Search results for: flight test data

Authors: Fahad Raj Khan, Suleman Khan

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There is a lack of consensus about the predictive value of raised blood glucose levels in terms of major adverse cardiac events (MACEs) in non-diabetic patients admitted for acute decompensated heart failure. The purpose of this research was to examine the long-term prognosis of acute decompensated heart failure (ADHF) in non-diabetic persons who had increased blood glucose levels, i.e., stress hyperglycemia, at the time of their ADHF hospitalization. The research involved 650 non-diabetic patients. Based on their admission stress hyperglycemia, they were divided into two groups.ie with and without (SHGL). The two groups' one-year outcomes for major adverse cardiac events (MACEs) were compared, and key predictors of MACEs were discovered. For statistical analysis, the two-tailed Mann-Whitney U test, Fisher's exact test, and binary logistic regression analysis were utilized. SHGL was found in 353 (54.3%) individuals. It was more frequent in men than in women. About 27% of patients with SHGL had previously been admitted for ADHF. Almost 62% were hypertensive, whereas 14 % had CKD. MACEs were significantly predicted by SHGL, HTN, prior hospitalization for ADHF, CKD, and cardiogenic shock upon admission. SHGL at the time of ADHF admission, independent of DM status, may be a predictive indication of MACEs.

Keywords: stress hyperglycemia, acute heart failure, major adverse cardiac events, MACEs

Procedia PDF Downloads 92

Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

Procedia PDF Downloads 363

Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

Procedia PDF Downloads 187

Authors: Toleen Alaqqad, Kadi Alshabramiy, Suad Zaafarany, Basma Musallam

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CADmapper is a significant tool of software for transforming geographic data into realistic CAD drawings. It speeds up and simplifies the conversion process by automating it. This allows architects, urban planners, engineers, and geographic information system (GIS) experts to solely concentrate on the imaginative and scientific parts of their projects. While the future incorporation of AI has the potential for further improvements, CADmapper's current capabilities make it an indispensable asset in the business. It covers a combination of 2D and 3D city and urban area models. The user can select a specific square section of the map to view, and the fee is based on the dimensions of the area being viewed. The procedure is straightforward: you choose the area you want, then pick whether or not to include topography. 3D architectural data (if available), followed by selecting whatever design program or CAD style you want to publish the document which contains more than 200 free broad town plans in DXF format. If you desire to specify a bespoke area, it's free up to 1 km2.

Keywords: cadmaper, gdata, 2d and 3d data conversion, automated cad drawing, urban planning software

Procedia PDF Downloads 61

Authors: Edward Fosu

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Green innovation has emerged as a significant environmental concern across the world. Green innovation refers to the utilization of technological developments that facilitate energy savings and waste material recycling. The stakeholder theory and resourced-based theory were used to examine how stakeholders' expectations affect corporate green innovation activities and how corporate innovation initiatives affect the corporate image and social performance. This study used structural equation modelling (SEM) and hierarchical regression to test the effects of environmental corporate social responsibility on social performance through mediators: green innovation and corporate image. A quantitative design was employed using data from Chinese companies in Ghana for this study. The study assessed. The results revealed that environmental practices promote corporate social performance (β = 0.070, t = 1.974, p = 0.049), positively affect green product innovation (β = 0.251, t = 7.478, p < 0.001), and has direct effect on green process innovation (β = 0.174, t = 6.192, p < 0.001). Green product innovation and green process innovation significantly promote corporate image respectively (β = 0.089, t = 2.581, p = 0.010), (β = 0.089, t = 2.367, p = 0.018). Corporate image has significant direct effects on corporate social performance (β = 0.146, t = 4.256, p < 0.001). Corporate environmental practices have an impact on the development of green products and processes which promote companies’ social performance. Additionally, evidence supports that corporate image influences companies’ social performance.

