Search results for: Antonio Avalos Ramirez

Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi

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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.

Keywords: Camera calibration, ego motion, kalman filters, object tracking, real time systems.

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: Deep-learning, image classification, image identification, industrial engineering.

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Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: Cloud storage, decision trees, diagnostic image, search, telemedicine.

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Authors: Antonio Breda d’Azevedo

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Regularity has often been present in the form of regular polyhedra or tessellations; classical examples are the nine regular polyhedra consisting of the five Platonic solids (regular convex polyhedra) and the four Kleper-Poinsot polyhedra. These polytopes can be seen as regular maps. Maps are cellular embeddings of graphs (with possibly multiple edges, loops or dangling edges) on compact connected (closed) surfaces with or without boundary. The n-dimensional abstract polytopes, particularly the regular ones, have gained popularity over recent years. The main focus of research has been their symmetries and regularity. Planification of polyhedra helps its spatial construction, yet it destroys its symmetries. To our knowledge there is no “planification” for n-dimensional polytopes. However we show that it is possible to make a “surfacification” of the n-dimensional polytope, that is, it is possible to construct a restrictedly-marked map representation of the abstract polytope on some surface that describes its combinatorial structures as well as all of its symmetries. We also show that there are infinitely many ways to do this; yet there is one that is more natural that describes reflections on the sides ((n−1)-faces) of n-simplices with reflections on the sides of n-polygons. We illustrate this construction with the 4-tetrahedron (a regular 4-polytope with automorphism group of size 120) and the 4-cube (a regular 4-polytope with automorphism group of size 384).

Keywords: Maps, representation, polytopes.

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Authors: Carlos A. D. Torres, Antonio D. Delgado

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In this work we study the thermodynamic behavior of some ventilated facades under summer operating conditions in Southern Spain. Under these climatic conditions, indoor comfort implies a high energetic demand due to high temperatures that usually are reached in this season in the considered geographical area.

The aim of this work is to determine if during summer operating conditions in Southern Spain, ventilated façades provide some energy saving compared to the non-ventilated façades and to deduce their behavior patterns in terms of energy efficiency.

The modelization of the air flow in the channel has been performed by using Navier-Stokes equations for thermodynamic flows. Numerical simulations have been carried out with a 2D Finite Element approach.

This way, we analyze the behavior of ventilated façades under different weather conditions as variable wind, variable temperature and different levels of solar irradiation.

CFD computations show the combined effect of the shading of the external wall and the ventilation by the natural convection into the air gap achieve a reduction of the heat load during the summer period. This reduction has been evaluated by comparing the thermodynamic performances of two ventilated and two unventilated façades with the same geometry and thermophysical characteristics.

Keywords: Passive cooling, ventilated façades, energy-efficient building, CFD, FEM.

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Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: Active learning, blended learning, maker movement, new product development, open innovation laboratory.

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Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi

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Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at international level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work, an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.

Keywords: Ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol.

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention, however, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem is the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement final run V06B SPP in a semi-arid region of Mexico, using four rain gauges sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing moderate overestimations and underestimations, respectively. The study zone presented 80 to 85% of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and rain gauges. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation.

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg⋅m- 3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg·m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: Biodiesel, Correlation, Density, Equation of state, Prediction.

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Authors: Luís Antonio de Almeida Rodriguez, José Maria Parente de Oliveira, Ednelson Oliveira

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In the last two decades, the world’s aviation authorities have made several attempts to create consensus about a global and accepted approach for applying semantics to web services registry descriptions. This problem has led communities to face a fat and disorganized infrastructure to describe aeronautical web services. It is usual for developers to implement ad-hoc connections among consumers and providers and manually create non-standardized service compositions, which need some particular approach to compose and semantically discover a desired web service. Current practices are not precise and tend to focus on lightweight specifications of some parts of the OWL-S and embed them into syntactic descriptions (SOAP artifacts and OWL language). It is necessary to have the ability to manage the use of both technologies. This paper presents an implementation of the ontology OWL-S that describes a Brazilian Aeronautical Web Service Registry, which makes it able to publish, advertise, make multi-criteria semantic discovery aligned with the ideas of the System Wide Information Management (SWIM) Program, and invoke web services within the Air Traffic Management context. The proposal’s best finding is a generic approach to describe semantic web services. The paper also presents a set of functional requirements to guide the ontology development and to compare them to the results to validate the implementation of the OWL-S Ontology.

Keywords: Aeronautical Web Services, OWL-S, Semantic Web Services Discovery, Ontologies.

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: Artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L, Schinus terebinthifolius raddi.

