Search results for: consumer data right
24847 Sourcing and Compiling a Maltese Traffic Dataset MalTra
Authors: Gabriele Borg, Alexei De Bono, Charlie Abela
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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns
Procedia PDF Downloads 10924846 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study
Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar
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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices
Procedia PDF Downloads 50824845 Streamlining Cybersecurity Risk Assessment for Industrial Control and Automation Systems: Leveraging the National Institute of Standard and Technology’s Risk Management Framework (RMF) Using Model-Based System Engineering (MBSE)
Authors: Gampel Alexander, Mazzuchi Thomas, Sarkani Shahram
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The cybersecurity landscape is constantly evolving, and organizations must adapt to the changing threat environment to protect their assets. The implementation of the NIST Risk Management Framework (RMF) has become critical in ensuring the security and safety of industrial control and automation systems. However, cybersecurity professionals are facing challenges in implementing RMF, leading to systems operating without authorization and being non-compliant with regulations. The current approach to RMF implementation based on business practices is limited and insufficient, leaving organizations vulnerable to cyberattacks resulting in the loss of personal consumer data and critical infrastructure details. To address these challenges, this research proposes a Model-Based Systems Engineering (MBSE) approach to implementing cybersecurity controls and assessing risk through the RMF process. The study emphasizes the need to shift to a modeling approach, which can streamline the RMF process and eliminate bloated structures that make it difficult to receive an Authorization-To-Operate (ATO). The study focuses on the practical application of MBSE in industrial control and automation systems to improve the security and safety of operations. It is concluded that MBSE can be used to solve the implementation challenges of the NIST RMF process and improve the security of industrial control and automation systems. The research suggests that MBSE provides a more effective and efficient method for implementing cybersecurity controls and assessing risk through the RMF process. The future work for this research involves exploring the broader applicability of MBSE in different industries and domains. The study suggests that the MBSE approach can be applied to other domains beyond industrial control and automation systems.Keywords: authorization-to-operate (ATO), industrial control systems (ICS), model-based system’s engineering (MBSE), risk management framework (RMF)
Procedia PDF Downloads 9524844 Effect of Genuine Missing Data Imputation on Prediction of Urinary Incontinence
Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno
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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index
Procedia PDF Downloads 16824843 Database Management System for Orphanages to Help Track of Orphans
Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta
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Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.Keywords: database, orphans, programming, C⁺⁺
Procedia PDF Downloads 15624842 COVID-19 Impact: How the Pandemic Changed the Fashion Industry
Authors: Akshata Patel, Reenu Singh
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This paper focuses on current and upcoming fashion trends and global impact on the fashion industry due to the COVID-19 pandemic. The pandemic has had a major impact on the fashion industry worldwide. At the same time, the fashion market also faces challenges in consumer demand. As the supply chain and distribution channels are interconnected, this outbreak has a global impact due to travel restrictions and raw materials shortages. Given that this particular period represents an unprecedented market situation with almost no prior research on how the industry will recover from such a crisis and mold back to its original form, this research aims to propose new possibilities by evaluating the framework of specific segments. Based on the analysis and extensive literature review, the study develops a conceptual model that will illustrate the various connections among the different segments of the fashion industry. The findings provide actionable considerations for fashion industry pupils when implementing appropriate strategies to prevent unfavourable outcomes during times of crisis, such as the COVID-19 outbreak.Keywords: COVID-19, fashion industry, global impact, new possibilities, pandemic
Procedia PDF Downloads 28524841 Corn Flakes Produced from Different Cultivars of Zea Mays as a Functional Product
Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić
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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.Keywords: corn types, flakes product, nutritive quality, acceptability
Procedia PDF Downloads 5724840 The Effect of the Combination of Mouthwash and Saliva Substitutes on Tooth Erosion: An in Vitro Study
Authors: Young-Eun Jang, Mi-Hye Ma, Yemi Kim
