Search results for: survival data analysis
39898 Algorithm for Modelling Land Surface Temperature and Land Cover Classification and Their Interaction
Authors: Jigg Pelayo, Ricardo Villar, Einstine Opiso
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The rampant and unintended spread of urban areas resulted in increasing artificial component features in the land cover types of the countryside and bringing forth the urban heat island (UHI). This paved the way to wide range of negative influences on the human health and environment which commonly relates to air pollution, drought, higher energy demand, and water shortage. Land cover type also plays a relevant role in the process of understanding the interaction between ground surfaces with the local temperature. At the moment, the depiction of the land surface temperature (LST) at city/municipality scale particularly in certain areas of Misamis Oriental, Philippines is inadequate as support to efficient mitigations and adaptations of the surface urban heat island (SUHI). Thus, this study purposely attempts to provide application on the Landsat 8 satellite data and low density Light Detection and Ranging (LiDAR) products in mapping out quality automated LST model and crop-level land cover classification in a local scale, through theoretical and algorithm based approach utilizing the principle of data analysis subjected to multi-dimensional image object model. The paper also aims to explore the relationship between the derived LST and land cover classification. The results of the presented model showed the ability of comprehensive data analysis and GIS functionalities with the integration of object-based image analysis (OBIA) approach on automating complex maps production processes with considerable efficiency and high accuracy. The findings may potentially lead to expanded investigation of temporal dynamics of land surface UHI. It is worthwhile to note that the environmental significance of these interactions through combined application of remote sensing, geographic information tools, mathematical morphology and data analysis can provide microclimate perception, awareness and improved decision-making for land use planning and characterization at local and neighborhood scale. As a result, it can aid in facilitating problem identification, support mitigations and adaptations more efficiently.Keywords: LiDAR, OBIA, remote sensing, local scale
Procedia PDF Downloads 28039897 Adaptive Data Approximations Codec (ADAC) for AI/ML-based Cyber-Physical Systems
Authors: Yong-Kyu Jung
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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity
Procedia PDF Downloads 7439896 Identifying the Faces of colonialism: An Analysis of Gender Inequalities in Economic Participation in Pakistan through Postcolonial Feminist Lens
Authors: Umbreen Salim, Anila Noor
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This paper analyses the influences and faces of colonialism in women’s participation in economic activity in postcolonial Pakistan, through postcolonial feminist economic lens. It is an attempt to probe the shifts in gender inequalities that have existed in three stages; pre-colonial, colonial, and postcolonial times in the Indo-Pak subcontinent. It delves into an inquiry of pre-colonial as it is imperative to understand the situation and context before colonisation in order to assess the deviations associated with its onset. Hence, in order to trace gender inequalities this paper analyses from Mughal Era (1526-1757) that existed before British colonisation, then, the gender inequalities that existed during British colonisation (1857- 1947) and the associated dynamics and changes in women’s vulnerabilities to participate in the economy are examined. Followed by, the postcolonial (1947 onwards) scenario of discriminations and oppressions faced by women. As part of the research methodology, primary and secondary data analysis was done. Analysis of secondary data including literary works and photographs was carried out, followed by primary data collection using ethnographic approaches and participatory tools to understand the presence of coloniality and gender inequalities embedded in the social structure through participant’s real-life stories. The data is analysed using feminist postcolonial analysis. Intersectionality has been a key tool of analysis as the paper delved into the gender inequalities through the class and caste lens briefly touching at religion. It is imperative to mention the significance of the study and very importantly the practical challenges as historical analysis of 18th and 19th century is involved. Most of the available work on history is produced by a) men and b) foreigners and mostly white authors. Since the historical analysis is mostly by men the gender analysis presented misses on many aspects of women’s issues and since the authors have been mostly white European gives it as Mohanty says, ‘under western eyes’ perspective. Whereas the