Search results for: multivariate time series data

Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

Procedia PDF Downloads 393

Authors: Thomas Suarez, Anne-Sophie Grenouilleau, Erwan Autin, Alexandre Biosse-Duplan, Emmanuelle Blondet, Laurence Chazalette, Marie Coniel, Agnes Dessaigne, Sylvie Lascols, Andrea Lasserre, Candice Legris, Pierre Liot, Aline Metais, Karine Petitprez, Christophe Varlet, Christian Saout

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Background: The role of biological sex and gender identity -whether assigned or chosen- as health determinants are far from a recent discovery: several reports have stressed out how being a woman or a man could affect health on various scales. However, taking it into consideration beyond stereotypes and rigid binary assumptions still seems to be a work in progress. Method: The report is a synthesis on a variety of specific topics, each of which was studied by a specialist from the French National Authority for Health (HAS), through an analysis of existing literature on both healthcare policy construction process and instruments (norms, data analysis, clinical trials, guidelines, and professional practices). This work also implied a policy analysis of French recent public health laws and a retrospective study of guidelines with a gender mainstreaming approach. Results: The analysis showed that though sex and gender were well-known determinants of health, their consideration by both public policy and health operators was often incomplete, as it does not incorporate how sex and gender interact, as well as how they interact with other factors. As a result, the health and social care systems and their professionals tend to reproduce some stereotypical and inadequate habits. Though the data available often allows to take sex and gender into consideration, such data is often underused in practice guidelines and policy formulation. Another consequence is a lack of inclusiveness towards transgender or intersex persons. Conclusions: This report first urges for raising awareness of all the actors of health, in its broadest definition, that sex and gender matter beyond first-look conclusions. It makes a series of recommendations in order to reshape policy construction in the health sector on the one hand and to design public health instruments to make them more inclusive regarding sex and gender on the other hand. The HAS finally committed to integrate sex and gender preoccupations in its workings methods, to be a driving force in the spread of these concerns.

Keywords: biological sex, determinants of health, gender, healthcare policy instruments, social accompaniment

Procedia PDF Downloads 110

Authors: Preeti Aghalayam, Jay Shah

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Underground coal gasification (UCG) is the in-situ gasification of unmineable coals to produce syngas. In UCG, gasifying agents are injected into the coal seam, and a reactive cavity is formed due to coal consumption. The cavity formed is typically hemispherical, and this report consists of the MATLAB model of the UCG cavity to predict the composition of the output gases. There are seven radial and two time-variant ODEs. A MATLAB solver (ode15s) is used to solve the radial ODEs from the above equations. Two for-loops are implemented in the model, i.e., one for time variations and another for radial variation. In the time loop, the radial odes are solved using the MATLAB solver. The radial loop is nested inside the time loop, and the density odes are numerically solved using the Euler method. The model is validated by comparing it with the literature results of laboratory-scale experiments. The model predicts the radial and time variation of the product gases inside the cavity.

Keywords: gasification agent, MATLAB model, syngas, underground coal gasification (UCG)

Procedia PDF Downloads 182

Authors: Mohammad Javad Esmaeili

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Background: Coagulopathy is one of the complications with end stage renal disease with high prevalence in the world. Thromboelastogram is adynamic test for evaluation of coagulopathy and we have compared our patient's coagulation profiles with the results of TEG. Material and methods: In this study 50 patients with ESRD who were on regular hemodialysis for at least 6 months was selected with simple sampling and their coagulation profile was done with blood sampling and also TEG was done for every patient. Data were analyzed with SPSS and P<0.05 consider significant. Results: Protein s, Protein c and Antithrombin III deficiency was detected in 32%, 16% and 20% of patients and activated protein c resistance was abnormal in 2% of patients. In TEG, R time in 49% and K in 22/5% of patients was lower than normal and a-angle in 26% and maximum amplitude in 36% of patients was upper than normal (Hypercoagulable state). PS with R and ATIII with K have correlation. Conclusion: R time and K in TEG can be a suitable screening test in patients with suspicious to PS and ATIII deficiency.

