Search results for: intelligent distribution grids

Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics

Procedia PDF Downloads 127

Authors: Deepa S N, Srinivasan a D, Veeramanju K T

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The power transformer is a critical equipment in the transmission and distribution network that must be managed to ensure uninterrupted power service. The liquid insulation is essential for the proper functioning of the transformer, as it serves as both coolant and insulating medium, which influences the transformer’s durability. Further, the insulating state of a power transformer has a significant impact on its reliability. Mineral oil derived from petroleum crude oil has been employed as liquid dielectrics for decades due to its superior functional characteristics, however as a resource for the same are getting depleted over the years. Research is undertaken across the globe to identify a viable substitute for mineral oil. Further, alternate insulating oils are being investigated for better environmental impact, biodegradability and economics. Several combinations of vegetable oil derived natural esters are being inspected by researchers across the globe in these domains. In this work, mineral oil is blended with soyabean oil with various proportions and dielectric properties such as dielectric breakdown voltage, relative permittivity, dissipation factor, viscosity, flash and fire point have been investigated according to international standards. A quantitative comparison is made among various samples and is observed that the blended oil sample of equal proportion of mineral oil and soyabean oil, MO50+SO50 exhibits superior dielectric properties such as breakdown voltage of 65kV, dissipation factor of 0.0044, relative permittivity of 3.1680 that are closer to the range of values recommended for power transformer applications. Also, Breakdown voltage values of all the investigated oil samples obeyed the Weibull and Normal probability distribution.

Keywords: blended oil, dielectric breakdown, liquid insulation, power transformer

Procedia PDF Downloads 90

Authors: Jeremie Coullon, Robert J. Webber

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We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

Procedia PDF Downloads 154

Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

Procedia PDF Downloads 516

Authors: Takashi Nakamura

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In the Tokyo metropolitan area, traffic congestion and long commute times are caused by overconcentration in the central area. To resolve these problems, a core business city development policy was adopted in 1988. The core business cities, which include Yokohama, Chiba, Saitama, Tachikawa, and others, have designated business facilities accumulation districts where assistance measures are applied. Focusing on Yokohama city, this study investigates the trends in the number of offices, employees, and commuters at 2001 and 2012 Economic Census, as well as the average commute time in the Tokyo metropolitan area from 2005 to 2015 Metropolitan Transportation Census. Surveys were administered in 2001 and 2012 Economic Census to participants who worked in Yokohama, according to their distribution in the city's 1,757 subregions. Four main findings emerged: (1) The number of offices increased in Yokohama when the number of offices decreased in the Tokyo metropolitan area overall. Additionally, the number of employees at Yokohama increased. (2) The number of commuters to Tokyo's central area increased from Saitama prefecture, Tokyo Tama area, and Tokyo central area. However, it decreased from other areas. (3) The average commute time in the Tokyo metropolitan area was 67.7 minutes in 2015, a slight decrease from 2005 and 2010. (4) The number of employees at business facilities accumulation districts in Yokohama city increased greatly.

Keywords: core business city development policy, commute time, number of employees, Yokohama city, distribution of employees

