Search results for: data comparison
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28647

Search results for: data comparison

27147 Effect of Season on Semen Production of Nubian and Saanen Bucks in Sudan

Authors: E. A. Babiker, S. A. Makawi

Abstract:

The influence of the season (autumn, winter, and summer) on semen production in Nubian and Saanen bucks was studied. Seven mature bucks (4 Nubian and 3 Saanen) were used in this study to prepare semen samples which were collected with an artificial vagina. The samples were extended in Tris-egg yolk-glycerol-glucose extender, frozen, and stored in liquid nitrogen at –196 0C for 48 hours. Straws were thawed in water at –37 0C for 15 seconds before sperm evaluation (post-thaw sperm motility). There was a significant seasonal variation in both semen quantity (volume, concentration, and the total number of spermatozoa per ejaculate) and quality (percentage of sperm motility, percentage of post-thaw sperm motility, and dead spermatozoa). Greater ejaculate volumes were observed during summer and autumn in comparison to winter. Higher values of sperms concentration were observed during autumn, while the lowest sperm concentration values were observed during summer. Higher values of sperm motility were observed during autumn in comparison to summer. Lower values of dead spermatozoa were recorded during autumn, while the highest percentages of dead spermatozoa were observed during summer for the two breeds of bucks. The influence of season on post-thaw sperm motility was significant. Semen frozen during autumn and winter had the highest values, while during summer, lower mean values were observed. The best semen was produced during autumn and winter, while during summer, poor semen quality was recorded.

Keywords: season, Nubian, Saanen, semen production, Sudan

Procedia PDF Downloads 113
27146 Improving Security in Healthcare Applications Using Federated Learning System With Blockchain Technology

Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

Abstract:

Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

Procedia PDF Downloads 134
27145 Effect of Dietarty Diversity on Maternal Dietary Diversity of Anemia of the Mother during Pregnancy and Prenatal Outcomes: Prospective Cohort Study in Rural Central Ethiopia

Authors: Taddese Alemu Zerfu, Melaku Umeta Deressa, Kaleab Baye

Abstract:

Background: Maternal and child under-nutrition is the underlying cause of 3•5 million annual deaths, globally. Anemia during pregnancy is among the leading nutritional disorders with serious short and long term consequences to both the mother and fetus. Objective: Examine the effect of dietary diversity on maternal anemia, nutritional status and key pregnancy outcomes of pregnancy. Methods: A prospective cohort study design, involving a total of 432 eligible pregnant women, in their second antenatal care visit was conducted between August 2014 to March, 2015. The individual dietary diversity status of mothers was used as the exposure variable to select, enroll and follow the mothers. All mothers were enrolled during second antenatal care visit and followed until delivery. Epi-data, SPSS and STATA software are used to enter and analyze the data. Chi-square test, independent 't'-test, and GLM are used to calculate risk, association and differences between key variables at P < 0.05. Results: Study participants did not differ in many of the basic characteristics (p < 0.05). The incidence of maternal anemia increased significantly from 28.6% to 32.1% between baseline and term. Pregnant mothers with inadequate dietary diversity groups had more (56% at baseline and 68% at term) risk of anemia than the comparison (adequate) groups, (RR, 1.56 and 1.68; 95% CI, 1.24 - 1.83 and 1.39 - 2.04). The overall incidence of still birth, low birth weight and pre-term birth was 4.5%, 9.1% and 13.6%, respectively. The variation of these outcomes was significant across study groups (P < 0.05). Conclusion and recommendations: Dietary diversity status of pregnant mothers has significant effect on the incidence of anemia and key pregnancy outcomes in resource limited settings, like rural Ethiopia. Therefore, apart from the ongoing routine IFA supplementation, special emphasis should be given to dietary diversity of mothers to improve related outcomes of pregnancy and maternal health.

Keywords: anemia, birth weight, dietary diversity, pregnancy, pregnancy outcome

Procedia PDF Downloads 363
27144 A Concept of Data Mining with XML Document

Authors: Akshay Agrawal, Anand K. Srivastava

Abstract:

The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

Procedia PDF Downloads 384
27143 Speed-Up Data Transmission by Using Bluetooth Module on Gas Sensor Node of Arduino Board

Authors: Hiesik Kim, YongBeum Kim

Abstract:

Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

Procedia PDF Downloads 483
27142 Regulating the Emerging Platform Economy in Ethiopia: Issues in the Ride-Hailing Platforms

Authors: Nebiat Lemenih Lenger

Abstract:

