Search results for: reliable facility location model

Authors: Buse T. Aydın, Enver Ozdemir

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In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 161

Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: He Chao, Zhang Lei, Liu Ran, Li Ang

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Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keep the shrouds in the temperature range from -150℃ to +150℃. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.

Keywords: space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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During the recent years, demand for healthcare services has dramatically increased. As the demand for healthcare services increases, so does the necessity of constructing new healthcare buildings and redesigning and renovating existing ones. Increasing demands necessitate the use of optimization techniques to improve the overall service efficiency in healthcare settings. However, high complexity of care processes remains the major challenge to accomplish this goal. This study proposes a method based on process mining results to address the high complexity of care processes and to find the optimal layout of the various medical centers in an emergency department. ProM framework is used to discover clinical pathway patterns and relationship between activities. Sequence clustering plug-in is used to remove infrequent events and to derive the process model in the form of Markov chain. The process mining results served as an input for the next phase which consists of the development of the optimization model. Comparison of the current ED design with the one obtained from the proposed method indicated that a carefully designed layout can significantly decrease the distances that patients must travel.

Keywords: Mixed Integer programming, Facility layout problem, Process Mining, Healthcare Operation Management

Procedia PDF Downloads 340

Authors: Mbuso Siwela

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Background: The Sub-Saharan Africa region has the greatest number of people eligible to receive antiretroviral treatment (ART). Multi-month Drug dispensing (MMD) of antiretroviral treatment (ART) aims to reduce patient-related barriers to access long-term treatment and improve health system efficiency. In Eswatini, however, few children and adolescents are on MMD. Young Heroes is implementing an HIV program that aims to avert new HIV infections in children and youth and improve treatment outcomes for children and adolescents living with HIV (C/ALHIV: 0-19 Years) and OVC caregivers with HIV prevention and impact mitigation interventions that prevent new HIV infections and reduce vulnerability. Aim of the study: The study aimed to ascertain factors that are associated with the assignment of the MMD model on C/ALHIVs. Methodology: The project provides treatment adherence support through well-trained community cadres (Home Visitors - HVs) at both community and health facility levels. During door-to-door visits, HVs track all C/ALHIV enrolled in the project monthly and refer any who might have stopped or interrupted treatment. C/ALHIV with unsuppressed viral load is supported through case conferencing and teen clubs. A quantitative cross-sectional analysis was conducted using STATA for children and adolescents living with HIV enrolled in the project. Bivariate analysis was conducted, and the Logistic Regression model was used to ascertain the effects of duration on ART on the choice of MMD model. Results: Data for 544 C/ALHIV (0-19 Years) was analyzed in STATA. Results show a strong association between (duration on ART, Age, being in teen club) and enrolment in an MMD model. Duration on ART is a major predictor for the choice of MMD model at (95% CI: 0.0012905 – 0.0039812; P = <0.0001). C/ALHIV who have been on ART for less than a year are less likely to be on MMD. C/ALHIVs who are 1 or more years on ART are more likely to be in 3 months dispensing, while those who are 5 years or more are most likely to be in 6 months model.

Keywords: C/ALHIV, OVC, HIV, treatment

Procedia PDF Downloads 44

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Mehdi Ghatei, Masoomeh Lorestani

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Upstream Tailings Storage Facilities (TSFs) may experience slope instabilities due to soil liquefaction, especially in regions known to be seismically active. In this study, liquefaction susceptibility of an upstream-raised TSF in Western Australia was assessed using two different approaches. The first approach assessed liquefaction susceptibility using Cone Penetration Tests with pore pressure measurement (CPTu) as described by the National Centre for Earthquake Engineering Research (NCEER). This assessment was based on the four CPTu tests that were conducted on the perimeter embankment of the TSF. The second approach used the Finite Element (FE) method with application of an equivalent linear model to predict the undrained cyclic behavior, the pore water pressure and the liquefaction of the materials. The tailings parameters were estimated from the CPTu profiles and from the laboratory tests. The cyclic parameters were estimated from the literature where test results of similar material were available. The results showed that there was a good agreement, in the liquefaction susceptibility of the tailings material, between the NCEER and FE methods with equivalent linear model.

