Search results for: RLS identification algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6294

Search results for: RLS identification algorithm

3204 Product Design and Development of Wearable Assistant Device

Authors: Hao-Jun Hong, Jung-Tang Huang

Abstract:

The world is gradually becoming an aging society, and with the lack of laboring forces, this phenomenon is affecting the nation’s economy growth. Although nursing centers are booming in recent years, the lack of medical resources are yet to be resolved, thus creating an innovative wearable medical device could be a vital solution. This research is focused on the design and development of a wearable device which obtains a more precise heart failure measurement than products on the market. The method used by the device is based on the sensor fusion and big data algorithm. From the test result, the modified structure of wearable device can significantly decrease the MA (Motion Artifact) and provide users a more cozy and accurate physical monitor experience.

Keywords: big data, heart failure, motion artifact, sensor fusion, wearable medical device

Procedia PDF Downloads 348
3203 Programmed Speech to Text Summarization Using Graph-Based Algorithm

Authors: Hamsini Pulugurtha, P. V. S. L. Jagadamba

Abstract:

Programmed Speech to Text and Text Summarization Using Graph-based Algorithms can be utilized in gatherings to get the short depiction of the gathering for future reference. This gives signature check utilizing Siamese neural organization to confirm the personality of the client and convert the client gave sound record which is in English into English text utilizing the discourse acknowledgment bundle given in python. At times just the outline of the gathering is required, the answer for this text rundown. Thus, the record is then summed up utilizing the regular language preparing approaches, for example, solo extractive text outline calculations

Keywords: Siamese neural network, English speech, English text, natural language processing, unsupervised extractive text summarization

Procedia PDF Downloads 212
3202 Low-Level Forced and Ambient Vibration Tests on URM Building Strengthened by Dampers

Authors: Rafik Taleb, Farid Bouriche, Mehdi Boukri, Fouad Kehila

Abstract:

The aim of the paper is to investigate the dynamic behavior of an unreinforced masonry (URM) building strengthened by DC-90 dampers by ambient and low-level forced vibration tests. Ambient and forced vibration techniques are usually applied to reinforced concrete or steel buildings to understand and identify their dynamic behavior, however, less is known about their applicability for masonry buildings. Ambient vibrations were measured before and after strengthening of the URM building by DC-90 dampers system. For forced vibration test, a series of low amplitude steady state harmonic forced vibration tests were conducted after strengthening using eccentric mass shaker. The resonant frequency curves, mode shapes and damping coefficients as well as stress distribution in the steel braces of the DC-90 dampers have been investigated and could be defined. It was shown that the dynamic behavior of the masonry building, even if not regular and with deformable floors, can be effectively represented. It can be concluded that the strengthening of the building does not change the dynamic properties of the building due to the fact of low amplitude excitation which do not activate the dampers.

Keywords: ambient vibrations, masonry buildings, forced vibrations, structural dynamic identification

Procedia PDF Downloads 405
3201 Quantifying Multivariate Spatiotemporal Dynamics of Malaria Risk Using Graph-Based Optimization in Southern Ethiopia

Authors: Yonas Shuke Kitawa

Abstract:

Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

Procedia PDF Downloads 74
3200 Investigation of Utilizing L-Band Horn Antenna in Landmine Detection

Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

Abstract:

Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: full wave analysis, ground penetrating radar, horn antenna design, landmine detection

Procedia PDF Downloads 214
3199 Global Race for Talent: Exploring Global Talent Management (GTM) and its Impact on Organizational Development: From the Prospective of Malaysian MNEs

Authors: Asma Moomal, Zukarnain Zakaria

Abstract:

In this uncertain, highly competitive and hasty moving era, most of the organizations are surviving under the pressure of complex dynamics, fierce competition and many challenges in terms of global talent management within the global market. One key result of these challenges is that the organizations have to be organized and good at handling human capital if they want to gain sustainable and steady success in near future. By keeping in mind the importance of global competition, many human resource (HR) professionals are diagnosing the complexities in managing talent of human capital at global level, especially those of multinational enterprises (MNEs). As, there has been little research in the country regarding identification of the GTM in MNEs, this paper reviewed the relevant literature in order to examine the role of GTM strategies in enhancing the organizational development in the MNEs of Malaysia. The data collection technique used in this study was done through the secondary data resources (i.e. the existing literature analysis). This study contributes to extend our understanding of the impact of GTM on organizational development of MNEs within the country.