Keywords: thromboelastography, chronic kidney disease, Coagulating disorder, hemodialysis

Procedia PDF Downloads 57

Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

Procedia PDF Downloads 215

Authors: Metkel Gebremedhin, Biruk Kebede, Guash Abay

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Job satisfaction largely determines the productivity and efficiency of human resources for health. There is scanty evidence on factors influencing the job satisfaction of health extension professionals (HEPs) in Addis Ababa. The objective of this study was to determine the level of and factors influencing job satisfaction among extension health workers in Addis Ababa city. This was a cross-sectional study conducted in Addis Ababa, Ethiopia. Among all public health centers found in the Addis Ababa city administration health bureau that would be included in the study, a multistage sampling technique was employed. Then we selected the study health centers randomly and urban health extension professionals from the selected health centers. In-depth interview data collection methods were carried out for a comprehensive understanding of factors affecting job satisfaction among Health extension professionals (HEPs) in Addis Ababa. HEPs working in Addis Ababa areas are the primary study population. Multivariate logistic regression with 95% CI at P ≤ 0.05 was used to assess associated factors to job satisfaction. The overall satisfaction rate was 10.7% only, while 89.3%% were dissatisfied with their jobs. The findings revealed that variables such as marital status, staff relations, community support, supervision, and rewards have a significant influence on the level of job satisfaction. For those who were not satisfied, the working environment, job description, low salary, poor leadership and training opportunities were the major causes. Other factors influencing the level of satisfaction were lack of medical equipment, lack of transport facilities, lack of training opportunities, and poor support from woreda experts. Our study documented a very low level of overall satisfaction among health extension professionals in Addis Ababa city public health centers. Considering the factors responsible for this state of affairs, urgent and concrete strategies must be developed to address the concerns of extension health professionals as they represent a sensitive domain of the health system of Addis Ababa city. Improving the overall work environment, review of job descriptions and better salaries might bring about a positive change.

Keywords: job satisfaction, extension health professionals, Addis Ababa

Procedia PDF Downloads 57

Authors: Luís Miguel Cabeça Marques, Alberto Manuel Martinho Vale, José Pedro Miragaia Trancoso Vaz, Ana Sofia Baptista Fernandes, Rui Alexandre de Barros Coito, Tiago Miguel Prates da Costa

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The detection and localization of hidden radioactive sources are of significant importance in countering the illicit traffic of Special Nuclear Materials and other radioactive sources and materials. Radiation portal monitors are commonly used at airports, seaports, and international land borders for inspecting cargo and vehicles. However, these equipment can be expensive and are not available at all checkpoints. Consequently, the localization of SNM and other radioactive sources often relies on handheld equipment, which can be time-consuming. The current study presents the advantages of real-time analysis of gamma-ray count rate data from a mobile radiation detection system based on simulated data and field tests. The incorporation of profit functions and decision criteria to optimize the detection system's path significantly enhances the radiation field information and reduces survey time during cargo inspection. For source position estimation, a maximum likelihood estimation algorithm is employed, and confidence intervals are derived using the Fisher information. The study also explores the impact of uncertainties, baselines, and thresholds on the performance of the profit function. The proposed detection system, utilizing a plastic scintillator with silicon photomultiplier sensors, boasts several benefits, including cost-effectiveness, high geometric efficiency, compactness, and lightweight design. This versatility allows for seamless integration into any mobile platform, be it air, land, maritime, or hybrid, and it can also serve as a handheld device. Furthermore, integration of the detection system into drones, particularly multirotors, and its affordability enable the automation of source search and substantial reduction in survey time, particularly when deploying a fleet of drones. While the primary focus is on inspecting maritime container cargo, the methodologies explored in this research can be applied to the inspection of other infrastructures, such as nuclear facilities or vehicles.

Keywords: plastic scintillators, profit functions, path planning, gamma-ray detection, source localization, mobile radiation detection system, security scenario

Procedia PDF Downloads 87

Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

Procedia PDF Downloads 61

Authors: Sinchai Poolklai

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The purpose of this research paper was aimed to examine the level of satisfaction of the faculty members who participated in the ASEAN camp, Chantaburi, Thailand. The population of this study included all the faculty members of Suan Sunandha Rajabhat University who participated in the training and activities of the ASEAN camp during March, 2014. Among a total of 200 faculty members who answered the questionnaire, the data was complied by using SPSS program. Percentage, mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of satisfaction was 4.37, and standard deviation was 0.7810. Moreover, the mean average can be used to rank the level of satisfaction from each of the following factors: lower cost, less time consuming, faster delivery, more effective learning, and lower environment impact.

