Search results for: ground data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26309

Search results for: ground data

24569 Assessing the Ways of Improving the Power Saving Modes in the Ore-Grinding Technological Process

Authors: Baghdasaryan Marinka

Abstract:

Monitoring the distribution of electric power consumption in the technological process of ore grinding is conducted. As a result, the impacts of the mill filling rate, the productivity of the ore supply, the volumetric density of the grinding balls, the specific density of the ground ore, and the relative speed of the mill rotation on the specific consumption of electric power have been studied. The power and technological factors affecting the reactive power generated by the synchronous motors, operating within the technological scheme are studied. A block diagram for evaluating the power consumption modes of the technological process is presented, which includes the analysis of the technological scheme, the determination of the place and volumetric density of the ore-grinding mill, the evaluation of the technological and power factors affecting the energy saving process, as well as the assessment of the electric power standards.

Keywords: electric power standard, factor, ore grinding, power consumption, reactive power, technological

Procedia PDF Downloads 551
24568 Collaboration of Game Based Learning with Models Roaming the Stairs Using the Tajribi Method on the Eye PAI Lessons at the Ummul Mukminin Islamic Boarding School, Makassar South Sulawesi

Authors: Ratna Wulandari, Shahidin

Abstract:

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

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

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24567 Probabilistic Study of Impact Threat to Civil Aircraft and Realistic Impact Energy

Authors: Ye Zhang, Chuanjun Liu

Abstract:

In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.

Keywords: composite structure, damage tolerance, impact threat, probabilistic

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24566 Wedding Organizer Strategy in the Era Covid-19 Pandemic In Surabaya, Indonesia

Authors: Rifky Cahya Putra

Abstract:

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

Keywords: strategy, wedding organizer, pandemic, indonesia

Procedia PDF Downloads 130
24565 Influence of Surface Fault Rupture on Dynamic Behavior of Cantilever Retaining Wall: A Numerical Study

Authors: Partha Sarathi Nayek, Abhiparna Dasgupta, Maheshreddy Gade

Abstract:

Earth retaining structure plays a vital role in stabilizing unstable road cuts and slopes in the mountainous region. The retaining structures located in seismically active regions like the Himalayas may experience moderate to severe earthquakes. An earthquake produces two kinds of ground motion: permanent quasi-static displacement (fault rapture) on the fault rupture plane and transient vibration, traveling a long distance. There has been extensive research work to understand the dynamic behavior of retaining structures subjected to transient ground motions. However, understanding the effect caused by fault rapture phenomena on retaining structures is limited. The presence of shallow crustal active faults and natural slopes in the Himalayan region further highlights the need to study the response of retaining structures subjected to fault rupture phenomena. In this paper, an attempt has been made to understand the dynamic response of the cantilever retaining wall subjected to surface fault rupture. For this purpose, a 2D finite element model consists of a retaining wall, backfill and foundation have been developed using Abaqus 6.14 software. The backfill and foundation material are modeled as per the Mohr-Coulomb failure criterion, and the wall is modeled as linear elastic. In this present study, the interaction between backfill and wall is modeled as ‘surface-surface contact.’ The entire simulation process is divided into three steps, i.e., the initial step, gravity load step, fault rupture step. The interaction property between wall and soil and fixed boundary condition to all the boundary elements are applied in the initial step. In the next step, gravity load is applied, and the boundary elements are allowed to move in the vertical direction to incorporate the settlement of soil due to the gravity load. In the final step, surface fault rupture has been applied to the wall-backfill system. For this purpose, the foundation is divided into two blocks, namely, the hanging wall block and the footwall block. A finite fault rupture displacement is applied to the hanging wall part while the footwall bottom boundary is kept as fixed. Initially, a numerical analysis is performed considering the reverse fault mechanism with a dip angle of 45°. The simulated result is presented in terms of contour maps of permanent displacements of the wall-backfill system. These maps highlighted that surface fault rupture can induce permanent displacement in both horizontal and vertical directions, which can significantly influence the dynamic behavior of the wall-backfill system. Further, the influence of fault mechanism, dip angle, and surface fault rupture position is also investigated in this work.