edge of this paper is the authors’ deep attachment, belongingness as lived reality and work with women in Pakistan as postcolonial subjects, a better position to relate with the social reality and understand the phenomenon. The study brought some key results as gender inequalities existed before colonisation when women were hidden wheel of stable economy which was completely invisible. During the British colonisation, the vulnerabilities of women only increased and as compared to men their inferiority status further strengthened. Today, the postcolonial woman lives in deep-rooted effects of coloniality where she is divided in class and position within the class, and she has to face gender inequalities within household and in the market for economic participation. Gender inequalities have existed in pre-colonial, during colonisation and postcolonial times in Pakistan with varying dynamics, degrees and intensities for women whereby social class, caste and religion have been key factors defining the extent of discrimination and oppression. Colonialism may have physically ended but the coloniality remains and has its deep, broad and wide effects in increasing gender inequalities in women’s participation in the economy in Pakistan.Keywords: colonialism, economic participation, gender inequalities, women
Procedia PDF Downloads 20139895 In-situ Acoustic Emission Analysis of a Polymer Electrolyte Membrane Water Electrolyser
Authors: M. Maier, I. Dedigama, J. Majasan, Y. Wu, Q. Meyer, L. Castanheira, G. Hinds, P. R. Shearing, D. J. L. Brett
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Increasing the efficiency of electrolyser technology is commonly seen as one of the main challenges on the way to the Hydrogen Economy. There is a significant lack of understanding of the different states of operation of polymer electrolyte membrane water electrolysers (PEMWE) and how these influence the overall efficiency. This in particular means the two-phase flow through the membrane, gas diffusion layers (GDL) and flow channels. In order to increase the efficiency of PEMWE and facilitate their spread as commercial hydrogen production technology, new analytic approaches have to be found. Acoustic emission (AE) offers the possibility to analyse the processes within a PEMWE in a non-destructive, fast and cheap in-situ way. This work describes the generation and analysis of AE data coming from a PEM water electrolyser, for, to the best of our knowledge, the first time in literature. Different experiments are carried out. Each experiment is designed so that only specific physical processes occur and AE solely related to one process can be measured. Therefore, a range of experimental conditions is used to induce different flow regimes within flow channels and GDL. The resulting AE data is first separated into different events, which are defined by exceeding the noise threshold. Each acoustic event consists of a number of consequent peaks and ends when the wave diminishes under the noise threshold. For all these acoustic events the following key attributes are extracted: maximum peak amplitude, duration, number of peaks, peaks before the maximum, average intensity of a peak and time till the maximum is reached. Each event is then expressed as a vector containing the normalized values for all criteria. Principal Component Analysis is performed on the resulting data, which orders the criteria by the eigenvalues of their covariance matrix. This can be used as an easy way of determining which criteria convey the most information on the acoustic data. In the following, the data is ordered in the two- or three-dimensional space formed by the most relevant criteria axes. By finding spaces in the two- or three-dimensional space only occupied by acoustic events originating from one of the three experiments it is possible to relate physical processes to certain acoustic patterns. Due to the complex nature of the AE data modern machine learning techniques are needed to recognize these patterns in-situ. Using the AE data produced before allows to train a self-learning algorithm and develop an analytical tool to diagnose different operational states in a PEMWE. Combining this technique with the measurement of polarization curves and electrochemical impedance spectroscopy allows for in-situ optimization and recognition of suboptimal states of operation.Keywords: acoustic emission, gas diffusion layers, in-situ diagnosis, PEM water electrolyser
Procedia PDF Downloads 15039894 Hidden Hot Spots: Identifying and Understanding the Spatial Distribution of Crime
Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell
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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.Keywords: crime, narrative, video, neighborhood
Procedia PDF Downloads 23539893 An Infinite Mixture Model for Modelling Stutter Ratio in Forensic Data Analysis
Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer
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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter
Procedia PDF Downloads 32139892 Determination of Hydrocarbon Path Migration from Gravity Data Analysis (Ghadames Basin, Southern Tunisia, North Africa)
Authors: Mohamed Dhaoui, Hakim Gabtni
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The migration of hydrocarbons is a fairly complicated process that depends on several parameters, both structural and sedimentological. In this study, we will try to determine secondary migration paths which convey hydrocarbon from their main source rock to the largest reservoir of the Paleozoic petroleum system of the Tunisian part of Ghadames basin. In fact, The Silurian source rock is the main source rock of the Paleozoic petroleum system of the Ghadames basin. However, the most solicited reservoir in this area is the Triassic reservoir TAGI (Trias Argilo-Gréseux Inférieur). Several geochemical studies have confirmed that oil products TAGI come mainly from the Tannezuft Silurian source rock. That being said that secondary migration occurs through the fault system which affects the post-Silurian series. Our study is based on analysis and interpretation of gravity data. The gravity modeling was conducted in the northern part of Ghadames basin and the Telemzane uplift. We noted that there is a close relationship between the location of producing oil fields and gravity gradients which separate the positive and negative gravity anomalies. In fact, the analysis and transformation of the Bouguer anomaly map, and the residual gravity map allowed as understanding the architecture of the Precambrian in the study area, thereafter gravimetric models were established allowed to determine the probable migration path.Keywords: basement, Ghadames, gravity, hydrocarbon, migration path
Procedia PDF Downloads 35339891 Endothelial Dysfunction in Non-Alcoholic Fatty Liver Disease: An Updated Meta-Analysis
Authors: Anit S. Malhotra, Ajay Duseja, Neelam Chadha
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Endothelial dysfunction is a precursor to atherosclerosis, and flow-mediated dilatation (FMD) in the brachial artery is the commonest method to evaluate endothelial function in humans. Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver disorders encountered in clinical practice. An earlier meta-analysis had quantitatively assessed the degree of endothelial dysfunction using FMD. However, the largest study investigating the relation of FMD with NAFLD was published after that meta-analysis. In addition, that meta-analysis did not include some studies, including one from our centre. Therefore, an updating the previous meta-analysis was considered important. We searched PubMed, Cochrane Library, Embase, Scopus, SCI, Google Scholar, conference proceedings, and references of included studies till June 2017 to identify observational studies evaluating endothelial function using FMD in patients with non-alcoholic fatty liver disease. Data was analyzed using MedCalc. Fourteen studies were found eligible for inclusion in the meta-analysis. Patients with NAFLD had lower brachial artery FMD as compared to controls, standardized mean difference (random effects model) being –1.279%; 95% confidence interval (CI), –1.478 to –0.914. The effect size became smaller after addition of the recent study with the largest sample size was included compared with the earlier meta-analysis. In conclusion, patients with NAFLD had low FMD values indicating that they are at a higher risk of cardiovascular disease although our results suggest the effect size is not as large as reported previously.Keywords: endothelial dysfunction, flow-mediated dilatation, meta-analysis, non-alcoholic fatty liver disease
Procedia PDF Downloads 18739890 Unlocking Health Insights: Studying Data for Better Care
Authors: Valentina Marutyan
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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.Keywords: data mining, healthcare, big data, large amounts of data
Procedia PDF Downloads 6539889 Life Cycle Assesment (LCA) Study of Shrimp Fishery in the South East Coast of Arabian Sea
Authors: Leela Edwin, Rithin Joseph, P. H. Dhiju Das, K. A. Sayana, P. S. Muhammed Sherief
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The shrimp trawl fishery is considered one of the more valuable fisheries from the South east Coast of Arabian Sea. Inventory data for the shrimp were collected over 1 year period and used to carry out a life cycle assessment (LCA). LCA was performed to assess and compare the environmental impacts associated with the fishing operations related to shrimp fishery. This analysis included the operation of the vessels, together with major inputs related to the production of diesel, trawl nets, or anti-fouling paints. Data regarding vessel operation was obtained from the detailed questionnaires filled out by 180 trawlers. The analysis on environmental impacts linked to shrimp extraction on a temporal scale, showed that varying landings enhanced the environmental burdens mainly associated with activities related to diesel production, transport and consumption of the fishing vessels. Discard rates for trawlers were also identified as a major environmental impact in this fishery.Keywords: shrimp trawling, life cycle assesment (LCA), Arabian sea, environmental impacts