Keywords: environmental CSR, corporate image, green innovation, coprorate social performance

Procedia PDF Downloads 118

Authors: Khaled Sandjak, Boualem Tiliouine

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Structural analysis of flexible pavements has been and still is currently performed using multi-layer elastic theory. However, for thinly surfaced pavements subjected to low to medium volumes of traffics, the importance of non-linear stress-strain behaviour of unbound granular materials (UGM) requires the use of more sophisticated numerical models for structural design and performance of such pavements. In the present work, nonlinear unbound aggregates constitutive model is implemented within an axisymmetric finite element code developed to simulate the nonlinear behaviour of pavement structures including two local aggregates of different mineralogical nature, typically used in Algerian pavements. The performance of the mechanical model is examined about its capability of representing adequately, under various conditions, the granular material non-linearity in pavement analysis. In addition, deflection data collected by falling weight deflectometer (FWD) are incorporated into the analysis in order to assess the sensitivity of critical pavement design criteria and pavement design life to the constitutive model. Finally, conclusions of engineering significance are formulated.

Keywords: FWD backcalculations, finite element simulations, Nonlinear resilient behaviour, pavement response and performance, RLT test results, unbound granular materials

Procedia PDF Downloads 257

Authors: Andrew Cummings, Rhianne Boag, Sarah Bryson, Gordon Turner

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Packages designed for transport of radioactive material must satisfy rigorous safety regulations specified by the International Atomic Energy Agency (IAEA). Higher Activity Waste (HAW) transport packages have to maintain containment of their contents during normal and accident conditions of transport (NCT and ACT). To ensure containment criteria is satisfied these packages are required to be leak-tight in all transport conditions to meet allowable activity release rates. Package design safety reports are the safety cases that provide the claims, evidence and arguments to demonstrate that packages meet the regulations and once approved by the competent authority (in the UK this is the Office for Nuclear Regulation) a licence to transport radioactive material is issued for the package(s). The standard approach to demonstrating containment in the RWM transport safety case is set out in BS EN ISO 12807. In this document a method for measuring a leak rate from the package is explained by way of a small interspace test volume situated between two O-ring seals on the underside of the package lid. The interspace volume is pressurised and a pressure drop measured. A small interspace test volume makes the method more sensitive enabling the measurement of smaller leak rates. By ascertaining the activity of the contents, identifying a releasable fraction of material and by treating that fraction of material as a gas, allowable leak rates for NCT and ACT are calculated. The adherence to basic safety principles in ISO12807 is very pessimistic and current practice in the demonstration of transport safety, which is accepted by the UK regulator. It is UK government policy that management of HAW will be through geological disposal. It is proposed that the intermediate level waste be transported to the geological disposal facility (GDF) in large cuboid packages. This poses a challenge for containment demonstration because such packages will have long seals and therefore large interspace test volumes. There is also uncertainty on the releasable fraction of material within the package ullage space. This is because the waste may be in many different forms which makes it difficult to define the fraction of material released by the waste package. Additionally because of the large interspace test volume, measuring the calculated leak rates may not be achievable. For this reason a justification for a lower releasable fraction of material is sought. This paper considers the use of aerosol processes to reduce the releasable fraction for both NCT and ACT. It reviews the basic coagulation and removal processes and applies the dynamic aerosol balance equation. The proposed solution includes only the most well understood physical processes namely; Brownian coagulation and gravitational settling. Other processes have been eliminated either on the basis that they would serve to reduce the release to the environment further (pessimistically in keeping with the essence of nuclear transport safety cases) or that they are not credible in the conditions of transport considered.

Keywords: aerosol processes, Brownian coagulation, gravitational settling, transport regulations

