Search results for: multimodal data
20619 Interpretable Deep Learning Models for Medical Condition Identification
Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji
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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.Keywords: deep learning, interpretability, attention, big data, medical conditions
Procedia PDF Downloads 9120618 Remote Sensing and GIS Integration for Paddy Production Estimation in Bali Province, Indonesia
Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan
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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.Keywords: production estimation, paddy, remote sensing, geography information system, land suitability
Procedia PDF Downloads 34220617 Analysis of Reliability of Mining Shovel Using Weibull Model
Authors: Anurag Savarnya
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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.Keywords: reliability, Weibull model, electric mining shovel
Procedia PDF Downloads 51420616 Conservation Importance of Independent Smallholdings in Safeguarding Biodiversity in Oil Palm Plantations
Authors: Arzyana Sunkar, Yanto Santosa
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The expansions of independent smallholdings in Indonesia are feared to increase the negative ecological impacts of oil palm plantation on biodiversity. Hence, research is required to identify the conservation importance of independent smallholder oil palm plantations on biodiversity. This paper discussed the role of independent smallholdings in the conservation of biodiversity in oil palm plantations and to compare it with High Conservation Value Forest as a conservation standard of RSPO. The research was conducted from March to April 2016. Data on biodiversity were collected on 16 plantations and 8 private oil palm plantations in the Districts of Kampar, Pelalawan, Kuantan, Singingi and Siak of Riau Province, Indonesia. In addition, data on community environmental perceptions of both smallholder plantation and High Conservation Value (HCV) Forest were also collected. Species that were observed were birds and earthworms. Data on birds were collected using transect method, while identification of earthworm was determine by taking some soil samples and counting the number of individual earthworm found for each worm species. The research used direct interview with oil palm owners and community members, as well as direct observation to examine the environmental conditions of each plantation. In general, field observation and measurement have found that birds species richness was higher in the forested HCV Forest. Nevertheless, if compared to non-forested HCV, bird’s species richness was higher in the independent smallholdings. On the other hand, different results were observed for earthworm, where the density was higher in the independent smallholdings than in the HCV. It can be concluded from this research that managing independent smallholder oil palm plantations and forested HCV forest could enhance biodiversity conservation. The results of this study justified the importance of retaining forested area to safeguard biodiversity in oil palm plantation.Keywords: biodiversity conservation, high conservation value forest, independent smallholdings, oil palm plantations
Procedia PDF Downloads 22320615 The Comparison of Depression Level of Male Athlete Students with Non-Athlete Students
Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi
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The present study was done with the purpose of considering mental health and general purpose of describing and comparing depression level of athlete and non-athlete male students educational year of 2012 Research method in this study in proportion to the selective title, descriptive method is causative – comparative. Research samples were selected randomly from B.A students of different fields including 500 students. Average mean of research samples was between 20 to 25 years. Data collection tool is questionnaire of depression measurement of Aroun Beck (B.D.I) that analyzes and measures 21 aspects of depression in 6 ranges. Operation related to analysis of statistical data to extraction of results was done by SPSS software. To extraction of research obtained by comparison of depression level mean, show that the hypothesis of the research (H_1) based on the existence of the significance scientific difference was supported and showed that there’s a significance difference between depression level of athlete male students in comparison with depression level of non-athlete male students. Thus, depression level of athlete male students was lower in comparison with depression level of non-athlete male students.Keywords: depression, athlete students, non-athlete students
Procedia PDF Downloads 47920614 Software-Defined Networking: A New Approach to Fifth Generation Networks: Security Issues and Challenges Ahead
Authors: Behrooz Daneshmand