Procedia PDF Downloads 31439888 Disparities in the Levels of Economic Development in Uttar Pradesh: A Regional Analysis
Authors: Naushaba Naseem Ahmed
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Economic development does not merely depend upon the level of development but also on its distributive aspect. As it is a serious issue, the fruit of development is not equally distributed among the different section of peoples and different part of the country this cause the regional disparities in the levels of social economic development. Different part of the country has different resource endowments in term of natural, human and capital. If there is the uniform condition to grow, these areas that have better resources, are favourably placed grow comparatively faster as other areas. Thus with the very stage of development, gap between resourceful and less resourceful area goes on widening. This paper is an attempt to highlight the levels of disparities in term of economic development with the help of selected variables. Principal component analysis, correlation, and coefficient of variation are the techniques which were used in paper and employed published data for analysis. The result shows that Western region of Uttar Pradesh is more developed followed by Central Region. There will be urgent need in investment and developmental policies for the backward region like Bundelkhand region of Uttar Pradesh.Keywords: coefficient of variation, correlation, economic development, principal component analysis
Procedia PDF Downloads 25739887 Evidence of Climate Change from Statistical Analysis of Temperature and Rainfall Data of Kaduna State, Nigeria
Authors: Iliya Bitrus Abaje
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This study examines the evidence of climate change scenario in Kaduna State from the analysis of temperature and rainfall data (1976-2015) from three meteorological stations along a geographic transect from the southern part to the northern part of the State. Different statistical methods were used in determining the changes in both the temperature and rainfall series. The result of the linear trend lines revealed a mean increase in average temperature of 0.73oC for the 40 years period of study in the State. The plotted standard deviation for the temperature anomalies generally revealed that years of temperatures above the mean standard deviation (hotter than the normal conditions) in the last two decades (1996-2005 and 2006-2015) were more than those below (colder than the normal condition). The Cramer’s test and student’s t-test generally revealed an increasing temperature trend in the recent decades. The increased in temperature is an evidence that the earth’s atmosphere is getting warmer in recent years. The linear trend line equation of the annual rainfall for the period of study showed a mean increase of 316.25 mm for the State. Findings also revealed that the plotted standard deviation for the rainfall anomalies, and the 10-year non-overlapping and 30-year overlapping sub-periods analysis in all the three stations generally showed an increasing trend from the beginning of the data to the recent years. This is an evidence that the study area is now experiencing wetter conditions in recent years and hence climate change. The study recommends diversification of the economic base of the populace with emphasis on moving away from activities that are sensitive to temperature and rainfall extremes Also, appropriate strategies to ameliorate the scourge of climate change at all levels/sectors should always take into account the recent changes in temperature and rainfall amount in the area.Keywords: anomalies, linear trend, rainfall, temperature
Procedia PDF Downloads 31039886 An Interpretative Phenomenological Analysis on the Concept of Friends of Children in Conflict with the Law
Authors: Karla Kristine Bay, Jovie Ann Gabin, Allana Joyce Sasotona
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This research employed an Interpretative Phenomenological Analysis to explore the experiences of Children in Conflict with the Law (CICL) which gave light to their concept of ‘friends’. Derived from this context are the following objectives of the study: 1) determining the differentiation of the forms of friends of the CICL; 2) presenting the process of attachment towards detachment in the formation of friendship; and 3) discussing the experiences, and reflections of the CICL on the ‘self’ out of their encounter with friendship. Using the data gathered from the individual drawings of the CICL of their representations of the self, family, friends, community, and Bahay Kalinga as subjects in the meaning-making process utilizing Filipino Psychology