Technical Audit of an Electronic Polling Station: A Case Study

P. 16-30This paper shows the lack of standard procedures to audit e-voting systems and also describes a practical process of auditing an e-voting experience based on a Direct-recording Electronic system (D.R.E). This system has been tested in a real situation, in the city council of Coahuila, Mexico, in November 2008. During the auditing, several things were kept in mind, in particular those critical in complex contexts, as democratic election processes are. The auditing process is divided into three main complementary stages: analysis of voting protocol, analysis of polling station hardware elements, and analysis of the software involved. Each stage contains several items which have to be analyzed at low level with the aim to detect and resolve possible security problemsS

An ontology-based approach to knowledge representation for Computer-Aided Control System Design

P. 107-125Different approaches have been used in order to represent and build control engineering concepts for the computer. Software applications for these fields are becoming more and more demanding each day, and new representation schemas are continuously being developed. This paper describes a study of the use of knowledge models represented in ontologies for building Computer Aided Control Systems Design (CACSD) tools. The use of this approach allows the construction of formal conceptual structures that can be stated independently of any software application and be used in many different ones. In order to show the advantages of this approach, an ontology and an application have been built for the domain of design of lead/lag controllers with the root locus method, presenting the results and benefits found

INTECO Webmessenger: Study of the Usability in Instant Messaging Systems

The main aim of this project is dual. Firstly, it is to achieve a complete analysis of the necessities of disabled people on the Internet. Secondly, it is intended to develop an instant messaging system based on the Windows Live Messenger whose requirements are defined over the previous analysis. This software is called INTECO Webmessenge

Rhetorical structure and persuasive language in the subgenre of online advertisements

p. 38-47This paper aims to reveal the rhetorical structure and the linguistic features of persuasive language in online advertisements of electronic products. Nowadays, the bulk of e-commerce is carried out in English, and it is often the case that non-native speakers are required to write different text types for various professional purposes, including promotional texts. This need has prompted the present study and the results have been used to build software to help native speakers of Spanish when writing promotional texts in English. The analysis reveals that these texts typically have two main rhetorical moves: one for identifying the product and another one for describing it. The latter move is further divided into two steps: one including objective features (size, weight, etc.) and the other focusing on persuading the potential customer. This is mainly achieved with the use of a relatively informal style (imperatives, contractions, clipping, subject/auxiliary omissions, etc.) and lexico-grammatical elements conveying positive evaluation (multiple modification, multal quantifying expressions, etc.). The findings show that online advertisements of electronic products may be regarded as a specific subgenre with particular macro- and microlinguistic characteristics, which have been identified in this paper for technical writing assistance.S

A fault detection system for a geothermal heat exchanger sensor based on intelligent techniques

[Abstract ]:This paper proposes a methodology for dealing with an issue of crucial practical importance in real engineering systems such as fault detection and recovery of a sensor. The main goal is to define a strategy to identify a malfunctioning sensor and to establish the correct measurement value in those cases. As study case, we use the data collected from a geothermal heat exchanger installed as part of the heat pump installation in a bioclimatic house. The sensor behaviour is modeled by using six different machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks. The achieved results suggest that this methodology is a very satisfactory solution for this kind of systems.Junta de Castilla y León; LE078G18. UXXI2018/000149. U-220.Ministerio de Economía, Industria y Competitividad; DPI2016-79960-C3-2-

Dairy cow nutrition in organic farming systems. Comparison with the conventional system

