Search results for: time series data mining

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

Procedia PDF Downloads 235

Authors: Kotaro Sasai, Daijiro Mizutani, Kiyoyuki Kaito

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Expressways in Japan have been built in an accelerating manner since the 1960s with the aid of rapid economic growth. About 40 percent in length of expressways in Japan is now 30 years and older and has become superannuated. Time-related deterioration has therefore reached to a degree that administrators, from a standpoint of operation and maintenance, are forced to take prompt measures on a large scale aiming at repairing inner damage deep in pavements. These measures have already been performed for bridge management in Japan and are also expected to be embodied for pavement management. Thus, planning methods for the measures are increasingly demanded. Deterioration of layers around road surface such as surface course and binder course is brought about at the early stages of whole pavement deterioration process, around 10 to 30 years after construction. These layers have been repaired primarily because inner damage usually becomes significant after outer damage, and because surveys for measuring inner damage such as Falling Weight Deflectometer (FWD) survey and open-cut survey are costly and time-consuming process, which has made it difficult for administrators to focus on inner damage as much as they have been supposed to. As expressways today have serious time-related deterioration within them deriving from the long time span since they started to be used, it is obvious the idea of repairing layers deep in pavements such as base course and subgrade must be taken into consideration when planning maintenance on a large scale. This sort of maintenance requires precisely predicting degrees of deterioration as well as grasping the present situations of pavements. Methods for predicting deterioration are determined to be either mechanical or statistical. While few mechanical models have been presented, as far as the authors know of, previous studies have presented statistical methods for predicting deterioration in pavements. One describes deterioration process by estimating Markov deterioration hazard model, while another study illustrates it by estimating Proportional deterioration hazard model. Both of the studies analyze deflection data obtained from FWD surveys and present statistical methods for predicting deterioration process of layers around road surface. However, layers of base course and subgrade remain unanalyzed. In this study, data collected from FWD surveys are analyzed to predict deterioration process of layers deep in pavements in addition to surface layers by a means of estimating a deterioration hazard model using continuous indexes. This model can prevent the loss of information of data when setting rating categories in Markov deterioration hazard model when evaluating degrees of deterioration in roadbeds and subgrades. As a result of portraying continuous indexes, the model can predict deterioration in each layer of pavements and evaluate it quantitatively. Additionally, as the model can also depict probability distribution of the indexes at an arbitrary point and establish a risk control level arbitrarily, it is expected that this study will provide knowledge like life cycle cost and informative content during decision making process referring to where to do maintenance on as well as when.

Keywords: deterioration hazard model, falling weight deflectometer, inner damage, load bearing capacity, pavement

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 386

Authors: M. K. Benhaoua, A. K. Singh, A. E. Benyamina, P. Boulet

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Mapping parallelized tasks of applications onto these MPSoCs can be done either at design time (static) or at run-time (dynamic). Static mapping strategies find the best placement of tasks at design-time, and hence, these are not suitable for dynamic workload and seem incapable of runtime resource management. The number of tasks or applications executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet these constraints. This paper describes a new Spiral Dynamic Task Mapping heuristic for mapping applications onto NoC-based Heterogeneous MPSoC. This heuristic is based on packing strategy and routing Algorithm proposed also in this paper. Heuristic try to map the tasks of an application in a clustering region to reduce the communication overhead between the communicating tasks. The heuristic proposed in this paper attempts to map the tasks of an application that are most related to each other in a spiral manner and to find the best possible path load that minimizes the communication overhead. In this context, we have realized a simulation environment for experimental evaluations to map applications with varying number of tasks onto an 8x8 NoC-based Heterogeneous MPSoCs platform, we demonstrate that the new mapping heuristics with the new modified dijkstra routing algorithm proposed are capable of reducing the total execution time and energy consumption of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature.