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As the elderly population increases, the number of patients complaining of dry mouth is also increasing. Elderly people often use mouthwash to prevent periodontal disease. Mouthwash and saliva substitutes with low pH were reported to be able to cause enamel erosion. To the best of our knowledge, there have been no studies showing the effect of mouthwash on patients using saliva substitutes. Therefore, the purpose of this study was to evaluate the effect of the use of mouthwash in combination with saliva substitutes on tooth erosion using a quantitative light-induced fluorescence-digital (QLF-D) system. A total of 96 bovine specimens were embedded in putty blocks and randomly allocated to the following groups with n = 12 each: Group 1, application of mouthwash; Group 2, application of saliva substitutes; Group 3, application of saliva substitutes in combination with mouthwash; and control group, application of saline. The bovine samples were eroded using a demineralization solution and then saliva substitutes and mouthwash were applied according to the groups for 2 weeks. For saliva substitutes, three different products were used; Oasis (Oasis Consumer Health, Cleveland, OH, USA), Xeromia solution (Osstem Pharma Co., Seoul, Korea), and Drymund gel (Dong-A Pharma Co., Seoul, Korea). The pH values of the saliva substitutes were determined using a pH meter. Loss of enamel and root dentin was measured using the QLF-D system immediately after demineralization on the 3rd, 7th, and 14th days. The data were analyzed using repeated measures ANOVA followed by Tukey’s post hoc tests (p < 0.05). Mineral loss in enamel and root dentin was detected when mouthwash and saliva substitutes were used alone, respectively (p < 0.05). Also, when mouthwash was used with saliva substitutes, the mineral loss was observed in enamel and root dentin (p < 0.05). The use of Xeromia and Drymund gel increased mineral loss of enamel significantly compared to the use of Oasis (p < 0.05). However, when Drymund gel and Xeromia were used in combination with mouthwash, mineral loss of enamel was significantly reduced compared to when they were used alone (p < 0.05). The pH values of Drymund gel, Xeromia, Oasis, and mouthwash were 5.5, 5.52, 6.2, and 6.37, respectively. Based on these results, it can be concluded that the use of mouthwash with a higher pH value than that of saliva substitutes could help patients suffering from xerostomia avoid the risk of dental erosion.Keywords: saliva substitute, mouthwash, tooth erosion, dry mouth
Procedia PDF Downloads 9024839 New Two-Way Map-Reduce Join Algorithm: Hash Semi Join
Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel
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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.Keywords: map reduce, hadoop, semi join, two way join
Procedia PDF Downloads 51324838 Using Implicit Data to Improve E-Learning Systems
Authors: Slah Alsaleh
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In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.Keywords: e-learning, implicit data, user behavior, data mining
Procedia PDF Downloads 31024837 Enabling Quantitative Urban Sustainability Assessment with Big Data
Authors: Changfeng Fu
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Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data
Procedia PDF Downloads 35924836 Modeling and Analysis Of Occupant Behavior On Heating And Air Conditioning Systems In A Higher Education And Vocational Training Building In A Mediterranean Climate
Authors: Abderrahmane Soufi
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The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings but the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models are usually derived from statistical data and express occupant behavior by assuming a probabilistic relationship to one or more variables. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed multivariate models for higher education and vocational training buildings in a Mediterranean climate. Therefore, in this study, occupant behavior on heating and air conditioning systems was modeled using logistic regression. Occupant behavior related to the turn-on heating and air conditioning systems was studied through experimental measurements collected over a period of one year (June 2023–June 2024) in three classrooms occupied by several groups of students in engineering schools and professional training. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point were determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. The number of occupants, age, and sex were also considered. Logistic regression was used for modeling an occupant turning on the heating and air conditioning systems. The results yielded a proposed model that can be used in building simulation tools to predict the energy performance of teaching buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the air conditioning systems is affected by the indoor relative humidity and temperature in June, July, and August and by the indoor relative humidity, temperature, and number of occupants in September and October. Occupant behavior was analyzed monthly, and univariate and multivariate models were developed.Keywords: occupant behavior, logistic regression, behavior model, mediterranean climate, air conditioning, heating
Procedia PDF Downloads 6224835 Development of Generalized Correlation for Liquid Thermal Conductivity of N-Alkane and Olefin
Authors: A. Ishag Mohamed, A. A. Rabah
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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.Keywords: N-Alkanes, N-Alkenes, nonparametric, regression
Procedia PDF Downloads 65424834 COVID-19 Impact on Online Digital Marketing Business Activities
Authors: Balwinder Singh, Veerpaul Kaur Mann
