Search results for: Privacy and Data Protection Law

Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

Procedia PDF Downloads 146

Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

Procedia PDF Downloads 283

Authors: Mutshinye Manguvhewa, Maria Florence, Mansoo Yu, Elize Koch, Kamal Kamaloodien

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Substance use among pregnant women is a perennial problem in the Western Cape Province of South Africa. There are many influential factors are associated with substance use among women of childbearing age. The study explored factors associated with substance use among pregnant women using a qualitative research design and the bio-ecological theoretical framework to explore and guide the researcher throughout the study. Participants were selected using purposive sampling. Only participants accessed from the Department of Social Development meeting the inclusion criteria of the study were interviewed using semi structured interviews. Immediate referral for psychological intervention during the interview was available for participants who needed it. Braun and Clarke's six phases of thematic analysis were utilised to analyse the data. The study adheres to ethical guidelines for the participants' protection. Participants were informed about the study before the initiation of the interviews and the details of their voluntary participation were explained. The key findings from this study illustrate that socio-cultural factors, personal factors, emotional response and intimate relationships are the major contributing factors to substance use among pregnant women in this sample. The results outline the preventative measures that pregnant women implement. Lastly, the study reveals the positive and negative perceptions of substance use programmes that participants share. Some of the study findings are similar to the existing literature and some of the findings differed. Recommendations emanating from the study include that the stakeholders, rehabilitation centres, Department of Health and future researchers should act proactively against substance use during pregnancy.

Keywords: substance addiction, antenatal care, pregnancy, substance use

Procedia PDF Downloads 110

Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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Authors: Kedibone Masenya, Memory Tekere, Jasper Rees

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Sorghum is an important cereal crop in the world. In particular, it has attracted breeders due to capacity to serve as food, feed, fiber and bioenergy crop. Like any other plant, sorghum hosts a variety of microbes, which can either, have a neutral, negative and positive influence on the plant. In the current study, regions (V3/V4) of 16 S rRNA were targeted to extensively assess bacterial multitrophic interactions in the phyllosphere of sorghum. The results demonstrated that the presence of a pathogen has a significant effect on the endophytic bacterial community. Understanding these interactions is key to develop new strategies for plant protection.

Keywords: bacteria, multitrophic, sorghum, target sequencing

Procedia PDF Downloads 267

Authors: Mai Ghazal, Ahmed Hammad

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Cost overruns in construction projects are considered as worldwide challenges since the cost performance is one of the main measures of success along with schedule performance. To overcome this problem, studies were conducted to investigate the cost overruns' factors, also projects' historical data were analyzed to extract new and useful knowledge from it. This research is studying and analyzing the effect of some factors causing cost overruns using the historical data from completed construction projects. Then, using these factors to estimate the probability of cost overrun occurrence and predict its percentage for future projects. First, an intensive literature review was done to study all the factors that cause cost overrun in construction projects, then another review was done for previous researcher papers about mining process in dealing with cost overruns. Second, a proposed data warehouse was structured which can be used by organizations to store their future data in a well-organized way so it can be easily analyzed later. Third twelve quantitative factors which their data are frequently available at construction projects were selected to be the analyzed factors and suggested predictors for the proposed model.

Keywords: construction management, construction projects, cost overrun, cost performance, data mining, data warehousing, knowledge discovery, knowledge management

Procedia PDF Downloads 352

Authors: Temiloluwa J. Akinyemi, Denis W. Aheto, Wisdom Akpalu

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Capture fisheries in developing countries provide significant animal protein and directly supports the livelihoods of several communities. However, the misperception of biophysical dynamics owing to a lack of adequate scientific data has contributed to the suboptimal management in marine capture fisheries. This is because yield and catch potentials are sensitive to the quality of catch and effort data. Yet, studies on fisheries data collection practices in developing countries are hard to find. This study investigates the data collection methods utilized by fisheries technical officers within the four fishing regions of Ghana. We found that the officers employed data collection and sampling procedures which were not consistent with the technical guidelines curated by FAO. For example, 50 instead of 166 landing sites were sampled, while 290 instead of 372 canoes were sampled. We argue that such sampling errors could result in the over-capitalization of capture fish stocks and significant losses in resource rents.

