Search results for: Spatial Data Analyses
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28640

Search results for: Spatial Data Analyses

25610 Sedimentological and Petrographical Studies on the Cored samples from Bentiu Formation Muglad Basin

Authors: Yousif M. Makeen

Abstract:

This study presents the results of the sedimentological and petrographical analyses on the cored samples from the Bentiu Formation. The cored intervals consist of thick beds of sandstone, which are sometimes intercalated with beds of fine-grained sandstone and, in a minor case, with a siltstone bed. Detailed sedimentological facies analysis revealed the presence of six facies types, which can be clarified in order of their great percentage occurrences as follows: (i) Massive sandstone, (ii) Planar cross-bedded sandstone, (iii) Trough cross-bedded sandstone, (iv) Fine laminated sandstone (v) Fine laminated siltstone and (vi) Horizontally parted sandstone. The petrographical analyses under the plane polarized microscope and the scanning electron microscope (SEM) for the sandstone lithofacies types that exist within the cored intervals allowed classifying these lithofacies into Kaolinitic Subfeldspathic Arenites. Among the detrital components, quartz grains are the most abundant (mainly monocrystalline quartz), followed by feldspars, micas, detrital and authigenic clays, and carbonaceous debris. However, traces of lithic fragments, iron oxides and heavy minerals were observed in some of the analyzed samples, where they occur in minor amounts. Kaolinite is present mainly as an authigenic component in most of the analyzed samples, while quartz overgrowths occur in variable amounts in most of the investigated samples. Carbonates (calcite & siderite) are present in considerable amounts. The grain roundness in most of the investigated sandstone samples ranges from well-rounded to round, and, in fewer samples, is sub-angular to angular. Most of the sandstone samples are moderately compacted and display point, concavo-convex and long grain contacts, whereas the sutured grain contacts, which reflect a higher degree of compaction, are relatively observed in lesser amounts, while the float grain contact has also been observed in minor quantity. Pore types in the analyzed samples are dominantly primary and secondary interparticle forms. Point-counted porosity values range from 19.6% to 30%. Average pore sizes are highly variable and range from 20 to 350 microns. Pore interconnectivity ranges from good to very good.

Keywords: sandstone, sedimentological facies, porosity, quartz overgrowths

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25609 Inferring the Ecological Quality of Seagrass Beds from Using Composition and Configuration Indices

Authors: Fabrice Houngnandan, Celia Fery, Thomas Bockel, Julie Deter

Abstract:

Getting water cleaner and stopping global biodiversity loss requires indices to measure changes and evaluate the achievement of objectives. The endemic and protected seagrass species Posidonia oceanica is a biological indicator used to monitor the ecological quality of marine Mediterranean waters. One ecosystem index (EBQI), two biotic indices (PREI, Bipo), and several landscape indices, which measure the composition and configuration of the P. oceanica seagrass at the population scale have been developed. While the formers are measured at monitoring sites, the landscape indices can be calculated for the entire seabed covered by this ecosystem. This present work aims to search on the link between these indices and the best scale to be used in order to maximize this link. We used data collected between 2014 to 2019 along the French Mediterranean coastline to calculate EBQI, PREI, and Bipo at 100 sites. From the P. oceanica seagrass distribution map, configuration and composition indices around these different sites in 6 different grid sizes (100 m x 100 to 1000 m x 1000 m) were determined. Correlation analyses were first used to find out the grid size presenting the strongest and most significant link between the different types of indices. Finally, several models were compared basis on various metrics to identify the one that best explains the nature of the link between these indices. Our results showed a strong and significant link between biotic indices and the best correlations between biotic and landscape indices within the 600 m x 600 m grid cells. These results showed that the use of landscape indices is possible to monitor the health of seagrass beds at a large scale.

