Search results for: prediction modelling

Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: Junya Kouwa, Shinsuke Matsuno, Chihiro Inoue, Takehiro Himeno, Toshinori Watanabe

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Bi-propellant thrusters use impinging jet atomization to atomize liquid fuel and oxidizer. Atomized propellants are mixed and combusted due to auto-ignitions. Therefore, it is important for a prediction of thruster’s performance to simulate the primary atomization phenomenon; especially, the local mixture ratio can be used as indicator of thrust performance, so it is useful to evaluate it from numerical simulations. In this research, we propose a numerical method for considering bi-liquid and the mixture and install it to CIP-LSM which is a two-phase flow simulation solver with level-set and MARS method as an interfacial tracking method and can predict local mixture ratio distribution downstream from an impingement point. A new parameter, beta, which is defined as the volume fraction of one liquid in the mixed liquid within a cell is introduced and the solver calculates the advection of beta, inflow and outflow flux of beta to a cell. By validating this solver, we conducted a simple experiment and the same simulation by using the solver. From the result, the solver can predict the penetrating length of a liquid jet correctly and it is confirmed that the solver can simulate the mixing of liquids. Then we apply this solver to the numerical simulation of impinging jet atomization. From the result, the inclination angle of fan after the impingement in the bi-liquid condition reasonably agrees with the theoretical value. Also, it is seen that the mixture of liquids can be simulated in this result. Furthermore, simulation results clarify that the injecting condition affects the atomization process and local mixture ratio distribution downstream drastically.

Keywords: bi-propellant thrusters, CIP-LSM, free-surface flow simulation, impinging jet atomization

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Authors: Raymond E. Raguindin

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Objective: This research studied the teaching improvement of daycare workers in imitation, joint attention, and language activities using the play-based early intervention training program in Cabanatuan City, Nueva Ecija. Methods: Focus group discussions were developed to explore the attitude, beliefs, and practices of daycare workers. Results: Findings of the study revealed that daycare workers have existing knowledge and experience in teaching children with autism. Their workshops on managing inappropriate behaviors of children with autism resulting in a general positive perception of accepting and teaching children with autism in daycare centers. Play based activities were modelled and participated in by daycare workers. These include demonstration, modelling, prompting and providing social reinforcers as reward. Five lectures and five training days were done to implement the training program. Daycare workers’ levels of skill in teaching imitation, joint attention and language were gathered before and after the participation in the training program. Findings suggest significant differences between pre-test and post test scores. They have shown significant improvement in facilitating imitation, joint attention, and language children with autism after the play-based early intervention training. They were able to initiate and sustain imitation, joint attention, and language activities with adequate knowledge and confidence. Conclusions: 1. Existing attitudes and beliefs greatly influenced the positive delivery mode of instruction. 2. Teacher-directed approach to improve attention, imitation, joint attention, and language of children with autism can be acquired by daycare workers. 3. Teaching skills and experience can be used as reference and basis for identifying future training needs.

Keywords: early intervention, imitation, joint attention, language

Procedia PDF Downloads 123

Authors: Huajuan Shi

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Background: The biopsy of the preimplantation embryo may increase the potential risk and concern of embryo viability. Clinically discarded spent embryo medium (SEM) has entered the view of researchers, sparking an interest in noninvasive embryo screening. However, one of the major restrictions is the extremelty low quantity of cf-RNA, which is difficult to efficiently and unbiased amplify cf-RNA using traditional methods. Hence, there is urgently need to an efficient and low bias amplification method which can comprehensively and accurately obtain cf-RNA information to truly reveal the state of SEM cf-RNA. Result: In this present study, we established an agarose PCR amplification system, and has significantly improved the amplification sensitivity and efficiency by ~90 fold and 9.29 %, respectively. We applied agarose to sequencing library preparation (named AG-seq) to quantify and characterize cf-RNA in SEM. The number of detected cf-RNAs (3533 vs 598) and coverage of 3' end were significantly increased, and the noise of low abundance gene detection was reduced. The increasing percentage 5' end adenine and alternative splicing (AS) events of short fragments (< 400 bp) were discovered by AG-seq. Further, the profiles and characterizations of cf-RNA in spent cleavage medium (SCM) and spent blastocyst medium (SBM) indicated that 4‐mer end motifs of cf-RNA fragments could remarkably differentiate different embryo development stages. Significance: This study established an efficient and low-cost SEM amplification and library preparation method. Not only that, we successfully described the characterizations of SEM cf-RNA of preimplantation embryo by using AG-seq, including abundance features fragment lengths. AG-seq facilitates the study of cf-RNA as a noninvasive embryo screening biomarker and opens up potential clinical utilities of trace samples.

