluates a fully digital circuit for one-way master-to-slave, highly precise time synchronization in a low-power wearable system equipped with a set of sensor nodes. These sensors are connected to each other in a mesh topology, with conductive yarns used as one-wire bidirectional communication links. The circuit is designed to perform synchronization in the MAC layer, so that the deterministic part of the clock skew between nodes is kept constant and compensated with a single message exchange. In each sensor node, the synchronization circuit provides a programmable clock signal and a real-time counter for time stamping. Experimental results from a fabricated ASIC (in a CMOS 0.35 mu m technology) show that the circuit keeps the one-hop average clock skew below 4.6 ns and that the skew grows linearly as the hop distance to the reference node increases. The sub-microsecond average clock skew achieved by the proposed solution satisfies the requirements of many wearable sensor network applications.

Abstract
Earthworks tasks arc often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Abstract