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Software Defined Networking (SDN) is designed to meet the future needs of 5G mobile networks. The SDN architecture offers a new solution that involves separating the control plane from the data plane, which is usually paired together. Network functions traditionally performed on specific hardware can now be abstracted and virtualized on any device, and a centralized software-based administration approach is based on a central controller, facilitating the development of modern applications and services. These plan standards clear the way for a more adaptable, speedier, and more energetic network beneath computer program control compared with a conventional network. We accept SDN gives modern inquire about openings to security, and it can significantly affect network security research in numerous diverse ways. Subsequently, the SDN architecture engages systems to effectively screen activity and analyze threats to facilitate security approach modification and security benefit insertion. The segregation of the data planes and control and, be that as it may, opens security challenges, such as man-in-the-middle attacks (MIMA), denial of service (DoS) attacks, and immersion attacks. In this paper, we analyze security threats to each layer of SDN - application layer - southbound interfaces/northbound interfaces - controller layer and data layer. From a security point of see, the components that make up the SDN architecture have a few vulnerabilities, which may be abused by aggressors to perform noxious activities and hence influence the network and its administrations. Software-defined network assaults are shockingly a reality these days. In a nutshell, this paper highlights architectural weaknesses and develops attack vectors at each layer, which leads to conclusions about further progress in identifying the consequences of attacks and proposing mitigation strategies.Keywords: software-defined networking, security, SDN, 5G/IMT-2020
Procedia PDF Downloads 9920613 Steady State Modeling and Simulation of an Industrial Steam Boiler
Authors: Amina Lyria Deghal Cheridi, Abla Chaker, Ahcene Loubar
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Relap5 system code is one among powerful tools, which is used in the area of design and safety evaluation. This work aims to simulate the behavior of a radiant steam boiler at the steady-state conditions using Relap5 code system. To perform this study, a detailed Relap5 model is built including all the parts of the steam boiler. The control and regulation systems are also considered. To reproduce the most important parameters and phenomena with an acceptable accuracy and fidelity, a strong qualification work is undertaken concerning the facility nodalization. It consists of making a comparison between the code results and the plant available data in steady-state operation mode. Therefore, the model qualification results at the steady-state are in good agreement with the steam boiler experimental data. The steam boiler Relap5 model has proved satisfactory; and the model was capable of predicting the main thermal-hydraulic steady-state conditions of the steam boiler.Keywords: industrial steam boiler, model qualification, natural circulation, relap5/mod3.2, steady state simulation
Procedia PDF Downloads 27220612 Water Demand Modelling Using Artificial Neural Network in Ramallah
Authors: F. Massri, M. Shkarneh, B. Almassri
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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.Keywords: water management, demand forecasting, consumption, ANN, Ramallah
Procedia PDF Downloads 21920611 The Impact of Interrelationship between Business Intelligence and Knowledge Management on Decision Making Process: An Empirical Investigation of Banking Sector in Jordan
Authors: Issa M. Shehabat, Huda F. Y. Nimri
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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector
Procedia PDF Downloads 14420610 Distributed Leadership and Emergency Response: A Study on Seafarers
Authors: Delna Shroff
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Merchant shipping is an occupation with a high rate of fatal injuries caused by organizational accidents and maritime disasters. In most accident investigations, the leader’s actions are under scrutiny and point out the necessity to investigate the leader’s decisions in critical conditions. While several leadership studies have been carried out in the past, there is a tendency for most research to focus on holders of formal positions. The unit of analysis in most studies has been the ‘individual.’ A need is, therefore, felt to adopt a practice-based perspective of leadership, understand how leadership emerges to affect maritime safety. This paper explores the phenomenon of distributed leadership among seafarers more holistically. It further examines the role of one form of distributed leadership, that is, planfully aligned leadership in the emergency response of the team. A mixed design will be applied. In the first phase, the data gathered by way of semi-structured interviews will be used to explore the seafarer’s implicit understanding of leadership. The data will be used to develop a conceptual framework of distributed leadership, specific to the maritime context. This framework will be used to develop a simulation. Experimental design will be used to examine the relationship between planfully aligned leadership and emergency response of the team members during navigation. Findings show that planfully aligned leadership significantly and positively predicts the emergency response of team members. Planfully aligned leadership leads to a better emergency response of the team members as compared to authoritarian leadership. In the third qualitative phase, additional data will be gathered through semi-structured interviews to further validate the findings to gain a more complete understanding of distributed leadership and its relation to emergency response. Above are the predictive results; the study expects to be a cornerstone of safety leadership research and has important implications for leadership development and training within the maritime industry.Keywords: authoritarian leadership, distributed leadership, emergency response , planfully aligned leadership
Procedia PDF Downloads 17520609 Ship Detection Requirements Analysis for Different Sea States: Validation on Real SAR Data
Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores
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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.Keywords: SAR, generalized gamma distribution, detection curves, radar detection
Procedia PDF Downloads 45220608 A New Reliability based Channel Allocation Model in Mobile Networks
Authors: Anujendra, Parag Kumar Guha Thakurta
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The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. Thus, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non-dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.Keywords: base station, channel, GA, pareto-optimal, reliability
Procedia PDF Downloads 40820607 Working Fluids in Absorption Chillers: Investigation of the Use of Deep Eutectic Solvents
Authors: L. Cesari, D. Alonso, F. Mutelet
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The interest in cold production has been on the increase in absorption chillers for many years. In fact, the absorption cycles replace the compressor and thus reduce electrical consumption. The devices also allow waste heat generated through industrial activities to be recovered and cooled to a moderate temperature in accordance with regulatory guidelines. Many working fluids were investigated but could not compete with the commonly used {H2O + LiBr} and {H2O + NH3} to author’s best knowledge. Yet, the corrosion, toxicity and crystallization phenomena of these mixtures prevent the development of the absorption technology. This work investigates the possible use of a glyceline deep eutectic solvent (DES) and CO2 as working fluid in an absorption chiller. To do so, good knowledge of the mixtures is required. Experimental measurements (vapor-liquid equilibria, density, and heat capacity) were performed to complete the data lacking in the literature. The performance of the mixtures was quantified by the calculation of the coefficient of performance (COP). The results show that working fluids containing DES + CO2 are an interesting alternative and lead to different trails of working mixtures for absorption and chiller.Keywords: absorption devices, deep eutectic solvent, energy valorization, experimental data, simulation
Procedia PDF Downloads 11020606 Investigation on the Changes in the Chemical Composition and Ecological State of Soils Contaminated with Heavy Metals
Authors: Metodi Mladenov
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Heavy metals contamination of soils is a big problem mainly as a result of industrial production. From this point of view, this is of interests the processes for decontamination of soils for crop of production with low content of heavy metals and suitable for consumption from the animals and the peoples. In the current article, there are presented data for established changes in chemical composition and ecological state on soils contaminated from non-ferrous metallurgy manufacturing, for seven years time period. There was done investigation on alteration of pH, conductivity and contain of the next elements: As, Cd, Cu, Cr, Ni, Pb, Zn, Co, Mn and Al. Also, there was done visual observations under the processes of recovery of root-inhabitable soil layer and reforestation. Obtained data show friendly changes for the investigated indicators pH and conductivity and decreasing of content of some form analyzed elements. Visual observations show augmentation of plant cover areas and change in species structure with increase of number of shrubby and wood specimens.Keywords: conductivity, contamination of soils, chemical composition, inductively coupled plasma–optical emission spectrometry, heavy metals, visual observation