Keywords: surface fault rupture, retaining wall, dynamic response, finite element analysis

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24564 Research on Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

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

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

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24563 MapReduce Algorithm for Geometric and Topological Information Extraction from 3D CAD Models

Authors: Ahmed Fradi

Abstract:

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

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

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24562 Data Hiding in Gray Image Using ASCII Value and Scanning Technique

Authors: R. K. Pateriya, Jyoti Bharti

Abstract:

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

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

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24561 DCASH: Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y Synchronizing Mobile Database Systems

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

Abstract:

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

Keywords: mobile databases, synchronization, cache, response time

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24560 Unified Structured Process for Health Analytics

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

Abstract:

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

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

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24559 Use of Life Cycle Data for State-Oriented Maintenance

Authors: Maximilian Winkens, Matthias Goerke

Abstract:

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

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

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24558 Influencing Factors of School Enterprise Cooperation: An Exploratory Study in Chinese Vocational Nursing Education

Authors: Xiao Chen, Alice Ho, Mabel Tie, Xiaoheng Xu

Abstract:

Background and Significance of the Study: School-enterprise cooperation has been the cornerstone of vocational education in China and many other countries. Researchers and policymakers have paid much attention to ensuring the implementation and improving the quality of school-enterprise cooperation. However, many problems still exist on the implementation level of the cooperation. On the one hand, the enterprises lack the motivation to participate in the cooperation. On the other hand, there is a lack of effective guidance and management during the cooperation. Furthermore, the current literature focuses greatly on policy recommendations on the national level while failing to provide a detailed practical understanding of how school-enterprise cooperation is carried out on the ground level. With emerging social problems, such as the aging population in China, there is an increasing need for diverse nursing services and better nursing quality. Methodology: To gain a deeper understanding of the influencing factors of the implementation of school-enterprise cooperation, this work conducted 37 exploratory interviews in four Chinese cities spanning first-tier to fourth-tier cities with hospital department directors, vocational school deans, nurses, and vocational students. Multiple critical policy documents that founded the current vocational education system in China were analyzed, along with the data collected from the interviews. Major Findings: Based on the policy and interview analyses, this work reveals a set of influencing factors for school-enterprise cooperation implementation. Findings from each region contribute to an overall model of influencing factors for implementing school-enterprise cooperation in vocational nursing education in China, which leads to practical insights for policy recommendation. The key influencing factors are found based on the policy, hospital, school, and social levels. Following practical policy recommendations were presented. Moving forward, further research on the implementation of school-enterprise cooperation in specific industries will become increasingly critical to improving the effectiveness of educational policies and the quality of vocational education.

Keywords: nursing, policy recommendation, school-enterprise cooperation, vocational education

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24557 A Hybrid System for Boreholes Soil Sample

Authors: Ali Ulvi Uzer

Abstract:

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

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

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24556 Predicting Customer Purchasing Behaviour in Retail Marketing: A Research for a Supermarket Chain

Authors: Sabri Serkan Güllüoğlu

Abstract:

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

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

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24555 Predicting Medical Check-Up Patient Re-Coming Using Sequential Pattern Mining and Association Rules

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

Abstract:

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

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

Procedia PDF Downloads 638
24554 Continual Learning Using Data Generation for Hyperspectral Remote Sensing Scene Classification

Authors: Samiah Alammari, Nassim Ammour

Abstract:

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

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

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24553 Influence of Cryo-Grinding on Particle Size Distribution of Proso Millet Bran Fraction

Authors: Maja Benkovic, Dubravka Novotni, Bojana Voucko, Duska Curic, Damir Jezek, Nikolina Cukelj

Abstract:

Cryo-grinding is an ultra-fine grinding method used in the pharmaceutical industry, production of herbs and spices and in the production and handling of cereals, due to its ability to produce powders with small particle sizes which maintain their favorable bioactive profile. The aim of this study was to determine the particle size distributions of the proso millet (Panicum miliaceum) bran fraction grinded at cryogenic temperature (using liquid nitrogen (LN₂) cooling, T = - 196 °C), in comparison to non-cooled grinding. Proso millet bran is primarily used as an animal feed, but has a potential in food applications, either as a substrate for extraction of bioactive compounds or raw material in the bakery industry. For both applications finer particle sizes of the bran could be beneficial. Thus, millet bran was ground for 2, 4, 8 and 12 minutes using the ball mill (CryoMill, Retsch GmbH, Haan, Germany) at three grinding modes: (I) without cooling, (II) at cryo-temperature, and (III) at cryo-temperature with included 1 minute of intermediate cryo-cooling step after every 2 minutes of grinding, which is usually applied when samples require longer grinding times. The sample was placed in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm). The oscillation frequency in all three modes was 30 Hz. Particle size distributions of the bran were determined by a laser diffraction particle sizing method (Mastersizer 2000) using the Scirocco 2000 dry dispersion unit (Malvern Instruments, Malvern, UK). Three main effects of the grinding set-up were visible from the results. Firstly, grinding time at all three modes had a significant effect on all particle size parameters: d(0.1), d(0.5), d(0.9), D[3,2], D[4,3], span and specific surface area. Longer grinding times resulted in lower values of the above-listed parameters, e.g. the averaged d(0.5) of the sample (229.57±1.46 µm) dropped to 51.29±1.28 µm after 2 minutes grinding without LN₂, and additionally to 43.00±1.33 µm after 4 minutes of grinding without LN₂. The only exception was the sample ground for 12 minutes without cooling, where an increase in particle diameters occurred (d(0.5)=62.85±2.20 µm), probably due to particles adhering to one another and forming larger particle clusters. Secondly, samples with LN₂ cooling exhibited lower diameters in comparison to non-cooled. For example, after 8 minutes of non-cooled grinding d(0.5)=46.97±1.05 µm was achieved, while the LN₂ cooling enabled collection of particles with average sizes of d(0.5)=18.57±0.18 µm. Thirdly, the application of intermediate cryo-cooling step resulted in similar particle diameters (d(0.5)=15.83±0.36 µm, 12 min of grinding) as cryo-milling without this step (d(0.5)=16.33±2.09 µm, 12 min of grinding). This indicates that intermediate cooling is not necessary for the current application, which consequently reduces the consumption of LN₂. These results point out the potential beneficial effects of millet bran grinding at cryo-temperatures. Further research will show if the lower particle size achieved in comparison to non-cooled grinding could result in increased bioavailability of bioactive compounds, as well as protein digestibility and solubility of dietary fibers of the proso millet bran fraction.