Keywords: liquefaction , CPTU, NCEER, finite element method, equivalent linear model

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Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Haitham J. M. Odeh

Abstract:

This paper introduced an analysis of the effect of tunneling near pile foundations. Accomplished by three-dimensional finite element modeling. The numerical simulation is conducted using Abaqus finite element software. By examining different Tunnel-pile scenarios. The paper presents the tunnel induced pile responses, Such as pile settlement, pile internal forces, and the comments made on changing the vertical and transversal location of the tunnel related to the piles, the study contains two pile-supported structure cases, single and a group of piles. A comprehensive comparison between real case study results and numerical simulation is presented. The results of the analysis reveal the critical and safe location of tunnel construction and the positive effect of a group of piles existing instead of single piles. Also, demonstrates the changes in pile responses by changing the tunnel location.

Keywords: pile responses, single pile, group of piles, pile-tunnel interaction

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Authors: P. Hajyalikhani, B. Hudson, D. Boll, L. Boren, Z. Sparks, M. Ward

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Wood Light frame construction is one of the most common types of construction methods for residential and light commercial building in North America and parts of Europe. The typical roof framing for wood framed building is sloped and consists of several structural members such as rafters, hips, and valleys which are connected to the ridge and ceiling joists. The common slopes for roofs are 3/12, 8/12, and 12/12. Wood framed residential roof failure is most commonly caused by wind damage in such buildings. In the recent study, one of the weaknesses of wood framed roofs is long unsupported structural member lengths, such as hips and valleys. The purpose of this research is to find the critical support location for long hips and valleys with different slopes. ForteWeb software is used to find the critical location. The analysis results demonstrating the maximum unbraced hip and valley length are from 8.5 to 10.25 ft. dependent on the slope and roof type.

Keywords: wood frame, stick framing, hip, valley

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Authors: A. Degale Desta, Tamirat Kebamo

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Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: S. M. T. Mustafa, D. Raes, M. Huysmans

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Proper utilization of water resource is very important in agro-based Bangladesh. Irrigation schedule based on local environmental conditions, soil type and water availability will allow a sustainable use of water resources in agriculture. In this study, the FAO crop water model (AquaCrop) was used to simulate the different water and fertilizer management strategies in different location of Bangladesh to obtain a management guideline for the farmer. Model was calibrated and validated for wheat (Triticum aestivum L.). The statistical indices between the observed and simulated grain yields obtained were very good with R2, RMSE, and EF values of 0.92, 0.33, and 0.83, respectively for model calibration and 0.92, 0.68 and 0.77, respectively for model validations. Stem elongation (jointing) to booting and flowering stage were identified as most water sensitive for wheat. Deficit irrigation on water sensitive stage could increase the grain yield for increasing soil fertility levels both for loamy and sandy type soils. Deficit irrigation strategies provides higher water productivity than full irrigation strategies and increase the yield stability (reduce the standard deviation). The practical deficit irrigation schedule for wheat for four different stations and two different soils were designed. Farmer can produce more crops by using deficit irrigation schedule under water stress condition. Practical application and validation of proposed strategies will make them more credible.

Keywords: crop-water model, deficit irrigation, irrigation scheduling, wheat

Procedia PDF Downloads 433

Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

Procedia PDF Downloads 298

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 76

Authors: Moustafa Osman Mohammed

Abstract:

This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: Mohammed Alharbi, Clare Wood, Vasileios Samaras

