Search results for: data cleaning

Authors: Sašo Pečnik, Borut Žalik

Abstract:

This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

Procedia PDF Downloads 277

Authors: Hasik Lee, Seung-Young Kho

Abstract:

Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

Procedia PDF Downloads 327

Authors: Aniruddha Mitra, Abbas Rashidi, Shane Lewis, Jefferson Doehling, Alexis Pawlak, Jacob Schwartz, Imaobong Ekpo, Atin Adhikari

Abstract:

Working or living close to demolition sites can increase risks of dust-related health problems. Demolition of concrete buildings may produce crystalline silica dust, which can be associated with a broad range of respiratory diseases including silicosis and lung cancers. Previous studies demonstrated significant associations between demolition dust exposure and increase in the incidence of mesothelioma or asbestos cancer. Dust is a generic term used for minute solid particles of typically <500 µm in diameter. Dust particles in demolition sites vary in a wide range of sizes. Larger particles tend to settle down from the air. On the other hand, the smaller and lighter solid particles remain dispersed in the air for a long period and pose sustained exposure risks. Submicron ultrafine particles and nanoparticles are respirable deeper into our alveoli beyond our body’s natural respiratory cleaning mechanisms such as cilia and mucous membranes and are likely to be retained in the lower airways. To our knowledge, how various demolition tasks release nanoparticles are largely unknown and previous studies mostly focused on course dust, PM2.5, and PM10. General belief is that the dust generated during demolition tasks are mostly large particles formed through crushing, grinding, or sawing of various concrete and wooden structures. Therefore, little consideration has been given to the generated submicron ultrafine and nanoparticles and their exposure levels. These data are, however, critically important because recent laboratory studies have demonstrated cytotoxicity of nanoparticles on lung epithelial cells. The above-described knowledge gaps were addressed in this study by a novel newly developed nanoparticle monitor, which was used for nanoparticle monitoring at two adjacent indoor and outdoor building demolition sites in southern Georgia. Nanoparticle levels were measured (n = 10) by TSI NanoScan SMPS Model 3910 at four different distances (5, 10, 15, and 30 m) from the work location as well as in control sites. Temperature and relative humidity levels were recorded. Indoor demolition works included acetylene torch, masonry drilling, ceiling panel removal, and other miscellaneous tasks. Whereas, outdoor demolition works included acetylene torch and skid-steer loader use to remove a HVAC system. Concentration ranges of nanoparticles of 13 particle sizes at the indoor demolition site were: 11.5 nm: 63 – 1054/cm³; 15.4 nm: 170 – 1690/cm³; 20.5 nm: 321 – 730/cm³; 27.4 nm: 740 – 3255/cm³; 36.5 nm: 1,220 – 17,828/cm³; 48.7 nm: 1,993 – 40,465/cm³; 64.9 nm: 2,848 – 58,910/cm³; 86.6 nm: 3,722 – 62,040/cm³; 115.5 nm: 3,732 – 46,786/cm³; 154 nm: 3,022 – 21,506/cm³; 205.4 nm: 12 – 15,482/cm³; 273.8 nm: Keywords: demolition dust, industrial hygiene, aerosol, occupational exposure

Procedia PDF Downloads 404

Authors: Jae Won Shin

Abstract:

We develop an evaluated nuclear data based photonuclear reaction model of GEANT4 for a more accurate simulation of photon-induced neutron production. The evaluated photonuclear data libraries from the ENDF/B-VII.1 are taken as input. Incident photon energies up to 140 MeV which is the threshold energy for the pion production are considered. For checking the validity of the use of the data-based model, we calculate the photoneutron production cross-sections and yields and compared them with experimental data. The results obtained from the developed model are found to be in good agreement with the experimental data for (γ,xn) reactions.