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Authors: Antônio Carlos da Rocha Costa

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This paper concerns a formal model to help the simulation of agent societies where institutional roles and institutional links can be specified operationally. That is, this paper concerns institutional roles that can be specified in terms of a minimal behavioral capability that an agent should have in order to enact that role and, thus, to perform the set of institutional functions that role is responsible for. Correspondingly, the paper concerns institutional links that can be specified in terms of a minimal interactional capability that two agents should have in order to, while enacting the two institutional roles that are linked by that institutional link, perform for each other the institutional functions supported by that institutional link. The paper proposes a cognitive architecture approach to institutional roles and institutional links, that is, an approach in which a institutional role is seen as an abstract cognitive architecture that should be implemented by any concrete agent (or set of concrete agents) that enacts the institutional role, and in which institutional links are seen as interactions between the two abstract cognitive agents that model the two linked institutional roles. We introduce a cognitive architecture for such purpose, called the Institutional BCC (IBCC) model, which lifts Yoav Shoham-s BCC (Beliefs-Capabilities-Commitments) agent architecture to social contexts. We show how the resulting model can be taken as a means for a cognitive architecture account of institutional roles and institutional links of agent societies. Finally, we present an example of a generic scheme for certain fragments of the social organization of agent societies, where institutional roles and institutional links are given in terms of the model.

Keywords: Simulation of agent societies, institutional roles, cognitive architecture of institutional roles.

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Authors: Richard C.M. Yam, William Lo, Esther P.Y. Tang, Antonio, K.W. Lau

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Technological innovation capability (TIC) is defined as a comprehensive set of characteristics of a firm that facilities and supports its technological innovation strategies. An audit to evaluate the TICs of a firm may trigger improvement in its future practices. Such an audit can be used by the firm for self assessment or third-party independent assessment to identify problems of its capability status. This paper attempts to develop such an auditing framework that can help to determine the subtle links between innovation capabilities and business performance; and to enable the auditor to determine whether good practice is in place. The seven TICs in this study include learning, R&D, resources allocation, manufacturing, marketing, organization and strategic planning capabilities. Empirical data was acquired through a survey study of 200 manufacturing firms in the Hong Kong/Pearl River Delta (HK/PRD) region. Structural equation modelling was employed to examine the relationships among TICs and various performance indicators: sales performance, innovation performance, product performance, and sales growth. The results revealed that different TICs have different impacts on different performance measures. Organization capability was found to have the most influential impact. Hong Kong manufacturers are now facing the challenge of high-mix-low-volume customer orders. In order to cope with this change, good capability in organizing different activities among various departments is critical to the success of a company.

Keywords: Hong Kong/Pearl River Delta, Innovationaudit, Manufacturing, Technological innovation capability

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Authors: Rui Sousa, Aurora Futuro, António Fiúza

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The exploitation of gold ore deposits is highly dependent on efficient mineral processing methods, although actual perspectives based on life-cycle assessment introduce difficulties that were unforeseen in a very recent past. Cyanidation is the most applied gold processing method, but the potential environmental problems derived from the usage of cyanide as leaching reagent led to a demand for alternative methods. Ammoniacal thiosulfate leaching is one of the most important alternatives to cyanidation. In this article, some experimental studies carried out in order to assess the feasibility of thiosulfate as a leaching agent for the ore from the unexploited Portuguese gold mine of Castromil. It became clear that the process depends on the concentrations of ammonia, thiosulfate and copper. Based on this fact, a few leaching tests were performed in order to assess the best reagent prescription, and also the effects of different combination of these concentrations. Higher thiosulfate concentrations cause the decrease of gold dissolution. Lower concentrations of ammonia require higher thiosulfate concentrations, and higher ammonia concentrations require lower thiosulfate concentrations. The addition of copper increases the gold dissolution ratio. Subsequently, some alternative operatory conditions were tested such as variations in temperature and in the solid/liquid ratio as well as the application of a pre-treatment before the leaching stage. Finally, thiosulfate leaching was compared to cyanidation. Thiosulfate leaching showed to be an important alternative, although a pre-treatment is required to increase the yield of the gold dissolution.

Keywords: Gold, leaching, pre-treatment, thiosulfate.

