El demonio y la visión del “otro” en la primera parte de la Crónica del "Perú" (1553) de Pedro Cieza de León

Many 16th century Spanish chroniclers and missionaries, arriving at what they interpreted as a New World, saw the Devil as a “hermeneutic wildcard” that allowed them to comprehend indigenous religions. Pedro Cieza de León, a soldier in the conquest of Peru, is a case in point. Cieza considers the Devil responsible for the most aberrant religious practices and customs of the Indians, although he views the natives in a positive light, as men susceptible to divine salvation. From a providentialist perspective of the history of the conquest, Cieza interprets that the evangelization and conversion of the Indians and the implantation of Christian civilization by the Spanish Crown, were able to defeat the Devil.Para muchos cronistas y misioneros españoles del siglo XVI que arribaron a lo que para ellos era un Nuevo Mundo, la figura del demonio se convirtió en un “comodín hermenéutico” para comprender la religión indígena. Pedro Cieza de León, soldado partícipe en la conquista del Perú, fue uno de ellos. En la primera parte de su Crónica del Perú, el demonio ocupa un gran protagonismo. Cieza considera al demonio responsable de las prácticas religiosas y costumbres más aberrantes de los indios, a quienes, no obstante, valora positivamente como hombres susceptibles de la salvación divina. Cieza, desde una perspectiva providencialista de la historia de la conquista, interpreta que la evangelización y conversión de los indios, unida a la implantación por la Corona española de la civilización cristiana, han logrado la derrota del demonio

An Expert System to Improve the Energy Efficiency of the Reaction Zone of a Petrochemical Plant

Energy is the most important cost factor in the petrochemical industry. Thus, energy efficiency improvement is an important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. This work describes the development of an expert system for the improvement of this efficiency of the reaction zone of a petrochemical plant. This system has been developed after a data mining process of the variables registered in the plant. Besides, a kernel of neural networks has been embedded in the expert system. A graphical environment integrating the proposed system was developed in order to test the system. With the application of the expert system, the energy saving on the applied zone would have been about 20%.Junta de Andalucía TIC-570

The jihad and the treatment of war in the Qur’an

The present study analyzes the meaning of the concept of jihad in the Qur’an, the main foundational text of Islam, and its treatment of violence and war. The study emphasizes the need to understand the foundational texts considered sacred, taking into account the historical context in which they arose, and concludes that the quranic rules on jihad and war participate in a religious-inspired humanitarianism that differs fully from the practices of jihadist terrorism.Received: 11 June 2018Accepted: 15 September 2018Published online: 11 December 2018</p

A joint multi-path and multi-channel protocol for traffic routing in smart grid neighborhood area networks

In order to improve the management mechanisms of the electric energy transport infrastructures, the smart grid networks have associated data networks that are responsible for transporting the necessary information between the different elements of the electricity network and the control center. Besides, they make possible a more efficient use of this type of energy. Part of these data networks is comprised of the Neighborhood Area Networks (NANs), which are responsible for interconnecting the different smart meters and other possible devices present at the consumers' premises with the control center. Among the proposed network technologies for NANs, wireless technologies are becoming more relevant due to their flexibility and increasing available bandwidth. In this paper, some general modifications are proposed for the routing protocol of the wireless multi-hop mesh networks standardized by the IEEE. In particular, the possibility of using multiple paths and transmission channels at the same time, depending on the quality of service needs of the different network traffic, is added. The proposed modifications have been implemented in the ns-3 simulator and evaluated in situations of high traffic load. Simulation results show improvements in the network performance in terms of packet delivery ratio, throughput and network transit time.Peer ReviewedPostprint (published version

Decision system based on neural networks to optimize the energy efficiency of a petrochemical plant

The energy efficiency of industrial plants is an important issue in any type of business but particularly in the chemical industry. Not only is it important in order to reduce costs, but also it is necessary even more as a means of reducing the amount of fuel that gets wasted, thereby improving productivity, ensuring better product quality, and generally increasing profits. This article describes a decision system developed for optimizing the energy efficiency of a petrochemical plant. The system has been developed after a data mining process of the parameters registered in the past. The designed system carries out an optimization process of the energy efficiency of the plant based on a combined algorithm that uses the following for obtaining a solution: On the one hand, the energy efficiency of the operation points occurred in the past and, on the other hand, a module of two neural networks to obtain new interpolated operation points. Besides, the work includes a previous discriminant analysis of the variables of the plant in order to select the parameters most important in the plant and to study the behavior of the energy efficiency index. This study also helped ensure an optimal training of the neural networks. The robustness of the system as well as its satisfactory results in the testing process (an average rise in the energy efficiency of around 7%, reaching, in some cases, up to 45%) have encouraged a consulting company (ALIATIS) to implement and to integrate the decision system as a pilot software in an SCADA

A testbed based performance evaluation of smart grid wireless neighborhood area networks routing protocols