Keywords: ecological indicators, decline, conservation, submerged aquatic vegetation

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25608 Artificial Neural Network Based Approach in Prediction of Potential Water Pollution Across Different Land-Use Patterns

Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

Abstract:

Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

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25607 Development and Evaluation of Removable Shear Link with Perforated Web

Authors: Daniel Y. Abebe, Jaehyouk Choi

Abstract:

The objective of this paper is to investigate, through an analytical study, the behavior of both stiffened and un-stiffened removable shear link with perforated web considering different number and size of web openings. Removable shear link with perforated web is a novel shear link beam proposed to be used in eccentrically braced frame (EBF). The proposed link overcomes the difficulties during construction slab due to less cross-sectional areas of the link to control the plastic deformation on the conventional EBF with removable shear link. Finite element analyses were conducted under both cyclic and monotonic loading and from the results obtained design equations are developed.

Keywords: eccentrically braced frame, removable shear link, perforated web, non-linear FE analysis

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25606 Secured Embedding of Patient’s Confidential Data in Electrocardiogram Using Chaotic Maps

Authors: Butta Singh

Abstract:

This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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25605 Association between Polygenic Risk of Alzheimer's Dementia, Brain MRI and Cognition in UK Biobank

Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

Abstract:

Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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25604 Open Distance Learning and Curriculum Transformation: Linkages, Alignment, and Innovation

Authors: Devanandan Govender

Abstract:

Curriculum design and development in higher education is a complex and challenging process. Amongst others, the extent to which higher education curriculum responds to a country's imperatives, industry requirements, and societal demands are some important considerations. Added to this is the whole notion of sustainable development, climate change and in the South African context the issue of ‘Africanising the curriculum’ is also significant. In this paper, the author describes and analyses the various challenges related to curriculum transformation, design and development within an ODL context and how we at Unisa engage and address curriculum transformation in mainstream curriculum design and development both at course design level and programme/ qualification level.

Keywords: curriculum transformation, curriculum creep, curriculum drift, curriculum mapping

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25603 Assessment of Urban Environmental Noise in Urban Habitat: A Spatial Temporal Study

Authors: Neha Pranav Kolhe, Harithapriya Vijaye, Arushi Kamle

Abstract:

The economic growth engines are urban regions. As the economy expands, so does the need for peace and quiet, and noise pollution is one of the important social and environmental issue. Health and wellbeing are at risk from environmental noise pollution. Because of urbanisation, population growth, and the consequent rise in the usage of increasingly potent, diverse, and highly mobile sources of noise, it is now more severe and pervasive than ever before, and it will only become worse. Additionally, it will expand as long as there is an increase in air, train, and highway traffic, which continue to be the main contributors of noise pollution. The current study will be conducted in two zones of class I city of central India (population range: 1 million–4 million). Total 56 measuring points were chosen to assess noise pollution. The first objective evaluates the noise pollution in various urban habitats determined as formal and informal settlement. It identifies the comparison of noise pollution within the settlements using T- Test analysis. The second objective assess the noise pollution in silent zones (as stated in Central Pollution Control Board) in a hierarchical way. It also assesses the noise pollution in the settlements and compares with prescribed permissible limits using class I sound level equipment. As appropriate indices, equivalent noise level on the (A) frequency weighting network, minimum sound pressure level and maximum sound pressure level were computed. The survey is conducted for a period of 1 week. Arc GIS is used to plot and map the temporal and spatial variability in urban settings. It is discovered that noise levels at most stations, particularly at heavily trafficked crossroads and subway stations, were significantly different and higher than acceptable limits and squares. The study highlights the vulnerable areas that should be considered while city planning. The study demands area level planning while preparing a development plan. It also demands attention to noise pollution from the perspective of residential and silent zones. The city planning in urban areas neglects the noise pollution assessment at city level. This contributes to that, irrespective of noise pollution guidelines, the ground reality is far away from its applicability. The result produces incompatible land use on a neighbourhood scale with respect to noise pollution. The study's final results will be useful to policymakers, architects and administrators in developing countries. This will be useful for noise pollution in urban habitat governance by efficient decision making and policy formulation to increase the profitability of these systems.

