Search results for: secure data sharing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25789

Search results for: secure data sharing

23989 Microbial Resource Research Infrastructure: A Large-Scale Research Infrastructure for Microbiological Services

Authors: R. Hurtado-Ortiz, D. Clermont, M. Schüngel, C. Bizet, D. Smith, E. Stackebrandt

Abstract:

Microbiological resources and their derivatives are the essential raw material for the advancement of human health, agro-food, food security, biotechnology, research and development in all life sciences. Microbial resources, and their genetic and metabolic products, are utilised in many areas such as production of healthy and functional food, identification of new antimicrobials against emerging and resistant pathogens, fighting agricultural disease, identifying novel energy sources on the basis of microbial biomass and screening for new active molecules for the bio-industries. The complexity of public collections, distribution and use of living biological material (not only living but also DNA, services, training, consultation, etc.) and service offer, demands the coordination and sharing of policies, processes and procedures. The Microbial Resource Research Infrastructure (MIRRI) is an initiative within the European Strategy Forum Infrastructures (ESFRI), bring together 16 partners including 13 European public microbial culture collections and biological resource centres (BRCs), supported by several European and non-European associated partners. The objective of MIRRI is to support innovation in microbiology by provision of a one-stop shop for well-characterized microbial resources and high quality services on a not-for-profit basis for biotechnology in support of microbiological research. In addition, MIRRI contributes to the structuring of microbial resources capacity both at the national and European levels. This will facilitate access to microorganisms for biotechnology for the enhancement of the bio-economy in Europe. MIRRI will overcome the fragmentation of access to current resources and services, develop harmonised strategies for delivery of associated information, ensure bio-security and other regulatory conditions to bring access and promote the uptake of these resources into European research. Data mining of the landscape of current information is needed to discover potential and drive innovation, to ensure the uptake of high quality microbial resources into research. MIRRI is in its Preparatory Phase focusing on governance and structure including technical, legal governance and financial issues. MIRRI will help the Biological Resources Centres to work more closely with policy makers, stakeholders, funders and researchers, to deliver resources and services needed for innovation.

Keywords: culture collections, microbiology, infrastructure, microbial resources, biotechnology

Procedia PDF Downloads 439
23988 Forensic Investigation: The Impact of Biometric-Based Solution in Combatting Mobile Fraud

Authors: Mokopane Charles Marakalala

Abstract:

Research shows that mobile fraud has grown exponentially in South Africa during the lockdown caused by the COVID-19 pandemic. According to the South African Banking Risk Information Centre (SABRIC), fraudulent online banking and transactions resulted in a sharp increase in cybercrime since the beginning of the lockdown, resulting in a huge loss to the banking industry in South Africa. While the Financial Intelligence Centre Act, 38 of 2001, regulate financial transactions, it is evident that criminals are making use of technology to their advantage. Money-laundering ranks among the major crimes, not only in South Africa but worldwide. This paper focuses on the impact of biometric-based solutions in combatting mobile fraud at the South African Risk Information. SABRIC had the challenges of a successful mobile fraud; cybercriminals could hijack a mobile device and use it to gain access to sensitive personal data and accounts. Cybercriminals are constantly looting the depths of cyberspace in search of victims to attack. Millions of people worldwide use online banking to do their regular bank-related transactions quickly and conveniently. This was supported by the SABRIC, who regularly highlighted incidents of mobile fraud, corruption, and maladministration in SABRIC, resulting in a lack of secure their banking online; they are vulnerable to falling prey to fraud scams such as mobile fraud. Criminals have made use of digital platforms since the development of technology. In 2017, 13 438 instances involving banking apps, internet banking, and mobile banking caused the sector to suffer gross losses of more than R250,000,000. The final three parties are forced to point fingers at one another while the fraudster makes off with the money. A non-probability sampling (purposive sampling) was used in selecting these participants. These included telephone calls and virtual interviews. The results indicate that there is a relationship between remote online banking and the increase in money-laundering as the system allows transactions to take place with limited verification processes. This paper highlights the significance of considering the development of prevention mechanisms, capacity development, and strategies for both financial institutions as well as law enforcement agencies in South Africa to reduce crime such as money-laundering. The researcher recommends that strategies to increase awareness for bank staff must be harnessed through the provision of requisite training and to be provided adequate training.