Procedia PDF Downloads 143

Authors: Vallence Ngabo Maniragaba

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This study aimed at examining the variations of undernutrition among children below 5 years of age in Uganda. The approach of spatial and spatiotemporal analysis helped in identifying cluster patterns, hot spots and emerging hot spots. Data from the 6 Uganda Demographic and Health Surveys spanning from 1990 to 2016 were used with the main outcome variable being undernutrition among children <5 years of age. All data that were relevant to this study were retrieved from the survey datasets and combined with the 214 shape files for the districts of Uganda to enable spatial and spatiotemporal analysis. Spatial maps with the spatial distribution of the prevalence of undernutrition, both in space and time, were generated using ArcGIS Pro version 2.8. Moran’s I, an index of spatial autocorrelation, rules out doubts of spatial randomness in order to identify spatially clustered patterns of hot or cold spot areas. Furthermore, space-time cubes were generated to establish the trend in undernutrition as well as to mirror its variations over time and across Uganda. Moreover, emerging hot spot analysis was done to help identify the patterns of undernutrition over time. The results indicate a heterogeneous distribution of undernutrition across Uganda and the same variations were also evident over time. Moran’s I index confirmed spatial clustered patterns as opposed to random distributions of undernutrition prevalence. Four hot spot areas, namely; the Karamoja, the Sebei, the West Nile and the Toro regions were significantly evident, most of the central parts of Uganda were identified as cold spot clusters, while most of Western Uganda, the Acholi and the Lango regions had no statistically significant spatial patterns by the year 2016. The spatio-temporal analysis identified the Karamoja and Sebei regions as clusters of persistent, consecutive and intensifying hot spots, West Nile region was identified as a sporadic hot spot area while the Toro region was identified with both sporadic and emerging hotspots. In conclusion, undernutrition is a silent pandemic that needs to be handled with both hands. At 31.2 percent, the prevalence is still very high and unpleasant. The distribution across the country is nonuniform with some areas such as the Karamoja, the West Nile, the Sebei and the Toro regions being epicenters of undernutrition in Uganda. Over time, the same areas have experienced and exhibited high undernutrition prevalence. Policymakers, as well as the implementers, should bear in mind the spatial variations across the country and prioritize hot spot areas in order to have efficient, timely and region-specific interventions.

Keywords: undernutrition, spatial autocorrelation, hotspots analysis, geographically weighted regressions, emerging hotspots analysis, under-fives, Uganda

Procedia PDF Downloads 86

Authors: Abhishek, Seema Devi, Jyoti Ohri

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A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.

Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, truetime

Procedia PDF Downloads 498

Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

Procedia PDF Downloads 323

Authors: Dmitry V. Pasynkov, Ivan A. Egoshin, Alexey A. Kolchev, Ivan V. Kliouchkin

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In most cases, typical cysts are easily recognized at ultrasonography. The specificity of this method for typical cysts reaches 98%, and it is usually considered as gold standard for typical cyst diagnosis. However, it is necessary to have all the following features to conclude the typical cyst: clear margin, the absence of internal echoes and dorsal acoustic enhancement. At the same time, not every breast cyst is typical. It is especially characteristic for protein-contained cysts that may have significant internal echoes. On the other hand, some solid lesions (predominantly malignant) may have cystic appearance and may be falsely accepted as cysts. Therefore we tried to develop the automatic method of cystic and solid breast lesions differentiation. Materials and methods. The input data were the ultrasonography digital images with the 256-gradations of gray color (Medison SA8000SE, Siemens X150, Esaote MyLab C). Identification of the lesion on these images was performed in two steps. On the first one, the region of interest (or contour of lesion) was searched and selected. Selection of such region is carried out using the sigmoid filter where the threshold is calculated according to the empirical distribution function of the image brightness and, if necessary, it was corrected according to the average brightness of the image points which have the highest gradient of brightness. At the second step, the identification of the selected region to one of lesion groups by its statistical characteristics of brightness distribution was made. The following characteristics were used: entropy, coefficients of the linear and polynomial regression, quantiles of different orders, an average gradient of brightness, etc. For determination of decisive criterion of belonging to one of lesion groups (cystic or solid) the training set of these characteristics of brightness distribution separately for benign and malignant lesions were received. To test our approach we used a set of 217 ultrasonic images of 107 cystic (including 53 atypical, difficult for bare eye differentiation) and 110 solid lesions. All lesions were cytologically and/or histologically confirmed. Visual identification was performed by trained specialist in breast ultrasonography. Results. Our system correctly distinguished all (107, 100%) typical cysts, 107 of 110 (97.3%) solid lesions and 50 of 53 (94.3%) atypical cysts. On the contrary, with the bare eye it was possible to identify correctly all (107, 100%) typical cysts, 96 of 110 (87.3%) solid lesions and 32 of 53 (60.4%) atypical cysts. Conclusion. Automatic approach significantly surpasses the visual assessment performed by trained specialist. The difference is especially large for atypical cysts and hypoechoic solid lesions with the clear margin. This data may have a clinical significance.

