Search results for: raw complex data

Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

Abstract:

This paper deals with human activity recognition from sensor data. It is an active research area, and the main objective is to obtain a high recognition rate. In this work, a recognition system based on expert systems is proposed; the recognition is performed using the objects, object states, and gestures and taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions and the activity). The system recognizes complex activities after decomposing them into simple, easy-to-recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

Procedia PDF Downloads 106

Authors: Nasser S. Shebka

Abstract:

Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

Procedia PDF Downloads 85

Authors: Amitha Puranik, V. S. Binu, Seena Biju

Abstract:

Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

Procedia PDF Downloads 374

Authors: Debraj Gangopadhyay, Moumita Das, Ranjan K. Singh, Poonam Tandon

Abstract:

Creatinine is a toxic chemical waste generated from muscle metabolism. Abnormally high levels of creatinine in the body fluid indicate possible malfunction or failure of the kidneys. This leads to a condition termed as creatinine induced nephrotoxicity. N-acetylcysteine is an antioxidant drug which is capable of preventing creatinine induced nephrotoxicity and is helpful to treat renal failure in its early stages. Taurine is another antioxidant drug which serves similar purpose. The kidneys have a natural power that whenever reactive oxygen species radicals increase in the human body, the kidneys make an antioxidant shell so that these radicals cannot harm the kidney function. Taurine plays a vital role in increasing the power of that shell such that the glomerular filtration rate can remain in its normal level. Thus taurine protects the kidneys against several diseases. However, taurine also has some negative effects on the body as its chloramine derivative is a weak oxidant by nature. N-acetylcysteine is capable of inhibiting the residual oxidative property of taurine chloramine. Therefore, N-acetylcysteine is given to a patient along with taurine and this combination is capable of suppressing the negative effect of taurine. Both N-acetylcysteine and taurine being affordable, safe, and widely available medicines, knowledge of the mechanism of their combined effect on creatinine, the favored route of administration, and the proper dose may be highly useful in their use for treating renal patients. Raman spectroscopy is a precise technique to observe minor structural changes taking place when two or more molecules interact. The possibility of formation of a complex between a drug molecule and an analyte molecule in solution can be explored by analyzing the changes in the Raman spectra. The formation of a stable complex of creatinine with N-acetylcysteinein vitroin aqueous solution has been observed with the help of Raman spectroscopic technique. From the Raman spectra of the mixtures of aqueous solutions of creatinine and N-acetylcysteinein different molar ratios, it is observed that the most stable complex is formed at 1:1 ratio of creatinine andN-acetylcysteine. Upon drying, the complex obtained is gel-like in appearance and reddish yellow in color. The complex is hygroscopic and has much better water solubility compared to creatinine. This highlights that N-acetylcysteineplays an effective role in reducing the toxic effect of creatinine by forming this water soluble complex which can be removed through urine. Since the drug taurine is also known to be useful in reducing nephrotoxicity caused by creatinine, the aqueous solution of taurine with those of creatinine and N-acetylcysteinewere mixed in different molar ratios and were investigated by Raman spectroscopic technique. It is understood that taurine itself does not undergo complexation with creatinine as no additional changes are observed in the Raman spectra of creatinine when it is mixed with taurine. However, when creatinine, N-acetylcysteine and taurine are mixed in aqueous solution in molar ratio 1:1:3, several changes occurring in the Raman spectra of creatinine suggest the diminishing toxic effect of creatinine in the presence ofantioxidant drugs N-acetylcysteine and taurine.

Keywords: creatinine, creatinine induced nephrotoxicity, N-acetylcysteine, taurine

Procedia PDF Downloads 148

Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

Abstract:

Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.

Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives

Procedia PDF Downloads 449

Authors: Chi Zhang, Jun Jiang

Abstract:

Constitutive equations are very important in finite element (FE) modeling, and the accuracy of the material constants in the equations have significant effects on the accuracy of the FE models. A wide range of constitutive equations are available; however, fitting the material constants in the constitutive equations could be complex and time-consuming due to the strong non-linearity and relationship between the constants. This work will focus on the development of a set of unified MATLAB programs for fitting the material constants in the constitutive equations efficiently. Users will only need to supply experimental data in the required format and run the program without modifying functions or precisely guessing the initial values, or finding the parameters in previous works and will be able to fit the material constants efficiently.