Keywords: ball mill, cryo-milling, particle size distribution, proso millet (Panicum miliaceum) bran

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24552 Local Differential Privacy-Based Data-Sharing Scheme for Smart Utilities

Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

Abstract:

The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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24551 Changes in the Subjective Interpretation of Poverty Due to COVID-19: The Case of a Peripheral County of Hungary

Authors: Eszter Siposne Nandori

Abstract:

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

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

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24550 Application of Response Surface Methodology (RSM) for Optimization of Fluoride Removal by Using Banana Peel

Authors: Pallavi N., Gayatri Jadhav

Abstract:

Good quality water is of prime importance for a healthy living. Fluoride is one such mineral present in water which causes many health problems in humans and specially children. Fluoride is said to be a double edge sword because lesser and higher concentration of fluoride in drinking water can cause both dental and skeletal fluorosis. Fluoride is one of the important mineral usually present at a higher concentration in ground water. There are many researches being carried out for defluoridation method. In the present research, fluoride removal is demonstrated using banana peel which is a biowaste as a biocoagulant. Response Surface Methodology (RSM) is a statistical design tool which is used to design the experiment. Central Composite Design (CCD) was used to determine the influence of the pH and dosage of the coagulant on the optimal removal of fluoride from a simulated water sample. 895 of fluoride removal were obtained in a acidic pH range of 4 – 9 and bio coagulant dosage of dosage of 18 – 20mg/L.

Keywords: Fluoride, Response Surface Methodology, Dosage, banana peel

Procedia PDF Downloads 156
24549 An Encapsulation of a Navigable Tree Position: Theory, Specification, and Verification

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

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

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

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24548 Accurate Position Electromagnetic Sensor Using Data Acquisition System

Authors: Z. Ezzouine, A. Nakheli

Abstract:

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

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

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24547 The Quality of the Presentation Influence the Audience Perceptions

Authors: Gilang Maulana, Dhika Rahma Qomariah, Yasin Fadil

Abstract:

Purpose: This research meant to measure the magnitude of the influence of the quality of the presentation to the targeted audience perception in catching information presentation. Design/Methodology/Approach: This research uses a quantitative research method. The kind of data that uses in this research is the primary data. The population in this research are students the economics faculty of Semarang State University. The sampling techniques uses in this research is purposive sampling. The retrieving data uses questionnaire on 30 respondents. The data analysis uses descriptive analysis. Result: The quality of presentation influential positive against perception of the audience. This proved that the more qualified presentation will increase the perception of the audience. Limitation: Respondents were limited to only 30 people.

Keywords: quality of presentation, presentation, audience, perception, semarang state university

Procedia PDF Downloads 386
24546 Managing Data from One Hundred Thousand Internet of Things Devices Globally for Mining Insights

Authors: Julian Wise

Abstract:

Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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24545 Examining Statistical Monitoring Approach against Traditional Monitoring Techniques in Detecting Data Anomalies during Conduct of Clinical Trials

Authors: Sheikh Omar Sillah

Abstract:

Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

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24544 Heating and Cooling Scenario of Blended Concrete Subjected to 780 Degrees Celsius

Authors: J. E. Oti, J. M. Kinuthia, R. Robinson, P. Davies

Abstract:

In this study, The Compressive strength of concretes made with Ground Granulated Blast furnace Slag (GGBS), pulverised Fuel Ash (PFA), rice Husk Ash (RHA) and Waste Glass Powder (WGP) after they were exposed 7800C (exposure duration of around 60 minutes) and then allowed to cool down gradually in the furnace for about 280 minutes at water binder ratio of 0.50 was investigated. GGBS, PFA, RHA and WGP were used to replace up to 20% Portland cement in the control concrete. Test for the determination of workability, compressive strength and tensile splitting strength of the concretes were carried out and the results were compared with control concrete. The test results showed that the compressive strength decreased by an average of around 30% after the concretes were exposed to the heating and cooling scenario.