methods of pagtatanong-tanong (interview), and pakikipagkwentuhan (conversation), data analysis produced a synthesis of seventeen individual cases. Overall results generated three superordinate themes on the differentiation of the forms of friends which include friends with good influences, friends with bad influences, and friends within the family. While two superordinate themes were produced on the process of attachment towards detachment, namely social, emotional, and psychological experiences on the process of attachment, and emotional and psychological experiences on the process of detachment. Lastly, two superordinate themes were created on the experiences, and reflections of the CICL on the ‘self’ out of their encounter with friendship. This consists of the recognition of the ‘self’ as a responsible agent in developing healthy relationships between the self and others, and reconstruction of the self from the collective experiences of healing, forgiveness, and acceptance. These findings, together with supporting theories discussed the impact of friendship on the emergence of criminal behavior and other dispositions; springing from the child’s dissociation from the family that led to finding belongingness from an external group called friends.Keywords: children in conflict with the law, criminal behavior, friends, interpretative phenomenological analysis
Procedia PDF Downloads 23039885 Application of Multilinear Regression Analysis for Prediction of Synthetic Shear Wave Velocity Logs in Upper Assam Basin
Authors: Triveni Gogoi, Rima Chatterjee
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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs
Procedia PDF Downloads 21739884 Offshore Facilities Load Out: Case Study of Jacket Superstructure Loadout by Strand Jacking Skidding Method
Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani
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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding
Procedia PDF Downloads 9939883 Gonadal Maturation in Pen Shells Pinna Rudis and Pinna Nobilis Stimulated by Reproductive Neuropeptides
Authors: Ntalamagka N., Sanchis-Benlloch P. J., Mayoral-Serrano R., Tena-Medialdea J., García-March J. R.
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The pen shell Pinna nobilis population has declined dramatically since 2016 due to die-off events observed in the whole extent of the Mediterranean Sea associated with the protozoan Haplosporidium pinnae. As of 2019, it is considered a critically endangered species. Due to its ecological importance and its endangered status, several initiatives have been developed for its salvation and recovery. This research is an effort to understand and control its reproduction under captivity. As a limited number of Pinna nobilis individuals could be used for experimentation, the possibility of using the Pinna rudis as a model animal was explored. The molecular mechanism that regulates the reproduction of both species is unknown; consequently, transcriptomic analysis was performed to identify neuropeptides that are expressed in the key regulatory tissues of the visceral ganglia and gonads of both species. Neuropeptides form an important group of signaling peptides that regulate reproductive, behavioral and physiological functions in molluscs. In total, 17 neuropeptide precursors were identified in P. nobilis and 14 in P. rudis transcriptomes; 14 of them were identical in both species. This affinity verified the genetic similarity of these species at the reproduction level. APGWamide, buccalin, ELH and GnRH were tested in P. rudis and demonstrated their capacity to advance gonadal maturation and trigger spawning while spawning was recorded in P. nobilis after the usage of APGWamide and buccalin. The neuropeptides were administered using intramuscular injection and cholesterol implants following relative literature as well as a new method was developed for external administration without the use of anesthesia using a mathematical model. The know-how of this research will not only lead to the survival of the species but also will narrow the horizons of broodstock conditioning of other similar species.Keywords: neuropeptides, Pinna nobilis, reproduction, transcriptomics
Procedia PDF Downloads 9339882 Sentiment Analysis of Chinese Microblog Comments: Comparison between Support Vector Machine and Long Short-Term Memory
Authors: Xu Jiaqiao
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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments
Procedia PDF Downloads 8339881 New Approach to Construct Phylogenetic Tree
Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui
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Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis
Procedia PDF Downloads 50139880 Real-Time Visualization Using GPU-Accelerated Filtering of LiDAR Data
Authors: Sašo Pečnik, Borut Žalik
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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization
