Search results for: violation data discovery
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25805

Search results for: violation data discovery

24935 A Comparison of Image Data Representations for Local Stereo Matching

Authors: André Smith, Amr Abdel-Dayem

Abstract:

The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 371
24934 Metabolomics Profile Recognition for Cancer Diagnostics

Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny

Abstract:

Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: cancer, metabolites, metabolic pathway, signaling pathway

Procedia PDF Downloads 403
24933 Early Childhood Teacher Turnover in an Early Head Start Setting: A Qualitative Examination

Authors: Jennifer Sturgeon

Abstract:

Stable relationships provide a predictable and trusting environment and are essential for early development, but high teacher turnover rates in childcare settings make it challenging for infants and toddlers to form stable relationships with their teachers. This can have an adverse effect on development and learning. The qualitative study discussed in this article draws from the experiences of early Head Start teachers and administrators to describe both the impact of teacher turnover and the motivational factors that contribute to teacher retention. A case study approach was used and included classroom observations, a review of exit interviews, and perceptions from focus groups of early Head Start staff in an urban early Head Start childcare center. Emerging from the case study was the discovery that teacher turnover has an impact on the social-emotional development of toddlers, particularly in self-regulation. Additional key findings that emerged include teacher turnover leading to negative effects on learning, a decrease in preschool preparation, and increased chaos in the classroom and center. Motivational factors that contributed to teacher retention included positive leadership, the mission to make a difference, and fair compensation.

Keywords: early childhood, teacher turnover, continuity of care, early head start

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24932 Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System

Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

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24931 Timing and Noise Data Mining Algorithm and Software Tool in Very Large Scale Integration (VLSI) Design

Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 254
24930 Introduction of Electronic Health Records to Improve Data Quality in Emergency Department Operations

Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

Abstract:

In its simplest form, data quality can be defined as 'fitness for use' and it is a concept with multi-dimensions. Emergency Departments(ED) require information to treat patients and on the other hand it is the primary source of information regarding accidents, injuries, emergencies etc. Also, it is the starting point of various patient registries, databases and surveillance systems. This interventional study was carried out to improve data quality at the ED of the National Hospital of Sri Lanka (NHSL) by introducing an e health solution to improve data quality. The NHSL is the premier trauma care centre in Sri Lanka. The study consisted of three components. A research study was conducted to assess the quality of data in relation to selected five dimensions of data quality namely accuracy, completeness, timeliness, legibility and reliability. The intervention was to develop and deploy an electronic emergency department information system (eEDIS). Post assessment of the intervention confirmed that all five dimensions of data quality had improved. The most significant improvements are noticed in accuracy and timeliness dimensions.

Keywords: electronic health records, electronic emergency department information system, emergency department, data quality

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24929 Data Presentation of Lane-Changing Events Trajectories Using HighD Dataset

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

Abstract:

We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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24928 Whole Coding Genome Inter-Clade Comparisons to Predict Global Cancer-Protecting Variants

Authors: Lamis Naddaf, Yuval Tabach

Abstract:

We identified missense genetic variants with the potential to enhance resistance against cancer. Such a field has not been widely explored as researchers tend to investigate the mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and have significant implications for improved risk estimation, diagnostics, prognosis, and even personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and selected the alleles that showed a correlation with the species’ cancer resistance. Interestingly, we found several amino acids that are more generally preferred (like the Proline) or avoided (like the Cysteine) by the resistant species. Furthermore, Cancer resistance in mammals and reptiles is significantly predicted by the number of the predicted protecting variants (PVs) a species has. Moreover, PVs-enriched-genes are enriched in pathways relevant to tumor suppression. For example, they are enriched in the Hedgehog signaling and silencing pathways, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are mostly more abundant in healthy people compared to cancer patients within different human races.