Procedia PDF Downloads 113

Authors: Joseph Bentil

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Successful acquisition of 21st-century competencies needed by students to navigate through the ever-changing world requires that they are taught and molded by 21st-century teachers with the needed professional competencies. Accordingly, this study sought to understand the readiness and how efficacious pre-service Social Studies specialism students are towards the implementation of the Common Core Social Studies Curriculum in the Junior High Schools in Ghana. Theory of Experience served as the theoretical lens for the study. Working within the pragmatist paradigm, this study utilized the cross-sectional descriptive survey design with a mixed method approach where, through census sampling technique, all the 120 pre-service Social Studies specialism students were sampled for the study. A structured questionnaire and an interview guide were the instruments employed for data collection. Descriptive statistics (mean, standard deviation and inferential statistics like independent samples t-test, one-way between groups ANOVA and Pearson Product Moment Correlation) were employed in the analysis the research questions and hypotheses with the aid of version 28 of SPSS while the qualitative data was analyzed using thematic analysis. The findings discovered that pre-service Social Studies teachers were highly ready and efficacious towards implementing the Common Core Junior High School Social Studies curriculum. However, male pre-service teachers were highly efficacious and ready than their female counterparts. Besides, it was disclosed that pre-service teachers within the 31-40 years age bracket were found to be highly efficacious and ready than their colleagues with 20-30 and below 20 years age bracket respectively. The findings further revealed that there was a moderate and statistically significant positive relationship between pre-service teachers’ readiness and efficacy in implementing the Common Core Social Studies curriculum. Therefore, the study recommended that interventional programmes aimed at raising the readiness and efficacy beliefs of pre-service teachers should be targeted towards female preservice teachers and those below 20 years age bracket for successful implementation and realization of the competencies enshrined in the common core social Studies curriculum.

Keywords: pre-service, readiness, social studies, teachers

Procedia PDF Downloads 78

Authors: Aya Al Masri, Kamel Guerchouche, Youssef Laynaoui, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: Mobile C-arms move throughout operating rooms of the operating theater. Being designed to move between rooms, they are not equipped with relays to retrieve the exposition information and export it outside the room. Therefore, no light signaling is available outside the room to warn the X-ray emission for staff. Inadvertent exposition of staff outside the operating theater is a real problem for radiation protection. The French standard NFC 15-160 require that: (1) access to any room containing an X-ray emitting device must be controlled by a light signage so that it cannot be inadvertently crossed, and (2) setting up an emergency button to stop the X-ray emission. This study presents a system that we developed to meet these requirements and the results of its clinical test. Materials and methods: The system is composed of two communicating boxes: o The "DetectBox" is to be installed inside the operating theater. It identifies the various operation states of the C-arm by analyzing its power supply signal. The DetectBox communicates (in wireless mode) with the second box (AlertBox). o The "AlertBox" can operate in socket or battery mode and is to be installed outside the operating theater. It detects and reports the state of the C-arm by emitting a real time light signal. This latter can have three different colors: red when the C-arm is emitting X-rays, orange when it is powered on but does not emit X-rays, and green when it is powered off. The two boxes communicate on a radiofrequency link exclusively carried out in the ‘Industrial, Scientific and Medical (ISM)’ frequency bands and allows the coexistence of several on-site warning systems without communication conflicts (interference). Taking into account the complexity of performing electrical works in the operating theater (for reasons of hygiene and continuity of medical care), this system (having a size <10 cm²) works in complete safety without any intrusion in the mobile C-arm and does not require specific electrical installation work. The system is equipped with emergency button that stops X-ray emission. The system has been clinically tested. Results: The clinical test of the system shows that: it detects X-rays having both high and low energy (50 – 150 kVp), high and low photon flow (0.5 – 200 mA: even when emitted for a very short time (<1 ms)), Probability of false detection < 10-5, it operates under all acquisition modes (continuous, pulsed, fluoroscopy mode, image mode, subtraction and movie mode), it is compatible with all C-arm models and brands. We have also tested the communication between the two boxes (DetectBox and AlertBox) in several conditions: (1) Unleaded room, (2) leaded room, and (3) rooms with particular configuration (sas, great distances, concrete walls, 3 mm of lead). The result of these last tests was positive. Conclusion: This system is a reliable tool to alert the staff present outside the operating room for X-ray emission and insure their radiation protection.