Keywords: Fisheries data quality, fisheries management, Ghana, Sustainable Fisheries

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Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

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Authors: M. H. Belahssen, S. Benramache

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This paper presents corrosion behavior of alloy 42CrMo4 steel nitrided by plasma. Different samples nitrided were tested. The corrosion behavior was evaluated by electrochemical impedance spectroscopy and the tests were carried out in acid chloride solution 1M. The best corrosion protection was observed for nitrided samples. The aim of this work is to compare equivalents circuits corresponding to Nyquist curves simulated and experimental and select who gives best results of impedance parameters with lowest error.

Keywords: pasma nitriding, steel, alloy 42CrMo4, elecrochemistry, corrosion behavior

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Authors: Peristera Baziana

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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

Procedia PDF Downloads 277

Authors: Liping Qiu, Xiaofeng Zhang

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The ion chromatography method for the rapid determination of four anions (F⁻、Cl⁻、SO₄²⁻、NO₃⁻) in burial ground poles was optimized. The L₉(₃⁴) orthogonal test was used to determine the optimal parameters of sample pretreatment: accurately weigh 2.000g of sample, add 10mL of ultrapure water, and extract for 40min under the conditions of shaking temperature 40℃ and shaking speed 180 r·min-1. The eluent was 25 mmol/L KOH solution, the analytical column was Ion Pac® AS11-SH (250 mm × 4.0 mm), and the purified filtrate was measured by a conductivity detector. Under this method, the detection limit of each ion is 0.066～0.078mg/kg, the relative standard deviation is 0.86%～2.44% (n=7), and the recovery rate is 94.6～101.9.

Keywords: ion chromatography, tomb, anion (F⁻, Cl⁻, SO₄²⁻, NO₃⁻), environmental protection

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Authors: Muhammad Zaman Khan, Vijay Baheti, Jiri Militky

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The present study is focused on the development of multifunctional cotton fabric while having good physiological comfort properties. The functional properties developed include superhydrophobicity (Lotus effect) and UV protection. For this, TiO₂ nanoparticles along with fluorocarbon and organic-inorganic binder have been used to optimize the multifunctional properties. Deposition of TiO₂ nanoparticles with water repellent finish on cotton fabric has been carried out using the pad dry cure method at fix parameters. The morphology and elemental composition of as-deposited particles have been studied by using SEM and EDS. The chemical composition of nanoparticles was determined using energy dispersive spectroscopy. The treated samples exhibited excellent water repellency and UV protection factor. The study of the comfort properties of fabric showed that it had excellent physiological comfort properties. Optimized concentration of water repellent chemical (50g/l) was used in formulations with TiO₂ nanoparticles and organic-inorganic binder. Four formulations were prepared according to the design of the experiment. The formulations were applied to the cotton fabric by roller padding at room temperature (15–20°C). Surface morphology was investigated via SEM images. EDS analysis was also carried out to analyze the composition and atomic percentage of elements. The water contact angle (WCA) of cotton fabric increases with increase in TiO₂ nanoparticles concentration and reaches its maximum value (157°) when the concentration of TiO₂ is 20g/l. The water sliding angle (WSA) decreases and gains minimum value at the same concentration of TiO₂ at which WCA is highest. It was seen samples treated with formulations of TiO₂ nanoparticles exhibits excellent UPF, UV-A and UV-B blocking. However, there was no significant deterioration of air permeability. The water vapor permeability was also slightly decreased (4%) but is acceptable. It can be concluded that there is no significant change in both air and water vapor permeability after nanoparticles coating on the surface of the cotton fabric. The coated cotton fabric has little effect on the stiffness. The stiffness of coated samples was not increased significantly; thus comfort of cotton fabric is not decreased. This functionalized cotton fabric also exhibits good physiological comfort properties. ''The authors are also thankful to student grant competition 21312 provided at Technical University of Liberec''.