Keywords: multiprocessor system on chip, MPSoC, network on chip, NoC, heterogeneous architectures, run-time mapping heuristics, routing algorithm

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Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Laila Alkhayat

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In this study, the researcher explored the positive and negative effects of children watching YouTube on changing social values from the perspective of parents in Kuwait. This study also explored whether any correlation exists between changed values from watching YouTube and the following variables: relationship with a child, social situation, school level, gender, and age. The researcher collected data from 286 questionnaires distributed randomly to parents in Kuwait. The results of the study show that parents face many disadvantages when dealing with children watching YouTube, such as children spending too much time in front of screens, inability to organize bedtime, and children’s social isolation. However, the researcher found some positives come from watching YouTube, such as learning new information, enabling children to search for new information, and introducing children to the culture of their society and other cultures around them. Moreover, this study found that boys are more likely to have negative viewing habits than girls. Given the results, this study shows that the biggest impact on social values from children watching YouTube is that they are preoccupied with watching YouTube and they waste time, which makes them feel disturbed, and this affects the value of time management and delays children’s sleeping times. This study concludes that watching YouTube simultaneously has negative and positive effects on changing social values, but it plays a negative role in changing social values of children from the parents’ perspective.

Keywords: YouTube, children, social value, social media effects

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

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Global awareness on energy security and climate change has created much interest in assessing energy efficiency performance. A number of previous studies have contributed to evaluate energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production frame work of desirable and undesirable outputs, in this paper we construct energy efficiency performance index for measuring energy efficiency performance by using environmental DEA model with CO2 emissions. We finally apply the index proposed to assess the energy efficiency performance in OPEC over time.

Keywords: energy efficiency, environmental, OPEC, data envelopment analysis

Procedia PDF Downloads 372

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 287

Authors: M. Humayun Kabir, Mahamuda Afroze, K. Maudood Elahi

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Since the late 1900s, unplanned and rapid urbanization processes have drastically altered the land, reduced water bodies, and decreased vegetation cover in the capital city of Bangladesh, Dhaka. The capitalist modes of urbanization results in the encroachment of the surface water bodies in this city. The main goal of this study is to investigate the change detection of water bodies in Dhaka city, analyzing spatial distribution of water bodies and calculating the changing rate of it. This effort aims to influence public policy for environmental justice initiatives around protecting water bodies for ensuring proper function of the urban ecosystem. This study accomplishes research goal by compiling satellite imageries into GIS software to understand the changes of water bodies in Dhaka city. The work focuses on the late 20th century to early 21st century to analyze this city before and after major infrastructural changes occurred in unplanned manner. The land use of the study area has been classified into four categories, and the areas of the different land use have been calculated using MS Excel and SPSS. The results reveal that the urbanization expanded from central to northern part and major encroachment occurred at the western and eastern part of the city. It has also been found that, in 1988, the total area of water bodies was 8935.38 hectares, and it gradually decreased, and in 1998, 2008, 2017, the total areas of water bodies reached 6065.73, 4853.32, 2077.56 hectares, respectively. Rapid population growth, unplanned urbanization, and industrialization have generated pressure to change the land use pattern in Dhaka city. These expansion processes are engulfing wetland, water bodies, and vegetation cover without considering environmental impact. In order to regain the wetland and surface water bodies, the concern authorities must implement laws and act as a legal instrument in this regard and take action against the violators of it. This research is the synthesis of time series data that provides a complete picture of the water body’s status of Dhaka city that might help to make plans and policies for water body conservation.