Keywords: cell-free RNA, agarose, spent embryo medium, RNA sequencing, non-invasive detection

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Asawari Ajay Avhad

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The Soil and Water Assessment Tool (SWAT) is a hydrological model designed to predict the complex interactions within natural and human-altered watersheds. This research applies the SWAT model to the Ulhas River basin, a small watershed undergoing urbanization and characterized by bowl-like topography. Three simulation scenarios (LC17, LC22, and LC27) are investigated, each representing different land use and land cover (LULC) configurations, to assess the impact of urbanization on runoff. The LULC for the year 2027 is generated using the MOLUSCE Plugin of QGIS, incorporating various spatial factors such as DEM, Distance from Road, Distance from River, Slope, and distance from settlements. Future climate data is simulated within the SWAT model using historical data spanning 30 years. A susceptibility map for runoff across the basin is created, classifying runoff into five susceptibility levels ranging from very low to very high. Sub-basins corresponding to major urban settlements are identified as highly susceptible to runoff. With consideration of future climate projections, a slight increase in runoff is forecasted. The reliability of the methodology was validated through the identification of sub-basins known for experiencing severe flood events, which were determined to be highly susceptible to runoff. The susceptibility map successfully pinpointed these sub-basins with a track record of extreme flood occurrences, thus reinforcing the credibility of the assessment methodology. This study suggests that the methodology employed could serve as a valuable tool in flood management planning.

Keywords: future land use impact, flood management, run off prediction, ArcSWAT

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Authors: F. Longo, G. Granello, G. Tecchio, F. Da Porto

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Unreinforced masonry (URM) infill walls are widely used throughout the world, also in seismic prone regions, as partitions in reinforced concrete building frames. Even if they do not represent structural elements, they can dramatically affect both strength and stiffness of RC structures by acting as a diagonal strut, modifying shear and displacements distribution along the building height, with uncertain consequences on structural safety. In the last decades, many refined models have been developed to describe infill walls effect on frame structural behaviour, but generally restricted to in-plane actions. Only very recently some new approaches were implemented to consider in-plane/out-of-plane interaction of URM infill walls in progressive collapse simulations. In the present work, a particularly promising macro-model was adopted for the progressive collapse analysis of infilled RC frames. The model allows to consider the bi-directional interaction in terms of displacement and strength capacity for URM infills, and to remove the infill contribution when the URM wall is supposed to fail during the analysis process. The model was calibrated on experimental data regarding two different URM panels thickness, modelling with particular care the post-critic softening branch. A frame specimen set representing the most common Italian structures was built considering two main normative approaches: a traditional design philosophy, corresponding to structures erected between 50’s-80’s basically designed to support vertical loads, and a seismic design philosophy, corresponding to current criteria that take into account horizontal actions. Non-Linear Static analyses were carried out on the specimen set and some preliminary evaluations were drawn in terms of different performance exhibited by the RC frame when the contemporary effect of the out-of-plane damage is considered for the URM infill.

Keywords: infill Panels macromodels, in plane-out of plane interaction, RC frames, URM infills

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: K. S. Sivakumaran, Bo Chen

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The floor beams of steel buildings, cold-formed steel floor joists, in particular, often require large web openings, which may affect their shear capacities. A cost effective way to mitigate the detrimental effects of such openings is to weld/fasten reinforcements. A difficulty associated with an experimental investigation to establish suitable reinforcement schemes for openings in shear zone is that moment always coexists with the shear, and thus, it is impossible to create pure shear state in experiments, resulting in moment influenced results. However, finite element analysis can be conveniently used to investigate the pure shear behaviour of webs including webs with reinforced opening. This paper presents that the details associated with the finite element analysis of thick/thin-plates (representing the web of hot-rolled steel beam, and the web of a cold-formed steel member) having a large reinforced openings. The study considered thin simply supported rectangular plates subjected to inplane shear loadings until failure (including post-buckling behaviour). The plate was modelled using geometrically non-linear quadrilateral shell elements, and non-linear stress-strain relationship based on experiments. Total Lagrangian (TL) with large displacement/small strain formulation was used for such analysis. The model also considered the initial geometric imperfections. This study considered three reinforcement schemes, namely, flat, lip, and angle reinforcements. This paper discusses the modelling considerations and presents the results associated with the various reinforcement schemes under consideration. The paper briefly compares the analysis results with the experimental results.