Keywords: breast cyst, breast solid lesion, differentiation, ultrasonography

Procedia PDF Downloads 270

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

Procedia PDF Downloads 130

Authors: Khalifa Maha, Ben Othman Hakim, Khaled Hussainey

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

Procedia PDF Downloads 359

Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

Procedia PDF Downloads 316

Authors: E. Yarar, E. A. Guven, S. Karabay

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In this study, a comprehensive simulation was made for the cold tube drawing with fixed plug. The cold tube drawing process is preferred due to its high surface quality and the high mechanical properties. In drawing processes applied to materials with low plastic deformability, cracks can occur on the surfaces and the process efficiency decreases. The aim of the work is to investigate the effects of different drawing parameters on drawing forces and stresses. In the simulations, optimum conditions were investigated for four different materials, Ti64Al4V, AA5052, AISI4140, and C365. One of the most important parameters for the cold drawing process is the die angle. Three dies were designed for the analysis with semi die angles of 5°, 10°, and 15°. Three different parameters were used for the friction coefficient between die and the material. In the simulations, reduction of area and the drawing speed is kept constant. Drawing is done in one pass. According to the simulation results, the highest drawing forces were obtained in Ti64Al4V. As the semi die angle increases, the drawing forces decrease. The change in semi die angle was most effective on Ti64Al4V. Increasing the coefficient of friction is another effect that increases the drawing forces. The increase in the friction coefficient has also increased in drawing stresses. The increase in die angle also increased the drawing stress distribution for the other three materials outside C365. According to the results of the analysis, it is found that the designed drawing die is suitable for drawing. The lowest drawing stress distribution and drawing forces were obtained for AA5052. Drawing die parameters have a direct effect on the results. In addition, lubricants used for drawing have a significant effect on drawing forces.

Keywords: cold tube drawing, drawing force, drawing stress, semi die angle

Procedia PDF Downloads 166

Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

Procedia PDF Downloads 73

Authors: Tsu-Yun Chiu, Tsung-Hsueh Lu, Tain-Junn Cheng

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Background: Traditional chronic disease management did not pay attention to effects of geographic factors on the compliance of treatment regime, which resulted in geographic inequality in outcomes of chronic disease management. This study aims to examine the geographic distribution and clustering of quality indicators of diabetes care. Method: We first extracted address, demographic information and quality of care indicators (number of visits, complications, prescription and laboratory records) of patients with diabetes for 2014 from medical information system in a medical center in Tainan City, Taiwan, and the patients’ addresses were transformed into district- and village-level data. We then compared the differences of geographic distribution and clustering of quality of care indicators between districts and villages. Despite the descriptive results, rate ratios and 95% confidence intervals (CI) were estimated for indices of care in order to compare the quality of diabetes care among different areas. Results: A total of 23,588 patients with diabetes were extracted from the hospital data system; whereas 12,716 patients’ information and medical records were included to the following analysis. More than half of the subjects in this study were male and between 60-79 years old. Furthermore, the quality of diabetes care did indeed vary by geographical levels. Thru the smaller level, we could point out clustered areas more specifically. Fuguo Village (of Yongkang District) and Zhiyi Village (of Sinhua District) were found to be “hotspots” for nephropathy and cerebrovascular disease; while Wangliau Village and Erwang Village (of Yongkang District) would be “coldspots” for lowest proportion of ≥80% compliance to blood lipids examination. On the other hand, Yuping Village (in Anping District) was the area with the lowest proportion of ≥80% compliance to all laboratory examination. Conclusion: In spite of examining the geographic distribution, calculating rate ratios and their 95% CI could also be a useful and consistent method to test the association. This information is useful for health planners, diabetes case managers and other affiliate practitioners to organize care resources to the areas most needed.

Keywords: catchment area of healthcare, chronic disease management, Geographic information system, quality of diabetes care

Procedia PDF Downloads 283

Authors: Guang Zou, Kian Banisoleiman, Arturo González

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Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally, there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach.