Keywords: concrete, heating, cooling, pulverised fuel ash, rice husk ash, waste glass powder, GGBS, workability

Procedia PDF Downloads 407
24543 Cr Induced Magnetization in Zinc-Blende ZnO-Based Diluted Magnetic Semiconductors

Authors: Bakhtiar Ul Haq, R. Ahmed, A. Shaari, Mazmira Binti Mohamed, Nisar Ali

Abstract:

The capability of exploiting the electronic charge and spin properties simultaneously in a single material has made diluted magnetic semiconductors (DMS) remarkable in the field of spintronics. We report the designing of DMS based on zinc-blend ZnO doped with Cr impurity. The full potential linearized augmented plane wave plus local orbital FP-L(APW+lo) method in density functional theory (DFT) has been adapted to carry out these investigations. For treatment of exchange and correlation energy, generalized gradient approximations have been used. Introducing Cr atoms in the matrix of ZnO has induced strong magnetic moment with ferromagnetic ordering at stable ground state. Cr:ZnO was found to favor the short range magnetic interaction that reflect the tendency of Cr clustering. The electronic structure of ZnO is strongly influenced in the presence of Cr impurity atoms where impurity bands appear in the band gap.

Keywords: ZnO, density functional theory, diluted agnetic semiconductors, ferromagnetic materials, FP-L(APW+lo)

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24542 12x12 MIMO Terminal Antennas Covering the Whole LTE and WiFi Spectrum

Authors: Mohamed Sanad, Noha Hassan

Abstract:

A broadband resonant terminal antenna has been developed. It can be used in different MIMO arrangements such as 2x2, 4x4, 8x8, or even 12x12 MIMO configurations. The antenna covers the whole LTE and WiFi bands besides the existing 2G/3G bands (700-5800 MHz), without using any matching/tuning circuits. Matching circuits significantly reduce the efficiency of any antenna and reduce the battery life. They also reduce the bandwidth because they are frequency dependent. The antenna can be implemented in smartphone handsets, tablets, laptops, notebooks or any other terminal. It is also suitable for different IoT and vehicle applications. The antenna is manufactured from a flexible material and can be bent or folded and shaped in any form to fit any available space in any terminal. It is self-contained and does not need to use the ground plane, the chassis or any other component of the terminal. Hence, it can be mounted on any terminal at different positions and configurations. Its performance does not get affected by the terminal, regardless of its type, shape or size. Moreover, its performance does not get affected by the human body of the terminal’s users. Because of all these unique features of the antenna, multiples of them can be simultaneously used for MIMO diversity coverage in any terminal device with a high isolation and a low correlation factor between them.

Keywords: IOT, LTE, MIMO, terminal antenna, WiFi

Procedia PDF Downloads 184
24541 An ALM Matrix Completion Algorithm for Recovering Weather Monitoring Data

Authors: Yuqing Chen, Ying Xu, Renfa Li

Abstract:

The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

Procedia PDF Downloads 380
24540 Field Production Data Collection, Analysis and Reporting Using Automated System

Authors: Amir AlAmeeri, Mohamed Ibrahim

Abstract:

Various data points are constantly being measured in the production system, and due to the nature of the wells, these data points, such as pressure, temperature, water cut, etc.., fluctuations are constant, which requires high frequency monitoring and collection. It is a very difficult task to analyze these parameters manually using spreadsheets and email. An automated system greatly enhances efficiency, reduce errors, the need for constant emails which take up disk space, and frees up time for the operator to perform other critical tasks. Various production data is being recorded in an oil field, and this huge volume of data can be seen as irrelevant to some, especially when viewed on its own with no context. In order to fully utilize all this information, it needs to be properly collected, verified and stored in one common place and analyzed for surveillance and monitoring purposes. This paper describes how data is recorded by different parties and departments in the field, and verified numerous times as it is being loaded into a repository. Once it is loaded, a final check is done before being entered into a production monitoring system. Once all this is collected, various calculations are performed to report allocated production. Calculated production data is used to report field production automatically. It is also used to monitor well and surface facility performance. Engineers can use this for their studies and analyses to ensure field is performing as it should be, predict and forecast production, and monitor any changes in wells that could affect field performance.

Keywords: automation, oil production, Cheleken, exploration and production (E&P), Caspian Sea, allocation, forecast

Procedia PDF Downloads 153