Keywords: cold-formed steel, finite element analysis, opening, reinforcement, shear resistance

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Authors: Habtamu Tkubet Ebuy

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Purpose Conventional dynamic energy simulation tools go beyond the static dimension of simplified methods by providing better and more accurate prediction of building performance. However, their ability to forecast actual performance is undermined by a low representation of human interactions. The purpose of this study is to examine the potential benefits of incorporating information on occupant diversity into occupant behavior models used to simulate building performance. The co-simulation of the stochastic behavior of the occupants substantially increases the accuracy of the simulation. Design/methodology/approach In this article, probabilistic models of the "opening and closing" behavior of the window of inhabitants have been developed in a separate multi-agent platform, SimOcc, and implemented in the building simulation, TRNSYS, in such a way that the behavior of the window with the interconnectivity can be reflected in the simulation analysis of the building. Findings The results of the study prove that the application of complex behaviors is important to research in predicting actual building performance. The results aid in the identification of the gap between reality and existing simulation methods. We hope this study and its results will serve as a guide for researchers interested in investigating occupant behavior in the future. Research limitations/implications Further case studies involving multi-user behavior for complex commercial buildings need to more understand the impact of the occupant behavior on building performance. Originality/value This study is considered as a good opportunity to achieve the national strategy by showing a suitable tool to help stakeholders in the design phase of new or retrofitted buildings to improve the performance of office buildings.

Keywords: occupant behavior, co-simulation, energy consumption, thermal comfort

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the northeast of the South Island of New Zealand, with alluvial deposits of fine-grained silts and sands combined with low-lying topography suggesting the presence of liquefiable deposits over significant portions of the region. Liquefaction manifestations were observed in past earthquakes, including the 1848 Marlborough and 1855 Wairarapa earthquakes, and more recently during the 2013 Lake Grassmere and 2016 Kaikōura earthquakes. Therefore, a good understanding of the deposits that may be susceptible to liquefaction is important for land use planning in the region and to allow developers and asset owners to appropriately address their risk. For this purpose, multiple approaches have been employed to develop regional-scale maps showing the liquefaction vulnerability categories for the region. After applying semi-qualitative criteria linked to geologic age and deposit type, the higher resolution surface mapping of geomorphologic characteristics encompassing the Wairau River and the Opaoa River was used for screening. A detailed basin geologic model developed for groundwater modelling was analysed to provide a higher level of resolution than the surface-geology based classification. This is used to identify the thickness of near-surface gravel deposits, providing an improved understanding of the presence or lack of potentially non-liquefiable crust deposits. This paper describes the methodology adopted for this project and focuses on the influence of geomorphic characteristics and analysis of the detailed geologic basin model on the liquefaction classification of the Lower Wairau Plains.

Keywords: liquefaction, earthquake, cone penetration test, mapping, liquefaction-induced damage

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Authors: Omolara Lade, David Oloke

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The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). However, in Nigeria, implementation of sustainable water management, such as RWH systems, is inefficient and social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of reinforced concrete cement (RCC) storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use decision support tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of household respondents, Nigerian Architects and Civil Engineers and focus group discussion with stakeholders. 18 selection attributes have been defined and three alternatives have been identified in this research. The questionnaires were analysed using SPSS, excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were modelled using RainCycle software. From the results, the MDA model chose RCC tank as the most appropriate storage system for RWH.

