Search results for: data integrity and privacy

Authors: Osiris Jorge Parcero, Néstor Gandelman, Flavia Roldán, Josef Montag

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This paper uses cross-country unbalanced panel data of up to 146 countries over the period 1996 to 2015 to be the first study to identify potential determinants of a country’s relative research output in Economics versus Business. More generally, it is also one of the first studies comparing Economics and Business. The results show that better policy-related data availability, higher income inequality, and lower ethnic fractionalization relatively favor economics. The findings are robust to two alternative fixed effects specifications, three alternative definitions of economics and business, two alternative measures of research output (publications and citations), and the inclusion of meaningful control variables. To the best of our knowledge, our paper is also the first to demonstrate the importance of policy-related data as drivers of economic research. Our regressions show that the availability of this type of data is the single most important factor associated with the prevalence of economics over business as a research domain. Thus, our work has policy implications, as the availability of policy-related data is partially under policy control. Moreover, it has implications for students, professionals, universities, university departments, and research-funding agencies that face choices between profiles oriented toward economics and those oriented toward business. Finally, the conclusions show potential lines for further research.

Keywords: research output, publication performance, bibliometrics, economics, business, policy-related data

Procedia PDF Downloads 134

Authors: Richard Okyere Boadu, Judith Obiri-Yeboah, Kwame Adu Okyere Boadu, Nathan Kumasenu Mensah, Grace Amoh-Agyei

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Routine health information system (RHIS) quality assurance has become an important issue, not only because of its significance in promoting a high standard of patient care but also because of its impact on government budgets for the maintenance of health services. A routine health information system comprises healthcare data collection, compilation, storage, analysis, report generation, and dissemination on a routine basis in various healthcare settings. The data from RHIS give a representation of health status, health services, and health resources. The sources of RHIS data are normally individual health records, records of services delivered, and records of health resources. Using reliable information from routine health information systems is fundamental in the healthcare delivery system. Quality assurance practices are measures that are put in place to ensure the health data that are collected meet required quality standards. Routine health information system quality assurance practices ensure that data that are generated from the system are fit for use. This study considered quality assurance practices in the RHIS processes. Methods: A cross-sectional study was conducted in eight health facilities in Tarkwa Sub-Municipal Health Service in the western region of Ghana. The study involved routine quality assurance practices among the 90 health staff and management selected from facilities in Tarkwa Sub-Municipal who collected or used data routinely from 24th December 2019 to 20th January 2020. Results: Generally, Tarkwa Sub-Municipal health service appears to practice quality assurance during data collection, compilation, storage, analysis and dissemination. The results show some achievement in quality control performance in report dissemination (77.6%), data analysis (68.0%), data compilation (67.4%), report compilation (66.3%), data storage (66.3%) and collection (61.1%). Conclusions: Even though the Tarkwa Sub-Municipal Health Directorate engages in some control measures to ensure data quality, there is a need to strengthen the process to achieve the targeted percentage of performance (90.0%). There was a significant shortfall in quality assurance practices performance, especially during data collection, with respect to the expected performance.

Keywords: quality assurance practices, assessment of routine health information system quality, routine health information system, data quality

Procedia PDF Downloads 79

Authors: Ali Berk Bozan, Reşat Atalay Oyguç

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The demand for precast reinforced concrete (RC) structures is growing, considering their certain benefits, including faster assembly, homogeneous materials, and high-quality labor. The structural integrity of precast reinforced concrete (RC) constructions is influenced by the effectiveness of the joints and connections. This paper contains an analytical study about four types of precast reinforced concrete frames, which vary according to the number of storeys and the number of bays with two different types of moment-resisting beam-to-column connection is investigated under cyclic displacement loading up to 5.6% drift rate by using ABAQUS software. The first connection type is the widely used moment-resisting connection that is defined as a wet connection in the Turkish Seismic Code (TBDY). The second connection type is known as Artificial Controllable Plastic Hinge. The goal of this connection is to defend reinforced concrete components from earthquake-related plastic deformations by keeping them in a specialized connecting section. It will be possible to repair the broken connections after the earthquake. The cyclic behavior of the four types of frames with the mechanical plastic hinge and wet connection was analytically investigated, and then comparisons and suggestions were made on period, ductility, and structural system behavior coefficient. The analytical study shows that the replaceable plastic hinge element provides a significant period increase. Especially in the case of two storeys and two bays, the change in the period was felt the most compared to other frames. The results for ductility show a significant change in the ductility of the frames with replaceable plastic hinges. For the structural system behavior coefficient, a recommendation between 3.90 and 4.52 values was made.