Keywords: biometric-based solution, investigation, cybercrime, forensic investigation, fraud, combatting

Procedia PDF Downloads 94
23987 Non-Linear Causality Inference Using BAMLSS and Bi-CAM in Finance

Authors: Flora Babongo, Valerie Chavez

Abstract:

Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

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23986 Managing Incomplete PSA Observations in Prostate Cancer Data: Key Strategies and Best Practices for Handling Loss to Follow-Up and Missing Data

Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal

Abstract:

Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.

Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer

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23985 Vibration-Based Data-Driven Model for Road Health Monitoring

Authors: Guru Prakash, Revanth Dugalam

Abstract:

A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

Procedia PDF Downloads 81
23984 General Architecture for Automation of Machine Learning Practices

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

Abstract:

Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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23983 Ama de Casa: Gender Division of Labor the Response to Environmental and Economic Constraints, Ecuador

Authors: Tyrus C. Torres, Michael Harris

Abstract:

In a coastal town of Ecuador, the role of women is commonly defined as an ama de casa, a woman who works in the house, raises children, and contributes to the community. This project, under the guidance of Dr. Michael Harris from the Florida Atlantic University, seeks to understand how the role of an ama de casa provides a secure environment for men and women, coexists with economic and environmental constraints that explain the origins of how this environment has been formed. The coastal community aspects of familia (family), trabajo (work), relación (relationships), machismo (masculinity), feminista (femininity), and the culture of Ecuador define the ways of life in a coastal setting. This ethnographic research project included the following methodologies: environment mapping, conducting interviews, surveys, participant observation, direct and indirect observations, and integration into daily life. Immersion into the daily life and building relationships with the local people allowed the documentation of intricacies of both the cultural and social spheres. The findings of this research offer insight on how culture, economics, and environment can form female and male agency. Our investigation shows that occupations such as fishermen, laborers, ama de casas, and even students utilize occupational routes to create social agency in the face of economic and environmental constraints in Ecuador.

Keywords: Ecuador, ethnography, gender division of labor, gender roles

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23982 Collaboration of Game Based Learning with Models Roaming the Stairs Using the Tajribi Method on the Eye PAI Lessons at the Ummul Mukminin Islamic Boarding School, Makassar South Sulawesi

Authors: Ratna Wulandari, Shahidin

Abstract:

This article aims to see how the Game Based Learning learning model with the Roaming The Stairs game makes a tajribi method can make PAI lessons active and interactive learning. This research uses a qualitative approach with a case study type of research. Data collection methods were carried out using interviews, observation, and documentation. Data analysis was carried out through the stages of data reduction, data display, and verification and drawing conclusions. The data validity test was carried out using the triangulation method. and drawing conclusions. The results of the research show that (1) children in grades 9A, 9B, and 9C like learning PAI using the Roaming The Stairs game (2) children in grades 9A, 9B, and 9C are active and can work in groups to solve problems in the Roaming The Stairs game (3) the class atmosphere becomes fun with learning method, namely learning while playing.

Keywords: game based learning, Roaming The Stairs, Tajribi PAI

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23981 Phylogenetic Analysis of the Thunnus Tuna Fish Using Cytochrome C Oxidase Subunit I Gene Sequence

Authors: Yijun Lai, Saber Khederzadeh, Lingshaung Han

Abstract:

Species in Thunnus are organized due to the similarity between them. The closeness between T. maccoyii, T. thynnus, T. Tonggol, T. atlanticus, T. albacares, T. obsesus, T. alalunga, and T. orientails are in different degrees. However, the genetic pattern of differentiation has not been presented based on individuals yet, to the author’s best knowledge. Hence, we aimed to analyze the difference in individuals level of tuna species to identify the factors that contribute to the maternal lineage variety using Cytochrome c oxidase subunit I (COXI) gene sequences. Our analyses provided evidence of sharing lineages in the Thunnus. A phylogenetic analysis revealed that these lineages are basal to the other sequences. We also showed a close connection between the T. tonggol, T. thynnus, and T. albacares populations. Also, the majority of the T. orientalis samples were clustered with the T. alalunga and, then, T. atlanticus populations. Phylogenetic trees and migration modeling revealed high proximity of T. thynnus sequences to a few T. orientalis and suggested possible gene flow with T. tonggol and T. albacares lineages, while all T. obsesus samples indicated unique clustering with each other. Our results support the presence of old maternal lineages in Thunnus, as a legacy of an ancient wave of colonization or migration.