Today, the digital economy is evolving faster than ever in Ethiopia. Platforms that provide a ride-hailing service are growing fast in the country. The market welcomed them as they disrupt it with quality services and lower prices. This revolution is, however, not without challenges. These include cybersecurity breaches, facilitating illegal economic activities, and challenging concepts of privacy. To mitigate the risks and utilize the benefits, appropriate regulation should be introduced in the economy. By identifying legal and institutional gaps in Ethiopia`s digital economy, this research work assists the government`s effort to create a better digital economy. Moreover, this study, being a pioneer study in the area, will be an input for further studies in academia. The research employs a qualitative legal research method and analyzes various legal and policy instruments in Ethiopia in comparison with best international experiences. As this research applies a qualitative research method, a grounded theory method of data analysis is used. The research concluded that Ethiopia is far from designing appropriate legal and regulatory infrastructures. Due to the government monopoly of the sector, there is poor digital infrastructure in the country. The existing labor laws have no specific provisions on the rights and obligations of gig workers.

Keywords: Ethiopia, gig economy, digital, ride-hailing, regulation

Procedia PDF Downloads 93
27141 Evaluating the Total Costs of a Ransomware-Resilient Architecture for Healthcare Systems

Authors: Sreejith Gopinath, Aspen Olmsted

Abstract:

This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 133
27140 Estimation of the Parameters of Muskingum Methods for the Prediction of the Flood Depth in the Moudjar River Catchment

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

Abstract:

The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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27139 Exploring the Capabilities of Sentinel-1A and Sentinel-2A Data for Landslide Mapping

Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

Abstract:

Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

Procedia PDF Downloads 171
27138 A DEA Model in a Multi-Objective Optimization with Fuzzy Environment

Authors: Michael Gidey Gebru

Abstract:

Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

Procedia PDF Downloads 53
27137 An Experimental Investigation on Productivity and Performance of an Improved Design of Basin Type Solar Still

Authors: Mahmoud S. El-Sebaey, Asko Ellman, Ahmed Hegazy, Tarek Ghonim

Abstract:

Due to population growth, the need for drinkable healthy water is highly increased. Consequently, and since the conventional sources of water are limited, researchers devoted their efforts to oceans and seas for obtaining fresh drinkable water by thermal distillation. The current work is dedicated to the design and fabrication of modified solar still model, as well as conventional solar still for the sake of comparison. The modified still is single slope double basin solar still. The still consists of a lower basin with a dimension of 1000 mm x 1000 mm which contains the sea water, as well as the top basin that made with 4 mm acrylic, was temporarily kept on the supporting strips permanently fixed with the side walls. Equally ten spaced vertical glass strips of 50 mm height and 3 mm thickness were provided at the upper basin for the stagnancy of the water. Window glass of 3 mm was used as the transparent cover with 23° inclination at the top of the still. Furthermore, the performance evaluation and comparison of these two models in converting salty seawater into drinkable freshwater are introduced, analyzed and discussed. The experiments were performed during the period from June to July 2018 at seawater depths of 2, 3, 4 and 5 cm. Additionally, the solar still models were operated simultaneously in the same climatic conditions to analyze the influence of the modifications on the freshwater output. It can be concluded that the modified design of double basin single slope solar still shows the maximum freshwater output at all water depths tested. The results showed that the daily productivity for modified and conventional solar still was 2.9 and 1.8 dm³/m² day, indicating an increase of 60% in fresh water production.

Keywords: freshwater output, solar still, solar energy, thermal desalination

Procedia PDF Downloads 135
27136 Parallelization of Random Accessible Progressive Streaming of Compressed 3D Models over Web

Authors: Aayushi Somani, Siba P. Samal

Abstract:

Three-dimensional (3D) meshes are data structures, which store geometric information of an object or scene, generally in the form of vertices and edges. Current technology in laser scanning and other geometric data acquisition technologies acquire high resolution sampling which leads to high resolution meshes. While high resolution meshes give better quality rendering and hence is used often, the processing, as well as storage of 3D meshes, is currently resource-intensive. At the same time, web applications for data processing have become ubiquitous owing to their accessibility. For 3D meshes, the advancement of 3D web technologies, such as WebGL, WebVR, has enabled high fidelity rendering of huge meshes. However, there exists a gap in ability to stream huge meshes to a native client and browser application due to high network latency. Also, there is an inherent delay of loading WebGL pages due to large and complex models. The focus of our work is to identify the challenges faced when such meshes are streamed into and processed on hand-held devices, owing to its limited resources. One of the solutions that are conventionally used in the graphics community to alleviate resource limitations is mesh compression. Our approach deals with a two-step approach for random accessible progressive compression and its parallel implementation. The first step includes partition of the original mesh to multiple sub-meshes, and then we invoke data parallelism on these sub-meshes for its compression. Subsequent threaded decompression logic is implemented inside the Web Browser Engine with modification of WebGL implementation in Chromium open source engine. This concept can be used to completely revolutionize the way e-commerce and Virtual Reality technology works for consumer electronic devices. These objects can be compressed in the server and can be transmitted over the network. The progressive decompression can be performed on the client device and rendered. Multiple views currently used in e-commerce sites for viewing the same product from different angles can be replaced by a single progressive model for better UX and smoother user experience. Can also be used in WebVR for commonly and most widely used activities like virtual reality shopping, watching movies and playing games. Our experiments and comparison with existing techniques show encouraging results in terms of latency (compressed size is ~10-15% of the original mesh), processing time (20-22% increase over serial implementation) and quality of user experience in web browser.

Keywords: 3D compression, 3D mesh, 3D web, chromium, client-server architecture, e-commerce, level of details, parallelization, progressive compression, WebGL, WebVR

Procedia PDF Downloads 170
27135 CFD Simulation for Air-Borne Infection Analysis in AII-Room

Authors: Young Kwon Yang, In Sung Kang, Jung Ha Hwang, Jin Chul Park

Abstract:

The present study is a foundational study for performance improvements on isolation wards to prevent proliferation of secondary infection of infectious diseases such as SARS, H1N1, and MERS inside hospitals. Accordingly, the present study conducted an analysis of the effect of sealing mechanisms and filling of openings on ensuring air tightness performance in isolation wards as well as simulation on air currents in improved isolation wards. The study method is as follows. First, previous studies on aerial infection type and mechanism were reviewed, and the review results were utilized as basic data of analysis on simulation of air current. Second, national and international legislations and regulations in relation to isolation wards as well as case studies on developed nations were investigated in order to identify the problems in isolation wards in Korea and improvement plans. Third, construction and facility plans were compared and analyzed between general and isolation wards focusing on large general hospitals in Korea, thereby conducting comparison and analysis on the performance and effects of air-tightness of general and isolation wards through CFD simulations. The study results showed that isolation wards had better air-tightness performance than that of general wards.

Keywords: AII Room, air-borne infection, CFD, computational fluid dynamics

Procedia PDF Downloads 287
27134 Data-Driven Decision Making: Justification of Not Leaving Class without It

Authors: Denise Hexom, Judith Menoher

Abstract:

Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

Procedia PDF Downloads 387
27133 Quantile Coherence Analysis: Application to Precipitation Data

Authors: Yaeji Lim, Hee-Seok Oh

Abstract:

The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

Procedia PDF Downloads 390
27132 Conception of a Predictive Maintenance System for Forest Harvesters from Multiple Data Sources

Authors: Lazlo Fauth, Andreas Ligocki

Abstract:

For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

Procedia PDF Downloads 145
27131 Induced Emotional Empathy and Contextual Factors like Presence of Others Reduce the Negative Stereotypes Towards Persons with Disabilities through Stronger Prosociality

Authors: Shailendra Kumar Mishra

Abstract:

In this paper, we focus on how contextual factors like the physical presence of other perceivers and then developed induced emotional empathy towards a person with disabilities may reduce the automatic negative stereotypes and then response towards that person. We demonstrated in study 1 that negative attitude based on negative stereotypes assessed on ATDP-test questionnaires on five points Linkert-scale are significantly less negative when participants were tested with a group of perceivers and then tested alone separately by applying 3 (positive, indifferent, and negative attitude levels) X 2 (physical presence condition and alone) factorial design of ANOVA test. In the second study, we demonstrate, by applying regression analysis, in the presence of other perceivers, whether in a small group, participants showed more induced emotional empathy through stronger prosociality towards a high distress target like a person with disabilities in comparison of that of other stigmatized persons such as racial biased or gender-biased people. Thus results show that automatic affective response in the form of induced emotional empathy in perceiver and contextual factors like the presence of other perceivers automatically activate stronger prosocial norms and egalitarian goals towards physically challenged persons in comparison to other stigmatized persons like racial or gender-biased people. This leads to less negative attitudes and behaviour towards a person with disabilities.