Keywords: ecosystem, GIS, industrialization, land use, remote sensing, urbanization

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Authors: A. C. Blaga, A. Cârlescu, M. Turnea, A. I. Galaction, D. Caşcaval

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The performance of an aerobic stirred bioreactor for fungal fermentation was analyzed on the basis of mixing time and oxygen mass transfer coefficient, by quantifying the influence of some specific geometrical and operational parameters of the bioreactor, as well as the rheological behavior of Penicillium chrysogenum broth (free mycelia and mycelia aggregates). The rheological properties of the fungus broth, controlled by the biomass concentration, its growth rate, and morphology strongly affect the performance of the bioreactor. Experimental data showed that for both morphological structures the accumulation of fungus biomass induces a significant increase of broths viscosity and modifies the rheological behavior. For lower P. chrysogenum concentrations (both morphological conformations), the mixing time initially increases with aeration rate, reaches a maximum value and decreases. This variation can be explained by the formation of small bubbles, due to the presence of solid phase which hinders the bubbles coalescence, the rising velocity of bubbles being reduced by the high apparent viscosity of fungus broths. By biomass accumulation, the variation of mixing time with aeration rate is gradually changed, the continuous reduction of mixing time with air input flow increase being obtained for 33.5 g/l d.w. P. chrysogenum. Owing to the superior apparent viscosity, which reduces considerably the relative contribution of mechanical agitation to the broths mixing, these phenomena are more pronounced for P. chrysogenum free mycelia. Due to the increase of broth apparent viscosity, the biomass accumulation induces two significant effects on oxygen transfer rate: the diminution of turbulence and perturbation of bubbles dispersion - coalescence equilibrium. The increase of P. chrysogenum free mycelia concentration leads to the decrease of kla values. Thus, for the considered variation domain of the main parameters taken into account, namely air superficial velocity from 8.36 10-4 to 5.02 10-3 m/s and specific power input from 100 to 500 W/m3, kla was reduced for 3.7 times for biomass concentration increase from 4 to 36.5 g/l d.w. The broth containing P. crysogenum mycelia aggregates exhibits a particular behavior from the point of view of oxygen transfer. Regardless of bioreactor operating conditions, the increase of biomass concentration leads initially to the increase of oxygen mass transfer rate, the phenomenon that can be explained by the interaction of pellets with bubbles. The results are in relation with the increase of apparent viscosity of broths corresponding to the variation of biomass concentration between the mentioned limits. Thus, the apparent viscosity of the suspension of fungus mycelia aggregates increased for 44.2 times and fungus free mycelia for 63.9 times for CX increase from 4 to 36.5 g/l d.w. By means of the experimental data, some mathematical correlations describing the influences of the considered factors on mixing time and kla have been proposed. The proposed correlations can be used in bioreactor performance evaluation, optimization, and scaling-up.

Keywords: biomass concentration, mixing time, oxygen mass transfer, P. chrysogenum broth, stirred bioreactor

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Authors: Taha Zakaraia Abdel Wahid

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The behavior of the unsteady non-equilibrium distribution function for a dilute gas under the effect of non-linear thermal radiation field is presented. For the best of our knowledge this is done for the first time at all. The distinction and comparisons between the unsteady perturbed and the unsteady equilibrium velocity distribution functions are illustrated. The equilibrium time for the dilute gas is determined for the first time. The non-equilibrium thermodynamic properties of the system (gas+the heated plate) are investigated. The results are applied to the Argon gas, for various values of radiation field intensity. 3D-Graphics illustrating the calculated variables are drawn to predict their behavior. The results are discussed.

Keywords: dilute gas, radiation field, exact solutions, travelling wave method, unsteady BGK model, irreversible thermodynamics, unsteady non-equilibrium distribution functions

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Thomas Suarez, Anne-Sophie Grenouilleau, Erwan Autin, Alexandre Biosse-Duplan, Emmanuelle Blondet, Laurence Chazalette, Marie Coniel, Agnes Dessaigne, Sylvie Lascols, Andrea Lasserre, Candice Legris, Pierre Liot, Aline Metais, Karine Petitprez, Christophe Varlet, Christian Saout