Keywords: Clinical test, Inadvertent staff exposition, Light signage, Operating theater

Procedia PDF Downloads 123

Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

Procedia PDF Downloads 60

Authors: Jaime R. Silva, Gabriel E. Reyes, Marianne Krause

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Background: The two-polarity model of the depressive personality argues that experience is organized around two axes: interpersonal relatedness and self-definition. Differential emphasis on one of these poles defines three types of depressive experience: Anaclitic, Introjective or Mixed pattern. On the one hand, Anaclitic pattern has been conceptually related with exaggerated biological stress sensitivity. On the other hand, the Introjective pattern was linked with anhedonic symptomatology. The general aim of the study was to find empirical support for this relationship. Methods: 101 non-clinical individuals participated in two experimental sessions. During the first session, the biological stress reactivity (cortisol concentration in saliva) and the subjective stress perceived (self-reported) during the Trier Social Stress Test (TSST), were investigated. In the second session, a visual discrimination task with a specific reward system, to study the reinforcement sensitivity (anhedonia), was performed. Results: Results evidenced that participants with Introjective depressive symptoms showed a higher interpersonal sensitivity and a diminished sensitivity to reinforcement. In addition, results also indicated that such a group has a poor psychological detection of its exacerbated reactivity to stress, which is the opposite pattern evidenced amongst the Anaclitic group. Conclusions: In perspective, these results empirically support the two-polarity of the depressive personality model. Clinical implications are discussed.

Keywords: depression, interpersonal stress, personality, trier social stress test

Procedia PDF Downloads 246

Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

Procedia PDF Downloads 303

Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

Procedia PDF Downloads 575

Authors: Zainab Mohammed Shukur, Najlaa Ali Alboshmina, Ali Safa Alsaegh

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The project was investigated tribological behavior of polyether ether ketone (PEEK1000) against PEEK1000 rolling sliding (non-conformal) configuration with slip ratio 83.3%, were tested applications using a TE77 wear mechanisms and friction coefficient test rig. Under marginal lubrication conditions and the absence of film thick conditions, load 100 N was used to simulate the torque in gears 7 N.m. The friction coefficient and wear mechanisms of PEEK were studied under reciprocating roll/slide conditions with water, ethylene glycol, silicone, and base oil. Tribological tests were conducted on a TE77 high-frequency tribometer, with a disc-on-plate slide/roll (the energy pulse criterion) configuration. An Alicona G5 optical 3D micro-coordinate measurement microscope was used to investigate the surface topography and wear mechanisms. The surface roughness had been a significant effect on the friction coefficient for the PEEK/PEEK the rolling sliding contact test ethylene glycol and on the wear mechanisms. When silicone, ethylene glycol, and oil were used as a lubricant, the steady state of friction coefficient was reached faster than the other lubricant. Results describe the effect of the film thick with slip ratio of 83.3% on the tribological performance.

Keywords: polymer, rolling- sliding, energy pulse, gear contact

Procedia PDF Downloads 136

Authors: Manal Sultan Alhussein, Xiang Michelle Liu

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Telehealth is an advanced technology using digital information and telecommunication facilities that provide access to health services from a distance. It slows the transmission factor of COVID-19, especially for elderly patients and patients with chronic diseases during the pandemic. Therefore, understanding patient perspectives on telehealth services and the factors impacting their option of telehealth service will shed light on the measures that healthcare providers can take to improve the quality of telehealth services. This study aimed to evaluate perceptions of telehealth services among different patient groups and explore various aspects of telehealth utilization in the United States during the COVID-19 pandemic. An online survey distributed via social media platforms was used to collect research data. In addition to the descriptive statistics, both correlation and regression analyses were conducted to test research hypotheses. The empirical results highlighted that the factors such as accessibility to telehealth services and the type of specialty clinics that the patients required play important roles in the effectiveness of telehealth services they received. However, the results found that patients’ waiting time to receive telehealth services and their annual income did not significantly influence their desire to select receiving healthcare services via telehealth. The limitations of the study and future research directions are discussed.