Keywords: ASEAN camp, e-learning, satisfaction, application

Procedia PDF Downloads 368

Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

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The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

Procedia PDF Downloads 322

Authors: Maressa Aires de Proenca

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The inclusion of a gender perspective in peace operations is based on a series of conventions, treaties, and resolutions designed to protect and include women addressing gender mainstreaming. The UN Security Council recognizes that women's participation and gender equality within peace operations are indispensable for achieving sustainable development and peace. However, the participation of women in the field of peace and security is still embryonic. There are gaps when we think about female participation in conflict resolution and peace promotion spaces, and it does not seem clear how women are present in these spaces. This absence may correspond to silence about representation and the guarantee of the female perspective within the context of peace promotion. Thus, the present research aimed to describe the panorama of the participation of women who are currently active in the 14 active UN peace operations, which are: 1) MINUJUSTH, Haiti, 2) MINURSO, Western Sahara, 3) MINUSCA, Central African Republic, 4) MINUSMA, Mali, 5) MONUSCO, the Democratic Republic of the Congo, 6) UNAMID, Darfur, 7) UNDOF, Golan, 8) UNFICYP, Cyprus, 9) UNIFIL, Lebanon, 10) UNISFA, Abyei, 11) UNMIK, Kosovo, 12) UNMISS, South Sudan, 13) UNMOGIP, India, and Pakistan, and 14) UNTSO, Middle East. A database was constructed that reported: (1) position held by the woman in the peace operation, (2) her profession, (3) educational level, (4) marital status, (5) religion, (6) nationality, (8) number of years working with peace operations, (9) whether the operation in which it operates has provided training on gender issues. For the construction of this database, official reports and statistics accessed through the UN Peacekeeping Resource Hub were used; The United Nations Statistical Commission, Peacekeeping Master Open Datasets, The Armed Conflict Database (ACD), The International Institute for Strategic Studies (IISS) database; Armed Conflict Location & Event Data Project (ACLED) database; from the Evidence and Data for Gender Equality (EDGE) database. In addition to access to databases, peacekeeping operations will be contacted directly, and data requested individually. The database showed that the presence of women in these peace operations is still incipient, but growing. There are few women in command positions, and most of them occupy administrative or human-care positions.

Keywords: women, peace and security, peacekeeping operations, peace studies

Procedia PDF Downloads 123

Authors: E. Maistrou, P. Themelis, D. Kosmopoulos, K. Boulougoura, A. M. Konidi, K. Moretti

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InterArch is an ongoing research project that is running since September 2020 and aims to propose a digital application for the enhancement of the cultural landscape, which emphasizes the contribution of physical space and time in digital data organization. The research case study refers to Ancient Messene in the Peloponnese, one of the most important archaeological sites in Greece. The project integrates an interactive approach to the natural environment, aiming at a manifold sensory experience. It combines the physical space of the archaeological site with the digital space of archaeological and cultural data while, at the same time, it embraces storytelling processes by engaging an interdisciplinary approach that familiarizes the user to multiple semantic interpretations. The research project is co‐financed by the European Union and Greek national funds, through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH - CREATE – INNOVATE (project code: Τ2ΕΔΚ-01659). It involves mutual collaboration between academic and cultural institutions and the contribution of an IT applications development company. New technologies and the integration of digital data enable the implementation of non‐linear narratives related to the representational characteristics of the art of collage. Various images (photographs, drawings, etc.) and sounds (narrations, music, soundscapes, audio signs, etc.) could be presented according to our proposal through new semiotics of augmented and virtual reality technologies applied in touch screens and smartphones. Despite the fragmentation of tangible or intangible references, material landscape formations, including archaeological remains, constitute the common ground that can inspire cultural narratives in a process that unfolds personal perceptions and collective imaginaries. It is in this context that cultural landscape may be considered an indication of space and historical continuity. It is in this context that history could emerge, according to our proposal, not solely as a previous inscription but also as an actual happening. As a rhythm of occurrences suggesting mnemonic references and, moreover, evolving history projected on the contemporary ongoing cultural landscape.

