Search results for: artificial neural networks; crop water stress index; canopy temperature
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24729

Search results for: artificial neural networks; crop water stress index; canopy temperature

22959 A Comparative Study to Employees' Work Stress of the Casino Hotels and Non-Casino Hotels

Authors: Xiaohong Wu, Tao Zhang

Abstract:

Since Macau opened its door to international gambling firms in 2002, Macau casino hotel industry has been booming. Casino hotels are different from the non-casino hotels in the main profit source and services. The paper aims to analyze differences in employees’ work stress and job satisfaction across the casino hotels and the non-casino hotels. Through questionnaires, the paper investigates 200 employees from casino hotels and 200 employees from non-casino hotels. Work stress and job satisfaction of employees in casino hotels and non-casino hotels are compared. Statistic techniques such as descriptive statistics and one-way analysis of variance (one-way ANOVA) are applied. The paper tries to achieve the below aims: Firstly, explore and compare the impact of gender, job position, marital status and fertility status on employees’ work stress and job satisfaction. Secondly, explore the perception of work stress and job satisfaction across casino hotel and non-casino hotel employees. Thirdly, explore the relationship between work stress and job satisfaction. The result indicates there are not significant differences in employees’ work stress and job satisfaction perception between different genders, positions, marital situations and fertility situations. The result confirms there are significant differences in employees’ work stress and job satisfaction perception between casino and non-casino employees. Moreover, Work stress negatively influences job satisfaction.

Keywords: casino, employee, job satisfaction, work stress

Procedia PDF Downloads 317
22958 Hydroinformatics of Smart Cities: Real-Time Water Quality Prediction Model Using a Hybrid Approach

Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

Abstract:

Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 187
22957 Evaluation of Geomechanical and Geometrical Parameters’ Effects on Hydro-Mechanical Estimation of Water Inflow into Underground Excavations

Authors: M. Mazraehli, F. Mehrabani, S. Zare

Abstract:

In general, mechanical and hydraulic processes are not independent of each other in jointed rock masses. Therefore, the study on hydro-mechanical coupling of geomaterials should be a center of attention in rock mechanics. Rocks in their nature contain discontinuities whose presence extremely influences mechanical and hydraulic characteristics of the medium. Assuming this effect, experimental investigations on intact rock cannot help to identify jointed rock mass behavior. Hence, numerical methods are being used for this purpose. In this paper, water inflow into a tunnel under significant water table has been estimated using hydro-mechanical discrete element method (HM-DEM). Besides, effects of geomechanical and geometrical parameters including constitutive model, friction angle, joint spacing, dip of joint sets, and stress factor on the estimated inflow rate have been studied. Results demonstrate that inflow rates are not identical for different constitutive models. Also, inflow rate reduces with increased spacing and stress factor.

Keywords: distinct element method, fluid flow, hydro-mechanical coupling, jointed rock mass, underground excavations

Procedia PDF Downloads 166
22956 The Urban Stray Animal Identification Management System Based on YOLOv5

Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

Abstract:

Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

Procedia PDF Downloads 99
22955 A Hybrid Simulation Approach to Evaluate Cooling Energy Consumption for Public Housings of Subtropics

Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

Abstract:

Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

Procedia PDF Downloads 168
22954 Modelling the Yield Stress of Magnetorheological Fluids

Authors: Hesam Khajehsaeid, Naeimeh Alagheband

Abstract:

Magnetorheological fluids (MRF) are a category of smart materials. They exhibit a reversible change from a Newtonian-like fluid to a semi-solid state upon application of an external magnetic field. In contrast to ordinary fluids, MRFs can tolerate shear stresses up to a threshold value called yield stress which strongly depends on the strength of the magnetic field, magnetic particles volume fraction and temperature. Even beyond the yield, a magnetic field can increase MR fluid viscosity up to several orders. As yield stress is an important parameter in the design of MR devices, in this work, the effects of magnetic field intensity and magnetic particle concentration on the yield stress of MRFs are investigated. Four MRF samples with different particle concentrations are developed and tested through flow-ramp analysis to obtain the flow curves at a range of magnetic field intensity as well as shear rate. The viscosity of the fluids is determined by means of the flow curves. The results are then used to determine the yield stresses by means of the steady stress sweep method. The yield stresses are then determined by means of a modified form of the dipole model as well as empirical models. The exponential distribution function is used to describe the orientation of particle chains in the dipole model under the action of the external magnetic field. Moreover, the modified dipole model results in a reasonable distribution of chains compared to previous similar models.