Keywords: ENDF/B-VII.1, GEANT4, photoneutron, photonuclear reaction

Procedia PDF Downloads 250

Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

Abstract:

In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

Procedia PDF Downloads 136

Authors: Benny Sand, Yotam Lurie, Shlomo Mark

Abstract:

Medical Internet of Things (MIoT), AI, and data privacy are linked forever in a gordian knot. This paper explores the conflicts of interests between the stakeholders regarding data privacy in the MIoT arena. While patients are at home during healthcare hospitalization, MIoT can play a significant role in improving the health of large parts of the population by providing medical teams with tools for collecting data, monitoring patients’ health parameters, and even enabling remote treatment. While the amount of data handled by MIoT devices grows exponentially, different stakeholders have conflicting understandings and concerns regarding this data. The findings of the research indicate that medical teams are not concerned by the violation of data privacy rights of the patients' in-home healthcare, while patients are more troubled and, in many cases, are unaware that their data is being used without their consent. MIoT technology is in its early phases, and hence a mixed qualitative and quantitative research approach will be used, which will include case studies and questionnaires in order to explore this issue and provide alternative solutions.

Keywords: MIoT, data privacy, stakeholders, home healthcare, information privacy, AI

Procedia PDF Downloads 77

Authors: Nihad Chakri, Btissam El Amrani, Faouzi Berrada, Fouad Amraoui

Abstract:

In Morocco, water scarcity requires the exploitation of non-conventional resources. Rural areas are under-equipped with sanitation infrastructure, unlike urban areas. Decentralized and low-cost solutions could improve the quality of life of the population and the environment. In this context, the Faculty of Sciences Ain Chock "FSAC" has undertaken an integrated project to treat part of its wastewater using a decentralized compact system. The project will propose alternative solutions that are inexpensive and adapted to the context of peri-urban and rural areas in order to treat the wastewater generated and use it for irrigation, watering, and cleaning. For this purpose, several tests were carried out in the laboratory in order to develop a liquid waste treatment system optimized for local conditions. Based on the results obtained at the laboratory scale of the different proposed scenarios, we designed and implemented a prototype of a mini wastewater treatment plant for the Faculty. In this article, we will outline the steps of dimensioning, construction, and monitoring of the mini-station in our Faculty.

Keywords: wastewater, purification, optimization, vertical filter, MBBR process, sizing, decentralized pilot, reuse, irrigation, sustainable development

Procedia PDF Downloads 92

Authors: Deepak Singh, Rail Kuliev

Abstract:

The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

Procedia PDF Downloads 43

Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

Abstract:

Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

Procedia PDF Downloads 471

Authors: F. Amin, S. Feizi

Abstract:

Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: big data, next generation networks, network transformation, strategy

Procedia PDF Downloads 334

Authors: Apkar Salatian

Abstract:

To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

Procedia PDF Downloads 185

Authors: Yuanyuan Fu

Abstract:

Background and Purpose: Along with the change of society and economy, the traditional home function of old people has gradually weakened in the contemporary China. Acknowledging these situations, to better meet old people’s needs on formal services and improve the quality of later life, this study seeks to identify patterns of intended service use among frail old people living in the communities and examined determinants that explain heterogeneous variations in old people’s intended service use patterns. Additionally, this study also tested the relationship between culture value and intended service use patterns and the mediating role of enabling factors in terms of culture value and intended service use patterns. Methods：Participants were recruited from Haidian District, Beijing, China in 2015. The multi-stage sampling method was adopted to select sub-districts, communities and old people aged 70 years old or older. After screening, 577 old people with limitations in daily life, were successfully interviewed. After data cleaning, 550 samples were included for data analysis. This study establishes a conceptual framework based on the Anderson Model (including predisposing factors, enabling factors and need factors), and further developed it by adding culture value factors (including attitudes towards filial piety and attitudes towards social face). Using a latent class analysis (LCA), this study classifies overall patterns of old people’s formal service utilization. Fourteen types of formal services were taken into account, including housework, voluntary support, transportation, home-delivered meals, and home-delivery medical care, elderly’s canteen and day-care center/respite care and so on. Structural equation modeling (SEM) was used to examine the direct effect of culture value on service use pattern, and the mediating effect of the enabling factors. Results: The LCA classified a hierarchical structure of service use patterns: multiple intended service use (N=69, 23%), selective intended service use (N=129, 23%), and light intended service use (N=352, 64%). Through SEM, after controlling predisposing factors and need factors, the results showed the significant direct effect of culture value on older people’s intended service use patterns. Enabling factors had a partial mediation effect on the relationship between culture value and the patterns. Conclusions and Implications: Differentiation of formal services may be important for meeting frail old people’s service needs and distributing program resources by identifying target populations for intervention, which may make reference to specific interventions to better support frail old people. Additionally, culture value had a unique direct effect on the intended service use patterns of frail old people in China, enriching our theoretical understanding of sources of culture value and their impacts. The findings also highlighted the mediation effects of enabling factors on the relationship between culture value factors and intended service use patterns. This study suggests that researchers and service providers should pay more attention to the important role of culture value factors in contributing to intended service use patterns and also be more sensitive to the mediating effect of enabling factors when discussing the relationship between culture value and the patterns.