The energy supplied by the high-forage diets used in organic farming may be insufficient to meet the requirements of dairy cattle. However, few studies have considered this problem. The present study aimed to analyze the composition of the diets and the nutritional status (focusing on the energy–protein balance of the diets) of dairy cattle reared on organic farms in northern Spain, which are similar to other organic farming systems in temperate regions. Exhaustive information about diets was obtained from organic (ORG) and representative conventional grazing (GRZ) and conventional no-grazing (CNG) farms. Samples of feed from the respective farms were analyzed to determine the composition. Overall, the diets used on the ORG farms were very different from those used on the CNG farms, although the difference was not as evident for GRZ. The CNG farms were characterized by a higher total dry matter intake with a high proportion of concentrate feed, maize silage and forage silage. By contrast, on ORG and GRZ farms, the forage, pasture and fibre intake were the most important variables. The ration used on ORG farms contained a significantly higher percentage of ADF and lower organic matter (OM) content than the rations used in both of the conventional farming systems, indicating that the diets in the former were less digestible. Although the protein concentration in the diets used on the grazing farms (ORG and GRZ) was higher than those used on CNG farms, the protein intake was similar. The results indicated an imbalance between energy and protein due to the low level of energy provided by the ORG diets, suggesting that more microbial protein could be synthesized from the available rumen-degraded dietary nitrogen if rumen-fermentable OM was not limiting. The imbalance between energy and protein led to a reduced amount of total digestible protein reaching the intestine and a lower milk yield per kilogram of CP intake on the ORG farms. In order to improve the protein use efficiency and consequently to reduce the loss of nitrogen to the environment, organic farming should aim to increase the energy content of cattle diets by improving forage quality and formulating rations with more balanced combinations of forage and grainThis study was supported by the Spanish Government (project code AGL2010-21026) and Centro Tecnológico Agroalimentario de Lugo (CETAL). I. Orjales is in receipt of a FPU fellowship (Ref. FPU14/01473) from the Spanish Ministry of Education, Culture and SportsS

Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network

.In this work, a sentiment analysis method that is capable of accepting audio of any length, without being fixed a priori, is proposed. Mel spectrogram and Mel Frequency Cepstral Coefficients are used as audio description methods and a Fully Convolutional Neural Network architecture is proposed as a classifier. The results have been validated using three well known datasets: EMODB, RAVDESS and TESS. The results obtained were promising, outperforming the state-of–the-art methods. Also, thanks to the fact that the proposed method admits audios of any size, it allows a sentiment analysis to be made in near real time, which is very interesting for a wide range of fields such as call centers, medical consultations or financial brokers.S

Intelligent one-class classifiers for the development of an intrusion detection system: the MQTT case study

[Abstarct] The ever-increasing number of smart devices connected to the internet poses an unprecedented security challenge. This article presents the implementation of an Intrusion Detection System (IDS) based on the deployment of different one-class classifiers to prevent attacks over the Internet of Things (IoT) protocol Message Queuing Telemetry Transport (MQTT). The utilization of real data sets has allowed us to train the one-class algorithms, showing a remarkable performance in detecting attacks

Application of Meta-Analysis and Machine Learning Methods to the Prediction of Methane Production from In Vitro Mixed Ruminal Micro-Organism Fermentation

peer-reviewedIn vitro gas production systems are utilized to screen feed ingredients for inclusion in ruminant diets. However, not all in vitro systems are set up to measure methane (CH4) production, nor do all publications report in vitro CH4. Therefore, the objective of this study was to develop models to predict in vitro CH4 production from total gas and volatile fatty acid (VFA) production data and to identify the major drivers of CH4 production in these systems. Meta-analysis and machine learning (ML) methodologies were applied to a database of 354 data points from 11 studies to predict CH4 production from total gas production, apparent DM digestibility (DMD), final pH, feed type (forage or concentrate), and acetate, propionate, butyrate and valerate production. Model evaluation was performed on an internal dataset of 107 data points. Meta-analysis results indicate that equations containing DMD, total VFA production, propionate, feed type and valerate resulted in best predictability of CH4 on the internal evaluation dataset. The ML models far exceeded the predictability achieved using meta-analysis, but further evaluation on an external database would be required to assess generalization ability on unrelated data. Between the ML methodologies assessed, artificial neural networks and support vector regression resulted in very similar predictability, but differed in fitting, as assessed by behaviour analysis. The models developed can be utilized to estimate CH4 emissions in vitro

An intelligent system for harmonic distortions detection in wind generator power electronic devices

The high concern about climate change has boosted the promotion of renewable energy systems, being the wind power one of the key generation possibilities in this field. In this context, with the aim of ensuring the energy efficiency, the present work deals with the fault detection in the power electronic circuits of a wind generator system placed in a bioclimatic house. To do so, different outliers that emulate harmonic distortion appearance are tested. To implement a system capable of detecting this anomalous situations, six different one-class techniques are used, whose performance is thoroughly analyzed, offering interesting performance.info:eu-repo/semantics/publishedVersio