Keywords: magnetorheological fluids, yield stress, particles concentration, dipole model

Procedia PDF Downloads 179
22953 Comparative Study of Medical and Fine Art Students on the Level of Perceived Stress and Coping Skills

Authors: Bushra Mussawar, Saleha Younus

Abstract:

Students often view their academic life demanding and stressful. However, apart from academics, stress springs from various other sources namely, finance, family, health, friends etc. The present study aims to assess the level of perceived stress in medical and fine arts students, and to determine the coping strategies used by the students to mitigate stress. The sample of the study consisted of 178 medical and fine arts students. The sample was selected through purposive sampling. Pearson correlation coefficient and T-test were used to analyze data. Results of the study revealed that there exists a positive relationship between perceived stress and coping strategies. Additionally, the two groups showed marked differences in terms of stress perception and coping styles. The level of perceived stress was found to be high in medical students nonetheless, they employed more positive coping strategies than fine arts students who scored high on negative coping strategies which are deleterious to the overall wellbeing.

Keywords: perceived stress, coping strategies, medical, fine arts students

Procedia PDF Downloads 307
22952 Stress and Social Support as Predictors of Quality of Life: A Case among Flood Victims in Malaysia

Authors: Najib Ahmad Marzuki, Che Su Mustaffa, Johana Johari, Nur Haffiza Rahaman

Abstract:

The purpose of this paper is to examine the effects and relationship of stress and social support towards the quality of life among flood victims in Malaysia. A total of 764 respondents took part in the survey via random sampling. The depression, anxiety, and stress scales were utilized to measure stress while The Multidimensional Scale of Perceived Social Support was used to measure the quality of life. The findings of this study indicate that there were significant correlations between variables in the study. The findings show a significant negative relation between stress and quality of life, and significant positive correlations between support from family as well as support from friends with the quality of life. Stress and support from family were found to be significant predictors and influences the quality of life among flood victims.

Keywords: stress, social support, quality of life, flood victims

Procedia PDF Downloads 557
22951 Quasi-Photon Monte Carlo on Radiative Heat Transfer: An Importance Sampling and Learning Approach

Authors: Utkarsh A. Mishra, Ankit Bansal

Abstract:

At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 223
22950 Understanding Surface Failures in Thick Asphalt Pavement: A 3-D Finite Element Model Analysis

Authors: Hana Gebremariam Liliso

Abstract:

This study investigates the factors contributing to the deterioration of thick asphalt pavements, such as rutting and cracking. We focus on the combined influence of traffic loads and pavement structure. This study uses a three-dimensional finite element model with a Mohr-Coulomb failure criterion to analyze the stress levels near the pavement's surface under realistic conditions. Our model considers various factors, including tire-pavement contact stresses, asphalt properties, moving loads, and dynamic analysis. This research suggests that cracking tends to occur between dual tires. Some key discoveries include the risk of cracking increases as temperatures rise; surface cracking at high temperatures is associated with distortional deformation; using a uniform contact stress distribution underestimates the risk of failure compared to realistic three-dimensional tire contact stress, particularly at high temperatures; the risk of failure is higher near the surface when there is a negative temperature gradient in the asphalt layer; and debonding beneath the surface layer leads to increased shear stress and premature failure around the interface.

Keywords: asphalt pavement, surface failure, 3d finite element model, multiaxial stress states, Mohr-Coulomb failure criterion

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22949 A Study on Numerical Modelling of Rigid Pavement: Temperature and Thickness Effect

Authors: Amin Chegenizadeh, Mahdi Keramatikerman, Hamid Nikraz

Abstract:

Pavement engineering plays a significant role to develop cost effective and efficient highway and road networks. In general, pavement regarding structure is categorized in two core group namely flexible and rigid pavements. There are various benefits in application of rigid pavement. For instance, they have a longer life and lower maintenance costs in compare with the flexible pavement. In rigid pavement designs, temperature and thickness are two effective parameters that could widely affect the total cost of the project. In this study, a numerical modeling using Kenpave-Kenslab was performed to investigate the effect of these two important parameters in the rigid pavement.   

