Ontologies versus relational databases: are they so different? A comparison

Two main data models are currently used for representing knowledge and information in computer systems. Database models, especially relational databases, have been the leader in last few decades, enabling information to be efficiently stored and queried. On the other hand, ontologies have appeared as an alternative to databases in applications that require a more ‘enriched’ meaning. However, there is controversy regarding the best information modeling technique, as both models present similar characteristics. In this paper, we present a review of how ontologies and databases are related, of what their main differences are and of the mechanisms used to communicate with each other.     

An algorithm comparison for dynamic optimization problems

This work presents a study on the performance of several algorithms on different continuous dynamic optimization problems. Eight algorithms have been used: SORIGA (an Evolutionary Algorithm), an agents-based algorithm, the mQSO (a widely used multi-population PSO) as well as three heuristic-rule-based variations of it, and two trajectory-based cooperative strategies. The algorithms have been tested on the Moving Peaks Benchmark and the dynamic version of the Ackley, Griewank and Rastrigin functions. For each problem, a wide variety of configuration variations have been used, emphasizing the influence of dynamism, and using a full-factorial experimental design. The results give an interesting overview of the properties of the algorithms and their applicability, and provide useful hints to face new problems of this type with the best algorithmic approach. Additionally, a recently introduced methodology for comparing a high number of experimental results in a graphical way is used.     

Implementation of a hybrid scheme for coherent plug-and-play quantum key distribution

We experimentally demonstrate a hybrid configuration for quantum key distribution that combines the simplicity of distributed-phase-reference protocols with the self-referencing features and polarization insensitivity of the so-called plug-and-play system. Additionally, all the components are arranged in a server–client scheme to allow for practical key distribution. Blank, coherent pulse pair trains are generated at the reception end of the link by means of a pulse sequence and an unbalanced interferometer and sent to the other end. The emitter writes the qubits by erasing one of the pulses from the pair as in a coherent one-way protocol. Detection, as well as eavesdropping monitoring, is performed at the receiver side, using the same interferometer that was used to generate the initial phase-referenced pulses.     

Investment optimization model for freshwater acquisition and wastewater handling in shale gas production

Major challenges of water use in the drilling and fracturing process in shale gas production are large volumes required in a short‐period of time and the nonsteady nature of wastewater treatment. A new mixed‐integer linear programming (MILP) model for optimizing capital investment decisions for water use for shale gas production through a discrete‐time representation of the State‐Task Network is presented. The objective is to minimize the capital cost of impoundment, piping, and treatment facility, and operating cost including freshwater, pumping, and treatment. The goal is to determine the location and capacity of impoundment, the type of piping, treatment facility locations and removal capability, freshwater sources, as well as the frac schedule. In addition, the impact of several factors such as limiting truck hauling and increasing flowback volume on the solution is examined. A case study is optimized to illustrate the application of the proposed formulation. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1770–1782, 2015     

Antecedents of construction project coalitions: a study of the Spanish construction industry

Research into the formation of alliances, relevant in the field of strategic management and especially, in the construction industry, is often explained in terms of interdependency and complementarities (exogenous factors). In contrast, the influence of a firm’s social relations networks (endogenous factors) has hardly been studied at all. Thus, a model is needed that includes both exogenous and endogenous factors as antecedents to the formation of strategic alliances in the construction industry. Cooperation in the construction sector is especially frequent, above all in public works programmes, as their scale requires coalitions of different‐sized firms. Accordingly, to explore how both exogenous and endogenous factors influence the formation of alliances, a social network analytical method—Multiple Regression Quadratic Assignment Procedure (MRQAP)—was applied to cooperative project coalitions in the Spanish public works construction sector from 2001–2007. Empirical findings confirm that construction companies form coalitions, principally on the basis of past alliances. Membership of business associations and groups is also a key factor, though the influence of geographic proximity is the most debatable result. In the construction industry, the formation of alliances is conditioned, among other factors, by previous social and economic relations that can generate the necessary information and trust for the selection of whichever partner is considered the most suitable for the development of the joint project.     

Hydrogenation of vegetable oil using highly dispersed Pt/γ-Al2O3 catalyst: Effects of key operating parameters and deactivation study

In the present work, Pt/γ-Al₂O₃ catalysts with high metal dispersion were prepared and characterized using chloroplatinic acid and platinum acetylacetonate as metal precursors. The activity and selectivity of the catalysts were evaluated in the hydrogenation of sunflower oil. A comprehensive analysis of the effects of key operational parameters on catalytic performance was carried out. The experimental variables were hydrogen pressure (275.8–551.6 kPa), temperature (160–200°C), and catalyst loading (0.005–0.015 kg Pt_exp/m³_oil). Platinum catalysts were active, with a double bond conversion of 28% at 2 h. The metal precursor affected catalyst selectivity. The catalyst prepared with chloroplatinic acid exhibited a lower formation of trans-isomers compared with Pt acetylacetonate. The γ-Al₂O₃ supported platinum catalyst with a metal loading of 0.51 wt.% and a metal dispersion of 98% maintained its initial catalyst activity and selectivity after 10 consecutive uses (1200 min accumulate operation time), without changes in its catalytic properties. The obtained results suggested that Pt catalysts are an attractive alternative to conventional nickel catalysts for the hydrogenation of vegetable oil.     

Optimization models for shale gas water management

There are four key aspects for water use in hydraulic fracturing, including source water acquisition, wastewater production, reuse and recycle, and subsequent transportation, storage, and disposal. Water use life cycle is optimized for wellpads through a discrete‐time two‐stage stochastic mixed‐integer linear programming model under uncertain availability of water. The objective is to minimize expected transportation, treatment, storage, and disposal cost while accounting for the revenue from gas production. Assuming freshwater sources, river withdrawal data, location of wellpads, and treatment facilities are given, the goal is to determine an optimal fracturing schedule in coordination with water transportation, and its treatment and reuse. The proposed models consider a long‐time horizon and multiple scenarios from historical data. Two examples representative of the Marcellus Shale play are presented to illustrate the effectiveness of the formulation, and to identify optimization opportunities that can improve both the environmental impact and economical use of water. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3490–3501, 2014