Smart Grid networks have a data communication network associated with the electrical energy distribution infrastructure. This network connects all the sub- scribers’ homes with the data control centers of the supplying companies, which in turn have access to the global Internet network. They are in charge of transporting the needed information between the elements that comprise the electricity network and the control centers. A part of these networks is the so-called Neighborhood Area Networks (NANs), which transports the data from the subscriber’s home to some data concentrators. This article presents a comparison of the performance of different routing protocols that can be used in this part of the data network, when a wireless technology is selected. For this comparison, a hardware testbed has been implemented, with a simple initial configuration, which allows the comparison of the OLSR v1, OLSR v2 and HWMP protocols. The numerical results are presented in terms of network throughput, protocol overhead, number of retransmissions, net- work transit and packet transfer times.This work was supported by the Spanish Research Council under project MAGOS (TEC2017-84197-C4-3-R), and Juan Pablo Astudillo León is the recipient of a full scholarship from the Secretaría de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT), Ecuador.Peer ReviewedPostprint (published version

An Approach to Detection of Tampering in Water Meters

Meter tampering is defined as a fraudulent manipulation which implies a service that is not billed by a utility company. It is a lack of consumption control for the utility company and a main problem because they represent an important loss of income. We have developed a methodology consists of a set of three algorithms for the detection of meter tampering in the Emasesa Company (a water distribution company in Seville and one of the most important of the country). The algorithms were generated and programmed after a data mining process from the database of the company and they detect three type of consumption patterns: Progressive drops, sudden drops and abnormally low consumption. The methodology has been tested with in situ inspections of the customers of a village of the province of Seville. Once carried out the inspections by the utility, the inspectors confirmed a good success rate taking into account that the detection of this type of fraud is very difficult because it is a noninvasive technique. Besides, this type of detections is a topic that, if we take a look at the state of the art, there are few references or works.Ministerio de Ciencia y Tecnología TEC2013-40767-

Emergency aware congestion control for smart grid neighborhood area networks

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The evolution of traditional electricity distribution infrastructures towards Smart Grid networks has generated the need to carry out new research. There are many fields that have attracted the attention of researchers, among which is the improvement of the performance of the so-called Neighborhood Area Networks (NAN). In this sense, and given the critical nature of some of the data transmitted by these networks, maintaining an adequate quality of service (QoS) is absolutely necessary. In emergency situations, this need becomes even more evident. This article presents a congestion control mechanism, whose parameters are modified according to the network state of emergency. The mechanism also applies a multi-channel allocation technique, together with a differentiation in the QoS offered to the different data flows according to their relevance. These proposals have been evaluated in the context of a wireless mesh networks (WMN) made up by a set of smart meter devices, where various smart grids (SG) applications are sending their data traffics. Each SG application must meet its unique quality of service (QoS) requirements, such as reliability and delay. To evaluate the proposals, some NAN scenarios have been built by using the ns-3 simulator and its 802.11s basic model, which was modified to implement the proposed techniques. Compared with the basic Hybrid Wireless Mesh Protocol (HWMP), Emergency Aware Congestion Control proposal (EA-HWMP), shows significant improvements in terms of packet delivery ratio, network throughput and transit time.Peer ReviewedPostprint (published version

Electricity clustering framework for automatic classification of customer loads

Clustering in energy markets is a top topic with high significance on expert and intelligent systems. The main impact of is paper is the proposal of a new clustering framework for the automatic classification of electricity customers’ loads. An automatic selection of the clustering classification algorithm is also highlighted. Finally, new customers can be assigned to a predefined set of clusters in the classificationphase. The computation time of the proposed framework is less than that of previous classification tech- niques, which enables the processing of a complete electric company sample in a matter of minutes on a personal computer. The high accuracy of the predicted classification results verifies the performance of the clustering technique. This classification phase is of significant assistance in interpreting the results, and the simplicity of the clustering phase is sufficient to demonstrate the quality of the complete mining framework.Ministerio de Economía y Competitividad TEC2013-40767-RMinisterio de Economía y Competitividad IDI- 2015004

Rule-based system to detect energy efficiency anomalies in smart buildings, a data mining approach

The rapidly growing world energy use already has concerns over the exhaustion of energy resources andheavy environmental impacts. As a result of these concerns, a trend of green and smart cities has beenincreasing. To respond to this increasing trend of smart cities with buildings every time more complex,in this paper we have proposed a new method to solve energy inefficiencies detection problem in smartbuildings. This solution is based on a rule-based system developed through data mining techniques andapplying the knowledge of energy efficiency experts. A set of useful energy efficiency indicators is alsoproposed to detect anomalies. The data mining system is developed through the knowledge extracted bya full set of building sensors. So, the results of this process provide a set of rules that are used as a partof a decision support system for the optimisation of energy consumption and the detection of anomaliesin smart buildings.Comisión Europea FP7-28522