Keywords: precast structures, replaceable plastic hinge, beam to column connections, ductility

Procedia PDF Downloads 48

Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

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Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

Procedia PDF Downloads 402

Authors: Tanuj Joshi

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Smart transportation is fast emerging as a solution to modern cities’ approach mobility issues, delayed emergency response rate and high congestion on streets. Present day scenario with Google Maps, Waze, Yelp etc. demonstrates how information and communications technologies controls the intelligent transportation system. This intangible and invisible infrastructure is largely guided by the big data analytics. On the other side, the exponential increase in Indian urban population has intensified the demand for better services and infrastructure to satisfy the transportation needs of its citizens. No doubt, India’s huge internet usage is looked as an important resource to guide to achieve this. However, with a projected number of over 40 billion objects connected to the Internet by 2025, the need for systems to handle massive volume of data (big data) also arises. This research paper attempts to identify the ways of exploiting the big data variables which will aid commuters on Indian tracks. This study explores real life inputs by conducting survey and interviews to identify which gaps need to be targeted to better satisfy the customers. Several experts at Mumbai Metropolitan Region Development Authority (MMRDA), Mumbai Metro and Brihanmumbai Electric Supply and Transport (BEST) were interviewed regarding the Information Technology (IT) systems currently in use. The interviews give relevant insights and requirements into the workings of public transportation systems whereas the survey investigates the macro situation.

Keywords: smart transportation, mobility issue, Mumbai transportation, big data, data analysis

Procedia PDF Downloads 178

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 358

Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

Procedia PDF Downloads 97

Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique

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Simulation and modelling of Unmanned Aero Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade. The reason is next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.

Keywords: aerospace, flight control, flightgear, communication, Simulink

Procedia PDF Downloads 286

Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

Procedia PDF Downloads 69

Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

Procedia PDF Downloads 72

Authors: Magu Raam Prasaad R., Venkatramani Jagadish

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Recent studies in the literature have shown that randomly fluctuating wind flows can give rise to a distinct regime of pre-flutter oscillations called intermittency. Intermittency is characterized by the presence of sporadic bursts of high amplitude oscillations interspersed amidst low-amplitude aperiodic fluctuations. The focus of this study is on investigating the energy harvesting potential of these intermittent oscillations. Available literature has by and large devoted its attention on extracting energy from flutter oscillations. The possibility of harvesting energy from pre-flutter regimes have remained largely unexplored. However, extracting energy from violent flutter oscillations can be severely detrimental to the structural integrity of airfoil structures. Consequently, investigating the relatively stable pre-flutter responses for energy extraction applications is of practical importance. The present study is devoted towards addressing these concerns. A pitch-plunge airfoil with cubic hardening nonlinearity in the plunge and pitch degree of freedom is considered. The input flow fluctuations are modelled using a sinusoidal term with randomly perturbed frequencies. An electromagnetic coupling is provided to the pitch-plunge equations, such that, energy from the wind induced vibrations of the structural response are extracted. With the mean flow speed as the bifurcation parameter, a fourth order Runge-Kutta based time marching algorithm is used to solve the governing aeroelastic equations with electro-magnetic coupling. The harnessed energy from the intermittency regime is presented and the results are discussed in comparison to that obtained from the flutter regime. The insights from this study could be useful in health monitoring of aeroelastic structures.

Keywords: aeroelasticity, energy harvesting, intermittency, randomly fluctuating flows