Keywords: frail old people, intended service use pattern, culture value, enabling factors, contemporary China, latent class analysis

Procedia PDF Downloads 207

Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

Abstract:

This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

Procedia PDF Downloads 320

Authors: Amy Gooden, Meshandren Naidoo

Abstract:

Genetic research is not confined to a particular jurisdiction. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

Procedia PDF Downloads 132

Authors: Baris Can Yalcin

Abstract:

Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

Procedia PDF Downloads 561

Authors: Eeva Wallenius-Nareneva, Tuula Toivanen-Labiad

Abstract:

Background: Oral health promotion event was organised for forty Afghanistan, Iraqi and Bangladeshi underage asylum seekers in Finland. The invitation to arrange this coaching occasion was accepted in the Degree Programme in Oral Hygiene in Metropolia. The personnel in the reception center found the need to improve oral health among the youngsters. The purpose was to strengthen the health literacy of the boys in their oral self-care and to reduce dental fears. The Finnish studies, especially the terminology of oral health was integrated to coaching with the help of interpreters. Cooperative learning was applied. Methods: Oral health was interactively discussed in four study group sessions: 1. The importance of healthy eating habits; - Good and bad diets, - Regular meals, - Acid attack o Xylitol. 2. Oral diseases − connection to general health; - Aetiology of gingivitis, periodontitis and caries, - Harmfulness of smoking 3. Tools and techniques for oral self-care; - Brushing and inter dental cleaning. 4. Sharing earlier dental care experiences; - Cultural differences, - Dental fear, - Regular check-ups. Results: During coaching deficiencies appeared in brushing and inter dental cleaning techniques. Some boys were used to wash their mouth with salt justifying it by salt’s antiseptic properties. Many brushed their teeth by vertical movements. The boys took feedback positively when a demonstration with model jaws revealed the inefficiency of the technique. The advantages of fluoride tooth paste were advised. Dental care procedures were new and frightening for many boys. Finnish dental care system was clarified. The safety and indolence of the treatments and informed consent were highlighted. Video presentations and the dialog lowered substantially the threshold to visit dental clinic. The occasion gave the students means for meeting patients from different cultural and language backgrounds. The information hidden behind the oral health problems of the asylum seekers was valuable. Conclusions: Learning dental care practices used in different cultures is essential for dental professionals. The project was a good start towards multicultural oral health care. More experiences are needed before graduation. Health education themes should be held simple regardless of the target group. The heterogeneity of the group does not pose a problem. Open discussion with questions leading to the theme works well in clarifying the target group’s knowledge level. Sharing own experiences strengthens the sense of equality among the participants and encourages them to express own opinions. Motivational interview method turned out to be successful. In the future coaching occasions must confirm active participation of everyone. This could be realized by dividing the participants to even smaller groups. The different languages impose challenges but they can be solved by using more interpreters. Their presence ensures that everyone understands the issues properly although the use of plain and sign languages are helpful. In further development, it would be crucial to arrange a rehearsal occasion to the same participants in two/three months’ time. This would strengthen the adaption of self-care practices and give the youngsters opportunity to pose more open questions. The students would gain valuable feedback regarding the effectiveness of their work.