Keywords: Global Talent Management (GTM), multinational enterprises (MNEs), organizational development, talent

Procedia PDF Downloads 436
3198 Biologically Inspired Small Infrared Target Detection Using Local Contrast Mechanisms

Authors: Tian Xia, Yuan Yan Tang

Abstract:

In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

Procedia PDF Downloads 463
3197 Reproductive Behavior of Caspian Red Deer (Cervus Elaphus Maral) in Wildlife Refuge of Semeskande, Sari

Authors: Behrang Ekrami, Amin Tamadon

Abstract:

Caspian red deer or maral (Cervus elaphus maral) is a ruminant from the family of Cervidae. Maintenance and protection of maral requires knowing the behavioral, physiological, environmental characteristics and factors harmful to this species. In this article, reproductive and behavioral traits of this species in both sexes are presented based on observations and the available records of protected deer in Wildlife Refuge of Semeskande, Sari (one of the sites that preserve the maral in the Free Zones of Hyrcanian forest) from 2006 to 2011. Hart characteristics including sexual behavior, apparent changes during reproductive season and reproductive physiology; and hind characteristics including of ovulation, reproductive cycle, mating, pregnancy and parturition, have been evaluated. Identification of maral reproductive characteristics in Wildlife Refuge of Semeskande, Sari is one of the most important information requirements to preserve and breed this species and will open up new routes for performing new methods of reproduction of this species in Iran wildlife parks or other refuge areas.

Keywords: caspian red deer, reproduction, behavior, Iran

Procedia PDF Downloads 478
3196 Compatibility of Disabilities for a Single Workplace through Mobile Technology: A Case Study in Brazilian Industries

Authors: Felyppe Blum Goncalves, Juliana Sebastiany

Abstract:

In line with Brazilian legislation on the inclusion of persons with disabilities in the world of work, known as the 'quota law' (Law 8213/91) and in accordance with the prerogatives of the United Nations Convention on Human Rights of people with disabilities, which was ratified by Brazil through Federal Decree No. 6.949 of August 25, 2009, the SESI National Department, through Working Groups, structured the product Affordable Industry. This methodology aims to prepare the industries for the adequate process of inclusion of people with disabilities, as well as the development of an organizational culture that values and respects human diversity. All industries in Brazil with 100 or more employees must comply with current legislation, but due to the lack of information and guidance on the subject, they end up having difficulties in this process. The methodology brings solutions for companies through the professional qualification of the disabled person, preparation of managers, training of human resources teams and employees. It also advocates the survey of the architectural accessibility of the factory and the identification of the possibilities of inclusion of people with disabilities, through the compatibility between work and job requirements, preserving safety, health, and quality of life.

Keywords: inclusion, app, disability, management

Procedia PDF Downloads 162
3195 Design of Reconfigurable Fixed-Point LMS Adaptive FIR Filter

Authors: S. Padmapriya, V. Lakshmi Prabha

Abstract:

In this paper, an efficient reconfigurable fixed-point Least Mean Square Adaptive FIR filter is proposed. The proposed architecture has two methods of operation: one is area efficient design and the other is optimized power. Pipelining of the adder blocks and partial product generator are used to achieve low area and reversible logic is used to obtain low power design. Depending upon the input samples and filter coefficients, one of the techniques is chosen. Least-Mean-Square adaptation is performed to update the weights. The architecture is coded using Verilog and synthesized in cadence encounter 0.18μm technology. The synthesized results show that the area reduction ratio of the proposed when compared with conventional technique is about 1.2%.

Keywords: adaptive filter, carry select adder, least mean square algorithm, reversible logic

Procedia PDF Downloads 324
3194 Feasibility Study of Distributed Lightless Intersection Control with Level 1 Autonomous Vehicles

Authors: Bo Yang, Christopher Monterola

Abstract:

Urban intersection control without the use of the traffic light has the potential to vastly improve the efficiency of the urban traffic flow. For most proposals in the literature, such lightless intersection control depends on the mass market commercialization of highly intelligent autonomous vehicles (AV), which limits the prospects of near future implementation. We present an efficient lightless intersection traffic control scheme that only requires Level 1 AV as defined by NHTSA. The technological barriers of such lightless intersection control are thus very low. Our algorithm can also accommodate a mixture of AVs and conventional vehicles. We also carry out large scale numerical analysis to illustrate the feasibility, safety and robustness, comfort level, and control efficiency of our intersection control scheme.