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Background: The role of biological sex and gender identity -whether assigned or chosen- as health determinants are far from a recent discovery: several reports have stressed out how being a woman or a man could affect health on various scales. However, taking it into consideration beyond stereotypes and rigid binary assumptions still seems to be a work in progress. Method: The report is a synthesis on a variety of specific topics, each of which was studied by a specialist from the French National Authority for Health (HAS), through an analysis of existing literature on both healthcare policy construction process and instruments (norms, data analysis, clinical trials, guidelines, and professional practices). This work also implied a policy analysis of French recent public health laws and a retrospective study of guidelines with a gender mainstreaming approach. Results: The analysis showed that though sex and gender were well-known determinants of health, their consideration by both public policy and health operators was often incomplete, as it does not incorporate how sex and gender interact, as well as how they interact with other factors. As a result, the health and social care systems and their professionals tend to reproduce some stereotypical and inadequate habits. Though the data available often allows to take sex and gender into consideration, such data is often underused in practice guidelines and policy formulation. Another consequence is a lack of inclusiveness towards transgender or intersex persons. Conclusions: This report first urges for raising awareness of all the actors of health, in its broadest definition, that sex and gender matter beyond first-look conclusions. It makes a series of recommendations in order to reshape policy construction in the health sector on the one hand and to design public health instruments to make them more inclusive regarding sex and gender on the other hand. The HAS finally committed to integrate sex and gender preoccupations in its workings methods, to be a driving force in the spread of these concerns.

Keywords: biological sex, determinants of health, gender, healthcare policy instruments, social accompaniment

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Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

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Authors: Mequanint Birhan

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Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for both vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options sometimes illegally. The root cause of this is corruption, which leads to traffic jams, stopping, and packing vehicles beyond their safe carrying capacity, and violating the human rights and freedoms of passengers. This study focused on the optimizing time of passengers had to wait in public vehicle stations. This applied research employed both data gathering sources and mixed approaches, then 166 samples of key informants of transport station were taken by using the Slovin sampling formula. The length of time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The minimal response time for passengers and vehicles queuing to reach their final destination at the stations of the Tepi, Mizan, and Bonga towns was determined. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4hr to 1.5hr, quality, safety and designed load performance calculations employed. Stakeholders are asked to put the model into practice and monitor the results obtained.

Keywords: Arena 14 automatic rockwell, queue, transport services, vehicle stations

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Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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Authors: Snehal L. Kadam, Shriniwas B. Kulkarni

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Flexible electrode material with high surface area and good electrochemical properties is the current trend captivating the researchers across globe for application in the next generation energy storage field. In the present work, crumpled sheet like reduced graphene oxide grown on carbon cloth by the hydrothermal method with a series of different deposition temperatures at fixed time. The influence of the deposition temperature on the structural, morphological, optical and supercapacitive properties of the electrode material was investigated by XRD, RAMAN, XPS, TEM, FE-SEM, UV-VISIBLE and electrochemical characterization techniques.The results show that the hydrothermally synthesized reduced graphene oxide on carbon cloth has sheet like mesoporous structure. The reduced graphene oxide material at 160°C exhibits the best supercapacitor performance, with a specific capacitance of 443 F/g at scan rate 5mV/sec. Moreover, stability studies show 97% capacitance retention over 1000 CV cycles. This result shows that hydrothermally synthesized RGO on carbon cloth is the potential electrode material and would be used in the next-generation wearable energy storage systems. The detailed analysis and results will be presented at the conference.

Keywords: graphene oxide, reduced graphene oxide, carbon cloth, deposition temperature, supercapacitor

Procedia PDF Downloads 178

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

Procedia PDF Downloads 609

Authors: Adem Acır

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In this study, time dependent neutronic analysis of incineration of minor actinides of a Laser Fusion Inertial Confinement Fusion Fission Energy (LIFE) engine was performed. The calculations were carried out by using MCNP codes with ENDF/B.VI neutron data library. In the neutronic calculations, TRISO particles fueled with minor actinides with natural lithium coolant were performed. The natural lithium cooled LIFE engine used 10 % TRISO fuel minor actinides composition. Tritium breeding ratios (TBR) and energy multiplication factor (M) burnup values were computed as 1.46 and 3.75, respectively. The reactor operation time was calculated as ~ 21 years. The burnup values were obtained as ~1060 GWD/MT, respectively. As a result, the very higher burnup were achieved of LIFE engine.