Keywords: cultural heritage, digital data, landscape, archaeological sites, visitors’ itineraries

Procedia PDF Downloads 63

Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 253

Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple Kinect sensor

Procedia PDF Downloads 348

Authors: M. Wigwe, J. G Akpa, E. N Wami

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Mathematical models of the absorber of a glycol dehydration facility was developed using the principles of conservation of mass and energy. Models which predict variation of the water content of gas in mole fraction, variation of gas and liquid temperatures across the parking height were developed. These models contain contributions from bulk and diffusion flows. The effect of diffusion on the process occurring in the absorber was studied in this work. The models were validated using the initial conditions in the plant data from Company W TEG unit in Nigeria. The results obtained showed that the effect of diffusion was noticed between z=0 and z=0.004 m. A deviation from plant data of 0% was observed for the gas water content at a residence time of 20 seconds, at z=0.004 m. Similarly, deviations of 1.584% and 2.844% were observed for the gas and TEG temperatures.

Keywords: separations, absorption, simulation, dehydration, water content, triethylene glycol

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Authors: Masaki Sakai, Tsuyoshi Nakajima, Kazuya Takahashi

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In order to improve the productivity of a factory, it is often the case to create an inference model by collecting and analyzing operational data off-line and then to develop an edge application (EAP) that evaluates the quality of the products or diagnoses machine faults in real-time. To accelerate this development cycle, an edge application framework for the smart factory is proposed, which enables to create and modify EAPs based on prepared inference models. In the framework, the preprocessing component is the key part to make it work. This paper proposes a language for preprocessing of edge applications, called LaPEA, which can flexibly process several sensor data from machines into explanatory variables for an inference model, and proves that it meets the requirements for the preprocessing.

Keywords: edge application framework, edgecross, preprocessing language, smart factory

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

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Authors: Ardalan Sabamehr, Ashutosh Bagchi

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Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods.

Keywords: ambient vibration, frequency domain decomposition, stochastic subspace identification, continuous wavelet transform

Procedia PDF Downloads 274

Authors: Farhana Karim, Abdullah N. S. Khan, Mohiuddin A. K. Chowdhury, Nabila Zaka, Alexander Manu, Shams El Arifeen, Sk Masum Billah

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Breastfeeding, an integral part of newborn care, can reduce 55-87% of all-cause neonatal mortality and morbidity. Early initiation of breastfeeding within 1 hour of birth can avert 22% of newborn mortality. Only 45% of world’s newborns and 42% of newborns in South-Asia are put to the breast within one hour of birth. In Bangladesh, only a half of the mothers practice early initiation of breastfeeding which is less likely to be practiced if the baby is born in a health facility. This study aims to generate strong evidence for early initiation of breastfeeding practices in the government health facilities and to explore the associated factors influencing the practice. The study was conducted in selected health facilities in three neighbouring districts of Northern Bangladesh. Total 249 normal vaginal delivery cases were observed for 24 hours since the time of birth. The outcome variable was initiation of breastfeeding within 1 hour while the explanatory variables included type of health facility, privacy, presence of support person, stage of labour at admission, need for augmentation of labour, complications during delivery, need for episiotomy, spontaneous cry of the newborn, skin-to-skin contact with mother, post-natal contact with the service provider, receiving a post-natal examination and counselling on breastfeeding during postnatal contact. The simple descriptive statistics were employed to see the distribution of samples according to socio-demographic characteristics. Kruskal-Wallis test was carried out for testing the equality of medians among two or more categories of each variable and P-value is reported. A series of simple logistic regressions were conducted with all the potential explanatory variables to identify the determining factors for breastfeeding within 1 hour in a health facility. Finally, multiple logistic regression was conducted including the variables found significant at bi-variate analyses. Almost 90% participants initiated breastfeeding at the health facility and median time to initiate breastfeeding was 38 minutes. However, delivering in a sub-district hospital significantly delayed the breastfeeding initiation in comparison to delivering in a district hospital. Maintenance of adequate privacy and presence of separate staff for taking care of newborn significantly reduced the time in early breastfeeding initiation. Initiation time was found longer if the mother had an augmented labour, obstetric complications, and the newborn needed resuscitation. However, the initiation time was significantly early if the baby was put skin-to-skin on mother’s abdomen and received a postnatal examination by a provider. After controlling for the potential confounders, the odds of initiating breastfeeding within one hour of birth is higher if mother gives birth in a district hospital (AOR 3.0: 95% CI 1.5, 6.2), privacy is well-maintained (AOR 2.3: 95% CI 1.1, 4.5), babies cry spontaneously (AOR 7.7: 95% CI 3.3, 17.8), babies are put to skin-to-skin contact with mother (AOR 4.6: 95% CI 1.9, 11.2) and if the baby is examined by a provider in the facility (AOR 4.4: 95% CI 1.4, 14.2). The evidence generated by this study will hopefully direct the policymakers to identify and prioritize the scopes for creating and supporting early initiation of breastfeeding in the health facilities.