Keywords: noise pollution, formal settlements, informal settlements, built environment, silent zone, residential area

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25602 The Impact of Socioeconomic Status on Citizens’ Perceptions of Social Justice in China

Authors: Yan Liu

Abstract:

The Gini coefficient indicates that the inequality of income distribution is rising in China. How individuals viewing the equality of current society is an important predicator of social turbulence. Perceptions of social justice may vary according to the social stratification. People usually use socioeconomic status to identify divisions between social stratifications. The objective of this study is to explore the potential influence of socioeconomic status on citizens’ perceptions of social justice in China. Socioeconomic status (SES) is usually reflected by either an SES indicator or a composite of three core dimensions: education, income and occupation. With data collected in the 2010 Chinese General Social Survey (CGSS), this study uses OLS regression analyses to examine the relationship between socioeconomic status (SES) and citizens’ perceptions of social justice. This study finds that most Chinese citizens believe that the current society is fair or more than fair. Socioeconomic status (SES) has a positive impact on citizens’ perceptions of social justice, which means individuals with higher indicator of socioeconomic status prefer to believe current society is fair. However, the three core dimensions which are used to measure socioeconomic status (SES) have different influences on perceptions of social justice: First, income helps enhance citizens’ sense of social justice. Second, education weakens citizens’ sense of social justice. Third, compared to the middle occupational status, people of both higher occupational status and lower occupational status have higher levels of perceptions of social justice. Though education creates a negative influence on perceptions of social justice, its effect is much weaker than that of income, which indicates income is a determining factor for enhancing people’s perceptions of social justice in China’s market society. Policy implications are discussed.

Keywords: education, income, occupation, perceptions of social justice, social stratification, socioeconomic status

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25601 Detection Efficient Enterprises via Data Envelopment Analysis

Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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25600 Accuracy of VCCT for Calculating Stress Intensity Factor in Metal Specimens Subjected to Bending Load

Authors: Sanjin Kršćanski, Josip Brnić

Abstract:

Virtual Crack Closure Technique (VCCT) is a method used for calculating stress intensity factor (SIF) of a cracked body that is easily implemented on top of basic finite element (FE) codes and as such can be applied on the various component geometries. It is a relatively simple method that does not require any special finite elements to be used and is usually used for calculating stress intensity factors at the crack tip for components made of brittle materials. This paper studies applicability and accuracy of VCCT applied on standard metal specimens containing trough thickness crack, subjected to an in-plane bending load. Finite element analyses were performed using regular 4-node, regular 8-node and a modified quarter-point 8-node 2D elements. Stress intensity factor was calculated from the FE model results for a given crack length, using data available from FE analysis and a custom programmed algorithm based on virtual crack closure technique. Influence of the finite element size on the accuracy of calculated SIF was also studied. The final part of this paper includes a comparison of calculated stress intensity factors with results obtained from analytical expressions found in available literature and in ASTM standard. Results calculated by this algorithm based on VCCT were found to be in good correlation with results obtained with mentioned analytical expressions.

Keywords: VCCT, stress intensity factor, finite element analysis, 2D finite elements, bending

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25599 Intelligent Process Data Mining for Monitoring for Fault-Free Operation of Industrial Processes

Authors: Hyun-Woo Cho

Abstract:

The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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25598 Kinetic Analysis for Assessing Gait Disorders in Muscular Dystrophy Disease

Authors: Mehdi Razeghi

Abstract:

Background: The purpose of this case series was to quantify gait to study muscular dystrophy disease. In this research, the quantitative differences between normal and waddling gaits were assessed by force plate analysis. Methods: Nineteen myopathy patients and twenty normal subjects serving as the control group participated in this research. In this study, quantitative analyses of gait have been used to investigate the differences between the mobility of normal subjects and myopathy patients. This study was carried out at the Iranian Muscular Dystrophy Association in Boali Hospital, Tehran, Iran, from October 2015 to July 2020. Patient data were collected from Iranian Muscular Dystrophy Association members. individuals signed an informed consent form approved by the ethics committee of the Azad University. All of the gait tests were performed using a Kistler force platform. Participants walked at a self-selected speed, barefoot, independently, and without assistive devices. Results: Our findings indicate that there were no significant differences between the patients and the control group in the anterior-posterior components of the ground reaction forces; however, there were considerable differences in the force components between the groups in the medial-lateral and vertical directions of the ground reaction force. In addition, there were significant differences in the time parameters between the groups in the vertical and medial-lateral directions.

