Search results for: data repair

Authors: Elena I. Oprita, Oana Craciunescu, Rodica Tatia, Teodora Ciucan, Reka Barabas, Orsolya Raduly, Anca Oancea

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Healing of osteochondral defects requires repair of the damaged articular cartilage, the underlying subchondral bone and the interface between these tissues (the functional calcified layer). For this purpose, developing a single monophasic scaffold that can regenerate two specific lineages (cartilage and bone) becomes a challenge. The aim of this work was to develop variants of biodegradable cross-linked composite hydrogel based on natural polypeptides (gelatin), polysaccharides components (chondroitin-4-sulphate and hyaluronic acid), in a ratio of 2:0.08:0.02 (w/w/w) and mixed with Si-hydroxyapatite (Si-Hap), in two ratios of 1:1 and 2:1 (w/w). Si-Hap was synthesized and characterized as a better alternative to conventional Hap. Subsequently, both composite hydrogel variants were cross-linked with (N, N-(3-dimethylaminopropyl)-N-ethyl carbodiimide (EDC) and enriched with a small bioactive molecule (icariin). The small molecule icariin (Ica) (C33H40O15) is the main active constituent (flavonoid) of Herba epimedium used in traditional Chinese medicine to cure bone- and cartilage-related disorders. Ica enhances osteogenic and chondrogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), facilitates matrix calcification and increases the specific extracellular matrix (ECM) components synthesis by chondrocytes. Afterward, the composite hydrogels were characterized for their physicochemical properties in terms of the enzymatic biodegradation in the presence of type I collagenase and trypsin, the swelling capacity and the degree of crosslinking (TNBS assay). The cumulative release of Ica and real-time concentration were quantified at predetermined periods of time, according to the standard curve of standard Ica, after hydrogels incubation in saline buffer at physiological parameters. The obtained cross-linked composite hydrogels enriched with small-molecule Ica were also characterized for morphology by scanning electron microscopy (SEM). Their cytocompatibility was evaluated according to EN ISO 10993-5:2009 standard for medical device testing. Thus, analyses regarding cell viability (Live/Dead assay), cell proliferation (Neutral Red assay) and cell adhesion to composite hydrogels (SEM) were performed using NCTC clone L929 cell line. The final results showed that both cross-linked composite hydrogel variants enriched with Ica presented optimal physicochemical, structural and biological properties to be used as a natural scaffold able to repair osteochondral defects. The data did not reveal any toxicity of composite hydrogels in NCTC stabilized cell lines within the tested range of concentrations. Moreover, cells were capable of spreading and proliferating on both composite hydrogel surfaces. In conclusion, the designed biodegradable cross-linked composites enriched with Si and Ica are recommended for further testing as natural temporary scaffolds, which can allow cell migration and synthesis of new extracellular matrix within osteochondral defects.

Keywords: composites, gelatin, osteochondral defect, small molecule

Procedia PDF Downloads 151

Authors: Enhui Wang, Qingzhu Ou, Yan Tang, Xiaodong Guo

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As one of most popular polyanionic compounds in lithium-ion cathode materials, Li3V2(PO4)3 has always suffered from the low rate capability especially during 3~4.8V, which is considered to be related with the ion diffusion resistance and structural transformation during the Li+ de/intercalation. Here, as the change of cut-off voltages, cycling numbers and current densities, the process of SEI interfacial film’s formation-growing- destruction-repair on the surface of the cathode, the structural transformation during the charge and discharge, the de/intercalation kinetics reflected by the electrochemical impedance and the diffusion coefficient, have been investigated in detail. Current density, cycle numbers and cut-off voltage impacting on interfacial film and structure was studied specifically. Firstly, the matching between electrolyte and material was investigated, it turned out that the batteries with high voltage electrolyte showed the best electrochemical performance and high voltage electrolyte would be the best electrolyte. Secondly, AC impedance technology was used to study the changes of interface impedance and lithium ion diffusion coefficient, the results showed that current density, cycle numbers and cut-off voltage influenced the interfacial film together and the one who changed the interfacial properties most was the key factor. Scanning electron microscopy (SEM) analysis confirmed that the attenuation of discharge specific capacity was associated with the destruction and repair process of the SEI film. Thirdly, the X-ray diffraction was used to study the changes of structure, which was also impacted by current density, cycle numbers and cut-off voltage. The results indicated that the cell volume of Li3V2 (PO4 )3 increased as the current density increased; cycle numbers merely influenced the structure of material; the cell volume decreased first and moved back gradually after two Li-ion had been deintercalated as the charging cut-off voltage increased, and increased as the intercalation number of Li-ion increased during the discharging process. Then, the results which studied the changes of interface impedance and lithium ion diffusion coefficient turned out that the interface impedance and lithium ion diffusion coefficient increased when the cut-off voltage passed the voltage platforms and decreased when the cut-off voltage was between voltage platforms. Finally, three-electrode system was first adopted to test the activation energy of the system, the results indicated that the activation energy of the three-electrode system (22.385 KJ /mol) was much smaller than that of two-electrode system (40.064 KJ /mol).