Keywords: constitutive equations, FE modelling, MATLAB program, non-linear curve fitting

Procedia PDF Downloads 93

Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

Abstract:

Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

Procedia PDF Downloads 155

Authors: Christine Hough, Eddie Abbott-Halpin, Tariq Mahmood, Jessica Giles

Abstract:

This paper draws together the findings from two research studies, each undertaken with cohorts of South Asian Muslim respondents located in the North of England between 2017 and 2019. The first study, entitled Faith Family and Crime (FFC), investigated the extent to which a Muslim family’s social and health well-being is affected by a family member’s involvement in the Criminal Justice System (CJS). This study captured a range of data through a detailed questionnaire and structured interviews. The data from the interview transcripts were analysed using open coding and an application of aspects of the grounded theory approach. The findings provide clear evidence that the respondents were neither well-informed nor supported throughout the processes of the CJS, from arrest to post-sentencing. These experiences gave rise to mental and physical stress, potentially unfair sentencing, and a significant breakdown in communication within the respondents’ families. They serve to highlight a particular aspect of complexity in the current needs of those South Asian Muslim families who find themselves involved in the CJS and is closely connected to family structure, culture, and faith. The second study, referred to throughout this paper as #ImamsBritain (that provides the majority of content for this paper), explores how Imams, in their role as community faith leaders, can best address the complex – and changing - needs of South Asian Muslims families, such as those that emerged in the findings from FFC. The changing socio-economic and political climates of the last thirty or so years have brought about significant changes to the lives of Muslim families, and these have created more complex levels of social, cultural, and faith-based needs for families and individuals. As a consequence, Imams now have much greater demands made of them, and so their role has undergone far-reaching changes in response to this. The #ImamsBritain respondents identified a pressing need to develop a wider range of pastoral and counseling skills, which they saw as extending far beyond the traditional role of the Imam as a religious teacher and spiritual guide. The #ImamsBritain project was conducted with a cohort of British Imams in the North of England. Data was collected firstly through a questionnaire that related to the respondents’ training and development needs and then analysed in depth using the Delphi approach. Through Delphi, the data were scrutinized in depth using interpretative content analysis. The findings from this project reflect the respondents’ individual perceptions of the kind of training and development they need to fulfill their role in 21st Century Britain. They also provide a unique framework for constructing a professional guide for Imams in Great Britain. The discussions and critical analyses in this paper draw on the discourses of professionalization and pastoral care and relevant reports and reviews on Imam training in Europe and Canada.

Keywords: criminal justice system, faith and culture, Imams, Muslim community leadership, professionalization, South Asian family structure

Procedia PDF Downloads 131

Authors: Melaku Tsehay

Abstract:

The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

Procedia PDF Downloads 107

Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

Abstract:

The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions

Procedia PDF Downloads 191

Authors: Hu Zhenxing, Gao Jianxin

Abstract:

Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

Procedia PDF Downloads 492

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 66

Authors: Mahfoodh Saleh Al Sabbagh, Amitabh Mishra, Anwar Al Sheyadi

Abstract:

A tremendous transformation is taking place in the state of education in Sultanate of Oman. The vision 2040 for Higher Education focuses on both academic and technical sides of education aims at improving the quality of education as per higher international standards with emphasis on learning and innovation, creativity and scientific research. The objective is to achieve a proficient education system that keeps abreast of the recent development, the essentials of sustainable development and enhancing the national identity. Higher Education Institutes have contributed immensely to the growth of education in Oman, in this context; Business Organization represents the most complex social structure known today due to its dynamic nature. Employees are considered as one of the dynamic resources of the organization and through their commitment and involvement organization becomes competitive. Organization Culture can be promoted to facilitate the achievement of job satisfaction and employees commitment. The purpose of the research is to explore the impact of Higher Educational Institutions Culture on employee satisfaction, and commitment. Based on primary data, the study was conducted in Higher Education Institutions in the Sultanate of Oman. Data was collected through questionnaire consisting of 60 questions related to culture, satisfaction, and commitment. The sample consisted of 330 employees of leading Higher Education Institutes in the Sultanate of Oman. Structural Equation Modeling was carried out on the data through SPSS and AMOS. Results indicate that culture of organization is significantly related with employees’ satisfaction and commitment both in direct and indirect ways. Significant theoretical and practical implications are driven from the outcomes of the study.