Keywords: contextual factors, high distress target, induced emotional empathy, stronger prosociality

Procedia PDF Downloads 138
27130 Sampled-Data Control for Fuel Cell Systems

Authors: H. Y. Jung, Ju H. Park, S. M. Lee

Abstract:

A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

Procedia PDF Downloads 565
27129 A Comparison of the Adsorption Mechanism of Arsenic on Iron-Modified Nanoclays

Authors: Michael Leo L. Dela Cruz, Khryslyn G. Arano, Eden May B. Dela Pena, Leslie Joy Diaz

Abstract:

Arsenic adsorbents were continuously being researched to ease the detrimental impact of arsenic to human health. A comparative study on the adsorption mechanism of arsenic on iron modified nanoclays was undertaken. Iron intercalated montmorillonite (Fe-MMT) and montmorillonite supported zero-valent iron (ZVI-MMT) were the adsorbents investigated in this study. Fe-MMT was produced through ion-exchange by replacing the sodium intercalated ions in montmorillonite with iron (III) ions. The iron (III) in Fe-MMT was later reduced to zero valent iron producing ZVI-MMT. Adsorption study was performed by batch technique. Obtained data were fitted to intra-particle diffusion, pseudo-first order, and pseudo-second-order models and the Elovich equation to determine the kinetics of adsorption. The adsorption of arsenic on Fe-MMT followed the intra-particle diffusion model with intra-particle rate constant of 0.27 mg/g-min0.5. Arsenic was found to be chemically bound on ZVI-MMT as suggested by the pseudo-second order and Elovich equation. The derived pseudo-second order rate constant was 0.0027 g/mg-min with initial adsorption rate computed from the Elovich equation was 113 mg/g-min.

Keywords: adsorption mechanism, arsenic, montmorillonite, zero valent iron

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27128 How Western Donors Allocate Official Development Assistance: New Evidence From a Natural Language Processing Approach

Authors: Daniel Benson, Yundan Gong, Hannah Kirk

Abstract:

Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

Procedia PDF Downloads 79
27127 Experimental Investigation of Folding of Rubber-Filled Circular Tubes on Energy Absorption Capacity

Authors: MohammadSadegh SaeediFakher, Jafar Rouzegar, Hassan Assaee

Abstract:

In this research, mechanical behavior and energy absorption capacity of empty and rubber-filled brazen circular tubes under quasi-static axial loading are investigated, experimentally. The brazen tubes were cut out of commercially available brazen circular tubes with the same length and diameter. Some of the specimens were filled with rubbers with three different shores and also, an empty tube was prepared. The specimens were axially compressed between two rigid plates in a quasi-static process using a Zwick testing machine. Load-displacement diagrams and energy absorption of the tested tubes were extracted from experimental data. The results show that filling the brazen tubes with rubber causes those to absorb more energy and the energy absorption of specimens are increased by increasing the shore of rubbers. In comparison to the empty tube, the first fold for the rubber-filled tubes occurs at lower load and it can be concluded that the rubber-filled tubes are better energy absorbers than the empty tubes. Also, in contrast with the empty tubes, the tubes that were filled with lower rubber shore deform asymmetrically.

Keywords: axial compression, quasi-static loading, folding, energy absorbers, rubber-filled tubes

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27126 Effect of Bonded and Removable Retainers on Occlusal Settling after Orthodontic Treatment: A Systematic Review and Meta-Analysis

Authors: Umair Shoukat Ali, Kamil Zafar, Rashna Hoshang Sukhia, Mubassar Fida, Aqeel Ahmed

Abstract:

Objective: This systematic review and meta-analysis aimed to summarize the effectiveness of bonded and removable retainers (Hawley and Essix retainer) in terms of improvement in occlusal settling (occlusal contact points/areas) after orthodontic treatment. Search Method: We searched the Cochrane Library, CINAHL Plus, PubMed, Web of Science, Orthodontic journals, and Google scholar for eligible studies. We included randomized control trials (RCT) along with Cohort studies. Studies that reported occlusal contacts/areas during retention with fixed bonded and removable retainers were included. To assess the quality of the RCTs Cochrane risk of bias tool was utilized, whereas Newcastle-Ottawa Scale was used for assessing the quality of cohort studies. Data analysis: The data analysis was limited to reporting mean values of occlusal contact points/areas with different retention methods. By utilizing the RevMan software V.5.3, a meta-analysis was performed for all the studies with the quantitative data. For the computation of the summary effect, a random effect model was utilized in case of high heterogeneity. I2 statistics were utilized to assess the heterogeneity among the selected studies. Results: We included 6 articles in our systematic review after scrutinizing 219 articles and eliminating them based on duplication, titles, and objectives. We found significant differences between fixed and removable retainers in terms of occlusal settling within the included studies. Bonded retainer (BR) allowed faster and better posterior tooth settling as compared to Hawley retainer (HR). However, HR showed good occlusal settling in the anterior dental arch. Essix retainer showed a decrease in occlusal contact during the retention phase. Meta-analysis showed no statistically significant difference between BR and removable retainers. Conclusions: HR allowed better overall occlusal settling as compared to other retainers in comparison. However, BR allowed faster settling in the posterior teeth region. Overall, there are insufficient high-quality RCTs to provide additional evidence, and further high-quality RCTs research is needed.