Keywords: telehealth, patient satisfaction, pandemic, healthcare, survey

Procedia PDF Downloads 108

Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

Procedia PDF Downloads 186

Authors: Mohammad Mardi

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Generally, the resistivity is high in oil layer and low in water layer. Yet there are intervals of oil-bearing zones showing low resistivity, high porosity, and low resistance. In the typical example, well A (depth: 4341.5-4372.0m), both Spectral Gamma Ray (SGR) and Corrected Gamma Ray (CGR) are relatively low; porosity varies from 12-22%. Above 4360 meters, the reservoir shows the conventional positive difference between deep and shallow resistivity with high resistance; below 4360m, the reservoir shows a negative difference with low resistance, especially at depths of 4362.4 meters and 4371 meters, deep resistivity is only 2Ω.m, and the CAST-V imaging map shows that there are low resistance substances contained in the pores or matrix in the reservoirs of this interval. The rock slice analysis data shows that the pyrite volume is 2-3% in the interval 4369.08m-4371.55m. A comprehensive analysis on the volume of shale (Vsh), porosity, invasion features of resistivity, mud logging, and mineral volume indicates that the possible causes for the negative difference between deep and shallow resistivities with relatively low resistance are erosional pores, caves, micritic texture and the presence of pyrite. Full-bore Drill Stem Test (DST) verified 4991.09 bbl/d in this interval. To identify and thoroughly characterize low resistivity intervals coring, Nuclear Magnetic Resonance (NMR) logging and further geological evaluation are needed.

Keywords: low resistivity pay, carbonates petrophysics, microporosity, porosity

Procedia PDF Downloads 161

Authors: Lojain Suliman, Xinrong Liu, Xiaohan Zhou

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Since most tunnels are built in crowded metropolitan settings, the excavation process must take place in highly condensed locations, including high-density cities. In this way, the tunnels are typically located close together, which leads to more interaction between the parallel existing tunnels, and this, in turn, leads to more settlement. This research presents an examination of the impact of a large-scale tunnel excavation on two forms of settlement: surface settlement and settlement surrounding the tunnel. Additionally, research has been done on the properties of interactions between two and three parallel tunnels. The settlement has been evaluated using three primary techniques: theoretical modeling, numerical simulation, and data monitoring. Additionally, a parametric investigation on how distance affects the settlement characteristic for parallel tunnels with short distances has been completed. Additionally, it has been observed that the sequence of excavation has an impact on the behavior of settlements. Nevertheless, a comparison of the model test and numerical simulation yields significant agreement in terms of settlement trend and value. Additionally, when compared to the FEM study, the suggested analytical solution exhibits reduced sensitivity in the settlement prediction. For example, the settlement of the small tunnel diameter does not appear clearly on the settlement curve, while it is notable in the FEM analysis. It is advised, however, that additional studies be conducted in the future employing analytical solutions for settlement prediction for parallel tunnels.

Keywords: settlement, FEM, analytical solution, parallel tunnels

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Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 199

Authors: M. Novak, E. Munoz, A. Jana, M. Nelemans

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Cities and local governments the world over are interested to employ circular strategies as a means to bring about food security, create employment and increase resilience. The selection and implementation of circular strategies is facilitated by modeling the effects of strategies locally and understanding the impacts such strategies have had in other (comparable) cities and how that would translate locally. Urban areas are heterogeneous because of their geographic, economic, social characteristics, governance, and culture. In order to better understand the effect of circular strategies on urban systems, we create a dataset for over 300 cities around the world designed to facilitate circular strategy scenario modeling. This new dataset integrates data from over 20 prominent global national and urban data sources, such as the Global Human Settlements layer and International Labour Organisation, as well as incorporating employment data from over 150 cities collected bottom up from local departments and data providers. The dataset is made to be reproducible. Various clustering techniques are explored in the paper. The result is sets of clusters of cities, which can be used for further research, analysis, and support comparative, regional, and national policy making on circular cities.

Keywords: data integration, urban innovation, cluster analysis, circular economy, city profiles, scenario modelling

Procedia PDF Downloads 177

Authors: Hossain A., Miah S., Ray P. K.