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Sustainability leadership is a controversial topic, particularly in the engineering context. The theoretical and practical technical focus of the engineering profession impacts our lives. Technologically, engineers significantly contribute to our modern civilization. Industrial revolutions are among the top engineering accomplishments that have contributed to the flourishing of our life. However, engineers have not always received the credit they deserve; instead, they have been blamed for the advent of various global issues, among them the global warming phenomena that are believed to be a result of the industrial revolutions. Global challenges demand engineers demonstrate more than their technical skills for effective contribution to a sustainable future. As a result, engineering leadership has emerged as a new research field. Sustainable manufacturing is a cornerstone for sustainable development. Investigating the change to more sustainable manufacturing practices is a significant issue for all, and even more in the field of engineering leadership. Engineers dominate the manufacturing industry; however, one of the main criticism of engineers is the lack of leadership skills. The literature on engineering leadership has not highlighted enough the engineers' leadership ability in leading sustainable manufacturing. Since we are at the cusp of a new industrial revolution -Industry 4.0, it is vital to investigate the ability of engineers to lead the industry towards a sustainable future. The primary purpose of this paper is to evaluate engineers' sustainability leadership competencies utilizing The Cambridge University Behavioral Competency Model. However, the practical application of the Cambridge model is limited due to the absence of a reliable measurement tool. Therefore, this study developed a valid and reliable survey instrument tool compatible with the Cambridge model as a secondary objective. More than 300 Saudi engineers from the manufacturing industry responded to an online questionnaire collected through the Qualtrics platform and analyzed using SPSS software. The findings provide a contemporary understanding of engineers' mindset related to sustainability leadership. The output of this research study could be valuable in designing effective engineering leadership programs in academia or industry, particularly for enhancing a sustainable manufacturing environment.

Keywords: engineer, leadership, manufacturing, sustainability

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Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

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The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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Authors: Haitham A. Hussein, Rozi Abdullah‏‎, Md Azlin Md Said ‎

Abstract:

Gravity separator tanks are used to separate oil from water in treatment units. Achieving the best flow ‎uniformity in a separator tank will improve the maximum removal efficiency of oil globules from water. ‎In this study, the effect on hydraulic performance of different baffle structure positions inside a tank ‎was investigated. Experimental data and 2D computation fluid dynamics were used for analysis. In the ‎numerical model, two-phase flow (drift flux model) was used to validate one-phase flow. For ‎laboratory measurements, the velocity fields were measured using an acoustic Doppler velocimeter. The ‎measurements were compared with the result of the computational model. The results of the ‎experimental and computational simulations indicate that the best location of a baffle structure is ‎achieved when the standard deviation of the velocity profile and the volume of the circulation zone ‎inside the tank are minimized.‎

Keywords: gravity separator tanks, CFD, baffle position, two phase flow, ADV, oil droplet

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Authors: Mojahid F. Saeed Osman

Abstract:

Repairable items inventory system is a management tool used to incorporate all information concerning inventory levels and movements for repaired and new items. This paper presents development of an effective simulation model for managing the inventory of repairable items for a production system where production lines send their faulty items to a repair shop considering the stochastic failure behavior and repair times. The developed model imitates the process of handling the on-hand inventory of repaired items and the replenishment of the inventory of new items using Economic Order Quantity and Reorder Point ordering policy in a flexible and risk-free environment. We demonstrate the appropriateness and effectiveness of the proposed simulation model using an illustrative case problem. The developed simulation model can be used as a reliable tool for estimating a healthy on-hand inventory of new and repaired items, backordered items, and downtime due to unavailability of repaired items, and validating and examining Economic Order Quantity and Reorder Point ordering policy, which would further be compared with other ordering strategies as future work.

Keywords: inventory system, repairable items, simulation, maintenance, economic order quantity, reorder point

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Authors: A. Clementking, C. Jothi Venkateswaran

Abstract:

Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Stewart A. Keir, Faik A. Hamad

Abstract:

This study aims to use both analytical and experimental methods of analysis to examine the accuracy of Computational Fluid Dynamics (CFD) models that can then be used for more complex analyses, accurately representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD model is taken from the experimental rig. The analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimize the redesign an experimental rig for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The CFD model is then optimized through the selection of different parameters, e.g. turbulence models (Spalart-Almaras, Realizable k-epsilon & Standard k-omega) in order to develop an accurate, robust model. The results from the CFD model can then be directly compared to experimental and analytical results in order to gauge the accuracy of each method of analysis. The CFD model will be used to visualize the variation of various parameters such as velocity/Mach number, pressure and turbulence across the shock. The CFD results will be used to investigate the interaction between the shock wave and the boundary layer. The validated model can then be used to modify the nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.