Keywords: cancer resistance, protecting variant, naked mole rat, comparative genomics

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24927 Intelligent Building as a Pragmatic Approach towards Achieving a Sustainable Environment

Authors: Zahra Hamedani

Abstract:

Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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24926 Characterization of Penicillin V Acid and Its Related Compounds by HPLC

Authors: Bahdja Guerfi, N. Hadhoum, I. Azouz, M. Bendoumia, S. Bouafia, F. Z. Hadjadj Aoul

Abstract:

Background: 'Penicillin V' is a narrow, bactericidal antibiotic of the beta-lactam family of the naturally occurring penicillin group. It is limited to infections due to the germs defined as sensitive. The objective of this work was to identify and to characterize Penicillin V acid and its related compounds by High-performance liquid chromatography (HPLC). Methods: Firstly phenoxymethylpenicillin was identified by an infrared absorption. The organoleptic characteristics, pH, and determination of water content were also studied. The dosage of Penicillin V acid active substance and the determination of its related compounds were carried on waters HPLC, equipped with a UV detector at 254 nm and Discovery HS C18 column (250 mm X 4.6 mm X 5 µm) which is maintained at room temperature. The flow rate was about 1 ml per min. A mixture of water, acetonitrile and acetic acid (65:35:01) was used as mobile phase for phenoxyacetic acid ‘impurity B' and a mixture of water, acetonitrile and acetic acid (650:150:5.75) for the assay and 4-hydroxypenicillin V 'impurity D'. Results: The identification of Penicillin V acid active substance and the evaluation of its chemical quality showed conformity with USP 35th edition. The Penicillin V acid content in the raw material is equal to 1692.22 UI/mg. The percentage content of phenoxyacetic acid and 4-hydroxypenicillin V was respectively: 0.035% and 0.323%. Conclusion: Through these results, we can conclude that the Penicillin V acid active substance tested is of good physicochemical quality.

Keywords: characterization, HPLC, Penicillin V acid, related substances

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24925 Evaluation of Golden Beam Data for the Commissioning of 6 and 18 MV Photons Beams in Varian Linear Accelerator

Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

Abstract:

Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

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24924 Variable-Fidelity Surrogate Modelling with Kriging

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

Abstract:

Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

Procedia PDF Downloads 558
24923 Robust Barcode Detection with Synthetic-to-Real Data Augmentation

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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24922 Analysis of Delivery of Quad Play Services

Authors: Rahul Malhotra, Anurag Sharma

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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24921 Classification of Manufacturing Data for Efficient Processing on an Edge-Cloud Network

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

Abstract:

The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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24920 Denoising Transient Electromagnetic Data

Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

Abstract:

Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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24919 The Droplet Generation and Flow in the T-Shape Microchannel with the Side Wall Fluctuation

Authors: Yan Pang, Xiang Wang, Zhaomiao Liu

Abstract:

Droplet microfluidics, in which nanoliter to picoliter droplets acted as individual compartments, are common to a diverse array of applications such as analytical chemistry, tissue engineering, microbiology and drug discovery. The droplet generation in a simplified two dimension T-shape microchannel with the main channel width of 50 μm and the side channel width of 25 μm, is simulated to investigate effects of the forced fluctuation of the side wall on the droplet generation and flow. The periodic fluctuations are applied on a length of the side wall in the main channel of the T-junction with the deformation shape of the double-clamped beam acted by the uniform force, which varies with the flow time and fluctuation periods, forms and positions. The fluctuations under most of the conditions expand the distribution range of the droplet size but have a little effect on the average size, while the shape of the fixed side wall changes the average droplet size chiefly. Droplet sizes show a periodic pattern along the relative time when the fluctuation is forced on the side wall near the T-junction. The droplet emerging frequency is not varied by the fluctuation of the side wall under the same flow rate and geometry conditions. When the fluctuation period is similar with the droplet emerging period, the droplet size shows a nice stability as the no fluctuation case.

Keywords: droplet generation, droplet size, flow flied, forced fluctuation

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24918 The Constitutional Rights of a Child to a Clean and Healthy Environment: A Case Study in the Vaal Triangle Region

Authors: Christiena Van Der Bank, Marjone Van Der Bank, Ronelle Prinsloo

Abstract:

The constitutional right to a healthy environment and the constitutional duty imposed on the state actively to protect the environment fulfill the specific duties to prevent pollution and ecological degradation and to promote conservation. The aim of this paper is to draw attention to the relationship between child rights and the environment. The focus is to analyse government’s responses as mandated with section 24 of the Bill of Rights for ensuring the right to a clean and healthy environment. The principle of sustainability of the environment encompasses the notion of equity and the harm to the environment affects the present as well as future generations. Section 24 obliges the state to ensure that the legacy of future generations is protected, an obligation that has been said to be part of the common law. The environment is an elusive and wide concept that can mean different things to different people depending on the context in which it is used for example clean drinking water or safe food. An extensive interpretation of the term environment would include almost everything that may positively or negatively influence the quality of human life. The analysis will include assessing policy measures, legislation, budgetary measures and other measures taken by the government in order to progressively meet its constitutional obligation. The opportunity of the child to grow up in a healthy and safe environment is extremely unjustly distributed. Without a realignment of political, legal and economic conditions this situation will not fundamentally change. South Africa as a developing country that needs to meet the demand of social transformation and economic growth whilst at the same time expediting its ability to compete in global markets, the country will inevitably embark on developmental programmes as a measure for sustainable development. The courts would have to inquire into the reasonableness of those measures. Environmental threats to children’s rights must be identified, taking into account children’s specific needs and vulnerabilities, their dependence and marginalisation. Obligations of states and violations of rights must be made more visible to the general public.