Procedia PDF Downloads 30039879 On the Analysis of Pseudorandom Partial Quotient Sequences Generated from Continued Fractions
Authors: T. Padma, Jayashree S. Pillai
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Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis
Procedia PDF Downloads 58239878 Data Analysis Tool for Predicting Water Scarcity in Industry
Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse
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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.Keywords: data mining, industry, machine Learning, shortage, water resources
Procedia PDF Downloads 11639877 Impact of Maternal Nutrition on Newborn Anthropometry and Hemoglobin
Authors: Vinay Mishra, Meena Malkani
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Objectives: To study the effect of physical maternal nutritional markers (viz. weight, height, gestational weight gain, BMI) and third-trimester haemoglobin concentration on anthropometry and cord blood haemoglobin of their newborn. Methods: Study area: Post-natal ward of a tertiary care hospital in an urban area. Study population: All post-partum women and their newborns. Sample size: 100. Maternal and neonatal data and anthropometric measurements were recorded in semi-structured case proforma. Data analysis: The data obtained was analysed using SPSS 20 software.The comparison between the groups was done using One-Way Analysis of Variance for two groups. For more than two groups comparisons further posthoc analysis was done using Tukey test. Pearson correlation coefficient was used for correlating the variables. A P value less than 0.05 was considered significant. Results: 1. Out of the 100 studied mothers, 52% were anaemic. 2. Cord blood haemoglobin values decreased significantly with the order of birth. 3. Cord blood haemoglobin of normal-weight newborns is significantly higher as compared to that of LBW newborns. 4. Cord blood haemoglobin has strong statistical significance with maternal anaemia. 5. Pre-pregnancy weight and gestational weight gain significantly influence the neonates anthropometry. Conclusions: 1. Birth order has a prominent inverse effect on the cord blood haemoglobin. 2. Majority of the expectant mothers are anaemic and give birth to LBW babies with reduced anthropometric markers. 3. Pre-pregnancy weight, height and gestational weight gain has a very significant impact on the neonatal anthropometry. 4. Thus, maternal nutrition during gestation and during the crucial periods of growth in the pre-child bearing age group has a very significant impact on foetal development.Keywords: maternal nutrition, anthropometry, cord blood hemoglobin, newborn
Procedia PDF Downloads 38739876 A Documentary Review of Theoretical and Practical Elements for a Genre Analysis of Thailand Travel Listicles
Authors: Pinyada Santisarun, Yaowaret Tharawoot, Songyut Akkakoson
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This paper reports on a literature review sub-study of a larger research project which has been designed to identify the rhetorical organization of a travel writing genre, together with the use of lexical choices, syntactical structures, and graphological features, based on a randomly-selected corpus of Thailand travel listicles. Conducted as a library-based overview, this study aims to specify theoretical and practical elements for the said larger study. The materials for the review have been retrieved from various Internet sources, covering both public search engines and library databases. Generally, the article focuses on answering questions about the ‘what’ and the ‘how’ of such background elements widely discussed in the literature as the meaning of listicles, how the travel listicles’ patterns and regularities can be categorized to form a new genre, the effect of computer-mediated communication on the travel world, the travel language, and the current situation concerning the importance of travel listicles. The theoretical and practical data derived from this study provide valuable insights into the way in which the genre analysis and lexico-syntactical examination of Thailand travel listicles in the present authors’ larger research project can be properly conducted. The data gained can be added to the expanding body of knowledge in the field of the ESP genre.Keywords: computer-mediated communication, digital writing, genre-based analysis, online travel writing, tourism language
Procedia PDF Downloads 13339875 Seal Capacity Evaluation by Using Mercury Injection Capillary Pressure Method Integrated with Petrographic Data: A Case Study in Green Dragon Oilfield Offshore Vietnam
Authors: Quoc Ngoc Phan, Hieu Van Nguyen, Minh Hong Nguyen
