Search results for: open queueing network

Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

Procedia PDF Downloads 134

Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Jose A. Pomilio, Olavo Bet, Mateus P. Vieira

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The power converter that feeds high-frequency, high-voltage transformers must be carefully designed due to parasitic components, mainly the secondary winding capacitance and the leakage inductance, that introduces resonances in relatively low-frequency range, next to the switching frequency. This paper considers applications in which the load (resistive) has an unpredictable behavior, changing from open to short-circuit condition faster than the output voltage control loop could react. In this context, to avoid over voltage and over current situations, that could damage the converter, the transformer or the load, it is necessary to find an operation point that assure the desired output voltage in spite of the load condition. This can done adjusting the frequency response of the transformer adding an external inductance, together with selecting the switching frequency to get stable output voltage independently of the load.

Keywords: high-voltage transformer, resonant converter, soft-commutation, external inductance

Procedia PDF Downloads 487

Authors: Thulane Paepae, Tumisang Seodigeng

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This paper demonstrates the use of a method of synthesizing process flowsheets using a graphical tool called the GH-plot and in particular, to look at how it can be used to compare the reactions of a combined simultaneous process with regard to their thermodynamics. The technique uses fundamental thermodynamic principles to allow the mass, energy and work balances locate the attainable region for chemical processes in a reactor. This provides guidance on what design decisions would be best suited to developing new processes that are more effective and make lower demands on raw material and energy usage.

Keywords: attainable regions, dimethyl ether, optimal reaction network, GH Space

Procedia PDF Downloads 243

Authors: M. Khal, Ab. Algouti, A. Algouti

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Water erosion is the major cause of the erosion that shapes the earth's surface. Modeling water erosion requires the use of software and GIS programs, commercial or closed source. The very high prices for commercial GIS licenses, motivates users and researchers to find open source software as relevant and applicable as the proprietary GIS. The objective of this study is the modeling of water erosion and the hydrogeological and morphophysical characterization of the Oued M'Goun watershed (southern flank of the Central High Atlas) developed by free programs of GIS. The very pertinent results are obtained by executing tasks and algorithms in a simple and easy way. Thus, the various geoscientific and geostatistical analyzes of a digital elevation model (SRTM 30 m resolution) and their combination with the treatments and interpretation of satellite imagery information allowed us to characterize the region studied and to map the area most vulnerable to water erosion.

Keywords: central High-Atlas, hydrogeology, M’Goun watershed, OpenGis, water erosion

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Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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Authors: Sphiwe Simelane, Daniel Madyira

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The use of natural fibers requires that they should be treated in preparation for their use in Natural Fiber-reinforced polymer composites. This paper reports on the effects of sodium hydroxide (NaOH) treatment on the surface of coconut fibers. The fibers were subjected to 5%, 10%, 15% and 20% NaOH concentrations and soaked for 4 hours and thoroughly rinsed and allowed to dry in the open air for seven days, after which time they were dried in an oven for 30 minutes. Untreated and treated coconut fibers were observed under the Scanning Electron Microscope and it was noted that the surface structure of the fibers was modified differently by the different NaOH concentrations, and the resultant colour of the treated fibers got darker as the solution concentration increased, and the texture felt rougher to the touch as a result of the erosion of the fiber surface. Further, the increase in alkali concentration striped the surface of more constituents, thus exposing “pits” and other surface components rendering the surface rough.

Keywords: coconut fiber, scanning electron microscope, sodium hydroxide, surface treatment

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Authors: Tebah KH A AlFouzan, Meznah Dahlous Ali Alkreebani, Fatemah Salem Dekheel Alrasheedi, Hanadi Bandar Rughayan AlNomas, Muneerah Mohammad Sulaiman ALOjairi

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Article spotlights the heat transfer process based beneath the earth’s surface. The process starts by exchanging the heat found in the building as fluid in the pipes absorbs it, then transports it down the soil consuming cool temperature exchange, recirculating, and rebounding to deliver cool air. This system is a renewable energy that is reliable and sustainable. The analysis showed the disposal of fossil fuels, energy preservation, 400% efficiency, long lifespan, and lower maintenance. Investigation displays the system’s types of design, whether open or closed loop and piping layout. Finally, the geothermal cooling study presents the challenges of creating a prototype in Kuwait, as constraints are applicable due to geography.