Keywords: comfort, functional, nanoparticles, UV protective

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Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

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Authors: Akshay Agrawal, Anand K. Srivastava

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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

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Authors: Hiesik Kim, YongBeum Kim

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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

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Authors: Deeksha Karunakar

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The gaming industry is one of the biggest industries in the world. Video games are interactive works of authorship that require the execution of a computer programme on specialized hardware but which also incorporate a wide variety of other artistic mediums, such as music, scripts, stories, video, paintings, and characters, into which the player takes an active role. Therefore, video games are not made as singular, simple works but rather as a collection of elements that, if they reach a certain level of originality and creativity, can each be copyrighted on their own. A video game is made up of a wide variety of parts, all of which combine to form the overall sensation that we, the players, have while playing. The entirety of the components is implemented in the form of software code, which is then translated into the game's user interface. Even while copyright protection is already in place for the coding of software, the work that is produced because of that coding can also be protected by copyright. This includes the game's storyline or narrative, its characters, and even elements of the code on their own. In each sector, there is a potential legal framework required, and the gaming industry also requires legal frameworks. This represents the importance of intellectual property laws in each sector. This paper will explore the beginnings of video games, the various aspects of game copyrights, and the approach of the courts, including examples of a few different instances. Although the creative arts have always been known to draw inspiration from and build upon the works of others, it has not always been simple to evaluate whether a game has been cloned. The video game business is experiencing growth as it has never seen before today. The majority of today's video games are both pieces of software and works of audio-visual art. Even though the existing legal framework does not have a clause specifically addressing video games, it is clear that there is a great many alternative means by which this protection can be granted. This paper will represent the importance of copyright and trademark laws in the gaming industry and its regulations with the help of relevant case laws via utilizing doctrinal methodology to support its findings. The aim of the paper is to make aware of the applicability of intellectual property laws in the gaming industry and how the justice system is evolving to adapt to such new industries. Furthermore, it will provide in-depth knowledge of their relationship with each other.

Keywords: copyright, DMCA, gaming industry, trademark, WIPO

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Authors: Sreejith Gopinath, Aspen Olmsted

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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 119

Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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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 151

Authors: R. Rezaeipour, A. R. Mehrabi

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Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

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Authors: Michael Gidey Gebru

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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

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Authors: Denise Hexom, Judith Menoher

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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 369

Authors: Yaeji Lim, Hee-Seok Oh

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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

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Authors: Lazlo Fauth, Andreas Ligocki

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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

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

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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

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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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

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Authors: Abdelmenen Abobghala, Mahmud Ahmed, Mohamed Alwaheshi, Anwar Fanan, Meftah Mehdawi, Ahmed Abuhatira

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This research aims to predict academic performance and identify weak points in students to aid teachers in understanding their learning needs. Both quantitative and qualitative methods are used to identify difficult test items and the factors causing difficulties. The study uses interventions like focus group discussions, interviews, and action plans developed by the students themselves. The research questions explore the predictability of final grades based on mock exams and assignments, the student's response to action plans, and the impact on learning performance. Ethical considerations are followed, respecting student privacy and maintaining anonymity. The research aims to enhance student engagement, motivation, and responsibility for learning.