Keywords: rainwater harvesting, modelling, hydraulic assessment, whole life cost, decision support system

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Authors: Victor Igwemezie, Ali Mehmanparast

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The correct knowledge of corrosion fatigue mechanism in marine steel is very important. This is because it enables the design, selection, and use of steels for offshore applications. It also supports realistic corrosion fatigue life prediction of marine structures. A study has been conducted to increase the understanding of corrosion fatigue mechanism in marine steels. The materials investigated are normalized and advanced S355 Thermomechanical control process (TMCP) steels commonly used in the design of offshore wind turbine support structures. The experimental study was carried out by conducting corrosion fatigue tests under conditions pertinent to offshore wind turbine operations, using the state of the art facilities. A careful microstructural study of the crack growth path was conducted using metallurgical optical microscope (OM), scanning electron microscope (SEM) and Energy Dispersive X-Ray Spectroscopy (EDX). The test was conducted on three subgrades of S355 steel: S355J2+N, S355G8+M and S355G10+M and the data compared with similar studies in the literature. The result shows that the ferrite-pearlite morphology primarily controls the corrosion-fatigue crack growth path in marine steels. A corrosion fatigue mechanism which relies on the hydrogen embrittlement of the grain boundaries and pearlite phase is used to explain the crack propagation behaviour. The crack growth trend in the Paris region of the da/dN vs. ΔK curve is used to explain the dependency of the corrosion-fatigue crack growth rate on the ferrite-pearlite morphology.

Keywords: corrosion-fatigue mechanism, fatigue crack growth rate, ferritic-pearlitic steel, microstructure, phase morphology

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Authors: Usama Mohamed, Sam Booth, Aliysn J. Nedoma

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As part of the transition to electric vehicles, there has been a recent increase in demand for battery manufacturing. Cathodes typically account for approximately 50% of the total lithium-ion battery cell cost and are a pivotal factor in determining the viability of new industrial infrastructure. Cathodes which offer lower costs whilst maintaining or increasing performance, such as nickel-rich layered cathodes, have a significant competitive advantage when scaling up the manufacturing process. This project evaluates the techno-economic value proposition of an integrated industrial scale cathode active material (CAM) production process, closing the mass and energy balances, and optimizing the operation conditions using a sensitivity analysis. This is done by developing a process model of a co-precipitation synthesis route using Aspen Plus software and validated based on experimental data. The mechanism chemistry and equilibrium conditions were established based on previous literature and HSC-Chemistry software. This is then followed by integrating the energy streams, adding waste recovery and treatment processes, as well as testing the effect of key parameters (temperature, pH, reaction time, etc.) on CAM production yield and emissions. Finally, an economic analysis estimating the fixed and variable costs (including capital expenditure, labor costs, raw materials, etc.) to calculate the cost of CAM ($/kg and $/kWh), total plant cost ($) and net present value (NPV). This work sets the foundational blueprint for future research into sustainable industrial scale processes for CAM manufacturing.

Keywords: cathodes, industrial production, nickel-rich layered cathodes, process modelling, techno-economic analysis

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Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

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Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: R. Bakr, M. Elmeligy, A. Ibrahim

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When the building loads are relatively small, challenges are often facing the foundation design especially when inappropriate soil conditions exist. These may be represented in the existence of soft soil in the upper layers of soil while sandy soil or firm cohesive soil exist in the deeper layers. In such cases, the design becomes infeasible if the piles are extended to the deeper layers, especially when there are sandy layers existing at shallower depths underlain by stiff clayey soil. In this research, models of piles terminated in sand underlain by clay soils are numerically simulated by different modelling theories. Finite element software, Plaxis 3-D Foundation was used to evaluate the pile behavior under different loading scenarios. The standard static load test according to ASTM D-1143 was simulated and compared with the real-life loading scenario. The results showed that the pile behavior obtained from the current static load test do not realistically represent that obtained from real-life loading. Attempts were carried out to capture the proper numerical loading scenario that simulates the pile behavior in real-life loading including the long-term effect. A modified method based on this research findings is proposed for the static pile loading tests. Field loading tests were carried out to validate the new method. Results obtained from both numerical and field tests by using the modified method prove that this method is more accurate in predicting the pile behavior in sand soil underlain by clay more than the current standard static load.