Keywords: Thunnus Tuna, phylogeny, maternal lineage, COXI gene

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23980 Wedding Organizer Strategy in the Era Covid-19 Pandemic In Surabaya, Indonesia

Authors: Rifky Cahya Putra

Abstract:

At this time of corona makes some countries affected difficult. As a result, many traders or companies are difficult to work in this pandemic era. So human activities in some fields must implement a new lifestyle or known as new normal. The transition from the one activity to another certainly requires high adaptation. So that almost in all sectors experience the impact of this phase, on of which is the wedding organizer. This research aims to find out what strategies are used so that the company can run in this pandemic. Techniques in data collection in the form interview to the owner of the wedding organizer and his team. Data analysis qualitative descriptive use interactive model analysis consisting of three main things, namely data reduction, data presentaion, and conclusion. For the result of the interview, the conclusion is that there are three strategies consisting of social media, sponsorship, and promotion.

Keywords: strategy, wedding organizer, pandemic, indonesia

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23979 Culture and Health Equity: Unpacking the Sociocultural Determinants of Eye Health for Indigenous Australian Diabetics

Authors: Aryati Yashadhana, Ted Fields Jnr., Wendy Fernando, Kelvin Brown, Godfrey Blitner, Francis Hayes, Ruby Stanley, Brian Donnelly, Bridgette Jerrard, Anthea Burnett, Anthony B. Zwi

Abstract:

Indigenous Australians experience some of the worst health outcomes globally, with life expectancy being significantly poorer than those of non-Indigenous Australians. This is largely attributed to preventable diseases such as diabetes (prevalence 39% in Indigenous Australian adults > 55 years), which is attributed to a raised risk of diabetic visual impairment and cataract among Indigenous adults. Our study aims to explore the interface between structural and sociocultural determinants and human agency, in order to understand how they impact (1) accessibility of eye health and chronic disease services and (2) the potential for Indigenous patients to achieve positive clinical eye health outcomes. We used Participatory Action Research methods, and aimed to privilege the voices of Indigenous people through community collaboration. Semi-structured interviews (n=82) and patient focus groups (n=8) were conducted by Indigenous Community-Based Researchers (CBRs) with diabetic Indigenous adults (> 40 years) in four remote communities in Australia. Interviews (n=25) and focus groups (n=4) with primary health care clinicians in each community were also conducted. Data were audio recorded, transcribed verbatim, and analysed thematically using grounded theory, comparative analysis and Nvivo 10. Preliminary analysis occurred in tandem with data collection to determine theoretical saturation. The principal investigator (AY) led analysis sessions with CBRs, fostering cultural and contextual appropriateness to interpreting responses, knowledge exchange and capacity building. Identified themes were conceptualised into three spheres of influence: structural (health services, government), sociocultural (Indigenous cultural values, distrust of the health system, ongoing effects of colonialism and dispossession) and individual (health beliefs/perceptions, patient phenomenology). Permeating these spheres of influence were three core determinants: economic disadvantage, health literacy/education, and cultural marginalisation. These core determinants affected accessibility of services, and the potential for patients to achieve positive clinical outcomes at every level of care (primary, secondary, tertiary). Our findings highlight the clinical realities of institutionalised and structural inequities, illustrated through the lived experiences of Indigenous patients and primary care clinicians in the four sampled communities. The complex determinants surrounding inequity in health for Indigenous Australians, are entrenched through a longstanding experience of cultural discrimination and ostracism. Secure and long term funding of Aboriginal Community Controlled Health Services will be valuable, but are insufficient to address issues of inequity. Rather, working collaboratively with communities to build trust, and identify needs and solutions at the grassroots level, while leveraging community voices to drive change at the systemic/policy level are recommended.