Keywords: rigid pavement, Kenpave, Kenslab, thickness, temperature

Procedia PDF Downloads 372
22948 6G: Emerging Architectures, Technologies and Challenges

Authors: Abdulrahman Yarali

Abstract:

The advancement of technology never stops because the demands for improved internet and communication connectivity are increasing. Just as 5G networks are rolling out, the world has begun to talk about the sixth-generation networks (6G). The semantics of 6G are more or less the same as 5G networks because they strive to boost speeds, machine-to-machine (M2M) communication, and latency reduction. However, some of the distinctive focuses of 6G include the optimization of networks of machines through super speeds and innovative features. This paper discusses many aspects of the technologies, architectures, challenges, and opportunities of 6G wireless communication systems.

Keywords: 6G, characteristics, infrastructures, technologies, AI, ML, IoT, applications

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22947 Improved Multi-Channel Separation Algorithm for Satellite-Based Automatic Identification System Signals Based on Artificial Bee Colony and Adaptive Moment Estimation

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

Abstract:

The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

Procedia PDF Downloads 186
22946 Improve of Power Quality in Electrical Network Using STATCOM

Authors: A. R. Alesaadi

Abstract:

Flexible AC transmission system (FACTS) devices have an important rule on expended electrical transmission networks. These devices can provide control of one or more AC transmission system parameters to enhance controllability and increase power transfer capability. In this paper the effect of these devices on reliability of electrical networks is studied and it is shown that using of FACTS devices can improve the reliability of power networks and power quality in electrical networks, significantly.

Keywords: FACTS devices, power networks, power quality, STATCOM

Procedia PDF Downloads 668
22945 Lung HRCT Pattern Classification for Cystic Fibrosis Using a Convolutional Neural Network

Authors: Parisa Mansour

Abstract:

Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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22944 Ripening Conditions Suitable for Marketing of Winter Squash ‘Bochang’

Authors: Do Su Park, Sang Jun Park, Cheon Soon Jeong

Abstract:

This study was performed in order to investigate the optimum ripening conditions for the marketing of Squash. Research sample 'Bochang' was grown at Hongcheonin in Gangwon province in August 2014. Ripening the samples were stored under the conditions of 25℃, 30℃, and 35℃ with the humidity RH70 ± 5%. They were checked every 3 days for 21 days. The respiration rate, water loss, hardness, coloration, the contents of soluble solids, starch, total sugar were evaluated after storage. Respiration rate was reduced in all treatments with longer storage period. Water loss was increased in the higher temperature. The 13% water loss was found at 35℃ on 21st storage day. The store initially 25℃ and 30℃ Hardness 47N and the ripening 21 days decreased slightly. On the other hand, in the case of 35℃ showed a large reduction than 25℃ and 30℃. Soluble solid contents were increased with longer ripening period. 30℃ and 35℃ was highest ripening 15 days. In the case of 25℃, it was highest on 21th day. The higher the temperature, the higher the soluble solids content are. 25℃ and 30℃ Coloration was increased rapidly until the ripening 12 days. In case of 35℃, continued increase up to 21 days. 25℃ and 30℃ showed no differences. Meanwhile, in case of 35℃, appearance quality was reduced in Occurrence of yellowing phenomenon of pericarp occurs from after ripening for 9 days. The coloration of fruit flesh is increase until after ripening for 9 days and decrease from after ripening for 9 days. There was no significant difference depending on the conditions of temperature. The higher the temperature, the lower the content of the starch. In case of 30℃ and 35℃, was reduced with longer storage period. 25℃ was minimal content change. Total sugar was increased in all treatments with longer storage period. The higher the temperature, the higher the amount of total sugar content is. Therefore, at 25℃ for 18-21 days and at 30℃ for 12-15 days is suitable for ripening.