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The COVID-19 had a dramatic impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole marketing processes because of the relevant issues emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital technologies that may ensure connections and, thus, help business activities to run smoothly. This could be true, especially with the emergence of strong limitations on physical interactions during the COVID-19 pandemic. In such a scenario, the online channel becomes the most important conducive for online customers to get in contact with the firm and carry out online purchasing activities.Keywords: COVID-19, business, digital marketing, online customers
Procedia PDF Downloads 5624833 Tourist Behavior Towards Blockchain-Based Payments
Authors: A. Šapkauskienė, A. Mačerinskienė, R. Andrulienė, R. Bruzgė, S. Masteika, K. Driaunys
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The COVID-19 pandemic has affected not only world markets and economies but also the daily lives of customers and their payment habits. The pandemic has accelerated the digital transformation, so the role of technology will become even more important post-COVID. Although the popularity of cryptocurrencies has reached unprecedented heights, there are still obstacles, such as a lack of consumer experience and distrust of these technologies, so exploring the role of cryptocurrency and blockchain in the context of international travel becomes extremely important. Research on tourists’ intentions to use cryptocurrencies for payment purposes is limited due to the small number of research studies. To fill this research gap, an exploratory study based on the analysis of survey data was conducted. The purpose of the research is to explore how the behavior of tourists has changed making their financial transactions when paying for the tourism services in order to determine the intention to pay in cryptocurrencies. Behavioral intention can be examined as a dependent variable that is useful for the study of the acceptance of blockchain as cutting-edge technology. Therefore, this study examines the intention of travelers to use cryptocurrencies in electronic payments for tourism services. Several studies have shown that the intention to accept payments in a cryptocurrency is affected by the perceived usefulness of these payments and the perceived ease of use. The findings deepen our understanding of the readiness of service users to apply for blockchain-based payment in the tourism sector. The tourism industry has to focus not only on the technology but on consumers who can use cryptocurrencies, creating new possibilities and increasing business competitiveness. Based on research results, suggestions are made to guide future research on the use of cryptocurrencies by tourists in the tourism industry. Therefore, in line with the rapid expansion of virtual currency users, market capitalization, and payment in cryptographic currencies, it is necessary to explore the possibilities of implementing a blockchain-based system aiming to promote the use of services in the tourism sector as the most affected by the pandemic.Keywords: behavioral intention, blockchain-based payment, cryptocurrency, tourism
Procedia PDF Downloads 10524832 Survey on Arabic Sentiment Analysis in Twitter
Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb
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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.Keywords: big data, social networks, sentiment analysis, twitter
Procedia PDF Downloads 57624831 Estimating Current Suicide Rates Using Google Trends
Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis
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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.Keywords: nowcasting, search data, Google Trends, official statistics
Procedia PDF Downloads 35724830 Interpretive Structural Modeling Technique for Hierarchal Ranking of Barriers in Implementation ofGreen Supply Chain Management-Case of Indian Petroleum Industry
Authors: Kavish Kejriwal, Richa Grover
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Consumer awareness and pending legislation have pushed environmental issues into the spotlight, making it imperative for organizations to have a plan of action for “going green.” This is the reason why Green Supply Chain Management has become the integral part of many organization with a goal to reduce cost, increase efficiency and be environmental friendly. Implementation of GSCM involves many factors which act as barriers, making it a tedious task. These barriers have different relationship among themselves creating different impact on implementation Green Supply Chain Management. This work focuses on determining those barriers which have essentially to be removed in the initial stages of GSCM adoption. In this work, the author has taken the case of a petroleum industry in order to come up with a solution. A DEMATEL approach is used to reach the solution.Keywords: barriers, environment, green supply chain management, impact, interpretive structural modeling
Procedia PDF Downloads 27824829 On the Network Packet Loss Tolerance of SVM Based Activity Recognition
Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir
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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss
Procedia PDF Downloads 47524828 The Relationship between Brand Recall and Brand Attitude in Advergame
Authors: Azaze-Azizi Abdul Adis, Hyung Jun Kim, Mohamad Rizwan Abdul Majid, Zaiton Osman, Izyanti Awang Razli