Procedia PDF Downloads 18020605 Microbubbles Enhanced Synthetic Phorbol Ester Degradation by Ozonolysis
Authors: D. Kuvshinov, A. Siswanto, W. Zimmerman
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A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil can also be used as a food stock due to its significant nutrition content. The limitations for utilizing the oil as a food stock are mainly due to a toxicity of PE. Nowadays a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence. Ozone is considered as a strong oxidative agent. It reaction with PE it attacks the carbon double bond of PE. This modification of PE molecular structure results into nontoxic ester with high lipid content. This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is a simultaneous application of new microscale plasma unit for ozone production and patented gas oscillation technology. In combination with a reactor design the technology permits ozone injection to the water-TPA mixture in form of microbubbles. The efficacy of a heterogeneous process depends on diffusion coefficient which can be controlled by contact time and interface area. The low velocity of rising microbubbles and high surface to volume ratio allow fast mass transfer to be achieved during the process. Direct injection of ozone is the most efficient process for a highly reactive and short lived chemical. Data on the plasma unit behavior are presented and influence of the gas oscillation technology to the microbubbles production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.Keywords: microbubble, ozonolysis, synthetic phorbol ester, chemical engineering
Procedia PDF Downloads 21720604 Modelling Fluidization by Data-Based Recurrence Computational Fluid Dynamics
Authors: Varun Dongre, Stefan Pirker, Stefan Heinrich
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Over the last decades, the numerical modelling of fluidized bed processes has become feasible even for industrial processes. Commonly, continuous two-fluid models are applied to describe large-scale fluidization. In order to allow for coarse grids novel two-fluid models account for unresolved sub-grid heterogeneities. However, computational efforts remain high – in the order of several hours of compute-time for a few seconds of real-time – thus preventing the representation of long-term phenomena such as heating or particle conversion processes. In order to overcome this limitation, data-based recurrence computational fluid dynamics (rCFD) has been put forward in recent years. rCFD can be regarded as a data-based method that relies on the numerical predictions of a conventional short-term simulation. This data is stored in a database and then used by rCFD to efficiently time-extrapolate the flow behavior in high spatial resolution. This study will compare the numerical predictions of rCFD simulations with those of corresponding full CFD reference simulations for lab-scale and pilot-scale fluidized beds. In assessing the predictive capabilities of rCFD simulations, we focus on solid mixing and secondary gas holdup. We observed that predictions made by rCFD simulations are highly sensitive to numerical parameters such as diffusivity associated with face swaps. We achieved a computational speed-up of four orders of magnitude (10,000 time faster than classical TFM simulation) eventually allowing for real-time simulations of fluidized beds. In the next step, we apply the checkerboarding technique by introducing gas tracers subjected to convection and diffusion. We then analyze the concentration profiles by observing mixing, transport of gas tracers, insights about the convective and diffusive pattern of the gas tracers, and further towards heat and mass transfer methods. Finally, we run rCFD simulations and calibrate them with numerical and physical parameters compared with convectional Two-fluid model (full CFD) simulation. As a result, this study gives a clear indication of the applicability, predictive capabilities, and existing limitations of rCFD in the realm of fluidization modelling.Keywords: multiphase flow, recurrence CFD, two-fluid model, industrial processes
Procedia PDF Downloads 7520603 Digital Structural Monitoring Tools @ADaPT for Cracks Initiation and Growth due to Mechanical Damage Mechanism
Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman
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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model
Procedia PDF Downloads 7620602 A Study on the Different Components of a Typical Back-Scattered Chipless RFID Tag Reflection
Authors: Fatemeh Babaeian, Nemai Chandra Karmakar
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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS
Procedia PDF Downloads 20020601 Students’ Assessment of Teachers’ Attitude in Universities in Ondo State, Nigeria
Authors: Omoniyi A. Olubunmi, Omoniyi Olayide M.