Keywords: organization culture, employee satisfaction and commitment, higher education, Sultanate of Oman

Procedia PDF Downloads 303

Authors: Ankan Roy, Niharika, Samir Kumar Patra

Abstract:

Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

Procedia PDF Downloads 125

Authors: Ariful Islam, Showkat Ahmad Lone

Abstract:

Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

Procedia PDF Downloads 344

Authors: Benbiao Song, Yan Gao, Zhuo Liu

Abstract:

Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

Procedia PDF Downloads 257

Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

Abstract:

The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

Procedia PDF Downloads 387

Authors: Sudeshna Sengupta

Abstract:

Women’s work lives weave a complex fabric of myriad work relations and complex structures. Lives, when seen from the lens of work, is a saga of conjugated oppression by intertwined structures that are vertically and horizontally interwoven in a very complex manner. Women interact with multiple institutions through their work. The interactions and interplay of institutions shape their organization of work. They intersperse productive work with reproductive work, unpaid economic activities with unpaid care work, and all kinds of activities with leisure and self-care. The proposed paper intends to understand how women working as home-based workers in the National Capital Region (NCR) of India are organizing their everyday work, and how the organization of work is influenced by the interplay of structures. Situating itself in a multidisciplinary theoretical framework, this paper brings out how the gendering of work is playing out in the political, economic and social domain and shaping the work-life within the family, and in the paid workspace. The paper will use a primary data source, which is qualitative in nature. It will comprise 15 qualitative interviews of women home-based workers from the National Capital Region. The research uses a life history approach. The sampling was purposive using snowballing as a method. The dataset is part of the primary data (qualitative) collected for the ongoing Ph.D. work in Gender Studies at Ambedkar University Delhi. The home-based workers interviewed were in “non-factory” wage relations based on piece rates with flexible working hours. Their workplaces were their own homes with no spatial divide between living spaces and workspaces. Home-based workers were recognized as a group in the domain of labor economics in the 1980s. When menial work was cheaper than machine work, the capital owners preferred to outsource work as home-based work to women. These production spaces are fragmented and the identity of gender is created within labor processes to favor material accumulation. Both the employers and employees acknowledged the material gain of the capital owner when work was subcontracted to women at home. Simultaneously the market reinforced women’s reproductive role by conforming to patriarchal ideology. The contractors played an important role in implementing localized control on workers and also in finding workers for fragmented, gendered production processes. Their presence helped the employers in bringing together multiple forms of oppression that ranged from creating a structure to flout laws by creating shadow employers. It created an intertwined social and economic structure as well as a workspace where the line between productive and reproductive work gets blurred. The state invisibilized itself either by keeping the sector out of the domain of laws or by not implementing its own laws regulating working conditions or social security. It allowed the local hierarchy to function and define localized working conditions. The productive reproductive continuum reveals a labor control that influenced both the productive and reproductive work of women.

Keywords: informal sector, paid work, women workers, labor processes

Procedia PDF Downloads 159

Authors: Maria Paula Santos, Ana Lucas

Abstract:

Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

Procedia PDF Downloads 210

Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

Abstract:

Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

Procedia PDF Downloads 510

Authors: Maide Yesilyurt, Saide Faydalı

Abstract:

Patients experience pain at different intensities in postoperative. The diagnosis of the pain, the assessment and the success of the treatment and care make the measurement of this finding compulsory. The aim of the study is to determine the evaluation differences numeric pain scales. The descriptive study was conducted with 360 patients with in postoperative. The data were obtained from questionnaires related to six numeric pain scales most preferred in clinical use, and a face-to-face interview technique was used by the researcher. Regarding to numeric pain scale, questions include forth positive and one negative statement. In evaluating the data; chi-square and Pearson correlation tests were used. For the study, the patients’ informed consents, the institution and the ethics committee received permission. In this study, patients' ages are between 18-80, 95.8% of the patients were not informed about pain assessment. Patients evaluated the 5-item numeric scale as the easy, can be answered quickly, accurate, and appropriate for clinical use and the 101 items numeric scale as complex than other scales. Regarding to numeric pain scales with positive statements between age, marital status, educational status, previous surgery, having chronic disease and getting information about pain assessment significant difference has been detected. All numeric pain scales are correlated to each other. As a result, it was determined that as the items in the numerical scales decreased, the patients were able to perceive the scales better, and the items in the scales increased, the patients were in trouble to understand.