Keywords: cut-off voltage, de/intercalation kinetics, solid electrolyte interphase film, structural transformation

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: Mayada Mazher, Ahmed Moustafa, Ahmed Abdellatif

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Background: Autophagy is a eukaryotic, highly conserved catabolic process implicated in many pathophysiologies such as wound healing. Autophagy-associated genes serve as a scaffolding platform for signal transduction of macrophage polarization during the inflammatory phase of wound healing and tissue repair process. In the current study, we report a model for the interplay between autophagy-associated genes and macrophages polarization associated genes. Methods: In silico analysis was performed on 249 autophagy-related genes retrieved from the public autophagy database and gene expression data retrieved from Gene Expression Omnibus (GEO); GSE81922 and GSE69607 microarray data macrophages polarization 199 DEGS. An integrated protein-protein interaction network was constructed for autophagy and macrophage gene sets. The gene sets were then used for GO terms pathway enrichment analysis. Common transcription factors for autophagy and macrophages' polarization were identified. Finally, microRNAs enriched in both autophagy and macrophages were predicated. Results: In silico prediction of common transcription factors in DEGs macrophages and autophagy gene sets revealed a new role for the transcription factors, HOMEZ, GABPA, ELK1 and REL, that commonly regulate macrophages associated genes: IL6,IL1M, IL1B, NOS1, SOC3 and autophagy-related genes: Atg12, Rictor, Rb1cc1, Gaparab1, Atg16l1. Conclusions: Autophagy and macrophages' polarization are interdependent cellular processes, and both autophagy-related proteins and macrophages' polarization related proteins coordinate in tissue remodelling via transcription factors and microRNAs regulatory network. The current work highlights a potential new role for transcription factors HOMEZ, GABPA, ELK1 and REL in wound healing.

Keywords: autophagy related proteins, integrated network analysis, macrophages polarization M1 and M2, tissue remodelling

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Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Ehsan Kaviani, Azin Golmoradizade

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Introduction: Traditionally, tendons are considered to only contain tenocytes that are responsible for the maintenance, repair, and remodeling of tendons. Stem cells, which are termed tendon-derived stem cells, so this study we investigate the effect of transcranial direct current stimulation combined with swallowing training on post-stroke dysphagia. Methods: This review article is about effects of transcranial direct current stimulation (tDCS) on post-stroke dysphagia that were extracted from Science Direct, Pro quest, and Pub med Data Bases. 15 articles had been selected according to inclusion criteria from 2014 to 2019, and 6 of them had been deleted by exclusion criteria. Results: The results of our systematic review suggest that tDCS may represent a promising novel treatment for post-stroke dysphagia. However, to date, little is known about the optimal parameters of tDCS for relieving post-stroke dysphagia. Further studies are warranted to refine this promising intervention by exploring the optimal parameters of tDCS. Conclusion: anodal tDCS over the affected hemisphere may be as effective as cathodal tDCS on the unaffected hemisphere to enhance recovery after subacute ischemic stroke and anodal tdcs applied over the affected pharyngeal motor cortex can enhance the outcome of swallowing training in post-stroke dysphagia.