Keywords: indigenous, Australia, culture, public health, eye health, diabetes, social determinants of health, sociology, anthropology, health equity, aboriginal and Torres strait islander, primary care

Procedia PDF Downloads 292
23978 Research on Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 455
23977 MapReduce Algorithm for Geometric and Topological Information Extraction from 3D CAD Models

Authors: Ahmed Fradi

Abstract:

In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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23976 Potential of Visualization and Information Modeling on Productivity Improvement and Cost Saving: A Case Study of a Multi-Residential Construction Project

Authors: Sara Rankohi, Lloyd Waugh

Abstract:

Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.

Keywords: image-based technologies, project management, cost, productivity improvement

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23975 Data Hiding in Gray Image Using ASCII Value and Scanning Technique

Authors: R. K. Pateriya, Jyoti Bharti

Abstract:

This paper presents an approach for data hiding methods which provides a secret communication between sender and receiver. The data is hidden in gray-scale images and the boundary of gray-scale image is used to store the mapping information. In this an approach data is in ASCII format and the mapping is in between ASCII value of hidden message and pixel value of cover image, since pixel value of an image as well as ASCII value is in range of 0 to 255 and this mapping information is occupying only 1 bit per character of hidden message as compared to 8 bit per character thus maintaining good quality of stego image.

Keywords: ASCII value, cover image, PSNR, pixel value, stego image, secret message

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23974 Mediation Effect of Mindful Parenting on Parental Self Efficacy and Parent-Child Attachment in Hong Kong

Authors: Man Chung Chu

Abstract:

In the dynamic family interaction, parental self-efficacy is connected with parent-child attachment. Parental self-efficacy and its corresponding behavior played an influential role in the lifespan development of the child. Recently, Mindful parenting is popularly addressed as it lightens parents’ awareness to their own thoughts feelings and behaviors by adapting a nonjudgmental attitude in the present moment being with the child. The effectiveness of mindful parent is considerably significant in enhancing parent-child relationship as well as family functioning. Parenting in early developmental stage is always challenging and essential for later growth, however, literature is rarely exploring the mediation of mindful parenting on the effect of parent self-efficacy on parent-child attachment in preschoolers’ families. The mediation effect of the research shed light on how mindful parenting should head, where parental self-efficacy training should be incorporated together with mindful family program in attempt to yield the best outcome in the family of young-aged children. Two hundred and eight (208) parents, of two to six years old children, were participated in the study and results supported the significance in the mediator effect of mindful parenting in both facets, i.e. Parent-focused - ‘Mindful Discipline’ and Child-focused – ‘Being in the moment with the child’ where parental self-efficacy is a significant predictor of mindful parenting. The implication of the result suggests that mindful parenting would be a therapeutic framework in promoting family functioning and child’s well-being, it would also be a ‘significant helping hand’ in maintaining continuous secure attachment relationship and growing their mindful children in a family.

Keywords: mediation effect, mindful parenting, parental self efficacy, parent-child attachment, preschoolers

Procedia PDF Downloads 194
23973 Reverse Logistics in Clothing Recycling: A Case Study in Chengdu

Authors: Guo Yan

Abstract:

Clothing recycling bin is a traditional way to collect textile waste in many areas. In the clothing recycling business, the transportation cost normally takes over 50% of total costs. This case gives a good way to reduce transportation cost by reverse logistics system. In this reverse logistics system, there are offline strategic alliance partners, such as transport firms, convenience stores, laundries, and post office which are integrated onto the mobile APP. Offline strategic alliance partners provide the service of textile waste collection, and transportation by their vacant vehicles return journey from convenience stores, laundries and post offices to sorting centers. The results of the case study provide the strategic alliance with a valuable and light - asset business model by using the logistics of offline memberships. The company in this case just focuses on textile waste sorting, reuse, recycling etc. The research method of this paper is a case study of a clothing recycling company in Chengdu by field research and interview; the analysis is based on the theory of the reverse logistics system.

Keywords: closed-loop recycles system, clothing recycling, end-of-life clothing, sharing economy, strategic alliance, reverse logistics.