Keywords: prediction, academic performance, weak points, understanding, learning, quantitative methods, qualitative methods, formative assessments, feedback, emotional responses, intervention, focus group discussion, interview, action plan, student engagement, motivation, responsibility, ethical considerations

Procedia PDF Downloads 52

Authors: Claire Baudry, Jessica Pearson, Laura-Emilie Savage, George Tarbulsy

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Over the last fifty years, maternal sensitivity and child development among vulnerable families have been a priority for researchers. For this reason, attachment-based interventions have been implemented and been shown to be effective in enhancing child development. Most of the time, child outcomes are measured shortly after the intervention. Objectives: The goal of the study was to investigate the effects of an attachment-based intervention on child development shortly after the intervention ended and one-year post-intervention. Methods: Over the seventy-two mother-child dyads referred by Child Protective Services in the province of Québec, Canada, forty-two were included in this study: 24 dyads who received 6 to 8 intervention sessions and 18 dyads who did not. Intervention and none intervention dyads were matched for the following variables: duration of child protective services, the reason for involvement with child protection, age, sex, and family status. Internalizing and externalizing behaviors were measured 3 and 12 months after the end of the intervention when the average age of children were respectively 45 and 54 months old. Findings: Independent-sample t-tests were conducted to compare scores between the two groups and the two data collection times. In general, on differences observed between the two groups three months after the intervention ended, just a few of them were still present nine months later. Conclusions: This first set of analyses suggests that the effects of attachment-based intervention observed three months following the intervention are not lasting for most of them. Those results inform us of the importance of considering the possibility to offer more attachment-based intervention sessions for those highly vulnerable families.

Keywords: attachment-based intervention, child behaviors, child protective services, highly vulnerable families

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Authors: A. Kourou, A. Ioakeimidou, E. Pelli, M. Panoutsopoulou, V. Abramea

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Worldwide there is a growing recognition that education is a critical component of any disaster impacts reduction effort and a great challenge too. Given this challenge, a broad range of awareness raising projects at all levels are implemented and are continuously evaluated by Earthquake Planning and Protection Organization (EPPO). This paper presents an overview of EPPO educational initiative (seminars, lectures, workshops, campaigns and educational material) and its evaluation results. The abovementioned initiative is focused to aware the public, train teachers and civil protection staff, inform students and educate people with disabilities on subjects related to earthquake reduction issues. The better understating of how human activity can link to disaster and what can be done at the individual, family or workplace level to contribute to seismic reduction are the main issues of EPPO projects. Survey results revealed that a high percentage of teachers (included the ones of special schools) from all over the country have taken the appropriate preparedness measures at schools. On the other hand, the implementation of earthquake preparedness measures at various workplaces (kindergartens, banks, utilities etc.) has still significant room for improvement. Results show that the employees in banks and public utilities have substantially higher rates in preventive and preparedness actions in their workplaces than workers in kindergartens and other workplaces. One of the EPPO educational priorities is to enhance earthquake preparedness of people with disabilities. Booklets, posters and applications have been created with the financial support of the Council of Europe, addressed to people who have mobility impairments, learning difficulties or cognitive disability (ή intellectual disabilities). Part of the educational material was developed using the «easy-to-read» method and Makaton language program with the collaboration of experts on special needs education and teams of people with cognitive disability. Furthermore, earthquake safety seminars and earthquake drills have been implemented in order to develop children’s, parents’ and teachers abilities and skills on earthquake impacts reduction. To enhance the abovementioned efforts, EPPO is a partner at prevention and preparedness projects supported by EU Civil Protection Financial Instrument. One of them is E-PreS’ project (Monitoring and Evaluation of Natural Hazard Preparedness at School Environment). The main objectives of E-PreS project are: 1) to create smart tools which define, simulate and evaluate drills procedure at schools, centers of vocational training of people with disabilities or other workplaces, and 2) to involve students or adults with disabilities in the E-PreS system evacuation procedure in case of earthquake, flood, or volcanic occurrence. Two other EU projects (RACCE educational kit and EVANDE educational platform) are also with the aim of contributing to raising awareness among people with disabilities, students, teachers, volunteers etc. It is worth mentioning that even though in Greece many efforts have been done till now to build awareness towards earthquakes and establish preparedness status for prospective earthquakes, there are still actions to be taken.

Keywords: earthquake, emergency plans, E-PreS project, people with disabilities, special needs education

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Authors: Guo Wenyu, Qu Youli

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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

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

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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 182