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Introduction: Single channel and tri-channel applicators are used in the traditional treatment of cervical cancer. Total reference air kerma (TRAK) and treatment outcomes in high-dose-rate brachytherapy for cervical cancer using single-channel and tri-channel applicators were the main objectives of this retrospective study. Material and Methods: Patients in the radiotherapy division who received brachytherapy, chemotherapy, and external radiotherapy (EBRT) using single and tri-channel applicators were the subjects of a retrospective cohort study from 2016 to 2020. All brachytherapy parameters, including TRAK, were calculated in accordance with the international protocol. The Kaplan Meier method was used to analyze survival rates using a log-rank test. Results and Discussions: Based on treatment times of 15.34 (10-20) days and 21.35 (6.5-28) days, the TRAK for the tri-channel applicator was 0.52 cGy.m² and for the single-channel applicator was 0.34 cGy.m². Based on TRAK, the rectum, bladder, and tumor had respective Pearson correlations of 0.082, 0.009, and 0.032. The 1-specificity and sensitivity were 0.70 and 0.30, respectively. At that time, AUC was 0.71. The log-rank test showed that tri-channel applicators had a survival rate of 95% and single-channel applicators had a survival rate of 85% (p=0.565). Conclusions: The relationship between TRAK and treatment duration and Pearson correlation for the tumor, rectum, and bladder suggests that TRAK should be taken into account for the proper operation of single channel and tri-channel applicators.

Keywords: single-channel, tri-channel, high dose rate brachytherapy, cervical cancer

Procedia PDF Downloads 97

Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds is not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: structural healthcare monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation

Procedia PDF Downloads 431

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: clustering, unsupervised learning, pattern recognition, categorical datasets, knowledge discovery, k-means

Procedia PDF Downloads 255

Authors: Steve Apell

Abstract:

Transit-oriented development (TOD) is a popular intervention for local governments endeavoring to reduce auto-dependency and the adverse effects of sprawl. At the same time, American households such as the millennial generation, are shifting their residential preferences from the suburbs to the central city. These changes have intensified demand for TOD housing which generates high rents. This leads to displacement of low-income, transit-dependent households by more affluent middle class families. Critics argue that, the effectiveness of TOD might be compromised as newer affluent residents drive more and use transit less. However, there has not been a comprehensive study to test this hypothesis. Using census data ( 1990 – 2012) from six metropolitans areas, this research investigated if block groups within one-mile radius of TOD are gentrifying. Our findings reveal that the price of housing and number of college graduates, increased more in TODs compared to the metropolitan area. Similarly, the percentage of immigrants increased in TOD, while those of blacks and whites declined. Most importantly, TOD residents generally commuted less by car, while transit use increased in some metropolitan areas. TOD in the south of the United States registered higher cost of housing and less transit use. These findings have significant implications for the future of equitable and sustainable transportation policy.

Keywords: commuting, equity, gentrification, mode choice, transit oriented development

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Authors: Jinshou Shi, Xiaozhou Zhou, Yingwei Zhou, Tuoyang Zhou, Ning Li, Chi Zhang, Zhanshuo Zhang, Ziang Chen

Abstract:

In order to select the optimal interaction method for common computer click tasks, the click experiment test adopts the ISO 9241-9 task paradigm, using four common operations: mouse, trackball, touch, and eye control under visual feedback, auditory feedback, and no feedback. Through data analysis of various parameters of movement time, throughput, and accuracy, it is found that the movement time of touch-control is the shortest, the operation accuracy and throughput are higher than others, and the overall operation performance is the best. In addition, the motion time of the click operation with auditory feedback is significantly lower than the other two feedback methods in each operation mode experiment. In terms of the size of the click target, it is found that when the target is too small (less than 14px), the click performance of all aspects is reduced, so it is proposed that the design of the interface button should not be less than 28px. In this article, we discussed in detail the advantages and disadvantages of the operation and feedback methods, and the results of the discussion of the click operation can be applied to the design of the buttons in the interactive interface.