Keywords: numerical simulation, static load test, pile behavior, sand underlain with clay, creep

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Smart cities and intelligent transportation systems rely heavily on effective traffic management and infrastructure planning. This research tackles the data scarcity challenge by generating realistically synthetic traffic data from the PeMS-Bay dataset, enhancing predictive modeling accuracy and reliability. Advanced techniques like TimeGAN and GaussianCopula are utilized to create synthetic data that mimics the statistical and structural characteristics of real-world traffic. The future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is anticipated to capture both spatial and temporal correlations, further improving data quality and realism. Each synthetic data generation model's performance is evaluated against real-world data to identify the most effective models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are employed to model and predict complex temporal dependencies within traffic patterns. This holistic approach aims to identify areas with low vehicle counts, reveal underlying traffic issues, and guide targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study facilitates data-driven decision-making that improves urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory (LSTM), synthetic data generation, traffic management

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Authors: C. C. Egwuonwu, N. A. A. Okereke, K. O. Chilakpu, S. O. Ohanyere

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In this study, initial soil strength indices (qu) and stress-strain characteristics, namely failure strain (ϵf), area under the stress-strain curve up to failure (Is) and stress-strain modulus between no load and failure (Es) were investigated as potential indicators for characterizing the erosion resistance of two compacted soils, namely sandy clay loam (SCL) and clay loam (CL) in some selected sites in Enugu State, Nigeria. The unconfined compressive strength (used in obtaining strength indices) and stress-strain measurements were obtained as a function of moisture content in percentage (mc %) and dry density (γd). Test were conducted over a range of 8% to 30% moisture content and 1.0 g/cm3 to 2.0 g/cm3 dry density at applied loads of 20, 40, 80, 160 and 320 kPa. Based on the results, it was found out that initial soil strength alone was not a good indicator of erosion resistance. For instance, in the comparison of exponents of mc% and γd for jet index or erosion resistance index (Ji) and the strength measurements, qu and Es agree in signs for mc%, but are opposite in signs for γd. Therefore, there is an inconsistency in exponents making it difficult to develop a relationship between the strength parameters and Ji for this data set. In contrast, the exponents of mc% and γd for Ji and ϵf and Is are opposite in signs, there is potential for an inverse relationship. The measured stress-strain characteristics, however, appeared to have potential in providing useful information on erosion resistance. The models developed for the prediction of the extent or the susceptibility of soils to erosion and subjected to sensitivity test on some selected sites achieved over 90% efficiency in their functions.

Keywords: characterization of erodibility, selected sites in Enugu state, soil strength, stress-strain indices

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Authors: Roy Y. C. Huang, J. S. Kuang, Hamdolah Behnam

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Beam-column connections play an important role in the reinforced concrete moment resisting frame (RCMRF), which is one of the most commonly used structural systems around the world. The premature failure of such connections would severely limit the seismic performance and increase the vulnerability of RCMRF. In the past decades, researchers primarily focused on investigating the structural behaviour and failure mechanisms of conventional beam-column joints, the beam width of which is either smaller than or equal to the column width, while studies in wide beam-column joints were scarce. This paper presents the preliminary experimental results of two full-scale exterior wide beam-column connections, which are mainly designed and detailed according to ACI 318-14 and ACI 352R-02, under reversed cyclic loading. The ratios of the design shear force to the nominal shear strength of these specimens are 1.0 and 1.7, respectively, so as to probe into differences of the joint shear strength between experimental results and predictions by design codes of practice. Flexural failure dominated in the specimen with ratio of 1.0 in which full-width plastic hinges were observed, while both beam hinges and post-peak joint shear failure occurred for the other specimen. No sign of premature joint shear failure was found which is inconsistent with ACI codes’ prediction. Finally, a modification of current codes of practice is provided to accurately predict the joint shear strength in wide beam-column joint.