Keywords: cooling system, engineering, geothermal cooling, natural ventilation, renewable energy

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

Procedia PDF Downloads 422

Authors: Patrik Scajev, Pavels Onufrijevs, Algirdas Mekys, Tadas Malinauskas, Dominykas Augulis, Liudvikas Subacius, Kuo-Chih Lee, Jevgenijs Kaupuzs, Arturs Medvids, Hung Hsiang Cheng

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In this study, we focused on the optoelectronic properties of the photodiodes prepared by using 200 nm thick Ge₀.₉₅Sn₀.₀₅ epitaxial layers on Ge/n-Si substrate with aluminum contacts. Photodiodes were formed on non-irradiated and Nd: YAG laser irradiated Ge₀.₉₅Sn₀.₀₅ layers. The samples were irradiated by pulsed Nd: YAG laser with 136.7-462.6 MW/cm² intensity. The photodiodes were characterized by using short laser pulses with the wavelength in the 2.0-2.6 μm range. The laser-irradiated diode was found more sensitive in the long-wavelength range due to laser-induced Sn atoms redistribution providing formation of graded bandgap structure. Sub-millisecond photocurrent relaxation in the diodes revealed their suitability for image sensors. Our findings open the perspective for improving the photo-sensitivity of GeSn alloys in the mid-infrared by pulsed laser processing.

Keywords: GeSn, laser processing, photodetector, infrared

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Authors: Tuğba Horzum, Ahmet Arikan

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This paper was part of a broader study that investigated what blind students (BSs) understood and how they used concept definitions (CDs) and concept images (CIs) for some mathematical concepts. This paper focused on the polygon concept. For this purpose, four open-ended questions were asked to five blind middle school students. During the interviews, BSs were presented with raised-line materials and were given opportunities to construct geometric shapes with magnetic sticks and micro-balls. Qualitative research techniques applied in grounded theory were used for analyzing documents pictures which were taken from magnetic geometric shapes that BSs constructed, raised-line materials and researcher’s observation notes and interviews. At the end of the analysis, it was observed that BSs used mostly their CIs and never took into account the CDs. Besides, BSs encountered with the difficulties associated with the combination of polygon edges’ endpoints consecutively. Additionally, they focused on the interior of the polygon and the angles which have smaller a size. Lastly, BSs were often conflicted about triangle, rectangle, square and circle whether or not a polygon.

Keywords: blind students, concept definition, concept image, polygon

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Authors: Kulwinder Singh Mann

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The innovative features of information system, known as Radiology Information System (RIS), for electronic medical records has shown a good impact in the hospital. The objective is to help and make their work easier; such as for a physician to access the patient’s data and for a patient to check their bill transparently. The interoperability of RIS with the other intra-hospital information systems it interacts with, dealing with the compatibility and open architecture issues, are accomplished by two novel mechanisms. The first one is the particular message handling system that is applied for the exchange of information, according to the Health Level Seven (HL7) protocol’s specifications and serves the transfer of medical and administrative data among the RIS applications and data store unit. The second one implements the translation of information between the formats that HL7 and Digital Imaging and Communication in Medicine (DICOM) protocols specify, providing the communication between RIS and Picture and Archive Communication System (PACS) which is used for the increasing incorporation of modern medical imaging equipment.

Keywords: RIS, PACS, HIS, HL7, DICOM, messaging service, interoperability, digital images

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Authors: Maria Hornell, Marcus Ohman

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Nature, and the society it is a part of, is under constant change. The landscape, climate and game populations vary over time, as well as society's priorities and the way it uses the land where wildlife may proliferate. Sweden currently has historically large wildlife populations which are a resource for the benefit and joy of many people. Wildlife may also be seen as a problem as it may cause damage in contradiction to other human interests. The Swedish Environmental Protection Agency introduces a new long-term strategy for national wildlife management. The strategy envisions a wildlife management in balance. It focuses on wildlife values in a broad sense including outdoor recreation and tourism as well as conservation of biodiversity. It is fundamental that these values should be open and accessible for the major part of the population. For that to be possible new ways to manage, mitigate and prevent damages and other problems that wildlife causes need to be developed. The strategy describes a roadmap for the development and strengthening of Sweden's wildlife management until 2020. It aims at being applicable for those authorities and stakeholders with interest in wildlife management being a guide for their own strategies, goals, and activities.