Keywords: biomechanics, force plate analysis, gait disorder, ground reaction force, kinetic analysis, myopathy disease, rehabilitation engineering

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25597 The Design of an Afghan Refugee Camp in Kerman City through Ecotech Architecture

Authors: Kourosh Ghaffari, Baghaei Azhang

Abstract:

This study aims to address two main questions whether a camp designed for refugees will affect their quality of life and how to effectively incorporate ecotech architecture into the architectural design of a refugee camp. The current study planned to ensure that the final design reflects the principles of ecotech architecture in most refugee camps. The design process has taken into account various factors, including flexibility, diversity in the camp space according to the ecotech approach, expandability in the building, spatial hierarchy in the design of camp spaces, and the assignment of territories and space sanctuaries to refugees. It should be noted that this study is not a research-oriented type of study and is only limited to collecting information and making hypotheses and questions related to the plan. The researchers attempted to provide a general summary of similar domestic and foreign examples and examine them in similar conditions using the ecotech architecture. The research method utilized in this study was qualitative. Afterwards, the climate studies of the target area, citing and paying attention to the criteria and points extracted from the theoretical framework, reaching the desired conclusion and examining similar examples were followed. Additionally, placement on the site, compliance with relevant standards and regulations, attention to the content and physical program, and addressing the idea and its evolution in all the details of the plan were presented. The data collection procedure included observation and library studies, and the design method was to determine and recognize the subject and examine similar samples. In conclusion, the principles of theoretical foundations, the design protocols in ecotech architecture and the scope of the study are dealt. Furthermore, the site analysis, the design process and the final plan are presented.

Keywords: ecotech architecture, livable city, shelter, refugee camp

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25596 Content-Based Color Image Retrieval Based on the 2-D Histogram and Statistical Moments

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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25595 Web-Based Decision Support Systems and Intelligent Decision-Making: A Systematic Analysis

Authors: Serhat Tüzün, Tufan Demirel

Abstract:

Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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25594 Ocean Planner: A Web-Based Decision Aid to Design Measures to Best Mitigate Underwater Noise

Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

Abstract:

Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

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25593 A Machine Learning Approach for the Leakage Classification in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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25592 Analysis of Cyber Activities of Potential Business Customers Using Neo4j Graph Databases

Authors: Suglo Tohari Luri

Abstract:

Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

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25591 Decision Making System for Clinical Datasets

Authors: P. Bharathiraja

Abstract:

Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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25590 Indenyl and Allyl Palladates: Synthesis, Bonding, and Anticancer Activity

Authors: T. Scattolin, E. Cavarzerani, F. Visentin, F. Rizzolio

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Organopalladium compounds have recently attracted attention for their high stability even under physiological conditions and, above all, for their remarkable in vitro cytotoxicity towards cisplatin-resistant cell lines. Among the organopalladium derivatives, those bearing at least one N-heterocyclic carbene ligand (NHC) and the Pd(II)-η³-allyl fragment have exhibited IC₅₀ values in the micro and sub-micromolar range towards several cancer cell lines in vitro and in some cases selectivity towards cancerous vs. non-tumorigenic cells. Herein, a selection of allyl and indenyl palladates were synthesized using a solvent-free method consisting of grinding the corresponding palladium precursors with different saturated and unsaturated azolium salts. All compounds have been fully characterized by NMR, XRD and elemental analyses. The intramolecular H, Cl interaction has been elucidated and quantified using the Voronoi Deformation Density scheme. Most of the complexes showed excellent cytotoxicity towards ovarian cancer cell lines, with I₅₀ values comparable to or even lower than cisplatin. Interestingly, the potent anticancer activity was also confirmed in a high-serous ovarian cancer (HGSOC) patient-derived tumoroid, with a clear superiority of this class of compounds over classical platinum-based agents. Finally, preliminary enzyme inhibition studies of the synthesized palladate complexes against the model TrxR show that the compounds have high activity comparable to or even higher than auranofin and classical Au(I) NHC complexes. Based on such promising data, further in vitro and in vivo experiments and in-depth mechanistic studies are ongoing in our laboratories.