Keywords: joint shear strength, reversed cyclic loading, seismic vulnerability, wide beam-column joints

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Authors: Wajid Rehman, Sirajul Haq, Bakhtiar Muhammad, Syed Fahad Hassan, Amin Badshah, Muhammad Waseem, Fazal Rahim, Obaid-Ur-Rahman Abid, Farzana Latif Ansari, Umer Rashid

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Five novel triorganotin (IV) compounds have been synthesized and characterized. The tin atom is penta-coordinated to assume trigonal-bipyramidal geometry. Using in silico derived parameters; the objective of our study is to design and synthesize promiscuous antibacterials potent enough to combat resistance. Among various synthesized organotin (IV) complexes, compound 5 was found as potent antibacterial agent against various bacterial strains. Further lead optimization of drug-like properties was evaluated through in silico predictions. Data mining and computational analysis were utilized to derive compound promiscuity phenomenon to avoid drug attrition rate in designing antibacterials. Xanthine oxidase and human glucose- 6-phosphatase were found as only true positive off-target hits by ChEMBL database and others utilizing similarity ensemble approach. Propensity towards a-3 receptor, human macrophage migration factor and thiazolidinedione were found as false positive off targets with E-value 1/4> 10^-4 for compound 1, 3, and 4. Further, displaying positive drug-drug interaction of compound 1 as uricosuric was validated by all databases and docked protein targets with sequence similarity and compositional matrix alignment via BLAST software. Promiscuity of the compound 5 was further confirmed by in silico binding to different antibacterial targets.

Keywords: antibacterial activity, drug promiscuity, ADMET prediction, metallo-pharmaceutical, antimicrobial resistance

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Authors: Chi Wu, Dean Wu, Wen-Te Liu, Cheng-Yu Tsai, Shin-Mei Hsu, Yin-Tzu Lin, Ru-Yin Yang

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Background: The results of previous studies compared the benefits and risks of receiving insomnia medication. However, the effects between hypnotic drugs used and enhancement of sleep quality were still unclear. Objective: The aim of this study is to establish a prediction model for hypnotic drugs' dosage used for insomnia subjects and associated the relationship between sleep stage ratio change and drug types. Methodologies: According to American Academy of Sleep Medicine (AASM) guideline, sleep stages were classified and transformed to hypnogram via the polysomnography (PSG) in a hospital in New Taipei City (Taiwan). The subjects with diagnosis for insomnia without receiving hypnotic drugs treatment were be set as the comparison group. Conversely, hypnotic drugs dosage within the past three months was obtained from the clinical registration for each subject. Furthermore, the collecting subjects were divided into two groups for training and testing. After training convolution neuron network (CNN) to predict types of hypnotics used and dosages are taken, the test group was used to evaluate the accuracy of classification. Results: We recruited 76 subjects in this study, who had been done PSG for transforming hypnogram from their sleep stages. The accuracy of dosages obtained from confusion matrix on the test group by CNN is 81.94%, and accuracy of hypnotic drug types used is 74.22%. Moreover, the subjects with high ratio of wake stage were correctly classified as requiring medical treatment. Conclusion: CNN with hypnogram was potentially used for adjusting the dosage of hypnotic drugs and providing subjects to pre-screening the types of hypnotic drugs taken.

Keywords: convolution neuron network, hypnotic drugs, insomnia, polysomnography

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Authors: Lian Song, Shao-Bo Kang, Bo Yang

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Concrete filled steel tubular (CFST) structure has been widely used in construction practices due to its superior performances under various loading conditions. However, limited studies are available when this type of structure is subjected to impact or explosive loads. Current methods in relevant design codes are not specific for preventing progressive collapse of CFST structures. Therefore, it is necessary to carry out numerical simulations on CFST structure under impact loads. In this study, finite element analyses are conducted on the mechanical behaviour of composite frames which composed of CFST columns and steel beams subject to impact loading. In the model, CFST columns are simulated using finite element software ABAQUS. The model is verified by test results of solid and hollow CFST columns under lateral impacts, and reasonably good agreement is obtained through comparisons. Thereafter, a multi-scale finite element modelling technique is developed to evaluate the behaviour of a five-storey three-span planar composite frame. Alternate path method and direct simulation method are adopted to perform the dynamic response of the frame when a supporting column is removed suddenly. In the former method, the reason for column removal is not considered and only the remaining frame is simulated, whereas in the latter, a specific impact load is applied to the frame to take account of the column failure induced by vehicle impact. Comparisons are made between these two methods in terms of displacement history and internal force redistribution, and design recommendations are provided for the design of CFST structures under impact loads.