Keywords: dysphagia, stroke, cortical stimulation, transcranial direct current stimulation

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Authors: Priscilla Akua Agyapong

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Background: In a country of nearly 34 million people, Ghana suffers from rapidly growing pediatric CHD cases and not enough pediatric specialists to attend to the burgeoning needs of these children. Most of the cases are either missed or diagnosed late, resulting in increased mortality. According to the National Cardiothoracic Centre, 1 in every 100,000 births in Ghana has CHD; however, there is limited data on the clinical presentation and its management, one of the many reasons I decided to do this case study coupled with the loss my 2 month old niece to multiple Ventricular Septal Defect 3 years ago due late diagnoses. Method: A retrospective cohort study was performed at the child health clinic of one of Ghana’s public tertiary Institutions using data from their electronic health record (EHR) from February 2021 to April 2022. All suspected or provisionally diagnosed cases were included in the analysis. Results: Records of over 3000 children were reviewed with an approximate male to female ratio of 1:1.53 cases diagnosed during the period of study, most of whom were less than 5 years of age. 25 cases had complete clinical records, with acyanotic septal defects being the most diagnosed. 62.5% of the cases were ventricular septal defects, followed by Patent Ductus Arteriosus (23%) and Atrial Septal Defects (4.5%). Tetralogy of Fallot was the most predominant and complex cyanotic CHD with 10%. Conclusion: The indeterminate coronary anatomy of infants makes it difficult to use only echocardiography and other conventional clinical methods in screening for CHDs. There are rising modernizations and new innovative ways that can be employed in Ghana for early detection, hence preventing the delay of a potential surgical repair. It is, therefore, imperative to create the needed awareness about these “SILENT CRISES” and help save the Ghanaian child’s life.

Keywords: congenital heart defect(CHD), ventricular septal defect(VSD), atrial septal defect(ASD), patent ductus arteriosus(PDA)

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

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System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Shahnewaz Khan

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Machine learning (ML) techniques are often used in projects for creating data-driven applications. These tasks typically demand additional research and analysis. The proper technique and strategy must be chosen to ensure the success of data-driven projects. Otherwise, even exerting a lot of effort, the necessary development might not always be possible. In this post, an effort to examine the workflow of data-driven software development projects and its implementation process in order to describe how to manage a project successfully. Which will assist in minimizing the added workload.

Keywords: data, data-driven projects, data science, NLP, software project

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Vahid Bairami Rad

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Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

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Authors: Kakali Roy, Sahana P. Raju, Subhra Dhar, Sandipan Dhar

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Introduction: Xeroderma pigmentosa (XP) is a rare inherited (autosomal recessive) disease resulting from impairment in DNA repair that involves recognition and repair of ultraviolet radiation (UVR) induced DNA damage in the nucleotide excision repair pathway. Which results in increased photosensitivity, UVR induced damage to skin and eye, increased susceptibility of skin and ocular cancer, and progressive neurodegeneration in some patients. XP is present worldwide, with higher incidence in areas having frequent consanguinity. Being extremely rare, there is limited literature on XP and associated complications. Here, the clinico-pathological experience (spectrum of clinical presentation, histopathological findings of malignant skin lesions, and progression) of managing 8 cases of XP is presented. Methodology: A retrospective study was conducted in a pediatric tertiary care hospital in eastern India during a ten-year period from 2013 to 2022. A clinical diagnosis was made based on severe sun burn or premature photo-aging and/or onset of cutaneous malignancies at early age (1st decade) in background of consanguinity and autosomal recessive inheritance pattern in family. Results: The mean age of presentation was 1.2 years (range of 7month-3years), while three children presented during their infancy. Male to female ratio was 5:3, and all were born of consanguineous marriage. They presented with dermatological manifestations (100%) followed by ophthalmic (75%) and/or neurological symptoms (25%). Patients had normal skin at birth but soon developed extreme sensitivity to UVR in the form of exaggerated sun tanning, burning, and blistering on minimal sun exposure, followed by abnormal skin pigmentation like freckles and lentiginosis. Subsequently, over time there was progressive xerosis, atrophy, wrinkling, and poikiloderma. Six patients had varied degree of ocular involvement, while three of them had severe manifestation, including madarosis, tylosis, ectropion, Lagopthalmos, Pthysis bulbi, clouding and scarring of the cornea with complete or partial loss of vision, and ophthalmic malignancies. 50% (n=4) cases had skin and ocular pre-malignant (actinic keratosis) and malignant lesions, including melanoma and non melanoma skin cancer (NMSC) like squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) in their early childhood. One patient had simultaneous occurrence of multiple malignancies together (SCC, BCC, and melanoma). Subnormal intelligence was noticed as neurological feature, and none had sensory neural hearing loss, microcephaly, neuroregression, or neurdeficit. All the patients had been being managed by a multidisciplinary team of pediatricians, dermatologists, ophthalmologists, neurologists and psychiatrists. Conclusion: Although till date there is no complete cure for XP and the disease is ultimately fatal. But increased awareness, early diagnosis followed by persistent vigorous protection from UVR, and regular screening for early detection of malignancies along with psychological support can drastically improve patients’ quality of life and life expectancy. Further research is required on formulating optimal management of XP, specifically the role and possibilities of gene therapy in XP.