Keywords: numeric pain scales, nurse, pain assessment, patient

Procedia PDF Downloads 288

Authors: Matan Cohen, Maxim Shoshany

Abstract:

Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

Procedia PDF Downloads 86

Authors: Dairo Jose Hernandez Paez

Abstract:

The quantum theory of atoms in molecules (QTAIM) allows us to obtain topological information on electronic density in quantum mechanical systems. The QTAIM starts by considering the electron density as a continuous mathematical object. On the other hand, the discretization of electron density is also a mathematical object, which, from discrete mathematics, would allow a new approach to its topological study. From this point of view, it is necessary to develop a series of steps that provide the theoretical support that guarantees its application. Some of the steps that we consider most important are mentioned below: (1) obtain good representations of the electron density through computational calculations, (2) design a methodology for the discretization of electron density, and construct the simplicial complex. (3) Make an analysis of the discrete vector field associating the simplicial complex. (4) Finally, in this research, we propose to use the discrete Morse theory as a mathematical tool to carry out studies of electron density topology.

Keywords: discrete mathematics, Discrete Morse theory, electronic density, computational calculations

Procedia PDF Downloads 96

Authors: Zahra Kouzehgari

Abstract:

Since the early emergence of chaos theory in the 1970s in mathematics and physical science, it has increasingly been developed and adapted in social sciences as well. The non-linear and dynamic characteristics of the theory make it a useful conceptual framework to interpret the complex social systems behavior. Regarding chaotic approach principals, sensitivity to initial conditions, dynamic adoption, strange attractors and unpredictability this paper aims to examine whether chaos approach could interpret the ancient social changes. To do this, at first, a brief history of the chaos theory, its development and application in social science as well as the principals making the theory, then its application in archaeological since has been reviewed. The study demonstrates that although based on existing archaeological records reconstruct the whole social system of the human past, the non-linear approaches in studying social complex systems would be of a great help in finding general order of the ancient societies and would enable us to shed light on some of the social phenomena in the human history or to make sense of them.

Keywords: archaeology, non-linear approach, chaos theory, ancient social systems

Procedia PDF Downloads 276

Authors: Zhibin Lei, Minghui Yang

Abstract:

Ningwu-Jingle basin is a structural syncline which has undergone a complex tectono-thermal history since Cretaceous. It stretches along the strike of the northern Lvliang Mountains which are the most important mountains in the middle and west of North China Craton. The Mesozoic units make up of the core of Ningwu-Jingle Basin, with pre-Mesozoic units making up of its flanks. The available low-temperature thermochronology implies that Ningwu-Jingle Basin has experienced two stages of uplifting: 94±7Ma to 111±8Ma (Albian to Cenomanian) and 62±4 to 75±5Ma (Danian to Maastrichtian). In order to constrain its tectono-thermal history in the Cenozoic, both apatite (U-Th-Sm)/He and fission track dating analysis are applied on 3 Middle Jurassic and 3 Upper Triassic sandstone samples. The central fission track ages range from 74.4±8.8Ma to 66.0±8.0Ma (Campanian to Maastrichtian) which matches well with previous data. The central He ages range from 20.1±1.2Ma to 49.1±3.0Ma (Ypresian to Burdigalian). Inverse thermal modeling is established based on both apatite fission track data and (U-Th-Sm)/He data. The thermal history obtained reveals that all 6 sandstone samples cross the high-temperature limit of fission track partial annealing zone by the uppermost Cretaceous and that of He partial retention zone by the uppermost Eocene to the early Oligocene. The result indicates that the middle and west of North China Craton is not stable in the Cenozoic.