Keywords: planar composite frame, collapse analysis, impact loading, direct simulation method, alternate path method

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Authors: Esha Saha, Pradip Kumar Ray

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A hospital inventory comprises of a large number and great variety of items for the proper treatment and care of patients, such as pharmaceuticals, medical equipment, surgical items, etc. Improper management of these items, i.e. stockouts, may lead to delay in treatment or other fatal consequences, even death of the patient. So, generally the hospitals tend to overstock items to avoid the risk of stockout which leads to unnecessary investment of money, difficulty in storing, more expiration and wastage, etc. Thus, in such challenging environment, it is necessary for hospitals to follow an inventory policy considering the stochasticity of demand in a hospital. Statistical analysis captures the correlation of patient condition based on bed occupancy with the patient demand which changes stochastically. Due to the dependency on bed occupancy, the markov model is developed that helps to map the changes in demand of hospital inventory based on the changes in the patient condition represented by the movements of bed occupancy states (acute care state, rehabilitative state and long-care state) during the length-of-stay of patient in a hospital. An inventory policy is developed for a hospital based on the fulfillment of patient demand with the objective of minimizing the frequency and quantity of placement of orders of inventoried items. The analytical structure of the model based on probability calculation is provided to show the optimal inventory-related decisions. A case-study is illustrated in this paper for the development of hospital inventory model based on patient demand for multiple inpatient pharmaceutical items. A sensitivity analysis is conducted to investigate the impact of inventory-related parameters on the developed optimal inventory policy. Therefore, the developed model and solution approach may help the hospital managers and pharmacists in managing the hospital inventory in case of stochastic demand of inpatient pharmaceutical items.

Keywords: bed occupancy, hospital inventory, markov model, patient condition, pharmaceutical items

Procedia PDF Downloads 325

Authors: Aung Phyo Kyaw, Kuo Chieh Chao

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Expansive soils are more complicated than normal soils, although the soil itself is not very complicated. When evaluating foundation performance on expansive soil, it is important to consider soil expansion. The primary focus of this study is on hydraulic cement and expansive soil mixtures, and the research aims to identify key parameters for controlling the swell of the expansive soil-hydraulic cement mixture. Treatment depths can be determined using hydraulic cement ratios of 4%, 8%, 12%, and 15% for treating expansive soil. To understand the effect of hydraulic cement percentages on the swelling of expansive soil-hydraulic admixture, performing the consolidation-swell test σ''ᶜˢ is crucial. This investigation primarily focuses on consolidation-swell tests σ''ᶜˢ, although the heave index Cₕ is also needed to determine total heave. The heave index can be measured using the percent swell in the specific inundation stress in both the consolidation-swell test and the constant-volume test swelling pressure. Obtaining the relationship between swelling pressure and σ''ᶜⱽ determined from the "constant volume test" is useful in predicting heave from a single oedometer test. The relationship between σ''ᶜˢ and σ''ᶜⱽ is based on experimental results of expansive soil behavior and facilitates heave prediction for each soil. In this method, the soil property "m" is used as a parameter, and common soil property tests include compaction, particle size distribution, and the Atterberg limit. The Electricity Generating Authority of Thailand (EGAT) provided the soil sample for this study, and all laboratory testing is performed according to American Society for Testing and Materials (ASTM) standards.

Keywords: expansive soil, swelling pressure, total heave, treatment depth

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Authors: Helene Thieblemont, Fariborz Haghighat

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Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

Procedia PDF Downloads 271

Authors: Vera Wilden, Benno Hoffmeister, Georgios Balaskas, Lukas Rauber, Burkhard Walter

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Light-weight timber frame elements represent an efficient structural solution for wooden multistory buildings. The wall elements of such buildings – which act as shear diaphragms- provide lateral stiffness and resistance to wind and seismic loads. The tendency towards multi-story structures leads to challenges regarding the prediction of stiffness, strength and ductility of the buildings. Lightweight timber frame elements are built up of several structural parts (sheeting, fasteners, frame, support and anchorages); each of them contributing to the dynamic response of the structure. This contribution describes the experimental and numerical investigation and development of enhanced lightweight timber frame buildings. These developments comprise high-performance timber frame walls with the variable arrangements of sheathing planes and dissipative anchors at the base of the timber buildings, which reduce damages to the timber structure and can be exchanged after significant earthquakes. In order to prove the performance of the developed elements in the context of a real building a full-scale two-story building core was designed and erected in the laboratory and tested experimentally for its seismic performance. The results of the tests and a comparison of the test results to the predicted behavior are presented. Observation during the test also reveals some aspects of the design and details which need to consider in the application of the timber walls in the context of the complete building.

