Search results for: Relationship Network
2342 Estimating the Traffic Impacts of Green Light Optimal Speed Advisory Systems Using Microsimulation
Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton
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Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.
Keywords: Connected vehicles, GLOSA, intelligent transportation systems, infrastructure-to-vehicle communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16132341 A Study on the User Experience Design of Mobile Twitter Application
Authors: Jeong Hoon Lee, Jin Hwan Yu
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The number of people using SNS with their mobile devices is soaring. This research focuses on the Twitter service that has the most third-party applications and delved into the fact that there were not sufficient studies on the UX design aspects of Twitter applications. Among social network services which have emerged as a major social topic lately, this research try to analyze the UX design of the Twitter application which is also called micro-blogging service. Therefore this research sets its goal to draw components of the UX design aspect of the Tweeter application on which there are not enough analysis yet. Moreover, this research suggests improvement of mobile application which will assure better users- experience. In order to analyze the UX design aspect of the mobile twitter application, with relevant document and user research, evaluating factors of the UX Design which would affect users- experience were organized. The subjects for cases were selected among six paid and free social networking applications that had been consistently ranked from 1st to 100th in the Korean application store during May, 2012 after closely monitoring the rank. From May 15th to May 11th in 2012, in accordance with the evaluating standard, surveys were conducted in a form of interviews with 20 subjects who have used the Twitter application to find out problems and solutions for the UX design of the mobile Twitter application.
Keywords: Social network service, twitter, user experience design, interface design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27022340 Rheological Characteristics of Ice Slurries Based on Propylene- and Ethylene-Glycol at High Ice Fractions
Authors: Senda Trabelsi, Sébastien Poncet, Michel Poirier
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Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.
Keywords: Ice slurry, propylene-glycol, ethylene-glycol, rheology, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11272339 The Relationship between Citizenship Acquisition and Ethnic Identity of Immigrant Women in Taiwan
Authors: Yuan-Yu Chiang, Yu-Han Tseng, Chin-Chen Wen
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In the last few decades, many southeast-Asia women migrate to Taiwan by marriage, and it usually takes several years for them to acquire Taiwanese citizenship. This study investigates the relationship between their citizenship acquisition and whether they develop Taiwanese identities, and how does it affect their ethnical identity towards their original ethnics. Furthermore, the present study also explores that whether citizenship acquisition help the immigrant women to explore the host society further and make commitment to it, or the identification towards mainstream Taiwanese society is only symbolic and superficial? One hundred and ninety-two immigrant women were measured using Multigroup Ethnic Identity Measure-Revised and a global 10-point ethnic identity question. Correlation tests, t-test, and hierarchical regression were performed to answer the above questions. The results revealed that citizenship acquisition does help immigrant women to identify with Taiwanese society, but it does not affect how they identify with their own ethnics. Furthermore, the results also indicated that acquiring citizenship would not help these immigrant women become involved in deeper cultural exploration of Taiwan nor would it encourage them to make commitments to the host society.
Keywords: Immigrants, international marriage, ethnic identity, Taiwan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16572338 Gender Differences in Entrepreneurship: Situation, Characteristics, Motivation and Entrepreneurial Behavior of Women Entrepreneurs in Switzerland
Authors: Mathias Rossi, Silna Borter, Marie Sansonnens
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Entrepreneurs are important for national labour markets and economies in that they contribute significantly to economic growth as well as provide the majority of jobs and create new ones. According to the Global Entrepreneurship Monitor’s “Report on Women and Entrepreneurship”, investment in women’s entrepreneurship is an important way to exponentially increase the impact of new venture creation finding ways to empower women’s participation and success in entrepreneurship are critical for more sustainable and successful economic development. Our results confirm that they are still differences between men and women entrepreneurs The reasons seems to be the lack of specific business skills, the less extensive social network, and the lack of identification patterns among women. Those differences can be explained by the fact that women still have fewer opportunities to make a career. If this is correct, we can predict an increasing proportion of women among entrepreneurs in the next years. Concerning the development of a favorable environment for developing and enhancing women entrepreneurship activities, our results show the insertion in a network and the role of a model doubtless represent elements determining in the choice to launch an entrepreneurship activity, as well as a precious resource for the success of her company.