Keywords: marketing, ripening, temperature, winter squash

Procedia PDF Downloads 598
22943 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network

Authors: Kamyar Fakhr, Roozbeh Salmani

Abstract:

Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

Procedia PDF Downloads 219
22942 Morpho-Agronomic Response to Water Stress of Some Nigerian Bambara Groundnut (Vigna Subterranea (L.) Verdc.) Germplasm and Genetic Diversity Studies of Some Selected Accessions Using Ssr Markers

Authors: Abejide Dorcas Ropo, , Falusi Olamide Ahmed, Daudu Oladipupo Abdulazeez Yusuf, Salihu Bolaji Zuluquri Neen, Muhammad Liman Muhammad, Gado Aishatu Adamu

Abstract:

Water stress is a major factor limiting the productivity of crops in the world today. This study evaluated the morpho-agronomic response of twenty-four (24) Nigerian Bambara groundnut landraces to water stress and genetic diversity of some selected accessions using SSR markers. The studies was carried out in the Botanical garden of the Department of Plant Biology, Federal University of Technology, Minna, Niger State, Nigeria in a randomized complete block design using three replicates. Molecular analysis using SSR primers was carried out at the Centre for Bio- Science, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria in order to characterize ten selected accessions comprising of the seven most drought tolerant and the three most susceptible accessions detected from the morpho-agronomic studies. Results revealed that water stress decreased morpho-agronomic traits such as plant height, leaf area, number of leaves per plant and seed yield etc. A total of 22 alleles were detected by the SSR markers used with a mean number of 4 allelles. Simple Sequence Repeat (SSR) markers MBamCO33, Primer 65 and G358B2-D15 each detected 4 allelles while Primer 3FR and 4FR detected 5 allelles each. The study revealed significantly high polymorphisms in 10 Loci. The mean value of Polymorpic information content was 0.6997 implying the usefulness of the primers used in identifying genetic similarities and differences among the Bambara groundnut genotypes. The SSR analysis revealed a comparable pattern between genetic diversity and drought tolerance of the genotypes. The Unweighted Paired Group Method with Arithmethic Mean (UPGMA) dendrogram showed that at a genetic distance of 0.1, the accessions were grouped into three groups according to their level of tolerance to drought. The two most drought tolerant accessions were grouped together and the 5th and 6th most drought tolerant accession were also grouped together. This suggests that the genotypes grouped together may be genetically close, may possess similar genes or have a common origin. The degree of genetic variants obtained could be useful in bambara groundnut breeding for drought tolerance. The identified drought tolerant bambara groundnut landraces are important genetic resources for drought stress tolerance breeding programme of bambara groundnut. The genotypes are also useful for germplasm conservation and global implications.

Keywords: bambara groundnut, genetic diversity, germplasm, SSR markers, water stress

Procedia PDF Downloads 20
22941 Governance Networks of China’s Neighborhood Micro-Redevelopment: The Case of Haikou

Authors: Lin Zhang

Abstract:

Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

Procedia PDF Downloads 89
22940 Monitorization of Junction Temperature Using a Thermal-Test-Device

Authors: B. Arzhanov, A. Correia, P. Delgado, J. Meireles

Abstract:

Due to the higher power loss levels in electronic components, the thermal design of PCBs (Printed Circuit Boards) of an assembled device becomes one of the most important quality factors in electronics. Nonetheless, some of leading causes of the microelectronic component failures are due to higher temperatures, the leakages or thermal-mechanical stress, which is a concern, is the reliability of microelectronic packages. This article presents an experimental approach to measure the junction temperature of exposed pad packages. The implemented solution is in a prototype phase, using a temperature-sensitive parameter (TSP) to measure temperature directly on the die, validating the numeric results provided by the Mechanical APDL (Ansys Parametric Design Language) under same conditions. The physical device-under-test is composed by a Thermal Test Chip (TTC-1002) and assembly in a QFN cavity, soldered to a test-board according to JEDEC Standards. Monitoring the voltage drop across a forward-biased diode, is an indirectly method but accurate to obtain the junction temperature of QFN component with an applied power range between 0,3W to 1.5W. The temperature distributions on the PCB test-board and QFN cavity surface were monitored by an infra-red thermal camera (Goby-384) controlled and images processed by the Xeneth software. The article provides a set-up to monitorize in real-time the junction temperature of ICs, namely devices with the exposed pad package (i.e. QFN). Presenting the PCB layout parameters that the designer should use to improve thermal performance, and evaluate the impact of voids in solder interface in the device junction temperature.