Keywords: dissipative anchoring, full scale test, push-over-test, wood shear walls

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Authors: Orose Rugchati, Khumthong Mahawongwiriya

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Dendrobium hybrid cv. Ear-Sakul has become one of the important commercial commodities in Thailand agricultural industry worldwide, either as potted plants or as cut flowers due to the attractive color produced in flower petals. Anthocyanins are the main flower pigments and responsible for the natural attractive display of petal colors. These pigments play an important role in functionality, such as to attract animal pollinators, classification, and grading of these orchids. Dendrobium hybrid cv. Ear-Sakul has been collected from local area farm in different stage flowers (F1, F2-F5, and F6). Anthocyanins pigment were extracted from the fresh flower by solvent extraction (MeOH–TFA 99.5:0.5v/v at 4ºC) and purification with ethyl acetate. The main anthocyanins components are cyanidin, pelargonidin, and delphinidin. Pure anthocyanin contents were analysis by UV-Visible spectroscopy technique at λ max 535, 520 and 546 nm respectively. The anthocyanins contents were converted in term of monomeric anthocyanins pigment (mg/L). The anthocyanins contents of all sample were compared with standard pigments cyanidin, pelargonidin and delphinidin. From this experiment is a simple extraction and analysis anthocyanins content in different stage of flowers results shown that monomeric anthocyanins pigment contents of different stage flowers (F1, F2-F5 and F6 ): cyanidin – 3 – glucoside (mg/l) are 0.85+0.08, 24.22+0.12 and 62.12+0.6; Pelargonidin 3,5-di- glucoside(mg/l) 10.37+0.12, 31.06+0.8 and 81.58+ 0.5; Delphinidin (mg/l) 6.34+0.17, 18.98+0.56 and 49.87+0.7; and the appearance of extraction pure anthocyanins in L(a, b): 2.71(1.38, -0.48), 1.06(0.39,-0.66) and 2.64(2.71,-3.61) respectively. Dendrobium Hybrid cv. Ear-Sakul could be used as a source of anthocyanins by simple solvent extraction and stage of flowers as a guideline for the prediction amount of main anthocyanins components are cyanidin, pelargonidin, and delphinidin could be application and development in quantities, and qualities with the advantage for food pharmaceutical and cosmetic industries.

Keywords: analysis, anthocyanins contents, different stage flowers, Dendrobium Hybrid cv. Ear-Sakul

Procedia PDF Downloads 151

Authors: Tetsya Sok, Seong Jae Hong, Young Kyu Kim, Seung Woo Lee

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The temperature distribution for asphalt concrete (AC)-Concrete composite pavement is one of main influencing factor that affects to performance life of pavement. The temperature gradient in concrete slab underneath the AC layer results the critical curling stress and lead to causes de-bonding of AC-Concrete interface. These stresses, when enhanced by repetitive axial loadings, also contribute to the fatigue damage and eventual crack development within the slab. Moreover, the temperature change within concrete slab extremely causes the slab contracts and expands that significantly induces reflective cracking in AC layer. In this paper, the numerical prediction of pavement temperature was investigated using one-dimensional finite different method (FDM) in fully explicit scheme. The numerical predicted model provides a fundamental and clear understanding of heat energy balance including incoming and outgoing thermal energies in addition to dissipated heat in the system. By using the reliable meteorological data for daily air temperature, solar radiation, wind speech and variable pavement surface properties, the predicted pavement temperature profile was validated with the field measured data. Additionally, the effects of AC thickness and daily air temperature on the temperature profile in underlying concrete were also investigated. Based on obtained results, the numerical predicted temperature of AC-Concrete composite pavement using FDM provided a good accuracy compared to field measured data and thicker AC layer significantly insulates the temperature distribution in underlying concrete slab.

Keywords: asphalt concrete, finite different method (FDM), curling effect, heat transfer, solar radiation

Procedia PDF Downloads 270

Authors: Ashkan Ebadi, Adam Krzyzak

Abstract:

Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

Procedia PDF Downloads 274