Procedia PDF Downloads 186

Authors: Stanley Fore, Sharon Chipeperekwa

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The start of the 2011 academic year in South Africa saw a number of Institutions of Higher Learning introducing online registration for their students. The efficiency and effectiveness of Information Systems are increasingly becoming a necessity and not an option for many organizations. An information system should be able to allow end users to access information easily and navigate with ease. The selected University of Technology (UoT) in this research is one of the largest public institution of higher learning in the Western Cape Province and boasts of an enrolment of more than 30000 students per academic year. An observation was made that, during registration students’ stand in long queues waiting to register or for assistance to register. The system tends to ‘freeze’ whilst students are registering and students are in most cases unfamiliar with the system interface. They constantly have to enquire what to do next when going through online registration process. A mixed method approach will be adopted which comprises of quantitative and qualitative approaches. The study uses constructs of the updated DeLone and McLean IS success model (2003) to analyse and explain the student’s perceptions of the online registration system. The research was undertaken to establish the student’s perceptions of the online registration system. This research seeks to identify and analyse the challenges and success factors of introducing an online registration system whilst highlighting the extent to which this system has been able to solve the numerous problems associated with the manual era. The study will assist management and those responsible for managing the current system to determine how well the system is working or not working to achieve user satisfaction. It will also assist them going forward on what to consider before, during and after implementation of an information system. Respondents will be informed of the objectives of the research, and their consent to participate will be sought. Ethical considerations that will be applied to this study include; informed consent and protection from harm, right to privacy and involvement of the research.

Keywords: online registration, information systems, University of Technology, end-users

Procedia PDF Downloads 258

Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

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The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

Procedia PDF Downloads 384

Authors: Erhan Berk

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The purpose of this study is to examine the efficiency and productivity of the health care sector in Turkey based on four years of health care cross-sectional data. Efficiency measures are calculated by a nonparametric approach known as Data Envelopment Analysis (DEA). Productivity is measured by the Malmquist index. The research shows how DEA-based Malmquist productivity index can be operated to appraise the technology and productivity changes resulted in the Turkish hospitals which are located all across the country.

Keywords: data envelopment analysis, efficiency, health care, Malmquist Index

Procedia PDF Downloads 335

Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

Procedia PDF Downloads 191

Authors: Alexander Rych

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Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

Procedia PDF Downloads 392

Authors: Rima T. Alfaraj, Murtadha J. Al Tammar, Khaqan Khan, Khalid M. Alruwaili

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OBJECTIVE/SCOPE (25-75): Caliper logging data provides critical information about wellbore shape and deformations, such as stress-induced borehole breakouts or washouts. Multiarm mechanical caliper logs are often run using wireline, which can be time-consuming, costly, and/or challenging to run in certain formations. To minimize rig time and improve operational safety, it is valuable to develop analytical solutions that can estimate caliper logs using available Logging-While-Drilling (LWD) data without the need to run wireline caliper logs. As a first step, the objective of this paper is to perform statistical analysis using an extensive datasetto identify important physical parameters that should be considered in developing such analytical solutions. METHODS, PROCEDURES, PROCESS (75-100): Caliper logs and LWD data of eleven wells, with a total of more than 80,000 data points, were obtained and imported into a data analytics software for analysis. Several parameters were selected to test the relationship of the parameters with the measured maximum and minimum caliper logs. These parameters includegamma ray, porosity, shear, and compressional sonic velocities, bulk densities, and azimuthal density. The data of the eleven wells were first visualized and cleaned.Using the analytics software, several analyses were then preformed, including the computation of Pearson’s correlation coefficients to show the statistical relationship between the selected parameters and the caliper logs. RESULTS, OBSERVATIONS, CONCLUSIONS (100-200): The results of this statistical analysis showed that some parameters show good correlation to the caliper log data. For instance, the bulk density and azimuthal directional densities showedPearson’s correlation coefficients in the range of 0.39 and 0.57, which wererelatively high when comparedto the correlation coefficients of caliper data with other parameters. Other parameters such as porosity exhibited extremely low correlation coefficients to the caliper data. Various crossplots and visualizations of the data were also demonstrated to gain further insights from the field data. NOVEL/ADDITIVE INFORMATION (25-75): This study offers a unique and novel look into the relative importance and correlation between different LWD measurements and wireline caliper logs via an extensive dataset. The results pave the way for a more informed development of new analytical solutions for estimating the size and shape of the wellbore in real-time while drilling using LWD data.