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This study was designed to assess the attitudes of Nigerian university teachers by their students in terms of teachers’ attitude to work, teaching and students. The study was a survey, and made use of the researcher’s designed questionnaire tagged Students’ Assessment Teachers Inventory (SATI), comprising 20 items, was used to collect data. The respondents were 300 students which were randomly selected from three universities in Ondo State. The SATI elicited information on different aspects of teachers’ attitude to work, teaching and students. The study was guided by two hypotheses. Data collected were analyzed using Pearson-r. The result showed that there was a significant relationship between teachers’ attitude to work (r = 0.343, p<0.01), teaching (r = 0.594, p<0.01) and students (r = 0.487, p<0.01). The study concluded that teachers’ attitudes to teaching profession in higher institutions in Ondo State were not favorable and this could be improved through capacity building for effective pedagogical skills, conducive environment, well equipped libraries and laboratories, and provision of incentives for university teachers.Keywords: capacity building, pedagogical skills, teachers’ attitude, students’ assessment
Procedia PDF Downloads 29220600 Smart Oxygen Deprivation Mask: An Improved Design with Biometric Feedback
Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li
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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth
Procedia PDF Downloads 21820599 Effect of Aging on the Second Law Efficiency, Exergy Destruction and Entropy Generation in the Skeletal Muscles during Exercise
Authors: Jale Çatak, Bayram Yılmaz, Mustafa Ozilgen
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The second law muscle work efficiency is obtained by multiplying the metabolic and mechanical work efficiencies. Thermodynamic analyses are carried out with 19 sets of arms and legs exercise data which were obtained from the healthy young people. These data are used to simulate the changes occurring during aging. The muscle work efficiency decreases with aging as a result of the reduction of the metabolic energy generation in the mitochondria. The reduction of the mitochondrial energy efficiency makes it difficult to carry out the maintenance of the muscle tissue, which in turn causes a decline of the muscle work efficiency. When the muscle attempts to produce more work, entropy generation and exergy destruction increase. Increasing exergy destruction may be regarded as the result of the deterioration of the muscles. When the exergetic efficiency is 0.42, exergy destruction becomes 1.49 folds of the work performance. This proportionality becomes 2.50 and 5.21 folds when the exergetic efficiency decreases to 0.30 and 0.17 respectively.Keywords: aging mitochondria, entropy generation, exergy destruction, muscle work performance, second law efficiency
Procedia PDF Downloads 42720598 Computational Fluid Dynamics Simulation and Comparison of Flow through Mechanical Heart Valve Using Newtonian and Non-Newtonian Fluid
Authors: D. Šedivý, S. Fialová
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The main purpose of this study is to show differences between the numerical solution of the flow through the artificial heart valve using Newtonian or non-Newtonian fluid. The simulation was carried out by a commercial computational fluid dynamics (CFD) package based on finite-volume method. An aortic bileaflet heart valve (Sorin Bicarbon) was used as a pattern for model of real heart valve replacement. Computed tomography (CT) was used to gain the accurate parameters of the valve. Data from CT were transferred in the commercial 3D designer, where the model for CFD was made. Carreau rheology model was applied as non-Newtonian fluid. Physiological data of cardiac cycle were used as boundary conditions. Outputs were taken the leaflets excursion from opening to closure and the fluid dynamics through the valve. This study also includes experimental measurement of pressure fields in ambience of valve for verification numerical outputs. Results put in evidence a favorable comparison between the computational solutions of flow through the mechanical heart valve using Newtonian and non-Newtonian fluid.Keywords: computational modeling, dynamic mesh, mechanical heart valve, non-Newtonian fluid
Procedia PDF Downloads 38620597 Integrated Marketing Communication to Influencing International Standard Energy Economy Car Buying Decision of Consumers in Bangkok
Authors: Pisit Potjanajaruwit
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The objective of this research was to study the influence of Integrated Marketing Communication on Buying Decision of Consumers in Bangkok. A total of 397 respondents were collected from customers who drive in Bangkok. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences. The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. In terms of occupation, the majority worked for private companies. The effect to the Buying Decision of Consumers in Bangkok to including sale promotion with the low interest and discount for an installment, selling by introducing and gave product information through sales persons, public relation by website, direct marketing by annual motor show and advertisement by television media.Keywords: Bangkok metropolis, ECO car, integrated marketing communication, international standard
