Search results for: data acquisition

Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta

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Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.

Keywords: database, orphans, programming, C⁺⁺

Procedia PDF Downloads 128

Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

Procedia PDF Downloads 499

Authors: Slah Alsaleh

Abstract:

In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

Procedia PDF Downloads 296

Authors: Changfeng Fu

Abstract:

Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

Procedia PDF Downloads 344

Authors: Lexi Li

Abstract:

This study aims to contribute to the field of how computer technology can be exploited to enhance EFL textbook design. Specifically, the study demonstrates how computerized native and learner corpora can be used to enhance modal verb treatment in EFL textbooks. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because the pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the “secondary school” section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was compared with the textbook corpus in terms of the use (distributional features, semantic functions, and co-occurring constructions) in order to examine the degree of influence of the textbook on learners’ use of modal verbs. Moreover, the learner corpus was analyzed for the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The results indicate discrepancies between the textbook presentation of modal verbs and authentic modal use in natural discourse in terms of distributions of frequencies, semantic functions, and co-occurring structures. Furthermore, there are consistent patterns of use between the learner corpus and the textbook corpus with respect to the three above-mentioned aspects, except could, will and must, partially confirming the correlation between the frequency effects and L2 grammar acquisition. Further analysis reveals that the exceptions are caused by both positive and negative L1 transfer, indicating that the frequency effects can be intercepted by L1 interference. Besides, error analysis revealed that could, would, should and must are the most difficult for Chinese learners due to both inter-linguistic and intra-linguistic interference. The discrepancies between the textbook corpus and the native corpus point to a need to adjust the presentation of modal verbs in the textbooks in terms of frequencies, different meanings, and verb-phrase structures. Along with the adjustment of modal verb treatment based on authentic use, it is important for textbook writers to take into consideration the L1 interference as well as learners’ difficulties in their use of modal verbs. The present study is a methodological showcase of the combination both native and learner corpora in the enhancement of EFL textbook language authenticity and appropriateness for learners.

Keywords: EFL textbooks, learner corpus, modal verbs, native corpus

Procedia PDF Downloads 107

Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 644

Authors: Z. Kurtaslan, H. Hakan Okay, E. Can Dönmez, I. Kuçukdoğan

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Music education aims to bring up individuals most appropriately and to advanced levels as a balanced whole physically, cognitively, affectively, and kinesthetically while making a major contribution to the physical and spiritual development of the individual. The most crucial aim of music education, an influential education medium per se, is to make music be loved; yet, among its educational aims are concepts such as affinity, friendship, goodness, philanthropy, responsibility, and respect all extremely crucial bringing up individuals as a balanced whole. One of the most essential assets of the music education is the training of making music together, solidifying musical knowledge and enabling the acquisition of cooperation. This habit requires internalization of values like responsibility, patience, cooperativeness, respect, self-control, friendship, and fairness. If musicians lack these values, the ensemble will become after some certain time a cacophony. In this qualitative research, the attitudes of music teacher candidates in orchestra/chamber music classes will be examined in terms of values.

Keywords: education, music, orchestra/chamber music, values

Procedia PDF Downloads 491

Authors: Khaled ElEbyary, Ramy Shabara

Abstract:

L2 research has generally acknowledged the role of noticing in language learning. The role of teacher feedback is to trigger learners’ noticing of errors and direct the writing process. Recently L2 learners are seemingly using computerized applications which provide corrective feedback (CF) at different stages of writing (i.e., during and after writing). This study aimed principally to answer the question, “Is noticing likely to be maximized when feedback on erroneous output is electronically provided either during or after the composing stage, or does teacher annotated feedback have a stronger effect?”. Seventy-five participants were randomly distributed into four groups representing four conditions. These include receiving automated feedback at the composing stage, automated feedback after writing, teacher feedback, and no feedback. Findings demonstrate the impact of CF on writing and the intensity of noticing certain language areas at different writing stages and from different feedback sources.