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Authors: Diamantino Ribeiro, António Pedro Costa, Jorge Remondes

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Dubai and the UAE governments have been investing in technology and digital communication for a long time. These governments are pioneers in introducing innovative strategies, policies and projects. They are also recognized worldwide for defining and implementing long term public programs. In terms of eGovernment Dubai and the UAE rank among the world’s most advanced. Both governments have surprised the world a few years ago by creating a Happiness Ministry. This paper focuses on UAE’s government digital strategies and its approach to the next era. The main goal of this exploratory study is to understand the new era of eGovernment and transfer of the happiness and wellness programs. Data were collected from the corpus latente and analysis was anchored in qualitative methodology using content analysis and observation as analysis techniques. The study allowed to highlight that the 2020 government reshuffle has a strong focus on digital reorganisation and digital sustainability, one of the newest trends in sustainability. Regarding happiness and wellbeing portfolio, we were able to observe that there has been a major change within the government organisation: The Ministry of Happiness was extinct and the Ministry of Community Development will manage the so-called ‘Happiness Portfolio’. Additionally, our observation allowed to note the government dual approach to governance: one through digital transformation, thus enhancing the digital sustainability process and, the second one trough government development.

Keywords: Ministry of Happiness, eGovernment, communication, digital sustainability.

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: Biomass, diatom, flocculation, microalgae.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz

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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Keywords: Community empowerment, food security, model, systemic approach.

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Authors: Andrea M. Rivas-Castillo, Marlenne Gómez-Ramirez, Isela Rodríguez-Pozos, Norma G. Rojas-Avelizapa

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Spent catalysts are considered as hazardous residues of major concern, mainly due to the simultaneous presence of several metals in elevated concentrations. Although hydrometallurgical, pyrometallurgical and chelating agent methods are available to remove and recover some metals contained in spent catalysts; these procedures generate potentially hazardous wastes and the emission of harmful gases. Thus, biotechnological treatments are currently gaining importance to avoid the negative impacts of chemical technologies. To this end, diverse microorganisms have been used to assess the removal of metals from spent catalysts, comprising bacteria, archaea and fungi, whose resistance and metal uptake capabilities differ depending on the microorganism tested. Acidophilic sulfur oxidizing bacteria have been used to investigate the biotreatment and extraction of valuable metals from spent catalysts, namely Acidithiobacillus thiooxidans and Acidithiobacillus ferroxidans, as they present the ability to produce leaching agents such as sulfuric acid and sulfur oxidation intermediates. In the present work, the ability of A. thiooxidans DSM 26636 for the bioleaching of metals contained in five different spent catalysts was assessed by growing the culture in modified Starkey mineral medium (with elemental sulfur at 1%, w/v), and 1% (w/v) pulp density of each residue for up to 21 days at 30 °C and 150 rpm. Sulfur-oxidizing activity was periodically evaluated by determining sulfate concentration in the supernatants according to the NMX-k-436-1977 method. The production of sulfuric acid was assessed in the supernatants as well, by a titration procedure using NaOH 0.5 M with bromothymol blue as acid-base indicator, and by measuring pH using a digital potentiometer. On the other hand, Inductively Coupled Plasma - Optical Emission Spectrometry was used to analyze metal removal from the five different spent catalysts by A. thiooxidans DSM 26636. Results obtained show that, as could be expected, sulfuric acid production is directly related to the diminish of pH, and also to highest metal removal efficiencies. It was observed that Al and Fe are recurrently removed from refinery spent catalysts regardless of their origin and previous usage, although these removals may vary from 9.5 ± 2.2 to 439 ± 3.9 mg/kg for Al, and from 7.13 ± 0.31 to 368.4 ± 47.8 mg/kg for Fe, depending on the spent catalyst proven. Besides, bioleaching of metals like Mg, Ni, and Si was also obtained from automotive spent catalysts, which removals were of up to 66 ± 2.2, 6.2±0.07, and 100±2.4, respectively. Hence, the data presented here exhibit the potential of A. thiooxidans DSM 26636 for the simultaneous bioleaching of metals contained in spent catalysts from diverse provenance.

Keywords: Acidithiobacillus thiooxidans, spent catalysts, bioleaching, metals, sulfuric acid, sulfur-oxidizing activity.

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Authors: Antonio Vitale, Nicola Genito, Giovanni Cuciniello, Ferdinando Montemari

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: Flapping Dynamics, Flight Dynamics, System Identification, Tilt-Rotor Modeling and Simulation.

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Authors: António Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also, analyses the strategy follow in the innovation process and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. The Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: Footwear industry, innovation strategy, low-tech industry, Oslo Manual.

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a realtime Simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three VelmexXSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed Simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: Haptic feedback, MATLAB, Simulink, Strain Gage, Surgical Robot.

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Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: Energy-efficient buildings, Hierarchical model predictive control, Microgrid power flow optimization, Price-optimal building climate control.

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

Abstract:

This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: Behavior of winds, wind power, fuzzy logic, sustainable development.

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio D. Grieco, Emanuela Guerriero

Abstract:

Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from a real-life pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: Constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries.

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