Search results for: electrical network

Authors: Tamanna Rimi

Abstract:

A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

Procedia PDF Downloads 160

Authors: Adenike Boyo Olasunkanmi Kesinro, Henry Boyo, Surukite Oluwole

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Utilizing solar energy in producing electricity can minimize environmental pollution generated by fossil fuel in producing electricity. Our research was base on the extraction of dye from Roystonea regia fruit by using methanol as solvent. The dye extracts were used as sensitizers in Dye-sensitized solar cell (DSSCs). Study was done on the electrical properties from the extracts of Roystonea regia fruit as Dye-sensitized solar cell (DSSCs). The absorptions of the extracts and extracts with dye were determined at different wavelengths (350-1000nm). Absorption peak was observed at 1.339 at wavelength 400nm. The obtained values for methanol extract Roystonea regia extract are, Imp = 0.015mA, Vmp = 12.0mV, fill factor = 0.763, Isc= 0.018 mA and Voc = 13.1 mV and efficiency of 0.32%. .The phytochemical screening was taken and it was observed that Roystonea regia extract contained less of anthocyanin compared to flavonoids. The nanostructured dye sensitized solar cell (DSSC) will provide economically credible alternative to present day silicon p–n junction photovoltaic.

Keywords: methanol, ethanol, titanium dioxide, roystonea regia fruit, dye-sensitized solar cell

Procedia PDF Downloads 399

Authors: A. A. Bajad, B. P. Sharma, Y. C. Gupta, B. S. Dilt, R. K. Gupta

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The present investigations were carried out at the experimental farm of Department of Floriculture and Landscape Architecture, Dr. Y. S. Parmar University of Horticulture and Forestry, Nauni, Solan, H.P. during 2015 and 2016. The experiment was laid out in a Randomized Block Design (factorial) consisting of 48 treatment combinations of four planting dates viz., D1- mid March, D2-mid April, D3-mid May and D4- mid June and two cultivars namely V1- Kamini and V2 -Poornima with six mulching materials M¬0¬- without mulch, M1- Black plastic mulch (100 µ), M2- Silver plastic mulch (100 µ), M3¬- Transparent plastic mulch (100 µ), M3-Transparent plastic mulch (100 µ), M4¬- Pine needle (100 µ) and M5- Grass (1 inch layer). Among different planting times, D4 i.e. mid June planting obtained best results for number of seed per flower (179.38), germination percent (83.92 %), electrical conductivity (0.97 ds/m), seedling length (7.93 cm), seedling dry weight (7.09 mg), seedling vigour index I (763.79), moisture content (7.83 %) and 1000 seed weight (1.94 g). However, seed yield per plant (14.30 g) was recorded to be maximum in mid of March. Among the cultivars, cv. ‘Poornima’ gave best results for number of seed per plant (187.30). However, cv. ‘Kamini’ recorded the best result for seed yield per plant (12.55), electrical conductivity (1.11 ds/m), germination percent (80.47 %), seedling length (6.39 cm), seedling dry weight (5.11 mg), seedling vigour index I (649.49), moisture content (9.28 %) and 1000 seed weight (1.70 g). Silver plastic obtained best results for number of seed per flower (170.10), seed yield per plant (15.66 g), germination percent (80.17 %), electrical conductivity (1.26 ds/m), seedling length (5.88 cm), seedling dry weight (4.46 mg), seedling vigour index I (616.78), Moisture content (9.35 %) and 100 seed weight (1.97 g).

Keywords: cultivars, mulch materials, planting times, flowers

Procedia PDF Downloads 274

Authors: Tianyu Cao, KIRA (Ruizhi Zhao)

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The purpose of our research is to study the possibility of people with physical disabilities manipulating mechanical prostheses through brain-computer interface (BCI) technology. The brain-machine interface (BCI) of the neural prosthesis records signals from neurons and uses mathematical modeling to decode them, converting desired movements into body movements. In order to improve the patient's neural control, the prosthesis is given a natural feeling. It records data from sensitive areas from the body to the prosthetic limb and encodes signals in the form of electrical stimulation to the brain. In our research, the brain-computer interface (BCI) is a bridge connecting patients’ cognition and the real world, allowing information to interact with each other. The efficient work between the two is achieved through external devices. The flow of information is controlled by BCI’s ability to record neuronal signals and decode signals, which are converted into device control. In this way, we could encode information and then send it to the brain through electrical stimulation, which has significant medical application.