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The increase of online advertising, specifically advergame has become a popular method of strengthening consumer brand recognition by inserting attractive characters and enhancing entertainment value. There have been several remarkable studies on spokes-characters in advertising effectiveness. However, few studies have examined the link between character presence and consumers' brand recall and attitude in advergame. Moreover, how the entertainment value of an advergame influences brand recall and brand attitude and the mediating role of brand recall in influencing character presence and entertainment on brand attitude are still lacking in the advergaming literature. An online survey was conducted with 366 Malaysian gamers. Using structural equation modeling, the results showed that character presence had no influence but entertainment value had a positive influence on brand recall and brand attitude. This study confirmed the role of brand recall as a mediator of the effect of between entertainment and brand attitude in advergame.Keywords: character presence, entertainment, brand recall, brand attitude, advergame
Procedia PDF Downloads 53624827 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman electricity Transmission Company
Authors: Rahma Saleh Hussein Al Balushi
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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.Keywords: asset management ISO55001, standard procedures process, governance, CMMS
Procedia PDF Downloads 12524826 Efects of Data Corelation in a Sparse-View Compresive Sensing Based Image Reconstruction
Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho
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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.Keywords: computed tomography, computed laminography, compressive sending, low-dose
Procedia PDF Downloads 46424825 From Values to Sustainable Actions: A Dual-Theory Approach to Green Consumerism
Authors: Jiyeon Kim
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This conceptual paper examines the psychological drivers of green consumerism and sustainable consumption by integrating the Value-Belief-Norm (VBN) Theory and the Theory of Reasoned Action (TRA). With growing environmental concerns, green consumerism promotes eco-friendly choices such as purchasing sustainable products and supporting environmentally responsible companies. However, there remains a need for research that effectively guides strategies to encourage sustainable behaviors. This paper evaluates VBN Theory’s role in driving pro-environmental behaviors. By incorporating TRA, the paper proposes an enhanced model that improves understanding of the factors driving sustained pro-environmental actions. Focusing on values, beliefs, and norms, this integrated model provides a deeper understanding of the cognitive and motivational factors that influence sustainable consumption. The findings offer valuable theoretical and practical insights for developing strategies to support long-term responsible consumer behavior.Keywords: green consumerism, sustainable behavior, TRA, VBN
Procedia PDF Downloads 924824 Fuzzy Wavelet Model to Forecast the Exchange Rate of IDR/USD
Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik
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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet
Procedia PDF Downloads 57124823 Humanising Digital Healthcare to Build Capacity by Harnessing the Power of Patient Data
Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky
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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.Keywords: digital health, equitable access, humanise healthcare, patient data
Procedia PDF Downloads 8224822 Barbie in India: A Study of Effects of Barbie in Psychological and Social Health
Authors: Suhrita Saha
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Barbie is a fashion doll manufactured by the American toy company Mattel Inc and it made debut at the American International Toy Fair in New York in 9 March 1959. From being a fashion doll to a symbol of fetishistic commodification, Barbie has come a long way. A Barbie doll is sold every three seconds across the world, which makes the billion dollar brand the world’s most popular doll for the girls. The 11.5 inch moulded plastic doll has a height of 5 feet 9 inches at 1/6 scale. Her vital statistics have been estimated at 36 inches (chest), 18 inches (waist) and 33 inches (hips). Her weight is permanently set at 110 pounds which would be 35 pounds underweight. Ruth Handler, the creator of Barbie wanted a doll that represented adulthood and allowed children to imagine themselves as teenagers or adults. While Barbie might have been intended to be independent, imaginative and innovative, the physical uniqueness does not confine the doll to the status of a play thing. It is a cultural icon but with far reaching critical implications. The doll is a commodity bearing more social value than practical use value. The way Barbie is produced represents industrialization and commodification of the process of symbolic production. And this symbolic production and consumption is a standardized planned one that produce stereotypical ‘pseudo-individuality’ and suppresses cultural alternatives. Children are being subject to and also arise as subjects in this consumer context. A very gendered, physiologically dissected sexually charged symbolism is imposed upon children (both male and female), childhood, their social worlds, identity, and relationship formation. Barbie is also very popular among Indian children. While the doll is essentially an imaginative representation of the West, it is internalized by the Indian sensibilities. Through observation and questionnaire-based interview within a sample population of adolescent children (primarily female, a few male) and parents (primarily mothers) in Kolkata, an Indian metropolis, the paper puts forth findings of sociological relevance. 