Keywords: crack initiation, fatigue reliability, inspection planning, welded joints

Procedia PDF Downloads 353

Authors: E. O. Clarke, O. J. Aderinola, O. A. Adeboyejo, M. A. Anetekhai

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Aims: The study is aimed at establishing the influence of some physical and chemical parameters on the abundance, distribution pattern and seasonal variations of the planktonic crustacean populations. Place and Duration of Study: A premier investigation into the dynamics of planktonic crustacean populations in Ologe lagoon was carried out from January 2011 to December 2012. Study Design: The study covered identification, temporal abundance, spatial distribution and diversity of the planktonic crustacea. Methodology: Standard techniques were used to collect samples from eleven stations covering five proximal satellite towns (Idoluwo, Oto, Ibiye, Obele, and Gbanko) bordering the lagoon. Data obtained were statistically analyzed using linear regression and hierarchical clustering. Results:Thirteen (13) planktonic crustacean populations were identified. Total percentage abundance was highest for Bosmina species (20%) and lowest for Polyphemus species (0.8%). The Pearson’s correlation coefficient (“r” values) between total planktonic crustacean population and some physical and chemical parameters showed that positive correlations having low level of significance occurred with salinity (r = 0.042) (sig = 0.184) and with surface water dissolved oxygen (r = 0.299) (sig = 0.155). Linear regression plots indicated that, the total population of planktonic crustacea were mainly influenced and only increased with an increase in value of surface water temperature (Rsq = 0.791) and conductivity (Rsq = 0.589). The total population of planktonic crustacea had a near neutral (zero correlation) with the surface water dissolved oxygen and thus, does not significantly change with the level of the surface water dissolved oxygen. The correlations were positive with NO3-N (midstream) at Ibiye (Rsq =0.022) and (downstream) Gbanko (Rsq =0.013), PO4-P at Ibiye (Rsq =0.258), K at Idoluwo (Rsq =0.295) and SO4-S at Oto (Rsq = 0.094) and Gbanko (Rsq = 0.457). The Berger-Parker Dominance Index (BPDI) showed that the most dominant species was Bosmina species (BPDI = 1.000), followed by Calanus species (BPDI = 1.254). Clusters by squared Euclidan distances using average linkage between groups showed proximities, transcending the borders of genera. Conclusion: The results revealed that planktonic crustacean population in Ologe lagoon undergo seasonal perturbations, were highly influenced by nutrient, metal and organic matter inputs from river Owoh, Agbara industrial estate and surrounding farmlands and were patchy in spatial distribution.

Keywords: diversity, dominance, perturbations, richness, crustacea, lagoon

Procedia PDF Downloads 721

Authors: Amin Akbari, Dongcai Wang, Huiru Li, Xiaoping Du, Jie Chen

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The effect of vibrational force (VF) on accelerating orthodontic tooth movement depends on the level of delivered stimulation to the tooth in terms of peak load (PL), which requires contacts between the tooth and the VF device. A personalized device ensures the contacts, but the resulting PL distribution on the teeth is unknown. Furthermore, it is unclear whether the PL on particular teeth can be adjusted to the prescribed values. The objective of this study was to investigate the efficacy of apersonalized VF device in controlling the level of stimulation on two teeth, the mandibular canines and 2nd molars. A 3-D finite element (FE) model of human dentition, including teeth, PDL, and alveolar bone, was created from the cone beam computed tomography images of an anonymous subject. The VF was applied to the teeth through a VFdevice consisting of a mouthpiece with engraved tooth profile of the subject and a VF source that applied 0.3 N force with the frequency of 30 Hz. The dentition and mouthpiece were meshed using 10-node tetrahedral elements. Interface elements were created at the interfaces between the teeth and the mouthpiece. The upper and lower teeth bite on the mouthpiece to receive the vibration. The depth of engraved individual tooth profile could be adjusted, which was accomplished by adding a layer of material as an interference or removing a layer of material as a clearance to change the PL on the tooth. The interference increases the PL while the clearance decreases it. Fivemouthpiece design cases were simulated, which included a mouthpiece without interference/clearance; the mouthpieces with bilateral interferences on both mandibular canines and 2nd molars with magnitudes of 0.1, 0.15, and 0.2-mm, respectively; and mouthpiece with bilateral 0.3-mm clearances on the four teeth. Then, the force distributions on the entire dentition were compared corresponding to these adjustments. The PL distribution on the teeth is uneven when there is no interference or clearance. Among all teeth, the anterior segment receives the highest level of PL. Adding 0.1, 0.15, and 0.2-mm interferences to the canines and 2nd molars bilaterally leads to increase of the PL on the canines by 10, 62, and 73 percent and on the 2nd molar by 14, 55, and 87 percent, respectively. Adding clearances to the canines and 2nd molars by removing the contactsbetween these teeth and the mouthpiece results in zero PL on them. Moreover, introducing interference to mandibular canines and 2nd molarsredistributes the PL on the entireteeth. The share of the PL on the anterior teeth are reduced. The use of the personalized mouthpiece ensures contactsof the teeth to the mouthpiece so that all teeth can be stimulated. However, the PL distribution is uneven. Adding interference between a tooth and the mouthpiece increases the PL while introducing clearance decreases the PL. As a result, the PL is redistributed. This study confirms that the level of VF stimulation on the individual tooth can be adjusted to a prescribed value.