Keywords: LWD measurements, caliper log, correlations, analysis

Procedia PDF Downloads 121

Authors: Arka Roy, Chandra Prakash Dubey

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Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

Procedia PDF Downloads 212

Authors: Engy S. El-Kayal, Mohamed M. S. Arafa

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There are various causes of ankle pain including traumatic and non-traumatic causes. Various imaging techniques are available for assessment of AP. MRI is considered to be the imaging modality of choice for ankle joint evaluation with an advantage of its high spatial resolution, multiplanar capability, hence its ability to visualize small complex anatomical structures around the ankle. However, the high costs and the relatively limited availability of MRI systems, as well as the relatively long duration of the examination all are considered disadvantages of MRI examination. Therefore there is a need for a more rapid and less expensive examination modality with good diagnostic accuracy to fulfill this gap. HRU has become increasingly important in the assessment of ankle disorders, with advantages of being fast, reliable, of low cost and readily available. US can visualize detailed anatomical structures and assess tendinous and ligamentous integrity. The aim of this study was to compare the diagnostic accuracy of HRU with MRI in the assessment of patients with AP. We included forty patients complaining of AP. All patients were subjected to real-time HRU and MRI of the affected ankle. Results of both techniques were compared to surgical and arthroscopic findings. All patients were examined according to a defined protocol that includes imaging the tendon tears or tendinitis, muscle tears, masses, or fluid collection, ligament sprain or tears, inflammation or fluid effusion within the joint or bursa, bone and cartilage lesions, erosions and osteophytes. Analysis of the results showed that the mean age of patients was 38 years. The study comprised of 24 women (60%) and 16 men (40%). The accuracy of HRU in detecting causes of AP was 85%, while the accuracy of MRI in the detection of causes of AP was 87.5%. In conclusions: HRU and MRI are two complementary tools of investigation with the former will be used as a primary tool of investigation and the latter will be used to confirm the diagnosis and the extent of the lesion especially when surgical interference is planned.

Keywords: ankle pain (AP), high-resolution ultrasound (HRU), magnetic resonance imaging (MRI) ultrasonography (US)

Procedia PDF Downloads 190

Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Mohammed Al-Shalabi, Alaa Obeidat

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In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

Procedia PDF Downloads 410

Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Tamar Bikashvili, Tamar Lordkipanidze, Ilia Lazrishvili

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Heavy metals remain one of serious environmental problems due to their toxic effects. The effect of arsenic and manganese compounds on rat behavior and neuromorphology was studied. Wistar rats were assigned to four groups: rats in control group were given regular water, while rats in other groups drank water with final manganese concentration of 10 mg/L (group A), 20 mg/L (group B) and final arsenic concentration 68 mg/L (group C), respectively, for a month. To study exploratory and anxiety behavior and also to evaluate aggressive performance in “home cage” rats were tested in “Open Field” and to estimate learning and memory status multi-branched maze was used. Statistically significant increase of motor and oriental-searching activity in experimental groups was revealed by an open field test, which was expressed in increase of number of lines crossed, rearing and hole reflexes. Obtained results indicated the suppression of fear in rats exposed to manganese. Specifically, this was estimated by the frequency of getting to the central part of the open field. Experiments revealed that 30-day exposure to 10 mg/ml manganese did not stimulate aggressive behavior in rats, while exposure to the higher dose (20 mg/ml), 37% of initially non-aggressive animals manifested aggressive behavior. Furthermore, 25% of rats were extremely aggressive. Obtained data support the hypothesis that excess manganese in the body is one of the immediate causes of enhancement of interspecific predatory aggressive and violent behavior in rats. It was also discovered that manganese intoxication produces non-reversible severe learning disability and insignificant, reversible memory disturbances. Studies of rodents exposed to arsenic also revealed changes in the learning process. As it is known, the distribution of metal ions differs in various brain regions. The principle manganese accumulation was observed in the hippocampus and in the neocortex, while arsenic was predominantly accumulated in nucleus accumbens, striatum, and cortex. These brain regions play an important role in the regulation of emotional state and motor activity. Histopathological analyzes of brain sections illustrated two morphologically distinct altered phenotypes of neurons: (1) shrunk cells with indications of apoptosis - nucleus and cytoplasm were very difficult to be distinguished, the integrity of neuronal cytoplasm was not disturbed; and (2) swollen cells - with indications of necrosis. Pyknotic nucleus, plasma membrane disruption and cytoplasmic vacuoles were observed in swollen neurons and they were surrounded by activated gliocytes. It’s worth to mention that in the cortex the majority of damaged neurons were apoptotic while in subcortical nuclei –neurons were mainly necrotic. Ultrastructural analyses demonstrated that all cell types in the cortex and the nucleus caudatus represent destructed mitochondria, widened neurons’ vacuolar system profiles, increased number of lysosomes and degeneration of axonal endings.