Procedia PDF Downloads 144
23972 DCASH: Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y Synchronizing Mobile Database Systems

Authors: Gunasekaran Raja, Kottilingam Kottursamy, Rajakumar Arul, Ramkumar Jayaraman, Krithika Sairam, Lakshmi Ravi

Abstract:

The synchronization server maintains a dynamically changing cache, which contains the data items which were requested and collected by the mobile node from the server. The order and presence of tuples in the cache changes dynamically according to the frequency of updates performed on the data, by the server and client. To synchronize, the data which has been modified by client and the server at an instant are collected, batched together by the type of modification (insert/ update/ delete), and sorted according to their update frequencies. This ensures that the DCASH (Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y synchronizing Mobile Database Systems) gives priority to the frequently accessed data with high usage. The optimal memory management algorithm is proposed to manage data items according to their frequency, theorems were written to show the current mobile data activity is reverse Y in nature and the experiments were tested with 2g and 3g networks for various mobile devices to show the reduced response time and energy consumption.

Keywords: mobile databases, synchronization, cache, response time

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23971 The Relationship between Infill Development Indicators and Quality of Life in Urban Neighborhoods

Authors: S. Mohammad Reza Khatibi

Abstract:

Statistics on urbanization in Iran and around the world show that urbanization rate and urban population had had an increasing growth and, during five decades, this trend shows the fact that growth will still continue for a long time. Therefore, instead of an irregular horizontal city development and growth, a sustainable development is achievable by filling the existing city fabric, organizing the density and changing the use of incompatible old or urban buildings. One approach is the infill development. Infill development is the development of vacant land or wasteland abandoned within built areas or where there already exist facilities and equipment. Simply put, infill development is the use of empty spaces or those lacking intra-city use for city development. Additionally, fulfillment of social justice and creating a safe, secure and desirable atmosphere for citizens to live and stay active along with acquiring equal life opportunities, are among the goals of vision plan of Iran in conflict with which, certain environments have been created by city neighborhoods having physical, social, economic, etc. problems. Accordingly, in order to meet the extensive need of many cities for openness to growing population, this paper aims to investigate the relationship between infill development indicators and life quality in urban neighborhoods, using descriptive-analytical research method. Findings show that infill development indicators in three physical, social and economic categories can be adapted with quality components of urban environments, especially urban neighborhoods, and related guidelines can be offered.

Keywords: infill development, life quality, urban neighborhoods, indicator

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23970 Unified Structured Process for Health Analytics

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

Abstract:

Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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23969 Use of Life Cycle Data for State-Oriented Maintenance

Authors: Maximilian Winkens, Matthias Goerke

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The state-oriented maintenance enables the preventive intervention before the failure of a component and guarantees avoidance of expensive breakdowns. Because the timing of the maintenance is defined by the component’s state, the remaining service life can be exhausted to the limit. The basic requirement for the state-oriented maintenance is the ability to define the component’s state. New potential for this is offered by gentelligent components. They are developed at the Corporative Research Centre 653 of the German Research Foundation (DFG). Because of their sensory ability they enable the registration of stresses during the component’s use. The data is gathered and evaluated. The methodology developed determines the current state of the gentelligent component based on the gathered data. This article presents this methodology as well as current research. The main focus of the current scientific work is to improve the quality of the state determination based on the life-cycle data analysis. The methodology developed until now evaluates the data of the usage phase and based on it predicts the timing of the gentelligent component’s failure. The real failure timing though, deviate from the predicted one because the effects from the production phase aren’t considered. The goal of the current research is to develop a methodology for state determination which considers both production and usage data.

Keywords: state-oriented maintenance, life-cycle data, gentelligent component, preventive intervention

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23968 A Hybrid System for Boreholes Soil Sample

Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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23967 Enjoyable Learning Experience, but also Difficult: Young, Unaccompanied Refugees' Perspectives on Participatory Research

Authors: Kristina Johansen

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Participation is a universal right that all children and young people are entitled to, according to the Convention on the Rights of the Child. Social work and action research share participation as a core value. However, we have limited knowledge of how children and young people of refugee background experience taking part in participatory research. The point of departure of this presentation is a qualitative study involving young, unaccompanied refugees, addressing the issues of psychosocial health and participation. The research design included participatory methods and action research. The presentation highlights the perspectives of young, unaccompanied refugees on what made participating in the research process valuable, what created challenges for participation and what created challenges for the action part in the research process. Feedback from participants indicated that taking part in enjoyable experiences, being listened to, sharing experiences, and learning from each other contributed to making the participation valuable. At the same time, participants addressed challenges related to communication, sensitive topics, participation in decision-making and powerlessness. The presentation will end with implications for social work research and practice involving young refugees.