Keywords: environment, children rights, pollution, healthy, violation

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24917 Attribute Analysis of Quick Response Code Payment Users Using Discriminant Non-negative Matrix Factorization

Authors: Hironori Karachi, Haruka Yamashita

Abstract:

Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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24916 Developing Guidelines for Public Health Nurse Data Management and Use in Public Health Emergencies

Authors: Margaret S. Wright

Abstract:

Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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24915 An Embarrassingly Simple Semi-supervised Approach to Increase Recall in Online Shopping Domain to Match Structured Data with Unstructured Data

Authors: Sachin Nagargoje

Abstract:

Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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24914 Development of Open Source Geospatial Certification Model Based on Geospatial Technology Competency Model

Authors: Tanzeel Ur Rehman Khan, Franz Josef Behr, Phillip Davis

Abstract:

Open source geospatial certifications are needed in geospatial technology education and industry sector. In parallel with proprietary software, free and open source software solutions become important in geospatial technology research and play an important role for the growth of the geospatial industry. ESRI, GISCI (GIS Certification Institute), ASPRS (American Society of Photogrammetry and remote sensing), and Meta spatial are offering certifications on proprietary and open source software. These are portfolio and competency based certifications depending on GIS Body of Knowledge (Bok). The analysis of these certification approaches might lead to the discovery of some gaps in them and will open a new way to develop certifications related to the geospatial open source (OS). This new certification will investigate the different geospatial competencies according to open source tools that help to identify geospatial professionals and strengthen the geospatial academic content. The goal of this research is to introduce a geospatial certification model based on geospatial technology competency model (GTCM).The developed certification will not only incorporate the importance of geospatial education and production of the geospatial competency-based workforce in universities and companies (private or public) as well as describe open source solutions with tools and technology. Job analysis, market analysis, survey analysis of this certification opens a new horizon for business as well.

Keywords: geospatial certification, open source, geospatial technology competency model, geoscience

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24913 Genodata: The Human Genome Variation Using BigData

Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

Abstract:

Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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24912 Extracting Therapeutic Grade Essential Oils from the Lamiaceae Plant Family in the United Arab Emirates (UAE): Highlights on Great Possibilities and Sever Difficulties

Authors: Suzan M. Shahin, Mohammed A. Salem

Abstract:

Essential oils are expensive phytochemicals produced and extracted from specific species belonging to particular families in the plant kingdom. In the United Arab Emirates country (UAE), which is located in the arid region of the world, nine species, from the Lamiaceae family, having the capability to produce therapeutic grade essential oils. These species include; Mentha spicata, Ocimum forskolei, Salvia macrosiphon, Salvia aegyptiaca, Salvia macilenta, Salvia spinosa, Teucrium polium, Teucrium stocksianum, and Zataria multiflora. Although, such potential species are indigenous to the UAE, however, there are almost no studies available to investigate the chemical composition and the quality of the extracted essential oils under the UAE climatological conditions. Therefore, great attention has to be given to such valuable natural resources, through conducting highly supported research projects, tailored to the UAE conditions, and investigating different extraction techniques, including the application of the latest available technologies, such as superficial fluid CO2. This is crucially needed; in order to accomplish the greatest possibilities in the medicinal field, specifically in the discovery of new therapeutic chemotypes, as well as, to achieve the sustainability of this natural resource in the country.