Keywords: cursor control performance, feedback, human computer interaction, throughput

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Alireza Monzavi Chaleshtari, Maryam Aliakbari

Abstract:

Objective: The aim of this study was to investigate the prediction of child attachment style based on a positive and safe combination parenting method mediated by maternal attachment styles in children with attention deficit hyperactivity disorder. Method: The design of the present study was descriptive of correlation and structural equations and applied in terms of purpose. The population of this study includes all children with attention deficit hyperactivity disorder living in Chaharmahal and Bakhtiari province and their mothers. The sample size of the above study includes 165children with attention deficit hyperactivity disorder in Chaharmahal and Bakhtiari province with their mothers, who were selected by purposive sampling method based on the inclusion criteria. The obtained data were analyzed in two sections of descriptive and inferential statistics. In the descriptive statistics section, statistical indices of mean, standard deviation, frequency distribution table and graph were used. In the inferential section, according to the nature of the hypotheses and objectives of the research, the data were analyzed using Pearson correlation coefficient tests, Bootstrap test and structural equation model. findings:The results of structural equation modeling showed that the research models fit and showed a positive and safe combination parenting style mediated by the mother attachment style has an indirect effect on the child attachment style. Also, a positive and safe combined parenting style has a direct relationship with child attachment style, and She has a mother attachment style. Conclusion:The results and findings of the present study show that there is a significant relationship between positive and safe combination parenting methods and attachment styles of children with attention deficit hyperactivity disorder with maternal attachment style mediation. Therefore, it can be expected that parents using a positive and safe combination232 parenting method can effectively lead to secure attachment in children with attention deficit hyperactivity disorder.

Keywords: child attachment style, positive and safe parenting, maternal attachment style, ADHD

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Authors: Nikita Bharadia, Vikas Gupta, Sushant Koshy

Abstract:

Mobile phone applications (“apps”) have generated substantial interest among marketers and researchers because of the developments in the smartphone technology and the availability of affordable phones to a large number of consumers. Apps are enabling brands to engage with consumers at any time and any place. This study utilizes a pre-test/post-test experimental design to determine if apps can have a persuasive impact on the consumer attitude towards the brand and her purchase intention. The study also tests the impact of informational vs. interactive style of apps on categories with high and low level of involvement. The results show that for high involvement brands, consumers have a predetermined brand image and apps that satisfy consumer needs through an interactive interface can increase purchase intention. For low involvement brands, while informational apps do not create substantial engagement, interactive apps can increase consumer focus on the brand and establish personal connect with the consumers. This has a positive impact in the attitude towards the brand. These results suggest that understanding how to maximize the consumer interaction with mobile phone apps will be a key topic of future research. This research indicates that managers need to evaluate the how apps can solve consumer needs before investing resources towards digital marketing campaign for their brands, following the global trend to capitalize on the digital platforms.

Keywords: App execution style, high and low involvement categories, mobile marketing, smartphone applications

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Authors: Kritiyaporn Kunsook

Abstract:

Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

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Authors: Judith Klostermann, Miguel Segura, Wilma Jans, Dragana Bojovic, Isadora Christel Jimenez, Francisco Doblas-Reyees, Judit Snethlage

Abstract:

The Climate Data Store (CDS), developed by the Copernicus Climate Change Service (C3S) implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Union, is intended to become a key instrument for exploring climate data. The CDS contains both raw and processed data to provide information to the users about the past, present and future climate of the earth. It allows for easy and free access to climate data and indicators, presenting an important asset for scientists and stakeholders on the path for achieving a more sustainable future. The C3S Evaluation and Quality Control (EQC) is assessing the quality of the CDS by undertaking a comprehensive user requirement assessment to measure the users’ satisfaction. Recommendations will be developed for the improvement and expansion of the CDS datasets and products. User requirements will be identified on the fitness of the datasets, the toolbox, and the overall CDS service. The EQC function of the CDS will help C3S to make the service more robust: integrated by validated data that follows high-quality standards while being user-friendly. This function will be closely developed with the users of the service. Through their feedback, suggestions, and contributions, the CDS can become more accessible and meet the requirements for a diverse range of users. Stakeholders and their active engagement are thus an important aspect of CDS development. This will be achieved with direct interactions with users such as meetings, interviews or workshops as well as different feedback mechanisms like surveys or helpdesk services at the CDS. The results provided by the users will be categorized as a function of CDS products so that their specific interests will be monitored and linked to the right product. Through this procedure, we will identify the requirements and criteria for data and products in order to build the correspondent recommendations for the improvement and expansion of the CDS datasets and products.

Keywords: climate data store, Copernicus, quality, user engagement

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