Keywords: childhood malignancies, dermato-pathological findings, eastern India, Xeroderma pigmentosa

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Natalie M. Wride, Xueyu Geng

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Subgrade soils of railway infrastructure are subjected to a significant number of load applications over their design life. The use of slab track on existing and future proposed rail links requires a reduced maintenance and repair regime for the embankment subgrade, due to restricted access to the subgrade soils for remediation caused by cyclic deformation. It is, therefore, important to study the deformation behaviour of soft cohesive subsoils induced as a result of long term cyclic loading. In this study, a series of oedometer tests and cyclic triaxial tests (10,000 cycles) have been undertaken to investigate the undrained deformation behaviour of soft kaolin. X-ray Computer Tomography (CT) scanning of the samples has been performed to determine the change in porosity and soil structure density from the sample microstructure as a result of the laboratory testing regime undertaken. Combined with the examination of excess pore pressures and strains obtained from the cyclic triaxial tests, the results are compared with an existing analytical solution for long term settlement considering repeated low amplitude loading. Modifications to the analytical solution are presented based on the laboratory analysis that shows good agreement with further test data.

Keywords: creep, cyclic loading, deformation, long term settlement, train loading

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Winfred Okoe Addy, Jean Jacques Dominique Beraud

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Access control systems (ACs) are some of the most important components in safety areas. Inaccuracies of regulatory frameworks make personal policies and remedies more appropriate than standard models or protocols. This problem is exacerbated by the increasing complexity of software, such as integrated Big Data (BD) software for controlling large volumes of encrypted data and resources embedded in a dedicated BD production system. This paper proposes a general access control strategy system for the diffusion of Big Data domains since it is crucial to secure the data provided to data consumers (DC). We presented a general access control circulation strategy for the Big Data domain by describing the benefit of using designated access control for BD units and performance and taking into consideration the need for BD and AC system. We then presented a generic of Big Data access control system to improve the dissemination of Big Data.

Keywords: access control, security, Big Data, domain

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Authors: Aena Iqbal

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The lack of access to maternal and reproductive health in Pakistan poses a great threat to global public health. Obstetric issues, including vesicovaginal fistulas (VVF), are the most common in South Asian countries, leaving women in a more vulnerable state. Koohi Goth Women’s Hospital offers free VVF operations, which draws in women from all over Pakistan. Although reproductive health is being handled, mental health is often neglected in these scenarios. Using a series of questions inspired by the Warwick Edinburgh Model, this paper builds on the results from interviewing women who have received vesicovaginal fistula repair surgery on their mental health, a taboo topic in Pakistan.

Keywords: obstetrics, VVF, Pakistan, reproductive health

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis 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 Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Stephanie Cornish

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The use of synthetic dermal templates, also known as dermal matrices, such as PolyNovo® Biodegradable Temporising Matrix (BTM), has been well established in the reconstruction of acute wounds with a full thickness defect of the skin. Its use has become common place in the treatment of full thickness burns and is not unfamiliar in the realm of necrotising fasciitis, free flap donor site reconstruction, and the management of acute traumatic wounds. However, the use of dermal templates for more chronic wounds is rare. The authors present the successful use of BTM in the reconstruction of a chronic scalp wound following the excision of a malignancy and multiple previous failed attempts at repair, thus demonstrating the potential for an increased scope of use.

Keywords: dermal template, BTM, chronic, scalp wound, reconstruction

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

Procedia PDF Downloads 51

Authors: Abdullah Alsaeed

Abstract:

Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

Procedia PDF Downloads 59

Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

Abstract:

Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

Procedia PDF Downloads 209

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

Procedia PDF Downloads 488