Keywords: Bangladesh, early initiation of breastfeeding, health facility, normal vaginal delivery, skin to skin contact

Procedia PDF Downloads 136

Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

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FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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Authors: Snehal L. Kadam, Shriniwas B. Kulkarni

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Flexible electrode material with high surface area and good electrochemical properties is the current trend captivating the researchers across globe for application in the next generation energy storage field. In the present work, crumpled sheet like reduced graphene oxide grown on carbon cloth by the hydrothermal method with a series of different deposition temperatures at fixed time. The influence of the deposition temperature on the structural, morphological, optical and supercapacitive properties of the electrode material was investigated by XRD, RAMAN, XPS, TEM, FE-SEM, UV-VISIBLE and electrochemical characterization techniques.The results show that the hydrothermally synthesized reduced graphene oxide on carbon cloth has sheet like mesoporous structure. The reduced graphene oxide material at 160°C exhibits the best supercapacitor performance, with a specific capacitance of 443 F/g at scan rate 5mV/sec. Moreover, stability studies show 97% capacitance retention over 1000 CV cycles. This result shows that hydrothermally synthesized RGO on carbon cloth is the potential electrode material and would be used in the next-generation wearable energy storage systems. The detailed analysis and results will be presented at the conference.

Keywords: graphene oxide, reduced graphene oxide, carbon cloth, deposition temperature, supercapacitor

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Authors: Carlos Alberto Rivera-corredor, Angie Dayana Vargas-Ceballos, Edison Gilpavas, Izabela Dobrosz-Gómez, Miguel Ángel Gómez-García

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Hexavalent chromium, Cr (VI) is present in the effluents from different industries such as electroplating, mining, leather tanning, etc. This compound is of great academic and industrial concern because of its toxic and carcinogenic behavior. Its dumping to both environmental and public health for animals and humans causes serious problems in water sources. The amount of Cr (VI) in industrial wastewaters ranges from 0.5 to 270,000 mgL-1. According to the Colombian standard for water quality (NTC-813-2010), the maximum allowed concentration for the Cr (VI) in drinking water is 0.05 mg L-1. To comply with this limit, it is essential that industries treat their effluent to reduce the Cr (VI) to acceptable levels. Numerous methods have been reported for the treatment removing metal ions from aqueous solutions such as: reduction, ion exchange, electrodialysis, etc. Adsorption has become a promising method for the purification of metal ions in water, since its application corresponds with an economic and efficient technology. The absorbent selection and the kinetic and thermodynamic study of the adsorption conditions are key to the development of a suitable adsorption technology. The Ce0.25Zr0.75O2.nH2O presents higher adsorption capacity between a series of hydrated mixed oxides Ce1-xZrxO2 (x = 0, 0.25, 0.5, 0.75, 1). This work presents the kinetic and thermodynamic study of Cr (VI) adsorption on Ce0.25Zr0.75O2.nH2O. Experiments were performed under the following experimental conditions: initial Cr (VI) concentration = 25, 50 and 100 mgL-1, pH = 2, adsorbent charge = 4 gL-1, stirring time = 60 min, temperature=20, 28 and 40 °C. The Cr (VI) concentration was spectrophotometrically estimated by the method of difenilcarbazide with monitoring the absorbance at 540 nm. The Cr (VI) adsorption over hydrated Ce0.25Zr0.75O2.nH2O models was analyzed using pseudo-first and pseudo-second order kinetics. The Langmuir and Freundlich models were used to model the experimental data. The convergence between the experimental values and those predicted by the model, is expressed as a linear regression correlation coefficient (R2) and was employed as the model selection criterion. The adsorption process followed the pseudo-second order kinetic model and obeyed the Langmuir isotherm model. The thermodynamic parameters were calculated as: ΔH°=9.04 kJmol-1,ΔS°=0.03 kJmol-1 K-1, ΔG°=-0.35 kJmol-1 and indicated the endothermic and spontaneous nature of the adsorption process, governed by physisorption interactions.