Keywords: quad flat no-Lead packages, exposed pads, junction temperature, thermal management and measurements

Procedia PDF Downloads 286
22939 Cluster-Based Multi-Path Routing Algorithm in Wireless Sensor Networks

Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

Procedia PDF Downloads 403
22938 The Impact of an Ionic Liquid on Hydrogen Generation from a Redox Process Involving Magnesium and Acidic Oilfield Water

Authors: Mohamed A. Deyab, Ahmed E. Awadallah

Abstract:

Under various conditions, we present a promising method for producing pure hydrogen energy from the electrochemical reaction of Mg metal in waste oilfield water (WOW). Mg metal and WOW are primarily consumed in this process. The results show that the hydrogen gas output is highly dependent on temperature and solution pH. The best conditions for hydrogen production were found to be a low pH (2.5) and a high temperature (338 K). For the first time, the Allyl methylimidazolium bis-trifluoromethyl sulfonyl imide) (IL) ionic liquid is used to regulate the rate of hydrogen generation. It has been confirmed that increasing the solution temperature and decreasing the solution pH accelerates Mg dissolution and produces more hydrogen per unit of time. The adsorption of IL on the active sites of the Mg surface is unrestricted by mixing physical and chemical orientation. Inspections using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and FT-IR spectroscopy were used to identify and characterise surface corrosion of Mg in WOW. This process is also completely safe and can create energy on demand.

Keywords: hydrogen production, Mg, wastewater, ionic liquid

Procedia PDF Downloads 158
22937 Exploring the Impact of Tillage and Manure on Soil Water Retention and Van Genuchten

Authors: Azadeh Safadoust, Ali Akbar Mahboubi

Abstract:

A study was conducted to evaluate hydraulic properties of a sandy loam soil and corn (Zea mays L.) crop production under a short-term tillage and manure combinations field experiment carried out in west of Iran. Treatments included composted cattle manure application rates [0, 30, and 60 Mg (dry weight) ha-1] and tillage systems [no-tillage (NT), chisel plowing (CP), and moldboard plowing (MP)] arranged in a split-plot design. Soil water characteristic curve (SWCC) and saturated hydraulic conductivity (Ks) were significantly affected by manure and tillage treatments. At any matric suction, the soil water content was in the order of MP>CP>NT. At all matric suctions, the amount of water retained by the soil increased as manure application rate increased (i.e. 60>30>0 Mg ha-1). Similar to the tillage effects, at high suctions the differences of water retained due to manure addition were less than that at low suctions. The change of SWCC from tillage methods and manure applications may attribute to the change of pore size and aggregate size distributions. Soil Ks was in the order of CP>MP>NT for the first two layers and in the order of MP>CP and NT for the deeper soil layer. The Ks also increased with increasing rates of manure application (i.e. 60>30>0 Mg ha-1). This was due to the increase in the total pore size and continuity.

Keywords: corn, manure, saturated hydraulic conductivity, soil water characteristic curve, tillage

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22936 Impact of Air Pressure and Outlet Temperature on Physicochemical and Functional Properties of Spray-dried Skim Milk Powder

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

Abstract:

Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder, to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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22935 MindFlow: A Collective Intelligence-Based System for Helping Stress Pattern Diagnosis

Authors: Andres Frederic

Abstract:

We present the MindFlow system supporting the detection and the diagnosis of stresses. The heart of the system is a knowledge synthesis engine allowing occupational health stakeholders (psychologists, occupational therapists and human resource managers) to formulate queries related to stress and responding to users requests by recommending a pattern of stress if one exists. The stress pattern diagnosis is based on expert knowledge stored in the MindFlow stress ontology including stress feature vector. The query processing may involve direct access to the MindFlow system by occupational health stakeholders, online communication between the MindFlow system and the MindFlow domain experts, or direct dialog between a occupational health stakeholder and a MindFlow domain expert. The MindFlow knowledge model is generic in the sense that it supports the needs of psychologists, occupational therapists and human resource managers. The system presented in this paper is currently under development as part of a Dutch-Japanese project and aims to assist organisation in the quick diagnosis of stress patterns.

Keywords: occupational stress, stress management, physiological measurement, accident prevention

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22934 Foot Recognition Using Deep Learning for Knee Rehabilitation

Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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22933 A Video Surveillance System Using an Ensemble of Simple Neural Network Classifiers

Authors: Rodrigo S. Moreira, Nelson F. F. Ebecken

Abstract:

This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs.