Keywords: written corrective feedback, error correction, noticing, automated written corrective feedback, L2 acquisition

Procedia PDF Downloads 70

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

Procedia PDF Downloads 554

Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis

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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Keywords: nowcasting, search data, Google Trends, official statistics

Procedia PDF Downloads 340

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 457

Authors: Rahma Saleh Hussein Al Balushi

Abstract:

Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, CMMS

Procedia PDF Downloads 106

Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

Procedia PDF Downloads 125

Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

Procedia PDF Downloads 452

Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik

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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.

Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet

Procedia PDF Downloads 548

Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

Procedia PDF Downloads 64

Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

Procedia PDF Downloads 133

Authors: Xiaoyang Zhao, Kaiying Wang

Abstract:

The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

Procedia PDF Downloads 141

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

Abstract:

In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

Procedia PDF Downloads 138

Authors: S. S. Nafee, A. M. Al-Ramady, S. A. Shaheen

Abstract:

Evaluated nuclear decay data for the 217Po nuclide ispresented in the present work. These data include recommended values for the half-life T1/2, α-, β--, and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons has been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.

Keywords: nuclear decay data evaluation, mass evaluation, total converison coefficients, atomic mass evaluation

Procedia PDF Downloads 415

Authors: I. Nyoman Mahayasa Adiputra

Abstract:

Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

Procedia PDF Downloads 113

Authors: Rana Zeina

Abstract:

Cognitive and behavioral symptoms may, in fact, overlap and be related to the level of the general cognitive function. We measured the behavioral aspects of autism and its correlation to the cognitive ability in 30 children with ASD. We used a neuropsychological battery CANTAB eclipse to evaluate the ASD children's cognitive ability. Individuals with ASDs and challenging behaviors showed significant correlation between some cognitive abilities and motor behavior aspects. Based on these findings we can conclude that the motor behavioral problems in autism affect specific cognitive abilities in ASDs such as comprehension, learning, reversal, acquisition, attention set shifting, and speed of reaction to one stimulus. Future research should also focus on the relationship between motor stereotypes and other subtypes of repetitive behaviors, such as verbal stereotypes, and ritual and routine adherence and use different types of CANTAB tests.

Keywords: cognitive ability, CANTAB test, behaviour motor aspects, autism spectrum disorders

Procedia PDF Downloads 477

Authors: Mitzi S. Brammer

Abstract:

Given that the cultural make-up of programs of study in institutions of higher learning is becoming increasingly diverse, much has been written about cultural diversity from a university-level perspective. However, there are little data in the way of specific programs and how they address inclusive practices when teaching and working with marginalized populations. This research study aimed to discover baseline knowledge and attitudes of health sciences faculty, instructional staff, and students related to inclusive teaching/learning and interactions. Quantitative data were collected via an anonymous online survey (one designed for students and another designed for faculty/instructional staff) using a web-based program called Qualtrics. Quantitative data were analyzed amongst the faculty/instructional staff and students, respectively, using descriptive and comparative statistics (t-tests). Additionally, some participants voluntarily engaged in a focus group discussion in which qualitative data were collected around these same variables. Collecting qualitative data to triangulate the quantitative data added trustworthiness to the overall data. The research team analyzed collected data and compared identified categories and trends, comparing those data between faculty/staff and students, and reported results as well as implications for future study and professional practice.

Keywords: inclusion, higher education, pedagogy, equity, diversity

Procedia PDF Downloads 47

Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

Procedia PDF Downloads 321

Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

Abstract:

Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

Procedia PDF Downloads 378

Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

Procedia PDF Downloads 305

Authors: Rahma Al Balushi

Abstract:

Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS dept. This paper will describe in detail the GIS data submission process and the journey to develop the current process. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting, and data alterations salso aided to reduce the missing attributes of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the year 2017 and the year 2021. Overall, concluding that by governance, asset information & GIS department can control GIS data process; collect, properly record, and manage asset data and information within OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, geodatabase, NOC, CMMS

Procedia PDF Downloads 189

Authors: Pallavi Malhotra

Abstract:

This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

Procedia PDF Downloads 310

Authors: Olayinka Adeniyi, Melissa Omino

Abstract:

The field of data privacy and data protection in Africa is still an evolving area, with many African countries yet to enact legislation on the subject. While African Governments are bringing their legislation to speed in this field, how patriarchy pervades every sector of African thought and manifests in society needs to be considered. Moreover, the laws enacted ought to be inclusive, especially towards women. This, in a nutshell, is the essence of data feminism. Data feminism is a new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Feminising data privacy and protection will involve thinking women, considering women in the issues of data privacy and protection, particularly in legislation, as is the case in this paper. The line of thought of women inclusion is not uncommon when even international and regional human rights specific for women only came long after the general human rights. The consideration is that these should have been inserted or rather included in the original general instruments in the first instance. Since legislation on data privacy is coming in this century, having seen the rights and shortcomings of earlier instruments, then the cue should be taken to ensure inclusive wholistic legislation for data privacy and protection in the first instance. Data feminism is arguably an area that has been scantily researched, albeit a needful one. With the spate of increase in the violence against women spiraling in the cyber world, compounding the issue of COVID-19 and the needful response of governments, and the effect of these on women and their rights, fast forward, the research on the feminism of data privacy and protection in Africa becomes inevitable. This paper seeks to answer the questions, what is data feminism in the African context, why is it important in the issue of data privacy and protection legislation; what are the laws, if any, existing on data privacy and protection in Africa, are they women inclusive, if not, why; what are the measures put in place for the privacy and protection of women in Africa, and how can this be made possible. The paper aims to investigate the issue of data privacy and protection in Africa, the legal framework, and the protection or provision that it has for women if any. It further aims to research the importance and necessity of feminizing data privacy and protection, the effect of lack of it, the challenges or bottlenecks in attaining this feat and the possibilities of accessing data privacy and protection for African women. The paper also researches the emerging practices of data privacy and protection of women in other jurisprudences. It approaches the research through the methodology of review of papers, analysis of laws, and reports. It seeks to contribute to the existing literature in the field and is explorative in its suggestion. It suggests a draft of some clauses to make any data privacy and protection legislation women inclusive. It would be useful for policymaking, academic, and public enlightenment.

Keywords: feminism, women, law, data, Africa

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Authors: Kaczmarzyk Piotr, Anna Dziechciarz, Wojciech Klapsa

Abstract:

The purpose of this paper is demonstration the test results of research influence of temperature on the velocity of flame propagation using gas and air mixtures for selected gas mixtures. The research was conducted on the test apparatus in the form of duct 2 m long. The test apparatus was funded from the project: “Development of methods to neutralize threats of explosion for determined tanks contained technical gases, including alternative sources of supply in the fire environment, taking into account needs of rescuers” number: DOB-BIO6/02/50/2014. The Project is funded by The National Centre for Research and Development. This paper presents the results of measurement of rate of pressure rise and rate in flame propagation, using test apparatus for mixtures air and methane or air and propane. This paper presents the results performed using the test apparatus in the form of duct measuring the rate of flame and overpressure wave. Studies were performed using three gas mixtures with different concentrations: Methane (3% to 8% vol), Propane (3% to 6% vol). As regard to the above concentrations, tests were carried out at temperatures 20 and 30 ̊C. The gas mixture was supplied to the inside of the duct by the partial pressure molecules. Data acquisition was made using 5 dynamic pressure transducers and 5 ionization probes, arranged along of the duct. Temperature conditions changes were performed using heater which was mounted on the duct’s bottom. During the tests, following parameters were recorded: maximum explosion pressure, maximum pressure recorded by sensors and voltage recorded by ionization probes. Performed tests, for flammable gas and air mixtures, indicate that temperature changes have an influence on overpressure velocity. It should be noted, that temperature changes do not have a major impact on the flame front velocity. In the case of propane and air mixtures (temperature 30 ̊C) was observed DDT (Deflagration to Detonation) phenomena. The velocity increased from 2 to 20 m/s. This kind of explosion could turn into a detonation, but the duct length is too short (2 m).

Keywords: flame propagation, flame propagation velocity, explosion, propane, methane

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