Keywords: wildlife management, strategy, Sweden, SEPA

Procedia PDF Downloads 220

Authors: Beatriz Cortés, Andrés Boza, David Pérez, Llanos Cuenca

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The Internet of Things (IoT) field is been applied in industries with different purposes. Sensing Enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the internet. These fields have come into focus recently on the enterprises and there is some evidence of the use and implications in supply chain management while finding it as an interesting aspect to work on. This paper presents a revision and proposals of IoT applications in supply chain management.

Keywords: industrial, internet of things, production systems, sensing enterprises, sensor, supply chain management

Procedia PDF Downloads 429

Authors: Fernando Miguel Campos, Carlos Ferreira, João Pestana, Pedro Campos, Nils Ehrenberg, Wojciech Hydzik

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The current trend of organizations offering their workers open-office spaces and co-working offices has been primed for stimulating teamwork and collaboration. However, this is not always valid as these kinds of spaces bring other types of challenges that compromise workers productivity and creativity. We present an approach for improving creativity and productivity at the workspace by redesigning an office chair that incorporates subtle technological elements that help users focus, relax and being more productive and creative. This sheds light on how we can better design interactive furniture for such popular contexts, as we develop this new chair through a multidisciplinary approach using ergonomics, interior design, interaction design, hardware and software engineering and psychology.

Keywords: creativity, co-working, ergonomics, human-computer interaction, interaction, interactive furniture, productivity

Procedia PDF Downloads 335

Authors: R. C. Sharma, Rishabh Bansal, Prajwal Menon, Manoj K. Sharma

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Silicon-air battery is highly promising for electric vehicles due to its high theoretical energy density (8470 Whkg⁻¹) and its discharge products are non-toxic. For the first time, pure silicon and germanium powders are used as anode material. Nickel wire meshes embedded with charcoal and manganese dioxide powder as cathode and concentrated potassium hydroxide is used as electrolyte. Voltage-time curves have been presented in this study for pure silicon and germanium powder and 5% and 10% germanium with silicon powder. Silicon powder cell assembly gives a stable voltage of 0.88 V for ~20 minutes while Si-Ge provides cell voltage of 0.80-0.76 V for ~10-12 minutes, and pure germanium cell provides cell voltage 0.80-0.76 V for ~30 minutes. The cell voltage is higher for concentrated (10%) sodium hydroxide solution (1.08 V) and it is stable for ~40 minutes. A sharp decrease in cell voltage beyond 40 min may be due to rapid corrosion.

Keywords: Silicon-air battery, Germanium-air battery, voltage-time curve, open circuit voltage, Anodic corrosion

Procedia PDF Downloads 241

Authors: Babagana Mohammed, Fidelis Patrick Afangide

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This research investigated the possibility of using waste low-dense polyethylene and waste plastic bottles for the production of interlock pavement blocks. In many parts of the world, interlock pavement block is used widely as modern day solution to outdoor flooring applications and the blocks have different shapes, sizes and colours suiting the imagination of landscape architects. Using suitable and conventional mould having a 220 x 135 x 50 mm³ shape, the interlock blocks were produced. The material constituents of the produced blocks were waste low-dense polyethylene and waste plastic bottles mixed in varying, respective percentage-weight proportions of; 100%+0%, 75%+25%, 50%+50% and 25%+75%. The blocks were then tested for unconfined compressive strength and water absorption properties. The test results compared well with those of conventional concrete interlock blocks and the research demonstrates the possibility of value recovery from the waste streams which are currently dumped in open-spaces thereby affecting the environment.