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This study presents an integrated approach using Mercury Injection Capillary Pressure (MICP) and petrographic analysis to assess the seal quality of the inter-bedded shale formations which are considered the intra-formation top seals of hydrocarbon bearing zones in Green Dragon structure. Based on the hydrocarbon column height (HCH) at leak point derived from capillary pressure data, four seal types were identified. Furthermore, the results of scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were interpreted to clarify the influence of clay minerals on seal capacity. The result of the study indicated that the inter-bedded shale formations are the good sealing quality with a majority of analyzed samples ranked type A and B seals in the sample set. Both seal types occurred mainly in mudstones with pore radius estimated less than 0.251 µm. Overall, type A and B seals contained a large amount of authigenic clay minerals such as illite, chlorite which showed the complexity of morphological arrangement in pore space. Conversely, the least common seal type C and D were presented in moderately compacted sandstones with more open pore radius. It is noticeable that there was a reduction of illite and chlorite in clay mineral fraction of these seal type. It is expected that the integrated analysis approach using Mercury Injection Capillary Pressure and petrographic data employed in this study can be applied to assess the sealing quality of future well sites in Green Dragon or other structures.Keywords: seal capacity, hydrocarbon height column, seal type, SEM, XRD
Procedia PDF Downloads 15539874 Engineering Management and Practice in Nigeria
Authors: Harold Jideofor
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The application of Project Management (PM) tools and techniques in the public sector is gradually becoming an important issue in developing economies, especially in a country like Nigeria where projects of different size and structures are undertaken. The paper examined the application of the project management practice in the public sector in Nigeria. The PM lifecycles, tools, and techniques were presented. The study was carried out in Lagos because of its metropolitan nature and rapidly growing economy. Twenty-three copies of questionnaire were administered to 23 public institutions in Lagos to generate primary data. The descriptive analysis techniques using percentages and table presentations coupled with the coefficient of correlation were used for data analysis. The study revealed that application of PM tools and techniques is an essential management approach that tends to achieve specified objectives within specific time and budget limits through the optimum use of resources. Furthermore, the study noted that there is a lack of in-depth knowledge of PM tools and techniques in public sector institutions sampled, also a high cost of the application was also observed by the respondents. The study recommended among others that PM tools and techniques should be applied gradually especially in old government institutions where resistance to change is perceived to be high.Keywords: project management, public sector, practice, Nigeria
Procedia PDF Downloads 33239873 Methodology of Automation and Supervisory Control and Data Acquisition for Restructuring Industrial Systems
Authors: Lakhoua Najeh
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Introduction: In most situations, an industrial system already existing, conditioned by its history, its culture and its context are in difficulty facing the necessity to restructure itself in an organizational and technological environment in perpetual evolution. This is why all operations of restructuring first of all require a diagnosis based on a functional analysis. After a presentation of the functionality of a supervisory system for complex processes, we present the concepts of industrial automation and supervisory control and data acquisition (SCADA). Methods: This global analysis exploits the various available documents on the one hand and takes on the other hand in consideration the various testimonies through investigations, the interviews or the collective workshops; otherwise, it also takes observations through visits as a basis and even of the specific operations. The exploitation of this diagnosis enables us to elaborate the project of restructuring thereafter. Leaving from the system analysis for the restructuring of industrial systems, and after a technical diagnosis based on visits, an analysis of the various technical documents and management as well as on targeted interviews, a focusing retailing the various levels of analysis has been done according a general methodology. Results: The methodology adopted in order to contribute to the restructuring of industrial systems by its participative and systemic character and leaning on a large consultation a lot of human resources that of the documentary resources, various innovating actions has been proposed. These actions appear in the setting of the TQM gait requiring applicable parameter quantification and a treatment valorising some information. The new management environment will enable us to institute an information and communication system possibility of migration toward an ERP system. Conclusion: Technological advancements in process monitoring, control and industrial automation over the past decades have contributed greatly to improve the productivity of virtually all industrial systems throughout the world. This paper tries to identify the principles characteristics of a process monitoring, control and industrial automation in order to provide tools to help in the decision-making process.Keywords: automation, supervision, SCADA, TQM