Keywords: biomedical engineering, brain-computer interface, prosthesis, neural control

Procedia PDF Downloads 169

Authors: Christodoulou Christos, Politis Anastasios

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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

Procedia PDF Downloads 46

Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: K. W. Nam, B. J. Kim, S. J. Lee

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Along with the development of network infrastructures, such as high-speed Internet and mobile environment, the explosion of multimedia data is expanding the range of multimedia services beyond voice and data services. Amid this flow, research is actively being done on the creation, management, and transmission of metadata on digital content to provide different services to users. This paper proposes a system for the insertion, storage, and retrieval of metadata about digital content. The metadata server with Binary XML was implemented for efficient storage space and retrieval speeds, and the transport data size required for metadata retrieval was simplified. With the proposed system, the metadata could be inserted into the moving objects in the video, and the unnecessary overlap could be minimized by improving the storage structure of the metadata. The proposed system can assemble metadata into one relevant topic, even if it is expressed in different media or in different forms. It is expected that the proposed system will handle complex network types of data.

Keywords: video, multimedia, metadata, editing tool, XML

Procedia PDF Downloads 162

Authors: Saeed Karimi, Ali Behbahaninia

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In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

Procedia PDF Downloads 84

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

Procedia PDF Downloads 328

Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

Procedia PDF Downloads 195

Authors: Md. Armin Islam, Les Dallin, Mark Boland, W. J. Zhang

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This paper reports a study on the optimal magnetic design of a compact quadrupole electromagnet for the Canadian Light Source (CLS 2.0). The nature of the design is to determine a quadrupole with low relative higher order harmonics and better field quality. The design problem was formulated as an optimization model, in which the objective function is the higher order harmonics (multipole errors) and the variable to be optimized is the material distribution on the pole. The higher order harmonics arose in the quadrupole due to truncating the ideal hyperbola at a certain point to make the pole. In this project, the arisen harmonics have been optimized both transversely and longitudinally by adjusting material on the poles in a controlled way. For optimization, finite element analysis (FEA) has been conducted. A better higher order harmonics amplitudes and field quality have been achieved through the optimization. On the basis of the optimized magnetic design, electrical and cooling calculation has been performed for the magnet.

Keywords: drift, electrical, and cooling calculation, integrated field, magnetic field gradient, multipole errors, quadrupole

Procedia PDF Downloads 139

Authors: Saeed Ullah Jan

Abstract:

This study has examined the e-readiness in libraries of public sector universities in Khyber Pakhtunkhwa. Efforts were made to evaluate the availability of human resources, electronic infrastructure, and network services and programs in the public sector university libraries. The population of the study was the twenty-seven public sector university libraries of Khyber Pakhtunkhwa. A quantitative approach was adopted, and a questionnaire-based survey was conducted to collect data from the librarian/in charge of public sector university libraries. The collected data were analyzed using Statistical Package for Social Sciences version 22 (SPSS). The mean score of the knowledge component interpreted magnitudes below three which indicates that the respondents are poorly or moderately satisfied regards knowledge of libraries. The satisfaction level of the respondents about the other components, such as electronic infrastructure, network services and programs, and enhancers of the networked world, was rated as average or below. The study suggested that major aspects of existing public-sector university libraries require significant transformation. For this purpose, the government should provide all the required resources and facilities to meet the population's informational and recreational demands. The Information Communication Technology (ICT) infrastructure of public university libraries needs improvement in terms of the availability of computer equipment, databases, network servers, multimedia projectors, digital cameras, uninterruptible power supply, scanners, and backup devices such as hard discs and Digital Video Disc/Compact Disc.

Keywords: ICT-libraries, e-readiness-libraries, e-readiness-university libraries, e-readiness-Pakistan

Procedia PDF Downloads 82

Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

Procedia PDF Downloads 316

Authors: Khaled Selatnia

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Nowadays, the traffic congestion becomes increasingly a chronic problem. Sometimes, the cause is attributed to the recurrent road works that create barriers to the efficient movement. But congestion, which usually occurs in cities, can take diverse forms and magnitudes. The case study of Biskra city in Algeria and the diagnosis of its road network show that throughout all the micro regional system, the road network seems at first quite dense. However, this density although it is important, does not cover all areas. A major flow is concentrated in the axis Sidi Okba – Biskra – Tolga. The largest movement of people in the Wilaya (prefecture) revolves around these three centers and their areas of influence. Centers farthest from the trio are very poorly served. This fact leads us to ask questions about the extent of congestion in Biskra city and its relationship to the imbalance of the urban framework. The objective of this paper is to highlight the impact of the urban fact on the traffic congestion.