Keywords: Women entrepreneurship, entrepreneurship motivation, entrepreneurial behavior.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33532337 Architectural Stratification and Woody Species Diversity of a Subtropical Forest Grown in a Limestone Habitat in Okinawa Island, Japan
Authors: S. M. Feroz, K. Yoshimura, A. Hagihara
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The forest stand consisted of four layers. The species composition between the third and the bottom layers was almost similar, whereas it was almost exclusive between the top and the lower three layers. The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom layer upward, except for H' -value of the top layer. The values of H' and J ' were 4.21 bit and 0.73, respectively, for the total stand. High woody species diversity of the forest depended on large trees in the upper layers, which trend was different from a subtropical evergreen broadleaf forest grown in silicate habitat in the northern part of Okinawa Island. The spatial distribution of trees was overlapped between the third and the bottom layers, whereas it was independent or slightly exclusive between the top and the lower three layers. Mean tree weight of each layer decreased from the top toward the bottom layer, whereas the corresponding tree density increased from the top downward. This relationship was analogous to the process of self-thinning plant populations.Keywords: Canopy multi-layering, limestone habitat, mean tree weight-density relationship, species diversity, subtropical forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12272336 An Efficient Burst Errors Combating for Image Transmission over Mobile WPANs
Authors: Mohsen A. M. El-Bendary, Mostafa A. R. El-Tokhy
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This paper presents an efficient burst error spreading tool. Also, it studies a vital issue in wireless communications, which is the transmission of images over wireless networks. IEEE ZigBee 802.15.4 is a short-range communication standard that could be used for small distance multimedia transmissions. In fact, the ZigBee network is a Wireless Personal Area Network (WPAN), which needs a strong interleaving mechanism for protection against error bursts. Also, it is low power technology and utilized in the Wireless Sensor Networks (WSN) implementation. This paper presents the chaotic interleaving scheme as a data randomization tool for this purpose. This scheme depends on the chaotic Baker map. The mobility effects on the image transmission are studied with different velocity through utilizing the Jakes’ model. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes.
Keywords: WPANs, Burst Errors, Mobility, Interleaving Techniques, Fading channels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20332335 Generator Capability Curve Constraint for PSO Based Optimal Power Flow
Authors: Mat Syai'in, Adi Soeprijanto, Takashi Hiyama
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An optimal power flow (OPF) based on particle swarm optimization (PSO) was developed with more realistic generator security constraint using the capability curve instead of only Pmin/Pmax and Qmin/Qmax. Neural network (NN) was used in designing digital capability curve and the security check algorithm. The algorithm is very simple and flexible especially for representing non linear generation operation limit near steady state stability limit and under excitation operation area. In effort to avoid local optimal power flow solution, the particle swarm optimization was implemented with enough widespread initial population. The objective function used in the optimization process is electric production cost which is dominated by fuel cost. The proposed method was implemented at Java Bali 500 kV power systems contain of 7 generators and 20 buses. The simulation result shows that the combination of generator power output resulted from the proposed method was more economic compared with the result using conventional constraint but operated at more marginal operating point.Keywords: Optimal Power Flow, Generator Capability Curve, Particle Swarm Optimization, Neural Network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25752334 Adaptation Learning Speed Control for a High- Performance Induction Motor using Neural Networks
Authors: M. Zerikat, S. Chekroun
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This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20272333 Multiple Model and Neural based Adaptive Multi-loop PID Controller for a CSTR Process
Authors: R.Vinodha S. Abraham Lincoln, J. Prakash
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Multi-loop (De-centralized) Proportional-Integral- Derivative (PID) controllers have been used extensively in process industries due to their simple structure for control of multivariable processes. The objective of this work is to design multiple-model adaptive multi-loop PID strategy (Multiple Model Adaptive-PID) and neural network based multi-loop PID strategy (Neural Net Adaptive-PID) for the control of multivariable system. The first method combines the output of multiple linear PID controllers, each describing process dynamics at a specific level of operation. The global output is an interpolation of the individual multi-loop PID controller outputs weighted based on the current value of the measured process variable. In the second method, neural network is used to calculate the PID controller parameters based on the scheduling variable that corresponds to major shift in the process dynamics. The proposed control schemes are simple in structure with less computational complexity. The effectiveness of the proposed control schemes have been demonstrated on the CSTR process, which exhibits dynamic non-linearity.Keywords: Multiple-model Adaptive PID controller, Multivariableprocess, CSTR process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20122332 Determinants of Capital Structure in Malaysia Electrical and Electronic Sector
Authors: Mazila Md-Yusuf, Fauziah Mohamad Yunus, Nur Zahraatul Lail Md Supaat
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Capital structure is one of the most important financial decisions in corporate financing strategy. It involves the choice of debt and equity level in financing a company-s operations. This study aims to investigate whether the capital structure choice of Malaysian electrical and electronic manufacturing companies that are listed in the Bursa Malaysia can be explained by factors that have been found by most studies as dominant determinants of capital structure (company size, profitability, asset tangibility, liquidity and growth). Using debt ratio as the proxy for capital structure and applying pooled ordinary least square multiple regression estimation, the results showed that on average, Malaysian electrical and electronic manufacturing companies used less debt in funding their business operations. The findings also showed that size and asset tangibility has a significant positive relationship with debt level, while liquidity has a negative significant relationship with leverage.Keywords: Capital structure, capital structure theories, leverage, manufacturing companies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53362331 Computational Model for Predicting Effective siRNA Sequences Using Whole Stacking Energy (% G) for Gene Silencing
Authors: Reena Murali, David Peter S.