Keywords: anticancer activity, palladium complexes, organoids, indenyl and allyl ligands

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25589 Exploring Coping Strategies among Caregivers of Children Who Have Survived Cancer

Authors: Noor Ismael, Somaya Malkawi, Sherin Al Awady, Taleb Ismael

Abstract:

Background/Significance: Cancer is a serious health condition that affects individuals’ quality of life during and after the course of this condition. Children who have survived cancer and their caregivers may deal with residual physical, cognitive or social disabilities. There is little research on caregivers’ health and wellbeing after cancer. To the authors’ best knowledge; there is no specific research about how caregivers cope with everyday stressors after cancer. Therefore, this study aimed to explore the coping strategies that caregivers of children who have survived cancer utilize to overcome everyday stressors. Methods: This study utilized a descriptive survey design. The sample consisted of 103 caregivers, who visited the health and wellness clinic at a national cancer center (additional demographics are presented in the results). The sample included caregivers of children who were off cancer treatments for at least two years from the beginning of data collection. The institution’s internal review board approved this study. Caregivers who agreed to participate completed the survey. The survey collected caregiver reported demographic information and the Brief COPE which measures caregivers' frequency of engaging in certain coping strategies. The Brief COPE consisted of 14 coping sub-scales, which are self-distraction, active coping, denial, substance use, use of emotional support, use of instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame. Data analyses included calculating sub-scales’ scores for the fourteen coping strategies and analysis of frequencies of demographics and coping strategies. Results: The 103 caregivers who participated in this study were 62% mothers, 80% married, 45% finished high school, 50% do not work outside the house, and 60% have low family income. Result showed that religious coping (66%) and acceptance (60%) were the most utilized coping strategies, followed by positive reframing (45%), active coping (44%) and planning (43%). The least utilized coping strategies in our sample were humor (5%), behavioral disengagement (8%), and substance-use (10%). Conclusions: Caregivers of children who have survived cancer mostly utilize religious coping and acceptance in dealing with everyday stressors. Because these coping strategies do not directly solve stressors like active coping and planning coping strategies, it is important to support caregivers in choosing and implementing effective coping strategies. Knowing from our results that some caregivers may utilize substance use as a coping strategy, which has negative health effects on caregivers and their children, there must be direct interventions that target these caregivers and their families.

Keywords: caregivers, cancer, stress, coping

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25588 Estimating Bridge Deterioration for Small Data Sets Using Regression and Markov Models

Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

Abstract:

The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

Procedia PDF Downloads 336
25587 Spectral Mixture Model Applied to Cannabis Parcel Determination

Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

Abstract:

Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, Worldview-2, land parcels

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25586 Validation of Visibility Data from Road Weather Information Systems by Comparing Three Data Resources: Case Study in Ohio

Authors: Fan Ye

Abstract:

Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

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25585 Design and Simulation of All Optical Fiber to the Home Network

Authors: Rahul Malhotra

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 555
25584 Publishing Formats of Scientific Journals in the XXI Century: the Case of Small Publishing Market

Authors: Arūnas Gudinavičius, Andrius Šuminas

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The analysis of scholarly journals formats is fragmented and needs to be studied from a point of view of scientific communication. While PDF is to the author’s best knowledge probably the most popular digital format of XXI century, but there are more formats available: HTML, EPUB, etc. Our aim is to analyze how these formats important to the readers and what is their contribution to scientific communication. We want to investigate how printed journals are still popular between scholars and does different formats are preferred between fields of science . In most cases, publishing of scientific journals are examined from a narrow perspective of a particular university science affair administrators or research funding institution. We believe that more data o n formats used in scholarly periodicals currently published in Lithuania as well as in Eastern Europe are needed. Science communication is often analyzed as a directed chain of information in the author-publisher-reader cycle. The paper is focusing on the publishing part of this chain. A distinction is made between formal and informal forms of scientific communication, which is relevant in today's context, when both forms of communication intertwine and complement each other. In our research, we will analyze formal documentary (formats of publication of scientific articles) communication - scientific information recorded in a certain medium and formatted in certain format (printed, PDF, HTML, EPUB, etc.). In our research, we will analyze the stage of publication of research results in scientific journals and their dissemination through specific publication formats. The paper is to systematize and analyze the various types of formats of scientific journal published in XXI century in Lithuania (small publishing market). The research analyses the case of small European country and presents publishing formats characteristics of the publication of scientific periodicals.