Keywords: apatite fission track thermochronology, apatite (u–th)/he thermochronology, Ningwu-Jingle basin, North China craton, tectono-thermal history

Procedia PDF Downloads 253

Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

Abstract:

Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

Procedia PDF Downloads 143

Authors: Meisam Moghadasi, Hassan Ali Ozgoli, Foad Farhani

Abstract:

In this research, firstly, a commercial gas sweetening unit with methyl-di-ethanol-amine (MDEA) solution is simulated and comprised in an integrated model in accordance with Aspen HYSYS software. For evaluation purposes, in the second step, the results of the simulation are compared with operating data gathered from South Pars Gas Complex (SPGC). According to the simulation results, the considerable energy potential contributed to the pressure difference between absorber and regenerator columns causes this energy driving force to be applied in power recovery turbine (PRT). In the last step, the amount of waste hydraulic energy is calculated, and its recovery methods are investigated.

Keywords: gas sweetening unit, simulation, MDEA, power recovery turbine, waste-to-energy

Procedia PDF Downloads 172

Authors: Yassir Abdelrazig, Ren Moses

Abstract:

Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

Procedia PDF Downloads 333

Authors: Awotidebe Taofeek, Oyinsuyi Oluwafunmbi

Abstract:

Psychosocial factors play a significant role in physical activity participation in diseased conditions and the general population. However, little is known about the role of exercise self-efficacy (ESE), exercise perceived barriers (EPB), and social support (SOS) in patients with asthma. This study investigated the influence of psychosocial factors on physical activity participation in patients with asthma in ile-ife. This cross-sectional study involved 130 patients with asthma. They were recruited from the Chest Clinic of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife using purposive sampling technique. Ethical approval was obtained from the Ethics and Research Committee of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife, Nigeria. Socio-demographic characteristics of respondents were recorded. Information on ESE, EPB, and SOS were obtained using Exercise Self-Efficacy, Exercise Benefit, and Barrier and Medical Outcome Social Support Scales respectively. Physical activity level was assessed in the last 7 days using international physical activity questionnaire. Descriptive and inferential statistics were used to analyze the data. Alpha level was set at p<0.5. The mean age of the respondents was 25.15 ± 9.38, and a majority, 110 (84.60%), engaged in low physical activity, 69(53%) had low exercise self-efficacy. However, less than two-third 80 (62.20%) reported high social support, with the majority of 95 (73.10%) reported high exercise perceived barriers. The means of ESE for male and femalerespondents were 29.01 ± 20.62 and 24.35 ± 17.36, respectively. The means of SOS formale and female respondents were 49.52 ± 22.22 and 61.87 ± 22.66, respectively. Themeans of EPB for male and female respondents were 53.37 ± 10.23 and 57.43 ± 9.65, respectively. The respondents were comparable in exercise self-efficacy and physicalactivity level (p>0.05). However, there were significant differences in social support (t=-2.791; p=0.006) and exercise perceived barriers (t=-2.108, p=0.037).Theresultsshowthattherewasasignificantrelationshipbetweenexerciseperceivedbarriersandlowphysicalactivitylevel(r=-0.216;p=0.023).TherewasasignificantassociationbetweenExerciseself-efficacyandmarried individuals(OR=0.967;95%CI=0.936-0.998;p= 0.037). Similarly, However,thereweresignificantassociationsbetweensocialsupport Andagegroup35-54years(OR=1.036;95%CI=1.007-1.067;p=0.014),females(OR= 1.024;95%CI=1.006;p=0.009)andmarriedindividuals(OR=1.049;95%CI=1.020-1.079. p=0.001).Therewasasignificantassociationbetweenexerciseperceivedbarriersand females(OR=1.043;95%CI=1.002-1.085;p=0.040).However, thereweresignificant associationsbetweenexerciseperceivedbarriersandoccupationgroup;civilservants (OR=1.092;95%CI=1.009-1.182;p=0.028),retiree(OR=1.092;95%CI=1.040-1.469;p= 0.016)andstudents(OR=1.110;95%CI=1.040;p=0.002). Inconclusion,agreaterpercentageofpatientswithasthmahadlowphysicalactivityleveland it was associatedwithhighexerciseperceivedbarriers,whileexerciseself-efficacyandsocialsupportwerenot.

Keywords: asthma, psychosocial factors, physical activity, physical fitness

Procedia PDF Downloads 122

Authors: C. Mayr, J. Periya, A. Kariminezhad

Abstract:

In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 235