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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies show that upregulation of mRNA because serious diseases like cancer. So designing effective siRNA with good knockdown effects plays an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (%G), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.
Keywords: Artificial Neural Network, Double Stranded RNA, RNA Interference, Short Interfering RNA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26662330 A Safety Analysis Method for Multi-Agent Systems
Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller
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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.Keywords: Multi-agent system, safety analysis, safety model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10872329 Relay Node Placement for Connectivity Restoration in Wireless Sensor Networks Using Genetic Algorithms
Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri
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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.
Keywords: Connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11042328 Bayesian Network Model for Students- Laboratory Work Performance Assessment: An Empirical Investigation of the Optimal Construction Approach
Authors: Ifeyinwa E. Achumba, Djamel Azzi, Rinat Khusainov
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There are three approaches to complete Bayesian Network (BN) model construction: total expert-centred, total datacentred, and semi data-centred. These three approaches constitute the basis of the empirical investigation undertaken and reported in this paper. The objective is to determine, amongst these three approaches, which is the optimal approach for the construction of a BN-based model for the performance assessment of students- laboratory work in a virtual electronic laboratory environment. BN models were constructed using all three approaches, with respect to the focus domain, and compared using a set of optimality criteria. In addition, the impact of the size and source of the training, on the performance of total data-centred and semi data-centred models was investigated. The results of the investigation provide additional insight for BN model constructors and contribute to literature providing supportive evidence for the conceptual feasibility and efficiency of structure and parameter learning from data. In addition, the results highlight other interesting themes.Keywords: Bayesian networks, model construction, parameterlearning, structure learning, performance index, model comparison.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17272327 Low Pressure Binder-Less Densification of Fibrous Biomass Material using a Screw Press
Authors: Tsietsi J. Pilusa, Robert Huberts, Edison Muzenda
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In this study, the theoretical relationship between pressure and density was investigated on cylindrical hollow fuel briquettes produced of a mixture of fibrous biomass material using a screw press without any chemical binder. The fuel briquettes were made of biomass and other waste material such as spent coffee beans, mielie husks, saw dust and coal fines under pressures of 0.878-2.2 Mega Pascals (MPa). The material was densified into briquettes of outer diameter of 100mm, inner diameter of 35mm and 50mm long. It was observed that manual screw compression action produces briquettes of relatively low density as compared to the ones made using hydraulic compression action. The pressure and density relationship was obtained in the form of power law and compare well with other cylindrical solid briquettes made using hydraulic compression action. The produced briquettes have a dry density of 989 kg/m3 and contain 26.30% fixed carbon, 39.34% volatile matter, 10.9% moisture and 10.46% ash as per dry proximate analysis. The bomb calorimeter tests have shown the briquettes yielding a gross calorific value of 18.9MJ/kg.
Keywords: Bio briquettes, biomass fuel, coffee grounds, fuelbriquettes
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26742326 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data
Authors: Rohan Putatunda, Aryya Gangopadhyay
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Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).
Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4322325 Motor Imagery Signal Classification for a Four State Brain Machine Interface
Authors: Hema C. R., Paulraj M. P., S. Yaacob, A. H. Adom, R. Nagarajan
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Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Keywords: Motor Imagery, Brain Machine Interfaces, Neural Networks, Particle Swarm Optimization, EEG signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24562324 A Reliable Secure Multicast Key Distribution Scheme for Mobile Adhoc Networks
Authors: D. SuganyaDevi, G. Padmavathi
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Reliable secure multicast communication in mobile adhoc networks is challenging due to its inherent characteristics of infrastructure-less architecture with lack of central authority, high packet loss rates and limited resources such as bandwidth, time and power. Many emerging commercial and military applications require secure multicast communication in adhoc environments. Hence key management is the fundamental challenge in achieving reliable secure communication using multicast key distribution for mobile adhoc networks. Thus in designing a reliable multicast key distribution scheme, reliability and congestion control over throughput are essential components. This paper proposes and evaluates the performance of an enhanced optimized multicast cluster tree algorithm with destination sequenced distance vector routing protocol to provide reliable multicast key distribution. Simulation results in NS2 accurately predict the performance of proposed scheme in terms of key delivery ratio and packet loss rate under varying network conditions. This proposed scheme achieves reliability, while exhibiting low packet loss rate with high key delivery ratio compared with the existing scheme.Keywords: Key Distribution, Mobile Adhoc Network, Multicast and Reliability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16372323 Statistical Analysis of the Impact of Maritime Transport Gross Domestic Product on Nigeria’s Economy
Authors: K. P. Oyeduntan, K. Oshinubi
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Nigeria is referred as the ‘Giant of Africa’ due to high population, land mass and large economy. However, it still trails far behind many smaller economies in the continent in terms of maritime operations. As we have seen that the maritime industry is the sparkplug for national growth, because it houses the most crucial infrastructure that generates wealth for a nation, it is worrisome that a nation with six seaports lag in maritime activities. In this research, we have studied how the Gross Domestic Product (GDP) of the maritime transport influences the Nigerian economy. To do this, we applied Simple Linear Regression (SLR), Support Vector Machine (SVM), Polynomial Regression Model (PRM), Generalized Additive Model (GAM) and Generalized Linear Mixed Model (GLMM) to model the relationship between the nation’s Total GDP (TGDP) and the Maritime Transport GDP (MGDP) using a time series data of 20 years. The result showed that the MGDP is statistically significant to the Nigerian economy. Amongst the statistical tool applied, the PRM of order 4 describes the relationship better when compared to other methods. The recommendations presented in this study will guide policy makers and help improve the economy of Nigeria.
Keywords: Economy, GDP, maritime transport, port, regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1422322 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line
Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez
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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.Keywords: Deep-learning, image classification, image identification, industrial engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7582321 Identifying a Drug Addict Person Using Artificial Neural Networks
Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh
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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.
Keywords: Artificial Neural Network, Decision Support System, drug abuse, drug addiction, Multilayer Perceptron.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16812320 Implementation of Neural Network Based Electricity Load Forecasting
Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw
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This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.Keywords: Neural network, Load forecast, Time series, wavelettransform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24932319 The Dependence of the Liquid Application on the Coverage of the Sprayed Objects in Terms of the Characteristics of the Sprayed Object during Spraying
Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń
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When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.
Keywords: Degree of coverage, deposition of liquid, nozzle, spraying.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7652318 An Improved Learning Algorithm based on the Conjugate Gradient Method for Back Propagation Neural Networks
Authors: N. M. Nawi, M. R. Ransing, R. S. Ransing
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The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of the activation function, (2) Calculating the gradient descent on error with respect to the weights and gains values and (3) the determination of the new search direction by exploiting the information calculated by gradient descent in step (2) as well as the previous search direction. The proposed method improved the training efficiency of back propagation algorithm by adaptively modifying the initial search direction. Performance of the proposed method is demonstrated by comparing to the conjugate gradient algorithm from neural network toolbox for the chosen benchmark. The results show that the number of iterations required by the proposed method to converge is less than 20% of what is required by the standard conjugate gradient and neural network toolbox algorithm.Keywords: Back-propagation, activation function, conjugategradient, search direction, gain variation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28382317 An Integrative Review of Changes of Family Relationship and Mental Health that Chinese Men Experience during Transition to Fatherhood
Authors: Mo Zhou, Samantha Ashby, Lyn Ebert
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In China, the changes that men experience in the perinatal period are not well researched. Men are also at risk of maladaptation to parenthood. The aim of this research is to review current studies regarding changes that Chinese men experience during transitioning to parenthood. 5 databases were employed to search relevant papers. The search found 128 articles. Based on the inclusion and exclusion criteria, 35 articles were included in this integrative review. Results showed the changes that Chinese fathers experienced during the transition to parenthood can be divided into two aspects: family relationships and mental problems. During transition to parenthood, fathers usually experienced an increase in their disappointment with marital conflict resolution and decreased sexual intimacy with their partner. Mental health declined, with fathers often feeling depressed and/or anxious during this time. Some men were diagnosed with clinical depression. The predictors of these changes included three domains: personal background (age and income), family background (gender of infant, relationship status and unplanned child) and cultural background (‘doing the month’, Confucianism, policy, social support).