Keywords: scientific communication, scientific journals, publishing formats, reading

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25583 Troubleshooting Petroleum Equipment Based on Wireless Sensors Based on Bayesian Algorithm

Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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25582 Incidence, Risk Factors and Impact of Major Adverse Events Following Paediatric Cardiac Surgery

Authors: Sandipika Gupta

Abstract:

Objective: Due to admirably low 30-day mortality rates for paediatric cardiac surgery, it is now pertinent to turn towards more intermediate-length outcomes such as morbidities closely associated with these surgeries. One such morbidity, major adverse events (MAE) comprises a group of adverse outcomes associated with paediatric cardiac surgery (e.g. cardiac arrest, major haemorrhage). Methods: This is a retrospective study that analysed the incidence and impact of MAE which was the primary outcome in the UK population. The data was collected in 5 centres between October 2015 and June 2017, amassing 3090 surgical episodes. The incidence and risk factors for MAE, were assessed through descriptive statistical analyses and multivariate logistic regression. The secondary outcomes of life status at 6 months and the length of hospital stay were also evaluated to understand the impact of MAE on patients. Results: Out of 3090 episodes, 134 (4.3%) had a postoperative MAE. The majority of the episodes were in: neonates (47%, P<0.001), high-risk cardiac diagnosis groups (20.1%, P<0.001), episodes with longer 5mes on the bypass (72.4%, P<0.001) and urgent surgeries (57.9%, P<0.001). Episodes reporting MAE also reported longer lengths of stay in hospital (29 days vs 9 days, P<0.001). Furthermore, patients experiencing MAE were at a higher risk of mortality at the 6-month life status check (mortality rates: 29.2% vs 2%, P<0.001).Conclusions: Key risk factors were identified. An important negative impact of MAE was found for patients. The identified risk factors could be used to profile and flag at-risk patients. Monitoring of MAE rates and closer investigation into the care pathway before and after individual MAEs in children’s heart units may lead to a reduction in these terrible events.

Keywords:

Procedia PDF Downloads 232
25581 Development of Standard Thai Appetizer in Rattanakosin Era‘s Standard: Case Study of Thai Steamed Dumpling

Authors: Nunyong Fuengkajornfung, Pattama Hirunyophat, Tidarat Sanphom

Abstract:

The objectives of this research were: To study of the recipe standard of Thai steamed dumpling, to study the ratio of modified starch in Thai steamed dumpling, to study chemical elements analyzing and Escherichia coli in Thai steamed dumpling. The experimental processes were designed in two stages as follows: To study the recipe standard of Thai steamed dumpling and to study the ratio of rice flour: modify starch by three levels 90:10, 73:30, and 50:50. The evaluation test used 9 Points Hedonic Scale method by the sensory evaluation test such as color, smell, taste, texture and overall liking. An experimental by Randomized Complete Block Design (RCBD). The statistics used in data analyses were means, standard deviation, one-way ANOVA and Duncan’s New Multiple Range Test. Regression equation, at a statistically significant level of .05. The results showed that the recipe standard was studied from three recipes by the sensory evaluation test such as color, odor, taste, spicy, texture and total acceptance. The result showed that the recipe standard of second was suitably to development. The ratio of rice flour: modified starch had 3 levels 90:10, 73:30, and 50:50 which the process condition of 50:50 had well scores (like moderately to like very much; used 9 Points Hedonic Scale method for the sensory test). Chemical elements analyzing, it showed that moisture 58.63%, fat 5.45%, protein 4.35%, carbohydrate 30.45%, and Ash 1.12%. The Escherichia coli is not found in lab testing.

Keywords: Thai snack in Rattanakosin era, Thai steamed dumpling, modify starch, recipe standard

Procedia PDF Downloads 324