Keywords: pavement blocks, polyethylene, plastic bottle, wastes, valorization

Procedia PDF Downloads 407

Authors: Hazim Abdulsada

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The inspection of underneath vehicle system has been given significant attention by governments after the threat of terrorism become more prevalent. New technologies such as mobile robots and computer vision are led to have more secure environment. This paper proposed that a mobile robot like Aria robot can be used to search and inspect the bombs under parking a lot vehicle. This robot is using fuzzy logic and subsumption algorithms to control the robot that movies underneath the vehicle. An OpenCV library and laser Hokuyo are added to Aria robot to complete the experiment for under vehicle inspection. This experiment was conducted at the indoor environment to demonstrate the efficiency of our methods to search objects and control the robot movements under vehicle. We got excellent results not only by controlling the robot movement but also inspecting object by the robot camera at same time. This success allowed us to know the requirement to construct a new cost effective robot with more functionality.

Keywords: fuzzy logic, mobile robots, Opencv, subsumption, under vehicle inspection

Procedia PDF Downloads 477

Authors: Santos Andressa M. N.

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The research brings reflections on the importance of Instagram for the clothing trade, aiming to analyze the use of this social network as a sales tool by small companies in the fashion/clothing sector in Boqueirão-PI. Thus, field research was carried out, with the application of questionnaires, to raise and analyze data related to the topic. Thus, it is believed that Instagram positively influences the dissemination, visibility, reach and profitability of companies in Boqueirão do Piauí. The survey had a low number of companies due to the lack of availability of the owners during the COVID-19 pandemic.

Keywords: Instagram, sales, fashion, marketing

Procedia PDF Downloads 65

Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 657

Authors: Mohamed A. Baba, Gazy Rodowan, Brigita Abakevičienė, Sigitas Tamulevičius, Bartlomiej Lemieszek, Sebastian Molin, Tomas Tamulevičius

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Solid oxide fuel cells (SOFC) efficiently convert hydrogen to energy without producing any disturbances or contaminants. The core of the cell is electrolyte. For improving the performance of electrolyte-supported cells, it is desirable to extend the available exchange surface area by micro-structuring of the electrolyte with laser-based micromachining. This study investigated the electrochemical performance of cells micro machined using a femtosecond laser. Commercial ceramic SOFC (Elcogen, AS) with a total thickness of 400 μm was structured by 1030 nm wavelength Yb: KGW fs-laser Pharos (Light Conversion) using 100 kHz repetition frequency and 290 fs pulse length light by scanning with the galvanometer scanner (ScanLab) and focused with a f-Theta telecentric lens (SillOptics). The sample height was positioned using a motorized z-stage. The microstructures were formed using a laser spiral trepanning in Ni/YSZ anode supported membrane at the central part of the ceramic piece of 5.5 mm diameter at active area of the cell. All surface was drilled with 275 µm diameter holes spaced by 275 µm. The machining processes were carried out under ambient conditions. The microstructural effects of the femtosecond laser treatment on the electrolyte surface were investigated prior to the electrochemical characterisation using a scanning electron microscope (SEM) Quanta 200 FEG (FEI). The Novo control Alpha-A was used for electrochemical impedance spectroscopy on a symmetrical cell configuration with an excitation amplitude of 25 mV and a frequency range of 1 MHz to 0.1 Hz. The fuel cell characterization of the cell was examined on open flanges test setup by Fiaxell. Using nickel mesh on the anode side and au mesh on the cathode side, the cell was electrically linked. The cell was placed in a Kittec furnace with a Process IDentifier temperature controller. The wires were connected to a Solartron 1260/1287 frequency analyzer for the impedance and current-voltage characterization. In order to determine the impact of the anode's microstructure on the performance of the commercial cells, the acquired results were compared to cells with unstructured anode. Geometrical studies verified that the depth of the -holes increased linearly according to laser energy and scanning times. On the other hand, it reduced as the scanning speed increased. The electrochemical analysis demonstrates that the open circuit voltage OCV values of the two cells are equal. Further, the modified cell's initial slope reduces to 0.209 from 0.253 of the unmodified cell, revealing that the surface modification considerably decreases energy loss. Plus, the maximum power density for the cell with the microstructure and the reference cell respectively, are 1.45 and 1.16 Wcm⁻².

Keywords: electrochemical performance, electrolyte-supported cells, laser micro-structuring, solid oxide fuel cells

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: Linda Smail, Zineb Azouz

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Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution P(S) where S is a subset of I. The general idea is to write the expression of P(S) in the form of a product of factors where each factor is easy to compute. More importantly, it will be very useful to give an interpretation of each of the factors in terms of conditional probabilities. This paper considers a semantic interpretation of the factors involved in computing marginal probabilities in Bayesian networks. Establishing such a semantic interpretations is indeed interesting and relevant in the case of large Bayesian networks.