Keywords: intersection control, autonomous vehicles, traffic modelling, intelligent transport system

Procedia PDF Downloads 453
3193 A Multiobjective Damping Function for Coordinated Control of Power System Stabilizer and Power Oscillation Damping

Authors: Jose D. Herrera, Mario A. Rios

Abstract:

This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

Procedia PDF Downloads 587
3192 Hand Motion Trajectory Analysis for Dynamic Hand Gestures Used in Indian Sign Language

Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

Abstract:

Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

Procedia PDF Downloads 364
3191 Tongue Image Retrieval Based Using Machine Learning

Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

Abstract:

In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

Procedia PDF Downloads 73
3190 EhfadHaya (SaveLife) / AateHayah (GiveLife) Blood Donor Website

Authors: Sameer Muhammad Aslam, Nura Said Mohsin Al-Saifi

Abstract:

This research shows the process of creating a blood donation website for Oman. Blood donation is a widespread, crucial, ongoing process, so it is important that this website is easy to use. Several automated blood management systems are available, but none provides an effective algorithm that takes into account variables such as frequency of donation, donation date, and gender. In Oman, the Ministry of Health maintains a blood bank and keeps donors informed about the need for blood through a website. They also inform donors and the wider public where and when is their next blood donation event. The website's main goals are to educate the community about the benefits of blood donation. It also manages donor and receiver documentation and encourages voluntary blood donation by providing easy access to information about blood types and blood distribution in various hospitals in Oman, based on hospital needs.

Keywords: Oman, blood bank, blood donors, donor website

Procedia PDF Downloads 213
3189 Isogeometric Topology Optimization in Cracked Structures Design

Authors: Dongkyu Lee, Thanh Banh Thien, Soomi Shin

Abstract:

In the present study, the isogeometric topology optimization is proposed for cracked structures through using Solid Isotropic Material with Penalization (SIMP) as a design model. Design density variables defined in the variable space are used to approximate the element analysis density by the bivariate B-spline basis functions. The mathematical formulation of topology optimization problem solving minimum structural compliance is an alternating active-phase algorithm with the Gauss-Seidel version as an optimization model of optimality criteria. Stiffness and adjoint sensitivity formulations linked to strain energy of cracked structure are proposed in terms of design density variables. Numerical examples demonstrate interactions of topology optimization to structures design with cracks.

Keywords: topology optimization, isogeometric, NURBS, design

Procedia PDF Downloads 488
3188 DGA Data Interpretation Using Extension Theory for Power Transformer Diagnostics

Authors: O. P. Rahi, Manoj Kumar

Abstract:

Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

Procedia PDF Downloads 408
3187 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems

Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

Abstract:

The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes

Procedia PDF Downloads 599
3186 Optimal Injected Current Control for Shunt Active Power Filter Using Artificial Intelligence

Authors: Brahim Berbaoui

Abstract:

In this paper, a new particle swarm optimization (PSO) based method is proposed for the implantation of optimal harmonic power flow in power systems. In this algorithm approach, proportional integral controller for reference compensating currents of active power filter is performed in order to minimize the total harmonic distortion (THD). The simulation results show that the new control method using PSO approach is not only easy to be implanted, but also very effective in reducing the unwanted harmonics and compensating reactive power. The studies carried out have been accomplished using the MATLAB Simulink Power System Toolbox.

Keywords: shunt active power filter, power quality, current control, proportional integral controller, particle swarm optimization

Procedia PDF Downloads 610
3185 Analysis of Nonlinear and Non-Stationary Signal to Extract the Features Using Hilbert Huang Transform

Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

Abstract:

It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

Procedia PDF Downloads 575
3184 Drug-Drug Interaction Prediction in Diabetes Mellitus

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

Procedia PDF Downloads 97
3183 How Does the Interaction between Environmental and Intellectual Property Rights Affect Environmental Innovation? A Study of Seven OECD Countries

Authors: Aneeq Sarwar

Abstract:

This study assesses the interaction between environmental and intellectual property policy on the rate of invention of environmental inventions and specifically tests for whether there is a synergy between stricter IP regimes and stronger environmental policies. The empirical analysis uses firm and industry-level data from seven OECD countries from 2009 to 2015. We also introduce a new measure of environmental inventions using a Natural Language Processing Topic Modelling technique. We find that intellectual property policy strictness demonstrates greater effectiveness in encouraging inventiveness in environmental inventions when used in combination with stronger environmental policies. This study contributes to existing literature in two ways. First, it devises a method for better identification of environmental technologies, we demonstrate how our method is more comprehensive than existing methods as we are better able to identify not only environmental inventions, but also major components of said inventions. Second, we test how various policy regimes affect the development of environmental technologies, we are the first study to examine the interaction of the environmental and intellectual property policy on firm level innovation.

