Miguel Franklin de Castro

Toxic-oil syndrome: case reports associated with the ITH oil refinery in Sevilla.

Toxic-oil syndrome (TOS), a new disease that occurred in epidemic form in Spain in 1981, has been associated with the ingestion of unlabelled oil bought principally from travelling salesmen. Chemical analysis of oils taken from ill families has shown them to consist of varying proportions of different vegetable oils and animal fats, often showing chemical evidence of prior treatment with aniline. We investigated the unusual circumstances surrounding the reported occurrence of three TOS cases in two families in Sevilla, a city located far away (approximately 300 km) from the group of 14 provinces in central and northwestern Spain where 99% of the TOS cases occurred. Each case we investigated fitted the clinical picture of TOS and was not consistent with any other diagnosis. Illness apparently occurred as a result of ingestion of oil taken from the ITH oil refinery in Sevilla, a plant in which rapeseed and grapeseed oils were refined for the distributing firm through which oil bearing the causative agent of TOS is thought to have entered the market. These data provide further strong support for the hypothesis that food oil was the vehicle by which the aetiological agent of TOS was transmitted. Because ingestion of refined denatured rapeseed oil was most closely associated with the illness in time, the TOS agent was probably contained initially in this type of oil. The agent very probably entered later oil mixtures through such contaminated rapeseed oil.

An autonomic bio-inspired algorithm for wireless sensor network self-organization and efficient routing

Self-configuration and autonomy are key features required for the next generation of gadgets and networks, since regular users are willing to have computationally enabled devices pervasively spread into their environment. Sensors are among the most promising devices into this new scenario. However, their low battery and processing power raise several issues to these autonomy requirements. This paper presents BiO4SeL (Bio-Inspired Optimization for Sensor Network Lifetime), a swarm intelligence-based algorithm to perform self-organization and optimization of lifetime by means of routing into a Wireless Sensor Network. Results show that BiO4SeL achieves its objectives when compared to similar approaches: ARAMA (Ant-based Routing Algorithm for MANETs), EAR (Energy-Aware Routing) and AODV (Ad-hoc On-demand Distance Vector).

A fair QoS-aware dynamic LTE scheduler for machine-to-machine communication

The long term evolution (LTE) standard plays an important role in the development of internet of things (IoT) and machine-to-machine (M2M) communication because of its high data rates, low latency, high flexibility and low cost. However, improvements are needed in the network to support the uplink-heavy traffic generated by M2M communication and also to ensure the diversity of service requirements of this communication and to control the performance reduction in the classical mobile services of human-to-human (H2H) communication. In this paper, we present a new LTE uplink scheduler that dynamically adjusts to the level of congestion of the network based on the current traffic information of each device to support the M2M traffic. Furthermore, the main goals of our approach are (i) satisfy the quality of service (QoS) requirements, (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.

Do users write about the system in use?: an investigation from messages in natural language on Twitter

Social Network Sites have grown considerably in recent years. Studies have revealed that users write in Social Systems about services, opinions or facts concerning personal life. However, no studies have been found regarding the following question: Do users write about the system in use? How? Is it valid to evaluate the users experience in Social Network Sites through their written texts? A methodology to search for postings of users on Twitter was used, composed of filters which combine patterns which may be related to the use of the system. The results have shown evidence that some messages posted in these types of systems are about the system in use. As a contribution, we presented some characteristics of the messages of the users of social networking sites in order to facilitate the understanding of its usage experience.

How Do Users Express Their Emotions Regarding the Social System in Use? A Classification of Their Postings by Using the Emotional Analysis of Norman

Social Networking Sites SNS allow users to post messages aboutany event which has occurred with them, including the system itself. In this study, we conducted two experiments with postings of users on SNS in order to investigate i how users express their emotions regarding the use of the system, and ii how to assess the user experience by using their postings during the system interaction. The results showed some characteristics of postings related to the use which may be useful for UX evaluation in SNS.

State of the art and challenges of security SLA for cloud computing

There are users and organizations that resist adopting cloud computing solutions, due to concerns about the security and privacy of their data. A Service Level Agreement (SLA) can be used to address these concerns, increasing trust in the purchased services through the clear description of the guarantees offered by the provider to the subscribers. For this purpose, the authors performed a literature systematic mapping to enumerate existing solutions and open issues in security SLAs in cloud computing. This review is presented in this paper as well as an analysis of the state of art. This paper also presents a classification of the selected papers and a discussion about management of security SLAs in clouds.

Investigating Usability and User Experience from the User Postings in Social Systems

Social Systems (SS) are dynamic systems, with features such as: frequent exchange of messages and expression of feelings spontaneously. The postings of users on SS reveal their opinions on various issues, including on what they think of the system. In this study, we classified postings of users from two SS of different contexts: a popular SS (entertainment) - Twitter and an academic SS of a university – forums, to investigate information related to usability and user experience (UX) of such systems. Results showed they are useful to (i) obtain user’s sentiments about the system; (ii) to identify possible problems during their experience and (iii) to perceive from the set of classified postings the context of use of the system.

MLM-rank: A Ranking Algorithm Based on the Minimal Learning Machine

Ranking is an important task in information retrieval and has gained much attention in recent years. Among the most used strategies, machine learning has achieved important results. The current work proposes a new machine learning based ranking algorithm, the MLM-RANK. MLM-RANK is based on the recently proposed Minimal Learning Machine (MLM). MLM is a supervised learning method that requires the adjustment of a single hyper parameter. The proposed method was evaluated against Prank and ELM Rank, both state of the art point wise ranking methods. In these tests MLM-RANK achieved promising results.

A dynamic LTE uplink packet scheduler for Machine-to-Machine communication

The Long Term Evolution (LTE) standard plays an important role in the development of Machine-to-Machine (M2M) communication. However, the M2M communication has several different characteristics regarding to Human-to-Human (H2H) communication. Therefore, the shortage of radio resources, satisfaction of the Quality of Service (QoS) requirements and the reduction of the H2H traffic performance are important issues to be addressed when introducing the M2M communication in the network. In this article, we present a scheduler that may dynamically adjust to the level of congestion of the network based on the current traffic information of each device. The main goals of our approach are (i) satisfy the QoS requirements (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.

A mechanism for uplink packet scheduler in LTE network in the context of machine-to-machine communication

This paper proposes a mechanism for uplink packet scheduler in LTE network in the context of Machine-to-Machine (M2M) communication. The proposed approach uses the current and past information of the system to satisfy the Quality of Service (QoS) requirements, to ensure fairness in resource allocation and to control the congestion caused by M2M devices. We carried out some network simulations by using a NS-3 simulator so as to show the effectiveness of the proposed approach. The results indicate that our solution can reduce the impact of M2M communication on Human-to-Human (H2H) communication and avoid the problem of starvation, when compared to related approaches.