Keywords: essential oils, extraction techniques, Lamiaceae, traditional medicine, United Arab Emirates (UAE)

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24911 Ontology for a Voice Transcription of OpenStreetMap Data: The Case of Space Apprehension by Visually Impaired Persons

Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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24910 Nature of the Prohibition of Discrimination on Grounds of Sexual Orientation in EU Law

Authors: Anna Pudlo

Abstract:

The EU law encompasses many supranational legal systems (EU law, ECHR, international public law and constitutional traditions common to the Member States) which guarantee the protection of fundamental rights, with partly overlapping scopes of applicability, various principles of interpretation of legal norms and a different hierarchy. In EU law, the prohibition of discrimination on grounds of sexual orientation originates from both the primary and secondary EU legislation. At present, the prohibition is considered to be a fundamental right in pursuance of Article 21 of the Charter, but the Court has not yet determined whether it is a right or a principle within the meaning of the Charter. Similarly, the Court has not deemed this criterion to be a general principle of EU law. The personal and materials scope of the prohibition of discrimination on grounds of sexual orientation based on Article 21 of the Charter requires each time to be specified in another legal act of the EU in accordance with Article 51 of the Charter. The effect of the prohibition of discrimination on grounds of sexual orientation understood as above will be two-fold, for the States and for the Union. On the one hand, one may refer to the legal instruments of review of EU law enforcement by a Member State laid down in the Treaties. On the other hand, EU law does not provide for the right to individual petition. Therefore, it is the duty of the domestic courts to protect the right of a person not to be discriminated on grounds of sexual orientation in line with the national procedural rules, within the limits and in accordance with the principles set out in EU law, in particular in Directive 2000/78. The development of the principle of non-discrimination in the Court’s case-law gives rise to certain doubts as to its applicability, namely whether the principle as the general principle of EU law may be granted an autonomous character, with respect to the applicability to matters not included in the personal or material scope of the Directives, although within the EU’s competence. Moreover, both the doctrine and the opinions of the Advocates-General have called for the general competence of CJEU with regard to fundamental rights which, however, might lead to a violation of the principle of separation of competence. The aim of this paper is to answer the question what is the nature of the prohibition of discrimination on grounds of sexual orientation in EU law (a general principle in EU law, or a principle or right under the Charter’s terminology). Therefore, the paper focuses on the nature of Article 21 of the Charter (a right or a principle) and the scope (personal and material) of the prohibition of discrimination based on sexual orientation in EU law as well as its effect (vertical or horizontal). The study has included the provisions of EU law together with the relevant CJEU case-law.

Keywords: EU law, EU principles, non-discrimination in EU law, Charter of the Fundamental Rights

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24909 Design and Development of a Platform for Analyzing Spatio-Temporal Data from Wireless Sensor Networks

Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 256
24908 Purification and Pre-Crystallization of Recombinant PhoR Cytoplasmic Domain Protein from Mycobacterium Tuberculosis H37Rv

Authors: Oktira Roka Aji, Maelita R. Moeis, Ihsanawati, Ernawati A. Giri-Rachman

Abstract:

Globally, tuberculosis (TB) remains a leading cause of death. The emergence of multidrug-resistant strains and extensively drug-resistant strains have become a major public concern. One of the potential candidates for drug target is the cytoplasmic domain of PhoR Histidine Kinase, a part of the Two Component System (TCS) PhoR-PhoP in Mycobacterium tuberculosis (Mtb). TCS PhoR-PhoP relay extracellular signal to control the expression of 114 virulent associated genes in Mtb. The 3D structure of PhoR cytoplasmic domain is needed to screen novel drugs using structure based drug discovery. The PhoR cytoplasmic domain from Mtb H37Rv was overexpressed in E. coli BL21(DE3), then purified using IMAC Ni-NTA Agarose his-tag affinity column and DEAE-ion exchange column chromatography. The molecular weight of the purified protein was estimated to be 37 kDa after SDS-PAGE analysis. This sample was used for pre-crystallization screening by applying sitting drop vapor diffusion method using Natrix (HR2-116) 48 solutions crystal screen kit at 25ºC. Needle-like crystals were observed after the seventh day of incubation in test solution No.47 (0.1 M KCl, 0.01 M MgCl2.6H2O, 0.05 M Tris-Cl pH 8.5, 30% v/v PEG 4000). Further testing is required for confirming the crystal.

Keywords: tuberculosis, two component system, histidine kinase, needle-like crystals

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24907 Prediction of Marine Ecosystem Changes Based on the Integrated Analysis of Multivariate Data Sets

Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

Abstract:

The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

Procedia PDF Downloads 118
24906 Optical Fiber Data Throughput in a Quantum Communication System

Authors: Arash Kosari, Ali Araghi

Abstract:

A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

Procedia PDF Downloads 287