Keywords: orthodontic retainers, occlusal contact, Hawley, fixed, vacuum-formed

Procedia PDF Downloads 125
27125 Fake Accounts Detection in Twitter Based on Minimum Weighted Feature Set

Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

Abstract:

Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

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27124 Compressed Suffix Arrays to Self-Indexes Based on Partitioned Elias-Fano

Authors: Guo Wenyu, Qu Youli

Abstract:

A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

Procedia PDF Downloads 252
27123 Data, Digital Identity and Antitrust Law: An Exploratory Study of Facebook’s Novi Digital Wallet

Authors: Wanjiku Karanja

Abstract:

Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 123
27122 Recommendations for Data Quality Filtering of Opportunistic Species Occurrence Data

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

Abstract:

In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 203
27121 Data Quality Enhancement with String Length Distribution

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 318
27120 Finite Element Simulation of Limiting Dome Height Test on the Formability of Aluminium Tailor Welded Blanks

Authors: Lakhya Jyoti Basumatary, M. J. Davidson

Abstract:

Tailor Welded Blanks (TWBs) have established themselves to be a revolutionary and foremost integral part of the automotive and aerospace industries. Metals sheets with varied thickness, strength and coatings are welded together to form TWBs through friction stir welding and laser welding prior to stamping operations. The formability of the TWBs completely varies from those of conventional blanks due to the diverse strength levels of individual sheets which are made to deform under the same forming load uniformly throughout causing unequal and unsatisfactory deformation in the blank. Limiting Dome Height(LDH) test helps predicting the formability of each blanks and assists in determining the appropriate TWB. Finite Element Simulation of LDH test for both base material and TWBs was performed and analysed for both before and after the solution heat treatment. The comparison and validation of simulation results are done with the experimental data and correlated accordingly. The formability of solution heat treated TWBs had enhanced than those of blanks made from non-heat treated TWBs.

Keywords: tailor welded blanks, friction stir welding, limiting dome height test, finite element simulation

Procedia PDF Downloads 224
27119 Comprehensive Analysis and Optimization of Alkaline Water Electrolysis for Green Hydrogen Production: Experimental Validation, Simulation Study, and Cost Analysis

Authors: Umair Ahmed, Muhammad Bin Irfan

Abstract:

This study focuses on designing and optimization of an alkaline water electrolyser for the production of green hydrogen. The aim is to enhance the durability and efficiency of this technology while simultaneously reducing the cost associated with the production of green hydrogen. The experimental results obtained from the alkaline water electrolyser are compared with simulated results using Aspen Plus software, allowing a comprehensive analysis and evaluation. To achieve the aforementioned goals, several design and operational parameters are investigated. The electrode material, electrolyte concentration, and operating conditions are carefully selected to maximize the efficiency and durability of the electrolyser. Additionally, cost-effective materials and manufacturing techniques are explored to decrease the overall production cost of green hydrogen. The experimental setup includes a carefully designed alkaline water electrolyser, where various performance parameters (such as hydrogen production rate, current density, and voltage) are measured. These experimental results are then compared with simulated data obtained using Aspen Plus software. The simulation model is developed based on fundamental principles and validated against the experimental data. The comparison between experimental and simulated results provides valuable insight into the performance of an alkaline water electrolyser. It helps to identify the areas where improvements can be made, both in terms of design and operation, to enhance the durability and efficiency of the system. Furthermore, the simulation results allow cost analysis providing an estimate of the overall production cost of green hydrogen. This study aims to develop a comprehensive understanding of alkaline water electrolysis technology. The findings of this research can contribute to the development of more efficient and durable electrolyser technology while reducing the cost associated with this technology. Ultimately, these advancements can pave the way for a more sustainable and economically viable hydrogen economy.

Keywords: sustainable development, green energy, green hydrogen, electrolysis technology

Procedia PDF Downloads 90
27118 Temporally Coherent 3D Animation Reconstruction from RGB-D Video Data

Authors: Salam Khalifa, Naveed Ahmed

Abstract:

We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

Procedia PDF Downloads 374