Keywords: Monte Carlo, minor actinides, nuclear waste, LIFE engine

Procedia PDF Downloads 279

Authors: Andrew Terhemen Tyowua, Zhibing Zhang, Michael J. Adams

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Water vapor sorption data at a range of temperatures (25–70 °C) have been obtained for starch (corn and wheat) and non-starch (carrageenan and xanthan gum) hydrocolloid particles in the form of a thin slab. The results reveal that the data may be more accurately described by an existing sigmoidal rather than a Fickian model. The sigmoidal model accounts for the initial surface sorption before the onset of bulk diffusion. At relatively small water activities (≤ 0.3), the absorption of the moisture caused the particles to be plasticized, but at greater activity values (> 0.3), anti-plasticization was induced. However, it was found that for the whole range of water activities and temperatures studied, the data could be characterized by a single non-dimensional number, which was termed the non-Fickian diffusion number where τ is the characteristic time of surface sorption, D is the bulk diffusion coefficient and L is the thickness of the layer of particles. The activation energy suggested that the anti-plasticization mechanism was the result of a reduction in the molecular free volume or an increase in crystallinity.

Keywords: anti-plasticization, arrhenius behavior, diffusion coefficient, hygroscopic polymers, moisture migration, non-fickian sigmoidal model

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Authors: Maressa Aires de Proenca

Abstract:

The inclusion of a gender perspective in peace operations is based on a series of conventions, treaties, and resolutions designed to protect and include women addressing gender mainstreaming. The UN Security Council recognizes that women's participation and gender equality within peace operations are indispensable for achieving sustainable development and peace. However, the participation of women in the field of peace and security is still embryonic. There are gaps when we think about female participation in conflict resolution and peace promotion spaces, and it does not seem clear how women are present in these spaces. This absence may correspond to silence about representation and the guarantee of the female perspective within the context of peace promotion. Thus, the present research aimed to describe the panorama of the participation of women who are currently active in the 14 active UN peace operations, which are: 1) MINUJUSTH, Haiti, 2) MINURSO, Western Sahara, 3) MINUSCA, Central African Republic, 4) MINUSMA, Mali, 5) MONUSCO, the Democratic Republic of the Congo, 6) UNAMID, Darfur, 7) UNDOF, Golan, 8) UNFICYP, Cyprus, 9) UNIFIL, Lebanon, 10) UNISFA, Abyei, 11) UNMIK, Kosovo, 12) UNMISS, South Sudan, 13) UNMOGIP, India, and Pakistan, and 14) UNTSO, Middle East. A database was constructed that reported: (1) position held by the woman in the peace operation, (2) her profession, (3) educational level, (4) marital status, (5) religion, (6) nationality, (8) number of years working with peace operations, (9) whether the operation in which it operates has provided training on gender issues. For the construction of this database, official reports and statistics accessed through the UN Peacekeeping Resource Hub were used; The United Nations Statistical Commission, Peacekeeping Master Open Datasets, The Armed Conflict Database (ACD), The International Institute for Strategic Studies (IISS) database; Armed Conflict Location & Event Data Project (ACLED) database; from the Evidence and Data for Gender Equality (EDGE) database. In addition to access to databases, peacekeeping operations will be contacted directly, and data requested individually. The database showed that the presence of women in these peace operations is still incipient, but growing. There are few women in command positions, and most of them occupy administrative or human-care positions.

Keywords: women, peace and security, peacekeeping operations, peace studies

Procedia PDF Downloads 126

Authors: Chong-Yang Qiao

Abstract:

Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: mobile augmented reality, remote collaboration, user experience, cognition model

Procedia PDF Downloads 184

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 106

Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

Procedia PDF Downloads 396