1. Barbie creates, recreates, and accentuates already existing divides between the binaries like male- female, fat- thin, sexy- nonsexy, beauty- brain and more. 2. The Indian girl child in her associative process with Barbie wants to be like her and commodifies her own self. The male child also readily accepts this standardized commodification. Definition of beauty is thus based on prejudice and stereotype. 3. Not being able to become Barbie creates health issues both psychological and physiological varying from anorexia to obesity as well as personality disorder. 4. From being a plaything Barbie becomes the game maker. Barbie along with many other forms of simulation further creates a consumer culture and market for all kind of fitness related hyper enchantment and subsequent disillusionment. The construct becomes the reality and the real gets lost in the play world. The paper would thus argue that Barbie from being an innocuous doll transports itself into becoming social construct with long term and irreversible adverse impact.Keywords: barbie, commodification, personality disorder, sterotype
Procedia PDF Downloads 36224821 Use of Machine Learning in Data Quality Assessment
Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho
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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.Keywords: machine learning, data quality, quality dimension, quality assessment
Procedia PDF Downloads 14824820 Exploring Data Leakage in EEG Based Brain-Computer Interfaces: Overfitting Challenges
Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars
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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting
Procedia PDF Downloads 15324819 Determining Disparities in the Distribution of the Energy Efficiency Resource through the History of Michigan Policy
Authors: M. Benjamin Stacey
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Energy efficiency has been increasingly recognized as a high value resource through state policies that require utility companies to implement efficiency programs. While policymakers have recognized the statewide economic, environmental, and health related value to residents who rely on this grid supplied resource, varying interests in energy efficiency between socioeconomic groups stands undifferentiated in most state legislation. Instead, the benefits are oftentimes assumed to be distributed equitably across these groups. Despite this fact, these policies are frequently sited by advocacy groups, regulatory bodies and utility companies for their ability to address the negative financial, health and other social impacts of energy poverty in low income communities. Yet, while most states like Michigan require programs that target low income consumers, oftentimes no requirements exist for the equitable investment and energy savings for low income consumers, nor does it stipulate minimal spending levels on low income programs. To further understand the impact of the absence of these factors in legislation, this study examines the distribution of program funds and energy efficiency savings to answer a fundamental energy justice concern; Are there disparities in the investment and benefits of energy efficiency programs between socioeconomic groups? This study compiles data covering the history of Michigan’s Energy Efficiency policy implementation from 2010-2016, analyzing the energy efficiency portfolios of Michigan’s two main energy providers. To make accurate comparisons between these two energy providers' investments and energy savings in low and non-low income programs, the socioeconomic variation for each utility coverage area was captured and accounted for using GIS and US Census data. Interestingly, this study found that both providers invested more equitably in natural gas efficiency programs, however, together these providers invested roughly three times less per household in low income electricity efficiency programs, which resulted in ten times less electricity savings per household. This study also compares variation in commission approved utility plans and actual spending and savings results, with varying patterns pointing to differing portfolio management strategies between companies. This study reveals that for the history of the implementation of Michigan’s Energy Efficiency Policy, that the 35% of Michigan’s population who qualify as low income have received substantially disproportionate funding and energy savings because of the policy. This study provides an overview of results from a social perspective, raises concerns about the impact on energy poverty and equity between consumer groups and is an applicable tool for law makers, regulatory agencies, utility portfolio managers, and advocacy groups concerned with addressing issues related to energy poverty.Keywords: energy efficiency, energy justice, low income, state policy
Procedia PDF Downloads 18724818 Nuclear Decay Data Evaluation for 217Po
Authors: S. S. Nafee, A. M. Al-Ramady, S. A. Shaheen
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Evaluated nuclear decay data for the 217Po nuclide ispresented in the present work. These data include recommended values for the half-life T1/2, α-, β--, and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons has been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.Keywords: nuclear decay data evaluation, mass evaluation, total converison coefficients, atomic mass evaluation
Procedia PDF Downloads 433