Keywords: finite element method, orthodontic treatment, stress analysis, tooth movement, vibrational force

Procedia PDF Downloads 224

Authors: Rundong Li, Peng Wu, Junfeng Zhang, Zhipeng Ren, Chen Yang, Jiahui Gan, Lu Feng, Haibo Tong, Xuemei Xiao, Yuying Chen

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The research of Beidou-3 satellite navigation is on the rise, but in actual work, it is inevitable that satellite data is insecure, research and development is inefficient, and there is no ability to deal with failures in advance. Digital twin technology has obvious advantages in the simulation of life cycle models of aerospace satellite navigation products. In order to meet the increasing demand, this paper builds a Beidou-3 satellite navigation digital twin platform (BDSDTP). The basic establishment of BDSDTP was completed by establishing a digital twin double, Beidou-3 comprehensive digital twin design, predictive maintenance (PdM) mathematical model, and visual interaction design. Finally, this paper provides a time application case of the platform, which provides a reference for the application of BDSDTP in various fields of navigation and provides obvious help for extending the full cycle life of Beidou-3 satellite navigation.

Keywords: BDS-3, digital twin, visualization, PdM

Procedia PDF Downloads 142

Authors: Miky Lee, K. Kim, D. Lim, D. Cho

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This paper presents the planning, rationale for test specification derivation, sampling requirements, test facilities, and result analysis used to conduct lifetime expectancy endurance tests on power window switches (PWS) considering thermally induced mechanical stress under diurnal cyclic temperatures during normal operation (power cycling). The detail process of analysis and test results on the selected PWS set were discussed in this paper. A statistical approach to ‘life time expectancy’ was given to the measurement standards dealing with PWS lifetime determination through endurance tests. The approach choice, within the framework of the task, was explained. The present task was dedicated to voltage drop measurement to derive lifetime expectancy while others mostly consider contact or surface resistance. The measurements to perform and the main instruments to measure were fully described accordingly. The failure data from tests were analyzed to conclude lifetime expectancy through statistical method using Weibull cumulative distribution function. The first goal of this task is to develop realistic worst case lifetime endurance test specification because existing large number of switch test standards cannot induce degradation mechanism which makes the switches less reliable. 2nd goal is to assess quantitative reliability status of PWS currently manufactured based on test specification newly developed thru this project. The last and most important goal is to satisfy customer’ requirement regarding product reliability.

Keywords: power window switch, endurance test, Weibull function, reliability, degradation mechanism

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Authors: Mustafa Metin Donma, Orkide Donma