Procedia PDF Downloads 31620596 Modeling Of The Random Impingement Erosion Due To The Impact Of The Solid Particles
Authors: Siamack A. Shirazi, Farzin Darihaki
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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid
Procedia PDF Downloads 16920595 The Influence of a Radio Intervention on Farmers’ Practices in Climate Change Mitigation and Adaptation in Kilifi, Kenya
Authors: Fiona Mwaniki
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Climate change is considered a serious threat to sustainable development globally and as one of the greatest ecological, economic and social challenges of our time. The global demand for food is projected to increase by 60% by 2050. Small holder farmers who are vulnerable to the adverse effects of climate change are expected to contribute to this projected demand. Effective climate change education and communication is therefore required for smallholder and subsistence farmers’ in order to build communities that are more climate change aware, prepared and resilient. In Kenya radio is the most important and dominant mass communication tool for agricultural extension. This study investigated the potential role of radio in influencing farmers’ understanding and use of climate change information. The broad aims of this study were three-fold. Firstly, to identify Kenyan farmers’ perceptions and responses to the impacts of climate change. Secondly, to develop radio programs that communicate climate change information to Kenyan farmers and thirdly, to evaluate the impact of information disseminated through radio on farmers’ understanding and responses to climate change mitigation and adaptation. This study was conducted within the farming community of Kilifi County, located along the Kenyan coast. Education and communication about climate change was undertaken using radio to make available information understandable to different social and cultural groups. A mixed methods pre-and post-intervention design that provided the opportunity for triangulating results from both quantitative and qualitative data was used. Quantitative and qualitative data was collected simultaneously, where quantitative data was collected through semi structured surveys with 421 farmers’ and qualitative data was derived from 11 focus group interviews, six interviews with key informants and nine climate change experts. The climate change knowledge gaps identified in the initial quantitative and qualitative data were used in developing radio programs. Final quantitative and qualitative data collection and analysis enabled an assessment of the impact of climate change messages aired through radio on the farming community in Kilifi County. Results of this study indicate that 32% of the farmers’ listened to the radio programs and 26% implemented technologies aired on the programs that would help them adapt to climate change. The most adopted technologies were planting drought tolerant crops including indigenous crop varieties, planting trees, water harvesting and use of manure. The proportion of farmers who indicated they knew “a fair amount” about climate change increased significantly (Z= -5.1977, p < 0.001) from 33% (at the pre intervention phase of this study) to 64% (post intervention). However, 68% of the farmers felt they needed “a lot more” information on agriculture interventions (43%), access to financial resources (21%) and the effects of climate change (15%). The challenges farmers’ faced when adopting the interventions included lack of access to financial resources (18%), high cost of adaptation measures (17%), and poor access to water (10%). This study concludes that radio effectively complements other agricultural extension methods and has the potential to engage farmers’ on climate change issues and motivate them to take action.Keywords: climate change, climate change intervention, farmers, radio
Procedia PDF Downloads 33820594 Decision-Tree-Based Foot Disorders Classification Using Demographic Variable
Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi
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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.Keywords: decision tree, demographic characteristics, foot disorders, machine learning
Procedia PDF Downloads 26220593 The Use of Respiratory Index of Severity in Children (RISC) for Predicting Clinical Outcomes for 3 Months-59 Months Old Patients Hospitalized with Community-Acquired Pneumonia in Visayas Community Medical Center, Cebu City from January 2013 - June 2
Authors: Karl Owen L. Suan, Juliet Marie S. Lambayan, Floramay P. Salo-Curato
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Objective: To predict the outcome among patients admitted with community-acquired pneumonia (ages 3 months to 59 months old) admitted in Visayas Community Medical Center using the Respiratory Index of Severity in Children (RISC). Design: A cross-sectional study design was used. Setting: The study was done in Visayas Community Medical Center, which is a private tertiary level in Cebu City from January-June 2013. Patients/Participants: A total of 72 patients were initially enrolled in the study. However, 1 patient transferred to another institution, thus 71 patients were included in this study. Within 24 hours from admission, patients were assigned a RISC score. Statistical Analysis: Cohen’s kappa coefficient was used for inter-rater agreement for categorical data. This study used frequency and percentage distribution for qualitative data. Mean, standard deviation and range were used for quantitative data. To determine the relationship of each RISC score parameter and the total RISC score with the outcome, a Mann Whitney U Test and 2x2 Fischer Exact test for testing associations were used. A p value less of than 0.05 alpha was considered significant. Results: There was a statistical significance between RISC score and clinical outcome. RISC score of greater than 4 was correlated with intubation and/or mortality. Conclusion: The RISC scoring system is a simple combination of clinical parameters and a reliable tool that will help stratify patients aged 3 months to 59 months in predicting clinical outcome.Keywords: RISC, clinical outcome, community-acquired pneumonia, patients