Keywords: congestion, urban framework, regional, urban and regional studies

Procedia PDF Downloads 620

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 168

Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

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In this research, the capability of neural networks in modeling and learning complicated and nonlinear relations has been used to develop a model for the prediction of changes in the diameter of bubbles in pool boiling distilled water. The input parameters used in the development of this network include element temperature, heat flux, and retention time of bubbles. The test data obtained from the experiment of the pool boiling of distilled water, and the measurement of the bubbles form on the cylindrical element. The model was developed based on training algorithm, which is typologically of back-propagation type. Considering the correlation coefficient obtained from this model is 0.9633. This shows that this model can be trusted for the simulation and modeling of the size of bubble and thermal transfer of boiling.

Keywords: bubble diameter, heat flux, neural network, training algorithm

Procedia PDF Downloads 440

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

Procedia PDF Downloads 247

Authors: Raghvendra Singh Yadav, Ivo Kuřitka

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In this report, we studied the impact of Gd3+ substitution on structural, magnetic and electrical properties of CoFe2O4 nanoparticles synthesized by sonochemical method. X-ray diffraction pattern confirmed the formation of cubic spinel structure at low concentration of Gd3+ ions, however, GdFeO3 additional phase was observed at higher concentration of Gd3+ ions. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of Gd3+ substituted CoFe2O4 nanoparticles. The field emission scanning electron microscopy study revealed that Gd3+ substituted CoFe2O4 nanoparticles were in the range of 5-20 nm. The magnetic properties of Gd3+ substituted CoFe2O4 nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with Gd3+ concentration in CoFe2O4 nanoparticles was observed. The variation of real and imaginary part of dielectric constant, tan δ, and AC conductivity were studied at room temperature.

Keywords: spinel ferrites, nanoparticles, sonochemical method, magnetic properties

Procedia PDF Downloads 288

Authors: Gokhan Kilic, Pelin Celik

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Structural health monitoring (SHM) is widely used in evaluating the state and health of membrane structures. In the past, in order to collect data and send it to a data collection unit on membrane structures, wire sensors had to be put as part of the SHM process. However, this study recommends using wireless sensors instead of traditional wire ones to construct an economical, useful, and easy-to-install membrane structure health monitoring system. Every wireless sensor uses a software translation program that is connected to the monitoring server. Operational neural networks (ONNs) have recently been developed to solve the shortcomings of convolutional neural networks (CNNs), such as the network's resemblance to the linear neuron model. The results of using ONNs for monitoring to evaluate the structural health of a membrane are presented in this work.

Keywords: wireless sensor network, non-destructive testing, operational neural networks, membrane structures, dynamic monitoring

Procedia PDF Downloads 81

Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

Procedia PDF Downloads 289

Authors: Chandra Mukherjee

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The prevalent knowledge of the biological systems is based on the standard scientific perception of natural equilibrium, determination and predictability. Recently, a rethinking of concepts was presented and a new scientific perspective emerged that involves complexity theory with deterministic chaos theory, nonlinear dynamics and theory of fractals. The unpredictability of the chaotic processes probably would change our understanding of diseases and their management. The mathematical definition of chaos is defined by deterministic behavior with irregular patterns that obey mathematical equations which are critically dependent on initial conditions. The chaos theory is the branch of sciences with an interest in nonlinear dynamics, fractals, bifurcations, periodic oscillations and complexity. Recently, the biomedical interest for this scientific field made these mathematical concepts available to medical researchers and practitioners. Any biological network system is considered to have a nominal state, which is recognized as a homeostatic state. In reality, the different physiological systems are not under normal conditions in a stable state of homeostatic balance, but they are in a dynamically stable state with a chaotic behavior and complexity. Biological systems like heart rhythm and brain electrical activity are dynamical systems that can be classified as chaotic systems with sensitive dependence on initial conditions. In biological systems, the state of a disease is characterized by a loss of the complexity and chaotic behavior, and by the presence of pathological periodicity and regulatory behavior. The failure or the collapse of nonlinear dynamics is an indication of disease rather than a characteristic of health.

Keywords: HRV, HRVI, LF, HF, DII

Procedia PDF Downloads 414

Authors: Salem Alajmi, Bader Altaweel

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Kuwait, like many parts of the world, has started facing the dangerous growth of electrical and electronic wastes. This growth has been noted last two decades, coming along with the development of mobile phones, computers, TVs, as well as other electronic devices and electrical equipment. Kuwait is already among the highest global producers of electronic waste (E-waste) in kg per capita. Furthermore, Kuwait is among the global countries that set high-level future targets in renewable energy projects. Accumulation of this electronic waste, as well as accelerated renewable energy projects, will lead to the increase of future threats to the country. In this research, factors that lead to the increase the e-waste in Kuwait are presented. Also, the current situations of dealing with e-waste in the country as well as current challenges are examined. The impact of renewable energy projects on future E-wastes accumulation is considered. Moreover, this research proposes the best strategies and practices toward successfully dealing with the waste of electronic devices and renewable energy technologies.