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Obesity in children particularly draws attention because it may threaten the individual’s future life due to many chronic diseases it may lead to. Most of these diseases, including obesity itself altogether are related to inflammation. For this reason, inflammation-related parameters gain importance. Within this context, complete blood cell counts, ratios or indices derived from these counts have recently found some platform to be used as inflammatory markers. So far, mostly adipokines were investigated within the field of obesity. The liver is at the center of the metabolic pathways network. Metabolic inflammation is closely associated with cellular dysfunction. In this study, hematologic inflammatory markers and two major hepatokines, cytokines produced predominantly by the liver, fibroblast growth factor-21 (FGF-21) and fetuin A were investigated in pediatric obesity. Two groups were constituted from seventy-six obese children based on World Health Organization criteria. Group 1 was composed of children whose age- and sex-adjusted body mass index (BMI) percentiles were between 95 and 99. Group 2 consists of children who are above the 99ᵗʰ percentile. The first and the latter groups were defined as obese (OB) and morbid obese (MO). Anthropometric measurements of the children were performed. Informed consent forms and the approval of the institutional ethics committee were obtained. Blood cell counts and ratios were determined by an automated hematology analyzer. The related ratios and indexes were calculated. Statistical evaluation of the data was performed by the SPSS program. There was no statistically significant difference in terms of neutrophil-to lymphocyte ratio, monocyte-to-high density lipoprotein cholesterol ratio and the platelet-to-lymphocyte ratio between the groups. Mean platelet volume and platelet distribution width values were decreased (p<0.05), total platelet count, red cell distribution width (RDW) and systemic immune inflammation index values were increased (p<0.01) in MO group. Both hepatokines were increased in the same group; however, increases were not statistically significant. In this group, also a strong correlation was calculated between FGF-21 and RDW when controlled by age, hematocrit, iron and ferritin (r=0.425; p<0.01). In conclusion, the association between RDW, a hematologic inflammatory marker, and FGF-21, an inflammation-related hepatokine, found in MO group is an important finding discriminating between OB and MO children. This association is even more powerful when controlled by age and iron-related parameters.

Keywords: childhood obesity, fetuin A , fibroblast growth factor-21, hematologic markers, red cell distribution width

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: A. Hadadi, M. Abdollahi, A. Dustmohammadi

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The growing use of DGs in distribution networks provide many advantages and also cause new problems which should be anticipated and be solved with appropriate solutions. One of the problems is transient voltage drop and short circuit in the electrical network, in the presence of distributed generation - which can lead to instability. The appearance of the short circuit will cause loss of generator synchronism, even though if it would be able to recover synchronizing mode after removing faulty generator, it will be stable. In order to increase system reliability and generator lifetime, some strategies should be planned to apply even in some situations which a fault prevent generators from separation. In this paper, one fault current limiter is installed due to prevent DGs separation from the grid when fault occurs. Furthermore, an innovative objective function is applied to determine the impedance optimal amount of fault current limiter in order to improve transient stability of distributed generation. Fault current limiter can prevent generator rotor's sudden acceleration after fault occurrence and thereby improve the network transient stability by reducing the current flow in a fast and effective manner. In fact, by applying created impedance by fault current limiter when a short circuit happens on the path of current injection DG to the fault location, the critical fault clearing time improve remarkably. Therefore, protective relay has more time to clear fault and isolate the fault zone without any instability. Finally, different transient scenarios of connection plan sustainability of small scale synchronous generators to the distribution network are presented.

Keywords: critical clearing time, fault current limiter, synchronous generator, transient stability, transient states

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Andre M. Carvalho, Pedro Sebastiao

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This article is based on a dissertation that intends to analyze and make a model, intelligently, algorithms based on stochastic processes of a gamification application applied to marketing. Gamification is used in our daily lives to engage us to perform certain actions in order to achieve goals and gain rewards. This strategy is an increasingly adopted way to encourage and retain customers through game elements. The application of gamification aims to encourage children between 6 and 10 years of age to have healthy habits and the purpose of serving as a model for use in marketing. This application was developed in unity; we implemented intelligent algorithms based on stochastic processes, web services to respond to all requests of the application, a back-office website to manage the application and the database. The behavioral analysis of the use of game elements and stochastic processes in children’s motivation was done. The application of algorithms based on stochastic processes in-game elements is very important to promote cooperation and to ensure fair and friendly competition between users which consequently stimulates the user’s interest and their involvement in the application and organization.