Procedia PDF Downloads 16839872 Bioinformatics High Performance Computation and Big Data
Authors: Javed Mohammed
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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.Keywords: high performance, big data, parallel computation, molecular data, computational biology
Procedia PDF Downloads 35839871 Comparative Study of Titanium and Polyetheretherketone Cranial Implant Using Finite Element Model
Authors: Khaja Moiduddin, Sherif Mohammed Elseufy, Hisham Alkhalefah
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Recent advances in three-dimensional (3D) printing, medical imaging, and implant design may alter how craniomaxillofacial surgeons construct individualized treatments using patient data. By utilizing medical image data, medical professionals can obtain detailed information about a patient's injuries, enabling them to conduct a thorough preoperative assessment while ensuring the implant's accuracy. However, selecting the right implant material requires careful consideration of various mechanical properties. This study aims to compare the two commonly used implant material for cranial reconstruction which includes titanium (Ti6Al4V) and Polyetheretherketone (PEEK). Biomechanical analysis was performed to study the implant behavior, by keeping the implant design and fixation constant in both cases. A finite element model was created and analyzed under loading conditions. The finite element analysis proves that although Ti6Al4V is stronger than PEEK but, its mechanical strength is adequate to bear the loads of the adjacent bone tissue.Keywords: cranial reconstruction, titanium implants, PEEK, finite element model
Procedia PDF Downloads 6339870 Modeling and Simulation of Ship Structures Using Finite Element Method
Authors: Javid Iqbal, Zhu Shifan
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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.Keywords: dynamic analysis, finite element methods, ship structure, vibration analysis
Procedia PDF Downloads 12639869 Development of Muay Thai Competition Management for Promoting Sport Tourism in the next Decade (2015-2024)
Authors: Supasak Ngaoprasertwong
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The purpose of this research was to develop a model for Muay Thai competition management for promoting sport tourism in the next decade. Moreover, the model was appropriately initiated for practical use. This study also combined several methodologies, both quantitative research and qualitative research, to entirely cover all aspects of data, especially the tourists’ satisfaction toward Muay Thai competition. The data were collected from 400 tourists watching Muay Thai competition in 4 stadiums to create the model for Muay Thai competition to support the sport tourism in the next decade. Besides, Ethnographic Delphi Futures Research (EDFR) was applied to gather the data from certain experts in boxing industry or having significant role in Muay Thai competition in both public sector and private sector. The first step of data collection was an in-depth interview with 27 experts associated with Muay Thai competition, Muay Thai management, and tourism. The second step and the third step of data collection were conducted to confirm the experts’ opinions toward various elements. When the 3 steps of data collection were completely accomplished, all data were assembled to draft the model. Then the model was proposed to 8 experts to conduct a brainstorming to affirm it. According to the results of quantitative research, it found that the tourists were satisfied with personnel of competition at high level (x=3.87), followed by facilities, services, and safe high level (x=3.67). Furthermore, they were satisfied with operation in competition field at high level (x=3.62).Regarding the qualitative methodology including literature review, theories, concepts and analysis of qualitative research development of the model for Muay Thai competition to promote the sport tourism in the next decade, the findings indicated that there were 2 data sets as follows: The first one was related to Muay Thai competition to encourage the sport tourism and the second one was associated with Muay Thai stadium management to support the sport tourism. After the brain storming, “EE Muay Thai Model” was finally developed for promoting the sport tourism in the next decade (2015-2024).Keywords: Muay Thai competition management, Muay Thai sport tourism, Muay Thai, Muay Thai for sport tourism management
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