Keywords: CFD, nozzle, fluent, gas dynamics, shock-wave

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Authors: Jungyeol Hong, Dongjoo Park

Abstract:

The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Salim Belouettar, Kodjo Attipou

Abstract:

The thermal wrinkling behavior of thin membranes is investigated. The Fourier double scale series are used to deduce the macroscopic membrane wrinkling equations. The obtained equations account for the global and local wrinkling modes. Numerical examples are conducted to assess the validity of the approach developed. Compared to the finite element full model, the present model needs only few degrees of freedom to recover accurately the bifurcation curves and wrinkling paths. Different parameters such as membrane’s aspect ratio, wave number, pre-stressed membranes are discussed from a numerical point of view and the properties of the wrinkles (critical load, wavelength, size and location) are presented.

Keywords: wrinkling, thermal stresses, Fourier series, thin membranes

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

Abstract:

This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Abdullah Aljumah, Tariq Ahamad

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The simplest possible human-computer interaction is mobile cloud computing as it emerges and makes the use of all modern-day human-oriented technology. The main aim of this idea is the QoS (quality of service) by using user-friendly and reliable software over the global network in order to make it economical by reducing cost, reliable, and increase the main storage. Since we studied and went through almost all the existing related work in this area and we came up with some challenges that will rise or might be rising for some basic areas in mobile cloud computing and mostly stogie and security area. In this research article, we suggest some recommendation for mobile cloud computing and for its security that will help in building more powerful tools to handle all this pressure.

Keywords: Cloud Computing, MCC, SAAS, computer interaction

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Authors: Lochan Basyal

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Global Automation is an emerging technology of today’s era and is based on Internet of Things (IoT). Global automation deals with the controlling of electrical appliances throughout the world. The fabrication of this system has been carried out with interfacing an electrical control system module to Raspberry Pi. An electrical control system module includes a relay driver mechanism through which appliances are controlled automatically in respective condition. In this research project, one email ID has been assigned to Raspberry Pi, and the users from different location having different email ID can mail to Raspberry Pi on assigned email address “[email protected]” with subject heading “Device Control” with predefined command on compose email line. Also, a notification regarding current working condition of this system has been updated on respective user email ID. This approach is an innovative way of implementing smart automation system through which a user can control their electrical appliances like light, fan, television, refrigerator, etc. in their home with the use of email facility. The development of this project helps to enhance the concept of smart home application as well as industrial automation.

Keywords: control circuit, e-mail, global automation, internet of things, IOT, Raspberry Pi

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Authors: Shah Md. Imran Kabir, Md. Mostafa Ali

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Karnafuli is one of the most important rivers of Bangladesh which is playing a vital role in our national economy. The major sea port of Bangladesh is the Chittagong port located on the right bank of Karnafuli River Bangladesh. Karnafuli river port is considered as the lifeline of the economic activities of the country. Therefore, it is always necessary to keep the river active and live in terms of its navigability. Due to man-made intervention, the river flow becomes interrupted and thereby may cause the change in the river morphology. The specific objective of this study is the application of 2D model to assess different hydrodynamic and morphological characteristics of the river due to normal flow condition and sea level rise condition. The model has been set with the recent bathymetry data collected from CPA hydrography division. For model setup, the river reach is selected between Kalurghat and Khal no-18. Time series discharge and water level data are used as boundary condition at upstream and downstream. Calibration and validation have been carried out with the recent water level data at Khal no-10 and Sadarghat. The total reach length of the river has been divided into four parts to determine different hydrodynamic and morphological assessments like variation of velocity, sediment erosion and deposition and bed level changes also have been studied. This model has been used for the assessment of river response due sediment transport and sea level rise. Model result shows slight increase in velocity. It also changes the rate of erosion and deposition at some location of the selected reach. It is hoped that the result of the model simulation will be helpful to suggest the effect of possible future development work to be implemented on this river.