Keywords: China, fathers, life change, prenatal, postpartum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6752316 Knowledge and Attitude of Palliative Care Towards Work Performance of Nurses in Indonesia Private Hospital
Authors: Novita Verayanti Manalu, Alvin Salim, Esti Yunitasari
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Background: Palliative care is caring holistically for patients and families to improve their quality of life. The approach by a multidisciplinary team requires integrated collaboration based on sufficient knowledge of the principles of palliative care as a whole, especially for nurses. Therefore, this study wants to find out the level of knowledge about palliative care of the nurses along the relationship with attitude and performance. Method: This study applies cross-sectional survey design and allows the respondents to fill two questionnaires to determine the level of knowledge and attitude toward palliative care, while one questionnaire is filled by the head nurse to evaluate nurses’ performance. The relationship was analyzed by Spearman rho’s correlation in alpha < 0.05 by SPSS. Results: The majority of respondents were females, age above 25 years old, and married. Most of the nurses are staff nurses and the ratio of education level is not significantly different. The knowledge level is poor, while the attitude and performance are in adequate level. Knowledge may affect attitude, but it does not happen toward performance. Conclusion: There is a need for increased knowledge about palliative care to improve attitude and work performance. Future researchers might use this finding as reference to conduct further study in improving knowledge of palliative care.
Keywords: Knowledge, attitude, work performance, palliative care.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4522315 Corporate Governance Practices and Audit Quality: An Empirical Study of the Listed Companies in Egypt
Authors: Mohamed Moustafa Soliman, Mohamed Abd Elsalam
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Recent financial international scandals around the world have led to a number of investigations into the effectiveness of corporate governance practices and audit quality. Although evidence of corporate governance practices and audit quality exists from developed economies, very scanty studies have been conducted in Egypt where corporate governance is just evolving. Therefore, this study provides evidence on the effectiveness of corporate governance practices and audit quality from a developing country. The data for analysis are gathered from the top 50 most active companies in the Egyptian Stock Exchange, covering the three year period 2007-2009. Logistic regression was used in investigating the questions that were raised in the study. Findings from the study show that board independence; CEO duality and audit committees significantly have relationship with audit quality. The results also, indicate that institutional investor and managerial ownership have no significantly relationship with audit quality. Evidence also exist that size of the company; complexity and business leverage are important factors in audit quality for companies quoted on the Egypt Stock Exchange.
Keywords: Corporate governance, Boards of directors, corporate ownership, Audit Committees, Audit quality, and Egypt.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39242314 Comparative Analysis of Different Control Strategies for Electro-hydraulic Servo Systems
Authors: Ismail Algelli Sassi Ehtiwesh, Željko Đurović
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The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the control strategy that may be used for the control of the servomechanism system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy (classical feedback (PID) & neural network) using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with classical control.Keywords: Electro-hydraulic systems, PID, Neural network controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18392313 Long Term Evolution Multiple-Input Multiple-Output Network in Unmanned Air Vehicles Platform
Authors: Ashagrie Getnet Flattie
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Line-of-sight (LOS) information, data rates, good quality, and flexible network service are limited by the fact that, for the duration of any given connection, they experience severe variation in signal strength due to fading and path loss. Wireless system faces major challenges in achieving wide coverage and capacity without affecting the system performance and to access data everywhere, all the time. In this paper, the cell coverage and edge rate of different Multiple-input multiple-output (MIMO) schemes in 20 MHz Long Term Evolution (LTE) system under Unmanned Air Vehicles (UAV) platform are investigated. After some background on the enormous potential of UAV, MIMO, and LTE in wireless links, the paper highlights the presented system model which attempts to realize the various benefits of MIMO being incorporated into UAV platform. The performances of the three MIMO LTE schemes are compared with the performance of 4x4 MIMO LTE in UAV scheme carried out to evaluate the improvement in cell radius, BER, and data throughput of the system in different morphology. The results show that significant performance gains such as bit error rate (BER), data rate, and coverage can be achieved by using the presented scenario.Keywords: BER, LTE, MIMO, path loss, UAV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1392