Keywords: Bayesian networks, D-Separation, level two Bayesian networks, factorization of computation

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Authors: Jandot Aurélia

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As the nuclear power is a sensitive field leading to controversy, the quality of the communication about it is important. Between 1965 and 1981, in France, this one had gradually changed. This change is studied here in the main French news magazine L’Express, in connection with several parameters. As this represents a huge number of copies and occurrences, thus a considerable amount of information; this paper is focused on the main articles as well as the main “mental images”. These ones are important, as their aim is to direct the thought of the readers, and as they have led the public awareness to evolve. Over this 17 years, two trends are in confrontation: The first one is promoting the perception of the nuclear power, while the second one is discrediting it. These trends are organized in two axes: the evolution of engineering, and the risks. In both cases, the changes in the language allow discerning the deepest intentions of the magazine editing, over a period when the nuclear technology, to there a laboratory object accompanied with mystery and secret, has become a social issue seemingly open to all.

Keywords: French news magazine, mental images, nuclear power, public awareness

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Juan Ignacio Arango, Andres Diaz, Giacomo Barbieri

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In soilless culture, the definition of efficient fertigation strategies is fundamental for the growth of crops. Flexible test-benches able to independently manage groups of crops are key for investigating efficient fertigation practices through experimentation. These test-benches must be able to provide nutrient solution (NS) in a precise, uniform and repeatable way in order to effectively implement and compare different fertigation strategies. This article describes a distribution module for investigating fertigation practices able to control the fertigation dose and frequency. The proposed solution is characterized in terms of precision, uniformity and repeatability since these parameters are fundamental in the implementation of effective experiments for the investigation of fertigation practices. After a calibration process, the implemented system reaches a precision of 1mL, a uniformity of 98.5% at a total cost of 735USD.

Keywords: recision horticulture, test-bench, fertigation strategy, automation, flexibility

Procedia PDF Downloads 143

Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

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Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: additive manufacturing, decision-makings, environmental impact, predictive models

Procedia PDF Downloads 137

Authors: R. Loukil, M. Chtourou, T. Damak

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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

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Authors: Desmond Young

Abstract:

In building services electrical design, a key element of any project will be assessing the electrical load requirements. This needs to be done early in the design process to allow the selection of infrastructure that would be required to meet the electrical needs of the type of building. The type of building will define the type of assessment made, and the values applied in defining the maximum demand for the building, and ultimately the size of supply or infrastructure required, and the application that needs to be made to the distribution network operator, or alternatively to an independent network operator. The fact that this assessment needs to be undertaken early in the design process provides limits on the type of assessment that can be used, as different methods require different types of information, and sometimes this information is not available until the latter stages of a project. A common method applied in the earlier design stages of a project, typically during stages 1,2 & 3, is the use of benchmarks. It is a possibility that some of the benchmarks applied are excessive in relation to the current loads that exist in a modern installation. This lack of accuracy is based on information which does not correspond to the actual equipment loads that are used. This includes lighting and small power loads, where the use of more efficient equipment and lighting has reduced the maximum demand required. The electrical load can be used as part of the process to assess the heat generated from the equipment, with the heat gains from other sources, this feeds into the sizing of the infrastructure required to cool the building. Any overestimation of the loads would contribute to the increase in the design load for the heating and ventilation systems. Finally, with the new policies driving the industry to decarbonise buildings, a prime example being the recently introduced London Plan, loads are potentially going to increase. In addition, with the advent of the pandemic and changes to working practices, and the adoption of electric heating and vehicles, a better understanding of the loads that should be applied will aid in ensuring that infrastructure is not oversized, as a cost to the client, or undersized to the detriment of the building. In addition, more accurate benchmarks and methods will allow assessments to be made for the incorporation of energy storage and renewable technologies as these technologies become more common in buildings new or refurbished.

Keywords: energy, ADMD, electrical load assessment, energy benchmarks

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

Abstract:

In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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