Keywords: adsorption, hexavalent chromium, kinetics, thermodynamics

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Authors: Nguyen Huy Hoang, Do Thanh Quan, Tran Vu Kien

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The use of the active radar to measure the coordinates of ultra-light drones is frequently difficult due to long-distance, absolutely small radar cross-section (RCS) and obstacles. Since ultra-light drones are usually controlled by the Time Difference of Arrival (RF), the paper proposed a method to measure the coordinates of ultra-light drones in the space based on the arrival time of the signal at receiving antennas and the time difference of arrival (TDOA). The experimental results demonstrate that the proposed method is really potential and highly accurate.

Keywords: ultra-light drone, TDOA, radar cross-section (RCS), RF

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Authors: Romi Dey

Abstract:

Introduction: One of the most important criteria for technology to sustain and grow is through it’s elaborate and intuitive design methodology and design thinking. Designing for enterprise applications that cater to Just in Time Technology is one of the most challenging and detailed processes any User Experience Designer would come across. Description: The basic principles of Design, when applied to tailor to these technologies, creates an immense challenge and that’s how a set of redefined and revised design principles that can be applied to designing any Just In Time manufacturing solution. Findings: The thorough process of understanding the end user, their existing pain points which they’ve faced in the real world, their responsibilities and expectations, the core needs and last but not the least the demands, creates havoc nurturing of the design methodologies for the Just in Time solutions. With respect to the business aspect, design and design principles play a strong role in any form of innovation. Conclusion: Innovation and knowledge about the latest technologies are the keywords in the manufacturing industry. It becomes crucial for the product development team to be precise in their understanding of the technology and being sure of end users expectation.

Keywords: design thinking, enterprise application, Just in Time, user experience design

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Authors: Mehdi Montakhabrazlighi, Ercan Balikci

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The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

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Authors: M. Berrehail, F. Benamira

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We study the quantum motion of a particle in the presence of a time- dependent linear potential using an operator invariant that is quadratic in p and linear in q within the framework of the Lewis-Riesenfeld invariant, The special invariant operator proposed in this work is demonstrated to be an Hermitian operator which has an Airy wave packet as its Eigenfunction

Keywords: airy wave packet, ivariant, time-dependent linear potential, unitary transformation

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Authors: Rhodine Hickman, Craig Wylie, Michael G. McCaul

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Introduction: The World Health Organisation has called on governments around the world to recognise emergency conditions as a global public health problem and respond with appropriate steps for effective preventative strategies. However, to understand the magnitude of the problem, good quality epidemiological data is required. This is especially challenging in low and middle-income countries, where routine data is scarce, specifically within the prehospital setting. Methods: We conducted a retrospective cross-sectional study of a national prehospital private sector EMS database. The database being the property of ER24 (private Emergency Medical Services (EMS) company in South Africa) contains claims submitted by the majority of ambulance services in South Africa during the period between 1 January 2008 to 28 March 2017. We used descriptive statistics and control charts to describe the data using STATA 14. Results: 299,257 calls were included in the analysis. The top clinical conditions requiring ambulance transport were transport accidents (10% of total call volume) and ischaemic heart disease (4.4%). The number of transport accidents consistently increased between 2009 and 2014 and reached beyond the limit for normal variation in 2015. Victims of transport accidents required basic life support services 60% of the time with 80% of injuries being minor to moderate. The frequency of ischaemic heart disease had a steady incline from 2011 to 2016. Advanced life support services were required about 50% of the time, with 60% of patients needing urgent care. Conclusion: Transport accidents, followed by ischaemic heart disease, are the most prevalent conditions in South African private EMS. There is a potential to address these conditions by developing the capacity of low and mid-level providers in trauma and advanced EMS providers in ischaemic heart disease.

Keywords: emergency care, emergency medicine, prehospital providers, South Africa

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Authors: Maram Saleh

Abstract:

Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

Procedia PDF Downloads 187