Keywords: ram memory, WiSARD weightless neural network, object tracking, quantization

Procedia PDF Downloads 310
22932 Physical and Microbiological Evaluation of Chitosan Films: Effect of Essential Oils and Storage

Authors: N. Valderrama, W. Albarracín, N. Algecira

Abstract:

It was studied the effect of the inclusion of thyme and rosemary essential oils into chitosan films, as well as the microbiological and physical properties when storing chitosan film with and without the mentioned inclusion. The film forming solution was prepared by dissolving chitosan (2%, w/v), polysorbate 80 (4% w/w CH) and glycerol (16% w/w CH) in aqueous lactic acid solutions (control). The thyme (TEO) and rosemary (REO) essential oils (EOs) were included 1:1 w/w (EOs:CH) on their combination 50/50 (TEO:REO). The films were stored at temperatures of 5, 20, 33°C and a relative humidity of 75% during four weeks. The films with essential oil inclusion did not show an antimicrobial activity against strains. This behavior could be explained because the chitosan only inhibits the growth of microorganisms in direct contact with the active sites. However, the inhibition capacity of TEO was higher than the REO and a synergic effect between TEO:REO was found for S. enteritidis strains in the chitosan solution. Some physical properties were modified by the inclusion of essential oils. The addition of essential oils does not affect the mechanical properties (tensile strength, elongation at break, puncture deformation), the water solubility, the swelling index nor the DSC behavior. However, the essential oil inclusion can significantly decrease the thickness, the moisture content, and the L* value of films whereas the b* value increased due to molecular interactions between the polymeric matrix, the loosing of the structure, and the chemical modifications. On the other hand, the temperature and time of storage changed some physical properties on the chitosan films. This could have occurred because of chemical changes, such as swelling in the presence of high humidity air and the reacetylation of amino groups. In the majority of cases, properties such as moisture content, tensile strength, elongation at break, puncture deformation, a*, b*, chrome, ΔE increased whereas water resistance, swelling index, L*, and hue angle decreased.

Keywords: chitosan, food additives, modified films, polymers

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22931 The Effects of Displacer-Cylinder-Wall Conditions on the Performance of a Medium-Temperature-Differential γ-Type Stirling Engine

Authors: Wen-Lih Chen, Chao-Kuang Chen, Mao-Ju Fang, Hsiang-Cheng Hsu

Abstract:

In this study, we conducted CFD simulation to study the gas cycle of a medium-temperature-differential (MTD) γ-type Stirling engine. Mesh compression and expansion as well as overset mesh techniques are employed to simulate the moving parts of the engine. Shear-Stress Transport (SST) k-ω turbulence model has been adopted because the model is not prone to generate excessive turbulence upon impingement regions. Hence, wall heat transfer rates at the hot and cold ends will not be overestimated. The effects of several different displacer-cylinder-wall temperature setups, including smooth and finned walls, on engine performance are investigated. The results include temperature contours, pressure versus volume diagrams, and variations of heat transfer rates, indicated power, and efficiency. It is found that displacer-wall heat transfer is one of the most important factors on engine performance, and some wall-temperature setups produce better results than others.

Keywords: CFD, finned wall, MTD Stirling engine, heat transfer

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22930 The Gasification of Acetone via Partial Oxidation in Supercritical Water

Authors: Shyh-Ming Chern, Kai-Ting Hsieh

Abstract:

Organic solvents find various applications in many industrial sectors and laboratories as dilution solvents, dispersion solvents, cleaners and even lubricants. Millions of tons of Spent Organic Solvents (SOS) are generated each year worldwide, prompting the need for more efficient, cleaner and safer methods for the treatment and resource recovery of SOS. As a result, acetone, selected as a model compound for SOS, was gasified in supercritical water to assess the feasibility of resource recovery of SOS by means of supercritical water processes. Experiments were conducted with an autoclave reactor. Gaseous product is mainly consists of H2, CO, CO2 and CH4. The effects of three major operating parameters, the reaction temperature, from 673 to 773K, the dosage of oxidizing agent, from 0.3 to 0.5 stoichiometric oxygen, and the concentration of acetone in the feed, 0.1 and 0.2M, on the product gas composition, yield and heating value were evaluated with the water density fixed at about 0.188g/ml.

Keywords: acetone, gasification, SCW, supercritical water

Procedia PDF Downloads 386