Procedia PDF Downloads 30220592 The Relationship between Marketing Mix Strategy and Valuable of Muay Thai Training and Thai Massage in Foreign Tourists' Perception
Authors: Thammamonr Khunrattanaporn
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The purpose of the research was to examine the relationship between the marketing mix factors and valuable of Muay Thai Training and Thai massage in foreign tourists’ perception. The research used the 8 P’s of marketing framework presented in the theory of compound marketing services strategy. Data was collect using survey for 400 questionnaires using the Quota sampling from foreign tourists travelling in Thailand. The data was analyzed to determine valuation statistics, the frequency, percent average, means and standard deviation and pearson's correlation coefficients. The result shows the foreign tourists’ perception with the marketing mix strategy in term of Muay Thai training and massage regarding curriculum areas: product, pricing, channel distribution, Promotion, Personnel services, Physical evidence and external partnerships the overall, it significant at a high level. The awareness level of service and value for travelers had two aspects of service quality and value for money it significant at the highest level.Keywords: foreign tourists’ perception, marketing mix strategy, Muay Thai training, the massage
Procedia PDF Downloads 26520591 Stock Prediction and Portfolio Optimization Thesis
Authors: Deniz Peksen
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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.Keywords: stock prediction, portfolio optimization, data science, machine learning
Procedia PDF Downloads 8020590 Reasons for Lack of an Ideal Disinfectant after Dental Treatments
Authors: Ilma Robo, Saimir Heta, Rialda Xhizdari, Kers Kapaj
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Background: The ideal disinfectant for surfaces, instruments, air, skin, both in dentistry and in the fields of medicine, does not exist.This is for the sole reason that all the characteristics of the ideal disinfectant cannot be contained in one; these are the characteristics that if one of them is emphasized, it will conflict with the other. A disinfectant must be stable, not be affected by changes in the environmental conditions where it stands, which means that it should not be affected by an increase in temperature or an increase in the humidity of the environment. Both of these elements contradict the other element of the idea of an ideal disinfectant, as they disrupt the solubility ratios of the base substance of the disinfectant versus the diluent. Material and methods: The study aims to extract the constant of each disinfectant/antiseptic used during dental disinfection protocols, accompanied by the side effects of the surface of the skin or mucosa where it is applied in the role of antiseptic. In the end, attempts were made to draw conclusions about the best possible combination for disinfectants after a dental procedure, based on the data extracted from the basic literature required during the development of the pharmacology module, as a module in the formation of a dentist, against data published in the literature. Results: The sensitivity of the disinfectant to changes in the atmospheric conditions of the environment where it is kept is a known fact. The care against this element is always accompanied by the advice on the application of the specific disinfectant, in order to have the desired clinical result. The constants of disinfectants according to the classification based on the data collected and presented are for alcohols 70-120, glycols 0.2, aldehydes 30-200, phenols 15-60, acids 100, povidone iodine halogens 5-75, hypochlorous acid halogens 150, sodium hypochlorite halogens 30-35, oxidants 18-60, metals 0.2-10. The part of halogens should be singled out, where specific results were obtained according to the representatives of this class, since it is these representatives that find scope for clinical application in dentistry. Conclusions: The search for the "ideal", in the conditions where its defining criteria are also established, not only for disinfectants but also for any medication or pharmaceutical product, is an ongoing search, without any definitive results. In this mine of data in the published literature if there is something fixed, calculable, such as the specific constant for disinfectants, the search for the ideal is more concrete. During the disinfection protocols, different disinfectants are applied since the field of action is different, including water, air, aspiration devices, tools, disinfectants used in full accordance with the production indications.Keywords: disinfectant, constant, ideal, side effects
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