Keywords: environmental economics, economics of innovation, environmental policy, firm level

Procedia PDF Downloads 149
3182 The Benefits of Mountain Climbing in the Physical Well-Being of Young People

Authors: Zylfi Shehu, Rozeta Shatku

Abstract:

The aim of this study is the identification of the goods and the consequences it brings up the mountain climbing to the youth, how mountain climbing influences in physical activity and the health of young people. Taken to study 37 young people aged 18-30 years, 25 males and 12 females. The selection was made at random and voluntary. Subjects were not professionals but amateurs climbing in the mountain. They were informed and instructed for the test to be carried out. The ascent was made in January 2016 in the Mount of Gjallica in Kukës, Albania, the height of the mountain is 2489 m above sea level. Backpack for each subject weighing 32 kg. Time of ascent, attitude and descent was 6 days. In 22 males, 2 of them did not afford the ascent on the first day and went back. Of the 12 women, 5 of them withdrew on the first day. During the descent on day six, 20 males 7 of them had minor injuries, three with serious injuries. While a total of 7 women, 4 of them had minor injuries and one with serious injuries. Most of the men and women who deal with physical activity throughout life faced the light and were not injured, and the rest that were not dealt with physical activity were more injured. Lack of experience and knowledge was one of the causes of injuries. The subjects had anxiety all the time, uncertainty and fear of avalanches of snow and difficult terrain.

Keywords: climbing, physical activity, young people

Procedia PDF Downloads 339
3181 Impairments Correction of Six-Port Based Millimeter-Wave Radar

Authors: Dan Ohev Zion, Alon Cohen

Abstract:

In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.

Keywords: radar, FMCW Radar, IQ mismatch, six port

Procedia PDF Downloads 149
3180 New Gas Geothermometers for the Prediction of Subsurface Geothermal Temperatures: An Optimized Application of Artificial Neural Networks and Geochemometric Analysis

Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

Abstract:

Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

Procedia PDF Downloads 346
3179 Analysis of Trends in Equity of Maternal Health Care in South India

Authors: Anushree S. Panikkassery

Abstract:

The paper analyses the pattern and trend of maternal health care in south Indian states. It studies the interstate disparities in terms of maternal health care. It also compares the trends in terms of achieving the target of sustainable development Goal is related to maternal health. The maternal health care (MHC) development is one of the key indicators for the development of health sector in the country and assumes significance from the socioeconomic and developmental perspectives. Maternal health care mainly consists of composite care during pregnancy, child birth as well as postpartum period. Antenatal care, identification, referral and management of high risk pregnancies, safe and healthy child birth and early postnatal care are some of the important issues pertaining to maternal health. Data is collected from national family health survey 1992-93, 1998-99, 2005-06, and 2015-16. A concentration index is used to study the disparities in equity of maternal health among south Indian states. The study shows that there has been an improvement in maternal health care in south Indian states with Kerala topping among the states. But there exist disparities among the south Indian states.

Keywords: antenatal care, disparities, equity, maternal health

Procedia PDF Downloads 382
3178 Walkability and Urban Social Identity

Authors: Reihaneh Rafiemanzelat

Abstract:

One of the most recent fields of investigation in urban issues focuses on the walkability in urban spaces. The paper aims to establish the theoretical relationship between the people's link with definite urban public spaces and the social identity processes derived from the relation with these places. The theoretical aspects which are examined for this purpose are: the concept of walkability and its developments and the social identity theories derived from walkable spaces. In fact, the paper presents the main results obtained from an empirical investigation which concern to the genesis of urban social identity in particular street as one of the main elements of public spaces in cities. İsmet İnönü Blvd which known as Salamis Street in Famagusta, North Cyprus is one of the main street in city whit high level of physical and social activities all the time. The urban social identity of users was analyzed, focusing on three main factors: walkability of space, social identification, and image of the space. These three factors were analyzed in relation to a series of items in the initial questionnaire, evaluation of existing natural resources, and environmental attitudes.