Keywords: CCHE 2D, hydrodynamic, morphology, sea level rise

Procedia PDF Downloads 382

Authors: James Gallagher, Phillip Benachour

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As location aware mobile technologies become ever more omnipresent, the prospect of exploiting their context awareness to enforce learning approaches thrives. Utilizing the growing acceptance of ubiquitous computing, and the steady progress both in accuracy and battery usage of pervasive devices, we present a case study of remote location viewing, how the application can be utilized to support mobile learning in situ using an existing scenario. Through the case study we introduce a new innovative application: Mobipeek based around a request/response protocol for the viewing of a remote location and explore how this can apply both as part of a teacher lead activity and informal learning situations. The system developed allows a user to select a point on a map, and send a request. Users can attach messages alongside time and distance constraints. Users within the bounds of the request can respond with an image, and accompanying message, providing context to the response. This application can be used alongside a structured learning activity such as the use of mobile phone cameras outdoors as part of an interactive lesson. An example of a learning activity would be to collect photos in the wild about plants, vegetation, and foliage as part of a geography or environmental science lesson. Another example could be to take photos of architectural buildings and monuments as part of an architecture course. These images can be uploaded then displayed back in the classroom for students to share their experiences and compare their findings with their peers. This can help to fosters students’ active participation while helping students to understand lessons in a more interesting and effective way. Mobipeek could augment the student learning experience by providing further interaction with other peers in a remote location. The activity can be part of a wider study between schools in different areas of the country enabling the sharing and interaction between more participants. Remote location viewing can be used to access images in a specific location. The choice of location will depend on the activity and lesson. For example architectural buildings of a specific period can be shared between two or more cities. The augmentation of the learning experience can be manifested in the different contextual and cultural influences as well as the sharing of images from different locations. In addition to the implementation of Mobipeek, we strive to analyse this application, and a subset of other possible and further solutions targeted towards making learning more engaging. Consideration is given to the benefits of such a system, privacy concerns, and feasibility of widespread usage. We also propose elements of “gamification”, in an attempt to further the engagement derived from such a tool and encourage usage. We conclude by identifying limitations, both from a technical, and a mobile learning perspective.

Keywords: context aware, location aware, mobile learning, remote viewing

Procedia PDF Downloads 291

Authors: Ahmad Odeh, Ahmad Jrade

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Energy assessment is an evidently significant factor when evaluating the sustainability of structures especially at the early design stage. Today design practices revolve around the selection of material that reduces the operational energy and yet meets their displinary need. Operational energy represents a substantial part of the building lifecycle energy usage but the fact remains that embodied energy is an important aspect unaccounted for in the carbon footprint. At the moment, little or no consideration is given to embodied energy mainly due to the complexity of calculation and the various factors involved. The equipment used, the fuel needed, and electricity required for each material vary with location and thus the embodied energy will differ for each project. Moreover, the method and the technique used in manufacturing, transporting and putting in place will have a significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at helping designers select the construction materials based on their embodied energy. Moreover, this paper presents a systematic approach that uses an efficient method of calculation and ultimately provides new insight into construction material selection. The model is developed in a BIM environment targeting the quantification of embodied energy for construction materials through the three main stages of their life: manufacturing, transportation and placement. The model contains three major databases each of which contains a set of the most commonly used construction materials. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by tools and cranes needed to place an item in its intended location. The model provides designers with sets of all available construction materials and their associated embodied energies to use for the selection during the design process. Through geospatial data and dimensional material analysis, the model will also be able to automatically calculate the distance between the factories and the construction site. To remain within the sustainability criteria set by LEED, a final database is created and used to calculate the overall construction cost based on R.M.S. means cost data and then automatically recalculate the costs for any modifications. Design criteria including both operational and embodied energies will cause designers to revaluate the current material selection for cost, energy, and most importantly sustainability.

Keywords: building information modelling, energy, life cycle analysis, sustainablity

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Authors: Asifa Fitriani, Galih Prakoso

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This study aims to improve the design layout of a Micro, Small and Medium Enterprises (SMEs) to minimize material handling and redesigning the layout of production facilities based on the safety and health and standards of food production facilities. Problems layout in the one of chip making industry mushrooms in Indonesia is cross movement between work stations, work accidents, and the standard of facilities that do not conform with the standards of the food industry. Improvement layout design using CORELAP and 5S method to give recommendation and implementation of occupational health and safety standards of food production facilities. From the analysis, improved layout using CORELAP provide a smaller displacement distance is 155.84 meters from the initial displacement distance of 335.9 meters, and providing a shorter processing time than the original 112.726 seconds to 102.831 seconds. 5S method also has recommended the completion of occupational health and safety issues as well as the standard means of food production by changing the working environment better.

Keywords: Layout Design, Corelap, 5S

Procedia PDF Downloads 534