Keywords: engage, games, gamification, randomness, stochastic processes

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Authors: Vivek Vaishnav, Shamim Akhtar Ansari

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Teak (Tectona grandis L.f.) belonging to plant family Lamiaceae and the most commercialized timber species is endemic to South-Asia. The adaptive fitness of the species metapopulation was evaluated through its genetic differentiation and assessing the influence of geo-climatic conditions. 290 genotypes were sampled from 29 locations of its natural distribution and the genetic data was incorporated with geo-climatic parameters. Through Bayesian approach based analysis of 43 highly polymorphic ISSR markers, six homogeneous clusters (0.8% genetic variability) were identified. The six clusters were found with the various regimes of the temperature range, i.e., I - 9.10±1.35⁰C, II -6.35±0.21⁰C, III -12.21±0.43⁰C, IV - 10.8±1.06⁰C, V - 11.67±3.04⁰C, and VI - 12.35±0.21⁰C. The population had a very high percentage of LD (21.48%) among the amplified loci possibly due to experiencing restricted gene flow as well as co-adaptation and association of distant/diverse loci/alleles as a result of the stabilized climatic conditions and countless cycles of historical recombination events on a large geological timescale. The same possibly accounts for the narrow distribution of teak as a climax species in the tropical deciduous forests of the country. The regions of strong LD in teak genome significantly associated with climatic parameters also reflect that the species is tolerant to the wide regimes of the temperature range and may possibly withstand global warming and climate change in the coming millennium.

Keywords: Bayesian analysis, inter simple sequence repeat, linkage disequilibrium, marker-geoclimatic association

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

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Authors: Dicky R. Munaf, Ayu Bulan Tisna

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Competitive intelligence (business intelligence) is the process of observing the external environment which often conducted by many organizations to get the relevant information which will be used to create the organization policy, whereas, security intelligence is related to the function of the officers who have the duties to protect the country and its people from every criminal actions that might harm the national and individual security. Therefore, the intelligence dimension of maritime security is associated with all the intelligence activities including the subject and the object that connected to the maritime issues. The concept of intelligence business regarding the maritime security perspective is the efforts to protect the maritime security using the analysis of economic movements as the basic strategic plan. Clearly, a weak maritime security will cause high operational cost to all the economic activities which uses the sea as its media. Thus, it affects the competitiveness of a country compared to the other countries that are able to maintain the maritime law enforcement and secure their marine territory. So, the intelligence business within the security intelligence is important to conduct as the beginning process of the identification against the opponent strategy that might happen in the present or in the future. Thereby, the scenario of the potential impact of all the illegal maritime activities, as well as the strategy in preventing the opponent maneuver can be made.

Keywords: competitive intelligence, maritime security intelligence, intelligent systems, information technology

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Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

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Authors: A. Fernandez Zuvich, I. Gana Watkins, H. Zolotucho, H. Troiani, A. Caneiro, M. Prado, A. L. Soldati

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The study of actinide nanoparticles (NPs) has attracted the attention of the scientific community not only because the lack of information about their ecotoxicological effects but also because the use of NPs could open a new way in the production of nuclear energy. Indeed, it was recently demonstrated that UO2 NPs sintered pellets exhibit closed porosity with improved fission gas retention and radiation-tolerance , ameliorated mechanical properties, and less detriment of the thermal conductivity upon use, making them an interesting option for new nuclear fuels. In this work, we used a combination of diffraction and microscopy tools to characterize the morphology, the crystalline structure and the composition of UO2 nanoparticles doped with 10%wt Gd2O3. The particles were synthesized by a modified sol-gel method at low temperatures. X-ray Diffraction (XRD) studies determined the presence of a unique phase with the cubic structure and Fm3m spatial group, supporting that Gd atoms substitute U atoms in the fluorite structure of UO2. In addition, Field Emission Gun Scanning (FEG-SEM) and Transmission (FEG-TEM) Electron Microscopy images revealed the presence of micrometric agglomerates of nanoparticles, with rounded morphology and an average crystallite size < 50 nm. Energy Dispersive Spectroscopy (EDS) coupled to TEM determined the presence of Gd in all the analyzed crystallites. Besides, FEG-SEM-EDS showed a homogeneous concentration distribution at the micrometer scale indicating that the small size of the crystallites compensates the variation in composition by averaging a large number of crystallites. These techniques, as combined tools resulted thus essential to find out details of morphology and composition distribution at the sub-micrometer scale, and set a standard for developing and analyzing nanoparticulated nuclear fuels.

Keywords: actinide nanoparticles, burnable poison, nuclear fuel, sol-gel

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