Keywords: arsenic, manganese, behavior, learning, neuron

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Authors: Shaho Ghafur Ahmed

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The right to self-determination of peoples is a fundamental human right recognized by the principles of international law. It could be embodied in the internal level in the form of federalism. Most federal constitutions prevented the secession of constituent entities, while some remained silent, as the case of Iraq, and rare instances of them recognize it. But, after the failure of federalism, these entities seek to separate whenever the opportunity arises. In several cases, they have resort to peaceful methods in some others they resort to force. The constitutional Supreme Court, which guaranty the unity and integrity of the State, often prevent these attempts. After not a commitment of federalism in Iraq, which has been founded since 2004, the Kurdistan region, as the only federated entity, has conducted a unilateral referendum on 25 September 2017 for its independence. The Iraqi government refused it. The Iraqi Federal Supreme Court, through interpreting the constitutional provisions, decided that this referendum and it’s purposes, which was the independence of the region, was unconstitutional. Subsequently, the Iraqi government used forces and blockaded the region so as to force it to turn off this process. So, in this paper, the right to self-determination of the peoples in federated entities and its obstacles will be discussed through the comparative legal basis and analyzing the decisions of the Federal Constitutional Courts. We will compare the role that the Supreme Court of Canada played regarding the referendum that operated in Quebec in 1995, in which it refused only the unilaterally attempts for the independence of this province. While, in the case of the Kurdistan region, the Iraqi Federal Supreme Court has definitively refused this right. No measures were taken by this Court to protect the region from the Iraqi government reactions. This decision led to the questioning of the neutrality of this Court. So, from the point of view of the Kurdistan region, this Court became a political instrument to prevent it to be independent in the international community, in the absence of a clear constitutional provision, through an abstract and an incomplete interpretation of federal constitutional provisions.

Keywords: right of self-determination, federal supreme court, supremacy of federal constitution

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Radek Richtr, Petr Pauš

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Social media nowadays connects people more tightly and intensively than ever, but simultaneously, some sort of social distance, incomprehension, lost of social integrity appears. People can be strongly connected to the person on the other side of the world but unaware of neighbours in the same district or street. The Stoa is a type of application from the ”serious games” genre- it is research augmented reality experiment masked as a gaming environment. In the Stoa environment, the player can plant and grow virtual (organic) structure, a Pillar, that represent the whole suburb. Everybody has their own idea of what is an acceptable, admirable or harmful visual intervention in the area they live in; the purpose of this research experiment is to find and/or define residents shared subconscious spirit, genius loci of the Pillars vicinity, where residents live in. The appearance and evolution of Stoa’s Pillars reflect the real world as perceived by not only the creator but also by other residents/players, who, with their actions, refine the environment. Squares, parks, patios and streets get their living avatar depictions; investors and urban planners obtain information on the occurrence and level of motivation for reshaping the public space. As the project is in product conceptual design phase, the function is one of its most important factors. Function-based modelling makes design problem modular and structured and thus decompose it into sub-functions or function-cells. Paper discuss the current conceptual model for Stoa project, the using of different organic structure textures and models, user interface design, UX study and project’s developing to the final state.

Keywords: augmented reality, urban computing, interaction design, mixed reality, social engineering

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Authors: Mohamed Bin Alhaj, Hexu Liu, Mohammed Sulaiman, Osama Abudayyeh

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An effective facility maintenance management (FMM) system plays a crucial role in improving the quality of services and maintaining the facility in good condition. Current FMM heavily relies on the quality of the data collection function of the FMM systems, at times resulting in inefficient FMM decision-making. The new technology-based crowdsourcing provides great potential to improve the current FMM practices, especially in terms of timeliness and quality of data. This research aims to investigate the feasibility of using new technology-driven crowdsourcing for FMM and highlight its opportunities and challenges. A survey was carried out to understand the human, data, system, geospatial, and automation characteristics of crowdsourcing for an educational campus FMM via social networks. The survey results were analyzed to reveal the challenges and recommendations for the implementation of crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges and opportunities of using crowdsourcing for facility maintenance and providing a road map for applying crowdsourcing technology in FMM. In future work, a conceptual framework will be proposed to support data-driven FMM using social networks.

Keywords: crowdsourcing, facility maintenance management, social networks

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Authors: Elyta Widyaningrum

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The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

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Authors: Taehan Bae

Abstract:

In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

Procedia PDF Downloads 224