Keywords: Kuwait, e-waste, extended producer responsibility, environment, recycle, recovery

Procedia PDF Downloads 170

Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

Procedia PDF Downloads 467

Authors: Dulal Bhaumik, Fei Jie, Runa Bhaumik, Bikas Sinha

Abstract:

Human brain is an amazingly complex network. Aberrant activities in this network can lead to various neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and autism. fMRI has emerged as an important tool to delineate the neural networks affected by such diseases, particularly autism. In this paper, we propose mixed-effects models together with an appropriate procedure for controlling false discoveries to detect disrupted connectivities in whole brain studies. Results are illustrated with a large data set known as Autism Brain Imaging Data Exchange or ABIDE which includes 361 subjects from 8 medical centers. We believe that our findings have addressed adequately the small sample inference problem, and thus are more reliable for therapeutic target for intervention. In addition, our result can be used for early detection of subjects who are at high risk of developing neurological disorders.

Keywords: ABIDE, autism spectrum disorder, fMRI, mixed-effects model

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Authors: Lopamudra Bakshi Basu

Abstract:

Transport is one of the most important characteristic features of Indian cities. The physical and societal requirements determine the selection of a particular transport system along with the uniqueness of road networks. Kolkata has a mixed traffic of which Paratransit system plays a crucial role. It is an indispensable transport system in Kolkata mainly because of its size and service flexibility which has led to a unique network character. The paratransit system, mainly the autorickshaws, is the most favoured mode of transport in the city. Its fast movement and comfortability make it a vital transport system of the city. Since the inception of the autorickshaws in Kolkata in 1981, this mode has gained popularity and presently serves nearly 80 to 90 percent of the total passenger trips. This employment generating mode of transport has increased its number rapidly affecting the city’s traffic. Minimal check on their growth by the authority has led to traffic snarls along many streets of Kolkata. Indiscipline behavior, violation of traffic rules and rash driving make situations even worse. The rise in the number and increasing popularity of the autorickshaws make it an interesting study area. Autorickshaws as a paratransit mode play its role as a leader or a follower. However, it is informal in its planning and operations, which makes it a problem area for the city. The entire research work deals with the growth and expansion of the number of vehicles and the routes within the city. The development of transport system has been interesting in the city, which has been studied. The growth of the paratransit modes in the city has been rapid. The network pattern of the paratransit mode within Kolkata has been analysed.

Keywords: growth, informal, network characteristics, paratransit, service flexibility

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Authors: Van Dong Phung, Igor Hawryszkiewycz, Kyeong Kang, Muhammad Hatim Binsawad

Abstract:

Knowledge sharing (KS) is the key to creativity and innovation in any organizations. Overcoming the KS barriers has created new challenges for designing in dynamic and complex environment. There may be interrelations and interdependences among the barriers. The purpose of this paper is to present a review of literature of KS barriers and impute the relative importance of them through the fuzzy analytic network process that is a generalization of the analytical hierarchy process (AHP). It helps to prioritize the barriers to find ways to remove them to facilitate KS. The study begins with a brief description of KS barriers and the most critical ones. The FANP and its role in identifying the relative importance of KS barriers are explained. The paper, then, proposes the model for research and expected outcomes. The study suggests that the use of the FANP is appropriate to impute the relative importance of KS barriers which are intertwined and interdependent. Implications and future research are also proposed.

Keywords: FANP, ANP, knowledge sharing barriers, knowledge sharing, removing barriers, knowledge management

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

Abstract:

This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

Abstract:

Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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Authors: Tanit Pruktara

Abstract:

The research aimed to study the students’ learning achievement and awareness level on electrical energy consumption and conservation and also to investigate the students’ attitude on the developed multimedia supplemented instructional unit for learning household electrical energy consumption and conservation in grade 10 Thailand student. This study used a quantitative method using MCQ for pre and post-achievement tests and Likert scales for awareness and attitude survey questionnaires. The results from this were employed to improve the multimedia to be appropriate for the classroom and with real life situations in the second phase, the main study. The experimental results showed that the developed learning unit significantly improved the students’ learning achievement as well as their awareness of electric energy conservation. Additional we found the student will enjoy participating in class activities when the lessons are taught using multimedia and helps them to develop the relevance between the course and real world situations.

Keywords: lesson plan, media and animations, training course, vocational school in Thailand

Procedia PDF Downloads 170