Keywords: cooperative learning, interactive methods, motivational interviewing, oral health promotion, underage asylum seekers

Procedia PDF Downloads 265

Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

Abstract:

Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

Procedia PDF Downloads 55

Authors: Ashish Dhamaniya, Satish Chandra

Abstract:

Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

Procedia PDF Downloads 392

Authors: Ming Wei

Abstract:

Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

Procedia PDF Downloads 263

Authors: Lima Priscila, Gianotto Raiza, Arruda Leonan, Magalhães Filho Fernando

Abstract:

Industrialization and especially the accentuated population growth in developing countries and the lack of drainage, public cleaning, water and sanitation services has caused concern about the need for expansion of water treatment units and sewage. However, these units have been generating by-products, such as the sludge. This paper aims to investigate aspects of operation and maintenance of sludge from a wastewater treatment plant (WWTP - 90 L.s-1) and two water treatment plants (WTPs; 1.4 m3.s-1 and 0.5 m3.s-1) for the purpose of proper disposal and reuse, evaluating their qualitative and quantitative characteristics, the Brazilian legislation and standards. It was concluded that the sludge from the water treatment plants is directly related to the quality of raw water collected, and it becomes feasible for use in construction materials, and to dispose it in the sewage system, improving the efficiency of the WWTP regarding precipitation of phosphorus (35% of removal). The WTP Lageado had 55,726 kg/month of sludge production, more than WTP Guariroba (29,336 kg/month), even though the flow of WTP Guariroba is 1,400 L.s-1 and the WTP Lagedo 500 L.s-1, being explained by the quality that influences more than the flow. The WWTP sludge have higher concentrations of organic materials due to their origin and could be used to improve the fertility of the soil, crop production and recovery of degraded areas. The volume of sludge generated at the WWTP was 1,760 ton/month, with 5.6% of solid content in the raw sludge and in the dewatered sludge it increased its content to 23%.

Keywords: disposal, sludge, water treatment, wastewater treatment

Procedia PDF Downloads 281

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 378

Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

Abstract:

Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

Procedia PDF Downloads 194

Authors: Zhenqiu Liu

Abstract:

Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

Procedia PDF Downloads 203

Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

Abstract:

Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 279

Authors: Kyle De Freitas, Margaret Bernard

Abstract:

Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

Procedia PDF Downloads 299

Authors: Fatemeh Aghamohammadzadeh, Mahdi Asghari Ozma

Abstract:

SARS-CoV-2 was transmitted from animals to humans in China and through air transport to almost all world countries, including Iran, creating the first pandemic of the 21st century. The virus was spread through droplets from sneezing, coughing, loud talking, and exhalation of sick and asymptomatic people, even during incubation. It was transmitted from human to human directly by inhalation of viruses in droplets or indirectly through contact with infected surfaces, resulting in the death of a significant number of patients, especially the elderly and those with underlying diseases. The virus is more likely to be transmitted in places with high population densities. The chain of transmission of infection can be broken by observing the following: risk perception, reduced travel, complete quarantine in a particular area, home quarantine, social distancing, use of personal protective equipment (PPE), prevention of gatherings, cleaning and disinfection of public utilities and busy places, identifying, isolating and treating infected people, tracking calls, continuing health education, following health principles by people, especially in poor areas, and washing their hands frequently with soap and water or disinfecting them with 70% ethanol.

Keywords: COVID-19, transmission, population density, home quarantine, social distancing

Procedia PDF Downloads 78

Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

Abstract:

Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

Procedia PDF Downloads 133

Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

Abstract:

Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

Procedia PDF Downloads 82

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

Abstract:

Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

Procedia PDF Downloads 601

Authors: Andrew R. Winters, Gregor J. Gassner

Abstract:

A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

Procedia PDF Downloads 321