Keywords: participatory research, power, young unaccompanied refugeees, relationships, participation

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23966 Predicting Customer Purchasing Behaviour in Retail Marketing: A Research for a Supermarket Chain

Authors: Sabri Serkan Güllüoğlu

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Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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23965 Predicting Medical Check-Up Patient Re-Coming Using Sequential Pattern Mining and Association Rules

Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

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23964 Augmenting Classroom Reality

Authors: Kerrin Burnell

Abstract:

In a world of increasingly technology-dependent students, the English language classroom should ideally keep up with developments to keep students engaged as much as possible. Unfortunately, as is the case in Oman, funding is not always adequate to ensure students have the most up to date technology, and most institutions are still reliant on paper-based textbooks. In order to try and bridge the gap between the technology available (smartphones) and textbooks, augmented reality (AR) technology can be utilized to enhance classroom, homework, and extracurricular activities. AR involves overlaying media (videos, images etc) over the top of physical objects (posters, book pages etc) and then sharing the media. This case study involved introducing students to a freely available entry level AR app called Aurasma. Students were asked to augment their English textbooks, word walls, research project posters, and extracurricular posters. Through surveys, interviews and an analysis of time spent accessing the different media, a determination of the appropriateness of the technology for the classroom was determined. Results indicate that the use of AR has positive effects on many aspects of the English classroom. Increased student engagement, total time spent on task, interaction, and motivation were evident, along with a decrease in technology-related anxiety. As it is proving very difficult to get tablets or even laptops in classrooms in Oman, these preliminary results indicate that many positive outcomes will come from introducing students to this innovative technology.

Keywords: augmented reality, classroom technology, classroom innovation, engagement

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23963 Continual Learning Using Data Generation for Hyperspectral Remote Sensing Scene Classification

Authors: Samiah Alammari, Nassim Ammour

Abstract:

When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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23962 Changes in the Subjective Interpretation of Poverty Due to COVID-19: The Case of a Peripheral County of Hungary

Authors: Eszter Siposne Nandori

Abstract:

The paper describes how the subjective interpretation of poverty changed during the COVID-19 pandemic. The results of data collection at the end of 2020 are compared to the results of a similar survey from 2019. The methods of systematic data collection are used to collect data about the beliefs of the population about poverty. The analysis is carried out in Borsod-Abaúj-Zemplén County, one of the most backward areas in Hungary. The paper concludes that poverty is mainly linked to material values, and it did not change from 2019 to 2020. Some slight changes, however, highlight the effect of the pandemic: poverty is increasingly seen as a generational problem in 2020, and another important change is that isolation became more closely related to poverty.

Keywords: Hungary, interpretation of poverty, pandemic, systematic data collection, subjective poverty

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23961 An Encapsulation of a Navigable Tree Position: Theory, Specification, and Verification

Authors: Nicodemus M. J. Mbwambo, Yu-Shan Sun, Murali Sitaraman, Joan Krone

Abstract:

This paper presents a generic data abstraction that captures a navigable tree position. The mathematical modeling of the abstraction encapsulates the current tree position, which can be used to navigate and modify the tree. The encapsulation of the tree position in the data abstraction specification avoids the use of explicit references and aliasing, thereby simplifying verification of (imperative) client code that uses the data abstraction. To ease the tasks of such specification and verification, a general tree theory, rich with mathematical notations and results, has been developed. The paper contains an example to illustrate automated verification ramifications. With sufficient tree theory development, automated proving seems plausible even in the absence of a special-purpose tree solver.

Keywords: automation, data abstraction, maps, specification, tree, verification

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23960 Accurate Position Electromagnetic Sensor Using Data Acquisition System

Authors: Z. Ezzouine, A. Nakheli

Abstract:

This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

Procedia PDF Downloads 281