Keywords: walkability, urban public space, pedestrian, social activity, social identity

Procedia PDF Downloads 428
3177 Phage Therapy of Staphylococcal Pyoderma in Dogs

Authors: Jiri Nepereny, Vladimir Vrzal

Abstract:

Staphylococcus intermedius/pseudintermedius bacteria are commonly found on the skin of healthy dogs and can cause pruritic skin diseases under certain circumstances (trauma, allergy, immunodeficiency, ectoparasitosis, endocrinological diseases, glucocorticoid therapy, etc.). These can develop into complicated superficial or deep pyoderma, which represent a large group of problematic skin diseases in dogs. These are predominantly inflammations of a secondary nature, associated with the occurrence of coagulase-positive Staphylococcus spp. A major problem is increased itching, which greatly complicates the healing process. The aim of this work is to verify the efficacy of the developed preparation Bacteriophage SI (Staphylococcus intermedius). The tested preparation contains a lysate of bacterial cells of S. intermedius host culture including culture medium and live virions of specific phage. Sodium Merthiolate is added as a preservative in a safe concentration. Validation of the efficacy of the product was demonstrated by monitoring the therapeutic effect after application to indicated cases from clinical practice. The indication for inclusion of the patient into the trial was an adequate history and clinical examination accompanied by sample collection for bacteriological examination and isolation of the specific causative agent. Isolate identification was performed by API BioMérieux identification system (API ID 32 STAPH) and rep-PCR typing. The suitability of therapy for a specific case was confirmed by in vitro testing of the lytic ability of the bacteriophage to lyse the specific isolate = formation of specific plaques on the culture isolate on the surface of the solid culture medium. So far, a total of 32 dogs of different sexes, ages and breed affiliations with different symptoms of staphylococcal dermatitis have been included in the testing. Their previous therapy consisted of more or less successful systemic or local application of broad-spectrum antibiotics. The presence of S. intermedius/pseudintermedius has been demonstrated in 26 cases. The isolates were identified as a S. pseudintermedius, in all cases. Contaminant bacterial microflora was always present in the examined samples. The test product was applied subcutaneously in gradually increasing doses over a period of 1 month. After improvement in health status, maintenance therapy was followed by application of the product once a week for 3 months. Adverse effects associated with the administration of the product (swelling at the site of application) occurred in only 2 cases. In all cases, there was a significant reduction in clinical signs (healing of skin lesions and reduction of inflammation) after therapy and an improvement in the well-being of the treated animals. A major problem in the treatment of pyoderma is the frequent resistance of the causative agents to antibiotics, especially the increasing frequency of multidrug-resistant and methicillin-resistant S. pseudintermedius (MRSP) strains. Specific phagolysate using for the therapy of these diseases could solve this problem and to some extent replace or reduce the use of antibiotics, whose frequent and widespread application often leads to the emergence of resistance. The advantage of the therapeutic use of bacteriophages is their bactericidal effect, high specificity and safety. This work was supported by Project FV40213 from Ministry of Industry and Trade, Czech Republic.

Keywords: bacteriophage, pyoderma, staphylococcus spp, therapy

Procedia PDF Downloads 168
3176 Automatic Moment-Based Texture Segmentation

Authors: Tudor Barbu

Abstract:

An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

Procedia PDF Downloads 413
3175 Innovation and Technologies Synthesis of Various Components: A Contribution to the New Precision Irrigation Development for Open-Field Fruit Orchards

Authors: Pipop Chatrabhuti, S. Visessri, T. Charinpanitkul

Abstract:

Precision irrigation (PI) technology has emerged as a solution to optimize water usage in agriculture, aiming to maximize crop yields while minimizing water waste. Developing a new PI for commercialization requires developers to research, synthesize, evaluate, and select appropriate technologies and make use of such information to produce innovative products. The objective of this review is to facilitate innovators by providing them with a summary of existing knowledge and the identification of gaps in research linking to the innovative development of PI. This paper reviews and synthesizes technologies and components relevant to precision irrigation, highlighting its potential benefits and challenges. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework is used for the review. The study is intended to contribute to innovators who apply for collaborative approach to problem-solving and idea generation that involves seeking external input and resources from a diverse range of individuals and organizations.

Keywords: innovation synthesis, technology assessment, precision irrigation technologies, precision irrigation components, new product development

Procedia PDF Downloads 61